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Systematics of atmospheric environment monitoring in China via satellite remote sensing

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Abstract

Satellite remote sensing is increasingly applied in the field of environmental protection, especially in atmospheric monitoring. Here, a comprehensive review is provided on the development, limits, and prospects of remote sensing of the atmospheric environment in China. Firstly, the paper introduced the principle of detection of three types of atmospheric parameters and commonly used satellite data. Secondly, advances in retrieval methods, product validations, and applications in China were summarized. This included aerosol, particulate matter, haze, straw burning, dust storm, gaseous pollutant (sulfur dioxide, nitrogen dioxide, and ozone), greenhouse gas (carbon dioxide and methane), and air quality monitoring and control. Thirdly, products widely applied in monitoring the atmospheric environment in China were analyzed. Finally, the outlooks for future development were discussed. This included application of China’s satellite data, enhancement of the accuracy of air pollution monitoring, and services for environmental management.

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References

  • Bao FW, Gu XF, Cheng TH, Wang Y, Guo H, Chen H, Wei X, Xiang K, Li Y (2016) High-spatial-resolution aerosol optical properties retrieval algorithm using Chinese high-resolution earth observation satellite I. IEEE T Geosci Remote 54(9):5544–5552

    Google Scholar 

  • Bella D, Culpepper J, Khaimova J, Ahmed N, Belkalai A, Arroyo I, Andrews J, Gentle S, Emmanuel S, Lahmouh M, Ealy J, King Z, Jenkins O, Fu D, Choi Y, Osterman G, Gruszczynski J, Skeete D, Blaszczak-Boxe CS (2016) Characterization of pollution transport into Texas using OMI and TES satellite, GIS and in situ data, and HYSPLIT back trajectory analyses: implications for TCEQ State Implementation Plans. Air Qual Atmos Health 9:569–588

  • Chen LF, Zhang Y, Zou MM, Xu Q, Li LJ, Li XY, Tao JH (2015) Advances in satellite remote sensing of atmospheric CO2 concentration. J Remote Sens 19(1):1–11 (in Chinese with English abstract)

  • Chen H, Li Q, Wang ZT, Sun Y, Mao HQ, Cheng B (2018) Utilization of MERSI and MODIS data to monitor PM2.5 concentration in Beijing–Tianjin–Hebei and its surrounding areas. J Remote Sens 22(5):822–832

  • Crisp D, Fisher BM, Dell CO,Frankenberg C, Basilio R, Bösch H, Brown LR, Castano R, Connor B, Deutscher NM, Eldering A, Griffith D, Gunson M, Kuze A, Mandrake L, McDuffie J, Messerschmidt J, Miller CE, Morino I, Natraj V, Notholt J, O'Brien DM, Oyafuso F, Polonsky I, Robinson J, Salawitch R, Sherlock V, Smyth M, Suto H, Taylor TE, Thompson DR, Wennberg PO, Wunch D, Yung YL (2012) The ACOS CO2 retrieval algorithm part II: global XCO data characterization. Atmos Meas Tech 5(4):687–707

  • Gao J, Zha Y (2010) Meteorological influence on predicting air pollution from MODIS-derived aerosol optical thickness: a case study in Nanjing, China. Remote Sens 2(9):2136–2147

  • Giglio L, Descloitres J, Justice CO, Kaufman YJ (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sens Environ 87:273–282

  • Guo M, Wang X, Liu Y, Li J, Wang H, Matsuoka N, Tani H (2012) The effects of sand dust storms on greenhouse gases. Int J Remote Sens 33(21):6838–6853

  • He H (2012) Air pollutant concentrations and trends over the eastern U.S. and China: aircraft measurements and numerical simulations. USA: University of Maryland Libraries

  • He H (2014) Atmospheric haze tracing and control. Report of the General Meeting of the Joint Academic Conference of Geosciences of China 2014

  • Hsu N, Jeong MJ, Bettenhausen C,Sayer AM, Hansell R, Seftor CS, Huang J, Tsay SC (2013) Enhanced deep blue aerosol retrieval algorithm: the second generation. J Geophys Res 118:9296–9315

  • Hu XQ, Lu NM, Zhang P (2006) Remote sensing and detection of dust storm in China using the thermal bands of geostationary meteorological satellite. Chinese Meteorological Society 2006:395–405

  • Hua DX, Song XQ (2008) Advances in lidar remote sensing techniques. Infrared Laser Eng 37(S):21–27 (in Chinese with English abstract)

  • Huang JP, Ge JM, Weng FZ (2007) Detection of Asia dust storms using multi-sensor satellite measurements. Remote Sens Environ 110(2):186–191

  • Huang J, Xia LH, Gao YL, Wang XX (2009) Remote sensing monitoring on photochemical pollution caused by haze in Pearl River Delta. Urban Remote Sensing Event Joint 2009:1–6

  • Hutchison K (2003) Application of MODIS satellite data and products for monitoring air quality in the state of Texas. Atmos Environ 37:2403–2412

  • Jing X, Jiang J (2011) Temporal-spatial distribution of SO2 and NO2 in Yangtze River Delta, China from 2005 to 2010, vol 2011. International Conference on Remote Sensing, Environment and Transportation Engineering, pp 5457–5460

  • Jiang Q, Christakos G (2018) Space-time mapping of ground-level PM2.5 and NO2 concentrations in heavily polluted northern China during winter using the Bayesian maximum entropy technique with satellite data. Air Qual Atmos Health 11(1):23–33

  • Jiang X, Liu Y, Yu B, Jiang M (2007) Comparison of MISR aerosol optical thickness with AERONET measurements in Beijing metropolitan area. Remote Sens Environ 107:45–53

  • Jiao J, Liu MX, Li LR, Che YD (2018) Spatio-temporal change and influencing factors of tropospheric HCHO column density of the five provinces of North China in the 12 years. Acta Sci Circumst 38(6):2191–2200 (in Chinese with English abstract)

  • Kai Q, Hu MY, Wu LX, Rao LL, Lang HM, Wang LY, Yang B (2016) Satellite remote sensing of aerosol optical depth, SO2 and NO2 over China’s Beijing-Tianjin-Hebei region during 2002–2013. IEEE Geosci Remote Sens Sym 2016:5727–5728

  • Krotkov NA, Mclinden CA, Li C,Li C, Lamsal LN, Celarier EA, Marchenko SV, Swartz WH, Bucsela EJ, Joiner J, Duncan BN, Boersma K F, Veefkind JP, Levelt PF, Fioletov VE, Dickerson RR, He H, Lu Z, Streets DG (2016) Aura OMI observations of regional SO2 and NO2 pollution changes from 2005 to 2015. Atmos Chem Phys 16(7):4605–4629

  • Lee HJ, Koutrakis P (2014) Daily ambient NO2 concentration predictions using satellite ozone monitoring instrument NO2 data and land use regression. Environ Sci Technol 48:2305–2311

  • Lee YC, Chan KL, Wenig MO (2019) Springtime warming and biomass burning causing ozone episodes in South and Southwest China. Air Qual Atmos Health 12:919–931

  • Levy RC, Remer LA, Mattoo SN,Vermote EF, Kaufman YJ (2007) Second-generation operational algorithm: retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. J Geophys Res Atmos 112(13):D13211

  • Li CC, Mao JT, Liu QH,Yuan ZB, Wang MH, Liu XY (2005) Application of MODIS satellite remote sensing aerosol products in the study of air pollution in Beijing. Chin Sci (Ser D Geosci) 48(S1):177–186

  • Li SS, Chen LF, Xiong XZ, Tao JH, Su L, Han D, Liu Y (2013) Retrieval of the haze optical thickness on North China plain using MODIS data. IEEE T Geosci Remote 51(5):2528–2540

  • Li Y, Lin CQ, Lau AK,Liao CH, Zhang YB, Zeng WT, Li CC, Fung JCH, Tse TKT (2015) Assessing long-term trend of particulate matter pollution in the Pearl River Delta region using satellite remote sensing. Environ Sci Technol 49(19):11670–11678

  • Li Z, Zhang Y, Shao J, Li BS, Hong J, Liu D, Li DH, Wei P, Li W, Lei L, Zhang FX, Guo J, Deng Q, Wang BX, Cui CL, Zhang WC, Wang ZZ, Lv Y, Xu H, Chen XF, Li L, Qie LL (2016) Remote sensing of atmospheric particulate mass of dry PM 2.5 near the ground: method validation using ground-based measurements. Remote Sens Environ 173:59–68

  • Li TW, Shen HF, Zeng C, Yuan QQ, Zhang LP (2017) Point-surface fusion of station measurements and satellite observations for mapping PM2.5 distribution in China: methods and assessment. Atmos Environ 152:477–489

  • Lin CQ, Li Y, Lau AK, Li CC, Fung JCH (2018) 15-year PM2.5 trends in the Pearl River Delta region and Hong Kong from satellite observation. Aerosol Air Qual Res 18(9):2355–2362

  • Liu XD, Tian L, Zhang XY (2004) Influence of spring dust activities over the Taklimakan Desert area on concentrations of atmospheric PM10 in east of Northwest China. China Environ Sci 24(5):528–532 (in Chinese with English abstract)

  • Liu Y, Sarnat JA, Kilaru V, Jacob DJ, Koutrakis P (2005) Estimating ground-level PM2.5, in the Eastern United States using satellite remote sensing. Environ Sci Technol 39(9):3269–3278

  • Liu Y, Lv DR, Chen HB, Yang DX, Min M (2011) Advances in technology and methods of satellite remote sensing of atmospheric CO are reviewed. Remote Sens Technol Appl 26(2):247–254 (in Chinese with English abstract)

  • Liu MM, Huang YY, Ma ZW, Jin Z, Liu X, Wang H, Liu Y, Wang J, Jantunen M, Bi J, Kinney PL (2017) Spatial and temporal trends in the mortality burden of air pollution in China: 2004-2012. Environ Int 98:75–81

  • Luo BB, Chen ZY, Zhang TS,Fan GQ, Xiang Y (2019) Comparison of aerosol vertical distribution based on CALIPSO satellite and ground observation data. Chin J Lasers 46(12): 31-39 (in Chinese with English abstract)

  • Ma PF, Chen LF, Wang ZT, Zhao S, Li Q, Tao M, Wang Z (2016) Ozone profile retrievals from the cross-track infrared sounder. IEEE Trans Geosci Remote 54(7):3985–3994

  • Rodgers CD (2000) Inverse methods for atmospheric sounding: theory and practice. World Sci, Singapore

  • Safarianzengir V, Sobhani B, Yazdani MH, Kianian M (2020) Monitoring, analysis and spatial and temporal zoning of air pollution (carbon monoxide) using Sentinel-5 satellite data for health management in Iran, located in the Middle East. Air Qual Atmos Health 13:709–719

  • Song H, Yang M (2014) Analysis on effectiveness of SO2 emission reduction in Shanxi, China by satellite remote sensing. Atmosphere 5(4):830–846

  • Su WJ, Liu C, Hu QH, Zhao S, Sun Y, Wang W, Zhu Y, Liu J, Kim J (2019) Primary and secondary sources of ambient formaldehyde in the Yangtze River Delta based on OMPS observation. Atmos Chem Phys 19:6717–6736

  • Sun L, Wei J, Bilal M,Tian X, Jia C, Guo Y, Mi X (2016) Aerosol optical depth retrieval over bright areas using Landsat 8 OLI images. Remote Sens 8:23

  • Sun K, Chen XL, Zhu ZM, Zhang T (2017) High resolution aerosol optical depth retrieval using Gaofen-1 WFV camera data. Remote Sens 9:89

  • Tan W, Zhao SH, Liu C, Chan KL, Xie Z, Zhu Y, Su W, Zhang C, Liu H, Xing C, Liu J (2019) Estimation of winter time NOx emissions in Hefei, a typical inland city of China, using mobile MAX-DOAS observations. Atmos Environ 200:228–242

  • Tanré D, Herman M, Deschamps PY, Leffe A (1979) Atmospheric modeling for space measurements of ground reflectances, including bidirectional properties. Appl Opt 18(21):3587–3594

  • Tao MH, Chen LF, Wang ZF, Wang J, Che HZ, Xu XG, Wang WC, Tao JH, Zhu H, Hou C (2017) Evaluation of MODIS deep blue aerosol algorithm in desert region of East Asia: ground validation and intercomparison. J Geophys Res 122(19):10,357–10,368

  • Wang ZF, Chen LF, Gu XF (2008) Monitoring of crop residue burning in North China on the basis of MODIS data. Remote Sens Technol Appl 23(6):611–617 (in Chinese with English abstract)

  • Wang Q, Li Q, Chen LF, Zhang MG, Zhang XY (2011) Satellite remote sensing technology of atmospheric environment and its application. Science Press, Beijing

  • Wang ZT, Ma PF, Chen H, Zhang YH, Zhang LJ, Li SS, Li Q, Chen LF (2019) Aerosol retrieval in the autumn and winter over the Beijing-Tianjin-Hebei region from the red and 2.12μm bands of MODIS. IEEE Trans Geosci Remote 57(4):2372–2380

  • Wang ZT, Li Q, Li SS, Chen LF, Zhou CY, Wang ZF, Zhang LJ (2012) Application of haze monitoring based on Environment-1 satellite. Spectrosc Spect Anal 32(3):775–780 (in Chinese with English abstract)

  • Wu J, Yao F, Li W, Si M (2016) Viirs-based remote sensing estimation of ground-level pm2.5 concentrations in Beijing–Tianjin–Hebei: a spatiotemporal statistical model. Remote Sens Environ 184:316–328

  • Xiang JM, Zhu SY, Zhang GX,Liu Y, Zhou Y (2019) Progress in haze monitoring by remote sensing technology. Remote Sens Tech Appl 34(1):12–20 (in Chinese with English abstract)

  • Xing C, Liu C, Wang S, Chan KL, Gao Y, Huang X, Su W, Zhang C, Dong Y, Fan G, Zhang T, Chen Z, Hu Q, Su H, Xie Z, Liu J (2017) Observations of the vertical distributions of summertime atmospheric pollutants and the corresponding ozone production in Shanghai, China. Atmos Chem Phys 17:14275–14289

  • Xue T, Zheng Y, Geng G, Zheng B, Jiang X, Zhang Q, He K (2017) Fusing observational, satellite remote sensing and air quality model simulated data to estimate spatiotemporal variations of PM2.5 exposure in China. Remote Sens 9(3):221

  • Yan HH, Li XJ, Zhang XY, Wang WH, Chen LF, Zhang MG, Xu J (2016) Comparison and validation of band residual difference algorithm and principal component analysis algorithm for retrievals of atmospheric SO columns from satellite observations. Acta Phys Sin 65(8):084204 (in Chinese with English abstract)

  • Yoshida Y, Ota Y, Eguchi N, Kikuchi N, Nobuta K, Tran H, Morino I, Yokota T (2011) Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the greenhouse gases observing satellite. Atmos Meas Tech 4:717–734

  • Yu X, Zhao WJ, Sun CY, Xiong QL, Ou Y (2017) Advances in atmospheric PM2.5 remote sensing inversion. Environ Pollut Control 39(10):1153–1158 (in Chinese with English abstract)

  • Zhang X, Bai W, Zhang P, Wang WH (2011) Spatiotemporal variations in mid-upper tropospheric methane over China from satellite observations. Chin Sci Bull 56(31):3321–3327 (in Chinese with English abstract)

  • Zhang C, Liu C, Wang Y, Si F, Zhou H, Zhao M, Su W, Zhang W, Chan KL, Liu X, Xie P, Liu J, Wagner T (2018) Preflight evaluation of the performance of the Chinese Environmental trace gas Monitoring Instrument (EMI) by spectral analyses of nitrogen dioxide. IEEE Trans Geosci Remote 56(6):3323–3332

  • Zhang ZL, Yu HY, Lin Y, Yu J, Hu ZY, Gu Q (2019) Application of satellite remote sensing in air quality guarantee of major events. Environ Monit Forewarn 11(5): 84-90 (in Chinese with English abstract)

  • Zhang Y, Li ZQ, Li DH, Xu H, Ma Y, Zhang YH (2014) Study on remote sensing monitoring method of fine particulate matter near the ground. The First Chinese Academic Conference on Geodesy and Geophysics

  • Zhang XY, Zhou MQ, Wang WH, Li XJ (2015) Progress of global satellite remote sensing of atmospheric compositions and its' applications. Sci Technol Rev 33(17):13–22 (in Chinese with English abstract)

  • Zhao SW, Xu YW, Shi HY (2009) Research and Prospect of remote sensing monitoring on Chinese sand-dust disaster. Meteorol Environ Sci 32(4):65–68 (in Chinese with English abstract)

  • Zhao SH, Wang Q, Li Y, Liu S, Wang Z, Zhu L, Wang Z (2017) An overview of satellite remote sensing technology used in China’s environmental protection. Earth Sci Inf 10(2):137–148

  • Zhao SH, Liu SH, Liu QQ, Wu YT, Wu D (2019) Progress of urban ecological environment monitoring by remote sensing in China. Ecol Environ Sci 28(06):1261–1271 (in Chinese with English abstract)

  • Zheng FX, Hou WZ, Li ZQ (2019) Optimal estimation retrieval for directional polarimetric camera onboard Chinese Gaofen-5 satellite: an analysis on multi-angle dependence and a posteriori error. Acta Phys Sin 68(4):040701

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Acknowledgments

We thank the editors and anonymous reviewers for the insightful suggestion during the manuscript review process.

Funding

This work was supported by the National Key R&D Program of China (Grant No. 2017YFB0503905), the Major Projects of High-Resolution Earth Observation Systems of National Science and Technology (Grant No. 05-Y30B01-9001-19/20), and the Natural Science Foundation of China (Grant No. 41971324).

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Correspondence to Shaohua Zhao.

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Wang, Z., Ma, P., Zhang, L. et al. Systematics of atmospheric environment monitoring in China via satellite remote sensing. Air Qual Atmos Health 14, 157–169 (2021). https://doi.org/10.1007/s11869-020-00922-7

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