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

• DOI: 10.1007/s11027-017-9779-3
• Publication Date: 2018-01-11T15:57:26Z
• Authors: Nadiia Charkovska; Joanna Horabik-Pyzel; Rostyslav Bun; Olha Danylo; Zbigniew Nahorski; Matthias Jonas; Xu Xiangyang
• Keywords: Emission inventory; Agricultural land

Agricultural activity plays a significant role in the atmospheric carbon balance as source and sink of greenhouse gases (GHGs) has high mitigation potential. The agricultural emissions display evident geographical differences regional, national, even local levels, not only due to spatially differentiated activity, but also very geographically different emission coefficients. Thus, resolved inventories are important for obtaining better estimates content design GHG processes adapt global rise atmosphere. This study develops geoinformation approach high-resolution spatial inventory from sector, following categories United Nations Intergovernmental Panel on Climate Change guidelines. Using Corine Land Cover data, digital map sources is built, with elementary areal objects that split up by administrative boundaries. Various procedures developed disaggregation available data down level objects, conditional covariate information, such land use, observable object scale. Among them, statistical scaling method suitable correlated applied. As an example implementation this approach, distribution methane (CH4) Nitrogen Oxide (N2O) was obtained agriculture sector Poland resolution 100 m. We calculated specific total types animal manure systems well CO2-equivalent. demonstrated located highly nonuniformly them vary substantially, so average may provide insufficient approximation. In our case, over 11% smaller estimated using compared national report where were used. addition, we quantified uncertainties associated analysed dominant components sector. used lowest possible (municipal) level. depth these arable lands minimal, hence, relative uncertainty when comparing traditional gridded emissions. proposed technique allows us discuss factors driving be particularly useful modelling dispersion