Spatial surrogates for the disaggregation of CORINAIR emission inventories |
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| Authors: | Joachim Maes Jo Vliegen Karen Van de Vel Stijn Janssen Felix Deutsch Koen De Ridder Clemens Mensink |
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| Institution: | 1. UBC James Hogg Research Centre, Institute for Heart + Lung Health, St. Paul''s Hospital, The University of British Columbia, Vancouver, BC;2. Department of Anesthesiology, Pharmacology and Therapeutics, The University of British Columbia, Vancouver, BC;3. Environmental Health, Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada;1. Department of Industrial Engineering, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy;2. Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Naples, Italy;3. Centro Interdipartimentale di Ricerca “Ambiente” (CIRAM), University of Naples Federico II, Via Mezzocannone 16, 80134 Naples, Italy;4. Department of Life Science, University of Trieste, Via L. Giorgieri 10, 34127 Trieste, Italy;5. Department of Biology, University of Naples Federico II, Monte S. Angelo Campus, Via Cinthia 4, 80126 Naples, Italy |
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| Abstract: | CORINAIR atmospheric emission inventories are frequently used input data for air quality models with a domain situated in Europe. In CORINAIR emission inventories, sources are broken down over 11 major source categories. This paper presents spatial surrogates for the disaggregation of CORINAIR atmospheric emission inventories for input of air pollutants and particulate matter to grid or polygon based air quality model domains inside Europe. The basis for the disaggregation model was the CLC2000 land cover data to which statistical weights were added. Weights were population census data for residential emissions, employment statistics for agricultural and industrial area emissions, livestock statistics for ammonia emissions and annual aircraft movements for emissions realized by air transport. Additional road and off-road network information was used to disaggregate emissions realized by traffic. A comparison of top down produced emission estimates with spatially resolved national emission data for The Netherlands and the United Kingdom gave confidence in the present spatial surrogates as a tool for the top down production of atmospheric emission maps. Explained variance at a spatial resolution of 5 km was >70% for CO, NMVOC and NOx, >60% for PM10 and almost 50% for SO2. |
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