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

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.

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.

Measured NO_x levels ranged from 22.3-50.9μg/m³ with a median of 36μg/m³. The model developed accounts for 73% of the variance in ambient NO_x 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 R² of 0.59. Subsequent participant exposure estimates indicated exposure to ambient NO_x ranged from 19.9-53.2μg/m³, with a mean of 39μg/m³.

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.