2015—2023年“乌-昌-石”城市群PM2.5与PM10时空变化及潜在源分析

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2015—2023年“乌-昌-石”城市群PM_2.5与PM₁₀时空变化及潜在源分析

Spatiotemporal variations and potential sources of PM_2.5 and PM₁₀ in the “Urumqi-Changji-Shihezi” urban agglomeration from 2015 to 2023

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doi:10.12118/j.issn.1000-6060.2024.249

摘要：

使用HYSPLIT模型等方法解析2015—2023年“乌鲁木齐-昌吉回族自治州-石河子（乌-昌-石）”城市群PM_2.5与PM₁₀的时空变化及来源。结果表明：（1）在空间尺度上，2019—2022年“乌-昌-石”城市群PM_2.5与PM₁₀浓度在城市中心和西北部较高，PM₁₀浓度与海拔成反比。（2）从2015—2023年“乌-昌-石”城市群的时间尺度来看，在年际尺度上，乌鲁木齐市和昌吉回族自治州的PM_2.5与PM₁₀年均浓度呈现整体下降趋势，石河子市和五家渠市的PM_2.5与PM₁₀年均浓度直到2023年才显著下降。在季节尺度上，PM_2.5与PM₁₀季均浓度总体下降，相对下降幅度春季最大，夏秋次之，冬季最小。在月尺度上，PM_2.5与PM₁₀月均浓度呈现“U”型分布，其中1月降幅显著。在周尺度上，工作日大量堵车等原因使4个城市的PM_2.5周均浓度呈现“负周末效应”，而PM₁₀周均浓度只在乌鲁木齐市呈现“正周末效应”。在日尺度上，冬季PM_2.5与PM₁₀日均浓度远高于其他季节，PM_2.5日均浓度整体下降，高浓度天数减少，PM₁₀日均浓度受沙尘影响波动较大。（3） 2019—2021年“乌-昌-石”城市群的污染物来源表现为：2019年以本地源为主，污染源广泛且浓度高；2020年由于疫情防控措施的实施，本地排放减少，污染源向中亚地区转移；2021年污染源再次扩大并转向国内。研究可为“乌-昌-石”城市群的大气污染治理和环境政策优化提供数据支持，有助于推动该地区的生态环境保护和经济的高质量增长。

关键词: PM_2.5与PM₁₀, “乌-昌-石”城市群, 时空变化, 潜在源解析

Abstract:

Using the HYSPLIT model and other methods, we analyzed the spatiotemporal variations and sources of PM_2.5 and PM₁₀ in the Urumqi, Changji Hui Autonomous Prefecture, and Shihezi urban agglomeration from 2015 to 2023. The results indicate the following: (1) Spatial scale: From 2019 to 2022, PM_2.5 and PM₁₀ concentrations were higher in the central and northwestern parts of the urban agglomeration. PM₁₀ concentrations showed an inverse relationship with elevation. (2) Temporal scale: From 2015 to 2023, on an interannual scale, the annual average concentrations of PM_2.5 and PM₁₀ in Urumqi City and Changji Hui Autonomous Prefecture showed an overall downward trend. In contrast, Shihezi City and Wujiaqu City experienced significant decreases in PM_2.5 and PM₁₀ concentrations only in 2023. On a seasonal scale, the average concentrations of PM_2.5 and PM₁₀ generally declined, with the largest relative reduction in spring, followed by summer and autumn, and the smallest reduction in winter. On a monthly scale, the average concentrations of PM_2.5 and PM₁₀ displayed a “U-shaped” distribution, with a significant reduction in January. On a weekly scale, heavy weekday traffic congestion led to a “negative weekend effect” for PM_2.5 concentrations across all four cities, while PM₁₀ concentrations exhibited a “positive weekend effect” only in Urumqi City. On a daily scale, PM_2.5 and PM₁₀ concentrations in winter were significantly higher than in other seasons. PM_2.5 concentrations decreased overall, with fewer high-concentration days, while PM₁₀ concentrations fluctuated more due to dust events. (3) Pollution sources (2019—2021): In 2019, pollution was predominantly from local sources, resulting in widespread and high concentrations. In 2020, pandemic-related restrictions reduced local emissions, shifting pollution sources toward Central Asia. In 2021, pollution sources expanded again, returning to domestic regions. This study provides essential data for air pollution control and environmental policy optimization in the Urumqi, Changji Hui Autonomous Prefecture, and Shihezi urban agglomeration, contributing to regional ecological protection and sustainable economic development.

Key words: PM_2.5 and PM₁₀, Urumqi, Changji Hui Autonomous Prefecture, and Shihezi urban agglomeration, spatiotemporal variations, potential source apportionment

闫劲烨, 马正权, 孙萱萱, 阿力木·阿巴斯, 帕丽达·牙合甫. 2015—2023年“乌-昌-石”城市群PM_2.5与PM₁₀时空变化及潜在源分析[J]. 干旱区地理, 2025, 48(3): 405-420.

YAN Jinye, MA Zhengquan, SUN Xuanxuan, Alim ABBAS, Palida YAHEFU. Spatiotemporal variations and potential sources of PM_2.5 and PM₁₀ in the “Urumqi-Changji-Shihezi” urban agglomeration from 2015 to 2023[J]. Arid Land Geography, 2025, 48(3): 405-420.

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城市	PM_2.5日均浓度偏差/%	PM₁₀日均浓度偏差/%
乌鲁木齐市	-1.26	4.27
昌吉州	-2.66	0.84
石河子市	-2.14	-0.50
五家渠市	-2.32	0.18

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