Ground-Based Hyperspectral Stereoscopic Remote Sensing Network: A Promising Strategy to Learn Coordinated Control of O3 and PM2.5 over China

Liu, Cheng; Xing, Chengzhi; Hu, Qihou; Li, Yongling; Liu, Haoran; Hong, Qianqian; Tan, Wanlong; Ji, Xiangguang; Lin, Hua; Lu, Chuan; Lin, Jingbo; Liu, Hanyang; Wei, Shaocong; Chen, Jian; Yang, Kunpeng; Wang, Shuntian; Liu, Ting; Chen, Yujia

doi:10.1016/j.eng.2021.02.019

Cited by 34 publications

(25 citation statements)

References 66 publications

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“…As industrial and traffic emission sources are mainly near the ground level, the u atmospheric NO2 has an overall exponential distribution in the vertical directio evidenced by the MAX-DOAS vertical profile data [37,41]. Therefore, the correl between the TROPOMI NO2 TVCD and NO2 concentrations at ground level statio strong.…”

Section: Satellite and Ground Correlation Analysismentioning

confidence: 96%

“…The MAX-DOAS NO 2 data used in the study were obtained from the Chinese Landbased Hyperspectral Stereo Remote Sensing Network established by the University of Science and Technology of China [37]. The network consists of 34 standard stations covering different regions in China, mainly concentrated in northern and eastern China.…”

Section: Max-doas Datamentioning

confidence: 99%

“…In this study, MAX-DOAS NO 2 measurements with a temporal resolution of 15 min and a vertical resolution of 100 m were used. The retrieval accuracy of NO 2 slant column densities is 7 × 10 14 molecules/cm 2 [37,38]. Data from the Chinese Academy of Meteorological Sciences (CAMS) site (116.32 • E, 39.94 • N) located in Beijing were mainly selected to analyze the correlation between satellite remote sensing observations and ground-based monitoring data.…”

Section: Max-doas Datamentioning

confidence: 99%

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Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements

et al. 2022

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Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production.

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Section: Satellite and Ground Correlation Analysismentioning

confidence: 96%

Section: Max-doas Datamentioning

confidence: 99%

Section: Max-doas Datamentioning

confidence: 99%

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Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements

et al. 2022

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“…Zeng et al (2020) [ 28 ] implied that the concentrations of PM 2.5 and O 3 showed different seasonal trends in eastern China. Liu et al (2021) [ 29 ] used the ground-based hyperspectral stereoscopic remote sensing network to provide a promising strategy to support management of PM 2.5 and O 3 and their precursors and conduct attribution of sources. In the formation of surface O 3 , meteorological factors play a crucial role [ 30 , 31 , 32 , 33 , 34 ].…”

Section: Introductionmentioning

confidence: 99%

Multi-Year Variation of Ozone and Particulate Matter in Northeast China Based on the Tracking Air Pollution in China (TAP) Data

Zhao

Gui

et al. 2022

IJERPH

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With the rapid development of economy and urbanization acceleration, ozone (O3) pollution has become the main factor of urban air pollution in China after particulate matter. In this study, 90th percentile of maximum daily average (MDA) 8 h O3 (O3-8h-90per) and PM2.5 data from the Tracking Air Pollution in China (TAP) dataset were used to determine the mean annual, seasonal, monthly, and interannual distribution of O3-8h-90per and PM2.5 concentrations in Northeast China (NEC). The O3-8h-90per concentration was highest in Liaoning (>100 μg/m3), whereas the highest PM2.5 concentration was observed mainly in urban areas of central Liaoning and the Harbin–Changchun urban agglomeration (approximately 60 μg/m3). The O3-8h-90per concentrations were highest in spring and summer due to more intense solar radiation. On the contrary, the PM2.5 concentration increased considerably in winter influenced by anthropogenic activities. In May and June, the highest monthly mean O3-8h-90per concentrations were observed in central and western Liaoning, about 170–180 μg/m3, while the PM2.5 concentrations were the highest in January, February, and December, approximately 100 μg/m3. The annual mean O3-8h-90per concentration in NEC showed an increasing trend, while the PM2.5 concentration exhibited an annual decline. By 2020, the annual mean O3-8h-90per concentration in southern Liaoning had increased considerably, reaching 120–130 μg/m3. From the perspective of city levels, PM2.5 and O3-8h-90per also showed an opposite variation trend in the 35 cities of NEC. The reduced tropospheric NO2 column is consistent with the decreasing trend of the interannual PM2.5, while the increased surface temperature could be the main meteorological factor affecting the O3-8h-90per concentration in NEC. The results of this study enable a comprehensive understanding of the regional and climatological O3-8h-90per and PM2.5 distribution at distinct spatial and temporal scales in NEC.

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“…Modeling studies of boundary layer ozone over northern China showed different sensitivities of the ozone regime in the vertical direction (Tang et al, 2017). Liu, Xing, et al (2021) utilized the FNR total to diagnose the ozone formation sensitivities in vertical space over Beijing and found that the ozone formation sensitivities changed from predominantly VOC-limited regimes in the 0-100 m layer to the mainly transitional regime in the 200-300 m layer. One drawback of this study is that the overestimated FNR total may misdiagnose ozone formation sensitivity.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of Ozone Formation Sensitivities in Different Height Layers via MAX‐DOAS Observations in Guangzhou

et al. 2022

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Diagnosing the vertical distributions of ozone formation sensitivities within the boundary layers is the prerequisite for formulating proper ozone control strategies. From 1 January 2020, to 20 August 2021, a multi‐function MAX‐DOAS instrument was set up in Guangzhou to detect the NO2 and HCHO vertical profiles. The ozone formation sensitivities in different height layers were diagnosed using the FNRsec, which was defined as the ratio of secondary HCHO to NO2 VMRs (HCHOsec/NO2). The secondary sources in ambient HCHO participate in the photochemical reactions directly, and the FNRsec can indicate the ozone formation sensitivities more accurately. Therefore, the secondary source was separated from ambient HCHO via a multi‐linear regression method, and its relative contribution was approximately 66.9 ± 6.3%. The sensitivity thresholds of ozone formation were determined by the slope of the linear regression analysis for O3 versus the normalized secondary HCHO or NO2 mixing ratios for different FNRsec ranges, which were 0.22 and 0.36. For the ground layer, the VOC‐limited, transitional, and NOx‐limited regimes accounted for 40.66%, 32.42%, and 26.92%, respectively. Diurnally, the ground layer was usually in the VOC‐limited regime in morning, but in the transitional regime in noon and afternoon. Vertically, the ozone formation sensitivity changed with altitude from VOC‐limited (0.02–0.22 km) to transitional (0.22–0.42 km) to NOx‐limited (0.42–2.02 km). These findings can help formulate proper ozone control strategies in time according to the varying local conditions.

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Ground-Based Hyperspectral Stereoscopic Remote Sensing Network: A Promising Strategy to Learn Coordinated Control of O3 and PM2.5 over China

Cited by 34 publications

References 66 publications

Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements

Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements

Multi-Year Variation of Ozone and Particulate Matter in Northeast China Based on the Tracking Air Pollution in China (TAP) Data

Diagnosis of Ozone Formation Sensitivities in Different Height Layers via MAX‐DOAS Observations in Guangzhou

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