Ref. Ares(2016)6709748 - 30/11/2016
URBAN‐WASTE – 690452 D2.1 URBAN‐WASTE Urban Strategies for Waste Management in Tourist Cities D2.1 Literature Review on Urban Metabolism Studies and Projects Grant Agreement No:
Project Acronym:
Project Title:
Cities
Contractual delivery date:
Actual delivery date:
Contributing WP:
Dissemination level:
Editors:
690452
URBAN-WASTE
Urban Strategies for Waste Management in Tourist
31/08/2016
31/08/2016
WP 2
Public
Roland
Ramusch
&
Gudrun
Obersteiner
Abstract: This report gives a comprehensive review on previous urban metabolism studies in order to
identify and compare methodologies, and provide knowledge on which indicator sets and
background data are suitable for linking tourism activities with waste and use of resources. In most
of the reviewed literature on urban metabolism, waste is included as an indicator in various ways.
However, it has proven complicated to estimate material flows from tourism separately.
It is recommended, that a selection of complementary approaches is applied in order to meet the
different objectives of the project. A combination of MFA and LCA can provide a descriptive ap-
proach to map the current state and also to enable scenario analysis for future planning and policy
making and allows an environmental assessment of the current systems and future scenarios.
The results of waste as a function of tourism shows, that a top-down approach in the data
collection is proposed. This has influence on the development of a template for data collection in
the eleven pilot cities.
This document includes also starting points for WP3: especially the section on behavioural
analysis and gender aspects.
The sole responsibility for the content of this report lies with the authors. It does not necessarily reflect
the opinion of the European Union. Neither EASME nor the European Commission are responsible for
any use that may be made of the information contained therein
Document History: Version Date Editor Modification Contributors: Name Gudrun Obersteiner Roland Ramusch Iris Gruber Arie Romein Erik Louw Mattias Eriksson Christian Fertner Juliane Große Trine Bjørn Olsen Company Universität für Bodenkultur Wien Contributions include Chapter 1, Chapter 2, Chapter 3.3, Chapter 4, Chapter 5, Chapter 6 Technische Universiteit Delft (Delft Chapter 3.2, Chapter 6 University of Technology) Sveriges Lantbruksuniversitet – Swedish Chapter 3.3.7, Chapter 6 University of Agricultural Sciences University of Copenhagen Chapter 3.1, Chapter 6 Aarhus University ‐ AU Herning Chapter 6 2
D2.1 Literature Review on Urban Metabolism Studies and Projects 1
Content 1 INTRODUCTION .............................................................................................................................................. 6 2 METHODS ....................................................................................................................................................... 7 3 STATE OF RESEARCH ....................................................................................................................................... 8 3.1 WASTE AND TOURISM FROM AN URBAN METABOLISM PERSPECTIVE ............................................................ 8 3.1.1 Methodological approaches .................................................................................................................... 9 3.1.1.1 Material‐ and energy‐flow‐analysis (MFA / EFA) .......................................................................... 9 3.1.1.2 Ecological footprint (EF) and Life‐cycle analyses (LCA) ................................................................ 13 3.1.1.3 Drives‐Pressures‐State‐Impact‐Response (DPSIR) ....................................................................... 14 3.1.1.4 Global interrelations, value chains, telecoupling etc. .................................................................. 16 3.1.1.5 Sustainability and quality of life in Urban Metabolism ............................................................... 18 3.1.2 Which role does waste and tourism play in UM studies? ....................................................................... 22 3.1.2.1 Background Data and important/critical issues .......................................................................... 25 3.1.2.2 Gender aspects ............................................................................................................................ 26 3.1.2.3 Sub‐conclusions............................................................................................................................ 27 3.2 WASTE BEHAVIOUR AND MANAGEMENT ...................................................................................................... 28 3.2.1 Waste generation and treatment in the European Union ...................................................................... 29 3.2.1.1 Attitudes towards waste generation ............................................................................................ 33 3.2.1.2 Waste management behaviour .................................................................................................... 37 3.2.2 WASTE GENERATION BY TOURISM ........................................................................................................ 40 3.2.3 WASTE BEHAVIOUR ............................................................................................................................... 41 3.2.4 Environmental Management Systems (EMS) in the tourist sector and the hospitality industry ............. 43 3.2.5 LOCAL AND REGIONAL POLICY FRAMEWORK ......................................................................................... 49 3.3 WASTE GENERATION AS A FUNCTION OF TOURISM ...................................................................................... 50 3.3.1 Introduction ........................................................................................................................................... 50 3.3.2 Tourism's three main impact areas ........................................................................................................ 53 3.3.3 Touristic processes ................................................................................................................................ 53 3.3.4 Scope of the reviewed literature ........................................................................................................... 55 3.3.5 Waste types covered and indicator sets used ........................................................................................ 63 3.3.6 Quantified Indicator Results .................................................................................................................. 79 3.3.7 Food waste ............................................................................................................................................ 83 3.3.7.1 Waste related data used ............................................................................................................. 84 3.3.7.2 Tourist Indicator Sets ................................................................................................................... 84 3.3.7.3 Critical processes ......................................................................................................................... 85 3.3.8 Waste management issues on islands .................................................................................................... 87 3.3.9 Gender aspects ...................................................................................................................................... 89 4 LESSONS LEARNED FROM CASE STUDIES FROM PARTNER CITIES ................................................................... 91 4.1 FLORENCE/ITALY ........................................................................................................................................... 91 4.1.1 Waste‐Less in Chinati ............................................................................................................................. 91 2
4.1.2 RES MAR – Marine environmental defence ........................................................................................... 93 4.1.2.1 Typologies of tourist municipalities .............................................................................................. 93 4.2 KVALA/GREECE .............................................................................................................................................. 94 4.2.1 WASTE‐C‐CONTROL ............................................................................................................................... 94 4.2.2 Evaluation and Optimisation of the ISWM system of Kavala .................................................................. 95 4.2.2.1 Assessment indicators .................................................................................................................. 95 4.3 LISBON/PORTUGAL ....................................................................................................................................... 97 4.3.1 MFA Case Study of the Lisbon Metropolitan Area using the Urban Metabolism Analyst Model ............ 97 4.4 NICOSIA CYPRUS ............................................................................................................................................ 98 4.4.1 Guidelines for meeting the Cyprus Tourism Organisation minimum standards for sustainability in hotel establishments .................................................................................................................................................... 98 4.4.2 Waste Mapping Guidance for Hotels in Cyprus ...................................................................................... 98 4.5 PONTA DELGADA / AZORES ........................................................................................................................... 99 4.5.1 SIET‐MAC project System of Sustainable Tourism Indicators in Macaronesia ........................................ 99 4.6 TENERIFE / SPAIN ........................................................................................................................................ 100 4.6.1 Environmental performance in the hotel sector: the case of the Western Canary Islands. .................. 100 5 COMPILATION OF EXISTING INDICATORS AND NECESSARY BACKGROUND DATA FROM PREVIOUS STUDIES 101 6 CONCLUSIONS FOR URBAN‐WASTE ASSESSMENT CRITERIA ......................................................................... 109 6.1 6.2 LITERATURE REVIEW ................................................................................................................................... 109 METHODOLOGY FOR DATA COLLECTION ON WASTE AND TOURISM ........................................................... 109 REFERENCES ........................................................................................................................................................ 119 APPENDIX ............................................................................................................................................................ 129 3
List of Figures + Tables FIGURE 1: MULTIPLE SCALES AND DISCIPLINES OF URBAN METABOLISM (ZHANG ET AL. 2015) .............................................................. 8 FIGURE 2: LINEAR AND CIRCULAR URBAN METABOLISM (GIRARDET 2008; LEDUC AND VAN KANN 2013) ............................................... 9 FIGURE 3: MATERIAL FLOW ACCOUNTING (MFA) AT THE URBAN LEVEL (ROSADO ET AL. 2016) ......................................................... 12 FIGURE 4: ECOLOGICAL FOOTPRINT OF AN AVERAGE CANADIAN (WACKERNAGEL AND REES 1995) ...................................................... 13 FIGURE 5: LIFE‐CYCLE CHAIN: EXTRACTION – PRODUCTION – CONSUMPTION – WASTE (EEA 2010) ..................................................... 14 FIGURE 6: DPSIR FRAMEWORK USED BY THE EUROPEAN ENVIRONMENT AGENCY (EEA 2007) .......................................................... 15 FIGURE 7: A DPSIR‐FRAMEWORK FOR URBAN METABOLISM (FERRÃO AND FERNÁNDEZ 2013) .......................................................... 16 FIGURE 11: ADDITIONAL ELEMENTS OF AN EXPANDED URBAN METABOLISM FRAMEWORK (PINCETL ET AL. 2012) ................................... 20 FIGURE 12: EXTENDED CONCEPT FOR URBAN METABOLISM (MINX ET AL. 2011) ............................................................................. 20 FIGURE 13: HEADLINE INDICATOR SET FOR THE FOUR PROPOSED DIMENSIONS (URBAN FLOWS, URBAN QUALITY, URBAN PATTERNS, URBAN DRIVERS) ........................................................................................................................................................... 21 FIGURE 14: EXTENDED URBAN METABOLISM FRAMEWORK (NEWMAN 1999) ................................................................................. 23 FIGURE 15: MODEL FOR THE ANALYSIS OF AN URBAN METABOLIC SYSTEM BASED ON THE ROLES PLAYED BY DIFFERENT METABOLIC ACTORS (ZHANG ET AL. 2013) .......................................................................................................................................... 23 FIGURE 16: WASTE MANAGEMENT AND RECOVERY MATERIAL FLOWS (ECKELMAN AND CHERTOW 2009) ............................................. 25 FIGURE 18 TOTAL WASTE GENERATION BY HOUSEHOLDS IN EUROPE IN 2012 IN KILOGRAMS PER CAPITA BY COUNTRY. ............................. 30 FIGURE 19: COMPARISON BETWEEN THE WASTE GENERATION BY HOUSEHOLDS AND MUNICIPAL WASTE GENERATION IN EUROPE IN 2012 IN KILOGRAMS PER CAPITA BY COUNTRY. ....................................................................................................................... 31 FIGURE 20: MUNICIPAL WASTE TREATMENT BY TYPE OF TREATMENT AND COUNTRY IN 2013 (IN % OF TOTAL WASTE TREATMENT). ............ 33 FIGURE 21: SHARE OF RESPONDENTS THAT TOTAL AGREE WITH STATEMENTS MY HOUSEHOLD IS GENERATING TOO MUCH WASTE AND MY COUNTRY IS GENERATING TOO MUCH WASTE BY COUNTRY IN 2014. ................................................................................ 34 TABLE 1: PERCENTAGE TOTAL ‘AGREE’ (TOTAL OF TOTALLY AND TEND TO AGREE) FOR THE FOLLOWING ................................................. 35 FIGURE 22: CORRELATION BETWEEN THE AMOUNT OF WASTE GENERATED BY HOUSEHOLDS (2012) AND THE STATEMENT THAT MY HOUSEHOLD IS GENERATING TO MUCH WASTE BY COUNTRY (2014). ................................................................................................ 37 FIGURE 23: PERCENTAGE OF RESPONDENTS THAT REDUCE WASTE AND SEPARATE MOST OF WASTE FOR RECYCLING IN 2014 BY COUNTRY. .... 38 TABLE 2: PERCENTAGE RESPONDENTS WHO SEPARATE MOST OF THEIR WASTE AND WHO REDUCE WASTE BY SEX, AGE AND EDUCATION IN 2014.
....................................................................................................................................................................... 39 TABLE 3: DEVELOPMENT OF GLOBAL INTERNATIONAL TOURIST ARRIVALS 1950 – 2015;SOURCE: WORLD TOURISM ORGANISATION (2016) 50 TABLE 4: OVERVIEW OF THE REVIEWED LITERATURE ................................................................................................................... 58 TABLE 5: OVERVIEW OF WASTE RELATED INDICATOR SETS USED, WASTE TYPES COVERED AND RESULTS OF REVIEWED LITERATURE ................ 66 FIGURE 24: BOXPLOT OF THE DISTRIBUTION OF THE INDICATOR “WASTE GENERATED PER TOURIST AND DAY (N=50) ................................ 79 FIGURE 25: DISTRIBUTION OF 50 DATASETS ON TOURIST WASTE GENERATION ................................................................................. 81 FIGURE 26: BENCHMARKS OF TOURIST WASTE GENERATION FOT DIFFERENT HOTEL TYPES ................................................................... 81 FIGURE 27: WASTE COMPOSITION IN HOTEL ROOMS IN HONG KONG ............................................................................................ 82 TABLE 6: INDEXES AND INDICATORS USED FOR THE EVALUATION OF MUNICIPAL WASTE MANAGEMENT SYSTEMS ..................................... 96 TABLE 7: WASTE RELATED DATA REQUIREMENTS .................................................................................................................... 102 TABLE 8: DATA ON FACTORS OF INFLUENCE ........................................................................................................................... 103 TABLE 9: TOURISM RELATED DATA REQUIREMENTS (EUROSTAT TOURISM STATISTICS) ..................................................................... 104 TABLE 10: LIST OF ASPECTS RELEVANT TO UNDERSTAND WASTE GENERATION IN CONNECTION WITH TOURISM THAT SHOULD BE COVERED BY A QUALITATIVE DESCRIPTION ................................................................................................................................... 107 TABLE 11: BOTTOM‐UP AND TOP‐DOWN APPROACHES RELATED TO THE REVIEWED LITERATURE ........................................................ 111 FIGURE 28: DIFFERENT METHODOLOGICAL APPROACHES IN ASSESSING WASTE AND TOURISM ........................................................... 113 4
FIGURE 29: CROSS‐SECTIONAL WASTE DATA (SCHEMATICALLY) .................................................................................................. 113 FIGURE 30: SCHEMATIC TIME SERIES BASED ON ANNUAL DATA AND MONTHLY DATA ....................................................................... 114 FIGURE 31: SCHEMATIC TIME SERIES WITH WINTER AND SUMMER TOURISM SEASON BASED ON MONTHLY DATA ................................... 114 FIGURE 32: PANEL DATA FOR MUNICIPALITIES WITH WINTER AND SUMMER TOURISM SEASON (SCHEMATICALLY) ................................... 115 TABLE 12: APPROACHES FOR ESTIMATING TOURISM‐RELATED WASTE GENERATION AND COLLECTION SORTED BY ANALYSED UNIT AND TIME SCALE .............................................................................................................................................................. 116 TABLE 13: DEFINITIONS FOR CATALOGUE OF INDICATORS AND BACKGROUND DATA REQUIREMENTS. ................................................... 129 5
1 Introduction Tourism has a high impact related to different aspects, on the one hand it is a worldwide important economic sector, 10% of the world´s GDP is directly or indirectly generated by the tourism sector, one out of eleven jobs are related to tourism. Beside the economic implications, 1.1 billion tourists every year have environmental impacts – beside emissions from transport and the impacts of all necessary infrastructure (airports, hotels etc.) there is a high impact on natural resources (renewable and non‐renewable), incl. water resources. It is therefore important that the tourism industry continues to improve and adapt its operation towards waste minimization; following that, waste should be collected, transported and disposed of in an environmentally sound and cost‐effective manner. Improper management of waste can lead to substantial and irreversible environmental impacts, such as increases in greenhouse gas emission, land degradation, resource deprivation, surface and groundwater water pollution or loss of biodiversity. In comparison with other cities, tourist cities have to face additional challenges related to waste prevention and management due to their geographical and climatic conditions, the seasonality of tourism flow and the specificity of tourism industry and of tourists as waste producers. One major objective of the UrBAN‐WASTE project is to support policy makers in answering these challenges and in developing strategies that aim at reducing the amount of municipal waste production and at further support the re‐use, recycle, collection and disposal of waste in tourist cities. The concept of urban metabolism will be used to understand and analyze how cities that are influenced by tourism use their resources and how touristic activities are linked to waste management and resource conservation. Therefore UrBAN‐WASTE will perform a metabolic analysis of the state of art of urban metabolism in 11 pilot cities. As first procedural step to meet the projects objectives the development of a proper methodology and the adjustment and definition of data requirements is envisaged. Metabolism indicator sets and a database for the selected pilot tourist cities shall be developed.The database focusses on the touristic processes and the link to resource use, waste generation, prevention, recycling, waste treatment and disposal activities. The database provides the information in order to analyse how tourism is responsible for positive and negative impacts considering the three pillars of sustainability (environment, society and economy). This deliverable is a report where methodologies, indicator sets and needed background data are reviewed related to urban metabolism studies and waste management linked to the tourism sector. An important part is related to obtaining information on what data / indicator sets are suitable, practicable and comparably easy to obtain. The review will provide knowledge on what data / indicator sets are most suitable for linking touristic activities with waste generation and resource use by a comprehensive review about previous urban metabolism studies and research dealing with tourism. 6
2 Methods To compare and assess at the one hand different methodological approaches in order to find the best tools that will be used in the following steps of the project and at the other hand to find out what indicator sets are currently used and what data are needed for these indicator sets the literature review was split into three main parts also taking into account the practicability of data sets (including for different spatial scales and time periods). First of all literature was screened focussing on waste and tourism from the Urban Metabolsim perspective. In this section different approaches and methods used to conceptualise and operationalise urban metabolism and how these tackle issues of waste, more specific from touristic activities were reviewed. Secondly the key words waste behaviour and management were analysed to focus on main issues about waste behaviour and management. This was done by firstly looking for review papers and from this on looking at more recent papers. The last part focusses on studies dealing with waste generation as a function of tourism. The papers where analysed and classified in a MS Excel file according to certain categories, allowing a subsequent analysis and illustration based on different characteristics. 7
3 State of Research 3.1
Waste and tourism from an Urban Metabolism perspective The concept of urban metabolism (UM) was developed by Wolman (1965). Kennedy et al. (2007) define urban metabolism as “the sum total of the technical and socioeconomic processes that occur in cities, resulting in growth, production of energy, and elimination of waste”. Waste, and therewith waste from tourists occurring in the urban sphere, are main components of urban metabolism. In this section we review different approaches and methods used to conceptualise and operationalise urban metabolism and how these tackle issues of waste, more specific from tourist activities. Figure 1: Multiple scales and disciplines of urban metabolism (Zhang et al. 2015) Depending on the approach chosen, the analysis of urban metabolism can be used for four purposes (Kennedy et al. 2011): 1.
2.
3.
4.
provision of sustainability indicators provision of inputs to urban greenhouse gas (GHG) accounting provision of dynamic mathematical models for policy analysis development of design tools. 8
The focus of this study lies on point 1, to provide knowledge on sustainability indicators for further use in the Urban Waste project. However, the comprehensive and inclusive concept of urban metabolism has the potential to analyse waste and tourism in a systemic and impact oriented way, which can also be used for policy advice and which is why we chose to use an urban metabolism perspective (besides others) in workpackage 2 of the project. An important aspect is therefore the sustainability dimension within urban metabolism. How can cities reduce resource consumption and minimize waste and emissions while improving or maintaining the quality of life of their citizens (and visitors). A recurring idea is the move from a linear to circular urban metabolism and urban economy, as illustrated in Figure 2. Figure 2: Linear and circular urban metabolism (Girardet 2008; Leduc and Van Kann 2013) 3.1.1 Methodological approaches In the following we will review different approaches to urban metabolism and how they have been applied. 3.1.1.1 Material‐ and energy‐flow‐analysis (MFA / EFA) A recent review of urban metabolism methodologies (Zhang 2013; Zhang et al. 2015) distinguishes “two main accounting and assessment methods for urban metabolism [that] are based on an analysis of material and energy flows”: “Material‐flow‐analysis” (MFA) or “mass balance” has the 9
goal to provide a system level understanding of how a city, region or nation functions (Holmes and Pincetl 2012). MFA traces the input, storage, transformation, and output processes and it allows following the material flows throughout the life cycle within an urban system, based on the physical principle that matter can neither be created nor destroyed. MFA also allows for comparisons across cities and inputs (Pincetl 2012). A concept strongly related to MFA, but using a different methodology is substance‐flow‐analysis (SFA). SFA “observes the changes in the substance flows among different life‐cycle stages”, whereas MFA, in contrast, “investigates the quantity and state of cross‐sectional data at different life‐cycle stages” (Zhang et al. 2015) and is a such an external and static analysis. However, there is no standardized method for SFA (Barles 2010). A second approach, which is a modification of the MFA framework, is “energy‐flow‐analysis” (EFA) or “energy balance”. It was developed to provide a more detailed understanding of urban metabolic processes (Zhang 2013). A further development of EFA is the concept of “emergy” and “exergy”, which represent embodied energy and “the amount of useful work that can be performed by the energy in a system” (Zhang 2013; Zhang et al. 2015). This concept allows integrating material flows with different measurement units. Emergy provides a method for studying the energetic flows in a socio‐economic system and can also provide a comparative tool to understand “the relative work of other materials flowing through a socio‐economic system” (Holmes and Pincetl 2012). However, MFA has long been favoured over EFA which resulted in overlooking major environmental and social issues (Barles 2010; Holmes and Pincetl 2012). Within the framework of MFA and EFA different simulation models are used for the quantitative analysis of the metabolic flows of an urban system, such as the ecological network analysis (ENA) or input‐output‐analysis (Zhang 2013; Zhang et al. 2015). In a case study on Beijing, Zhang et al. (2013) conduct a MFA by applying network theory for the years 1998‐2007. The authors divide Beijing’s urban metabolic system into seven components (agriculture, materials and energy transformation, mining, recycling, domestic consumption, processing and manufacturing, construction) and describe the flows between these components by linking them in a network model. Additionally, they define six input and six output paths with the environment. They furthermore introduce four metabolic indicators (metabolic scale, intensity, efficiency and impact) to assess the structural characteristics of the metabolic system and each of its components. A case study on Paris (Barles 2010) uses Local Bulk Material Balance to conduct a MFA at three different scales (Paris, Paris and its inner suburbs (PPC) and Paris Greater Metropolitan Region (Île‐
de‐France)). Material Balance uses balancing inputs (BI) and balancing outputs (BO) to balance the MFA. The balancing inputs and outputs can be defined by different indicators, such as Total Material Requirement (TMR), Total Material Input (TMI), Direct Material Input (DMI), Net Addition to Stock (NAS), Direct Processed Output (DPO), Local and Exported Processed Output (LEPO), Total Domestic Output (TDO), Direct Material Output (DMO), Total Material Output (TMO). By means of a case study on Lisbon Metropolitan Area, Rosado et al. (2014) developed a new simulation model for MFA, the urban metabolism analyst (UMAn). The model provides values for materials accounting, throughput over time, distribution by economic activity, and spatial distribution. UMAn thereby “associates material flows with economic activities and their spatial 10
location within the urban area” (Rosado et al. 2014) and allows to bridge seven methodological gaps in previous urban metabolism studies: 



lack of a unified methodology lack of material flows data at the urban level limited categorizations of material types limited results about material flows as they are related to economic activities; limited understanding of the origin and destination of flows  lack of understanding about the dynamics of added stock  lack of knowledge about the magnitude of the flow of materials that are imported and then, to a great extent, exported (Rosado et al. 2014) In a further study on three metropolitan areas in Sweden (Rosado et al. 2016) – using material‐
flow‐analysis and the urban metabolism analyst (UMAn) simulation model – the authors adapt the Economy Wide MFA principles (European Commission, eurostat 2001) by excluding water from the accounting. The study considers the following indicators in the MFA: Direct Material Input (DMI), Imports (Imp), Exports (Exp), Domestic Extraction (DE), Domestic Material Consumption (DMC), Net Addition to Stock (NAS), Industrial Production (IP), Domestic Processed Output (DPO), and Recovery (Figure 3). The study further applies a framework of eight urban metabolism characteristics, which are described by the above named indicators, in order to deduce urban metabolism profiles and describe the resilience of urban areas. The UM characteristics are: Material needs, accumulation of materials, urban metabolism efficiency, diversity of processes, support provided by an urban area, dependency on other systems, self‐sufficiency and pressure on the environment. 11
Figure 3: Material Flow Accounting (MFA) at the urban level (Rosado et al. 2016) One first approach to come up with a standardized and comprehensive urban metabolism framework was introduced by Kennedy and Hoornweg (2012), which also includes a list of abbreviated parameters. Their framework builds on the Eurostat material‐flow‐analysis system (European Commission, eurostat 2001) and combines it with methods of water‐, energy‐ and substance‐flow‐analysis. The parameters refer to inflows, production, stocks and outflows of biomass, minerals, water and energy. For its application on megacities, Kennedy et al. (2014) adapted their framework in order to focus only on parameters which are major components of urban metabolism, such as energy, water, material and waste flows. Their adapted set of parameters is organized in four layers: (1) Definition of a megacity, (2) biophysical characteristics, (3) aggregate urban metabolism parameters and (4) role of utilities (Kennedy et al. 2014). The framework of Kennedy and Hoornweg (2012) and Kennedy et al. (2014) is applied in a case study of Curitiba (Brazil) by Conke and Ferreira (2015) and their study also includes a social dimension, an extension of the urban metabolism framework that is introduced by Newman (1999). 12
3.1.1.2 Ecological footprint (EF) and Life‐cycle analyses (LCA) A main critique of MFA and similar approaches is, that they can hardly be used to evaluate the sustainability of an urban system as they are not (directly) relating to the impact of material (and non‐material) flows (Zhang 2013; Zhang et al. 2015). A concept dealing with the impact of urban growth and consumption is the concept of the Ecological footprint (EF). It measures the land area necessary to sustain city’s (or also a person’s) resource consumption and waste discharge. Figure 4 illustrates the main idea, which was broadly introduced by Wackernagel and Rees (1995). Figure 4: Ecological footprint of an average Canadian (Wackernagel and Rees 1995) The advantages of EF are that it combines socioeconomic development demands with ecological capacity and that, as mentioned above, can therewith reveal ecologically unsustainable situations. However, problems of the concept are that it neglects the ability of land to provide multiple functions, and that, because of incomplete descriptions of resource provision (and waste discharge) by the natural system, it underestimates human impact (Zhang 2013). Via an expert survey, Wiedmann and Barrett (2010) found that EF “(a) is seen as a strong communication tool, (b) has a limited role within a policy context, (c) is limited in scope, (d) should be closer aligned to the UN System of Environmental and Economic Accounting and (e) is most useful as part of a basket of indicators.” (Wiedmann and Barrett 2010) A different approach to analyse the impacts of material flows is life‐cycle assessment (LCA). According to Pincetl (2012) mass balance analysis (MFA) “can incorporate [LCA] to capture the 13
indirect and supply chain impacts of cities beyond their borders and materials flow analysis (MFA)”. By these means MFA and LCA allow cradle‐to‐grave assessments of the flows in a city’s metabolism. Figure 5: Life‐cycle chain: extraction – production – consumption – waste (EEA 2010) Additional information on LCA is provided by different authors ((Barles 2010), (Holmes and Pincetl 2012)). 3.1.1.3 Drives‐Pressures‐State‐Impact‐Response (DPSIR) In the 1990s the European Environment Agency developed (based on the PSR model of the OECD) a causal‐indicator framework to describe interactions between society and the environment (Figure 6). The DPSIR model (driving forces, pressures, states, impacts, responses) applies a systems‐view: “social and economic developments exert pressure on the environment which changes its state. This leads to impacts (human/ecosystem) which may result in responses by the society, which feeds back the other components (EEA 2007). 14
Figure 6: DPSIR Framework used by the European Environment Agency (EEA 2007) Using the model might be most helpful when focusing on the linkages between D‐P‐S‐I‐R. Indicators reflecting these are (EEA 2007): 




“Eco‐efficiency indicators (between D and P). Increasing eco‐efficiency means that economic activities can expand without an equivalent increase in pressure on the environment. Pathways and dispersion patterns link P and S. The combination of these indicators tells a story of time delay in natural processes and the ‘time bombs’ created in the environment. Knowledge of dispersion patterns can be useful to model current and future changes in the state of the environment and in impacts. Dose/response relationships link S to I. Knowledge of dose/response relationships can be used to predict or quantify the health impacts of pollution, or help in choosing the most appropriate state indicator to act as an early warning. Economic costs of the impact and other indicators that confirm societal perception of the seriousness of the impacts are key for triggering societal responses. These highlight the link between I and R. Policy‐effectiveness indicators generally summarise the relations between the response and targets for expected change in driving forces or pressures and sometimes in responses, state or even impacts. ” (EEA 2007) However, the model was critized for not considering social and socio‐economic aspects very well (Svarstad et al. 2008). Tscherning et al. (2012) reviewed the potential of DPSIR to support decision making, by applying two main criteria: (1) the development of conceptual models integrating knowledge from different disciplines, specialists and policy makers, as well as those affected by their decisions; and (2) the potential to explain the results and analysis of research to different disciplines, specialists, stakeholders and the public and to demonstrate alternatives and provide decision options. They found that DPSIR can be useful by means of showing solid evidence with alternatives and decision options, rather than by presenting predetermined solutions. 15
Figure 7 illustrates another example of the DPSIR approach in an urban context (Ferrão and Fernández 2013). The authors underscore the importance of defining all elements and specifying the relationships between them. However, they also state that the task of defining those has been an ongoing challenge since DPSIR was developed, probably not least because in many occasions end users were not addressed during its development, as Tscherning et al. (2012) notice. Figure 7: A DPSIR‐framework for urban metabolism (Ferrão and Fernández 2013) 3.1.1.4 Global interrelations, value chains, telecoupling etc. An issue not always addressed by the previous mentioned approaches dealing with urban metabolism are interrelations going beyond the city context (Zhang et al. 2015). In LCA and footprint analysis it is though the ambition to include the impact of the whole product chain until its final consumption. However, some further approaches might be useful to mention in this 16
context as they particularly expand on indirect relations, spillover systems, hidden effects or anthropogenic / global metabolism. A widely used concept within the analysis of world trade and production are global value chains (GVC), or supply chain analysis. GVC typically identifies all activities that firms undertake to produce, transform and supply a product (OECD 2012). GVC are thereby especially useful to uncover the global relations and dependencies of specific economic sectors, and cause‐effect relations on a global scale. Figure 8: Global value chain of Nutella (OECD 2012) A concept going even further is “telecoupling”, which aims as increasing our understanding of “how the world functions over distances and identify solutions to achieve socioeconomic and environmental sustainability across local to global levels, because it is uniquely integrative in several ways” (Liu et al. 2013). Telecoupling intergrates socioeconomic and environmental interactions over distances (Figure 9). Also, it includes “spillover systems” in the analysis and ‘hidden’ or ‘indirect’ effects in different locations than where the supply and demand of specific services and products is taking place (Figure 10). 17
Figure 9: Definitions of teleconnections, globalisation and telecoupling (Liu et al. 2013) Figure 10: Relations between sending, receiving in spillover system (Liu et al. 2013) 3.1.1.5 Sustainability and quality of life in Urban Metabolism As mentioned earlier, a major shortcoming of the established methodologies in the urban metabolism / MFA framework is that they are not suitable to assess the level of sustainability of a system. This deficit is addressed by several studies that aim for an extension of the framework of 18
urban metabolism / MFA in order to gain a more comprehensive picture, including components of sustainability and quality of life. A study addressing interdisciplinary boundaries of urban metabolism (Broto et al. 2012) highlights that politics influence socio‐environmental metabolisms and that “the metabolism of the city is not only shaped by visible flows, but also by the ways in which different forms of circulation are imagined and represented through the city” (Broto et al. 2012). The study argues that looking closer at the organization of production and consumption patterns into flows – of materials, energy, people, meanings, and power – is necessary for addressing the challenges of urban sustainability; however, the study does not suggest a respective indicator set. An important extension of the urban metabolism model was conducted by Newman (1999) by adding a further dimensions of “social metabolism” to the classic model applying a socio‐economic perspective. Newman (1999) refers to a social dimension by including the dynamics of settlements and liveability in these settlements in the model. The extended metabolism model applies an indicator set that covers metabolic flows and liveability; the indicators are classified in five groups: (1) energy and air quality, (2) water, materials and waste, (3) land, green spaces and biodiversity, (4) transportation and (5) liveability, human amenity and health. In this extended version the urban metabolism model does not only assess liveability but also sustainability of cities. Also Kennedy et al. (2011) see a need for considering social, health and economic indicators in urban metabolism models, but in contrast to Newman (1999) they suggest the integration of those indicators instead of only adding them. Zhang et al. (2015) provide a concept (see Figure 1) for the multiple scales and disciplines that should be considered in urban metabolism in order to get a fuller understanding of it: Beyond the scale of urban metabolism they outline regional metabolism (RM) at the regional scale, social metabolism (SM) at the national scale and anthroposphere metabolism (AM) at the global scale. Minx et al. (2011) also go the other way, looking at sub‐city and district scale. This is also an attempt to compensate for a “fundamental blindness” (Pincetl et al. 2012) of the established urban metabolism methodologies in the inability to attribute flows to places, people or uses; according to them it requires understanding on “who‐is‐using‐what‐flows‐where‐to‐do‐
what”, in other words it lacks a specific spatial reference to energy or material flows. Pincetl et al. (2012) suggest an expanded urban metabolism framework (see Figure 11) that integrates the existing methodologies and theories, such as LCA, political ecology or ecosystem services, instead of limiting it to one of them in order to provide “comprehensible assessments of energy and material use in cities” (Pincetl et al. 2012). 19
Figure 11: Additional elements of an expanded urban metabolism framework (Pincetl et al. 2012) Pincetl et al. (2012) emphasize the importance of recognizing scalar relationships (geographic specificities) of urban metabolism, as included in their expanded framework. A comprehensive extension of the urban metabolism concept (see Figure 12) is suggested by Minx et al. (2011) including aspects of environmental quality, urban drivers and urban patterns, and urban quality and co‐benefits. Figure 12: Extended concept for urban metabolism (Minx et al. 2011) 20
In their study they present two approaches for an extended concept of urban metabolism. The first one – “A simple indicator system for monitoring urban metabolism in Europe” – provides a comprehensive indicator set for each of the four proposed dimensions – urban flows, urban quality, urban patterns and urban drivers –, which are summarized in a headline indicator set (see Figure 13). Figure 13: Headline indicator set for the four proposed dimensions (urban flows, urban quality, urban patterns, urban drivers) With the second approach – “Small area estimates for carbon footprints and energy consumption” – the study addresses two main restrictions of the first approach: those are data restrictions related to calculations of consumption‐based indicators and the fact that the first approach is only applicable on the administrative city level. The second approach is tested and applied for the UK in the study. The authors use more comprehensive data, comprehensive consumption based estimates of CO2 emissions in the UK, which cover the whole country and allow a downscaling methodology towards smaller spatial scales. The calculation of carbon footprints at smaller spatial scales requires local consumer expenditure data. As this data is usually not available in sufficient sample sizes the authors suggest using geodemographic data, lifestyle classification by clustering, to downscale the data. The model includes scaling and updating procedures to secure consistency through the different scales. The study further includes a validation of the downscaling method by comparing the results when instead using detailed domestic electricity and gas consumption data; which shows reasonable evidence for following up on the downscaling method. Summarizing, the second approach extends the indicator set proposed in the first approach in the following three aspects (Minx et al. 2011): 21


“A complete consumption based account has been provided, which covers all indirect CO2 emissions associated with consumption in cities; Small area estimates of CO2 emissions have been provided not only for urban, but also rural areas; CO2 emission estimates with a much higher spatial resolution have been provided.” 
A methodology developed to study “biophysical and socioeconomic issues in an integrated manner, both for the level of the society and for the different compartments of that society” is the so‐called Multi‐Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) (Ginard‐Bosch and Ramos‐Martín 2016). The methodology is a static analysis that measures congruence between flows and funds over several scales (time, space etc.) and thereby allows observing the evolution of a system over time. But being a static analysis is at the same time one of the shortcomings of the methodology as it provides a snapshot of a system but not of its dynamics (Ginard‐Bosch and Ramos‐Martín 2016). The methodology uses flow and fund indicators, those are in a case study of the Balearic Islands (ibid.) the following: Total energy throughput (TET), total human activity (THA), gross domestic product (GDP), energy throughput in activity i (ETi), human activity in activity i (HAi), GDP per hour in the society (GDPhour), exosomatic metabolic rate, average of the society (MJ/h) (EMRSA), exosomatic metabolic rate (MJ/h) (EMRi), economic labour productivity (h/h) (ELPi), economic energy intensity (MJ/€) (EEIi). 3.1.2 Which role does waste and tourism play in UM studies? The reviewed studies on urban metabolism methodologies include waste or more specific tourism‐
related waste in different ways in its respective indicator sets. In their detailed guideline on MFA, Brunner and Rechberger (2004) explain the importance of MFA for waste management because MFA “can cost‐efficiently determine the elemental composition of wastes exactly” (Brunner, Paul H. and Rechberger, Helmut 2004) and thereby provide crucial information about the most suitable recycling/treatment technology. Newman (1999) includes waste in his extended framework for urban metabolism as output category by itself (Figure 14). 22
Figure 14: Extended urban metabolism framework (Newman 1999) A case study on Beijing (Zhang et al. 2013) that applies MFA with network theory uses an urban metabolic model that looks separately at resource metabolism and waste metabolism (see Figure 15). Waste metabolism “focuses on the generation, reuse, and final discharge of wastes, and can be described in terms of the environmental impacts of these wastes and their cycling” (Zhang et al. 2013). Figure 15: Model for the analysis of an urban metabolic system based on the roles played by different metabolic actors (Zhang et al. 2013) 23
A case study on Paris (Barles 2010) summarizes waste as Local and Exported Processed Output (LEPO) and distinguishes between local and exported outputs to nature that consist of emissions to air and water, wastes landfilled and dissipative flows. In the study of Kennedy and Hoornweg (2012) that attempts to provide a standardized and comprehensive urban metabolism framework, waste is included both in the categories stocks (landfill waste, construction/demolition waste) and outflows (exported landfill waste, incinerated waste, exported recyclables, wastewater, emissions, pollutants and particulates). In the adapted version of their framework (Kennedy et al. 2014), which is organized in four layers, waste is included in layer 3 – aggregate urban metabolism – as waste water, solid waste disposal on land and waste incineration as well as in layer 4 – role of utilities – in different indicators assessing the quality of service and again as waste water. The comprehensive indicator set that is provided as part of the study of Minx et al. (2011) on an extended concept of urban metabolism considers waste in the dimension of “urban flows” and distinguishes waste intensity of production, residential waste intensity, waste recycling, waste incineration and landfill (Minx et al. 2011). The case study on three Swedish cities (Rosado et al. 2016) categorizes waste a bit different in its applied indicator set: Waste is included in the Domestic Processed Output (DPO), but categorized into air emissions (carbon of fossil fuels origin vs. biomass origin) on the one hand and household vs. industrial waste on the other hand. The study takes thereby a more origin oriented perspective instead of destination (e.g. recyclable) oriented perspective as the other studies. A study dealing particularly with long‐term waste management (Eckelman and Chertow 2009), distinguishes waste as part of the outputs in recycled waste on the one hand and landfilled or released into the environment (land, water, air) on the other hand. This study is one of the few that tries to also estimate material flows related to tourism, in consumption and transportation. That is, however, complicated as a distinction between goods and services consumed by tourists vs. residents is difficult. 24
Figure 16: Waste management and recovery material flows (Eckelman and Chertow 2009) Figure 16 illustrates in detail the material flow model used to explain the waste management system, which allows estimating the different types of waste output (e.g. recycling, energy generation, export). Summarizing waste is considered in different ways in the various indicator sets, however, mostly distinguished by its final destination (e.g. recyclable, landfill). Touristic waste is in almost no study addressed separately. 3.1.2.1 Background Data and important/critical issues Yetano Roche et al. (2014) list some typical data used in urban metabolism studies. Figure 17 lists besides typically used data from MFA/EFA also information on ecological footprint (EF). This combination is used to tackle the drawbacks of both methods. However, socio‐economic driving forces, as illustrated in the DPSIR concept of in indicator systems including sustainability aspects should also be included. Also, major contextual factors as climate, infrastructure, resource availability, cultural/historical path‐dependency have to be included (e.g. as a city typology) to consider some major limiting/ or enabling differences in the urban systems. 25
Figure 17: Examples of basic data requirements for urban metabolism studies (Yetano Roche et al. 2014) However, a major limitation of many UM studies the coarse spatial level used. Shahrokni et al. (2015) even suggest a “Smart urban metabolism”, where they combine real time urban data and illustrate urban metabolism flows on the household and urban district level. In the URBAN WASTE project it will be important to work with spatial explicit data which can be used to differentiate between different types of areas in the city, e.g. those which are important for tourism, specific ecosystems and sensitive areas, or areas contributing differently to the urban economy, urban resource use or pollution etc. 3.1.2.2 Gender aspects The reviewed studies on urban metabolism do not consider gender aspects explicitly. If they at all consider social aspects, then only on a very general scale. However, some studies as e.g. Minx et al. (2009; 2011) highlight the great potential to differentiate studies by different life styles, as e.g. carbon footprints can be very different in different household types. They use market segmentation from model MOSAIC, developed by the UK company Experian, to differentiate 11 lifestyle groups and 61 lifestyle types. However, gender is not specifically used here, besides that it might be differently represented in the different groups. 26
3.1.2.3 Sub‐conclusions Yetano Roche et al. (2014) summarize nicely how different approaches support different questions and recommend a complimentary approach:  “Territorial approaches may help best in understanding urban and regional planning needs;  Supply‐chain approaches may help to identify the role of the process chain;  Whereas consumption‐based approaches may reveal policy needs for behavioural and macroeconomic changes.” Futhermore we have to decide between the analytical power of approaches, the policy‐support potential and not least the feasibility to apply them in the project. E.g. ecological footprint analysis might have great communication potential while the analytical power is limited. MFA/EFA on the other hand have to be combined with aspects of sustainability if they should be used in a later policy discussion. Minx et al. (2011) recommends to 


link the urban metabolism to environmental pressures and aspects of environmental quality at multiple scales; link urban metabolism to urban drivers, patterns and lifestyles; link urban metabolism to aspects of quality of life. Measuring synergies and trade‐offs between sustainability goals is a way forward, as well as the “coupling of MFA and LCA (connecting mass balances with insights about the varying pressures that different flows might have on the environment).” (Yetano Roche et al. 2014). Important hereby is not to stay on the descriptive approach and try to understand the past only but try to move forward and include modelling and scenario analysis to think about future development. Or as Minx et al. (2011) put it “Ultimately the aim of urban metabolism research is to understand how cities can move from one metabolic state (e.g. uni‐directional economy) to another (e.g. circular economy).” 27
3.2
Waste behaviour and management In this section we present and discuss the results of the comprehensive literature about waste behaviour and waste management. The aim was not to make an inventory of the total (scholarly) literature about the subjects but to review the main issues about waste behaviour and management. This was done by firstly looking for review papers and from this on looking at more recent papers. In total we found three relevant review papers (Pirani and Arafat 2014, Myung et al., 2012; Chan and Hsu, 2016). In general it can be concluded that is only a small amount of literature that is aimed at solid waste in the tourism industry. There is more literature about environmental management (systems) and ‘green initiatives’ in the tourism industry. Often these systems and initiatives include actions to minimize solid waste generation and/or management of solid waste in a sustainable way. However in most studies no distinction is made between solid waste and other types of (municipal) waste. From our comprehensive review we conclude in line with Qian and Schneider (2016: 19) that “To date, research on waste minimization practices within the tourism industry focuses primarily on the hospitality sector, is geographically limited, and addresses practices cross‐sectionally”. The same applies for studies about environmental management systems (EMSs). There is hardly any attention to other subsectors of the tourism industry such as for instance campsites or conference venues. Most studies are also case studies, mainly about a city, a region and even a single hotel. There seem to be relative much attention for tourist islands because there the problems with waste generation by tourists are particularly serious (Ezeah et al., 2015). These problems are more pressing where the number of people that stay on the island is more times larger than the resident population. This number is largest in the high season, but Arbulú et al. (2016: 252) calculate approximately 10 tourist per resident per year in Mallorca. They also comment that these islands face high opportunity costs of land needed for waste storage and processing, in particular in case of small geographic areas (op. cit: 257). Surprisingly there are also very few studies that deal with the result of EMSs (Environmental Management Systems) and green initiatives in terms of the amount of waste that is reduced or recycled. The studies that deal with this issue are either model simulations or aim at best practices. This section is organised as follows. After a comprehensice summary on European waste statistics (3.2.1) we begin or review with some literature about waste generation by tourism (3.2.2). In 3.2.3 we focus on waste behaviour. By this we mean the behaviour of tourists about waste generation, recycling etc. at their destination. In 3.2.4 we focus on research concerning the implementation of EMSs in the hospitality industry and explain the roles of various stakeholders including employees. Finally, 3.2.5 deals with the local and regional policy framework of waste management in cities and tourist islands. A mature local or regional waste management system should combine these various topics into one integrated waste management plan (UNEP & GTZ, 2003). 28
3.2.1 Waste generation and treatment in the European Union In this chapter we give a brief overview of some basic statistics about waste generation and waste management practices in Europe on a country level. This info gives a general insight into the amount of (solid) waste and the way it is treated. Also information is gathered about the attitudes of European citizens about (their) waste generation and waste management practices. We conclude this chapter with an attempt to relate waste generation and management with tourism. European statistics about waste make a distinctions between waste generated by economic activities and households. Because there are no waste statistics which focus on tourism, we focus on waste generation by households to give a general impression of the magnitude of waste generation. In 2012 the total annual waste generation per capita in the EU (28 countries) was 4,982 kilograms. Most of the waste comes from economic activities. Households ‘only’ generated 423 kilograms of waste per capita. Across the EU Member States, waste generation by households ranged, in 2012 from an average of 232 kg per capita in Romania to 667 kg per capita in Denmark (see Figure 18). The variations reflect differences in consumption patterns and economic wealth. There are also variations in the composition of the waste generated by households (see also Figure 18). In 2012 on average in the EU 65% of the household waste is categorised in the category ‘mixed ordinary wastes’. On a country level this share ranged from 23% in Cyprus to 99% in Greece. Two other main waste categories arms recyclable waste (class, paper, metal, etc.) and animal and vegetal wastes (including food waste). Their share in the total household waste generation in the EU in 2012 was resp. 17% and 13%. We find the highest share of recyclable waste in Cyprus (55%) and the lowest share in Greece). These variations not only reflect differences in consumption patterns and economic wealth; it is also conceivable that differences in national statistics and data collection contribute to these variations. Another EU statistic that sheds light on the waste generation of households is that of municipal waste. These data are widely used for comparing municipal waste generation and treatment in different countries, and as indicators to monitor countries’ waste policies. These data are also often used as a proxy for quantities of (municipal) solid waste (European Environment Agency, 2013). Municipal waste is defined by Eurostat as follows: ‘Municipal waste is mainly produced by households, though similar wastes from sources such as commerce, offices and public institutions are included. The amount of municipal waste generated consists of waste collected by or on behalf of municipal authorities and disposed of through the waste management system’.1 Unlike the general Eurostat waste statistics, its municipal waste statistic provides no information on waste composition. However, it has information over waste treatment and data is available over a longer period of time (1995‐current) than the general waste statistic. For Europe as a whole the amount (measured in kilograms per capita) of municipal waste is larger than the amount of waste generated by households. In 2012 the amount of municipal generation waste was 485 kilograms per capita vs 423 kilograms per capita waste generated by households. The differences 1
Eurostat, Reference Metadata in Euro SDMX Metadata Structure (ESMS).
http://ec.europa.eu/eurostat/cache/metadata/en/env_wasmun_esms.htm accessed 1 august 2016.
29
by country between these figures are displayed in Figure 19 and show that these are most countries in line with the waste generation by households. The differences in municipal waste generation not only reflects differences consumption patterns and economic wealth, but also on how municipal waste is collected and managed.2 Figure 18 Total waste generation by households in Europe in 2012 in kilograms per capita by country. 2
Eurostat:
http://ec.europa.eu/eurostat/statisticsexplained/index.php/Municipal_waste_statistics#Data_sources_and_availability accessed 1 august
2016.
30
Iceland
Denmark
Latvia
Netherlands
Cyprus
Italy
Norway
Austria
Luxembourg
France
Spain
Germany
Portugal
Belgium
Sweden
Greece
United Kingdom
European Union (28 countries)
Lithuania
Bulgaria
Malta
Ireland
Estonia
Finland
Slovenia
Czech Republic
Slovakia
Croatia
Hungary
Poland
Romania
0
100
200
300
400
500
600
700
800
Kilograms per capita
Recyclable wastes
Animal and vegetal wastes
Mixed ordinary wastes
Remaining
Source: Eurostat (Waste Statistics). Figure 19: Comparison between the waste generation by households and municipal waste generation in Europe in 2012 in kilograms per capita by country. 31
Iceland
Denmark
Latvia
Netherlands
Cyprus
Italy
Norway
Austria
Luxembourg
France
Spain
Germany
Portugal
Belgium
Sweden
Greece
United Kingdom
European Union (28 countries)
Lithuania
Bulgaria
Malta
Ireland
Estonia
Finland
Slovenia
Czech Republic
Slovakia
Croatia
Hungary
Poland
Romania
0
100
200
300
400
500
600
700
800
Kilograms per capita
Total municipal waste generation
Total waste generated by households
Source: Eurostat (Municipal waste statistics). Differences in the management of municipal waste are show in Figure 20. In 2013 in the EU (28 countries) landfill was the largest municipal waste treatment category (31%), followed by recycling (27%) and incineration (26%). Although landfill is still the largest category its share has dropped significantly from 64% in 1995 to 27% in 2013 (EU‐27). Despite this decrease landfill still shows considerable variance between European countries (86% in Malta and 1% in Sweden). For incineration this variance between countries is smaller but still considerable (64 in Estonia to 0% in Latvia, Cyprus, Croatia and Malta). Recycling ranges from 47% in Germany to 5% in Romania. 32
Figure 20: Municipal waste treatment by type of treatment and country in 2013 (in % of total waste treatment). Malta
Croatia
Cyprus
Latvia
Romania
Greece
Slovakia
Bulgaria
Hungary
Lithuania
Poland
Czech Republic
Spain
Portugal
Iceland
Slovenia
Ireland
Italy
United Kingdom
European Union (28 countries)
France
Finland
Luxembourg
Estonia
Austria
Norway
Denmark
Netherlands
Germany
Belgium
Sweden
0%
Landfill
10%
20%
Incineration
30%
40%
Recycling
Source: Eurostat (Municipal waste statistics). 50%
60%
70%
80%
90% 100%
Composting
3.2.1.1 Attitudes towards waste generation The EU conducts various surveys among its citizens to investigate the motivations, feelings and reactions towards the environment, waste generation and waste management. In the survey about attitudes towards the environment the respondents were asked to select the five environmental issues that worried them most (European Commission, 2014a). In 2014 56% of the respondents stated that they are worried about air pollution, 50% about water pollution, 43% 33
about the impact on health of chemicals used in everyday products and 43% about the growing amount of waste. The growing amount of waste worries a relatively high proportion of respondents in the Czech Republic (61%), Hungary (59%), Finland (57%), Croatia (55%) and Slovakia (55%). At the other end of the scale, less than a third of people say they are worried about this in Spain (30%) and the Netherlands (32%). The data show that women are more likely than men to worry about growing amount of waste (46% vs. 41%). Age and education hardly differentiate between the answers. These proportions hardly differ between age groups and levels of education. In a survey about attitudes towards waste management and resource efficiency respondents were asked if they agreed with the statements that their country and households generated too much waste (European Commission, 2014b). In 2014 a majority of the respondents across Europe (87%) considered that their country generates too much waste. Interestingly, only half of this large share, a minority of 43%, believed that their own household did the same. In Figure 21 the outcomes for each country are presented. This figure shows that the range in country shares total ‘agree’ with both statement are the same (27%). However, a higher percentage on one statement did not always corresponds with a higher percentage on the other statement. For The Netherlands and Denmark the difference between the scores on both statements was 28 percent‐points, whereas in the United Kingdom and Hungary it was 53 and 54 percent‐points. Figure 21: Share of respondents that total agree with statements my household is generating too much waste and my country is generating too much waste by country in 2014. 34
Netherlands
Denmark
France
Slovenia
Spain
Sweden
Ireland
Belgium
Austria
Greece
Lithuania
Luxembourg
EU 28
Portugal
Cyprus
Malta
Finland
United Kingdom
Germany
Croatia
Italy
Romania
Hungary
Bulgaria
Estonia
Poland
Slovakia
Czech Republic
Latvia
My household is generating too
much waste (total 'agree')
My country as a whole is
generating too much waste (total
'agree')
0%
20%
40%
60%
80%
Source: European Commission (2014b: 17‐18). 100%
Regarding respondent socio‐demographic characteristics, women are slightly more likely than men to agree with the statements that their household is generating too much waste (45% vs. 42%). Age and education are more important factors on the issue of whether the respondent’s own household is generating too much waste (see Table 1). While a majority (51%) of 25‐39 year‐olds agree with this statement, only 35% of people aged 55 and over do so. The respondent’s level of education is also important to this issue: 48% of people who finished their education aged 20 or over agree that their household is generating too much waste, compared with 35% of people who left school aged 15 or under. Table 1: Percentage total ‘Agree’ (total of totally and tend to agree) for the following My country generates too My household generates too 35
EU 28 Sex Male Female Age 15‐24 25‐39 40‐45 55+ End of education (age) Until 15 year of age 16‐19 20+ Still studying much waste 87% 85% 90% 88% 87% 88% 88% 85% 88% 88% 88% much waste
43%
42%
45%
42%
51% 47% 35%
35%
41%
48%
42%
Source: European Commission (2014b:). It is interesting to see whether the scores on the statement that a household generates too much waste, corresponds with the actual amount of waste generated. To analyze this we correlate the waste generated by households per capita (see Figure 18) with the scores on the statement “My household generates too much waste”. The correlation coefficient is 0.46 witch indicate a positive relationship on the country level. So at the country level it seems as if households that generate larger amounts of waste more likely agree with the statement that they generate too much waste (see also Figure 22). 36
Figure 22: Correlation between the amount of waste generated by households (2012) and the statement that my household is generating to much waste by country (2014). Waste generater by households in kg per capita 2012
800
700
600
500
400
300
200
100
0
20
25
30
35
40
45
50
55
60
65
70
My household is generating too much waste (% total 'agree')
Source: European Commission (2014b) and Eurostat (Waste Statistics). 3.2.1.2 Waste management behaviour Most Europeans practice some form of waste management behaviour. According to the survey ‘Attitudes of European citizens towards the environment’ in 2014 (European Commission, 2014a), 72% of the respondents separated most of their waste for recycling, while 33% reduced waste (e.g. by avoiding over‐packaged product and buying products with a longer life). Both percentages are relatively stable over time. In the 2004, 2007 and 2011 surveys, the shares of respondents that separated waste for recycling were roughly twice as high as the shares of respondents that reduced waste. Waste management behaviour shows large differences across the EU. In several EU member states separating waste for recycling is particularly common. In seven countries, over four‐fifth of the respondents did so: Slovenia (92%), Luxembourg (92%), Sweden (86%), Ireland (84%), France (82%), Belgium and Malta (both 81%). On the other hand fewer than half did so in four countries: Bulgaria (23%), Romania (33%), Latvia (39%) and Croatia (49%). Reducing waste is most common among respondents in Germany (52%), Austria (49%) and Belgium (44%), but least common among those in Bulgaria (15%) and Portugal (18%). 37
High scores on separating waste for recycling do not always correspond with high scores on waste reduction. For Luxembourg high scores for separating waste for recycling go hand in hand with high scores on waste reduction, but this is not the case for Slovenia and the Czech Republic. This may imply that differences between EU member states can be explained by individuals’ attitudes towards waste, but also that institutional differences about waste management practices between countries are important. Differences in the share of people who reduce waste may also be related to differences in consumption patterns and economic wealth, which is partly reflected in the amount of waste generated by households. However, there is hardly a correlation between the amount of waste generated by households (Figure 18) and the share of respondents that reduce waste (correlation coefficient is 0.09). Also there is no correlation between the amount of waste generated by households and the share of respondents that separate waste for recycling (correlation coefficient is 0.07). It seems that women are somewhat more likely than man to take environmentally‐friendly measures. More woman than men are engaged in reducing waste and separating waste for recycling, although the differences are relatively small (see Table 2). Both age and education are also correlated to the level of waste reduction and separating waste. As respondents become older they are more likely to reduce waste and separate waste, however this trend stops in for the group respondents over the age of 55. Education is also positively related to both the reduction of waste and the separation of waste. Figure 23: Percentage of respondents that reduce waste and separate most of waste for recycling in 2014 by country. 38
Germany
Austria
Ireland
Finland
France
Spain
Sweden
Reducing waste
Hungary
Separate most of waste for
recycling
Slovakia
Netherlands
Latvia
Greece
Cyprus
Czech Republic
Bulgaria
0%
20%
40%
60%
Source: European Commission (2014a: 27). 80%
100%
Table 2: Percentage respondents who separate most of their waste and who reduce waste by sex, age and education in 2014. EU 28 Sex Male Female Age 15‐24 25‐39 40‐45 55+ Separate most of waste for recycling 72% 70% 74% 63% 69% 75% 75% 39
Reduce waste 33%
30% 36%
23%
32%
38% 35% End of education (age) Until 15 year of age 16‐19 20+ Still studying 70% 72% 77% 65% 31%
34% 38%
22%
3.2.2 WASTE GENERATION BY TOURISM In their paper on tourist destinations in the Ukrainian Carpathians, Murava and Korobeinykova (2016: 43) observe the urgency to identify the waste problem in order to design a waste management system (WMS) in order “to meet the growing demand of customers for environmentally friendly conditions of recreation”. In many papers, these data are given for the total flow of municipal solid waste but the contribution by tourism is not distinguishable. That quantity can be estimated by multiplying the number of tourist‐days in a tourist destination by a figure for the average amount of solid waste that each tourist generates per day. Not surprisingly, Pirani & Arafat (2014: 322) comment that “there is much variation between hotels when it comes to how much waste per room they are generating on a daily basis. This is because the waste generation rate depends on many variables such as the hotel type, guest attributes, guest and employee activities, and occupancy rate.” This ‘forces’ research into the amount, or percentage of municipal waste generated by tourism into locally specific estimations rather than calculating with the 1 kg per day per tourist. Both Fortuny et al. (2008) and Mateu‐
Sbert et al. (2013) suggest a method that takes the seasonal fluctuation of tourism into account.3 Fortuny et al. (2008) explain differences in total amounts between calendar months in a tourist destination by the monthly differences in its total population due to number of tourist‐days divided by the number of days in that month. These authors themselves only conclude that “a huge amount of the total solid municipal waste generated each year is produced by tourists activities” by comparing the data on the amount generated per person‐day in winter and summer in the Balearic Islands in 2004: resp. 1.50 and 2.50 kg (op. cit.: 861). The average figure in 2004 was 1.82 kg. The conclusion that the contribution of tourism to (municipal) waste generation is both large and increasing is shared by quite a number of authors (e.g. Cummings, 1997; Dileep, 2007; Pirani & Arafat, 2014; Arbulú et al., 2015; Matai, 2015; Murava & Korobeinykova, 2016). According to Arbulú et al. (2015: 634), “[…] tourism tends to produce more municipal solid waste than other productive activities”. This is related to the growth of tourism as one of the largest industries in the world (Dileep, 2007: 378). Moreover, as an economic sector, tourism has suffered 3
Various studies stress that the seasonal fluctuation in the amount of tourists can have a
large effect on the total amount of waste generation (see for instance Rada, et al., 2014: Ranieri et
al. 2014).
40
relatively little, if at all, of the global economic downturn that started in that same year 2007. Referring to the hotel industry only, Matai (2015: 1445) remarks that “it is expected [to] generate[s] huge amounts of waste since it has been identified as the largest consumer of durable and non‐durable goods”. Similarly, Zorpas et al. (2015: 1142) observe that hotels “occupy a crucial place in concerns over environmental protection related to tourism and travel”. Regarding the composition of the waste that is generated by the tourist industry, quite a few various types are discerned from different ‘departments’ ‐ food and beverage (e.g. food, glass), administration (office waste like paper, ink cartridges, printers and computers), and household (cleaning materials, plastic bottles etc.) ‐ and old furniture, bed linen and towels. Most explicit attention in literature is being paid to food waste (e.g. Pirani & Arafat, 2014; Sullivan Sealey & Smith, 2014): a very significant type in the hospitality industry of hotels and restaurants, the branch of tourist industry that produces most of its solid waste. On a high level of generalisation, Pirani and Arafat (2014: 321) comment that food waste “can account for more than 50% of the hospitality waste”. In the UK, about 920,000 tons of food is wasted in the hospitality sector, 75% of which ‐ equivalent to 1.3 billion meals ‐ is avoidable (op. cit. 328). This average of over 50% is composed of approximately 40% from hotels and 60% from restaurants (op. cit.: 334). 3.2.3 WASTE BEHAVIOUR In 2012 Myung et al. (2012) reviewed environment related research in scholarly journals for the period from 2000 to 2010. In total they found 58 articles of which sixteen deal with consumer behaviour. Twelve of these studies focus on the lodging sector and three on restaurants.4 All these studies examined micro consumer behaviour such as specific belief, knowledge, attitudes and their relationship to behavioural intentions and behaviour. The majority of research focused on measuring environmental awareness or concern to establish a relationship between these measures and environmentally related behaviour such as willingness to pay, use of green products, enhancement of the image of a hotel, and interest in energy conservation and recycling. Myung et al. (2012: 1269) concluded that “these studies often found contradictory results”. They do not go into possible reasons for this. For the case of ‘willingness to pay’ Kang et al. (2012) give possible explanations. They found several studies that revealed a gap between customers’ perceptions and attitudes towards corporate social responsibility concept (such as green initiatives) and their actual purchasing behaviour, while other studies show that company’s specific socially responsible initiatives seem to positively influence purchasing behaviour. So, consumers’ positive perceptions and attitudes towards environmental issues do not necessarily lead to a willingness to pay for a company’s green initiatives. For instance, if customers identify a company’s motivation as one of increased self‐interest (such as profit enhancement and not public service) customers’ willingness to pay for 4
One other study deals with the relationship between environmental attributes and customer
satisfaction.
41
green initiatives may turn negative, despite positive perceptions for environmental issues. Also, customers’ willingness to pay for green initiatives vary according to hotel types or segments. Another possible explanation for the contradictory results between studies that can be derived from the work by Kang et al. is the heterogeneity of the samples of various studies. For example the level of environmental concern may differ between countries which affects not only the consumers’ behaviour, but also the likelihood that hotels will introduce green initiatives. Also cultural differences may play a role, for instance cultures with a higher degree of ‘power distance’ may generate a lower degree of people’s involvement in open discussions and decision‐making processes for social responsibility, which consequently leads to less interest in green initiatives in countries with greater power distance.5 The last explanation is that the studies were conducted in different time periods and that concern for environmental issues in the hospitality industry has grown incrementally over time. This implies that more recent studies can have substantially different outcome than ‘older’ studies. In their research Kang et al. (2012) among U.S. hotel guests found that guests with higher degrees of environmental concerns declare a higher willingness to pay premiums for hotels’ green initiatives. Also, they found that luxury and mid‐priced hotel guests are more willing to pay premium for hotels’ green practices than economy hotel quests. Contrary to previous studies, Kang et al. found that male customers showed a greater willingness to pay such a premium than female customers. They ascribe this to different responsibilities for pro‐environmental action in households (men are more often responsible for outside practices) in combination with an overrepresentation of men in the survey. Like Kang et al. (2012), Han et al. (2009) also found that a green hotel’s overall image significantly affected the willingness to pay more for these hotels. Although this counts for both women and men, the relationship is stronger for female customers than for male customers. In the studies by Ranieri et al. (2014) and Rada et al. (2014) interesting claims are made about waste behaviour of tourists. These studies are based on aggregate data on community levels, so their conclusions are not based on data on the level of individual tourists. The case study analysis of Ranieri et al. (2014) in two Italian and one Romanian tourist areas – resp. a Province, a region and a County ‐ records that inefficient behaviour of tourists in selective collection (source separation for recycling) of solid waste contributes to the increase in the amount of residual municipals solid waste. One of the problems the authors observe is that tourists at their tourist destination have to be accustomed to a waste collection generally quite different to their area of original. “A tourist could have a too short time to learn the rules of the collection system before the end of the holiday” (Ranieri et al, 2014: 283). They also assume that mountain tourists are more careful about selective collection compared to other tourists. Contrary to the study of Ranieri et al. (2014), Rada et al. (2014) found in their study in five communities in the Province of Trento (Italy) that the seasonal variations in the number of tourists 5
Power distance is the extent to which less powerful members of organizations and
institutions accept and expect that power is distributed unequally.
42
hardly seem to influence the selective collection efficiency. These authors claim that “the trend of tourists towards shorter periods of holiday does not affect selective collection; possibly because they are used to coming back to the same municipality, where they have already learned the local principles of source separation” (Rada et al. 2014:187). The studies by Ranieri et al. (2014) and Rada et al. (2014), together with the findings of Kang et al. (2012) suggests that there are different ‘types’ of tourists concerning their waste behaviour, not only by socio‐demographic characteristics’, attitudes to green behaviour, but also by country of origin and destination. A study that empirically compares pro‐environmental behaviour of tourist at home and at their tourist destination was done by Miller et al. (2015) and looked especially at the poorly understood belief that pro‐environmental behaviour weakens when residents become tourists. Either tourists feel more morally obligated in their own communities, or alternatively destinations may not provide an infrastructure that supports environmentally friendly behaviour. After a survey among visitors to Melbourne (Australia), Miller et al. concluded that although paper and plastic recycling were frequently done in both the domestic and tourist context, a recycling drop of 16% was observed which was higher than other pro‐environmental behaviours such as green transport use, energy use and green consumption. Interestingly Miller et al. (2015) found that attitudes are not statistically significant related to recycling in the tourism context, whereas habits of domestic recycling, the availability of recycle bins and the sense of tourist social responsibility are. They suggest that the findings regarding attitudes can be explained by the way the relationship between attitudes and actual behaviour may broke down. “Environmental attitudes may be strongly held, but when exposed to greater challenges and difficulties in a tourism context, they are less likely to be fulfilled in behaviour. Attitudes, per se, are not a strong predictor of urban tourist pro‐environmental behaviour”6. Domestic habits seem to play a slightly lower role in explaining vacation recycling than in domestic recycling. An explanation by Miller et al. . (2015:?)7 is “…that recycling behaviour is institutionalised in the home city, with a convenient, regular, and tightly controlled waste and recycling pick‐up service. Therefore, the household exerts minimal cognitive effort in the home city, just fitting in with a house‐to‐house pre‐scheduled service. The same household in a mass tourism destination has no scheduled system and that leaves the household members to their own devices, experiencing moderate rather than high habit carry‐over”. 3.2.4 Environmental Management Systems (EMS) in the tourist sector and the hospitality industry According to Pirani and Arafat (2014: 333), “….environmental management is increasingly becoming a standard part of policy in the hospitality sector”. The longitudinal study by Qjan and Schneider (2016) about waste mineralization practices in the tourism industry sectors in de U.S. 6
7
Pdf at moment of citing (August 17, 2016) not available on publisher website.
Pdf at moment of citing (August 17, 2016) not available on publisher website.
43
state of Minnesota does confirm this quote and concludes that the tourist industry has an ‘active’ engagement in waste minimization, which progressed over time. However, the low implementation rate of some practices indicates that the tourism industry still need assistance to adopt waste minimization practices. Overall, the literature review of implementation of environmentally conscious waste management practices in this section also pays attention to critical factors that oppose their implementation. There is a relative substantial literature about the implementation of Environmental Management Systems (EMS) in the tourist sector and the hospitality industry in particular. Although EMS is dealing with more issues than solid waste alone, policies to reduce waste is a fixed part of an EMS. However, as Pirani and Arafat (2014) already concluded, these studies hardly focus on the waste management aspect of environmental management. Nevertheless, some provide insights in the (barriers and opportunities of) implementation of EMS in the hospitality industry and can shed light on behaviour of actors in the hospitality industry such as hotel organisations, managers and employees. Chan and Hsu (2016) and Waligo et al. (2013) stress the important role of all stakeholders for the implementation of EMSs and sustainable tourism. “Implementing a successful environmental programme depends on the full co‐operation and involvement of a hospitality firm’s stakeholders, including employees, customers, suppliers, business partners and governments. The introduction of a firm’s environmental programmes may result in resistance from some stakeholders because of changes in routine operations” (Chan & Hsu, 2016: 905). However, they also conclude that this issue has received limited interest from hospitality researchers. Prevention of food waste can be achieved by Food & Beverage Departments, more in particular the kitchen and salon staff. Referring to avoidable causes of food waste as listed by Pirani and Arafat (2014: 329), this can be realised rather directly by improving the storage of the food stock, the size of preparation and portions, the frequency of delivery of ingredients, and the forecasting of demand. Radwan et al. (2012: 535) word a shared opinion in literature that “Waste reduction in hospitality industry should start at the point of purchasing […]”. ‘Green Purchasing’ is an environmentally conscious practice which reduces waste at source and increase the potential for re‐using and recycling of purchased material”. A comparable practice is ‘Buying Recycled’ that has the additional benefit of creating demand for the recyclables that the industry collects (Snarr & Pezza, 2000: 12). Environmental consciousness by those in charge of purchasing is the more important because buying green or recycled substitutes is ‘not always’ (an understatement…) the economically most viable or a readily suitable type. Moreover, it is often supressed by lack of awareness and of information, in particular in the case of small‐scale hoteliers (Matai, 2015: 1447; Radwan et al., 2012: 535). One of the key elements of waste management is to get inside in the amount and the composition of (solid) waste. A waste audit is an essential component of ‘waste mapping’, presented by Pirani and Arafat (2014: 326 – 7) as a “… relatively new strategy which is being increasingly used by organizations [hospitality industry] to facilitate more effective waste management. It helps the establishments understand where and how waste occurs, and how much it is really costing them. 44
[…] which types of waste are generated, in what amounts, and in which locations”. Owen et al. (2013: 8) prepared a Waste Mapping Guidance for the hotels in Cyprus according to four steps: Step 1: Develop a simple site plan. Step 2: Complete a site walk round and map the waste types and locations
Step 3: Create an activity map to show costs of resources used and how / why waste is produced in key activity areas Calculate the true costs of waste Step 4: Complete an opportunity action plan for the hotel
Prioritise actions, assign responsibility and start making savings.
Businesses in the hospitality and tourism industry can apply for various ecolabels or other certification schemes which (if awarded) express their commitment to the environment. These schemes are largely voluntary and can be very expensive to acquire. The varying marketing power of these schemes depends on what part of the world the business is located in, but in generally is quite limited. “After all, how much importance a tourist gives to environment issues is highly dependent on where they are from [see also 3.2.3].[ ….]. As a result, hotels also shape their environmental politics’ accordingly; putting more green policies into place if they expect to have more guests for whom environmental issues take priority” (Pirani and Arafat, 2014: 332). Nevertheless, Chan and Hsu (2016) conclude in their review paper that the effectiveness of green marketing strategies is ‘questionable’. Although Pirani and Arafat (2014: 333) comment that “….environmental management is increasingly becoming a standard part of policy in the hospitality sector”, they also state “..that implementing ‘green strategies’ is not necessarily a straightforward process. In some countries there are still no sufficient regulations to support such eco‐friendly initiatives and even if a supportive framework exists, implementing the different strategies may not be judged to be in the best interest of the property, either from a financial, marketing, or social perspective, etc.” (op. cit.: 333). They point out that it is mainly the larger establishments who have been implementing environmental management practices. The other side of the coin is their overview of various, partly overlapping reasons why small businesses are reluctant to implement environmental management practices. Some of these are confirmed by the study of Radwan et al (2012) on solid waste management in small hotels in Wales: 

Smaller establishments do not always have the financial means or administrative structure’s to make EMS possible. Managers of small businesses are less interested in carrying out environmental management in general and waste management in particular, due to the fact that their 45



businesses are generating small quantities of waste which many waste carriers are not interested in. Managers of small businesses are less motivated because it is their feeling that the waste quantities their properties generate are not significant enough to make viable their spending of time and money on sorting and recycling of waste. These managers also feel that these practices are more a responsibility of larger businesses’. Smaller establishments may not have access to relevant information and guidelines or may not have time or motivation to implement eco‐friendly practises. Managers of small businesses felt that there is not enough support was provided by external stakeholders such as local governments. Chan (2011) who was not cited by Pirani and Arafat, also looked at the obstacles for implementing EMSs in small‐and medium‐sized hotels (in Hong Kong). He indicated five factors that can hinder the adoption of EMSs in these hotels. In descending order, they are (1) lack of a sense of urgency, (2) ambiguity of EMS standards, (3) lack of qualified verifiers/consultants, (4) conflicting guidance, and (5) inconsistent support. Some of these factors show resemblance with the factors that Pirani and Arafat found in their literature review (particularly 1 and 5) but others do not. These later factors focus on formal EMS practices, like the confusion among managers about different EMS standards in the market and the sometimes too complex guidelines to be comprehended by small and medium‐sized hotels. Also, mangers of these hotels indicated that EMS implementation is an “…interrupted and interruptible process that is likely to affect their existing system and core business” (Chan, 2011:15‐16). Behavioural intentions are an important dimension to explain the differences that are brought to the fore by some authors between small and large hotels about how they put waste management into practice. Leaving aside the exact definitions of small and large hotels – usually measured in numbers of beds but without undisputed lower and upper boundaries (for some examples, see Radwan et al, 2012: 534) ‐, sustainable or eco‐tourism is habitually associated with small‐scale accommodations and non‐sustainable or standard 3S tourism (sand, sea and sun) with large scale hotels (Fortuny et al, 2008). Due to their eco‐label, these small accommodations generate less waste per guest‐day than the large hotels by definition. This conclusion does not hold for all small hotels, however. Quite the contrary: small hotels in general are less willing or less able to implement measures that support the environmental sustainability of their everyday activities. This is a matter of either high costs in terms of money and time, awareness or insufficient staff skills, but also the absence of efficient waste collecting and disposal mechanisms. In fact, the amount of waste each generates is too limited to be economically beneficial for a waste carrier. What is more, certain tools to improve the environmental sustainability of hotels are not only expensive to obtain, but also aimed at large companies with totally different organizational structures (Fortuny et al., 2008). Waste management of quite a few large hotels also balance between economic performance and ecological sustainability, but these are more inclined to adapt to the growing market of environmentally consciousness customers. Radwan et al (2012: 533) then, refer explicitly to small hotels when they state that “solid waste generation and disposal is one of the[ir] most negative environmental impacts”. 46
The hoteliers that were interviewed by Radwan et al (2012: 538) in their research of the effects of accreditation of small hotels for Green Dragon Environmental Standard (GDES) eco‐label mentioned various suggestions for the government to improve the environmental responsibility of the hotel industry: 



Training in ‘how and where’ of environmentally more friendly practices than landfill Simply enforce environmental responsibility by lawmaking Offering an award to eco‐friendly hotels which would enable them to gain competitive advantages amongst more environmentally consciousness tourists Building up networks of entrepreneurs in the hospitality industry and with related stakeholders in tourism sector as a whole, in order to exchange ideas and information, mutual learning etc. A precondition for the first and second is the availability of more environmental friendly alternatives for landfill and composting. To address the obstacles of implementing EMS in small businesses, Pirani and Arafat (2014) suggest that small hotels in close proximity to each other may work together to achieves sustainable waste management targets. Interestingly they also found a study about the Michican’s (USA) lodging sector that smaller properties are more likely to segregate and recycle the waste from guest rooms, than to conduct an overall recycling program. Chan and Hsu (2016) also conclude that many small tourism business owners are reluctant to implement environmental management. Based on research of Tzschentke et al. who found that “…the owners’ personal values and beliefs played a critical role, such that a greater understanding is needed of the complexity of motives that drive small hospitality business owners” (Chan & Hsu, 2016: 905). Tzschentke et al further found “… that the development of environmental consciousness and personal, socio‐cultural and situational factors were all significant influences in convincing small hospitality operators to go green” (op. cit.: 905). Chan and Hsu (2016) stress the importance of ‘frontline staff’ for the execution of environmental measures. Although only a small amount of studies was found on this issue by Chan and Hsu, they point at potential personal problems as some employees may feel threatened when their existing responsibilities are changed, “especially when their responsibilities and authority are redefined to ensure that success of some environmental programmes” (Chan and Hsu, 2016: 905). An in‐depth single case study by Chan and Hawkins (2010 and 2012) in a deluxe class hotel in Hong Kong on EMS implementation show that it is a learning process in which problems and errors need to be detected and responded to on a continuous basis. Also, they recommend to establish an independent EMS unit and select and develop individuals to lead the EMS (Chan & Hawkins, 2012). Chan et al. (in press (a): 15) emphasise the importance of employees for a successful implementation of EMSs: “Because the hotel industry is labor intensive, greater employee awareness and concern about organizations’ environmental programs can not only improve employees’ involvement but also promote organizations’ environmental friendly images and reputations, which lead to customer satisfaction and loyalty.” Chan and Hawkins (2010) also point 47
at the importance of the employees for a successful implementation of EMS, but also observed possible obstacles: “The organisational motivations for implementing an EMS and the outcomes of the adopted system also have an impact on hotel employees. Meaningful organisational goals result in a more harmonious working environment and positively affect worker involvement in EMS implementation. Conversely, reduced employee commitment can be expected if an EMS is promoted as just another business strategy to save money and improve a company’s reputation. Emphasis of the better, safer and healthier working environment that results from EMS implementation and the achievement of ISO 14001 accreditation could make hotel employees more committed to their jobs.” (Chan & Hawkins, 2010: 649). Interestingly, Chan and Hawkins (2010) found in their case study that the EMS could have both positive and negative effects on hotel employees, which were triggered by several human resource factors, organisational motivations to adopt an EMS and option outcomes. Although EMSs can help promote a bottom‐up approach to change within predominantly top‐down cultures, a top‐down approach to EMS implementation was found to be more suitable for a hotel with a predominantly Chinese workforce because of cultural issues. In a study that is still in press (a), Chan et al. conclude that environmental knowledge positively influences environmental concern and ecological behaviour among employees of international tourists hotels in Hong Kong. They underline the importance of environmental training for all levels of hotel employees. At first employees’ environmental awareness should be developed, which differs from just teaching hotel employees the required skills to improve the company’s desired environmental performance. In a later stage hotel management can take things a step further and encourage employees to consider what they can do to help reduce the effects of environmental problems by, for instance organizing different discussion sessions during training or placing suggestion boxes. Training should be provided continually and regularly. Environmental performance in the tourist sector can also be improve by the implementation of technology. In hotels technology can be used for instance to sort solid waste and to compost kitchen waste. By interviewing senior staff in various hotel in Hong Kong, Chan et al. (2016) concluded that hoteliers appeared to use technology first and for all to save energy, rather than reducing solid or food waste. The technologies that were used on a small scale are compressor or packing machines to compress paper and amply plastic bottles for recycling; food waste decomposers to handle hotels’ leftover food (which reduces the quantity of waste) and paperless systems such as the iPad. Although food waste decomposers were hardly used, some hotel managers desired them, despite high costs and technical constraints. In their study in press (a), Chan et al observed among the same hoteliers various types of barriers to the adoption of environmental technology, although without specifying the barriers that are especially related to technologies that manage or reduce solid waste. In spite of a substantial literature about the EMSs in the tourist sector and the hospitality industry in particular, there are hardly any studies which investigate the effects of EMS on waste minimization or waste collection for recycling. The few exceptions are studies that present either model estimations of the effects (for instance Singh et al. 2014) or inventories of good practices 48
(for instance Styles et al., 2013). Based on various examples of waste prevention schemes, Styles et al. (2013: 325) state that “..implementation of waste prevention measures could easily lead to a reduction in waste‐incurred environmental impact of 30% to 50% for average hotels and other accommodations.” They also estimate 84% waste recycling rate as a benchmark for excellence in the hotel sector.8 3.2.5 LOCAL AND REGIONAL POLICY FRAMEWORK In recent years, several authors have suggested that promotion of cooperation between public and private sectors is an important strategy to achieve more efficient results of waste management (Arbulú et al, 2016: 253). These authors analyse the main characteristics, problems and challenges of PPPs (Public Private Partnerships) in municipal solid waste management in the ‘mature’ tourist destination of Mallorca. PPPs in this public service of municipal waste collection, storage and treatment imply the sharing of activities, risks, costs and benefits between public and private actors. Regarding activities, the public sector in Mallorca is responsible for most of planning and supervision of the whole MSWM system, including the setting of environmental goals, whereas the private sector focuses on design, investment, planning, management and supervision of all the technical operations of MSWM facilities, including waste treatment. A successful PPP in MSWM requires adequate policies that set environmental goals, with consequences for issues like needed labour input and required technical facilities, and a legal framework that regulates the division of responsibilities between multi‐level public authorities. In Mallorca these are municipalities, the island council and Balearic government. What is more, agreement has to be reached on the tariffs that the government pays as its client to the private sector. Tourism has a strong impact on PPPs in waste management in tourist destinations like Mallorca and other islands because tourist arrivals multiply the population in high seasons, in Mallorca by a factor 10. According to Arbulú et al (2016: 255,), “the economic effects of seasonality is the problem to define the optimal infrastructure size”. To put it in other words: overcapacity of such high fixed capital structures costs money (op. cit.:256). This makes adequately balancing of revenues with capital investment and operational costs between public and private sector in order to achieve sustainability “the major challenge of the system” (Arbulú et al, 2016: 253). 8
Singh et al. (2014) use a similar percentage for their model estimation.
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3.3
Waste generation as a function of tourism 3.3.1 Introduction Munoz and Navia (2015) state that tourism is one of the most important industries worldwide and a driver for socio‐economic development in many regions, including countries with unique cultural, historic and natural resources. According to the World Tourism Organization (UNWTO), international tourism revenues reached a record of US$ 1,245 billion in 2014. Moreover, an additional US$ 221 billion was generated from international passenger transport, bringing total exports from international tourism up to US$ 1,500 billion. However, tourism has been recognised as a high energy and water resources demanding activity, simultaneously generating significant amounts of solid wastes from lodgings and recreational areas. On the global scale, this situation has been already highlighted by the United Nations Environment Programme (UNEP). In fact, during 2011 UNEP estimated a worldwide solid waste generation of 4.8 million t just from international tourism, representing about 14% of the total municipal solid wastes generated during this year. The World Tourism Organisation (2016) estimates, that the global international tourist arrivals increased approx. with the factor 50 in the period 1950 to 2015 (see Table 3). Similarily, the receipts increased in the same period, yet with a factor 630. 1950 1980 2000 2011 2015 Global international tourist arrivals [million] 25 278 674
980
1,186
International tourism receipts earned by destinations worldwide [billion USD] 2 104 495
710
1,260
Table 3: Development of global international tourist arrivals 1950 – 2015;Source: World Tourism Organisation (2016) In addition the World Tourism Organisation states, that international tourism now represents 7% of the world’s exports in goods and services, up from 6% in 2014, this means tourism has grown faster than world trade over the past four years. The World Tourism Organisation (2016) also estimates, that the Americas and Asia and the Pacific both recorded close to 6% growth in international tourist arrivals, with Europe, the world’s most visited region, recording 5%. Arrivals in the Middle East increased by 2%, while in Africa they declined by 3%, mostly due to weak results in North Africa, the main factors of influence on tourism flows for 2015 are reported as strong exchange rate fluctuations, the decline in the price of oil and other commodities, and increased global concern about safety and security. 50
It is furthermore depicted, that France, the United States, Spain and China continued to top the rankings in both international arrivals and receipts. In receipts, Thailand climbed three places to 6th position, and Hong Kong (China) climbed one place to 9th. Mexico moved up one position to come 9th in arrivals. China, the United States and the United Kingdom led outbound tourism in their respective regions in 2015, fuelled by strong currencies and economies. International tourist arrivals worldwide are expected to increase by 3.3% a year between 2010 and 2030 to reach 1.8 billion by 2030, according to UNWTO’s long‐term forecast report Tourism Towards 2030. Between 2010 and 2030, arrivals in emerging destinations (+4.4% a year) are expected to increase at twice the rate of those in advanced economies (+2.2% a year). The market share of emerging economies increased from 30% in 1980 to 45% in 2015, and is expected to reach 57% by 2030, equivalent to over 1 billion international tourist arrivals. Depending on the means of transport and the destination, the trip to tourist destinations may contribute to the overall environmental impact of tourism (Gössling et al., 2005). According to the World Tourism Organisation (2016), in 2015, slightly over half of all overnight visitors travelled to their destination by air (54%), while the remainder travelled by surface transport (46%) – whether by road (39%), rail (2%) or water (5%). The trend over time has been for air transport to grow at a somewhat faster pace than surface transport, thus the share of air transport is gradually increasing. Regarding the motivation to go on a trip it is estimated, that travel for holidays, recreation and other forms of leisure accounted for just over half of all international tourist arrivals in 2015 (53% or 632 million). Some 14% of all international tourists reported travelling for business and professional purposes, and another 27% travelled for other reasons such as visiting friends and relatives (VFR), religious reasons and pilgrimages, health treatment, etc. The purpose of visit for the remaining 6% of arrivals was not specified. Tourism has a high impact related to different aspects, on the one hand it is a worldwide important economic sector,10% of the world´s GDP is directly or indirectly generated by the tourism sector, one out of eleven jobs are related to tourism. Beside the economic implications, 1.1 billion tourists every year have environmental impacts – beside emissions from transport and the impacts of all necessary infrastructure (airports, hotels etc.) there is a high impact on natural resources (renewable and non‐renewable), incl. water resources. Chapter 3.3.2 gives a short overview on touristic impacts. Despite the impacts, there are many initiatives, international and national labels focussing on promoting sustainable tourism9 or initiatives to reduce impacts related to tourism. Other initiatives are related to reduce impacts on greenhouse gas emissions, e.g. including possibilities to compensate for emissions baesd on air travelling, but also related to waste management, e.g. ISO 14,000 series or the EU eco‐management and audit scheme (EMAS), where waste management is an important part. Despite this, a general approximation to what sustainable tourism development (STD) may be, according to Weaver (2005) is: ‘‘A tourism product that seeks to avoid or minimize environmentally irreversible impacts and preserves 9
http://www.ecolabelindex.com/ecolabels/?st=category,tourism (Last access: 22.08.2016)
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cultural heritage at the same time as providing learning opportunities and contributing to the maintenance or improvement of local community structures, including positive benefits for the local economy’’. Related to waste management, tourism can play a major role in putting pressure on the waste management systems in touristic locations, this holds true especially in touristic regions with a high variation of tourism troughout the year. Munoz and Navia (2015) consider, that the high variation regarding solid waste generation in touristic locations depends on several factors, such as type and occupation rate of touristic installations, tourist attributes, season of the year and environmental legislation of the country. Because of the aforementioned facts, solid waste generation is nowadays considered as one of the most relevant environmental aspects from touristic activities, especially owing to the fact that many of the establishments that make up this sector, such as hotels, bars and restaurants, use large quantities of expendable single‐use consumer goods as part of their operations. In addition, tourists are not always aware of how waste management in a specific region is supposed to function. As tourists are there for just a short period of time, it is unlikely that they will adapt to a specific need of the solid waste management system. This seems to be the reason why solid waste management systems in touristic regions have their own rules. Moreover, this reality is even harder when tourism is concentrated in one season only, like winter or summer, putting even more stress into waste management systems as the generated solid wastes mass and volume flow is totally season dependent. Without a doubt, solid waste generation rates in touristic regions can be significantly higher compared with municipal solid waste generation, a situation that can lead to serious environmental impacts, particularly in the case of low density population touristic regions without sufficient infrastructure in place to deal with wastes generated by the relatively small indigenous population. Besides, in several zones of high touristic interest, visitor amounts can even overcome the volume of wastes generated by the local population during the ‘high season’. Many studies have reported the phenomenon where municipal solid waste increases as the seasonal population of the tourist areas or regions rises, e.g. Shamshiry et al. (2011), Espinosa Lloréns et al. (2008), Teh and Cabanban (2007), and Mateu‐Sbert et al. (2013). As Munoz and Navia (2015) report, inefficient solid waste management operations can produce contrary effects in touristic regions, namely higher operational costs and blight owing to litter and contaminated water, reducing the touristic value of the otherwise attractive location. Therefore, high standard solid waste management programmes have become a must in touristic regions, which can also generate positive opportunities for the local community including higher competitiveness, new employment opportunities and even incrementing the touristic attractiveness by reducing environmental impacts. Regarding touristic regions, urban and rural areas must be distinguished. In urban touristic regions, such as cities and beaches for example, selective collection systems focused on recovering value from the waste stream via recycling may be the right approach. However, in rural areas or in geographically dispersed touristic regions, this strategy may be not applicable. In these areas, normally no formal recycling channels exist, because of low population and low normative control, negatively impacting the economic feasibility of recycling. Finally, and from a municipal point of view, solid waste minimisation in touristic activities should also become a major task in future waste management programmes, 52
aimed at reducing the costs for collection, transport and disposal, which may finally resound in more affordable costs for those touristic activities where the territory needs to be valorised (Munoz and Navia, 2015). 3.3.2 Tourism's three main impact areas According to the United Nations Environment Programme10 it is possible to detect three main impact areas of tourism: the depletion of natural resources, pollution and physical impacts. The depletion of natural resources includes (fresh) water resources, local resources like energy, food, and other raw materials, land resources like minerals, fossil fuels, fertile soil, forests, wetland and wildlife, natural resources (both renewable and non‐renewable). Tourism can cause the same forms of pollution as any other industry: air emissions, noise, solid waste and littering, releases of sewage, oil and chemicals, even architectural/visual pollution. Attractive landscape sites, such as sandy beaches, lakes, riversides, and mountain tops and slopes, are often transitional zones, characterized by species‐rich ecosystems. Typical physical impacts include the degradation of such ecosystems caused on the one hand by tourism development (e.g. construction activities and infrastructure development, deforestation and intensified or unsustainable use of land, marina development) and on the other hand by touristic activities (e.g. trampling, anchoring and other marine activities, alteration of ecosystems by tourist activities). As De Camillis et al. (2010) point it out, it is commonly thought that many services have little impact, due to the limited level of direct material intensity and polluting emissions in the supply phase of these services. Nevertheless, the overall environmental impact of services may be significantly increased by the supply of inputs they require. 3.3.3 Touristic processes It is difficult to allocate (environmental) impacts to specific “touristic processes”, especially due to the reason, that no classification of touristic processes exists. The authors distinct between the following “touristic processes”: 
Travel and transport: includes arrival and departure and all related transports, e.g. at the destination or the trip from home to the airport. Different means of transport could be used (having different impacts on the environment): aircrafts, cars, busses, trains, (cruise) ships and ferries etc. 
Accommodation 10
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Tourism/ImpactsofTourism/EnvironmentalImpacts/TourismsThreeMainImpactAreas/tabid/78776/D
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
Food and beverage provision for tourists 
Leisure activities -
Shopping -
Cultural activities (museum, theater, heritage sites, city tours etc.) -
Sports and outdoor activities (e.g. water park) -
Sun and beach De Camillis et al. (2010) divide the following categories based on Life Cycle Assessment studies found in literature: accommodation services; buildings (hotel structures); tourist package holiday; the entire tourism industry. Kuo and Chen (2009) categorize the following “category of services”: transportation, accommodation and recreation activity. Gössling et al. (2005) assessed eco‐
efficiency with regard to the emissions of greenhouse gases. The authors analyzed several tourism destinations as case studies, and found travel distance to be the factor most likely to result in an unfavorable eco‐efficiency, and that air travel was the most inefficient mode of transport. Overall, and in order of importance, travel distance, means of transport, average length of stay, and expenditures per day are the factors influencing eco‐efficiency. In addition, they tried to depict very energy consuming “processes” and compared for example accommodation with other leisure activities. On the one hand the results show, that for example the average energy consumption per bed night in hotels might be in the order of 130 MJ (155 MJ stated by Kuo and Chen (2009)). Hotels use generally more energy per visitor, as they have energy intense facilities, such as bars, restaurants, and pools, and more spacious rooms. Accommodation establishments in the category “pensions” may have a comparably low number of beds and occupancy rates are assumed to be somewhat lower than those of hotels (bed and breakfast 110 MJ). Campsites were assumed to have the lowest energy use of all categories with 25 MJ per bed night, while holiday villages were calculated with 90 MJ per bed night. When compared with selected touristic activities, it can be seen, this of course depends on the type of activity: Becken and Simmons (2002) identified activities of New Zealand tourists and calculated their energy‐intensity, which ranged between 7 MJ per tourist (visitor centers) and 1,300 MJ per tourist (heli‐skiing). Kuo and Chen (2009) display data from Taiwan and it is shown, that energy consumption of visitors are different for varying activities: for example historic sites visiting (3.5 MJ/visitor), landscape visiting (8.5 MJ/visitor), motorized water activity (236.8 MJ/visitor), swimming (26.5 MJ/visitor), nature watching (8.5 MJ/visitor), rafting (35.1 MJ/visitor), fishing (26.5 MJ/visitor). Beside this, it is also possible to extend this and even consider the following as part of a “touristic product”: according to Middleton (1989), a tourist experience generally starts, right after a process of information acquisition, with a booking phase. Before departure, a number of pre‐departure activities may take place (e.g. vaccinations, purchase or rental of goods — e.g. clothes — for the holiday). The transport phase includes all movements carried out by tourists from departure to their return home. At destinations, accommodations receive guests for one or more nights, restaurants offer food services and leisure enterprises offer tourist activities. Public services and other supporting services should also be considered to be part of the tourist experience. After the return at home, a final phase includes all the activities to restart the everyday life. 54
Depending on these results it is assumed, that in terms of waste generation, the processes “accommodation” and “food and beverage provision for tourists” are considered as the hotspots in touristic processes. The general distinction between “tourist trip” vs. “business trip” is not made within the scope of this study, as it is assumed that overnight stays during a business trip are usually considered as tourist overnight stay in tourist statistics. The results of the literature review do not show a hint, that business trips are recorded separately. It can be assumed, that top‐down approaches generally contain all touristic processes, no matter where the activities take place. Bottom‐up approaches, on the contrary, only depict processes at the place where the observation takes place. Of course it is possible to extrapolate the results to higher geographical levels, nevertheless one has to be aware, that not all touristic processes are covered. Beside the distinction between different touristic processes, one has also to consider the consideration of certain or different waste types in study results or when planning a study. Usually the information of what types of wastes are considered in a study is given only to smaller extent: on the one hand if waste separation / sorting analysis is carried out within bottom‐up approaches, the waste types sorted are known. But the decision what waste types shall be covered is not easy. For example, at the level of a hotel it has to be defined if non‐durables are also considered, e.g. furniture, mattresses, WEEE (e.g. TV‐sets, refrigerators, cooling devices) or if tourist related construction waste or infrastructure is part of the scope. In top‐down approaches, calculated data usually refer to available statistical data and calculate the tourist‐related share of this waste stream, e.g. municipal solid waste. In the following, the results of an extensive literature review are presented related to waste and tourism. 3.3.4 Scope of the reviewed literature In total, 79 papers and reports were analysed, they were downloaded, and classified in a MS Excel file according to certain categories, allowing a subsequent analysis and illustration based on different characteristics. In a first step, the non‐relevant literature was selected, of the total 79 papers, 52 papers were considered as relevant. The general overview Excel file was sorted and is presented in three parts (see Table 4, Table 5 and Table 6). In addition, 7 papers and reports were assessed related to waste management, tourism and islands, main results are presented in Chapter 3.3.8. The following Table 4 shows the results of sorting the 52 papers according to the two sorting criteria “methodological approach” and “level of data collection”. This sorting criteria reflect a classifaction according to the location, where data was originally collected: “bottom‐up” stands for a data collection, that is close to the waste generator (mostly related to different methods used to collect primary, disaggregated data). 23 papers (44 %) are considered as bottom‐up, dealing with data on waste and tourism that were generated at the level of waste generators 55
related to accommodation (and also to food and beverage provision). 15 of these 23 papers contain data that were generated at hotels, guesthouses and the like. 8 of these 23 papers deal with results from “sector studies”, this means that data were not only collected at accommodation places, but also include restaurant, pubs, touristic attractions (souvenir shops, scenic points, museums), transit stations (border crossings, bus stations), sports & leisure (e.g. golf courts, beaches, state parks) etc. On the other hand “top‐down approaches” are dealing with data that are used to derive touristic contributions to waste management, e.g. based on waste statistics and influencing factors, but in this nomenclature these data are usually not collected directly at the level of waste generators, but are aggregated, e.g. waste and / or tourism statistics collected at regional / national level. 15 out of 52 papers are considered as using this top‐down approach (29 %). Chapter 6.2 is presenting methodological considerations on data collection and its statistical and practical implications related to “bottom‐up” and “top‐down” approaches. Out of these 15 papers, one paper aims at modelling tourism waste at national level (Croatia) and 14 papers consider modelling at a regional scale: a selsction of regions covered in these papers are for example Basqe Country (Spain), Mallorca and Menorca (Spain), Rimini (Italy), Province of Salzburg (Austria), Province of Trento, Tuscany and Apulia (Italy), Area of Marcelli ‐ Municipality of Numana in Marche Region (Italy), a region in Poland, prefectures in Crete (Greece) and the area of Saranda in the region of Valona (Albania). 4 papers (8 %) are “review” papers, that mainly present data already published – these review papers compile information from various studies and provide benchmarks for certain parts of the tourism sector and also information on waste composition. 9 papers are marked with “n.a.” (17 %), these paper do not clearly outline methodologies how data were collected, or contain data that do not fit 100% to the scope of this literature review, but it was decided to keep them and not to sort them out. The 52 papers in total cover the following regions: Tabasco (Mexico), Costa Brava (Girona, Spain), Blackpool (UK), Dominica, St. Lucia, and the Dominican Republic (Punta Cana Region), HaLong City (Vietnam), Hong Kong, Kuala Lumpur (Malaysia), New York City (USA), Thailand (Golden Triangle border region with Laos and Myanmar), Pennsylvania (USA), Kashmir valley (India), Ireland, Zanzibar (Tanzania), Bali (Indonesia), Cairo (Egypt), Hat Yai and Phuket cities (Southern Thailand), Hawaii (the Big Island, USA), Cyprus, Chalkidiki (Greece), Poland, Sweden, Vienna (Austria), Balearic Islands (Spain), Catalonia (Sapin), Croatia, Federal province of Salzburg (Austria), Mallorca and Menorca (Spain), Province of Rimini (Italy), Province of Trento (Italy), Basque Country (Spain), Tourist area in the north of Italy (Alto Garda and Ledro, belonging to the Autonomous Province of Trento) and another area in the south (Apulia), Valle di Sole (Province of Trento, Italy), Val di Merse (Tuscany, Italy), Crete (Greece), Area of Saranda in the Region of Valona (Albania), Area of Marcelli, Municipality of Numana in Marche Region (Italy). Table 4 also includes information on the “methods used to derive waste generation”. Generally spoken, this column depicts information on the methodologies that were used to collect data. In the bottom‐up approach 9 out of 23 papers report, that data were collected by “personal 56
interviews” and “questionnaires”, whereas 13 papers used “on‐site measurement of waste quantities and compostition” and one paper used “other”. Beside the author(s), year of publication and a running ID of the paper, Table 4 also contains information on “origin of waste”, this column gives additional information on types of establishments or touristic processes where data were collected from. 57
Doc. ID Table 4: Overview of the reviewed literature Methodo‐
logical Approach Level of data collection 5 Bottom Up Hotel(s) 35 Bottom Up Hotel(s) 39 Bottom Up Hotel(s) 40 Bottom Up Hotel(s) 62 Bottom Up Hotel(s) 65 Bottom Up Hotel(s) 63 Bottom Up Hotel(s) 18 Bottom Up 1 Methods used to derive waste generation On‐site measurement of waste quantities and composition On‐site measurement of waste quantities and composition On‐site measurement of waste quantities and composition On‐site measurement of waste quantities and composition On‐site measurement of waste quantities and composition On‐site measurement of waste quantities and composition Author(s) + Year Keywords Origin of waste (Williams and Fielding, 2008) Bagged waste, hotel, bedroom bins Bagged waste from hotel bedroom Blackpool, UK bins (Hoang, 2005) Vietnam, hotel, waste generation, waste composition, waste audit, Hotels composting trial, HaLong City, Vietnam Local (DPPEA, s.a.) Recycling, hotel, motel, lodging, NYC Hotels, motels NYC Local (Downing et al., 1999) Hotels, waste generation, waste composition, Dominica, St. Lucia, and the Dominican Republic, cruise ships, Hotels Dominica, St. Lucia, and the Dominican Republic National (Punta Cana Region) (Singh et al., 2014) Recycling, Hotel waste, Salvage value, GHG emission, Environment benefits Hotels University Park, Center County, Pennsylvania (USA) Regional (Chan and Lam, 2001) Municipal solid waste; landfill; hotel; plastic toiletries; environmental costs Hotel industry Hong Kong Local Other (Hogan and Bergin, 2007) Irish hotels, cleaner production programme, EMS activities, waste management, water management, energy management, GHG emissions Hotels Ireland National Hotel(s) Personal interview On‐site measurement of waste quantities and composition (Spitzbart et al., 2013) Zanzibar, hotels, waste collection, waste disposal hotels Zanzibar Regional Bottom Up Hotel(s) Questionnaire (Zorpas et al., 2015) Waste minimization practices, Hospitality industry; Waste prevention; Cost‐benefit analysis, Cyprus Hotels Municipality of Paralimni, Cyprus; Worldwide Local 10 Bottom Up Hotel(s) Questionnaire (Trung and Kumar, 2005) Hotel industry Vietnam National 16 Bottom Up Hotel(s) Questionnaire (Tang, 2004) Hotels Bali, Indonesia National Hotel energy consumption; Hotel water use; Hotel waste; Hotel industry’s environmental performance; Vietnam Bali, Hotel solid waste management program, case study, stakholder, planning, recommendations, improvement, 58
Geographical scope Spatial Scale National Doc. ID Methodo‐
logical Approach Level of data collection Methods used to derive waste generation Author(s) + Year Keywords 66 Bottom Up Hotel(s) Questionnaire (Ball and Taleb, 2011) Benchmarking ; waste management ; sustainability ; waste disposal ; legislation ; Egypt 73 Bottom Up Hotel(s) Questionnaire (Sridang et al., 2005) Solid waste management, hotel solid waste, Southern Thailand 74 Bottom Up Hotel(s) Questionnaire (Bohdanowicz, 2005) Hotels, environmental awareness, environmental initiatives, survey, Poland, Sweden Hotel Poland and Sweden (Papargyropoulou et al., 2016) Food waste, Hospitality sector, Social practices, Food provisioning, Food consumption, Behaviour, Material flow. Eco‐efficiency, food waste generation and prevention Hotel restaurants Malaysia, Kuala Lumpur Other (Youngs et al., 1983) food waste, hotel, restaurants, UK, edible and inedible food Hotels, restaurants UK On‐site measurement of waste quantities and composition On‐site measurement of waste quantities and composition On‐site measurement of waste quantities and composition 27 Bottom Up Hotel(s) 2 Bottom Up Sector Study 4 Bottom Up Sector Study 78 Bottom Up Sector Study On‐site measurement of waste quantities and composition 19 Bottom Up Sector Study Questionnaire 56 Bottom Up Sector Study Questionnaire 69 Bottom Up Sector study On‐site measurement of waste quantities and composition Origin of waste Geographical scope Egypt, (metropolitan Hotel industry (five Cairo ie Cairo, Giza and star hotels) Qaliubya) Hat Yai and Phuket Hotel cities (Southern Thailand) Hotels, restaurants, pubs and quick UK service restaurants (QSRs) Thailand (Golden Different touristic Triangle border region Sustainable tourism, source separation, waste compositiuon, waste activities: guest‐
with Laos and (Manomaivibool, 2015) diversion, waste generation, houses, touristic Myanmar), Chiang Rai Thailand, Golden Triangle, attractions, Hotels, province / Chiang Saen Transit station district Accommodations, restaurants, golf Energy, food consumption, Hawaii, industrial ecology, survey, island of Hawaii (the (Saito, 2013) courses, tourism water consumption Big Island) services (tours), and rental cars Gastronomy sector (hotels, Waste gereration, gastronomy, Vienna, waste prevention and (Graggaber et al., 1999) restaurants, Vienna (Austria) reduction measures cafés/bars, snack bar/cafeteria) Yusmarg, a forest Municipal solid waste, combustible, composting, Yusmarg, forest ecosystem and Yusmarg, Kashmir (Bhat et al., 2014) ecosystem tourist resort, in valley (India) the Kashmir valley (WRAP, 2011) Hotels, restaurants, pubs and quick service restaurants (QSRs), food waste, composition 59
Spatial Scale National Local National National National Regional Regional Local Local Doc. ID Methodo‐
logical Approach Level of data collection Methods used to derive waste generation 57 Bottom Up Sector study On‐site measurement of waste quantities and composition Other 68 Bottom Up Sector study Keywords Origin of waste (Ariza et al., 2008) Beach waste and litter composition, urban beaches, summer season Urban (located in the main nucleus of the munici‐
pality) and urban‐
ized (located in residential areas outside the main nucleus) beaches Beaches in three towns of the southern Regional Costa Brava (Girona, Spain) (Catalan coast) On‐site measurement of waste quantities and composition (Canepa et al., 2012) Basic diagnosis, natural protected area, solid waste, Mexican regulations, waste management strategies State Park (natural protected area) Agua Blanca State Park, Macuspana, Tabasco, Other Mexico 79 Bottom Up Tourism sustainability indicators Questionnaire (Michailidou et al., 2015) All‐sized hotel categories Northern Greece, Chalkidiki Other 58 n.a. Hotel(s) n.a. (ITP, 2008) (Luxury) hotels Non‐geographical Other 75 n.a. Hotel(s) n.a. (Bohdanowicz, 2005) Hotel Europe Other Balearic Islands (Spain) Single enterprise 77 n.a. 11 n.a. 12 n.a. 14 n.a. 15 n.a. Hotel(s) Tourism sustainability indicators Tourism sustainability indicators Tourism sustainability indicators Tourism sustainability indicators Author(s) + Year Combined environmental pressure, Tourism environmental composite indicator, Life cycle assessment, Air and road transport, Accommodation, Normalized key performance indicators on energy/water consumption, kg CO2‐eq for accommodation and transport, Seasonality, Case study Luxury hotels, benchmarks, waste types by department / activity,
paper recycling programme, Hotel waste checklist, Sample waste audit table, Waste paper record Hotels, Europe, survey, environmental attitudes, incentives, independent hotels, chain‐affiliated hotels Geographical scope Spatial Scale n.a. (Fortuny et al., 2008) Renewable energies, composting, sustauinable tourism, waste prevention, electricity consumption, water conservation, methodology, General metho‐
dology and case study at one rural guesthouse n.a. (ADEME et al., 2001) benchmarking, waste, hotels, indicators, Energy consumption indicator, Water consumption indicator Hotels Europe Other n.a. (Torres‐Delgado and Palomeque, 2014) Tourism sustainability, Indicators, Indicator system, Tourism municipalities, Catalonia n.a. Spain, Catalonia Other n.a. (Tanguay et al., 2013) tourism sustainability; sustainable development; assessment; indicators; selection criteria n.a. Non‐geographical Other n.a. UNWTO Indicators of sustainable development in tourism + destination application n.a. Non‐geographical Other Energy Efficiency, Water Conservation, Solid Waste, hotel, zero waste Hotels Non‐geographical Other Benchmarks, Water, energy, waste, case study, good practice Hotel Non‐geographical Other Editorial, overview, impacts n.a. selected world regions Other 64 n.a. Hotel(s) Other 67 n.a. Hotel(s) Other 70 Review Other Literature review (Alexander and Kennedy, 2002) (WWF‐UK and IBLF, 2005) (Munoz and Navia, 2015) 60
Doc. ID Methodo‐
logical Approach 25 Review Level of data collection Methods used to derive waste generation Author(s) + Year Sector Study Literature review (Pirani and Arafat, 2014) Keywords Origin of waste Waste management, Food waste, Hospitality industry, Hotels, Restaurants, Ecolabels, Characterization and quantification of waste, Initiatives for waste reduction Best Environmental Management Practice, destination management, water consumption, waste, energy consumption, accommodation buildings, key performance indicators, benchmarks, prevent and avoid waste, waste management costs, campsites 17 Review Sector Study n.a. (Styles et al., 2013) 7 Tourism sustainability indicators n.a. (UNEP, 2003) Examples of Solid Waste Generated by Tourist Facilities, Ways to avoid solid waste Household waste generation, Relevant municipal characteristics, Forecasting, Regression, Biscay Review 29 Top down Tourism on Modelling using local / regional statistical data level (Oribe‐Garcia et al., 2015) 42 Top down Tourism on Modelling using local / regional statistical data level (Arbulu et al., 2016) 43 Top down Tourism on Modelling using local / regional statistical data level (Arbulú et al., 2016) 44 Top down 48 Top down Tourism on local / regional level Tourism on local / regional level Environmental economics, industrial ecology, IPAT equation, tourism, tourist arrivals, waste generation, econometric models, impact of tourist growth on MSW generation, tourist expenditure, model for separating waste generation by tourists and by residents Public‐private partnership, Sustainable tourism, Waste management, Mature tourist destination, options to charge the waste management fee to hotels seasonality, treatment costs, econometric models Hotels, restaur‐
ants, cafeterias Geographical scope Spatial Scale Non‐geographical Other Non‐geographical Other worldwide Other Spain, Autonomous Community of the Basque Country Regional Tourism in the study area Mallorca Regional Tourism in the study area Mallorca (case study) Regional Regional Hotel, restaurant, hotel kitchens, campsite, tour operator, related activities'. Small + medium tourism enter‐
prises (mainly accommodation, incl. restaurants) Influence of tourism on municipal household waste generation Modelling using statistical data (Arbulú et al., 2013) IPAT Model, municipal solid waste, tourism growth Tourism in the study area Mallorca (case study) Modelling using statistical data (Caramiello et al., 2009)
Impact, municipal solid waste, sustainable development, tourism, separate collection Summer tourism (adriatic coast) Province of Rimini, Italy Regional 53 Top down Tourism on Modelling using local / regional statistical data level (Ofner, 2011) Waste generation, tourism, summer, winter, seasonality, Salzburg, Austria Waste generation from summer and winter tourism on munucipal level Federal province of Salzburg (Austria) 61 Top down Tourism on Modelling using local / regional statistical data level (Rada et al., 2014) Municipal solid waste, selective collection, SRF, tourism, tourist Tourism in the study area Province of Trento (Italy), 5 case studies: Val di Fassa, Val di Sole, Regional Val di Fiemme, Giudicarie, Val di Non 72 Top down Tourism on Modelling using local / regional statistical data level (Mateu‐Sbert et al., 2013) Modelling tourist share of MSW and recyclables, time series, dynamic regression models, seasnonal variation, Menorca, Island Tourism in the study area Menorca (Spain) 61
Regional Regional Doc. ID Methodo‐
logical Approach 20 Top down 45 Top down 49 Top down 55 Top down Level of data collection Methods used to derive waste generation Tourism on local / regional n.a. level Tourism on local / regional n.a. level On‐site Tourism on measurement of local / regional waste quantities level and composition Tourism on local / regional Other level Other: Assumption of fixed rates of waste generation per tourist and night and extrapolating with total overnight Tourism on local / regional stays Waste separation level analysis at transfer stations / disposal sites throughout the year in order to derive changes in waste composition Author(s) + Year Keywords Origin of waste Geographical scope (Ranieri et al., 2014) Seasonal variations in waste generation, Incineration, Mechanical‐
Biological Treatment, municipal solid waste, selective collection, Solid Recovered Fuel, tourist area North of Italy. Alto Garda, Ledro Waste generation (Autonomous Province in whole study area of Trento); South of Italy:Apulia Regional (Iwan et al., 2014) Municipal waste management; sustainable development; environmental order; sustainable urban development Tourism in study area Local (Ragazzi et al., 2004) Contribution of tourism to waste generation Summer tourism "Valle di Sole", Province Local (mountain tourism) of Trento, Italy (Patterson et al., 2007) Ecological footprint, Tourism, Consumption Tourism in a rural "Hinterland" Poland, selected spa cities Spatial Scale Val di Merse, a rural Local region of Tuscany, Italy. Crete (Greece), Prefectures of: Rethymnon, Heraklion and Lassithi in the island of Crete (Fig. 2). Regions of Chania and Sitia were excluded from this study. Regional (Gidarakos et al., 2006) Greece, MSW, composition, country report, seasonal variation, Tourism Regions with high seasonal variability in population due to tourism, 54 Top down Other: TCCA Tourism on Tourism Tourism local / regional Carrying Capacity level Assessment (ASTA, 2006) Tourism development, adriatic sea, coastal area, tourism carrying capacity, TCCA – Tourism Carrying Capacity Assessment, seasonality, municipal planning Tourism in the coastal areas, summer tourism (high season) Adriatic Sea, Area of Saranda (Valona, Albania), Area of Marcelli, Municipality of Numana (Marche Region,Italy), Other 59 Top down Tourism on national level (Kulisic et al., 2008) Tourism, renewable energy sources, energy demand Tourism in the study area Croatia National 36 Top down Modelling using statistical data 62
3.3.5 Waste types covered and indicator sets used Table 5 is a comprehensive overview on the main results of the assessed literature. The document ID in the first column allows to identify the authors and the tile of the study and to allocate also the main information as outlined in Table 4. Column 1 displays the “waste related indicator sets” that were used in the studies. It can be stated, that in multitude of waste related indicators were used in the study, mainly volume‐ based (e.g. in m3 or litres) or weight‐based indicators and to a certain extent also waste composition data were presented. It is important to consider on the one hand, that volume‐based indicators might be derived by estimating the emptied volume of bins (e.g. out of the accounting department where for example bills can be used or real counting of bins emptied per time unit) or also for example volume of collection vehicles going to a waste disposal plant. Yet, one has to consider the filling percentage of bins / vehicles and on the other hand, if volume is transformed into weight, the question is what conversion factor is used for this calculation. In some cases absolute numbers were presented, e.g. “total amount of waste generated by hotels” or “waste generation [t] per fraction”, yet these figures are only somewhat meaningful. Other examples of absolute indicators are “volume (m3 or litres) or weight (kg) of non‐hazardous waste sent to landfill over the last full calendar year”. On the one hand, when it comes down to comparisons, relative numbers are better and on the other hand, as long as absolute numbers do not include important information like hotel size and level of capacity (in terms of beds or guest nights etc.), the absolute numbers are less meaningful. A very common weight‐based indicator used is “kg/guest/day”, similarily “kg/tourist/night” is in use. In some cases, depending on the method used, the “total waste generation rate” (= total waste) is reported, for example, as per guest per unit of time (e.g. kg/guest/day), but also a “waste disposal rate” (= total waste ‐ recyclables) can be depicted. Other relative numbers used in the papers and reports are for example based on the unit “kg/day/hotel room” or “kg/day/hotel kitchen” this unit is also only on a limited level significant. The unit “kg/employee/year” does consider the size of the establishment to some extent, yet the number of employees depend also on the layout and structure of the establishment and therefore might distort results. Some studies use as reference value the unit “square meter”, of course it again depends on the layout and structure of the establishment, whether square meter is a useful unit and whether total square meter are used or built‐up area or of the rooms etc. Some studies researched different touristic processes and therefore divided into different “collection spots”, this might be bins or a number of bins at a location. Some studies focus on food waste from hotels and restaurants (or other establishment providing food and beverages), the main indicators used are again waste‐based, some others depict the same information on an energy basis, e.g. “food wastage (in % of food input on an energy basis)” or the “average loss of energy occurring during meal preparation and consumption (expressed as a percentage of the energy value of the presented meal varies)”. Other indicator options used in literature are for example the “average food waste generation per customer served for breakfast buffet / lunch "a la carte" / lunch buffet / Dinner " a la carte" / dinner buffet” or also related to certain food waste categories, e.g. “preparation waste per customer” (kg/person), “customer plate leftover waste per customer” (kg/person), “buffet leftover waste per customer” (kg/person) or the “total food waste per customer” (kg/person). Similarily the unit used is “average weight of waste per cover”. More information on food waste is given in the Chapter 3.3.7. 63
A study on beaches used for example the indicators “total solid waste from bins generated per beach user” (kg/day) and the “waste density” (g/m2/day). Some of the studies additionally provided data on other impacts beside waste, such as water consumption, electricity consumption and more seldom wastewater production. The reference values that could be used to “normalize” absolute values could be similar then the ones used for waste (e.g. number of employees, square meter floor area, one guest night, tourist etc.), examples from the studies are water consumption in litres of water per sleeper, energy consumption was depicted as kilowatt hours (kWh) per square metre of internal hotel space per annum. In some of the studies also composite indicators were provided, like as Michailidou et al. (2015) propose a “tourism environmental composite indicator” (TECI): TECI provides the basis for a comparative analysis for typical all‐sized hotel categories in terms of their combined environmental pressure. Different normalized key performance indicators are used, i.e. pressure per m2, pressure per room, pressure per guest night are combined in one single composite indicator. Five main categories of key performance indicators are presented: (i) Energy‐oriented environmental pressures for hotels, (ii) water‐oriented environmental pressures for hotels, (iii) waste‐oriented environmental pressures for hotels, (iv) carbon footprint‐oriented environmental pressures for hotels, and (v) carbon footprint‐oriented environmental pressures mainly from air and road transport to the destination and back and from recreation activities. Some studies that provide more a sectoral view by not only assessing on single establishment, use indicators to compare, such as “number of tourism establishments collecting waste separately”, “number of tourism establishments recycling their own waste” (e.g. composting) or “percentage of tourism establishments covered by waste collection programs” (most likely not applicable in the European context). Related to hazardous wastes, at the level of establishments it is possible to use indicators related to the proper handling and disposal of hazardous substances, e.g. “number and volume of hazardous substances in use” (for key substances, volume of use over time), “percentage of these substances for which appropriate management and disposal policies and programs are in place” and “percentage of employees informed and trained in the use and disposal of the substances they use” (e.g. number of cleaning personnel knowledgeable of how to deal with waste cleaning fluids, engineers trained in emergency spill handling). When it comes down to data on waste composition, it is first of all important to have a common terminology on waste types. This helps to interpret and compare international studies (please see also Appendix of this document). For example the indicator “unsorted waste per overnight stay (kg / overnight stay)” is not 100% clear. Unsorted implies, that there is a separate collection somewhere, e..g. at hotel level. Is this waste type coming out of the residual waste bin, then it would be simply “residual waste”. Other questions to be answered next would be: Are there partly wastes separated at the source at a hotel? When waste generation is related to tourism, it is of course necessary to collect and assess tourist data. Generally spoken, these data should be made available in a way they fit to the level of detail of waste data. Usually tourist data are of higher quality compared to waste data, so in order to align and assess waste and tourism it is recommended to have both data available in the same time period and level of detail. E.g. tourist data on a monthly level is more likely to be available, whereas waste data on a monthly level needs extra effort by municipalities. Tourist data shall depict seasonal variations (in case there are seasonal variations), examples for tourist related information: “tourist arrivals by month or quarter” (distribution throughout the year), “occupancy 64
rates for licensed (official) accommodation by month” (peak periods relative to low season) and “percentage of all occupancy in peak quarter or month”, “percentage of business establishments open all year” or “number and percentage of tourist industry jobs which are permanent or full‐
year” (compared to temporary jobs). If it is intended to control the use intensity, then for example indicators could be the “total number of tourist arrivals” (mean, monthly, peak periods) and the “number of tourists per square metre of the site (e.g., at beaches, attractions), per square kilometre of the destination” (mean number/peak period average). In order to relate tourists to the local population, it is of course necessary to have data available on the local resident population. In some cases, where it is assumed, that both tourists and residents generate the same quantity of waste (e.g. 1 kg/capita/day), it is possible to calculate population equivalents, e.g. the “total yearly equivalent” population, as derived from the sum of the “resident” population and the definable “yearly equivalent touristic” population. The units of “yearly equivalent tourist” can be achieved from the ratio between the yearly touristic overnight stays and the days in one year. Some studies display, that it is more likely, that tourists and resident population do not generate the same relative waste quantities. In addition, Table 5 includes also all quantified results, i.e. benchmarks or study results on certain waste quantities or composition data. 65
Doc. ID Table 5: Overview of waste related indicator sets used, waste types covered and results of reviewed literature 5 35 Waste related Indicator (sets) used Waste types covered Results • Waste generation per guest per day Food found in room bags, metal, glass, plastic bottles, other plastic and films, paper and card, other compostibles (green plants, paper towels, serviettes), other residual , waste (e.g. co‐mingled waste such as cigarette packets), other components (WEEE, textiles, wood, ceramics, oil (any type), medicines, tetrapaks, silica gel and rubble/DIY waste) • On average, guest room waste is 15.4% (by weight) of a hotel’s generated waste, however, this only accounts for 10.2% of the recyclables from the hotel waste. • Room bags contributed 10.2%, of the total recyclables available. These were mainly plastics, paper and card with only small amounts of metal and glass. • The largest hotel waste component at 21.5% was the other residual waste (which was regarded as currently not practicably recyclable). This is made up of 6.94% arising from the room bags and 14.60% from other hotel sources. • The amount of waste generated by guests in their room was found to be 0.56 kg of hotel waste/guest. This compares with the international figure for guest waste quoted by Hogan and Bergin (2007) of 1.5 kg of hotel waste per sleeper (2004) and 2.5 kg for guests in Irish hotels in 2005. Total waste, recyclables (glass, metal, plastics and paper), compostables (leftover food, fruit waste, vegetable waste, yard waste), miscellanous (non‐recyclable paper, non‐recyclable plastics, rubber, cloth, dirt, ...) • Among disposed waste, approximately 60% was compostables and recyclables made up around 5%.
• Waste generated and disposed per guest per day for different hotel categories (star‐rating): Generated (4* / 3* / 2*): 0.90 / 0.60 / 0.81 kg/guest/day (range: 0.69 ‐ 0.90) Disposed (4* / 3* / 2*): 0.51 / 0.43 / 0.53 kg/guest/day (range 0.43 ‐ 0.53) • The ratios of disposal rate to generation rate for three hotels are 57% (SaiGon‐HaLong Hotel* * * *), 63% (CongDoan Hotel * * * ), and 65% (TienLong Hotel * *) respectively (generation = total waste, disposal = waste to landfill = total without recyclables). • Generation‐based composition of solid waste in hotels (average) (total=100%): 4* hotel: Compostables / Recyclables / Miscellanous = 74.7 / 10.7 / 14.6 3* hotel: Compostables / Recyclables / Miscellanous = 74.2 / 6.8 / 19.0 2* hotel: Compostables / Recyclables / Miscellanous = 73.1 / 4.7 / 22.2 • Disposal‐based composition of solid waste in hotels (average) (total=100%) 4* hotel: Compostables / Recyclables / Miscellanous = 73.3 / 0.9 / 25.8 3* hotel: Compostables / Recyclables / Miscellanous = 60.4 / 9.3 / 30.3 2* hotel: Compostables / Recyclables / Miscellanous = 59.3 / 6.6 / 34.1 • Of the amount generated, approximately 75% was compostables and 5% to 10% were recyclables. However, after some recyclables and leftover food were collected for selling and feeding pigs, the percentage of compostables in the disposed waste reduced to about 60% to 70%. The main categories of the disposed compostables were fruit waste, vegetable waste, and yard waste. • Waste generation rate (=total waste) for each hotel in kg/guest/day • Waste disposal rate (=total waste ‐ recyclables) for each hotel in kg/guest/day • Composition of waste generated and disposed 39 Waste composition 40 • Amounts of waste generated by hotels (kg/guest/day) • Amounts of recyclables by hotels (kg/guest/day) • Waste generated by cruise ships (per year) Paper (includes mixed paper, newspaper, corrugated cardboard, Waste Composition Analysis for New York City Hotels and high grade paper), Paper (includes mixed paper, newspaper, corrugated cardboard, and high grade paper) 39.9%, Organics/ Food 27.8%, Glass organics/food, glass, plastic, yard 7.6%, Plastic 7.1%, Yard Waste 6.7%, Metals 6.1%, Other and Special Waste 4.5% waste, metals , other and special waste • Waste composition with yard waste (average over all three islands): Metal 0.7%, Paper 4.0%, Glass 4.2%, Plastics 0.3%, Organics 79.6%, Remainder 11.2% • Waste composition without yard waste (average over all three islands): Metal 1.1%, Paper 6.8%, Glass 7.1%, Plastics 0.6%, Metal, paper, glass , plastics, Organics 65.5%, Remainder 18.9% organics, remainder, total • Volumetric Waste Flows per Guest, kg (average over all three islands): Metal 0.001, Paper 0.004, Glass 0.001, Plastics 0.001, Organics 0.030, Remainder 0.012, Total 0.048 • Total Weight Flows per Guest, kg per guest per day (average over all three islands): Metal 0.033, Paper 0.204, Glass 0.211, 66
Doc. ID Waste related Indicator (sets) used 62 • Daily waste quantities (lb per hotel) • Total Waste (tons per hotel per day) 65 • Average weight of waste per room (kg) • Average weight of waste per cover (kg) 63 Kilograms of landfill waste per sleeper 18 • Waste production per guest per day • Waste composition 1 • Total amount of waste generated by hotels (tons/day) • Waste generation [t] per fraction • Waste composition 10 • Solid waste discharge (ton/m2 year)
• kg solid waste/guest/day Waste types covered Results Plastics 0.017, Organics 4.030, Remainder 0.567, Total 5.062
• Total Weight Flows without Beach Waste, kg per Guest per day (average over all three islands): Metal 0.033, Paper 0.204, Glass 0.211, Plastics 0.017, Organics 1.961, Remainder 0.567, Total 2.994 • Waste composition for hotels with F&B services (Total: 100%): Plastic bottle: 10%; Other plastic: 2%;Teracycles: 3%; Aluminum: 5%; Glass: 6%; Newspaper: 7%; Mixed office: 6%; Cardboard: 2%; Compost: 47%; Trash: 13% • Waste composition for hotels without F&B services (Total: 100%): Plastic bottle: 18%; Other plastic: 6%; Teracycles: 6%; Aluminum: 12%; Glass: 15%; Newspaper: 4%; Mixed office: 5%; Cardboard: 7%; Compost: 19%; Trash: 12% Plastic bottle, other plastic, • Hotels with F&B services (n=3): Out of total trash thrown in the dumpster only 13%,11%, and 16%, respectively are “true” teracycle, aluminum, glass, trash, which should go to the landfill, the rest is recyclables. newspaper, mixed office, cardboard, • Hotels without F&B services (n=2): Out of total trash only 12% trash is the ‘true trash’ and 88% of the trash is recyclable for compost, trash, total waste the both hotels. • Waste generation of hotels: half a pound to 28.5 pounds (0,2 to 13 kg) of trash per day per room (source???). • Sridang et al. (2005): on average hotel waste ranges between 0.05 and 17.35 kg/room/day or 3.51 kg/room/day in the two cities of Hat Yai and Phuket in Southern Thailand. Municipal Solid Waste (MSW), •The Weight of Municipal Solid Waste Generated in Rooms and Restaurants (mean, based on measurement 1996): Waste from rooms: in‐room plastic Per Room Basis (kg): Plastic toiletries: 0.742 (SD: 0.078), Laundry bag: 0.181 (SD: 0.011), Paired slippers: 0.451 (SD: 0.065), waste, unused soaps, disposed Original soap: 0.833 (SD: 0.055), Newspapers: 0.554 (SD: 0.081) slippers, discarded newspapers; Per cover basis (kg): Room Waste: 2.761 (SD: 0.119), Restaurant Waste: 0.751 (SD: 0.100) MSW from hotel restaurants •The amount of MSW generated from the hotel restaurants was estimated to be 0.751 kg per meal cover. This is slightly including paper napkins, paper place higher than the average of 0.665 kg reported in the United States (Pettay, 1992). mats, straw, organic food remains • Waste generation without "Cleaner Production Programme": 3.5 kg of landfilled waste per sleeper
Landfilled waste • Waste generation with "Cleaner Production Programme": 2.5 kg landfilled waste per sleeper International Average: 1.5 kg of landfilled waste per sleeper (source???) • Waste from hotels:
Average waste production: 5 kg per guest per day Average waste density: 0,3 kg/l (300 kg/m³) Composition: 80‐85% organic waste, 2‐5% plastic bottles • Comparison with international studies: Total waste Tang [2004]: each hotel room in Bali generates 9.2 kg of waste per day Thomas [1999]: The waste generated by hotels in the Dominican Republic is 3 to 7 kg per guest per day. Sridang [2005]: solid waste generation for hotels in Phuket Cities: average of 3.5 kg/room/day. Williams, Fielding [2008]: waste from hotels in Ireland: bedrooms bins contribute about 15% to the total waste production in hotels. Plastics, glass, paper, wood, organic waste, old durables (e.g. old furniture, computers, bed linen), WEEE, green waste (grass, etc.), clinical waste (sanitary towels, etc.), International Hotel Environmental Initiative (2002): approx. 1 kg of waste per day and hotel guest hazardous (plastic containing chemicals, etc.) sands (Backwash), dust (filters), metals packaging and waste packaging and batteries Food waste; plastics, packaging, • Solid waste in hotels and resorts of Vietnam (in % of total): paper; aluminum cans, metal, glass; Resort: 20% food waste; 13% plastics/packaging, paper; 6% aluminum cans, metal, glass; 60% Garden waste; 2% others 67
Doc. ID Waste related Indicator (sets) used Waste types covered • Percent of solid waste recycled2 (%) garden waste; others
16 • Waste generation rates (kg/day/hotel room) 66 Weight of waste per guest (kg, lb) 73 kg/room/day (wet weight) 74 Only information related to environmental attitudes Results 2‐star hotel: 36% food waste; 12% plastics/packaging, paper; 4% aluminum cans, metal, glass; 2% Garden waste; 46% others 3‐star hotel: 44% food waste; 27% plastics/packaging, paper; 5% aluminum cans, metal, glass; 7% Garden waste; 17% others 4‐star hotel: 45% food waste; 25% plastics/packaging, paper; 7% aluminum cans, metal, glass; 5% Garden waste; 18% others • Waste benchmarks for efficient use of resources in Vietnamese hotels (kg solid waste/guest/day) Coastland Vietnam: 4‐star 2.5–7.2; 3‐star 0.4–0.5; 2‐star n/a Highland Vietnam: 2‐star 2.2–3.8 Inland Vietnam: 4‐star 9.7–17.5; 3‐star 5.2–9; 2‐star 8.3–13.9 Overall: 4‐star 13.5–32.3; 3‐star 8.2–17.9; 2‐star 0.7–5.6; resort 5.7–18.7 • Solid waste performance benchmarks for hotels (kg solid waste/guest day): 4‐star: Vietnam 13.5–32.3 // Europe (ADEME 1999) 0.5–1.5 3‐star: Vietnam 8.2–17.9 // Europe (ADEME 1999) 0.51.5 2‐star: Vietnam 0.7–5.6 // Europe (ADEME 1999) 0.5–1.5 Resort: Vietnam 5.7–18.7 // Europe (ADEME 1999) n/a • Wisnu (1999b): Each hotel room in Bali generates an estimated 9.2 kg of waste per day. The average waste generation rates for the hotels ranged between 4 and 12 kilograms per room per day. • Jindal et al. 1998: In Indonesia, per capita waste generation rates were 0.65‐0.83 kg/day in large cities, 0.55‐0.63 kg/day in Total waste, food waste medium cities and 0.47‐0.5 kg/day in small towns. • Waste Composition (%) for Hotels in Bali in 1998 (Wisnu 1999c): 4.11% paper & cardboard, 0.69% Metal, 2.41% Glass, 84% Yard & Kitchen, 1.27% Plastics, leather and rubber, 7.8% Miscellaneous and dry residue. • 5‐star‐hotels:
Mean (24 five‐star hotels): 1,5 kg per guest night Range MIN: 0,4 kg per guest night Non‐hazardous waste sent to landfill Range MAX: 2,8 kg per guest night or dumped • Axler (1973): Guest rooms produce 2 pounds in weight of trash a day, whereas a quality dining room and kitchen produces about 1 pound of trash per guest meal served. • Bohdanowicz (2005): A typical hotel produces in excess of 1 kg of waste per guest per day. Best practices in waste minimization and recycling can limit waste generation to 50 g of unsorted waste per guest night • Hat Yai: Large hotels (>200 rooms): average 1.16 kg/room/day (wet) Medium hotels (80‐200rooms): 0.78 kg/room/day (wet) Small hotels (<80 rooms): 0.1 kg/room/day (wet) n.a. • Phuket: Large hotels (>200 rooms): average 3.51 kg/room/day (wet) Medium hotels (80‐200rooms): 3.15 kg/room/day (wet) Small hotels (<80 rooms): 1.02 kg/room/day (wet) • Ratio of food waste compared to total solid waste generated: Hat Yai 29.9% and Phuket 31.5 % Swedish hotels consume, on average, 198–379kWh of energy per square meter of area, depending on the location and services offered (CHOSE, 2001). The acceptable upper limits established by the Nordic Swan Ecolabel are 235–460kWh/m2, depending on climatic conditions and services offered (Nordic Ecolabelling, 2002). A recent report from one of the European hotel chains provides a figure of 440 l/guest‐night (Radisson SAS, 2003). Others report consumption of 224 l/guest‐night (Scandic Hotels AB, 2000). A more recent benchmark value from IHEI states the n.a. quantity of water below 540 l/guest‐night as satisfactory, and below 480 l/guest‐night as excellent in the case of luxury hotels (IHEI, 2005), while the range of allowable water consumption according to Nordic Swan is 200–300 l/guest‐night (Nordic Ecolabelling, 2002). A typical hotel guest is estimated to produce at least 1 kg of waste per day (IHEI, 2002). A large proportion (50–60 per cent) of this waste could be recycled or reused (Smith et al., 1993). At 1.5 kg/guest‐night, the average quantity of unsorted waste in 68
Doc. ID 27 2 4 Waste related Indicator (sets) used Waste types covered Results Scandinavian Radisson SAS hotels (data for 2002) scored appreciably below the chain‐wide corporate average of 3.1 kg/guest‐
night (Radisson SAS, 2003). Scandic Hotels reported an even lower average of 0.515 kg of unsorted waste per guest‐night (Scandic Hotels AB, 2000). Swedish best practice has shown that efficient waste management can reduce this volume to 50 g of unsorted waste per guest‐night (Sanga Säby Course and Conference (SSCC), 2003). The Nordic Swan eco‐label, limits unsorted waste generation to 0.5–1.5 kg/guest‐night (Nordic Ecolabelling, 2002). • Food waste per customer (kg/person) Daily average: 1.1 kg/person (SD 0.4) Breakfast buffet: 1.2 kg per customer served • Average food waste generation per Lunch time buffet: 1.1 kg per customer customer served for breakfast buffet, Dinner time buffet and ‘a la carte’ service, with 1 kg per customer Lunch "a la carte", Lunch buffet, Dinner " a • Table 3 contains further details on average food waste generation per customer served (kg/person) split into preparation la carte", dinner buffet waste, customer plate leftover waste, buffet leftover waste for breakfast buffet, lunch 'a la carte', lunch buffet, dinner 'a la • Preparation waste per customer carte' and dinner buffet. (kg/person) Food waste • According to the analysis of incoming food and the outgoing food waste, it was calculated that approximately 30% of • Customer plate leftover waste per purchased food was lost in the form of food waste (no re‐use of surplus food waste was observed in this case study). In more customer (kg/person) detail, approximately 17% of food was lost during preparation, 7% as customer plate waste and 6% as buffet leftover waste. • Buffet leftover waste per customer • Avoidable and unavoidable food waste fractions of food waste: (kg/person) Total food waste: 56% avoidable; 44% unavoidable • Total food waste per customer Buffet leftover: 94% avoidable; 6% unavoidable (kg/person) Customer plate waste: 92% avoidable; 8% unavoidable Preparation waste: 26% avoidable; 74% unavoidable Edible and inedible waste ranged from 20 to 38% of the energy value of meals served in the hotels, 9% in the city center restaurant complex and 42% in the college restaurant. The average energy value for meals in the four hotels of 6.5 MJ per cover reflects the calculated average for lunch of 5.6 MJ Food wastage: Average loss of energy (SD 0.9 MJ) and for dinner of 7.4 MJ (SD 1.3 MJ). Waste values represented 31 and 33% of food input on an energy basis in the hotels and 3% of food input on an energy basis occurring during meal preparation and Food waste in the restaurant complex. consumption (expressed as a percentage of the energy value of the meal) The apparently high waste values in the hotels studied are attributed to their traditional catering methods using a high proportion of unprocessed foods and offering extensive menus . The low waste values in the restaurant complex reflects the almost total use of pre‐prepared food items, restricted menus, customers paying for each meal at the time of eating and established company control procedures. • The average total waste per employee (tons per year)
Hotels: 1,583 (4,34 kg/day) Restaurants: 1,467 (4,02 kg/day) QSRs: 1,4 (3,84 kg/day) Pubs: 2,467 (6,76 kg/day) • Waste generation at each business (litres • The composition (%) of mixed (residual) waste disposed of by the hospitality sector (138 samples) in the UK by primary per day and kg per day) Mixed (residual) waste, food waste, material category: Food: 41%; Glass: 14%; Paper: 13%; Cardboard: 9%; Dense plastic: 5%; Plastic film: 5%; Other: 13% • Composition of waste streams (especially bulky waste, brown glass, clear glass, • The composition (%) of mixed (residual) waste disposed of by hotels (35 samples) in the UK by primary material category: food waste and residual / mixed waste) green glass, paper and card , metals, Food: 37%; Paper: 18%; Glass: 10%; Cardboard: 7%; Dense plastic: 7%; Plastic film: 8%; Other: 13% • Carbon benefits of preventing, recycling mixed plastic, oils, hazardous waste • The composition (%) of mixed (residual) waste disposed of by pubs (29 samples) in the UK by primary material category: and recovering waste Food: 37%; Paper: 11%; Glass: 18%; Cardboard: 9%; Dense plastic: 5%; Plastic film: 5%; Other: 16% • The composition (%) of mixed (residual) waste disposed of by QSRs (32 samples) in the UK by primary material category: Food: 51%; Paper: 15%; Glass: 3%; Cardboard: 9%; Dense plastic: 5%; Plastic film: 6%; Other: 12% • The composition (%) of mixed (residual) waste disposed of by restaurants (42 samples) in the UK by primary material category: Food: 44%; Paper: 14%; Glass: 14%; Cardboard: 10%; Dense plastic: 4%; Plastic film: 5%; Other: 9% 69
Doc. ID Waste related Indicator (sets) used Waste types covered 78 Waste generation of collection spot [kg/day] MSW, food waste, yard waste, recyclables, hazardous waste, contaminated waste and other waste. 19 Daily waste generation per guest, per employee, guest room, and per seat Total solid waste 56 Annual waste generation per type of establishment (kg per employee and year) Residual waste, recyclables (paper and cardboard, organic waste, glass packaging, lightweight plastic packaging, metal packaging), sector‐
specific wastes (WEEE, yard waste, food waste, cooking oils), hazardous wastes (residues of printing ink and toner cartridges, fluorescent lamps, batteries), total waste generated 57 Quantitative Analysis: plastic, wrapping and non‐glass beverage containers; paper; glass; organic, • Total solid waste from bins generated per domestic and other miscellaneous beach user (kg/day) waste •Waste density (g/m2/day) Qualitative Analysis: water and sand • Waste composition litter components such as oil, foam, tar, human‐generated litter, terrestrial and marine vegetation, and jellyfish Results • Carbon savings from food waste recovery: 0.5 tons of CO2e emissions are generated for every ton of food waste currently sent for disposal • Carbon savings from food waste prevention: 4.2 tons of CO2e emissions are produced for each ton of food disposed To calculate a waste generation rate for accommodations, an occupancy rate of 50% was assumed for hotels and 30% for guesthouses with two persons per unit Based on this assumption, a tourist’s stay would lead to the generation of 1.74 kg per night of solid waste compared to 0.8 kg / day of local waste generation rate per capita. The generation rate for the guesthouses was 1.98 kg per night while those of the hotels was 0.62 kg per night. However, luxury can dwarf economies of scale. For the 5* establishments a night stay could result in 3.77 kg per night of solid waste per guest. Composition data from the 20 collection spots: 56 % food waste, 17 % recyclables, 13 % other waste, 9 % yard waste, 4 % contaminated waste, 1 % hazardous waste. Waste generation (kg/year):
• Accommodations: 360740.3 per establishment / 883.7 per employee / 5.9 per visitor / 832.3 per guest room • Restaurants: 87647.4 per establishment / 3558.5 per employee / 2.0 per visitor • Golf courses: 108721.2 per establishment / 1144.4 per employee / 2.2 per visitor / 4530.0 per hole • Tour operators: 11270.4 per establishment / 784.0 per employee / 1.4 per visitor • Car rentals: 63013.2 per establishment / 1188.9 per employee / 0.6 per visitor The average food input per employee, per seat, and per guest was 3.11 tons, 0.66 tons, and 1.16 kg, respectively, while the average food output was 1.08 tons, 0.23 tons, and 0.40 kg, respectively. Visitor expenditures by these sectors (excluding golf courses) accounted for 72.9% of the total tourism expenditures in 2008 (table 1). Average waste quantities (kg per employee and year) for: Hotels // restaurants // cafés/bars // snack bars/cafeterias • Residual waste: 1.129 // 972 // 350 // 2.101 • Recyclables: 323 // 132 // 89 // 340 • Sector‐specific wastes: 57 // 317 // 40 // 264 • Hazardous wastes: 1,1 // 0,3 // ‐‐ // ‐‐ • Total waste: 1.511// 1.422 // 479 // 2.705 Waste quantities in "best practice establishments" (kg per employee and year) for: Hotels // restaurants // cafés/bars // snack bars/cafeterias • residual waste: 708 // 451 // 139 // 1.198 • recyclables: 565 // 631 // 174 // 831 • sector‐specific wastes: 46 // 522 // ‐‐ // 756 • hazardous wastes: 1,5 // 0,6 // ‐‐ // ‐‐ • total waste: 1.320 // 1.605 // 313 // 2.785 Urban beaches had higher densities of waste deposition and lower percentages of organic, domestic and other miscellaneous waste than urbanized beaches. Analysis of monthly waste production data from various municipalities located on the Catalan coast demonstrates that waste production is much larger in summer than the rest of the year. The waste density (g/m2/day) on most beaches was relatively constant from the end of July to the end of August, and then declined sharply at the beginning of September. • Most beaches had a similar composition of waste: (1) organic, domestic and other miscellaneous waste (31‐63%); (2) plastic, wrapping and beverage containers (26‐35%); (3) glass (7‐29%); and (4) paper (2‐7%). • Average composition of the waste and litter from the beach of Lloret Centre in August 2005: Pl/W/BC, plastic, wrapping and beverage containers (21); O & D, organic, domestic and other miscellaneous waste (28%); Gl, glass (22%); P, paper (4%); BSL, big‐sized litter on sand (13%); ST, sand withdrawn by tractor (10%); SSLT, small‐sized litter withdrawn by tractor (2%). 70
Doc. ID Waste related Indicator (sets) used Waste types covered 68 Average weight of the generated solid waste per day (kg/day) as well as per person and day (kg/person/day) Aluminum, cardboard, metal, tinplate, wood, organic matter, cloth, multilaminated containers, paper, toilet paper, disposable diaper, plastic film, rigid plastic, PET plastic, No 6 plastic, small waste, hazardous waste, glass, others, total 69 Municipal solid waste (MSW) generation rates per capita and on a daily basis Food waste, cardboard, glass, paper, metals, bones and egg shells, polythene, cloth rags, textiles, ceramics, wooden chips, leather and rubber, plastic, inert, total MSW 79 58 75 Tourism environmental composite indicator (TECI): TECI provides the basis for a comparative analysis for typical all‐sized hotel categories in terms of their combined environmental pressure. Different normalized key performance indicators, i.e., pressure per m2, pressure per room, pressure per guest night are combined in one single composite indicator. • Waste per litres and guest night
• Waste per kg and guest night • Waste paper per employee per month • Volume (litres) or weight (kg) of non‐
hazardous waste sent to landfill over the last full calendar year only information related to environmental attitudes Waste not included in case study Results • Average percentage of beach waste and litter of the total amount of waste collected in the municipality during summer:
1.46% (Lloret Centre), 3.24 (all Lloret beaches). Waste and litter values from Lloret Centre include litter retired from tractors and big‐sized litter left by users. Waste and litter from all beaches of the municipality do not. • Sant Sebastia` beach in Barcelona, where 0.046 kg per user day was estimated (Environmental Study of the Beach of St. Sebastia`, 2004). • The generated solid waste average per capita was 0.155 kg per person and day. During the high season, the average increased to 0.188 kg per person and day, and during the low season the average decreased to 0.144 kg per person and day (Table 1). Sundays were the days with more waste generation in both seasons. • Waste composition: inorganic matter: 54.52%; organic matter: 32.03%; nonrecyclable: 10.60% and others: 2.85% • In 2007, the Iztaccíhuatl‐Popocatépetl National Park received an average of 128 000 visitors during the year and the waste generated was 0.010 kg per person per day (Simon, 2007). • In the same year, Chapultepec Park in Mexico City received an average of 175 000 visitors every week; generating 35 000 kg of solid waste per week, which is equivalent to 0.2 kg per person per day (SMADF, 2007). • Site 1 (tourist huts, hotels‐cum‐restaurants and a huge military base camp): 0.970 kg/person/day (net weight) • Site 2 (area with only a few temporary restaurants; remote location, with a narrow and risky passage through the hilly terrain): 0.201 kg/person/day (net weight) • Site 3 (village of Yusmarg, 40 households, life‐sustaining domestic and agricultural activities): 0.288 kg/person/day (net weight) • Average study area (Yusmarg): 0.484 kg/person/day (net weight) • Over all sites, 56% of waste was recyclable materials, 29% was compostable wastes, 9% was combustible wastes and 6% was inert materials • A typical tourist generates at least 1 kilogram (kg) of solid waste per day (Davies and Cahill, 2000), whereas, a tourist from developed countries probably generates up to 2 kg per day in the United States (UNEP, 2003). • Waste generation is excluded from this study since the hotels studied did not hold such records. • Key performance indicators per guest night // per square meter // per room for: (a) energy consumption, (b) water consumption, (c) kg CO2‐eq for accommodation, (d) kg CO2‐eq for transport of the sample of hotels in Chalkidiki, Greece. Waste benchmarks for luxury hotels (excellent // satisfactory // high) Non‐hazardous waste sent to litres waste / guest night: < 3.0 // < 5.0 // < 7.0 landfill, waste paper from hotel kg waste / guest night: < 0.6 // < 1.2 // < 2.0 offices A conventional hotel office generates about 14 kg of waste paper per employee per month, and around one third of this (4.6 kg) is high grade recyclable paper that can be conveniently recovered. n.a. Results interesting could be the following: The hotel industry is among the most energy‐intensive sectors of the tourism industry. It is estimated that a typical hotel annually releases between 160 and 200 kg of CO2 per m2 of room floor area, depending on the fuel used to generate electricity, heating, or cooling. European hotels consume 39 TWh (terawatt hours) of energy annually, half of which is in the form of electricity. It is estimated that, depending on the hotel standard, guests generally consume between 170 and 360 liters of water per night.14 By comparison, a recent report from a European hotel chain provided a figure of 440 liters per guest‐night,15 while another source reports a consumption of 224 liters per guest‐night. By one estimate, a typical hotel produces in excess of 1 kg of waste per guest per day, which results in tons of waste each 71
Doc. ID Waste related Indicator (sets) used Waste types covered Results month. A large proportion (50 to 60 percent) of the materials that constitute this waste could be recycled or reused.17 The average quantity of unsorted waste materials for Radisson SAS hotels was reported as 3.1 kg per guest‐night in 2002, for instance, with Scandinavian and German facilities producing considerably less waste (1.5 kg per guest‐night) than the corporate average. 18 On the other hand, Scandic Hotels reported an average of 0.515 kg of unsorted waste per guest per night.19 Best practices in waste minimization and recycling have shown that waste generation can be limited to 50 g of unsorted waste per guest‐night. 77 11 12 14 15 Benchmarks from Vietnamese and European hotels compared with case study: • kWh/guest/day (elctricity consumption) • m3/guest/day (Water consumption) • kg MSW/guest/day (MSW generation) • m3 wastewater/guest/day • Unsorted waste per overnight stay (kg / overnight stay) • Waste production indicator (SUM waste volume of non‐recycled waste categories / weighted number of guests) [weighted number of guests = overnight stays + 0,25 * warm meals] • Generation of waste • Separated collection of waste Volume of waste recycled
Indicators of waste production: • Total amount of waste collected • Waste volume produced by the destination (tons) pa / Person years pa (by month) • Waste disposed by different methods (specify, e.g. incinerated, deposited in landfill, etc.); • Waste volume attributable (by month or season) to tourism. Indicators of waste reduction: • Volume of waste recycled (m3) • Total volume of waste (m3) • Number of tourism establishments collecting waste separately, capacity of collecting separated waste from local residents; • Number of tourism establishments recycling their own waste (e.g. composting). Indicators of adequacy of waste collection services: • % of destination area (especially in urban 1.82 kg MSW/person/day (Balearic Islands for 2004) MSW incl. Organic matter, paper 2.50 kg MSW / person / day in summer and cardboard, plastics, glass and 1.50 kg MSW / person / day in winter hazardous waste) 0.77 kg MSW / person / day (Guesthouse) Total waste, recyclables Nordic Ecolabelling: Benchmarking: 0,5‐1,5 kg unsorted waste/ovn stay n.a. No (quantified) results related to waste generation from tourism n.a. No (quantified) results related to waste generation from tourism n.a. No (quantified) results related to waste generation from tourism 72
Doc. ID Waste related Indicator (sets) used Waste types covered Results sites) covered by solid waste collection services; • Percentage of tourism establishments covered by waste collection programs. Indicators relating to handling and disposal of hazardous substances: • Number and volume of hazardous substances in use (for key substances, volume of use over time); • % of these substances for which appropriate management and disposal policies and programs are in place; • % of employees informed and trained in the use and disposal of the substances they use (e.g., cleaners knowledgeable of how to deal with waste cleaning fluids, engineers trained in emergency spill handling). Other potential indicators: • Whether or not the enterprise or attraction has an environmental management system or a hazardous waste program; • For destinations, percentage of enterprises with toxic waste management programs; • % of hazardous waste generated in the community which is collected in a special waste program. Indicators of impact of waste on the destination: • Quantity of waste collected from public areas and streets; • Quantity of waste strewn in public areas (Garbage counts on key sites) • Image of cleanliness of the destination (questionnaire based). 64 Waste composition 67 Waste production (kilograms per guest night and/or liters per guest night) 70 Waste generation in kg / person / day Food waste, paper, cardboard, The examination of wastes from city 25 hotels showed that from 1991‐1993 the hotel waste consisted of 46% food waste, plastics, glass, metals 25.3% paper, 11.7% cardboard, 6.7% plastics, 5.6% glass, and 4.5% metals (source???). Benchmark values for waste production in typical hotels in all climate zones (source: www.benchmarkhotel.com): Waste production (kg per guest night) per hotel type Hotel type: Excellent // Satisfactory // High // Excessive Waste in general • Luxury fully serviced hotels: <0.60 // 0.60–1.20 // 1.20–2.00 // >2.00 • Midrange fully serviced hotels: <0.40 // 0.40–1.00 // 1.00–1.50 // >1.50 • Small / budget fully serviced hotels: <0.60 // 0.60–0.80 // 0.80–1.50 // >1.50 n.a. European tourists: 1 kg / person / day when touring in Europe 73
Doc. ID 25 Waste related Indicator (sets) used Waste types covered Results US tourists: 2 kg / person / day when touring in USA
Broad range of solid waste generation in touristic locations: varying between 1 and 12 kg / guest / day WASTE GENERATION IN HOTELS
• a hotel guest is estimated to generate up to 1 kg of waste per day on average (International Hotel Environmental Initiative, 2002) • guest rooms generated about 0.91 kg of waste per day, while quality dining rooms and the hotel kitchen produced about 0.45 kg of waste per guest meal served (Axler, 1973). • On comparison with Shanklin et al. (1991), it can be initially perceived that the daily waste generated per room has halved from 1973 to 1991. However, if the waste generated on checkout days is considered, then the rates from both studies become similar. • On the other hand, Earle and Townsend (1991) reported the waste generated daily per room to vary from 1.81 to 3.18 kg. • In the same paper, Earle and Townsend (1991) mention a waste audit conducted prior to their study, through which it was found that thewaste production in guest rooms in the Orlando area ranged from 0.23 to 12.93 kg per day. • A third publication mentions how, on the global scale, a hotel guest produces about 1 kg of waste per day (Losanwe, 2013). • All the studies mentioned here collectively account for a large time span. Although significant variation has been observed in the results, the most common value was around 0.45 ‐ 0.91 kg per day per room. • About 95% of a restaurant's general waste could typically be recycled or composted (Nielsen and Green Restaurant Association, 2004), and as is clear from the solid waste breakdown, the fraction of organics in restaurant waste is almost double that of hotels. • Additionally, the two entries in the last part of Table 3 show how organics are a more significant component of the waste from restaurants in Malaysia than of the waste from restaurants in Chicago. This is paralleled by many studies which show a greater proportion of organics in the municipal solid waste generated in developing countries (Hoornweg and Bhada‐Tata, • Waste generation per hotel guest per day Unsorted waste, total waste, food 2012; Karak et al., 2012). • Waste generation per guest per hotel waste (avoidable, possibly avoidable, • Swedish best practice has shown that efficient waste management can reduce the quantity of unsorted waste per guest‐
room unavoid‐able; edible = avoidable + night to only 50 g (Bohdanowicz, 2006). • Waste generation per guest per hotel possibly avoid‐able) kitchen Food Waste • Food waste is reported to account for about 56% of the garbage from restaurants and 28% of the garbage from hotels (Iowa Waste Reduction Center (IWRC), 2013). • Quantification of food waste in the hospitality industry ‐ In Sweden, plate waste is the single largest source of loss, between 11% and 13% of the amount of food served at food service institutions (Engstr€om and Carlsson‐Kanyama, 2004). ‐ In UK restaurants, 65% of food waste comes from preparation ‐ peelings, off cuts and anything ruined while cooking; 30% of food waste comes back from customers' plates; 5% of food waste is classified as ‘spoilage’ e out‐of‐date or unusable items (Sustainable Restaurant Association, 2010) ‐ UK hospitality and food service sector: on average, 21% of food waste arises from spoilage; 45% from food preparation and 34% from consumer plates (Parfitt et al., 2013). ‐ According to a Swiss report, a typical food portion weighing 300 g and served in the hotel industry can lead to a maximum of 835 g of waste material, 780 g preparation waste and 55 g upon disposal (i.e. what remains of the portion after the guest has eaten and is therefore disposed of) (Zein et al., 2008). ‐ In Finland, it was found that restaurants belonging to the catering sector discarded 19% of all produced and served food. Of this 6% was kitchen waste, 5% was service waste, and 7% was leftovers. It was therefore concluded that food waste in licensed restaurants in Finland amounts to approximately 18e20 million kg annually (Silvennoinen et al., 2012). ‐ The National Solid Waste Management Association reported that, in the United States, cafeterias generate 0.45 kg of waste per meal served; and restaurants generate 0.68 kg per meal served (Shanklin, 1993). ‐ In the UK, an average of 0.48 kg of food waste is generated per guest at a restaurant (Sustainable Restaurant Association, 74
Doc. ID Waste related Indicator (sets) used Waste types covered Results 2010). ‐ In the United States, restaurants produce an average of 45,360 kg of waste per outlet per year (Horovitz and USA Today, 2008; Jeong, 2010) ‐ For resorts/conference properties: food waste (kg/yr) [in Massachusetts and Connecticut, USA] ¼ 0.45 kg/meal*number of meals/seat/day*number of seats*365 days/yr (Draper/Lennon, Inc and Atlantic Geoscience Corp., 2001; Draper/Lennon, Inc, 2002) ‐ For restaurants: Food waste (kg/year) [in Massachusetts and Connecticut, USA] ¼ number of employees*1360.78 kg/ employee/yr (Draper/Lennon, Inc and Atlantic Geoscience Corp., 2001; Draper/Lennon, Inc, 2002) These various food waste formulae/estimations/calculators give an indication of the large variety of reported values for these different quantities. For example, plate waste due to spoilage varies from 5 to 21%, though studies carried out at food service institutions have shown that plate waste has the potential of being eliminated almost completely (Engstr€om and Carlsson‐
Kanyama, 2004). • Total waste generation averaged 1.98 kg (6 litres), per guest‐night (Austria & Germany)
• Packaging alone can account for up to 40 % of a hotel’s waste stream (Travel Foundation, 2011) • Across an entire hotel chain, the median rate of total waste generation across hotels in this chain is 1.05 kg per guest‐
night. Based on the top tenth percentile of hotels in this chain, the following benchmark of excellence is proposed: BM: total waste generation (sorted plus unsorted) of ≤0.6 kg per guest‐night. • On average, hotels generate approximately one kg of unsorted waste per guest per night (ITP, 2008) • Across an entire hotel chain, the median quantity of unsorted waste per guest‐night is 0.46 kg, and the top tenth percentile best performers generate less than 0.16 kg of unsorted waste per guest‐night. Thus, the following benchmarks of excellence are proposed: BM: at least 84 % of waste, expressed on a weight basis, is recycled. BM: unsorted waste sent for disposal is less than 0.16 kg per guest‐night. Compliance across the entire hotel chain represented with the proposed benchmark of 0.16 kg waste per guest‐night would lead to a reduction in unsorted waste sent to landfill or incineration of 0.3 kg per guest‐night. Compliance with the proposed benchmark across average hotels generating one kg residual waste per guest‐night (ITP, 2008) would reduce the quantity of unsorted waste sent to landfill or incineration by 0.84 kg per guest‐night. • On average in UK restaurants, 0.48 kg of food waste is generated per diner (SRA, 2010). dominated by kitchen preparation (65 %), followed by returns on customer plates (30 %). Spoilage of stored food made only a minor contribution (5 %). • Two large German restaurants within a theme park serve, respectively, 470 000 and 315 000 dining guests annually. They generate 0.26 and 0.36 kg organic waste per diner, respectively. • Organic waste can represent 37 % of residual waste generated by accommodation, and almost 50 % of residual waste generated by restaurants (WRAP, 2011). • BM: total organic waste generation ≤0.25 kg per cover, and avoidable waste generation ≤0.18 kg per cover. CAMPSITES Campsites: total residual waste sent for disposal of <=0.2 kg per guest‐night BENCHMARKS WASTE Hotels and similar accommodation • total waste generation (sorted and unsorted) of <=0.6 kg per guest‐night • at least 84% of waste, expressed on a weight basis, is recycled • unsorted waste sent for disposal is less than 0.16kg per guest‐night • total organic waste generation <=0.25 kg per cover and avoidable waste generation <=0.18 kg per cover 17 • Total waste generated, sorted and unsorted, expressed as kg per guest‐night • % waste reused (%‐age of total waste generated) • % waste recycled (%‐age of total waste generated) • the quantity of unsorted residual waste sent for disposal, expressed as kg per guest‐night. • Organic waste in kg/dining guest (cover) • % organic waste recycled Total waste, food waste 7 • Quantity (volume and/or weight) of waste per tourist and day (e.g. kg waste/tourist/day) • Composition of waste • Cost of different waste management techniques Municipal solid waste (MSW), paper, plastics, glass, metals, organic materials, textiles, demolition and • Every international tourist in Europe generates at least 1 kg of solid waste per day (IFEN 1999). In fact, tourists from construction debris, chemicals and developed countries probably produce more (up to 2 kg/ person/day for the United States ‐ EPA, UNEP/Infoterra). products with chemical components, rubber and rubber products, human 75
Doc. ID Waste related Indicator (sets) used Waste types covered Results / animal waste, others
29 42 43 44 48 53 Explanatory variables Correlation with HW (rs) (Significant level at 99%.) (regression model)
Household waste (HW), glass, paper • Spaces for tourist accommodation (‰ inhabitants) tACCO: 0.225 and cardboard, lightweight • Hotel and catering establishments (‰ inhabitants) HOCA: 0.361  Tourism has an influence packaging and mixed waste Lorena et al. (2013) estimate that a tourist can represent 0.3–0.6 kg of sorted HW per day. Results showed that an increase of 1% on tourist arrivals growth rate would generate an increase in waste disposal MSW generation by tourists Total amount of disposed MSW generation of 1.25%. Furthermore, an increase of tourist expenditures by 1% on the destination would lead to an increase of municipal solid waste generation of 0.51%. • Fixed treatment cost/ton (Euros)
Non‐sorted MSW, recycled glass, Empirical findings show that there is a strong correlation between seasonality in MSW generation and tourist arrivals for all • Average monthly evolution of use (% of recycled light packaging, recycled categories (non‐sorted and sorted MSW). total capacity of waste treatment facilities) paper and card‐board If we consider that local population growth rate does not change, then an increase of 1% on nomad population (tourist arrivals) would produce an increase in waste disposal generation of 2.024%. Furthermore, if Destination Management MSW generation by tourists Total amount of disposed MSW Offices (DMO) seeks to increase tourist expenditure by 1% on the destination, subsequently the increase of waste disposal generation would be of 0.31%. It is central to take into account that both concepts are important to measure the impact of tourism growth on the environment. • MSW per‐capita productions per year per “resident” (inhabitant) population and per • MSW per‐capita production attributable to the tourist‐type person, which on a daily basis corresponds to 2.6 kg MSW per “total yearly equivalent” population person per day • Separate collection yields per‐capita (as • MSW per‐capita production attributable to residents: approx. 2.0 kg MSW per person per day weight quantity) individually attributable • Higher incidence of the organic fraction and glass during the touristic summer months (Aug‐Sep) as compared with a typical to the “resident” person and the “yearly winter month (Feb) equivalent tourist” person • Lower incidence of both the cellulosic and plastic components during the summer months • Monthly separate collection rates of • decreasing of SC (separate collection) efficiency values (as percentage) during the summer‐time (especially June, July and MSW fractions collected separately MSW (as both weight quantity and August) in “Coastal Municipalities” and of residual MSW efficiency percentage) MSW per‐capita productions (2006) in the “Coastal Municipalities” area. “total yearly equivalent” population = the • individually attributable to the “resident” person: 745 kg per year sum of the “resident” population and the • attributable to the “yearly equivalent tourist” person: 954 kg per year definable “yearly equivalent touristic” Per‐capita weight SC yields(2006) in the “Coastal Municipalities” area. population. The units of “yearly equivalent • individually attributable to the “resident” person: 223.5 kg per year tourist” have been achieved from the ratio • attributable to the “yearly equivalent tourist” person: 132.5 kg per year between the yearly touristic overnight stays and the days in one year. • A significant linear relationship between tourism (overnight stay per day) and the amount of residual waste and organic waste in kg was identified. • Residual waste: 0.3 – 0.4 kg per tourist per day (The production of residual waste per inhabitant shows similar daily amounts.) Per capita waste generation (for tourists Residual waste, organic waste, bulky • Organic waste: 0.09 – 0.11 kg per tourist and day and 0.11 – 0.13 kg per inhabitant and day. and residents) (kg) waste • The relationship between overnight stays and employees in tourism is statistically significant. The analysis shows 2.82 – 3.43 overnight stays per employee in tourism (assumption: full time employment the wohle year) and 1.67 – 2.67 kg/d residual waste per employee. • IAIAsa International Association for Impact Assessment, South Africa (2007): 4 kg waste per tourist and day (for visitors of selected national parks (e.g. Kruger National Park) and World Heritage Sites and cities (e.g. Cape Town, Johannesburg)) Annual household waste generation per capita at municipal level 76
Doc. ID Waste related Indicator (sets) used Waste types covered 61 • Waste quantities (kg per inhabitant equ.) • Percentage of separate collection (SC) per month (kg fraction per kg total fractions) Food waste; green waste; paper and cardboard; glass, plastics and cans; other fractions; RMSW (residual municipal solid waste); bulky waste 72 MSW generation of tourist per day MSW total; MSW tourism share 20 • MSW kg /inh/month
• Separate collection SC in % of total MSW • Residual MSW kg /inh/month Municipal solid waste (MSW), separate collected recyclables, residual MSW 45 • Rates of relative growth based on a fixed value for mixed municipal waste collected in selected health resorts [%]. • Share of collected municipal waste from households in municipal waste collected in total [%] Mixed municipal waste 49 Waste generation per day from residents and tourists (kg/day) Residual waste, separately collected waste fractions (e.g. organic waste) 55 • Waste Ecological Footprint as % of total Waste in general Results • Schade, U. (1996) calculated for the Region of Güstrow in Mecklenburg‐Vorpommern (Germany):
1.1 kg waste produced per tourist and overnight stay 0.2 kg waste per excursionist and day For comparison: waste generation in Germany approx. 1.0 kg per resident and day • Müller (2007): 2‐5 liters (volume) of waste are produced per guest per day in the lodging and hospitality industry. • FEIGE and MÖLLER (1992) calculated 0.64 kg operational waste of accommodation establishments in Munich (Germany) per overnight stay. Tourists produce 1.1 kg waste per tourist and day, residents also produce 1.1 kg per inhabitant and day. Day trippers / Excursionists leave 0.2 kg of waste per day tripper and day behind on the visited site. Table 2: Changes in Percentage of SC (Separate Collection) in 2012 in the Val di Fassa case study (112% increase in population due to tourism). The most tourist months for the Val di Fassa case study are both in winter and in summer and their effect is seen in the increase of the factions connected with the tourists meals and also the increase of RMSW and in the decrease of the ones connected only to the residential population (green and bulky waste or other factions). On average, between 1998 and 2010, a 1% increase in the tourist population in Menorca causes an overall MSW increase of 0.282% over all months. Therefore, the effect of a 1% increase in the resident population on MSW is 0.718%. An additional tourist on the island generates 1.31 kg / day, while an additional resident generates 1.48 kg / day. MSW generation by the average resident is greater than that generated by a tourist. According to the estimate, one resident generates, on average, approximately 13.2% more MSW than one tourist in Menorca over all months. Thus, the average of MSW per resident generated in EU‐27 countries during 1998–2010, is 1.41 kg, and in Spain it is 1.65 kg / day (EUROSTAT, 2011). The dynamic regression performed also indicates another result. The estimate of the parameters shows that the effect on MSW caused by tourists in Menorca is not only contemporary because it also has consequences in the immediately following months. This is because, on the one hand, there is an offset between the moment when waste is generated and when it is recorded at the waste management plant and, on the other hand, individuals’ behavior in relation to the generation of waste in the present depends on the past. Therefore, an increase of 1% in tourists in a given month causes an increase of 0.249% of MSW in the same month (1 additional tourist causes an increase of 1.16 kg day 1 in the same month); during the month immediately following an increase of 0.016% (0.07 kg / day1), and two months later it is 0.008% (0.04 kg / day), while the effects for subsequent months is negligible. In both regions, but especially in Apulien, seasonal changes in amounts of waste generated per capita are clearly visible. The summer period (high tourism season) shows the lowest values of separate collection and the highest values of per capita MSW generation. The total quantity of collected municipal waste in the selected spa cities does not always go along with the amount of collected household municipal waste – a situation recorded in Świnoujście, Sopot, Ustroń and Ustka. In these cities, the amount of collected municipal waste in 2012 was bigger than compared to 2004, but it was the other way around in terms of municipal waste collected from households. Considering the fact that spa cities are characterized by large tourist flows, the problem of municipal waste is also linked with the well developed spa infrastructure. Municipal waste is a more complicated problem in spa cities though. The average annual quantity of waste collected per capita tends to be overestimated by the large tourist traffic connected with the resort functions of these cities. • Total waste (= residual waste + separately collected waste fractions): 1.10 kg per resident and day (excluding tourism) // 0.66 kg per tourist and day • Residual waste: 0.84 kg per resident and day // 0.59 kg per tourist and day • Organic waste: 0.28 kg per resident and day // 0.18 kg per tourist and day Waste Ecological Footprint totaled 1% of the total tourist footprint, or .045 gha/year per tourist equivalent resident (same 77
Doc. ID Waste related Indicator (sets) used Waste types covered tourist footprint per tourist equivalent resident • “equivalent residents” = average number of tourist individuals present on in the area using bed‐nights divided by days in a year Results quantities for local residents assumed). • Estimate of the tourist footprint as an equivalent resident (5.28 gha) is similar to that estimated for residents (5.47 gha), excluding arrival transport. • Arrival transport contributes an additional 32.8 gha per tourist equivalent resident (0.48 gha per arrival), and accounts for 86% of the total tourism impact. Total MSW; Organics: Paper (all kinds, magazines, newspapers, books, packaging materials, cardboard); Putrescibles (food waste, yard waste, leaves); Plastics (PVC, PET, HDPE, LDPE, others); LWTR (leather, wood, textiles, rubber).Inorganic: Glass (all kinds and colours); Metals (all kinds except aluminum); Aluminum (all kinds); Inert materials (stones, ground, construction and demolition wastes).Miscellaneous (nappies, sanitary napkins, materials that do not fit in any of the above categories) Waste • During ‘‘high season’’ months (months with increased number of tourists) not only are increased MSW quantities produced, but also MSW composition is accordingly altered. High fractions of materials like aluminum cans and glass bottles (especially non‐refillable ones) and paper and/or plastics packaging materials are representative characteristics of intense tourist activities and greenhouses operation in the area. • MSW production from tourists in the region of ... Rethymnon: 71.378 kg/d and 26.053 ton/y Heraklion: 289.522 kg/d and 105.676 ton/y Lassithi: 66.301 kg/d and 24.200 ton/y Total: 427.201 kg/d and 155.928 ton/y • The mean produced quantity of MSW per tourist per day (=1.2 kg/tourist/day). Further details on MSW composition (%) in some Greek regions and cities, (wet weight) in Table 1. 36 Quantities of MSW (kg/resident/day) 54 Waste production (kg per tourist per day) Waste production per capita per tourist in NUMANA: 2.27 kg per day • Total waste induced from tourism related activities (tons / year) Tourist (resident and non‐resident) waste generation: approx. 2.6 kg municipal waste per overnight stay and 0.40 kg organic Municipal solid waste, organic waste • Tons of organic waste per year related to waste per overnight stay tourism (= total overnight stays) 59 78
3.3.6 Quantified Indicator Results In this Chapter a compilation of benchmarks and quantified indicator results will be provided, based on the literature review. All quantified data were collected in an Excel form and analysed accordingly. For the hotel, guesthouses etc. related data (bottom‐up approach), 50 datasets were analysed (just a few data also include data provided at national level). The boxplot analysis of this 50 datasets show (see Figure 24), a 25% quantile at 0.58 and a 75 % quantile at 2.39 kg/tourist/day, leading to an interquartile range of 1.81 kg/tourist/day. The median of “waste generated per tourist and day” is lying at 1.10 kg/tourist/day (the average value is 1.67 kg/tourist/day). Figure 24: Boxplot of the distribution of the indicator “waste generated per tourist and day (n=50) 79
Figure 25 displays the distribution of 50 datasets on tourist waste generation [kg/tourist/day]. The green are symbolizes the are, where the median (1.10 kg) and the average value (1.67 kg) of the distribution is situated. Some of the datasets show ranges of values that were displayed in the corresponding literature. 80
Figure 25: Distribution of 50 datasets on tourist waste generation Figure 26 shows benchmarks given in the respective literature. 20 benchmarks were described and related to different hotel types. 7 reports depict ranges from 0.4 to 1.0 kg and 8 reports report between 1.0 and 2.0 kg / tourist / day. The higher ranges given in this Figure are from a case study of Vietnamese hotels. It is not possible to derive useful information on the hotel types ‐ it can not be stated, that the more luxurious the hotel, the more waste is generated. Yet, Sridang (2005) display data for large hotels (>200 rooms) with 1 .16 to 3.5; medium hotels (80‐200 rooms) with 0.78 to 3.15 and small hotels (<80 rooms) with 0.1 to 1.02 kg/room/day for hotels in Thailand. Generally spoken, the benchmarks set for different hotel types range from 0.4 kg / tourist / day (excellent), to 0.7 – 0.9 kg (satisfactory), to 1.15 – 1.6 kg (high), to 1.5 – 2.0 kg / tourist / day excessive). Figure 26: Benchmarks of tourist waste generation fot different hotel types Some papers also report quantified results and relate it to room level [kg / room /day]. This means that the toal waste generated is divided by the number of rooms. Results vary between 2.3, 3.5 and 9.2 kg / room and day. Some papers relate the generated waste to the number of employees: WRAP (2011) report approx. 4.7 kg / employee / day, Saito (2013) report 2.4 kg / employee for accommodation, 9.7 kg / employee for restaurants (of which 3 kg / employee are food waste). Graggaber et al. (1999) present results of a sector srudy in Austria and the authors depict 4.0 kg / employee total waste in hotels (3.1 kg / employee residual waste and 0.9 kg / employee 81
recyclables). Ofner (2011) report for an Austrian tourist region 1.7 to 2.7 kg /employee / day residual waste at hotels. Several studies report, that the highest share of the total waste generates is related to organic waste. Spitzbart et al. (1999) researched hotels in Zanzibar and reported approx. 80 % of the total waste is of biodegradable nature, Hoang (2005) report >75% organics in Vietnam. Zorpas et al. (2015) report > 40 % biodegradables in Cyprus´ hotels. Chan and Lam (2001) researched waste generated only from hotel rooms in Hong Kong. It turned out the the generated waste was 2.76 kg / room / day. The authors divided into 5 different waste categories, the percentage is given in Figure 27. Figure 27: Waste composition in hotel rooms in Hong Kong Hotels in New York wer assessed and lead to composition data of paper (including mixed paper, newspaper, corrugated cardboard, and high grade paper) with 39.9%, organics / food 27.8%, glass 7.6%, plastics 7.1%, yard waste 6.7%, metals 6.1% and other / special waste 4.5%. WRAP (2011) carried out a study on the UK hospitality sector. Results show for the composition (%) of mixed (residual) waste disposed of by the hospitality sector (138 samples) in the UK by primary material category: Food: 41%; Glass: 14%; Paper: 13%; Cardbord: 9%; Dense plastic: 5%; Plastic film: 5%; Other: 13%. The composition (%) of mixed (residual) waste disposed of by hotels (35 samples) in the UK by primary material category: Food: 37%; Paper: 18%; Glass: 10%; Cardbord: 7%; Dense plastic: 7%; Plastic film: 8%; Other: 13%. The composition (%) of mixed (residual) waste disposed of by pubs (29 samples) in the UK by primary material category: Food: 37%; Paper: 11%; Glass: 18%; Cardbord: 9%; Dense plastic: 5%; Plastic film: 5%; Other: 16%. The composition (%) of mixed (residual) waste 82
disposed of by quick service restaurants (32 samples) in the UK by primary material category: Food: 51%; Paper: 15%; Glass: 3%; Cardbord: 9%; Dense plastic: 5%; Plastic film: 6%; Other: 12%. The composition (%) of mixed (residual) waste disposed of by restaurants (42 samples) in the UK by primary material category: Food: 44%; Paper: 14%; Glass: 14%; Cardbord: 10%; Dense plastic: 4%; Plastic film: 5%; Other: 9%. Hogan and Bergin (2007) report a reduction potential in Irish hotels from 2.5 to 1.5 kg/tourist/day (30 % reduction). Hotel restaurant data are ranging from 0.67 to 0.75 kg/cover. Restaurants from 0.5 (food waste only) to 2.0 kg / guest served. An extensive food waste research was carried out by Papargyropoulou et al. (2016). According to the analysis of incoming food and the outgoing food waste, it was calculated that approximately 30% of purchased food was lost in the form of food waste (no re‐use of surplus food waste was observed in this case study). In more detail, approximately 17% of food was lost during preparation, 7% as customer plate waste and 6% as buffet leftover waste. The avoidable and unavoidable food waste fractions of food waste are depicted with: 



Total food waste: 56% avoidable; 44% unavoidable; Buffet leftover: 94% avoidable; 6% unavoidable; Customer plate waste: 92% avoidable; 8% unavoidable; Preparation waste: 26% avoidable; 74% unavoidable. 3.3.7 Food waste The studies reviewed regarding food waste can be divided in two groups in terms of scope and boundaries. The first group of studies include studies of hotels and restaurants where food waste quantification is somtimes the main focus, but most often just a part focus on the way to describe the general sustainability of the studied facilities or to provide data on a more aggregated level. The second group consist of studies where different waste management options for food waste, organic waste or municipal solid waste has been analysed to compare the environmental impact. In the second group there were also studies assessing waste prevention measures, but they were normally only making example calculations of the benefits of waste prevention rather then actual case studies. However, no studies that evaluate a combination of environmental assesment of waste management or prevention of food waste specifically from hotels/restaurants has been found. Of the studies quantifying food waste in hotels/restaurants they either limits the studies to a specific (and often rather small) group of hotels or restaurants in order to study a specific case (Engström & Carlsson‐Kanyama, 2013; Cummings, 2010; Papargyropoulou et al., 2016; Ball & Taleb, 2010) or they include a larger sample in order to provide e.g. national figures (Katajajuuri et al., 2014; Jensen et al., 2010; Beretta et at., 2013). Chifaria et al. (2016) try to create a holistic framework for the integrated assessment of urban waste management systems and here food waste is included in the framework as one of several waste flows. The environmental assesments of waste management often includes the treatment methods landfill, composting, incineration and anaerobic digestion (Bernstad & la Cour Jansen, 2012; Laurent et al., 2013a; b). A few studies like Eriksson et al. (2015) and Vandermeersch et al. (2014) also include specific fractions of the food waste as animal feed. Environmental 83
assesments of higher prioritised waste management options (i.e. prevention) is more rare (Laurent et al., 2013a) and the few ones that exist often just calculate or discuss the needs and benefits of preventing food waste rather than evaluating actual prevention measures (e.g. Gentil et al. 2011; Giuseppe et al., 2014; Prefier et al., 2016; Mourad, 2016; Garrone et al., 2014). The most commonly used impact assessment category for waste management studies is global warming potential (Bernstad & la Cour Jansen, 2012; Laurent et al., 2013a; b). Even though a LCA normally consider several impact assessment categories there are even studies only considering the carbon footprint of waste management (e.g. Eriksson et al., 2015). However, additional to the assesment of global warming potential other commonly used envornmental impact categories were acidification, eutrophication and energy use, but also photochemical ozone formation, ozone depletion potential, fossil energy use, ecotoxicity potential, renewable energy use, land use, water use, resource use and human toxicity potential were found to be used occasionally (Bernstad & la Cour Jansen, 2012). 3.3.7.1 Waste related data used The case studies of hotels and restaurants were using waste data that were in some studies (e.g. Engström & Carlsson‐Kanyama, 2013; Katajajuuri et al., 2014) recorded solely for the purpose of the study. In Beretta et al. (2013) the food services recorded the waste and handed out the records to the authors for further analyses. The same thing was done in Cummings (2010) but here the waste collector did the recording and the information was then documented by the hotel through the waste bills. The waste collection billing system was also used in Jensen et al. (2010) but here the actual record of waste collection bills was used without interference of the food services, since they where kept in a public municipality record. In addition to these data collection methods Cummings (2010) also audited the investigated hotel in order to verify the waste records. Chifaria et al. (2016) uses interviews with a number of stakeholders in the city of Naples in Italy to create a framework of all waste flows in the whole city. However the authors point out, how difficult it is to obtain data of all nodes in the waste management network not just beacuse the experts interviewed for the study were hard to get hold of, but also beacuse different experts provided widely different estimates of the technical coefficients for the same plant/facility. 3.3.7.2 Tourist Indicator Sets To be able to compare the results from different studies, they are normally using a reference base to compare the quantities of food waste. For hotels a reference base used by Ball & Taleb (2010) was quantity of waste per guest nights, but here the food waste was included in the general waste stream. For restaurants the commonly used reference base was quantity of waste per served portion or per served customer (which could be assumed to be synonymously used) (Engström & Carlsson‐Kanyama, 2013). Since the main part of the food waste from hotels can be assumed to be generated in a hotel restaurant the indicator value quantity of waste per served guest was used when only the food waste in a hotel was studied (Papargyropoulou et al., 2016). This indicator is also practical, since the number of 84
customers might vary between breakfast, lunch and dinner, and the quantity could therefore be divided by the number of customers at each meal. For hotels where the guest can be assumed to eat all meals in the hotel restaurant (i.e. all‐inclusive hotels) the indicator quantity of waste per guest night should be a useful indicator, and correspond to the waste per customer for each serving. For studies focusing on an aggregated level of hotels and restaurant food waste uses number of employees as a reference base (Jensen et al., 2010), since this is a useful number to extrapolate the values to a whole nation if there is national statistics of employees in different types of busnesses. Also the quantity of served food (Engström & Carlsson‐
Kanyama, 2013; Hrad & Obersteiner, 2016) or the purchased quantity of food (Beretta et at., 2013) can be used as a reference base to make the results from food waste quantifications comparable. Using the total quantity of food as a reference base also have the flexibility to be used both in case studies of single kitchens as in Engström & Carlsson‐Kanyama (2013) or on a national level as in Beretta et at. (2013). The studies evaluating the environmental impact from different waste management options depict no specific indicators that relate specifically to tourism. However, since a common functional unit is environmental impact per quantity unit of waste treated (food‐, organic‐ or municipality solid waste) (e.g. Eriksson et al., 2015; Vandermeersch et al., 2014; Parkes et al. 2015), the results are independent if they are generated by a tourist hotel/restaurant or by a local school or household. Another way of relating waste to tourism is by assesing the waste management alternatives of a specific event or tourism area like the London Olympic Park that was investigated by Parkes et al. (2015). 3.3.7.3 Critical processes For studies that assess the environmental impact of food waste management options (with the focus on energy recovery and nutrient recycling) there are some areas that are often foreseen and that have the potential to effect the result. According to the review made by Bernstad & la Cour Jansen (2012) examples of these areas are: 
Potential emissions of carbon, nutrients and others in food waste during pre‐
collection and transportation. 
Losses during physical pretreatment of food waste (rejects). 
Potentials for energy recovery through incineration of food waste. 
Ash generation from waste incineration. 
Direct emissions from composting of food waste during different circumstances. 
Emissions from bio‐fertilizers and chemical fertilizers during storage and land application under different circumstances. Additionally, two focus areas have to be mentioned that are crucial for the results of environmental assessment studies based on the life cycle approach. 1. Substituted systems 85
The most critical process of food waste management in LCA studies seems to be the substituted system (or compensatory system) in the system expansion (or the allocation method of the outcome, depending on the methodology). This means that the recovered products (i.e. biogas, district heating, electricity, food, feed, compost) are normally used to replace a similar product or service produced from virgin material. If the waste recovery can be used to replace a product or service with a high environmental burden the savings in terms of avoided environmental impact of the waste management system will be large. The more prioritised levels of the waste hierarchy generally correspond to high environmental impact from the substituted systems that can be replaced by recovering or recycling the waste (Eriksson, 2015). According the Bernstad & la Cour Jansen (2012) the substituted systems could have a high impact on the results of a waste management assessment. However these systems are often not in focus in the studies, and literature values are therefore used. This means that the substituted systems sometimes are assumed to replace old technology with high environmental impact, which can make the waste management system look better than it actually is. 2. Local context The environmental impact from food waste management options is highly dependent on the local context (Laurent et al., 2013a). Since food waste is heavy, bulky and fast degradable it is unpractical to transport it on longer distances, which makes the waste treatment dependent on the available local infrastructure. This means that hotels and restaurants are likely to use the same waste treatment method as the sounding society, and often the waste is simply included in the municipal solid waste for collection and treatment. The environmental impact can therefore differ between different geographical places, not just depending on the waste treatment method but also, as mentioned above, of the substituted products or services in the specific local context. 86
3.3.8 Waste management issues on islands Generally spoken, islands pose geographical regions that are of special interest. Islands are unique in terms of their demographic, economic and physical characteristics such as relatively limited surface areas and natural resource bases (arable land, freshwater, mineral resources, conventional energy sources). Islands are more sensitive to natural disasters (typhoons, hurricanes, cyclones, earthquakes, volcanoes); and their isolation from mainlands contribute to the vulnerability of their water resources. In addition, resources in general can be problematic, especially when a huge share of processed materials have to be imported from the mainland, such as construction materials, products, even food related products etc. This is of paramount importance when tourism comes in, especially when huge seasonal variations in tourism occurs, this may lead to special challenges for infrastructure, water supply, energy supply, waste management, transport, supply with food and beverages and many more. Touristic islands usually tend to have problems with the provision of sufficient freshwater resources, in some cases desalination plants are supporting water provision. This problem tightens, when improper waste management endage the scarcely available groundwater resources. Ezeah et al. (2015) state, that touristic islands exemplify EU‐regions with characteristic limitations which often affect how waste is collected, transported, treated and disposed of. Such locations have common waste management problems which may include: 
Reduced number of facilities for waste treatment or disposal. 
Significant variations in waste generation based on tourism seasons. 
High population density. 
Limited land mass to locate landfills and other waste treatment infrastructure. 
Difficulties in achieving economies of scale. The management of solid waste in tourism dominated island communities is particularly problematic due to climatic conditions, land mass and topography, financial restraints, poor planning, changing consumption patterns, transient population (i.e. tourism flows), and seasonal variations in solid waste quantity and composition. The isolated geographies of most island communities also mean that materials are most times imported with little or no thought as to how to manage waste that arise after those materials might have been used. This situation often exacerbates the pressure on carrying capacity of the islands waste management infrastructure and further challenges the inefficient and unsustainable management practices of waste collection and disposal (Ezeah et al., 2015). The sweeping and cleaning of streets, parks, public areas, and beaches is also especially essential on islands because they are surrounded by marine ecosystems that are extremely sensitive to waste contamination. In contrast to mainland coastal cities, island territories have a 360‐degree coastline. Thus the likelihood of contaminating marine ecosystems is much higher (Castillo and Hardter, 2014). In many small islands developing states (SIDS) the most prevalent method of disposal continues to be open and uncontrolled dumping, which leads to human health problems, as well as risks to the marine ecosystems, especially to mangroves, sea grasses and coral reefs; and other sensitive land areas and water courses (Wilson and Carpintero Rogero, 2015). 87
For example in touristic small islands in Thailand almost all supplies are imported from the mainland and for some recyclables an economic incentive leads to trading with the mainland, but all this is related to a lot of transportation activities. E.g. Castillo and Hardter (2014) report, that even though recycling activities in many island regions may not be directly profitable due to transport logistics and costs, the long‐term benefits of recycling for the local government and population are evident due to the abovementioned reasons and in island regions, it’s desirable to return the highest amount possible of recyclable materials to the mainland for further processing. However, the logistics of sea transportation for recyclable materials pose political and economic challenges in most cases, since boat operators are generally not willing to transport recyclable materials to the mainland without charging for this service. Problems occur also due to other products, e.g. in Kiribati, like in other small Pacific island countries, a significant waste problem occurred with end‐of‐life vehicles, white goods (refrigerators, freezers, and washing machines), and electronic equipment. These materials need to be exported for recycling (ADB, 2014). Wilson and Carpintero Rogero (2015) state, that another barrier, which is characteristic of SIDS in general, is the constraints to greater recycling. Segregation of waste streams in SIDS is still uncommon and recycling is generally not well developed in most of the islands. The constraints are mostly related to the small size and population of SIDS and to their relative geographic isolation: specifically, the resultant low quantities of recyclable waste mean that economies of scale cannot be achieved; their small size restricts local recyclables markets; other recycling markets require expensive transportation. Skordilis (2004) report, that the combination of material recovery at the source with the utilization of the organic fraction is the optimum solution for small local communities (Corfu). Other authors report, that compared with mainland locations, the content of organic waste within the total composition of municipal solid waste in oceanic islands is quite low, since most of the organic products imported from the continent are pre‐
processed and packaged for transport. Therefore, in comparison to the mainland, the relative amount of organic waste within the overall amount of MSW on islands is less and the relative amount of recyclable materials is higher, and is comparable to the composition of MSW in cities (Castillo and Hardter, 2014). Small‐island developing states (SIDS) are experiencing an increase in waste generation due not only to common factors such as increasing population, urbanization, and change of consumption patterns, but most acutely due to the large quantities of imported material and packaging, and the excess amount of waste produced by tourism, including cruise‐ship generated wastes. Additionally the complexity and hazard of particular waste streams such as e‐waste, pesticides, asbestos, used oil, items containing heavy metals and also biomedical wastes is also adding pressure to local waste management systems, since facilities for their treatment and disposal are often not in place (Wilson and Carpintero Rogero, 2015). Another barrier, which is characteristic of SIDS in general, is the constraints to greater recycling. Segregation of waste streams in SIDS is still uncommon and recycling is generally not well developed in most of the islands. The constraints are mostly related to the small size and population of SIDS and to their relative geographic isolation: specifically, the resulting low quantities of recyclables mean that economies of scale cannot be achieved; their small size restricts local recyclables markets; other recycling markets require expensive transportation. Separately collected recyclables may have to be exported for the actual recycling process (e.g. in Kiribati, an island nation in the central Pacific Ocean, cans, brass, and copper is 88
exported to Australia and PET bottles and lead‐acid batteries are exported to Hong Kong, China). The recently published Global Waste Management Outlook (Wilson and Carpintero Rogero, 2015) included a chapter on solid waste management in small islands developing states (SIDS). It is stated, that SIDS, (…), are experiencing an increase in waste generation due not only to common factors such as increasing population, urbanization, and change of consumption patterns, but most acutely due to the large quantities of imported material and packaging, and the excess amount of waste produced by tourism, including cruise‐ship generated wastes.11 Additionally the complexity and hazard of particular waste streams such as e‐waste, pesticides, asbestos, used oil, items containing heavy metals and also biomedical wastes is also adding pressure to local waste management systems, since facilities for their treatment and disposal are often not in place. 3.3.9 Gender aspects Typically, the search terms “gender” and “waste management” are not leading to results in scientific search engines, as gender and behavioural analyses are not often included in the traditionally technology‐based field of research. Gender aspects are more considered in studies and projects related to informal employment in general and in waste management, for example the group WIEGO12. Only a few studies consider gender differences and potential impacts on waste disposal and differences related to waste quantities and composition. Especially related to waste forecasting and prognosis, socio‐economic indicators are used in order to predict future waste generation or to explain time‐series. Usually socio‐economic indicators are related to income and affluence, but also related to demographic data (ace structure, unemployment etc.) or geographical patterns (population density etc.) or the design of the waste collection system itself. Talalaj and Walery (2015) present an analysis, showing that gender and age structure influence the waste quantity. The results showed that the greater the share of women in society this contributes to greater waste production. Among the women, the greatest waste quantity are generated in the group from 14 to 64 years, or so‐called: working age. The more unemployed women in this group, the greater the waste generation rate can be expected. Yet it has to be stated that such results have to be interpreted in interdisciplinary teams, where also social scientists are involved. Results showing for example “women produce more waste” have to be interpreted in the right way, as for example the women´s role as head of the household might be linked to this. Only one (Katajajuuri et al., 2014) of the reviewed studies was found to analyze gender aspects of food waste management or food waste generation. Of the Finnish households analyzed by Katajajuuri et al. (2014) the ones where a woman was mainly responsible for 11
Tourism generates substantial amounts of solid waste in some SIDS with tourists
generating twice as much as solid waste per capita as local residents in the Caribbean.
Cruise ship passengers are estimated to produce as much as four times the amount of
garbage per day compared to local residents.
12
http://wiego.org/
89
grocery shopping had the highest level of food waste (mean 26 kg/capita). This was significantly higher then the avarage waste level of households where the main responsibility of grocery shopping was handled by a man or shared (mean 19 kg/capita for both shared and male responsible). Other demograpic factors such as age, form of recidence, educational level or occupation of the adults in the household where not found to have a clear correlation to food waste according to Katajajuuri et al. (2014). An interesting starting point is also an initiative carried out by the GIZ in Serbia form the period 2009 to 2011, aiming at gender mainstreaming of local waste management plans.13 Lebersorger (1998) describes that waste generation is primarily determined by the circumstances and habits of and in private households. The author defines life cycle stage of inhabitants and divides into certain groups like “older residents”, “families with small kids”, “families with pupils”, “elderly couples” etc. and describes waste disposal behavior depending on certain life cycle stages of the residents. Beside the traditional methods in order to assess waste generation, that are mainly based on economic indicators, this approach focusses more on social realities in the life of people. When it comes down to tourism and waste, things get even more complicated, because waste disposal behavior is taking place at a different place (compared to home) in a different setting and at a special time (holidays). Del Mar Alonso‐Almeida (2013) state that “the tourist industry can only operate with adequate energy, water and waste management facilities. This work analyzes the perceptions among university students attending tourism degree courses of the most important responsibilities in this respect for companies operating in the tourist sector, and examines the adoption of environmental practices by companies from a gender perspective.” One additional starting point to tackle gender aspects related to tourism, is to first assess the general differences between men and women related to environmental aspects. A limited gender analysis is presented in the Special Eurobarometer (2005) on “The Attitudes of European Citizens towards environment”14. Lee et al. (2013) state that “in previous research, stronger pro‐environmental attitudes and behaviors have been identified more often in white, younger, more educated and female individuals.” The authors also include a chapter on “Gender Differences in Environmental Attitudes and Behaviors”, stating in general that several studies show that women are more concerned related to environmental issues compared to men. In addition, Hanne Marit Dalen and Bente Halvorsen assess “Gender differences in environmental related behavior”15 From a gender perspective, this deliverable shall serve as starting point for further researching gender, urban metabolism, waste management and disposal behavior, and tourism. In‐depth research on the aforementioned issues is carried out within workpackage 3 of this project. Formatiert: Abstand Nach: 6 Pt.
13
http://www.gender-in-german-development.net/serbia.html (Last access: 31.08.2016)
http://ec.europa.eu/public_opinion/archives/ebs/ebs_217_en.pdf (Last access: 31.08.2016)
15
https://www.ssb.no/a/english/publikasjoner/pdf/rapp_201138_en/rapp_201138_en.pdf
(Last access: 31.08.2016)
14
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4 Lessons learned from case studies from partner cities Beside the review of scientific literature to find out which methodologies would be appropriate for urban metabolism studies focusing on waste generated by tourists as well as appropriate indicators for the assessment and data needed a review of already existing studies in the partner cities of the UrBan Waste project was conducted to find out which data are already available or could be in principle provided. Seven out of eleven case study cities or regions responded to the request to send specific information from their municipality. The studies provided ranged from scientific publication to project summaries. In some cases English summaries from longer localized studies were provided. In the following sector the focus was laid on the data collected and the indicators used within the studies. 4.1
Florence/Italy 4.1.1 Waste‐Less in Chinati The project waste‐less in Chinati (LIFE09 ENV/IT/000068 (2013)) dealt with the implementation and monitoring of an integrated programme for waste reduction in the municipalities of Florentine Chianti. It provides a demonstrative example for the effective implementation of the priorities of the European Union in the field of sustainable management. Within the project preliminary analysis of the Chianti territory, including a detailed description of the waste management services already in place in the pilot area, with reference to collection, reuse, recycling and final disposal systems was performed. This analysis was seen as fundamental basis for designing waste prevention actions and for monitoring and evaluating the achievement of the targets set. The following data were collected  Inhabitant population at municipal level  Inhabitant population at neighbourhood level  Tourist arrivals and nights  Waste production  Companies and employees  Value added  Administrative structure  Waste assimilation management policies  Waste fee plan The territorial and socio economic analysis was done using data from the National Institute of Statistics (ISTAT). Specifically, 2009 demographic data coming from the census of municipal civil registry were used. For all the elaborations at sub municipal level it was possible to use the data from Population Census of 2001. For the analysis of tourist arrivals and nights spent, data were collected from the Agency for Tourism in Florence – Office of accommodation statistic, in relation to the period between 2004 and 2010. 91
The economic data came from the Chamber of commerce of Florence, regarding the number of companies and employees, while the analysis on the added value used data from Regional Institute Economic Program of Tuscany (IRPET) 1995‐2009. The data about waste production were collected from the Regional Agency of resources recovery (ARRR) from 1999 to 2009. The analysis of the operational set up of waste management services and the application of the waste fee was made using municipal documents that regulate the subject matter, and also acquiring further detailed information from the local utility “Quadrifoglio”. 92
4.1.2 RES MAR – Marine environmental defence Within the “RES MAR – Marine environmental defence” project (AmbienteItalia, 2010) guidelines for the application of a model for the integrated waste management in touristic areas have been developed. In particular, the guidelines focus on methodology and models enhancing waste management optimization in touristic areas. Within the project, pilot actions have been implemented in some municipalities in the province of Livorno (Elba Island) and in the Liguria region. As regards the waste reduction strategies, the guidelines have been defined taking into account the results coming from a context analysis, a preliminary analysis based on the touristic flows data (touristic visits and accommodation offer) and the related waste production and recycling actions developed in the project. The analysis takes into account the following indicators:  Demographic evolution  Tourist arrivals and night stays  Occupied and unoccupied residential buildings  Average length of stay of tourists  Tourist supply: number of accommodations and number of beds per accommodation’s typology  Tourist occupation: ratio of annual nights and available beds  Tourist pressure: density of tourist nights (daily average) compared to inhabitants  Tourist pressure: density of tourist nights (daily average) compared to surface land  Total production of waste  Per capita production of waste  Selective collection/recycling rate  Waste flows, per waste fraction 4.1.2.1 Typologies of tourist municipalities Thanks to detailed analysis of tourist population it was possible within RES‐MAR to find different typologies of municipalities characterized by different kind of tourisms.  municipalities characterized by second home tourists 
municipalities characterized by mixed tourists in accommodations and second homes 
municipalities characterized by tourists mainly in camping and tourist resort 
municipalities characterized by tourists staying in hotels This analysis was fundamental to plan and carry out waste management actions, suitable and effective on different territories, according to the specific kind of tourist population. 93
4.2
Kvala/Greece 4.2.1 WASTE‐C‐CONTROL By relating the life cycle of materials to the waste hierarchy, an assessment of how each stage impacts on climate change can be made. The treatment and disposal of slowly biodegradable organic wastes (e.g. kitchen and garden waste) has a direct influence on GHG emissions. Solid waste management in Europe mainly produces GHG emissions through the decaying of biodegradable wastes under anaerobic conditions in landfills. This process emits about a third of anthropogenic emissions of CH4 in the EU. Currently, over 80% of waste in Greece is landfilled, presenting a significant problem with regards to the management and control of methane emissions. The WASTE‐C‐CONTROL project (http://www.epem.gr/waste‐c‐control/index.html) aimed to reduce GHG emissions by developing a software tool to assess, monitor, control and report on the emissions resulting from the entire life cycle of solid waste management activities. Using a systematic approach, different waste management options were assessed with regards to their GHG emissions, with the goal of enabling the project to identify procedures and practical tools within Local Action Plans (LAPs). The project aimed to reduce GHG emissions in pilot studies in three regions in Greece: Eastern Macedonia and Thrace, Western Macedonia, and Chania (Crete). The knowledge of the whole framework of a solid waste management system is crucial for the appropriate assessment of the available options to process and handle the waste. Consequently in the Midterm Report (LIFE09 ENV/GR/000294) on the “Reference Case for the Region of Eastern Macedonia & Thracein” a brief background regarding the Municipal Solid Waste (MSW) management system in the Region of Eastern Macedonia and Thrace (REMTH) is given. The Region of EMTH has an official Regional Waste Management Plan (RWMP 2009) that was approved by the General Secretary of REMTH on 03/09/2009. The RWMP provides strategic goals, as well objectives, regarding the solid waste management in the Region of Eastern Macedonia and Thrace. Data used:  Waste generation per inhabitant and year It has to be taken into account that according to LIFE09 ENV/GR/000294 in REMTH the existing data based on weighbridge data logger are very scarce, not accurate and unreliable. For this reason, the waste quantities are estimated according to the Regional Waste Management Plan of the Region of Eastern Macedonia – Thrace (RWMP, 2009). The estimation is based on the daily production rate of Municipal Solid Waste (MSW) per inhabitant. This rate is estimated as 1,40 kg per inhabitant per day (365 days/year) for the main municipalities of REMTH (e.g. Drama, Kavala, Xanthi, Komotini, Alexandroupoli) and as 1,14 kg per inhabitant per day (365 days/year) for the rest municipalities of REMTH. The estimation is a fair enough approximation of the real waste quantities produced. This is verified by sample weighing of the MSW collection vehicles. 94
4.2.2 Evaluation and Optimisation of the ISWM system of Kavala The study (Promis, 2015) concerns the evaluation and optimization of the existing system of municipal waste collection of Municipality of Drama in order to complete drafting of an Environmental Planning for solid waste in the municipality area. The following design parameters were identified for waste management in the Municipality of Kavala:  Sources of origin and categories of solid waste  Planning population of the Municipality  Qualitative composition of municipal solid waste in the study area  Waste quantity per district  Number of bins Also success factors of recycling systems were defined:  Recycling services must serve all households.  Collection of wide range of materials  Proper education and care for the user  Frequency of collection of the recycling program  Collection of sorting at source materials,  Provide an easily used storage bin  Incentives for participation in recycling 4.2.2.1 Assessment indicators According to Promis (2015) an important chapter in the organization of municipal solid waste management systems is the possibility of systems for monitoring and evaluation, to be able to judge the efficiency and productivity of these systems. This monitoring and evaluation can be performed with the use of monitoring and evaluation indexes, which describe specific areas of the overall system of administrative to operational level. The following tables show the monitoring and evaluation indexes, which can be used by area of interest of municipal waste management systems. For each monitoring & evaluation index or certain preferred indicators can arise a value (number) which should be recorded and periodically monitored by the relevant departments of the Municipality. This value of any index or the preferred index can be compared with a base price with previous periods prices and thus is logged the evolution of the index which may be either upward (growth index) or downward (index fall). 95
Table 6: Indexes and Indicators used for the evaluation of municipal waste management systems Index Economical indexes Indexes at the administrative level Indicator Expenditures/Revenues/costs per month/residents/year/collected ton Informing of affected people Number of participants in seminars, conferences, congresses, Actions/year Indexes of source separation programs Landfilling rate Quantity led to landfills, WTS (tn) / total collected quantity of MSW (tn) Diversion rate (covers all quantities Total amount diverted from landfill / total collected quantity of MSW not driven to WTS, landfills) (tn) Efficiency of routes Number of routes were not done / Total scheduled routes / month or year Management of vehicles Newly vehicles or vehicles withdrawn / Total vehicles Collection efficiency Collected tons/ vehicle / month Workload Tons of collected waste (tn) / Total Employees of collection service Repair of bins Number of repaired bins / Year Disposal of bulky and heavy objects Total weight of bulky collected (tn) / Month Performance of staff Tons of waste collected / Total employees in the Percentage of Recycled waste Annual amount collected recycled waste (tn) / Generated Annual amount of MSW (tn) Recovery Percentage of materials Quantities of target‐materials recovered from serviced households (tn) / Total quantities of target‐ materials present in waste generated by households serviced (tn) Diversion Percentage of materials Quantities of target‐materials diverted from landfills (tn) / Total amount of MSW (tn) 96
4.3
Lisbon/Portugal 4.3.1 MFA Case Study of the Lisbon Metropolitan Area using the Urban Metabolism Analyst Model Rosado et al (2014) describe a new methodological framework to account for urban material flows and stocks, using material flow accounting (MFA) as the underlying method. The proposed model, urban metabolism analyst (UMAn), bridges seven major gaps in previous urban metabolism studies: lack of a unified methodology; lack of material flows data at the urban level; limited categorizations of material types; limited results about material flows as they are related to economic activities; limited understanding of the origin and destination of flows; lack of understanding about the dynamics of added stock; and lack of knowledge about the magnitude of the flow of materials that are imported and then, to a great extent, exported. To explore and validate the UMAn model, a case study of the Lisbon Metropolitan Area was used. An annual time series of material flows from 2003 to 2009 is disaggregated by the model into 28 material types, 55 economic activity categories, and 18 municipalities. Additionally, an annual projection of the obsolescence of materials for 2010–2050 was performed. The results of the case study validate the proposed methodology, which broadens the contribution of existing urban MFA studies and presents pioneering information in the field of urban metabolism. In particular, the model associates material flows with economic activities and their spatial location within the urban area. Data and Data sources used for the MFA: Rosado et al. (2014) identified as one of the major difficulties in quantifying material flows at regional or urban scales the availability of data at the established boundaries. Although some material flow data for regions or metropolitan areas are available, some of the needed information has to be assembled using data from a combination of sources. Data sources used by the Eurostat and national statistical offices to compile economywide MFAs can be applied to the specificities of metropolitan areas, but an additional major data source must also be used: the Standard Goods Classification for Transport Statistics.16 The Standard Goods Classification for Transport Statistics is useful for studies of urban metabolism because it is available at the Eurostat’s Nomenclature of Territorial Units for Statistics (NUTS) 2 level. This nomenclature has five levels of hierarchical classification. In the case of Portugal, the NUTS 3 level corresponds to municipalities. 16
The Standard goods classification for transport statistics abbreviated as NST (2007), is a statistical nomenclature for the
goods transported by four modes of transport: road, rail, inland waterways and sea (maritime). As NST 2007 considers the
economic activity from which the goods originate, each of its items is strongly connected to an item of the European Union
product and activity classifications Classification of products by activity (CPA) and Statistical classification of economic activities
(NACE), which themselves are consistent with their counterparts at UN level, CPC and ISIC.
97
4.4
Nicosia Cyprus 4.4.1 Guidelines for meeting the Cyprus Tourism Organisation minimum standards for sustainability in hotel establishments In their guidelines for minimum standards in hotel establishments the Travel Foundation (n.y.) include as evealuation criteria concerning waste generation the amount of waste produced in kg per guest and night. At the beginning of their sustainability initiative, they propose to identify the different waste streams each hotel produces. These are likely to include glass, paper and card, cans, food waste and other general waste. Over a period of seven days, all waste generated (and if possible, each waste stream separately) shall be weighed in kilograms (kg). To identify the volumes of waste of each type the hotel is producing – and where waste should be colleced in different coloured bags according to the different hotel operations such as the kitchens, the gardens, rooms etc, or by type of waste (plastics, card and paper, glass, cans, food, general waste and so on). This differentiation shall help to find out which to focus on first. 4.4.2 Waste Mapping Guidance for Hotels in Cyprus Owen et al. (2013) tailored their guidance document principally to meet the needs of hotel operators and other organisations working in the Cypriot tourism industry to highlight the financial and environmental benefits of undertaking waste mapping as part of their on‐going business operations . According to Owen et al. (2013) waste mapping enables hotel managers to identify the sources, types and quantities of waste produced. The mapping approach allows to investigate where and how waste arises, and present this visually in a way that can help to identify hidden costs of waste (purchasing costs, staff time etc). The process will help to prioritise areas where simple actions can be taken to minimise waste, save money and achieve lasting sustainable waste management. Data to be collected In their mapping approach Owen et al. (2013) propose a simplified approach for data collection based on the number, volume and degree of filling of bins and therefore avoid the often complicated survey on the amount of waste generated per weight. According to their methodology the following data have to be collected at the hotel level. 




Waste Type (landfilled/recycled) Number of bins Bin volume (litres) % volume of each bin filled with waste Frequency of bin emptying/No. times bins emptied each week Based on this data the Weekly waste volume (WWV) (litres) is calculated and with conversion factor (depending on the type of waste) the weight per week in kg is estimated. 98
4.5
Ponta Delgada / Azores 4.5.1 SIET‐MAC project System of Sustainable Tourism Indicators in Macaronesia SIET‐MAC was a joint project between the Statistical Institutes of the Azores, Madeira and the Canary Islands, approved under the Community Initiative INTERREG IIIB. The aim of this project was to develop and maintain a system of statistical indicators of Tourism, through which one can measure and monitor the sustainability of tourism in each of the three regions involved in the project. It was a complex project that required a close work between official statistical bodies of the Azores, Madeira and the Canary Islands, particularly in comparing underlying concepts and methodologies to variables that comprised the indicators. The development of this joint project provided added benefits to statistical agencies participating, including training of technicians, the creation of joint work teams and increasing the institutional relationship between them. The System of Sustainable Tourism Indicators in Macaronesia allowed the studies under that economic activity for the three regions, following a common methodology, thus facilitating a comparative view of their situation. 99
4.6
Tenerife / Spain 4.6.1 Environmental performance in the hotel sector: the case of the Western Canary Islands. The fundamental objective of the study of Oreja‐Rodríguez & Armas‐Cruz (2012) is to develop and validate a measurement instrument to evaluate environmental performance in the hotel sector. This sector has productive processes which generate an evident environmental impact. On the basis of an extended literature review, the authors developed a measurement instrument capable of confirming the validity of that construct. The so called Rasch model is applied in the empirical analysis, to a sample of 187 hotel establishments in one of the most internationally important tourist destinations, the Western Canary Islands (Spain). The results confirm the content validity of the environmental performance construct. Other important results identify the frequency of achievement of excellence in the distinct aspects of environmental performance for hotel firms and suggest the need to expand the delimitation of the construct. Data collected Based on questionaires, information on exisiting activities in each hotel on the following issues was collected :  Personnel qualified in environmental aspects  Valuing environmental efforts  Improvement in environmental behavior  Adoption of ecological attitudes  Promotion of environmental education  Environmentally responsible purchases  Resolving environmental problems  Conservation of culture  Adequate waste management  Reduction of health risks  Reduction of waste  Reduction of visual impact and noise  Saving natural resource 100
5 Compilation of existing indicators and necessary background data from previous studies In addition to the literature review results presented in the previous Chapters, a list of indicators and corresponding background data requirements was compiled and, in a second step, assessed by the project partners to assemble a catalogue of indicators and background data requirements that are suitable and practicable to connect waste generation with tourism. This is of specific importance as the results of the literature review on the indicators are subsequently leading to a database template that is developed within WP 2 (Task 2.4) and filled in by the eleven partner municipalities. The following Tables show draft versions of this template. The waste‐related data requirements presented in Table 7 as well as the data requirements focussing on economic and social influencing factors (Table 8) are commonly used and already proved useful in several EU waste management projects17. The tourism‐ related data requirements listed in Table 9 are mainly derived from European tourism statistics provided by Eurostat and reflect key indicators commonly used to characterize the tourism industry. The definitions corresponding to the presented indicators and background data sets are provided in the Appendix, Table 13. Experience from past projects show, that data should be collected, at best, on a monthly time scale (if available) in order to be able to find seasonal variations in e.g. waste generation due to tourist arrivals etc., as well as for several years and at the smallest geographical scale available (i.e. in best at city level if the the study area is a city). If possible, it might be even useful to distinct between different districts at city level, as it might be true, that there are different tourist hot‐spots in cities that might be different compared to other city areas. 17
E.g.Project “LCA-IWM”: http://cordis.europa.eu/result/rcn/39023_en.html
101
Table 7: Waste related data requirements ID Indicator / Data set Waste Quantities [1]=[2]+[4] Municipal solid waste (MSW) [2] • Household waste (including hazardous hh waste) [3] ○ Hazardous household waste (including WEEE and ba eries) [4] • Non‐household waste collected by or on behalf of the municipalities (including hazardous hh waste)
[5] ○ Non‐household hazardous waste (including WEEE and batteries) collected by accredited bodies
[6]=[6a]+[6b]+ Separately collected recyclables (as part of MSW) [6c]+[6d]+[6e] Unit [6a] • Paper and cardboard [6b] • Glass [6c] • Metals [6d] • Plastics and compounds (e.g. multilayer packaging) [6e] • Other recyclables [7]= [7a]+[7b] Organic waste (as part of MSW) [7a] • Separately collected organic waste (bio‐bin) [7b] • Yard waste [8] WEEE (as part of MSW) [9] Residual waste (as part of MSW)
[10] Bulky waste (as part of MSW) [11] Waste oils (e.g. used cooking oils) (as part of MSW) [12] Hazardous waste (as part of MSW)
[12a] • Batteries (as part of hazardous waste) [12b] • Medicines (as part of hazardous waste) Waste Composition (Residual Waste) [13]= Sum of Composition of residual waste (total=100%) [13a] to [13j] [13a] • Paper and cardboard [13b] • Glass [13c] • Metals [13d] • Plastics and compounds (e.g. multilayer packaging) [13e] • Organic waste [13f] • Textiles [13g] • Batteries [13h] • Medicines [13i] • Other hazardous waste [13j] • Others Waste management Number of provided bags or bins per separately collected fraction (e.g. paper & cardboard, …) for [14] households • e.g. split into bags, bins smaller 300 ltr, bins from 300 to 1.100 ltr, bins or containers larger 1.100 ltr
[15] Number of bins / containers for separately collected recyclables in public areas • split into number of bins / containers per separately collected waste fraction
• Average size of bins / containers per separately collected waste fraction
[16] Collection (service) coverage rate [16a] • e.g. split into households and commercial waste [16b] • e.g. split into type of waste [17]=[ 17a]+ [17b]+[ 17c]+ Treatment rate (total amount of MSW treated) [17d] [17a] • Incineration [17b] • Mechanical‐biological treatment (MBT) [17c] • Composting [17d] • Export for treatment abroad [18] Recycling rate (total amount of MSW recycled) [18a] • Export for recycling abroad [19] Total amount of MSW landfilled [19a] • Export for landfilling abroad [20] Capacity of waste treatments plants [20a] • Recycling plant [20b] • Mechanical‐biological treatment [20c] • Composting plant [20d] • Incineration plant with energy recovery [20e] • Incineration plant without energy recovery [21] Capacity of landfills [21a] • split into types of landfills available in the city/region [t]
[t] [t]
[t]
[t] [t] [t]
[t]
[t]
[t]
[t] [t]
[t]
[t] [t]
102
[t] [t]
[t] [t]
[t]
[t] [%]
[%]
[%] [%]
[%] [%]
[%]
[%] [%]
[%]
[Number] [Number]
[Number] [Number]
[m³]
[%] [%] of [1] [%] of [1]
[%] of [1] [%] of [1]
[%] of [1] [%] of [1]
[%] of [1]
[%] of [1] [%] of [1]
[t/a]
[t/a] [t/a]
[t/a]
[t/a] [t/a]
[t/a]
[t/a] ID [22] [22a] [22b] [23] [23a] [24] [25] [25a] [25b] [26] [26a] [26b] [27] [27a] [27b] [27c] [27d] [27e] [27f] [27g] [27h] [28] Indicator / Data set Waste management fee for private individuals / private households per assessment basis • potential assessment basis = e.g. person, household, type of waste bag / bin / container, frequency of collection, … Number of private individuals that are charged a waste fee Number of private households that are charged a waste fee Waste management fee for commercial clients per assessment basis • potential assessment basis = e.g. number of employees, commercial space, turnover, …
Number of enterprises in the tourism industry that are charged a waste fee • e.g. split into hotels and similar accommodation establishments, bars, cafes, restaurants, …
Number of employees in waste management • e.g. split into administrative personnel (municipal and waste industry respectively), garbage collectors and staff at local recycling stations, treatment sites etc., employees in re‐/up‐cycling industry Municipal expenditures for the removal of litter from public spaces (total) • Municipal expenditures on street cleaning • Municipal expenditures on beach cleaning Municipal expenditures for the removal of litter from public spaces (total) • Municipal expenditures on street cleaning • Municipal expenditures on beach cleaning Survey of existing separate collection • Paper and cardboard • Glass • Plastics • Metals • Food and garden waste (bio‐bin) • Yard waste • Clothing • Hazardous waste Survey of existing treatment of waste fractions • split into separate collected recyclables as well as residual waste
• possible types of treatment: Recycling, mechanical‐biological treatment, composting, incineration with or without energy recovery, landfilling without prior treatment, export for treatment abroad, export for landfilling abroad Unit [€]
[Number]
[Number] [€]
[Number] [Number]
[€]
[€]
[€]
[Working time equivalents] [Working time equivalents] [Working time equivalents] yes/no
yes/no
yes/no
yes/no yes/no yes/no
yes/no
yes/no [Type of treatment]
[Type of treatment]
Table 8: Data on factors of influence ID Indicator / Data set Description of the city / region [29] Total population [29a] • Number of commuters (if included in "total population") [29b] • Number of tourists (if included in "total population") [30] Total Area [31] Total number of households [31a] • Private households [31b] • Other types of households such as nursing homes, … [32] Distribution of household sizes (total=100%) [32a] • Number of households with 1 person [32b] • Number of households with 2 persons [32c] • Number of households with 3 persons [32d] • Number of households with 4 persons [32e] • Number of households with more than 4 persons [33] Number of occupied and unoccupied residential buildings (second homes) Economy [34] Number of jobs in the tourism industry (full time equivalents) • split into hotels, restaurants, …
• e.g. split into different categories of tourist attractions such as cultural/natural heritage, entertainment, sports, events etc. [35] Number of commuters working in the tourism industry [36] Number of seasonal workers in the tourism industry [37] GDP per capita (at special scale of study area i.e. city or region) [38] GNI per capita (at special scale of study area i.e. city or region)
[39] Economically active persons by sectors [39a] • Sector Agriculture (NACE Rev. 1 A, B) 103
Unit [Number] [Number]
[Number]
[km²] [Number]
[Number]
[Number] [%] [%]
[%]
[%]
[%] [Number]
[Number] [Number]
[Number]
[€] [€]
[%] ID Indicator / Data set [39b] • Sector Industry (NACE Rev. 1 C‐F) [39c] • Sector Services (NACE Rev. 1 G‐P) [40] Employment rate [41] Unemployment rate Society [42] Population by broad age groups (total=100%) [42a] • Age 0‐14 [42b] • Age 15‐59 [42c] • Age 60 and more Building statistics [43] Type of building [%] [%]
[%]
• e.g. split into: Residential buildings (dwellings) with 1 or 2 flats, 3 to 10 flats, 11 or more flats; Residential buildings belonging to communities; Non‐residential buildings [44] [45] [46] [Number per type of building] or [% of total] Ownership of buildings • e.g. split into: Private individual(s), regional authorities (e.g. municipalities), non‐profit building associations, other legal entities Unit [%]
[%] [%]
[%] [Number per type of ownership] or [% of total] Predominant utilisation of buildings • e.g. split into: Residential buildings with 1 or 2 flats; residential buildings with 3 or more flats; residential buildings of communities; hotels or similar buildings; office buildings; wholesale and retail trade services buildings; buildings of the transportation and communication sector/industry; workshops, industrial warehouses, storage facilities; buildings for culture and leisure; buildings of the education and healthcare sector; other buildings Predominant heating type of buildings [Number per type of utilisation] or [% of total] • e.g. split into: District heating / Block heating; central heating (whole building); gas heating system; electric heating system; central heating (apartment level); single stove heating; no heating [Number per heating type] or [% of total] Table 9: Tourism related data requirements (Eurostat tourism statistics)18 ID Indicator / Data set Key economic indicators for the tourism industry [47]= Sum of Number of enterprises in the tourism industry (total) [47a] to [47i] [47a] • Total non‐financial business economy [47b] • Tourism industries (total) [47c] • Tourism industries (mainly tourism) [47d] •Tourism industries (partially tourism) [47e] • Transport (total) [47f] • Accommodation [47g] • Food and beverage (total) [47h] • Car and other rental (total) [47i] • Travel agency, tour operators and other reservation services
[48]= Sum of Number of persons employed (total) [48a] to [48i] [48a] • Total non‐financial business economy [48b] • Tourism industries (total) [48c] • Tourism industries (mainly tourism) [48d] • Tourism industries (partially tourism) [48e] • Transport (total) [48f] • Accommodation [48g] • Food and beverage (total) [48h] • Car and other rental (total) [48i] • Travel agency, tour operators and other reservation services [49] Number of persons employed in different categories of tourist attractions • e.g. split into: cultural/natural heritage, entertainment, sports, events etc.
[50] Turnover of the tourism industry [51] Added value of the tourism industry [52] Tourism receipts [52a] • Total Receipts (million EUR) 18
http://ec.europa.eu/eurostat/statistics-explained/index.php/Tourism_statistics
104
Unit [Number] [Number]
[Number]
[Number] [Number]
[Number] [Number]
[Number]
[Number] [Number]
[Number] [Number] [Number]
[Number]
[Number] [Number]
[Number]
[Number] [Number]
[Number] [Number]
[Number]
[million EUR] [million EUR] [million EUR]
ID Indicator / Data set [52b] • Receipts relative to GDP (%) [53] Tourism expenditure [53a] • Total expenditure (millions EUR) [53b] • Expenditure relative to GDP (%) Variables for (accommodation) capacity [54] Number of tourist accommodation establishments by accommodation type • split into different types of tourist accommodation such as: hotels and similar accommodation; holiday and other short‐stay accommodation; camping grounds, recreational vehicle parks and trailer parks • e.g. split of accommodation types according to “star‐rating”
[55] Number of bedrooms by accommodation type • split into different types of tourist accommodation such as: hotels and similar accommodation; holiday and other short‐stay accommodation; camping grounds, recreational vehicle parks and trailer parks • e.g. split of accommodation types according to “star‐rating” [56] Number of bed places by accommodation type • split into different types of tourist accommodation such as: hotels and similar accommodation; holiday and other short‐stay accommodation; camping grounds, recreational vehicle parks and trailer parks • e.g. split of accommodation types according to “star‐rating”
[57] Average number of bedrooms per establishment type [58] Average number of bed places per establishment type Variables for occupancy [59] Total number of tourist arrivals • split into residents and non‐residents • split into types of tourist accommodation [60] Number of nights spent (overnight stays) in total [60a] • Nights spent by residents [60b] • Nights spent by non‐residents
[61] Number of nights spent in different types of accommodation • split into different types of tourist accommodation such as: hotels and similar accommodation; holiday and other short‐stay accommodation; camping grounds, recreational vehicle parks and trailer parks [62] Average length of stay [63] Country of origin of tourists Unit [%]
[million EUR]
[%] [Number]
[Number] [Number]
[Number]
[Number] [Number]
[Number] [Number] [Number]
[Number]
[Days] [Number per country] Past experience also shows, that some further information is needed to facilitate the understanding of waste generation processes in a study area (city, municipality, region, nation etc.) such as a (qualitative) description of the waste management system, a basic description of geography and demography of the target region or a description of the municipal (waste management) fee structure. 105
Table 10 presents an indicative list assembled by the Task 2.1 partners of aspects relevant to understand waste generation in connection with tourism that should be covered by such a qualitative description. 106
Table 10: List of aspects relevant to understand waste generation in connection with tourism that should be covered by a qualitative description 1)
DESCRIPTION OF THE WASTE MANAGEMENT SYSTEM OF THE TARGET REGION General aspects 
Who is responsible for …? o
… the organization of the local waste management system o
… the implementation of municipal waste collection o
… charging waste fees o
… 
User instructions: How are the users guided to the waste system? Which media (brochures, signposting, pictograms, videos, education, games, direct guidance of businesses in connection to periodic environmental supervision etc.)? 
User involvement: Does the responsible entity apply user involvement in the waste management planning, and if so how? (Focus groups, interviews, surveys etc.)? 
Incentives: Does the sale of recyclable fractions benefit the waste producers, and if so how (directly or indirectly)? Do certain fractions have return deposits (e.g. packages and beverage cans/bottles)? 
Producer responsibility: For which waste streams? How is quality control carried out (by random check, compulsory check or other)? Is this producer responsibility actually executed, and how, or does is only exist on paper? 
Littering: Is littering a problem? Is there a municipal road / beach cleaning? How much € or working time equivalents does the municipality spend on the removal of litter from public spaces? 
… Waste disposal of households 
Separate collection of recyclables o
What waste fractions are separately collected? (e.g. paper and cardboard, glass, plastics, …) o
What happens with these separately collected fractions? E.g. treatment method (MBT19, incineration with or without energy recovery) or direct landfilling without treatment? Recycling? o
How is the separate collection of different recyclables organized? Which recyclables are collected by kerbside collection? For which recyclables there is a bring‐it‐yourself system20? o
Kerbside collection of recyclables: What types of bags / bins / containers are used? What is the average size of these bins / containers used for households and for housing complexes respectively? Collection frequency? o
Bring‐it‐yourself system: Are there collection points for separately collected waste fractions in the public area? Which waste fractions are collected there? Who is in charge of maintaining these collection points (e.g. the municipality, private waste disposal companies)? What is the average size of containers for different recyclables at public collection points? Collection frequency? o
Are the containers tagged e.g. with chip or optical code and linked to a specific location/customer? Is the waste weighed on site when collected? o
Who performs the collection of separately collected waste fractions? E.g. municipal or private waste disposal companies? o
… 
Collection of residual waste o
What kind of collection systems are used for residual waste? E.g. kerbside collection? Others? o
What happens with residual waste? E.g. treatment method (MBT, incineration with or without energy recovery) or direct landfilling without treatment? o
What types of bags / bins / containers are used for residual waste? What is the average size of bags / bins / containers used for households and for housing complexes respectively? Collection frequency? o
Are the containers tagged e.g. with chip or optical code and linked to a specific location/customer? Is the waste weighed on site when collected? o
Who performs the collection of residual waste? E.g. municipal or private waste disposal companies? o
… 
Waste treatment o
What types of waste treatment technologies are available in this city/region? E.g. incineration with or without energy recovery, mechanical‐biological treatment, composting etc. What capacities do these treatments plants have? o
Which waste fractions are exported for treatment outside the region or abroad? Why? (e.g. more profitable business models, lack of local treatment capacity, better treatment quality elsewhere, …) o
Where do treatment residues go? (e.g. to which type of landfill in the target region? export for further treatment / landfilling outside the region or abroad, …) o
What types of landfills do exist in this city/region? Capacities of these landfills? o
… 19
MBT = mechanical biological treatment
Bring-it-yourself system = a system where you have to bring it to collection points for
separately collected waste fractions in the public area or to a recycling centre
20
107
Waste disposal in the commercial sector 
Organisation of waste disposal in the commercial sector: Do businesses have the freedom to choose between municipal and private waste disposal companies? Is there a threshold quantity? (meaning: If the amount of a waste type is below this threshold, the waste is collected by the municipality, if it exceeds the threshold, the business enterprise has to hire a private waste disposal company.) o
… Description of waste fee structure 
Waste fee for individuals / households: What is the assessment basis for waste fees charged from individuals / households: Per person, household, waste bag, type of waste container, frequency of emptying…? Amount of fee? 
Waste fee for commercial clients: What is the assessment basis for waste fees charged from commercial clients: Number of employees, operating area/factory space, turnover, …? Amount of fee? 
How are waste collection fees charged (via taxes, differentiated user fees or other)? 
Description of other taxes and fees in the commercial sector: What type of taxes is a hotel / restaurant /etc. charged? (e.g. tourism levy, tax on sold beverages, …) How many establishments (hotels, restaurants …) have to pay these taxes/fees? 
… 2)
DESCRIPTION OF GEOGRAPHY AND DEMOGRAPHY OF THE STUDY AREA: Geography 
Description of topography, land use (i.e. area dedicated as residential area, industrial area, area for recreation/leisure/sport, area for commerce/finance/ business), settlement structures (dense high‐rise, dense low‐rise, scattered setlements), etc. 
If available: GIS map with settlement structures and construction /building type 
If available: GIS map with land use (residential, commercial, industrial, recreational area …) 
… Demography 
Do the numbers for "total population" include commuters and / or tourists as well? 
Information on seasonal / daily variations regarding population: e.g. tourists, commuters, … 
… 108
6 Conclusions for UrBAN‐Waste assessment criteria 6.1
Literature review From our comprehensive review we conclude in line with Qian and Schneider (2016) that state that “to date, research on waste minimization practices within the tourism industry focuses primarily on the hospitality sector, is geographically limited, and addresses practices cross‐sectionally”. The same applies for studies about environmental management systems (EMSs). There is hardly any attention to other subsectors of the tourism industry such as for instance campsites or conference venues. Most studies are also case studies, mainly about a city, a region and even a hotel. There seem to be relative much attention for tourist islands because there the problems with waste generation by tourists is particularly serious (Ezeah et al., 2015). The problematic with island destinations is specifically covered in Chapter 3.3.7. Based on the literature review it is possible to derive different approaches, methodologies and the necessary (background) data that have to be collected in order to assess waste management related to tourism. The following chapter compiles this and discusses potential benefits and drawbacks. The literature review about waste management and waste behaviour did not show many indicators about waste generation and waste management. Most studies reviewed are case studies in a particular area, town or (group of) hotel(s). In the case studies about a particular area or town the total amount of (solid) solid waste generated is often used (monthly per capita generation of solid waste), sometimes in combination with the recovery rate of recyclable waste. In some cases the amount of generated waste was related to the ratio between the number of inhabitants and the number of tourist in the area. In general the indicators are not very detailed and broadly defined. The waste generated by hotels (but also for campsites) is measured by the total amount of waste (in kilograms) per guest‐night. This amount can be subdivided by sorted and unsorted waste, but also by type of waste (food, paper, etc.). The studies which focus on waste management (or environmental management systems) hardly use quantitative indicators about the amount of waste. In some cases the frequency of collection of municipal solid waste is used as an indicator. Many studies about waste management are based on highly aggregated data or data collected on basis of interviews and surveys. The former type of data are usually used in model simulation studies, while the latter type of data are used to gather information about the implementation of waste management in the hospitality industry. These interviews and surveys do not deal with the amount of recycled or saved waste, but only give insight in the implementation processes of waste reduction systems. Studies that give insight in amounts or reduces or recycled waste are case studies on the firm level in the hospitality sector, but it is unknown how representative they are for this sector. 6.2
Methodology for data collection on waste and tourism As this Task 2.1 is mainly a preparatory task for the subsequent choice of relevant indicators describing waste and tourism and the necessary data collection in the eleven pilot cities of this project, it is important to consider different methodological approaches and the related data availability prior to the preparation of a data collection form. 109
In the following, the different options to collect and analyze data on waste and tourism are presented and discussed. Mainly these approaches aim at deriving information on how is tourism contributing to the generation of total municipal solid waste. On the one hand this information is a prerequisite for waste management planning (both for collection systems and recycling / disposal plants), on the other hand the literature review reveals, that it can be assumed, that accommodation can be considered as important contribution to waste generation within touristic activities. Table 11 gives an overview of the reviewed studies and the classification related to top‐
down and bottom‐up approaches. 110
Methodological approach Level of data collection Hotel(s) Bottom‐up (snapshot Sector study (hotels, analysis at restaurants, pubs, touristic places bars, cafés, bus and companies stations, campsites, scenic points, souvenir shops, museum, temple, golf course) Depicted touristic process Methods used to derive tourist‐
related waste generation 
Accommodation 
(partly incl. food and 
beverage provision) Interviews Questionnaires On‐site measurement of waste quantities and composition Accommodation, food and beverage 
provision, leisure 
activities (cultural, 
sports and other outdoor activities) Interviews Questionnaires On‐site measurement of waste quantities and composition 
Top‐down Total waste 
Tourism on local / (mainly time‐
generated by all regional level series analysis touristic processes based on waste statistics and influencing 
factors) Total waste Tourism on national generated by all level touristic processes 
Assumption of fixed rates of waste generation per tourist and night and extrapolating with total overnight stays Waste separation analysis at transfer stations / disposal sites throughout the year in order to derive changes in waste composition Modelling using statistical data Modelling using statistical data Table 11: Bottom‐up and top‐down approaches related to the reviewed literature Based on the literature review on “waste and tourism”, it is possible to divide the methodological approaches for estimation of tourism‐related waste generation and collection into 
bottom‐up approaches based on waste quantity and composition data and characteristics collected at source, i.e. closely related to the waste generator, e.g. tourism companies such as hotels, restaurants, etc. or to the waste collection infrastructure in touristic regions, or to 
top‐down approaches, that are mainly connected to waste statistics at municipal or regional level that are based on shipment data of waste collection companies or on statistics on input for waste treatment operators. Figure 28 shows these different approaches. Most studies included in the literature review applying bottom‐up approaches are based on sorting analyses (waste separation analyses) 111
of municipal solid waste (MSW) directly at tourism companies or public bins, thus allow to get profound insight into waste generating processes in the tourism industry and related waste prevention (=reduction, avoidance) and recycling measures. As these analyses are cost‐intensive, most studies are snapshot analyses of a limited sample and thus have solely an explorative character. Three studies included waste sorting in two seasons in order to analyse seasonal variation of waste composition. In the best cases, stratified sampling allows to statisticallly extrapolate the results of single tourism companies to large regions, such as done in United Kingdom (WRAP, 2001) or in Thailand (Manomaivibool, 2015). Variants of bottum‐up approaches without waste sorting use self‐reported waste quantity and composition data as inquired by questionnaires, interviews and, in some cases, on‐site visits. Top‐down approaches are mainly based on waste collection statistics of municipalities and regions at monthly or annual basis and try to relate variation in time with tourism‐related activities, e.g. overnight stays or tourist arrivals, as reported by statistical offices. Possible ways of statistical estimation of tourism impacts on MSW generation and composition can be done by 


cross‐sectional analyses, i.e. comparisons between regions (without time perspective), by time‐series analyses for one region or by analysis of panel data, i.e. time series of different regions in time. 112
Figure 28: Different methodological approaches in assessing waste and tourism A cross‐sectional analysis of Polish municipalities was done by Mesjasz‐Lech (2014) in order find impacts of health centres on MSW generation and collection in a series of municipalities. A schematic example in Figure 29 shows, that in this case only regional comparisons for the years 2004 and 2012 are possible. In order to explain the variation of MSW between the municipalities, socio‐demographic and tourism‐related indicators have to be available for each municipality. Figure 29: Cross‐sectional waste data (schematically) Applications of time‐series analyses for in single regions may be based on annual data, as done by Arbulú (2016a), or on monthly data, e.g. for Menorca (Spain) or Trento region in Italy (Caramiello et al., 2009; Mateu‐Sbert et al., 2013). Schematic time series are shown in Figure 30 and Figure 31, for annual and monthly data, respectively. 113
Figure 30: Schematic time series based on annual data and monthly data Figure 31: Schematic time series with winter and summer tourism season based on monthly data 114
Most suitable information for estimations of the impact of tourism on MSW generation and composition can be applied on the basis of data for a high number of municipalities, long annual time‐series and at monthly basis. Such panel data are schematically shown in Figure 32. Figure 32: Panel data for municipalities with winter and summer tourism season (schematically) An overview of all published approaches including details on used waste‐related data, sampling approach and coverage is shown in Table 12. Considering the urban metabolism approach and the potential inclusion of other environmentally relevant aspects, like electricity consumption, water consumption and waste water generation, the it might be possible under certain circumstances to use similar methodological approaches in order to allocate this to touristic activities. 115
Table 12: Approaches for estimating tourism‐related waste generation and collection sorted by analysed unit and time scale Approach Unit of analysis Waste quantity & Sampling principle and composition data no. of units On‐site measurement of waste quantity and Snap‐shot Case examples (random analysis up to selection): sorting of 1‐
composition 3 – 27 Bottom‐up (i.e. collecting data at Tourism company week source) Periods covered Key results 

waste Stratified samples for 
regional representativity: – 
138; 207 Inquired by questionnaires, interviews and on‐site visits 
Mostly random selection due to response rate: 
– 8 – 50 
Stratified samples for regional representativity: – 
50; 110 On‐site measurement Public bins of waste quantity and composition Sorting analysis at Regional seasonal level, waste statistics or benchmarks Top‐down (i.e. using Municipality aggregates) Waste statistics at annual basis Sorting for 12 – 57 samples 1week (2 cases) in one or two 

seasons (1 case) Regional stratification, number of units not available N/A 
Sorting in two seasons 
Years 2004 and 
2012 116
Williams and Fielding, 2008; Hoang, 2005; DPPEA, s.a.; Downing et al., 1999; Singh et al., 2014; Chan and Lam, 2001; Youngs et al., 1983; generation Waste relevance by process Insight into reduction and recycling potential Sources by method Estimate of regional or national quantity and composition Reduction and recycling potential by activity and company types Waste generation rates by hotel, partly process Status and potential regarding prevention and minimisation practices Estimate of regional quantity and composition Insight into recycling and reduction potential Quantity and composition of waste collected in public bins Insight into recycling practice and potential Waste quantity and composition in seasonal variation Quantification of tourism‐related MSW Quantification of tourism‐related MSW WRAP, 2011; Manomaivibool, 2015 Tang, 2004; Sridang et al., 2005; Hogan and Bergin, 2007; Zorpas et al., 2015; Trung and Kumar, 2005; Ball and Taleb, 2011; Spitzbart et al., 2013 Graggaber et al., 1999; Saito, 2013 Ariza et al., 2008; Canepa et al., 2012; Bhat et al., 2014 Ragazzi et al., 2004; Gidarakos et al., 2006 Mesjasz‐Lech, 2014 
Region Waste statistics at monthly basis 5 – 119; complete regional coverage in 2 12 – 14 years 
cases Waste statistics at 1 region with approx. annual basis Waste statistics at monthly basis 0.85 mio. inh.) Single 
regions with between 80,000 and 0.9 mio. inhabitants 7 years 

Impact of tourism on MSW in time Impact of low and high income tourists 
Impact of tourism‐related MSW quantity, composition and separate collection rate Impact on waste management infrastructure (e.g. capacity planning) 1 – 13 years at monthly basis 117
Estimates of tourism‐related MSW quantity by waste types Seasonal variation of separate collection rate Identification and exclusion of interfering impacts (commerce, 
Ofner, 2011; Rada et al., 2014; Oribe‐
Garcia et al., 2015 Arbulú et al., 2016a; Arbulú et al., 2013 Arbulú et al., 2016b; Caramiello et al., 2009; Mateu‐Sbert et al., 2013; Ranieri et al., 2014 Related to the special topic “food waste” it can be stated, that food waste in hotels/restaurants is normally quantified using a case study (or bottom‐up) approach. The positive side of this might lead to reliable data, but it would require large resources to use this approach at a large number of waste generators (e.g. hotels). Since waste from hotels and restaurants are commonly collected together with household waste, it could be challenging to distinguish what part of the mixed waste flow is actually related to tourist activities. Food waste data from food services are either recorded manually to get a high degree of resolution, or waste collection data is used. Again the high resolution gives the possibility to describe the waste in more detail, but requires resources. Waste collection data can also be considered as reliable, even though the resolution is lesser, but the large obstacle is that these kind of data are only recorded in places where the waste collection fee is dependent on the mass of waste of certain fractions. Even if restaurants have a record of wasted quantities, there is still no method to differ a tourist consumer from a local consumer in a restaurant, which means that the whole restaurant has to be defined as either tourist or non‐tourist in order to distinguish how much food waste are generated from tourism. Life Cycle Assessment (LCA) is a common and useful method for assessing the environmental impact from the management of food waste, and global warming potential (GWP) is by far the most commonly used impact category. By only assessing a few environmental impact categories the LCA will be limited, but the obvious benefit is that it is less time consuming. One of the most influential processes in life cycle assessments was the substituted system in the system expansion, especially in the higher levels of the waste hierarchy where more beneficial waste management options are supposed to be found. It is therefore important to put effort in assessing these processes with care, and make assumptions as transparent as possible. As long as the waste is only used for energy recover the substitution should be possibly to model based on available data, but the more efficient the waste reduction measures are the more difficult it will be to find out what is the actual substituted product or service. 118
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Appendix Table 13: Definitions for catalogue of indicators and background data requirements Data‐set ID Definition Definitions for waste related data requirements [1]‐[13] Waste generation The weight or volume of materials and products that enter the waste stream before recycling, composting, landfilling, or combustion takes place. Also can represent the amount of waste generated by a given source or category of sources. Source: EEA [1]‐[13] Waste composition Composition by weight Source: LCA‐IWM‐Project [1] Municipal waste Municipal wastes are waste collected by municipalities or by order of them. They include waste originating from households, commercial activities, office buildings, institutions such as schools and government buildings and small businesses that dispose of waste at the same facilities used for municipally collected waste. They also include similar waste from rural areas, even if they are disposed by the generator. The definition goes on to include: similar wastes generated by the same sources that are collected or purchased for recycling, even if the material does not enter the same waste stream (including separately collected fractions); white goods, bulky waste; street sweepings and the content of litter containers, if managed as solid waste. Source: EEA Report [2] Household waste Waste generated by the domestic activity of households collected by or on behalf of the municipalities and collected by or on behalf of accredited bodies(e.g. by retail) and social organizations (e.g.: WEEE, batteries, textiles). Also included is waste from street litter bins, street and market sweepings. Source: LCA‐IWM‐PROJECT and R4R‐project [4] Non‐household waste collected by or on behalf of the municipalities [6] Recyclables Waste streams collected separately (one waste stream not mixed with other waste streams) with negligible contamination going to a recycling facility, Source: R4R‐project [6b] Glass Bottles and jars without deposit Source: LCA/IWM‐project [6c] Metals Total of packaging and non‐packaging Source: LCA/IWM‐project [6d] Plastics and compounds Total of packaging and non‐packaging Source: LCA/IWM‐project [6e] Other recyclables Textiles etc.. Source: LCA/IWM‐project [7] Organic waste Food (kitchen) waste and garden waste (including pruning wood). Source: LCA/IWM‐project and R4R‐project [7a] Bio‐bin collected waste Food and garden waste collected in bio‐bins
Source: LCA/IWM‐project [7b] Yard waste Bulky organic waste from private and public gardens Source: LCA/IWM‐project [8] WEEE Waste from electrical and electronic equipment Source: LCA/IWM‐project -
Commercial waste only if it is collected by or on behalf of the municipalities Waste from schools, hospitals, institutions,... only if it is collected by or on behalf of the municipalities Waste from the municipality itself only if it is collected together with household waste" Source: R4R‐project [9] Residual waste Mixed waste collected from households and other sources. Source: EEA [10] Bulky waste Large items of waste material such as furniture, large car parts, trees, etc. Source: EEA [12] Hazardous waste Waste that because of their chemical reactivity, toxic, explosive, corrosive, radioactive or other characteristics, cause danger, or likely to cause danger, to health or the environment. See also: EC Directive on hazardous waste, HWC (hazardous waste catalogue). Source: LCA‐IWM‐project [11] Waste oils E.g. used cooking oils, etc. [14] Bags and bins provided Type of bags and bins: e.g. bags, bins smaller 300 ltr, bins from 300 to 1.100 ltr, bins larger 1.100 ltr, large containers Source: LCA‐IWM‐project [16] Collection (service) coverage rate How many people are served as a % of the total population.
Source: draft WATRA‐Project 129
Data‐set ID Definition [17] Treatment rate [%] Total amount of MSW treated Incineration MBT Composting Source: xls‐file”Data needs catalogue_template” [18] Recycling rate [%] Total amount of MSW recycled Source: xls‐file”Data needs catalogue_template” Definitions for data requirements for factors of influence [29] Total population For census purposes, the total population of the country consists of all persons falling within the scope of the census. In the broadest sense, the total may comprise either all usual residents of the country or all persons present in the country at the time of the census. The total of all usual residents is generally referred to as the de jure population and the total of all persons present as the de facto population. Source: OECD [30] Total area of the city, region Total area of a city or region including green space, built‐up area, roads/streets, bodies of water, ... Source: LCA/IWM‐Project [31] Total number of households Total number of households existing within the region/city. Source: LCA/IWM‐Project [31a] Private household A household is a small group of persons who share the same living accommodation, who pool some, or all, of their income and wealth and who consume certain types of goods and services collectively, mainly housing and food. Source: Eurostat [33] Second home /vacation home A second home/ vacation home (sometimes also designated as a holiday home) is a secondary dwelling that is visited by the members of the household mostly for purposes of recreation, vacation or any other form of leisure. Trips should not be so frequent and the duration of the stay so large as to turn the secondary dwelling into the principal dwelling of the visitor. Source: UN_Dep.ESA_2010_International Recommendations for Tourism Statistics 2008 [37] GDP Gross domestic product is an aggregate measure of production equal to the sum of the gross values added of all resident institutional units engaged in production (plus any taxes, and minus any subsidies, on products not included in the value of their outputs). The sum of the final uses of goods and services (all uses except intermediate consumption) measured in purchasers' prices, less the value of imports of goods and services, or the sum of primary incomes distributed by resident producer units. Source: OECD [38] GNI Gross national income (GNI) is GDP less net taxes on production and imports, less compensation of employees and property income payable to the rest of the world plus the corresponding items receivable from the rest of the world (in other words, GDP less primary incomes payable to non‐ resident units plus primary incomes receivable from non‐resident units). Source: OECD [39] Economically active population (Economically active persons) by economic sectors according to NACE Rev. 1 & ISIC Rev. 3 Economically active population comprises all persons of either sex who furnish the supply of labour for the production of economic goods and services as defined by the United Nations System of National Accounts during a specified time‐reference period (=Economically active persons). Source: OECD Classification NACE Rev. 1 (resp. ISIC Rev. 3): Sector Agriculture: A Agriculture, hunting and forestry B Fishing Sector Industry: C Mining and quarrying D Manufacturing E Electricity, gas and water supply F Construction Sector Services: G Wholesale and retail trade; repair of motor vehicles, motorcycles and personal and household goods H Hotels and restaurants I Transport, storage and communication J Financial intermediation K Real estate, renting and business activities L Public administration and defence; compulsory social security M Education N Health and social work O Other community, social and personal service activities P Private households with employed persons [40] Employment rate Employment rate represent persons in employment as a percentage of the population of working age (15‐64 years). Source: Eurostat [41] Unemployment rate The unemployment rate gives the number of unemployed persons as a percentage of the civilian labour force (total labour force excluding armed labour force). Source: OECD 130
Data‐set ID [42] Population by broad age groups Definition Fill the percentage of population divided into three age groups: 
Age 0 to 14 [%] 
Age 15 to 59 [%] 
Age 60 and more [%] Source: LCA/IWM‐Project Definitions for tourism related data requirements [47] Enterprises in the tourism industry Total non‐financial business economy Tourism industries (total) Tourism industries (mainly tourism) Tourism industries (partially tourism) Transport (total) Accommodation Food and beverage (total) (¹) NACE sections: B‐N_S95_X_K (Total business economy; repair of computers, personal and household goods; except financial and insurance activities). 2012 data for Ireland and FYR of Macedonia. (²) NACE classes: H491, H4932, H4939, H501, H503, H511, I551, I552, I553, I561, I563, N771, N7721 and division N79. (³) NACE classes: H511, I551, I552, I553 and N791.
(⁴) NACE classes: H491, H4932, H4939, H501, H503, I561, I563, N771, N7721 and N799. (⁵) NACE classes: H491, H4932, H4939, H501, H503 and H511.
(⁶) NACE classes: I551, I552 and I553. (⁷) NACE classes: I561 and I563. 2012 data for Ireland and Bosnia and Herzegovina. (⁸) NACE classes: N771 and N7721. (⁹) NACE division N79. 2012 data for Ireland and Bosnia and Herzegovina.
Car and other rental (total) Travel agency, tour operators and other reservation services Source: http://ec.europa.eu/eurostat/statistics‐explained/index.php/Tourism_industries_‐
_economic_analysis (07.07.2016) [50] Turnover Turnover, in the context of structural business statistics, comprises the totals invoiced by the observation unit during the reference period, and this corresponds to the total value of market sales of goods and services to third parties. Turnover includes: 
all duties and taxes on the goods or services invoiced by the unit with the exception of the value‐added tax (VAT) invoiced by the unit vis‐à‐vis its customer and other similar deductible taxes directly linked to turnover;  all other charges (transport, packaging, etc.) passed on to the customer, even if these charges are listed separately on the invoice. Reductions in price, rebates and discounts as well as the value of returned packing must be deducted. Excluded are: 
income classified as other operating income, financial income and extraordinary income in company accounts; 
operating subsidies received from public authorities or the institutions of the European Union (EU). Source: http://ec.europa.eu/eurostat/statistics‐explained/index.php/Glossary:Turnover_‐_SBS (08.07.2016) [51] Value added at factor cost Value added at factor cost is the gross income from operating activities after adjusting for operating subsidies and indirect taxes. It is an indicator in the domain of structural business statistics. It can be calculated as the total sum of items to be added (+) or subtracted (‐): 






turnover (+); capitalized production (+); other operating income (+); increases (+) or decreases (‐) of stocks; purchases of goods and services (‐); other taxes on products which are linked to turnover but not deductible (‐); duties and taxes linked to production (‐). Alternatively, it can be calculated from the gross operating surplus by adding personnel costs. Source: http://ec.europa.eu/eurostat/statistics‐
explained/index.php/Glossary:Value_added_at_factor_cost (08.07.2016) [52] Tourism receipts No definition, Source: http://ec.europa.eu/eurostat/statistics‐
explained/index.php/Tourism_statistics (07.07.2016) [53] Expenditure Tourism expenditure refers to the amount paid for the acquisition of consumption goods and services, as well as valuables, for own use or to give away, for and during tourism trips. It includes expenditures by visitors themselves, as well as expenses that are paid for or reimbursed by others. Source: Eurostat_2014: Methodological Manual for tourism statistics 131
Data‐set ID Definition [54] Tourist accommodation establishment A tourist accommodation establishment is a local kind‐of‐activity unit (an enterprise or part of an enterprise). It includes all establishments providing, as a paid service, accommodation for tourists, regardless of whether or not the provision of tourist accommodation is the main or a secondary activity of the enterprise to which the establishment belongs. As such, all establishments providing accommodation are covered, even if a major part of their turnover comes from restaurant / catering services or other services. Tourism accommodation establishments are classified and described in groups according to Section I.55 of NACE Rev. 2 classification as follow: 55.1 (hotels and similar accommodation), 55.2 (holiday and other short‐stay accommodation) and 55.3 (camping grounds, recreational vehicle parks and trailer parks). Class 55.1 ‐ Hotels and similar accommodation. This class includes the provision of accommodation, typically on a daily or weekly basis, principally for short stays by visitors. This includes the provision of furnished accommodation in guest rooms and suites. Services include daily cleaning and bed‐making. A range of additional services may be provided such as food and beverage services, parking, laundry services, swimming pools and exercise rooms, recreational facilities as well as conference and convention facilities. This class includes accommodation provided by: hotels (and similar establishments, for instance operating under the name 'bed & breakfast'); resort hotels; suite/apartment hotels; motels. This class excludes provision of homes and furnished or unfurnished flats or apartments for more permanent use, typically on a monthly or annual basis, see division 68. Class 55.2 ‐ Holiday and other short‐stay accommodation. This class includes the provision of accommodation, typically on a daily or weekly basis, principally for short stays by visitors,in self‐contained space consisting of complete furnished rooms or areas for living/dining and sleeping, with cooking facilities or fully equipped kitchens. This may take the form of apartments or flats in small free‐standing multi‐storey buildings or clusters of buildings, or single storey bungalows, chalets, cottages and cabins. Very minimal complementary services, if any, are provided. This class includes accommodation provided by: children and other holiday homes; visitor flats and bungalows; cottages and cabins without housekeeping services; youth hostels and mountain refuges. Class 55.3 ‐ Camping grounds, recreational vehicle parks and trailer parks. This class includes: provision of accommodation in campgrounds, trailer parks, recreational camps and fishing and hunting camps for short stay visitors; provision of space and facilities for recreational vehicles. This class also includes accommodation provided by: protective shelters or plain bivouac facilities for placing tents and/or sleeping bags. This class excludes: mountain refuge, cabins and hostels, see 55.20. No regional statistics are available for nights spent in non‐rented accommodation (= occupancy of dwellings by tourists, on a non‐commercial basis, either as a service provided without charge by family or friends or on own account like secondary homes…) or for same‐day visits. Source: Eurostat_2014: Methodological Manual for tourism statistics [55] Bedroom A bedroom in an accommodation establishment or dwelling is the unit formed by one room or groups of rooms which are rented by tourists as a whole (and constituting an indivisible rental). Rooms may be single, double or multiple, depending on whether they are equipped permanently to accommodate one, two or several people. The number of existing rooms is the number that the establishment has available to accommodate guests (overnight visitors), excluding rooms used by non‐tourists (e.g. the employees working for the establishment). If a room is used as a permanent residence (for more than a year) it should not be included either. Bathrooms and toilets do not count as a room. An apartment is a special type of room. It should be counted as one unit / bedroom irrespective of the number of rooms (one or more) it consists of. It has a kitchen unit, its own bathroom and toilet. Apartments may be with hotel services (in apartment hotels) or without hotel services, then they should be classified accordingly (in NACE 55.1 and 55.2 respectively). Cabins, cottages, huts, chalets, bungalows and villas shall be treated like apartments, i.e. to be count as one unit (e.g. one bedroom). Eurostat_2014: Methodological Manual for tourism statistics [56] Bed places The number of bed places in a tourist accommodation establishment is determined by the number of persons who can stay overnight in the beds set up in the establishment, ignoring any extra beds that may be set up upon customer request. The term bed place applies to a single bed; a double bed is counted as two bed places. The unit serves to measure the capacity of any type of accommodation. A bed place is also a place on a pitch or on a mooring in a boat to accommodate one person. One pitch for camping / tent, caravan or similar shelter and one mooring for boat should be counted for 4 bed places if the actual number of bed places is not known. Source: Eurostat_2014: Methodological Manual for tourism statistics 132
Data‐set ID Definition [60] Night spent or tourist night (overnight stay) A night spent or tourist night (overnight stay) is each night a guest / tourist (resident or non‐
resident) actually spends (sleeps or stays) in a tourist accommodation establishment or non‐
rented accommodation. Source: Eurostat_2014: Methodological Manual for tourism statistics It covers the total number of nights spent at destination. Source: (LCA‐IWM / Eurostat) [60a] Residents (in tourism context) Domestic tourists. Source: http://ec.europa.eu/eurostat/statistics‐
explained/index.php/Tourism_statistics_at_regional_level (07.07.2016) [60b] Non‐residents (in tourism context) Inbound tourists. Source: http://ec.europa.eu/eurostat/statistics‐
explained/index.php/Tourism_statistics_at_regional_level (07.07.2016) 133