Environmental Science And Technology - Research Publications

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    Temporal Variation of Water Quality Parameters during COVID-19: A Case Study of River Yamuna
    (2023-07-20T00:00:00) Singh, Bhupendra Pratap; Pandey, Puneeta; Koul, Monika; Bhatia, Bela; Singh, Amit Kumar; Mehra, Kriti; Chowdhary, Khyati; Kumar, Ranjeet; Goel, Vanshika
    Abstract: The novel coronavirus (COVID-19) originated in Wuhan city of China in late December 2019 and affected the (atmosphere and hydrosphere) and also impacted economic activities due to the lockdown. Several studies have reported the impact of the COVID-19 pandemic on significant changes in the air quality index, but only a few studies have reported the relationship between water quality parameters and COVID-19. The findings of the current study revealed that the mean values of pH in the Yamuna river were reported to be 7.77 � 0.31, 7.55 � 0.40, and 7.31 � 0.44 for pre-, during, and post-pandemic periods. The changes in the pH values indicated that Yamuna water quality became less alkaline due to restricted industrial activities along the river during the lockdown period. Further, the mean values of COD were observed to be 60.57 � 16.79, 62.99 � 23.17, and 129.06 � 36.96; the BOD values were 18.20 � 8.42, 20.16 � 5.22, and 33.35 � 10.35, and DO values were 3.30 � 1.15, 3.20 � 0.96, and 3.49 � 1.56 respectively for pre-, during, and post-pandemic periods. The results of these parameters indicated that agriculture, including local source discharges, was a major factor affecting water quality parameters during the pandemic period. According to the study, there is a significant positive association between the BOD and COD with values 0.99, 0.98, and 0.94, respectively, whereas a strong negative correlation was calculated between DO, COD, BOD for pre-, during, and post-pandemic periods. This study would be enlightening among the scientists, researchers, and government to address the water issues along with policy formulation. � 2023, Pleiades Publishing, Ltd.
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    Distribution and concentration pathway of particulate pollution during pandemic-induced lockdown in metropolitan cities in India
    (Institute for Ionics, 2023-06-12T00:00:00) Anand, A.; Garg, V.K.; Agrawal, A.; Mangla, S.; Pathak, A.
    To characterize the pollutant dispersal across major metropolitan cities in India, daily particulate matter (PM10 and PM2.5) data for the study areas were collected from the National Air Quality Monitoring stations database provided by the Central Pollution Control Board (CPCB) of India. The data were analysed for three temporal ranges, i.e. before the pandemic-induced lockdown, during the lockdown, and after the upliftment of lockdown restrictions. For the purpose, the time scale ranged from 1st April to 31st May for the years 2019 (pre), 2020, and 2021 (post). Statistical distributions (lognormal, Weibull, and Gamma), aerosol optical thickness, and back trajectories were assessed for all three time periods. Most cities followed the lognormal distribution for PM2.5 during the lockdown period except Mumbai and Hyderabad. For PM10, all the regions followed the lognormal distribution. Delhi and Kolkata observed a maximum decline in particulate pollution of 41% and 52% for PM2.5 and 49% and 53% for PM10, respectively. Air mass back trajectory suggests local transmission of air mass during the lockdown period, and an undeniable decline in aerosol optical thickness was observed from the MODIS sensor. It can be concluded that statistical distribution analysis coupled with pollution models can be a counterpart in studying the dispersal and developing pollution abatement policies for specific sites. Moreover, incorporating remote sensing in pollution study can enhance the knowledge about the origin and movement of air parcels and can be helpful in taking decisions beforehand. � 2023, The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University.
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    Substantial changes in Gaseous pollutants and health effects during COVID-19 in Delhi, India
    (PeerJ Inc., 2023-01-09T00:00:00) Singh, Bhupendra; Pandey, Puneeta; Wabaidur, Saikh Mohammad; Avtar, Ram; Kumar, Pramod; Rahman, Shakilur
    Background. Coronavirus disease has affected the entire population worldwide in terms of physical and environmental consequences. Therefore, the current study demonstrates the changes in the concentration of gaseous pollutants and their health effects during the COVID-19 pandemic in Delhi, the national capital city of India. Methodology. In the present study, secondary data on gaseous pollutants such as nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), ammonia (NH3), and ozone (O3) were collected from the Central Pollution Control Board (CPCB) on a daily basis. Data were collected from January 1, 2020, to September 30, 2020, to determine the relative changes (%) in gaseous pollutants for pre-lockdown, lockdown, and unlockdown stages of COVID-19. Results. The current findings for gaseous pollutants reveal that concentration declined in the range of 51%�83% (NO), 40%�69% (NOx), 31%�60% (NO2), and 25%�40% (NH3) during the lockdown compared to pre-lockdown period, respectively. The drastic decrease in gaseous pollutants was observed due to restricted measures during lockdown periods. The level of ozone was observed to be higher during the lockdown periods as compared to the pre-lockdown period. These gaseous pollutants are linked between the health risk assessment and hazard identification for non-carcinogenic. However, in infants (0�1 yr), Health Quotient (HQ) for daily and annual groups was found to be higher than the rest of the exposed group (toddlers, children, and adults) in all the periods. Conclusion. The air quality values for pre-lockdown were calculated to be ��poor category to ��very poor�� category in all zones of Delhi, whereas, during the lockdown period, the air quality levels for all zones were calculated as ��satisfactory,�� except for Northeast Delhi, which displayed the ��moderate�� category. The computed HQ for daily chronic exposure for each pollutant across the child and adult groups was more than 1 (HQ > 1), which indicated a high probability to induce adverse health outcomes. � Copyright 2023 Singh et al.
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    Urban to rural COVID-19 progression in India: The role of massive migration and the challenge to India's traditional labour force policies
    (John Wiley and Sons Ltd, 2021-09-15T00:00:00) Sahoo, Prafulla Kumar; Biswal, Suchismita; Kumar, Hemant; Powell, Mike
    The coronavirus disease?2019 (COVID-19) has emerged as a deadliest disease in the 21st century. Initially in India, this disease was concentrated in major urban cities like Mumbai, Delhi, Gujarat, and Chennai, which were the national hotspots for the COVID-19 pandemic. However, in subsequent months, returning migrants (mainly day labour) brought the disease back to their home; this vector triggered significant spread to semi-urban and rural areas. This highlighted serious concerns in rural India, where access to sophisticated healthcare and mitigation strategies were lacking. There is little data on this new pattern of disease spread. This article provides a short review for tracking the spread of COVID-19 into major rural states in India based on understanding urban-rural workforce migration relative to the growing proportion of the nation's COVID-19 caseload between May-September 2020. � 2021 John Wiley & Sons Ltd.
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    Impact of environmental indicators on the COVID-19 pandemic in Delhi, India
    (MDPI, 2021-08-09T00:00:00) Mangla, Sherry; Pathak, Ashok Kumar; Arshad, Mohd.; Ghosh, Doyel; Sahoo, Prafulla Kumar; Garg, Vinod Kumar; Haque, Ubydul
    Currently, there is a massive debate on whether meteorological and air quality parameters play a crucial role in the transmission of COVID-19 across the globe. With this background, this study aims to evaluate the impact of air pollutants (PM2.5, PM10, CO, NO, NO2, and O3) and meteorological parameters (temperature, humidity, wind speed, and rainfall) on the spread and mortality due to the COVID-19 outbreak in Delhi from 14 Mar 2020 to 3 May 2021. The Spearman�s rank correlation method employed on secondary data shows a significant correlation between the COVID-19 incidences and the PM2.5, PM10, CO, NO, NO2, and O3 concentrations. Amongst the four meteorological parameters, temperature is strongly correlated with COVID-19 infections and deaths during the three phases, i.e., pre-lockdown (14 March 2020 to 24 March 2020) (r = 0.79), lockdown (25 March 2020 to 31 May 2020) (r = 0.87), and unlock (1 June 2020 to 3 May 2021) (r = ?0.75), explaining the variability of about 20�30% in the lockdown period and 18�19% in the unlock period. NO2 explained the maximum variability of 10% and 7% in the total confirmed cases and deaths among the air pollutants, respectively. A generalized linear model could explain 80% and 71% of the variability in confirmed cases and deaths during the lockdown and 82% and 81% variability in the unlock phase, respectively. These findings suggest that these factors may contribute to the transmission of the COVID-19 and its associated deaths. The study results would enhance the ongoing research related to the influence of environmental factors. They would be helpful for policymakers in managing the outbreak of COVID-19 in Delhi, India. � 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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    COVID-19 pandemic: An outlook on its impact on air quality and its association with environmental variables in major cities of Punjab and Chandigarh, India
    (Bellwether Publishing, Ltd., 2020-10-31T00:00:00) Sahoo, Prafulla Kumar; Chauhan, Amit Kumar; Mangla, Sherry; Pathak, Ashok Kumar; Garg, V.K.
    The present study aims to evaluate the impact of COVID-19 lockdown on air quality and to explore the association of daily COVID-19 confirmed cases with meteorological parameters and criteria pollutants in the major cities of Punjab and Chandigarh, India during the different phase of pre-lockdown (March 1 to March 24), lockdown (1.0, 2.0, 3.0, 4.0; March 25 to May 31), and unlock (1.0, 2.0; > June 1) in 2020. Our results show that the COVID-19 lockdown has drastically improved the quality of air in major cities of Punjab and Chandigarh. Compared to pre-lockdown, maximum reduction of PM2.5 and PM10 levels (up to ?52 and ?53.5%, respectively) was witnessed during lockdown 1.0, but their levels were rising again during the last phase of lockdown and unlock phases. This is due to more relaxation and traffic returned on the road. Among other pollutants, NO2 also reduced during lockdown 1.0, but remained variable between cities and different phases of lockdown and unlock periods. However, surface-level ozone resulted in an overall increase trend during the lockdown and unlock phases. Regarding the relationship between COVID-19 and meteorological parameters, Spearman correlation test shows that ambient temperature is positively correlated with COVID-19 daily confirmed cases (r < 0.77, p < 0.01). This result indicates that the study region�s hot tropical weather is less effective in controlling the spread of COVID-19. Relative humidity and wind speed are also weakly correlated with COVID-19. Furthermore, among criteria pollutants, PM2.5 and PM10 are positively correlated (r < 0.55, p < 0.01) with COVID-19 pandemic, especially in Jalandhar and Ludhiana, suggesting that these pollutants could lead to the spreading of the virus. However, further in-depth studies are required to validate this finding. The results of this study can contribute to the understanding of the role of environmental factors in the transmission of COVID-19 in tropical and sub-tropical countries like India, Brazil, etc. This study also indicates that the temporarylockdown like COVID-19 can be emerged as an effective way to control environmental imbalancein the study area, as well as in other areas. � 2020 Informa UK Limited, trading as Taylor & Francis Group.