Long-term observations of NO2 using GEMS in China: Validations and regional transport

被引:8
|
作者
Li, Yikai [1 ]
Xing, Chengzhi [2 ]
Peng, Haochen [2 ]
Song, Yuhang [3 ]
Zhang, Chengxin [3 ]
Xue, Jingkai [1 ]
Niu, Xinhan [3 ]
Liu, Cheng [2 ,3 ,4 ,5 ]
机构
[1] Univ Sci & Technol China, Sch Environm Sci & Optoelect Technol, Hefei 230026, Peoples R China
[2] Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Key Lab Environm Opt & Technol, Hefei 230031, Peoples R China
[3] Univ Sci & Technol China, Dept Precis Machinery & Precis Instrumentat, Hefei 230026, Peoples R China
[4] Chinese Acad Sci, Ctr Excellence Reg Atmospher Environm, Inst Urban Environm, Xiamen 361021, Peoples R China
[5] Univ Sci & Technol China, Key Lab Precis Sci Instrumentat Anhui Higher Educ, Hefei 230026, Peoples R China
基金
中国国家自然科学基金;
关键词
GEMS; MAX-DOAS; Validations; Long-term variation; Regional transport; ABSORPTION CROSS-SECTIONS; MAX-DOAS MEASUREMENTS; VERTICAL COLUMN DENSITIES; TROPOSPHERIC NO2; AIR-QUALITY; NITROGEN-DIOXIDE; SATELLITE; OZONE; SO2; OMI;
D O I
10.1016/j.scitotenv.2023.166762
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In 2019, South Korea launched the Geostationary Environment Monitoring Spectrometer (GEMS) to observe trace gases with an hourly temporal resolution. Compared to previous payloads on polar-orbiting satellites, the GEMS payload has significant advantages in detecting the diurnal variation characteristics of NO2. However, there is still a lack of ground-based validations regarding the overall accuracy of GEMS in the Chinese region. In this study, we conducted a systematic ground validation of GEMS NO2 data in China for the first time. We validated the accuracy of GEMS NO2 data in four typical pollution regions in China, namely the Beijing-TianjinHebei region (JJJ), the Yangtze River Delta region (YRD), the Pearl River Delta region (PRD), and the Sichuan Basin region (SCB), based on MAX-DOAS and CNEMC data. The averaged correlations using the two datasets for validation were 0.81 and 0.57, respectively, indicating a high level of accuracy for the data in China. Using the GEMS seasonal averaged NO2 data, we studied the distribution of NO2 levels in the four regions. We found that the highest NO2 in all four regions occurred during winter with concentrations of 1.84 x 1016 molecules cm-2, 1.59 x 1016 molecules cm-2, 1.58 x 1016 molecules cm-2 and 9.47 x 1015 molecules cm-2, respectively. The distribution of NO2 was closely related to the terrain. Additionally, we observed a significant underestimation issue with TROPOMI, exceeding 30 % in many regions. Based on MAX-DOAS, we investigated the vertical distribution of NO2 in the four regions and found that NO2 was mainly concentrated below 0.5 km. with the HNU station having the lowest concentration, averaging only 2.12 ppb, which was approximately 41 % of the highest concentration recorded at the CQ station. Furthermore, we conducted a study on regional and cross-regional transport using a combination of MAX-DOAS and GEMS data. We found that the transport flux of NO2 could increase by over 500 % within 1 h, making a significant contribution to local NO2 concentrations. The joint observations of GEMS and MAX-DOAS will provide reliable data support for NO2 research and control in China, making a substantial contribution to environmental protection and sustainable development.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] A long-term regional simulation and observations of the hydroclimate in China
    Qian, Yun
    Leung, L. Ruby
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2007, 112 (D14)
  • [2] Deep learning bias correction of GEMS tropospheric NO2: A comparative validation of NO2 from GEMS and TROPOMI using Pandora observations
    Ghahremanloo, Masoud
    Choi, Yunsoo
    Singh, Deveshwar
    ENVIRONMENT INTERNATIONAL, 2024, 190
  • [3] Excess deaths associated with long-term exposure to ambient NO2 in China
    Qi, Ling
    Fu, Anqi
    Duan, Xiaoli
    ENVIRONMENTAL RESEARCH LETTERS, 2022, 17 (12)
  • [4] Long-Term Trends Worldwide in Ambient NO2 Concentrations Inferred from Satellite Observations
    Geddes, Jeffrey A.
    Martin, Randall V.
    Boys, Brian L.
    van Donkelaar, Aaron
    ENVIRONMENTAL HEALTH PERSPECTIVES, 2016, 124 (03) : 281 - 289
  • [5] Long-term observations of tropospheric NO2, SO2 and HCHO by MAX-DOAS in Yangtze River Delta area, China
    Xin Tian
    Pinhua Xie
    Jin Xu
    Ang Li
    Yang Wang
    Min Qin
    Zhaokun Hu
    Journal of Environmental Sciences, 2018, (09) : 207 - 221
  • [6] Long-term observations of tropospheric NO2, SO2 and HCHO by MAX-DOAS in Yangtze River Delta area, China
    Tian, Xin
    Xie, Pinhua
    Xu, Jin
    Li, Ang
    Wang, Yang
    Qin, Min
    Hu, Zhaokun
    JOURNAL OF ENVIRONMENTAL SCIENCES, 2018, 71 : 207 - 221
  • [7] Long-term countywide NO2 variations in Surrey
    Lythe, MS
    Hughes, SJ
    Hellawell, EE
    AIR POLLUTION IX, 2001, 10 : 559 - 568
  • [8] Using satellite observations of tropospheric NO2 columns to infer long-term trends in US NOx emissions: the importance of accounting for the free tropospheric NO2 background
    Silvern, Rachel F.
    Jacob, Daniel J.
    Mickley, Loretta J.
    Sulprizio, Melissa P.
    Travis, Katherine R.
    Marais, Eloise A.
    Cohen, Ronald C.
    Laughner, Joshua L.
    Choi, Sungyeon
    Joiner, Joanna
    Lamsal, Lok N.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2019, 19 (13) : 8863 - 8878
  • [9] Long-term exposure to ambient NO2 and adult mortality: A nationwide cohort study in China
    Zhang, Yunquan
    Li, Zunyan
    Wei, Jing
    Zhan, Yu
    Liu, Linjiong
    Yang, Zhiming
    Zhang, Yuanyuan
    Liu, Riyang
    Ma, Zongwei
    JOURNAL OF ADVANCED RESEARCH, 2022, 41 : 13 - 22
  • [10] GEMS: Underwater spectrometer for long-term radioactivity measurements
    Sartini, Ludovica
    Simeone, Francesco
    Pani, Priscilla
    Lo Bue, Nadia
    Marinaro, Giuditta
    Grubich, Andry
    Lobko, Alexander
    Etiope, Giuseppe
    Capone, Antonio
    Favali, Paolo
    Gasparoni, Francesco
    Bruni, Federico
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2011, 626 : S145 - S147