Browsing by Author "Pawan K. Joshi"

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Characteristics of atmospheric aerosol over indo-gangetic basin: Trend, origin of sources and impact on climate
(Nova Science Publishers, Inc., 2021) Pradeep Kumar; Arti Choudhary; Pawan K. Joshi; Abhay Kumar Singh
Aerosols are omnipresent in air in solid and liquid forms and noticed most likely as dust, smoke, haze, etc. Natural and anthropogenic processes contribute to aerosol concentrations in the atmosphere. Aerosols affect Earth's energy budget by scattering and absorbing radiation and by modifying amounts and microphysical as well as radiative properties of clouds. Aerosols, when concentrated near the surface, have been recognized as affecting pulmonary function and other aspects of human health. Indo Gangetic Basin (IGB) experiences a high aerosol loading throughout the year; therefore, there is a need to study aerosol characteristics over IGB and its impacts on climate. IGB has dynamic meteorological patterns and has undergone severe aerosol episodes including dust storms, increased biomass and agricultural burning, which increase aerosols loading over the region. The management of near-surface air quality is necessary because of its possible impacts on public health, visibility, climate, and agricultural output. Aerosol optical depth (AOD) is one of the important parameters for the investigation of aerosol characteristics and it is associated with direct solar radiation by scattering and absorption process. At present, satellite-based AOD information is available in variety of spatial and temporal scales are generally utilized at good spatial as well as temporal coverage for aerosols characterization. Along with this National Aeronautics and Space Administration (NASA) has set up a ground-based aerosol monitoring network under the AERONET (Aerosol Robotic Network) Program, which uses automatic sun/sky radiometers deployed at various places around the IGB. Additionally, MICROTOPS-II Sun-photometer is a valuable instrument used for in-situ-based AOD measurement. The ground-based and satellite information simultaneously is widely acknowledged these days for urban air quality management among both the scientific and the policy-making communities. The present chapter discusses optical characteristics of aerosols in Kanpur, Jaipur, Gandhi College, and Varanasi while focusing on sources and impact on climate. © 2021 Nova Science Publishers, Inc.
Development of decadal (1985-1995-2005) land use and land cover database for India
(MDPI AG, 2015) Parth S. Roy; Arijit Roy; Pawan K. Joshi; Manish P. Kale; Vijay K. Srivastava; Sushil K. Srivastava; Ravi S. Dwevidi; Chitiz Joshi; Mukunda D. Behera; Prasanth Meiyappan; Yeshu Sharma; Atul K. Jain; Jamuna S. Singh; Yajnaseni Palchowdhuri; Reshma. M. Ramachandran; Bhavani Pinjarla; V. Chakravarthi; Nani Babu; Mahalakshmi S. Gowsalya; Praveen Thiruvengadam; Mrinalni Kotteeswaran; Vishnu Priya; Krishna Murthy V.N. Yelishetty; Sandeep Maithani; Gautam Talukdar; Indranil Mondal; Krishnan S. Rajan; Prasad S. Narendra; Sushmita Biswal; Anusheema Chakraborty; Hitendra Padalia; Manoj Chavan; Satish N. Pardeshi; Swapnil A. Chaudhari; Arur Anand; Anjana Vyas; Mruthyunjaya K. Reddy; M. Ramalingam; R. Manonmani; Pritiranjan Behera; Pulakesh Das; Poonam Tripathi; Shafique Matin; Mohammed L. Khan; Om P. Tripathi; Jyotihman Deka; Prasanna Kumar; Deepak Kushwaha
India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study. © 2015 by the authors.
Evaluating air quality and criteria pollutants prediction disparities by data mining along a stretch of urban-rural agglomeration includes coal-mine belts and thermal power plants
(Frontiers Media SA, 2023) Arti Choudhary; Pradeep Kumar; Chinmay Pradhan; Saroj K. Sahu; Sumit K. Chaudhary; Pawan K. Joshi; Deep N. Pandey; Divya Prakash; Ashutosh Mohanty
Air pollution has become a threat to human life around the world since researchers have demonstrated several effects of air pollution to the environment, climate, and society. The proposed research was organized in terms of National Air Quality Index (NAQI) and air pollutants prediction using data mining algorithms for particular timeframe dataset (01 January 2019, to 01 June 2021) in the industrial eastern coastal state of India. Over half of the study period, concentrations of PM2.5, PM10 and CO were several times higher than the NAQI standard limit. NAQI, in terms of consistency and frequency analysis, revealed that moderate level (ranges 101–200) has the maximum frequency of occurrence (26–158 days), and consistency was 36%–73% throughout the study period. The satisfactory level NAQI (ranges 51–100) frequency occurrence was 4–43 days with a consistency of 13%–67%. Poor to very poor level of air quality was found 13–50 days of the year, with a consistency of 9%–25%. Random Forest (RF), Support Vector Machine (SVM), Bagged Multivariate Adaptive Regression Splines (MARS) and Bayesian Regularized Neural Networks (BRNN) are the data mining algorithms, that showed higher efficiency for the prediction of PM2.5, PM10, NO2 and SO2 except for CO and O3 at Talcher and CO at Brajrajnagar. The Root Mean Square Error (RMSE) between observed and predicted values of PM2.5 (ranges 12.40–17.90) and correlation coefficient (r) (ranges 0.83–0.92) for training and testing data indicate about slightly better prediction of PM2.5 by RF, SVM, bagged MARS, and BRNN models at Talcher in comparison to PM2.5 RMSE (ranges 13.06–21.66) and r (ranges 0.64–0.91) at Brajrajnagar. However, PM10 (RMSE: 25.80–43.41; r: 0.57–0.90), NO2 (RMSE: 3.00–4.95; r: 0.42–0.88) and SO2 (RMSE: 2.78–5.46; r: 0.31–0.88) at Brajrajnagar are better than PM10 (RMSE: 35.40–55.33; r: 0.68–0.91), NO2 (RMSE: 4.99–9.11; r: 0.48–0.92), and SO2 (RMSE: 4.91–9.47; r: 0.20–0.93) between observed and predicted values of training and testing data at Talcher using RF, SVM, bagged MARS and BRNN models, respectively. Taylor plots demonstrated that these algorithms showed promising accuracy for predicting air quality. The findings will help scientific community and policymakers to understand the distribution of air pollutants to strategize reduction in air pollution and enhance air quality in the study region. Copyright © 2023 Choudhary, Kumar, Pradhan, Sahu, Chaudhary, Joshi, Pandey, Prakash and Mohanty.