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The efforts to encourage sustainable development have brought to attention the use of secondary materials in civil engineering applications. Global experimental data suggest that municipal solid waste (MSW) incineration bottom ash (IBA) can potentially replace natural aggregates in field applications. However, IBA is currently disposed in open dumps or sanitary landfills in India. Assessing contaminant leaching from IBA is crucial to ascertain its options for disposal or reuse. The current study analyzes the mineralogy, chemical constituents, organic content, and leaching of contaminants from IBA collected from two incineration plants in Delhi. The study takes into consideration the effect of particle size, liquid-to-solid (L/S) ratio, and pH on contaminant leaching. The experimental results revealed that the leaching concentration of contaminants and organic content of IBA decreases with an increase in particle size. A considerable influence of pH was noted on the leaching of all contaminants except chlorides, sulfates, and antimony. The results further indicate that IBA is suitable for disposal in non-hazardous waste landfills regardless of particle size at its intrinsic pH. However, it is recommended to dispose IBA in monofils as co-disposal with MSW in sanitary landfills can cause the pH of IBA to shift toward the acidic range, which may exacerbate the contaminant leaching from IBA. The comparison of leaching test results with international regulatory standards for reuse demonstrates that using IBA in unbound applications is feasible in paved roads and earthworks subjected to minimal infiltration of water. [ABSTRACT FROM AUTHOR]

Mobile banking liberates people from spatial and temporal constraints and delivers significant convenience but people are still hesitant to use mobile banking. The purpose of this study is to examine the most important factors influencing and impeding consumer adoption of mobile banking. This study uses Unified Theory of Acceptance and Use of Technology (UTAUT) and Technology Readiness (TR) as a theoretical basis and integrates it with cognitive resistance to propose a conceptual model for m-banking adoption in India. Data was collected from 536 mobile banking customers from Delhi/NCR, using convenience sampling and was analysed using structural equation modelling. The findings revealed that the impact of facilitating factors namely, performance expectancy, effort expectance, social influence, optimism and innovativeness on behavioural intention to use m-banking is much more than the impact of inhibiting factors namely, discomfort, insecurity and cognitive resistance and also that behavioral intention has a significant impact on adoption of m-banking. In examining the relationship between facilitating factors and behavioral intention, there is no substantial moderation impact of age groups. However, gender moderated the relationship between effort expectancy and behavioral intention, as well as the relationship between optimism and behavioral intention. This research would help policymakers to understand and overcome the reluctance and barriers of adoption and would result in ensuring more adoption of advanced technological channels. [ABSTRACT FROM AUTHOR]

COVID-19 have significant impact on travel behaviour and greenhouse gases (GHG), especially for the most affected city in India, Mumbai metropolitan region (MMR). The present study attempts to explore the risk on different modes of transportation and GHG emissions (based on change in travel behavior) during peak/non-peak hours in a day by an online/offline survey for commuters in Indian metropolitan cities like MMR, Delhi and Bengaluru. In MMR, the probability of infection in car estimated to be 0.88 and 0.29 during peak and non-peak hour, respectively, considering all windows open. The risk of infection in public transportation system such as in bus (0.307), train (0.521), and metro (0.26) observed to be lower than in private vehicles. Furthermore, impact of COVID-19 on GHG emissions have also been explored considering three scenarios. The GHG emissions have been estimated for base (3.83–16.87 tonne), lockdown (0.22–0.48 tonne) and unlocking (2.13–9.30 tonne) scenarios. It has been observed that emissions are highest during base scenario and lowest during lockdown situation. This study will be a breakthrough in understanding the impact of pandemic on environment and transportation. The study shall help transport planners and decision makers to operate public transport during pandemic like situation such that the modal share of public transportation is always highest. It shall also help in regulating the GHG emissions causing climate change. [ABSTRACT FROM AUTHOR]

Bacterial panicle blight (BPB) caused by Burkholderia glumae (BG) has become significantly more prevalent in the rice-growing regions of North India. Based on virulence screening and in vitro quantification of toxoflavin, the BG strains were classified as hyper- (BG1 and BG3), moderate- (BG2, BG4, BG6, BG8, and BG9), and hypo- (BG5, BG7, and BG10) virulent. Plant inoculation assays with cell-free culture filtrate revealed strains with higher toxoflavin-producing ability had higher virulence. Based on 16S rRNA sequence, 6 isolates from Uttar Pradesh were grouped in clad C1; whereas, clad C2 exhibited 4 isolates, two each from Delhi and Uttar Pradesh. Strain BG1 being the most virulent Indian strain from Uttar Pradesh was further profiled for 11 tox genes. We found all the 11 tox genes present in strain BG1. In toxRABCDE cluster, all tox genes showed high similarity to B. glumae BGR1 except toxB, whereas in toxFGHIJ cluster toxF, toxG, toxH and toxI shared maximum similarity to B. glumae 336gr-1. tox genes of BG1 exhibited homology as well as divergence with B. gladioli. The domain prediction and protein association network analysis indicated the possible involvement of tox genes in the toxoflavin biosynthesis. As per our knowledge, this is the first report in India on characterization of tox genes cluster in B. glumae. Altogether, our study unravels a reliable method for identifying and characterizing B. glumae using tox genes and its relationship with disease production. [ABSTRACT FROM AUTHOR]

Stubble burning is an emerging environmental issue in Northern India, which has severe implications for the air quality of the region. Although stubble burning occurs twice during a year, first during April–May and again in October–November due to paddy burning, the effects are severe during October–November months. This is exacerbated by the role of meteorological parameters and presence of inversion conditions in the atmosphere. The deterioration in the atmospheric quality can be attributed to the emissions from stubble burning which can be perceived from the changes observed in land use land cover (LULC) pattern, fire events, and sources of aerosol and gaseous pollutants. In addition, wind speed and wind direction also play a role in changing the concentration of pollutants and particulate matter over a specified area. The present study has been carried out for the states of Punjab, Haryana, Delhi, and western Uttar Pradesh to study the influence of stubble burning on the aerosol load of this region of Indo-Gangetic Plains (IGP). In this study, the aerosol level, smoke plume characteristics, long-range transport of pollutants, and affected areas during October–November from year 2016 to 2020 were examined over the Indo-Gangetic Plains (Northern India) region by the satellite observations. By MODIS-FIRMS (Moderate Resolution Imaging Spectroradiometer-Fire Information for Resource Management System) observations, it was revealed that there was an increase in stubble burning events with the highest number of events being observed during the year 2016 and then a decrease in the number of events in subsequent years from 2017 to 2020. MODIS observations revealed a strong AOD gradient from west to east. The prevailing north-westerly winds assist the spread of smoke plumes over Northern India during the peak burning season of October to November. The findings of this study might be used to expand on the atmospheric processes that occur over northern India during the post-monsoon season. The pollutant, smoke plume features, and impacted regions of biomass-burning aerosols in this region are critical for weather and climate research, especially given the rising trend in agricultural burning over the previous two decades. [ABSTRACT FROM AUTHOR]

Methane is an important greenhouse gas, which constitutes minimum 90% of automotive grade compressed natural gas (CNG) used in India. The use of CNG as automotive fuel has been implemented in almost all major tier I to tier III cities of the country. Delhi, the capital city of India, has world largest CNG-fuelled public transport system. The cylinders fitted to the CNG-fuelled vehicles are required to be subjected to hydrostatic stretch test every 3 years at Government of India approved CNG cylinder testing stations, as mandated under Rule 35 of Gas Cylinders Rules, 2016. During the testing of cylinders, CNG present in the cylinders are discharged in the atmosphere at the degassing point of CNG testing stations. This study estimates annual methane emissions from the CNG cylinder testing stations of Delhi. The annual average methane emission from the CNG cylinder testing stations of Delhi was found to be 30.8 tons during the year 2019. The uncertainties in the emission estimate are also identified and discussed. [ABSTRACT FROM AUTHOR]

The present study investigates the reduction in nitrogen dioxide (NO2) levels using satellite-based (Sentinel-5P TROPOMI) and ground-based (Central Pollution Control Board) observations of 2020. The lockdown duration, monthly, seasonal and annual changes in NO2 were assessed comparing the similar time period in 2019. The study also examines the role of atmospheric parameters like wind speed, air temperature, relative humidity, solar radiation and atmospheric pressure in altering the monthly and annual values of the pollutant. It was ascertained that there was a mean reduction of ~ 61% (~ 66.5%), ~ 58% (~ 51%) in daily mean NO2 pollution during lockdown phase 1 when compared with similar period of 2019 and pre-lockdown phase in 2020 from ground-based (satellite-based) measurements. April month with ~ 57% (~ 57%), summer season with ~ 48% (~ 32%) decline and an annual reduction of ~ 20% (~ 18%) in tropospheric NO2 values were observed (p < 0.001) compared to similar time periods of 2019. It was assessed that the meteorological parameters remained almost similar during various parts of the year in 2019 and 2020, indicating a negligent role in reducing the values of atmospheric pollution, particularly NO2 in the study area. It was concluded that the halt in anthropogenic activities and associated factors was mainly responsible for the reduced values in the Delhi conglomerate. Similar work can be proposed for other pollutants to holistically describe the pollution scenario as an aftermath of COVID-19-induced lockdown. [ABSTRACT FROM AUTHOR]

Yamuna is one of the main tributaries of the river Ganga and passes through Delhi, the national capital of India. In the last few years, it is considered one of the most polluted rivers of India. We carried out the analysis for the physiochemical and biological conditions of the river Yamuna based on measurements acquired at Palla station, Delhi during 2009–19. For our analysis, we considered various physicochemical and biological parameters (Dissolved Oxygen (DO) Saturation, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Alkalinity, Total Dissolved Solids (TDS), and Total Coliform. The water stats of river Yamuna at Palla station were matched with Water Standards of India, United Nations Economic Commission for Europe (UNECE), and World Health Organization (WHO). Maximum changes are observed in DO saturation and total coliform, while BOD and COD values are also seen higher than the upper limits. Total alkalinity rarely meets the minimum standards. TDS is found to be satisfactory as per the standard limit. The river quality falls under Class D or E (IS2296), Class III or IV (UNECE), and fails to fulfill WHO standards for water. After spending more than 130 million USD for the establishment of a large number of effluent treatment plants, sewage treatment plants, and common effluent treatment plants, increasing discharges of untreated sewage, partially treated industrial effluents and reduced discharge of freshwater from Hathnikund are causing deterioration in water quality and no major improvements are seen in water quality of river Yamuna. [ABSTRACT FROM AUTHOR]

The extreme temperature events are a concern in recent years due to climate variability particularly in India as there is an increase in the temperature intensity, frequency, and duration. This study represents stationary temperature-duration-frequency (TDF) analysis over two mega cities in India Delhi (north) and Bengaluru (south) using the daily maximum temperatures at meteorological stations for the period 1969–2016 observed by India Meteorological Department (IMD).The interannual variability of maximum temperature and the maximum daily recorded value indicates the increasing trend in both the cities. The study investigates the extreme analysis of the maximum temperature using two distributions, i.e., Gumbel's Extreme Value Type 1 (GEVT) and Log Pearson Type III (LPT), for return periods 2, 5, 10, 25, 50, and 100 years at both the locations and the positive temporal trend is observed. The TDF curves were build using annual maximum temperature values for total 8 durations (different days) of 48 years analyzed and results show the increasing trend of maximum temperature at lower duration and high return period values. The TDF is also used for prediction of the maximum temperature for the 2 hottest years in India, i.e., 2012 and 2015, and it is comparable with the observed maximum temperature. Similarly, the predictions for 11 years, i.e. 2006 to 2016, over both the cities are simulated using both the GEVT-I and LPT-III and the models have better potential skill in predicting the extreme maximum temperature. These results can be useful for the sectors like health, energy, agriculture, urban management, and ecology management and can help the policy decision makers and disaster managers in the mitigation and adoption steps to face the extreme temperature disaster at city scale. [ABSTRACT FROM AUTHOR]

Lockdown was imposed by the Indian government in the month of March 2020 as an early precaution to the COVID-19 pandemic which obstructed the socio-economic growth globally. The main aim of this study was to analyse the impact of lockdown (imposed in March and continued in April 2020) on the existing air quality in three megacities of India (Delhi, Mumbai and Kolkata) by assessing the trends of PM10 and NO2 concentrations. A comparison of the percentage reduction in concentrations of lockdown period with respect to same period in year 2019 and pre-lockdown period (February 14–March 24) was made. It was observed from the study that an overall decrease of pollutant concentrations was in the ranges of 30–60% and 52–80% of PM10 and NO2, respectively, in the three cities during lockdown in comparison with previous year and pre-lockdown period. The overall decrease in concentrations of pollutants at urban sites was greater than the background sites. Highest decline in concentrations of PM10 were observed in Kolkata city, followed by Mumbai and Delhi, while decline in NO2 was highest in Mumbai. Results also highlighted that capital city Delhi had the worst air quality amongst three cities, with particulate matter (PM10) being the dominant pollutant. Although COVID-19 has significantly affected the human life considering the mortality and morbidity, lockdowns imposed to control the pandemic had significantly improved the air quality in the selected study locations, although for the short amount of period. [ABSTRACT FROM AUTHOR]

Identification of the most relevant parameters of a sustainable transportation system is regarded as a significant choice that influences the success of policy-related intervention to improve efficiency. A hybrid-based approach has been used to analyze the data in multiple steps to improve accuracy and objectivity. In the first step, evidence on social, economic, and environmental indicators was formed for each opinion and then combined. The second step proposed a mathematical framework to treat indecision on the indicators collected from multiple sources, viz. expert and public opinion survey, models, and actual measurement during pre- and post-implementation stages of the Odd–Even scheme. By setting up, a reliability function and consistency index are used to evaluate and rank the Odd–Even transportation scheme introduced by the Government of Delhi. A case study in South Delhi's surrounding areas has been examined to demonstrate the proposed hybrid approach and evaluate the parameters in terms of the index. The result shows that the indicators like trip cost, trip time, safety and security, user's satisfaction, congestion level, parking demand, and fuel consumption affected positively by 1766.6, 22.9, 283.3, 19.1, 187.5, 200, and 17.2 percent, respectively, after the implementation of the scheme. The overall increase in the index was found as 28.2%, which favors the "Odd–Even" scheme as a sustainable transportation measure in Delhi. [ABSTRACT FROM AUTHOR]

The increasing frequency of heat waves (HW) in many parts of the world is emerging as one of the climatic vulnerabilities across the world resulting in elevated thermal stress and high mortality. With increase in HW intensity, frequency and duration at global level, India has seen several major HW events in the last decade. HW conditions have mostly been studied by analysing ground-based observations; however, this approach lacks information on spatial variability at the local scale, which is not adequate to identify HW risk and vulnerability hotspots. In this study, gridded analysis of spatio-temporal variability of HW indices has been carried out by utilising freely available Moderate Resolution Imaging Spectrometer (MODIS) Land Surface Temperature (LST) data on Google Earth Engine (GEE) platform in the Indo-Gangetic Plains of India. HW indices to analyse duration, frequency and intensity of HW have been identified and further computed on a grid size of 10 km*10 km area. HW risk and vulnerability hotspot in the study region have been identified by spatial modelling of HW indices, LULC change and population density. The HW risk and vulnerability hotspot layer identified NCT Delhi and its surrounding region at the highest risk of HW with high vulnerability. A strong positive correlation of variability of HW indicators with increasing built-up shows that built-up surfaces affect strongly the HW conditions. [ABSTRACT FROM AUTHOR]

A cross-sectional study was conducted among 775 adolescent girls (11-18 years) residing in a slum of Delhi to assess plasma vitamin C levels. The mean (SD) plasma levels of vitamin C were 0.76 (0.45) mg/dL. Overall, 6.3% and 27.6% girls had deficient (<0.2 mg/dL) and suboptimal levels (0.2-0.49 mg/dL) of plasma vitamin C, respectively. [ABSTRACT FROM AUTHOR]