Search

Agro-based pulp and paper mills in India are one of the most polluting industries; in addition, they are high consumers of raw water. Growing scarcity of high quality freshwater as well as stringent regulatory standards is compelling these units to explore appropriate water management options. Based on data obtained through a questionnaire survey and plant visits, this work provides an overview of the water use and effluent treatment status in Indian agro-residue and recycled pulp and paper mills. The challenges faced by this sector are reviewed and practices adopted by progressive units to minimize freshwater use are illustrated through case studies.

In the present study, plant-scale process integration was applied to an Indian paper mill using the water cascade analysis (WCA) technique. Three limiting constraints, chemical oxygen demand (COD), total dissolved solids (TDS), and adsorbable organic halides (AOX), were considered for the study. A nearest neighbor algorithm was used to distribute the freshwater and recycled water among the plant operations. It was found that the limiting critical constraint depends upon the types of processes and streams involved in the integration. The limiting critical constraint can differ for different sections of the same industry, and can differ in different schemes of integration. After process integration, a 55.6% reduction in effluent flow, a 36% reduction in COD, and a 73% reduction in AOX were observed. After process integration, a 35.21% reduction in pollution costs can be achieved and, assuming the average production of the mill to be 225 tons per day, a savings of Indian rupees (INR) 1.73 per kg of paper produced can be achieved by employing process integration. The water cess was calculated as INR 3024.77 per day without integration for the sections that were considered for integration, while after integration, a 41.53% savings in the form of water cess was calculated., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

In the pursuit of understanding surface water quality for sustainable urban management, we created a machine learning modeling framework that utilized Random Forest (RF), Cubist, Extreme Gradient Boosting (XGB), Multivariate Adaptive Regression Splines (MARS), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), and their hybrid stacking ensemble RF (SE-RF), as well as stacking Cubist (SE-Cubist), to predict the distribution of water quality in the Howrah Municipal Corporation (HMC) area in West Bengal, India. Additionally, we employed the ReliefF and Shapley Additive exPlanations (SHAP) methods to elucidate the underlying factors driving water quality. We first estimated the water quality index (WQI) to model seven water quality parameters: total hardness (TH), pH, total dissolved solids (TDS), dissolved oxygen (DO), biochemical oxygen demand (BOD), calcium (Ca), magnesium (Mg). Then six independent factors were utilized (i.e. Precipitation (Pr), Maximum Temperature (Tmax), Minimum Temperature (Tmin), Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and Total Dissolved Solids (TDS)) for predicting the WQI mapping through the different ML models. This study demonstrated that the SE-Cubist model outperforms other ML models. During the testing phase, it achieved the best modeling results with an R 2  = 0.975, RMSE = 0.351, and MAE = 0.197. The ReliefF and SHAP analyses identified Pr and Tmax as the most significant factors influencing WQI within the study area., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Understanding the complex interactions between bacteriophages (phages) and bacteria within varied environmental niches is critical yet underexplored for improving microbe-assisted ecological restoration. This study investigates the influence of microhabitat heterogeneity within an abandoned mine on phage-bacteria interaction patterns, focusing on Pseudomonas-enriched bacterial communities. By isolating viral communities and purifying bacteria from soils of three distinct microhabitats, we assessed the regulatory role of environmental factors on these interactions, crucial for bacterial success in environmental applications. We characterized microhabitat variability by analyzing soil particle size fractions, minerals composition, and elemental content using X-ray diffraction and energy-dispersive X-ray analyses. 16S rRNA sequencing and cross-infection assays revealed that although bacterial communities across different microhabitats are taxonomically similar, their interaction patterns with phages are distinct. Phage communities showed nonselective infectivity across soil types, while bacterial communities exhibited selective adaptation, facilitating colonization across diverse microhabitats. Minerals such as mica, kaolinite, and hematite were found to increase phage infectivity, whereas mixed-layer clay correlated with early lysis. Additionally, higher levels of iron (Fe) and potassium (K) were linked to bacterial resistance strategies. Our findings highlight the importance of understanding asymmetric adaptive strategies between bacteria and phages, driven by microhabitat heterogeneity, for enhancing microbial-mediated nature-based restoration of degraded ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Despite its critical importance for health, agriculture, and the economy, and its key role in supporting climate change adaptation, groundwater quality remains vulnerable to contamination and is often neglected until significant deterioration. The groundwater resources of Kerala, one of the southernmost states of India, are under escalating stress and scarcity, despite a high well density with 62% of the population relying on groundwater from approximately 6.5 million open wells. This study investigates the detailed hydrogeochemistry and predicts groundwater quality zones of the state using machine-learning techniques viz, extreme gradient boosting (XGBoost), support vector regression (SVR), artificial neural network (ANN) and random forest (RF) regression. The hydrogeochemical analysis reveals varying groundwater quality across the state. Among the different machine learning models, RF shows higher goodness of fit (R 2 : 0.922) with minimal prediction error (root mean square error: 6.29 and mean absolute error: 3.12). The predicted groundwater quality was validated using the spatially distributed stiff diagrams, visually representing water composition trends of each well. The very good, good, moderate and poor groundwater quality zones occupy 31.7%, 40.4%, 20.4%, and 7.4% of the state aligning accurately with the groundwater quality scenario of the state. Additionally, groundwater drinking risk assessment was conducted, considering that 7.4% of the state experiences poor-quality groundwater. Integrating groundwater quality maps with population data, the study assessed potential health risks due to consuming untreated water. Nearly 0.59 million people across 252 local self-government bodies (LSGs) are susceptible to consuming poor quality groundwater, which may pose potential health risks. This observation provides valuable insights for sustainable groundwater management and public health safeguarding and the findings of the present study are useful for achieving sustainable development goal (SGD) 6 (clean water and sanitation) and long-term groundwater management in Kerala., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Land Use/Land Cover (LULC) dynamics provide a crucial role in the monitoring, planning, and management of resources. They also offer valuable information for developing strategies to balance conservation efforts, resolve conflicts between different land uses, and address pressures from growth. The present study focuses on the assessment of LULC dynamics, their forecasting, and their changes for Prayagraj city (including its surroundings) of India. Using long-term spatiotemporal Landsat datasets (1988-2018), we have explored the interlinkages between the change dynamics and human population pressure to explore the impact of agriculture and urbanization on the city landscape. Future growth prediction is carried out by incorporating Cellular Automaton (CA) and Artificial Neural Network (ANN) models. Six exploratory layers (viz., roads, educational institutes, railway transition, slope, river, and restricted area) are used in the learning process to determine LULC change (1997-2008) simulation. The validation of real and predicted LULC is carried out for 2018, where the correctness percentage and kappa value are found to be 90.29% and 0.87, respectively. Then, the ANN- Multilayer perceptron (MLP) and CA model are applied to predict LULC-2028 using the same trained transition probabilities. Results show that Built-land has grown highly by 10.03%, whereas Agriculture land and Forest land have significantly decreased by 13.43% and 3.03%, respectively, from 1988 to 2018. The predicted LULC of 2028 reveals that Built-land will keep growing by 2.83% during 2018-2028 at the cost of Agriculture land and Forest land, especially in northern, south-western and southern region, including city's inner sphere. United Nations' human population projection reveals that the city is expected to reach a population of 1.625 million by 2028. This indicates that tremendous pressure will be placed on land resources, particularly on agricultural, barren, and forested areas. To address this alarming scenario, it is imperative to delineate future development areas, ensuring better urban planning for the environmental sustainability and economic prosperity of Prayagraj city., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The coastal regions of India, particularly the Bay of Bengal, are highly vulnerable to the severe weather conditions induced by tropical cyclones. This study presents a comprehensive analysis of the changes in vegetation cover, shoreline dynamics, and meteorological variations resulting from Cyclone Michaung and subsequent post-monsoon events along the coastal zones of Andhra Pradesh and Tamil Nadu, India. A suite of vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Modified Vegetation Condition Index (mVCI), and Disaster Vegetation Damage Index (DVDI), were employed to assess changes in vegetation cover. The Digital Shoreline Assessment System (DSAS) was utilized to evaluate shoreline changes, and a range of meteorological variables were analyzed to assess the impacts of Cyclone Michaung and post-monsoon events. The findings reveal significant ecological impacts, with a notable decrease in Very Healthy Vegetation from 5.71% to 1.30%. The mean value of mVCI shifted from -0.2 to -0.16, indicating vegetation stress. DVDI analysis showed that 56.49% of the area experienced moderate damage, while 40.24% suffered severe vegetation damage. Additionally, erosion was observed along 79.46% of the shoreline transects in the study area. These insights are critical for assisting coastal managers in developing resilient coastal systems. Remarkably, a significant change in rainfall was recorded between the pre-cyclone period and the landfall day, with maximum rainfall intensifying from 13.93 mm/h on December 3rd to 164.26 mm/h on December 4th, and subsequently decreasing to 144.39 mm/h on December 5th., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Antimicrobial resistance (AMR) is a significant threat that demands surveillance to identify and analyze trends of the emerging antibiotic resistance genes (ARGs) and potential microbial carriers. The influent of the wastewater treatment plants (WWTPs) reflects the microbes derived from the population and effluent being the source of dissemination of potential pathogenic microbes and AMR. The present study aimed to monitor microbial communities and antibiotic resistance genes in WWTPs employing a whole metagenome shotgun sequencing approach. The samples were collected from a sewage treatment plant (STP) and a common effluent treatment plant (CETP) in Delhi, India. The results showed the influent of STP to be rich in Bifidobacterium, Bacteroides, Escherichia, Arcobacter, and Pseudomonas residents of gut microbiota and known to cause diseases in humans and animals; whereas the CETP sample was abundant in Aeromonas, Escherichia, and Shewanella known to be involved in the degradation of different compounds. Interestingly, the effluent samples from both STPs and CETP were rich in microbial diversity, comprising organic and xenobiotic compound degrading and disease-causing bacteria, indicating the effluent being the source of dissemination of concerning bacteria to the environment. The functional profile at both sites displayed similarity with an abundance of housekeeping function genes as analyzed by Clusters of Orthologous Genes (COG), KEGG Orthology (KO), and subsystem databases. Resistome profiling by MEGARes showed the dominance of ARGs corresponding to beta-lactams having relative abundance ranging from 16% to 34% in all the metagenome datasets, followed by tetracycline (8%-16%), aminoglycosides (7%-9%), multi-drug (5%-9%), and rifampin (3%-9%). Also, AMR genes oxa, ant3-DPRIME, and rpoB, which are of clinical importance were predominantly and most prevalently present in all the samples. The presence of AMR in effluents from both types of treatment plants indicates that wastewater from both sources contributes to the spread of pathogenic bacteria and resistance genes, increasing the environmental AMR burden and therefore requires tertiary treatment before discharge. This work will facilitate further research towards the identification of suitable biomarkers for monitoring antibiotic resistance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The groundwater quality in the vicinity of the Makum coalfield, renowned for its high-sulfur coal deposits, was investigated. The oxidation of sulfur in the coal generates acid mine drainage (AMD), a global environmental challenge that contaminates natural resources. The region's high sulfur coal content intensifies AMD formation, necessitating a comprehensive assessment of its impact on human health and the environment. This study analyzes the water quality parameters such as pH, EC, TDS, Na + , Ca +2 , Mg +2 , K + , HCO 3 - , SO 4 -2 , F - , Cl - , and NO 3 - in groundwater, findings concerning low pH levels (5.8) and fluoride concentration (0.15 mg/L) compared to standards. Groundwater chemistry was analyzed to identify the sources controlling water composition through Gibbs diagrams, Piper diagrams, and saturation indices. The Gibbs diagram shows that rock weathering is the crucial factor controlling groundwater chemistry, while the Piper diagram indicates Ca-Cl as the Principal water type. Additionally, an in-depth analysis of groundwater chemistry reveals that carbonate dissolution primarily occurs due to minerals like calcite, dolomite, and gypsum, findings supported by saturation indices. The present study yielded an average water quality index of 40.19, indicating excellent to good water quality in 51 out of 52 samples analyzed. The average hazard index values for adults and children were 0.60 and 0.58, respectively, indicating that 49 of 52 samples pose negative non-carcinogenic risks associated with nitrate and fluoride contamination. The irrigation indices, graphical representations such as the Wilcox and Doneen classification, and the USSL diagram elucidate the suitability for irrigation purposes. Moreover, the Principal Component Analysis identified the sources of ions as originating from geogenic processes and mining activities. The study stresses environmental assessments, health risk management, and sustainable practices for groundwater in high-sulfur coal mining areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The COVID-19 pandemic impacted the solar power industry, business, and supply chain for 2019-2021, and installations are falling behind the mission plan. However, Indian PV manufacturers see it as a chance to engage in solar manufacturing to establish a competitive, sustainable, and robust domestic solar industry instead of import-based installations. Given the country's current environmental concerns, green and sustainable local manufacturing is the only viable alternative. By conducting a life cycle assessment (LCA), this study compared the environmental impacts generated by the five most promising photovoltaic technologies-mono-silicon, polysilicon, copper indium gallium selenide (CIGS), cadmium telluride (CdTe), and passivated emitter and rear contact (PERC) solar modules considering manufacturing in India. The study utilizes the ReCiPe method supported by Ecoinvent 3 databases and Simapro V9.0 software, and the functional unit for the data collection is in 'per square meter', which is later converted to 'per kWh' standard for comparison with the existing studies. The system boundary selected is from cradle to gate. The results demonstrate that cadmium telluride (CdTe) is the best technology for Indian climatic conditions in terms of environmental impact, with a global warming potential of 0.015 kg CO 2 eq/kWh, stratospheric ozone depletion of 5.41E-09 kg CFC11 eq/kWh, human carcinogenic and non-carcinogenic toxicity of 6.67E-04 kg 1,4-DCB/kWh and 1.48E-02 kg 1,4-DCB/kWh, respectively and fine particulate matter formation of 3.96E-05 kg PM 2.5 eq/kWh assuming a lifetime of 25 years for these modules. CIGS follows CdTe in almost every environmental impact category., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The non-stationary behavior of climatic variables has been increasingly recognized as a challenge that disrupts the equilibrium of human-defined climate-based stationary processes, including hydrological and agricultural practices, and irrigation systems. This study aims to investigate long-term trends and non-stationarity in climatic variables across 23 stations of the Krishna River basin, India. Prominent trends in rainfall, temperature, and their extreme indices were identified using the Modified Mann-Kendall (MMK), Bootstrapped Mann-Kendall (BMK), and Sen's Slope Estimator tests, while the Innovative Trend Analysis (ITA) test uncovered hidden trends and potential shifts in climatic patterns. This study addresses a critical research gap by exploring both significant and hidden trends in climatic variables, providing a better understanding of future dynamics. Traditional methods like MMK and Sen's Slope were insufficient to reveal these hidden trends, but ITA offered a more comprehensive analysis. The findings revealed an increase in total annual rainfall for almost 50% of the basin, which aligns with rising maximum temperatures, suggesting enhanced evaporation rates and subsequent fluctuations in rainfall patterns. Seasonal analysis indicated a shift towards decreased rainfall during winter and pre-monsoon seasons, contrasted by increased precipitation during the monsoon and post-monsoon periods, highlighting a clear alteration in rainfall distribution. The Simple Daily Intensity Index (SDII) and other indices suggest intensified rainfall events despite a decrease in the number of rainy days, indicating fewer but more intense events. Temperature analysis showed an overall increase in maximum temperatures, with the Diurnal Temperature Range (DTR) significantly increasing across all stations, implying greater daily temperature variations and potential for intensified water cycles and extreme climatic events. Furthermore, the study simplifies these trends by classifying them into two attributes: intensity and frequency, aiding policymakers in site-specific management of water resources and planning for future climatic scenarios. The presence of non-stationarity in extreme rainfall was confirmed by the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests. These findings are significant as they conclude how climate change is altering hydrological patterns at each station. The study emphasizes the necessity for adaptive management strategies to mitigate the adverse impacts on agriculture, infrastructure, and human safety., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Urban flooding poses a significant challenge to the rapidly growing Indian cities. Low-impact development strategies such as green roofs have shown the potential to reduce urban flooding. However, their performance assessment significantly varies across different studies. Therefore, the study's primary objective is to evaluate green roofs in the Indian context. For this evaluation, the green roofs are assessed based on building-level implementation scenarios for a high-density urban area in India for 25%,50%, and 75% application rates and different rainfall intensities (2,3 and 4-h duration and 2,5,10 and 25-year frequencies). Secondly, to probe the variations in the green roof performance across studies, uncertainty contributions to the runoff reduction from different parameters are quantified. The results show that green roofs can reduce up to 62% of flood volume and 24% of runoff. However, they are reasonably effective only beyond 25% application rates. Further, rainfall intensity contributes the most to the uncertainty of runoff reduction from green roofs. This uncertainty assessment implies that localized evaluation of green roofs depending on local rainfall conditions is required for city-wide policy planning. The study has a significant contribution to building confidence in the ability of green roofs to reduce urban floods in the context of developing countries like India., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Efficient domestic wastewater management is essential for mitigating the impact of wastewater on human health and the environment. Wastewater management with conventional technologies generates sewage sludge. The present study considered a modelling approach to evaluate various processing pathways to produce energy from the sewage sludge. Anaerobic digestion, gasification, pyrolysis, and hydrothermal liquefaction are analysed in terms of their energy generation potentials with the Aspen Plus software. A techno-economic assessment is performed to assess the economic viability of each pathway. It reveals that gasification appears as the most promising method to produce electricity, with 0.76 kWh/kg drysludge , followed by anaerobic digestion (0.53 kWh/kg drysludge ), pyrolysis (0.34 kWh/kg drysludge ), and hydrothermal liquefaction (0.13 kWh/kg drysludge ). In contrast, the techno-economic analysis underscores the viability of anaerobic digestion with levelized cost of electricity as 0.02 $/kWh followed by gasification (0.11 $/kWh), pyrolysis (0.14 $/kWh), and hydrothermal liquefaction (2.21 $/kWh). At the same time, if the products or electricity from the processing unit is sold, equivalent results prevail. The present study is a comprehensive assessment of sludge management for researchers and policymakers. The result of the study can also assist policymakers and industry stakeholders in deciding on alternative options for energy recovery and revenue generation from sewage sludge., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The use of fixed emission factors (EFs), combined with insufficient temporal distribution, leads to substantial uncertainties in current emission inventories for India, the world's second-largest producer and consumer of synthetic N-fertilizers. Our study aimed to improve the NH 3 and N 2 O emission estimates by utilizing crop-specific district-level activity data and refined EFs tailored to Indian conditions. In this study, a comprehensive NH 3 and N 2 O emission inventory (EI) is methodically developed at 0.1° * 0.1° spatial and monthly temporal resolution for the year 2018-19 considering 52 crops. The data for developing this inventory is aggregated through detailed field surveys, conducted across 102 districts of 14 states, and relevant government databases. EFs have been adjusted for the Indian context by refining them to reflect local conditions through consideration of ambient temperature, application rate, and other factors. Further, upon preparing an EI for FA, a spectrum of mitigation strategies are evaluated to assess their effectiveness in reducing emissions. Yearly total NH 3 and N 2 O emissions amount to 3.15 Tg and 138.53 Gg, with urea fertilizer as the dominant contributor accounting for 93.85% and 96.44% of emissions, respectively. Key crops such as rice, wheat, maize, sugarcane, and cotton collectively represent approximately 82% of the total N consumption. The state of Uttar Pradesh emerges as the largest emitter, contributing 706.5 Gg and 25.31 Gg of NH 3 and N 2 O emissions, respectively. Conversely, PB and HR exhibit the highest NH 3 emissions per capita. Temporally, NH 3 emissions peak in August, while N 2 O emissions peak in July, with both pollutants reaching their nadir in February. Among the array of mitigation strategies assessed in this study, 'adhering to recommended fertilizer doses' and 'incorporating urease inhibitors' demonstrated substantial potential for reducing emissions. The current study aids policymaking to mitigate the environmental and health impacts of atmospheric emissions from synthetic N-fertilizers. Future researchers can adopt this study as a benchmark to improve Indian FA emission estimates, which helps in promoting sustainable agricultural practices and contributes to climate change mitigation efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The East Kolkata Wetlands (EKW) in Kolkata, India, span 12,500 ha and are a vital ecological zone providing several benefits, including water purification, flood control, and biodiversity support. This study investigated land use and land cover (LULC) alterations in the EKW from 1991 to 2023, using a random forest (RF) machine learning model. Significant LULC changes were observed over the 32 years, with wetland areas decreasing from 91.2 km 2 in 1991 to 33.4 km 2 in 2023, reflecting substantial habitat loss and reduced ecosystem services. Conversely, agricultural land expanded from 27.8 km 2 to 58.7 km 2 , driven by economic and food production needs, and built-up areas increased dramatically from 0.2 km 2 to 10.5 km 2 , indicating rapid urbanization. This study evaluated the health, resilience, and ecosystem functionality of EKW by analysing human-induced land use changes and using ecological indicators and landscape metrics. Landscape and class level metrics such as PLAND, largest patch index (LPI), total edge (TE), edge density (ED), number of patches (NP), and patch density (PD) were used to analyse the spatiotemporal dynamics of the wetlands. This study revealed a significant increase in fragmentation, with the number of patches increasing from 2689 in 1991 to 4532 in 2023, despite a consistent decrease in core wetland areas. Ecosystem health indicators, such as the ecosystem structure index (ESI) and landscape deviation degree (LDD), were used to assess landscape metrics and fragmentation changes. The ESI and other metrics revealed significant temporal fluctuations, providing insights into landscape structure, connectivity, and heterogeneity. The ESI improved from 0.87 in 1991 to 1.03 in 2023, indicating enhanced connectivity and diversity. Conversely, the LDD increased from 20.6% to 56.85%, indicating a shift towards impervious surfaces. The vegetation productivity and ecosystem health index (EHI) decreased, indicating biodiversity loss and reduced carbon sequestration. The EHI also dropped from 0.67 to 0.55, signifying ongoing environmental stress. This study emphasizes the need for conservation efforts to maintain the ecological integrity of the EKW amidst urbanization and land use changes and recommends a balanced approach for sustainable urban development and enhanced wetland resilience., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The escalating environmental concerns arising from soils contamination with heavy metals (HMs) and pesticides (PSTs) necessitate the development of sustainable and effective remediation strategies. These contaminants, known for their carcinogenic properties and toxicity even at small amounts, pose significant threats to both environmental ecology and human health. While various chemical and physical treatments are employed globally, their acceptance is often hindered by prolonged remediation times, high costs, and inefficacy in areas with exceptionally high pollutant concentrations. A promising emerging trend in addressing this issue is the utilization of microalgae for bioremediation. Bioremediation, particularly through microalgae, presents numerous benefits such as high efficiency, low cost, easy accessibility and an eco-friendly nature. This approach has gained widespread use in remediating HM and PST pollution, especially in large areas. This comprehensive review systematically explores the bioremediation potential of microalgae, shedding light on their application in mitigating soil pollutants. The paper summarizes the mechanisms by which microalgae remediate HMs and PSTs and considers various factors influencing the process, such as pH, temperature, pollutant concentration, co-existing pollutants, time of exposure, nutrient availability, and light intensity. Additionally, the review delves into the response and tolerance of various microalgae strains to these contaminants, along with their bioaccumulation capabilities. Challenges and future prospects in the microalgal bioremediation of pollutants are also discussed. Overall, the aim is to offer valuable insights to facilitate the future development of commercially viable and efficient microalgae-based solutions for pollutant bioremediation., Competing Interests: Declaration of competing interest The authors declare that no known conflicting financial interests or personal relationships exist that could have seemed to impact the work presented in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Landfills are a major source of many emerging pollutants, including microplastics (MPs). This makes them a potential threat to human and environmental health and calls for a more detailed analysis of their hazard potential. India is a developing country with multiple unscientific waste dumping sites. In spite of their hazardous nature, detailed studies on the abundance of microplastics in landfills in India are scanty. Current work investigates the abundance and diversity of MPs in two landfills of India, Uruli Devachi in Pune (S1) and Deonar in Mumbai (S2). MPs collected from landfill leachate using multiple filters were analyzed using an optical microscope and categorized on the basis of shape, color and size to give information on their distribution. MP abundance in S1 was 1473 ± 273.01 items/L while 2067 ± 593.75 items/L were found in leachate from S2. Film and fragment were the dominant shape and black was the dominant color of MP found in both the landfills. Maximum number of MPs were in the size range below 100 μm in both the landfills necessitating the study of small sized particles. Chemical characterization revealed the prevalence of four types of MPs (polyethylene terephthalate, polypropylene, cellulose acetate and polyvinyl chloride). This study sheds light on the prevalence, characteristics, abundance and distribution of MPs in landfill leachate in Western India, sparking more research into the processes followed for capturing the factual small sized microplastic abundance data. This study is vital for a detailed management of landfill leachate enabling a sustainable waste management and targeted actions for ecosystem preservation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Managed aquifer recharge (MAR) has emerged as a potential solution to resolve water insecurity, globally. However, integrated studies quantifying the surplus source water, suitable recharge sites and safe recharge capacity is limited. In this study, a novel methodology is presented to quantify transient injection rates in unconfined aquifers and generate MAR suitability maps based on estimated surplus water and permissible aquifer recharge capacity (PARC). Subbasin scale monthly surplus surface runoff was estimated at 75% dependability using a SWAT model. A linear regression model based on numerical solution was used to capture the aquifer response to injection and to calculate PARC values at subbasin level. The available surplus runoff and PARC values was then used to determine the suitable site and recharge rate during MAR operation. The developed methodology was applied in the semi-arid region of Lower Betwa River Basin (LBRB), India. The estimated surplus runoff was generally confined to the monsoon months of June to September and exhibited spatial heterogeneity with an average runoff rate of 5000 m 3 /d in 85% of the LBRB. Analysis of the PARC results revealed that thick alluvial aquifers had large permissible storage capacity and about 50% of the LBRB was capable of storing over 3500 m 3 /d of water. This study revealed that sufficient surplus runoff was generated in the LBRB, but it lacked the adequate safe aquifer storage capacity to conserve it. A total 65 subbasins was identified as the best suited sites for MAR which had enough surplus water and storage capacity to suffice 20% of the total water demand in the LBRB. The developed methodology was computationally efficient, could augment the field problem of determining scheduled recharge rates and could be used as a decision-making tool in artificial recharge projects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Stability of soil organic carbon (SOC) is pre-requisite for stabilization of C leading to long-term C sequestration. However, development of a comprehensive metric of SOC stability is a major challenge. The objectives for the study were to develop novel SOC stability indices by encompassing physical, chemical, and biochemical SOC stability parameters and identifying the most important indicators from a Mollisol, an Inceptisol, a Vertisol, and an Alfisol under long-term manuring and fertilization. The treatments were control, 100%NPK, 50% NPK+ 50% N through either farmyard manure, cereal residue, or green manure. SOC stability indicators were selected, transformed and integrated into unique SOC stability indices via conceptual framework and principal component analysis. Principal component analysis identified Al-macroaggregate, humic acid C-microaggregate, microaggregate-C, particulate organic matter-C-macroaggregate and polyphenol-microaggregate as the important SOC stability indicators. The principal component analysis -based SOC stability index varied from 0.2 to 0.9, 0.1 to 0.5, 0.2 to 0.6, 0.1 to 0.5 for Mollisol, Inceptisol, Vertisol and Alfisol, respectively. The SOC-stability index derived from conceptual framework and principal component analysis significantly lined up well with one another, although NaOCl-Res-C showed a high correlation with both conceptual framework (r = 0.8) and principal component analysis-based (r = 0.7) SOC stability indexes, suggesting that both methods might be used to quickly assess SOC stability in four soil orders. Overall, 50%NPK+50%N by farmyard manure or green manure emerged as the most effective management practices for enhancing stability of SOC in Mollisol, Inceptisol, Vertisol, and Alfisol of India which might act as major C sink in rice-wheat and maize-wheat cropping systems. The other aspect of C sequestration is to enhance agricultural productivity without depending much on expensive chemical fertilizers. The model yardstick thus developed for assessing SOC stability might be useful to other systems as well., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Rainfall is a key hydro meteorological variable. Climate change is disrupting the hydrological cycle and altering the usual cycle of rainfall, which frequently results in long-lasting storms with significant rainfall. A first step in hydrologic design of project is to determine the design storm or rainfall events to be used. For deriving design storm, researchers concluded that instead of using generalized readily available curves or maps, it is better to estimate design storm based on site specific historical rainfall data. The objective of the study is to analyze the rainfall data in the koyna watershed area in order to evaluate the design storm, which will be further used as an input data for HEC-HMS event based hydrological modelling of flood peak attenuation of design storm flow at koyna dam during extreme rainfall event. In this study, 40 years (1982-2021) of rainfall data from 8 rain gauge stations in Koyna Dam Catchment area is used initially for performing trend analysis through statistical and graphical techniques and then for Isopluvial analysis. The Sen's slope test and the Mann-Kendall test are the statistical techniques employed, and Innovative Trend Analysis is the graphical technique used. IDF approach is used for deriving design storm, and using Gumbel's frequency distribution method Isohyetal maps, IDF tables and curves are prepared for 2,10,25,50,75 and 100 year return periods and 6,12,24,48 and 96 h durations. Results obtained from statistical and graphical trend analysis of annual rainfall series are consistent. No statistically significant trend in annual rainfall series is observed, however there is rising and falling trend was observed in annual as well as monthly rainfall series. From the results of design storm study, the design storm hyetograph of 10 years return period and 96 h duration is selected, which gives the rainfall intensity of 10.88 mm/h for the koyna catchment. There are various dams nearby koyna catchment, The Isohyet maps, IDF curves and table output available from this study can be more reliably used during planning and design of hydraulic structure for other areas near by koyna catchment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Groundwater serves as an important resource for drinking and agriculture in many countries, including India. Assessing the quality of groundwater is essential for understanding its chemical characteristics and suitability for consumption. This study aims to explore the factors affecting the hydrogeochemical changes in groundwater within Guwahati City, Assam, India. Groundwater samples were collected and analyzed for major and trace elements, as well as anion concentrations. Concentrations of As, Al, Ba, Cu, F - , Fe, Mn, and Pb exceeded the permissible limits set by both World Health Organization (WHO) and Bureau of Indian Standards (BIS), indicating serious health concerns for the local inhabitants. The distribution pattern of trace elements exceeding the guideline values is intricate, suggesting widespread contamination of groundwater throughout the study area. The Heavy Metal Pollution Index (HPI) and Water Quality Index (WQI) revealed that, except for the central zone, groundwater across the entire study area requires intervention. Piper plot illustrated that the groundwater is predominantly of Ca-HCO 3 type, indicating the dominance of alkaline earth and weak acids. Groundwater hydrogeochemistry is mainly controlled by rock-water interaction and evolves through silicate weathering, carbonate weathering, and cation exchange processes. Multivariate statistical analysis identified distinct groups of groundwater based on chemical characteristics, emphasizing the role of both natural processes and anthropogenic activities in influencing groundwater quality. Regular monitoring, management, and intervention of groundwater sources throughout the study area are crucial for long-term use. The findings of this study will assist stakeholders, regulators, and policymakers in formulating strategies for the sustainable use of groundwater., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Crop residue management has become more challenging with intensive agricultural operations. Zero tillage and crop residue returns, along with the enhancement of in-situ residue decomposition through microbial intervention, are essential measures for preserving and enhancing soil quality. To address this problem in view of stubble burning, field experiments were conducted in rice-rice (variety Swarna) cropping systems under lowland conditions, wherein the following different residue management practices were adopted viz., conventional cultivation (CC), residue incorporation (RI @ 6 t paddy straw ha -1 ), residue retention (RR @6 t paddy straw ha -1 ), and zero tillage (ZT). In this experiment, two microbial products i.e. solid microbial consortium (SMC) at 2.0 kg ha -1 ) and capsule (10 numbers ha -1 ), were evaluated in both Rabi (dry) and Kharif (wet) seasons under different residue management practices. The results on soil microbial properties showed that application of either SMC or capsule based formulation could significantly improve the soil organic carbon (SOC) content in ZT (9.51 g/kg), followed by RI (9.36 g/kg), and RR (9.34 g/kg) as compared to CC (7.61 g/kg). There were significant differences in the soil functional properties (AcP, AkP, FDA, and DHA) with microbial interventions across all residue management practices. SOC was significantly positive correlated with cellulase (R 2  = 0.64, p < 0.001), β-glucosidase (R 2  = 0.61, p < 0.001), and laccase (R 2  = 0.66, p < 0.001) activity; however, the regression coefficients varied significantly with microbial intervention. Moreover, the availability of N, P, and K in soil was significantly (p < 0.05) improved under microbial treatments with either RR or RI practices. Among the different methods of residues management practices, RI with microbial intervention registered a consistent yield improvement (8.4-17.8%) compared to conventional practices with microbial intervention. The present findings prove that the application of decomposing microbial consortia for in-situ rice residue management under field conditions significantly enhances soil quality and crop yield compared to conventional practices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Cement is one of the widely used materials in construction, and its production is both energy- and emission-intensive, contributing significantly to industrial emissions. This study investigates multiple methods for reducing emissions in the Indian cement sector based on the mass and energy balances of a representative cement plant. A novel methodology for calculating the overall emissions reduction per tonne of cement with multiple emission reduction measures and their interdependencies is proposed. The effect of captive power plants in the cement industry on emissions reduction is also considered. The results are depicted using an emission abatement curve, which gives the CO 2 abatement cost against cumulative emission reduction per tonne of cement, and a cost premium curve, which shows the cumulative abatement cost against percentage abatement. The analysis shows that up to 30% emissions reduction is possible using existing emission reduction measures in all the cases considered with no additional cost, and near-zero emission reduction is only possible with the adoption of emerging technologies such as carbon capture and storage. The proposed methodology is the first to explore the impact of multiple measures for emission reduction on a given cement plant, allowing for a realistic estimate of emission reduction from the measures implemented., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Microplastics are ubiquitous, and their widespread prevalence in the ecosphere has generated concerns about their potential effects on terrestrial and aquatic organisms. However, studies pertaining to ecologically sensitive freshwater ecosystems, such as Ramsar wetlands, is scarce. Therefore, the study was conducted in Loktak, the world's only floating lake, and one of the largest wetland in the Indian Himalayan region. The wetland's degradation and pollution have resulted its inclusion in the Montreux Record, underscoring the need for studying this eco-sensitive freshwater system. This work investigated the (i) abundance, morphotype and size of microplastics in fish, and (ii) chemical composition of the microplastics consumed and accumulated in the fish of Loktak lake. Fish samples representing eight species were collected and analyzed for microplastics. Results revealed that ∼91% of the sampled fish ingested microplastics. Fragment was identified as the predominant morphotype (∼82%). Plastic polymers including polyamide (PA), polystyrene (PS), polycarbonate (PC) and carboxymethyl cellulose (CMC) were detected. The occurrence of heavy metals - chlorine (Cl), palladium (Pd), sodium (Na), zinc (Zn), lead (Pb) and copper (Cu) suggests their adhesion on the microplastics. The occurrence of microplastics in fish indicates pollution in the lake and poses a potential health risks to humans through consumption. Therefore, implementing comprehensive management approaches is imperative to mitigate this emerging pollution and uphold the ecological integrity of the Ramsar site. Substantial information on microplastics and their potential human exposure through fish consumption, particularly in the Indian Himalayan region, remains to be assessed, underscoring the need for extensive study., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Continuous Emission Monitoring Systems (CEMS) are devices used to measure and report real-time emission of air pollutants. Although CEMS have been extensively deployed in developed countries to ensure compliance with emission standards and enhance their environmental performance, their adoption in India is still in its early stages. The present study aims to evaluate the effectiveness of CEMS in India, identify obstacles in terms of policy, regulation, technology and finance that impede their adoption and suggest mechanisms and incentives to facilitate their expansion. The findings indicate that CEMS offer benefits for air pollution control in India by improving monitoring accuracy, transparency, accountability and enforcement. The study also highlights institutional challenges faced by CEMS, including the absence of a certification system, lack of quality assurance measures, issues with data validation and challenges in its calibration as well as integration concerns with existing regulatory framework. To address these challenges effectively it is recommended that India must develop a policy framework for CEMS along with regulations. Essential steps such as establishing a certification and accreditation system should be taken while enhancing stakeholders' capacity and awareness., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Ashish Tiwari reports a relationship with Uttar Pradesh Climate Change Authority Directorate of Environment Vineet Khand-6, Gomti Nagar, Lucknow, Uttar Pradesh 226,010 that includes: employment. NA If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Extensive global dependency on rice and wheat crops has necessitated the adoption of intensive cultivation practices, thereby compelling to closely monitor the potential yield-limiting factors, among which, boron (B) deficiency stands out to be a prime concern. The present study explores the effects of B fertilization strategies within the Rice-Wheat Cropping System (RWCS) in the Tarai region of North-West India. A comprehensive six-year field experiment was conducted (2013-2019) at G.B. Pant University of Agriculture and Technology, Uttarakhand, India. The experiment tested graded B doses (0.5, 1.0, 1.5, and 2.0 kg ha -1 ) at varied frequencies (single, alternate, and annual) in a factorial design. The study revealed significant impacts of alternate B application at 1.5 kg ha -1 on crop yields and the Sustainable Yield Index (SYI). The System Rice Equivalent Yield (SREY) exhibited an increase of 6.7% with B supplementation over B-deprived plots, highlighting the pivotal role of B fertilizer in enhancing productivity within the RWCS. The economic optimum B dose was found to be 1.422 kg ha -1 using a linear plus plateau model, resulting in a calculated annual SREY of 9.73 t ha -1 when applied alternately to the cropping system. Continuous application and higher B rates demonstrated substantial increases in various B fractions, while the mobility factor remained within 10%, depicting safe ecological limits. The distribution of fractions in B-treated plots on average followed the order: residual B > organically-bound B > oxide bound B > specifically adsorbed B > readily soluble B. Similarities in the distribution patterns of B fractions between B-treated plots and the control indicated potential influence of biotic or abiotic processes on B fraction dynamics, even in the absence of external B application. To sum up, B application in alternate years at 1.5 kg ha -1 was most sustainable in enhancing the SREY, SYI, available soil B, and B fractions and lowering the environmental hazards., Competing Interests: Declaration of competing interest The author(s) declared no potential conflict of interest that could have appeared to influence the work reported in the present paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Solid waste management in low- and middle-income countries like India faces significant challenges due to the increasing waste generation that surpasses the current capacity. Therefore, the informal waste sector (IWS) is more vital than ever in handling consumer waste alongside municipal solid waste management (SWM) systems. However, the integration of the IWS into formal waste management systems remains unresolved due to adverse social and economic conditions. This study focuses on identifying the root causes that hinder the integration of the IWS in India's waste management system, using the city of Chennai as a case study. Adopting an institutional perspective, we analyse the institutional landscape of the waste management system, considering both formal rules (in policy documents) and informal rules (i.e., social norms and routines). The institutional network analysis reveals a significant misalignment in perceptions among governance levels concerning the integration of the IWS. The study shows a considerable gap between rules-in-form and rules-in-use, leading to 1) Preclusion of waste pickers in collecting door-to-door source-segregated waste (i.e., recyclables). 2) Unfair pricing in transactions with small aggregators. 3) Lack of ID cards for waste pickers. These barriers are ultimately rooted in caste discrimination, misalignment between governance levels, and the exclusion of waste pickers in the policymaking process. In conclusion, understanding and rectifying the institutional gaps and discriminatory practices are essential steps towards effectively integrating the IWS in India's waste management system, promoting a more inclusive and sustainable approach to waste management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The Indian coastal waters are stressed due to a multitude of factors, such as the discharge of industrial effluents, urbanization (municipal sewage), agricultural runoff, and river discharge. The coastal waters along the eastern and western seaboard of India exhibit contrasting characteristics in terms of seasonality, the magnitude of river influx, circulation pattern, and degree of anthropogenic activity. Therefore, understanding these processes and forecasting their occurrence is highly necessary to secure the health of coastal waters, habitats, marine resources, and the safety of tourists. This article introduces an integrated buoy-satellite based Water Quality Nowcasting System (WQNS) to address the unique challenges of water quality monitoring in Indian coastal waters and to boost the regional blue economy. The Indian National Centre for Ocean Information Services (INCOIS) has launched a first-of-its-kind WQNS, and positioned the buoys at two important locations along the east (Visakhapatnam) and west (Kochi) coast of India, covering a range of environmental conditions and tourist-intensive zones. These buoys are equipped with different physical-biogeochemical sensors, data telemetry systems, and integration with satellite-based observations for real-time data transmission to land. The sensors onboard these buoys continuously measure 22 water quality parameters, including surface current (speed and direction), salinity, temperature, pH, dissolved oxygen, phycocyanin, phycoerythrin, Coloured Dissolved Organic Matter, chlorophyll-a, turbidity, dissolved methane, hydrocarbon (crude and refined), scattering, pCO 2 (water and air), and inorganic macronutrients (nitrite, nitrate, ammonium, phosphate, silicate). This real-time data is transmitted to a central processing facility at INCOIS, and after necessary quality control, the data is disseminated through the INCOIS website. Preliminary results from the WQNS show promising outcomes, including the short-term changes in the water column oxic and hypoxic regimes within a day in coastal waters off Kochi during the monsoon period, whereas effluxing of high levels of CO 2 into the atmosphere associated with the mixing of water, driven by local depression in the coastal waters off Visakhapatnam. The system has demonstrated its ability to detect changes in the water column properties due to episodic events and mesoscale processes. Additionally, it offers valuable data for research, management, and policy development related to coastal water quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Anthropogenic land use and land cover changes are major drivers of environmental degradation and declining soil health across heterogeneous landscapes in Central India. To examines the land cover changes and spatio-temporal variations in forest carbon stock and soil organic carbon (SOC) over the past 25 years in central India. Geospatial techniques, coupled with ground measurements were employed to detect changes in land cover, carbon stocks in vegetation, and soil carbon in various vegetation types. The results indicate that forested areas have decreased, while agriculture and habitation have expanded between 1997 and 2022. Vegetation C stocks varied significantly (P < 0.05) from 39.42 to 139.95 Mg ha -1 and the SOC varied from 7.02 to 17.98 Mg ha -1 under different soil profiles across vegetation types, which decreased with soil depth, while the pH and bulk density increased. The maximum bulk density in the soil was found at a depth of 40-60 cm (lower profile) in Bamboo Brake, while the minimum was observed under Dense Mixed Forest at a depth of 0-20 cm (top profile). The topsoil profile contributed 33.6%-39%, the middle profile (20-40 cm) was 33.6%-34.4%, and the lower profile was 26.5%-30.8% of soil organic carbon. The study site has experienced rapid carbon losses due to changes in land cover, such as illegal expansion of agriculture, encroachments into forest fringes, and activities like selective logging and overgrazing, which have degraded dense forests. The ecological engineering of degraded ecosystems poses a great challenge and application of complex biological, mechanical and engineering measures is highly cumbersome, expensive, uneconomical and practically not feasible for upscaling. Nevertheless, proposed nature-based solutions mimic natural reparation and processes provide sustainable interventions for the reclamation of ruined landscapes besides improving ecological integrity and rendering many co-benefits to ecosystems and human societies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In order to obtain extended storage life of food-grade materials and better barrier properties against environmental factors, a multilayer plastic packaging (MLP) is often used. The multilayer packaging plastics are labelled as "other" (SPI#7) category, and are manufactured with a combination of barrier plastics, rigid plastics and printing surface. Owing to their complex composition and difficulty in separating the layers of MLP, its mechanical recycling is challenging. In this study, MLP wastes (MLPWs) were collected from zero-waste garbage collection center of IIT Madras, India, and thoroughly characterized to determine their composition and plastic types. MLPWs were characterized using various physico-chemical methods such as thermogravimetric/differential scanning calorimetric analysis, Fourier transform infrared spectroscopy, bomb calorimetry, and proximate and ultimate analyses. The MLPWs were mainly made up of polyethylene (PE) and polyethylene terephthalate (PET). Further, the non-catalytic and zeolite-catalyzed fast pyrolysis of these MLPWs were studied using analytical pyrolysis coupled with gas chromatograph/mass spectrometer (Py-GC/MS). The non-catalytic fast pyrolysis of MLPWs primarily produced a mixture of aliphatic and alicyclic hydrocarbons, while zeolite catalyzed fast pyrolysis resulted in the formation of mono-aromatic hydrocarbons (MAHs). The activity of HZSM-5, zeolite Y (HY) and zeolite beta (Hβ) catalysts were evaluated, and the salient products were quantified. The yields of MAHs like benzene, toluene, ethylbenzene and xylene using the zeolites followed the trend: HZSM-5 (14.9 wt%) > HY (8.1 wt%) > Hβ (7.8 wt%), at 650 °C. The use of HZSM-5 resulted in highest yield of MAHs, viz. 16.1 wt%, at the optimum temperature of 550 °C and MLPW-to-catalyst ratio of 1:15 (w/w). The superior activity of HZSM-5 is due to its nominal acidity and larger pore size of 4.24 nm, as compared to HY and Hβ. The MAHs yield from three other types of MLPWs varied in the range of 9-16 wt%. The present study demonstrates a promising pathway for the catalytic upcycling of highly heterogeneous MLPWs in the context of circular economy., Competing Interests: Declaration of competing interest It is declared that the authors have no conflicts of interest or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Loktak Lake, one of the largest freshwater lakes in Manipur, India, is critical for the eco-hydrology and economy of the region, but faces deteriorating water quality due to urbanisation, anthropogenic activities, and domestic sewage. Addressing the urgent need for effective pollution management, this study aims to assess the lake's water quality status using the water quality index (WQI) and develop advanced machine learning (ML) tools for WQI assessment and ML model interpretation to improve pollution management decision making. The WQI was assessed using entropy-based weighting arithmetic and three ML models - Gradient Boosting Machine (GBM), Random Forest (RF) and Deep Neural Network (DNN) - were optimised using a grid search algorithm in the H2O Application Programming Interface (API). These models were validated by various metrics and interpreted globally and locally via Partial Dependency Plot (PDP), Accumulated Local Effect (ALE) and SHapley Additive exPlanations (SHAP). The results show a WQI range of 72.38-100, with 52.7% of samples categorised as very poor. The RF model outperformed GBM and DNN and showed the highest accuracy and generalisation ability, which is reflected in the superior R 2 values (0.97 in training, 0.9 in test) and the lower root mean square error (RMSE). RF's minimal margin of error and reliable feature interpretation contrasted with DNN's larger margin of error and inconsistency, which affected its usefulness for decision making. Turbidity was found to be a critical predictive feature in all models, significantly influencing WQI, with other variables such as pH and temperature also playing an important role. SHAP dependency plots illustrated the direct relationship between key water quality parameters such as turbidity and WQI predictions. The novelty of this study lies in its comprehensive approach to the evaluation and interpretation of ML models for WQI estimation, which provides a nuanced understanding of water quality dynamics in Loktak Lake. By identifying the most effective ML models and key predictive functions, this study provides invaluable insights for water quality management and paves the way for targeted strategies to monitor and improve water quality in this vital freshwater ecosystem., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Quantifying anthropogenic impacts on blue space (BS) and its effect on human and socio-ecological health was least explored. The present study aimed to do this in reference to the urban BS transformation scenario of Eastern India. To measure BS transformation, Landsat image-based water indices were run from 1990 to 2021. Anthropogenic impact score (AIS) and 7 components scores of 78 selected BS on 70 parameters related data driven from the field. Total 345 respondents were taken for human and socio-ecological health assessment. For this, depression (DEP), anxiety (ANX), stress (STR), physical activities (PA), social capital (SC), therapeutic landscape (TL) and environment building (EB) parameters were taken. The result exhibited that BS was reduced. About 50% of urban core BS was reported highly impacted. Human and socio-ecological health was identified as good in proximity to BS, but it was observed better in the cases of larger peripheral BS. AIS on BS was found to be positively associated with mental health (0.47-0.63) and negatively associated with PA, SC, TL and EB (-0.50 to -0.90). Standard residual in ordinary least square was reported low (-1.5 to 1.5) in 95% BS. Therefore, BS health restoration and management is crucial for sustaining the living environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Tempero-spatial analysis of groundwater to disseminate the level of drinking water quality and industrial suitability to meet the developmental requirement of a region is a significant area of research. Accordingly, groundwater quality and geochemical interactions prevailed in a black sand mineral rich coastal village is systematically presented in appraisal of drinking and industrial uses for economic engineering purposes. The study area focused is Alappad village, Kollam, Kerala, India has numerous ecological features in a sustainable perspective. The region is unique with placer deposits where an alluvial soil aquifer-saline water-freshwater interaction occurs. This dynamics decides the pertinent hydro geochemistry, potable and designated uses of ground water in season wise. Coastal area is hereby presented based on water quality parameters predicted with the health risk assessment model with a view on human health and cancer risk due to ions (Pb, Ni, Cu, Ba, Fe, Al, Mn, Zn) in groundwater.. To ascertain industrial usage, ground water is evaluated by Langelier saturation index (LSI), Ryznar stability index (RSI), Aggressive index (AI), Larson-Skold index (LS) and Puckorius scaling index (PSI) and inferences are complemented. Chemical weathering and evaporation processes are the natural factors controlling hydrochemistry of this aquifer. This complex coastal system has Nemerow pollution index (NPI) of moderate pollution for total dissolved ions of Fe and lesser for Cu, and Cr present in groundwater. LSI indicates, water is scale forming but non corrosive (46% in PRM, 20% in MON and 47% in POM). Water quality index (WQI) in POM (ranged 28.7-79.9) was excellent for drinking, followed by PRM (23.6-218.2) and MON (33.4-202.7) seasons. This groundwater bears temporary hardness with the dominance of Ca-Mg-HCO 3 water type. Health risk assessment of non-carcinogenic risk index of trace metals (Fe, Zn, Mn, and Pb) revealed, children are at 'low risk' and 'medium' risk with Ni and Cu. The carcinogenic risk index indicated 93% of samples were high Ni induced cancer risk for children, and 87% for adults due to long term ingestion (drinking water intake) pathway. Studies specific on placer mineral deposited coastal region of India are not sufficiently reported with a focus on the above perspectives. Growing need of rare earths for material, device and energy applications, placer mineral explorations can destabilise the coastal hydrosphere. Interrelations of mineral soil - water chemistry prevailed and health hazard predicted would kindle a set of sustainable deliberations. This study summarises the drinking and industrial use of coastal groundwater for future development and human well-being on the basis of quality criteria, corrosion proneness, water stability and health risk factors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Tribal farmers in the Himalayas are vulnerable to climatic changes, as their rain-fed cultivation systems, practiced on steep, sloping terrain, are susceptible to changes in rainfall while at the same time being the primary means of livelihood. Soil and water conservation practices (SWCP) can improve the resilience of these cultivation systems to adverse climatic conditions. However, little is known about adaptation within these tribal farming communities. This is the first empirical study on the adaptation decisions of tribal farmers in the Himalayan uplands of Northeast India. Starting from the analysis of future climate risks, we surveyed 372 tribal farmers in Nagaland state to analyze perceived climate and environmental changes in relation to socio-demographic factors. We estimate current adoption rates of SWCP together with farmers' goals and values and employ a binary logit model (BLM) to quantify the influence of diverse factors on adaptation decisions. Our results show that increases in temperatures and crop diseases were the most perceived changes by tribal farmers. Climate projections indicate that precipitation amount and intensity, along with temperatures, will increase towards the end of the century, underlining the importance of SWCP. However, all considered SWCP were employed by less than half of the tribal farmers. Adoption probabilities for all practices were significantly increased when farmers participated in agricultural training. After that, participation in a civil society organization, livestock ownership, high-altitude locations, and perceived increases in droughts were found to increase adoption probabilities significantly, while socio-demographic factors were of only minor importance. If the most effective factor was employed to all farmers, average adoption rates of SWCP could at least double. Adoption decisions were mainly motivated by improving livelihoods, sustaining natural resources, reducing workload, and preserving cultural aspects of cultivation. This research contributes to understanding adaptation decisions of tribal farmers and quantifies the untapped potential for climate change adaptation of marginalized and climate-vulnerable farming communities in mountain regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Worldwide, environmental concerns about MPs pollution have increased. Microplastic contamination that pollutes the ocean is mostly caused by terrestrial transfer from close proximity locations. A study of MPs pollution near coastal locations becomes necessary to address the MPs transit, fate, and mitigation. In the current study MPs pollution in the surface water and sediment of the Mahanadi River estuary was assessed during Pre-MS and MS. The size, shape, and colour of the MPs were determined using a stereomicroscope, and the MPs polymer composition was identified by Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The mean concentration of MPs that were potentially discovered in water was 16.6 ± 5.2 and sediments 197.3 ± 5.4 during Pre-MS. In the MS observed mean abundance of MPs was 15.1 ± 5.4 in water and 164.6 ± 76.9 in sediments. The highest abundant size was smaller than 1 mm; the most prevalent shape were fibers followed by film and fragments; black and white was a prominent colour in water and sediments respectively. Polyesters (PEs), polyethylene (PE), polyvinyl chloride (PVC), polypropylene (PP), polyamide (PA), Polystyrene (PS), and Polycarbonates (PC) were found in the analysis of the chemical composition of MPs in water and sediments samples. The calculated PLI value shows pollution load at category I, with polymer hazard levels at categories III, IV, and V, indicating very high risk. The current research results show that river inflows and fishing-related actions are probably the main causes of MPs pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The exacerbation of the historical and geopolitical tensions between India and Pakistan, largely attributed to colonial legacies, is further amplified due to climate change-induced water conflicts. These environmental management issues stemming from the climate crisis are urgent, demanding innovative and collaborative solutions. The primary aim of this article is to elucidate the complexities of the water conflict between India and Pakistan and propose more effective environmental management strategies that will ultimately foster regional peace and stability. The article applies the metabolic rift theory, a sociological approach, to comprehensively explain crisis-led ecological challenges in the Indo-Pak context. By applying this theory, the article reveals that collective environmental management strategies, particularly those aimed at water resource management, can significantly mitigate the impact of climate crisis and the related climate-induced conflicts. The study also proposes a need-based approach to environmental management, stressing the importance of having integrated water resource planning (harmoniously) shared between India and Pakistan. This includes ensuring sustainable wastewater treatment, securing freshwater quality, and guaranteeing an equitable distribution and utilization of water resources between these two nations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Nitrous oxide (N 2 O) is the third most potent greenhouse gas (GHG) and the most important ozone depleting substance. But how global N 2 O emissions are connected through the interwoven trade network remains unclear. This paper attempts to specifically trace anthropogenic N 2 O emissions via global trade networks using a multi-regional input-output model and a complex network model. Nearly one quarter of global N 2 O emissions can be linked to products traded internationally in 2014. The top 20 economies contribute to about 70% of the total embodied N 2 O emission flows. In terms of the trade embodied emissions classified by sources, cropland-, livestock-, chemistry-, and other industries-related embodied N 2 O emissions account for 41.9%, 31.2%, 19.9%, and 7.0%, respectively. Clustering structure of the global N 2 O flow network is revealed by the regional integration of 5 trading communities. Hub economies such as mainland China and the USA are collectors and distributors, and some emerging countries, such as Mexico, Brazil, India, and Russia, also exhibit dominance in different kinds of networks. This study selects the cattle sector to further verify that low production-side emission intensities and trade cooperation can lead to N 2 O emission reduction. In view of the impact of trade networks on global N 2 O emissions, achieving N 2 O emission reduction calls for vigorous international cooperation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Implementing unified municipal solid waste management (MSWM) is often difficult due to socio-economic variables. However, spatial GIS models and statistical analysis of solid waste characterized by the weekdays, weekends, and festivals can somewhat mitigate the variance and assist with selecting suitable waste management methods. This paper presents the example of Rajouri, India, to propose a suitable MSWM based on Inverse Distance Weighted (IDW) intensity maps and statistical findings. The considered region was divided into different sample sites based on the local population density, and Municipal Solid Waste (MSW) was collected from four locations in each site on weekdays, weekends, and festivals. Compositional analysis of the MSW was then used to generate spatial IDW models in QGIS 3.22.7 to interpolate MSW generation over the entire area. Finally, statistical analysis was conducted to gain insight into the waste generation and accumulation trends. The results show that Rajouri produces 245 tonnes of waste daily (per capita: 0.382 kg/day) with a large organic fraction compared to other waste categories. Besides, waste generation is observed to increase over weekends and festivals due to increased consumption of material goods. Composting could serve as a vector for municipal solid waste because of its increased organic component and cost constraints. However, further research on the potential segregation techniques for the organic fraction of solid waste is needed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Second-generation bioenergy, a carbon neutral or negative renewable resource, is crucial to achieving India's net-zero emission targets. Crop residues are being targeted as a bioenergy resource as they are otherwise burned on-field, leading to significant pollutant emissions. But estimating their bioenergy potential is problematic because of broad assumptions about their surplus fractions. Here, we use comprehensive surveys and multivariate regression models to estimate the bioenergy potential of surplus crop residues in India. These are with high sub-national and crop disaggregation that can facilitate the development of efficient supply chain mechanisms for its widespread usage. The estimated potential for 2019 of 1313 PJ can increase the present bioenergy installed capacity by 82% but is likely insufficient alone to meet India's bioenergy targets. The shortage of crop residue for bioenergy, combined with the sustainability concerns raised by previous studies, imply a need to reassess the strategy for the use of this resource., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Accurate estimation of carbon cycle is a challenging task owing to the complexity and heterogeneity of ecosystems. Carbon Use Efficiency (CUE) is a metric to define the ability of vegetation to sequester carbon from the atmosphere. It is key to understand the carbon sink and source pathways of ecosystems. Here, we quantify CUE using remote sensing measurements to examine its variability, drivers and underlying mechanisms in India for the period 2000-2019, by applying the principal component analyses (PCA), multiple linear regression (MLR) and causal discovery. Our analysis shows that the forests in the hilly regions (HR) and northeast (NE), and croplands in the western areas of South India (SI) exhibit high (>0.6) CUE. The northwest (NW), Indo-Gangetic plain (IGP) and some areas in Central India (CI) show low (<0.3) CUE. In general, the water availability as soil moisture (SM) and precipitation (P) promote higher CUE, but higher temperature (T) and air organic carbon content (AOCC) reduce CUE. It is found that SM has the strongest relative influence (33%) on CUE, followed by P. Also, SM has a direct causal link with all drivers and CUE; reiterating its importance in driving vegetation carbon dynamics (VCD) for the cropland dominated India. The long-term analysis reveals that the low CUE regions in NW (moisture induced greening) and IGP (irrigation induced agricultural boom) have an increasing trend in productivity (greening). However, the high CUE regions in NE (deforestation and extreme events) and SI (warming induced moisture stress) exhibit a decreasing trend in productivity (browning), which is a great concern. Our study, therefore, provides new insights on the rate of carbon allocation and the need of proper planning for maintaining balance in the terrestrial carbon cycle. This is particularly important in the context of drafting policy decisions for the mitigation of climate change, food security and sustainability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

A first hand study on guild structure of fish species (n = 148) in Ashtamudi Estuary, a Ramsar Site of International importance, was carried out from May 2019 to April 2020 based on temporal (monsoon, pre-monsoon and post-monsoon seasons) and spatial (upper, middle and lower zones) data. Guild composition consisted of eight estuarine use guilds (marine estuarine opportunist, marine estuarine dependent, estuarine resident species, anadromous species, freshwater migrants, freshwater stragglers, catadromous and marine stragglers) and eight feeding guilds (zooplanktivore, zoobenthivore, carnivores, herbivores, invertebrate feeders, omnivores, detritus feeders and piscivores). The most dominant estuarine use guilds comprised of marine migrants (marine estuarine opportunist and marine estuarine dependent), whereas carnivore, omnivore and zooplanktivore formed the dominant feeding guilds in Ashtamudi Estuary. The species diversity decreased from upper to lower zone and was highest during the post-monsoon period. The present study has seen a decrease in estuarine resident and freshwater species due to reduced freshwater inflow, saltwater intrusion, unsustainable fishing and inadequate environmental management practices. Hence, we propose a management framework to improve the ecosystem of Ashtamudi Estuary with a special focus on its fish species and their estuarine use., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Sensitivity analysis determines how perturbation or variation in the values of an independent variable affects a particular dependent variable. The present study attempts to comprehend the sensitivity of the static input parameters on the accuracy of the outputs in a hydrodynamic flood model, which subsequently improves the model accuracy. Hydrodynamic flood modeling is computationally strenuous and data-intensive. Moreover, the accuracy of the flood model outputs is extremely sensitive to the quality of hydrologic and hydraulic inputs, along with a set of static parameters that are traditionally assumed and primarily used for calibration. Therefore, we focus on developing a framework for global sensitivity analysis (GSA) of static input parameters in a 1D-2D coupled hydrodynamic flood modeling system. A set of numerical experiments is conducted by perturbing various combinations of input parameters from their standard (or observed) values to generate flow hydrographs. Nonparametric probability density functions (PDFs) of the river discharge at different locations are compared to calculate the Kullback-Leibler (KL) entropy or KL-divergence, which is used to quantify the sensitivity of the input parameters. We demonstrated the proposed framework on a highly flood-prone rural catchment of the Shilabati River in West Bengal, India, and infer that the sensitivity of the static input parameters is highly dynamic, and their importance varies spatially from the upstream to the downstream of the river. However, Manning's n values of the channel and the banks are significantly sensitive irrespective of the location in the river reach. We suggest that any flood modeling exercise should accompany a GSA, which sets a guideline for the modelers to prioritize the set of sensitive static input parameters during data monitoring, collection, and retrieval. This study is the first attempt at a GSA in a 1D-2D coupled hydrodynamic flood modeling system, whose importance cannot be over-emphasized in any flood modeling platform. The proposed novel framework is generic and can be implemented prior to flood risk analyses for any floodplain management exercise. All free and commercially-available flood models can incorporate the proposed framework for a GSA as an extension toolbox., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

-Enhancing the productivity of rainfed crops, especially rice, while coping with climate adversities and saving critical natural resources is essential for ensuring the food and nutrition security of a growing population. With this context, the present study was undertaken to validate promising farm innovation and adaptation practices used by small-medium landholding farmers for rice cultivation in eastern Uttar Pradesh (UP), north India, as well as to examine the sustainability of innovative practices for large-scale adoption. For this, a 3-year study comprising extensive field surveys and experiments was undertaken to compare single transplantation (ST) and double transplantation (DT) in rice along with organic addition (farm-yard manure, FYM) on crop growth, yield, climate resilience, soil quality, and overall sustainability i.e., social (women involvements and labour productivity), environmental (water productivity and nutrient use efficiency), and economic (benefit:cost ratio) dimensions of sustainability. Field experiments were conducted in triplicate using two local rice varieties (MotiNP-360 and Sampurna Kaveri) in two agroclimatic zones, namely the middle Gangetic plains and the Vindhyan zone, in the Mirzapur district of eastern Uttar Pradesh. The DT practices of rice with and without farm yard manure (FYM) (replacing at a dose of 25% NPK) were evaluated over conventional methods of rice cultivation (i.e., ST, as control) and analysis was done periodically. The DT practice improved growth (p < 0.05), percent fertile tiller and grain (p < 0.05), and rice yield (15-20% higher than ST), while also improving soil quality, yield indices, water and labour productivity, and the benefit-cost ratio. The DT practice also resulted in early maturity (10-15 days earlier than ST), created more labour days for women, decreased lodging and pest/disease incidence, as well as a subsequent reduction in the use of synthetic chemical pesticides and associated environmental costs. Importantly, the residual effects of FYM application significantly improved (p < 0.05) the grain yield in subsequent years of cropping. Optimizing DT cultivation practices, preferably with FYM input for various agro-climatic regions, is essential for large-scale sustainable rice production under changing climatic conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Lockdowns enforced amid the pandemic facilitated the evaluation of the impact of emission reductions on air quality and the production regime of O 3 under NOx reduction. Analysis of space-time variation of various pollutants (PM10, PM2.5, NOx, CO, O 3 and VOC or TNMHC) through the lockdown phases at eight typical stations (Urban/Metro, Rural/high vegetation and coastal) is carried out. It reveals how the major pollutant (PM10 or PM2.5 or O 3 , or CO) differs from station to station as lockdowns progress depending on geography, land-use pattern and efficacy of lockdown implementation. Among the stations analyzed, Delhi (Chandnichowk), the most polluted (PM10 = 203 μgm -3 ; O 3  = 17.4 ppbv) in pre-lockdown, experienced maximum reduction during the first phase of lockdown in PM2.5 (-47%), NO 2 (-40%), CO (-37%) while O 3 remained almost the same (2% reduction) to pre-lockdown levels. The least polluted Mahabaleshwar (PM10 = 45 μgm -3 ; O 3  = 54 ppbv) witnessed relatively less reduction in PM2.5 (-2.9%), NO 2 (-4.7%), CO (-49%) while O 3 increased by 36% to pre-lockdown levels. In rural stations with lots of greenery, O 3 is the major pollutant attributed to biogenic VOC emissions from vegetation besides lower NO levels. In other stations, PM2.5 or PM10 is the primary pollutant. At Chennai, Jabalpur, Mahabaleshwar and Goa, the deciding factor of Air Quality Index (AQI) remained unchanged, with reduced values. Particulate matter, PM10 decided AQI for three stations (dust as control component), and PM2.5 decided the same for two but within acceptable limits for stations. Improvement of AQI through control of dust would prove beneficial for Chennai and Patiala; anthropogenic emission control would work for Chandani chowk, Goa and Patiala; emission control of CO is required for Mahabaleshwar and Thiruvanathapuram. Under low VOC/NOx ratio conditions, O 3 varies with the ratio, NO/NO 2 , with a negative (positive) slope indicating VOC-sensitive (NOx-sensitive) regime. Peak O 3 isopleths as a function of NOx and VOC depicting distinct patterns suggest that O 3 variation is entirely non-linear for a given NOx or VOC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Global meat consumption is on a rise with around 253 million metric tons of meat produced globally in the year 2020. Because of the rise in population and change in food preferences, meat consumption trend is likely to continue. Meat production by animal slaughtering increases the slaughterhouse wastes in the form of both solid and liquid wastes. Although various technologies for slaughterhouse waste management are available in developed countries, the effective utilization of slaughterhouse waste management is still missing in developing countries like India. India plays an active role in the meat export business globally and stood 2nd in the world with a total export valuation of 2.89 billion US $ in the year 2020. In this context, this study presents a critical overview of the current technological advancements in the global slaughterhouse waste management including utilization of by-products and further, the prevailing slaughterhouse waste management of India is discussed. Finally, a sustainable slaughterhouse waste management strategy emphasizing circular economy and regulations improvements have been suggested for India to compete in this sector at global scale., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The transition of the Earth's climate from one zone to another is one of the major causes behind biodiversity loss, rural-urban migration, and increasing food crises. The rising rate of arid-humid zone transition due to climate change has been substantially visible in the last few decades. However, the precise quantification of the climate change-induced rainfall variation on the climate zone transition still remained a challenge. To solve the issue, the Representative Grid Location-Multivariate Adaptive Regression Spline (RGL-MARS) downscaling algorithm was coupled with the Koppen climate classification scheme to project future changes in various climate zones for the study area. It was observed that the performance of the model was better for the humid clusters compared to the arid clusters. It was noticed that, by the end of the 21 st century, the arid region would increase marginally and the humid region would rise by 24.28-36.09% for the western province of India. In contrast, the area of the semi-arid and semi-humid regions would decline for the study area. It was observed that there would be an extensive conversion of semi-humid to humid zone in the peripheral region of the Arabian sea due to the strengthening of land-sea thermal contrast caused by climate change. Similarly, semi-arid to arid zone conversion would also increase due to the inflow of dry air from the Arabian region. The current research would be helpful for the researchers and policymakers to take appropriate measures to reduce the rate of climate zone transition, thereby developing the socioeconomic status of the rural and urban populations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Heavy metals contamination in sediment poses serious threats to bacterial communities that play critical roles in sediment biogeochemical processes. However, the physicochemical factors and the major heavy metals fractions that affect sediment bacterial communities are still unclear. Here, we performed heatmap and redundancy analyses to examine the effects of physico-chemical characteristics and heavy metals fractions on the sediment bacterial community from rivers in the UK (River Tyne and Ouseburn) and India (River Ganga and Yamuna). The results revealed that physicochemical characteristics and heavy metals fractions altered the diversity, richness, and structures of the bacterial community. Moreover, the fractions of Co, Zn, Pb, Cr, and Cu played significant roles in shaping the bacterial community structure, and physicochemical variables, particularly NH 4 + -N and NO 2 - -N, also influenced the bacterial diversity and structure. Firmicutes showed strong associations with both physicochemical factors and heavy metals fractions. Chloroflexi and Actinobacteriota can be used as biomarkers for Zn contamination. Overall, our study identified the significance of sediment chemical characteristics and heavy metals fractions in determining the bacterial community structure as well as bioremediation and environmental management of metals contaminated sites., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Impact of heavy metal (HM) pollution and its understanding on environment as well as human beings has grown a lot during the last few decades. The goal of this study is to create a scientometric study on heavy metal contamination, in the period 1989 to 2020, in order to provide futuristic goals for the new researchers on wastewater treatment. For this, a search was conducted in the Web of Science (WoS) and Scopus databases, related to heavy metal pollution. Totally, 37,154 records were collected during the study period from 1989 to 2020. The findings revealed that China, the United States, and India has most referenced papers across a wide range of trans disciplinary issues such as toxicity, technology, and pollution. As a result, this study concludes that more research on various treatment methods is required in order to obtain high-quality water for consumption and routine activities, with the incorporation of various treatment tasks poses various challenges for the upcoming future studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The ever-growing concern of sustainability and survivability attracts academicians and practitioners to develop strategies and supply chain capabilities that cater to the challenges and helps in achieving the sustainability development goals. There is a need to develop a holistic model that facilitates understanding the relationships among supply chain practices, industry 4.0 technologies, and supply chain performance measures. Thus, this study examines the mediating effect of industry 4.0 technologies on supply chain management practices and supply chain performance measures. A survey-based data was collected from manufacturing organizations across India, and 361 complete responses were obtained. Structural equation modeling (SEM) was utilized for data analysis. This study has multiple contributions. First, the results indicate that the supply chain management practices influence the industry 4.0 technologies adoption. Second, the results also revealed that the industry 4.0 technologies significantly positively affect supply chain performance measures. Finally, industry 4.0 technologies mediated the relations between supply chain management practices and supply chain performance measures. Furthermore, the findings offer important insights into understanding the underlying mechanisms in successfully adopting and effectively using industry 4.0 technologies. The implications for theory and practices are also discussed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This study investigates the co-benefits from the utilization of the battery-electric bus (BEB) fleet in the Delhi public transportation system as a part of the Delhi electric vehicles policy 2020. To this aim, an integrated quantitative assessment framework is developed to estimate the expected environmental, health, and economic co-benefits from replacing the currently existing public bus fleet with the new BEBs in Delhi. First, the model estimates the avoided emissions from deploying the BEB fleet, using a detailed battery energy simulation model, considering the impact of the battery capacity loss on the annual operational time (hours of service) of the BEB. The annual operational time of the BEB is greatly affected by its battery degradation, which results in time lost due to charging the battery. This indicates that the annual passenger-kilometer (PKM) delivered by the BEB is less than the regular bus, under the same traveling condition. Second, considering fine particles (PM 2.5 ) as the most health-harming pollutant, the model calculates the near roadway avoided PM 2.5 exposure in the selected traffic zones of 11 major districts of Delhi, using a Gaussian dispersion model. Third, the near roadway avoided PM 2.5 exposure is further used in a health impact assessment model, which considers concentration-response functions for several diseases to evaluate the public health benefits from introducing the BEB fleet in Delhi. The research findings indicate that, the utilization of the new BEB fleet leads to a 74.67% reduction in the total pollutant emissions from the existing bus fleet in Delhi. The results of the integrated co-benefits assessment reveal a significant reduction in PM 2.5 emissions (44 t/y), leading to avoidance of mortality (1370 cases) and respiratory diseases related hospital admissions (2808 cases), respectively, and an annual savings of about USD 383 million from the avoided mortality and morbidity cases in Delhi., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)