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Characterization of five-year observation data of fine particulate matter in the metropolitan area of Lahore.

Fatima KhanumMuhammad Nawaz ChaudhryPrashant Kumar
Published in: Air quality, atmosphere, & health (2017)
This study aims to assess the long-term trend of fine particles (PM2.5; ≤2.5 μm) at two urban sites of Lahore during 2007-2011. These sites represent two distinct areas: commercial (Townhall) and residential cum industrial (Township). The highest daily mean concentrations of PM2.5 were noted as 389 and 354 μg m-3 at the Townhall and Township sites, respectively. As expected, the annual seasonal mean of PM2.5 was about 53 and 101% higher during winter compared with the summer and monsoon/post-monsoon seasons, respectively. On contrary to many observations seen in developing cities, the annual mean PM2.5 during the weekends was higher than weekdays at both monitoring sites. For example, these were 100 (142) and 142 μg m-3 (148) during the weekdays (weekends) at the Townhall and Township sites, respectively. The regression analysis showed a significant positive correlation of PM2.5 with SO2, NO2 and CO as opposed to a negative correlation with O3. The bivariate polar plots suggested a much higher influence of localized sources (e.g., road vehicles) at the Townhall site as opposed to industrial sources affecting the concentrations at the Township site. The imageries from the MODIS Aqua/Terra indicated long-range transport of PM2.5 from India to Pakistan during February to October whereas from Pakistan to India during November to January. This study provides important results in the form of multiscale relationship of PM2.5 with its sources and precursors, which are important to assess the effectiveness of pollution control mitigation strategies in Lahore and similar cities elsewhere. Graphical abstract.
Keyphrases
  • particulate matter
  • air pollution
  • heavy metals
  • drinking water
  • polycyclic aromatic hydrocarbons
  • randomized controlled trial
  • systematic review
  • risk assessment
  • climate change
  • heat stress
  • big data
  • data analysis