الصين والهند تدفعان أعلى ثمن لتلوث الجسيمات الدقيقة
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الصين والهند تدفعان أعلى ثمن لتلوث الجسيمات الدقيقة
Read the full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=49591 DOI: 10.4236/ojap.2014.33008 Author(s) Raúl Arasa, Antonio Lozano-García, Bernat Codina Affiliation(s) Air Quality Department, Meteosim S.L., Barcelona, Spain. Environment and Water Agency of Andalusia, Seville, Spain. Air Quality Department, Meteosim S.L., Barcelona, Spain & Department of Astronomy and Meteorology, Barcelona, Spain. ABSTRACT In this contribution, we present an evaluation of different mitigation plans to improve NO2 levels in Andalusia, a region in the south of Spain. Specifically, we consider four possible mitigation plans: the effects over NO2 concentration of apply changes in the distribution of Vehicles Park; the effect of realize traffic restrictions (affecting to the density flow of vehicles) over highways and main roads; the effect of replacement of diesel use by natural gas in urban areas; and the effect of applying new velocity limits to access to urban areas. A sophisticated air quality modelling (AQM) system has been used to evaluate these mitigation plans. AQM implemented is composed on WRF meteorological model, an emission model created by the authors and CMAQ photochemical model. AQM analyzes mitigation plans during fifteen episodes of 2011 where NO2 levels were the highest of the year; so we analyze the effect of mitigation plans in worst conditions. Results provided by the AQM system show that: 1-h maximum daily NO2 is reduced to 10μg.m-3 near circulation roads when traffic restrictions and velocity limits plans are applied (NOx emissions are reduced in 9% - 15%); 1-h maximum daily NO2 is reduced to 12 μg.m-3 affecting all municipalities when changes in the distribution of Vehicles Park are applied (NOx emissions are reduced in 25% - 26%); and the replacement of fuel of urban buses does not affect considerably NO2 levels.gjreww140915 KEYWORDS CMAQ, Air Quality Modelling, Environmental Assessment