Seasonal contribution of mineral dust and other major components to particulate matter at two remote sites in Central Asia

Abstract

Dust storms are significant contributors to ambient levels of particulate matter (PM) in many areas of the world. Central Asia, an area that is relatively understudied in this regard, is anticipated to be affected by dust storms due to its proximity to several major deserts that are in and generally surround Central Asia (e.g., the Aral Sea region, the Taklimakan desert in Western China). To investigate the relative importance of mineral dust (dust specifically composed of soil related minerals and oxides) in Central Asia, PM10 and PM2.5, and by difference, coarse particles (particles with diameters between 2.5 and 10 μm) were measured at two sites, Bishkek and Lidar Station Teplokluchenka (Lidar), in the Kyrgyz Republic. Samples were collected every other day from July 2008 to July 2009. Daily samples were analyzed for mass and organic and elemental carbon. Samples were also composited on a bi-weekly basis and analyzed for elemental constituents and ionic components. In addition, samples collected on days with relatively high and low PM concentrations were analyzed before, and separately, from the biweekly composites to investigate the chemical differences between the episodic events. Data from the episodic samples were averaged into the composited averages. Using the elemental component data, several observational models were examined to estimate the contribution of mineral dust to ambient PM levels. A mass balance was also conducted.Results indicate that at both sites, mineral dust (as approximated by the “dust oxide” model) and organic matter (OM) were the dominant contributors to PM10 and PM2.5. Mineral dust was a more significant contributor to the coarse PM (PM10-2.5) during high event samples at both sites, although the relative contribution is greater at the Lidar site (average ± standard deviation = 42 ± 29%) as compared with the Bishkek site (26 ± 16%). Principal Components Analysis (PCA) was performed using data from both sites, and PCA indicated that mineral dust explained the majority of the variance in PM concentrations, and that the major apportioned factors of PM10 and PM2.5 were chemically similar between sites.