Use of Simulated and Observed Meteorology for Air Quality Modeling and Source Ranking for an Industrial Region

Abstract

The Gaussian-based dispersion model American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) is being used to predict concentration for air quality management in several countries. A study was conducted for an industrial area, Chembur of Mumbai city in India, to assess the agreement of observed surface meteorology and weather research and forecasting (WRF) output through AERMOD with ground-level NOx and PM10 concentrations. The model was run with both meteorology and emission inventory. When results were compared, it was observed that the air quality predictions were better with the use of WRF output data for a model run than with the observed meteorological data. This study showed that the onsite meteorological data can be generated by WRF which saves resources and time, and it could be a good option in low-middle income countries (LIMC) where meteorological stations are not available. Also, this study quantifies the source contribution in the ambient air quality for the region. NOx and PM10 emission loads were always observed to be high from the industries but NOx concentration was high from vehicular sources and PM10 concentration was high from industrial sources in ambient concentration. This methodology can help the regulatory authorities to develop control strategies for air quality management in LIMC.