Analysis of Air Pollutants and Their Potential Sources in Eastern Xinjiang, Northwestern Inland China, from 2018 to 2022

Abstract

Air pollution in the developed regions of eastern China has been intensively investigated in the past decade. However, there is a relative dearth of air pollution studies on the northwest of inland China (e.g., Xinjiang). In this work, hourly measurement data of six criteria air pollutants (PM2.5, PM10, CO, NO2, O3, and SO2) for the past five years (2018–2022) from Hami and Turpan cities of eastern Xinjiang were analyzed to reveal air pollution characteristics and the distribution of potential sources. Hami and Turpan had the highest AQI values in winter due to increased coal combustion for domestic heating and unfavorable meteorological conditions. The slight elevations of AQI values in spring were caused by frequent dust storms. PM10 was the most frequent main pollutant in both Hami (63.1%) and Turpan (74.1%), followed by PM2.5 and O3. Except for O3, PM2.5, PM10, SO2, NO2, and CO exhibited a generally decreasing pattern in annual average values. But the annual average concentrations of PM10 in Hami (83.5 μg·m−3) and Turpan (139 μg·m−3) in 2022 were still higher than those in eastern China. Diurnal and monthly variations of the six criteria pollutants were influenced by a combination of emission sources and meteorological conditions. The air masses in eastern Xinjiang mainly originated from the west and north and were affected by both inter-regional and intra-regional transport. Analysis of the distribution of potential sources showed that local emissions strongly impacted particulate matter pollution in winter, while regional transport played a dominant role in other seasons. O3 showed a broad distribution of potential sources across all four seasons. Considering that the trend that O3 pollution increased year by year, eastern Xinjiang might face a similar pollution situation as eastern China, i.e., the combined pollution of particulate matter and O3.

Keywords

• eastern Xinjiang
• criteria pollutant
• hourly measurement
• temporal variation
• potential source contribution