Integrating Fixed Monitoring Systems with Low-Cost Sensors to Create High-Resolution Air Quality Maps for the Northern China Plain Region
Integrating Fixed Monitoring Systems with Low-Cost Sensors to Create High-Resolution Air Quality Maps for the Northern China Plain Region
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DOI：
10.1021/acsearthspacechem.1c00174
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发表时间：
2021-10-18
影响因子：
3.4
通讯作者：
Biswas, Pratim
中科院分区：
文献类型：
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作者：
Chao, Chun-Ying;Zhang, Huang;Biswas, Pratim
针对华北平原大气颗粒物（PM）污染严重的现状，利用固定的空气质量监测站对污染源进行了追踪研究。然而，这些固定的监测器具有很高的维护成本，这使得构建用于空气质量测量的空间密集网络在经济上不可行。或者，使用卫星监测系统和低成本的空气质量传感器网络可以大大提高给定区域的地面PM浓度数据的时空分辨率。本研究全面考察了中国环保局监测站（CN-EPA）、低成本PM传感器网络和卫星气溶胶光学厚度（AOD）测量的性能。本文的目的是提高新乡市地面PM浓度数据的时空分辨率。推断结果表明，低成本的PM传感器表现出高线性与CN-EPA数据集的PM，…s浓度，R-2值为0.82。从AOD反演推断的PM2.5浓度与固定监测站的R-2值为0.53，表现出中度相关性。为了评价人类活动对空气污染的影响，选取了春节、清明节、中元节和中秋节4个传统节日，观测了新乡市大气颗粒物的分布特征。地面PM2.5浓度的热图揭示了高人口密度地区的污染热点。交叉验证是用来评估所创建的污染地图的准确性。结果表明，从CN-EPA数据集测量的数据插值的污染图具有最小的均方根误差（RMSE）。最后，我们的研究结果表明，低成本的PM传感器数据可以与传统的固定空气质量测量相结合，以提供更详细的信息，在城市和农村地区的污染地图上的排放源。
To address and remediate severe particulate matter (PM) pollution in the North China Plain (NCP), many studies have traced pollution sources by using fixed air quality monitoring stations. However, these fixed monitors have high maintenance costs that make it economically infeasible to construct spatially dense networks for air quality measurement. Alternatively, using satellite monitoring systems and a low-cost air quality sensor network can greatly increase the spatiotemporal resolution of the ground-level PM concentration data for a given region. This study comprehensively examines the performance of China's EPA monitoring stations (CN-EPA), low-cost PM sensor networks and satellite aerosol optical depth (AOD) measurements. The goal is to improve the spatiotemporal resolution of ground-level PM concentration data for Xinxiang, a typical industrial city in the NCP. The inferred results show that low-cost PM sensors demonstrate high linearity with CN-EPA data sets for PM,.. s concentrations with an R-2 value of 0.82. The PM2.5 concentration inferred from the AOD retrievals demonstrates a moderate correlation with fixed monitoring stations with an R-2 value of 0.53. To evaluate the impact of human activities on air pollution, four traditional Chinese festivals, Chinese New Year, Tomb Sweeping Day, Ghost Festival, and Moon Festival, are chosen to observe the PM distribution in Xinxiang. Heat-maps of the ground-level PM2.5 concentration reveal pollution hotspots in areas of high population density. Cross-validation is employed to evaluate the accuracy of the created pollution maps. The results demonstrate that pollution maps that were interpolated from data measured by CN-EPA data sets have the smallest root mean squared error (RMSE). Finally, our results show that low-cost PM sensor data can be integrated with traditional fixed air quality measurements to provide more detailed information about emission sources on pollution maps in urban and rural areas.