Articles | Volume 23, issue 14
https://doi.org/10.5194/acp-23-8059-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-8059-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Jul 2023
Research article |
| 19 Jul 2023
| 19 Jul 2023
Satellite (GOSAT-2 CAI-2) retrieval and surface (ARFINET) observations of aerosol black carbon over India
Mukunda M. Gogoi
CORRESPONDING AUTHOR
Space Physics Laboratory, Vikram Sarabhai Space Centre, Indian Space Research Organisation,
Thiruvananthapuram 695-022, India
S. Suresh Babu
Space Physics Laboratory, Vikram Sarabhai Space Centre, Indian Space Research Organisation,
Thiruvananthapuram 695-022, India
Ryoichi Imasu
CORRESPONDING AUTHOR
Atmosphere and Ocean Research Institute, The University of Tokyo,
Chiba 277-8568, Japan
Makiko Hashimoto
Earth Observation Research Center,
Japan Aerospace Exploration Agency, Ibaraki 305-8505, Japan
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This study presents fused aerosol optical depth (AOD) from a combination of single-view and multi-angle space-borne sensors with ground-based observations across India using Universal Kriging (UK) and a novel hybrid Residual Kriging–Machine Learning (RK-ML) approach. Both methods improve aerosol representation compared to individual datasets. UK-based fused maps highlight the need for better ground coverage, addressed by the RK-ML approach under data-sparse conditions.
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India poses a significant methane emission burden, but limited observations challenge accurate national estimations. This study combines satellite retrievals, ground measurements, and models to improve India’s 2018–2019 methane budget. Derived emissions are higher than national reports but lower than global inventories. The findings highlight the potential of satellite instruments to report emissions accurately. Expanded methane monitoring is vital for meeting climate change mitigation targets.
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Characteristics of particle number size distributions and new particle formation in six locations in India were analyzed. New particle formation occurred frequently during the pre-monsoon (spring) season and it significantly modulates the shape of the particle number size distributions. The contribution of newly formed particles to cloud condensation nuclei concentrations was ~3 times higher in urban locations than in mountain background locations.
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Cited articles
Babu, S. S. and Moorthy, K. K.: Aerosol black carbon over a tropical coastal
station in India, Geophys. Res. Lett., 29, 13-11–13-14,
https://doi.org/10.1029/2002GL015662, 2002.
Babu, S. S., Manoj, M. R., Moorthy, K. K., Gogoi, M. M., Nair, V. S.,
Kompalli, S. K., Satheesh, S. K., Niranjan, K., Ramagopal, K., Bhuyan, P.
K., and Singh, D.: Trends in aerosol optical depth over Indian region:
Potential causes and impact indicators, J. Geophys. Res.-Atmos., 118, 11794–711806, https://doi.org/10.1002/2013JD020507,
2013.
Babu, S. Suresh, Nair, V. S., Gogoi, M. M., and Moorthy, K. K.: Seasonal
variation of vertical distribution of aerosol single scattering albedo over
Indian sub-continent: RAWEX aircraft observations, Atmos. Environ.,
125, 312–323, https://doi.org/10.1016/j.atmosenv.2015.09.041, 2016.
Bao, F., Cheng, T., Li, Y., Gu, X., Guo, H., Wu, Y., Wang, Y., and Gao, J.:
Retrieval of black carbon aerosol surface concentration using satellite
remote sensing observations, Remote Sens. Environ., 226, 93–108,
https://doi.org/10.1016/j.rse.2019.03.036, 2019.
Bao, F., Li, Y., Cheng, T., Gao, J., and Yuan, S.: Estimating the Columnar
Concentrations of Black Carbon Aerosols in China Using MODIS Products.
Environ. Sci. Technol., 54, 11025–11036,
https://doi.org/10.1021/acs.est.0c00816, 2020.
Barkley, A. E., Prospero, J. M., Mahowald, N., Hamilton, D. S., Popendorf,
K. J., Oehlert, A. M., Pourmand, A., Gatineau, A., Panechou-Pulcherie, K.,
Blackwelder, P., and Gaston, C. J.: African biomass burning is a substantial
source of phosphorus deposition to the Amazon, Tropical Atlantic Ocean, and
Southern Ocean, P. Natl. Acad. Sci. USA, 116,
16216–16221, https://doi.org/10.1073/pnas.1906091116, 2019.
Beegum, S. N., Moorthy, K. K., Babu, S. S., Satheesh, S. K., Vinoj, V.,
Badarinath, K. V. S., Safai, P. D., Devara, P. C. S., Sacchidanand, S.,
Vinod, Dumka, U. C., and Pant, P.: Spatial distribution of aerosol black
carbon over India during pre-monsoon season, Atmos. Environ., 43,
1071–1078, https://doi.org/10.1016/j.atmosenv.2008.11.042, 2009.
Bond, T. C., Streets, D. G., Yarber, K. F., Nelson, S. M., Woo, J.-H., and
Klimont, Z.: A technology-based global inventory of black and organic carbon
emissions from combustion, J. Geophys. Res.-Atmos.,
109, D14203, https://doi.org/10.1029/2003JD003697, 2004.
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T.,
DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne,
S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M.,
Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K.,
Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U.,
Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C.
S.: Bounding the role of black carbon in the climate system: A scientific
assessment, J. Geophys. Res.-Atmos., 118, 5380–5552,
https://doi.org/10.1002/jgrd.50171, 2013.
Brooks, J., Allan, J. D., Williams, P. I., Liu, D., Fox, C., Haywood, J., Langridge, J. M., Highwood, E. J., Kompalli, S. K., O'Sullivan, D., Babu, S. S., Satheesh, S. K., Turner, A. G., and Coe, H.: Vertical and horizontal distribution of submicron aerosol chemical composition and physical characteristics across northern India during pre-monsoon and monsoon seasons, Atmos. Chem. Phys., 19, 5615–5634, https://doi.org/10.5194/acp-19-5615-2019, 2019.
Ceolato, R., Bedoya-Velásquez, A. E., Fossard, F., Mouysset, V., Paulien, L., Lefebvre, S., Mazzoleni, C., Sorensen, C., Berg, M. J., and Yon, J.: Black carbon
aerosol number and mass concentration measurements by picosecond short-range
elastic backscatter lidar, Sci. Rep., 12, 8443,
https://doi.org/10.1038/s41598-022-11954-7, 2022.
Cheremisin, A. A., Marichev, V. N., Bochkovskii, D. A., Novikov, P. V., and
Romanchenko, I. I.: Stratospheric Aerosol of Siberian Forest Fires According
to Lidar Observations in Tomsk in August 2019, Atmospheric and Oceanic
Optics, 35, 57–64, https://doi.org/10.1134/S1024856022010043, 2022.
Choi, Y. and Ghim, Y. S.: Estimation of columnar concentrations of absorbing
and scattering fine mode aerosol components using AERONET data, J.
Geophys. Res.-Atmos., 121, 13628–13640,
https://doi.org/10.1002/2016JD025080, 2016.
d'Almeida, G. A., Koepke, P., and Shettle, E. P.: Atmospheric aerosols.
Global climatology and radiative characteristics. A. Deepak Publishing, ISBN 0937194220,
1991.
Diner, D. J., Beckert, J. C., Reilly, T. H., Bruegge, C. J., Conel, J. E.,
Kahn, R., Martonchik, J. V., Ackerman, T. P., Davies, R., Gerstl, S. A. W.,
Gordon, H., Muller, J. P., Myneni, R. B., Sellers, P., Pinty, B., and
Verstraete, M.: Multiangle Imaging SptectrRadiometer (MISR) description and
experiment overview, IEEE T. Geosci. Remote,
36, 1072–1087, https://doi.org/10.1109/36.700992, 1998.
Dixon, R. K. and Krankina, O. N.: Forest fires in Russia: carbon dioxide
emissions to the atmosphere, Can. J. Forest Res., 23,
700–705, 1993.
Drinovec, L., Močnik, G., Zotter, P., Prévôt, A. S. H., Ruckstuhl, C., Coz, E., Rupakheti, M., Sciare, J., Müller, T., Wiedensohler, A., and Hansen, A. D. A.: The ”dual-spot” Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation, Atmos. Meas. Tech., 8, 1965–1979, https://doi.org/10.5194/amt-8-1965-2015, 2015.
Dubovik, O., Herman, M., Holdak, A., Lapyonok, T., Tanré, D., Deuzé, J. L., Ducos, F., Sinyuk, A., and Lopatin, A.: Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations, Atmos. Meas. Tech., 4, 975–1018, https://doi.org/10.5194/amt-4-975-2011, 2011.
Dubovik O., Fuertes D., Litvinov P., Lopatin, A., Lapyonok, T., Doubovik, I., Xu, F., Ducos, F., Chen, C., Torres, B., Derimian, Y., Li, L., Herreras-Giralda, M., Herrera, M., Karol, Y., Matar, C., Schuster, G. L., Espinosa, R., Puthukkudy, A., Li, Z., Fischer, J., Preusker, R., Cuesta, J., Kreuter, A., Cede, A., Aspetsberger, M., Marth, D., Bindreiter, L., Hangler, A., Lanzinger, V., Holter, C. and Federspiel, C.: A Comprehensive Description of Multi-Term LSM for Applying Multiple a Priori Constraints in Problems of Atmospheric Remote Sensing: GRASP Algorithm, Concept, and Applications, Front. Remote Sens., 2, 706851, https://doi.org/10.3389/frsen.2021.706851, 2021.
Falah, S., Kizel, F., Banerjee, T., and Broday, D. M.: Accounting for the
aerosol type and additional satellite-borne aerosol products improves the
prediction of PM2.5 concentrations, Environ. Pollut., 320, 121119,
https://doi.org/10.1016/j.envpol.2023.121119, 2023.
Fukuda, S., Nakajima, T., Takenaka, H., Higurashi, A., Kikuchi, N.,
Nakajima, T. Y., and Ishida, H.: New approaches to removing cloud shadows
and evaluating the 380 nm surface reflectance for improved aerosol optical
thickness retrievals from the GOSAT/TANSO-Cloud and Aerosol Imager, J.
Geophys. Res.-Atmos., 118, 13520–513531,
https://doi.org/10.1002/2013JD020090, 2013.
Gautam, R., Hsu, N. C., Lau, K.-M., Tsay, S.-C., and Kafatos, M.: Enhanced
pre-monsoon warming over the Himalayan-Gangetic region from 1979 to 2007,
Geophys. Res. Lett., 36, L07704, https://doi.org/10.1029/2009GL037641,
2009.
Gautam, R., Hsu, N. C., and Lau, K.-M.: Premonsoon aerosol characterization
and radiative effects over the Indo-Gangetic Plains: Implications for
regional climate warming, J. Geophys. Res.-Atmos., 115, D17208,
https://doi.org/10.1029/2010JD013819, 2010.
Giglio, L., Schroeder, W., Hall, J. V., and Justice, C. O.: MODIS Collection
6 Active Fire Product User's Guide, Revision C, NASA, https://modis-fire.umd.edu/files/MODIS_C6_Fire_User_Guide_C.pdf (last access: 25 June 2023), 2020.
Gogoi, M. M., Babu, S. S., Moorthy, K. K., Manoj, M. R., and Chaubey, J. P.: Absorption
characteristics of aerosols over the northwestern region of India: Distinct
seasonal signatures of biomass burning aerosols and mineral dust,
Atmos. Environ., 73, 92–102,
https://doi.org/10.1016/j.atmosenv.2013.03.009, 2013.
Gogoi, M. M., Moorthy, K. K., Sobhan Kumar, K., Jai Prakash, C., Babu, S.
S., Manoj, M. R., Vijayakumar, S. N., and Tushar, P. P.: Physical and
optical properties of aerosols in a free tropospheric environment: Results
from long-term observations over western trans-Himalayas, Atmos.
Environ., 84, 262–274, https://doi.org/10.1016/j.atmosenv.2013.11.029,
2014.
Gogoi, M. M., Babu, S. S., Moorthy, K. K., Bhuyan, P. K., Pathak, B., Subba,
T., Chutia, L., Kundu, S. S., Bharali, C., Borgohain, A., Guha, A., De, B.
K., Singh, B., and Chin, M.: Radiative effects of absorbing aerosols over
northeastern India: Observations and model simulations, J.
Geophys. Res.-Atmos., 122, 1132–1157,
https://doi.org/10.1002/2016JD025592, 2017.
Gogoi, M. M., Lakshmi, N. B., Nair, V. S., Kompalli, S. K., Moorthy, K. K.,
and Babu, S. S.: Seasonal contrast in the vertical profiles of aerosol
number concentrations and size distributions over India: Implications from
RAWEX aircraft campaign, J. Earth Syst. Sci., 128, 225,
https://doi.org/10.1007/s12040-019-1246-y, 2019.
Gogoi, M. M., Jayachandran, V. N., Vaishya, A., Babu, S. N. S., Satheesh, S. K., and Moorthy, K. K.: Airborne in situ measurements of aerosol size distributions and black carbon across the Indo-Gangetic Plain during SWAAMI–RAWEX, Atmos. Chem. Phys., 20, 8593–8610, https://doi.org/10.5194/acp-20-8593-2020, 2020.
Gogoi, M. M., Babu, S. S., Arun, B. S., Moorthy, K. K., Ajay, A., Ajay, P., Suryavanshi, A., Borgohain, A., Guha, A., Saikh, A., Pathak, B., Gharai, B., Ramaswamy, B., Balakrishnaiah, G., Menon, H. B., Kuniyal, J. C., Jayabala, K., Kotalu, R. G., Maheswari, M., Naja, M., Kaur, P., Bhuyan, P. K., Gupta, P., Singh, P. R., Srivastava, P., Singh, R. S., Kumar, R., Rastogi, S., Kundu, S. S., Kompalli, S. K., Panda, S., Tendule, C. R., Das, D., and Kant, Y.: Response of ambient BC
concentration across the Indian region to the nation-wide lockdown: Results
from the ARFINET measurements of ISRO-GBP, Curr. Sci., 120, 341–351,
https://doi.org/10.18520/cs/v120/i2/341-351, 2021.
Guha, A., De, B. K., Dhar, P., Banik, T., Chakraborty, M., Roy, R.,
Choudhury, A., Gogoi, M. M., Babu, S. S., and Moorthy, K. K.: Seasonal
Characteristics of Aerosol Black Carbon in Relation to Long Range Transport
over Tripura in Northeast India, Aerosol Air Qual. Res., 15,
786–798, https://doi.org/10.4209/aaqr.2014.02.0029, 2015.
Gustafsson, Ö. and Ramanathan, V.: Convergence on climate warming by
black carbon aerosols, P. Natl. Acad. Sci. USA, 113,
4243–4245, https://doi.org/10.1073/pnas.1603570113, 2016.
Hansen, A. D. A., Rosen, H., and Novakov, T.: The aethalometer – An
instrument for the real-time measurement of optical absorption by aerosol
particles, Sci. Total Environ., 36, 191–196,
https://doi.org/10.1016/0048-9697(84)90265-1, 1984.
Hara, Y., Nishizawa, T., Sugimoto, N., Osada, K., Yumimoto, K., Uno, I.,
Kudo, R., Ishimoto, H.: Retrieval of Aerosol Components Using
Multi-Wavelength Mie-Raman Lidar and Comparison with Ground Aerosol
Sampling, Remote Sensing, 10, 937, https://doi.org/10.3390/rs10060937,
2018.
Hashimoto, M. and Shi, C.:
GOSAT-2 TANSO-CAI-2 L2 Pre-processing Algorithm Theoretical Basis Document-ATBD, NIES-GOSAT2-ALG-20191008-008-01, https://prdct.gosat-2.nies.go.jp/documents/pdf/ATBD_CAI-2_L2_C2PR_en_01.pdf (last access: 25 June 2023), 2020.
Hashimoto, M. and Nakajima, T.: Development of a remote sensing algorithm to
retrieve atmospheric aerosol properties using multiwavelength and multipixel
information, J. Geophys. Res.-Atmos., 122, 6347–6378,
https://doi.org/10.1002/2016JD025698, 2017.
Hersbach H., Bell, B., Berrisford P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis.
Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Higurashi, A. and Nakajima, T.: Detection of aerosol types over the East
China Sea near Japan from four-channel satellite data, Geophys. Res. Lett., 29, 17-11–17-14, https://doi.org/10.1029/2002GL015357, 2002.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F., Jankowiak, I., and Smirnov, A.: AERONET – A federated instrument network and data archive for aerosol characterization, Remote Sens. Environ., 66, 1–16, https://doi.org/10.1016/S0034-4257(98)00031-5, 1998.
Hsu, N. C., Si-Chee, T., King, M. D., and Herman, J. R.: Aerosol properties
over bright-reflecting source regions, IEEE T. Geosci.
Remote, 42, 557–569, https://doi.org/10.1109/TGRS.2004.824067, 2004.
Hsu, N. C., Tsay, S., King, M. D., and Herman, J. R.: Deep Blue Retrievals
of Asian Aerosol Properties During ACE-Asia, IEEE T. Geosci.
Remote, 44, 3180–3195, https://doi.org/10.1109/TGRS.2006.879540,
2006.
Hsu, N. C., Jeong, M.-J., Bettenhausen, C., Sayer, A. M., Hansell, R.,
Seftor, C. S., Huang, J., and Tsay, S.-C.: Enhanced Deep Blue aerosol
retrieval algorithm: The second generation, J. Geophys. Res.-Atmos., 118, 9296–9315, https://doi.org/10.1002/jgrd.50712, 2013.
IPCC, Climate Change 2021 – The Physical Science Basis. Contribution of
Working Group I to the Sixth Assessment Report of the Intergovernmental
Panel on Climate Change: edited by: Masson-Delmotte, V., Zhai, P., Pirani, A.,
Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I.,
Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K.,
Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University
Press, Cambridge, United Kingdom and New York, NY, USA,
https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_FullReport_small.pdf (last access: 4 July 2023), 2021.
Ishida, H. and Nakajima, T. Y.: Development of an unbiased cloud detection
algorithm for a spaceborne multispectral imager, J. Geophys.
Res.-Atmos., 114, D07206, https://doi.org/10.1029/2008JD010710, 2009.
Ishida, H., Oishi, Y., Morita, K., Moriwaki, K., and Nakajima, T. Y.: Development of a support vector machine based cloud detection method for MODIS with the adjustability to various conditions, Remote Sens. Environ., 205, 390–407, https://doi.org/10.1016/j.rse.2017.11.003, 2018.
Jayaraman, A., Satheesh, S. K., Mitra, A. P., and Ramanathan, V.: Latitude
gradient in aerosol properties across the Inter Tropical Convergence Zone:
Results from the joint Indo-US study onboard Sagar Kanya, Curr. Sci., 80, 128–137, http://repository.ias.ac.in/13401/1/321.pdf (last access: 4 July 2023), 2001.
Junghenn Noyes, K. T., Kahn, R. A., Limbacher, J. A., and Li, Z.: Canadian and Alaskan wildfire smoke particle properties, their evolution, and controlling factors, from satellite observations, Atmos. Chem. Phys., 22, 10267–10290, https://doi.org/10.5194/acp-22-10267-2022, 2022.
Justice, C. O., Kendall, J. D., Dowty, P. R., and Scholes, R. J.: Satellite
remote sensing of fires during the SAFARI campaign using NOAA Advanced Very
High Resolution Radiometer data, J. Geophys. Res.-Atmos., 101, 23851–23863, https://doi.org/10.1029/95JD00623, 1996.
Kahn, R. A. and Gaitley, B. J.: An analysis of global aerosol type as
retrieved by MISR, J. Geophys. Res.-Atmos., 120,
4248–4281, https://doi.org/10.1002/2015JD023322, 2015.
Kaufman, Y. J.: Satellite sensing of aerosol absorption, J.
Geophys. Res.-Atmos., 92, 4307–4317,
https://doi.org/10.1029/JD092iD04p04307, 1987.
Kharuk, V. I., Dvinskaya, M. L., Im, S. T., Golyukov, A. S., and Smith, K.
T.: Wildfires in the Siberian Arctic, Fire, 5, 106, https://doi.org/10.3390/fire5040106,
2022.
Kim, J., Lee, J., Lee, H. C., Higurashi, A., Takemura, T., and Song, C. H.:
Consistency of the aerosol type classification from satellite remote sensing
during the Atmospheric Brown Cloud–East Asia Regional Experiment campaign,
J. Geophys. Res.-Atmos., 112, D22S33,
https://doi.org/10.1029/2006JD008201, 2007.
Kim, M., Kim, J., Torres, O., Ahn, C., Kim, W., Jeong, U., Go, S., Liu, X.,
Moon, K. J., and Kim, D.-R.: Optimal Estimation-Based Algorithm to Retrieve
Aerosol Optical Properties for GEMS Measurements over Asia, Remote Sensing,
10, 162, https://doi.org/10.3390/rs10020162, 2018.
Kompalli, S. K., Babu, S. S., Moorthy, K. K., Manoj, M. R., Kumar, N. V.
P. K., Shaeb, K. H. B., and Ashok Kumar, J.: Aerosol black carbon
characteristics over Central India: Temporal variation and its dependence on
mixed layer height, Atmos. Res., 147–148, 27–37,
https://doi.org/10.1016/j.atmosres.2014.04.015, 2014.
Kompalli, S. K., Babu, S. N. S., Moorthy, K. K., Satheesh, S. K., Gogoi, M. M., Nair, V. S., Jayachandran, V. N., Liu, D., Flynn, M. J., and Coe, H.: Mixing state of refractory black carbon aerosol in the South Asian outflow over the northern Indian Ocean during winter, Atmos. Chem. Phys., 21, 9173–9199, https://doi.org/10.5194/acp-21-9173-2021, 2021.
Kondo, Y., Sahu, L., Kuwata, M., Miyazaki, Y., Takegawa, N., Moteki, N.,
Imaru, J., Han, S., Nakayama, T., Oanh, N. T. K., Hu, M., Kim, Y. J., and
Kita, K.: Stabilization of the Mass Absorption Cross Section of Black Carbon
for Filter-Based Absorption Photometry by the use of a Heated Inlet, Aerosol
Sci. Tech., 43, 741–756,
https://doi.org/10.1080/02786820902889879, 2009.
Lee, K. H. and Kim, Y. J.: Satellite remote sensing of Asian aerosols: a case study of clean, polluted, and Asian dust storm days, Atmos. Meas. Tech., 3, 1771–1784, https://doi.org/10.5194/amt-3-1771-2010, 2010.
Lesins, G., Chylek, P., and Lohmann, U.: A study of internal and external mixing
scenarios and its effect on aerosol optical properties and direct radiative
forcing, J. Geophys. Res., 107, 4094,
https://doi.org/10.1029/2001JD000973, 2002.
Leskinen, P., Lindner, M., Verkerk, P. J., Nabuurs, G. J., Van Brusselen, J.,
Kulikova, E., Hassegawa, M., and Lerink, B. (Eds.): Russian forests and
climate change. What Science Can Tell Us 11, European Forest Institute, https://doi.org/10.36333/wsctu11,
2020.
Levy, R. C., Remer, L. A., Mattoo, S., Vermote, E. F., and Kaufman, Y. J.:
Second-generation operational algorithm: Retrieval of aerosol properties
over land from inversion of Moderate Resolution Imaging Spectroradiometer
spectral reflectance, J. Geophys. Res.-Atmos., 112, D13211,
https://doi.org/10.1029/2006JD007811, 2007.
Li, L., Dubovik, O., Derimian, Y., Schuster, G. L., Lapyonok, T., Litvinov, P., Ducos, F., Fuertes, D., Chen, C., Li, Z., Lopatin, A., Torres, B., and Che, H.: Retrieval of aerosol components directly from satellite and ground-based measurements, Atmos. Chem. Phys., 19, 13409–13443, https://doi.org/10.5194/acp-19-13409-2019, 2019.
Li, L., Che, H., Derimian, Y., Dubovik, O., Schuster, G.L., Chen, C., Li,
Q., Wang, Y., Guo, B., and Zhang, X.: Retrievals of fine mode
light-absorbing carbonaceous aerosols from POLDER/PARASOL observations over
East and South Asia, Remote Sens. Environ., 247, 111913, https://doi.org/10.1016/j.rse.2020.111913, 2020.
Lyapustin, A., Wang, Y., Laszlo, I., Kahn, R., Korkin, S., Remer, L., Levy,
R., and Reid, J. S.: Multiangle implementation of atmospheric correction
(MAIAC): 2. Aerosol algorithm, J. Geophys. Res.-Atmos.,
116, D03211, https://doi.org/10.1029/2010JD014986, 2011.
Macias Fauria, M. and Johnson, E. A.: Climate and wildfires in the North
American boreal forest, Philos. T. R. Soc. B, 363, 2317–2329,
https://doi.org/10.1098/rstb.2007.2202, 2008.
Mahowald, N., Albani, S., Kok, J. F., Engelstaeder, S., Scanza, R., Ward, D. S., Flanner, M. G.: The size distribution of desert dust aerosols and its impact on the Earth system, Aeolian Res., 15, 53–71, https://doi.org/10.1016/j.aeolia.2013.09.002, 2014.
Manoj, M. R., Satheesh, S. K., Moorthy, K. K., Gogoi, M. M., and Babu, S.
S.: Decreasing Trend in Black Carbon Aerosols Over the Indian Region,
Geophys. Res. Lett., 46, 2903–2910,
https://doi.org/10.1029/2018GL081666, 2019.
Mao, Q., Huang, C., Chen, Q., Zhang, H., and Yuan, Y.: Satellite-based
identification of aerosol particle species using a 2D-space aerosol
classification model, Atmos. Environ., 219, 117057,
https://doi.org/10.1016/j.atmosenv.2019.117057, 2019.
Martins, J. V., Artaxo, P., Liousse, C., Reid, J. S., Hobbs, P. V., and
Kaufman, Y. J.: Effects of black carbon content, particle size, and mixing
on light absorption by aerosols from biomass burning in Brazil, J.
Geophys. Res.-Atmos., 103, 32041–32050,
https://doi.org/10.1029/98JD02593, 1998.
Nair, V. S., Moorthy, K. K., Alappattu, D. P., Kunhikrishnan, P. K., George,
S., Nair, P. R., Babu, S. S., Abish, B., Satheesh, S. K., Tripathi, S. N.,
Niranjan, K., Madhavan, B. L., Srikant, V., Dutt, C. B. S., Badarinath, K.
V. S., and Reddy, R. R.: Wintertime aerosol characteristics over the
Indo-Gangetic Plain (IGP): Impacts of local boundary layer processes and
long-range transport, J. Geophys. Res.-Atmos., 112, D13205,
https://doi.org/10.1029/2006JD008099, 2007.
Nair, V. S., Moorthy, K. K., Babu, S. S., Narasimhulu, K., Sankara Reddy, L.
S., Ramakrishna Reddy, R., Gopal, K. R., Sreekanth, V., Madhavan, B. L., and
Niranjan, K.: Size segregated aerosol mass concentration measurements over
the Arabian Sea during ICARB, J. Earth Syst. Sci., 117, 315–323,
https://doi.org/10.1007/s12040-008-0034-x, 2008.
Nair, V. S., Babu, S. S., Gogoi, M. M., and Moorthy, K. K.: Large-scale
enhancement in aerosol absorption in the lower free troposphere over
continental India during spring, Geophys. Res. Lett., 43,
11453–411461, https://doi.org/10.1002/2016GL070669, 2016.
Nakajima, T., Yoon, S.-C., Ramanathan, V., Shi, G.-Y., Takemura, T.,
Higurashi, A., Takamura, T., Aoki, K., Sohn, B.-J., Kim, S.-W., Tsuruta, H.,
Sugimoto, N., Shimizu, A., Tanimoto, H., Sawa, Y., Lin, N.-H., Lee, C.-T.,
Goto, D., and Schutgens, N.: Overview of the Atmospheric Brown Cloud East
Asian Regional Experiment 2005 and a study of the aerosol direct radiative
forcing in east Asia, J. Geophys. Res., 112, D24S91,
https://doi.org/10.1029/2007JD009009, 2007.
National Institute for Environmental Studies, GOSAT-2 Project: GOSAT-2 TANSO-CAI-2 L2 Aerosol Property Product, CAI-2 L2 Release note, Product
version 01.03, NIES-GOSAT2-SYS-20210310-019-00, https://fxp.nies.go.jp/gosat-2_document-g/gosat-2_document/CAI-2_L2/ReleaseNote_CAI-2_L2_AERP_ver0103_RA_en_00.pdf (last access: 27 June 2023), 2021.
National Institute for Environmental Studies:
GOSAT-2 product archive,
https://prdct.gosat-2.nies.go.jp/app/searchproduct/display,
last access: 25 June 2023.
Nishizawa, T., Sugimoto, N., Matsui, I., Shimizu, A., Hara, Y., Itsushi, U.,
and Kim, S.-W.: Ground-based network observation using Mie–Raman lidars and
multi-wavelength Raman lidars and algorithm to retrieve distributions of
aerosol components, J. Quant. Spectrosc. Ra., 188, 79–93, 2017.
Oishi, Y., Ishida, H., Nakajima, T. Y., Nakamura, R., and Matsunaga, T.: The
Impact of Different Support Vectors on GOSAT-2 CAI-2 L2 Cloud
Discrimination, Remote Sensing, 9, 1236, https://doi.org/10.3390/rs9121236, 2017.
Oishi, Y., Ishida, H., and Nakajima, T. Y.: GOSAT-2 TANSO-CAI-2 L2 Cloud Discrimination Processing Algorithm Theoretical
Basis Document-ATBD, Release note, NIES-GOSAT2-ALG-20191008-009-00, https://prdct.gosat-2.nies.go.jp/documents/pdf/ATBD_CAI-2_L2_CLDD_en_00.pdf (last access: 25 June 2023), 2020.
Omar, A. H., Won, J.-G., Winker, D. M., Yoon, S.-C., Dubovik, O., and
McCormick, M. P.: Development of global aerosol models using cluster
analysis of Aerosol Robotic Network (AERONET) measurements, J.
Geophys. Res.-Atmos., 110, D10S14,
https://doi.org/10.1029/2004JD004874, 2005.
Park, R. J., Minjoong, J. K., Jaein, I. J., Daeok, Y., and Sangwoo, K.: A
contribution of brown carbon aerosol to the aerosol light absorption and its
radiative forcing in East Asia, Atmos. Environ., 44, 1414–1421,
https://doi.org/10.1016/j.atmosenv.2010.01.042, 2010.
Pathak, B., Kalita, G., Bhuyan, K., Bhuyan, P. K., and Moorthy, K. K.:
Aerosol temporal characteristics and its impact on shortwave radiative
forcing at a location in the northeast of India, J. Geophys.
Res.-Atmos., 115, D19204, https://doi.org/10.1029/2009JD013462, 2010.
Pathak, B., Subba, T., Dahutia, P., Bhuyan, P. K., Moorthy, K. K., Gogoi, M.
M., Babu, S. S., Chutia, L., Ajay, P., Biswas, J., Bharali, C., Borgohain,
A., Dhar, P., Guha, A., De, B. K., Banik, T., Chakraborty, M., Kundu, S. S.,
Sudhakar, S., and Singh, S. B.: Aerosol characteristics in north-east India
using ARFINET spectral optical depth measurements, Atmos. Environ.,
125, 461–473, https://doi.org/10.1016/j.atmosenv.2015.07.038, 2016.
Prasad, P., Raman, M. R., Ratnam, M. V., Chen, W. N., Rao, S. V. B., Gogoi, M. M., Kompalli, S. K., Kumar, S. K., and Babu, S. S.: Characterization of atmospheric Black Carbon over a semi-urban site of
Southeast India: Local sources and long-range transport, Atmos.
Res., 213, 411–421, https://doi.org/10.1016/j.atmosres.2018.06.024,
2018.
Ramnarine, E., Kodros, J. K., Hodshire, A. L., Lonsdale, C. R., Alvarado, M. J., and Pierce, J. R.: Effects of near-source coagulation of biomass burning aerosols on global predictions of aerosol size distributions and implications for aerosol radiative effects, Atmos. Chem. Phys., 19, 6561–6577, https://doi.org/10.5194/acp-19-6561-2019, 2019.
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding, Series on
Atmospheric, Oceanic and Planetary Physics, Volume 2, World Scientific, 256 pp., https://doi.org/10.1142/3171, 2000.
Sahu, S. K., Mangaraj, P., Beig, G., Samal, A., Pradhan, C., Dash, S., and
Tyagi, B.: Quantifying the high-resolution seasonal emission of air
pollutants from crop residue burning in India, Environ. Pollut., 286,
117165, https://doi.org/10.1016/j.envpol.2021.117165, 2021.
Sand, M., Samset, B. H., Myhre, G., Gliß, J., Bauer, S. E., Bian, H., Chin, M., Checa-Garcia, R., Ginoux, P., Kipling, Z., Kirkevåg, A., Kokkola, H., Le Sager, P., Lund, M. T., Matsui, H., van Noije, T., Olivié, D. J. L., Remy, S., Schulz, M., Stier, P., Stjern, C. W., Takemura, T., Tsigaridis, K., Tsyro, S. G., and Watson-Parris, D.: Aerosol absorption in global models from AeroCom phase III, Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, 2021.
Schuster, G. L., Dubovik, O., Holben, B. N., and Clothiaux, E. E.: Inferring
black carbon content and specific absorption from Aerosol Robotic Network
(AERONET) aerosol retrievals, J. Geophys. Res.-Atmos.,
110, D10S17, https://doi.org/10.1029/2004JD004548, 2005.
Shin, S.-K., Tesche, M., Noh, Y., and Müller, D.: Aerosol-type classification based on AERONET version 3 inversion products, Atmos. Meas. Tech., 12, 3789–3803, https://doi.org/10.5194/amt-12-3789-2019, 2019.
Singh, A., Rajput, P., Sharma, D., Sarin, M. M., and Singh, D.: Black Carbon
and Elemental Carbon from Postharvest Agricultural-Waste Burning Emissions
in the Indo-Gangetic Plain, Adv. Meteorol., 2014, 179301,
https://doi.org/10.1155/2014/179301, 2014.
Soni, V.K., Pandithurai, G., and Pai, D. S.: Evaluation of long-term changes of
solar radiation in India, Int. J. Climatol., 32,
540–551, https://doi.org/10.1002/joc.2294, 2012.
Subba, T., Gogoi, M. M., Moorthy, K. K., Bhuyan, P. K., Pathak, B., Guha,
A., Srivastava, M. K., Vyas, B. M., Singh, K., Krishnan, J., Lakshmikumar,
T. V. S., and Babu, S. S.: Aerosol Radiative Effects over India from Direct
Radiation Measurements and Model Estimates, Atmos. Res., 276,
106254, https://doi.org/10.1016/j.atmosres.2022.106254, 2022.
Torres, O., Bhartia, P. K., Herman, J. R., Ahmad, Z., and Gleason, J.:
Derivation of aerosol properties from satellite measurements of
backscattered ultraviolet radiation: Theoretical basis, J.
Geophys. Res.-Atmos., 103, 17099–17110,
https://doi.org/10.1029/98JD00900, 1998.
Torres, O., Bhartia, P. K., Herman, J. R., Sinyuk, A., Ginoux, P., and
Holben, B.: A Long-Term Record of Aerosol Optical Depth from TOMS
Observations and Comparison to AERONET Measurements, J.
Atmos. Sci., 59, 398–413,
https://doi.org/10.1175/1520-0469(2002)059<0398:Altroa>2.0.Co;2, 2002.
Torres, O., Tanskanen, A., Veihelmann, B., Ahn, C., Braak, R., Bhartia, P.
K., Veefkind, P., and Levelt, P.: Aerosols and surface UV products from
Ozone Monitoring Instrument observations: An overview, J.
Geophys. Res.-Atmos., 112, D24S47,
https://doi.org/10.1029/2007JD008809, 2007.
Torres, O., Ahn, C., and Chen, Z.: Improvements to the OMI near-UV aerosol algorithm using A-train CALIOP and AIRS observations, Atmos. Meas. Tech., 6, 3257–3270, https://doi.org/10.5194/amt-6-3257-2013, 2013.
Vaishya, A., Prayagraj, S., Shantanu, R., and Babu, S. S.: Aerosol black
carbon quantification in the central Indo-Gangetic Plain: Seasonal
heterogeneity and source apportionment, Atmos. Res., 185, 13–21,
https://doi.org/10.1016/j.atmosres.2016.10.001, 2017.
Vaishya, A., Babu, S. N. S., Jayachandran, V., Gogoi, M. M., Lakshmi, N. B., Moorthy, K. K., and Satheesh, S. K.: Large contrast in the vertical distribution of aerosol optical properties and radiative effects across the Indo-Gangetic Plain during the SWAAMI–RAWEX campaign, Atmos. Chem. Phys., 18, 17669–17685, https://doi.org/10.5194/acp-18-17669-2018, 2018.
Vermote, E. F., Tanre, D., Deuze, J. L., Herman, M., and Morcette, J. J.:
Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an
overview, IEEE T. Geosci. Remote, 35,
675–686, https://doi.org/10.1109/36.581987, 1997.
Vignati, E., Karl, M., Krol, M., Wilson, J., Stier, P., and Cavalli, F.: Sources of uncertainties in modelling black carbon at the global scale, Atmos. Chem. Phys., 10, 2595–2611, https://doi.org/10.5194/acp-10-2595-2010, 2010.
Voronova, O. S., Zimaa, A. L., Kladova, V. L., and Cherepanova, E. V.:
Anomalous Wildfires in Siberia in Summer 2019, Izv. Atmos. Ocean. Phys., 56,
1042–1052, https://doi.org/10.1134/S000143382009025X, 2020.
Wang, L., Li, Z., Tian, Q., Ma, Y., Zhang, F., Zhang, Y., Li, D., Li, K.,
and Li, L.: Estimate of aerosol absorbing components of black carbon, brown
carbon, and dust from ground-based remote sensing data of sun-sky
radiometers, J. Geophys. Res.-Atmos., 118, 6534–6543,
https://doi.org/10.1002/jgrd.50356, 2013.
Wang, R., Balkanski, Y., Boucher, O., Ciais, P., Schuster, G. L.,
Chevallier, F., Samset, B. H., Liu, J., Piao, S., Valari, M., and Tao, S.:
Estimation of global black carbon direct radiative forcing and its
uncertainty constrained by observations, J. Geophys. Res.-Atmos., 121, 5948–5971, https://doi.org/10.1002/2015JD024326, 2016.
Wooster, M. J., Zhukov, B., and Oertel, D.: Fire radiative energy for
quantitative study of biomass burning: derivation from the BIRD experimental
satellite and comparison to MODIS fire products, Remote Sens.
Environ., 86, 83–107, https://doi.org/10.1016/S0034-4257(03)00070-1,
2003.
Wurl, D., Grainger, R. G., McDonald, A. J., and Deshler, T.: Optimal estimation retrieval of aerosol microphysical properties from SAGE II satellite observations in the volcanically unperturbed lower stratosphere, Atmos. Chem. Phys., 10, 4295–4317, https://doi.org/10.5194/acp-10-4295-2010, 2010.
Xu, W., Scholten, R. C., Hessilt, T. D., Liu, Y., and Veraverbeke, S.:
Overwintering fires rising in eastern Siberia, Environ. Res.
Lett., 17, 045005, https://doi.org/10.1088/1748-9326/ac59aa, 2022.
Short summary
Considering the climate warming potential of atmospheric black carbon (BC), satellite-based retrieval is a novel idea. This study highlights the regional distribution of BC based on observations by the Cloud and Aerosol Imager-2 on board the GOSAT-2 satellite and near-surface measurements of BC in ARFINET. The satellite retrieval fairly depicts the regional and seasonal features of BC over the Indian region, which are similar to those recorded by surface observations.
Considering the climate warming potential of atmospheric black carbon (BC), satellite-based...
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