Articles | Volume 14, issue 10
https://doi.org/10.5194/amt-14-6601-2021
© Author(s) 2021. 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-14-6601-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmospheric carbon dioxide measurement from aircraft and comparison with OCO-2 and CarbonTracker model data
Qin Wang
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters, Nanjing University of Information Science and
Technology (NUIST), Nanjing 210044, China
Farhan Mustafa
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters, Nanjing University of Information Science and
Technology (NUIST), Nanjing 210044, China
Lingbing Bu
CORRESPONDING AUTHOR
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters, Nanjing University of Information Science and
Technology (NUIST), Nanjing 210044, China
Shouzheng Zhu
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters, Nanjing University of Information Science and
Technology (NUIST), Nanjing 210044, China
Key Laboratory of Space Laser Communication and Detection Technology,
Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of
Sciences, Shanghai 201800, China
Jiqiao Liu
Key Laboratory of Space Laser Communication and Detection Technology,
Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of
Sciences, Shanghai 201800, China
Weibiao Chen
Key Laboratory of Space Laser Communication and Detection Technology,
Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of
Sciences, Shanghai 201800, China
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Pingyi Dong, Xingwen Jiang, Xingbing Zhao, Yuanchang Dong, Jiafeng Zheng, Chun Hu, Guolu Gao, Lei Liu, Shulei Li, and Lingbing Bu
EGUsphere, https://doi.org/10.5194/egusphere-2025-2523, https://doi.org/10.5194/egusphere-2025-2523, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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A method is developed and validated for retrieving vertical profiles of DSD parameters from a single-frequency Ka-band radar in this study. Some unique characteristics of the vertical profiles of DSD parameters in the eastern Tibetan Plateau are found. The empirical relationships for quantitative precipitation estimates and attenuation correction in the eastern Tibetan Plateau with Ka-band radar are derived.
Xuanye Zhang, Hailong Yang, Lingbing Bu, Zengchang Fan, Wei Xiao, Binglong Chen, Lu Zhang, Sihan Liu, Zhongting Wang, Jiqiao Liu, Weibiao Chen, and Xuhui Lee
Atmos. Chem. Phys., 25, 6725–6740, https://doi.org/10.5194/acp-25-6725-2025, https://doi.org/10.5194/acp-25-6725-2025, 2025
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This study utilized the IPDA (integrated path differential absorption) lidar on board the DQ-1 satellite to monitor emissions from localized strong point sources and, for the first time, observed the diurnal variation in CO2 emissions from a high-latitude power plant. Overall, power plant CO2 emissions were largely consistent with local electricity consumption patterns, with most plants emitting less at night than during the day and with higher emissions in winter compared to spring and autumn.
Fanqian Meng, Junwu Tang, Guangyao Dai, Wenrui Long, Kangwen Sun, Zhiyu Zhang, Xiaoquan Song, Jiqiao Liu, Weibiao Chen, and Songhua Wu
Atmos. Meas. Tech., 18, 2021–2039, https://doi.org/10.5194/amt-18-2021-2025, https://doi.org/10.5194/amt-18-2021-2025, 2025
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This paper presents a comprehensive calibration procedure for the first spaceborne high-spectral-resolution lidar with an iodine vapor absorption filter Aerosol and Carbon Detection Lidar (ACDL) on board DQ-1 by utilizing nighttime 532 nm multi-channel data. We analyzed the error sources of the multi-channel calibration coefficients and assessed the results. The results indicate that the uncertainty of the clear-air scattering ratio was within the anticipated range of 7.9 %.
Chenxing Zha, Lingbing Bu, Zhi Li, Qin Wang, Ahmad Mubarak, Pasindu Liyanage, Jiqiao Liu, and Weibiao Chen
Atmos. Meas. Tech., 17, 4425–4443, https://doi.org/10.5194/amt-17-4425-2024, https://doi.org/10.5194/amt-17-4425-2024, 2024
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China has launched the atmospheric environment monitoring satellite DQ-1, which consists of an advanced lidar system. Our research presents a retrieval algorithm of the DQ-1 lidar system, and the retrieval results are consistent with other datasets. We also use the DQ-1 dataset to investigate dust and volcanic aerosols. This research shows that the DQ-1 lidar system can accurately measure the Earth's atmosphere and has potential for scientific applications.
Kangwen Sun, Guangyao Dai, Songhua Wu, Oliver Reitebuch, Holger Baars, Jiqiao Liu, and Suping Zhang
Atmos. Chem. Phys., 24, 4389–4409, https://doi.org/10.5194/acp-24-4389-2024, https://doi.org/10.5194/acp-24-4389-2024, 2024
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This paper investigates the correlation between marine aerosol optical properties and wind speeds over remote oceans using the spaceborne lidars ALADIN and CALIOP. Three remote ocean areas are selected. Pure marine aerosol optical properties at 355 nm are derived from ALADIN. The relationships between marine aerosol optical properties and wind speeds are analyzed within and above the marine atmospheric boundary layer, revealing the effect of wind speed on marine aerosols over remote oceans.
Guangyao Dai, Songhua Wu, Wenrui Long, Jiqiao Liu, Yuan Xie, Kangwen Sun, Fanqian Meng, Xiaoquan Song, Zhongwei Huang, and Weibiao Chen
Atmos. Meas. Tech., 17, 1879–1890, https://doi.org/10.5194/amt-17-1879-2024, https://doi.org/10.5194/amt-17-1879-2024, 2024
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An overview is given of the main algorithms applied to derive the aerosol and cloud optical property product of the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The paper demonstrates the observational capabilities of ACDL for aerosol and cloud vertical structure and global distribution through two optical property product measurement cases and global aerosol optical depth profile observations.
Qiantao Liu, Zhongwei Huang, Jiqiao Liu, Weibiao Chen, Qingqing Dong, Songhua Wu, Guangyao Dai, Meishi Li, Wuren Li, Ze Li, Xiaodong Song, and Yuan Xie
Atmos. Meas. Tech., 17, 1403–1417, https://doi.org/10.5194/amt-17-1403-2024, https://doi.org/10.5194/amt-17-1403-2024, 2024
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The achieved results revealed that the ACDL observations were in good agreement with the ground-based lidar measurements during dust events. The heights of cloud top and bottom from these two measurements were well matched and comparable. This study proves that the ACDL provides reliable observations of aerosol and cloud in the presence of various climatic conditions, which helps to further evaluate the impacts of aerosol on climate and the environment, as well as on the ecosystem in the future.
Fanqian Meng, Junwu Tang, Guangyao Dai, Wenrui Long, Kangwen Sun, Zhiyu Zhang, Xiaoquan Song, Jiqiao Liu, Weibiao Chen, and Songhua Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-588, https://doi.org/10.5194/egusphere-2024-588, 2024
Preprint archived
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This paper presents a comprehensive calibration procedure for the first spaceborne high-spectral-resolution lidar with an iodine vapor absorption filter ACDL on board DQ-1 by utilizing nighttime 532 nm multi-channel data. And analyzed the error sources of the multi-channel calibration coefficients and assessed the results. The results shows that the ACDL polarization channel calibration is reliable and operates within the expected error range of approximately 5 %.
Farhan Mustafa, Lingbing Bu, Qin Wang, Na Yao, Muhammad Shahzaman, Muhammad Bilal, Rana Waqar Aslam, and Rashid Iqbal
Atmos. Meas. Tech., 14, 7277–7290, https://doi.org/10.5194/amt-14-7277-2021, https://doi.org/10.5194/amt-14-7277-2021, 2021
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A neural-network-based approach was suggested to estimate CO2 emissions using satellite-based net primary productivity (NPP) and XCO2 retrievals. XCO2 anomalies were calculated for each year using OCO-2 retrievals. A Generalized Regression Neural Network (GRNN) model was then built; NPP, XCO2 anomalies, and ODIAC CO2 emissions from 2015 to 2018 were used as a training dataset; and, finally, CO2 emissions were predicted for 2019 based on the NPP and XCO2 anomalies calculated for the same year.
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Short summary
In this work, an airborne experiment was carried out to validate a newly developed CO2 monitoring IPDA lidar against the in situ measurements obtained from a commercial CO2 monitoring instrument installed on an aircraft. The XCO2 values calculated with the IPDA lidar measurements were compared with the dry-air CO2 mole fraction measurements obtained from the in situ instruments, and the results showed a good agreement between the two datasets.
In this work, an airborne experiment was carried out to validate a newly developed CO2...