Assessment of household water consumption during COVID-19 pandemic: a cross-sectional web-based study in India.

The fatal novel COVID-19 creates precarious threats to humans through speedy diffusion. This virus not only disrupts human health but also makes multidirectional loss and slowdown of modern earth. Almost all countries strictly imposed lockdown and social distancing norms to prevent the infection of COVID-19 virus. In almost all parts of the world, people are using more water for washing, cleaning, bathing and hand washing practices. As a result, per capita water demand along with expenditure have been significantly increased. The principal objective of this study is to evaluate the household level water consumption status and to improve the water security with management for future. The current study has been conducted among the general population of India to assess household level water consumption through internet E-Surveys Google form from August 18 to September 8, 2020. Around 1850 respondents have sent their comments from different sites (rural and urban areas in various climatic regions) of Indian subcontinent. The results show the tremendous increase of water usage along with electrical consumption and expenditure during COVID-19 pandemic situation. Our results revels that 10%, 15% and 17% of higher water consumption per day in rural, urban and peri-urban residential respectively. We hypothesize that the reasons for the increasing water demand and household consumption per day may be found in changed behavioral routines through bathing, washing clothes, and hand washing practices. This web-based study also suggests that few alternative and dependable management techniques i.e. rain water harvesting can be installed to fight the crisis and for the sustainable future. Subsequently, research and development are highly required for long-term management of water resources or reuse of water.

Effects of COVID-19 lockdown and unlock on the health of tropical large river with associated human health risk.

River Damodar (India) is one of the most significant tropical large rivers and this river is carrying predominantly industrial effluents, urban sewage, and non-degradable chemical agricultural fertilizers. Several industries, cities, and townships directly depend on this important river throughout the year. It is highly essential to evaluate its surface water quality, characteristics, and improvement status during the COVID-19 lockdown and unlock phases. The major objectives of the present study are to analyse changing nature of heavy metals (Zn, Cd, Pb, Ni, Cr, and Fe) and microbial load (TVC, TC, and FC) of river water and to identify heavy metals impact on water quality and human health in pre, during, and after unlocking of COVID-19 lockdown. Here, a total of 33 water samples have been collected in the pre-lockdown, lockdown, and unlock phases. The results showed that decreasing trend of the microbial load was found in the lockdown phase. Heavy metal pollution index (HPI) illustrated that all samples are highly polluted (HPI > 150) during the pre-lockdown phase, while during the lockdown phase; HPI showed that around 54.54% of samples have been positively changed (low pollution level). During the unlock phase, 45.45% of samples were again amplified to the high pollution level. Pearson's correlation coefficient and hierarchical cluster analysis indicated strong relation among heavy metals with faecal coliform at a 0.05% level of significance. Noncarcinogenic hazard index (HI) shows the higher possibility of health risk (HI > 1) particularly for children in all the phases and during the lockdown phase, 36.36% of samples showed no possible health risk for adults (HI < 1). However, HI of dermal contact showed no possible health risk for children and adults in the assessment periods. This applied research can definitely assist planners and administrators in making effective solutions regarding public health.

Effects of COVID-19 lockdown and unlock on health of Bhutan-India-Bangladesh trans-boundary rivers

The COVID-19 pandemic significantly destructs the rhythm of global modern human civilization but worldwide lockdown radically recovers the health of the total environment. The Himalayan trans-boundary rivers provide huge provisional, regulatory and cultural ecosystem services to millions of people throughout the year but in the recent years the water quality is being deteriorated due to multiple reasons. In the last decade, India-Bangladesh political relationship has been slightly broken down due to water sharing and environmental flow of rivers.The COVID-19 lockdown offered a great scope to execute the comparative study among pre, lockdown and unlock phase. The research attempts to investigate the spatiotemporal water quality of trans-boundary rivers through WAWQI and irrigation water quality indices such as Sodium absorption ratio, Soluble sodium percentage, Potential salinity, Magnesium hazard and Kelly's index considering eighteen water quality parameters (pH, EC, TDS, TSS, Ca²⁺, Mg²⁺, Na²⁺, K⁺, Fˉ, Clˉ, NO3−, SO₄²ˉ, PO43ˉ, DO, T, TUR, COD and BOD). The result shows the strong positive correlation between EC and TDS during three phases. Significant reduction of BOD, COD and TUR has been noticed almost 70% stations during lockdown compared with prelockdown while augmentation of DO has been recorded around 40% stations. WQI of most of the stations shows around 80% improvement of water quality during lockdown period. Moreover, worst kind of WQI was found in the Mathabhanga-Churni river followed by Mahananda. During lockdown, the striking results show that SAR and MH were significantly amplified in most of the stations due to agricultural run-off.

Positive effects of COVID-19 lockdown on river water quality: evidence from River Damodar, India.

The global economic activities were completely stopped during COVID-19 lockdown and continuous lockdown partially brought some positive effects for the health of the total environment. The multiple industries, cities, towns and rural people are completely depending on large tropical river Damodar (India) but in the last few decades the quality of the river water is being significantly deteriorated. The present study attempts to investigate the river water quality (RWQ) particularly for pre- lockdown, lockdown and unlock period. We considered 20 variables per sample of RWQ data and it was analyzed using novel Modified Water Quality Index (MWQI), Trophic State Index (TSI), Heavy Metal Index (HMI) and Potential Ecological Risk Index (RI). Principal component analysis (PCA) and Pearson's correlation (r) analysis are applied to determine the influencing variables and relationship among the river pollutants. The results show that during lockdown 54.54% samples were brought significantly positive changes applying MWQI. During lockdown, HMI ranged from 33.96 to 117.33 with 27.27% good water quality which shows the low ecological risk of aquatic ecosystem due to low mixing of toxic metals in the river water. Lockdown effects brought river water to oligotrophic/meso-eutrophic condition from eutrophic/hyper-eutrophic stage. Rejuvenation of river health during lockdown offers ample scope to policymakers, administrators and environmentalists for restoration of river health from huge anthropogenic stress.

Variation and dispersal of PM10 and PM2.5 during COVID-19 lockdown over Kolkata metropolitan city, India investigated through HYSPLIT model

The higher concentration of PM10 and PM2.5 in the lower atmosphere is severely harmful for human health and it also makes visibility diminution along with weather and climate modifications. The main objective is to find out the spatiotemporal variation and dispersal of PM10 and PM2.5 along with COVID-19 infection in the dusty city Kolkata. The consecutive two years PM10 and PM2.5 data of different stations have been obtained from State Pollution Control Board, Govt. of West Bengal. Forward trajectory analysis has been done through HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model to find the path and direction of air particles. The result showed that the various meteorological or environmental factors (such as temperature, relative humidity, wind, wind speed, pressure and gusty wind) and geographical location regulate the spatiotemporal variation of PM10 and PM2.5. These factors like high temperature with relative humidity and strong wind influence to disperse the particulate matters from north to south direction from city to outside during summer in Kolkata metropolitan city. During summer (both pre and lockdown years), the height of particles is extended up to 1000 m owing to active atmospheric ventilation whereas in winter it is confined within 100 m. The HYSPLIT model clearly specified that the particles dispersed from south, south-west to north and north east direction due to strong wind. The constant magnification of PM10 and PM2.5 in the lower atmosphere leads to greater frequency of COVID-19 infections and deaths. In Kolkata, the one of the crucial reasons of high infection and deaths (COVID-19) is co-morbidity of people.

Variation and correlation between ultraviolet index and tropospheric ozone during COVID-19 lockdown over megacities of India.

Worldwide spread out of COVID-19 in a short-time has brought a significant decline of road traffic, tourist flow and industrial ventures. During this emergency period, the restricted human dealings with nature have appeared as blessing for health of the total environment. The variation of atmospheric O3 may modulate the range of UV index (UVI) at any region of the earth. The objective of the study is to examine the variation of UV index over the megacities of India with respect to tropospheric O3 level modification during COVID-19 lockdown. The meteorological or environmental data (temperature in °C, gust in km/h, wind speed km/h, relative humidity in %, air pressure in mb and cloud cover in okta) of four selective megacities of India (Kolkata, Chennai, Delhi, Mumbai) during and pre lockdown period have been obtained to comprehend about the variation of UV index and tropospheric O3. The descriptive statistical applications i.e. standard deviation, standard errors and K-means clustering have been done through standard statistical software. In the present study, t-test has been used to understand level of significance of surface O3 and UVI during pre-lockdown (2019) and lockdown (2020) phase. The result shows that the four major megacities in India namely New Delhi, Mumbai, Kolkata and Chennai have experienced the vibrant diminution in terms of the concentration of UV index with slightly increasing the tropospheric O3 level during the lockdown phase. The higher accumulation of O3 during the lockdown in the lower atmosphere of four megacities does not exceed the permissible limit. The excess amount of O3 has remarkably contributed to trap the harmful UV radiation which has lowered the UVI in these worst polluted megacities of India. In the meantime, the prominent reduction of NOx during the lockdown period decreases the titration impact to O3 and this mechanism helps to revitalize the ozone concentration level. The uniqueness of the current study is highlighted the ground reality regarding reduction of UV index and amplification of tropospheric O3 concentration during lockdown phase. This study definitely assists to make new environmental policy, act and law for recover the health of the total environment.

PM2.5 concentration prediction during COVID-19 lockdown over Kolkata metropolitan city, India using MLR and ANN models

Kolkata is the third densely populated city of India and Kolkata stands in the World's 25 most polluted cities along with 10 worse polluted cities in India. The relevant study claims that due to the imposition of lockdown during COVID-19 pandemic, the atmospheric pollution level has been significantly reduced over the metropolitan city Kolkata like other cities of the world. The main objective of this study is to predict the concentration of PM2.5 using multiple linear regression (MLR) and artificial neural network (ANN) models and similarly, to compare the accuracy level of two models. The concentration of PM2.5 data has been obtained from state pollution control board, Govt. of West Bengal and daily meteorological data have been collected from the world weather website. The results show that non-linear artificial neural network model is more rational compared with multiple linear regression model due to its high precision and accuracy level (in respect to RMSE, MAE and R2). In this research artificial neural network (ANN) model exhibited higher accuracy during the training and testing phases (root mean square error (RMSE), mean absolute error (MAE) and R2 indicate 3.74, 1.14 and 0.91 respectively in training phase and 2.55, 4.32 and 0.69 in testing phase respectively). This model (ANN)) can be applied to predict the concentration of PM2.5 during the execution of urban air quality management plan.

Eco-restoration of river water quality during COVID-19 lockdown in the industrial belt of eastern India.

The sudden lockdown recovers the health of the total environment particularly air and water while the country's economic growth and socio-cultural tempo of people have been completely hampered due to the COVID-19 pandemic. Most of the industries within the catchment area of river Damodar have been closed; as a result, significant changes have been reflected throughout the stretch of river Damodar. The main objective of the study is to analyze the impact of lockdown on the water quality of river Damodar. A total of 55 samples was collected from eleven different confluence sites of nallas with the main river channel during and pre-lockdown period. The relevant methods like WQI, TSI, Pearson's correlation coefficient, and "t" test have been applied to evaluate the physical, chemical, and biological status of river water. The result of "t" test indicated that there are significant differences (α = 0.05) of each parameter between pre and during lockdown. Water quality index (WQI) is used for analysis of drinking water quality suitability followed by BIS. The values of WQI showed "very poor" (S1, S2, S3, S6, S7, and S11) to "unfit for drinking" (S4, S5, S8, S9, and S10) of river water during pre-monsoon season. The nutrient enrichment status of the river was analyzed by Trophic State Index (TSI) method and it shows the "High" eutrophic condition with a heavy concentration of algal blooms in almost an entire stretch. During lockdown, nutrient supplies like TN and TP have been reduced and is designated as "Low" (S1, S2) to "Moderate" (S3 to S11) eutrophic condition of middle stretch of Damodar. This research output of river Damodar will definitely assist to policy makers for sustainable environmental management despite the dilemma between development and conservation.

Cleaning the river Damodar (India): impact of COVID-19 lockdown on water quality and future rejuvenation strategies.

Globally, it is established that the partial lockdown system assists to improve the health of the total environment due to inadequate anthropogenic actions in different economic sectors. The ample research on fitness of environment has been proved that the strict imposition of lockdown was the blessings of environment. The river Damodar has historical significance and lifeline for huge population of Jharkhand and West Bengal state of India but in the recent years the water quality has been deteriorated due to untreated industrial effluents and urban sewage. The main objective of this study is to examine the water quality of river Damodar during and prelockdown phase for domestic use and restoration of river ecosystem. A total of eleven (11) effluent discharge sites were selected in prelockdown and during lockdown phase. A new approach of water quality assessment, i.e., water pollution index (WPI) has been applied in this study. WPI is weightage free, unbiased method to analysis of water quality. The result shows that the physical, chemical and heavy elements were found beyond the standard limit in prelockdown period. The cation and anion were arranged in an order of Na2+ > K+ > Ca2+ > Mg2+ and Cl- > So4 - > No3 - > F- in both the sessions. WPI of prelockdown showed that about 100% water samples are of highly polluted. WPI of lockdown period showed that around 90.90% samples improved to 'good quality' and 9.10% of samples are of 'moderately polluted.' Hypothesis testing by 't' test proved that there was a significant difference (ρ = 0.05%) in values of each parameter between two periods. Null hypothesis was rejected and indicated the improvement of river water quality statistically. Spatial mapping using Arc GIS 10.4 interpolation (IDW) helps to understand spatial intensity of pollution load in two periods. This research study should be helpful for further management and spatial diagnosis of water resource of river Damodar.

Significant impacts of COVID-19 lockdown on urban air pollution in Kolkata (India) and amelioration of environmental health.

The fatal novel coronavirus (COVID-19) pandemic disease smashes the normal tempo of global socio-economic and cultural livelihood. Most of the countries impose a lockdown system with social distancing measures to arrest the rapid transmission of this virus into the human body. The objective of this study is to examine the status of air quality during and pre-COVID-19 lockdown and to recommend some long-term sustainable environmental management plan. The pollution data like PM10, PM2.5, O3, SO2, NO2 and CO have been obtained from State Pollution Control Board under Govt. of West Bengal. Similarly, various land surface temperature (LST) maps have been prepared using LANDSAT-8 OLI and LANDSAT-7 ETM + images of USGS. The maps of NO2 and aerosol concentration over Indian subcontinent have been taken from ESA and NASA. The digital thematic maps and diagrams have been depicted by Grapher 13 and Arc GIS 10.3 platforms. The result shows that the pollutants like CO, NO2 and SO2 are significantly decreased, while the average level of O3 has been slightly increased in 2020 during the lockdown due to close-down of all industrial and transport activities. Meanwhile, around 17.5% was the mean reduction of PM10 and PM2.5 during lockdown compared with previous years owing to complete stop of vehicles movement, burning of biomass and dust particles from the construction works. This study recommends some air pollution-tolerant plant species (in urban vacant spaces and roof tops) for long-term cohabitation among environment, society and development.