Articles | Volume 17, issue 7
https://doi.org/10.5194/essd-17-3167-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-3167-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
03 Jul 2025
Data description article |
| 03 Jul 2025
| 03 Jul 2025
A dataset of ground-based vertical profile observations of aerosol, NO2, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023)
Peiyuan Jiao
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Yikai Li
School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
Xiangguang Ji
Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China
Wei Tan
Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Qihua Li
Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China
Haoran Liu
Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
Key Laboratory of Environmental Optics and 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
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Manuscript not accepted for further review
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Cited articles
Aliwell, S. R., Van Roozendael, M., Johnston, P. V., Richter, A., Wagner, T., Arlander, D. W., Burrows, J. P., Fish, D. J., Jones, R. L., Tørnkvist, K. K., Lambert, J.-C., Pfeilsticker, K., and Pundt, I.: Analysis for BrO in zenith-sky spectra: An intercomparison exercise for analysis improvement, J. Geophys. Res.-Atmos., 107, ACH10-1–ACH10-20, https://doi.org/10.1029/2001JD000329, 2002.
Altshuller, A. P.: Production of aldehydes as primary emissions and from secondary atmospheric reactions of alkenes and alkanes during the night and early morning hours, Atmos. Environ. A-Gen., 27, 21–32, https://doi.org/10.1016/0960-1686(93)90067-9, 1993.
Bai, K., Li, K., Guo, J., Cheng, W., and Xu, X.: Do More Frequent Temperature Inversions Aggravate Haze Pollution in China?, Geophys. Res. Lett., 49, e2021GL096458, https://doi.org/10.1029/2021GL096458, 2022.
Biswas, M. S., Pandithurai, G., Aslam, M. Y., Patil, R. D., Anilkumar, V., Dudhambe, S. D., Lerot, C., De Smedt, I., Van Roozendael, M., and Mahajan, A. S.: Effect of Boundary Layer Evolution on Nitrogen Dioxide (NO2) and Formaldehyde (HCHO) Concentrations at a High-altitude Observatory in Western India, Aerosol Air Qual. Res., 21, 200193, https://doi.org/10.4209/aaqr.2020.05.0193, 2020.
Buzcu Guven, B. and Olaguer, E. P.: Ambient formaldehyde source attribution in Houston during TexAQS II and TRAMP, Atmos. Environ., 45, 4272–4280, https://doi.org/10.1016/j.atmosenv.2011.04.079, 2011.
Cai, H., Nan, Y., Zhao, Y., Jiao, W., and Pan, K.: Impacts of winter heating on the atmospheric pollution of northern China's prefectural cities: Evidence from a regression discontinuity design, Ecol. Indic., 118, 106709, https://doi.org/10.1016/j.ecolind.2020.106709, 2020.
Cao, J., Situ, S., Hao, Y., Xie, S., and Li, L.: Enhanced summertime ozone and SOA from biogenic volatile organic compound (BVOC) emissions due to vegetation biomass variability during 1981–2018 in China, Atmos. Chem. Phys., 22, 2351–2364, https://doi.org/10.5194/acp-22-2351-2022, 2022.
Carlier, P., Hannachi, H., and Mouvier, G.: The chemistry of carbonyl compounds in the atmosphere – A review, Atmos. Environ., 20, 2079–2099, https://doi.org/10.1016/0004-6981(86)90304-5, 1986.
Carter, W. P. L.: Computer modeling of environmental chamber measurements of maximum incremental reactivities of volatile organic compounds, Atmos. Environ., 29, 2513–2527, https://doi.org/10.1016/1352-2310(95)00150-W, 1995.
Cerón, R. M., Cerón, J. G., and Muriel, M.: Diurnal and seasonal trends in carbonyl levels in a semi-urban coastal site in the Gulf of Campeche, Mexico, Atmos. Environ., 41, 63–71, https://doi.org/10.1016/j.atmosenv.2006.08.008, 2007.
Chan, K. L., Valks, P., Heue, K.-P., Lutz, R., Hedelt, P., Loyola, D., Pinardi, G., Van Roozendael, M., Hendrick, F., Wagner, T., Kumar, V., Bais, A., Piters, A., Irie, H., Takashima, H., Kanaya, Y., Choi, Y., Park, K., Chong, J., Cede, A., Frieß, U., Richter, A., Ma, J., Benavent, N., Holla, R., Postylyakov, O., Rivera Cárdenas, C., and Wenig, M.: Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products of atmospheric trace gas columns, Earth Syst. Sci. Data, 15, 1831–1870, https://doi.org/10.5194/essd-15-1831-2023, 2023.
Chang, S.-C. and Lee, C.-T.: Secondary aerosol formation through photochemical reactions estimated by using air quality monitoring data in Taipei City from 1994–2003, Atmos. Environ., 41, 4002–4017, https://doi.org/10.1016/j.atmosenv.2007.01.040, 2007.
Cheng, Y., Lee, S. C., Huang, Y., Ho, K. F., Ho, S. S. H., Yau, P. S., Louie, P. K. K., and Zhang, R. J.: Diurnal and seasonal trends of carbonyl compounds in roadside, urban, and suburban environment of Hong Kong, Atmos. Environ., 89, 43–51, https://doi.org/10.1016/j.atmosenv.2014.02.014, 2014.
Cheng, Y., Chen, L., Wu, H., Liu, J., Ren, J., and Zhang, F.: Wintertime fine aerosol particles composition and its evolution in two megacities of southern and northern China, Sci. Total Environ., 914, 169778, https://doi.org/10.1016/j.scitotenv.2023.169778, 2024.
Fan, H., Zhao, C., and Yang, Y.: A comprehensive analysis of the spatio-temporal variation of urban air pollution in China during 2014–2018, Atmos. Environ., 220, 117066, https://doi.org/10.1016/j.atmosenv.2019.117066, 2020.
Feng, Y., Ning, M., Lei, Y., Sun, Y., Liu, W., and Wang, J.: Defending blue sky in China: Effectiveness of the “Air Pollution Prevention and Control Action Plan” on air quality improvements from 2013–2017, J. Environ. Manage., 252, 109603, https://doi.org/10.1016/j.jenvman.2019.109603, 2019.
Filonchyk, M., Yan, H., and Li, X.: Temporal and spatial variation of particulate matter and its correlation with other criteria of air pollutants in Lanzhou, China, in spring-summer periods, Atmos. Pollut. Res., 9, 1100–1110, https://doi.org/10.1016/j.apr.2018.04.011, 2018.
Filonchyk, M., Yan, H., Zhang, Z., Yang, S., Li, W., and Li, Y.: Combined use of satellite and surface observations to study aerosol optical depth in different regions of China, Sci. Rep., 9, 6174, https://doi.org/10.1038/s41598-019-42466-6, 2019.
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.
Franco, B., Marais, E. A., Bovy, B., Bader, W., Lejeune, B., Roland, G., Servais, C., and Mahieu, E.: Diurnal cycle and multi-decadal trend of formaldehyde in the remote atmosphere near 46° N, Atmos. Chem. Phys., 16, 4171–4189, https://doi.org/10.5194/acp-16-4171-2016, 2016.
Gao, Y., Pan, H., Cao, L., Lu, C., Yang, Q., Lu, X., Ding, H., Li, S., and Zhao, T.: Effects of anthropogenic emissions and meteorological conditions on diurnal variation of formaldehyde (HCHO) in the Yangtze River Delta, China, Atmos. Pollut. Res., 14, 101779, https://doi.org/10.1016/j.apr.2023.101779, 2023.
Gu, J., Zhang, Y., Yang, N., and Wang, R.: Diurnal variability of the planetary boundary layer height estimated from radiosonde data, Earth Planet Phys., 4, 479–492, https://doi.org/10.26464/epp2020042, 2020.
Gui, K., Yao, W., Che, H., An, L., Zheng, Y., Li, L., Zhao, H., Zhang, L., Zhong, J., Wang, Y., and Zhang, X.: Record-breaking dust loading during two mega dust storm events over northern China in March 2021: aerosol optical and radiative properties and meteorological drivers, Atmos. Chem. Phys., 22, 7905–7932, https://doi.org/10.5194/acp-22-7905-2022, 2022.
Guo, J., Miao, Y., Zhang, Y., Liu, H., Li, Z., Zhang, W., He, J., Lou, M., Yan, Y., Bian, L., and Zhai, P.: The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data, Atmos. Chem. Phys., 16, 13309–13319, https://doi.org/10.5194/acp-16-13309-2016, 2016.
Harkey, M., Holloway, T., Oberman, J., and Scotty, E.: An evaluation of CMAQ NO2 using observed chemistry-meteorology correlations, J. Geophys. Res.-Atmos., 120, 11775-11797, https://doi.org/10.1002/2015JD023316, 2015.
Hassan, S. K., El-Abssawy, A. A., and Khoder, M. I.: Effect of Seasonal Variation on the Levels and Behaviours of Formaldehyde in the Atmosphere of a Suburban Area in Cairo, Egypt, Asian J. Atmos. Environ., 12, 356–368, https://doi.org/10.5572/ajae.2018.12.4.356, 2018.
He, C., Liu, J., Zhou, Y., Zhou, J., Zhang, L., Wang, Y., Liu, L., and Peng, S.: Synergistic PM2.5 and O3 control to address the emerging global PM2.5–O3 compound pollution challenges, Eco-Environ. Health, 3, 325–337, https://doi.org/10.1016/j.eehl.2024.04.004, 2024.
He, T., Tang, Y., Cao, R., Xia, N., Li, B., and Du, E.: Distinct urban–rural gradients of air NO2 and SO2 concentrations in response to emission reductions during 2015–2022 in Beijing, China, Environ. Pollut., 333, 122021, https://doi.org/10.1016/j.envpol.2023.122021, 2023.
Ho, K. F., Lee, S. C., Louie, P. K. K., and Zou, S. C.: Seasonal variation of carbonyl compound concentrations in urban area of Hong Kong, Atmos. Environ., 36, 1259–1265, https://doi.org/10.1016/S1352-2310(01)00570-2, 2002.
Ho, S. S. H., Ho, K. F., Lee, S. C., Cheng, Y., Yu, J. Z., Lam, K. M., Feng, N. S. Y., and Huang, Y.: Carbonyl emissions from vehicular exhausts sources in Hong Kong, J. Air Waste Manag., 62, 221–234, https://doi.org/10.1080/10473289.2011.642952, 2012.
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., Su, W., Ji, X., and Xiao, S.: Evaluating the feasibility of formaldehyde derived from hyperspectral remote sensing as a proxy for volatile organic compounds, Atmos. Res., 264, 105777, https://doi.org/10.1016/j.atmosres.2021.105777, 2021.
Huang, J., Minnis, P., Yi, Y., Tang, Q., Wang, X., Hu, Y., Liu, Z., Ayers, K., Trepte, C., and Winker, D.: Summer dust aerosols detected from CALIPSO over the Tibetan Plateau, Geophys. Res. Lett., 34, L18805, https://doi.org/10.1029/2007GL029938, 2007.
Huang, J., Feng, Y., Li, J., Xiong, B., Feng, J., Wen, S., Sheng, G., Fu, J., and Wu, M.: Characteristics of carbonyl compounds in ambient air of Shanghai, China, J. Atmos. Chem., 61, 1–20, https://doi.org/10.1007/s10874-009-9121-x, 2008.
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, 2018a.
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, 2018b.
Huang, X., Wang, Y., Shang, Y., Song, X., Zhang, R., Wang, Y., Li, Z., and Yang, Y.: Contrasting the effect of aerosol properties on the planetary boundary layer height in Beijing and Nanjing, Atmos. Environ., 308, 119861, https://doi.org/10.1016/j.atmosenv.2023.119861, 2023.
Jiang, L., Chen, Y., Zhou, H., and He, S.: NOx emissions in China: Temporal variations, spatial patterns and reduction potentials, Atmos. Pollut. Res., 11, 1473–1480, https://doi.org/10.1016/j.apr.2020.06.003, 2020.
Jiang, X., Li, G., and Fu, W.: Government environmental governance, structural adjustment and air quality: A quasi-natural experiment based on the Three-year Action Plan to Win the Blue Sky Defense War, J. Environ. Manage., 277, 111470, https://doi.org/10.1016/j.jenvman.2020.111470, 2021.
Jiao, P., Xing, C., and Liu, C.: A dataset of ground-based vertical profile observations of aerosol, NO2 and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023), Zenodo [data set], https://doi.org/10.5281/zenodo.15211604, 2024.
Justice, C. O., Townshend, J. R. G., Vermote, E. F., Masuoka, E., Wolfe, R. E., Saleous, N., Roy, D. P., and Morisette, J. T.: An overview of MODIS Land data processing and product status, Remote Sens. Environ., 83, 3–15, https://doi.org/10.1016/S0034-4257(02)00084-6, 2002.
Lamsal, L. N., Martin, R. V., Parrish, D. D., and Krotkov, N. A.: Scaling Relationship for NO2 Pollution and Urban Population Size: A Satellite Perspective, Environ. Sci. Technol., 47, 7855–7861, https://doi.org/10.1021/es400744g, 2013.
Lee, A. K. Y., Ling, T. Y., and Chan, C. K.: Understanding hygroscopic growth and phase transformation of aerosols using single particle Raman spectroscopy in an electrodynamic balance, Faraday Discuss., 137, 245–263, https://doi.org/10.1039/B704580H, 2008.
Lee, M., Heikes, B. G., Jacob, D. J., Sachse, G., and Anderson, B.: Hydrogen peroxide, organic hydroperoxide, and formaldehyde as primary pollutants from biomass burning, J. Geophys. Res.-Atmos., 102, 1301–1309, https://doi.org/10.1029/96JD01709, 1997.
Lee, Y. C. and Hills, P. R.: Cool season pollution episodes in Hong Kong, 1996–2002, Atmos. Environ., 37, 2927–2939, https://doi.org/10.1016/S1352-2310(03)00296-6, 2003.
Lei, W., Zavala, M., de Foy, B., Volkamer, R., Molina, M. J., and Molina, L. T.: Impact of primary formaldehyde on air pollution in the Mexico City Metropolitan Area, Atmos. Chem. Phys., 9, 2607–2618, https://doi.org/10.5194/acp-9-2607-2009, 2009.
Li, Y., Xing, C., Peng, H., Song, Y., Zhang, C., Xue, J., Niu, X., and Liu, C.: Long-term observations of NO2 using GEMS in China: Validations and regional transport, Sci. Total Environ., 904, 166762, https://doi.org/10.1016/j.scitotenv.2023.166762, 2023.
Li, Y., Xing, C., Hong, Q., Jiao, P., Peng, H., Tang, Z., and Liu, C.: Ozone Formation Sensitivity at Various Altitudes: Seeking the Optimal Method for Sensitivity Threshold Determination, Environ. Sci. Tech. Let., https://doi.org/10.1021/acs.estlett.4c00777, 2024.
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, 19, 71–83, https://doi.org/10.1016/j.eng.2021.02.019, 2022.
Liu, F., Beirle, S., Zhang, Q., van der A, R. J., Zheng, B., Tong, D., and He, K.: NOx emission trends over Chinese cities estimated from OMI observations during 2005 to 2015, Atmos. Chem. Phys., 17, 9261–9275, https://doi.org/10.5194/acp-17-9261-2017, 2017.
Liu, S., Jiang, X., Tsona, N. T., Lv, C., and Du, L.: Effects of NOx, SO2 and RH on the SOA formation from cyclohexene photooxidation, Chemosphere, 216, 794–804, https://doi.org/10.1016/j.chemosphere.2018.10.180, 2019.
Liu, S., Wang, H., Zhao, D., Ke, Y., Wu, Z., Shen, L., and Zhao, T.: Aircraft observations of aerosols and BC in autumn over Guangxi Province, China: Diurnal variation, vertical distribution and source appointment, Sci. Total Environ., 906, 167550, https://doi.org/10.1016/j.scitotenv.2023.167550, 2024.
Liu, Y., Lin, T., Hong, J., Wang, Y., Shi, L., Huang, Y., Wu, X., Zhou, H., Zhang, J., and de Leeuw, G.: Multi-dimensional satellite observations of aerosol properties and aerosol types over three major urban clusters in eastern China, Atmos. Chem. Phys., 21, 12331–12358, https://doi.org/10.5194/acp-21-12331-2021, 2021.
Luecken, D. J., Hutzell, W. T., Strum, M. L., and Pouliot, G. A.: Regional sources of atmospheric formaldehyde and acetaldehyde, and implications for atmospheric modeling, Atmos. Environ., 47, 477–490, https://doi.org/10.1016/j.atmosenv.2011.10.005, 2012.
Maji, K. J., Li, V. O. K., and Lam, J. C. K.: Effects of China's current Air Pollution Prevention and Control Action Plan on air pollution patterns, health risks and mortalities in Beijing 2014–2018, Chemosphere, 260, 127572, https://doi.org/10.1016/j.chemosphere.2020.127572, 2020.
Meller, R. and Moortgat, G. K.: Temperature dependence of the absorption cross sections of formaldehyde between 223 and 323 K in the wavelength range 225–375 nm, J. Geophys. Res.-Atmos., 105, 7089–7101, https://doi.org/10.1029/1999JD901074, 2000.
Meng, K., Xu, X., Cheng, X., Xu, X., Qu, X., Zhu, W., Ma, C., Yang, Y., and Zhao, Y.: Spatio-temporal variations in SO2 and NO2 emissions caused by heating over the Beijing–Tianjin–Hebei Region constrained by an adaptive nudging method with OMI data, Sci. Total Environ., 642, 543–552, https://doi.org/10.1016/j.scitotenv.2018.06.021, 2018.
Nussbaumer, C. M., Crowley, J. N., Schuladen, J., Williams, J., Hafermann, S., Reiffs, A., Axinte, R., Harder, H., Ernest, C., Novelli, A., Sala, K., Martinez, M., Mallik, C., Tomsche, L., Plass-Dülmer, C., Bohn, B., Lelieveld, J., and Fischer, H.: Measurement report: Photochemical production and loss rates of formaldehyde and ozone across Europe, Atmos. Chem. Phys., 21, 18413–18432, https://doi.org/10.5194/acp-21-18413-2021, 2021.
Ramanathan, V., Crutzen, P. J., Kiehl, J. T., and Rosenfeld, D.: Aerosols, Climate, and the Hydrological Cycle, Science, 294, 2119–2124, https://doi.org/10.1126/science.1064034, 2001.
Rothman, L. S., Gordon, I. E., Barbe, A., Benner, D. C., Bernath, P. F., Birk, M., Boudon, V., Brown, L. R., Campargue, A., Champion, J.-P., Chance, K., Coudert, L. H., Dana, V., Devi, V. M., Fally, S., Flaud, J.-M., Gamache, R. R., Goldman, A., Jacquemart, D., Kleiner, I., Lacome, N., Lafferty, W. J., Mandin, J.-Y., Massie, S. T., Mikhailenko, S. N., Miller, C. E., Moazzen-Ahmadi, N., Naumenko, O. V., Nikitin, A. V., Orphal, J., Perevalov, V. I., Perrin, A., Predoi-Cross, A., Rinsland, C. P., Rotger, M., Šimečková, M., Smith, M. A. H., Sung, K., Tashkun, S. A., Tennyson, J., Toth, R. A., Vandaele, A. C., and Vander Auwera, J.: The HITRAN 2008 molecular spectroscopic database, J. Quant. Spectrosc. Ra., 110, 533–572, https://doi.org/10.1016/j.jqsrt.2009.02.013, 2009.
Russell, A. G. and Brunekreef, B.: A Focus on Particulate Matter and Health, Environ. Sci. Technol., 43, 4620–4625, https://doi.org/10.1021/es9005459, 2009.
Schauer, J. J., Kleeman, M. J., Cass, G. R., and Simoneit, B. R. T.: Measurement of Emissions from Air Pollution Sources. 5. C1-C32 Organic Compounds from Gasoline-Powered Motor Vehicles, Environ. Sci. Technol., 36, 1169–1180, https://doi.org/10.1021/es0108077, 2002.
Seinfeld, J. H., Pandis, S. N., and Noone, K.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Phys. Today, 51, 88–90, https://doi.org/10.1063/1.882420, 1998.
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.
Shen, Y., Jiang, F., Feng, S., Zheng, Y., Cai, Z., and Lyu, X.: Impact of weather and emission changes on NO2 concentrations in China during 2014–2019, Environ. Pollut., 269, 116163, https://doi.org/10.1016/j.envpol.2020.116163, 2021.
Shen, Y., Jiang, F., Feng, S., Xia, Z., Zheng, Y., Lyu, X., Zhang, L., and Lou, C.: Increased diurnal difference of NO2 concentrations and its impact on recent ozone pollution in eastern China in summer, Sci. Total Environ., 858, 159767, https://doi.org/10.1016/j.scitotenv.2022.159767, 2023.
Song, Y., Xing, C., Liu, C., Lin, J., Wu, H., Liu, T., Lin, H., Zhang, C., Tan, W., Ji, X., Liu, H., and Li, Q.: Evaluation of transport processes over North China Plain and Yangtze River Delta using MAX-DOAS observations, Atmos. Chem. Phys., 23, 1803–1824, https://doi.org/10.5194/acp-23-1803-2023, 2023.
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.
Triantafyllou, A. G. and Kassomenos, P. A.: Aspects of atmospheric flow and dispersion of air pollutants in a mountainous basin, Sci. Total Environ., 297, 85–103, https://doi.org/10.1016/S0048-9697(02)00090-6, 2002.
Vandaele, A. C., Hermans, C., Simon, P. C., Carleer, M., Colin, R., Fally, S., Mérienne, 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 and 294 K, J. Quant. Spectrosc. Ra., 59, 171–184, https://doi.org/10.1016/S0022-4073(97)00168-4, 1998.
Wang, D., Zhou, B., Fu, Q., Zhao, Q., Zhang, Q., Chen, J., Yang, X., Duan, Y., and Li, J.: Intense secondary aerosol formation due to strong atmospheric photochemical reactions in summer: observations at a rural site in eastern Yangtze River Delta of China, Sci. Total Environ., 571, 1454–1466, https://doi.org/10.1016/j.scitotenv.2016.06.212, 2016.
Wang, J., Wang, S., Xu, X., Li, X., He, P., Qiao, Y., and Chen, Y.: The diminishing effects of winter heating on air quality in northern China, J. Environ. Manage., 325, 116536, https://doi.org/10.1016/j.jenvman.2022.116536, 2023.
Wang, R. and Cai, H.: City-Scale Aerosol Loading Changes in the Sichuan Basin from 2001–2020 as Revealed by MODIS 1 km Aerosol Product, Atmosphere, 14, 1715, https://doi.org/10.3390/atmos14121715, 2023.
Wang, Y., Hu, M., Hu, W., Zheng, J., Niu, H., Fang, X., Xu, N., Wu, Z., Guo, S., Wu, Y., Chen, W., Lu, S., Shao, M., Xie, S., Luo, B., and Zhang, Y.: Secondary Formation of Aerosols Under Typical High-Humidity Conditions in Wintertime Sichuan Basin, China: A Contrast to the North China Plain, J. Geophys. Res.-Atmos., 126, e2021JD034560, https://doi.org/10.1029/2021JD034560, 2021.
Wei, C.-B., Yu, G.-H., Cao, L.-M., Han, H.-X., Xia, S.-Y., and Huang, X.-F.: Tempo-spacial variation and source apportionment of atmospheric formaldehyde in the Pearl River Delta, China, Atmos. Environ., 312, 120016, https://doi.org/10.1016/j.atmosenv.2023.120016, 2023.
Wen, Y., Zhang, S., Zhang, J., Bao, S., Wu, X., Yang, D., and Wu, Y.: Mapping dynamic road emissions for a megacity by using open-access traffic congestion index data, Appl. Energy, 260, 114357, https://doi.org/10.1016/j.apenergy.2019.114357, 2020.
Wu, J., Bei, N., Li, X., Wang, R., Liu, S., Jiang, Q., Tie, X., and Li, G.: Impacts of Transboundary Transport on Coastal Air Quality of South China, J. Geophys. Res.-Atmos., 127, e2021JD036213, https://doi.org/10.1029/2021JD036213, 2022.
Xiao, Q., Ma, Z., Li, S., and Liu, Y.: The impact of winter heating on air pollution in China, PLoS One, 10, e0117311, https://doi.org/10.1371/journal.pone.0117311, 2015.
Xie, M., Zhu, K., Wang, T., Chen, P., Han, Y., Li, S., Zhuang, B., and Shu, L.: Temporal characterization and regional contribution to O3 and NOx at an urban and a suburban site in Nanjing, China, Sci. Total Environ., 551–552, 533–545, https://doi.org/10.1016/j.scitotenv.2016.02.047, 2016.
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.
Yang, D., Zhang, S., Niu, T., Wang, Y., Xu, H., Zhang, K. M., and Wu, Y.: High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets, Atmos. Chem. Phys., 19, 8831–8843, https://doi.org/10.5194/acp-19-8831-2019, 2019.
Yuan, J., Wang, X., Feng, Z., Zhang, Y., and Yu, M.: Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations, Remote Sens., 15, 4613, https://doi.org/10.3390/rs15184613, 2023.
Zhang, D., Li, Z., Wu, H., Wu, T., Ren, R., Cai, Z., Liang, C., and Chen, L.: Analysis of aerosol particle number size distribution and source attribution at three megacities in China, Atmos. Environ., 279, 119114, https://doi.org/10.1016/j.atmosenv.2022.119114, 2022.
Zhang, K., Zhao, C., Fan, H., Yang, Y., and Sun, Y.: Toward Understanding the Differences of PM2.5 Characteristics Among Five China Urban Cities, Asia-Pac. J. Atmospheric Sci., 56, 493–502, https://doi.org/10.1007/s13143-019-00125-w, 2020.
Zhao, H., Che, H., Zhang, X., Ma, Y., Wang, Y., Wang, X., Liu, C., Hou, B., and Che, H.: Aerosol optical properties over urban and industrial region of Northeast China by using ground-based sun-photometer measurement, Atmos. Environ., 75, 270–278, https://doi.org/10.1016/j.atmosenv.2013.04.048, 2013.
Zhao, H., Che, H., Xia, X., Wang, Y., Wang, H., Wang, P., Ma, Y., Yang, H., Liu, Y., Wang, Y., Gui, K., Sun, T., Zheng, Y., and Zhang, X.: Climatology of mixing layer height in China based on multi-year meteorological data from 2000–2013, Atmos. Environ., 213, 90–103, https://doi.org/10.1016/j.atmosenv.2019.05.047, 2019.
Short summary
Vertical profile observations are key to understanding regional air pollution but remain scarce due to existing limits. This study presents a high-time-resolution (ca. 15 min) dataset of aerosol, nitrogen dioxide, and formaldehyde vertical profiles from 32 sites in China (2019–2023) using passive remote sensing. It documents vertical distribution, seasonal variations, and diurnal patterns, revealing long-term trends. Data are available at Zenodo under https://doi.org/10.5281/zenodo.15211604.
Vertical profile observations are key to understanding regional air pollution but remain scarce...
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