Wetland health assessment using DPSI framework: a case study in Kolkata Metropolitan Area.

Wetlands are among the most valuable components of the ecosystem, playing an important role in preventing floods, maintaining the hydrological cycle, protecting against natural hazards, and controlling local weather conditions and ecological restoration. The Kolkata Metropolitan Area (KMA) is considered one of the most ecologically valuable regions in terms of wetland ecosystem, but due to haphazard development and human activities, the wetlands of the city are under constant threat of degradation. Therefore, this study aims to assess the factors responsible for wetland health and their dynamics using Driving Force-Pressure-State-Impact (DPSI) framework. To assess wetland health during 2011-2020, seventeen indicators and four sub-indicators were selected to calculate weights using the analytic hierarchy process (AHP). The results showed that most of the municipalities in the healthy category were in the pressure (P) section in 2011, while fluctuations were observed in the impact (I) section in several wards during 2011-20. The condition section (S) showed the overall change in the water, vegetation, and built-up categories from 2011 to 2020, so the most dominant category was "healthy," followed by "unhealthy" and "poor." The highly significant factors worsening wetland health were population density (B1), road density (B3), per capita wastewater generation (B5), per capita solid waste generation (B7), biological oxygen demand (D1a), dissolved oxygen (D1b), pH (D1c), and total coliform (D1d). The results of the study can help develop sustainable conservation and management of the wetland ecosystem in the KMA urban area and at the global level with similar geographical conditions.

Monitoring built-up area expansion led by industrial transformation in Delhi using geospatial techniques.

Historically, industrialization has been a catalyst for built-up expansion generated by economic growth that transforms a landscape. In India, there is a paucity of exploration into how the economic shift transforms the cityscape. Therefore, the objective of current research work was to monitor built-up growth induced by industrialization using Landsat datasets and registered industry data. The k-means clustering technique was applied for assessing land use/land cover, Shannon entropy for sprawl, and Pearson for correlation between industrial growth and built-up expansion. The results manifest exponential trend in industrialization with 102-year registered industry record along with increase in built-up density from 0.30 in 1989 to 0.69 by 2019 and in the entire Delhi; it rose from 0.16 to 0.39. Furthermore, Shannon entropy confirmed the sprawl and the strong positive correlation was found among built-up of industrial areas and built-up of Delhi and registered industries. The striking chorological change in industrial as well as city's landscape was observed co-occurring with the dynamics of economic reforms. The outcome of current research could be utilized for the sustainable planning of industrial landscape in Delhi and cities with alike geographical conditions.

Wildfire-induced pollution and its short-term impact on COVID-19 cases and mortality in California.

Globally, wildfires have seen remarkable increase in duration and size and have become a health hazard. In addition to vegetation and habitat destruction, rapid release of smoke, dust and gaseous pollutants in the atmosphere contributes to its short and long-term detrimental effects. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has emerged as a public health concern worldwide that primarily target lungs and respiratory tract, akin to air pollutants. Studies from our lab and others have demonstrated association between air pollution and COVID-19 infection and mortality rates. However, current knowledge on the impact of wildfire-mediated sudden outburst of air pollutants on COVID-19 is limited. In this study, we examined the association of air pollutants and COVID-19 during wildfires burned during August-October 2020 in California, United States. We observed an increase in the tropospheric pollutants including aerosols (particulate matter [PM]), carbon monoxide (CO) and nitrogen dioxide (NO2) by approximately 150%, 100% and 20%, respectively, in 2020 compared to the 2019. Except ozone (O3), similar proportion of increment was noticed during the peak wildfire period (August 16 - September 15, 2020) in the ground PM2.5, CO, and NO2 levels at Fresno, Los Angeles, Sacramento, San Diego and San Francisco, cities with largest active wildfire area. We identified three different spikes in the concentrations of PM2.5, and CO for the cities examined clearly suggesting wildfire-induced surge in air pollution. Fresno and Sacramento showed increment in the ground PM2.5, CO and NO2 levels, while San Diego recorded highest change rate in NO2 levels. Interestingly, we observed a similar pattern of higher COVID-19 cases and mortalities in the cities with adverse air pollution caused by wildfires. These findings provide a logical rationale to strategize public health policies for future impact of COVID-19 on humans residing in geographic locations susceptible to sudden increase in local air pollution.

Analysing the role of gender and place of residence in acceptability and satisfaction towards e-learning among university students' during COVID-19 pandemic in India.

This paper has two broad objectives; the first is to examine the challenges of e-learning faced by the students keeping in view their place of residence and gender in India, particularly during the second-wave of Covid-19. The second objective is to examine the role of place of residence and gender of students in the acceptance and satisfaction towards e-learning. The data has been obtained through an online survey of the students of University of Jamia Millia Islamia, New Delhi, India, in which a total of 490 students participated. Selection of students has been done through stratified sampling technique. Initially the obtained data was analysed and discussed through simple statistical analysis. Later, a chi-square test of independence was applied to find out the dependency of psychological stress, level of acceptance and level of satisfaction towards e-learning on the place of residence and the gender. The major finding of the paper reveals that the gender and the place of residence of the students is significantly associated with their psychological stress, acceptance and satisfaction towards e-learning. Extra money spent on the purchase of online learning resources was greater in case of rural students.

Spatio-temporal analysis of air quality and its relationship with major COVID-19 hotspot places in India.

The COVID-19 pandemic spread worldwide, such as wind, with more than 400,000 documented cases as of March 24th, 2020. In this regard, strict lockdown measures were imposed in India on the same date to stop virus spread. Thereafter, various lockdown impacts were observed, and one of the immediate effects was a reduction in air pollution levels across the world and in India as well. In this study, we have observed approximately 40% reduction in air quality index (AQI) during one month of lockdown in India. The detailed investigations were performed for 14 major hotspot places where the COVID-19 cases were >1000 (as of 1st June 2020) and represents more than 70% associated mortality in India. We assessed the impact of lockdown on different air quality indicators, including ground (PM2.5, PM10, NO2, SO2, O3, and AQI) and tropospheric nitric oxide (NO2) pollutants, through ground monitoring stations and Sentinel-5 satellite datasets respectively. The highest reductions were noticed in NO2 (-48.68%), PM2.5 (-34.84%) and PM10 (-33.89%) air pollutant (unit in µg/m3) post-lockdown. Moreover, tropospheric NO2 (mol/m2) concentrations were also improved over Delhi, Mumbai, Kolkata, Thane, and Ahmedabad metro cities. We found strong positive correlation of COVID-19 mortality with PM10 (R2 = 0.145; r = 0.38) and AQI (R2 = 0.17; r = 0.412) pollutant indicators that significantly improved next time point. The correlation finding suggests that long-term bad air quality may aggravate the clinical symptoms of the disease.

Improved air quality and associated mortalities in India under COVID-19 lockdown.

India enforced stringent lockdown measures on March 24, 2020 to mitigate the spread of the Severe Acute Respiratory Syndrome Coronovirus-2 (SARS-CoV-2). Here, we examined the impact of lockdown on the air quality index (AQI) [including ambient particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), and ammonia (NH3)] and tropospheric NO2 and O3 densities through Sentinel-5 satellite data approximately 1 d post-lockdown and one month pre-lockdown and post-lockdown. Our findings revealed a marked reduction in the ambient AQI (estimated mean reduction of 17.75% and 20.70%, respectively), tropospheric NO2 density, and land surface temperature (LST) during post-lockdown compared with the pre-lockdown period or corresponding months in 2019, except for a few sites with substantial coal mining and active power plants. We observed a modest increase in the O3 density post-lockdown, thereby indicating improved tropospheric air quality. As a favorable outcome of the COVID-19 lockdown, road accident-related mortalities declined by 72-folds. Cities with poor air quality correlate with higher COVID-19 cases and deaths (r = 0.504 and r = 0.590 for NO2; r = 0.744 and r = 0.435 for AQI). Conversely, low mortality was reported in cities with better air quality. These results show a correlation between the COVID-19 vulnerable regions and AQI hotspots, thereby suggesting that air pollution may exacerbate clinical manifestations of the disease. However, a prolonged lockdown may nullify the beneficial environmental outcomes by adversely affecting socioeconomic and health aspects.