Global greenhouse gas emissions associated with the production of crop and livestock products at 5 arc minutes resolution, 1997-2003

The overall methodology has been developed in the forthcoming publication by Dalin et al. (in prep.).

The greenhouse gas (GHG) emissions of crop products are calculated, at a 5arcmin spatial resolution for the production of year 2000 as the sum of: GHG from peatland drainage (directly from Carlson et al. 2016), GHG from rice cultivation, and GHG from manure and synthetic fertiliser application on cropland. Both GHG from rice cultivation and GHG from manure applied to cropland depend on the amount of manure available and used for fertilising cropland as evaluated here based on Herrero et al. 2013, re-estimated by Dalin et al. (in prep.), following methods as in Carlson et al. 2016. These amounts of manure are also relevant for, and consistent with, the livestock’s GHG emissions estimated here. In addition, we produced two versions of nitrous oxide emissions from cropland due to manure and synthetic fertiliser applied to cropland (and from grassland, due to manure deposited and synthetic fertiliser applied, relevant for livestock): one using a linear model and the other with a non-linear model (see Carlson et al. 2016).

The greenhouse gas emission and greenhouse gas emission intensities of livestock products are calculated, at a 5arcmin spatial resolution for the production of year 2000 as the sum of livestock’s farm-level GHG emissions and feed-related GHG emissions (feed coming from both cropland and grasslands).

Livestock farm-level GHG emissions include methane from enteric fermentation for ruminants (bovine, sheep and goat) as estimated by Herrero et al. 2013, methane and nitrous oxide from manure management as estimated by Herrero et al. 2013, and nitrous oxide from manure left on pasture estimated using the model used by Carlson et al. 2016.

Feed-related GHG emissions include nitrous oxide from three sources: synthetic fertiliser applied on cropland, synthetic fertiliser applied on grassland, and manure applied on cropland. We account for animals’ diet composition (Herrero et al. 2013), the country of origin of feed crops (FAOSTAT), and the forage use efficiency and productivity of grasslands (ORCHIDEE, Chang J. et al. 2016).

Quality control:

Testing of the computational steps has been ensured thanks to fully independent, parallel coding and computations done by 2 of the co-authors, with matching results.

Averages of the gridded data to aggregated at the national scale have been compared with reported national-level values by FAOSTAT.

References:

Herrero, M., et al., Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proceedings of the National Academy of Sciences, 2013. 110(52): p. 20888-20893.

FAO. FAOSTAT. 2022 Detailed trade matrix Available from: http://www.fao.org/faostat/.

Chang, J., et al., Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management. Biogeosciences Volume 13, issue 12 pp.3757–3776, 2016.

Dalin et al. Variability, interactions and drivers of key environmental stressors from food production worldwide (in prep)

Carlson, K.M., et al., Greenhouse gas emissions intensity of global croplands. Nature Climate Change, 2017. 7(1): p. 63-68.

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Water debt for the annual production of nine major crops globally at 5 arcmin resolution for the year 2000