Articles | Volume 18, issue 20
https://doi.org/10.5194/amt-18-5783-2025
© 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/amt-18-5783-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Global validation of the Particulate Observing Scanning Polarimeter (POSP) Aerosol Optical Depth products over land
State Key Laboratory of Remote Sensing and Digital Earth & Key Laboratory of Satellite Remote Sensing of Ministry of Ecology and Environment, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Zhengqiang Li
CORRESPONDING AUTHOR
State Key Laboratory of Remote Sensing and Digital Earth & Key Laboratory of Satellite Remote Sensing of Ministry of Ecology and Environment, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
State Key Laboratory of Spatial Datum, College of Remote Sensing and Geoinformatics Engineering, Faculty of Geographical Science and Engineering, Henan University, Zhengzhou, 450046, China
Gerrit de Leeuw
State Key Laboratory of Remote Sensing and Digital Earth & Key Laboratory of Satellite Remote Sensing of Ministry of Ecology and Environment, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Royal Netherlands Meteorological Institute (KNMI), R & D Satellite Observations, 3730 AE De Bilt, the Netherlands
Zihan Zhang
State Key Laboratory of Remote Sensing and Digital Earth & Key Laboratory of Satellite Remote Sensing of Ministry of Ecology and Environment, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Yan Ma
State Key Laboratory of Remote Sensing and Digital Earth & Key Laboratory of Satellite Remote Sensing of Ministry of Ecology and Environment, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Zheng Shi
The Administrative Center for China's Agenda 21, Beijing 100098, China
Cheng Fan
State Key Laboratory of Remote Sensing and Digital Earth & Key Laboratory of Satellite Remote Sensing of Ministry of Ecology and Environment, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Qian Yao
State Key Laboratory of Remote Sensing and Digital Earth & Key Laboratory of Satellite Remote Sensing of Ministry of Ecology and Environment, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
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Yuqin Liu, Tao Lin, Jiahua Zhang, Fu Wang, Meixia Lin, Yuan Chen, Yiyi Huang, Hongkai Geng, Xin Cao, and Gerrit de Leeuw
EGUsphere, https://doi.org/10.5194/egusphere-2025-3157, https://doi.org/10.5194/egusphere-2025-3157, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study reveals how air pollution affects cloud properties in eastern China using satellite data from 2008–2022. We find CER/LWP relationship exhibits three phases, modulated by aerosol concentration. The Twomey effect is confirmed, and its sensitivity shows significant spatial-scale dependence. Surprisingly, cleaner air after 2015 make clouds less sensitive to pollution's effects. The optimal buffer sizes show notable variations for the study area in the range from 6°×6° to 10°×10°.
Cheng Fan, Gerrit de Leeuw, Xiaoxi Yan, Jiantao Dong, Hanqing Kang, Chengwei Fang, Zhengqiang Li, and Ying Zhang
Atmos. Chem. Phys., 25, 11951–11973, https://doi.org/10.5194/acp-25-11951-2025, https://doi.org/10.5194/acp-25-11951-2025, 2025
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This study describes the analysis of time series of the MODIS-derived aerosol optical depth (AOD) over China between 2010 and 2024. Emission reduction policies were effective with respect to reducing the AOD until 2018. Thereafter, the overall reduction until the end of the study was very small due to unfavorable meteorological factors cancelling favorable anthropogenic effects and resulting in an AOD increase during extended periods. The variations over different areas in China are discussed.
Ying Zhang, Yuanyuan Wei, Gerrit de Leeuw, Ouyang Liu, Yu Chen, Yang Lv, Yuanxun Zhang, and Zhengqiang Li
Atmos. Chem. Phys., 25, 10643–10660, https://doi.org/10.5194/acp-25-10643-2025, https://doi.org/10.5194/acp-25-10643-2025, 2025
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Nitrogen dioxide (NO2) is a major pollutant that, at high concentrations, may affect human health. We evaluated the remote sensing column NO2 in relation to near-surface concentrations throughout the day and found that the prohibition of vertical transport in the morning and the mixing in the afternoon resulted in different relations between the near-surface (NS) and total column NO2 concentrations. These different relationships have consequences for the use of satellite remote sensing to estimate NS NO2 concentrations.
Cheng Chen, Xuefeng Lei, Zhenhai Liu, Haorang Gu, Oleg Dubovik, Pavel Litvinov, David Fuertes, Yujia Cao, Haixiao Yu, Guangfeng Xiang, Binghuan Meng, Zhenwei Qiu, Xiaobing Sun, Jin Hong, and Zhengqiang Li
Earth Syst. Sci. Data, 17, 3497–3519, https://doi.org/10.5194/essd-17-3497-2025, https://doi.org/10.5194/essd-17-3497-2025, 2025
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Particulate Observing Scanning Polarization (POSP) on board the second GaoFen-5 (GF-5(02)) satellite is the first space-borne ultraviolet–visible–near-infrared–shortwave-infrared (UV–VIS–NIR–SWIR) multi-spectral cross-track scanning polarimeter. Due to its wide spectral range and polarimetric capabilities, POSP measurements provide rich information for aerosol and surface characterization. We present the detailed aerosol/surface products generated from POSP's first 18 months of operation, including spectral aerosol optical depth, aerosol-size-/absorption-related properties, surface black-sky and white-sky albedos, etc.
Qiansi Tu, Frank Hase, Ying Zhang, Jiaxin Fang, Yanwu Jiang, Xiaofan Li, Matthias Schneider, Zhuolin Yang, Xin Zhang, and Zhengqiang Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-966, https://doi.org/10.5194/egusphere-2025-966, 2025
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Understanding GHG and air pollutant concentrations and emissions characteristics in the Qinghai-Tibetan Plateau cities remains limited. We present the first CO2, CH4 and CO column abundances using a portal FTIR spectrometer in Xining in 2024. Ground-based data exceeded satellite and model estimates, indicating higher local emissions. Significant CO discrepancies and a strong ∆XCO–∆XCO2 correlation under easterly winds highlight the value of portable FTIR for urban emission studies in the QTP.
Wenxin Zhao, Yu Zhao, Yu Zheng, Dong Chen, Jinyuan Xin, Kaitao Li, Huizheng Che, Zhengqiang Li, Mingrui Ma, and Yun Hang
Atmos. Chem. Phys., 24, 6593–6612, https://doi.org/10.5194/acp-24-6593-2024, https://doi.org/10.5194/acp-24-6593-2024, 2024
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We evaluate the long-term (2000–2020) variabilities of aerosol absorption optical depth, black carbon emissions, and associated health risks in China with an integrated framework that combines multiple observations and modeling techniques. We demonstrate the remarkable emission abatement resulting from the implementation of national pollution controls and show how human activities affected the emissions with a spatiotemporal heterogeneity, thus supporting differentiated policy-making by region.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
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A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Yuqin Liu, Tao Lin, Jiahua Zhang, Fu Wang, Yiyi Huang, Xian Wu, Hong Ye, Guoqin Zhang, Xin Cao, and Gerrit de Leeuw
Atmos. Chem. Phys., 24, 4651–4673, https://doi.org/10.5194/acp-24-4651-2024, https://doi.org/10.5194/acp-24-4651-2024, 2024
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A new method, the geographical detector method (GDM), has been applied to satellite data, in addition to commonly used statistical methods, to study the sensitivity of cloud properties to aerosol over China. Different constraints for aerosol and cloud liquid water path apply over polluted and clean areas. The GDM shows that cloud parameters are more sensitive to combinations of parameters than to individual parameters, but confounding effects due to co-variation of parameters cannot be excluded.
Ouyang Liu, Zhengqiang Li, Yangyan Lin, Cheng Fan, Ying Zhang, Kaitao Li, Peng Zhang, Yuanyuan Wei, Tianzeng Chen, Jiantao Dong, and Gerrit de Leeuw
Atmos. Meas. Tech., 17, 377–395, https://doi.org/10.5194/amt-17-377-2024, https://doi.org/10.5194/amt-17-377-2024, 2024
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Nitrogen dioxide (NO2) is a trace gas which is important for atmospheric chemistry and may affect human health. To understand processes leading to harmful concentrations, it is important to monitor NO2 concentrations near the surface and higher up. To this end, a Pandora instrument has been installed in Beijing. An overview of the first year of data shows the large variability on diurnal to seasonal timescales and how this is affected by wind speed and direction and chemistry.
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
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In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm is extended with a bi-directional reflection distribution function for snow surfaces. The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover > 75 %.
Hanqing Kang, Bin Zhu, Gerrit de Leeuw, Bu Yu, Ronald J. van der A, and Wen Lu
Atmos. Chem. Phys., 22, 10623–10634, https://doi.org/10.5194/acp-22-10623-2022, https://doi.org/10.5194/acp-22-10623-2022, 2022
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This study quantified the contribution of each urban-induced meteorological effect (temperature, humidity, and circulation) to aerosol concentration. We found that the urban heat island (UHI) circulation dominates the UHI effects on aerosol. The UHI circulation transports aerosol and its precursor gases from the warmer lower boundary layer to the colder lower free troposphere and promotes the secondary formation of ammonium nitrate aerosol in the cold atmosphere.
Jie Luo, Zhengqiang Li, Chenchong Zhang, Qixing Zhang, Yongming Zhang, Ying Zhang, Gabriele Curci, and Rajan K. Chakrabarty
Atmos. Chem. Phys., 22, 7647–7666, https://doi.org/10.5194/acp-22-7647-2022, https://doi.org/10.5194/acp-22-7647-2022, 2022
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The fractal black carbon was applied to re-evaluate the regional impacts of morphologies on aerosol–radiation interactions (ARIs), and the effects were compared between the US and China. The regional-mean clear-sky ARI is significantly affected by the BC morphology, and relative differences of 17.1 % and 38.7 % between the fractal model with a Df of 1.8 and the spherical model were observed in eastern China and the northwest US, respectively.
F. Zhang, Z. Zhang, L. Yan, J. Ding, K. Jiang, Y. Zhang, and Z. Cui
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 101–106, https://doi.org/10.5194/isprs-annals-V-3-2022-101-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-101-2022, 2022
Jie Luo, Zhengqiang Li, Cheng Fan, Hua Xu, Ying Zhang, Weizhen Hou, Lili Qie, Haoran Gu, Mengyao Zhu, Yinna Li, and Kaitao Li
Atmos. Meas. Tech., 15, 2767–2789, https://doi.org/10.5194/amt-15-2767-2022, https://doi.org/10.5194/amt-15-2767-2022, 2022
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A single model is difficult to represent various shapes of dust. We proposed a tunable model to represent dust with various shapes. Two tunable parameters were used to represent the effects of the erosion degree and binding forces from the mass center. Thus, the model can represent various dust shapes by adjusting the tunable parameters. Besides, the applicability of the spheroid model in calculating the optical properties and polarimetric characteristics is evaluated.
Kaixu Bai, Ke Li, Mingliang Ma, Kaitao Li, Zhengqiang Li, Jianping Guo, Ni-Bin Chang, Zhuo Tan, and Di Han
Earth Syst. Sci. Data, 14, 907–927, https://doi.org/10.5194/essd-14-907-2022, https://doi.org/10.5194/essd-14-907-2022, 2022
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The Long-term Gap-free High-resolution Air Pollutant concentration dataset, providing gap-free aerosol optical depth (AOD) and PM2.5 and PM10 concentration with a daily 1 km resolution for 2000–2020 in China, is generated and made publicly available. This is the first long-term gap-free high-resolution aerosol dataset in China and has great potential to trigger multidisciplinary applications in Earth observations, climate change, public health, ecosystem assessment, and environment management.
Boming Liu, Jianping Guo, Wei Gong, Yong Zhang, Lijuan Shi, Yingying Ma, Jian Li, Xiaoran Guo, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-26, https://doi.org/10.5194/amt-2022-26, 2022
Publication in AMT not foreseen
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Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China were thus far not evaluated by in-situ comparison. This work is the comparison of wind speed on a large scale between the Aeolus, ERA5 and RS , shedding important light on the data application of Aeolus wind products.
Yuqin Liu, Tao Lin, Juan Hong, Yonghong Wang, Lamei Shi, Yiyi Huang, Xian Wu, Hao Zhou, Jiahua Zhang, and Gerrit de Leeuw
Atmos. Chem. Phys., 21, 12331–12358, https://doi.org/10.5194/acp-21-12331-2021, https://doi.org/10.5194/acp-21-12331-2021, 2021
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The four-dimensional variation of aerosol properties over the BTH, YRD and PRD (east China) were investigated using satellite observations from 2007 to 2020. Distinct differences between the aerosol optical depth and vertical distribution of the occurrence of aerosol types over these regions depend on season, aerosol loading and meteorological conditions. Day–night differences between the vertical distribution of aerosol types suggest effects of boundary layer dynamics and aerosol transport.
Cheng Fan, Zhengqiang Li, Ying Li, Jiantao Dong, Ronald van der A, and Gerrit de Leeuw
Atmos. Chem. Phys., 21, 7723–7748, https://doi.org/10.5194/acp-21-7723-2021, https://doi.org/10.5194/acp-21-7723-2021, 2021
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Emission control policy in China has resulted in the decrease of nitrogen dioxide concentrations, which however leveled off and stabilized in recent years, as shown from satellite data. The effects of the further emission reduction during the COVID-19 lockdown in 2020 resulted in an initial improvement of air quality, which, however, was offset by chemical and meteorological effects. The study shows the regional dependence over east China, and results have a wider application than China only.
Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter J. T. Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 21, 6895–6917, https://doi.org/10.5194/acp-21-6895-2021, https://doi.org/10.5194/acp-21-6895-2021, 2021
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Absorptive aerosol has a potentially large impact on climate change. We evaluate and intercompare four global satellite datasets of absorptive aerosol optical depth (AAOD) and single-scattering albedo (SSA). We show that these datasets show reasonable correlations with the AErosol RObotic NETwork (AERONET) reference, although significant biases remain. In a follow-up paper we show that these observations nevertheless can be used for model evaluation.
Wenyuan Chang, Ying Zhang, Zhengqiang Li, Jie Chen, and Kaitao Li
Atmos. Chem. Phys., 21, 4403–4430, https://doi.org/10.5194/acp-21-4403-2021, https://doi.org/10.5194/acp-21-4403-2021, 2021
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Aerosol simulation in WRF-Chem often uses the MOSAIC aerosol mechanism. Still, we need variational data assimilation (DA) for the MOSAIC aerosols to blend aerosol optical measurements. This study provides a developed GSI variational DA system, with a tangent linear operator designed for multi-source and multi-wavelength aerosol optical measurements. We successfully applied the DA system in an aerosol field campaign to assimilate aerosol optical data in northwestern China.
Yang Zhang, Zhengqiang Li, Zhihong Liu, Yongqian Wang, Lili Qie, Yisong Xie, Weizhen Hou, and Lu Leng
Atmos. Meas. Tech., 14, 1655–1672, https://doi.org/10.5194/amt-14-1655-2021, https://doi.org/10.5194/amt-14-1655-2021, 2021
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The aerosol fine-mode fraction (FMF) is an important parameter reflecting the content of man-made aerosols. This study carried out the retrieval of FMF in China based on multi-angle polarization data and validated the results. The results of this study can contribute to the FMF retrieval algorithm of multi-angle polarization sensors. At the same time, a high-precision FMF dataset of China was obtained, which can provide basic data for atmospheric environment research.
Jianping Guo, Boming Liu, Wei Gong, Lijuan Shi, Yong Zhang, Yingying Ma, Jian Zhang, Tianmeng Chen, Kaixu Bai, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Chem. Phys., 21, 2945–2958, https://doi.org/10.5194/acp-21-2945-2021, https://doi.org/10.5194/acp-21-2945-2021, 2021
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Vertical wind profiles are crucial to a wide range of atmospheric disciplines. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China have thus far not been evaluated by in situ comparison. This work is expected to let the public and science community better know the Aeolus wind products and to encourage use of these valuable data in future research and applications.
Boming Liu, Jianping Guo, Wei Gong, Yong Zhang, Lijuan Shi, Yingying Ma, Jian Li, Xiaoran Guo, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-41, https://doi.org/10.5194/acp-2021-41, 2021
Revised manuscript not accepted
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Vertical wind profiles are crucial to a wide range of atmospheric disciplines. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China were thus far not evaluated by in-situ comparison. This work is expected to let the public and science community better know the Aeolus wind products and to encourage use of these valuable data in future researches and applications.
Qiaoyun Hu, Haofei Wang, Philippe Goloub, Zhengqiang Li, Igor Veselovskii, Thierry Podvin, Kaitao Li, and Mikhail Korenskiy
Atmos. Chem. Phys., 20, 13817–13834, https://doi.org/10.5194/acp-20-13817-2020, https://doi.org/10.5194/acp-20-13817-2020, 2020
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This study presents the characteristics of Taklamakan dust particles derived from lidar measurements collected in the dust aerosol observation field campaign. It provides comprehensive parameters for Taklamakan dust properties and vertical distributions of Taklamakan dust. This paper also points out the importance of polluted dust which was frequently observed in the field campaign. The results contribute to improving knowledge about dust and reducing uncertainties in the climatic model.
Ying Zhang, Zhengqiang Li, Yu Chen, Gerrit de Leeuw, Chi Zhang, Yisong Xie, and Kaitao Li
Atmos. Chem. Phys., 20, 12795–12811, https://doi.org/10.5194/acp-20-12795-2020, https://doi.org/10.5194/acp-20-12795-2020, 2020
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Observation of atmospheric aerosol components plays an important role in reducing uncertainty in climate assessment. In this study, an improved remote sensing method which can better distinguish scattering components is developed, and the aerosol components in the atmospheric column over China are retrieved based on the Sun–sky radiometer Observation NETwork (SONET). The component distribution shows there could be a sea salt component in northwest China from a paleomarine source in desert land.
Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457, https://doi.org/10.5194/acp-20-12431-2020, https://doi.org/10.5194/acp-20-12431-2020, 2020
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We intercompare 14 different datasets of satellite observations of aerosol. Such measurements are challenging but also provide the best opportunity to globally observe an atmospheric component strongly related to air pollution and climate change. Our study shows that most datasets perform similarly well on a global scale but that locally errors can be quite different. We develop a technique to estimate satellite errors everywhere, even in the absence of surface reference data.
Cited articles
Altieri, K., Eastham, S., Toure, N. 'Datchoh E., Jerez, S., Dada, L., Zhao, D., and Ojha, N.: Experts share priorities for addressing aerosol uncertainty, One Earth, 8, https://doi.org/10.1016/j.oneear.2025.101241, 2025.
Ångström, A.: On the Atmospheric Transmission of Sun Radiation and on Dust in the Air, Geogr. Ann., 11, 156–166, https://doi.org/10.1080/20014422.1929.11880498, 1929.
Bai, K., Li, K., Wu, C., Chang, N.-B., and Guo, J.: A homogenized daily in situ PM2.5 concentration dataset from the national air quality monitoring network in China, Earth Syst. Sci. Data, 12, 3067–3080, https://doi.org/10.5194/essd-12-3067-2020, 2020.
Beig, G., Sahu, S., Anand, V., Bano, S., Maji, S., Rathod, A., Korhale, N., Sobhana, S. B., Parkhi, N., Mangaraj, P., Srinivas R., Peshin, S. K., Singh S., Shinde R., and Trimbake, H. K.: India's Maiden air quality forecasting framework for megacities of divergent environments: The SAFAR-project, Environ. Model. Softw., 145, 105204, https://doi.org/10.1016/j.envsoft.2021.105204, 2021.
Bergametti, G., Dutot, A.-L., Buat-Menard, P., Losno, R., and Remoudaki, E.: Seasonal variability of the elemental composition of atmospheric aerosol particles over the northwestern Mediterranean, Tellus B Chem. Phys. Meteorol., 41, 353–361, 1989.
Bilal, M., Mhawish, A., Ali, M. A., Nichol, J. E., Leeuw, G. de, Khedher, K. M., Mazhar, U., Qiu, Z., Bleiweiss, M. P., and Nazeer, M.: Integration of surface reflectance and aerosol retrieval algorithms for multi-resolution aerosol optical depth retrievals over urban areas, Remote Sens., 14, 373, https://doi.org/10.3390/rs14020373, 2022.
Bréon, F.-M., Maignan, F., Leroy, M., and Grant, I.: Analysis of hot spot directional signatures measured from space, J. Geophys. Res.-Atmos., 107, AAC 1-1–AAC 1-15, https://doi.org/10.1029/2001JD001094, 2002.
Che, H., Zhang, X.-Y., Xia, X., Goloub, P., Holben, B., Zhao, H., Wang, Y., Zhang, X.-C., Wang, H., Blarel, L., Damiri, B., Zhang, R., Deng, X., Ma, Y., Wang, T., Geng, F., Qi, B., Zhu, J., Yu, J., Chen, Q., and Shi, G.: Ground-based aerosol climatology of China: aerosol optical depths from the China Aerosol Remote Sensing Network (CARSNET) 2002–2013, Atmos. Chem. Phys., 15, 7619–7652, https://doi.org/10.5194/acp-15-7619-2015, 2015.
Che, Y., Xue, Y., Mei, L., Guang, J., She, L., Guo, J., Hu, Y., Xu, H., He, X., Di, A., and Fan, C.: Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China, Atmos. Chem. Phys., 16, 9655–9674, https://doi.org/10.5194/acp-16-9655-2016, 2016.
Chen, C., Dubovik, O., Fuertes, D., Litvinov, P., Lapyonok, T., Lopatin, A., Ducos, F., Derimian, Y., Herman, M., Tanré, D., Remer, L. A., Lyapustin, A., Sayer, A. M., Levy, R. C., Hsu, N. C., Descloitres, J., Li, L., Torres, B., Karol, Y., Herrera, M., Herreras, M., Aspetsberger, M., Wanzenboeck, M., Bindreiter, L., Marth, D., Hangler, A., and Federspiel, C.: Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring, Earth Syst. Sci. Data, 12, 3573–3620, https://doi.org/10.5194/essd-12-3573-2020, 2020.
Chen, L., Shang, H., Fan, M., Tao, J., Husi, L., Zhang, Y., Wang, H., Cheng, L., Zhang, X., Wei, L., Li, M., Zou, M., and Liu, D.: Mission overview of the GF-5 satellite for atmospheric parameter monitoring, Natl. Remote Sens. Bull., 25, 1917–1931, https://doi.org/10.11834/JRS.20210582, 2021.
Chu, D. A., Kaufman, Y. J., Ichoku, C., Remer, L. A., Tanré, D., and Holben, B. N.: Validation of MODIS aerosol optical depth retrieval over land, Geophys. Res. Lett., 29, https://doi.org/10.1029/2001GL013205, 2002.
Cobourn, W. G.: Accuracy and reliability of an automated air quality forecast system for ozone in seven Kentucky metropolitan areas, Atmos. Environ., 41, 5863–5875, 2007.
de Leeuw, G., Kinne, S., Leon, J. F., Pelon, J., Rosenfeld, D., Schaap, M., Veefkind, P. J., Veihelmann, B., Winker, D. M., and von Hoyningen-Huene, W.: Retrieval of aerosol properties, in: The remote sensing of tropospheric composition from space, edited by: Burrows, J. P., Platt, U., and Borrell, P., 536 pp., Springer-Verlag Berlin Heidelberg 2011, 359–313, ISBN 978-3-64214790-6, https://doi.org/10.1007/978-3-642-14791-3, 2011.
de Leeuw, G., Sogacheva, L., Rodriguez, E., Kourtidis, K., Georgoulias, A. K., Alexandri, G., Amiridis, V., Proestakis, E., Marinou, E., Xue, Y., and van der A, R.: Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns, Atmos. Chem. Phys., 18, 1573–1592, https://doi.org/10.5194/acp-18-1573-2018, 2018.
Deng, Z. Z., Zhao, C. S., Ma, N., Liu, P. F., Ran, L., Xu, W. Y., Chen, J., Liang, Z., Liang, S., Huang, M. Y., Ma, X. C., Zhang, Q., Quan, J. N., Yan, P., Henning, S., Mildenberger, K., Sommerhage, E., Schäfer, M., Stratmann, F., and Wiedensohler, A.: Size-resolved and bulk activation properties of aerosols in the North China Plain, Atmos. Chem. Phys., 11, 3835–3846, https://doi.org/10.5194/acp-11-3835-2011, 2011.
Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanré, D., and Slutsker, I.: Variability of absorption and optical properties of key aerosol types observed in worldwide locations, J. Atmos. Sci., 59, 590–608, https://doi.org/10.1175/1520-0469(2002)059<0590:VOAAOP>2.0.CO;2, 2002.
Eck, T. F., Holben, B., Reid, J., Dubovik, O., Smirnov, A., O'neill, N., Slutsker, I., and Kinne, S.: Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols, J. Geophys. Res.-Atmos., 104, 31333–31349, 1999.
Fan, R., Ma, Y., Jin, S., Gong, W., Liu, B., Wang, W., Li, H., and Zhang, Y.: Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations, Sci. Total Environ., 856, 159117, https://doi.org/10.1016/j.scitotenv.2022.159117, 2023.
Frey, R. A., Ackerman, S. A., Liu, Y., Strabala, K. I., Zhang, H., Key, J. R., and Wang, X.: Cloud detection with MODIS. Part I: Improvements in the MODIS cloud mask for collection 5, J. Atmos. Ocean. Tech., 25, 1057–1072, https://doi.org/10.1175/2008JTECHA1052.1, 2008.
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019.
Goloub, P., Li, Z., Dubovik, O., Blarel, L., Podvin, T., Jankowiak, I., Lecoq, R., Deroo, C., Chatenet, B., Morel, J. P., Cuevas, E., and Ramos, R.: PHOTONS/AERONET sunphotometer network overview: description, activities, results, Proc. SPIE, 6936, 69360V, https://doi.org/10.1117/12.783171, 2008.
Guo, J. P., Deng, M. J., Lee, S.-S., Wang, F., Li, Z., Zhai, P. M., Liu, H., Lv, W. T., Yao, W., and Li, X.: Delaying precipitation and lightning by air pollution over Pearl River Delta. Part I: observational analyses, J. Geophys. Res.-Atmos., 121, 6472–6488, https://doi.org/10.1002/2015JD023257, 2016.
Gupta, A., Kant, Y., Mitra, D., and Chauhan, P.: Spatio-temporal distribution of INSAT-3D AOD derived particulate matter concentration over India, Atmos. Pollut. Res., 12, 159–172, 2021.
He, Q. and Huang, B.: Satellite-based mapping of daily high-resolution ground PM2.5 in China via space-time regression modelling, Remote Sens. Environ., 206, 72–83, 2018.
He, Q., Zhang, M., and Huang, B.: Spatio-temporal variation and impact factors analysis of satellite-based aerosol optical depth over China from 2002 to 2015, Atmos. Environ., 129, 79–90, https://doi.org/10.1016/j.atmosenv.2016.01.002, 2016.
Hidy, G.: Atmospheric aerosols: Some highlights and highlighters, 1950 to 2018, Aerosol Sci. Eng., 3, 1–20, 2019.
Hoff, R. M., Engel-Cox, J. A., Dimmick, F., Szykman, J. J., Johns, B., Kondragunta, S., Rogers, R., McCann, K., Chu, D.A., Torres, O., Prados, A., Al-Saadi, J., Kittaka, C., Boothe, V., Ackerman, S., and Wimmers, A.: 3D-AQS: a three-dimensional air quality system, in: Remote Sensing of Aerosol and Chemical Gases, Model Simulation/Assimilation, and Applications to Air Quality, edited by: Chu, A., Szykman, J., and Kondragunta, S., Proceedings of the SPIE, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference, Vol. 6299, https://doi.org/10.1117/12.677281, 2006.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y., 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, 1998.
Hou, W., Li, Z., Wang, J., Xu, X., Goloub, P., and Qie, L.: Improving Remote Sensing of Aerosol Microphysical Properties by Near-Infrared Polarimetric Measurements Over Vegetated Land: Information Content Analysis, J. Geophys. Res.-Atmos., 123, 2215-2243, https://doi.org/10.1002/2017JD027388, 2018.
Ichoku, C., Chu, D., Mattoo, S., Kaufman, Y., Remer, L., Tanre, D., Slutsker, I., and Holben, B.: A spatio-temporal approach for global validation and analysis of MODIS aerosol products, Geophys. Res. Lett., 29, 1616, https://doi.org/10.1029/2001GL013206, 2002.
Ji, Z., Ma, Y., de Leeuw, G., Shi, Z., and Li, Z.: An enhanced aerosol optical depth retrieval algorithm for Particulate Observing Scanning Polarimeter (POSP) data over land, IEEE Trans. Geosci. Remote Sens., 63, 1–18, https://doi.org/10.1109/TGRS.2024.3514170, 2025.
Jiao, Z., Schaaf, C. B., Dong, Y., Román, M., Hill, M. J., Chen, J. M., Wang, Z., Zhang, H., Saenz, E., Poudyal, R., Gatebe, C., Bréon, F.-M., Li, X., and Strahler, A.: A method for improving hotspot directional signatures in BRDF models used for MODIS, Remote Sens. Environ., 186, 135–151, https://doi.org/10.1016/j.rse.2016.08.007, 2016.
Kassianov, E. I. and Ovtchinnikov, M.: On reflectance ratios and aerosol optical depth retrieval in the presence of cumulus clouds, Geophys. Res. Lett., 35, https://doi.org/10.1029/2008GL033231, 2008.
Kaufman, Y. J., Tanré, D., Remer, L. A., Vermote, E. F., Chu, A., and Holben, B. N.: Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer, J. Geophys. Res.-Atmos., 102, 17051–17067, https://doi.org/10.1029/96JD03988, 1997.
Kim, H. S., Huh, J. B., Hopke, P. K., Holsen, T. M., and Yi, S. M.: Characteristics of the major chemical constituents of PM2.5 and smog events in Seoul, Korea in 2003 and 2004, Atmos. Environ., 41, 6762–6770, https://doi.org/10.1016/j.atmosenv.2007.04.060, 2007.
Lee, H., Calvin, K., Dasgupta, D., Krinner, G., Mukherji, A., Thorne, P., Trisos, C., Romero, J., Aldunce, P., and Barret, K.: IPCC, 2023: Climate Change 2023: Synthesis report, Summary for policymakers, Contribution of working groups I, II and III to the sixth assessment report of the intergovernmental panel on climate change, edited by: Core Writing Team, Lee, H. and Romero, J., IPCC, Geneva, Switzerland, 34 pp., https://cir.nii.ac.jp/crid/1360019997669261824 (last access: 2 March 2025), 2023.
Lei, X., Liu, Z., Tao, F., Dong, H., Hou, W., Xiang, G., Qie, L., Meng, B., Li, C., Chen, F., Xie, Y., Zhang, M., Fan, L., Cheng, L., and Hong, J.: Data Comparison and CrossCalibration between Level 1 Products of DPC and POSP Onboard the Chinese GaoFen-5(02) Satellite, Remote Sens., 15, 1933, https://doi.org/10.3390/RS15071933, 2023.
Levy, R. C., Remer, L. A., and Dubovik, O.: Global aerosol optical properties and application to Moderate Resolution Imaging Spectroradiometer aerosol retrieval over land, J. Geophys. Res.-Atmos., 112, https://doi.org/10.1029/2006JD007815, 2007.
Levy, R. C., Remer, L. A., Kleidman, R. G., Mattoo, S., Ichoku, C., Kahn, R., and Eck, T. F.: Global evaluation of the Collection 5 MODIS dark-target aerosol products over land, Atmos. Chem. Phys., 10, 10399–10420, https://doi.org/10.5194/acp-10-10399-2010, 2010.
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, 2013.
Li, H., Zhang, Q., Zhang, Q., Chen, C., Wang, L., Wei, Z., Zhou, S., Parworth, C., Zheng, B., Canonaco, F., Prévôt, A. S. H., Chen, P., Zhang, H., Wallington, T. J., and He, K.: Wintertime aerosol chemistry and haze evolution in an extremely polluted city of the North China Plain: significant contribution from coal and biomass combustion, Atmos. Chem. Phys., 17, 4751–4768, https://doi.org/10.5194/acp-17-4751-2017, 2017a.
Li, Z., Guo, J., Ding, A., Liao, H., Liu, J., Sun, Y., Wang, T., Xue, H., Zhang, H., 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, 2017b.
Li, Z., Hou, W., Hong, J., Zheng, F., Luo, D., Wang, J., Gu, X., and Qiao, Y.: Directional Polarimetric Camera (DPC): Monitoring aerosol spectral optical properties over land from satellite observation, J. Quant. Spectrosc. Ra., 218, 21–37, https://doi.org/10.1016/j.jqsrt.2018.07.003, 2018a.
Li, Z., Hou, W., Hong, J., Fan, C., Wei, Y., Liu, Z., Lei, X., Qiao, Y., Hasekamp, O. P., Fu, G., Wang, J., Dubovik, O., Qie, L. L., Zhang, Y., Xu, H., Xie, Y., Song, M., Zou, P., Luo, D., Wang, Y., and Tu, B.: The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM2.5 from space, J. Quant. Spectrosc. Ra., 286, 108217, https://doi.org/10.1016/j.jqsrt.2022.108217, 2022.
Li, Z., Xu, H., Li, K., Li, D., Xie, Y., Li, L., Zhang, Y., Gu, X., Zhao, W., Tian, Q., Deng, R., Su, X., Huang, B., Qiao, Y., Cui, W., Hu, Y., Gong, C., Wang, Y., Wang, X., Wang, J., Du, W., Pan, Z., Li, Z., and Bu, D.: Comprehensive study of optical, physical, chemical, and radiative properties of total columnar atmospheric aerosols over China: an overview of Sun–Sky Radiometer Observation Network (SONET) measurements, B. Am. Meteorol. Soc., 99, 739–755, 2018b.
Liu, B., Ma, X., Ma, Y., Li, H., Jin, S., Fan, R., and Gong, W.: The relationship between atmospheric boundary layer and temperature inversion layer and their aerosol capture capabilities, Atmos. Res., 271, 106121, https://doi.org/10.1016/j.atmosres.2022.106121, 2022.
Liu, P. F., Zhao, C. S., Göbel, T., Hallbauer, E., Nowak, A., Ran, L., Xu, W. Y., Deng, Z. Z., Ma, N., Mildenberger, K., Henning, S., Stratmann, F., and Wiedensohler, A.: Hygroscopic properties of aerosol particles at high relative humidity and their diurnal variations in the North China Plain, Atmos. Chem. Phys., 11, 3479–3494, https://doi.org/10.5194/acp-11-3479-2011, 2011.
Martins, J. V., Tanré, D., Remer, L., Kaufman, Y., Mattoo, S., and Levy, R.: MODIS Cloud screening for remote sensing of aerosols over oceans using spatial variability, Geophys. Res. Lett., 29, 1619, https://doi.org/10.1029/2001GL013252, 2002.
Moreno, S.: The WMO Global Atmosphere Watch Programme new implementation plan and strategic objectives, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14442, https://doi.org/10.5194/egusphere-egu23-14442, 2023.
Myhre, G., Bellouin, N., Berglen, T. F., Berntsen, T. K., Boucher, O., Grini, A., Isaksen, I. S. A., Johnsrud, M., Mishchenko, M. I., Stordal, F., and Tanré, D.: Comparison of the radiative properties and direct radiative effect of aerosols from a global aerosol model and remote sensing data over ocean, Tellus B, 59, 115129, https://doi.org/10.1111/j.1600-0889.2006.00226.x, 2007.
Oh, H.-R., Ho, C.-H., Kim, J., Chen, D., Lee, S., Choi, Y.-S., Chang, L.-S., and Song, C.-K.: Long-range transport of air pollutants originating in China: A possible major cause of multi-day high-PM10 episodes during cold season in Seoul, Korea, Atmos. Environ., 109, 23–30, 2015.
Omar, A. H., Winker, D. M., Vaughan, M. A., Hu, Y., Trepte, C. R., Ferrare, R. A., Lee, K. P., Hostetler, C. A., Kittaka, C., Rogers, R. R., Kuehn, R. E., and Liu, Z.: The CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm, J. Atmos. Ocean. Tech., 26, 1994–2014, https://doi.org/10.1175/2009JTECHA1231.1, 2009.
Popp, T., de Leeuw, G., Bingen, C., Brühl, C., Capelle, V., Chedin, A., Clarisse, L., Dubovik, O., Grainger, R., Griesfeller, J., Heckel, A., Kinne, S., Klüser, L., Kosmale, M., Kolmonen, P., Lelli, L., Litvinov, P., Mei, L., North, P., Pinnock, S., Povey, A., Robert, C., Schulz, M., Sogacheva, L., Stebel, K., Stein Zweers, D., Thomas, G., Tilstra, L., Vandenbussche, S., Veefkind, P., Vountas, M., and Xue, Y.: Development, Production and Evaluation of Aerosol Climate Data Records from European Satellite Observations (Aerosol_cci), Remote Sensing, 8, 421, https://doi.org/10.3390/rs8050421, 2016.
Rabha, S. and Saikia, B. K.: Advanced micro-and nanoscale characterization techniques for carbonaceous aerosols, in: Handbook of Nanomaterials in Analytical Chemistry, Elsevier, 449–472, https://doi.org/10.1016/B978-0-12-816699-4.00018-9, 2020.
Rosenfeld, D., Andreae, M. O., Asmi, A., Chin, M., de Leeuw, G., Donovan, D. P., Kahn, R., Kinne, S., Kivekas, N., Kulmala, M., Lau, W., Schmidt, K. S., Suni, T., Wagner, T., Wild, M., and Quaas, J.: Global observations of aerosol-cloudprecipitation-climate interactions, Rev. Geophys., 52, 750–808, https://doi.org/10.1002/2013rg000441, 2014.
Sayer, A. M., Hsu, N. C., Bettenhausen, C., and Jeong, M.-J.: Validation and uncertainty estimates for MODIS Collection 6 “Deep Blue” aerosol data, J. Geophys. Res.-Atmos., 118, 7864–7872, https://doi.org/10.1002/jgrd.50600, 2013.
Sayer, A. M., Hsu, N. C., Lee, J., Kim, W. V., and Dutcher, S. T.: Validation, Stability, and Consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue Aerosol Data Over Land, JGR Atmospheres, 124, 4658–4688, https://doi.org/10.1029/2018JD029598, 2019.
Schaaf, C. B., Gao, F., Strahler, A. H., Lucht, W., Li, X., Tsang, T., Strugnell, N. C., Zhang, X., Jin, Y., Muller, J.-P., Lewis, P., Barnsley, M., Hobson, P., Disney, M., Roberts, G., Dunderdale, M., Doll, C., d'Entremont, R. P., Hu, B., Liang, S., Privette, J. L., and Roy, D.: First operational BRDF, albedo nadir reflectance products from MODIS, Remote Sens. Environ., 83, 135–148, 2002.
Shi, Z., Xie, Y., Li, Z., Zhang, Y., Chen, C., Mei, L., Xu, H., Wang, H., Zheng, Y., Liu, Z., Hong, J., Zhu, M., Qie, L., Zhang, L., Fan, C., and Guang, J.: A generalized land surface reflectance reconstruction method for aerosol retrieval: Application to the Particulate Observing Scanning Polarimeter (POSP) onboard GaoFen-5 (02) satellite, Remote Sens. Environ., 295, 113683, https://doi.org/10.1016/j.rse.2023.113683, 2023.
Sogacheva, L., Kolmonen, P., Virtanen, T. H., Rodriguez, E., Saponaro, G., and de Leeuw, G.: Post-processing to remove residual clouds from aerosol optical depth retrieved using the Advanced Along Track Scanning Radiometer, Atmos. Meas. Tech., 10, 491–505, https://doi.org/10.5194/amt-10-491-2017, 2017.
Stocker, T. F., Dahe, Q., Plattner, G.-K., Alexander, L. V., Allen, S. K., Bindoff, N. L., Bréon, F.-M., Church, J. A., Cubash, U., Emori, S., Forster, P., Friedlingstein, P., Talley, L. D., Vaughan, D. G., and Xie, S.-P.: IPCC Technical Summary AR5, Climatic Change 2013, Phys. Sci. Basis, Contrib. Work. Gr. I to Fifth Assess. Rep. Intergov. Panel Clim. Chang., https://doi.org/10.1017/CBO9781107415324.005, 2013.
Sulla-Menashe, D. and Friedl, M. A.: User guide to collection 6 MODIS land cover (MCD12Q1 and MCD12C1) product, USGS, Reston, Va, Usa, 1, 18, http://girps.net/wp-content/uploads/2019/03/MCD12_User_Guide_V6.pdf (last access: 22 October 2025), 2018.
Tørseth, K., Aas, W., Breivik, K., Fjæraa, A. M., Fiebig, M., Hjellbrekke, A. G., Lund Myhre, C., Solberg, S., and Yttri, K. E.: Introduction to the European Monitoring and Evaluation Programme (EMEP) and observed atmospheric composition change during 1972–2009, Atmos. Chem. Phys., 12, 5447–5481, https://doi.org/10.5194/acp-12-5447-2012, 2012.
Tummon, F., Solmon, F., Liousse, C., and Tadross, M.: Simulation of the direct and semidirect aerosol effects on the southern Africa regional climate during the biomass burning season, J. Geophys. Res.-Atmos., 115, D19206, https://doi.org/10.1029/2009JD013738, 2010.
Vellalassery, A., Pillai, D., Marshall, J., Gerbig, C., Buchwitz, M., Schneising, O., and Ravi, A.: Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India, Atmos. Chem. Phys., 21, 5393–5414, https://doi.org/10.5194/acp-21-5393-2021, 2021.
Virtanen, T. H., Kolmonen, P., Sogacheva, L., Rodríguez, E., Saponaro, G., and de Leeuw, G.: Collocation mismatch uncertainties in satellite aerosol retrieval validation, Atmos. Meas. Tech., 11, 925–938, https://doi.org/10.5194/amt-11-925-2018, 2018.
Wei, J., Wang, J., Li, Z., Kondragunta, S., Anenberg, S., Wang, Y., Zhang, H., Diner, D., Hand, J., Lyapustin, A., Kahn, R., Colarco, P., da Silva, A., and Ichoku, C.: Long-term mortality burden trends attributed to black carbon and PM2.5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study, Lancet Planet. Health, 7, e963–e975, https://doi.org/10.1016/S2542-5196(23)00235-8, 2023.
Wong, M., Nichol, J., and Lee, K.: An operational MODIS aerosol retrieval algorithm at high spatial resolution, and its application over a complex urban region, Atmos. Res., 99, 579–589, https://doi.org/10.1016/j.atmosres.2010.12.015, 2011.
Wu, H. J., Tang, X., Wang, Z. F., Wu, L., Lu, M. M., Wei, L. F., and Zhu, J.: Probabilistic Automatic Outlier Detection for Surface Air Quality Measurements from the China National Environmental Monitoring Network, Adv. Atmos. Sci., 35, 1522–1532, https://doi.org/10.1007/s00376-018-8067-9, 2018.
Xian, D., Zhang, P., Gao, L., Sun, R., Zhang, H., and Jia, X.: Fengyun meteorological satellite products for earth system science applications, Adv. Atmos. Sci., 38, 1267–1284, https://doi.org/10.1007/s00376-021-0425-3, 2021.
Xie, G., Wang, M., Pan, J., and Zhu, Y.: Spatio-temporal variations and trends of MODIS C6.1 Dark Target and Deep Blue merged aerosol optical depth over China during 2000–2017, Atmos. Environ., 214, 116846, https://doi.org/10.1016/j.atmosenv.2019.116846, 2019.
Zhao, B., Jiang, J. H., Diner, D. J., Su, H., Gu, Y., Liou, K.-N., Jiang, Z., Huang, L., Takano, Y., Fan, X., and Omar, A. H.: Intra-annual variations of regional aerosol optical depth, vertical distribution, and particle types from multiple satellite and ground-based observational datasets, Atmos. Chem. Phys., 18, 11247–11260, https://doi.org/10.5194/acp-18-11247-2018, 2018.
Short summary
A global AOD product from Particulate Observing Scanning Polarimeter (POSP) has been proposed and validated using Aerosol Robotic Network (AERONET). Results show a high accuracy, with correlation coefficients (R) of 0.914, a root mean square error (RMSE) of 0.085, outperforming Moderate Resolution Imaging Spectroradiometer (MODIS). Error analysis reveals seasonal variation with lower accuracy in autumn/winter, and increased uncertainty with lower Normalized Difference Vegetation Index NDVI.
A global AOD product from Particulate Observing Scanning Polarimeter (POSP) has been proposed...