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Urbanization and regional air pollution across South Asian developing countries – A nationwide land use regression for ambient PM2.5 assessment in Pakistan

  • Yuan Shi
  • , Muhammad Bilal*
  • , Hung Chak Ho
  • , Abid Omar
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

107 Scopus citations

Abstract

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.

Original languageEnglish
Article number115145
JournalEnvironmental Pollution
Volume266
DOIs
StatePublished - Nov 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Ltd

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  3. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Exposure
  • Land use regression
  • PM
  • Pakistan
  • Urbanization

ASJC Scopus subject areas

  • Toxicology
  • Pollution
  • Health, Toxicology and Mutagenesis

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