Rapid economic growth, urban sprawl, and unplanned industrialization has increased socioeconomic statuses but also decreased air quality in South Asian developing countries. Therefore, severe increase in air pollution has been a threat of local population, regarding health statuses, livability and quality of life. It is necessary to estimate fine-scale spatiotemporal distribution of ambient PM2.5 in a national context so that the environmental planners and government officials can use it for environmental protocol development and policy-making. In this study, a spatiotemporal land use regression (LUR) model is developed to refine global air quality data to the national-scale ambient PM2.5 exposure in a high-density country in South Asia - Pakistan. Combining with transport network, patterns of land use, local meteorological conditions, geographic characteristics, landscape characteristics, and satellite-derived data, our resultant model explains 54.5% of the variation in ambient PM2.5 concentration level. Furthermore, tree coverage and road transport are identified to be two influential factors of the national-scale spatial variation of PM2.5 in Pakistan, which implied that urbanization might be the major cause of air pollution across the country. In conclusion, our resultant LUR model as well as the spatial map of ambient PM2.5 concentration level can be used as a supporting tool for national health risk management and environmental planning, and could also contribute to the air quality management and pollution reduction actions of Pakistan.
Keywords: Exposure; Land use regression; PM(2.5); Pakistan; Urbanization.
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