Land Use Regression Models for Alkylbenzenes in a Middle Eastern Megacity: Tehran Study of Exposure Prediction for Environmental Health Research (Tehran Sepehr) Publisher Pubmed



Amini H^{1, 2} ; Schindler C^{1, 2} ; Hosseini V³ ; Yunesian M⁴ ; Kunzli N^{1, 2}
Source: Environmental Science and Technology Published:2017

Abstract

Land use regression (LUR) has not been applied thus far to ambient alkylbenzenes in highly polluted megacities. We advanced LUR models for benzene, toluene, ethylbenzene, p-xylene, m-xylene, o-xylene (BTEX), and total BTEX using measurement based estimates of annual means at 179 sites in Tehran megacity, Iran. Overall, 520 predictors were evaluated, such as The Weather Research and Forecasting Model meteorology predictions, emission inventory, and several new others. The final models with R2 values ranging from 0.64 for p-xylene to 0.70 for benzene were mainly driven by traffic-related variables but the proximity to sewage treatment plants was present in all models indicating a major local source of alkylbenzenes not used in any previous study. We further found that large buffers are needed to explain annual mean concentrations of alkylbenzenes in complex situations of a megacity. About 83% of Tehran's surface had benzene concentrations above air quality standard of 5 μg/m3 set by European Union and Iranian Government. Toluene was the predominant alkylbenzene, and the most polluted area was the city center. Our analyses on differences between wealthier and poorer areas also showed somewhat higher concentrations for the latter. This is the largest LUR study to predict all BTEX species in a megacity. © 2017 American Chemical Society.