A seriously sand storm mixed air-polluted area in the margin of Tarim Basin: Temporal-spatial distribution and potential sources

摘要

In order to analyze the temporal-spatial distribution characteristics of PM2.5, PM10, SO2, NO2, CO and O-3 in five cities and the potential sources of PM10 in southern Xinjiang during 2016, we collected one year officially released data for analysis. The average PM10, PM2.5, SO2, NO2, O(3 )and CO concentrations were 289 +/- 363, 99 +/- 106, 17 +/- 9, 29 +/- 11, 65 +/- 25 mu g m(-3) and 1.3 +/- 0.6 mg m(-3 )in southern Xinjiang in 2016, respectively. The air pollutants presented distinct seasonal and spatial distribution characteristics. During sandstorm process, the particulate matters (PM) concentrations increased abruptly, with the PM(10)( )and PM2.5 maximum concentrations exceeding 1000 and 500 mu g m(-3) in each city. The backward trajectory results showed that the air masses in Akesu, Kuria, Hotan, Kashi and Atushi were mainly from the Bayingol Mongolian Autonomous Prefecture, Kyrgyzstan, Kizilesu Kirgiz Autonomous Prefecture and Taklimalcan Desert (M). In addition, TD was the main potential contributor to ambient PM10 in five cities during the dust season (DS), with a weighted potential source contribution function (WPSCF) 0.9. While the trajectories of air masses from TD, Bayingol Mongolian Autonomous Prefecture, Urumqi-Changji Area and local emission were potential sources contributing to PM2.5 in these five cities during DS, with a WPSCF 0.7. Moreover, the high weighted concentration weighted trajectory (WCWT) values were distributed in the Tarim basin, with PM10 700 mu g m(-3), however, the local emission and long distance transport contributed to the PM2.5 160 mu g m(-3) for five cities. This study comprehensively analyzes the pollution characteristics of air pollutants in five important cities in the southern margin of the Tarim Basin for the first time, and will provide an important reference basis for the prevention and control of air pollution in southern Xinjiang. (C) 2019 Elsevier B.V. All rights reserved.