title: PM2.5 Population Exposure in New Delhi Using a Probabilistic Simulation Framework.
abstract: This paper presents a Geographical Information System (GIS) based probabilistic simulation framework to estimate PM2.5 population exposure in New Delhi, India. The framework integrates PM2.5 output from spatiotemporal LUR models and trip distribution data using a Gravity model based on zonal data for population, employment and enrollment in educational institutions. Time-activity patterns were derived from a survey of randomly sampled individuals (n = 1012) and in-vehicle exposure was estimated using microenvironmental monitoring data based on field measurements. We simulated population exposure for three different scenarios to capture stay-at-home populations (Scenario 1), working population exposed to near-road concentrations during commutes (Scenario 2), and the working population exposed to on-road concentrations during commutes (Scenario 3). Simulated annual average levels of PM2.5 exposure across the entire city were very high, and particularly severe in the winter months: ∼200 μg m(-3) in November, roughly four times higher compared to the lower levels in the monsoon season. Mean annual exposures ranged from 109 μg m(-3) (IQR: 97-120 μg m(-3)) for Scenario 1, to 121 μg m(-3) (IQR: 110-131 μg m(-3)), and 125 μg m(-3) (IQR: 114-136 μ gm(-3)) for Scenarios 2 and 3 respectively. Ignoring the effects of mobility causes the average annual PM2.5 population exposure to be underestimated by only 11%.
authors.affiliation: Institute for Resources Environment and Sustainability, The University of British Columbia , Rm 411, 2202 Main Mall, Vancouver, BC V6T 4T1, Canada.
authors.forename: Arvind
authors.initials: A
authors.lastname: Saraswat
authors.affiliation: Liu Institute for Global Issues & Institute for Resources Environment and Sustainability, The University of British Columbia , Room 101B, 6476 NW Marine Drive, Vancouver, BC V6T 1Z2, Canada.
authors.forename: Milind
authors.initials: M
authors.lastname: Kandlikar
authors.affiliation: School of Population and Public Health, Faculty of Medicine, The University of British Columbia , Vancouver, BC V6T 4T1, Canada.
authors.forename: Michael
authors.initials: M
authors.lastname: Brauer
authors.affiliation: School of Environmental Sciences, Jawahar Lal Nehru University , New Delhi 110067, India.
authors.forename: Arun
authors.initials: A
authors.lastname: Srivastava
mesh_terms: D000393:Air Pollutants / Q000009:adverse effects / Q000032:analysis*; D002947:Cities; D004781:Environmental Exposure / Q000009:adverse effects / Q000032:analysis*; D004784:Environmental Monitoring; D040362:Geographic Information Systems; D006801:Humans; D007194:India; D015233:Models, Statistical; D052638:Particulate Matter / Q000009:adverse effects / Q000032:analysis*; D012621:Seasons
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter