Spatio-Temporal Variations of Satellite-Based PM2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China

Abstract

With the aggravation of air pollution in recent years, a great deal of research on haze episodes is mainly concentrated on the east-central China. However, fine particulate matter (PM2.5) pollution in northwest China has rarely been discussed. To fill this gap, based on the standard deviational ellipse analysis and spatial autocorrelation statistics method, we explored the spatio-temporal variation and aggregation characteristics of PM2.5 concentrations in Xinjiang from 2001 to 2016. The result showed that annual average PM2.5 concentration was high both in the north slope of Tianshan Mountain and the western Tarim Basin. Furthermore, PM2.5 concentrations on the northern slope of the Tianshan Mountain increased significantly, while showing an obviously decrease in the western Tarim Basin during the period of 2001–2016. Based on the result of the geographical detector method (GDM), population density was the most dominant factor of the spatial distribution of PM2.5 concentrations (q = 0.550), followed by road network density (q = 0.423) and GDP density (q = 0.413). During the study period (2001–2016), the driving force of population density on the distribution of PM2.5 concentrations showed a gradual downward trend. However, other determinants, like DEM (Digital elevation model), NSL (Nighttime stable light), LCT (Land cover type), and NDVI (Normalized Difference Vegetation Index), show significant increased trends. Therefore, further effort is required to reveal the role of landform and vegetation in the spatio-temporal variations of PM2.5 concentrations. Moreover, the local government should take effective measures to control urban sprawl while accelerating economic development.

Impact of SARS-CoV-2 on Ambient Air Quality in Northwest China (NWC)

“…[11,13,19] that were largely reduced during lockdowns, and helped significantly in pollution reduction [27,30,35,38]. XJ's southern region experienced the highest PM 10 pollution level due to increased emissions from natural sources, e.g., Taklimakan deserts [52][53][54][55]. About 73.58% of cities in NWC experienced a decrease in PM 10 with the highest number of cities in QH (90%), followed by XJ (75%), GS (42.85%), and NX (20%) in 2020.…”

Spatial and temporal variations of PM2.5 concentrations in Chinese cities during 2015-2019

“…Li et al (2018) found that Xinjiang in northwest China is also a PM 2.5 pollution center. We also observed this phenomenon, which may be caused by the frequent sandstorms in the region (Wang et al 2020). However, in 2017, the pollution centers in Xinjiang temporarily disappeared, which may be due to favorable weather conditions, such as cold air, in addition to the ongoing emission reduction measures (Zhang et al 2019).…”

Spatio-Temporal Characteristics of Air Quality Index (AQI) over Northwest China

“…Elevated pollution levels in southern Xinjiang (Kashgar) indicate the influences of emissions from natural sources, e.g., Taklimakan deserts, dust storms, haze events, etc. [61][62][63][64]. Similarly, higher particulate pollution in Shaanxi (FWP region) is associated with increased anthropogenic emissions, e.g., industrial activities, construction activities, etc.…”

“…The PM 2.5 /PM 10 ratio reflects air quality, pollution sources, and origin, e.g., a higher PM 2.5 /PM 10 ratio indicates the increased proportion of PM 2.5 , mainly emitted from anthropogenic activities, and a lower ratio indicates an increased proportion of PM 10 , mainly from natural activities [28,[61][62][63][64]. During the study period (2015-2018), the PM 2.5 /PM 10 ratio slightly decreased by 0.43% and in 50.9% of the cities of NWC.…”

“…Similarly, O 3 was a major pollutant (44.7%) in summer due to lower NOx levels as lower NOx levels prevent ozone depletion and the higher temperature in summer favors ozone generation and accumulation [78,80,82,83,[86][87][88], while PM 10 was a major pollutant in autumn (41.3%), spring (39.1%), and the second major pollutant in winter (34.3%). The number of days with PM 10 as a major pollutant was higher in southern Xinjiang due to emissions from natural sources, e.g., the Taklimakan desert, sand storms [61][62][63][64]89]. Any day with one or more pollutants exceeding CAAQS (Grade II) is considered as a non-attainment/pollution day [2,30].…”