2022, Volume 19, Issue 12
Engineering >> 2022, Volume 19, Issue 12 doi: 10.1016/j.eng.2021.02.019
Ground-based Hyperspectral Stereoscopic Remote Sensing Network: A Promising Strategy to Learn Coordinated Control of O3 and PM2.5 over China
a Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
b Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
c Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
d Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China
e Anhui Province Key Laboratory of Polar Environment and Global Change, University of Science and Technology of China, Hefei 230026, China
f School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
g School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
h Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China
i School of Environment and Civil Engineering, Jiangnan University, Wuxi 214122, China
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Abstract
With the coming of the “14th Five-Year Plan”, the coordinated control of particulate matter with an aerodynamic diameter no greater than 2.5 μm (PM2.5) and O3 has become a major issue of air pollution prevention and control in China. The stereoscopic monitoring of regional PM2.5 and O3 and their precursors is crucial to achieve coordinated control. However, current monitoring networks are currently inadequate for monitoring the vertical profiles of both PM2.5 and O3 simultaneously and support air quality control. The University of Science and Technology of China (USTC) has established a nationwide ground-based hyperspectral stereoscopic remote sensing network based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) since 2015. This monitoring network provides a significant opportunity for the regional coordinated control of PM2.5 and O3 in China. One-year vertical profiles of aerosol, NO2 and HCHO monitored from four MAX-DOAS stations installed in four megacities (Beijing, Shanghai, Shenzhen, and Chongqing) were used to characterize their vertical distribution differences in four key regions, Jing–Jin–Ji (JJJ), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB), respectively. The normalized and yearly averaged aerosol vertical profiles below 400 m in JJJ and PRD exhibit a box shape and a Gaussian shape, respectively, and both show exponential shapes in YRD and SB. The NO2 vertical profiles in four regions all exhibit exponential shapes because of vehicle emissions. The shape of the HCHO vertical profile in JJJ and PRD was Gaussian, whereas an exponential shape was shown in YRD and SB. Moreover, a regional transport event occurred at an altitude of 600–1000 m was monitored in the southwest–northeast pathway of the North China Plain (NCP) by five MAX-DOAS stations (Shijiazhuang (SJZ), Wangdu (WD), Nancheng (NC), Chinese Academy of Meteorological Sciences (CAMS), and University of Chinese Academy of Sciences (UCAS)) belonging to the above network. The aerosol optical depths (AOD) in these five stations decreased in the order of SJZ > WD > NC > CAMS > UCAS. The short-distance regional transport of NO2 in the 700–900 m layer was monitored between WD and NC. As an important precursor of secondary aerosol, the peak of NO2 air mass in WD and NC all occurred 1 h earlier than that of aerosol. This was also observed for the short-distance regional transport of HCHO in the 700–900 m layer between NC and CAMS, which potentially affected the O3 concentration in Beijing. Finally, CAMS was selected as a typical site to determine the O3–NOx–volatile organic compounds (VOCs) sensitivities in vertical space. We found the production of O3 changed from predominantly VOCs-limited conditions to mainly mixed VOCs–NOx-limited condition from the 0–100 m layer to the 200–300 m layer. In addition, the downward transport of O3 could contribute to the increase of ground surface O3 concentration. This ground-based hyperspectral stereoscopic remote sensing network provide a promising strategy to support management of PM2.5 and O3 and their precursors and conduct attribution of sources.
Keywords
MAX-DOAS ; Stereoscopic monitoring ; Regional transport ; Ozone production ; Control strategy
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