Global anthropogenic CO<sub>2</sub> emissions and uncertainties as prior for Earth system modelling and data assimilation

环境科学 温室气体 气候变化 气象学 排放清单 地球系统科学 大气科学 地理 空气质量指数 生态学 地质学 生物
作者
Margarita Choulga,Greet Janssens‐Maenhout,Ingrid Super,Anna Agustí‐Panareda,Gianpaolo Balsamo,Nicolas Bousserez,Monica Crippa,Hugo Denier van der Gon,Richard Engelen,Diego Guizzardi,Jeroen Kuenen,Joe McNorton,Gabriel Oreggioni,Efisio Solazzo,Antoon Visschedijk
标识
DOI:10.5194/essd-2020-68
摘要

Abstract. Anthropogenic carbon dioxide (CO2) emissions and their observed growing trends raise awareness in scientific, political and public sectors of the society as the major driver of climate-change. For an increased understanding of the CO2 emission sources, patterns and trends, a link between the emission inventories and observed CO2 concentrations is best established via Earth system modelling and data assimilation. In this study anthropogenic CO2 emission inventories are processed into gridded maps to provide an estimate of prior CO2 emissions for 7 main emissions groups: 1) power generation super-emitters and 2) energy production average-emitters, 3) manufacturing, 4) settlements, 5) aviation, 6) transport and 7) others, with estimation of their uncertainty and covariance to be included in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). The emission inventories are sourced from the Intergovernmental Panel on Climate Change (IPCC) 2006 Guidelines for National Greenhouse Gas Inventories and revised information from its 2019 Refinements, and the global grid-maps of Emissions Database for Global Atmospheric Research (EDGAR) inventory. The anthropogenic CO2 emissions for 2012 and 2015, (EDGAR versions 4.3.2 and 4.3.2_FT2015 respectively) are considered, updated with improved apportionment of the energy sector, energy usage for manufacturing and diffusive CO2 emissions from coal mines. These emissions aggregated into 7 ECMWF groups with their emission uncertainties are calculated per country considering its statistical infrastructure development level and sector considering the most typical fuel type and use the IPCC recommended error propagation method assuming fully uncorrelated emissions to generate covariance matrices of parsimonious dimension (7×7). While the uncertainty of most groups remains relatively small, the largest contribution to the total uncertainty is determined by the group with usually the smallest budget, consisting of oil refineries and transformation industry, fuel exploitation, coal production, agricultural soils and solvents and products use emissions. Several sensitivity studies are performed: for country type (with well-/less well-developed statistical infrastructure), for fuel type specification, and for national emission source distribution (highlights the importance of 30 accurate point source mapping). Uncertainties are compared with United Nations Framework Convention on Climate Change (UNFCCC) and the Netherlands Organisation for Applied Scientific Research (TNO) data. Upgraded anthropogenic CO2 emission maps with their yearly and monthly uncertainties are combined into the CHE_EDGAR-ECMWF_2015 dataset (Choulga et al., 2020) available from https://doi.org/10.5281/zenodo.3712339.

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