A hybrid air pollution / land use regression model for predicting air pollution concentrations in Durban, South Africa

The objective of this paper was to incorporate source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter (PM10). The study was undertaken across two regions in Durban, South Africa, one with a high industrial profile and a nearby harbour, and the other with a primarily commercial and residential profile. Multiple hybrid models were developed by integrating air pollution dispersion modelling predictions for source specific NO2, SO2, and PM10 concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban. Industrial point sources, ship emissions, domestic fuel burning, and vehicle emissions were key emission sources. Standard linear regression was used to develop annual, summer and winter hybrid models to predict air pollutant concentrations. Higher levels of NO2 and SO2 were predicted in south Durban as compared to north Durban as these are industrial related pollutants. Slightly higher levels of PM10 were predicted in north Durban as compared to south Durban and can be attributed to either traffic, bush burning or domestic fuel burning. The hybrid NO2 models for annual, summer and winter explained 60%, 58% and 63%, respectively, of the variance with traffic, population and harbour being identified as important predictors. The SO2 models were less robust with lower R(2) annual (44%), summer (53%) and winter (46%), in which industrial and traffic variables emerged as important predictors. The R(2) for PM10 models ranged from 80% to 85% with population and urban land use type emerging as predictor variables

Effect of short-term exposure to ambient nitrogen dioxide and particulate matter on repeated lung function measures in infancy: a South African birth cohort

BACKGROUND: The developing lung is highly susceptible to environmental toxicants, with both short- and long-term exposure to ambient air pollutants linked to early childhood effects. This study assessed the short-term exposure effects of nitrogen dioxide (NO2) and particulate matter (PM10) on lung function in infants aged 6 weeks, 6, 12 and 24 months, the early developmental phase of child growth. METHODS: Lung function was determined by multiple breath washout and tidal breathing measurement in non-sedated infants. Individual exposure to NO2 and PM10 was determined by hybrid land use regression and dispersion modelling, with two-week average estimates (preceding the test date). Linear mixed models were used to adjust for the repeated measures design and an age*exposure interaction was introduced to obtain effect estimates for each age group. RESULTS: There were 165 infants that had lung function testing, with 82 of them having more than one test occasion. Exposure to PM10 (mug/m(3)) resulted in a decline in tidal volume at 6 weeks [-0.4 ml (-0.9; 0.0), p = 0.065], 6 months [-0.5 ml (-1.0; 0.0), p = 0.046] and 12 months [-0.3 ml (-0.7; 0.0), p = 0.045]. PM10 was related to an increase in respiratory rate and minute ventilation, while a decline was observed for functional residual capacity for the same age groups, though not statistically significant for these outcomes. Such associations were however less evident for exposure to NO2, with inconsistent changes observed across measurement parameters and age groups. CONCLUSION: Our study suggests that PM10 results in acute lung function impairments among infants from a low-socioeconomic setting, while the association with NO2 is less convincing