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Child malnutrition remains a pervasive problem in India though there are significant improvements in several health indicators with country's consistent economic growth. Along with other factors, maternal autonomy is considered to be critical in influencing health outcome of a child. This paper attempts to examine the determinants of nutritional measures of children under age five with the focus to the role of mother's autonomy in India. There are studies which link characteristics of mother, like education, age, with nutrition of her children. But maternal autonomy is a complex subject as this variable is not tangible. Women's autonomy in daily life is more likely to result in their better healthcare which in turn influences children's birth weight and infant nutrition. We used nationally representative India Human Development Survey 2004–05 (IHDS- 1) and 2011–12 (IHDS 2) data for the analysis. This paper studies the association between maternal autonomy and childhood stunting, the indicator of chronic malnutrition, and the risk of having a stunted child. We have also used the panel data using both waves of IHDS and used mothers fixed effect model to evaluate the impact of maternal autonomy. The autonomy index is created using four dimensions-women's decision making, freedom of movement, financial autonomy and attitude toward domestic violence. The two dimensions of autonomy—physical autonomy, financial autonomy—remain significant determinants for childhood stunting. [ABSTRACT FROM AUTHOR]

Forest fire is a major disturbance in mountainous ecosystems across the world. It impacts the composition, functioning, and structure of the forest ecosystem. Demographic pressure and the related climatic factors are thought to exacerbate the danger of forest fires, although there is a lack of statistical data to support this, particularly in South Asian countries with limited historical records. The study looks at how forest fires interact with their causative variables, such as population, topography, vegetation, and climate regimes, in the forests of Northern India. In order to do so, the paper presents a 15-year trend analysis of forest burn scars. This investigation confirmed the utility of principal component analysis using multisource spatial data and correlation matrices. The findings reveal that the occurrence and intensity of forest fires in mountainous locations are influenced by anthropogenic activities, forests near roads and settlements are extremely vulnerable. Based on the analysis, we emphasize the need for restructuring the existing policies like National Action Plan for forest fires and forest fire prevention and management scheme into more practical science-based policies. These findings may be utilized in planning effective fire control processes in time, and the technique provided in this study may be used to discover potential fire-risk zones in other areas. [ABSTRACT FROM AUTHOR]

Modeling surface water quality has become crucial in providing better strategies for managing surface water resources, and adequate findings need accurate and geographically dispersed data. Hydrogeological modeling of these data sets is possible using empirically-based models. The other statistical models are also an alternative approach. In this study, a process with maximum probability is considered with the help of machine learning tools (MLT) to have optimized and valid output. The proposed method combines remote sensing and geographic information systems (RS and GIS) and MLT, which are appropriate for the predicament of neither small, large scale, nor long-term simulations. MLT methods such as VAR and ARIMA are developed in the Python programming with Jupyter notebook and tested according to the data in the spatial prediction for surface water quality parameters such as Tr, pH, Ec, TDS, AL, Ca++, NO−3, So, Cl, F−, Fe, and Mg2+ in the Krishna District, Andhra Pradesh, India—lower delta part. The delta with susceptible zones was identified using RS and GIS as those areas are prone to direct exposure to surface water contaminants from aquaculture, agricultural runoff, small- and medium-scale businesses, and household trash. Achieving effective surface water management for this ecosystem is critical for regional water management. The geographical information about the concentrations acquired via the RS and GIS was compared to the statistical modeling findings and verified using real-time measurements. MLT modeling seems more realistic than the experimental setting; data from the previous 20 years (2000–2020) were used for modeling, and the predicted values presented in the paper are predicted for the year 2021. The computed R2 value of ranges between 0.75 and 0.96% is recorded with ARIMA, and VAR posted range between 0.56 and 0.75% with the trained and tested data. The findings show the potential for MLT of geographically dispersed hydrogeological data to be used for pollution-free surface water management. From the surface water management perspective, combining RS and GIS and MLT offers an alternate data analysis approach for obtaining quick results utilizing a less laborious process that produces acceptable results. [ABSTRACT FROM AUTHOR]

Unexpected and sudden spread of the novel Coronavirus disease (COVID-19) has opened up many scopes for researchers in the fields of biotechnology, health care, educational sectors, agriculture, manufacturing, service sectors, marketing, finance, etc. Hence, the researchers are concerned to study, analyze and predict the impact of infection of COVID-19. The COVID-19 pandemic has affected many fields, particularly the stock markets in the financial sector. In this paper, we have proposed an econometric approach and stochastic approach to analyze the stochastic nature of stock price before and during a COVID-19-specific pandemic period. For our study, we considered the BSE SENSEX INDEX closing pricing data from the Bombay Stock Exchange for the period before and during COVID-19. We have applied the statistical tools, namely descriptive statistics for testing the normal distribution of data, unit root test for testing the stationarity, and GARCH and stochastic model for measuring the risk, also investigated drift and volatility (or diffusion) coefficients of the stock price SDE by using R Environment software and formulated the 95% confidence level bound with the help of 500 times simulations. Finally, the results have been obtained from these methods and simulations are discussed. [ABSTRACT FROM AUTHOR]

Slope instability problems due to widening of roads are very common in mountainous terrains particularly in Indian Himalayan region. Slope instability may occur due to action of different natural as well as anthropogenic activities or through combined action of both. The present paper deals with the slope stability assessment of natural and cut slopes along the Imphal–Moreh section of NH-39 in Manipur state, India. The factor of safety (FoS) for pre- and post-excavations is evaluated, and the FoS with the mitigation measures is examined using limit equilibrium and finite element method. Construction sequences are modeled, and the stability and deformation patterns are evaluated for each construction stage. It is found that about 78% of the slopes is having an angle more than 45° after cutting. The present study suggests that a FoS greater than 1.25 can be achieved by installing a 5.5 m anchor at 18° with the horizontal at a spacing of 1 m. Confirmatory field tests on the anchor are also conducted to ensure the accuracy of the adopted design parameters. This study provides useful informations to researchers and practitioner about the stability assessment of slopes and potential mitigative measures. Similar schemes of mitigative measures are effective for the same/similar geologic conditions in the Indian Himalayan terrain. [ABSTRACT FROM AUTHOR]

The 2030 Agenda for sustainable development was launched to achieve Sustainable Development Goals (SDGs) across the globe. This paper is based on the primary database to assess the nutritional status of 5–10 years children and the incidence of deprivation in their households of a backward district (Purulia), India in the context of the first two SDGs, e.g., no poverty and zero hunger. We conclude that around 74% of children are undernourished. The proportion of households multidimensionally deprived is 90%, and the majority of them live on less than $1.25 a day. Results reveal that the BMI of mother and the education of father are the two most statistically significant predictors of child malnutrition. Purulia has long been witnessing the persistent nature of deprivation, which is well reflected in the child's health. The district is quite far from the national targets in achieving the SDGs. Government, private sector, and civil society must come together to accelerate the progress of SDGs. [ABSTRACT FROM AUTHOR]

Wetlands provide numerous ecological and economic services to mankind. The soils of wetlands are one of the largest sinks of carbon (C) among the terrestrial ecosystems and can play an important role in offsetting the emission of C as a greenhouse gas (GHG) to the atmosphere. India is bestowed with enriched wetland ecosystems that support diverse and unique habitats. The potential of the wetlands in terms of C capture and sequestration has not been quantified. Therefore, in the present paper, an assessment of C capture from different sources and its ultimate deposition in soils leading to sequestration has been done in three different types of wetlands, one created sewage-fed and two natural floodplain oxbow lakes, in the West Bengal state of India. Multiple seasonal sampling of water, macrophytes, and soil was done to assess the primary productivity, dissolved C, and deposition of C in soils of the wetlands in comparison to reference upland sites. All these wetlands are productive ecosystems as indicated by the physicochemical parameters of water and soil. The quantity of C accumulated up to 0.3 m depth in the oxbow lakes was to the tune of 144–166 Mg/ha, which was 3.43–4.78 times higher than that in the corresponding reference upland sites. In the sewage-fed wetland, the C accumulation estimated as 50 Mg/ha was 1.27 times higher than its corresponding upland site. So, the wetland ecosystems, particularly the floodplains, are highly efficient in accumulating C in their soils and thus can somewhat negate the GHG emission. [ABSTRACT FROM AUTHOR]

The state of India was situated on fertile land and river deltas with appropriate agricultural land. In 2019, agricultural fields, primarily cropland, occupy more than 40% of the country's total surface area. Moreover, agricultural industry revenues less than 3% of the country's Gross Provincial Product (GPP). While manufacturing has become the country's major financial activity, accounting countries represent half of GPP's revenues. The objective of the study is to find a way to improve the financial profitability and efficiency of farming supply chain networks as follows: (1) Fixation of national-level targets for zonal-level groups information after assessment and forecasts that affect production and distribution of agriculture. (2) Producers risk can be reduced by directing people to multiple factory and industrialization options based on market assessment. (3) Insurance costs and reduction of bank borrowing by standardizing the connection between bankers and producers using the structure to centralise land information. (4), Stabilize the agricultural sector by looking at nearby potential destinations for production and regulation of the Public Distribution System (PDS) flow for the security stock. In this paper, the novel ML target prediction algorithm to inform the farmers about the market target product and improve the relationships between the farmer and bankers for centralizing the information about recent government plans. The crop prediction ML algorithm proposed to improve the revenue of agriculture field. [ABSTRACT FROM AUTHOR]

Mining and quarrying provide the basic raw materials for sustaining human well-being and are critical for achieving economic developments. At the same time, environmental degradation and its associated social impacts and inequalities have become a grave reality of mining sector that affects all nations, individually and/or collectively. Assessment of the environmental impacts arising from mining and quarrying is critical to limit the environmental problems within the barest minimum levels. Although many impact assessment studies are available on mining/quarrying of different major and minor minerals, not many studies exist on quarrying for laterite blocks which is being widespread in many of the fast developing tropical and sub-tropical regions of the world like India. Therefore, this paper evaluates the impact of laterite quarrying for construction blocks, in one of the twin river basins in SW India, the Netravati–Gurpur river basin, where the activity is widespread. The Rapid Impact Assessment Matrix (RIAM) method was used to evaluate the impacts of laterite quarrying as it allows a comprehensive analysis of the results based on the individual environmental score obtained for each component. RIAM is a valuable assessment tool, owing to its capability in quick, collective and reliable evaluation of the impacts that can aid decision making and minimization of environmental impacts, especially at early planning stages. Data pertaining to resource extraction, identification of impacting actions, mapping of mining hotspots, etc., were collected from primary and secondary sources through systematic field work and sample collection, questionnaire surveys within the local community and other stakeholders such as mine operators, labourers, officials of Government departments, etc. A total of 21 laterite quarries are located in the basin with a total production of 5.7 million laterite bricks/year (0.115 × 106 ty−1). The impact assessment study revealed that the activity not only disturbs the natural environment especially, hydrology, air quality and noise levels, ecology, land use and soil stability but has profound influence on the socio-economic factors of human health and immunity, displacement, etc., of the quarrying-hit areas. The activity also recorded both long-term and short-term positive impacts as a source of employment and income generation. Additionally, the activity favours groundwater replenishment and agriculture productivity of the area where appropriate mine closure measures were taken up. However, the positive impacts of the activity are far outweighed by the fact that most impacts of laterite quarrying are of class − C (moderate negative impact) and − D (significant negative impact) owing to the long-term socio-environmental and bio-ecological implications of the activity. Thus, it is imperative that there is significant improvement in policy and regulatory framework and its implementation for mining and quarrying of building materials which is vital for meeting future development requirements. [ABSTRACT FROM AUTHOR]

Using data from a survey of farm households in the Indian state of Uttar Pradesh and employing a sequential logit model, this paper has investigated the impact of farmers' participation in the Direct Benefit Transfer (DBT) subsidy scheme for micro-irrigation on crop performance. The findings show that over 91% of the farmers were aware of the scheme, 61% of them registered as potential beneficiaries and two-thirds of them actually benefitted from it. Registration is the critical transition stage for participation in the DBT scheme. Our findings show that conditional upon the ownership of tube-wells and water pumping devices, several personal and household-level factors such as age, education, access to information and membership of village-level organizations distinguish the beneficiaries of DBT from the non-beneficiaries. There appears no selection bias in the scheme as neither the farm size nor the social status of potential beneficiaries appeared significant in the sequential selection process. Further, the findings show that controlling for the farm and farmer characteristics, the DBT scheme has a positive and statistically significant impact on crop yield as well as net returns, but more on the latter implying its role in reduction in the cost of production. These findings imply the need to expand DBT scheme for its greater impact on farm income and inclusiveness. [ABSTRACT FROM AUTHOR]

India's 65% population resides in rural regions, making these places the heart and soul of the nation. These regions, along with their residents and houses, serve as a reflection of the nation. Previous researchers have described rural houses in social and humanities literature, but their observations have mostly been descriptive rather than analytical. Therefore, conducting a thorough analytical investigation is necessary to fully understand the mental image that people currently have of rural houses. This study aims to develop a theoretical framework for the typology of rural houses and identify the aspects that contribute to a thorough understanding of housing in rural India. The current state of rural houses must be examined as they are changing from traditional to modern architecture. The research study area was selected, Lakhan Village in the Indian state of Uttar Pradesh. In this village, fieldwork was carried out to determine the types and characteristics of long-established houses. A simple random sampling method was employed to collect the data, and the sample size was determined using the Cochrane formula. The authors' extensive professional first-hand experience in rural houses in Uttar Pradesh integrates with theoretical and analytical analysis in this research. The study sheds light on the development of rural houses in Lakhan Village and highlights several elements that have an impact on a house's overall imageability. It includes recommendations for future growth, gives an in-depth understanding of how rural housing has developed in India, and discusses the reasons that have influenced that development. The study's conclusion highlights the significance of utilizing a holistic strategy to address the challenges with rural housing. The findings of this study will be helpful to researchers, policymakers, and other officials involved in constructing rural houses. [ABSTRACT FROM AUTHOR]

This study aims to analyse the determinants of sustainable consumption behaviour (SCB) of guests in luxury hotels by extending the Theory of Planned Behaviour (TPB). This study adopted a quantitative cross-sectional approach to analyse the determinants of guests' SCB. Data for the study were collected between November 2021 to January 2022 from 298 respondents using Google Forms. The result indicates that the SCB of guests at luxury hotels is predominantly influenced by the guest's attitude towards sustainability. Other significant factors that determine the sustainable consumption behaviour of guests at luxury hotels are perceived cost, perceived benefit, and perceived behavioural control. The study also demonstrates the applicability of TPB and the need for its extension to understand individuals' SCB from the perspective of perceived cost and benefit. [ABSTRACT FROM AUTHOR]

Accurate monthly flow discharge prediction can yield significant evidence for sustainable management of water resources systems, optimal water allocation and use, mitigating flood events, and warning against famine. Inspiration to explore and develop skillful prediction models is a continuing attempt for various hydrologic assessments. The main aim of present study is to explore the potential of novel hybrid PSR-SVM-FFA model (integration of phase space reconstruction with support vector machine and firefly algorithm) and assess its performance against conventional radial basis function network, SVM, and hybrid SVM-FFA to predict flow discharge considering data from four gauge stations of Mahanadi River basin, India. PSR is applied to extract information and characteristics from flow time series and improve accuracy of hybrid SVM-FFA model. For assessing the model's enactment, Nash–Sutcliffe coefficient root-mean-square error and Willmott's Index (WI) indicators are calculated. The results showed that PSR-SVM-FFA model generated improved monthly flow predictions than other applied methods. The result indicates that best values of WI are 0.912–0.929, 0.949–0.956, 0.961–0.967, and 0.98–0.984 for RBFN, SVM, SVM-FFA, and PSR-SVM-FFA, respectively. This demonstrates that PSR-SVM-FFA provides prominent predictions compared to the other three approaches. [ABSTRACT FROM AUTHOR]

Devising effective strategies to retard the negative impacts of extreme climatic events on water security in general and environmental water balance in specific is imperative, especially in semi-arid rural-Western-India, where climate change has markedly increased water scarcity in domestic and agricultural sectors. This exploratory research thus aimed at investigating the water budget against mismanagement of available water resources for remote-marginalized villages in rural-Nashik (West-India). Investigation entailed visual interpretation of LULC analysis (2008–2017) using fine-scale Google Earth imageries, rainfall-runoff analysis using SCS-CN method, determining the supply-demand potential of water storage structures using field-experimentations and PRA tools, and estimation of season-wise water-budget using hydrological (water-balance) equations. Results identified agriculture as the major land-use (~ 78%) followed by hilly regions (~ 16%) and water bodies (~ 3%). Surface runoff was found as the dominating hydrological phenomenon (33–89% of monsoonal rainfall) followed by surface storage (6–36% of annual rainfall) and groundwater flow (4–82% of annual rainfall). Deforestation over hills for firewood, which reduced forest cover by 52%, was observed as the primary concern for soil erosion, thereby siltation of water bodies and higher runoff against percolation. Erratic rainfall patterns (departure range − 42 to 83% during 1998–2017) coupled with sub-graded irrigational systems confined the agricultural practices to one season [South–West monsoon (June–September)]. High unmet drinking water demand (73% to 98%) forced women communities to fetch water by walking 4.5 ± 1.5 km. Considering the urgent response to collectively combat water-budget imbalance, integrated water security plans were proposed using decentralized participatory watershed development approaches. [ABSTRACT FROM AUTHOR]

Flash flood is the most recurrent natural threat in northeastern India, especially during the peak of the monsoon season. In recent decades, the frequency of flash floods has considerably increased in the Himalayan watersheds, causing enormous human suffering, infrastructure damage, ecosystem disruption, and economic losses. Considering the exponential rise in the frequency of flash flood events, identifying the Flash Flood Vulnerable Zones (FFVZs) is one of the most crucial findings to limit their negative consequences. In this study, grey fuzzy analytic hierarchy process-based model integrated with the geographic information system is implemented to assess the flash flood vulnerability in the Ranikhola watershed, East Sikkim, India. Additionally, a novel Flash Flood Vulnerability Index (FFVI) is proposed to determine the flash flood vulnerability that takes into account twelve natural and anthropogenic parameters. Further, the FFVI map is classified into three FFVZs: low, moderate, and high. The effectiveness of the methodology implemented is judged by the high EV value (6.4286) and the comparison parameter. The harshest conclusion of this analysis, the major cities, such as Gangtok, Ranipool, and Singtam, are designated high FFVZ. The sensitivity analysis results show the LULC has the maximum positive influence on high FFVZ. [ABSTRACT FROM AUTHOR]

Monitoring groundwater level provides sufficient information on groundwater quantity and quality and is vital in effective management of water resources. This study applies transfer entropy coupled with directed-weighted complex network for the analysis of groundwater levels in the Sina river-basin, Maharashtra, India. All observation wells present in study area have been classified into five clusters using canopy clustering method. The direction and weight of the links of this complex network have been obtained by employing transfer entropy. Seasonal groundwater level data for pre-monsoon (May) and post-monsoon (October) were obtained from centre for groundwater board, Pune, Maharashtra for the period 1990–2009. Data analysis show that both pre-monsoon and post-monsoon groundwater level show significant decreasing trend. The proposed methodology determines the directional relationships between the selected observation wells of different clusters. It recognizes the most influenced well by using node strength and directed clustering coefficients. For each cluster, clustering coefficients and in-strength and out-strength have been calculated. Clustering coefficients for the selected wells of cluster 0 are 1, 1, 1, 0.6844 and 0.6342 which indicates Cluster 0 emerges as the strongest cluster. Similarly, clustering coefficients for cluster 4 are 0.6604, 0.6540, 0.3095, 0.2616 and 0 which means cluster 4 is the weakest among all the clusters formed. Clustering coefficients obtained for all clusters indicate that all wells within a cluster are forming clusters among themselves, however, some are strong whereas others are weak clusters. Therefore, transfer entropy can be effectively applied to groundwater and results obtained from it can be used for forecasting and water resources management. [ABSTRACT FROM AUTHOR]

India is one of the rapidly urbanizing major economies in the developing world. As it embarks on its urban transition, many small tier-2 cities are already experiencing a large-scale transformation. This study examines the effects of surface urban heat island intensity (SUHI) effect from 2001 to 2020 on a tropical coastal urban complex, Bhubaneswar and Cuttack, a rapidly expanding tier-2 twin city in the Eastern Indian region. Our study reveals a clear discernible annual nighttime SUHI for both Bhubaneswar and Cuttack (0.75 ± 0.08 and 1.22 ± 0.07 °C) with a growth rate of 0.18 ± 0.07 and 0.13 ± 0.07 °C/decade, respectively. Surprisingly, the annual daytime SUHI is weakening for Bhubaneswar. Both night and daytime SUHI showed substantial seasonality with a clear asymmetry during the day and night. Daytime urban cool island effect was observed for Cuttack with Bhubaneswar reporting weak SUHI for daytime during dry seasons. Around the periphery of the cities, the diurnal temperature range (DTR) was found to be the highest. Furthermore, A decrease of 2 °C in the DTR has been reported over the past two decades. The urbanization effect on the local thermal climate of both cities is seen beyond the physical urban limits. Such changes, even in tier-2 cities, have significant potential to modulate local climate and underscore the need for detailed studies in the rapidly urbanizing cities of India and the world to enable disaster resilience, climate-proofing, and sustainability. [ABSTRACT FROM AUTHOR]

Groundwater plays an important part in protecting the ecological values of the earth's systems. Assessment of groundwater (GW) recharge due to change in land use/land cover (LULC) and climate variables is essential for integrated water management and adaptation. This study is an attempt to check the combined influence of change in LULC and climate variables on GW recharge in Kallada river basin, Kerala, India. The LULC map is predicted for the year 2030 based on LULC maps during the years 1985, 1995, 2005 and 2015 using Markov chain and multilayer perceptron model. The major LULC category in the study area is plantation with an area of 797.8 km2 (49.6% in 2015) and dense forest with an area of 366.5 km2 (22.8% in 2015). Considering the period 1985–2005, a decrease of 7.43% dense forest and an increase of 2.55% built area were observed. The predicted LULC shows that there is a reduction in plantation (3.77%) and dense forest (1.28%) and increase in built-up land (4.12%) by 2030 as compared to the year 2015. The CMIP5 General Circulation Model is used for future projections of climate variables, namely daily precipitation, maximum temperature and minimum temperature under RCP 4.5 and RCP 8.5 scenarios. Multilayer perceptron neural network model was used for statistical downscaling of GCM projections. The SWAT model was used to estimate the groundwater recharge for the year 2030 using the predicted LULC map and hydro-meteorological variables. The results illustrate a significant drop in GW recharge in Kallada river basin by the year 2030. Average GW recharge in the Vettikavala and kottarakkara, which is in the western region of the basin, is reduced to 4.6% and 9.3% under RCP 4.5 and RCP 8.5 scenarios, compared to the average GW recharge in 2005, which was 24.8% of rainfall. The decline in the groundwater recharge in the western regions may be due the increase in built-up area and decrease in plantation. The proposed model results provide a reliable insight for water resources planners in conducting future research on groundwater resources. [ABSTRACT FROM AUTHOR]

The increasing concentrations of greenhouse gas emissions in the atmosphere along with the increasing temperatures exacerbate the situation, making it one of the major issues for food security. This research aims to explore the effects of climate change on food production in India. More specifically, this study investigates the impact of temperature, rainfall, CO2, methane, and N2O emissions and energy use on food production using a time spanning from 1990 to 2019 and explores the major critical factors impacting food production in India. The study used autoregressive distributed (ARDL) estimates for long-run and short-run cointegration. The empirical results demonstrated that energy use, rainfall, and methane emissions improve food productivity, whereas temperature and N2O emissions undermine food production in the long run and short run. However, the results revealed that CO2 emissions do not affect food production. Additionally, we used the dynamic ordinal least squared approach to verify the robustness of ARDL results. The results also demonstrate that N2O emissions and temperature are critical determinants of food production, indicating that a rise in temperature and N2O emissions significantly reduces food production in India. On the other hand, the findings show that methane emissions and rainfall significantly increase food production with a coefficient of 0.19 and 0.059, respectively. The most important adaptation strategies that should be considered due to climate change are reducing greenhouse gas emissions, expanding renewable energy investment, and adopting new technologies to combat environmental challenges. [ABSTRACT FROM AUTHOR]

Scientific information on the spatial variability of soil properties is critical for sustainable production and designing appropriate measures for efficient soil–crop management. The growing urban areas in fertile landscapes are a major concern experiencing a huge anthropogenic onslaught and lack of information on spatial variability of soil properties. Therefore, the present study was carried out to delineate the spatial distribution of some selected soil properties from Balh Valley and its catchment area (Suketi basin) in lower Himachal Himalaya, India. A total of 468 geo-referenced surface soil samples were collected and analyzed for soil pH, EC, OC; primary nutrients (N, P, K); secondary nutrients (Ca and Mg); and DTPA-extractable micronutrients (Zn, Fe, Mn and Cu)following standard procedures. The results showed a significant variation in soil pH (acidic to alkaline), EC (0.08–0.70 dS/m), OC (3–26 g/kg), major nutrients N (41.96–208.03 mg/kg), P (5.80–18.75 mg/kg), and K (53.57–163.64 mg/kg). Among micronutrients, Zn was found below the critical limit toward the extreme fringes of the basin. The data were analyzed with descriptive statistics and geostatistical approach. The spatial maps were prepared with ordinary kriging (OK) technique after semivariogram modeling and cross-validation approach. The five principal components (PCs) chosen depicted a moderate correlation between the calculated soil attributes. The two management zones (MZs) were derived by performing the fuzzy c-means clustering analysis based on fuzzy performance index (FPI) and normalized classification entropy (NCE) analysis. The spatial maps represent the distribution of soil properties in the valley and its catchment area. The information generated provides baseline data for site-specific fertilizer recommendations for precision agriculture and minimize downstream adverse environmental impact in the Himalayan ecosystem. [ABSTRACT FROM AUTHOR]

Developing groundwater potential zones (GWPz) is important to determine the realistic groundwater availability scenario and to formulate plans for its optimal utilization to achieve groundwater sustainability. This investigation aimed to delineate GWPz in the Nand Samand Catchment, Rajasthan, India, utilizing an integrated method of remote sensing, geographic information system, and analytical hierarchy process (AHP). The present study used ten thematic layers, viz., lineament density, well recharge, geomorphology, soil, topographic elevation, slope, rainfall, transmissivity, the post-monsoon water level in the well and land use/land cover for the GWPz delineation. The delineated GWPz in the research area were classified as 'good (G),' 'moderate (M),' 'poor (P)' and 'very poor (VP).' Results showed that 'good' GWPz constituted about 21.23% of the catchment area. The southeast area and small patches of the western side of the research area have 'moderate' groundwater potential, covering 53.18% of the total area. Approximately 23.77% area was found with poor GWPz. In the research area, 1.82% area represents very poor groundwater potential. In the present study, the GWPz map was validated using sixteen randomly selected wells yield data (liters per day), and an accuracy of 81.25% was found with the delineated GWPz map. Furthermore, the receiver operating characteristics curve was also used for the validation, indicating a satisfactory accuracy prediction (AUC = 0.889). Validation by both methods justifies the efficiency of the AHP technique for the groundwater potential zoning. Finally, this work establishes a viable method for assessing the potential availability of groundwater, which will be helpful in the future for the planning and managing groundwater resources. [ABSTRACT FROM AUTHOR]

Agricultural practices naturally interject greenhouse gases (GHGs) into the atmosphere; consequently, analyzing decadal variation in N2O, CO2, and CH4 is indispensable over a major rice cultivating area (West Bengal) in subtropical India. Analysis of EDGAR data shows an unremitting increase in GHGs in the study region over two decades. The increasing global warming makes us revisit climate-resilient strategies to mitigate the risk of climate change on paddy production in agrarian economies. However, adapting to these strategies and impact assessment is necessary to comprehend their productiveness and further policy recommendation. Therefore, this study identifies the determinants of adaptation and measures the impact of these strategies on farm performance (yield and net income) and food security of smallholder paddy farmers in India. We used primary data from 612 paddy farmers from 20 villages in the Hooghly district, West Bengal, India. The study used probit regression analysis to identify adaptation constraints and Multinomial Logistic Regression (MLR) to determine the change in the direction and magnitude of the determinants of adaptation strategies. The study also used the Propensity Score Matching (PSM) approach to estimate the causal impact of climate adaptation on paddy yield, net income, and food security. Probit model outcomes identified that education level, cooperative membership, access to extension services, and institutional credit adoption positively and significantly impacted climate change adaptation across smallholders. MLR analysis identified that the direction and magnitude of the discussed determinants changed with different combinations of adaptation choices. The PSM results estimated that adaptation of climate-resilient strategies impacted paddy productivity, net income, and food security positively and significantly. In addition, paddy farmers using a more significant number of climate adaptation strategies experienced better yield, revenue, and food security than those farmers using fewer adaptation strategies. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the quality of irrigation water, assess the ion concentration in irrigation water and their source of origin and irrigation water suitability. For this purpose, water samples from surface and groundwater sources were collected and used to analyzed various physico-chemical properties pH, EC, TDS, TH, Ca2+, Mg2+, Na+, K+, HCO3−, Cl−, SO42− during pre-monsoon, monsoon, and post-monsoon seasons. Quality of irrigation water was evaluated through SAR, RSC, Na%, KR, MHR, PS, PI, RSBC and also calculated the IWQI for appropriateness of the irrigation water. For the evaluation of hydro-geochemical process Piper, Gibbs, correlations and other bivariate plots were used. The spatio-temporal map was also prepared with the use of IDW method by ArcGIS 10.4 software. The surface water was found with Na+ > Mg2+ > Ca2+ > K+ in pre-monsoon, and Na+ > Ca2+ > Mg2+ > K+ in both monsoon and post-monsoon period and groundwater with cation Na+ > Ca2+ > Mg2+ > K+ in pre-monsoon, Ca2+ > Na+ > Mg2+ > K+ in monsoon and Na+ > Mg2+ > Ca2+ > K+ in post-monsoon season. While, anion was dominated with HCO3− > SO42− > Cl− in both surface and groundwater samples during all seasons. The Ca (Mg)- HCO3−type water was found in the study area which was originated through silicate weathering of rock–water interaction, evaporate dissolution, ion exchange phenomena and secondary contribution from anthropogenic activities. The KR, MHR, Na%, RSC, PS and RSBC were reported to exceed limit in few surface and groundwater samples. However, almost 75% surface water samples and 30% groundwater samples were having more risk to use as irrigation water and observed unsuitable for irrigation use based on IWQI. As, results the present study indicated that the surface water was more contaminated than groundwater which was primarily controlled by geogenic process and also associated with anthropogenic sources under recently weathered soil conditions. Thus, the current study suggests safely use of irrigation water with strategic measure and improve the sustainable agriculture production. [ABSTRACT FROM AUTHOR]

This study marks the pioneering use of time-series econometric techniques and methods, including ARDL, FMOLS, and CCR framework, to examine the short-run dynamic and long-run impacts of climatic change and agricultural technologies on wheat production in India. The research covers the period from 1991 to 2018, thereby spanning nearly three decades. To enhance the assessment of factors influencing wheat production, we incorporated agricultural employment, agricultural credit, and cultivated land into the empirical model. By doing so, we aimed to gain a deeper understanding of the influence of fundamental factors on wheat production dynamics during the study period. In addition, the Granger causality test was employed to determine causational direction among the underlying variables. Results indicate that climatological factors such as precipitation pattern and carbon emissions contribute to an increase in wheat production. In addition, the results indicate that advanced technology has considerably contributed to the increase in wheat production. The ARDL method's long-term results were confirmed and validated by econometric techniques including FMOLS and CCR. According to Granger's estimation of causality, the relationship between farm equipment, agricultural labor, and wheat crop yield is bidirectional. The findings regarding causality indicate that climatological factors had a significant impact on wheat production. To mitigate this issue, the government should develop new crop varieties that are well-suited to the agroclimatic conditions. [ABSTRACT FROM AUTHOR]

The hydrologic cycle's fundamental component, evapotranspiration, is a crucial parameter for research on climate, hydrology, and water use in agriculture. Efficient water management in agriculture requires an accurate assessment of reference evapotranspiration (ETo). The Food and Agriculture Organization recommended Penman–Monteith (PM) approach is among the most precise models for computing ETo. Nevertheless, this technique requires a comprehensive climate dataset, typically only accessible at a few meteorological observatories. As a result, estimating ETo using a small climatic dataset may be an alternative for water management aspects. Thus, in the current study, 12 temperature, ten radiation, and seven mass transfer-based models were assessed using 31 years of meteorological data (1990–2020) and compared with the traditional PM approach in the semiarid environment of Central Delhi, India. Moreover, ranking different models in data-limited situations was attempted using multi-criteria decision-making (MCDM) techniques viz.,TOPSIS (technique for order performance by similarity to ideal solution) and entropy. Results showed that the Priestley–Taylor (PRTY) and Blaney–Criddle (BLCD) models were found to be the most appropriate alternatives to the PM model, with Pearson's coefficient of correlation (r) values of 0.93 and 0.96, respectively, and mean absolute percentage error (MAPE) values of 13.30 and 21.11%. According to the performance evaluation indices, the performance of the radiation-based models was superior to that of the temperature and mass transfer models. Nevertheless, this ranking would aid in precisely estimating ETo with minimal data, resulting in efficient irrigation scheduling and water resource management. [ABSTRACT FROM AUTHOR]

Thermal power generation is economical in the current scenario, but it is a water-intensive process, resulting in a high-water footprint. In this research, life cycle water use (LCWU) was assessed for three coal-based thermal power plant in India. The LCWU was found to be in the range of 2.5 to 3.5 L-kWh−1. The results of the LCWU of coal-based thermal power plants in India are higher than the global average of 1.75 L-kWh−1. In order to reduce the dependency on water, air-cooled condenser (ACC) with a novel approach of reducing temperature of air before entering into condenser is purposed using vapour absorption chillers. A 300 MW thermal power plant located in the South India region is chosen to illustrate the application of the proposed system. Initially, waste heat from flue gas is used to run a vapour absorption chiller, and finally a solar-assisted vapour compression chiller is used. Also, in order to utilize large coastal lines in India, an alternate approach of sea water cooling-based thermal power generation is investigated. A 2 MW steam turbine plant utilizing deep sea water is designed and analysed. In seawater cooling system the condenser temperature is reduced, increasing efficiency by 1.9% and power output by 133 kW. It resulted in power generation with multiple benefits, including cooling, desalinated water, and increased plant efficiency. The outcomes of this study provide information on water use in Indian thermal power plants along with its comparative assessment. A study of ACCs and seawater-cooled condensers is also an opportunity to reduce the life-cycle water use in thermal power plants in India. [ABSTRACT FROM AUTHOR]

The world is facing immense pressure due to expanding discourse on resource security. The study is conducted in the water–energy–food (WEF) Nexus context to understand the inter-relatedness of the sectors for sustainable development, eliciting stakeholders' perspectives. Banda District lies in Bundelkhand region of India. It is drought-hit and lacks basic infrastructure and hence has been selected for this research. It is facing challenges stemming from WEF resources insecurity which has triggered mass migration, farmer suicide, unemployment, and indebtedness. In this exploratory research study, nineteen parameters are analyzed using multi-criteria decision analysis and weighted index method to calculate the Stakeholder opinion-based development index (SODI). GIS is used for spatial mapping to characterize the grassroots disparity highlighting the perspective and expectations of the 534 surveyed households. The SODI of Banda District is calculated to be 10.157, which lies in the average category. Most parameters (78.95 percent) fall below the average category, showing that the region is backward and the spatial mapping helps in identifying lacunae in the development of the District. The novelty of this research lies in using the analytical method to examine qualitative parameters that highlight stakeholders' perspectives and usage of unique methodology in formulating the index to study the region holistically for sustainable development. It is concluded with recommendations based on findings using a system-based approach. The modified structural approach of the Stakeholder Opinion-based Development Index and research methodology can be employed for profiling and analyzing the Districts of the same characteristics in and out of India. [ABSTRACT FROM AUTHOR]

In a mountainous basin, flash-flood-induced soil erosion and its assessment are of major concern to the researchers. Cloudburst-induced extreme rainfall, undulating terrain, and inadequate water and soil conservation practices aggravate the problem of soil erosion. Alaknanda, a major basin of the upper Ganges in India, has experienced several incidents of flash floods. These have resulted in heavy soil loss, water siltation, and pollution in the basin. This study uses the revised universal soil-loss equation (RUSLE) in the GIS framework to assess the soil loss rate in various sub-basins of the Alaknanda. Further, the study suggests sub-basin prioritisation based on high soil erosion rate and past vulnerability that need attention of the decision-makers. RUSLE, an empirical soil erosion model, is easy to comprehend physically, involves minimum resources, and works on readily available inputs. The parameters used in the assessment include R-Rainfall Erosivity, Cover Management-C, Topographic-LS, Conservation Practice-P, and Soil Erodibility-K. The average R, K, LS, C & P factors for the Alaknanda basis are estimated as 437 MJ mm/ha/yr., 0.07 t ha h MJ-1 ha-1 mm-1, 1.4, 0.7, and 0.62, respectively. The mean annual soil erosion rate in the sub-basins varies from 6 to 27.9 t /ha/year with a mean rate of 13.4 t/ha/year and total erosion of 13.7 Mt/year. The results show that out of the twelve sub-basins, two (WS7 and WS5) fall in the high erosional class (18–30 t/ha/year), nine fall in the moderate erosional class (7–18 t /ha /year) and one basin in the low erosional class (1.0–7.0 t /ha/year). It is hoped that the present study will be helpful to the decision-makers while prioritising the actions to be taken for the water and soil conservation purposes. [ABSTRACT FROM AUTHOR]

Inland saline water (ISW)-based Penaeus vannamei aquaculture system is an emerging field of fisheries, which came as a magic capsule to boost the overall agri-cum-aquacultural economy of many countries including India. The standardized technology for ISW-based P. vannamei culture includes ameliorating the culture water with K+-ion supplementation and amending Ca++/Mg++ ratio to 1:2–3, so as to simulate the natural seawater (NSW) equivalence, and replicating the NSW-culture parameters in the ISW system. However, for sustained growth and enhanced profitability, there was a need for formulation of ISW-specific culture parameters. In view of this, the present study was undertaken wherein P. vannamei seeds (post-larvae 8) were experimentally reared in ISW ponds with three different stocking densities (30, 45 and 60 PL8/m2) for a period of 75 and 110 days across two culture seasons followed by evaluation of growth and economic performances. Our study revealed highest mean weight (21.21–28.10 g), specific growth rate (8.75–6.22%) and survival percentage (92.93–90.34%) and lowest feed-conversion ratio (1.14–1.21) in the 30/m2 stocking group over the two respective seasons. The lower stocking density group also displayed maximum economic viability, recording benefit–cost ratio of 2.01 and net profit of 2.73 USD/Kg at 110 days. Further, in terms of profit sensitivity it ensures comfortable margins at any uncertain inflationary/deflationary scenarios. Thus, it can be inferred that at 30/m2 stocking density, the ISW-based P. vannamei culture can become a financially viable and sustainable aqua-venture for aspirant farmers, which have the potential to transform salt-degraded wasteland into profit-making asset. [ABSTRACT FROM AUTHOR]

Energy efficiency gains are advocated to be a plausible strategy to mitigate rising carbon emissions in the Indian transportation sector. This study, thus, estimates the energy efficiency across transportation modes in India for 2000–2014, employing the panel stochastic frontier approach. Further, the long-run effect of energy efficiency gains on carbon emissions is also examined by employing the panel fully modified least square (FMOLS) and panel dynamic ordinary least square (DOLS) estimators. The empirical findings indicate an inverted U-shaped trend in energy efficiency for land transportation and a substantial rise for air transportation with higher volatility. However, the trend in energy efficiency for water transportation only shows a minor uptick with nearly stable movement. The long-run effect reveals that a 1% increase in energy efficiency will reduce carbon emissions in the transportation sector by more than 1%, between 1.343 (FMOLS) and 1.665% (DOLS). Based on such findings, a few implications are discussed to achieve a low-carbon energy system. [ABSTRACT FROM AUTHOR]

The Indo-Ganga–Brahmaputra plain is one of the world's most vulnerable areas to catastrophic flood events. The severity and frequency of floods in this region have grown dramatically during the last few decades. As a result, an authentic map providing detailed spatial information on floods is required for reducing future flood disasters. This sort of map can be an invaluable tool for displaying flood-prone areas and determining the magnitude of flood risk. The Ramganga river (~ 200 km length) flowing in the western Gangetic plain was chosen for this investigation. This river is well known for its channel movement and flood hazards. The analytical hierarchy process model in GIS ambiance was used in this work to quantify and map flood risk in the lower Ramganga river basin. Six hazard-forming factors, namely relief, distance from active channel, slope, geomorphology, rainfall, and vegetation, and seven vulnerability factors, namely population density, household density, female density, road density, land use/land cover, female literacy, and total literacy, were chosen to determine flood risk zone (FRZ). According to the findings, about 35.29 per cent of the basin's total area is in a high to very high flood risk zone, where flooding occurs at one- to three-year recurring intervals. The flood risk map has been validated using ground truth data, and the Kappa index has been computed, indicating a high degree of accuracy for the FRZ thematic classes. [ABSTRACT FROM AUTHOR]

This study investigates the demographic, social and economic factors as key determinants of green toilet adoption among rural households in India. The Rural Impact Survey data of the World Bank have been used for this study, covering 2731 rural households from Bihar, Madhya Pradesh, and Uttar Pradesh. The chi-square test and regression analysis with marginal estimate have been used to analyze the data. Result of the analysis indicates that about 36.2 percent surveyed rural households have reported access to green toilets having proper effluent discharge systems as per the environmental norms. Further, there is a significant association between the adoption of green toilets and demographic, social and economic characteristics of rural households. Finally, the regression analysis indicates that a number of demographic, social and economic factors i.e., age, education, income, social category, access to information, access to drinking water, and asset ownership have a significant marginal effect on the adoption of green toilets in rural India. Considering the importance of ensuring total sanitation and commitment under the Sustainable Development Goals (SDGs) of the United Nations for eradicating open defecation for all by 2030 in the country, the results of the study provide useful policy directions for enhancing the adoption of green toilets among the rural households in India. [ABSTRACT FROM AUTHOR]

Irrigation, along with a high-yielding variety of seeds and chemical fertilizer, is a crucial component of contemporary agricultural technology for enhancing yield in a semi-arid agrarian region of Rarh Bengal. The investigation aims to determine the spatio-temporal disparity in irrigation intensity, the source-wise irrigation utilization index (IUI), and the cumulative annual exponential growth rate (CAEGR) of irrigation in the study region from 2009–2010 to 2017–2018 and also tries to find out the link between irrigation intensity (II) and source-wise irrigation utilization (IUI) using Karl Pearson's product-moment correlation coefficient, linear regression analysis, and residual mapping through the Ordinary least squares method. Irrigation intensity is mostly concentrated in the eastern and south-eastern areas, as opposed to the dry, upland western and north-western districts. The district's net irrigated area has a significantly positive CAEGR (+ 3.34); however, at the block level, there is a downward tendency in both the river lift and other irrigated areas. The study also explores a considerable association between the source-wise IUI and II [F (5,16) = 25.341, p < 0.001]. Canal IUI, being the dominant source of surface irrigation, proved to be inevitable for the irrigational development of the entire study domain (B = 46.724, t = 7.383, p ≤ 0.001) and (B = 48.202, t = 6.850, p ≤ 0.001), which accounts 72.09% and 80.61% variation in II in both years. Finally, to maintain the sustainability of irrigation, effective management of water has become a concerning issue in this semi-arid region of Rarh Bengal. Therefore, the minor surface irrigation schemes along with the conservation of traditional irrigation and water harvesting systems as an alternative irrigation management approach are becoming increasingly important for future irrigation development. [ABSTRACT FROM AUTHOR]

Agriculture-based livelihoods, dominant in rural areas of developing countries, have been facing the challenges to cope up with climate change and extreme climatic events. Therefore, livelihood analysis along with vulnerability to climate change is an important aspect to address the climate change issues. Present research was contemplated to assess the livelihood status of dominant farm livelihood groups and their vulnerability in both coastal and non-coastal ecosystems of Odisha, an Indian state that suffers from climate-induced natural disasters. It also aimed to delineate livelihood assets determining climatic vulnerability of farm households. Sustainable livelihood framework was followed in analysing differential level of physical, social, human, financial and natural assets covering a random sample of 200 farm households representing three dominant farm livelihood groups, viz. farmers cultivating crops, rearing livestock and farmers occupied with both crop + livestock farming. The farmers under study were the beneficiaries of national innovations in climate-resilient agriculture programme launched by Indian council of agricultural research since 2011. Both crop and livestock farmers belonged to similar level of livelihood with no significant differences. Farmers engaged in crop + livestock farming had overall livelihood status at above average level and social assets contributing highest to it. However, farmers engaged in crop + livestock farming significantly differed from both crop and livestock farmers with livelihood status index values of 51.73 and 62.72 in coastal and non-coastal districts, respectively. The livelihood indicators delineated as determinants of vulnerability of farm households to climate change would help in climate policy advocacy regarding institutional innovations. Climate smart technological and institutional innovations, partnership between the stakeholders and diversified livelihood options provide farm households better resilience to climate change as reflected from lower vulnerability index values in coastal regions. This calls for policy advocacy to designing and deploying climate smart socio-technical innovations bundling in terms of both technological and institutional innovations through good partnership to provide farm households diversified livelihood options and better insulation against the vulnerability to climate change in a specific agro-ecosystem. Government support in terms of financial assistance, subsidies, insurance, extension advisories and adequate institutional infrastructure would enable farmers to adopting climate smart agriculture innovations, building sustainable livelihoods and improving resilience to climate change impacts. [ABSTRACT FROM AUTHOR]

Global warming, threats to humankind as driven by the emissions of different greenhouse gases (GHGs) including carbon dioxide (CO2), is becoming a great concern to deal with the vagaries of climate. Plantation ecotypes with greater carbon(C) sink capability are leading among the potential abatement strategies for sequestration of terrestrial C. The present investigation emphasizes on total C stock and litter C status under 13 years old Swietenia macrophylla (Mahogany) pure plantation in Terai belt of West Bengal, India. Stratified tree technique was adopted to estimate the above ground biomass through non-destructive method whereas quadrate method of sampling was followed for estimating leaf litter. The present investigation showed that the total above ground biomass (AGB) of the plantation was 179.73 Mg ha−1 including 95.02 Mg ha−1 (52.83%) shared by stem and in other hand the branch contributed 55.37 Mg ha−1 (30.81%) and the remaining 29.34 Mg ha−1 (16.32%) by leaves. The below ground (root) biomass (BGB) was assessed to be 53.91 Mg ha−1. The biosphere part recorded C was 109.81 Mg ha−1, comprising the total C of AGB and BGB of 84.47 Mg ha−1 and 25.34 Mg ha−1, respectively. Soil C stock (at 0–60 cm) of 40.36 Mg ha−1 comprised 25.30 Mg ha−1 at 0–20 cm followed by 10.46 Mg ha−1 at 20–40 cm and 4.60 Mg ha−1 at 40–60 cm depth, respectively. The total litter production was 6.92 Mg ha−1 yr−1 in 2016–17 and 8.39 Mg ha−1 yr−1 in 2017–18, respectively. The amount of total C storage of plantation was observed to be 150.17 Mg ha−1, comprising 109.81 Mg ha−1 in biosphere and 40.36 Mg ha−1 in soil. The litter C stock of 3.48 Mg ha−1, was excluded from the ecosystem carbon budgeting (ECB), because it acts as a transitional between lithosphere and biosphere. Conclusively, the mahogany-based plantation is not only remunerative to the farmers but also provisions significant improvement in soil fertility along with C sequestration which deploys a crucial part in the sustainable maintenance of the ecosystem in addition to providing a guideline for ECB of the plantation. [ABSTRACT FROM AUTHOR]

Watersheds are vital dynamic natural systems with varying climatic, hydro-geologic and land-use and land-cover conditions. Hence, the resilience assessment of watersheds is a cumbersome task and imperative for natural resources managers. The study of watershed resilience necessitates a large amount of data, time and process-based modelling approaches. To address this problem, the study put forward a framework for the watershed resilience assessment based on the changes and the signal given by the watershed during the transition from one state to another. Streamflow is considered the key parameter for the assessment of watershed resilience, which is the response of watersheds to hydro-climatic conditions and anthropogenic activities inside the watershed boundary. The proposed framework is demonstrated with the help of watersheds of the Budhabalanga River basin in the Odisha state of India. The study revealed that the flow of the Budhabalanga River is highly influenced by the hydro-climatic conditions as well as land-use and land-cover, which has varied due to various anthropogenic activities. The upstream area of the river basin is found to be more resilient compared to other parts. Further, the streamflow at the three stations, namely Baripada, Manitri and Govindpur, in the Budhabalanga River basin shows potential for critical transition or even possible drift towards a lower resilience condition after 2013. The study illustrates the usefulness of the framework to study watershed resilience where time and availability of data are key issues for studying the resilience of watershed systems through an integrated hydro-climatological and ecosystem model. [ABSTRACT FROM AUTHOR]

Exploring public perception and attitude about environmental issues is essential to promote ecological sustainability. The ecological worldview, as tapped by New Ecological Paradigm (NEP) Scale, depicts an individual's sensitivity toward the environment and further informs their consumption behavior. There is a paucity of research exploring the ecological worldview of Indian consumer segments and their socio-demographic characteristics. In this study, an online cross-sectional survey was conducted on a sample of 1858 Indian adults, and ecological worldview was assessed using NEP Scale. A combination approach of clustering was employed to find consumer segments distinguishable in terms of ecological attitude following dimensional analysis of the NEP Scale using principal component analysis. Socio-demographic predictors of ecological worldview were identified using multiple linear regression. Indian adults endorsed a pro-ecological worldview with a mean NEP score of 3.45. NEP Scale tapped three dimensions of ecological worldview among the Indian sub-sample instead of five, which were "Environmental concern," "Humans over nature," and "Limits of earth." "Ecologically conscious," "Conscious anthropocentric," and "Ecologically sensitive" were three identified segments endorsing facets of ecological worldview to a varying degree. Education, occupation, religion, caste, number of children or adolescents in a family, family type, house location, and residential zone were significant predictors of pro-ecological worldview among Indian adults. Thus, the worldview of Indian adults was inspired by the New Ecological Paradigm. Environmental sustainability must be emphasized from earlier years of education with women in policymaking. Policy framework to promote environmental awareness and ecological sensitivity must consider the socio-demographic characteristics of various population segments. [ABSTRACT FROM AUTHOR]

The livelihood of indigenous people, residing in the forest fringe area of developing countries like India, are primarily dependent on the forest. These forest fringe communities represent the country's poorest people and are the most vulnerable due to their high dependency on natural resources, lack of energy, unemployment, poor quality of life and poor socio-economic conditions. Additionally, climate change and lesser adaptive capacity have further exacerbated their struggle to meet their livelihoods. Thus, alleviating poverty, strengthening adaptive capacity to climate change and improving energy access are interlinked and complementary to each other, forming an energy–poverty–climate nexus. The study attempted to understand and analyse the nexus between poverty, energy access and climate vulnerability of the most impoverished villages of India. The study was conducted in 29 forest fringe villages, spread in Mandla and Hoshangabad districts of the state of Madhya Pradesh, India. The state has the distinction of having the highest forest cover and tribal population in the country. A detailed household survey was conducted to assess poverty, climate vulnerability and energy access of 325 households by using progress out of poverty index (PPI), climate change vulnerability index (CCVI) and energy access index (EAI), respectively. The data were collected through interview sessions with the respondents in the regional language. After computing scores of all indices, correlation, regression and chi-square were applied to test the integration of these three variables to understand the energy–poverty–climate nexus. The study found a nexus between energy access, poverty and climate vulnerability and also identified 14 indicators, which significantly influenced the nexus. These indicators were related to agriculture, energy, income and infrastructure, and education and awareness that together help to form an institutional framework for sustainable development. The framework suggests the formation of a block-level committee for monitoring and evaluation, a district-level committee for mobilizing funds, and a state-level inter-departmental committee for planning and implementation. Furthermore, the analysis on scores of different indices revealed that parameters like economic class, type of livelihood options/occupation and education level of a household may be the appropriate indicators for the selection of households to prioritize the target beneficiaries of programmes and policies related to poverty, energy and climate change in the forest fringe villages of India. Based on this, a site-specific framework was designed to act and prioritize programme implementation to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Sustainable ecosystem is of essence to the river for its survival and maintenance of ecological balance. Gomti river, a groundwater-fed tributary of the Holy Ganges, is the lifeline of the middle Indo-Gangetic Plains. Screening of river pollutants for river cleanup is a challenging task. To this end, 20 km Lucknow stretch of Gomti was sampled at 5 locations for physicochemical–bacteriological analysis. Collected samples were analyzed for pH, TA, turbidity, DO, BOD, TH, COD, TDS, fecal coliform, and E. coli. Analytical instruments AAS and GC-ECD were used for heavy metal and organochlorine pesticide analysis. DO was 3.2 ± 0.3 to 7.4 ± 0.4 (avg 5 ± 1.8) mg/l, BOD was 10.6 ± 0.5 to 41 ± 1.7 (avg 22.9 ± 13.3) mg/l, while COD was 26.6 ± 4.6 to 93.5 ± 4.6 (avg 56 ± 31.3) mg/l. WQI values gradually increased from S1 (56.7) to S5 (181.8) which denotes a significant deterioration of water quality downstream of the river. Cd, Mn, Fe, Pb, and Cr had increment of 64, 18, 12, 6, and 2 fold, respectively, as compared to individual BIS:10500 standards. Among the OCPs, concentrations were in the order: aldrin > pp-DDT > β-HCH > γ-HCH > α-endosulfan > pp-DDE > α-HCH. Statistically strong positive correlation (r > 0.95 at 0.01) was observed among physicochemical parameters. Furthermore, bacterial species Aeromonas salmonicida subsp. Achromogenes, Aeromonas salmonicida strain A527, Aeromonas encheleia strain NCTC12917, and Aeromonas salmonicida strain ATCC33658 were identified by 16S rRNA gene amplification and molecular phylogenetic analysis. The study indicated heavy contamination of the river with organic and inorganic pollutants owing to mixing of untreated sewage, industrial effluents, and associated toxicants along with pathogenic bacteria which are a barrier to the harmony of aquatic life. [ABSTRACT FROM AUTHOR]

In the recent era of globalization and climatic uncertainties, farmers are continuously adopting new strategies and crops to ensure substantial production and income. However, these adaptations always need to be based on systematic decisions; otherwise, the entire environment may degrade. The present study is one of such attempts to understand where to adopt an emerging crop (Maize) in lower Gangetic West Bengal. The decision on suitable sites was taken based on the analysis of fourteen important indicators in a GIS integrated fuzzy-MCE environment aided with different geostatistical interpolation models. The output shows that 18 and 30% of the total agricultural area of the study region is highly suitable and suitable for Maize cultivation following the FAO-based suitability classification arena. Spatially, it can be said that the farmers from a few blocks of the study area, namely Chanchal-I, II, Harishchandrapur I, II, Lalgola, Bamangola, Ratua-I, II, Suti, Burwan, etc., can ensure a sustainable profit by adopting Maize cultivation. [ABSTRACT FROM AUTHOR]

In India, ethanol is recognised as a fuel for its potential to provide environmental and energy security-related benefits to the country. So, an Ethanol Blending Programme (EBP) has been initiated by the Government of India to harvest the benefits of ethanol. However, India has consistently failed to achieve the blending target, which indicates the necessity to recognise the barriers and drivers of the programme. In this present study, an integrated methodology has been proposed based on a hybrid Delphi-PESTEL (political, economic, social, technological, environmental, and legal) and Fuzzy-AHP (Analytic Hierarchy Process) analysis to identify and prioritise the barriers and drivers associated with the Indian ethanol blending programme. 25 PESTEL indicators have been identified, quantified, and ranked according to the opinion of the experts using the Fuzzy-AHP analysis. Further, the sensitivity of the Fuzzy-AHP result has been checked. The study shows that "Insufficient infrastructure" is the most significant barrier for the EBP while "Energy security of the country" is the most crucial driver of the programme. The present study is expected to help policymakers achieve the ethanol blending target. [ABSTRACT FROM AUTHOR]