Articles | Volume 23, issue 3
https://doi.org/10.5194/acp-23-1803-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-1803-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Feb 2023
Research article |
| 02 Feb 2023
| 02 Feb 2023
Evaluation of transport processes over North China Plain and Yangtze River Delta using MAX-DOAS observations
Yuhang Song
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, 230026, China
Chengzhi Xing
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
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, 230026, China
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
Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei, 230026, China
Jinan Lin
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
Hongyu Wu
School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei, 230026, China
Ting Liu
School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, China
Hua Lin
School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei, 230026, China
Chengxin Zhang
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, 230026, China
Wei Tan
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
Xiangguang Ji
School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei, 230026, China
Haoran Liu
Institute of Physical Science and Information Technology, Anhui University, Hefei, 230601, China
Qihua Li
Institute of Physical Science and Information Technology, Anhui University, Hefei, 230601, China
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Short summary
The paper presents an improved retrieval of the TROPOMI tropospheric HCHO column over China. The new retrieval optimized both slant column retrieval and air mass factor calculation for TROPOMI observations of HCHO over China. The improved TROPOMI HCHO is subsequently validated by MAX-DOAS observations. Compared to the operational product, the improved HCHO agrees better with the MAX-DOAS data and thus is better suited for the analysis of regional- and city-scale pollution in China.
Yang Wang, Arnoud Apituley, Alkiviadis Bais, Steffen Beirle, Nuria Benavent, Alexander Borovski, Ilya Bruchkouski, Ka Lok Chan, Sebastian Donner, Theano Drosoglou, Henning Finkenzeller, Martina M. Friedrich, Udo Frieß, David Garcia-Nieto, Laura Gómez-Martín, François Hendrick, Andreas Hilboll, Junli Jin, Paul Johnston, Theodore K. Koenig, Karin Kreher, Vinod Kumar, Aleksandra Kyuberis, Johannes Lampel, Cheng Liu, Haoran Liu, Jianzhong Ma, Oleg L. Polyansky, Oleg Postylyakov, Richard Querel, Alfonso Saiz-Lopez, Stefan Schmitt, Xin Tian, Jan-Lukas Tirpitz, Michel Van Roozendael, Rainer Volkamer, Zhuoru Wang, Pinhua Xie, Chengzhi Xing, Jin Xu, Margarita Yela, Chengxin Zhang, and Thomas Wagner
Atmos. Meas. Tech., 13, 5087–5116, https://doi.org/10.5194/amt-13-5087-2020, https://doi.org/10.5194/amt-13-5087-2020, 2020
Cited articles
Aliwell, S. R.: Analysis for BrO in zenith-sky spectra: An intercomparison
exercise for analysis improvement, J. Geophys. Res., 107, ACH 10-1–ACH 10-20,
https://doi.org/10.1029/2001jd000329, 2002.
Anderson, G. P., Clough, S. A., Kneizys, F., Chetwynd, J. H., and Shettle,
E. P.: AFGL Atmospheric Constituent Profiles (0.120 km), Air Force Geophysics Laboratory, Hanscom AFB MA, Tech. rep., 1986.
Barrett, E. W. and Ben-Dov, O.: Application of the Lidar to Air Pollution
Measurements, J. Appl. Meteorol. Clim., 6, 500–515,
https://doi.org/10.1175/1520-0450(1967)006<0500:AOTLTA>2.0.CO;2, 1967.
Bauer, S. E., Balkanski, Y., Schulz, M., Hauglustaine, D. A., and Dentener, F.: Global modeling of heterogeneous chemistry on mineral aerosol surfaces: Influence on tropospheric ozone chemistry and comparison to observations, J. Geophys. Res., 109, D02304, https://doi.org/10.1029/2003JD003868, 2004.
Behera, S. N. and Sharma, M.: Degradation of SO2, NO2 and NH3 leading to
formation of secondary inorganic aerosols: An environmental chamber study,
Atmos. Environ., 45, 4015–4024, https://doi.org/10.1016/j.atmosenv.2011.04.056, 2011.
Bessho, K., Date, K., Hayashi, M., Ikeda, A., Imai, T., Inoue, H., Kumagai,
Y., Miyakawa, T., Murata, H., Ohno, T., Okuyama, A., Oyama, R., Sasaki, Y.,
Shimazu, Y., Shimoji, K., Sumida, Y., Suzuki, M., Taniguchi, H., Tsuchiyama,
H., Uesawa, D., Yokota, H., and Yoshida, R.: An Introduction to Himawari-8/9 – Japan's New-Generation Geostationary Meteorological Satellites, J. Meteorol. Soc. Jpn., Ser. II, 94, 151–183, https://doi.org/10.2151/jmsj.2016-009, 2016.
Bharali, C., Nair, V. S., Chutia, L., and Babu, S. S.: Modeling of the
Effects of Wintertime Aerosols on Boundary Layer Properties Over the Indo
Gangetic Plain, J. Geophys. Res.-Atmos., 124, 4141–4157, https://doi.org/10.1029/2018jd029758, 2019.
Castellanos, P., Marufu, L. T., Doddridge, B. G., Taubman, B. F., Schwab, J.
J., Hains, J. C., Ehrman, S. H., and Dickerson, R. R.: Ozone, oxides of nitrogen, and carbon monoxide during pollution events over the eastern United States: An evaluation of emissions and vertical mixing, J. Geophys. Res., 116, D16307, https://doi.org/10.1029/2010jd014540, 2011.
Chance, K. and Spurr, R. J. D.: Ring effect studies: Rayleigh scattering,
including molecular parameters for rotational Raman scattering and the
Fraunhofer spectrum, Appl. Optics, 36, 5224–5230, https://doi.org/10.1364/AO.36.005224, 1997.
Chan, K. L., Wiegner, M., Wenig, M., and Pohler, D.: Observations of
tropospheric aerosols and NO2 in Hong Kong over 5years using ground based
MAX-DOAS, Sci. Total Environ., 619–620, 1545–1556,
https://doi.org/10.1016/j.scitotenv.2017.10.153, 2018.
Chan, K. L., Wang, Z., Ding, A., Heue, K.-P., Shen, Y., Wang, J., Zhang, F., Shi, Y., Hao, N., and Wenig, M.: MAX-DOAS measurements of tropospheric NO2 and HCHO in Nanjing and a comparison to ozone monitoring instrument observations, Atmos. Chem. Phys., 19, 10051–10071, https://doi.org/10.5194/acp-19-10051-2019, 2019.
Chang, S. and Allen, D. T.: Atmospheric chlorine chemistry in southeast
Texas: impacts on ozone formation and control, Environ. Sci. Technol., 40, 251–262, https://doi.org/10.1021/es050787z, 2006.
Charlson, R. J.: Atmospheric visibility related to aerosol mass
concentration, Environ. Sci. Technol., 3, 913–918,
https://doi.org/10.1021/es60033a002, 1969.
Charlson, R. J., Ahlquist, N. C., and Horvath, H.: On the generality of correlation of atmospheric aerosol mass concentration and light scatter, Atmos. Environ., 2, 455–464, https://doi.org/10.1016/0004-6981(68)90039-5, 1968.
Che, H., Gui, K., Xia, X., Wang, Y., Holben, B. N., Goloub, P., Cuevas-Agulló, E., Wang, H., Zheng, Y., Zhao, H., and Zhang, X.: Large contribution of meteorological factors to inter-decadal changes in regional aerosol optical depth, Atmos. Chem. Phys., 19, 10497–10523, https://doi.org/10.5194/acp-19-10497-2019, 2019.
Chen, T., Xue, L., Zheng, P., Zhang, Y., Liu, Y., Sun, J., Han, G., Li, H., Zhang, X., Li, Y., Li, H., Dong, C., Xu, F., Zhang, Q., and Wang, W.: Volatile organic compounds and ozone air pollution in an oil production region in northern China, Atmos. Chem. Phys., 20, 7069–7086, https://doi.org/10.5194/acp-20-7069-2020, 2020.
Chen, T., Zheng, P., Zhang, Y., Dong, C., Han, G., Li, H., Yang, X., Liu,
Y., Sun, J., Li, H., Zhang, X., Li, Y., Wang, W., and Xue, L.:
Characteristics and formation mechanisms of atmospheric carbonyls in an
oilfield region of northern China, Atmos. Environ., 274, 118958,
https://doi.org/10.1016/j.atmosenv.2022.118958, 2022.
Collis, R. T. H.: Lidar: A new atmospheric probe, Q. J. Roy. Meteor. Soc., 92, 220–230, https://doi.org/10.1002/qj.49709239205, 1966.
Corrigan, C. E., Roberts, G. C., Ramana, M. V., Kim, D., and Ramanathan, V.: Capturing vertical profiles of aerosols and black carbon over the Indian Ocean using autonomous unmanned aerial vehicles, Atmos. Chem. Phys., 8, 737–747, https://doi.org/10.5194/acp-8-737-2008, 2008.
Dentener, F. J., Carmichael, G. R., Zhang, Y., Lelieveld, J., and Crutzen,
P. J.: Role of mineral aerosol as a reactive surface in the global
troposphere, J. Geophys. Res.-Atmos., 101, 22869–22889, https://doi.org/10.1029/96jd01818, 1996.
Ding, A. J., Wang, T., Thouret, V., Cammas, J.-P., and Nédélec, P.: Tropospheric ozone climatology over Beijing: analysis of aircraft data from the MOZAIC program, Atmos. Chem. Phys., 8, 1–13, https://doi.org/10.5194/acp-8-1-2008, 2008.
Ding, A. J., Fu, C. B., Yang, X. Q., Sun, J. N., Zheng, L. F., Xie, Y. N., Herrmann, E., Nie, W., Petäjä, T., Kerminen, V.-M., and Kulmala, M.: Ozone and fine particle in the western Yangtze River Delta: an overview of 1 yr data at the SORPES station, Atmos. Chem. Phys., 13, 5813–5830, https://doi.org/10.5194/acp-13-5813-2013, 2013.
Dong, Z., Wang, S., Xing, J., Chang, X., Ding, D., and Zheng, H.: Regional
transport in Beijing-Tianjin-Hebei region and its changes during 2014–2017:
The impacts of meteorology and emission reduction, Sci. Total Environ., 737,
139792, https://doi.org/10.1016/j.scitotenv.2020.139792, 2020.
Ferrero, L., Mocnik, G., Ferrini, B. S., Perrone, M. G., Sangiorgi, G., and
Bolzacchini, E.: Vertical profiles of aerosol absorption coefficient from
micro-Aethalometer data and Mie calculation over Milan, Sci. Total Environ.,
409, 2824–2837, https://doi.org/10.1016/j.scitotenv.2011.04.022, 2011.
Fleischmann, O. C., Hartmann, M., Burrows, J. P., and Orphal, J.: New
ultraviolet absorption cross-sections of BrO at atmospheric temperatures
measured by time-windowing Fourier transform spectroscopy, J. Photoch.
Photobio. A, 168, 117–132, https://doi.org/10.1016/j.jphotochem.2004.03.026, 2004.
Friedrich, M. M., Rivera, C., Stremme, W., Ojeda, Z., Arellano, J., Bezanilla, A., García-Reynoso, J. A., and Grutter, M.: NO2 vertical profiles and column densities from MAX-DOAS measurements in Mexico City, Atmos. Meas. Tech., 12, 2545–2565, https://doi.org/10.5194/amt-12-2545-2019, 2019.
Frieß, U., Monks, P. S., Remedios, J. J., Rozanov, A., Sinreich, R.,
Wagner, T., and Platt, U.: MAX-DOAS O4 measurements: A new technique to
derive information on atmospheric aerosols: 2. Modeling studies, J.
Geophys. Res., 111, D14203, https://doi.org/10.1029/2005jd006618, 2006.
Gao, M., Saide, P. E., Xin, J., Wang, Y., Liu, Z., Wang, Y., Wang, Z.,
Pagowski, M., Guttikunda, S. K., and Carmichael, G. R.: Estimates of Health
Impacts and Radiative Forcing in Winter Haze in Eastern China through
Constraints of Surface PM2.5 Predictions, Environ. Sci. Technol., 51, 2178–2185, https://doi.org/10.1021/acs.est.6b03745, 2017.
George, C., Strekowski, R. S., Kleffmann, J., Stemmler, K., and Ammann, M.:
Photoenhanced uptake of gaseous NO2 on solid organic compounds: A
photochemical source of HONO?, Faraday Discuss., 130, 195–210, 2005.
Ge, B., Wang, Z., Lin, W., Xu, X., Li, J., Ji, D., and Ma, Z.: Air pollution
over the North China Plain and its implication of regional transport: A new
sight from the observed evidences, Environ. Pollut., 234, 29–38,
https://doi.org/10.1016/j.envpol.2017.10.084, 2018.
Ge, B. Z., Xu, X. B., Lin, W. L., Li, J., and Wang, Z. F.: Impact of the
regional transport of urban Beijing pollutants on downwind areas in summer:
ozone production efficiency analysis, Tellus B, 64, 17348, https://doi.org/10.3402/tellusb.v64i0.17348, 2012.
Grainger, J. F. and Ring, J.: Anomalous Fraunhofer line profiles, Nature,
193, 762, https://doi.org/10.1038/193762a0, 1962.
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G.,
Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within
the WRF model, Atmos. Environ., 39, 6957–6975, https://doi.org/10.1016/j.atmosenv.2005.04.027, 2005.
Guo, X., He, S., Liu, K., Song, G., Wang, X., and Shi, Z.: Oil generation as
the dominant overpressure mechanism in the Cenozoic Dongying depression,
Bohai Bay Basin, China, AAPG Bulletin, 94, 1859–1881, https://doi.org/10.1306/05191009179, 2010.
Han, P., Zeng, N., Oda, T., Zhang, W., Lin, X., Liu, D., Cai, Q., Ma, X.,
Meng, W., Wang, G., Wang, R., and Zheng, B.: A city-level comparison of
fossil-fuel and industry processes-induced CO2 emissions over the
Beijing-Tianjin-Hebei region from eight emission inventories, Carbon Balance and Management, 15, 25, https://doi.org/10.1186/s13021-020-00163-2, 2020.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F., Jankowiak, I., and Smirnov, A.: AERONET–A Federated Instrument Network and Data Archive for Aerosol Characterization, Remote Sens. Environ., 66, 1–16,
https://doi.org/10.1016/S0034-4257(98)00031-5, 1998.
Hong, Q., Liu, C., Hu, Q., Zhang, Y., Xing, C., Ou, J., Tan, W., Liu, H.,
Huang, X., and Wu, Z.: Vertical distribution and temporal evolution of
formaldehyde and glyoxal derived from MAX-DOAS observations: The indicative
role of VOC sources, J. Environ. Sci., 122, 92–104,
https://doi.org/10.1016/j.jes.2021.09.025, 2022a.
Hong, Q., Zhu, L., Xing, C., Hu, Q., Lin, H., Zhang, C., Zhao, C., Liu, T.,
Su, W., and Liu, C.: Inferring vertical variability and diurnal evolution of
O3 formation sensitivity based on the vertical distribution of summertime
HCHO and NO2 in Guangzhou, China, Sci. Total Environ., 827, 154045,
https://doi.org/10.1016/j.scitotenv.2022.154045, 2022b.
Hönninger, G. and Platt, U.: Observations of BrO and its vertical
distribution during surface ozone depletion at Alert, Atmos. Environ., 36,
2481–2489, https://doi.org/10.1016/S1352-2310(02)00104-8, 2002.
Hönninger, G., von Friedeburg, C., and Platt, U.: Multi axis differential optical absorption spectroscopy (MAX-DOAS), Atmos. Chem. Phys., 4, 231–254, https://doi.org/10.5194/acp-4-231-2004, 2004.
Huang, M., Crawford, J. H., Diskin, G. S., Santanello, J. A., Kumar, S. V.,
Pusede, S. E., Parrington, M., and Carmichael, G. R.: Modeling regional
pollution transport events during KORUS-AQ: Progress and challenges in
improving representation of land-atmosphere feedbacks, J. Geophys. Res.-Atmos., 123, 10732–10756, https://doi.org/10.1029/2018JD028554, 2018.
Huang, R. J., Zhang, Y., Bozzetti, C., Ho, K. F., Cao, J. J., Han, Y.,
Daellenbach, K. R., Slowik, J. G., Platt, S. M., Canonaco, F., Zotter, P.,
Wolf, R., Pieber, S. M., Bruns, E. A., Crippa, M., Ciarelli, G., Piazzalunga, A., Schwikowski, M., Abbaszade, G., Schnelle-Kreis, J., Zimmermann, R., An, Z., Szidat, S., Baltensperger, U., El Haddad, I., and Prevot, A. S.: High secondary aerosol contribution to particulate pollution during haze events in China, Nature, 514, 218–222, https://doi.org/10.1038/nature13774, 2014.
Huang, X., Zhou, L., Ding, A., Qi, X., Nie, W., Wang, M., Chi, X., Petäjä, T., Kerminen, V.-M., Roldin, P., Rusanen, A., Kulmala, M., and Boy, M.: Comprehensive modelling study on observed new particle formation at the SORPES station in Nanjing, China, Atmos. Chem. Phys., 16, 2477–2492, https://doi.org/10.5194/acp-16-2477-2016, 2016.
Huang, X., Wang, Z., and Ding, A.: Impact of Aerosol-PBL Interaction on Haze
Pollution: Multiyear Observational Evidences in North China, Geophys. Res. Lett., 45, 8596–8603, https://doi.org/10.1029/2018gl079239, 2018.
Huang, X., Ding, A., Wang, Z., Ding, K., Gao, J., Chai, F., and Fu, C.:
Amplified transboundary transport of haze by aerosol–boundary layer
interaction in China, Nat. Geosci., 13, 428–434,
https://doi.org/10.1038/s41561-020-0583-4, 2020.
Irie, H., Kanaya, Y., Akimoto, H., Iwabuchi, H., Shimizu, A., and Aoki, K.: First retrieval of tropospheric aerosol profiles using MAX-DOAS and comparison with lidar and sky radiometer measurements, Atmos. Chem. Phys., 8, 341–350, https://doi.org/10.5194/acp-8-341-2008, 2008.
Kong, S., Lu, B., Ji, Y., Zhao, X., Bai, Z., Xu, Y., Liu, Y., and Jiang, H.:
Risk assessment of heavy metals in road and soil dusts within PM2.5, PM10 and PM100 fractions in Dongying city, Shandong Province, China, J. Environ. Monitor., 14, 791–803, https://doi.org/10.1039/c1em10555h, 2012.
Kong, S., Ji, Y., Lu, B., Zhao, X., Han, B., and Bai, Z.: Similarities and
Differences in PM2.5, PM10 and TSP Chemical Profiles of Fugitive Dust Sources in a Coastal Oilfield City in China, Aerosol Air Qual. Res., 14, 2017–2028, https://doi.org/10.4209/aaqr.2013.06.0226, 2014.
Kraus, S. G.: DOASIS: A Framework Design for DOAS, PhD thesis, University of Mannheim, Mannheim, Germany, 2006.
Kumar, R., Barth, M. C., Madronich, S., Naja, M., Carmichael, G. R., Pfister, G. G., Knote, C., Brasseur, G. P., Ojha, N., and Sarangi, T.: Effects of dust aerosols on tropospheric chemistry during a typical pre-monsoon season dust storm in northern India, Atmos. Chem. Phys., 14, 6813–6834, https://doi.org/10.5194/acp-14-6813-2014, 2014.
Kumar, V., Beirle, S., Dörner, S., Mishra, A. K., Donner, S., Wang, Y., Sinha, V., and Wagner, T.: Long-term MAX-DOAS measurements of NO2, HCHO, and aerosols and evaluation of corresponding satellite data products over Mohali in the Indo-Gangetic Plain, Atmos. Chem. Phys., 20, 14183–14235, https://doi.org/10.5194/acp-20-14183-2020, 2020.
Lampel, J., Frieß, U., and Platt, U.: The impact of vibrational Raman scattering of air on DOAS measurements of atmospheric trace gases, Atmos. Meas. Tech., 8, 3767–3787, https://doi.org/10.5194/amt-8-3767-2015,
2015.
Li, J., Du, H. Y., Wang, Z. F., Sun, Y. L., Yang, W. Y., Li, J. J., Tang,
X., and Fu, P. Q.: Rapid formation of a severe regional winter haze episode
over a mega-city cluster on the North China Plain, Environ. Pollut., 223, 605–615, 2017.
Li, S., Feng, K., and Li, M.: Identifying the main contributors of air
pollution in Beijing, J. Clean. Prod., 163, S359–S365, https://doi.org/10.1016/j.jclepro.2015.10.127, 2017.
Li, Z. Q., Guo, J. P., Ding, A. J., Liao, H., Liu, J. J., Sun, Y. L., Wang,
T. J., Xue, H. W., Zhang, H. S., and Zhu, B.: Aerosol and boundary-layer
interactions and impact on air quality, Natl. Sci. Rev., 4, 810–833,
https://doi.org/10.1093/nsr/nwx117, 2017.
Liu, C., Xing, C., Hu, Q., Li, Q., Liu, H., Hong, Q., Tan, W., Ji, X., Lin,
H., Lu, C., Lin, J., Liu, H., Wei, S., Chen, J., Yang, K., Wang, S., Liu,
T., and Chen, Y.: Ground-based Hyperspectral Stereoscopic Remote Sensing
Network: A Promising Strategy to Learn Coordinated Control of O3 and PM2.5 over China, Engineering, https://doi.org/10.1016/j.eng.2021.02.019, in press, 2021.
Liu, C., Xing, C., Hu, Q., Wang, S., Zhao, S., and Gao, M.: Stereoscopic
hyperspectral remote sensing of the atmospheric environment: Innovation and
prospects, Earth-Sci. Rev., 226, 103958, https://doi.org/10.1016/j.earscirev.2022.103958, 2022.
Liu, Y., Song, M., Liu, X., Zhang, Y., Hui, L., Kong, L., Zhang, Y., Zhang,
C., Qu, Y., An, J., Ma, D., Tan, Q., and Feng, M.: Characterization and
sources of volatile organic compounds (VOCs) and their related changes
during ozone pollution days in 2016 in Beijing, China, Environ. Pollut., 257,
113599, https://doi.org/10.1016/j.envpol.2019.113599, 2020.
Lv, L., Liu, W., Zhang, T., Chen, Z., Dong, Y., Fan, G., Xiang, Y., Yao, Y.,
Yang, N., Chu, B., Teng, M., and Shu, X.: Observations of particle
extinction, PM2.5 mass concentration profile and flux in north China based on mobile lidar technique, Atmos. Environ., 164, 360–369,
2017.
Mayer, B. and Kylling, A.: Technical note: The libRadtran software package for radiative transfer calculations – description and examples of use, Atmos. Chem. Phys., 5, 1855–1877, https://doi.org/10.5194/acp-5-1855-2005, 2005.
McCormick, R. A. and Ludwig, J. H.: Climate modification by atmospheric
aerosols, Science, 156, 1358–1359, https://doi.org/10.1126/science.156.3780.1358, 1967.
McMurry, P. H. and Wilson, J. C.: Droplet phase (Heterogeneous) and gas
phase (homogeneous) contributions to secondary ambient aerosol formation as
functions of relative humidity, J. Geophys. Res., 88, 5101–5108, https://doi.org/10.1029/JC088iC09p05101, 1983.
Meena, G.: Influence of tropospheric clouds on ground-based measurements of
stratospheric trace gases at Tropical station, Pune, Atmos. Environ., 38,
3459–3468, https://doi.org/10.1016/j.atmosenv.2004.02.050, 2004.
Mitchell Jr., J. M.: The Effect of Atmospheric Aerosols on Climate with
Special Reference to Temperature near the Earth's Surface, J. Appl. Meteorol. Clim., 10, 703–714 https://doi.org/10.1175/1520-0450(1971)010<0703:TEOAAO>2.0.CO;2, 1971.
Nasse, J.-M., Eger, P. G., Pöhler, D., Schmitt, S., Frieß, U., and Platt, U.: Recent improvements of long-path DOAS measurements: impact on accuracy and stability of short-term and automated long-term observations, Atmos. Meas. Tech., 12, 4149–4169, https://doi.org/10.5194/amt-12-4149-2019, 2019.
Ndour, M., D'Anna, B., George, C., Ka, O., Balkanski, Y., Kleffmann, J.,
Stemmler, K., and Ammann, M.: Photoenhanced uptake of NO2 on mineral dust:
Laboratory experiments and model simulations, Geophys. Res. Lett., 35, L05812, https://doi.org/10.1029/2007gl032006, 2008.
Orphal, J. and Chance, K.: Ultraviolet and visible absorption cross-sections
for HITRAN, J. Quant. Spectrosc. Ra., 82, 491–504, https://doi.org/10.1016/s0022-4073(03)00173-0, 2003.
Petäjä, T., Järvi, L., Kerminen, V. M., Ding, A. J., Sun, J. N., Nie, W.,
Kujansuu, J., Virkkula, A., Yang, X. Q., Fu, C. B., Zilitinkevich, S., and
Kulmala, M.: Enhanced air pollution via aerosol-boundary layer feedback in
China, Sci. Rep., 6, 18998, https://doi.org/10.1038/srep18998, 2016.
Platt, U. and Stutz, J.: Differential Absorption Spectroscopy: Principles and Applications, Springer, Heidelberg, Berlin, https://doi.org/10.1007/978-3-540-75776-4, 2008.
Pokharel, M., Guang, J., Liu, B., Kang, S. C., Ma, Y. M., Holben, B. N.,
Xia, X. A., Xin, J. Y., Ram, K., Rupakheti, D., Wan, X., Wu, G. M.,
Bhattarai, H., Zhao, C. F., and Cong, Z. Y.: Aerosol Properties Over Tibetan
Plateau From a Decade of AERONET Measurements: Baseline, Types, and
Influencing Factors, J. Geophys. Res.-Atmos., 124, 13357–13374,
https://doi.org/10.1029/2019jd031293, 2019.
Qi, J., Zheng, B., Li, M., Yu, F., Chen, C., Liu, F., Zhou, X., Yuan, J.,
Zhang, Q., and He, K.: A high-resolution air pollutants emission inventory
in 2013 for the Beijing-Tianjin-Hebei region, China, Atmos. Environ., 170,
156–168, https://doi.org/10.1016/j.atmosenv.2017.09.039, 2017.
Ran, L., Deng, Z., Xu, X., Yan, P., Lin, W., Wang, Y., Tian, P., Wang, P., Pan, W., and Lu, D.: Vertical profiles of black carbon measured by a micro-aethalometer in summer in the North China Plain, Atmos. Chem. Phys., 16, 10441–10454, https://doi.org/10.5194/acp-16-10441-2016, 2016.
Ravishankara, A. R.: Heterogeneous and Multiphase Chemistry in the Troposphere, Science, 276, 1058–1065, https://doi.org/10.1126/science.276.5315.1058, 1997.
Serdyuchenko, A., Gorshelev, V., Weber, M., Chehade, W., and Burrows, J. P.: High spectral resolution ozone absorption cross-sections – Part 2: Temperature dependence, Atmos. Meas. Tech., 7, 625–636, https://doi.org/10.5194/amt-7-625-2014, 2014.
Stemmler, K., Ammann, M., Donders, C., Kleffmann, J., and George, C.:
Photosensitized reduction of nitrogen dioxide on humic acid as a source of
nitrous acid, Nature, 440, 195–198, https://doi.org/10.1038/nature04603, 2006.
Stutz, J., Kim, E. S., Platt, U., Bruno, P., Perrino, C., and Febo, A.:
UV-visible absorption cross sections of nitrous acid, J. Geophys.
Res.-Atmos., 105, 14585–14592, https://doi.org/10.1029/2000jd900003, 2000.
Su, H., Cheng, Y. F., and Poschl, U.: New Multiphase Chemical Processes
Influencing Atmospheric Aerosols, Air Quality, and Climate in the
Anthropocene, Accounts Chem. Res., 53, 2034–2043,
https://doi.org/10.1021/acs.accounts.0c00246, 2020.
Su, W., Liu, C., Chan, K. L., Hu, Q., Liu, H., Ji, X., Zhu, Y., Liu, T., Zhang, C., Chen, Y., and Liu, J.: An improved TROPOMI tropospheric HCHO retrieval over China, Atmos. Meas. Tech., 13, 6271–6292, https://doi.org/10.5194/amt-13-6271-2020, 2020.
Sun, J., Huang, L., Liao, H., Li, J., and Hu, J.: Impacts of Regional
Transport on Particulate Matter Pollution in China: a Review of Methods and
Results, Current Pollution Reports, 3, 182–191, https://doi.org/10.1007/s40726-017-0065-5, 2017.
Tan, W., Liu, C., Wang, S., Xing, C., Su, W., Zhang, C., Xia, C., Liu, H., Cai, Z., and Liu, J.: Tropospheric NO2, SO2, and HCHO over the East China Sea, using ship-based MAX-DOAS observations and comparison with OMI and OMPS satellite data, Atmos. Chem. Phys., 18, 15387–15402, https://doi.org/10.5194/acp-18-15387-2018, 2018.
Tao, W., Su, H., Zheng, G., Wang, J., Wei, C., Liu, L., Ma, N., Li, M., Zhang, Q., Pöschl, U., and Cheng, Y.: Aerosol pH and chemical regimes of sulfate formation in aerosol water during winter haze in the North China Plain, Atmos. Chem. Phys., 20, 11729–11746, https://doi.org/10.5194/acp-20-11729-2020, 2020.
Thalman, R. and Volkamer, R.: Temperature dependent absorption
cross-sections of O2–O2 collision pairs between 340 and 630 nm and at
atmospherically relevant pressure, Phys. Chem. Chem. Phys., 15, 15371–15381,
https://doi.org/10.1039/c3cp50968k, 2013.
Tripathi, S. N., Dey, S., Tare, V., Satheesh, S. K., Lal, S., and Venkataramani, S.: Enhanced layer of black carbon in a north Indian industrial city, Geophys. Res. Lett., 32, L12802, https://doi.org/10.1029/2005GL022564, 2005.
Vandaele, A. C., Hermans, C., Simon, P. C., Carleer, M., Colin, R., Fally,
S., Merienne, M. F., Jenouvrier, A., and Coquart, B.: Measurements of the
NO2 absorption cross-section from 42 000 cm−1 to 10 000 cm−1 (238–1000 nm) at 220 K and 294 K, J. Quant. Spectrosc. Ra., 59, 171–184, https://doi.org/10.1016/S0022-4073(97)00168-4, 1998.
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J.,
Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele,
M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann,
P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.:
TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and
ozone layer applications, Remote Sens. Environ., 120, 70–83,
https://doi.org/10.1016/j.rse.2011.09.027, 2012.
Volkamer, R., Jimenez, J. L., San Martini, F., Dzepina, K., Zhang, Q., Salcedo, D., Molina, L. T., Worsnop, D. R., and Molina, M. J.: Secondary
organic aerosol formation from anthropogenic air pollution: Rapid and higher
than expected, Geophys. Res. Lett., 33, L17811, https://doi.org/10.1029/2006GL026899, 2006.
Wagner, T., Dix, B., Friedeburg, C. v., Frieß, U., Sanghavi, S.,
Sinreich, R., and Platt, U.: MAX-DOAS O4 measurements: A new technique to
derive information on atmospheric aerosols–Principles and information
content, J. Geophys. Res., 109, D22205, https://doi.org/10.1029/2004jd004904, 2004.
Wang, L., Liu, J., Gao, Z., Li, Y., Huang, M., Fan, S., Zhang, X., Yang, Y., Miao, S., Zou, H., Sun, Y., Chen, Y., and Yang, T.: Vertical observations of the atmospheric boundary layer structure over Beijing urban area during air pollution episodes, Atmos. Chem. Phys., 19, 6949–6967, https://doi.org/10.5194/acp-19-6949-2019, 2019.
Wang, S. and Hao, J.: Air quality management in China: Issues, challenges,
and options, J. Environ. Sci., 24, 2–13, https://doi.org/10.1016/s1001-0742(11)60724-9, 2012.
Wang, Y., Chen, Z., Wu, Q., Liang, H., Huang, L., Li, H., Lu, K., Wu, Y., Dong, H., Zeng, L., and Zhang, Y.: Observation of atmospheric peroxides during Wangdu Campaign 2014 at a rural site in the North China Plain, Atmos. Chem. Phys., 16, 10985–11000, https://doi.org/10.5194/acp-16-10985-2016, 2016.
Wang, Y., Lampel, J., Xie, P., Beirle, S., Li, A., Wu, D., and Wagner, T.: Ground-based MAX-DOAS observations of tropospheric aerosols, NO2, SO2 and HCHO in Wuxi, China, from 2011 to 2014, Atmos. Chem. Phys., 17, 2189–2215, https://doi.org/10.5194/acp-17-2189-2017, 2017.
Wang, Z., Liu, C., Dong, Y., Hu, Q., Liu, T., Zhu, Y., and Xing, C.:
Profiling of Dust and Urban Haze Mass Concentrations during the 2019
National Day Parade in Beijing by Polarization Raman Lidar, Remote Sens.,
13, 3326, https://doi.org/10.3390/rs13163326, 2021.
Wang, Z., Liu, C., Xie, Z., Hu, Q., Andreae, M. O., Dong, Y., Zhao, C., Liu, T., Zhu, Y., Liu, H., Xing, C., Tan, W., Ji, X., Lin, J., and Liu, J.: Elevated dust layers inhibit dissipation of heavy anthropogenic surface air pollution, Atmos. Chem. Phys., 20, 14917–14932, https://doi.org/10.5194/acp-20-14917-2020, 2020.
Wilcox, E. M., Thomas, R. M., Praveen, P. S., Pistone, K., Bender, F. A.,
and Ramanathan, V.: Black carbon solar absorption suppresses turbulence in
the atmospheric boundary layer, P. Natl. Acad. Sci. USA, 113, 11794–11799,
https://doi.org/10.1073/pnas.1525746113, 2016.
Wittrock, F., Oetjen, H., Richter, A., Fietkau, S., Medeke, T., Rozanov, A., and Burrows, J. P.: MAX-DOAS measurements of atmospheric trace gases in Ny-Ålesund – Radiative transfer studies and their application, Atmos. Chem. Phys., 4, 955–966, https://doi.org/10.5194/acp-4-955-2004, 2003.
Wu, H., Wang, Y., Li, H., Huang, L., Huang, D., Shen, H., Xing, Y., and
Chen, Z.: The OH-initiated oxidation of atmospheric peroxyacetic acid:
Experimental and model studies, Atmos. Environ., 164, 61–70,
https://doi.org/10.1016/j.atmosenv.2017.05.038, 2017.
Wu, J., Li, G., Cao, J., Bei, N., Wang, Y., Feng, T., Huang, R., Liu, S., Zhang, Q., and Tie, X.: Contributions of trans-boundary transport to summertime air quality in Beijing, China, Atmos. Chem. Phys., 17, 2035–2051, https://doi.org/10.5194/acp-17-2035-2017, 2017.
Wu, Y., Wang, R., Zhou, Y., Lin, B., Fu, L., He, K., and Hao, J.: On-Road
Vehicle Emission Control in Beijing: Past, Present, and Future, Environ. Sci. Technol., 45, 147–153, https://doi.org/10.1021/es1014289, 2011.
Xiang, Y., Zhang, T., Ma, C., Lv, L., Liu, J., Liu, W., and Cheng, Y.: Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain, Atmos. Chem. Phys., 21, 7023–7037, https://doi.org/10.5194/acp-21-7023-2021, 2021.
Xing, C., Liu, C., Wang, S., Chan, K. L., Gao, Y., Huang, X., Su, W., Zhang, C., Dong, Y., Fan, G., Zhang, T., Chen, Z., Hu, Q., Su, H., Xie, Z., and Liu, J.: Observations of the vertical distributions of summertime atmospheric pollutants and the corresponding ozone production in Shanghai, China, Atmos. Chem. Phys., 17, 14275–14289, https://doi.org/10.5194/acp-17-14275-2017, 2017.
Xing, C., Liu, C., Hu, Q., Fu, Q., Lin, H., Wang, S., Su, W., Wang, W.,
Javed, Z., and Liu, J.: Identifying the wintertime sources of volatile
organic compounds (VOCs) from MAX-DOAS measured formaldehyde and glyoxal in
Chongqing, southwest China, Sci. Total Environ., 715, 136258,
https://doi.org/10.1016/j.scitotenv.2019.136258, 2020.
Xing, C., Liu, C., Wu, H., Lin, J., Wang, F., Wang, S., and Gao, M.: Ground-based vertical profile observations of atmospheric composition on the Tibetan Plateau (2017–2019), Earth Syst. Sci. Data, 13, 4897–4912, https://doi.org/10.5194/essd-13-4897-2021, 2021a.
Xing, C., Liu, C., Hu, Q., Fu, Q., Wang, S., Lin, H., Zhu, Y., Wang, S.,
Wang, W., Javed, Z., Ji, X., and Liu, J.: Vertical distributions of
wintertime atmospheric nitrogenous compounds and the corresponding OH
radicals production in Leshan, southwest China, J. Environ. Sci., 105,
44–55, https://doi.org/10.1016/j.jes.2020.11.019, 2021b.
Xu, J., Chang, L., Qu, Y., Yan, F., Wang, F., and Fu, Q.: The meteorological
modulation on PM2.5 interannual oscillation during 2013 to 2015 in Shanghai, China, Sci. Total Environ., 572, 1138–1149, https://doi.org/10.1016/j.scitotenv.2016.08.024, 2016.
Yang, W., Yu, C., Yuan, W., Wu, X., Zhang, W., and Wang, X.: High-resolution
vehicle emission inventory and emission control policy scenario analysis, a
case in the Beijing-Tianjin-Hebei (BTH) region, China, J. Clean. Prod., 203, 530–539, https://doi.org/10.1016/j.jclepro.2018.08.256, 2018.
Zhang, H., Wang, S., Hao, J., Wang, X., Wang, S., Chai, F., and Li, M.: Air
pollution and control action in Beijing, J. Clean. Prod., 112, 1519–1527, https://doi.org/10.1016/j.jclepro.2015.04.092, 2016.
Zhang, Y., Chen, J., Yang, H., Li, R., and Yu, Q.: Seasonal variation and
potential source regions of PM2.5-bound PAHs in the megacity Beijing, China:
Impact of regional transport, Environ. Pollut., 231, 329–338,
https://doi.org/10.1016/j.envpol.2017.08.025, 2017.
Zhu, C., Tian, H., Hao, Y., Gao, J., Hao, J., Wang, Y., Hua, S., Wang, K.,
and Liu, H.: A high-resolution emission inventory of anthropogenic trace
elements in Beijing-Tianjin-Hebei (BTH) region of China, Atmos. Environ., 191, 452–462, https://doi.org/10.1016/j.atmosenv.2018.08.035, 2018.
Zhu, S., Li, X., Yu, C., Wang, H., Wang, Y., and Miao, J.: Spatiotemporal
Variations in Satellite-Based Formaldehyde (HCHO) in the
Beijing-Tianjin-Hebei Region in China from 2005 to 2015, Atmosphere, 9, 5,
https://doi.org/10.3390/atmos9010005, 2018.
Short summary
Using the MAX-DOAS network, we successfully analyzed three typical transport types (regional, dust, and transboundary long-range transport), emphasizing the unique advantages provided by the network in monitoring pollutant transport. We think that our findings provide the public with a thorough understanding of pollutant transport phenomena and a reference for designing collaborative air pollution control strategies.
Using the MAX-DOAS network, we successfully analyzed three typical transport types (regional,...
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