Exploring the Mass Concentration of Particulate Matter and Its Relationship with Meteorological Parameters in the Hindu-Kush Range
AffiliationDepartment of Chemical and Environmental Engineering, University of Arizona
Department of Hydrology and Atmospheric Sciences, University of Arizona
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CitationUsman, F., Zeb, B., Alam, K., Valipour, M., Ditta, A., Sorooshian, A., Roy, R., Ahmad, I., & Iqbal, R. (2022). Exploring the Mass Concentration of Particulate Matter and Its Relationship with Meteorological Parameters in the Hindu-Kush Range. Atmosphere, 13(10).
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AbstractParticulate matter (PM) is among the deadliest air pollutants due to its negative health impacts and environmental harm. This study reports on monthly and seasonal concentrations of PM10, PM2.5, and PM1, along with their ratios. Twelve-day samples were collected once a month in Mingora city (Swat, Pakistan) from January to December 2019 using a low volume sampler. Maximum average mass concentrations of PM10, PM2.5, and PM1 were recorded in December having values of 78, 56, and 32 μg m−3, respectively. Minimum average values for PM10 (44 μg m−3) and PM2.5 (25.1 μg m−3) were recorded in April, while the lowest PM1 (11 μg m−3) was recorded in August. In comparison to other months, the maximum average mass concentrations were 1.77 times (PM10), 2.23 times (PM2.5), and 2.9 times (PM1) higher in December. During the winter season, average mass concentrations remained high. Substantial correlation coefficients of 0.92, 0.79, and 0.75 were recorded between PM10 and PM2.5, PM2.5 and PM1, and PM2.5 and PM1, respectively. The overall average ratios PM2.5: PM10, PM1: PM2.5, and PM1: PM10 were 68.3, 52.6, and 35.4%, respectively. A moderate negative correlation of PM10, PM2.5, and PM1 with wind speed (−0.34, −0.39, and −0.41), a strong negative correlation with temperature (−0.69, −0.71, and −0.74) and rainfall (−0.63, −0.61, and −0.59), and a weak relationship with relative humidity (−0.32, −0.1, and −0.02) were recorded. © 2022 by the authors.
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Except where otherwise noted, this item's license is described as Copyright © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).