Land use Regression Model for Exposure Assessment in the Mace Birth Cohort Study in Ethekwini

Abstract

OPS 46: Exposure assessment to air pollution in Asia and Africa, Room 315, Floor 3, August 27, 2019, 4:30 PM - 5:30 PM Background: The Mother and Child in the Environment (MACE) birth cohort aims to determine the effects of ambient air pollution on pregnancy outcomes and childhood respiratory disorders in Durban, South Africa. A land use regression model (LUR) was developed to characterise exposure. Methods: Based on the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology, particulate matter (PM10 and PM2.5), sulphur dioxide (SO2), and nitrogen dioxide (NO2) were measured over a period of one year, at 41 sites, with Ogawa Badges and 21 sites with PM Monitors. Results: Air pollution concentrations showed a clear seasonal trend with higher concentrations being measured during winter (25.75 µg/m3, 4.18 µg/m3, 50.44 µg/m3, and 20.90 µg/m3 for NO2, SO2, PM10 and PM2.5 respectively) as compared to summer (10.51 µg/m3, 2.8 µg/m3, 20.49 µg/m3, and 8.49 µg/m3 for NO2, SO2, PM10 and PM2.5 respectively). The LUR NO2 models for annual, summer and winter explained 73%, 60% and 59% of the variance with elevation, traffic, population, open space and a regional variable being identified as important predictors. The SO2 models were less robust with lower R2 annual (37%), summer (49%) and winter (33%) with industrial and traffic variables being important predictors. The R2 for PM10 models ranged from 59-66% while for PM2.5 models this range was 62%-73% with only total length of major roads emerging as a predictor. Variables such as urban area and length of minor roads remained statistically insignificant in each model. Conclusion: These results highlight the influence of industrial and traffic emissions from major roads on air pollution concentrations. Furthermore, this is the first study in South Africa highlighting the importance of a regional variable serving as a proxy marker for industry, as areas of higher industrial activity are geographically grouped within the city.