|
|
Study on ozone precursors in Beijing based on OLI and TROPOMI satellite data |
PU Dong-chuan1,2, WANG Da-kang3, ZHU Lei2, YANG Xian-kun3, WANG Jin-nian3 |
1. School of Environment, Harbin Institute of Technology, Harbin 150090, China; 2. School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China; 3. School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China |
|
|
Abstract Formaldehyde (HCHO) and nitrogen dioxide (NO2) are important precursors to ozone. HCHO to NO2 ratio (FNR) indicates the sensitivity of ozone production, serving as a primary reference for ozone pollution control. This study enhances the spatial resolution of TROPOMI HCHO and NO2 columns by oversampling algorithms, and reduces the uncertainty of TROPOMI data. It reveals the spatial distribution characteristics of HCHO and NO2 in Beijing during the summer of 2021. Based on FNR, the study diagnoses the sensitivity of ozone production in the Beijing areas. The study utilizes Landsat 8OLI data to calculate environmental indices and the proportion of impervious surfaces in the Beijing areas, and analyses their relationships with HCHO, NO2, and FNR. This Study aims to reveal the relationship between the degree of urbanization and the emissions of O3, VOCs, and NOx in Beijing. It finds that high NO2 columns are mainly distributed in the center of Beijing urban areas, with significantly reduced NO2 columns in non-urban areas. The mean NO2 columns increases with the proportion of impervious surfaces, but their standard deviation decreases, indicating that as urbanization in the urban areas of Beijing intensifies, the differences in NO2 emissions within urban areas diminish. The HCHO columns in urban Beijing are generally higher than those in non-urban areas, but the contribution of isoprene emissions from vegetation somewhat mitigates the disparity in VOCs emissions caused by the urbanization degree differences. Ozone in the urban area of Beijing and eastern Langfang area is controlled by VOCs, while ozone in the northern suburbs of Beijing is primarily controlled by NOx. The FNR mean decreases with an increase in the proportion of impervious surfaces, indicating that as urbanization in the Beijing area advances, the sensitivity of ozone production gradually shifts to a VOCs-controlled mechanism.
|
Received: 14 December 2023
|
|
|
|
|
[1] 蒋美青,陆克定,苏榕,等.我国典型城市群O3污染成因和关键VOCs活性解析[J]. 科学通报, 2018,63(12):1130-1141. Jiang M Q, Lu K D, Su R, et al. Origin and key VOCs activity analysis of O3pollution in typical urban agglomerations in China [J]. Science Bulletin, 2018,63(12):1130-1141. [2] 安俊琳,王跃思,孙扬.气象因素对北京臭氧的影响[J]. 生态环境学报, 2009,18(3):944-951. An J L, Wang Y S, Sun Y. Influence of meteorological factors on ozone in Beijing [J]. Journal of Ecology and Environment, 2009,18(3): 944-951. [3] 倪登峰,刘素,曹力媛,等.太原市采暖季PM2.5组分特征及重污染事件分析[J]. 中国环境科学, 2020,40(7):2821-2828. Ni D F, Liu S, Cao L Y, et al. Composition characteristics of PM2.5 and heavy pollution events in Taiyuan City during heating season [J]. China Environmental Science, 2020,40(7):2821-2828. [4] Jin X, Fiore A M, Murray L T, et al. Evaluating a space‐based indicator of surface ozone‐NOx‐VOC sensitivity over midlatitude source regions and application to decadal trends [J]. Journal of Geophysical Research: Atmospheres, 2017,122(19):101-119. [5] Seinfeld J H. Urban air pollution: state of the science [J]. Science, 1989,243(4892):745-752. [6] Sillman S, Samson P J. Impact of temperature on oxidant photochemistry in urban, polluted rural, and remote environments [J]. Journal of Geophysical Research: Atmospheres, 1995,100(D6):11497-114508. [7] Abbot D S, Palmer P I, Martin R V, et al. Seasonal and interannual variability of North American isoprene emissions as determined by formaldehyde column measurements from space [J]. Geophysical Research Letters, 2003,30(17):322-329. [8] Wittrock F, Richter A, Oetjen H, et al. Simultaneous global observations of glyoxal and formaldehyde from space [J]. Geophysical Research Letters, 2006,33(16):8893-8901. [9] Zhu L, Jacob D J, Mickley L J, et al. Anthropogenic emissions of highly reactive volatile organic compounds in eastern Texas inferred from oversampling of satellite (OMI) measurements of HCHO columns [J]. Environmental Research Letters, 2014,9(11):152-163. [10] De Smedt I, Stavrakou T, Hendrick F, et al. Diurnal, seasonal, and long-term variations of global formaldehyde columns inferred from combined OMI and GOME-2observations [J]. Atmospheric Chemistry and Physics, 2015,15(21):12519-12545. [11] Gao J B, Chen H B, Liu Y, et al. The effect of after-treatment techniques on the correlations between driving behaviors and NOx emissions of passenger cars [J]. Journal of Cleaner Production, 2021:288-301. [12] 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. [13] De Smedt I, Muller J F, Stavrakou T, et al. Twelve years of global observations of formaldehyde in the troposphere using GOME and SCIAMACHY sensors [J]. Atmospheric Chemistry and Physics, 2008, 8(16):4947-4963. [14] Choi W, Faloona I C, Bouvier-Brown N C, et al. Observations of elevated formaldehyde over a forest canopy suggest missing sources from rapid oxidation of arboreal hydrocarbons [J]. Atmospheric Chemistry and Physics, 2010,10(18):8761-8781. [15] Cazorla M, Wolfe G M, Bailey S A, et al. A new airborne laser- induced fluorescence instrument for in situ detection of formaldehyde throughout the troposphere and lower stratosphere [J]. Atmospheric Measurement Techniques, 2015,8(2):541-552. [16] Wang Y, Beirle S, Lampel J, et al. Validation of OMI, GOME-2A and GOME-2B tropospheric NO2, SO2 and HCHO products using MAX- DOAS observations from 2011 to 2014 in Wuxi, China: investigation of the effects of priori profiles and aerosols on the satellite products [J]. Atmospheric Chemistry and Physics, 2017,17(8):5007-5033. [17] Fioletov V E, McLinden C A, Krotkov N, et al. Application of OMI, SCIAMACHY, and GOME-2 satellite SO2 retrievals for detection of large emission sources [J]. Journal of Geophysical Research: Atmospheres, 2013,118(19):11,399-11,418. [18] Marais E A, Jacob D J, Kurosu T P, et al. Isoprene emissions in Africa inferred from OMI observations of formaldehyde columns [J]. Atmospheric Chemistry and Physics, 2012,12(14):6219-6235. [19] De Smedt I, Theys N, Yu H, et al. Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project [J]. Atmospheric Measurement Techniques, 2018,11(4):2395-2426. [20] Griffin D, McLinden C A, Boersma F, et al. High-resolution mapping of nitrogen dioxide with TROPOMI: First results and validation over the Canadian oil sands [J]. Geophysical Research Letters, 2019,46(2):1049-1060. [21] Van Geffen J, Boersma K F, Eskesl H, et al. S5P TROPOMI NO2 slant column retrieval: Method, stability, uncertainties and comparisons with OMI [J]. Atmospheric Measurement Techniques, 2020,13(3):1315-1335. [22] Veefkind J P, Aben I, McMullan K, et al. TROPOMI on the ESA Sentinel-5Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality, and ozone layer applications [J]. Remote Sensing of Environment, 2012,120:70-83. [23] Zhu L, Mickley L J, Jacob D J, et al. Long-term (2005~2014) trends in formaldehyde (HCHO) columns across North America as seen by the OMI satellite instrument: Evidence of changing emissions of volatile organic compounds [J]. Geophysical Research Letters, 2017,44(13):7079-7086. [24] Roy D P, Wulder M A, Loveland T R, et al. Landsat-8: Science and product vision for terrestrial global change research [J]. Remote Sensing of Environment, 2014,145:154-172. [25] De Smedt I, Pinardi G, Vigouroux C, et al. Comparative assessment of TROPOMI and OMI formaldehyde observations and validation against MAX-DOAS network column measurements [J]. Atmospheric Chemistry and Physics, 2021,21(16):12561-12593. [26] Chan K L, Wiegner M, Van Geffen J, et al. MAX-DOAS measurements of tropospheric NO2 and HCHO in Munich and the comparison to OMI and TROPOMI satellite observations [J]. Atmospheric Measurement Techniques, 2020,13(8):4499-4520. [27] Vigouroux C, Langerock B, Aquino C A B, et al. TROPOMI- Sentinel-5 Precursor formaldehyde validation using an extensive network of ground-based Fourier-transform infrared stations [J]. Atmospheric Measurement Techniques, 2020,13(7):3751-3767. [28] Verhoelst T, Compernolle S, Pinardi G, et al. Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS, and Pandonia global networks [J]. Atmospheric Measurement Techniques Discussions, 2020,2020:1-40. [29] Holden C E, Woodcock C E. An analysis of Landsat 7 and Landsat 8 underflight data and the implications for time series investigations [J]. Remote Sensing of Environment, 2016,185:16-36. [30] Zhang Z M, Pu D C, Wei M Y, et al. Assessment of annual composite images obtained by Google Earth Engine for urban areas mapping using random forest [J]. Remote Sensing, 2021,13(4):78-92. [31] Zhu L, Abad G G, Nowlan C R, et al. Validation of satellite formaldehyde (HCHO) retrievals using observations from 12 aircraft campaigns [J]. Atmospheric Chemistry and Physics, 2020,20(20): 12329-12345. [32] Jin X, Fiore A, Boersma K F, et al. Inferring changes in summertime surface ozone–NOx–VOC chemistry over US urban areas from two decades of satellite and ground-based observations [J]. Environmental Science & Technology, 2020,54(11):6518-6529. [33] Ren J, Guo F, Xie S. Diagnosing ozone–NOx–VOC sensitivity and revealing causes of ozone increases in China based on 2013~2021 satellite retrievals [J]. Atmospheric Chemistry and Physics, 2022, 22(22):15035-15047. [34] Souri A H, Nowlan C R, Wolfe G M, et al. Revisiting the effectiveness of HCHO/NO2 ratios for inferring ozone sensitivity to its precursors using high resolution airborne remote sensing observations in a high ozone episode during the KORUS-AQ campaign [J]. Atmospheric Environment, 2020,224:117341-117363. [35] Acdan J J M, Pierce R B, Dickens A F, et al. Examining TROPOMI formaldehyde to nitrogen dioxide ratios in the Lake Michigan region: Implications for ozone exceedances [J]. Atmospheric Chemistry and Physics, 2023,23(14):7867-7885. [36] De Hoogh K, Gulliver J, Donkelaar A V, et al. Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modeling data [J]. Environmental Research, 2016,151:1-10. [37] Sun Y, Yin H, Liu C, et al. Mapping the drivers of formaldehyde (HCHO) variability from 2015~2019 over eastern China: Insights from FTIR observation and GEOS-Chem model simulation [J]. Atmospheric Chemistry & Physics Discussions, 2020,12:990-1002. [38] Green J R, Fiddler M N, Fibiger D L, et al. Wintertime formaldehyde: airborne observations and source apportionment over the Eastern United States [J]. Journal of Geophysical Research: Atmospheres, 2021,126(5):518-535. [39] 桂海林,江琪,康志明,等.2016年冬季北京地区一次重污染天气过程边界层特征[J]. 中国环境科学, 2019,39(7):2739-2747. Gui H L, Jiang Q, Kang Z M, et al. Analysis of boundary layer characteristics of a heavily polluted weather process in Beijing in winter 2016[J]. China Environmental Science, 2019,39(7):2739-2747. [40] 蔡斌,程昊淼,亓浩雲,等.京津冀植被类型对典型城市夏季O3和PM2.5贡献[J]. 中国环境科学, 2023,43(6):2734-2743. Cai B, Cheng H M, Qi H Y, et al. Contributions to O3 and PM2.5 in summer of vegetation types in typical cities in Beijing-Tianjin-Hebei region [J]. China Environmental Science, 2023,43(6):2734-2743. |
|
|
|