Skip to main content
SpringerLink
Log in

An Analysis of Atmospheric Aerosol Characteristics Using Remote Sensing Data in the Indian Region

  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

The aerosols present in the atmosphere are considered to be an essential element that directly affects the cloud properties, radiation budget of Earth, human health, and quality of air. Therefore, it is mandatory to investigate aerosol concentration and properties both in the local and global regions while studying global climate change. In this paper, an analysis of aerosol properties such as single scattering albedo (SSA), aerosol optical depth (AOD) at 500 nm, angstrom exponent (AE) (440–870 nm), and aerosol volume size distribution (VSD), which are retrieved from relatively long term AErosol RObotic NETwork (AERONET) at Karunya University, Kanpur, Gandhi College, Pune, and Jaipur is made for the years from 2010 to 2019. The comparisons of the parameters based on wavelength and seasons for the five places considered are provided. The result analysis shows that the indo gangetic plain (IGP) region places such as Gandhi College and Kanpur experience larger AOD values during the 10-year period considered as compared to other sites. The seasonal analysis of AE, SSA, and VSD reveals that the dominance of fine particles is available mainly in post-monsoon and winter season except Jaipur, whereas coarse particles always occurred in monsoon and pre-monsoon seasons at all the places except Karunya University. The comparison between the AODs retrieved from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite and AERONET is also provided. The comparison shows that 50% and 43.48% of MODIS-derived AOD match well with the AERONET-derived AOD within the expected error values for Gandhi College and Kanpur, respectively.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18

Similar content being viewed by others

Data Availability

Not applicable.

References

  • Abdillah, S. F., & Wang, Y. F. (2022). Ambient ultrafine particle (PM0.1): Sources, characteristics, measurements and exposure implications on human health. Environmental Research, 218, 115061.

    Article  ADS  PubMed  Google Scholar 

  • Anitha, M., & Kumar, L.S. (2020). Ground based remote sensing of aerosols using AERONET in Indian Region. IEEE, pp. 72–77.

  • Anitha, M., & Kumar, L. S. (2023a). Development of an IoT-enabled air pollution monitoring and air purifier system. MAPAN, 38, 669–688.

    Article  Google Scholar 

  • Anitha, M., & Kumar, L. S. (2023b). Tracking of NO2 and SO2 trace gases emission from Thermal Power Plants in Tamil Nadu using Sentinel 5P Tropomi Satellite with observations from CPCB CAAQM station. In 2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT), IEEE, pp. 1–6.

  • Annapurna, S. M., Anitha, M., & Kumar, L. S. (2024). Composition and source based aerosol classification using machine learning algorithms. Advances in Space Research, 73(1), 474–497.

    Article  ADS  Google Scholar 

  • Burton, S. P., Ferrare, R. A., Hostetler, C. A., Hair, J. W., Rogers, R. R., Obland, M. D., Butler, C. F., Cook, A. L., Harper, D. B., & Froyd, K. D. (2012). Aerosol classification using airborne High Spectral Resolution Lidar measurements—methodology and examples. Atmospheric Measurement Techniques, 5, 73–98.

    Article  ADS  Google Scholar 

  • Buseck, P. R., & Pósfai, M. (1999). Airborne minerals and related aerosol particles: Effects on climate and the environment. Proceedings of the National Academy of Sciences, 96(7), 3372–3379.

    Article  ADS  CAS  Google Scholar 

  • Chen, H., Cheng, T., Xingfa, Gu., Li, Z., & Yu, Wu. (2016). Characteristics of aerosols over Beijing and Kanpur derived from the AERONET dataset. Atmospheric Pollution Research, 7, 162–169.

    Article  Google Scholar 

  • Chen, G., Guang, J., Xue, Y., Li, Y., Che, Y., & Gong, S. (2018). A physically based PM2.5 estimation method using AERONET data in Beijing area. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(6), 1957–1965.

    Article  ADS  Google Scholar 

  • Choudhry, P., Misra, A., & Tripathi, S. N. (2012). Study of MODIS derived AOD at three different locations in the Indo Gangetic Plain: Kanpur, Gandhi College, and Nainital. Annales Geophysicae, 30, 1479–1493.

    Article  ADS  Google Scholar 

  • Devara, P. C. S., Sumit, K., Vijayakumar, K., & Pandithurai, G. (2014). Sun-sky radiometer synthesis of interplay between aerosols and monsoon activity over Pune, India. Pure and Applied Geophysics, 171, 2501–2517.

    Article  ADS  Google Scholar 

  • Dey, S., Tripathi, S. N., Sinhg, R. P., & Holben, B. N. (2005). Seasonal variability of the aerosol parameters over Kanpur, an urban site in Indo-Gangetic basin. Advances in Space Research, 36, 778–782.

    Article  ADS  Google Scholar 

  • Duc, H. N., Bang, H. Q., Quan, N. H., & Quang, N. X. (2021). Impact of biomass burnings in Southeast Asia on air quality and pollutant transport during the end of the 2019 dry season. Environmental Monitoring and Assessment, 193, 565.

    Article  CAS  PubMed  Google Scholar 

  • Earth System Research Laboratories. (2019). SURFRAD aerosol opticel depth. Retrieved march 10, 2020. https://www.esrl.noaa.gov/gmd/grad/surfrad/aod/.

  • Environmental Protection Agency. (2021). Particle pollution exposure. Retrieved July 21, 2021. https://www.epa.gov/pmcourse/particle-pollution-exposure.

  • Fatima, H., George, J. P., Rajagopal, E. N., & Basu, S. (2017). Seasonal variation of dust forecast over the Indian Region. Pure and Applied Geophysics, 174, 4225–4240.

    Article  ADS  Google Scholar 

  • Flesch, M. M., Christiansen, A. E., Burns, A. M., Ghate, V. P., & Carlton, A. G. (2022). Ambient aerosol is physically larger on cloudy days in Bondville Illinois. ACS Earth and Space Chemistry, 6(12), 2910–2918.

    Article  ADS  CAS  PubMed  Google Scholar 

  • Fortunato dos Santos Oliveira, D. C., Montilla-Rosero, E., da Silva Lopes, F. J., Morais, F. G., Landulfo, E., & Hoelzemann, J. J. (2021). Aerosol properties in the atmosphere of Natal/Brazil measured by an AERONET Sun-photometer. Environmental Science and Pollution Research, 28(8), 9806–9823. https://doi.org/10.1007/s11356-020-11373-z.

    Article  PubMed  Google Scholar 

  • Fuertes, D., Toledano, C., Gonzalez, R., Berjon, A., Torres, B., Cachorro, V.E., & de Frutos, A.M. (2018). CÆLIS: A system for aerosol measurement network. IEEE IGARSS.

  • Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., & Wargan, K. (2017). The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Journal of Climate, 30(14), 5419–5454.

    Article  ADS  Google Scholar 

  • Global Climate Change. (2009). Just 5 questions: Aerosols. Retrieved June 27, 2023. https://climate.nasa.gov/news/215/just-5-questions-aerosols/.

  • Gong, C., Xin, J., Wang, S. H., Wang, Y., Wang, P., Wang, L., & Li, P. (2014). The aerosol direct radiative forcing over the Beijing metropolitan area from 2004 to 2011. Journal of Aerosol Science, 69, 62–70.

    Article  ADS  CAS  Google Scholar 

  • Hamill, P., Giordano, M., Ward, C., Giles, D., & Holben, B. (2016). An AERONET-based aerosol classification using the Mahalanobis distance. Atmospheric Environment, 140, 213–233.

    Article  ADS  CAS  Google Scholar 

  • Harrison, R.M., Hester, R.E., & Querol, X. eds. (2016). Airborne particulate matter: sources, atmospheric processes and health. In Royal Society of Chemistry.

  • He, L., Wang, L., Lin, A., Zhang, M., Bilal, M., & Wei, J. (2018). Performance of the NPP-VIIRS and Aqua-MODIS aerosol optical depth products over the Yangtze River Basin. Remote Sensing, 10, 117.

    Article  ADS  Google Scholar 

  • Hyvarinen, A. P., Lihavainen, H., Komppula, M., Sharma, V. P., Kerminen, V. M., Panwar, T. S., & Viisanen, Y. (2009). Continuous measurements of optical properties of atmospheric aerosols in Mukteshwar, northern India. Journal of Geophysical Research, 114, D08207.

    Article  ADS  Google Scholar 

  • Kaskaoutis, D. G., Kambezidis, H. D., Hatzianastassiou, N., Kosmopoulos, P. G., & Badarinath, K. V. S. (2007). Aerosol climatology: On the discrimination of aerosol types over four AERONET sites. Atmospheric Chemistry and Physics Discussions, 7, 6357–6411.

    ADS  Google Scholar 

  • Kim, M., Kim, S. H., Kim, W. V., Lee, Y. G., Kim, J., & Kafatos, M. C. (2021). Assessment of Aerosol optical depth under background and polluted conditions using AERONET and VIIRS datasets. Atmospheric Environment, 245, 117994.

    Article  CAS  Google Scholar 

  • Kirešová, S., & Guzan, M. (2022). Measurement of particulate matter: Principles and options of measurement at present. Acta Electrotechnica Et Informatica, 22(2), 8–18.

    Article  Google Scholar 

  • Kirešová, S., Guzan, M., & Sobota, B. (2023). Using low-cost sensors for measuring and monitoring particulate matter with a focus on fine and ultrafine particles. Atmosphere, 14(2), 324.

    Article  ADS  Google Scholar 

  • Kulkarni, P., Baron, P. A., & Willeke, K. (2011). Aerosol measurement (3rd ed.). Wiley.

    Book  Google Scholar 

  • Kumar, S., Kumar, S., Singh, A. K., & Singh, R. P. (2012). Seasonal variability of atmospheric aerosol over the North Indian region during 2005–2009. Advances in Space Research, 50, 1220–1230.

    Article  ADS  Google Scholar 

  • Laakso, L., Kopenen, I. K., Monkkonen, P., Kulmala, M., Kerminen, V.-M., Wehner, B., Wiedensohler, A., Zhijun, Wu., & Min, Hu. (2006). Aerosol Particles in the developing world: A comparison between New Delhi in India and Beijing in China. Water, Air, and Soil Pollution, 173, 5–20.

    Article  ADS  CAS  Google Scholar 

  • Leena, P. P., Sravanthi, N., Anil Kumar, V., Pandithurai, G., & Panicker, A. S. (2021). Aerosol-cloud-rainfall properties inferred from satellite observations over different regions of the Indian subcontinent: Variability, trends and relationships during the summer monsoon. Pure and Applied Geophysics, 178, 4619–4631.

    Article  ADS  Google Scholar 

  • Li, K. (2021). Climate change and aerosol sciences. Journal of Earth Sciences and Geotechnical Engineering, 11(1), 1–13.

    Article  Google Scholar 

  • Liu, Q., Xu, C., Ji, G., Liu, H., Shao, W., Zhang, C., Gu, A., & Zhao, P. (2017). Effect of exposure to ambient PM2.5 pollution on the risk of respiratory tract diseases: A meta-analysis of cohort studies. Journal of Biomedical Research, 31(2), 130–142.

    Article  PubMed  PubMed Central  Google Scholar 

  • Mahesh, B., Rama, B. V., Spandana, B., Sarma, M. S. S. R. K. N., Niranjan, K., & Sreekanth, V. (2019). Evaluation of MERRAero PM2.5over Indian cities. Advances in Space Research, 64, 328–334.

    Article  ADS  CAS  Google Scholar 

  • Masri, S., Kang, C. M., & Koutrakis, P. (2015). Composition and sources of fine and coarse particles collected during 2002–2010 in Boston, MA. Journal of the Air & Waste Management Association, 65(3), 287–297.

    Article  CAS  Google Scholar 

  • Mohan, A. S., Manisekaran, A., & Kumar, L. S. (2021). Aerosol classification using machine learning algorithms. Indian Journal of Radio & Space Physics, 50, 217–223.

    Google Scholar 

  • Monteiro, L. A., Sentelhas, P. C., & Pedra, G. U. (2018). Assessment of NASA/POWER satellite-based weather system for Brazilian conditions and its impact on sugarcane yield simulation. International Journal of Climatology, 38(3), 1571–1581.

    Article  ADS  Google Scholar 

  • More, S., Pradeep Kumar, P., Gupta, P., Devara, P. C. S., & Aher, G. R. (2013). Comparison of aerosol products retrieved from AERONET, MICROTOPS, and MODIS over a Tropical Urban City, Pune, India. Aerosol and Air Quality Research, 13, 107–121.

    Article  Google Scholar 

  • NASA. (2023). Goddard Earth Sciences Division Projects. Retrieved November 1, 2023. https://earth.gsfc.nasa.gov/climate/data/deep-blue/science.

  • Ogunjobi, K. O., & Kim, Y. J. (2008). Aerosol characteristics and surface radiative forcing components during a dust outbreak in Gwangju, Republic of Korea. Environmental Monitoring and Assessment, 137, 111–126.

    Article  CAS  PubMed  Google Scholar 

  • Ogunjobi, K. O., He, Z., & Simmer, C. (2008). Spectral aerosol optical properties from AERONET Sun-photometric measurements over West Africa. Atmospheric Research, 88, 89–107.

    Article  ADS  CAS  Google Scholar 

  • Ojha, N., Sharma, A., Kumar, M., Girach, I., Ansari, T. U., Sharma, S. K., Singh, N., Pozzer, A., & Gunthe, S. S. (2020). On the widespread enhancement in fine particulate matter across the Indo-Gangetic Plain towards winter. Nature Scientific Reports, 10, 5862.

    Article  ADS  CAS  Google Scholar 

  • Olcese, L. E., Palancar, G. G., & Toselli, B. M. (2014). Aerosol optical properties in central Argentina. Journal of Aerosol Science, 68, 25–37.

    Article  ADS  CAS  Google Scholar 

  • Pandithurai, G., Dipu, S., Dani, K. K., Tiwari, S., Bisht, D. S., Devara, P. C. S., & Pinker, R. T. (2008). Aerosol radiative forcing during dust event over New Delhi, India. Journal of Geophysical Research. https://doi.org/10.1029/2008JD009804

    Article  Google Scholar 

  • Raghavendra Kumar, K., Joseph Adesina, A., & Sivakumar, V. (2013). Aerosol radiative forcing from spectral solar attenuation measurements due to aerosol loading using AERONET over Pretoria in South Africa. International Conference on Microelectronics, Communication and Renewable Energy IEEE.

  • Raman, R. S., Ramachandran, S., & Kedia, S. (2011). A methodology to estimate source-specific aerosol radiative forcing. Journal of Aerosol Science, 42, 305–320.

    Article  ADS  CAS  Google Scholar 

  • Raptis, I.-P., Kazadzis, S., Amiridis, V., Gkikas, A., Gerasopoulos, E., & Mihalopoulos, N. (2020). A decade of aerosol optical properties measurements over Athens, Greece. Atmosphere, 11, 154.

    Article  ADS  CAS  Google Scholar 

  • Sabetghadam, S., Alizadeh, O., Khoshsima, M., & Pierleoni, A. (2021). Aerosol Properties, trends and classification of key types over the Middle East from satellite-derived atmospheric optical data. Atmospheric Environment, 246, 118100.

    Article  CAS  Google Scholar 

  • Salinas, S. V., Chew, B. N., & Liew, S. C. (2009). Retrievals of aerosol optical depth and Ångström exponent from ground-based Sun-photometer data of Singapore. Applied Optics, 48(8), 1473–1484.

    Article  ADS  PubMed  Google Scholar 

  • Schraufnagel, D. E. (2020). The health effects of ultrafine particles. Experimental & Molecular Medicine, 52(3), 311–317.

    Article  CAS  Google Scholar 

  • Shaik, D. S., Kant, Y., Mitra, D., & Suresh Babu, S. (2017). Assessment of aerosol characteristics and radiative forcing over northwest Himalayan Region. IEEE Journal of Selected Topics in Applied Earth, 10(12), 5314–5321.

    Article  ADS  Google Scholar 

  • Sharma, V., Ghosh, S., Bilal, M., Dey, S., & Singh, S. (2021). Performance of MODIS C6.1 dark target and deep blue aerosol products in Delhi National Capital Region, India: Application for aerosol studies. Atmospheric Pollution Research., 12, 65–74.

    Article  Google Scholar 

  • Shi, S., Cheng, T., Xingfa, G., Guo, H., Chen, H., Wang, Y., & Yu, W. (2018). Multisensor data synergy of terra-MODIS, aqua-MODIS, and suomi NPP-VIIRS for the retrieval of aerosol optical depth and land surface reflectance properties. IEEE Transactions on Geoscience and Remote Sensing, 56(11), 6306–6323.

    Article  ADS  Google Scholar 

  • Song, G., Zhicheng, Z., Zhiwei, T., & Xiaotian, B. (2018). Variation of aerosol particle and its impact on pollution flashover events over Eastern China. International Conference on Power System Technology, IEEE.

  • Sung-Nam, Oh., Sohn, B.-J., & Lee, S.-S. (2004). Aerosol optical and radiative properties observed at Anmyeon and Jeju, Korea in the spring of 2000 and 2001. Environmental Monitoring and Assessment, 92, 95–115.

    Article  Google Scholar 

  • Suresh Babu, S., Manoj, M. R., Krishna Moorthy, K., Gogoi, M. M., Nair, V. S., Kompalli, S. K., Satheesh, S. K., Niranjan, K., Ramagopal, K., Bhuyan, P. K., & Singh, D. (2013). Trends in aerosol optical depth over Indian region: Potential causes and impact indicators. Journal of Geophysical Research: Atmospheres, 118, 11794–11806.

    ADS  Google Scholar 

  • Takemura, T., Nakajima, T., Dubovik, O., Holben, B. N., & Kinne, S. (2002). Single scattering albedo and radiative forcing of various aerosol species with a global three-dimensional model. Journal of Climate, 15(4), 333.

    Article  ADS  Google Scholar 

  • Tan, F., Lim, H. S., Abdullah, K., & Holben, B. (2016). Estimation of aerosol optical depth at different wavelengths by multiple regression method. Environmental Science and Pollution Research, 23, 2735–2748.

    Article  PubMed  Google Scholar 

  • Tan, F., Lim, H. S., Abdullah, K., Yoon, T. L., & Holben, B. (2015). AERONET data-based determination of aerosol types. Atmospheric Pollution Research, 6, 682–695.

    Article  CAS  Google Scholar 

  • Tariq, S., Ul-Haq, Z., & Ali, M. (2015). Analysis of optical and physical properties of aerosols during crop residue burning event of October 2010 over Lahore, Pakistan. Atmospheric Pollution Research, 6, 969–978.

    Article  Google Scholar 

  • Tariq, S., Ul-Haq, Z., Mahmood, K., & Rana, A. D. (2018). Spatio-temporal distributions and trends of aerosol parameters over Pakistan using remote sensing. Applied Ecology & Environmental Research, 16(3), 261.

    Article  Google Scholar 

  • Thangavel, P., Park, D., & Lee, Y. C. (2022). Recent insights into particulate matter (PM2.5)-mediated toxicity in humans: An overview. International Journal of Environmental Research and Public Health, 19(12), 1–22.

    Article  Google Scholar 

  • Tiwari, S., Srivastava, A. K., Singh, A. K., & Singh, S. (2015). Identification of aerosol types over Indo-Gangetic Basin: Implications to optical properties and associated radiative forcing. Environmental Science and Pollution Research, 22, 12246–12260.

    Article  CAS  PubMed  Google Scholar 

  • Varpe, S. R., Kolhe, A.R., Kutal, G.C., Pawar, G.V., Payra, S., Budhavant, K.B., Aher, G.R., & Devara, P.C.S. (2018). Heterogeneity in aerosol characteristics at the semi-arid and island AERONETobserving sites in India and Maldives. International Journal of Remote Sensing, ISSN: 0143–1161 (Print) 1366–5901(Online).

  • Verma, S., Prakash, D., Ricaud, P., Payra, S., Attié, J.-L., & Soni, M. (2015). A new classification of aerosol sources and types as measured over Jaipur, India. Aerosol and Air Quality Research, 15, 985–993.

    Article  Google Scholar 

  • World Health Organization. (2016). Air quality database: Update 2016. Retrieved December 5, 2019. https://www.who.int/data/gho/data/themes/air-pollution/who-air-quality-database/2016.

  • Xiaojing, S., Zhongfeng, Q., & Muhammad, B. (2018). Validation of modis aerosol optical depth over south China Sea. IEEE Igarss, pp. 9130–9133.

  • Zaman, S. U., Riad Sarkar Pavel, Md., Joy, K. S., Jeba, F., Safiqul Islam, Md., Paul, S., Aynul Bari, Md., & Salam, A. (2021). Spatial and temporal variation of aerosol optical depths over six major cities in Bangladesh. Atmospheric Research, 262, 105803.

    Article  CAS  Google Scholar 

  • Zhang, B. (2020). The effect of aerosols to climate change and society. Journal of Geoscience and Environment Protection, 8(08), 55–78.

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the financial support provided by the National Institute of Technology Puducherry, India, for carrying out research in this area. The entire data used in this analysis was downloaded from AErosol RObotic NETwork.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Department of ECE, NIT Puducherry, Karaikal, India

    M. Anitha & Lakshmi Sutha Kumar

Authors
  1. M. Anitha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lakshmi Sutha Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study's conception and design. Material preparation, data collection, analysis, and the first draft of the manuscript were performed by MA. All authors commented on previous versions of the manuscript. GLS read and approved the final manuscript.

Corresponding author

Correspondence to M. Anitha.

Ethics declarations

Conflict of Interest

The authors declare no competing interests.

Ethics Approval

Not applicable.

Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Anitha, M., Kumar, L.S. An Analysis of Atmospheric Aerosol Characteristics Using Remote Sensing Data in the Indian Region. Pure Appl. Geophys. 181, 625–654 (2024). https://doi.org/10.1007/s00024-023-03415-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-023-03415-7

Keywords

Search

Navigation