Spatial and Seasonal Distribution of PM₁₀-Bound Heavy Metals in Urban and Agricultural Areas of Rawalpindi, Pakistan
Keywords:
PM₁₀, Heavy metals, Seasonal variation, Spatial distribution, Air pollution, Pakistan, ICP-OESAbstract
Atmospheric particulate matter PM₁₀ is an important carrier of toxic heavy metals and is associated with significant risks to environmental quality and human health. This Study describes the spatial and seasonal distribution of lead (Pb), chromium (Cr), cadmium (Cd), and copper (Cu) bound to PM₁₀ in the built-up and agricultural areas of Rawalpindi, Pakistan. This is, to the best of our knowledge, one of the first studies comparing the PM₁₀ -bound heavy metal concentrations of built-up and agricultural environments of Rawalpindi using year-round monitoring. Out of these, six monitoring sites were chosen to collect monthly samples of PM₁₀ from May 2022 to April 2023 for further analysis of Pb, Cr, Cd, and Cu by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES). Clear seasonal variation was observed in all the studied metals with increased concentrations in winter months and decreased concentrations in summer months. Lead was the most dominant heavy metal in both land use categories, followed by Cu, Cr, and Cd. The mean concentrations at the built-up sites were 0.61 ± 0.19 µg m⁻³ (Pb), 0.08 ± 0.04 µg m⁻³ (Cu), 0.02 ± 0.02 µg m⁻³ (Cr), and 0.008 ± 0.006 µg m⁻³ (Cd), while the corresponding concentrations at the agricultural sites were 0.64 ± 0.16 µg m⁻³, 0.09 ± 0.04 µg m⁻³, 0.02 ± 0.02 µg m⁻³, and 0.012 ± 0.015 µg m⁻³, respectively. The results indicate that the average concentrations of Pb, Cu, and Cd were slightly higher in agricultural sites, while the concentrations of Cr were comparable between the land use categories. The observed seasonal variation is probably related to reduced atmospheric dispersion and increased accumulation of pollutants in winter, while lower concentrations in summer are indicative of better atmospheric mixing and wet deposition. Land-use characteristics and previous studies suggest possible emission sources including vehicle traffic, re-suspension of road dust, biomass burning, agricultural activities and industrial emissions. However, these sources are inferred from land-use characteristics and previous studies and not confirmed by source apportionment analysis. The current study provides baseline information about the spatial and seasonal distribution of heavy metals associated with PM₁₀ in Rawalpindi and underscores the necessity for further monitoring and effective emission control techniques to reduce particle pollution and protect human health.
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