Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Analysis of spatial and temporal variability of aerosol optical depth over China using MODIS combined Dark Target and Deep Blue product

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

This study reviews spatial and temporal variability of aerosol optical depth (AOD) at 550 nm, obtained with Moderate Resolution Imaging Spectroradiometer (MODIS) (Terra) Collection 6.1 aerosol products with use of combined Dark Target and Deep Blue algorithm. Data was analyzed for 18-year period from 2000 to 2017 over the territory of the whole continental China, covering the largest cities as well as various ecological and geographical regions. Spatial distribution of AOD has distinct geographical differences with gradual decrease from the east to the west of the country. The lowest values (up to 0.25) of annual mean AOD at 550 nm occur in sparsely populated areas on the Tibetan Plateau and in the north forest ecosystems in the north-eastern part of China. Areas of desert and semidesert landscapes of Northwest China are characterized by high concentrations of naturally occurring aerosols with moderate values of AOD (0.4–0.7). The most populous regions (Pearl River Delta, Yangtze River Delta, North China Plain, and Sichuan Basin) with the highest density of agricultural and industrial activity are characterized with maximum values of AOD (over 0.7). Seasonal variation of aerosols in the most regions of China has maximum AODs in spring or summer and minimum in autumn or winter. Ångström exponent (AE), being 0.31–1.7 for the most part of China, was used to detect the size of aerosol particles, with the lowest values (0.31–0.84) in desert north and north-west regions of the country, and the higher values in the south (1.3–1.7). Comparison of results, obtained with MODIS Terra and AERONET (Aerosol Robotic Network) at 550 nm, demonstrate a high interrelation (r = 0.8949), where 68.3% fall within the range of expected errors, set by MODIS over the land (± 0.05 ± 0.15 × AOD). The conducted Pearson’s correlation analysis between various cities of the country showed that cities in one region with shortest distances from one another demonstrated higher correlations, suggesting distinct regional dependence in aerosols distribution.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Bian H, Chin M, Rodriguez JM, Yu H, Penner JE, Strahan S (2009) Sensitivity of aerosol optical thickness and aerosol direct radiative effect to relative humidity. Atmos Chem Phys 9:2375–2386

    Article  Google Scholar 

  • Bilal M, Nichol JE (2015) Evaluation of MODIS aerosol retrieval algorithms over the Beijing-Tianjin-Hebei region during low to very high pollution events. J Geophys Res Atmos 120(15):7941–7957

    Article  Google Scholar 

  • Che H, Wang Y, Sun J, Zhang X, Zhang X, Guo J (2013) Variation of aerosol optical properties over the Taklimakan Desert in China. Aerosol Air Qual Res 13:777–785

    Article  Google Scholar 

  • Che H, Xia X, Zhu J, Wang H, Wang Y, Sun J, Shi G (2015a) Aerosol optical properties under the condition of heavy haze over an urban site of Beijing, China. Environ Sci Pollut Res 22(2):1043–1053

    Article  Google Scholar 

  • Che H, Zhang XY, Xia X, Goloub P, Holben B, Zhao H, Wang Y, Zhang XC, Wang H, Blarel L (2015b) 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

    Article  Google Scholar 

  • Che H, Zhao H, Wu Y, Xia X, Zhu J, Wang H, Wang Y, Sun J, Yu J, Zhang X (2015c) Analyses of aerosol optical properties and direct radiative forcing over urban and industrial regions in northeast China. Meteorog Atmos Phys 127:345–354

    Article  Google Scholar 

  • Chen J, Xin J, An J, Wang Y, Liu Z, Chao N, Meng Z (2014) Observation of aerosol optical properties and particulate pollution at background station in the Pearl River Delta region. Atmos Res 143:216–227

    Article  Google Scholar 

  • Chen W, Tang H, Zhao H, Yan L (2016) Analysis of aerosol properties in Beijing based on ground-based sun photometer and air quality monitoring observations from 2005 to 2014. Remote Sens 8(2):110

    Article  Google Scholar 

  • Cheng Z, Wang S, Jiang J, Fu Q, Chen C, Xu B, Hao J (2013) Long-term trend of haze pollution and impact of particulate matter in the Yangtze River Delta, China. Environ Pollut 182:101–110

    Article  Google Scholar 

  • Cui Q, Pan D, Bai Y, He X, Chen J (2012) Assessment of suspended particulate matter concentration retrieved by Aqua-MODIS and SeaWiFS in the East China Sea, Proc. SPIE, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2012, (October 19, 2012), pp. 85320Y-85327

  • Deng X, Wu D, Yu J, Lau AKH, Li F, Tan H, Yuan Z, Ng WM, Deng T, Wu C, Zhou X (2013) Characterization of secondary aerosol and its extinction effects on visibility over the Pearl River Delta Region, China. J Air Waste Manag Assoc 63:1012–1021

    Article  Google Scholar 

  • Dickerson R, Kondragunta S, Stenchikov G, Civerolo K, Doddridge B, Holben B (1997) The impact of aerosols on solar ultraviolet radiation and photochemical smog. Science 278:827–830

    Article  Google Scholar 

  • Filonchyk M, Yan H, Yang S, Hurynovich V (2016) A study of PM2.5 and PM10 concentrations in the atmosphere of large cities in Gansu Province, China, in summer period. J Earth Syst Sci 125(6):1175–1187

    Article  Google Scholar 

  • Filonchyk M, Yan H, Yang S, Lu X (2018a) Detection of aerosol pollution sources during sandstorms in Northwestern China using remote sensed and model simulated data. Adv Space Res 61(4):1035–1046

    Article  Google Scholar 

  • Filonchyk M, Yan H, Shareef TME, Yang S (2018b) Aerosol contamination survey during dust storm process in Northwestern China using ground, satellite observations and atmospheric modeling data. Theor Appl Climatol:1–15. https://doi.org/10.1007/s00704-017-2362-8

  • Ge JM, Huang JP, Xu CP, Qi YL, Liu HY (2015) Characteristics of Taklamakan dust emission and distribution: a satellite and reanalysis field perspective. J Geophys Res Atmos 119(20):772–783

    Google Scholar 

  • Georgeson L, Maslin M, Poessinouw M, Howard S (2016) Adaptation responses to climate change differ between global megacities. Nat Clim Chang 6(6):584–588

    Article  Google Scholar 

  • Gerelmaa D, Liu GR, Kuo TH, Lin TH (2016) Investigation of permanent aerosol source regions over Asia using multi-year MODIS observations. J Mar Sci Tech 24(2):269–281

    Google Scholar 

  • Guan Q, Yang J, Zhao S, Pan B, Liu C, Zhang D, Wu T (2015) Climatological analysis of dust storms in the area surrounding the Tengger Desert during 1960–2007. Clim Dyn 45(3–4):903–913

    Article  Google Scholar 

  • He Q, Li C, Tang X, Li H, Geng F, Wu Y (2010) Validation of MODIS derived aerosol optical depth over the Yangtze River Delta in China. Remote Sens Environ 114(8):1649–1661

    Article  Google Scholar 

  • He Q, Li C, Geng F, Lei G, Li Y (2012a) Study on long-term aerosol distribution over the land of East China using MODIS data. Aerosol Air Qual Res 12:304–319

    Article  Google Scholar 

  • He Q, Li C, Geng F, Yang H, Li P, Li T, Liu D, Pei Z (2012b) Aerosol optical properties retrieved from sun photometer measurements over Shanghai, China. J Geophys Res 117:D16204. https://doi.org/10.1029/2011JD017220

  • He Q, Zhou G, Geng F, Gao W, Yu W (2016) Spatial distribution of aerosol hygroscopicity and its effect on PM2.5 retrieval in East China. Atmos Res 170:161–167

    Article  Google Scholar 

  • Holben BN, Eck TF, Slutsker I, Tanre D, Buis JP, Setzer A, Lavenu F (1998) AERONET—a federated instrument network and data archive for aerosol characterization. Remote Sen Environ 66(1):1–16

    Article  Google Scholar 

  • Hong Y, Zhou D, Qi Y, Liu D, Ma Y, Liu N, Gan L (2010) Distribution characteristics of aerosol mass concentrations in northeastern China. Arid Land Geogr 33:224–230 (in Chinese)

    Google Scholar 

  • Hsu NC, Tsay SC, King MD, Herman JR (2004) Aerosol properties over bright-reflecting source regions. IEEE Trans Geosci Remote Sen 42(3):557–569

    Article  Google Scholar 

  • Hsu NC, Tsay SC, King MD, Herman JR (2006) Deep blue retrievals of Asian aerosol properties during ACE-Asia. IEEE Trans Geosci Remote Sen 44(11):3180–3195

    Article  Google Scholar 

  • Hsu NC, 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 Atmos 118:9296–9315

    Article  Google Scholar 

  • Hu J, Wang Y, Ying Q, Zhang H (2014) Spatial and temporal variability of PM2.5 and PM10 over the North China Plain and the Yangtze River Delta, China. Atmos Environ 95:598–609

    Article  Google Scholar 

  • Huang L, Wang K, Yuan C-S, Wang G (2010) Study on the seasonal variation and source apportionment of PM10 in Harbin, China. Aerosol Air Qual Res 10:86–93

    Article  Google Scholar 

  • Huang J, Ji M, Xie Y, Wang S, He Y, Ran J (2016) Global semi-arid climate change over last 60 years. Clim Dyn 46:1131–1150

    Article  Google Scholar 

  • Huang Y, Yan Q, Zhang C (2018) Spatial–temporal distribution characteristics of PM 2.5 in China in 2016. J Geovis Spat Anal 2(2):12

    Article  Google Scholar 

  • Ichoku C, Chu DA, Mattoo S, Kaufman YJ, Remer LA, Tanré D, Holben BN, (2002) A spatio-temporal approach for global validation and analysis of MODIS aerosol products. Geophys Res Lett 29(12):1616. https://doi.org/10.1029/2001GL013206

  • Kang N, Kumar KR, Yin Y, Diao Y, Yu X (2015) Correlation analysis between AOD and cloud parameters to study their relationship over China using MODIS data (2003–2013): impact on cloud formation and climate change. Aerosol Air Qual Res 15:958–973

    Article  Google Scholar 

  • Kang N, Kumar KR, Hu K, Yu X, Yin Y (2016) Long-term (2002–2014) evolution and trend in collection 5.1 level-2 aerosol products derived from the MODIS and MISR sensors over the Chinese Yangtze River Delta. Atmos Res 181:29–43

    Article  Google Scholar 

  • Kaufman YJ, Tanré D, Remer LA, Vermote EF, Chu A, Holben BN (1997) Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer. J Geophys Res Atmos 102(27):51–17

    Google Scholar 

  • Kaufman YJ, Koren I, Remer LA, Rosenfeld D, Rudich Y (2005) The effect of smoke, dust, and pollution aerosol on shallow cloud development over the Atlantic Ocean. Proc Natl Acad Sci 102:11207–11212

    Article  Google Scholar 

  • Kim DH, Sohn BJ, Nakajima T, Takamura T, Takemura T, Choi BC, Yoon SC (2004) Aerosol optical properties over East Asia determined from ground-based sky radiation measurements. J Geophys Res Atmos 109(D2):D02209. https://doi.org/10.1029/2003JD003387

  • Lee KH, Kim YJ, Kim MJ (2006) Characteristics of aerosol observed during two severe haze events over Korea in June and October 2004. Atmos Environ 40:5146–5155

    Article  Google Scholar 

  • Lee HJ, Chatfield RB, Strawa AW (2016) Enhancing the applicability of satellite remote sensing for PM2.5 estimation using MODIS deep blue AOD and land use regression in California, United States. Environ Sci Technol 50(12):6546–6555

    Article  Google Scholar 

  • Leeuw GD, Sogacheva L, Rodriguez E, Kourtidis K, Georgoulias AK, Alexandri G (2018) 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(3):1573–1592

    Article  Google Scholar 

  • Levy RC, Remer LA, Mattoo S, 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(D13)

  • Levy RC, Remer LA, Kleidman RG, Mattoo S, Ichoku C, Kahn R, Eck TF (2010) Global evaluation of the Collection 5 MODIS dark-target aerosol products over land. Atmos Chem Phys 10(21):10399–10420

    Article  Google Scholar 

  • Levy RC, Mattoo S, Munchak LA, Remer LA, Sayer AM, Patadia F, Hsu NC (2013) The Collection 6 MODIS aerosol products over land and ocean. Atmos Meas Tech 6(11):2989–3034

    Article  Google Scholar 

  • Li Z, Niu F, Lee KH, Xin J, Hao WM, Nordren B, Wang Y, Wang P (2007) Validation and understanding of Moderate Resolution Imaging Spectroradiometer aerosol products (C5) using ground-based measurements from the handheld sun photometer network in China. J Geophys Res Atmos 112:D22S07. https://doi.org/10.1029/2007JD008479

  • Li B, Yuan H, Niu F, Tao S (2010) Spatial and temporal variations of aerosol optical depth in China during the period from 2003 to 2006. Int J Remote Sens 31:1801–1817

    Article  Google Scholar 

  • Li Z, Zhao S, Edwards R, Wang W, Zhou P (2011) Characteristics of individual aerosol particles over Ürümqi Glacier No. 1 in eastern Tianshan, central Asia, China. Atmos Res 99(1):57–66

    Article  Google Scholar 

  • Li X, Xia X, Wang S, Mao J, Liu Y (2012) Validation of MODIS and Deep Blue aerosol optical depth retrievals in an arid/semi-arid region of northwest China. Particuology 10(1):132–139

    Article  Google Scholar 

  • Luo Y, Daren L, Xiuji Z, Weiliang L, Qing H (2001) Characteristics of the spatial distribution and yearly variation of aerosol optical depth over China in last 30 years. J Geophys Res Atmos 106:14501–14513

    Article  Google Scholar 

  • Luo Y, Zheng X, Zhao T, Chen J (2013) A climatology of aerosol optical depth over China from recent 10 years of MODIS remote sensing data. Int J Climatol 34:863–870

    Article  Google Scholar 

  • Penner JE, Andreae MO, Annegarn H, Barrie L, Feichter J, Hegg D, Pitari G (2001) Aerosols, their direct and indirect effects. In: Climate change 2001: the scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 289–348

    Google Scholar 

  • Platnick S, King MD, Ackerman SA, Menzel WP, Baum BA, Riédi JC, Frey RA (2003) The MODIS cloud products: algorithms and examples from Terra. IEEE Trans Geosci Remote Sens 41:459–473

    Article  Google Scholar 

  • Platnick S, Meyer KG, King MD, Wind G, Amarasinghe N, Marchant B, Yang P (2017) The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua. IEEE Trans Geosci Remote Sens 55:502–525

    Article  Google Scholar 

  • Qi YL, Ge JM, Huang JP (2013) Spatial and temporal distribution of MODIS and MISR aerosol optical depth over northern China and comparison with AERONET. Chin Sci Bull 58(20):2497–2506

    Article  Google Scholar 

  • Qiu X, Duan L, Gao J, Wang S, Chai F, Hu J, Yun Y (2016) Chemical composition and source apportionment of PM10 and PM2.5 in different functional areas of Lanzhou, China. J Environ Sci 40:75–83

    Article  Google Scholar 

  • Remer LA, Kaufman YJ, Tanré D, Mattoo S, Chu DA, Martins JV (2005) The MODIS aerosol algorithm, products, and validation. J Atmos Sci 62(4):947–973

    Article  Google Scholar 

  • Sakerin SM, Andreev SY, Bedareva TV, Kabanov DM, Poddubnyi VA, Luzhetskaya AP (2012) Spatiotemporal variations in the atmospheric aerosol optical depth on the territory of Povolzhye, Urals, and Western Siberia. Opt Atmos Okeana 25(11):958–962

    Google Scholar 

  • Sayer AM, Munchak LA, Hsu NC, Levy RC, Bettenhausen C, Jeong MJ (2014) MODIS Collection 6 aerosol products: comparison between Aqua’s e-Deep Blue, Dark Target, and “merged” data sets, and usage recommendations. J Geophys Res Atmos 119(24):13,965–13,989

    Article  Google Scholar 

  • Sayer AM, Hsu NC, Bettenhausen C, Jeong MJ, Meister G (2015) Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: validation and Terra/Aqua consistency. Geophys Res Atmos 120(23):12157–12174

    Article  Google Scholar 

  • Seinfeld JH, Pandis SN (1998) Atmospheric chemistry and physics: from air pollution to climate change. John Wiley, New York

    Google Scholar 

  • Sellers WD (1969) A global climatic model based on the energy balance of the earth-atmosphere system. J Appl Meteorol 8(3):392–400

    Article  Google Scholar 

  • Shi Y, Zhang J, Reid JS, Hyer EJ, Eck TF, Holben BN, Kahn RA (2011) Where do we need additional in situ aerosol and sun photometer data: a critical examination of spatial biases between MODIS and MISR aerosol products. Atmos Meas Tech Discuss 4:4295–4323

    Article  Google Scholar 

  • Sogacheva L, Leeuw GD, Rodriguez E, Kolmonen P, Georgoulias AK, Alexandri G, Xue Y (2018) Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations–part 1: ATSR (1995–2011) and MODIS C6.1 (2000–2017). Atmos Chem Phys 18(15):11389–11407

    Article  Google Scholar 

  • Song W, Jia H, Huang J, Zhang Y (2014) A satellite-based geographically weighted regression model for regional PM2.5 estimation over the Pearl River Delta region in China. Remote Sens Environ 154(1–7):1–7

    Article  Google Scholar 

  • Statistics Press of China (2014) Population yearbook of China: 2014. Statistics Press of China, Beijing

    Google Scholar 

  • Thurston GD, Jiyoung A, Cromar KR, Shao Y, Reynolds HR, Michael J, Lim CC, Ryan S, Yikyung P, Hayes RB (2015) Ambient particulate matter air pollution exposure and mortality in the NIH-AARP diet and health cohort. Environ Health Perspect 124:484–490

    Article  Google Scholar 

  • Wang Y, Zhang W, Kong L, Wang J (2013) Analysis of applicability and characteristics of MODIS aerosol products in agricultural regions. Remot Sens Technol Appl 28(3):505–510 (in Chinese)

    Google Scholar 

  • Watts N, Adger WN, Agnolucci P, Blackstock J, Byass P, Cai W, Chaytor S, Colbourn T, Collins M, Cooper A, Cox PM, Depledge J, Drummond P, Ekins P, Galaz V, Grace D, Graham H, Grubb M, Haines A, Hamilton I, Hunter A, Jiang X, Li M, Kelman I, Liang L, Lott M, Lowe R, Luo Y, Mace G, Maslin M, Nilsson M, Oreszczyn T, Pye S, Quinn T, Svensdotter M, Venevsky S, Warner K, Xu B, Yang J, Yin Y, Yu C, Zhang Q, Gong P, Montgomery H, Costello A (2015) Health and climate change: policy responses to protect public health. Lancet 386(10006):1861–1914

    Article  Google Scholar 

  • Xia X, Chen H, Goloub P, Zhang W, Chatenet B, Wang P (2007) A compilation of aerosol optical properties and calculation of direct radiative forcing over an urban region in northern China. J Geophys Res Atmos 112(D12)

  • Xia X, Wang P, Wang Y, Li Z, Xin J, Liu J, Chen H (2008) Aerosol optical depth over the Tibetan Plateau and its relation to aerosols over the Taklimakan Desert. Geophys Res Lett 35(16)

  • Xia X, Chen H, Goloub P, Zong X, Zhang W, Wang P (2013) Climatological aspects of aerosol optical properties in North China Plain based on ground and satellite remote-sensing data. J Quant Spectrosc Radiat Transf 127:12–23

    Article  Google Scholar 

  • Xin J, Wang Y, Li Z, Wang P, Hao WM, Nordgren BL, Sun Y (2007) Aerosol optical depth (AOD) and Ångström exponent of aerosols observed by the Chinese Sun Hazemeter Network from August 2004 to September 2005. J Geophys Res Atmos 112:D05203. https://doi.org/10.1029/2006JD007075

  • Xin J, Zhang Q, Wang L, Gong C, Wang Y, Liu Z, Gao W (2014) The empirical relationship between the PM2.5 concentration and aerosol optical depth over the background of North China from 2009 to 2011. Atmos Res 138:179–188

    Article  Google Scholar 

  • Xu S, Liu W, Tao S (2006) Emission of polycyclic aromatic hydrocarbons in China. Environ Sci Technol 40(3):702–708

    Article  Google Scholar 

  • Xu X, Qiu J, Xia X, Sun L, Min M (2015) Characteristics of atmospheric aerosol optical depth variation in China during 1993–2012. Atmos Environ 119:82–94

    Article  Google Scholar 

  • Ye X, She B, Benya S (2018) Exploring regionalization in the network urban. J Geovis Spat Anal 2(1):4

    Article  Google Scholar 

  • You W, Zang Z, Pan X, Zhang L, Chen D (2015) Estimating PM2.5 in Xi’an, China using aerosol optical depth: a comparison between the MODIS and MISR retrieval models. Sci Total Environ 505:1156–1165

    Article  Google Scholar 

  • Zhang J, Reid JS (2010) A decadal regional and global trend analysis of the aerosol optical depth using a data-assimilation grade over-water MODIS and Level 2 MISR aerosol products. Atmos Chem Phys 10(22):10949–10963

    Article  Google Scholar 

  • Zhao H, Che H, Zhang X, Ma Y, Wang Y, Wang X, Liu C, Hou B, Che H (2013) Aerosol optical properties over urban and industrial region of northeast China by using ground-based sun-photometer measurement. Atmos Environ 75:270–278

    Article  Google Scholar 

  • Zong X, Xia X, Che H (2015) Validation of aerosol optical depth and climatology of aerosol vertical distribution in the Taklimakan Desert. Atmos Pollut Res 6(2):239–244

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to express our gratitude to the Atmosphere Archive and Distribution System (LAADS) and NASA’s Giovanni web site for providing the MODIS AOD products.

Funding

The work was financially supported by the China Postdoctoral Science Foundation Funded Project (2018M633605), the Postdoctoral Fund of Lanzhou Jiaotong University (2018BH03001), and the National Key R&D Program of China (2017YFB0504203 and 2017YFB0504201).

Author information

Authors and Affiliations

  1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou, 730070, China

    Mikalai Filonchyk & Haowen Yan

  2. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou, 730070, China

    Mikalai Filonchyk & Haowen Yan

  3. School of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou, 730070, China

    Zhongrong Zhang

Authors
  1. Mikalai Filonchyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haowen Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhongrong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Haowen Yan.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Filonchyk, M., Yan, H. & Zhang, Z. Analysis of spatial and temporal variability of aerosol optical depth over China using MODIS combined Dark Target and Deep Blue product. Theor Appl Climatol 137, 2271–2288 (2019). https://doi.org/10.1007/s00704-018-2737-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-018-2737-5

Search

Navigation