Study on the Effects of NO2 Pollution Under COVID-19 Epidemic
Prevention and Control in Urumqi
CAO Yang1, 2, LI Yan-hong1, 2*
1. School of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
2. Xinjiang Normal University, School of Geography and Tourism, Xinjiang Arid Area Lake Environment and Resources Laboratory, Urumqi 830054, China
摘要： 为了探究新冠疫情防控措施对乌鲁木齐市NO2污染的影响，更有效的推动大气污染治理，基于OMI(Ozone Monitoring Instrument)卫星遥感高光谱技术与地面监测资料相互结合，估算了NO2干沉降通量，并利用聚类分析与PSCF(潜在源贡献因子)潜在源方法，对2019年—2021年疫情防控期间乌鲁木齐市NO2扩散轨迹与潜在源进行研究。利用夜间灯光数据，百度地图热力图工具，高德地图POI(Point of Interface)功能区情况，进一步分析讨论了乌鲁木齐市NO2污染来源。研究表明：（1）乌鲁木齐市NO2浓度整体表现为：新市区>沙依巴克区>天山区>水磨沟区>米东区，2020年（疫情爆发期）与2019年（疫情爆发前期）同期对比发现，各城区NO2浓度下降明显，其中沙依巴克区减少幅度最大，为47.63%，2021年（后疫情时代）与2020年（疫情爆发期）同期对比发现，各城区NO2浓度逐渐回升，其中沙依巴克区增长幅度最大，为60.09%。城市热力情况表现为：天山区>沙依巴克区>水磨沟区>新市区>米东区。城市热力情况与NO2浓度变化情况大致相同，米东区城市人口集聚度最低，故城市热力值与NO2浓度均最低。（2）长支流为远距离西北方向输送，距离最远来自于哈萨克斯坦，气流占比最大，达80.32%。短支流主要来自于乌鲁木齐市周边，气流占比为19.69%，NO2为短寿命气体，故气流短距离输送对乌鲁木齐NO2影响较大。各类气流所经过的潜在源区的概率等在空间分布较为一致。PSCF分析法模拟的潜在源贡献具有较大的可信度。（3）将大气系统作为一个灰色系统进行分析，按灰色关联度大小划分为：标准煤消耗量＞第二产业＞工业总产值＞工业用电量＞人口密度＞汽车拥有量＞第三产业＞第一产业。在静稳天气条件下基于OMI卫星遥感资料估算乌鲁木齐市各区干沉降通量结果，该方法可以弥补地面监测的不足，为干沉降通量的估算提供证据。
关键词：高光谱遥感；干沉降通量；乌鲁木齐；PSCF；OMI
Abstract：To explore the impact of the new crown epidemic prevention and control measures on NO2 pollution in Urumqi, and to promote air pollution control more effectively. In this study, based on the combination of OMI (Ozone Monitoring Instrument) satellite remote sensing hyperspectral technology and ground monitoring data, the NO2 dry deposition flux was estimated. To study the NO2 diffusion trajectory and potential sources in Urumqi City during epidemic prevention and control in 2019—2021. Using night light data, the Baidu map heat map tool, and AutoNavi map POI (Point Of Interface) functional area, the source of NO2 pollution in Urumqi was further analyzed and discussed. The research shows that: (1) The overall performance of NO2 concentration in Urumqi City is: Xincheng District>Shayibak District>Tianshan District>Shuimogou District>Midong District, the comparison between 2020 (epidemic outbreak period) and 2019 (pre-epidemic period) during the same period. It is found that the NO2 concentration in each urban area has decreased significantly, among which the Shaybak District has the largest decrease of 47.63%. The comparison between 2021 (post-epidemic era) and 2020 (epidemic outbreak period) shows that the NO2 concentration in each urban area has gradually recovered. The Ibarque district saw the largest increase, at 60.09%. The urban thermal conditions are as follows: Tianshan District>Shayibak District>Shuimogou District>Xincheng District>Midong District. The urban thermal conditions and NO2 concentration changes are roughly the same, and the urban population agglomeration in Midong District is the lowest, so the urban thermal value and NO2 concentration are both the lowest. (2) The long tributaries are transported in the long-distance northwest direction. The farthest distance is from Kazakhstan, and the airflow accounts for the largest proportion, reaching 80.32%. The short tributaries mainly come from and around Urumqi, and the air flow accounts for 19.69%. NO2 is a short-lived gas, so the short-distance transportation of air flow has a greater impact on NO2 in Urumqi. The probabilities of the potential source regions passed by various types of airflow are relatively consistent in the spatial distribution. The potential source contributions simulated by the PSCF analysis method have great credibility. (3) Analyze the atmospheric system as a gray system, and divide it into: standard coal consumption>secondary industry>total industrial output value>industrial electricity consumption>population density>car ownership>tertiary industry>primary industry. Under static and stable weather conditions, the dry deposition flux was estimated based on OMI satellite remote sensing data. This method can compensate for the shortage of ground monitoring and provide evidence for the estimation of dry deposition flux.
Key words：Hyperspectral remote sensing; Dry deposition flux; Urumchi; PSCF; OMI
曹 扬，李艳红. 新冠肺炎疫情防控下乌鲁木齐市NO2污染影响研究[J]. 光谱学与光谱分析, 2023, 43(06): 1981-1987.
CAO Yang, LI Yan-hong. Study on the Effects of NO2 Pollution Under COVID-19 Epidemic
Prevention and Control in Urumqi. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1981-1987.
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