| 摘要: |
| 新冠肺炎疫情管控期间为探究空气质量变化机制提供了良好的控制环境。基于监测站点数据，运用数理统计和空间分析法探讨污染物时空变化特征及相关性，利用聚类分析、潜在源贡献、浓度权重轨迹分析乌鲁木齐市三次管控期首要污染物（PM2.5）的潜在来源。结果表明：（1）整体来看，三次管控期PM2.5、PM10、CO、NO2、SO2浓度平均分别下降15.02 μg∙m−3、36.83 μg∙m−3、0.26 mg∙m−3、19.83 μg∙m−3、1.18 μg∙m−3，O3浓度平均上升9.15 μg·m−3。日内变化上，PM2.5、PM10、CO、NO2浓度呈现“W”型，SO2、O3呈现“几”字型，各污染物浓度季节差异明显。高值区集中在新市区、天山区、水磨沟区、沙依巴克区及头屯河区的东南部，低值区集中在城郊。（2）温度对PM2.5、O3影响较为显著，相对湿度对CO、NO2影响较为显著；整体上，夏季气象因子与污染物之间相关性较差。（3）乌鲁木齐管控期主要气团沿天山山脉的走向流动，受到西风的长距离气流和盆地内部的短距离气流双重影响。乌鲁木齐市空气质量变化受多种气象条件及气团相互运动影响，研究结果可为今后城市大气污染控制提供参考。 |
| 关键词: 大气污染 空间插值 潜在源分析 新冠肺炎 乌鲁木齐 |
| DOI：10.7515/JEE242005 |
| CSTR： |
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| 基金项目:国家自然科学基金项目（41861033）；新疆维吾尔自治区自然科学基金项目（2022D01A212） |
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| Spatiotemporal changes and its influencing factors of air pollution in Urumqi of China during the COVID-19 lockdowns |
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XIE Siqi, CHEN Xuegang, FAN Jiayu, LI Na
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1. School of Geographical Science and Tourism, Xinjiang Normal University, Urumqi 830054, China
2. Xinjiang Key Laboratory of Lake Environment and Resources in Arid Zone, Urumqi 830054, China
3. Urban Ecosystem National Positioning Observation and Research Station, Urumqi 830000, China
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| Abstract: |
| Background, aim, and scope Urban air pollution is becoming increasingly serious, posing a threat to human health and sustainable socio-economic development. Urumqi, a typical city in the arid region of northwest China, has serious air pollution in winter, and the air quality problem has been widely concerned. Urumqi has adopted control measures to effectively curb the spread of COVID-19 from January 27 to March 8, 2020, from July 16 to September 7, 2020, and August 10 to November 28, 2022. Such as blocking traffic arteries, restricting the movement of people, closing factories and schools. These measures provide a control environment for studying changes in air quality. The focus of this study is to investigate the temporal and spatial changes and influencing factors of air pollution in Urumqi during three lockdowns, and analyze the clustering, potential source areas and concentration weight trajectories of the main pollutant (PM2.5) in order to better understand the air pollution situation and provide data support for air treatment. Materials and methods Based on data from 11 air quality monitoring stations in Urumqi, mathematical statistics and spatial analysis were used to investigate the spatial and temporal changes of pollutants. Pearson correlation is used to analyze the relationship between pollutants and meteorological factors. Cluster analysis, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were used to analyze the potential sources of the main pollutant (PM2.5) during lockdowns in Urumqi. Results PM2.5, PM10, CO, NO2, and SO2 concentrations decreased by an average of 15.02 μg·m−3, 36.83 μg·m−3, 0.26 mg·m−3, 19.83 μg·m−3, and 1.18 μg·m−3, and O3 concentration increased by an average of 9.15 μg·m−3. The concentrations of PM2.5, PM10, CO and NO2 show a “W” shape, while SO2 and O3 are inverted “U” shape, and the seasonal difference of pollutant concentration is obvious. The high pollution areas during the three lockdowns are concentrated in the Xinshi District, Tianshan District, Shuimogou District, Saybagh District and the southeast area of Toutunhe District, and the low pollution areas are concentrated in the suburbs of the city. Discussion Meteorological factors had significant influence on the concentration of air pollutants during three lockdowns. When residents worked at home, transportation emissions reduced sharply, and the concentrations of PM2.5, PM10, O3 and NO2 decreased the most during lockdowns. The influence of temperature on O3 is significant, and O3 concentration increased by 14.13% year-on-year, which may be caused by high temperature, high radiation and high building density in summer. After the lockdown, the concentrations of PM2.5, PM10, CO and NO2 increased, indicating that the concentration of pollutants was greatly affected by human activities and traffic emissions. The cluster analysis showed that the main air masses in Urumqi during lockdowns was the strike flow along the Tianshan Mountains, which was mainly influenced by the long distance flow of the west wind and the short distance flow in the basin. PSCF and CWT showed that the potential sources of PM2.5 during lockdowns of Urumqi were mainly affected by short-distance transport around Ili Kazak Autonomous Prefecture in Xinjiang. Conclusions During lockdowns, man-made sources of pollution were reduced and air quality was effectively improved. In addition, the change of air quality in Urumqi were related to various meteorological conditions and the mutual movement of air mass. Pay attention to both the long-distance flow of westerly winds and the short distance flow within the basin. Recommendations and perspectives The paper provides a reference for the control of air pollution in Urumqi. In the later stage, the exploration of influencing factors of pollutants and the detection of other potential source areas of pollutants will be further enriched. |
| Key words: air pollution spatial interpolation potential source analysis COVID-19 Urumqi |
