PM2.5 Estimation with the WRF/Chem Model,Produced by Vehicular Flow in the Lima Metropolitan Area
作者机构：School of SciencesUniversidad Nacional Agraria La Molina(UNALM)LimaPeru School of Chemical Engineering and Textile(FIQT)Universidad Nacional de Ingeniería(UNI)RímacLimaPeru School of Environmental EngineeringUniversidad Nacional Tecnológica deLimaSur(UNTELS)Villa El SalvadorLimaPeru Department of Atmospheric Sciences at the Institute of AstronomyGeophysics and Atmospheric Sciences(IAG)University of Sao PauloSao PauloBrazil Centro Meteorológico Provincial Santa ClaraCuba Instituto Geofísico del Peru(IGP)Calle Badajoz N°169 Urb.Mayorazgo IV Etapa AteLimaPeru
出 版 物：《Open Journal of Air Pollution》 (大气污染开放期刊（英文）)
年 卷 期：2018年第7卷第3期
页 面：215-243页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Air Quality Aerosol WRF/Chem Model PM2.5 Lima-Peru
摘 要：Lima is the capital of the Republic of Peru. It is the most important city in the country and as other Latin America metropolises have multiple problems, including air pollution due to particulate material above air quality standards, emitted by 1.6 million vehicles. The “on-line coupled model of meteorology and chemistry of transport and meteorological/chemistry, WRF/Chem (Weather and Research Forecasting with Chemistry) has been used in the Lima Metropolitan Area, and validated against data observed at ground level with ten air quality stations of the National Service of Meteorology and Hydrology for the year 2016. The goal of this study was to estimate the concentration of PM2.5 particulate matter in the months of February and July of 2016. In both months, the model satisfactorily predicts temperature and relative humidity. The average observed PM2.5 concentrations in the month of July are higher than in February, probably because the relative humidity in July is greater than the relative humidity in February. In the months of February and July the standard observed deviations of the model have a factor of 2.4 and 3.7 respectively, indicating a greater dispersion in the data of the model. In the month of July, the model captures the characteristics of transport, shows characteristic peaks during peak hours, therefore, the model estimates transport behavior better in July than in February. The quality of the air is strongly influenced by the vehicular transport. The PM2.5 particulate material in February had an average bias that varied from [?13.2 to 4.4 μg/m3] and in July [?9.63 to 11.65 μg/m3] and a normalized average bias in February that varied from [?0.68 to 0.43] and in July of [?0.46 to 0.48].
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