Characteristics and sources of atmospheric pollutants in typical inland cities in arid regions of central Asia: A case study of Urumqi city

• Published in: PloS one Vol. 16; no. 4; p. e0249563
• Main Authors: Li, Zongying, Wang, Yao, Xu, Zhonglin, Cao, Yue'e
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 20-04-2021; Public Library of Science (PLoS)
• Subjects: Air pollution; Air quality; Arid regions; Arid zones; Biology and Life Sciences; Carbon monoxide; Case reports; Chemical properties; Cities; Desert meteorology; Drafting software; Earth Sciences; Ecology; Ecology and Environmental Sciences; Editing; Education; Electronic mail; Environmental aspects; Environmental impact; Environmental science; Laboratories; Meteorological data; Meteorology; Methodology; Nitrogen dioxide; Oases; Outdoor air quality; Ozone; Particulate emissions; Particulate matter; People and Places; Physical Sciences; Pollutants; Pollution sources; Social Sciences; Statistical analysis; Sulfur; Sulfur dioxide; Trajectory analysis; Urban air; Urban air quality; Urban areas; Urbanization; China; Beijing China; Central Asia; Asia
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0249563

The arid zone of central Asia secluded inland and has the typical features of the atmosphere. Human activities have had a significant impact on the air quality in this region. Urumqi is a key city in the core area of the Silk Road and an important economic center in Northwestern China. The urban environment is playing an increasingly important role in regional development. To study the characteristics and influencing factors of the main atmospheric pollutants in Urumqi, this study selected Urumqi's daily air quality index (AQI) data and observation data of six major pollutants including fine particulate matter (PM2.5), breathable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3_8h) from 2014 to 2018 in conjunction with meteorological data to use a backward trajectory analysis method to study the main characteristics of atmospheric pollutants and their sources in Urumqi from 2014 to 2018. The results showed that: (1) From 2014 to 2018, the annual average of PM2.5, PM10, SO2, NO2 and CO concentrations showed a downward trend, and O3_8h concentrations first increased, then decreased, and then increased, reaching the highest value in 2018 (82.15 μg·m-3); The seasonal changes of PM2.5, PM10, SO2, NO2 and CO concentrations were characterized by low values in summer and fall seasons and high values in winter and spring seasons. The concentration of O3_8h, however, was in the opposite trend, showing the high values in summer and fall seasons, and low values in winter and spring seasons. From 2014 to 2018, with the exception of O3_8h, the concentration changes of the other five major air pollutants were high in December, January, and February, and low in May, June, and July; the daily changes showed a "U-shaped" change during the year. The high-value areas of the "U-shaped" mode formed around the 50th day and the 350th day. (2) The high-value area of AQI was from the end of fall (November) to the beginning of the following spring (March), and the low-value area was from April to October. It showed a U-shaped change trend during the year and the value was mainly distributed between 50 and 100. (3) The concentrations of major air pollutants in Urumqi were significantly negatively correlated with precipitation, temperature, and humidity (P<0.01), and had the highest correlation coefficients with temperature. (4) Based on the above analysis results, this study analyzed two severe pollution events from late November to early December. Analysis showed that the PM2.5/PM10 ratio in two events remained at about 0.1 when the pollution occurred, but was higher before and after the pollution (up to 1.46). It was shown that the pollution was a simple sandstorm process. Backward trajectory analysis clustered the airflow trajectories reaching Urumqi into 4 categories, and the trajectories from central Asia contributed the maximum values of average PM2.5 and PM10 concentrations.