Assessment of uncertainties in greenhouse gas emission profiles of livestock sectors in Africa, Latin America and Europe

Abstract

The global animal food chain has a large contribution to the global anthropogenic greenhouse gas (GHG) emissions, but its share and sources vary highly across the world. However, the assessment of GHG emissions from livestock production is subject to various uncertainties, which have not yet been well quantified at large spatial scale. We assessed the uncertainties in the relations between animal production (milk, meat, egg) and the CO 2 , CH 4 , and N 2 O emissions in Africa, Latin America and the European Union, using the MITERRA-Global model. The uncertainties in model inputs were derived from time series of statistical data, literature review or expert knowledge. These model inputs and parameters were further divided into nine groups based on type of data and affected greenhouse gas. The final model output uncertainty and the uncertainty contribution of each group of model inputs to the uncertainty were quantified using a Monte Carlo approach, taking into account their spatial and cross-correlation. GHG emissions and their uncertainties were determined per livestock sector, per product and per emission source category. Results show large variation in the GHG emissions and their uncertainties for different continents, livestock sectors products or source categories. The uncertainty of total GHG emissions from livestock sectors is higher in Africa and Latin America than in the European Union. The uncertainty of CH 4 emission is lower than that for N 2 O and CO 2 . Livestock parameters, CH 4 emission factors and N emission factors contribute most to the uncertainty in the total model output. The reliability of GHG emissions from livestock sectors is relatively high (low uncertainty) at continental level, but could be lower at country level.

High-resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector

“…These uncertainties are greater than estimated, e.g. by Zhu et al (2016), who estimated the methane emission uncertainty for EU-27 to be 16-19%, but our results are for small territories, so less statistical averaging occurs.…”

“…Following the IPCC (2001) recommendations, uncertainties of the compiled emissions have been assessed in some papers. For example, Zhang et al (2014) and Zhu et al (2016) performed uncertainty calculations for rice paddies and livestock, respectively, applying the Monte Carlo method. Berdanier and Conant (2012) used data from 32 national emission inventories and a model for emission of N 2 O from soils to estimate regional model parameter distributions using the Bayesian Markov Chain Monte Carlo method to compute emission distributions.…”

Towards improving the manure management chain

“…Uncertainty analysis was carried out to achieve insight in how variation in the key parameters in the model affected the results, using a Monte Carlo (MC) based method (Zhu et al, 2015). Six groups of parameter were included in this analysis: i) animal numbers, ii) parameters related to nutrient excretion, iii) parameters used to quantify emissions from housing and manure storages (e.g.…”

“…Fraction of N in biochar, as % of N input a range 5-40% f biochar_p 99% Fraction of P in biochar, as % of P input a range of 97-100% was reported EF applic_biochar _ NH3 1% NH 3 EFs during application of biochar (Kookana et al, 2011;Cayuela et al, 2014) EF applic_biochar_N2O 0.5% N 2 O EFs from application of biochar (Pardo et al, 2015) Re compost_N2O N 2 O reduction factor, composting EFT normal 0.79 1 (Pardo et al, 2015) Re compost_CH4 CH 4 reduction factor, composting EFT normal 0.5 1 (Pardo et al, 2015) f biochar_C&N&P Nutrient fractions remained in biochar EFT normal 0.25 1 This study EF applic_slurry/solid/compost(etc. )_NH3 NH 3 EFs for applied manure products EFA normal 0.25 0.8 (Zhu et al, 2015) EF graz_slurry_NH3 NH 3 EFs from excreta of gazing animal EFA normal 0.25 0.8 (Zhu et al, 2015) Re applic_LF/acid NH 3 reduction factors, applied (separated) liquid fraction and acidified slurry EFA normal 0.5 1 EF applic_slurry//compost(etc. )__N2O N 2 O EFs for applied manure products EFA Lognormal 0.28 0.5 (Zhu et al, 2015) Re applic_dig/sep.SF(etc.…”

“…)_NH3 NH 3 EFs for applied manure products EFA normal 0.25 0.8 (Zhu et al, 2015) EF graz_slurry_NH3 NH 3 EFs from excreta of gazing animal EFA normal 0.25 0.8 (Zhu et al, 2015) Re applic_LF/acid NH 3 reduction factors, applied (separated) liquid fraction and acidified slurry EFA normal 0.5 1 EF applic_slurry//compost(etc. )__N2O N 2 O EFs for applied manure products EFA Lognormal 0.28 0.5 (Zhu et al, 2015) Re applic_dig/sep.SF(etc. )_N2O N 2 O reduction factors, applied treated manure EFA normal 0.49 1 EF graz_slurry_N2O N 2 O EFs from excreta of gazing animal EFA Lognormal 0.57 0.5 (Zhu et al, 2015) a The uncertainty analysis was performed according to the methodology described by Zhu et al (2015) who analyzed the uncertainty of the MITERRA model for global animal production; the uncertainties (CV or SD) were also mainly derived from Zhu et al (2015), and other meta-analysis studies Miranda et al, 2015;Pardo et al, 2015).…”