1
Attributing global carbon releases
to local consumption activities:
method and applications
Jan Minx
Technische Universität Berlin (TUB)
Department for the Economics of Climate Change
Department for Sustainable Engineering
2
Motivation
• Analytical results are dependent on definition of
city;
• Understanding the relevance of cities in climate
change mitigation requires information about
non-urban areas for comparison;
• Drivers of emissions associated with cities are
still insufficiently understood;
3
Aim
• Develop a methodology for the estimation of
local carbon footprints given data shortages:
▫ Provides a consistent set of estimates;
▫ For a large number of local areas;
▫ With a high level of spatial granularity
• Analyse emission determinants of local carbon
footprints in the UK
4
Definition carbon footprint
• The carbon footprint of an
area is defined as the direct
and indirect CO2/GHG
emitted throughout the word
in the production of goods and
services finally consumed in
that area.
• This is different to scope 1,2,3
accounting!
5
Local emission accounting – the
importance of scale
• The smaller the “territorial” boundary the more
emissons you can potentially miss -> higher trade
dependency
▫ E.g., US has smaller share of imported emissions then
Switzerland
▫ E.g., The GHG emissions emitted from the property of your
house could be zero!
Derived from a slide by Glen Peters
6
Local emission accounting – the
growing importance of the global
Hinterland
Peters, Minx, Weber and Edenhofer (2011)
7
The Challenge for the estimation of
local carbon footprints
Experian, 2008
Global production
MRIO
Local consumption
Approach
Geodemographics
8
Modelling global production using
multi-regional input-output analysis
|
 EUU   fU   LUU

  
 E EU   f E   L EU
E   f  L
 OU   O   OU
E  f  L
 RU   R   RU
UK carbon footprint
Emission intensity
O
O
L EE
O
O
L OO
O
O
Leontief Inverse
O  YUU 


O  YEU 
O  YOU 


L RR  YRU 
Final demand
9
Imputing local consumption patterns:
Geodemographic data (1)
• Challenge: Comprehensive information on local
consumption missing -> downscaling – 3 ingredients
Experian, 2008
required
Experian, 2008
What lifestyle
groups/neighbourh
hoods are there?
61 lifestyle groups
• >400 variables
• Geo-referenced data
• Adressses key dimensions relevant for
environmental analysis
Ingredient 1
10
Imputing local consumption patterns:
Geodemographic data (2)
Combining Ingredients 1 & 2
44 consumption categories
What do lifestyle
groups consume?
(national level)
Ingredient 2
11
Imputing local consumption patterns:
Geodemographic data (3)
Experian, 2008
Combining Ingredients 1,2 & 3
Where do
those people
live? Lifestyle
composition
across spatial
scales
Ingredient 3
12
Downscaling methodology: Making
things as good as possible
Step 1
Step 2
Step 3
13
Scope 1 and 2 emissions vs carbon
footprint for selected local authorities
• Much smaller
CF variability
• Problems for
comparability
• Information
suitable for
different
purposes
Scope 1 and 2 emissions
Carbon footprint
14
Household carbon footprint of rural
and urban areas
15
CF of all local authorities
Income can explain a substantial part, but not all of the
variation. So what are the drivers?
Scope 1 and 2 emissions
Scope 1 and 2 emissions
Minx et al., 2009
16
Regression analysis – independent
variables
• Structural variables:
▫
▫
▫
▫
▫
▫
Heating degree days ***
Degress of ruralness
Population density
Population density per sealed surface
Area of domestic buildings per capita
Job density
▫
▫
▫
▫
▫
▫
Income ***
Household size ***
Car ownership ***
Education ***
Ethnicity
Age
• Socio-economic variables:
17
Factors determining local carbon
footprints in the UK
Kern, 2011
GHG emissions
The impact of
income on GHG
grows with rising
income levels
Income
18
Factors determining local carbon
footprints in the UK
Kern, 2011
GHG emissions
The impact of
household size on
GHG decreases
with increasing
household size
Household size
19
Factors determining local carbon
footprints in the UK
Kern, 2011
GHG emissions
• The more cars
are owned per
capita the higher
the impact of car
ownership on
GHG emissions
• Lifestyle
identifier
Per capita car ownership
20
Factors determining local carbon
footprints in the UK
Kern, 2011
GHG emissions
The impact of
education on GHG
emissions grows
with rising
education levels,
but at an
decreasing rate
Education levels
21
Factors determining local carbon
footprints in the UK
Kern, 2011
GHG emissions
Statistically
significant but not
immediately
intuitive impact of
heating degree
days on GHG
emissions
Heating degree days
22
The carbon footprint of Freiburg –
cities’ and communities’ Hinterlands
Almost 60%
of carbon
footprint
not
determined
on the city
territory
Preliminary results
23
National determinants of local carbon
footprints
24
Future research - adding spatial
resolution – the case of London
Minx et al., 2009
25
Discussion - method
• Is this method consistently good or consistently
bad?
▫ “Averaging” in the context of IO;
▫ “Averaging” in downscaling.
• At which spatial level should we “measure”
emissions for insightful urban analysis?
• Which components of the carbon footprint matter in
the context of local decision making?
▫ Which can be affected?
▫ How can we improve robustness of these components?
• How can these multi-level results be used for multilevel governance in climate change mitigation?
26
Discussion – results (1)
• To understand questions related to the global
sustainability of urban and rural lifestyles
consumption based accounting approaches are
required
• Cities and communities trigger GHG emissions
far beyond their territory in their global
Hinterland
▫ E.g. 60% of Freiburg„s carbon footprint is released
outside ist territory
27
Discussion – results (2)
• Cities and communities are to some degree
locked into a particular emission pattern
through regional and national infrastructure
• The average carbon footprint of urban areas are
slightly lower than for rural areas
• GHG emissions of local areas in the UK are
currently mainly determined by differences in
their socio-economic make-up and lifestyles ->
contribution of infrastructure remains unclear
28
Outlook
• Re-do current analysis based on improved data
• Analysis of emission patterns of individual
cities;
• Typology of cities with regard to their
metabolism?
• Methodological improvements;
• One consistent framework framework
integrating
▫ scope 1,2,3 and consumption based accounting
▫ Process and input-output data