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

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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 CO2, CH4, and N2O 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 CH4 emission is lower than that for N2O and CO2. Livestock parameters, CH4 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.

Original languageEnglish
Pages (from-to)1571-1582
JournalRegional Environmental Change
Volume16
Issue number6
DOIs
Publication statusPublished - 2016

Keywords

  • CH
  • Global assessment modelling
  • Livestock
  • Monte Carlo simulation
  • NO
  • Uncertainty analysis

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