Analysing temporal variability of particulate matter and possible contributing factors over Mahabaleshwar, a high-altitude station in Western Ghats, India. (November 2017)

• Record Type: Journal Article
• Authors: Leena, P.P.; Vijayakumar, K.; Anilkumar, V.; Pandithurai, G.
• Is Part Of: Journal of atmospheric and solar-terrestrial physics. Volume 164(2017)
• Page Start: 105
• Page End: 115
• Publication Date: 2017-11
• Subjects: Ground based observation -- Particulate matter variability -- Pollutants -- High altitude site; Geophysics -- Periodicals; Atmospheric physics -- Periodicals; Géophysique -- Périodiques; Météorologie physique -- Périodiques; Electronic journals; 551.51
• DOI: 10.1016/j.jastp.2017.08.013
• Languages: English
• ISSNs: 1364-6826

Abstract

Abstract: Airborne particulate matter (PM) plays a vital role on climate change as well as human health. In the present study, temporal variability associated with mass concentrations of PM10, PM2.5, and PM1.0 were analysed using ground observations from Mahabaleswar (1348 m AMSL, 17.56 0 N, 73.4 0 E), a high-altitude station in the Western Ghats, India from June 2012 to May 2013. Concentrations of PM10, PM2.5, and PM1.0 showed strong diurnal, monthly, seasonal and weekday-weekend trends. The seasonal variation of PM1.0 and PM2.5 has showed highest concentrations during winter season compared to monsoon and pre-monsoon, but in the case of PM10 it showed highest concentrations in pre-monsoon season. Similarly, slightly higher PM concentrations were observed during weekends compared to weekdays. In addition, possible contributing factors to this temporal variability has been analysed based on the variation of secondary pollutants such as NO2, SO2, CO and O3 and long range transport of dust. Highlights: Measurements of mass concentrations of particulate matter (PM) i. e.PM10, PM2.5, and PM1.0 were made at Mahabaleshwar (17.56 o N, 73.4 o E), a high-altitude station in India, for the first time. Concentrations of PM10, PM2.5, and PM1.0 show strong temporal variability (i.e. monthly, diurnal, seasonal) and weekday-weekend effects. Possible factors contributing to PM loading is analysed which showed pollutants and dust storm play significant role.