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Refining emission rate estimates using a coupled receptor–dispersion modeling approach |
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| Authors: | N Selvaraju S Pushpavanam |
| Institution: | 1. SCK?CEN, Belgian Nuclear Research Centre, Boeretang 200, BE-2400 Mol, Belgium;2. Department of Mechanical Engineering, KU Leuven, Celestijnenlaan 300, BE-3000 Leuven, Belgium;1. LMEE, Universite d''Evry-Val d''Essonne, 40 Rue Du Pelvoux, 91080 Courcouronnes, France;2. Centre for Atmospheric Sciences, IIT Delhi, Hauz Khas, New Delhi 110016, India;1. Ovidius University of Constanta, 124 Mamaia Blvd., Constanta, Romania;2. Higher Colleges of Technology, University City, P.O. Box 7947, Sharjah, United Arab Emirates;1. Department of Mechanical Engineering, COPPE, Federal University of Rio de Janeiro, Centro de Tecnologia, Bloco G, Rio de Janeiro, RJ 21945-970, Brazil;2. Computational Nucleus for Air Quality Studies (NCQAr), Department of Meteorology, IGEO, Federal University of Rio de Janeiro, CCMN, Bloco H, Rio de Janeiro, RJ 21941-916, Brazil |
| Abstract: | Receptor modeling techniques like chemical mass balance are used to attribute pollution levels at a point to different sources. Here we analyze the composition of particulate matter and use the source profiles of sources prevalent in a region to estimate quantitative source contributions. In dispersion modeling on the other hand the emission rates of various sources together with meteorological conditions are used to determine the concentrations levels at a point or in a region. The predictions using these two approaches are often inconsistent. In this work these differences are attributed to errors in emission inventory. Here an algorithm for coupling receptor and dispersion models is proposed to reduce the differences of the two predictions and determine the emission rates accurately. The proposed combined approach helps reconcile the differences arising when the two approaches are used in a stand-alone mode. This work is based on assuming that the models are perfect and uses a model-to-model comparison to illustrate the concept. |
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