Regional scale modelling of particulate matter in the UK,source attribution and an assessment of uncertainties |
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| Institution: | 1. Department of Geography, Lancaster University, Lancaster LA1 4YB, UK;2. School of Geography, University of Nottingham, Nottingham NG7 2RD, UK;3. School of Geosciences, University of Edinburgh, Edinburgh EH8 9XP, UK;4. rdscientific, Newbury RG14 6LH, UK;5. netcen, AEA Technology Environment, Harwell OX11 0QJ, UK;1. Department of Environmental Science and Engineering, Beijing University of Technology, Beijing 100124, China;2. State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China;1. Department of Marine Environmental Informatics, National Taiwan Ocean University, #2 Peining Road, Keelung 202, Taiwan;2. Department of Atmospheric Physics, National Central University, Taiwan;1. Department of Chemical and Material Engineering, Kanazawa University, Kakuma, Kanazawa 920-1192, Japan;2. Center for Regional Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba 305-8506, Japan;3. Global Environment Study Group, National Institute of Advanced Industrial Science and Technology, 16-1 Onogawa, Tsukuba 305-8568, Japan;4. Department of Applied Science and Engineering, Muroran Institute of Technology, 27-1 Mizumoto-cho, Muroran 050-8585, Japan;5. Department of Chemical Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8527, Japan;6. Center for Environmental Remote Sensing (CEReS), Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan;7. Institute of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwaicho, Fuchu, Tokyo 183-8509, Japan;1. Key Laboratory of Resource Exploration Research of Hebei Province, Hebei University of Engineering, Handan 056038, Heibei, China;2. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083, China;3. State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China;4. Faculty of Environmental and Symbiotic Sciences, Prefectural University of Kumamoto, Kumamoto 862-8502, Japan |
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| Abstract: | The models HARM and ELMO are used to investigate the importance of different source categories contributing to total PM10 (SIA, SOA and primary particulate matter) across the UK and the impact of uncertainties on both present day and future concentration estimates. Modelled concentrations of SIA (secondary inorganic aerosol) are compared against data from the UK's Nitric Acid and Aerosol Network and SOA (secondary organic aerosol) against measurements made at the Bush Estate, Edinburgh. These data indicate that the HARM/ELMO modelling approach comes close to achieving mass closure. Comparison with national maps of total PM10 indicate that the models underestimate particulate matter concentrations around large conurbations, probably due to the localised nature of emissions of primary particulates in these areas and model scale. The models are used to attribute particulate matter to different source and size categories, assessing the relative importance of primaries, SIA and SOA; the contributions of anthropogenic and biogenic precursors of SOA; the relative importance of PMcoarse (PM10–PM2.5) and PMfine (PM2.5) and UK vs. other EMEP area sources. The implications of these attributions for emissions control policies are discussed. The impact of uncertainties in emissions of the sources of primaries, SIA and SOA are explored. For primary PM10 and SOA this has been achieved through emissions scaling and for SIA using the GLUE (Generalised Likelihood Uncertainty Estimation) approach. The selection of acceptable model parameter sets has been based on the need to retain the capability to model deposition of S and N species. The impact of uncertainty on estimates of present day SIA concentrations is illustrated for sites in the Nitric Acid and Aerosol Network. A more limited assessment for 2010 has been carried out at the national scale, illustrating that inclusion of uncertainty can change modelled concentrations from no exceedance of current air quality objectives, to one of exceedance over large areas of south and east England. |
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