基于OMI数据的新冠疫情影响下福建省臭氧敏感性变化

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Abstract Based on the OMI satellite data, the characteristics of atmospheric ozone sensitivity in Fujian province and its nice municipalities during the period of COVID-19 epidemic were assessed with HCHO and NO₂ vertical column densities as proxies for ozone sensitivity. The results showed that Fujian Province was dominated by VOCs-limited regime before the pandemic with the controlled area proportion of 46.5%. The other two regimes:NO_x-VOCs-limited regime and NO_x-limited regime, controlled 25.0% and 28.5% of the area, respectively. The area proportion controlled by VOXs-limited regime was highest in Xiamen and lowest in Nanping. During the period with strict pandemic control policies, VOXs-limited regime, NO_x-VOCs-limited regime and NO_x-limited regime controlled 29.5%, 21.1%, and 49.4% of the area, respectively. The area proportion controlled by NO_x-limited regime was highest in Ningde and lowest in Putian. During the stable period, VOXs-limited regime, NO_x-VOCs-limited regime and NO_x-limited regime controlled 23.1%, 29.1%, and 47.8% of the area, respectively. NO_x-limited regime was the dominant regime with highest area proportion controlled in Nanping and lowest area proportion in Xiamen. Compared with the before pandemic period, the area proportion of Xiamen controlled by VOCs-limited regime was obviously reduced (38.1% less) during the period with strict control policies, and the lowest reduction was in Sanming with a moderate decrease of 7.9%. According to the conversion results, Putian, Quanzhou, and Xiamen were categorized into the first city group where changes in ozone sensitivity were jointly influenced by its precursors including formaldehyde (HCHO) and nitrogen dioxide (NO₂), while other cities could be categorized into the second group where ozone sensitivities were mainly affected by NO₂ column concentrations. Therefore, effective strategies for ozone reduction would be more complex in the first group of cities.

Key words： OMI satellite data COVID-19 ozone formation sensitivity Fujian Province

Received: 30 September 2020

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X513

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	DAN Yang-bin
	YU Rui-lian
	BIAN Ya-hui
	CHEN Jin-sheng
	HU Gong-ren

Cite this article:

DAN Yang-bin,YU Rui-lian,BIAN Ya-hui等. The change of atmospheric ozone formation sensitivity in Fujian Province based on OMI satellite data during the period of COVID-19[J]. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(5): 2056-2063.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2021/V41/I5/2056

[1]	梁永贤,尹魁浩,胡泳涛,等.深圳地区臭氧污染来源的敏感性分析[J]. 中国环境科学, 2014,34(6):1390-1396. Liang Y X, Yin K H, Hu Y, T. et al. Sensitivity analysis of ozone precursor emission in Shenzhen, China[J]. China Environmental Science, 2014,34(6):1390-1396.
[2]	程麟钧,王帅,宫正宇,等.中国臭氧浓度的时空变化特征及分区[J]. 中国环境科学, 2017,37(11):4003-4012. Chen L J, Wang S, Gong Z N, et al. Spatial and seasonal variation and regionalization of ozone concentrations in China[J]. China Environmental Science, 2017,37(11):4003-4012.
[3]	Lehman J, Swinton K, Bortnick S, et al. Spatio-temporal characterization of tropospheric ozone across the eastern United States[J]. Atmospheric Environment, 2004,38(26):4357-4369.
[4]	陈仁杰,陈秉衡,阚海东.上海市近地面臭氧污染的健康影响评价[J]. 中国环境科学, 2010,30(5):603-608. Chen R J, Chen B H, Kan H D. Health impact assessment of surface ozone pollution in Shanghai[J]. China Environmental Science, 2017, 37(11):4003-4012.
[5]	列淦文,叶龙华,薛立.臭氧胁迫对植物主要生理功能的影响[J]. 生态学报, 2014,34(2):294-306. Lie G W, Ye L H, Xue L. Effects of ozone stress on major plant physiological functions[J]. Acta Ecologica Sinica, 2014,34(2):294-306.
[6]	耿春梅,王宗爽,任丽红,等.大气臭氧浓度升高对农作物产量的影响[J]. 环境科学研究, 2014,27(3):239-245. Geng C M, Wang Z S, Ren L H, et al. Study on the impact of elevated atmospheric ozone on crop yield[J]. Research of Environmental Sciences, 2014,27(3):239-245.
[7]	Atkinson R. Atmospheric chemistry of VOCS and NOx[J]. Atmospheric Environment, 2000,34(12-14):2063-2101.
[8]	Wang T, Xue L, Brimblecombe P, et al. Ozone pollution in China:A review of concentrations, meteorological influences, chemical precursors, and effects[J]. Science of the Total Environment, 2017, 575:1582-1596.
[9]	庄立跃.中国三大城市群近地面臭氧污染特征及其敏感性研究[D]. 广州:华南理工大学, 2019. Zhuang L Y. Ground level ozone concentration characteristics and formation sensitivity in China's Three Agglomerations[D]. Guangzhou:South China University of Technology, 2019.
[10]	Ramboll US Corporation. User's guide comprehensive air quality model with extensions version 6.3.[EB/OL]. http://www.camx.com/files/camxusersguide_v6-50.pdf.
[11]	王雪松,李金龙,张远航,等.北京地区臭氧污染的来源分析[J]. 中国科学(B辑:化学), 2009,39(6):548-559. Wang X S, Li J L, Zhang Y H, et al. Ozone source attribution during a severe photochemical smog episode in Beijing, China[J]. Scientia Sinica (Chimica), 2009,39(6):548-559.
[12]	吴琳,薛丽坤,王文兴.基于观测的臭氧污染研究方法[J]. 地球环境学报, 2017,8(6):479-491. Wu L, Xue L K, Wang W X. Review on the observation-based methods for ozone air pollution research[J]. Journal of Earth Environmen, 2017,8(6):479-491.
[13]	Sillman S. The use of NOy, H2O2 and HNO3 as indicators for O3-NOx-VOC sensitivity in urban locations[J]. Journal of Geophysical Research Atmospheres, 1995,100:175-188.
[14]	陈天赐,潘文斌.基于光化学模型的臭氧生成敏感性研究进展[J]. 环境科学与技术, 2019,42(11):201-207. Chen T C, Pan W B. Research prog⁃ress of ozone formation sensitivity based on photochemical model[J]. Environmental Science & Technology, 2019,42(11):201-207.
[15]	武卫玲,薛文博,雷宇,等.基于OMI数据的京津冀及周边地区O3生成敏感性[J]. 中国环境科学, 2018,38(4):1201-1208. Wu W L, Xue W B, Lei Y, et al. Sensitivity analysis of ozone in Beijing-Tianjin-Hebei (BTH) and its surrounding area using OMI satellite remote sensing data[J]. China Environmental Science, 2018, 38(4):1201-1208.
[16]	庄立跃,陈瑜萍,范丽雅,等.基于OMI卫星数据和MODIS土地覆盖类型数据研究珠江三角洲臭氧敏感性[J]. 环境科学学报, 2019, 39(11):3581-3592. Zhuang L Y, Chen Y P, Fan L Y, et al. Study on the ozone formation sensitivity in the Pearl River Delta based on OMI satellite data and MODIS land cover type products[J]. Acta Scientiae Circumstantiae, 2019,39(11):3581-3592.
[17]	单源源,李莉,刘琼,等.基于OMI数据的中国中东部臭氧及前体物的时空分布[J]. 环境科学研究, 2016,29(8):1128-1136. Shan Y Y, LI L, Liu Q, et al. Spatio-temporal distribution of ozone and its precursors over Central and Eastern China based on OMI data[J]. Research of Environmental Sciences, 2016,29(8):1128-1136.
[18]	Smedt I D, Stavrakou T, Müller J F, et al. H2CO columns retrieved from GOME-2:first scientific results and progress towards the development of an operational product[A]//EUMETSAT Meteorological Satellite Conference[C]. Europe:EUMETSAT Meteorological Satellite Conference, 2009.
[19]	Jie J, Yong Z, Gao J, et al. Monitoring of SO2 column concentration change over China from Aura OMI data[J]. International Journal of Remote Sensing, 2012,33(6):1934-1942.
[20]	宋佳颖,刘旻霞,孙瑞弟,等.基于OMI数据的东南沿海大气臭氧浓度时空分布特征研究[J]. 环境科学学报, 2020,40(2):438-449. Song J Y, Liu M X, Sun R D, et al. Temporal and spatial distribution characteristics of atmospheric ozone concentration in Southeast Coast based on OMI data[J]. Acta Scientiae Circumstantiae, 2020,40(2):438-449.
[21]	Duncan B N, Yoshida Y, Olson J R, et al. Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation[J]. Atmospheric Environment, 2010,44(18):2213-2223.
[22]	刘彩霞,边玮瓅.天津市空气质量与气象因子相关分析[J]. 中国环境监测, 2007,23(5):63-65,70. Liu C X, Bian W C. The correlation of air quality and meteorologic factors in Tianjin[J]. Environmental Monitoring in China, 2007, 23(5):63-65,70.
[23]	刘洋洋,刘宏庆,王振乾,等.辽宁省近12年对流层甲醛柱浓度时空变化及其影响因素[J]. 环境科学学报, 2018,38(2):618-628. Liu Y Y, Liu H Q, Wang Z Q, et al. Spatial-temporal changes of tropospheric HCHO column density and its impact factors over Liaoning Province during 2005~2016[J]. Acta Scientiae Circumstantiae, 2018,38(2):618-628.
[24]	王培玉,巨天珍,刘文君,等.甘肃省植被与对流层甲醛关系及影响因素分析[J]. 环境科学研究, 2019,32(9):1556-1566. Wang P Y, Ju T Z, Liu W J, et al. Relationship between NDVI and Troposphere HCHO in Gansu Province and Its Influencing Factors[J]. Research of Environmental Sciences, 2019,32(9):1556-1566.
[25]	张玉洁,庞小兵,牟玉静.北京市植物排放的异戊二烯对大气中甲醛的贡献[J]. 环境科学, 2009,30(4):976-981. Zhang Y J, Pang X B, Mu Y J. Contribution of isoprene emitted from vegetable to atmospheric formaldehyde in the ambient air of Beijing City[J]. Environmental Science, 2009,30(4):976-981.
[26]	Witte J C, Duncan B N, Douglass A R, et al. The unique OMI HCHO/NO2 feature during the 2008 Beijing Olympics:Implications for ozone production sensitivity[J]. Atmospheric Environment, 2011, 45(18):3103-3111.
[27]	陈智海,杨显玉,古珊,等.基于OMI数据研究中国对流层甲醛时空分布特征及变化趋势[J]. 环境科学学报, 2019,39(9):2852-2859. Chen Z H, Yang X Y, Gu S, et al. Spatiotemporal variations and trend analysis of OMI satellite-based tropospheric formaldehyde over China[J]. Acta Scientiae Circumstantiae, 2019,39(9):2852-2859.
[28]	马超,巨天珍,温飞,等.基于甘肃省卫星遥感的对流层NO2时空变化[J]. 中国环境科学, 2020,40(3):956-966. Ma C, Ju T Z, Wen F, et al. Temporal and spatial variation of tropospheric NO2 based on satellite remote sensing in Gansu Province[J]. China Environmental Science, 2020,40(3):956-966.
[29]	福建统计局.福建统计年鉴-2020[M]. 北京:北京数通电子出版社, 2020. Fujian Provincial Bureau of Statistics. Fujian statistical yearbook-2020[M]. Beijing:Beijing Data Communication Press, 2020.
[30]	刘显通,郑腾飞,万齐林,等.OMI遥感珠三角城市群NO2的时空分布特征及人类活动影响分析[J]. 热带气象学报, 2015,31(2):193-201. Liu X T, Zheng T F, Wan Q L, et al. Spatio-temporal characteristics of NO2 in concentrated PRD urban districts and analysis of anthropogenic influences based on OMI remote sensing data[J]. Journal of Tropical Meteorology, 2015,31(2):193-201.