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

Abstract

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 (NOx) to develop a land use regression (LUR) model to explain the spatial variation of air pollution concentrations in this area. METHODS: Ambient NOx 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 NOx exposure of a sample of pregnant women living in South Durban. RESULTS: Measured NOx levels ranged from 22.3-50.9μg/m(3) with a median of 36μg/m(3). The model developed accounts for 73% of the variance in ambient NOx measurements using three input variables (length of minor roads within a 1000m radius, length of major roads within a 300m radius, and area of open space within a 1000m radius). Model cross validation yielded a R(2) of 0.59. Subsequent participant exposure estimates indicated exposure to ambient NOx ranged from 19.9-53.2μg/m(3), with a mean of 39μg/m(3). DISCUSSION AND CONCLUSION: This is the first study to develop a land use regression model that predicts ambient concentrations of NOx in a South African context. The findings of this study indicate that the participants in the South Durban are exposed to high levels of NOx that can be attributed mainly to traffic.