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Multi-gas and multi-source comparisons of six land use emission datasets and AFOLU estimates in the Fifth Assessment Report, for the tropics for 2000-2005

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  • Rosa Maria Roman-Cuesta
  • Martin Herold
  • Mariana C. Rufino
  • Todd S. Rosenstock
  • Richard A. Houghton
  • Simone Rossi
  • Klaus Butterbach-Bahl
  • Stephen Ogle
  • Benjamin Poulter
  • Louis Verchot
  • Christopher Martius
  • Sytze De Bruin
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<mark>Journal publication date</mark>24/10/2016
<mark>Journal</mark>Biogeosciences
Issue number20
Volume13
Number of pages21
Pages (from-to)5799-5819
Publication StatusPublished
<mark>Original language</mark>English

Abstract

The Agriculture, Forestry and Other Land Use (AFOLU) sector contributes with ca. 20-25% of global anthropogenic emissions (2010), making it a key component of any climate change mitigation strategy. AFOLU estimates, however, remain highly uncertain, jeopardizing the mitigation effectiveness of this sector. Comparisons of global AFOLU emissions have shown divergences of up to 25%, urging for improved understanding of the reasons behind these differences. Here we compare a variety of AFOLU emission datasets and estimates given in the Fifth Assessment Report for the tropics (2000-2005) to identify plausible explanations for the differences in (i) aggregated gross AFOLU emissions, and (ii) disaggregated emissions by sources and gases (CO2, CH4, N2O). We also aim to (iii) identify countries with low agreement among AFOLU datasets to navigate research efforts. The datasets are FAOSTAT (Food and Agriculture Organization of the United Nations, Statistics Division), EDGAR (Emissions Database for Global Atmospheric Research), the newly developed AFOLU "Hotspots", "Houghton", "Baccini", and EPA (US Environmental Protection Agency) datasets. Aggregated gross emissions were similar for all databases for the AFOLU sector: 8.2 (5.5-12.2), 8.4, and 8.0PgCO2 eq.yr1 (for Hotspots, FAOSTAT, and EDGAR respectively), forests reached 6.0 (3.8-10), 5.9, 5.9, and 5.4PgCO2 eq.yr1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and agricultural sectors were with 1.9 (1.5-2.5), 2.5, 2.1, and 2.0PgCO2 eq.yr1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating the emissions by sources, continents, and gases, particularly for the forest sector, with fire leading the differences. Agricultural emissions were more homogeneous, especially from livestock, while those from croplands were the most diverse. CO2 showed the largest differences among the datasets. Cropland soils and enteric fermentation led to the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (carbon-only vs. multi-gas assessments, definitions, land use vs. land cover, etc.), in methods (tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc.) and in assumptions (carbon neutrality of certain emissions, instantaneous emissions release, etc.) which call for more complete and transparent documentation for all the available datasets. An enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.