School Of Environment And Earth Sciences

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Subject: search.filters.subject.COVID-19 pandemic

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    Unveiling Nature�s Resilience: Exploring Vegetation Dynamics during the COVID-19 Era in Jharkhand, India, with the Google Earth Engine
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-09-08T00:00:00) Ahmad, Tauseef; Gupta, Saurabh Kumar; Singh, Suraj Kumar; Meraj, Gowhar; Kumar, Pankaj; Kanga, Shruti
    The Severe Acute Respiratory Syndrome Coronavirus Disease 2019 (COVID-19) pandemic has presented unprecedented challenges to global health and economic stability. Intriguingly, the necessary lockdown measures, while disruptive to human society, inadvertently led to environmental rejuvenation, particularly noticeable in decreased air pollution and improved vegetation health. This study investigates the lockdown�s impact on vegetation health in Jharkhand, India, employing the Google Earth Engine for cloud-based data analysis. MODIS-NDVI data were analyzed using spatio-temporal NDVI analyses and time-series models. These analyses revealed a notable increase in maximum vegetation greenery of 19% from April 2019 to 2020, with subsequent increases of 13% and 3% observed in March and May of the same year, respectively. A longer-term analysis from 2000 to 2020 displayed an overall 16.7% rise in vegetation greenness. While the maximum value remained relatively constant, it demonstrated a slight increment during the dry season. The Landsat data Mann�Kendall trend test reinforced these findings, displaying a significant shift from a negative NDVI trend (1984�2019) to a positive 17.7% trend (1984�2021) in Jharkhand�s north-west region. The precipitation (using NASA power and Merra2 data) and NDVI correlation were also studied during the pre- and lockdown periods. Maximum precipitation (350�400 mm) was observed in June, while July typically experienced around 300 mm precipitation, covering nearly 85% of Jharkhand. Interestingly, August 2020 saw up to 550 mm precipitation, primarily in Jharkhand�s southern region, compared to 400 mm in the same month in 2019. Peak changes in NDVI value during this period ranged between 0.6�0.76 and 0.76�1, observed throughout the state. Although the decrease in air pollution led to improved vegetation health, these benefits began to diminish post-lockdown. This observation underscores the need for immediate attention and intervention from scientists and researchers. Understanding lockdown-induced environmental changes and their impact on vegetation health can facilitate the development of proactive environmental management strategies, paving the way towards a sustainable and resilient future. � 2023 by the authors.
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    Pre-to-post lockdown impact on air quality and the role of environmental factors in spreading the COVID-19 cases - a study from a worst-hit state of India
    (Springer Science and Business Media Deutschland GmbH, 2020-10-09T00:00:00) Sahoo, Prafulla Kumar; Mangla, Sherry; Pathak, Ashok Kumar; Sal�mao, Gabriel Negreiros; Sarkar, Dibyendu
    The present�study aims to�examine the changes in air quality during different phases of the COVID-19 pandemic, including the lockdown (LD1�4) and unlock period (UL1�2) (post-lockdown) as compared to�pre-lockdown (PL1�3) and to�establish the relationships of the environmental and demographic variables with COVID-19 cases in the state of Maharashtra, the worst-hit state in India. Atmospheric pollutants such as PM2.5, PM10, NOx, and CO were substantially reduced during the lockdown and unlock�phases with the greatest reduction in cities having larger traffic volumes. Compared with the immediate pre-lockdown period (PL3), the averaged PM2.5 and PM10 reduced by up to 51% and 47% respectively during the lockdown periods, which resulted in �satisfactory� level of air quality index (AQI) as a result of reduced�vehicular traffic and industrial closing. These parameters continued to reduce as much as 80% during the unlock periods due to the additive impact of weather (rainfall and temperature) combined with the lockdown conditions. Kendall�s correlation matrix showed a significant negative correlation between temperature and air pollutants (r= ? 0.35 to ? 057). Conversely, SO2 and O3 did not improve, and in some cases, they increased during the lockdown and unlocking. COVID-19 spreading incidences were strongly and positively correlated with temperature (r < 0.62) and dew point (r < 0.73). Thus, this indicates that the increase in temperature and dew point cannot weaken the transmission of this virus. The number of COVID-19 cases relative to air pollutants was negatively correlated (r = ? 0.33 to ? 0.74), which may be�a mere coincidence as a result of lockdown. However, based on pre-lockdown�air quality data and demographic factors, it�was found that�particulate matter (PM2.5 and PM10) and population density are closely linked with higher morbidity and mortality although a more in-depth research is required in this direction to validate this finding. The onset of COVID-19 has allowed us to determine that �immediate� changes in air quality within densely populated/industrialized areas can improve livelihood based on pollution mitigation. These findings could be used by policymakers to set new benchmarks for air�pollution that would improve the quality of life for major sectors of the World�s population. COVID-19 has shown us that we can make changes when necessary, and findings may pave the way for future research to inform policy on the tough choices we will have to make between quality of life and survival.�Also, our results will enrich the ongoing discussion on the role of environmental factors on the transmission of COVID-19 and will help to take necessary steps for its control. � 2020, ISB.