Differences in benzene patterns among traffic and industrial areas and a prediction model for benzene rates based on NO_x values

Exposure to benzene has been associated with multiple severe impacts on health. This notwithstanding, at most monitoring stations, benzene is not monitored on a regular basis. Data were used from two different monitoring stations located on the eastern Mediterranean coast: (1) a traffic monitoring station in Tel Aviv located in an urban region with heavy traffic and (2) a general air quality monitoring station in Haifa Bay located in Israel's main industrial region. At each station, hourly, daily, monthly, seasonal, and annual data of benzene, NO _x, mean temperature, relative humidity, inversion level, and temperature gradient were analyzed over 3 years: 2008, 2009, and 2010. A prediction model for benzene rates based on NO _x levels (which are monitored regularly) was developed to contribute to a better estimation of benzene. The severity of benzene pollution was found to be considerably higher at the traffic monitoring station than at the general air quality station, despite the location of the latter in an industrial area. Hourly, daily, monthly, seasonal, and annual patterns have been shown to coincide with anthropogenic activities (traffic), the day of the week, and atmospheric conditions. A strong correlation between NO _x and benzene allowed the development of a prediction model for benzene rates based on NO _x, the day of the week, and the month. The model succeeded in predicting the benzene values throughout the year. The prediction model suggested in this study might be useful for identifying potential risk of benzene in other urban environments.