Overview of scenarios and methodology
In the analysis, we include CH4 from enteric fermentation, paddy rice, and manure management and N2O from agricultural soils and manure management. We consider CO2 from fossil fuels to be part of the energy system and not the food system, and it is therefore omitted. We also do not include CO2 from agricultural expansion and other land-use changes. Our methodological approach is purely biophysical and cannot capture the political and socioeconomic mechanisms behind deforestation and land use change.
To analyze future GHG emissions, we construct regionalized food consumption scenarios and calculate the corresponding crop and livestock production in each region. Application rates of N in fertilizer and manure in crop production are estimated from the N content in harvested crops and assumptions of N use efficiencies for different crops and regions. N2O from agricultural soils is estimated as an emission factor per mass unit N input in fertilizer and manure as well as crop residues left on the fields. Feed intake in livestock production is estimated from assumptions on feed energy conversion efficiencies and feed rations for different livestock systems and regions. Based on the feed intake we estimate N2O and CH4 from manure excretion and storage, as well as CH4 from enteric fermentation. For details on the scenario assumptions, see the online supplementary material.
We present GHG emission estimates for the years 2000, 2030, 2050 and 2070. The estimate for year 2000 is produced for validation purposes. Our main focus is 2050 and 2070 since the global aggregated emission trajectories to reach the 2 °C target at a chance more likely than not exhibit substantial emissions reductions by mid-century and beyond. Emissions of CH4 and N2O are converted to the CO2-equivalents using the 100-year global warming potential (GWP) that includes indirect climate-carbon cycle feedbacks as reported in Myhre et al. (2013).
We examine five different scenarios (see Table 1) that are partly interlinked. The scenarios are described in more detail in sections 2.2–2.5.
Table 1 Main characteristics of scenarios to 2070 of global agricultural greenhouse gas emissions
Methane and nitrous oxide emissions in the reference scenario
N2O emissions associated with fertilizer and manure application is estimated by calculating the required N input in crop and pasture production given the N content in the required biomass output and the N utilization efficiency of the applied N. The N efficiency is here defined as the proportion of applied N that ends up in the above-ground biomass. Regional estimates of N efficiencies range from 28 % for rice in China (Fan et al. 2009) to about 75 % in forages (Smil 2001; Lenssen et al. 2010). We use data from Cassman et al. (2002), Ladha et al. (2005), and Smil (2001) to estimate current N efficiencies for different crops in Europe. We then rescale the values for other regions based on Bouwman et al. (2009). The N efficiency is assumed to improve over time in most regions. In the reference (baseline) scenario, we assume that N efficiency remains constant in Europe and gradually converges to the European level in North America and Pacific OECD. In other regions, N efficiency is assumed to be 20 % lower than in Europe by 2050. Direct N2O emissions related to fertilizer and manure application were calculated using an emission factor of 1 % N2O-N per N applied (IPCC 2006).
CH4 emissions from enteric fermentation is estimated as a fraction of feed intake in energy terms (IPCC 2006), assumed to be 7 % for permanent pasture, 6.5 % for forages (silage/hay), 5 % for protein concentrates and 3.5 % for cereal grains in gross energy terms.
For N2O and CH4 from manure management, we estimate the fractions of different manure handling systems in different regions (based on IPCC 2006) and the respective emission factors (based on temperature-averages, according to IPCC 2006). Further, from the assumed feed–to-product ratios (Table 2) we estimate the amount of manure produced, which in combination with the assumptions on manure systems are used to estimate N2O and CH4 emissions.
Table 2 Feed-to-product ratios in year 2000 and 2050 for the reference (REF) and increased productivity (IP) scenarios (region acronyms are explained in the supplementary material)
Livestock productivity scenarios
Feed requirements are calculated using feed-to-product ratios, here defined as the amount of feed (in gross energy) required to produce one unit of product (in human-metabolizable energy). In addition to the feed-to-product ratio, the feed ration is of great importance for the overall land requirements for animal food production and the associated GHG emissions.
We use two scenarios that reflect different agricultural productivity developments. We construct one Reference (baseline) scenario (REF) and one Increased Productivity scenario (IP). In the REF scenario we assume moderate increases in livestock productivity, largely in line with FAO projections. In the IP scenario we assume faster livestock productivity growth, based on extrapolations from the ‘Increased Livestock Productivity’ scenario in Wirsenius et al. (2010). Table 2 presents the corresponding estimates of feed-to-product efficiencies.
Technical mitigation scenario
We construct a Technical Mitigation (TM) scenario, based on the IP scenario, where we assess mitigation potentials of different technologies and management practices, and how fast these technologies may be diffused in different regions.
We assume that the N efficiency in crop production gradually increases so that all regions reach the efficiency level of Europe by 2050. At the global aggregate level, this gives a reduction in N2O emissions of 12 % in 2070 compared to the IP scenario. No additional N2O mitigation is assumed. There is a rather large potential for mitigation options for CH4 from paddy rice production. We assume that emissions per kg rice are gradually abated over time; the abatement starts in 2030 and grows linearly to 80 % reduction by 2070 (Lucas et al. 2007).
We assume that CH4 from enteric fermentation may be reduced by 20 %, either by fat additives or other additives in non-pasture feed. We assume that this mitigation option is applied to all ruminant systems in Europe, Pacific Oceania and North America by 2070, and to 50 % of ruminant systems in the rest of the world. We assume a linear interpolation from 2030. This assumption is in line with previous estimates of the mitigation potential for ruminants (DeAngelo et al. 2006; Beach et al. 2008).
Mitigation of manure emissions is arguably most effectively done by using either anaerobic digester or coverage and flaring of methane in slurry systems. Both options reduce CH4 and N2O by around 70 % (Montes et al. 2013). There is an even greater N2O mitigation potential if solid manure systems are converted to slurry systems. We assume a gradual transition first from solid systems towards slurry systems, and thereafter to slurry systems with flaring. This means that regional aggregate emission factors of CH4 and N2O from manure management drop by 30–70 % to 2070 compared to year 2000.
Dietary change scenarios
We design two scenarios to explore the potential GHG mitigation from dietary changes. In both scenarios we use the TM scenario as a basis. The rationale for this is that substantial deviations from current dietary preferences are unlikely and would probably occur only as a result of policy interventions. However, policy-driven dietary changes are contentious and would almost certainly emerge only after productivity improvements and technical measures largely have been exhausted.
We construct a Climate Carnivore (CC) scenario where 75 % of the ruminant meat and dairy consumption is replaced by other meat (in kcal terms). This scenario represents an increase in total meat by consumption per capita by 45 % compared to the baseline, but the average GHG intensity of this meat consumption is lower. We also make a Flexitarian (FL) scenario, where 75 % of all meat and dairy products are replaced by cereals and pulses (in kcal terms). “Flexitarian” is a term assigned to people that often, but not always, choose to eat vegetarian food (Forestell et al. 2012). It should be noted that the degree of substitution of 75 % is not based on any systematic analysis of limiting factors, and should therefore be considered as a tentative basis for an estimate of the upper-end mitigation potential from dietary changes. In addition to the generally conservative nature of food preferences, factors that might limit a far-reaching shift away from meat and dairy consumption include, for example, preservation of landscapes and cultures related to grazing and pastoralism.
Emission pathways consistent with 2 °C stabilization
To estimate multi-gas emission pathways compatible with the 2 °C target, we use an integrated climate-economy model based on Johansson (2011). The emission pathways generated in the model represent the least-cost solutions for meeting the temperature target. The emissions of the three most important greenhouse gases CO2, CH4 and N2O are determined endogenously in the model. Abatement of these emissions is modeled by marginal abatement cost functions and with constraints on how rapidly emissions may fall over time. We generate two emission pathways, using two different assumptions on climate sensitivity (being either 3 or 4 °C for a doubling of the CO2 concentration). Climate sensitivity is defined as the equilibrium increase in the global annual average surface temperature from a doubling of the atmospheric CO2 concentration with respect to pre-industrial levels and its value is likely between 1.5 and 4.5 °C (IPCC 2013). Climate sensitivity is critical for the emission space compatible with a given climate target. The emission pathway generated with a climate sensitivity of 4 °C will have a larger chance of keeping the global temperature increase below 2 °C as compared to the emission pathways generated using a climate sensitivity of 3 °C, see supplementary information for further details.