Browsing by Author "Pawan Kumar Joshi"

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Health Risk Appraisal Associated with Air Quality over Coal-Fired Thermal Power Plants and Coalmine Complex Belts of Urban–Rural Agglomeration in the Eastern Coastal State of Odisha, India
(MDPI, 2022) Arti Choudhary; Pradeep Kumar; Saroj Kumar Sahu; Chinmay Pradhan; Pawan Kumar Joshi; Sudhir Kumar Singh; Pankaj Kumar; Cyrille A. Mezoue; Abhay Kumar Singh; Bhishma Tyagi
Manufacturing and mining sectors are serious pollution sources and risk factors that threaten air quality and human health. We analyzed pollutants at two study sites (Talcher and Brajrajnagar) in Odisha, an area exposed to industrial emissions, in the pre-COVID-19 year (2019) and consecutive pandemic years, including lockdowns (2020 and 2021). We observed that the annual data for pollutant concentration increased at Talcher: PM2.5 (7–10%), CO (29–35%), NO2 and NOx (8–57% at Talcher and 14–19% at Brajrajnagar); while there was slight to substantial increase in PM10 (up to 11%) and a significant increase in O3 (41–88%) at both sites. At Brajrajnagar, there was a decrease in PM2.5 (up to 15%) and CO (around half of pre-lockdown), and a decrease in SO2 concentration was observed (30–86%) at both sites. Substantial premature mortality was recorded, which can be attributed to PM2.5 (16–26%), PM10 (31–43%), NO2 (15–21%), SO2 (4–7%), and O3 (3–6%). This premature mortality caused an economic loss between 86–36 million USD to society. We found that although lockdown periods mitigated the losses, the balance of rest of the year was worse than in 2019. These findings are benchmarks to manage air quality over Asia’s largest coalmine fields and similar landscapes. © 2022 by the authors.
Machine learning models for estimating criteria pollutants and health risk-based air quality indices over eastern coast coal mine complex belts
(Frontiers Media SA, 2025) Pradeep Kumar; Arti K. Choudhary; Pawan Kumar Joshi; Ram Pravesh Kumar; R. Bhatla
Estimating criteria pollutants is crucial due to their continuous increase and impact on respiratory health. To mitigate the impact of air pollution on human health, it is essential to understand the concentration of air pollutants at specific locations. This study aims to evaluate the variation, estimate the levels of criteria pollutants, and assess their potential health risks in the vicinity of a coal mine complex and a thermal power plant situated in an eastern coastal state of India. The pre-existing hot spot regions—Talcher (T) and Brajrajnagar (B)—which host many coal-fired power plants and clusters of coal-mining blocks in the coastal state of Odisha, are considered. Talcher consistently shows higher levels of particulate matter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2), reflecting a greater industrial impact. Brajrajnagar, while also impacted, exhibits comparatively lower pollutant concentrations. The observed seasonal trends highlight the necessity for targeted mitigation strategies to address pollution levels and associated health risks in these regions. Novel machine learning (ML) models, including independent component regression (ICR), ElasticNet (ENET), and boosted tree (BT), are applied to estimate criteria pollutants. Statistical analyses highlight BT as the superior model, outperforming ENET and ICR in pollutant estimation, particularly in Talcher. Taylor plots and statistical evaluations further validate the BT model’s robustness in air pollutant estimation. Additionally, the study assesses the associated health risks posed to nearby populations of Talcher and Brajrajnagar. The analysis highlights significant spatial disparities in pollution levels, with Talcher consistently recording higher concentrations of PM10, NO2, and SO2 and poorer air quality index (AQI) than Brajrajnagar. Talcher also shows greater health risks, with pollutant exposure linked up to 6% higher risks for PM10, 5% for NO2, and up to 3% for SO2. The health risk-based air quality index (HAQI) reveals an underestimation of health risks by the current AQI, emphasizing the need for improved metrics to address the impacts of multi-pollutant exposure. © © 2025 Kumar, Choudhary, Joshi, Kumar and Bhatla.
Meteorological influences on air pollution dynamics in pollution epicentre of National Capital Region, India
(Elsevier Ltd, 2025) Susanta Mahato; Sonali Kundu; Jan Cermak; Pawan Kumar Joshi
This study analyzes the temporal variations and source characteristics of air pollution in Delhi, examining the influence of meteorological conditions on pollutant concentrations. The goal is to provide insights for policymakers to develop effective emission reduction strategies and improve air quality. Innovative Trend Analysis (ITA) and Detrended Fluctuation Analysis (DFA) were used to identify long-term trends and fluctuations in pollutants such as PM10, PM2.5, NO2, SO2, CO, O3, and NH3 from 2018 to 2023. Continuous Wavelet Transformation (CWT) and Cross-Wavelet Transformation (XWT) were utilized to explore seasonal patterns and pollutant-meteorology interactions. Receptor modeling techniques, including non-parametric wind regression and conditional probability function analysis, were applied to identify major pollution sources. The study found that key emission sources were located to the west, south, and southwest of the monitoring site for most pollutants, with ozone precursors predominantly originating from the north. ITA and DFA revealed persistent long-range correlations in pollutant levels, driven by stable emission sources and seasonal meteorological effects. CWT analysis showed distinct periodic patterns in air quality, with worsening conditions during winter and summer. The research highlights the role of temperature inversions, low wind speeds, and regional pollutant transport in exacerbating pollution levels but emphasizes that human-driven emission sources remain the primary contributors to air quality deterioration. While meteorological factors influence pollution dispersion, they do not diminish the urgency of emission control measures. The findings support the development of targeted pollution control policies, including emission reduction from industrial, vehicular, and biomass burning sources. Advancing real-time air quality monitoring and integrating socio-economic considerations into air pollution management will enhance the effectiveness of interventions, aligning with Sustainable Development Goals (SDG 11 - urban sustainability and SDG 3 - public health). © 2025 Elsevier Ltd
Retraction notice to “Meteorological influences on air pollution dynamics in pollution epicentre of National Capital Region, India” [Chemosphere 377, May 2025, 144353] (Chemosphere (2025) 377, (S0045653525002954), (10.1016/j.chemosphere.2025.144353))
(Elsevier Ltd, 2025) Susanta Mahato; Sonali Kundu; Jan Cermak; Pawan Kumar Joshi
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal). © 2025 Elsevier Ltd