Shutdown Of Industry Research Articles

An Overview of Electricity Consumption in Europe: Models for Prediction of the Electricity Usage for Heating and Cooling

Although aggregate electricity consumption provides valuable information for market analysis, demand composition, including industrial, residential, illumination, and other uses, and special days, such as national or religious holidays and annual industrial shutdowns, differ for each country. This paper analyzes the hourly electricity consumption of European countries in the European Transmission System Operation for Electricity (ENTSO-E) grid from 2006 to 2018. We propose an outlier detection method to identify special days and a modulated Fourier Series Expansion model to determine the breakdown of industrial versus household consumption and heating versus cooling consumption. The proposed outlier detection method uses the time series for each hour and checks whether a day has more than a threshold number of hours with exceptional electricity consumption levels. The proposed demand prediction model has a 3% average error when electricity usage for heating is not dominant. It also allows country classification based on consumption patterns to efficiently manage regional or country-based electricity markets.

Examining the Pandemic Induced Adoption of E-Learning Through a UTAUT Model Approach

The Covid-19 pandemic's worldwide disruption has significantly impacted many facets of society, including education and learning. This seismic effect results from the urgent need to stop the virus from spreading, which calls for strong limitations on leaving one's home. This has resulted in the mass shutdown of industries, offices, schools, universities, theatres, parks, gymnasiums, and retail stores. Consequently, students across countries were forced to adopt e-learning at a mass scale to continue their education. This study uses a unified theory of acceptance and use of technology (UTAUT) model method to list the elements that led to the adoption of e-learning by Indian college students during the Covid-19 epidemic. The empirical study is based on an extensive literature review and an online survey of 162 undergraduate students at Delhi University, India. Regression analysis results show that the most significant predictors of students' preference for e-learning during the pandemic are their evaluations of performance expectancy, effort expectancy, facilitating conditions, and the social isolation brought on by the Covid-19 crisis. Furthermore, the Covid-19 epidemic is seen by students as the primary driver behind their adoption of e-learning. A sophisticated understanding of the complexities associated with adopting e-learning is likely to greatly assist in developing creative educational projects and policies in the future.

Partially burnt wood fly ash characterization and its application in low-carbon mortar and concrete

The global shutdown of coal industries has led to a shortage of coal fly ash, a commonly used cement replacement. Wood fly ash (WFA), a byproduct abundant in Canada's timber-based construction industry, emerges as a potential alternative. This study comprehensively characterized a locally available partially-burnt WFA to assess its potential to be incorporated into mortar and concrete. The study was divided into three phases: characterization of the WFA, properties of WFA-based mortar, and concrete. Preliminary findings indicate WFA's similarity to class C fly ash. While WFA adversely impacted mechanical properties, at 15% replacement, mortar and concrete performed similarly to the reference mixtures. The compressive strength of mortar and concrete reduced by 6 and 21%, respectively, slump reduced by 6.7% and chloride resistance in fact improved by 19% at 15% WFA replacement. Considering these results, WFA-based concrete presents a viable option for low-carbon construction.

Regional variability and its impact on the decarbonization of emissions-intensive, trade-exposed industries in Canada

ABSTRACT Emissions-intensive, trade-exposed (EITE) industries must decarbonize to limit global warming to 1.5°C. This study explores how policy stringency and regional variability impact EITE industrial decarbonization. It uses Canada as a case study due to its heterogeneous industrial sector and high regional resource variability. The study has two scenarios: one with global climate action where the world pushes to limit warming to 1.5°C, and one where Canada acts to achieve net-zero emissions by 2050 and the rest of the world lags. The scenarios differ in three ways: the global price of oil, the pace of technological change for low emission technologies, and domestic climate policy. In the global action scenario, a carbon price of $430USD2020 was needed to achieve 75% decarbonization of EITE industries by 2050. In our global inaction scenario, EITE industries only decarbonize 25%, as domestic climate policy considered international competition and the risk of industrial shutdown. If competitiveness concerns persist as simulated in this scenario, Canada is highly unlikely to achieve deep industrial decarbonization by 2050. The results also show that regional variability plays a significant role in low emissions technology adoption. While all regions will need targeted innovation and commercialization support as well as market uptake mechanisms, we find that relative advantages and disadvantages in terms of resource availability and industrial mix play an important role in how regional decarbonization occurs. For instance, regions with inexpensive local fossil fuels and ready geology suitable for CO2 storage have a high uptake of carbon capture and storage. Regions with access to abundant hydroelectricity rely more on electrification as a decarbonization pathway. Regions with no relative resource advantages are at greater risk for industrial shutdown due to the higher cost of decarbonization.

Impact of the emergency response to COVID-19 on air quality and its policy implications: Evidence from 290 cities in China

The emergency response to the COVID-19 pandemic had an extreme exogenous impact on society and the economy. This paper aims to explore the impacts of the national emergency response and the subsequent emergency response termination on air quality and its policy implications through regression discontinuity design (RDD) estimation by employing panel data on daily air quality from January 1, 2019, to July 31, 2020, for 290 cities in China. The empirical results showed that the emergency response resulted in a significant decrease in most of the major pollutant concentrations within a short time frame, and the average air quality index (AQI) decreased by approximately 11.0%. The concentrations of PM2.5, PM10, SO2, NO2, and CO decreased by approximately 18.8%, 13.1%, 13.5%, 11.1% and 6.7%, respectively, while the O3 concentration did not change significantly. Further causal analysis found that mandatory traffic restrictions and the shutdown of industries were two important factors that contributed greatly to air quality improvement. Moreover, since the process of returning to normal daily activities and promoting the economy were gradual, the results showed that air pollution did not rebound immediately after the government called for the “resumption of production and work” and announced the “termination of the emergency response”. Our findings suggest that to achieve a substantial and sustainable improvement in air quality, it is necessary to continuously implement strict emission control routines and take co-control measures for various VOCs precursors of ozone.

Impact of coronavirus-driven reduction in aerosols on precipitation in the western United States

Among the many impacts of COVID-19, the pandemic led to improved air quality conditions in the countries under quarantine due to the shutdown of industries, drastically reduced traffic, and lockdowns. Meanwhile, the western United States, particularly the coastal areas from Washington to California, received much less precipitation than normal during early 2020. Is it possible that this reduction in precipitation was driven by the reduced aerosols due to the coronavirus? Here we show that the reduction in aerosols resulted in higher temperatures (up to ∼0.5 °C) and generally lower snow amounts but cannot explain the observed low precipitation amounts over this region. In addition to an assessment of the effects of the coronavirus-related reduction in aerosols on precipitation across the western United States, our findings also provide basic information on the potential impacts different mitigation efforts aimed at reducing anthropogenic aerosols would have on the regional climate.

Characteristics of Surface Ozone and Nitrogen Oxides over a Typical City in the Yangtze River Delta, China

The Yangtze River Delta (YRD) is the most developed region in China. Influenced by intensive and complex anthropogenic activities, atmospheric pollution in this region is highly variable, and reports are sparse. In this study, a seven-year history of the atmospheric O3 and NOx mixing ratios over a typical city, Hangzhou, was presented to enrich the studies on air pollution in the YRD region. Our results revealed that the diurnal variation in NOx corresponded to traffic rush hours, while O3 was mainly impacted by photochemical reactions in the daytime. The weekend effect was significant for NOx, but inapparent for O3. Two O3 peaks in May and September were caused by seasonal atmospheric stability and climatic conditions. The lower NOx and higher O3 levels observed suggested direct effects from traffic restrictions and large-scale industrial shutdowns during the COVID-19 lockdown in 2020 compared with those in the periods before and after lockdown. The model simulation results showed that O3 mixing ratios were not only related to regional anthropogenic emissions but were impacted by air mass transportation from surrounding provinces and the China shelf seas. The NOx mixing ratios showed a decreasing trend, while the O3 mixing ratios showed the opposite trend from 2015 to 2021, which is indicative of the implementation of the Air Pollution Prevention and Control Acton Plan issued by the Chinese government in 2013.

European Energy Crises, Climate Action and Emerging Market of Carbon-Neutral LNG

Liquified Natural Gas (LNG) has received world-wide attention due to its growing market demands as pointed out by International Energy Agency (IEA), and McKinsey. This article aims to observe contemporary European developments in accordance with the Union’s energy strategy and the Paris Agreement. With the reduction in import of Russian gas, purchasing LNG became an alternative policy option to meet overall energy needs in Europe. European governments and companies are making large investments in land-based regasification terminals and floating storage and regasification units (FSRUs). These trends have fueled hopes that Europe may be able to avoid the worst-case scenario of massive gas shortages, rationing, and industrial shutdowns in the coming months. Nonetheless, such positive short-term developments should not obscure the challenges Europe’s energy-dependent industries are facing due to high gas and electricity prices, which will likely remain elevated for some time. Industries with gas-intensive production or with high absolute demand for gas could still see disruptions during this winter.
 Moreover, this article also evaluates the role of carbon-neutral LNG in European energy crises and its link with eco-friendly processes as set out by the EU and its consequences for the Asian market. The major findings include that the existing carbon measurement framework does not meet the global needs of the LNG industry. Moreover, the breadth of LNG usage is linked to viable GHG emission framework availability.

Common Diagnosis Approach to Three-Class Induction Motor Faults Using Stator Current Feature and Support Vector Machine

Induction motors are becoming crucial components in numerous industries. The daily usage of induction motors creates the demand for proper maintenance and slight fault detection to avoid serious damage to the induction motor and the shutdown of industries. Among the various kinds of faults in induction motors, bearing failures, broken rotor bar failures, and short-circuit insulation failures are the most common. Thus, detection and classification of slight these faults are attracting great attention. There are conventional methods for detecting such faults, such as the vibration method for bearing failure, the self-organizing map in the case of broken rotor bar failure, and motor current signature analysis for short-circuit insulation failure. From an industrial point of view, diagnosis methods that can classify all these major faults are required. However, reports on the detection and classification of slight these faults using common diagnosis methods are scarce. In this paper, all three kinds of notable faults in an induction motor were artificially induced, and diagnoses using motor stator current spectral features and the rotation speed of the motor were performed. The diagnosis was accomplished using an auto-tunable and arbitrary featured support vector machine algorithm. Although the faults were minor, a high accuracy rate was obtained. The capability to classify the faults and the high diagnosis accuracy prove the robustness and high sensitivity of the method, enabling its practical applications in industries.

COVID-19 lockdown-driven changes in the Ganga River ecosystem in response to human perturbations.

We examined 10 subsurface water, 5 benthic water and 19 sediment (02 cm) samples along a 518 km of the middle segment of the Ganga River to assess the possible improvements that resulted from the industrial shutdown during the COVID-19 pandemic. The sites included the main stem river, tributary confluences, and two point sources, one of which releases metal-rich effluents and the other flushes municipal sewage. We found significant declines in the carbon, nutrient and metal concentrations in both the water and sediment. Even the most polluted zones did not show hypoxia (dissolve oxygen; DO < 2.0 mg L−1) that had been observed in the previous year. Despite a significant decline in carbon and nitrogen as substrates, the activities of extracellular enzymes (EEs), such as β-D-glucosidase, FDAase and protease in sediment (0–2 cm depth), increased significantly (p < 0.05) in response to the declining metal concentrations resulting from the industrial shutdown. We found strong negative correlations between EE activity and the concentrations of metal pollutants measured in 2019, but the correlations between these variables appeared poor in 2020 (lockdown period). Also, we found large variances (low stability coefficients) during the period of strong anthropogenic effects (2019). The study indicates that industrial sources are important contributors of metal pollution in the Ganga River and has relevance exploring river ecosystem recovery windows for management decisions.

Spatial variation of tropospheric NO2 concentration during first wave CoVID-19 induced lockdown estimated from Sentinel-5 Precursor

CoVID-19 pandemic has forced many countries to shut down their industries as most of these countries observed complete statewide lockdown during the first wave of this contagious virus. Factories and vehicles on the road are a major source of nitrogen dioxide (NO2 ), which is also one of the major air pollutants. The emission of NO₂ is considered as a good indicator of prevalant global economic activities as its predominant corollary affairs typically involve industrial oprtaions and these emissions are evidently visible from space. Sentinel-5 Precursor (launched in July 2018), equipped with spectrometer Tropomoi (Tropospheric Monitoring Instrument), is a low-earth-orbit atmosphere mission satellite dedicated towards monitoring air pollution sensing remotely. This study is focused primarily on, estimation and variation of NO2 emission over different parts of the world, before and during the first wave of CoVID-19 epidemic (07 weeks duration). It is found that in most of the countries during the lockdown period (7 weeks), air quality was cleaner by about 40 to 50 % over the last year, mainly due to the shutdown of industry and traffic activities. The technology is quite promising and provides a tool to access if a country or place followed complete lockdown.

Air quality status before, during and after the pandemic COVID-19 Movement Control Order (MCO) at urban and suburban areas in Malaysia

Abstract A severe acute respiratory syndrome, COVID-19 outbreak started in December 2019 reported in the city of Wuhan, China has spread rapidly in other countries around the world. Declared as a pandemic, the lockdowns, industrial shutdowns, closing international borders and overall reduced mobility of the population either for tourism or work commutes have led to air pollution reduction. The lockdown implemented worldwide including Malaysia has come as a respite to the environment, especially in air pollutant levels. Utilizing the Air Pollutant Index (API) data recorded on an hourly basis throughout different series of national lockdown phases, this study is undertaken to evaluate the air quality status before, during and after the implementation of MCO by comparing the selected urban and suburban areas in Malaysia. Six (6) locations including Bandaraya Melaka, Cheras and Alor Setar (urban) and Seri Manjung, Kangar and Kuantan (suburban) were chosen in this study. The result revealed that the air quality has shown improvements after a further extension of lockdown days at both urban (API 36.3-61.5%) and suburban areas (API 46.5-48.6%). It has indirectly changed the air quality status from ‘moderate’ to ‘good’ in all 6 urban and suburban areas. The air quality trends, however, gradually deteriorate and has increased as more restrictions were eased at a later stage. The implementation of lockdown measures not only restricted the spread of infection rate but has reduced ambient air pollutants levels that lead to enhanced air quality. The results obtained in this study can be a useful insight for the regulatory agencies in controlling air pollution and restore the environment quality.

Global impact of COVID-19 on agriculture: role of sustainable agriculture and digital farming.

The rise and spread of the coronavirus pandemic (COVID-19) has created an imbalance in all sectors worldwide, massively disrupting the global economy. Social distancing, quarantine regulations, and strict travel restrictions have led to a major reduction in the workforce and loss of jobs across all industrial sectors. One of the sectors completely exposed was the agriculture and food sector. The initiation of a nationwide lockdown by the government resulted in the shutdown of industries globally impacting the overall supply chain from farmer to consumer. The need of the hour is to propose effective solutions which can serve the dual purpose of market growth as well as customer satisfaction. This paper reviews the impact of COVID-19 on the agro-food system and its economy stressing critical factors like food production, demand, price hikes, security, and supply chain resilience. To conserve natural resources and meet the sustainable development goals (SDG), importance has been given to adopting sustainable agricultural practices with a prime focus on techniques like urban agriculture, crop rotation, hydroponics, and family farming. Possible advancements like the use of digital tools, mainly artificial intelligence, machine learning, deep learning, and block-chain technology, in the agro-food sector have been discussed as they could be a promising tool to develop a self-reliant society. This work would be a perfect platform to understand the growing impact of the pandemic as well as supporting cost-effective solutions for a green ecosystem.

Nature Bounce Back: Impacts of Novel Covid-19 Pandemic on Environmental Pollution and Biodiversity

The outbreak of the novel coronavirus infection, COVID-19 was initiated from the seafood market in Wuhan city of China in December 2019 and within a couple of months it turned out to be a pandemic and global health emergency. Due to increased human activity, transportation, industrialization and urbanization create a detrimental effect on the global environment in terms of air pollution, water pollution, noise pollution, soil pollution, climate change, ozone layer depletion and change of biodiversity and ecosystem. The reduction of air pollution was strongly associated with travel restrictions and industrial shutdown during this pandemic so that on average, the air quality index (AQI) and five air pollutants (PM2.5, PM10, NO2, aerosol and carbon emissions) have decreased. During the ongoing lockdown, nature has started to revive itself. Rare birds and animals have starting to come out of hiding. People residing near Yamuna River in Delhi, India say that the water is cleaner due to the lockdown. The dip in air pollution is leading to clearer skies and migratory birds can fly freely without human interference or threat. It all seems like nature is taking a breath of fresh air with the lack of human activity. The present study discusses the indirect impact of covid-19 pandemic on environment and nature. It also describes the behavioral changes of arial, aquatic and terrestrial life during the lockdown period.

The dynamics of the first wave of COVID-19 on environment and wildlife– a boon or a bane?

Even though COVID-19 has drastically weighed upon the humankind, still there is a “silver lining” to see in this dark time. Amidst of this pandemic, most of the human activities were restricted to break the chain of infection which resulted the remarkable change in nature. It has been reported that due to halt in air travel, reduction in the use of fossil fuels, way less functioning of vehicles, shutdown of industries has complied the change in air pollution levels and also change in river water quality. Reports also showed the reduction in particulate matter (PM 2.5 and PM 10), greenhouse gases emissions, massive improvement in the Air quality index (AQI), reduction in the NOX and SOX’s level has clearly stipulated that nature has got it’s time to “revive”. Even the global carbon emission has reported to reduced reluctantly which is expected to be the biggest such drop since World War II. Despite conducting water-cleansing projects and spending a lot of money, the situation of the water bodies were far better now during first lockdown. Moreover, migration and breeding of the birds and animals have been reported to be restored to normal pattern due to depletion in man-animal conflict. Apart from the positive, negative impacts on the nature are also being experienced. Our review work is highlighting such impacts witnessed during the first wave of COVID-19, like, the significant improvement in air and water quality, reduction in environmental noise, therefore an in turn cleaner and quieter habitat for the wildlife to mate and also to quench their curiosities by their surprising excursions; but there are also some negative aspects as well, like reduction in recycling and the increase in waste, increased poaching and even lone shuttering of zoo animals.

The Impacts on Greenhouse Gases Emission during the COVID-19 lockdown in the US: An Economic Input-Output Life Cycle Assessment

The SARS-CoV-2 virus pandemic (COVID-19) is causing disruptions to energy, finance, tourism, and trade industries all around the world. These disruptions are the result of quarantining and lockdowns that cause reductions in production and consumptions. This change in production and consumption rates has environmental consequences. This study investigates the environmental effects of COVID-19 lockdown in the United States by Input-Output Life Cycle Assessment (IO-LCA) approach. The analysis is based on extraction of economic data in the US. The simulated results are based on different durations and strategies of lockdown measures. Among all industrial categories, utilities, which include power generation and supply, water supply, and natural gas supply sectors, saw the most significant reductions by approximately 110 kt CO2-eq in the first quarter and 265 kt CO2-eq in the second quarter of 2020. The assessed reductions were the results of both direct emission reductions caused by the shutdown of certain industries and also indirect emission reductions from upstream industries. The proposed methodology provides an effective guideline to predict the greenhouse gases emissions, which can be used as a prediction method for different regions in the world.

Contributions of Traffic and Industrial Emission Reductions to the Air Quality Improvement after the Lockdown of Wuhan and Neighboring Cities Due to COVID-19.

Wuhan was locked down from 23 January to 8 April 2020 to prevent the spread of the novel coronavirus disease 2019 (COVID-19). Both public and private transportation in Wuhan and its neighboring cities in Hubei Province were suspended or restricted, and the manufacturing industry was partially shut down. This study collected and investigated ground monitoring data to prove that the lockdowns of the cities had significant influences on the air quality in Wuhan. The WRF-CMAQ (Weather Research and Forecasting-Community Multiscale Air Quality) model was used to evaluate the emission reduction from transportation and industry sectors and associated air quality impact. The results indicate that the reduction in traffic emission was nearly 100% immediately after the lockdown between 23 January and 8 February and that the industrial emission tended to decrease by about 50% during the same period. The industrial emission further deceased after 9 February. Emission reduction from transportation and that from industry was not simultaneous. The results imply that the shutdown of industry contributed significantly more to the pollutant reduction than the restricted transportation.

Family Business, Resilience, and Ethnic Tourism in Yunnan, China

The expansion in commodification through tourism and the transformation of communities and heritages into destination attributes have become the centre of tourism research facing the COVID-19 crisis. Since small family businesses comprise the majority of the tourism industry, theories and practices on surviving the crisis are urgently required. This research attempts to clarify the level of business resilience during the COVID-19 lock down when business can only be conducted at home with very few visitors. It provides insights on family businesses in Yunnan, China, moving ahead with ethnic tourism against the lockdown and shutdown of tourism industry. Data were collected through in-depth interviews. The researchers invited previous research respondents who agreed to continue for online interviews. Eight interviewees were selected by purposive sampling. Although the COVID-19 crisis was unexpected, external shocks need to be taken into account for business planning. Tourism will not necessarily grow massively in the total number of visitors as the destinations have become saturated. The diversification of a tourism business facilitates the resilience of the firm by venturing into other areas of practice, including taking advantage of online platforms in selling local food and herbs, live broadcasting the local flora and fauna, teaching school children in making the traditional pickles, and other business extensions from tourism. Businesses are working together with other stakeholders in the effort of overcoming the COVID-19 crisis. Previous visitors from not only China but also overseas, who have kept in touch with the hosts in Yunnan, are becoming part of the supporting team for the business. However, there appears to be a lack of coordination in the community when businesses are isolated. There is a call for skills in using technology for online business, complementarity in the community, and policy support in the ethnic family businesses. Small family businesses in ethnic Yunnan are actively adapting and progressing despite the odds. They are resilient in times of crisis, with a strong presence of entrepreneurship, diversification of activities, re-organising resources, and digital literacy. The research sheds light on how community-based small family businesses surviving the crisis through resilience, entrepreneurship, and celebrating their ethnic cultures in tourism. Small-scale tourism closely linked with the community, family, and people may provide more promising prospects for tourism.

Effect of COVID-19 pandemic-induced lockdown (general holiday) on air quality of Dhaka City.

A worldwide pandemic of COVID-19 has forced the Government of Bangladesh to implement a lockdown during April–May 2020 by restricting people’s movement; shutdown of industries and motor vehicles; and closing markets, public places, and schools to contain the virus. This type of strict measures caused an outcome, the reduction of urban air pollution, around the world. The present study aims to investigate the reduction of the concentration of pollutants in the air of Dhaka City and the reduction of the Air Quality Index (AQI). Necessary time-series data of the concentration of PM2.5, NO2, SO2, and CO have been collected from the archive of the Air Quality Monitoring Station of the US Embassy in Dhaka and Sentinel-5P. The time-series data have been analyzed by descriptive statistics, and AQI was calculated following an appropriate formula suggested by the Environmental Protection Agency (EPA) based on the criteria pollutants. The study found that the concentrations of PM2.5, NO2, SO2, and CO during April–May 2020 have been reduced by 26, 30, 07, and 07%, respectively, compared with the preceding year’s concentrations. Moreover, the AQI has also been reduced by about 35% on average during the lockdown period than the same times of the previous year. However, the magnitude of pollution reduction in Dhaka is lower than in other cities and countries globally, including Delhi, Sao Paulo, Wuhan, Spain, Italy, the USA. The main reasons may include, among others, the poor implementation of lockdown (especially in the first week of April and the second fortnight of May), pre-existing pollution, transboundary pollution, incineration of solid waste, etc. This study will help policymakers figure out how to regulate pollution sources and improve the air quality of Dhaka.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10661-021-09120-z.

COVID-19 lockdown impacts on heavy metals and microbes in shallow groundwater and expected health risks in an industrial city of South India

In this investigation, the positive impact of COVID-19 lockdown on heavy metals concentration and biological parameters in the shallow groundwater samples of Coimbatore city of South India was ascertained. The groundwater samples (n=15) were obtained from shallow open wells during before lockdown (24–25 February 2020) and after lockdown (2–3 June 2020) periods. These samples were analysed for heavy metals (Fe, Mn, Ni, Cr and Pb) and biological parameters (E. coli, Fecal coliforms, Fecal streptococci and Total coliforms). Fe concentration was within the permissible limit but, the concentrations of Mn, Ni, Cr and Pb were above the allowable limits for drinking uses as per the WHO. However, after lockdown the number of samples crossing the cutoff limit had considerably decreased (Mn: from 2 to 0 mg/L; Ni: from 13 to 10 mg/L; Cr: 7 to 5 mg/L and Pb: from 13 to 8 mg/L). The heavy metal pollution index (HPI) revealed that 176.75 km2 (67.4%) and 85.35 km2 (32.6%) areas fell under unsuitable and very poor categories, respectively, during the pre-lockdown period, whereas 138.23 km2 (52.6%), 118.98 km2 (45.3%) and 4.89 km2 (2.1%) areas fell under very poor, poor and good categories, respectively, during the post-lockdown period. Similarly, Total coliform, Fecal coliform and E. coli had decreased distinctly due to the pandemic lockdown. Therefore, the shutdown of small and large-scale industries during the lockdown period had improved the groundwater quality. The health risk assessment showed that 93%, 87% and 80% of pre-lockdown samples, and 87%, 80% and 73% of post-lockdown samples possessed non-carcinogenic risks (HI > 1) for children, female and male categories, respectively.