Articles | Volume 17, issue 21
https://doi.org/10.5194/acp-17-13473-2017
https://doi.org/10.5194/acp-17-13473-2017
Research article
 | 
13 Nov 2017
Research article |  | 13 Nov 2017

Analysis of influential factors for the relationship between PM2.5 and AOD in Beijing

Caiwang Zheng, Chuanfeng Zhao, Yannian Zhu, Yang Wang, Xiaoqin Shi, Xiaolin Wu, Tianmeng Chen, Fang Wu, and Yanmei Qiu

Related authors

A global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology based on deep-learning methods
Yuanyuan Wu, Jihu Liu, Yannian Zhu, Yu Zhang, Yang Cao, Kang-En Huang, Boyang Zheng, Yichuan Wang, Yanyun Li, Quan Wang, Chen Zhou, Yuan Liang, Jianning Sun, Minghuai Wang, and Daniel Rosenfeld
Earth Syst. Sci. Data, 17, 3243–3258, https://doi.org/10.5194/essd-17-3243-2025,https://doi.org/10.5194/essd-17-3243-2025, 2025
Short summary
Machine learning significantly improves the simulation of hourly-to-yearly scale cloud nuclei concentration and radiative forcing in polluted atmosphere
Jingye Ren, Songjian Zou, Honghao Xu, Guiquan Liu, Zhe Wang, Anran Zhang, Chuanfeng Zhao, Min Hu, Dongjie Shang, Lizi Tang, Ru-Jin Huang, Yele Sun, and Fang Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1483,https://doi.org/10.5194/egusphere-2025-1483, 2025
Short summary
IMPMCT: a dataset of Integrated Multi-source Polar Meso-Cyclone Tracks
Runzhuo Fang, Jinfeng Ding, Wenjuan Gao, Xi Liang, Zhuoqi Chen, Chuanfeng Zhao, Haijin Dai, and Lei Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-186,https://doi.org/10.5194/essd-2025-186, 2025
Preprint under review for ESSD
Short summary
Wildfires heat the middle troposphere over the Himalayas and Tibetan Plateau during the peak of fire season
Qiaomin Pei, Chuanfeng Zhao, Yikun Yang, Annan Chen, Zhiyuan Cong, Xin Wan, Haotian Zhang, and Guangming Wu
EGUsphere, https://doi.org/10.5194/egusphere-2025-1172,https://doi.org/10.5194/egusphere-2025-1172, 2025
Short summary
Lightning declines over shipping lanes following regulation of fuel sulfur emissions
Chris J. Wright, Joel A. Thornton, Lyatt Jaeglé, Yang Cao, Yannian Zhu, Jihu Liu, Randall Jones II, Robert Holzworth, Daniel Rosenfeld, Robert Wood, Peter Blossey, and Daehyun Kim
Atmos. Chem. Phys., 25, 2937–2946, https://doi.org/10.5194/acp-25-2937-2025,https://doi.org/10.5194/acp-25-2937-2025, 2025
Short summary

Related subject area

Subject: Aerosols | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Atmospheric processing and aerosol aging responsible for observed increase in absorptivity of long-range-transported smoke over the southeast Atlantic
Abdulamid A. Fakoya, Jens Redemann, Pablo E. Saide, Lan Gao, Logan T. Mitchell, Calvin Howes, Amie Dobracki, Ian Chang, Gonzalo A. Ferrada, Kristina Pistone, Samuel E. Leblanc, Michal Segal-Rozenhaimer, Arthur J. Sedlacek III, Thomas Eck, Brent Holben, Pawan Gupta, Elena Lind, Paquita Zuidema, Gregory Carmichael, and Connor J. Flynn
Atmos. Chem. Phys., 25, 7879–7902, https://doi.org/10.5194/acp-25-7879-2025,https://doi.org/10.5194/acp-25-7879-2025, 2025
Short summary
Discussion of the spectral slope of the lidar ratio between 355 and 1064 nm from multiwavelength Raman lidar observations
Moritz Haarig, Ronny Engelmann, Holger Baars, Benedikt Gast, Dietrich Althausen, and Albert Ansmann
Atmos. Chem. Phys., 25, 7741–7763, https://doi.org/10.5194/acp-25-7741-2025,https://doi.org/10.5194/acp-25-7741-2025, 2025
Short summary
Observational constraints suggest a smaller effective radiative forcing from aerosol–cloud interactions
Chanyoung Park, Brian J. Soden, Ryan J. Kramer, Tristan S. L'Ecuyer, and Haozhe He
Atmos. Chem. Phys., 25, 7299–7313, https://doi.org/10.5194/acp-25-7299-2025,https://doi.org/10.5194/acp-25-7299-2025, 2025
Short summary
Analysis of a saline dust storm from the Aralkum Desert – Part 1: Consistency between multisensor satellite aerosol products
Xin Xi, Jun Wang, Zhendong Lu, Andrew M. Sayer, Jaehwa Lee, Robert C. Levy, Yujie Wang, Alexei Lyapustin, Hongqing Liu, Istvan Laszlo, Changwoo Ahn, Omar Torres, Sabur Abdullaev, James Limbacher, and Ralph A. Kahn
Atmos. Chem. Phys., 25, 7403–7429, https://doi.org/10.5194/acp-25-7403-2025,https://doi.org/10.5194/acp-25-7403-2025, 2025
Short summary
Retrieval of microphysical properties of dust aerosols from extinction, backscattering and depolarization lidar measurements using various particle scattering models
Yuyang Chang, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Igor Veselovskii, Fabrice Ducos, Gaël Dubois, Masanori Saito, Anton Lopatin, Oleg Dubovik, and Cheng Chen
Atmos. Chem. Phys., 25, 6787–6821, https://doi.org/10.5194/acp-25-6787-2025,https://doi.org/10.5194/acp-25-6787-2025, 2025
Short summary

Cited articles

Alebrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989.
Bibi, H., Alam, K., Christie, F., Bibi, S., Shahid, I., and Blaschke, T.: Intercomparison of MODIS, MISR, OMI, and CALIPSO aerosol optical depth retrievals for four locations on the Indo-Gangetic plains and validation against AERONET data, Atmos. Environ., 111, 113–126, https://doi.org/10.1016/j.atmosenv.2015.04.013, 2015.
Charlson, R. J., Schwartz, S. E., Hales, J. M., Cess, R. D., Coakley, J. A., Hansen, J. E., and Hofmann, D. J.: Climate forcing by anthropogenic aerosols, Science, 255, 423–430, https://doi.org/10.1126/science.255.5043.423, 1992.
CMA (China Meteorological Administration): Hourly averaged meteorological parameters, available at: http://data.cma.cn/site/index.html (last access: March 2017), 2011–2015.
Corbin, K. C., Kreidenweis, S. M., and Vonder Haar, T. H.: Comparison of aerosol properties derived from Sun photometer data and ground-based chemical measurements, Geophys. Res. Lett., 29, 1363, https://doi.org/10.1029/2001gl014105, 2002.
Download
Short summary
This study analyzes influential factors including the aerosol type, relative humidity (RH), atmospheric boundary layer height (BLH), wind speed and direction, and aerosol vertical structure to the AOD–PM2.5 relationship. It shows that the ratio of PM2.5 to AOD, η, varies a lot with aerosol type. η is smaller for scattering-dominant (coarse mode) than for absorbing-dominant (fine mode) aerosol. The higher the RH (BLH), the larger (smaller) the η. η also decreases with the surface wind speed.
Share
Altmetrics
Final-revised paper
Preprint