ABSTRACT
Urban green space (UGS) provides multiple cultural ecosystem services (CES) and enhances people's physical and mental well-being. The importance of UGS was more critical during crisis periods such as the COVID-19 pandemic. Recently, UGS has been under severe threats due to rapid urban expansion and climate change. Particularly, the cities in developing countries have experienced a dramatic loss of green spaces due to land use and land cover (LULC) change. This study aims to assess the impact of the COVID-19 pandemic on CES perception obtained from two public UGS, i.e., Subhankar Sishu Uddyan (SSU) and Bandh Road (BR) in English Bazar Urban Agglomeration (EBUA), Eastern India. A survey was performed to assess the valuation of CES, CES obtained from UGS, and the use of CES difference during partial (unlock phases) and after lockdown periods. The non-parametric tests were carried out to understand the significant differences between CES and UGS perceived by the respondents. Explanatory factor analysis was also performed to find the association among CES for each UGS. The results reported substantial variations of UGS use during partial and after lockdown periods. During the after-lockdown period, the UGS mainly were used for social relations (51%), spending time with relatives and friends (25%), spending time with children (11%) in SSU and walking (25%), spending time with relatives and friends (21%), and physical activities (17%) in BR. During the partial lockdown period, a significant difference between SSU and BR was recorded from social relations and health value among all CES. After the full lockdown period, a significant difference was observed in recreation, social relations, health, and aesthetic value. The frequency and duration of UGS use during partial lockdown periods substantially increased. About 12% of the total visitor visited UGS daily after the lockdown, whereas it was 4% during the partial lockdown. The study's findings will assist urban planners and policymakers in understanding the need for UGS to promote the well-being of the citizens.
Subject(s)
COVID-19 , Ecosystem , Child , Humans , Parks, Recreational , Pandemics , Communicable Disease Control , Cities , IndiaABSTRACT
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.
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.
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.
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 with 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.
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.
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.
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.