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Baró, R., Jiménez, P., Balzarini, A., Curci, G., Forkel, R., Grell, G., Hirtl, M., Honzak, L., Langer, M., Pérez, J., Pirovano, G., San José, R., Tuccella, P., Werhahn, J. and Zabkar, R. (2015) Sensitivity Analysis of the Microphysics Scheme in WRF-Chem Contributions to AQMEII Phase 2. Atmospheric Environment, 115, 620-629. https://doi.org/10.1016/j.atmosenv.2015.01.047

has been cited by the following article:

• TITLE: PM2.5 Estimation with the WRF/Chem Model, Produced by Vehicular Flow in the Lima Metropolitan Area

  AUTHORS: Warren Reátegui-Romero, Odón R. Sánchez-Ccoyllo, María de Fatima Andrade, Aldo Moya-Alvarez

  KEYWORDS: Air Quality, Aerosol, WRF/Chem Model, PM2.5, Lima-Peru

  JOURNAL NAME: Open Journal of Air Pollution, Vol.7 No.3, August 21, 2018

  ABSTRACT: 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].