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Air pollution in New Delhi, India : spatial and temporal patterns of ambient concentrations and human exposure

University of British Columbia

Urban air pollution is a major health and environmental concern worldwide, and the levels are extremely high in New Delhi, India. This research is focused on the spatial and temporal variability of air pollutant concentrations and its implications for population exposure in New Delhi. Since traffic is considered a significant source of air pollutants in urban environments, robust and multiple linear regression models were used to understand the impact of local traffic flow on ambient concentrations of PM₂.₅, CO, NO and NO₂ at a busy intersection. To elicit the spatiotemporal variability of PM₂.₅ and its constituents (black carbon and ultrafine particles), land use regression (LUR) models were developed. Separate morning and afternoon models were developed using 136 hours (39 sites), 112 hours (26 sites) and 147 hours (39 sites) of PM₂.₅, BC and UFPN data, respectively. Finally, to understand how spatiotemporal variations in PM₂.₅ concentrations impact population exposure, a probabilistic simulation framework was developed to integrate the PM₂.₅ LUR models with time-activity data obtained from a field survey. Regression models explained about 50–80% variability in hourly pollutant concentrations and localized traffic flow explained up to 19% of variability on that scale. Auto-rickshaw and truck flow had a higher influence on NO₂ and PM₂.₅ concentrations, respectively. Independent variables in the LUR models included population density, distance from major roads, and major and minor road lengths in buffers of different radii; measurements from a fixed continuous monitoring site were also used as independent variables in the PM₂.₅ and BC models. The temporal term explained most of the variability (63–77%) in PM₂.₅ and BC models compared to spatial variables (4–16%). Exposure simulations indicate that the estimated annual average PM₂.₅ exposure (109 µg m-³) was high compared to North American or European cities. PM₂.₅ exposures were highest during the winter months (~200 µg m-³) compared to the summer months (~50 µg m-³). Ignoring mobility (i.e. exposure during transport or at work/school locations), as is generally assumed in epidemiologic studies of long-term exposure, underestimated PM₂.₅ population exposure by about 11%.

Text

2016-01-06

Attribution-NonCommercial-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/56224

Resource Management and Environmental Studies

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/