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Agricultural production and greenhouse gas emissions from world regions-The major
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trends over 40 years
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Bennetzen, E. H., Smith, P. & Porter, J. R.
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Abstract
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Since 1970, global agricultural production has more than doubled with agriculture and landuse change now responsible for ~1/4 of greenhouse gas emissions from human activities. Yet,
while greenhouse gas (GHG) emissions per unit of agricultural product have been reduced at
a global level, trends in world regions have been quantified less thoroughly. The KPI (KayaPorter Identity) is a novel framework for analysing trends in agricultural production and landuse change and related GHG emissions. We apply this to assess trends and differences in nine
world regions over the period 1970 to 2007. We use a deconstructed analysis of emissions
from the mix of multiple sources, and show how each is changing in terms of absolute
emissions on a per area and per produced unit basis, and how the change of emissions from
each source contributes to the change in total emissions over time. The doubling of global
agricultural production has mainly been delivered by developing and transitional countries,
and this has been mirrored by increased GHG emissions. The decoupling of emissions from
production shows vast regional differences. Our estimates show that emissions per unit crop
(as kg CO2-equivalents per Giga Joule crop product), in Oceania, have been reduced by 94%
from 1,093 to 69; in Central & South America by 57% from 849 to 362; in sub-Saharan
Africa by 27% from 421 to 309, and in Europe by 56% from 86 to 38. Emissions per unit
livestock (as kg CO2-eq. GJ-1 livestock product) have reduced; in sub-Saharan Africa by 24%
from 6,001 to 4,580; in Central & South America by 61% from 3,742 to 1,448; in Central &
Eastern Asia by 82% from 3,205 to 591, and; in North America by 28% from 878 to 632. In
general, intensive and industrialised systems show the lowest emissions per unit of
agricultural production.
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Highlights
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We use a novel identity-approach to analyse greenhouse gas emissions from agriculture
We analyse changes in emissions per unit produced in 9 world regions
Developed regions have increased production while reducing greenhouse gas emissions
Developing and transitional regions have increased both production and emissions
All regions have reduced emissions per produced product, but to varying degrees
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1. Introduction
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Since 1970, the human population has grown from 3.7 to more than 7 billion (UN, 2014) and
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higher consumption, accompanied by a shift towards more animal-based products in the diet,
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means that agricultural production has more than doubled (FAOSTAT, 2014). Agricultural
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production and land-use change (LUC) are currently responsible for ~1/4 of total greenhouse
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gas (GHG) emissions from human activities (Smith et al., 2014). However, it has recently
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been illustrated that global agriculture has been getting more efficient in terms of greenhouse
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gas emissions. While production has been growing fast, emissions have been increasingly
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decoupled from production. In 2007, the global average carbon footprint per produced unit
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crop and livestock was 39% and 44% lower than in 1970, respectively (Bennetzen et al.,
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2015). But these global trends tell us little about the trajectory in different world regions.
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GHG emissions from agriculture are most frequently reported on a per area basis, which
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tends to favour low-input system as the most environmentally benign (Gregory et al., 2002).
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But, for global environmental issues, such as GHG emissions, this makes little sense, since
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these do not affect the local area but the global climate. If one instead expresses GHG
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emissions per unit of product (i.e. emissions intensity), lower GHG emissions per area are not
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better than higher GHG emissions per area, if the production also also proportionately lower.
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Many authors argue that intensification and GHG emissions are closely linked (van Beek et
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al., 2010), but reality is more nuanced.
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When agricultural emissions are analysed, only rarely is the complete portfolio of emissions
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sources included; LUC is often neglected (Bellarby et al., 2013) although up to 90% of
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emissions from LUC are due to agricultural activities; be it crop production, pasture or
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shifting cultivation (Houghton, 2012; Gibbs et al., 2010). One of the major trade-offs, on the
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subject of GHG emissions and sustainable agriculture in general, is whether to increase
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production by expansion of cultivated area versus obtaining higher yields on areas that are
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already cultivated (Phalan et al., 2011a; Phalan et al., 2011b; Godfray, 2011; Pretty et al.,
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2010; Green et al., 2005). This makes it highly relevant to include LUC in the analysis since
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higher agricultural yields on already cultivated areas will lead to fewer emissions from LUC
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(Tilman et al., 2011; West et al., 2010). Furthermore, despite an increasing dependency on
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external energy inputs, energy-based emissions are most often totally neglected. In the
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UNFCCC system, energy-use in agriculture is accounted for in the transport-, energy- and
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buildings- sectors (Smith et al., 2008; Schneider & Smith, 2009). Yet, if we wish to analyse
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how agricultural production is contributing to climate change, or maybe mitigating climate
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change, we need to include all energy-uses; including those from fertilizer manufacture and
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transportation and indirect uses for farm infrastructure.
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By deploying the Kaya-Porter Identity (KPI: Bennetzen et al., 2015; Bennetzen et al., 2012),
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based on the concept of the well-known Kaya identity (e.g. Raupach et al., 2007), we estimate
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and analyse past trends in agricultural production and LUC and related GHG emissions for
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nine world regions in the years 1970-2007. The KPI provides a new metric for emissions
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control, monitoring and analysis and allows us to identify where things are going well and not
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so well, to design effective abatement strategies for the most important components of land
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based GHG emissions. We deconstruct emissions from the mix of multiple sources of GHGs
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into attributable elements. This enables analyses of, not only the absolute emissions but, a
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combined analysis of emissions per unit area and emissions per unit of production. It also
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allows an assessment of how the change of emissions from each source contributes to the
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change in total emissions over time. Energy use and energy-based emissions are also
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included, enabling an analysis of energy efficiency and carbon intensity of the energy and, by
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including all emission sources, the total carbon footprint of agriculture.
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2. Materials and Methods
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Using an identity approach, we estimate and analyse past GHG emissions from regional
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agricultural production and LUC. An identity is a mathematical construction by which the
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entity – the GHG emissions – can be deconstructed into elements, which affect the entity of
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emissions. The KPI is multi-scale and can be used to analyse any discrete agricultural system
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from field to farm and at national (Bennetzen et al., 2012) to global level (Bennetzen et al.,
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2015). In this study we apply the KPI at world regional level. We apply two identities – KPI-
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C for crop production (Equation 1) and KPI-L for livestock production (Equation 2) – which,
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when combined, estimate emissions from the total agricultural sector. Each identity and all
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elements are estimated for each year in the period from 1970 – 2007 for nine regions defined
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as Central- and Eastern Asia (CEA), Central- and South America (CSA), Eastern Europe and
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Russia (EER), Europe (EUR), Middle East and Northern Africa (MENA), North America
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(NA), Oceania (OCE), South- and South East Asia (SSEA) and Sub-Saharan Africa (SSA).
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Emission sources included are enteric fermentation by livestock (CH4), manure storage and
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handling (CH4 and N2O), application of N from fertilizer and manure (N2O), rice cultivation
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(CH4), direct on-farm energy use (CO2), indirect energy use for manufacture of fertilizers,
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machinery and buildings (CO2), LUC (CO2) and from production of used fodder (CO2, N2O
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and CH4). The CO2 net flux over continuously cultivated fields is argued to be largely in
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balance (Smith et al., 2014; USEPA, 2013; Houghton et al., 2012) and thus assumed to be
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zero. All data on area and production are derived at regional level from the FAOSTAT
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database (FAOSTAT, 2014). Emissions are estimated as activity data multiplied by emission
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factors (EmFs). Emissions from enteric fermentation and manure and from soils are estimated
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according to the tier 1 IPCC 1996 inventory guidelines using regional default EmFs (Table
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S1). Data on energy use and EmFs (Table S2) are from the UN Energy Statistics Database for
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fossil- and electricity energy use (UN, 2011), from the International Rice Research Institute
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(IRRI, 2012) combined with own assumptions based on literature (Starkey, 1988; Starkey,
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2011; Ramaswamy, 1987) for energy use by draught animals, and from FAOSTAT for labour
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power. Data on regional LUC emissions are derived directly from CDIAC (Carbon Dioxide
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Information Analysis Center) (Houghton, 2008); hence not our own estimates.
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We use the same data sources and methods as described in Bennetzen et al. (2015), with the
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exception that in this study, all analysis are conducted on a regional level. Hence, for full
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methods see the Supplementary Materials or Bennetzen et al. (2015).
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Briefly we illustrate the identities and the one variable – GHG emissions from fodder use –
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which differs from the method used in Bennetzen et al. (2015), by taking regional imports and
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exports of fodder into account.
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Equation 1. KPI-C:
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 GHGLUC GHGsoil  GHGc;in Ec;in   Ec;out
DM c;out
 
GHGcrop  

 


 areacrop; food
 Ec;out
Ec;out
Ec;out   DM c;out areacrop;all
 Ec;in

,where areacrop;food is the cropped area excluding that used for producing animal fodder, area crop;all is the total
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cropped area, DMc;out is the dry matter crop produced, Ec;out is the energy contained in harvested crops, Ec;in is the
energy use, GHGc;in is emissions from energy use, GHGsoil is CH4, N2O and CO2 emissions from cultivated soils
and GHGLUC is CO2 emissions from LUC.
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The KPI for livestock production (Equation 2) is conceptually similar to KPI-C and they are
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designed to be used simultaneously. The crop-identity (Equation 1) includes both GHG
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emissions directly from crop production and those from LUC.
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Equation 2: KPI-L
 GHG fodder GHGefmh  GHGl ;in El ;in   El ;out
DM l ;out
 
GHGlivestock  
 


 areal
  DM
 El ;out
E
E
E
area
l
;
out
l
;
in
l
;
out
l
;
out
l



,where
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areal is the area used for permanent pastures and meadows and for fodder production, DM l;out is the dry matter of
eatable produced animal products, El;out the energy contained in these animal products, El;in is the energy use,
GHGl;in is emissions from energy use, GHGefmh is CH4 and N2O emissions from enteric fermentation and manure
handling and GHGfodder is GHG emissions associated with production of consumed fodder.
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GHGfodder is the GHG emissions associated with production of the fodder used in the region.
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For each region, emissions from fodder come from what is produced plus what is imported
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minus what is exported. The method of calculation is illustrated below for region ‘j’ and all
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other regions being ‘i-x’. The use of fodder in region ‘j’ is partitioned by domestically
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produced and imported fodder (Equation 3). Emissions from domestically produced fodder
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are estimated as fodder produced minus fodder exported multiplied by regional emissions per
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unit crop for that year (Equation 4). Emissions from imported fodder are estimated as DM
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import multiplied by a regional and yearly specific EmF. The EmF is estimated as the sum of
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emissions from fodder exported from regions ‘i-x’ (regional GHG per DM crop multiplied by
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DM fodder exported), divided by the total amount of exported fodder from regions ’i-x’
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(Equation 5). This ensures that emission intensities from the high-exporting regions (e.g.
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CSA) are weighted proportionately and vice versa. Due to limited information on the origin of
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imported fodder and feedstuff, more exact emission factors are not possible and emissions
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may not be fully captured.
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Equation 3
GHG j ; fodder  GHG j ;own  GHG j ;import
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Equation 4
 GHGc;all 

GHG j ;own  DM j ; produced  DM j ;exp ort  

DM
c
;
out

j
Equation 5
   GHG 

c ;all
 



DM
i  x ;exp ort
    DM c;out 


ix

   DM

GHG j ;import 
j ;import


 DM i x;exp ort 






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3. Results
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There are vast differences between regions in both production and emissions, which we
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describe in the following sections – region by region.
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3.1
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CEA has experienced the greatest growth in production since 1970; yet, emissions have been
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relatively stable since mid-1980s. Crop- and livestock production have increased from 4.19 to
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9.44 EJ and from 0.16 to 1.24 EJ, respectively, in the years from 1970 to 2007. For livestock
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production, this is almost an eightfold increase, and in energy terms, is now producing 47% of
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global pig meat, 46% of eggs, 33% of sheep and goats and 20% of poultry meat. Meanwhile,
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total emissions have been reduced from 1.52 to 1.18 Pg CO2-eq., reducing emissions per unit
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product by 78% and 82% for crop- and livestock- production, respectively (Table 1; Table 2).
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Its share of global production has increased from 16% to 20% whilst its share of emissions
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has dropped from 16% to 10% (Figure 1). Emissions per produced crop are among the
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world’s lowest at 68 kg CO2-eq. MJ-1 crop in 2007. This is almost exclusively an effect of
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reduced emissions from LUC, which have been taken from 0.8 Pg CO2 yr-1 in 1970 to below
Central- & Eastern Asia (CEA)
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zero since year 2000 (Figure 2), responsible for 96% of its decoupling in crop production
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(Figure 3). Hence almost none of the decoupling is gained by direct improvements within the
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production system, but by efficient reforestation policies in e.g. China (Rudel et al., 2005;
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Meyfroidt et al., 2010). But this effect from reduced LUC has disappeared since the year
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2000. CEA is the region with the second largest emissions from soils per produced crop
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(following SSEA), mainly due to a large proportion of rice production, causing CH4
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emissions under water-saturated conditions. Emissions from industrial fertilizer use have
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increased by a factor of 6.4, from 42 to 310 Tg CO2-eq. (Figure 4), and have not been fully
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offset by higher production. Fertilizer use and mechanization have also increased energy use,
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more than tripling energy-based emissions per produced unit (Table 1). Hence, this
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contributes greatly to total emissions, due to the exceptionally high crop yields of 3.7 tonnes
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DM ha-1. The large increase in livestock production has not come at the expense of more
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GHG emissions. Pig production has increased by 560% from 0.098 EJ in 1970 to 0.65 EJ in
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2007 while stock numbers only increased by 140% from 186.1 to 449.1 million head
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(FAOSTAT, 2014); illustrating the intensification and industrialization that has also happened
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in the rest of the livestock sector. Since 1970, absolute energy use for livestock production
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increased by 300%, but since the contribution of human labour as an energy source has
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decreased from 83% to 46%, total emissions from energy use have increased more than 11-
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fold. However, a GHG intensity of used energy on 82 kg CO2 per GJ livestock is still just
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over the world average – due to a high contribution from human labour as we generally see in
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developing- and transition countries. Emissions from enteric fermentation and manures have
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doubled, yet, due to the much higher increase in production, emission intensity has decreased
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by 75% reaching 325 kg CO2-eq. per GJ produced livestock, which is among the lowest
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(Table 2). This is responsible for 37% of regional decoupling of emissions from livestock
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production (Figure 5). 54% of the decoupling is from reduced emissions from fodder use per
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livestock. The largest reduction in fodder use per livestock (-61%) is seen in CEA (Figure
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S1), which could be partly explained by the expansion of mainly poultry-, but also pig,
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production, which in general has a higher feed conversion efficiency (Steinfeld & Gerber,
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2010).
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3.2
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Agricultural production in CSA has increased greatly since 1970 – crop production has
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increased 160% (Table 1) and livestock production 216% (Table 2). This is mainly driven by
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higher yields, which have tripled for livestock and doubled for crop production. Emissions
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have increased from 2.6 to 3.0 Pg CO2-eq. yr-1 between 1970 and 2007; making CSA
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responsible for 25% of global emissions (Figure 1). The low rise in emissions, relative to
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production, means that emissions have been decoupled by 57% from crop production and
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61% from livestock production. Nevertheless, LUC has been, and still is, causing large
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emissions. Brazil alone accounts for one third of global emissions from deforestation
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(McKinsey & Company, 2009), though these fell in the last decade (Smith et al., 2014). The
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most noticeable result from CSA is the increase in emissions from LUC during the 1980s and
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the subsequent decline (Figure 2). Most of this has been driven by a large expansion in
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livestock farming, either directly by grazing or indirectly by clearing land for production of
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feed crops (Gibbs et al., 2010; Ibrahim et al., 2010; Steinfeld et al., 2006). Later, the export of
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soy bean to Europe and Asia became another driver of LUC in CSA (Zaks et al., 2009) and in
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2007, CSA exported 31 million tons DM fodder equivalent to almost 30% of all fodder
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produced in the region (FAOSTAT, 2014). Emissions from LUC are also clearly affecting
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emissions from fodder use. However, since fodder use has grown less than livestock
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production, and emissions per unit fodder have been reduced, emissions from fodder per unit
Central- & South America (CSA)
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livestock were reduced by 81% and responsible for 51% of the reduced emissions intensity of
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livestock production in CSA (Figure 5). Emissions from soils have been reduced per unit crop
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since 1980 (Figure 2) – even though the use of industrial nitrogen has been multiplied by 5.6
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– due to reduced rice cultivation, and since emissions from application of manure have
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increased far less than crop production. However, this has had a small impact on reducing
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emissions, due to the massive changes in LUC (Figure 3). A tripling of livestock production
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has caused emissions from enteric fermentation and manure to increase, but emissions per
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produced unit, from this source, have fallen by 47% (Table 2), contributing 38% of reduced
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emission intensity from livestock production (Figure 5). In terms of energy use intensity, CSA
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is at the very low end, and well below the global average (Table 1; Table 2). Both energy-use
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intensity and the GHG intensity of the energy is increasing, but neither of these trends has any
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distinct effect on the total changes in emissions (Figure 3; Figure 5).
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3.3
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The sensitivity of agricultural production to major political disruption is clear from trends in
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EER, where production fell since the fall of the Soviet Union in 1989 (Figure 2). From 1989
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to 1999, production of crops and livestock where reduced by 44% and 48% respectively, and
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since then have stayed low but relatively stable. Emissions in 2007 are just 40% of those in
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1970 and contribute 3% of global emissions (Figure 1). Emissions per produced unit have
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decreased relatively constantly from 130 to 63 and 1,125 to 614 kg CO2-eq. GJ-1 for crop and
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livestock production, respectively (Table 1; Table 2). This makes the livestock sector in EER
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the second most climate-efficient per produced unit; from 5% of global livestock area, 8% of
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livestock products are produced with just 4% of associated emissions. Reduced emission
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intensity from enteric fermentation and manure is the main drivers of this (23%); but also
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emissions from fodder use (17%). From energy use, emissions per unit livestock almost
Eastern Europe and Russia (EER)
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doubled and have tripled per unit crop. Total emissions per unit crop are relatively low, but
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crop yields have stayed very low at around 1 t DM ha-1. Hence, from 11% of global crop area
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just 7% of crops are produced. Emissions from LUC have been drastically reduced by 82%,
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fastest in the first two decades (Figure 3), contributing 72% of reduced emissions from crop
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production (Figure 3). Emissions from soils have also been reduced relative to production,
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contributing 4% of reduced emissions. It has been argued that intensifying Eastern European
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agriculture to the same level as Western Europe could double N2O emissions (Ciais et al.,
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2010). However, if this would bring a similar rise in yields (EUR=2.7, whereas EER=1.0),
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then this would still result in net mitigation per unit crop.
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3.4
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In EUR we see a case of how very high emissions per area are being offset by highly
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productive systems, resulting in emissions per produced unit being very low (Figure S2). This
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results from highly resource-use efficient systems, and net emissions from LUC within the
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first decade that were ‘negative’ due to reforestation, thus sequestering carbon in soil and
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biomass rather than emitting carbon to the atmosphere. This is also noticeable in NA, and can
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be explained by the fact that land was converted to agriculture, affecting GHG emissions,
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before the period we analyse, whereas LUC in most developing regions started later (Rudel et
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al., 2005; Rudel, 1998; Goldewijk, 2001; Houghton, 1999). EUR is, however, causing LUC
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indirectly by the so-called leakage effect (Meyfroidt et al., 2010; Lambin & Meyfroidt, 2011).
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In 2007, 30% of fodder used in EUR was imported (Figure S4). EUR is one of the few
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regions where emissions from fodder use per unit livestock have actually increased (Figure 5).
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Livestock production has not increased much and has largely been at a plateau since 1985
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(Figure 2). However, while the area has been reduced, especially for livestock, total
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production has been maintained, by remarkably high yields (Figure S2). Crop yields in EUR
Europe, excl. former Soviet and Eastern Block countries (EUR)
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(2.7 t DM ha-1 for crops) are only surpassed by CEA. Yields from livestock products (276 kg
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DM ha-1) are by far the highest in the world while emissions per unit livestock are among the
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lowest at 741 kg CO2-eq. GJ-1 product. This results from very intensive production, mainly of
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milk and pig meat. In 2007, the EUR livestock sector produced 17% of global production, but
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just 11% of emissions, from a livestock area of only 3% of the global total. 71% of emissions
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reductions from livestock are due to decreasing emissions from enteric fermentation and
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manures – the rest from reduced area. This has been reached through general productivity
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gains, higher feed-use efficiency and technological development for storage and handling of
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animal wastes (Mikkelsen et al., 2010). Energy-use intensity has increased, but from very low
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to slightly higher levels (0.62 kg CO2-eq. GJ-1 livestock product), and is still far below the
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world average (1.17 kg CO2-eq. GJ-1). For crop production, EUR occupies 3% of the global
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area, but produced 8% of all crops with just 1% of global emissions. Emissions per produced
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crop have been very low throughout the period, and in 2007 were the second lowest,
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following NA, with 38 kg CO2-eq. GJ-1 product (Table 1). 14% of this is due to higher
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energy-use efficiency, 16% from nitrogen-use efficiency and 49% from reduced emissions
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from LUC (Figure 3). Energy-based emissions per crop unit have been reduced by 24% since
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1970. GHG intensity of energy use has remained largely unchanged – however, energy-use
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efficiency has improved by 25%. Direct energy use and energy imported by the use of
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fertilizers increased until the mid-1980s but since then has been reduced, while yields
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continued to rise. A Danish case-study illustrates how energy use per produced crop was
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reduced by 26% since 1992 whilst yields have increased by 14% (Bennetzen et al., 2012).
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3.5
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Agricultural production and GHG emissions from MENA have increased steadily since 1970
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and show relatively small decoupling of emissions. Still, we see fewer emissions per
Middle-East & Northern Africa (MENA)
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produced unit compared to other developing regions (CSA, SSA and SSEA) (Figure S2;
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Figure S3). Crop yields have increased from 0.6 tons DM ha-1 to 1.1 tons DM ha-1, and for
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livestock from 7.8 to 20.6 kg DM ha-1; the latter being just more than 1/3 of the global
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average. Meanwhile emissions per produced crop reduced by 10% and emissions per
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produced unit livestock have been decoupled by 27% (Table 1; Table 2). A noticeable
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development in this region is the increase in energy use per produced unit and in GHG
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intensity of the energy; causing energy-based emissions to escalate to 47.7 and 194.2 kg CO2-
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eq. GJ-1 produced crop and livestock, respectively. These values are the worlds’ highest and
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are almost double the second highest regions (Table 1; Table 2). In MENA, energy-based
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emissions contribute 20% of agricultural emissions, compared to a global average of 8.6%
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(Bennetzen et al., 2015). Increased fertilizer use has contributed to this development (Table 1;
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Figure 4), but it has mainly been driven by an increase in direct fossil energy use through
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mechanisation. Energy inputs from human labour and from draught animals have remained
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relatively constant. Emissions from soils per unit crop have increased by 24% from 21.3 to
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26.3 kg CO2-eq. GJ-1. Just under half of this is from artificial N-fertilizer use; but also resulted
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from an increase in CH4 emissions from rice production and a doubling in N application from
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livestock manure. Emissions from LUC per produced unit have been reduced throughout the
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period (Figure 3) and is the only factor reducing total emissions per unit crop. In livestock
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production, enteric fermentation and manure together are responsible for 93% of the reduced
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emissions per produced unit, which is now 952 kg CO2-eq. GJ-1; still higher than the world
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average of 667 kg CO2-eq. GJ-1 and three times higher than that of EUR. The decoupling is
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partly due to a relative shift towards poultry and egg production, which together contribute
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26% of DM livestock production in 2007. That chickens show the highest growth rate is
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partly due to the favourable feed-conversion efficiency, but poultry has also increased as it is
13
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acceptable to all religious and cultural groups. The main factor though, is general efficiency
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gains in ruminant production, where meat production grew by more than 400% with only a
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doubling of cattle numbers; a similar trend is seen in the dairy sector. Livestock have
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increasingly been fed with fodder crops (Figure S5) and in MENA we see the highest increase
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in emission intensity from fodder use at 64% (Table 2).
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3.6
321
In 2007, 14% of global agricultural production came from NA, but only 5% of GHG
322
emissions (Figure 1), from 10% of global agricultural area. Since 1985, total emissions have
323
been relatively static while production has increased constantly since 1970 (Figure 2)
324
reducing emissions per unit crop and livestock to 34 and 632 kg CO2-eq. GJ-1, respectively
325
(Table 1; Table 2). This makes NA crop production the most, and livestock production among
326
the most, climate efficient. As for EUR, low emissions intensity is driven by highly resource-
327
use efficient systems and, even more so, net-emissions from LUC that are negative because of
328
reforestation. Yet NA is the only region where net LUC emissions have increased. However,
329
very importantly, LUC-emissions are actually negative throughout the period, but just more
330
so in the first two decades. 51% of reduced emissions from crops are due to reduced
331
emissions from soils per unit crop. While production has more than doubled, N2O emissions
332
from the application of fertilizers and animal waste have increased just 74% and 12%,
333
respectively. Despite a five-fold increase in production of pulses leading to increased N2O
334
emissions, and a 50% increase in rice production leading to increased CH4 emissions, these
335
quantities do not affect the result significantly. In terms of energy-based emissions, NA has
336
the largest contribution: 26% of all emissions from the agricultural sector (Figure 2). NA has
337
relatively low energy-use intensity but high GHG intensity of the energy used. In livestock
338
production, GHG intensity of energy use is double the global average. The yield energy
North America (NA)
14
339
content is responsible for 11% of reduced emissions (Figure 5) due to increased milk and
340
poultry production. In 2007, NA was producing 23% of global poultry meat. This
341
proportional change towards poultry and dairy, and with production of ruminant meat
342
relatively unchanged, has also contributed to the reduction in emissions intensity from enteric
343
fermentation and manure, which is responsible for 53% of reduced emissions. Higher feed use
344
efficiency is also noticeable (Figure S1), caused both by the change in livestock species and
345
technological developments.
346
3.7
347
OCE has decreased emissions drastically from 1970 and is now responsible for 1% of global
348
emissions, but also just 1% of production. Yet, it occupies 9% of global agricultural area. In
349
OCE we find the world’s lowest crop yields of 0.8 tons DM ha-1 in 2007. Still, emissions per
350
unit crop are relatively low – reduced from having the world’s highest emissions intensity in
351
1970. LUC is responsible for 100% of the decoupling of emissions from crop production. In
352
the 1970s emissions from LUC where reduced from 0.270 in 1970 to 0.045 in 1980 to 0.012
353
Pg CO2 in 1990, and since then have stayed relatively constant (Figure 2). This reduction
354
overshadows the almost tripled emissions from soils per unit crop. Only in OCE and MENA
355
have emissions from soils per unit crop increased. However, throughout the period, these
356
have stayed lower than in all other regions, despite an eightfold increase in industrial fertilizer
357
use, which is still maintained at a very low level per area, but at average level per unit crop
358
produced (Figure 4). Livestock production in OCE has grown 74% since 1970 with a minor
359
decrease in area. Yet, this region has the second lowest livestock yields of 12.8 kg DM ha-1 in
360
2007. Although fodder use is increasing (Figure S4), mainly in the dairy sector (Ho et al.,
361
2013; Bethune & Armstrong, 2004), meat production is characterized by relatively low input
362
systems based on grazing on extensive rangelands (Herrero et al., 2013; Wiedemann et al.,
Oceania (OCE)
15
363
2015). Also, OCE produce only limited amounts of eggs and meat from poultry and pigs.
364
Hence we see very low use of fodder (Figure S1) and the lowest emissions from fodder use
365
per unit livestock produced (Table 2). Total emissions per unit livestock largely follow the
366
world average throughout the period, thus being the highest of the developed regions. Energy
367
use intensity and the GHG intensity of the energy use remain relatively unchanged, indicating
368
that energy use has followed production with no overall changes in use efficiency.
369
3.8
370
Production has increased in SSEA by ~180%, and the region is now producing 25% of world
371
agricultural commodities, and is the absolute largest contributor to global agricultural
372
emissions, responsible for 34% (Figure 1). Emissions per produced crop have stayed
373
relatively constant, from 267 to 245 kg CO2-eq. GJ-1; hence emissions have increased
374
proportionately with the more than doubled yields (Table 1). SSEA now produces 27% of
375
global crops but is responsible for 47% of associated emissions. LUC emissions have
376
increased in SSEA; keeping emissions from LUC per unit crop relatively constant. Indonesia
377
in particular is experiencing vast LUCs (Harris et al., 2012; Baccini et al., 2012) and is
378
estimated alone to account for one third of global emissions from deforestation (McKinsey &
379
Company, 2009). Emissions from soils per unit crop are the worlds’ highest, but are being
380
reduced in spite of ten-fold increases in fertilizer use since 1970 (Figure 4). The case is
381
different for livestock production systems, where emissions per unit livestock have been
382
reduced by 55% from 3390 to 1532 kg CO2-eq. GJ-1 (Table 2). Livestock production from
383
SSEA has increased by 339% and is responsible for 20% of global emissions from livestock,
384
while producing 14% of livestock products. The area has stayed largely unchanged and
385
livestock yields have reached 255 kg DM ha-1, which is just below the European yield and far
386
higher than any other region. One major reason contributing to this is the very large dairy
South- & South-East Asia (SSEA)
16
387
sector, mainly in India (Steinfeld et al., 2006). In SSEA, milk represents 62% of all livestock
388
products, providing 23% of global milk production. Production growth has partially been
389
driven by the ~eight-fold increase in fodder use. Fodder use per unit livestock is still very low
390
(Figure S1) and, even though it is increasing, traditional feed resources and crop residues may
391
still be a major source (Steinfeld et al., 2006), and are not captured by the data used in this
392
analysis. In India, 50% of ruminant fodder is grass fed (Bouwman et al., 2005). Even though
393
the feed use is low, emissions per unit feed is relatively high; making emissions from fodder
394
per produced livestock just below the world average at 334 kg CO2-eq. GJ-1 livestock
395
produced. Emissions from enteric fermentation and manure have been reduced by 65% from
396
3,158 to 1,117 kg CO2-eq. GJ-1 livestock produced; partly resulting from the large dairy
397
sector, but also from the rapid increase in poultry meat (1000%) and eggs (550%), and to a
398
lesser degree, pig meat (400%). These create far fewer emissions than beef production, which
399
has increased by just ~130% since 1970. Similar proportions between changes in the different
400
livestock (chicken>eggs>pigs>milk>ruminant meat) are largely seen across all regions, yet
401
the individual magnitudes vary greatly.
402
3.9
403
SSA has 12% of global arable land and 21% of global pasture and meadows. But this region
404
is producing just 6% and of global crops and no more than 3% of global livestock products.
405
Together with OCE, this region has the absolute lowest yields. Still it has the highest
406
emissions per produced unit. SSA has the absolute highest emissions per unit livestock at
407
4,580 kg CO2-eq. GJ-1 of which emissions from enteric fermentation and manure contribute
408
2,877 kg CO2-eq. and 1,689 kg CO2-eq. from fodder production (Table 2). SSA has
409
approximately the same use of fodder as MENA, CSA and SSEA, yet emissions from fodder
410
per unit livestock vary greatly between these regions. Absolute emissions from fodder use are
Sub-Saharan Africa (SSA)
17
411
much lower in MENA than the other three regions, because the emissions per unit of fodder
412
used are less than half that of others due to relatively low emissions per produced crop, which
413
we use as an indicator of emissions from fodder production. SSA, together with CSA, has the
414
most emissions per unit of used fodder, mainly because crop production in both regions
415
accounts for large emissions from LUC. Yet emissions from fodder per produced livestock
416
are five times higher in SSA, because of the low livestock productivity. Throughout the
417
tropics, many livestock keepers are poor farmers; with >60% of them living in SSA and South
418
Asia, mainly having mixed livestock- and cropping systems (Thornton et al., 2003). The use
419
of fodder per produced livestock is also very limited in SSEA, as also seen for CSA and OCE.
420
However, emissions per used fodder are slightly lower in SSEA, and with the higher
421
production emissions from fodder per produced livestock are similar to that of EUR. Just 3%
422
of global livestock products are produced in SSA, yet this region is responsible for 13% of
423
global emissions from livestock. SSA is now responsible for 12% of all global agricultural
424
emissions (Figure 1), which have increased 81% from 0.78 to 1.42 Pg CO2-eq. since 1970
425
(Figure 2). Still, only 6% of global agricultural goods are produced here. The main source of
426
emissions is LUC, which increased until the late 1990s at a similar rate to production
427
increase, but since then has declined (Figure S3). Major forest conversion has occurred
428
mainly in West- and Central Africa (Thornton, 2010). SSA is the region with the lowest
429
emissions from energy use per produced unit. This is due to the very low GHG intensity of
430
the energy use, since a large proportion (71%) of this energy comes from human labour.
431
Compared to this, the global average proportion of human labour energy is 24%, with higher
432
levels seen only in SSEA (32%) and CEA (33%). A substantial number of draught animals
433
are used in SSA, and in many areas this is not in decline, as mechanisation has not increased
434
as quickly as in other regions (Steinfeld et al., 1997).
18
435
4. Discussion
436
Our study has several limitations. Being a top-down study our analysis tells us nothing about
437
sub-regional factors driving the trends we see from the results. Each of the world regions is
438
heterogeneous in terms of cultural traditions, economic competences and biophysical factors,
439
all of which affect the local agricultural system. Hence, relevant drivers and context may have
440
been omitted by taking a global-regional approach. Our metric of agricultural production
441
output in terms of energy units also ignores the nutritional qualities of different food items
442
and the multifunctional nature of agriculture producing other goods and services for farmers
443
and society. Also, the KPI is very new and not all of the issues associated with how
444
uncertainties propagate through a series of deconstructed identity terms have been fully
445
examined, and hence have not been included in the current analysis. The overall messages in
446
the paper (i.e. the direction and magnitude of the trends) are not altered by adding uncertainty.
447
However, these aspects should be examined in future studies, to strengthen the conclusions of
448
future analyses. We also acknowledge that the data and methods used can, and should, be
449
improved over time. The historical geopolitical disruption in Central Asia affects some of the
450
data we used. This can be seen in our results. The most southern part of the Former Soviet
451
Union is included in our EER region for the years 1970 to 1991, but since the fall of the
452
Soviet Union the countries Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan
453
were declared independent and from 1992 to 2007, these countries are included in our CEA
454
region. Also, energy use intensity in CEA show an unrealistic increase in the mid-1980s. The
455
reason for this is that data on electricity use in China is only provided from year 1979 and
456
from several other energy sources from year 1986 by the energy data source we use (UN,
457
2011). We have not been able to compensate for this inconsistency, so it affects the results on
458
energy use and associated emissions in the CEA region.
19
459
In our estimates, LUC feeds directly into emissions from crop production and is only
460
indirectly accounted for by livestock, through emissions associated with fodder-crop
461
production. In many cases this will give results close to reality, but in cases such as CSA,
462
where the absolute greatest cause of agricultural expansion is recognised as being cattle
463
pastures (Gibbs et al., 2010; Ibrahim et al., 2010), the burden attributed to crop production
464
may be overestimated, and underestimated for livestock, even though some of the emissions
465
will feed into the livestock identity through fodder use.
466
5. Conclusions and perspectives
467
The doubling of global agricultural production over the past 40 years has mainly been
468
delivered by developing and transitional countries, and the increased GHG emissions likewise
469
(Figure 2). From 1970 to 2007, the global average GHG emissions per unit crop was
470
decoupled by 39% (Bennetzen et al., 2015), but with regional variation between a decoupling
471
of 94% (OCE) to an actual increase in emissions per unit crop of 4% (NA) (Table 1). In
472
global livestock production, decoupling was 44% but with regional results ranging from 14%
473
(EUR) to 82% (CEA) (Table 2). There is a stark disconnect between regions where emissions
474
occur and those where goods are produced. Since 1970, developed regions (EUR, NA and
475
OCE) have reduced their agricultural area by 118 million ha (10%), whereas developing
476
countries together have expanded their agricultural area by 447 million ha (13%). While
477
reducing their agricultural area, developed countries have almost doubled crop production
478
from 6.54 to 11.76 EJ yr-1 and increased livestock production from 1.14 to 1.68 EJ yr-1, while
479
reducing total emissions by 7% from 1.56 to 1.46 Pg CO2-eq. yr-1. In the same period,
480
developing countries have doubled crop production from 17.9 to 37.71 EJ yr-1 and almost
481
tripled livestock production from 1.18 to 3.36 EJ yr-1, but, at the same time, have increased
482
total emissions by 34% from 7.85 to 10.53 Pg CO2-eq. yr-1.
20
483
Since most emissions from livestock are associated with extensive livestock systems in
484
developing countries, a shift towards more intensive management, improved pastures and
485
agroforestry, diet intensification and changing breeds, could provide further mitigation
486
(Thornton & Herrero, 2010). This trend of increased productivity/industrialization is
487
recognised in many developing regions (Wirsenius et al., 2010) and is expected to increase in
488
South America, Africa and Asia in the coming decades (Bouwman et al., 2005; Havlik et al.,
489
2014). Globally, industrialized systems are estimated to account for 76-79% of global pork
490
and poultry production, 69% of milk production and 61% of ruminant meat (Herrero et al.,
491
2013). However, in OCE, CSA, MENA and SSA, a large proportion of meat is produced in
492
grazing systems (Herrero et al., 2013). In many local areas, intensification of livestock
493
production, which could mean fewer animals, could also be challenged for cultural reasons,
494
since the livestock ownership in many cultures is a measure of wealth and/or essential to
495
manage risks (Thornton & Herrero, 2010). Improved livestock and grassland management,
496
and soil nutrient management can be strategies to deliver on both mitigation and improved
497
local livelihoods, and create further resilience to climate change. We also see a trend towards
498
relatively more production of monogastric animals such as pigs and poultry (Steinfeld et al.,
499
2006; Steinfeld et al., 1997), but ruminants still contribute ~80% of GHG emissions from
500
global livestock production (Gerber et al., 2013).
501
The main effect on GHG emissions are from LUC. In this study, the Western regions benefit
502
from having completed major LUC and deforestation prior to the period studied here
503
(Goldewijk, 2001). We see how emissions from LUC are negative in some regions (NA and
504
EUR), limited in others (EER, MENA, OCE), but very substantial in the tropics (CSA, SSA
505
and SSEA). It is now in tropical regions that agricultural production is expanding, which is
506
also where 80% of total mitigation potential has been recognised (Smith et al., 2008; Trines et
21
507
al., 2006). An emphasis towards higher yields, rather than expanding lands is especially
508
important in these tropical countries (West et al., 2010) in which occupation of uncultivated
509
areas and deforestation continues to release vast amounts of carbon to the atmosphere
510
(Houghton, 2012; McKinsey & Company, 2009; Harris et al., 2012; Baccini et al., 2012;
511
Thornton, 2010). LUC will remain the most critical issue, and avoiding future deforestation
512
may have the highest GHG mitigation effect (Bennetzen et al., 2015; Del Grosso & Cavigelli,
513
2012) at relatively low cost (Kindermann et al., 2008). At the local scale, sustainable
514
intensification in developing countries can enhance yields whilst reducing emissions and
515
other environmental costs (Pretty et al., 2006), and allow space for reforestation (Palm et al.,
516
2010). Yet there may be challenges in providing incentives for the desired land-sparing effect.
517
In practice, local yield increases tend to increase returns to farming and hence, perversely,
518
stimulate of the spread of agricultural land into new areas (Rudel et al., 2009). Also we need
519
to recognise that GHG emissions alone do not define the sustainability of the system, but are
520
only one of many factors. While intensive systems may cause fewer GHG emissions per
521
agricultural product, these may have other negative environmental impacts such as soil
522
degradation, eutrophication and chemical pollution, and loss of biodiversity (Foley et al.,
523
2005; Rockström et al., 2009; Tilman et al., 2001). Further intensification is necessary, so we
524
need to make sure that this intensification is sustainable (Smith, 2013; Garnett et al., 2013;
525
Pretty & Bharucha, 2014).
22
526
Tables
310
11.42 0.09 0.17 0.21 0.025
2.68
849
18.15 0.10 0.11 0.39 0.007
EER
162
1.0 15.8 0.15 40.4 27.1
96
6.2
0.016
0.070
0.249
0.335
4.36
130
2.06
0.16 0.18 0.07 0.038
EUR
52
1.7 15.9 0.43 63.2 40.9
18
27.4
0.039
0.058
0.025
0.121
2.85
86
2.34
0.05 0.12 0.03 0.040
MENA
64
0.6 15.7 0.19 24.7 21.3 112
4.8
0.003
0.012
0.064
0.079
0.71
138
1.24
0.06 0.03 0.02 0.004
NA
85
0.9 15.8 0.39 69.5 28.8
27.3
0.033
0.034
-0.028
0.039
3.39
32
0.45
0.08 0.14 0.01 0.042
OCE
39
0.4 16.2 0.31 78.2 11.2 1.058 24.1
0.006
0.003
0.270
0.279
0.30
1093
7.15
0.04 0.01 0.06 0.001
SSEA
283
1.0 16.0 0.23 12.4 98.4 166
2.8
0.013
0.445
0.751
1.208
4.68
267
4.27
0.28 0.19 0.25 0.014
SSA
104
0.5 16.1 0.18 7.2 22.7 397
1.3
0.001
0.021
0.363
0.385
1.29
421
3.71
0.10 0.05 0.08 0.002
World
1,023
1.1 15.9 0.26 41.3 48.2 216
10.6
0.186
0.846
3.790
4.822
24.44
275
4.71
1.00 1.00 1.00 0.174
0.10 0.19 0.07 0.187
GHG(soil) (Pg CO2-eq.)
GHG(fertilizer) (Pg CO2-eq.)
Crop GHG per area (Mg CO2-eq. / ha)
4.19
1.895
% of global emissions
Crop GHG intensity (kg CO2-eq. / GJ)
1.010
1.809
% of global production
Absolute production (EJ)
0.801
0.077
% of global area
Absolute crop emissions (Pg CO2-eq.)
0.192
0.009
GHG from energy use (Pg CO2-eq.)
0.017
4.1
GHG(soil) intensity (kg CO2-eq. / GJ)
5.3
1.3 16.5 0.10 40.8 34.3 811
Energy use intensity (GJ / GJ)
2.3 15.7 0.26 19.9 58.9 246
104
Yield (tonnes DM / ha)
88
CSA
Area (bill. Ha)
CEA
Region
GHG(LUC) (Pg CO2-eq.)
GHG(energy) intensity (kg CO2-eq. / GJ)
GHG(LUC) intensity (kg CO2-eq. / GJ)
GHG intensity of energy use (kg CO2-eq. / GJ)
Energy content of yield (GJ / tonnes DM)
Table 1. Results on crop production and greenhouse gas emissions in 1970 and 2007
1970
-24
2007
CEA
115
3.7 15.6 0.53 42.8 50.5
22.5
0.149
0.334
-0.033
0.450
9.44
68
3.91
CSA
140
2.5 16.8 0.20 61.8 26.0 323
-5
12.3
0.071
0.150
1.869
2.090
7.04
362
14.97 0.12 0.14 0.33 0.041
EER
124
1.0 15.9 0.28 70.0 20.8
23
19.3
0.039
0.042
0.046
0.127
3.27
63
1.03
0.11 0.07 0.02 0.024
EUR
37
2.7 15.9 0.33 64.4 33.4
-17
20.9
0.034
0.054
-0.026
0.061
4.03
38
1.62
0.03 0.08 0.01 0.051
MENA
61
1.1 15.9 0.63 75.4 26.3
50
47.7
0.053
0.029
0.055
0.137
1.70
124
2.25
0.05 0.03 0.02 0.022
NA
133
2.1 15.8 0.27 68.4 22.6
-7
18.6
0.081
0.098
-0.032
0.148
7.13
34
1.11
0.11 0.14 0.02 0.073
OCE
34
0.8 16.3 0.37 71.9 19.1
24
26.3
0.012
0.008
0.011
0.031
0.60
69
0.89
0.03 0.01 0.00 0.006
SSEA
307
2.4 16.2 0.34 40.4 59.6 172
13.6
0.164
0.720
2.079
2.963
13.12
245
9.64
0.26 0.27 0.47 0.140
SSA
147
1.0 16.1 0.20 16.2 22.0 284
3.3
0.007
0.050
0.648
0.706
3.13
309
4.79
0.13 0.06 0.11 0.006
World
1,172
2.0 16.1 0.34 51.0 39.0 110
17.5
0.667
1.487
4.187
6.342
49.47
166
5.41
1.00 1.00 1.00 0.548
% Change
CEA
30
56
0
99
115 -14 -102
328
769
74
-104
-55
126
-78
-66
14
11
-66
639
CSA
34
91
2
99
52
-24
-60
202
682
96
3
10
163
-57
-18
17
30
-16
460
EER
-24
3
1
80
73
-23
-77
213
146
-40
-82
-62
-25
-52
-50
-34
-63
-71
-38
EUR
-28
57
0
-25
2
-18 -194
-24
-13
-7
-207
-50
42
-56
-31
-37
-30
-62
27
MENA
-5
100
1
225 205
24
-55
891
1,802
138
-14
73
140
-10
81
-17
19
32
385
NA
55
136
0
-31
-2
-22
31
-32
150
187
14
282
110
4
146
35
4
190
74
OCE
-12
96
0
19
-8
71
-98
9
88
195
-96
-89
100
-94
-88
-23
-1
-92
713
SSEA
9
143
1
47
226 -39
4
378
1.177
62
177
145
181
-8
126
-5
39
87
888
SSA
42
76
0
12
124
-3
-28
151
528
142
79
83
143
-27
29
24
20
39
178
World
15
88
1
34
23
-19
-49
65
258
76
10
32
102
-39
15
0
0
0
215
527
528
529
23
Absolute production (EJ)
% of global area
% of global production
% of global emissions
0.29
0.51
0.16 3,205 1.16
0.12
0.07
0.11
0.40
0.34
0.74
0.20 3,742 1.48
0.14
0.09
0.16
EER
440
47.3
25.3
0.59
51.2
646
449
30.4
0.016
0.34
0.24
0.59
0.53 1,125 1.34
0.12
0.23
0.13
EUR
128
189.9
25.3
0.32
79.6
528
303
25.6
0.016
0.33
0.19
0.53
0.62
4.12
0.04
0.27
0.12
MENA
321
7.8
24.0
0.85
20.8 1,887
280
17.6
0.001
0.11
0.02
0.13
0.06 2,184 0.41
0.09
0.03
0.03
NA
418
40.8
26.1
0.48 122.8
163
59.4
0.027
0.29
0.07
0.39
0.45
0.94
0.12
0.19
0.09
OCE
460
6.3
26.0
0.06
36.0 2,049
582
2.1
0.000
0.16
0.04
0.20
0.08 2,633 0.43
0.13
0.03
0.04
SSEA
121
54.8
25.0
2.28
7.8
3,158
214
17.7
0.003
0.52
0.04
0.56
0.17 3,390 4.64
0.03
0.07
0.12
SSA
752
3.3
26.4
1.56
0.8
3,716 2,284
1.2
0.000
0.25
0.15
0.40
0.07 6,001 0.53
0.21
0.03
0.09
World
3,541
25.3
25.8
0.88
36.7 1,125
32.3
0.075
2.60
1.90
4.57
2.32 1,976 1.29
1
1
1
livestock GHG per area (Mg CO2-eq. / ha)
Absolute livestock emissions (Pg CO2-eq.)
Livestock GHG intensity (kg CO2-eq. / GJ)
GHG(fodder) (Pg CO2-eq.)
0.21
0.004
GHG from energy use (Pg CO2-eq.)
0.008
33.8 2,007 1,712 22.3
GHG(energy) intensity (kg CO2-eq. / GJ)
15.8 1,306 1,847 52.2
0.66
GHG(fodder) intensity (kg CO2-eq. / GJ)
3.31
27.4
Energy use intensity (GJ / GJ)
27.9
14.4
Energy content of yield (GJ / tonnes DM)
13.0
503
Yield (kg DM / ha)
439
CSA
Area (bill. Ha)
CEA
Region
GHG(ent.frem+manure) (Pg CO2-eq.)
GHG(ent.frem+manure) intensity (kg CO2-eq. / GJ)
GHG intensity of energy use (kg CO2-eq. / GJ)
Table 2. Results on livestock production and greenhouse gas emissions in 1970 and
2007
1970
655
819
857
878
2007
CEA
815
56.4
27.0
1.62
50.5
184
82.0
0.102
0.40
0.23
0.73
1.24
0.90
0.22
0.25
0.13
CSA
581
44.0
24.6
0.65
53.9 1,070
325
343
35.2
0.022
0.67
0.22
0.91
0.63 1,448 1.57
0.16
0.12
0.16
EER
191
85.0
24.2
0.82
66.4
318
241
54.7
0.022
0.13
0.09
0.24
0.39
614
1.26
0.05
0.08
0.04
EUR
118
276.0
25.7
0.62
95.9
356
325
59.6
0.050
0.30
0.27
0.62
0.84
741
5.25
0.03
0.17
0.11
MENA
455
20.6
22.9
1.92 101.1
952
458
194.2 0.042
0.20
0.10
0.34
0.21
1604
0.76
0.12
0.04
0.06
NA
338
86.5
24.4
0.83 127.3
383
142
106.2 0.076
0.27
0.10
0.45
0.71
632
1.33
0.09
0.14
0.08
OCE
405
12.8
25.4
0.20
88.5
976
110
18.1
0.002
0.13
0.01
0.15
0.13 1,105 0.36
0.11
0.03
0.03
SSEA
122
255.3
23.4
1.65
49.7 1,117
334
81.8
0.060
0.81
0.24
1.11
0.73 1,532 9.15
0.03
0.14
0.20
SSA
769
7.9
25.6
1.99
6.6
2,877 1,689 13.0
0.002
0.45
0.26
0.71
0.16 4,580 0.93
0.21
0.03
0.13
World
3,721
54.1
25.1
1.17
60.2
0.356
3.37
1.88
5.60
5.05 1,110 1.51
1
1
1
17
667
372
70.6
591
% Change
CEA
86
334
-3
-51
221
-75
-90
57
1,122
94
-22
44
679
-82
-23
77
257
CSA
16
205
-10
-1
59
-47
-80
58
398
69
-37
22
216
-61
6
10
45
0
EER
-56
80
-4
39
30
-51
-46
80
35
-63
-60
-59
-25
-45
-6
-59
-66
-67
132
215
EUR
-8
45
1
93
20
-33
7
MENA
42
163
-5
126
387
-50
64
1,003 3,825
-8
45
17
36
-14
27
-12
-38
-4
80
483
161
256
-27
84
35
63
114
NA
-19
112
-7
72
4
-42
-13
79
185
-7
39
15
60
-28
42
-23
-27
-6
OCE
-12
103
-2
243
146
-52
-81
742
1,366
-17
-67
-27
74
-58
-17
-16
-20
-40
SSEA
1
366
-6
-28
537
-65
56
361
1,924
55
584
98
339
-55
97
-4
101
62
SSA
2
137
-3
27
758
-23
-26
992
2,468
82
74
80
135
-24
76
-3
8
47
World
5
114
-3
33
64
-41
-55
119
377
29
-1
22
118
-44
17
0
0
0
530
24
531
Figures
532
533
534
Figure 1. Global greenhouse gas emissions from agriculture and land-use change by world regions from 1970 to
2007
535
25
536
537
538
539
Figure 2. Agricultural production and greenhouse gas emissions by source from world regions from 1970 to
2007. Emissions are read on the left axis as Pg CO2-eq. Crop production (black full line) is to be read at the right
axis as EJ produced and livestock production (black stippled line)is read at the left axis as EJ produced.
26
540
541
542
543
544
545
Figure 3. Decomposed changes of emissions in regional crop production from 1970 to 2007. It illustrates, for
each decade, the change in total emissions (black squares) and the contribution from each element in the KPI
(coloured bars). Illustrated is the area (red), yield (green), energy content of produced crops (not visible),
energy-use intensity (blue), GHG intensity of energy used (orange), emission intensities from soils (light blue)
and emission intensities from LUC (light red).
27
546
547
548
549
550
Figure 4. Total greenhouse gas emissions from fertilizer use (A) and emissions per produced crop (B) and per
cropped area (C). Emissions include N2O following application to soils and CO2-eq. from energy use for
fertilizer manufacture.
28
551
552
553
554
555
556
Figure 5. Decomposed changes of emissions in regional livestock production from 1970 to 2007. It illustrates,
for each decade, the change in total emissions (black squares) and the contribution from each element in the KPI
(coloured bars). Illustrated is the area (red), yield (green), energy content of the produced livestock (purple),
energy-use intensity (blue), GHG intensity of energy used (orange), emission intensities from enteric
fermentation plus manure (light blue) and emission intensities from fodder used (light red).
29
557
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