Land use regression modelling estimating nitrogen oxides exposure in industrial south Durban, South Africa.

Background The South Durban (SD) area of Durban, South Africa, has a history of air pollution issues due to the juxtaposition of low-income communities with industrial areas. This study used measurements of oxides of nitrogen (NO x ) to develop a land use regression (LUR) model to explain the spatial variation of air pollution concentrations in this area. Methods Ambient NO x was measured over two two-week sampling periods at 32 sites using Ogawa badges. Following the ESCAPE approach, an annual adjusted average was calculated for these results and regressed against pre-selected geographic predictor variables in a multivariate regression model. The LUR model was then applied to predict the NO x exposure of a sample of pregnant women living in South Durban. Results Measured NO x levels ranged from 22.3–50.9 μg/m 3 with a median of 36 μg/m 3 . The model developed accounts for 73% of the variance in ambient NO x measurements using three input variables (length of minor roads within a 1000 m radius, length of major roads within a 300 m radius, and area of open space within a 1000 m radius). Model cross validation yielded a R 2 of 0.59. Subsequent participant exposure estimates indicated exposure to ambient NO x ranged from 19.9–53.2 μg/m 3 , with a mean of 39 μg/m 3 . Discussion and Conclusion This is the first study to develop a land use regression model that predicts ambient concentrations of NO x in a South African context. The findings of this study indicate that the participants in the South Durban are exposed to high levels of NO x that can be attributed mainly to traffic. [ABSTRACT FROM AUTHOR]