Refine your search
Co-Authors
- D. C. S. Raju
- Sourav Das
- Abhra Chanda
- Suparna Dey
- Sanjibani Banerjee
- Anirban Mukhopadhyay
- Anirban Akhand
- Amit Ghosh
- Subhajit Ghosh
- Sugata Hazra
- Aneesh A. Lotliker
- K. H. Rao
- S. B. Choudhury
- V. K. Dadhwal
- K. K. Barik
- R. Annadurai
- S. R. Panda
- J. K. Tripathy
- Shuchita Srivastava
- Asfa Siddiqui
- Prakash Chauhan
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Mitra, D.
- Carrion Flowers of Coromandel
Abstract Views :131 |
PDF Views:104
Authors
D. C. S. Raju
1,
D. Mitra
1
Affiliations
1 Botanical Survey of India, Howrah, IN
1 Botanical Survey of India, Howrah, IN
Source
Nelumbo - The Bulletin of the Botanical Survey of India, Vol 36, No 1-4 (1994), Pagination: 233-234Abstract
Stapelia umbellata Roxb. (Asclepiadaceae), a native species of Coromandel coast is described and its value as an ornamental is discussed.- Comparing the Spatio-Temporal Variability of Remotely Sensed Oceanographic Parameters between the Arabian Sea and Bay of Bengal throughout a Decade
Abstract Views :248 |
PDF Views:100
Authors
Sourav Das
1,
Abhra Chanda
1,
Suparna Dey
1,
Sanjibani Banerjee
1,
Anirban Mukhopadhyay
1,
Anirban Akhand
1,
Amit Ghosh
1,
Subhajit Ghosh
1,
Sugata Hazra
1,
D. Mitra
2,
Aneesh A. Lotliker
3,
K. H. Rao
4,
S. B. Choudhury
4,
V. K. Dadhwal
4
Affiliations
1 School of Oceanographic Studies, Jadavpur University, 188 Raja S. C. Mullick Road, Kolkata 700 032, IN
2 Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun 248 001, IN
3 Indian National Centre for Ocean Information Services, Kukatpally, Hyderabad 500 090, IN
4 National Remote Sensing Centre, Balanagar, Hyderabad 500 042, IN
1 School of Oceanographic Studies, Jadavpur University, 188 Raja S. C. Mullick Road, Kolkata 700 032, IN
2 Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun 248 001, IN
3 Indian National Centre for Ocean Information Services, Kukatpally, Hyderabad 500 090, IN
4 National Remote Sensing Centre, Balanagar, Hyderabad 500 042, IN
Source
Current Science, Vol 110, No 4 (2016), Pagination: 627-639Abstract
The spatio-temporal variability of sea-surface temperature (SST), photosynthetically active radiation (PAR), chlorophyll-a (Chl-a), particulate organic carbon (POC) and particulate inorganic carbon (PIC) was evaluated in the Arabian Sea (ABS) and Bay of Bengal (BoB), from July 2002 to November 2014 by means of remotely sensed monthly composite Aqua MODIS level-3 data having a spatial resolution of 4.63 km. Throughout the time period under consideration, the surface waters of ABS (27.76±1.12°C) were slightly cooler than BoB (28.93±0.76°C); this was observed during all the seasons. On the contrary, the availability of PAR was higher in ABS (45.76±3.41 mol m-2 d-1) compared to BoB (41.75±3.75 mol m-2 d-1), and its spatial dynamics in the two basins was mainly regulated by cloud cover and turbidity of the water column. The magnitude and variability of Chl-a concentration were substantially higher in ABS (0.487±0.984 mg m-3), compared to BoB (0.187±0.243 mg m-3), and spatially higher values were observed near the coastal waters. Both POC and PIC exhibited higher magnitudes in ABS compared to BoB; however, the difference was substantially high in case of POC. None of the parameters showed any significant temporal trend during the 12-year span, except PIC, which exhibited a significant decreasing trend in ABS.Keywords
Marine Ecosystems, Oceanographic Parameters, Remote Sensing, River Basins, Spatio-Temporal Variability.References
- Tilstone, G. H., Angel-Benavides, I. M., Pradhan, Y., Shutler, J. D., Groom, S. and Sathyendranath, S., An assessment of chlorophylla algorithms available for SeaWiFs in coastal and open areas of the Bay of Bengal and Arabian Sea. Remote Sensing Environ., 2011, 115, 2277–2291.
- Holm-Hansen, O. et al., Temporal and spatial distribution of chlorophylla in surface waters of the Scotia Sea as determined by both shipboard measurements and satellite data. Deep-Sea Res. II, 2004, 51, 1323–1331.
- Moses, W. J., Gitelson, A. A., Berdnikov, S. and Povazhnyy, V., Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data – successes and challenges. Environ. Res. Lett., 2009, 4, 1–8.
- Jaswal, A. K., Singh, V. and Bhambak, S. R., Relationship between sea surface temperature and surface air temperature over Arabian Sea, Bay of Bengal and Indian Ocean. J. Indian Geophys. Union, 2012, 16, 41–53.
- Grossant, H. P. and Ploug, H., Microbial degradation of organic carbon and nitrogen on diatom aggregates. Limnol. Oceanogr., 2001, 46, 267–277.
- Eppley, R. W. and Peterson, B. J. Particulate organic matter flux and planktonic new production in the deep ocean. Nature, 1979, 282, 677–680.
- Gauns, M., Madhupratap, M., Ramaiah, N., Jyothibabu, R., Fernandes, V., Paul, J. T. and Prasanna Kumar, S., Comparative accounts of biological productivity characteristics and estimates of carbon fluxes in the Arabian Sea and the Bay of Bengal. Deep-Sea Res. II, 2005, 52, 2003–2017.
- UNESCO, River inputs to the ocean systems: status and recommendations for research. In UNESCO Technical Papers in Marine Science, No. 55, Final Report of the SCOR Working Group 46, Paris, 1988, p. 25.
- Subramanian, V., Sediment load of Indian rivers. Curr. Sci., 1993, 64, 928–930.
- Prasanna Kumar, S. et al., Why is the Bay of Bengal less productive during summer monsoon compared to the Arabian Sea? Geophys. Res. Lett., 2002, 29, 2235; doi: 10.1029/2002GL016013.
- Gill, A. E., Atmosphere Ocean Dynamics, Academic Press, New York, 1982.
- Paul, J. T., Ramaiah, N., Gauns, M. and Fernandes, V., Preponderance of a few diatom species among the highly diverse microphytoplankton assemblages in the Bay of Bengal. Mar. Biol., 2007, 152, 63–75.
- Dietrich, G., The unique situation in the environment of the Indian Ocean. In The Biology of the Indian Ocean (ed. Zeitzschel, B.), Springer, Berlin, 1973, pp. 1–6.
- Madhupratap, M. et al., Biogeochemistry of the Bay of Bengal: physical, chemical and primary productivity characteristics of the central and western Bay of Bengal during summer monsoon. Deep-Sea Res. II, 2003, 50, 881–896.
- Esaias, W. E. et al., An overview of MODIS capabilities for ocean science observations. IEEE Trans. Geosci. Remote Sensing, 1998, 36, 1250–1265.
- Salomonson, V., Guenther, B. and Masuoka, E., A summary of the status of the EOS Terra Mission Moderate Resolution Imaging Spectroradiometer (MODIS) and attendant data product development after one year of on-orbit performance. In Proceedings of the International Geoscience and Remote Sensing Symposium, Sydney, Australia, 2001.
- Savtchenko, A., Ouzounov, D., Ahmad, S., Acker, J., Leptoukh, G., Koziana, J. and Nickless, D., Terra and Aqua MODIS products available from NASA GES DAAC. Adv. Space Res., 2004, 34, 710–714.
- http://www.britannica.com/EBchecked/topic/31653/Arabian-Sea (accessed on 4 February 2015).
- http://www.britannica.com/EBchecked/topic/60740/Bay-of-Bengal (accessed on 4 February 2015).
- Laruelle, G. G., Dürr, H. H., Slomp, C. P. and Borges, A. V., Evaluation of sinks and sources of CO2 in the global coastal ocean using a spatially-explicit typology of estuaries and continental shelves. Geophys. Res. Lett., 2010, 37, L15607; doi: 10.1029/ 2010GL043691.
- Morel, A. and Prieur, L., Analysis of variations in ocean color. Limnol. Oceanogr., 1977, 22, 709–722.
- Dall’Olmo, G., Gitelson, A. A., Rundquist, D. C., Leavitt, B., Barrow, T., and Holz, J. C., Assessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands. Remote Sensing Environ., 2005, 96, 176–187.
- Darecki, M. and Stramski, D., An evaluation of MODIS and SeaWiFS bio-optical algorithms in the Baltic Sea. Remote Sensing Environ., 2004, 89, 326–350.
- O’Reilly, J. E. and 24 co-authors, SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3. In NASA Tech. Memo. 2000–206892 (eds Hooker, S. B. and Firestone, E. B.), NASA Goddard Space Flight Center, vol. 11, 2000, p. 49.
- Kilpatrick, K. A. et al., A decade of sea surface temperature from MODIS. Remote Sensing Environ., 2015, 165, 27–41.
- Moore, T. S., Campbell, J. W. and Dowell, M. D., A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product. Remote Sensing Environ., 2009, 113, 2424–2430.
- Hu, C., Feng, L. and Lee, Z. Uncertainties of SeaWiFS and MODIS remote sensing reflectance: Implications from clear water measurements. Remote Sensing Environ., 2013, 133, 168–182.
- Van Laake, P. E. and Sanchez-Azofeifa, G. A., Simplified atmospheric radiative transfer modelling for estimating incident PAR using MODIS atmosphere products. Remote Sensing Environ., 2004, 91, 98–113.
- Shenoi, S. S. C., Shankar, D. and Shetye, S. R., Differences in heat budgets of the near‐surface Arabian Sea and Bay of Bengal: implications for the summer monsoon. J. Geophys. Res.: Oceans 2002, 107, 5–1.
- Prasannakumar, S. et al., Is the biological productivity in the Bay of Bengal light limited? Curr. Sci., 2010, 98, 1331–1339.
- Brock, J. and McClain, C., Interannual variability in phytoplankton blooms observed in the northwestern Arabian Sea during the southwest monsoon. J. Geophys. Res., 1992, 97, 733–750.
- Madhupratap, M., Sawant, S. and Gauns, M., A first report on a bloom of the marine prymnesiophycean, Phaeocystis globosa from the Arabian Sea. Oceanol. Acta, 2000, 23, 83–90.
- Sarangi, R. K., Chauhan, P. and Nayak, S. R., Inter-annual variability of phytoplankton blooms in the northern Arabian Sea during winter monsoon period (February–March) using IRS-P4 OCM data. Indian J. Mar. Sci., 2005, 34, 163–173.
- Sarangi, R. K., Observation of algal bloom in the northwest Arabian Sea using multisensor remote sensing satellite data. Mar. Geod., 2012, 35, 158–174.
- Dey, S. and Singh, R. P., Comparison of chlorophyll distributions in the northeastern Arabian Sea and southern Bay of Bengal using IRS-P4 Ocean Color Monitor data. Remote Sensing Environ., 2003, 85, 424–428.
- Pattabiraman, V., Munavar, M. and Suresh, K., Comparative study on chlorophyll distributions in the coastal regions of northeastern Arabian Sea and southern Bay of Bengal based on Indian seasons and rainfall distributions. In Asia Pacific Conference on Environmental Science and Technology, Advances in Biomedical Engineering, 2012, vol. 6, pp. 453–458.
- Fernandes, L., Bhosle, N. B., Matondkar, S. P. and Bhushan, R., Seasonal and spatial distribution of particulate organic matter in the Bay of Bengal. J. Mar. Syst., 2009, 77, 137–147.
- Gundersen, J. S., Gardner, W. D., Richardson, M. J. and Walsh, I. D., Effects of monsoons on the seasonal and spatial distributions of POC and chlorophyll in the Arabian Sea. Deep-Sea Res. II, 1998, 45, 2103–2132.
- Gardner, W. D., Mishonov, A. V. and Richardson, M. J., Global POC concentrations from in situ and satellite data. Deep Sea Res. II, 2006, 53, 718–740.
- Izumo, T., Montegut, C. B., Luo, J. J., Behera, S. K., Masson, S. and Yamagata, T. The role of the western Arabian Sea upwelling in Indian monsoon rainfall variability. J. Climate, 2008, 21, 5603– 5623.
- Lotliker, A. A., Kumar, T. S., Reddem, V. S. and Nayak, S., Cyclone Phailin enhanced the productivity following its passage: evidence from satellite data. Curr. Sci., 2014, 106, 360–361.
- Freeman, N. M. and Lovenduski, N. S., Decreased calcification in the Southern Ocean over the satellite record. Geophys. Res. Lett., 2015, 42, 1834–1840.
- Spatio-Temporal Study of Coastal Dynamics in Odisha Coast, East Coast of India
Abstract Views :557 |
PDF Views:250
Authors
Affiliations
1 School of Civil Engineering, SRM University, Chennai-603203, IN
2 Department of Earth Sciences, Sambalpur University, Burla-768019, IN
3 Indian Institute of Remote Sensing, ISRO, Dehradun-248001, IN
1 School of Civil Engineering, SRM University, Chennai-603203, IN
2 Department of Earth Sciences, Sambalpur University, Burla-768019, IN
3 Indian Institute of Remote Sensing, ISRO, Dehradun-248001, IN
Source
International Journal of Earth Sciences and Engineering, Vol 10, No 4 (2017), Pagination: 878-884Abstract
The present study illustrates the integral approach of remote sensing and GIS for the assessment of coastal environment of a part of coastal Odisha. Multispectral and multi-temporal Landsat satellite imageries along with Linear Imaging Self scanning Sensor (LISS IV) data were used to carry out this piece of work. In this paper, an attempt has been made to study the coastal dynamics i.e., landuse/landcover (LULC), erosion and accretion of a part of Odisha coast (Baleswar, Bhadrak, Kendrapara and Jagatsinghpur districts). Supervised classification adopting maximum likelihood method was applied to analyze this work. The study resulted in different classes like Sand, mangroves, wetland, Plantation with settlement, forest, agricultural land etc. The LULC map showed that the area under plantation with settlement was larger than any other class and it also showed reduction of agricultural land in all the districts of the coastal environment. Similarly, mangroves increased in all the coastal districts. Shoreline changes (Erosion and accretion) were identified through maximum likelihood method. The analysis of LULC and shoreline changes in the study area revealed significant variations. The result showed increase in plantation with settlement and decrease in agricultural land. The map prepared for this research will contribute to both the landuse planner as well as the coastal planners for shoreline protection measurement.Keywords
LULC, Erosion, Accretion, LISS IV, Odisha Coast.References
- Babykalpana, Y., “Classification of LULC change detection using Remotely Sensed Data for Coimbatore city”, Tamil Nadu, India, 2010
- Blaschke, T., Lang, S., Lorup, E., Strobl, J., Zeil, P., “Object oriented image processing in an integrated GIS/remote sensing environment and perspectives for environmental applications.” In: Cremers, A., Greve, K. (Eds.), Environmental information for planning, Politics and the public, vol. II, Metropolis-Verlag, Marburg, pp. 555-570, 2000
- Chand, P. and Acharya, P “Shoreline change and sea level rise along coast of Bhitarkanika wildlife sanctuary, Orissa: An analytical approach of remote sensing and statistical techniques”, International Journal of Geomatics and Geosciences Volume 1, No 3, 436-455, 2010
- Choudhary, R., Gowthaman, R., & Sanil Kumar, V., “Shoreline change detection from Karwar to Gokarna-South West coast of India using remotely Sensed data.” International Journal of Earth Sciences. 6(3), 489-494., 2013
- Franklin, S.E., Hall, R.J., Moskal, L.M., Maudie, A.J., Lavigne, M.B., “Incorporating texture into classification of forest species composition from airborne multispectral images.” International journal of remote sensing, 21(1), pp 61-79., 2000
- Ghanavati, E., Firouzabadi, P. Z., Jangi, A. A., & Khosravi, S., “Monitoring geomorphologic changes usingLandsat TM and ETM+ data in the Hendijan River delta, southwest Iran.” International Journal of Remote Sensing, 29(4), 945-959., 2008
- Gong, P., Howarth, P.J., “The use of structural information for improving land cover classification accuracies at the rural urban fringe.” Photogrammetric engineering and remote sensing 56(1), pp 67-73., 1990
- Hutchinson, C.F., “Techniques for combining Landsat and ancillary data for digital classification improvement”. Photogrammetric engineering and remote sensing, 8 (1), pp 123-130., 1982
- Khan IA, Ali Z, Asaduzzaman M, Bhuyan MHR “The social dimensions of adaptation to climate change in Bangladesh.” The World Bank, Washington, 2010
- Kontoes, C., Wilkinson, G., Burril, A., Goffredo, S., Me´ gier, J., An experimental system for the integration of GIS data in knowledge-based analysis for remote sensing of agriculture. International journal of geographical information system, 7 (3), pp 247-262., 1993
- Kumar, A., & Jayappa, K. S., “Long and short-term shoreline changes along Mangalore coast, India. International Journal of Environmental Research, 3(2), 177-188., 2009
- Kumar, T.S., Mahendra, R.S., Nayak, S., Radhakrishnan, K., and Sahu, K.C., “Coastal vulnerability assessment for Orissa State, east coast of India”., Journal of Coastal Research, 26 523-534,2010
- Long, B.G., Skewes, T.D., “A technique for mapping mangroves with Landsat TM satellite data and geographic information system.” Estuarine, Coastal and shelf science, 43, pp 373-381., 1996
- Mas, J.F., Ramı´rez, I., “Comparison of landuse classifications obtained by visual interpretation and digital processing.” ITC journal 1996-3/4, pp 278-283., 1996
- Mukhopadhyay, A., Mukherjee, S., Hazra, S. and Mitra, D. “Sea Level Rise and Shoreline Changes: AGeoinformatic appraisal Of Chandipur Coast, Orissa.” International Journal of Geology, Earth and Environmental Sciences, Vol. 1 (1), 9-17., 2011
- Muttitanon, W., & Tripathi, N. K., “Landuse/land cover changes in the coastal zone of Ban Don Bay,Thailand using Landsat 5 TM data.” International Journal of Remote Sensing, 26(11), 2311-2323., 2005
- Palubinskas, G., Lucas, R.M., Foody, G.M., Curran, P.J., An evaluation of fuzzy and texture-based classification approaches for mapping regenerating tropical forest classes from Landsat-TM data. International journal of remote sensing, 16(4), pp 747-759., 1995
- Siddiqui, M. N., & Maajid, S., Monitoring of geomorphological changes for planning reclamation work in coastal area of Karachi, Pakistan. Advances in Space Research, 33(7), 1200-1205., 2004
- Srinivasan, A., Richards, J.A., Knowledge-based techniques for multisource classification. International journal of remote sensing, 3(3), pp 505-525., 1990
- T. N. Chase, R. A. Pielke Sr, T. G. F. Kittel, R. R. Nemani, S. W. Running, Simulated impacts of historical land cover changes on global climate in northern winter, Climate Dynamics, 16, 93-105., 2000
- Turner II, B. L., Meyer, W. B. & Skole, D. L., Global Land-Use/ Land-Cover Change: Towards an Integrated Study. 1994
- Veldkamp, A. & Lambin, E., Predicting land-use change, Agriculture, Ecosystems and Environment 85, pp. 1-6.,2001
- Effect of COVID-19 Lockdown on the Spatio-temporal Distribution of Nitrogen Dioxide Over India
Abstract Views :235 |
PDF Views:87
Authors
Affiliations
1 Marine and Atmospheric Sciences Department, Indian Institute of Remote Sensing, Dehradun 248 001, IN
1 Marine and Atmospheric Sciences Department, Indian Institute of Remote Sensing, Dehradun 248 001, IN
Source
Current Science, Vol 120, No 2 (2021), Pagination: 368-375Abstract
The nationwide lockdown was implemented in India from 25 March 2020 onwards to control the spread of deadly Coronavirus disease 2019 (COVID-19). A sudden shutdown of anthropogenic activities resulted in abrupt decrease of nitrogen dioxide (NO2) across the Indian region. OMI (Ozone Monitoring Instrument) tropospheric column NO2 observations show significantly decreased values during 2020 compared to previous years during 25 March to 19 April. The spatiotemporal variation of tropospheric column NO2 difference between 2020 and average 2017–2019 shows reduction by more than 1 × 1015 molecules/cm2 over the Indo Gangetic Plain, eastern and southern India due to lockdown. However, the western Indian region shows slight enhancement which may be attributed to combined effect of transport of polluted air from Middle East and Pakistan, and relatively higher biomass burning activity during 2020. A significant reduction is also observed on the surface distribution of NOx (NO + NO2) over different Indian cities due to COVID-19 lockdown. Maximum reduction in daily average surface NOx is observed over Kolkata (65.2 ± 18.7 ppbv to 30.3 ± 4.6 ppbv) followed by New Delhi (38.8 ± 17.5 ppbv to 11.5 ± 2.9 ppbv) which may be attributed to vehicle fleet, type of fuel used, power plants and industrial emissions.Keywords
COVID-19 Lockdown, Nitrogen Dioxide, NOx, OMI.References
- Kurokawa, J. and Ohara, T., Long-term historical trends in air pollutant emissions in Asia: Regional Emission inventory in ASia (REAS) version 3.1. Atmos. Chem. Phys. Discuss., 2019; https://doi.org/10.5194/acp-2019-1122.
- Balakrishnan, K. et al., The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: the Global Burden of Disease Study. Lancet Planetary Health, 2017, 5196(18), 30261–30244.
- Mahajan, A. S., Smedt, I. De, Biswas, M. S., Ghude, S. D., Fadnavis, S., Roy, C. and Roozendael, M. van, Inter-annual variations in satellite observations of nitrogen dioxide and formaldehyde over India. Atmos. Environ., 2015, 116, 194–201.
- IPCC, Climate Change, Atmospheric Chemistry and Greenhouse Gases, Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, 2001.
- Khreis, H., Kelly, C., Tate, J., Parslow, R., Lucas, K. and Nieuwenhuijsen, M., Exposure to traffic-related air pollution and risk of development of childhood asthma: a systematic review and meta-analysis. Environ. Int., 2017, 100, 1–31.
- Khreis, H. and Nieuwenhuijsen, M. J., Traffic-related air pollution and childhood asthma: recent advances and remaining gaps in the exposure assessment methods. Int. J. Environ. Res. Public Health, 2017, 14(3), 312; https://doi.org/10.3390/ijerph14030312
- Abbey, D. E., Colome, S. D., Mills, P. K., Burchette, R., Beeson, W. L. and Tian, Y., Chronic disease associated with long-term concentrations of nitrogen dioxide. J. Expo. Anal. Environ. Epidemiol., 1993, 3, 181–202.
- Blomberg, A. et al., Persistent airway inflammation but accommodated antioxidant and lung function responses after repeated daily exposure to nitrogen dioxide. Am. J. Respir. Crit. Care Med., 1999, 159, 536–543.
- Chen, T. M., Kuschner, W. G., Gokhale, J. and Shofer, S., Outdoor air pollution: nitrogen dioxide, sulfur dioxide, and carbon monoxide health effects. Am. J. Med. Sci., 2007, 333, 249–256.
- Beelen, R. et al., Long-term effects of traffic-related AIR pollution. Environ. Health Persp., 2008, 116(2), 196–202.
- Hoek, G., Krishnan, R. M., Beelen, R., Peters, A., Ostro, B., Brunekreef, B. and Kaufman, J. D., Long-term air pollution exposure and cardio-respiratory mortality: a review. Environ. Health, 2013, 12, 43.
- Bilal, Bashir, M. F. et al., Environmental pollution and COVID-19 outbreak: insights from Germany. Air Qual. Atmos. Health, 2020, 1–10; doi:10.1007/s11869-020-00893-9
- Conticini, E., Frediani, B. and Caro, D., Can atmospheric pollution be considered a co-factor in extremely high level of SARSCoV2 lethality in Northern Italy?*. Environ. Pollut., 2020, 261, 114465.
- Boersma, K. F. et al., An improved retrieval of tropospheric NO2 columns from the Ozone Monitoring Instrument, Atmos. Meas. Tech., 2011, 4, 1905–1928.
- Gerboles, M., Lagler, F., Rembges, D. and Brun, C., Assessment of uncertainty of NO2 measurements by the chemiluminescence method and discussion of the quality objective of the NO2 European Directive. J. Environ. Monitoring, 2003, 5, 529–540.
- Harrison, R. M. and Perry, R., Handbook of Air pollution Analysis, Chapman Hall, New York, 1986, 2nd edn.
- Schroeder, W., Oliva, P., Giglio, L. and Csiszar, I. A., The New VIIRS 375 m active fire detection data product: Algorithm description and initial assessment. Rem. Sens. Environ., 2014, 143, 85–96.
- Garg, A., Shukla, P. R., Bhattacharya, S. and Dadhwal, V. K., Sub‐region (district) and sector level SO2 and NOx emissions for India: Assessment of inventories and mitigation flexibility. Atmos. Environ., 2001, 35, 703–713.
- Beig, G. and Ali, K., Behavior of boundary layer ozone and its precursors over a great alluvial plain of the world: Indo-Gangetic Plains. Geophys. Res. Lett., 2006, 33, L24813; doi:10.1029/ 2006GL028352.
- Periaswamy, P. et al., Shifting cultivation in North East India: Social dimension, cross cultural reflection and strategies for improvement. Indian J. Agric. Sci., 2018, 88, 811–819.
- Yadav, P. K., Slash-and-burn agriculture in North-East India. Exp. Op. Environ. Biol., 2013, 2; 10.4172/2325-9655.1000102.
- Singh, R. P. and Kaskaoutis, D. G., Crop residue burning: a threat to South Asian air quality. EOS Trans. Am. Geophys. Union, 2014, 95(37), 333–340.
- Vadrevu, K. P., Ellicott, E. and Badarinath, K., MODIS derived fire characteristics and aerosol optical depth variations during the agricultural residue burning season, North India. Environ. Pollut., 2011, 159(6), 1560–1569.
- Mallik, C. et al., Variability of SO2, CO, and light hydrocarbons over a megacity in Eastern India: effects of emissions and transport. Environ. Sci. Pollut. Res., 2014, 21, 8692–8706.
- Srivastava, S., Lal, S., Subrahamanyamb, D. B., Gupta, S., Venkataramani, S. and Rajesh, T. A., Seasonal variability in mixed layer height and its impact on trace gas distribution over a tropical urban site: Ahmedabad. Atmos. Res., 2010, 96, 79–87.
- Jain, N., Bhatia, A. and Pathak, H., Emission of air pollutants from crop residue burning in India. Aerosol Air Quality Res., 2014, 14, 422–430.
- Road Transport Year Book 2015–16, Transport Research Wing, Ministry of Road Transport and Highways, Government of India.
- West Bengal Pollution Control Board, Annual Report 2008–2010; Government of West Bengal, Kolkata, India, 2010.
- Ghose, M. K., Air pollution in the city of Kolkata: Health effects due to chronic exposure. In Air Pollution in Kolkata: An Analysis of Current Status and Interrelation between Different Factors; SEEU Review, Tetovo, Macedonia, 2013, vol. 8, pp. 181–214.
- Farooqui, Z. M., John, K., Biswas, J. and Sule, N., Modeling analysis of the impact of anthropogenic emission sources on ozone concentration over selected urban areas in Texas. Atmos. Pollut. Res., 2013, 4, 33–42.
- Mahato, S., Pal, S. and Ghosh, K. G., Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India. Sci. Total Environ., 2020, 730, 139086.