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1.
Remote Sensing ; 13(21):4395, 2021.
Article in English | MDPI | ID: covidwho-1488700

ABSTRACT

An urban ecosystem’s ecological structure and functions can be assessed through Urban Surface Ecological Status (USES). USES are affected by human activities and environmental processes. The mapping of USESs are crucial for urban environmental sustainability, particularly in developing countries such as India. The COVID-19 pandemic caused unprecedented negative impacts on socio-economic domains;however, there was a reduction in human pressures on the environment. This study aims to assess the effects of lockdown on the USES in the Kolkata Metropolitan Area (KMA), India, during different lockdown phases (phases I, II and III). The land surface temperature (LST), normalized difference vegetation index (NDVI), and wetness and normalized difference soil index (NDSI) were assessed. The USES was developed by combining all of the biophysical parameters using Principal Component Analysis (PCA). The results showed that there was a substantial USES spatial variability in KMA. During lockdown phase III, the USES in fair and poor sustainability areas decreased from 29% (2019) to 24% (2020), and from 33% (2019) to 25% (2020), respectively. Overall, the areas under poor USES decreased from 30% to 25% during lockdown periods. Our results also showed that the USES mean value was 0.49 in 2019but reached 0.34 during the lockdown period (a decrease of more than 30%). The poor USES area was mainly concentrated in built-up areas (with high LST and NDSI), compared to the rural fringe areas of KMA (high NDVI and wetness). The mapping of USES are crucial in different biophysical environmental conditions, and they can be very helpful for the assessment of urban sustainability.

2.
Int J Disaster Risk Reduct ; 65: 102553, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1401502

ABSTRACT

UN-Habitat identified the present COVID-19 pandemic as 'city-centric'. In India, more than 50% of the total cases were documented in megacities and million-plus cities. The slums of cities are the most vulnerable due to its unhygienic environment and high population density that requires an urgent implementation of public healthcare measures. This study aims to examine habitat vulnerability in slum areas to COVID-19 in India using principal component analysis and Fuzzy AHP based technique to develop slum vulnerability index to COVID-19 (SVIcovid-19). Four slum vulnerability groups (i.e. principal components) were retained with eigen-values greater than 1 based on Kaiser criterion - poor slum household status; lack of social distance maintenance; high concentrations of slum population and towns and mobility of the households. This study also mapped composite SVIcovid-19 on the basis of PCA and Fuzzy AHP method at the state level for a better understanding of spatial variations. The result shows that slums located in the eastern and central parts of India (particularly Uttar Pradesh, Bihar, Jharkhand, Odisha, West Bengal) were more vulnerable to COVID-19 transmission due to lack of availability as well as accessibility to the basic services and amenities to slum dwellers. Thus, the findings of the study may not only help to understand the habitat vulnerability in slum areas to COVID-19 but it will also teach a lesson to implement effective policies for enhancing the quality of slum households (HHs) and to reduce the health risk from any infectious disease in future.

3.
Urban Clim ; 39: 100944, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1347845

ABSTRACT

Present study aims to examine the impact of lockdown on spatio-temporal concentration of PM2.5 and PM10 - categorized and recorded based on its levels during pre-lockdown, lockdown and unlock phases while noting the relationship of these levels with meteorological parameters (temperature, wind speed, relative humidity, rainfall, pressure, sun hour and cloud cover) in Delhi. To aid the study, a comparison was made with the last two years (2018 to 2019), covering the same periods of pre-lockdown, lockdown and unlock phases of 2020. Correlation analysis, linear regression (LR) was used to examine the impact of meteorological parameters on particulate matter (PM) concentrations in Delhi, India. The findings showed that (i) substantial decline of PM concentration in Delhi during lockdown period, (ii) there were substantial seasonal variation of particulate matter concentration in city and (iii) meteorological parameters have close associations with PM concentrations. The findings will help planners and policy makers to understand the impact of air pollutants and meteorological parameters on infectious disease and to adopt effective strategies for future.

4.
ISBT Sci Ser ; 2021 Jun 01.
Article in English | MEDLINE | ID: covidwho-1297953

ABSTRACT

BACKGROUND AND OBJECTIVES: The COVID-19 pandemic has spread across 87 million people with more than 1·8 million deaths in the world. As there is no definite treatment modality, the use of convalescent plasma has become increasingly popular worldwide. This study aimed to identify an appropriate strategy of donor recruitment and to evaluate the appropriateness of pre-set plasma donation guidelines. MATERIAL AND METHODS: In this prospective study conducted from May to September 2020, the donors were recruited under the following two circumstances: Group I, patients in the post-COVID-19 follow-up in the clinic, and Group II, patients recovered from COVID-19 recruited through mass and electronic media. A pre-set donor selection criteria and laboratory investigation was designed according to national and international guidelines. Approximately 500 ml of COVID-19 convalescent plasma (CCP) was collected from recovered individuals in each group by two different cell separators. The overall donor's attendance rate, deferral rate, adverse events and donor compliance was analysed and compared between the two groups. RESULTS: There was a significant difference in attendance in relation to registration between the groups (P < 0·0001). Donor deferral was significantly higher in group II compared with group I. The single most frequent cause of donor deferral was low antibody index (P = 0·0001). The total donor adverse event rate in CCP donation was significantly lower compared with routine plateletpheresis procedures. The donor's compliance to blood centre's protocol was satisfactory in both the groups. CONCLUSION: Recruitment of patients in the post-COVID-19 follow-up in the clinic was more effective than the general recruitment through mass and electronic media for convalescence plasma donation in a resource-constrained blood centre.

5.
Environmental Challenges ; : 100096, 2021.
Article in English | ScienceDirect | ID: covidwho-1174219

ABSTRACT

The first incident of COVID-19 case in India was recorded on 30th January, 2020 which turns to 100,000 marks on May 19th and by June 3rd it was over 200,000 active cases and 5,800 deaths. Geographic Information System (GIS) based spatial models can be helpful for better understanding different factors that have triggered COVID-19 spread at district level in India. In the present study, 19 variables were considered that can explain the variability of the disease. Different spatial statistical techniques were used to describe the spatial distribution of COVID-19 and identify significant clusters. Spatial lag and error models (SLM and SEM) were employed to examine spatial dependency, geographical weighted regression (GWR) and multi-scale GWR (MGWR) were employed to examine at local level. The results show that the global models perform poorly in explaining the factors for COVID-19 incidences. MGWR shows the best-fit-model to explain the variables affecting COVID-19 (R2= 0.75) with lowest AICc value. Population density, urbanization and bank facility were found to be most susceptible for COVID-19 cases. These indicate the necessity of effective policies related to social distancing, low mobility. Mapping of different significant variables using MGWR can provide significant insights for policy makers for taking necessary actions.

6.
Urban Climate ; : 100821, 2021.
Article in English | ScienceDirect | ID: covidwho-1127053

ABSTRACT

Air pollution in India during COVID-19 lockdown, which imposed on 25th March to 31st May 2020, has brought a significant improvement in air quality. The present paper mainly focuses on the scenario of air pollution level (PM2.5, PM10, SO2, NO2 and O3) across 57 urban agglomerations (UAs) of India during lockdown. For analysis, India has been divided into six regions - Northern, Western, Central, Southern, Eastern and North-Eastern. Various spatial statistical modelling of composite air quality index (CAQI) have been utilised to examine the spatial pattern of air pollution level. The result shows that concentration of all air pollutants decreased significantly (except O3) during lockdown. The maximum decrease is the concentration of NO2 (40%) followed by PM2.5 (32%), PM10 (24%) and SO2 (18%). Among 57 UA's, only five - Panipat (1.00), Ghaziabad (0.76), Delhi (0.74), Gurugram (0.72) and Varanasi (0.71) had least improvement in air pollution level considering entire lockdown period. The outcome of this study has an immense scope to understand the regional scenario of air pollution level and to implement effective strategies for environmental sustainability.

8.
Urban Climate ; 35:100758, 2021.
Article in English | ScienceDirect | ID: covidwho-989357

ABSTRACT

COVID-19 pandemic exhibited the entire world two aspects: human threats and environmental restoration. Due to pandemic, the nationwide lockdown in India imposed on 25 March and continued till 31 May 2020 in different phases. Again partial withdrawl of restrictions started from UnlockI (1–30 June 2020) to revive the Indian economy partially. The present research focused to assess impact of lockdown on the concentration of particulate matter (PM2.5) across the ten most polluted cities of Indo-Gangetic Plain of India alongwith incorporation of spatial distribution of PM2.5hotspots. It observed that during lockdown, the average concentration of PM2.5(μg/m3) across the cities decreased from 197 to 79 which is decrease of 60% since pre lockdown. In January 2020, the cities under considerations were in the category of ‘severe’ air quality index (AQI) but from March no cities fall under this category. The hotspot maps showed that in last three years (2017–2019), relatively higher concentration of PM2.5 was observed mostly around Delhi NCR but during same period of 2020 (lockdown and Unlock I), this concentartion decreased substantially. The findings of the study suggest that only by effective policies like short term lockdown, implementation of odd and even number motor vehicles, relocation of polluted industries need to be implemented by central and state governmental authorities to achive environmental sustainability.

9.
Sustain Cities Soc ; 65: 102577, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-894214

ABSTRACT

The emergence of COVID-19 has brought a serious global public health threats especially for most of the cities across the world even in India more than 50 % of the total cases were reported from large ten cities. Kolkata Megacity became one of the major COVID-19 hotspot cities in India. Living environment deprivation is one of the significant risk factor of infectious diseases transmissions like COVID-19. The paper aims to examine the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. COVID-19 hotspot maps were prepared using Getis-Ord-Gi* statistic and index of multiple deprivations (IMD) across the wards were assessed using Geographically Weighted Principal Component Analysis (GWPCA).Five count data regression models such as Poisson regression (PR), negative binomial regression (NBR), hurdle regression (HR), zero-inflated Poisson regression (ZIPR), and zero-inflated negative binomial regression (ZINBR) were used to understand the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. The findings of the study revealed that living environment deprivation was an important determinant of spatial clustering of COVID-19 hotspots in Kolkata megacity and zero-inflated negative binomial regression (ZINBR) better explains this relationship with highest variations (adj. R2: 71.3 %) and lowest BIC and AIC as compared to the others.

10.
Stoch Environ Res Risk Assess ; 35(6): 1301-1317, 2021.
Article in English | MEDLINE | ID: covidwho-885123

ABSTRACT

The outbreak of COVID-19 pandemic has impacted all the aspects of environment. The numbers of COVID-19 cases and deaths are increasing across the globe. In many countries lockdown has been imposed at local, regional as well as national level to combat with this global pandemic that caused the improvement of air quality. In India also lockdown was imposed on 25th March, 2020 and it was further extended in different phases. The lockdown due to outbreak of COVID-19 pandemic has showed substantial reduction of PM2.5 concentrations across the cities of India. The present study aims to assess concentration of PM2.5 across 12 cities located in different spatial segments Indo-Gangetic Plain (IGP). The result showed that there was substantial decrease of PM2.5 concentrations across the cities located in IGP after implementation of lockdown. Before 30 days of lockdown, average PM2.5 across cities was 65.77 µg/m3 that reached to 42.72 µg/m3 during lockdown periods (decreased by 35%). Maximum decrease of PM2.5 concentrations has been documented in Lower Gangetic Plain (LGP) cities (57%) followed by Middle Gangetic Plain (MGP) cities (34%) and Upper Gangetic Plain (UGP) cities (27%) respectively. Among all the cities of IGP, maximum decrease of PM2.5 concentrations was recorded in Kolkata (64%) (LGP) followed by Muzaffarpur (53%) (MGP), Asansol (51%) (LGP), Patna (43%) (MGP) and Varanasi (33%) (MGP).Therefore, this study has an immense potentiality to understand the impact of lockdown on a physical region (Ganga River Basin) and it may be also helpful for planners and policy makers to implement effective measures at regional level to control air pollution.

11.
Sustainability ; 13(12)20200701.
Article in English | WHO COVID, ELSEVIER | ID: covidwho-705343

ABSTRACT

The deadly COVID-19 virus has caused a global pandemic health emergency. This COVID-19 has spread its arms to 200 countries globally and the megacities of the world were particularly affected with a large number of infections and deaths, which is still increasing day by day. On the other hand, the outbreak of COVID-19 has greatly impacted the global environment to regain its health. This study takes four megacities (Mumbai, Delhi, Kolkata, and Chennai) of India for a comprehensive assessment of the dynamicity of environmental quality resulting from the COVID-19 induced lockdown situation. An environmental quality index was formulated using remotely sensed biophysical parameters like Particulate Matters PM10concentration, Land Surface Temperature (LST), Normalized Different Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). Fuzzy-AHP, which is a Multi-Criteria Decision-Making process, has been utilized to derive the weight of the indicators and aggregation. The results showing that COVID-19 induced lockdown in the form of restrictions on human and vehicular movements and decreasing economic activities has improved the overall quality of the environment in the selected Indian cities for a short time span. Overall, the results indicate that lockdown is not only capable of controlling COVID-19 spread, but also helpful in minimizing environmental degradation. The findings of this study can be utilized for assessing and analyzing the impacts of COVID-19 induced lockdown situation on the overall environmental quality of other megacities of the world.

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