Accidental benzene release risk assessment in an urban area using an atmospheric dispersion model

This study applied the American Meteorological Society and Environmental Protection Agency Regulatory Model (AERMOD) to assess the risk caused by an accidental release and dispersion of the toxic chemical benzene in the vicinity of a highly populated urban area. The modeling domain encompasses the Korean megacity of Ulsan, which includes two national industrial complexes and is characterized by a complex coastal terrain. Multiple AERMOD simulations were conducted for an assumed emission scenario using background wind data from August between 2009 and 2013. The series of experiments produced the spatial accident probability patterns for different concentration levels during daytime and nighttime scenarios based on the corresponding dominant wind patterns. This study further quantifies the potential accident risk based on the number of affected individuals by combining the accident probability with the indoor and outdoor population estimates. The chemical gas dispersion characteristics depend on various local meteorological conditions, such as the land-sea breeze direction, which alternates between daytime and nighttime, and the atmospheric stability. The results reveal that benzene dispersion affects a much larger area during the nighttime owing to the presence of a nocturnal stable boundary layer with significant temperature stratification. The affected area is smaller during the daytime owing to decreased stability and enhanced vertical mixing in the boundary layer. The results include a high degree of uncertainty during the nighttime owing to weak wind speeds and the lack of a prevailing wind direction, which impact the vulnerable area. However, vulnerable areas are more effectively identified during the daytime, when more consistent meteorological conditions exist. However, the potential risk becomes much lower during the nighttime owing to a substantial reduction of the outdoor population.ope

Impact of Urbanization on Local Air Quality: Differences in Urban and Rural Areas of Balikesir, Turkey

Ozone (O-3) is a secondary pollutant which is produced photo-chemically by reactions involving NOx and benzene, toluene, ethylbenzene, and m-, p-xylenes (BTEX) in the presence of sunlight. The present study determined outdoor air quality in both the urban area of Balikesir City and rural area (around Ikizcetepeler Dam) in the same region in the western part of Turkey. The main objectives of this study were to analyze the temporal evolution and qualify the spatial distribution by using geostatistical techniques; to determine the spatial variability of air pollutants using the spatial auto-correlation statistic; and to identify the local spatial patterns of the pollutants in order to highlight the areas of potential risk of O-3, NO2, and BTEX pollution and its possible causes. For this purpose firstly, the data were compiled by using passive sampling in winter and in summer. Concentrations of O-3 ranged from 14.03 to 42.43g/m(3) in winter and from 81.79 to 70.39g/m(3) in summer in urban area. The mean NO2 and BTEX concentrations varied between sites, while mean winter concentrations were higher than the mean in summer. During winter seasons, the motorway, residential areas, urban traffic, and industrial sites showed high BTEX levels compared to the suburban and rural sites. This paper investigates the spatial mapping of temporal trends in air quality for both urban and rural areas for annual, summer and winter means. The global Moran's I result demonstrated that O-3, NO2, and BTEX had significant positive global spatial correlations. In addition, the results of local spatial auto-correlation analysis showed the locations of significant high-high spatial clusters and low-low spatial outliers.TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [108Y166]We would like to expresses our sincere gratitude to TUBITAK for their financial support of this current work (project # 108Y166). We also thank to Tuncay Dogeroglu and Ozlem Ozden for their useful suggestions and data analysis