Articles | Volume 26, issue 6
https://doi.org/10.5194/acp-26-4231-2026
© Author(s) 2026. 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-26-4231-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Mar 2026
Research article |
| 26 Mar 2026
| 26 Mar 2026
Investigation of aerosol transport flux structure over Beijing based on lidar observations and the impact of dust transport on air quality
Zhengguo Tian
Hangzhou Institute of Advanced Studies, Zhejiang Normal University, Hangzhou, 311231, China
Hangzhou Institute of Advanced Studies, Zhejiang Normal University, Hangzhou, 311231, China
Si Liu
Hangzhou Institute of Advanced Studies, Zhejiang Normal University, Hangzhou, 311231, China
Cheng Yao
Hangzhou Institute of Advanced Studies, Zhejiang Normal University, Hangzhou, 311231, China
Tong Lu
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, China
Weijie Zou
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, China
Zhenping Yin
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, China
School of Earth and Space Science and Technology, Wuhan University, Wuhan, 430072, China
State Observatory for Atmospheric Remote Sensing, Wuhan, 430072, China
State Key Laboratory of Severe Weather Meteorological Science and Technology & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Bin Zhang
Hangzhou Institute of Advanced Studies, Zhejiang Normal University, Hangzhou, 311231, China
Daru Chen
Hangzhou Institute of Advanced Studies, Zhejiang Normal University, Hangzhou, 311231, China
Zhichao Bu
Meteorological Observation Center, China Meteorological Administration, Beijing, 100081, China
Yubao Chen
Meteorological Observation Center, China Meteorological Administration, Beijing, 100081, China
Xuan Wang
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, China
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Cheng Yao, Longlong Wang, Aoxiang Huang, Bin Zhang, Marija Bervida Mačak, Luka Drinovec, Asta Gregorič, Fei Gao, Janja Vaupotič, Miloš Miler, Mateja Gosar, Zhangwei Yu, Daru Chen, Griša Močnik, and Samo Stanič
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Aerosols affect climate by scattering and absorbing sunlight and heat. Light detection and ranging instruments can track aerosol distributions, but turning their signals into atmospheric information depends on particle size, absorption, and humidity. We developed a ground-measurement method and tested it in Slovenia. The results provide optical constraints that support more reliable retrieval of aerosol profile information when different particle types are mixed.
Zhaolong Wu, Patric Seifert, Yun He, Holger Baars, Cristofer Jimenez, Chengcai Li, Jing Li, Albert Ansmann, and Chuanfeng Zhao
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Using a full year of laser and radar observations in Beijing, this study shows when and where flat ice crystals tend to align horizontally instead of randomly, which suggests that flat ice crystals are most common in moderately cold, weakly turbulent clouds and often form below supercooled liquid water. This new finding can help weather and climate models better represent ice clouds.
Yun He, Dongzhe Jing, Zhenping Yin, Detlef Müller, Fuchao Liu, Yunpeng Zhang, Yang Yi, Kaiming Huang, and Fan Yi
Atmos. Chem. Phys., 26, 4937–4951, https://doi.org/10.5194/acp-26-4937-2026, https://doi.org/10.5194/acp-26-4937-2026, 2026
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Using polarization lidar observations during 2010–2024, we retrieve the vertical profiles of aerosol backscatter and extinction coefficients of anthropogenic pollution under dry and ambient atmospheric conditions over central China. The year-to-year and seasonal variations in anthropogenic AOD are largely changed after removing hygroscopic growth effect.
Dongzhe Jing, Yun He, Zhenping Yin, Detlef Müller, Kaiming Huang, and Fan Yi
Atmos. Meas. Tech., 19, 389–403, https://doi.org/10.5194/amt-19-389-2026, https://doi.org/10.5194/amt-19-389-2026, 2026
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Dongzhe Jing, Yun He, Zhenping Yin, Kaiming Huang, Fuchao Liu, and Fan Yi
Atmos. Chem. Phys., 25, 17047–17067, https://doi.org/10.5194/acp-25-17047-2025, https://doi.org/10.5194/acp-25-17047-2025, 2025
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Ioanna Tsikoudi, Eleni Marinou, Maria Tombrou, Eleni Giannakaki, Emmanouil Proestakis, Konstantinos Rizos, Ville Vakkari, Holger Baars, Annett Skupin, Ronny Engelmann, Zhenping Yin, and Vassilis Amiridis
Atmos. Chem. Phys., 25, 16491–16510, https://doi.org/10.5194/acp-25-16491-2025, https://doi.org/10.5194/acp-25-16491-2025, 2025
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We study the characteristics of the boundary layer over three areas: the tropical Atlantic, the tropical West African continent, and near Cabo Verde using PollyXT and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) lidar measurements, as well as ECMWF (European Centre for Medium-Range Weather Forecasts) data. The findings underline the strengths and limitations of different observational and modeling approaches, and emphasizes on the importance of considering aerosol conditions and local meteorology when interpreting boundary layer dynamics.
Yun He, Goutam Choudhury, Matthias Tesche, Albert Ansmann, Fan Yi, Detlef Müller, and Zhenping Yin
Atmos. Meas. Tech., 18, 5669–5685, https://doi.org/10.5194/amt-18-5669-2025, https://doi.org/10.5194/amt-18-5669-2025, 2025
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We present a global dataset of POlarization LIdar PHOtometer Networking (POLIPHON) dust conversion factors at 532 nm obtained using Aerosol RObotic NETwork (AERONET) observations at 137 sites for ice-nucleating particle (INP) and 123 sites for cloud condensation nucleation (CCN) calculations. We also conduct a comparison of dust CCN concentration profiles derived using both POLIPHON and the independent Optical Modelling of the CALIPSO Aerosol Microphysics (OMCAM) retrieval.
Zhaolong Wu, Patric Seifert, Yun He, Holger Baars, Haoran Li, Cristofer Jimenez, Chengcai Li, and Albert Ansmann
Atmos. Meas. Tech., 18, 3611–3634, https://doi.org/10.5194/amt-18-3611-2025, https://doi.org/10.5194/amt-18-3611-2025, 2025
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This study introduces a novel method to detect horizontally oriented ice crystals (HOICs) using two ground-based polarization lidars at different zenith angles, based on a yearlong dataset collected in Beijing. Combined with cloud radar and reanalysis data, the fine categorization results reveal HOICs occur in calm winds and moderately cold temperatures and are influenced by turbulence near cloud bases. The results enhance our understanding of cloud processes and improve atmospheric models.
Yun He, Dongzhe Jing, Zhenping Yin, Kevin Ohneiser, and Fan Yi
Atmos. Chem. Phys., 24, 11431–11450, https://doi.org/10.5194/acp-24-11431-2024, https://doi.org/10.5194/acp-24-11431-2024, 2024
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We present a long-term ground-based lidar observation of stratospheric aerosols at a mid-latitude site, Wuhan, in central China, from 2010 to 2021. We observed a stratospheric background period from 2013 to mid-2017, along with several perturbations from volcanic aerosols and wildfire-induced smoke. In summer, injected stratospheric aerosols are found to be captured by the Asian monsoon anticyclone, resulting in prolonged residence and regional transport in the mid-latitudes of East Asia.
Longlong Wang, Zhenping Yin, Zhichao Bu, Anzhou Wang, Song Mao, Yang Yi, Detlef Müller, Yubao Chen, and Xuan Wang
Atmos. Meas. Tech., 16, 4307–4318, https://doi.org/10.5194/amt-16-4307-2023, https://doi.org/10.5194/amt-16-4307-2023, 2023
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Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, https://doi.org/10.5194/amt-16-2353-2023, 2023
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DeLiAn is a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements and currently covers two wavelengths, 355 and 532 nm, for 13 aerosol categories ranging from basic aerosol types to mixtures.
Yun He, Zhenping Yin, Albert Ansmann, Fuchao Liu, Longlong Wang, Dongzhe Jing, and Huijia Shen
Atmos. Meas. Tech., 16, 1951–1970, https://doi.org/10.5194/amt-16-1951-2023, https://doi.org/10.5194/amt-16-1951-2023, 2023
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With the AERONET database, this study derives dust-related conversion factors at oceanic sites used in the POLIPHON method, which can convert lidar-retrieved dust extinction to ice-nucleating particle (INP)- and cloud condensation nuclei (CCN)-relevant parameters. The particle linear depolarization ratio in the AERONET aerosol inversion product is used to identify dust data points. The derived conversion factors can be applied to inverse 3-D global distributions of dust-related INPCs and CCNCs.
Yun He, Zhenping Yin, Fuchao Liu, and Fan Yi
Atmos. Chem. Phys., 22, 13067–13085, https://doi.org/10.5194/acp-22-13067-2022, https://doi.org/10.5194/acp-22-13067-2022, 2022
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A method is proposed to identify the sole presence of heterogeneous nucleation and competition between heterogeneous and homogeneous nucleation for dust-related cirrus clouds by characterizing the relationship between dust ice-nucleating particle concentration calculated from CALIOP using the POLIPHON method and in-cloud ice crystal number concentration from the DARDAR-Nice dataset. Two typical cirrus cases are shown as a demonstration, and the proposed method can be extended to a global scale.
Lei Li, Yevgeny Derimian, Cheng Chen, Xindan Zhang, Huizheng Che, Gregory L. Schuster, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Christian Matar, Fabrice Ducos, Yana Karol, Benjamin Torres, Ke Gui, Yu Zheng, Yuanxin Liang, Yadong Lei, Jibiao Zhu, Lei Zhang, Junting Zhong, Xiaoye Zhang, and Oleg Dubovik
Earth Syst. Sci. Data, 14, 3439–3469, https://doi.org/10.5194/essd-14-3439-2022, https://doi.org/10.5194/essd-14-3439-2022, 2022
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A climatology of aerosol composition concentration derived from POLDER-3 observations using GRASP/Component is presented. The conceptual specifics of the GRASP/Component approach are in the direct retrieval of aerosol speciation without intermediate retrievals of aerosol optical characteristics. The dataset of satellite-derived components represents scarce but imperative information for validation and potential adjustment of chemical transport models.
Ke Gui, Wenrui Yao, Huizheng Che, Linchang An, Yu Zheng, Lei Li, Hujia Zhao, Lei Zhang, Junting Zhong, Yaqiang Wang, and Xiaoye Zhang
Atmos. Chem. Phys., 22, 7905–7932, https://doi.org/10.5194/acp-22-7905-2022, https://doi.org/10.5194/acp-22-7905-2022, 2022
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This study investigates the aerosol optical and radiative properties and meteorological drivers during two mega SDS events over Northern China in March 2021. The MODIS-retrieved DOD data registered these two events as the most intense episode in the same period in history over the past 20 years. These two extreme SDS events were associated with both atmospheric circulation extremes and local meteorological anomalies that favor enhanced dust emissions in the Gobi Desert.
Yu Zheng, Huizheng Che, Yupeng Wang, Xiangao Xia, Xiuqing Hu, Xiaochun Zhang, Jun Zhu, Jibiao Zhu, Hujia Zhao, Lei Li, Ke Gui, and Xiaoye Zhang
Atmos. Meas. Tech., 15, 2139–2158, https://doi.org/10.5194/amt-15-2139-2022, https://doi.org/10.5194/amt-15-2139-2022, 2022
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Ground-based observations of aerosols and aerosol data verification is important for satellite and climate model modification. Here we present an evaluation of aerosol microphysical, optical and radiative properties measured using a multiwavelength photometer with a highly integrated design and smart control performance. The validation of this product is discussed in detail using AERONET as a reference. This work contributes to reducing AOD uncertainties in China and combating climate change.
Yang Yi, Fan Yi, Fuchao Liu, Yunpeng Zhang, Changming Yu, and Yun He
Atmos. Chem. Phys., 21, 17649–17664, https://doi.org/10.5194/acp-21-17649-2021, https://doi.org/10.5194/acp-21-17649-2021, 2021
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Our lidar observations reveal the complete microphysical process of hydrometeors falling from mid-level stratiform clouds. We find that the surface rainfall begins as supercooled mixed-phase hydrometeors fall out of a liquid parent cloud base. We find also that the collision–coalescence growth of precipitating raindrops and subsequent spontaneous breakup always occur around 0.6 km altitude during surface rainfalls. Our findings provide new insights into stratiform precipitation formation.
Ke Gui, Huizheng Che, Yu Zheng, Hujia Zhao, Wenrui Yao, Lei Li, Lei Zhang, Hong Wang, Yaqiang Wang, and Xiaoye Zhang
Atmos. Chem. Phys., 21, 15309–15336, https://doi.org/10.5194/acp-21-15309-2021, https://doi.org/10.5194/acp-21-15309-2021, 2021
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This study utilized the globally gridded aerosol extinction data from CALIOP during 2007–2019 to investigate the 3D climatology, trends, and meteorological drivers of tropospheric type-dependent aerosols. Results revealed that the planetary boundary layer (PBL) and the free troposphere contribute 62.08 % and 37.92 %, respectively, of the global tropospheric TAOD. Trends in
CALIOP-derived aerosol loading, in particular those partitioned in the PBL, can be explained to a large extent by meteorology.
Yun He, Yunfei Zhang, Fuchao Liu, Zhenping Yin, Yang Yi, Yifan Zhan, and Fan Yi
Atmos. Meas. Tech., 14, 5939–5954, https://doi.org/10.5194/amt-14-5939-2021, https://doi.org/10.5194/amt-14-5939-2021, 2021
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The POLIPHON method can retrieve the height profiles of dust-related particle mass and ice-nucleating particle (INP) concentrations. Applying a dust case data set screening scheme based on the lidar-derived depolarization ratio (rather than Ångström exponent for 440–870 nm and AOD at 532 nm), the mixed-dust-related conversion factors are retrieved from sun photometer observations over Wuhan, China. This method may potentially be extended to regions influenced by mixed dust.
Cited articles
Banakh, V. and Smalikho, I.: Coherent Doppler Wind Lidars in a Turbulent Atmosphere, Artech, ISBN 9781608076680, 2013.
Böckmann, C., Mironova, I., Müller, D., Schneidenbach, L., and Nessler, R.: Microphysical aerosol parameters from multiwavelength lidar, J. Opt. Soc. Am. A, 22, 518–528, https://doi.org/10.1364/JOSAA.22.000518, 2005.
Brunekreef, B. and Holgate, S. T. : Air pollution and health, Lancet, 360, 1233–1242, 2002.
Casquero-Vera, J. A., Lyamani, H., Titos, G., de A. Moreira, G., Benavent-Oltra, J. A., Conte, M., Contini, D., Järvi, L., Olmo-Reyes, F. J., and Alados-Arboledas, L.: Aerosol number fluxes and concentrations over a southern European urban area, Atmos. Environ., 269, 118849, https://doi.org/10.1016/j.atmosenv.2021.118849, 2022.
Che, H., Xia, X., Zhao, H., Dubovik, O., Holben, B. N., Goloub, P., Cuevas-Agulló, E., Estelles, V., Wang, Y., Zhu, J., Qi, B., Gong, W., Yang, H., Zhang, R., Yang, L., Chen, J., Wang, H., Zheng, Y., Gui, K., Zhang, X., and Zhang, X.: Spatial distribution of aerosol microphysical and optical properties and direct radiative effect from the China Aerosol Remote Sensing Network, Atmos. Chem. Phys., 19, 11843–11864, https://doi.org/10.5194/acp-19-11843-2019, 2019.
Chen, B., Xu, X. D., Yang, S., and Zhao, T. L.: Climatological perspectives of air transport from atmospheric boundary layer to tropopause layer over Asian monsoon regions during boreal summer inferred from Lagrangian approach, Atmos. Chem. Phys., 12, 5827–5839, https://doi.org/10.5194/acp-12-5827-2012, 2012.
Chen, R., Jiang, H., Xiao, Z.-Y., Yu, S.-Q., Jiao, L., and Hong, S.-M.: Monitoring Aerosol Optical Properties Using Ground Based Remote Sensing and the Change of Atmospheric Environment in Hangzhou Region, Res. Environ. Sci., 21, 22–26, 2008.
Chen, Y., Bu, Z., Li, Y., Dong, Y., Li, T., Wang, X., Wang, X., Liu, Z., and Wang, X.: A High-Performance 532 nm Raman–Mie Lidar for the Calibration of an Aerosol Lidar Network, Remote Sens., 16, 570, https://doi.org/10.3390/rs16030570, 2024.
Conte, M., Contini, D., and Held, A.: Multiresolution decomposition and wavelet analysis of urban aerosol fluxes in Italy and Austria, Atmos. Res., 248, 105267, https://doi.org/10.1016/j.atmosres.2020.105267, 2021.
Córdoba-Jabonero, C., Sicard, M., Ansmann, A., del Águila, A., and Baars, H.: Separation of the optical and mass features of particle components in different aerosol mixtures by using POLIPHON retrievals in synergy with continuous polarized Micro-Pulse Lidar (P-MPL) measurements, Atmos. Meas. Tech., 11, 4775–4795, https://doi.org/10.5194/amt-11-4775-2018, 2018.
D'Amico, G., Amodeo, A., Baars, H., Binietoglou, I., Freudenthaler, V., Mattis, I., Wandinger, U., and Pappalardo, G.: EARLINET Single Calculus Chain – overview on methodology and strategy, Atmos. Meas. Tech., 8, 4891–4916, https://doi.org/10.5194/amt-8-4891-2015, 2015.
Denjean, C., Cassola, F., Mazzino, A., Triquet, S., Chevaillier, S., Grand, N., Bourrianne, T., Momboisse, G., Sellegri, K., Schwarzenbock, A., Freney, E., Mallet, M., and Formenti, P.: Size distribution and optical properties of mineral dust aerosols transported in the western Mediterranean, Atmos. Chem. Phys., 16, 1081–1104, https://doi.org/10.5194/acp-16-1081-2016, 2016.
Ding, K., Liu, J., Ding, A., Liu, Q., Zhao, T. L., Shi, J., Han, Y., Wang, H., and Jiang, F.: Uplifting of carbon monoxide from biomass burning and anthropogenic sources to the free troposphere in East Asia, Atmos. Chem. Phys., 15, 2843–2866, https://doi.org/10.5194/acp-15-2843-2015, 2015.
Dipu, S., Prabha, T. V., Pandithurai, G., Dudhia, J., Pfister, G., Rajesh, K., and Goswami, B. N.: Impact of elevated aerosol layer on the cloud macrophysical properties prior to monsoon onset, Atmos. Environ., 70, 454–467, https://doi.org/10.1016/j.atmosenv.2013.01.011, 2013.
Drinovec, L., Močnik, G., Zotter, P., Prévôt, A., Ruckstuhl, C., Coz, E., Rupakheti, M., Sciare, J., Müller, T., Wiedensohler, A., and Hansen, A. D. A.: The “dual-spot” Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation, Atmos. Meas. Tech., 8, 1965–1979, https://doi.org/10.5194/amt-8-1965-2015, 2015.
Engelmann, R., Wandinger, U., Ansmann, A., Müller, D., Žeromskis, G., Althausen, D., and Wehner, B.: Lidar observations of the vertical aerosol flux in the planetary boundary layer, J. Atmos. Ocean. Tech., 25, 1296–1306, https://doi.org/10.1175/2007JTECHA967.1, 2008.
Floutsi, A. A., Baars, H., Engelmann, R., Althausen, D., Ansmann, A., Bohlmann, S., Heese, B., Hofer, J., Kanitz, T., Haarig, M., Ohneiser, K., Radenz, M., Seifert, P., Skupin, A., Yin, Z., and Petzold, A.: DeLiAn – a growing collection of depolarization ratio, lidar ratio and Ångström exponent for different aerosol types and mixtures from ground-based lidar observations, Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, 2023.
Freudenthaler, V.: About the effects of polarising optics on lidar signals and the Δ90 calibration, Atmos. Meas. Tech., 9, 4181–4255, https://doi.org/10.5194/amt-9-4181-2016, 2016.
Freudenthaler, V., Esselborn, M., Wiegner, M., Heese, B., Tesche, M., Ansmann, A., Müller, D., Althausen, D., Wirth, M., and Fix, A.: Depolarization ratio profiling at several wavelengths in pure Saharan dust during SAMUM 2006, Tellus B, 61, 165–179, https://doi.org/10.1111/j.1600-0889.2008.00396.x, 2009.
Geng, G., Xiao, Q., Zheng, Y., Tong, D., Zhang, Y., Zhang, X., Zhang, Q., He, K., and Liu, Y.: Impact of China's Air Pollution Prevention and Control Action Plan on PM2.5 chemical composition over eastern China, Sci. China Earth Sci., 62, 1872–1884, https://doi.org/10.1007/s11430-018-9353-x, 2019.
Gerbig, C., Körner, S., and Lin, J. C.: Vertical mixing in atmospheric tracer transport models: error characterization and propagation, Atmos. Chem. Phys., 8, 591–602, https://doi.org/10.5194/acp-8-591-2008, 2008.
He, Y., Yin, Z., Ansmann, A., Liu, F., Wang, L., Jing, D., and Shen, H.: POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites, Atmos. Meas. Tech., 16, 1951–1970, https://doi.org/10.5194/amt-16-1951-2023, 2023.
He, Y., Choudhury, G., Tesche, M., Ansmann, A., Yi, F., Müller, D., and Yin, Z.: Extended POLIPHON dust conversion factor dataset for lidar-derived cloud condensation nuclei and ice-nucleating particle concentration profiles, Atmos. Meas. Tech., 18, 5669–5685, https://doi.org/10.5194/amt-18-5669-2025, 2025.
Hu, Q., Liu, C., Li, Q., Liu, T., Jia, X., Zhu, Y., Xing, C., Tan, W., and Gao, M.: Vertical profiles of the transport fluxes of aerosol and its precursors between Beijing and its southwest cities, Environ. Pollut., 312, 119988, https://doi.org/10.1016/j.envpol.2022.119988, 2022.
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., Baltensperger, U., El Haddad, I., and Prévôt, A. S. H.: High secondary aerosol contribution to particulate pollution during haze events in China, Nature, 514, 218–222, https://doi.org/10.1038/nature13774, 2014.
Huang, T., Fang, T., Feng, L., Leong, C. Y., and Yim, S. H. L.: Investigating the interaction between transboundary haze and planetary boundary layer in Singapore, Geophys. Res. Lett., 51, e2023GL107667, https://doi.org/10.1029/2023GL107667, 2024.
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.
Kim, H. C., Chai, T., Stein, A., and Kondragunta, S.: Inverse modeling of fire emissions constrained by smoke plume transport using HYSPLIT dispersion model and geostationary satellite observations, Atmos. Chem. Phys., 20, 10259–10277, https://doi.org/10.5194/acp-20-10259-2020, 2020.
Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., and Schöpp, W.: Global anthropogenic emissions of particulate matter including black carbon, Atmos. Chem. Phys., 17, 8681–8723, https://doi.org/10.5194/acp-17-8681-2017, 2017.
Li, L., Dubovik, O., Derimian, Y., Schuster, G. L., Lapyonok, T., Litvinov, P., Ducos, F., Fuertes, D., Chen, C., Li, Z., Lopatin, A., Torres, B., and Che, H.: Retrieval of aerosol components directly from satellite and ground-based measurements, Atmos. Chem. Phys., 19, 13409–13443, https://doi.org/10.5194/acp-19-13409-2019, 2019.
Li, R., Wu, S., Sun, K., Wang, Q., Wang, X., Qin, S., Fan, M., Ma, L., Hao, Y., and Zheng, X.: Profiling of particulate matter transport flux based on dual-wavelength lidar and ensemble learning algorithm, Opt. Express, 32, 28892–28913, https://doi.org/10.1364/OE.522165, 2024.
Lin, C., Fung, J. C. H., Ren, C., Ng, E. Y. Y., Li, Y., He, Y., Leung, K. K. M., Ning, Z., and Lau, A. K. H.: Horizontal flux of ozone in the planetary boundary layer in Hong Kong using wind LiDAR measurements, Atmos. Environ., 312, 120046, https://doi.org/10.1016/j.atmosenv.2023.120046, 2023.
Liu, Q., Baumgartner, J., Zhang, Y., and Schauer, J. J.: Source apportionment of Beijing air pollution during a severe winter haze event and associated pro-inflammatory responses in lung epithelial cells, Atmos. Environ., 126, 28–35, https://doi.org/10.1016/j.atmosenv.2015.11.031, 2016.
Liu, Y. and Daum, P. H.: The effect of refractive index on size distributions and light scattering coefficients derived from optical particle counters, J. Aerosol Sci., 31, 945–957, https://doi.org/10.1016/S0021-8502(99)00573-X, 2000.
Lopatin, A., Dubovik, O., Chaikovsky, A., Goloub, P., Lapyonok, T., Tanré, D., and Litvinov, P.: Enhancement of aerosol characterization using synergy of lidar and sun-photometer coincident observations: the GARRLiC algorithm, Atmos. Meas. Tech., 6, 2065–2088, https://doi.org/10.5194/amt-6-2065-2013, 2013.
Lou, M., Guo, J., Wang, L., Xu, H., Chen, D., Miao, Y., Lv, Y., Li, Y., Guo, X., and Ma, S.: On the relationship between aerosol and boundary layer height in summer in China under different thermodynamic conditions, Earth Space Sci., 6, 887–901, https://doi.org/10.1029/2019EA000620, 2019.
Lv, M., Liu, D., Li, Z., Mao, J., Sun, Y., Wang, Z., Wang, Y., and Xie, C.: Hygroscopic growth of atmospheric aerosol particles based on lidar, radiosonde, and in situ measurements: Case studies from the Xinzhou field campaign, J. Quant. Spectrosc. Ra., 188, 60–70, https://doi.org/10.1016/j.jqsrt.2015.12.029, 2017.
Mamouri, R. E. and Ansmann, A.: Fine and coarse dust separation with polarization lidar, Atmos. Meas. Tech., 7, 3717–3735, https://doi.org/10.5194/amt-7-3717-2014, 2014.
Mamouri, R.-E. and Ansmann, A.: Potential of polarization/Raman lidar to separate fine dust, coarse dust, maritime, and anthropogenic aerosol profiles, Atmos. Meas. Tech., 10, 3403–3427, https://doi.org/10.5194/amt-10-3403-2017, 2017.
Mao, S., Yin, Z., Wang, L., Wei, Y., Bu, Z., Chen, Y., Dai, Y., Müller, D., and Wang, X.. Aerosol optical properties retrieved by polarization Raman lidar: Methodology and strategy of a quality-assurance tool, Remote Sens., 16, 207, https://doi.org/10.3390/rs16010207, 2024.
Müller, D., Wandinger, U., Althausen, D., and Fiebig, M.: Comprehensive particle characterization from three-wavelength Raman-lidar observations: case study, Appl. Optics, 40, 4863–4869, https://doi.org/10.1364/AO.40.004863, 2001.
Peng, L., Yi, F., Liu, F., Yin, Z., and He, Y.: Optical properties of aerosol and cloud particles measured by a single-line-extracted pure rotational Raman lidar, Opt. Express, 29, 21947–21964, https://doi.org/10.1364/OE.427864, 2021.
Pryor, S. C., Gallagher, M. W., Sievering, H., Larsen, S. E., Barthelmie, R. J., Birsan, F., Nemitz, E., Rinne, J., Kulmala, M., Grönholm, T., Taipale, R., and Vesala, T.: A review of measurement and modelling results of particle atmosphere–surface exchange, Tellus B, 60, 42–75, https://doi.org/10.1111/j.1600-0889.2007.00298.x, 2008.
Seinfeld, J. H., Pandis, S. N., and Noone, K. J.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Phys. Today, 51, 88–90, https://doi.org/10.1063/1.882420, 1998.
Smalikho, I. N.: Techniques of wind vector estimation from data measured with a scanning coherent Doppler lidar, J. Atmos. Ocean. Tech., 20, 276–291, https://doi.org/10.1175/1520-0426(2003)020<0276:TOWVEF>2.0.CO;2, 2003.
Swinbank, W. C.: The measurement of vertical transfer of heat and water vapor by eddies in the lower atmosphere, J. Meteorol., 8, 135–145, https://doi.org/10.1175/1520-0469(1951)008<0135:TMOVTO>2.0.CO;2, 1951.
Tanaka, T. Y., Kurosaki, Y., Chiba, M., Matsumura, T., Nagai, T., Yamazaki, A., Uchiyama, A., Tsunematsu, N., and Kai, K.: Possible transcontinental dust transport from North Africa and the Middle East to East Asia, Atmos. Environ., 39, 3901–3909, https://doi.org/10.1016/j.atmosenv.2005.03.034, 2005.
Tesche, M., Ansmann, A., Müller, D., Althausen, D., Mattis, I., Heese, B., Freudenthaler, V., Wiegner, M., Esselborn, M., Pisani, G., and Knippertz, P.: Vertical profiling of Saharan dust with Raman lidars and airborne HSRL in southern Morocco during SAMUM, Tellus B, 61, 144–164, https://doi.org/10.1111/j.1600-0889.2008.00390.x, 2009a.
Tesche, M., Ansmann, A., Müller, D., Engelmann, R., Freudenthaler, V., and Groß, S.: Vertically resolved separation of dust and smoke over Cape Verde using multiwavelength Raman and polarization lidars during Saharan Mineral Dust Experiment 2008, J. Geophys. Res.-Atmos., 114, D13202, https://doi.org/10.1029/2009JD011862, 2009b.
The State Council of the People's Republic of China: Action Plan on Air Pollution Prevention and Control, https://www.gov.cn/zwgk/2013-09/12/content_2486773.htm (last access: 6 July 2025), 2013.
Tian, P., Liu, D., Zhao, D., Yu, C., Liu, Q., Huang, M., Deng, Z., Ran, L., Wu, Y., Ding, S., Hu, K., Zhao, G., Zhao, C., and Ding, D.: In situ vertical characteristics of optical properties and heating rates of aerosol over Beijing, Atmos. Chem. Phys., 20, 2603–2622, https://doi.org/10.5194/acp-20-2603-2020, 2020.
Van Donkelaar, A., Martin, R. V., Brauer, M., Hsu, N. C., Kahn, R. A., Levy, R. C., Lyapustin, A., Sayer, A. M., and Winker, D. M.: Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors, Environ. Sci. Technol., 50, 3762–3772, https://doi.org/10.1021/acs.est.5b05833, 2016.
Wandinger, U., Linné, H., Bösenberg, J., Zeromskis, E., Althausen, D., and Müller, D.: Turbulent aerosol fluxes determined from combined observations with doppler wind and Raman aerosol lidar, in: 22nd International Laser Radar Conference (ILRC 2004), ESA Special Publications, 561, 743–746, 2004.
Wandinger, U., Freudenthaler, V., Baars, H., Amodeo, A., Engelmann, R., Mattis, I., Groß, S., Pappalardo, G., Giunta, A., D'Amico, G., Chaikovsky, A., Osipenko, F., Slesar, A., Nicolae, D., Belegante, L., Talianu, C., Serikov, I., Linné, H., Jansen, F., Apituley, A., Wilson, K. M., de Graaf, M., Trickl, T., Giehl, H., Adam, M., Comerón, A., Muñoz-Porcar, C., Rocadenbosch, F., Sicard, M., Tomás, S., Lange, D., Kumar, D., Pujadas, M., Molero, F., Fernández, A. J., Alados-Arboledas, L., Bravo-Aranda, J. A., Navas-Guzmán, F., Guerrero-Rascado, J. L., Granados-Muñoz, M. J., Preißler, J., Wagner, F., Gausa, M., Grigorov, I., Stoyanov, D., Iarlori, M., Rizi, V., Spinelli, N., Boselli, A., Wang, X., Lo Feudo, T., Perrone, M. R., De Tomasi, F., and Burlizzi, P.: EARLINET instrument intercomparison campaigns: overview on strategy and results, Atmos. Meas. Tech., 9, 1001–1023, https://doi.org/10.5194/amt-9-1001-2016, 2016.
Wang, L., Stanič, S., Eichinger, W., Močnik, G., Drinovec, L., and Gregorič, A.: Investigation of Aerosol Properties and Structures in Two Representative Meteorological Situations over the Vipava Valley Using Polarization Raman LiDAR, Atmosphere, 10, 128, https://doi.org/10.3390/atmos10030128, 2019a.
Wang, L., Stanič, S., Eichinger, W., Song, X., and Zavrtanik, M.: Development of an Automatic Polarization Raman LiDAR for Aerosol Monitoring over Complex Terrain, Sensors, 19, 3186, https://doi.org/10.3390/s19143186, 2019b.
Wang, L., Yin, Z., Bu, Z., Wang, A., Mao, S., Yi, Y., Müller, D., Chen, Y., and Wang, X.: Quality assessment of aerosol lidars at 1064 nm in the framework of the MEMO campaign, Atmos. Meas. Tech., 16, 4307–4318, https://doi.org/10.5194/amt-16-4307-2023, 2023.
Wang, W., Primbs, T., Tao, S., Zhu, T., and Simonich, S. L. M.: Atmospheric Particulate Matter Pollution during the 2008 Beijing Olympics, Environ. Sci. Technol., 43, 5314–5320, 2009.
Weinzierl, B., Sauer, D., Esselborn, M., Petzold, A., Veira, A., Rose, M., Mund, S., Wirth, M., Ansmann, A., Tesche, M., Gross, S., and Freudenthaler, V.: Microphysical and optical properties of dust and tropical biomass burning aerosol layers in the Cape Verde region – an overview of the airborne in situ and lidar measurements during SAMUM-2, Tellus B, 63, 589–618, https://doi.org/10.1111/j.1600-0889.2011.00566.x, 2011.
Weissmann, M., Braun, F. J., Gantner, L., Mayr, G. J., Rahm, S., and Reitebuch, O.: The structure of the Alpine mountain–plain circulation: airborne Doppler lidar measurements and numerical simulations, Mon. Weather Rev., 133, 3095–3109, https://doi.org/10.1175/MWR3012.1, 2005.
Yuan, R., Zhang, X., Liu, H., Gui, Y., Shao, B., Tao, X., Wang, Y., Zhong, J., Li, Y., and Gao, Z.: Aerosol vertical mass flux measurements during heavy aerosol pollution episodes at a rural site and an urban site in the Beijing area of the North China Plain, Atmos. Chem. Phys., 19, 12857–12874, https://doi.org/10.5194/acp-19-12857-2019, 2019.
Zhang, H., Wang, Y., Hu, J., Ying, Q., and Hu, X.-M.: Relationships between meteorological parameters and criteria air pollutants in three megacities in China, Environ. Res., 140, 242–254, https://doi.org/10.1016/j.envres.2015.04.004, 2015.
Zhang, R., Jing, J., Tao, J., Hsu, S.-C., Wang, G., Cao, J., Lee, C. S. L., Zhu, L., Chen, Z., Zhao, Y., and Shen, Z.: Chemical characterization and source apportionment of PM2.5 in Beijing: seasonal perspective, Atmos. Chem. Phys., 13, 7053–7074, https://doi.org/10.5194/acp-13-7053-2013, 2013.
Zhang, Y., Yi, F., Kong, W., and Yi, Y.: Slope characterization in combining analog and photon count data from atmospheric lidar measurements, Appl. Optics, 53, 7312–7320, https://doi.org/10.1364/AO.53.007312, 2014.
Zhang, Y., Guo, J., Yang, Y., Wang, Y., and Yim, S. H. L.: Vertical wind shear modulates particulate matter pollutions: A perspective from radar wind profiler observations in Beijing, China, Remote Sens., 12, 546, https://doi.org/10.3390/rs12030546, 2020.
Zhao, C., Wang, Y., Wang, Q., Li, Z., Wang, Z., and Liu, D.: A new cloud and aerosol layer detection method based on micropulse lidar measurements, J. Geophys. Res.-Atmos., 119, 6788–6802, https://doi.org/10.1002/2014JD021760, 2014.
Zou, W., Yin, Z., Dai, Y., Chen, Y., Bu, Z., and Li, S.: Robust Lidar-Radar Composite Cloud Boundary Detection Method With Rainfall Pixels Removal, IEEE T. Geosci. Remote, 62, 4111216, https://doi.org/10.1109/TGRS.2024.3476127, 2024.
Short summary
This study investigates aerosol transport flux structure over Beijing and dust transport's impact on air quality using polarization lidar and Doppler wind profiling lidar, focusing on a 2–4 November 2023, winter haze event. It classifies dust and non-dust aerosols via particle depolarization ratio, calculates their vertical/horizontal mass flux profiles with the covariance method, and analyzes meteorological influences.
This study investigates aerosol transport flux structure over Beijing and dust transport's...
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