Department of Environmental Science and Engineering

The rise in the production, utilization and disposal of mobile phones has created a global concern for environmental sustainability. In the present research, environmental impact evaluation for the different life stages of mobile phones was performed using the life cycle assessment (LCA) approach. The study was focused mainly on raw materials extraction and network utilization phase as these two stages are responsible for creating most of the environmental pollution and health hazards. A comparative life cycle assessment was performed to evaluate impacts associated with button- and touch types mobile phones. IMPACT 2002 + ® method was considered to evaluate the environmental impacts. Fifteen mid-point and four damage assessment categories were evaluated. The production phase is the major emission contributing stage to human health, ecosystem quality, climate change and resources categories followed by its utilization phase. Printed circuit board manufacturing contributes to the emission in production phase while electricity consumption in utilization phase. Avoidance of virgin material for the production of mobile phones and its charging is identified as key parameters for improving the environmental performance. © The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University 2024.

Bioremediation is an effective and sustainable method for removing xenobiotic pollutants from the environment, utilizing microorganisms and plants to metabolize harmful chemicals into harmless compounds like CO2 and water. Among various bioremediation strategies, mycoremediation stands out due to the unique enzymatic capabilities and metabolic diversity of fungi, enabling them to degrade persistent and toxic pollutants under harsh environmental conditions. This review specifically addresses the application of mycoremediation to emerging contaminants pharmaceuticals and personal care products (PPCPs) which pose significant environmental challenges due to their persistence, bioaccumulation potential, and ecotoxicity. This article provides a comprehensive overview of fungal-based strategies for PPCP remediation, documenting the fate, distribution, and impacts of these contaminants in soil. It highlights the enzymatic mechanisms and fungal species involved in PPCP degradation, with an emphasis on their ecological resilience and pollutant-specific adaptability. Additionally, the review explores under-discussed factors influencing fungal efficacy, such as pH, temperature, and contaminant concentration, alongside innovative advancements like myco-nanotechnology and enzyme engineering that enhance remediation efficiency. By integrating these aspects with policy perspectives and sustainable development goals, this review contributes novel insights into the potential of mycoremediation as a cutting-edge approach for mitigating PPCP contamination. It underscores the role of fungi in advancing circular economy principles and offers a foundation for future research and practical applications in environmental management. © 2025 The Authors

The need for a green and sustainable nanomaterial sourced from biomass in the form of nanochitin has raised interest in paving the way towards incorporating biological resources for the production of functional materials. Nanochitin as nanofibers and nanocrystals/whiskers have attractive features like their ability to self-assemble into multidimensional biomaterials while retaining their intrinsic characteristics. Herein, the review discusses chitin's molecular association and hierarchical assemblies and gives an overview of the extraction methods adopted to produce nanochitin. Recent progress in the development of advanced functional nanochitin-based materials/composites and their current application in agriculture and environmental remediation are reviewed to gain a better understanding of their applicability for forthcoming research and improvement. Furthermore, the environmental impact assessment of chitin has been discussed, followed by the techno-economic analysis, thus providing scope for improvement in manufacturing and perspectives on the potential of nanochitin in the context of sustainable material and their role in circular bioeconomy. © 2025 Elsevier B.V.

Rare earth elements (REEs) play a vital role in digitalization and industrialization. Naturally occurring in bastnasite, monazite, and xenotime, REEs are primarily concentrated in China, Australia, and the USA, leading to dependence on secondary sources. Recycling REEs from industrial waste such as E-waste, wastewater, red mud, slag, and fly ash offers a sustainable, low-emission, and energy-efficient solution. Advanced methods, including bio-metallurgy, have optimized recovery, achieving 80–95% efficiency for elements like Yttrium, Cerium, Neodymium, and Thorium. However, improper handling of secondary REE resources poses environmental and health risks. This study comprehensively explores REEs’ role in sustainable industrial growth, evaluating traditional and advanced recycling technologies. It also assesses the ecotoxicological impacts of REEs and emphasizes safety measures. Additionally, the review highlights circular economy strategies for sustainable development, addressing environmental challenges while promoting efficient resource utilization. © 2025 The Authors

A broad range of artificial or naturally occurring chemicals known as emerging contaminants (ECs) are increasingly found in landfill leachate and provide serious dangers to human health and the environment. This critical analysis investigates the origin, dispersion, and effects of ECs in relation to landfill settings. Landfills serve as EC reservoirs because of the diverse mix of e-waste, industrial compounds, pharmaceuticals, personal care items, and endocrine-disrupting chemicals. Factors including landfill design, waste type, and environmental conditions affect the mobility and permanence of these toxins as they seep into nearby soils, groundwater, and surface water through leachate. ECs have been found in trace amounts in the landfill leachate, and are polar substances having a brief half-life. Concerns over the consequences of newly discovered contaminants on the environment and human health have grown because of their increased detection in the landfill leachate. Additionally, they increase the hazards to human populations by having the ability to pollute agricultural soils and sources of drinking water. The significant finding is that the ECs in landfill leachate can be generated from various sites whether it is from municipal solid wastes, agricultural runoffs, or industrial wastes which become persistent in nature increasing risk to human health and environment. The study identifies important knowledge gaps regarding the development of harmful transformation products, the collective effects of EC combinations, and the inadequacy of traditional treatment techniques in reducing EC pollution. By this it can be concluded that advanced analytical methods, creative leachate treatment approaches, and strong regulatory frameworks are needed to address these issues and successfully stop EC discharge and control its negative effects on the environment and human health. In order to reduce the hazards caused by newly discovered pollutants in landfill leachate and to support environmentally friendly waste management techniques, this analysis emphasizes the necessity of both international and regional initiatives. © 2025 The Author(s)

Water pollution from Heavy metal (HM) contamination poses a critical threat to environmental sustainability and public health. Industrial activities have increased the presence of HMs in wastewater, necessitating effective remediation strategies. Conventional methods like chemical precipitation, ion exchange, adsorption, and membrane filtration are widely used but possess various limitations. These include high costs, environmental impacts, and the potential for generating secondary pollutants, highlighting the need for sustainable alternatives. Phytoremediation, enhanced by microbial interactions, offers an eco-friendly solution to this issue. The unique physiological and biochemical traits of plants, combined with microbial metabolic capabilities, enable efficient uptake and detoxification of HMs. Microbial enzymes play a crucial role in these processes by breaking down complex compounds, enhancing HM bioavailability, and facilitating their conversion into less toxic forms. Synergistic interactions between root-associated microbes and plants further improves metal absorption and stabilization, boosting phytoremediation efficiency. However, challenges remain, including the limited bioavailability of contaminants and plant resilience in highly polluted environments. Recent advancements focus on improving microbial-assisted phytoremediation through mechanisms like bioavailability facilitation, phytoextraction, and phytostabilization. Genetic engineering facilitates the altering of genes that control plant immune responses and growth which improves the ability of plants to interact beneficially with microbes to thrive in HM rich environments while efficiently cleaning contaminated wastewater. This review examines these strategies and highlights future research directions to enhance wastewater remediation using phytoremediation technologies. © 2025 Elsevier Ltd

Jharkhand is a mineral-rich state and there are many possibilities in pisciculture. Fish is the staple food of Jharkhand because of its nutritional values. In the present study, water, sediment, and the most favorite fish species (Labeo rohita, Catla catla, Cirrhinus mrigala, Cyprinus carpio, and Ctenopharyngodon idella) were collected from the lentic reservoirs and analyzed for assessing the ecological and human health risk assessment. The mean concentrations of Cd, Cr, Cu, Pb, and Zn in water samples varied within the ranges of 0.001–0.004 mg/L, 0.02–0.04 mg/L, 0.004–0.007 mg/L, 0.023–0.081 mg/L, and 0.003–0.12 mg/L, respectively. In sediment samples, the metal concentrations were recorded within the following ranges: 109.15–411.48 mg/kg for Zn, 0.79–22.87 mg/kg for Cd, 22.71–34.79 mg/kg for Pb, 93.44–581.38 mg/kg for Cr, and 19.61–129.09 mg/kg for Cu. The average concentrations of metals in fish were observed as follows: 82.98 − 91.81 mg/kg of Zn, 20.91 − 31 mg/kg of Cd, 81.48 − 91.81 mg/kg of Pb, 442.68 − 482.50 mg/kg of Cr, and 35.91 − 68.57 mg/kg of Cu. Ecological health assessment based on sediment indices shows the prevalence of Cd in the lentic ecosystems and their bioaccumulation (biota-sediment accumulation factor > 2) in fish species. Among the four reservoirs, HD is the most contaminated site. Local population, especially, children of Ranchi district, consuming fish species are prone to health risk due to the metal contamination. Conclusively, this study provides valuable data on metal concentrations in fish species, supporting future ecotoxicology research and policymaking for any mineral-rich state. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

Climate change and environmental degradation require computational environmental engineering. To simulate and optimize complex environmental processes, advanced computer models, big data analytics, and machine learning are used. A holistic assessment of environmental consequences and the design of interdisciplinary solutions that take into account socioeconomic, environmental, and environmental variables can be possible with the creation of integrated modeling frameworks that reflect the interconnected nature of environmental systems. Increasingly high-resolution remote sensing data and sensor networks enable real-time monitoring and decision-making about the environment. The use of these data streams in conjunction with computational models improves environmental predictions, allowing better management of natural resources and risk reduction. The most challenging aspects are improving model validation and uncertainty quantification, developing robust optimization algorithms, and ensuring accessibility for stakeholders of varying backgrounds. Lastly, computational environmental engineering offers significant promise for addressing future environmental problems by incorporating interdisciplinary approaches, using emerging technologies, and addressing important issues. Previous Chapter. © 2025 selection and editorial matter, Akhilesh Kumar Yadav; individual chapters, the contributors.

In order to achieve sustainable waste management solutions, we must integrate computational approaches to meet the challenges posed by escalating waste generation. Waste management and recycling are explored comprehensively in this book chapter with a focus on various computational tools and analyses. This chapter addresses a technologically driven approach to problem-solving based on diverse disciplines, such as Geographic Information Systems (GIS), optimization models, life cycle assessments, artificial intelligence, and sensor technology. This chapter examines GIS applications and explores how spatial analysis and mapping contribute to site selection for waste disposal facilities and route optimization for waste collection. Following this, it discusses optimization models, demonstrating mathematical methodologies used to improve decision-making processes, including linear programming and network optimization. Simulators are discussed in the context of predicting and understanding waste management processes, elucidating their role in this process. Various waste treatment methods are evaluated in detail in relation to the impact of life cycle assessment on the environment, highlighting the importance of this tool in evaluating environmental impacts. In addition, artificial intelligence and machine learning are discussed as tools to analyze data, recognize patterns, and optimize waste management processes. An overview of computational approaches shaping waste management and recycling is presented in this book chapter. It seeks to provide academics, practitioners, and policymakers with a basis for using technology breakthroughs for the creation of sustainable and effective waste management systems by clarifying the uses and advantages of these instruments. © 2025 selection and editorial matter, Akhilesh Kumar Yadav; individual chapters, the contributors.

The continuous release of heavy metals (HMs) from nearby industries leads to the contamination of surrounding agricultural areas. This study employed an integrated approach, combining contamination factor (CF), enrichment factor (EF) and geo-accumulation index (Igeo) for pollution assessment, alongside source apportionment using principal component analysis (PCA) and Geographic Information System (GIS)-based positive matrix factorization (PMF), to evaluate HM contamination in agricultural soils of the northeast Guntur district, India. The mean concentrations of HMs, Cu, Cr, Zn, Ni, Cd and Pb exceeded the Indian natural background soil values by 2.59, 1.21, 2.24, 2.09, 1.15 and 1.4 respectively. Pollution indices revealed high contamination for Ni (CF = 2.21) and Cr (CF = 2.05), with Cr showing moderate enrichment (EF ≈ 1.5) and contamination (Igeo = 0.75). PCA identified three components explaining 78.37% of the total variation while GIS-based PMF identified industrial discharges, waste incineration, agriculture and vehicular and industrial emissions as pollution sources. Ni, Cu and Cr were identified as the primary contaminants, with industrial emissions, vehicular traffic and agricultural activities as key contributors to HM pollution. Cr accounted for ~ 80% of the total hazard index, posing significant non-carcinogenic risks for children via ingestion. Carcinogenic risks through ingestion of Ni and Cr were 2.8 and 1.9 times higher than acceptable levels for adults and 3.9 and 2.6 times higher than acceptable levels for children. Additionally, the high bioconcentration factor (BCF) of Lantana viburnoides (Forssk.) with a BCF of 18.29 for Cd suggests a potential environmental hazard. It is imperative to monitor emissions rigorously to safeguard soil quality and optimize industry standards in this region. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

Microalgae-based wastewater treatment has resulted in a paradigm shift toward nutrient removal and simultaneous resource recovery. However, traditionally used microalgal biomass quantification methods are time-consuming and costly, limiting their large-scale use. The aim of this study is to develop a simple and cost-effective image-based method for microalgae quantification, replacing cumbersome traditional techniques. In this study, preprocessed microalgae images and associated optical density data were utilized as inputs. Three feature extraction methods were compared alongside eight machine learning (ML) models, including linear regression (LR), random forest (RF), AdaBoost, gradient boosting (GB), and various neural networks. Among these algorithms, LR with principal component analysis achieved an R2 value of 0.97 with the lowest error of 0.039. Combining image analysis and ML removes the need for expensive equipment in microalgae quantification. Sensitivity analysis was performed by varying the train-test splitting ratio. Training time was included in the evaluation, and accounting for energy consumption in the study leads to the achievement of high model performance and energy-efficient ML model utilization. © 2024 American Chemical Society.

Disturbance intensity plays an important role in influencing the structural and functional dynamics of ecosystems. The present study was undertaken in the tropical dry deciduous forests of Central India under varying disturbance intensities to understand their influence on structure, diversity and compositional attributes. In total, 242 rectangular plots of 0.5 ha each (50 m × 100 m) were laid in each 8 km2 grid for phytosociological analyses and assessment of disturbance factors and levels. The plots were categorized into four types based on the level of disturbance intensity: 0–20 % {undisturbed forest (UDF)}, 21–40 % {least disturbed forest (LDF)}, 41–60 % {moderately disturbed forest (MDF)} and >60 % {highly disturbed forest (HDF)}. Among the 242 plots, 48, 56, 72 and 66 plots come under UDF, LDF, MDF and HDF categories respectively. The predominant disturbance factors in HDF were fire and fuelwood collection, whereas in the case of MDF, grazing and cut stems were dominant. A total of 202 species (120 genera, 45 families) of adult trees (≥10 diameter at breast height (DBH)) were recorded across the disturbance intensity gradient, with highest species richness in UDF (175 species) and the lowest in HDF (145 species). A significant variation in the stand structure, species composition, richness and tree diversity (Shannon (H′) and Simpson (D) index) has been found across the disturbance intensity gradients. The plots with the highest disturbance intensity (HDF) had the significantly lowest tree density (p < 0.001), basal area (p < 0.001), species richness (p < 0.001), and tree diversity: H′ (p < 0.01), D (p < 0.01) than UDF, LDF and MDF intensity gradients. The diameter-class distribution showed high percentage of small-sized (11–30 cm) trees in UDF (68 %) and LDF (60 %), whereas the medium-sized trees (31–60 cm) were high in MDF (48 %) and HDF (53 %) respectively. The current findings highlight the profound impact of varying disturbance intensities on stand structure, composition and diversity, emphasizing an urgent need for restoration, protection, conservation, and sustainable management for long-term ecosystem services. © 2025 The Author(s)

Treeline ecotone in the Himalayan region is a relevant ecological indicator of environmental perturbations and anthropogenic disturbances. Given this, six representative sites (3 each in protected and non-protected areas) were selected for assessing forest dynamics and anthropogenic disturbances in treeline ecotone in the western Himalaya. The study reveals that treelines under protected areas show higher species richness (27) and species diversity (3.42) compared to species richness (17) and species diversity (2.22) in the non-protected areas. The average TBA of tree species was higher (36) at protected sites compared to 27 in the non-protected sites. Further, the average density of seedlings (7587) and saplings (633) was higher in protected sites than in non-protected sites (seedlings-1720 & 263-saplings). Thus, the better regeneration of dominant tree species with an expanding population structure in the protected area. This showed the efficient role of protected sites in biodiversity conservation and management. Livestock grazing and fuelwood harvesting were the key human-induced pressures in the non-protected sites. Fuelwood consumption was recorded as a maximum (5.4 kg/capita/day) for Kuti village (3800 m) in the Byans Valley, followed by Sipu (3.4) in Darma Valley and a minimum for Martoli (2.4) in Johar Valley. Anthropogenic disturbances have impacted the regeneration and recruitment of tree species in treeline ecotone in the non-protected sites. An increasing number of seedlings and saplings was observed in an open canopy of treeline ecotone, which indicates an expanding number of seedlings and saplings was observed in the open canopy treeline ecotone, which suggests the possibility of expansion of tree species towards higher elevations. Long-term ecological monitoring and observation are suggested to understand better spatial and temporal changes in treeline ecotone considering climate change and anthropogenic disturbances. © 2025 The Author(s)

Rubus ellipticus Sm. is native to the northern hemisphere particularly in south east Asia. Several phytochemicals including gallic acid, beta-carotene, tormentic acid, histidine, leucine, quinic acid, sericic acid and ursolic acid have been extracted from various parts of the plant. The plant has also been shown to contain minerals such as calcium, sodium, phosphorous, potassium, magnesium, sodium, iron, zinc, copper, lead, manganese and chromium. Owing to the presence of such biologically active chemicals, the extract of the plant shows several pharmacological activities like antinflmatory, antidiabetic, antimicrobial, antiproliferative, antitumor and anticancer. Moreover, the plant is being traditionally used to treat hypothermia, colic pains, cure fever, cough, diarrhea, antifertility, stomach pain, constipation and mouth ulcers. In this study we are providing the updated information in progress of research related to his plant. The current study focuses on its morphology, nutritional value, photochemistry, ethnobotanical uses, economic significance and commercialistaion prospects. It acknowledges the fragmented nature of existing knowledge suggesting that consolidating available data could aid researchers in maximizing its potential benefits particularly in pharmaceutical and agricultural applications. © The Author(s) under exclusive licence to Society for Plant Research 2025.

Ecosystem functioning and management are primarily concerned with addressing climate change and biodiversity loss, which are closely linked to carbon stock and species diversity. This research aimed to quantify forest understory (shrub and herb) diversity, tree biomass and carbon sequestration in the Binsar Wildlife Sanctuary. Using random sampling methods, data were gathered from six distinct forest communities. The study identified 271 vascular plants from 208 genera and 74 families. A notable positive correlation (r2 = 0.085, p < 0.05) was observed between total tree density and total tree basal area (TBA), shrub density (r2 = 0.09), tree diversity (D) (r2 = 0.58), shrub diversity (r2 = 0.81), and tree species richness (SR) (r2 = 0.96). Conversely, a negative correlation was found with the concentration of tree dominance (CD) (r2 = 0.43). The Quercus leucotrichophora, Rhododendron arboreum and Quercus floribunda (QL-RA-QF) community(higher altitudinal zone) exhibited the highest tree biomass (568.8 Mg ha−1), while the (Pinus roxburghii and Quercus leucotrichophora) PR-QL (N) community (lower altitudinal zone) in the north aspect showed the lowest (265.7 Mg ha−1). Carbon sequestration was highest in the Quercus leucotrichophora, Quercus floribunda and Rhododendron arboreum (QL-QF-RA) (higher altitudinal zone) community (7.48 Mg ha−1 yr−1) and lowest in the PR-QL (S) (middle altitudinal zone) community in the south aspect (5.5 Mg ha−1 yr−1). The relationships between carbon stock and various functional parameters such as tree density, total basal area of tree and diversity of tree showed significant positive correlations. The findings of the study revealed significant variations in the structural attributes of trees, shrubs and herbs across different forest stands along altitudinal gradients. This current study’s results highlighted the significance of wildlife sanctuaries, which not only aid in wildlife preservation but also provide compelling evidence supporting forest management practices that promote the planting of multiple vegetation layers in landscape restoration as a means to enhance biodiversity and increase resilience to climate change. Further, comprehending the carbon storage mechanisms of these forests will be critical for developing environmental management strategies aimed at alleviating the impacts of climate change in the years to come. © 2025 by the authors.

Prioritizing native and endemic species for conservation is fundamental to achieve broader objectives of safeguarding biodiversity, as these species are vulnerable to extinction risks. Forecasting the climatic niche of these species through species distribution models can be crucial for their habitat conservation and sustainable management in future. In this study, an ensemble modelling approach was used to predict the distribution of Bergenia stracheyi, a native alpine plant species of Himalayan region. The results revealed that the distribution of B. stracheyi is primarily influenced by Annual Mean Temperature (Bio1) and Annual Precipitation (Bio12). Ensemble model predictions revealed that under the current climatic conditions, the suitable habitats for B. stracheyi are distributed across higher elevations of Jammu and Kashmir and future ensemble model predictions indicate that, across all future climatic scenarios, the majority of the currently suitable habitats will remain suitable for the species. The model predicts a significant expansion in suitable habitats for B. stracheyi, particularly under more severe climate change scenarios (RCP8.5). However, some areas currently identified as suitable, including parts of the Pir Panjal range and Mirpur (Pakistan), are projected to become unsuitable for the species in the future. These shifts in plant distribution may have far-reaching consequences for ecosystem functioning and stability and the services provided to human communities. Additionally, these shifts may lead to mismatches between the plant phenological events and pollinators potentially causing more ecological disruptions. Thus, the predicted range shifts in the distribution of B. stracheyi highlight the importance of local conservation measures to mitigate the impacts of climate change. Copyright © 2025 Wani, Dar, Lone, Pant and Siddiqui.

Hydrogen, a carbon-free fuel, has the potential to aid global nations in achieving eight of the 17 Sustainable Development Goals (SDG). The shortcomings associated with H2 transportation and storage can be mitigated by using NH3 as hydrogen carrier because of its better safety, physical, and environmental properties. However, to achieve the global climate target, green ammonia production must be incremented by four times (688 MT) from the current level. Hence, understanding of advanced green NH3 production and storage technologies, along with the factors that influence them becomes necessary. It also aids in identifying the factors hindering green H2 and NH3 production, which can be resolved by promoting research. At the same time, drafting policies that encourage green H2 and NH3 production can abet in overcoming the bottleneck faced by the industry. Presently, green ammonia production can be made feasible only when the renewable electricity cost is less than $20/MWh and carbon price of $150/t of CO2 emissions is levied. Approximately 80 % of the energy consumed during NH3 is spent on H2 generation; therefore, it is necessary to enact policies that promote green H2 production globally. Producing green H2 can aid in mitigating ∼90 % of the greenhouse gases emitted during NH3 manufacturing thereby facilitating to reduce the carbon footprint of H2 carrier and decarbonize NH3 industry. © 2025 Elsevier B.V.

The use of micro-algae for wastewater treatment is a promising technique that contributes to CO2 capture and nutrient recovery. However, the lack of effective forecasting models limits the scalability of this technique. This study aims to develop a time-series-based forecasting model to predict the growth curve of microalgal biomass under environmental conditions similar to those found in wastewater. Data collected on microalgal growth was used to train six time-series models: Long Short-Term Memory (LSTM), Extreme Gradient Boosting (XGBoost), Auto-Regressive Integrated Moving Average (ARIMA), Random vector functional link (RVFL), Physics-informed neural networks (PINN) and Prophet. The model performance metrics were compared, and the best model was identified. The results demonstrated that the RVFL was the most accurate model, with minimal prediction errors ( < 0.01). Residual analysis confirmed a normal distribution of errors without outliers, supporting the model's reliability. These findings suggest that the proposed RVFL model can effectively forecast microalgal growth, potentially reducing the need for costly and labour-intensive laboratory trials and advancing microalgae-based wastewater treatment. © 2025 The Institution of Chemical Engineers

Microalgae cultivation is gaining interest as a sustainable alternative to the conventional wastewater (WW) treatment and nutrient recovery. Current study presents a comprehensive life cycle assessment (LCA) of microalgae cultivation in distinct wastewaters. Two different microalgae species in three different wastewaters were compared for sustainability performance in six scenarios. LCA was conducted using SimaPro (v9.3.0.3) and ReCiPe 2016 Midpoint method. The findings of the study reveal that global warming potential ranged between −678 and − 1357 g CO2eq./m3. Chlorella sp. cultivated in dairy WW shown higher environmental performance across the scenarios with GWP of −1357 g CO2eq./m3. The average global warming potential (GWP) of single-pot microalgae-based wastewater treatment got reduced by 240 %. The key inference of this study is that cultivation of the microalgae as single-pot treatment system not only helps in environmental sustainability but also holds significant promise for combating climate change as negative emission technology (NET). © 2025 Elsevier Ltd

Rooftop Rainwater Harvesting (RRWH) offers a viable solution to the pressing issue of saline groundwater in regions like Ainavolu, a village in Andhra Pradesh, India. This study examines the potential of RRWH systems to provide a sustainable alternative water source in rural settings faced with water scarcity due to saline groundwater. Firstly, in view of the limitation in terms of spatial resolution associated with satellite imagery, a UAV-based survey is conducted to create a high-resolution orthomosaic of the study region, enabling precise delineation and classification of rooftop materials to estimate harvestable rainwater. Findings of this study suggest that RRWH could significantly alleviate water shortages by potentially collecting approximately 20.16 million litres of rainwater annually. However, despite this substantial capacity, the adoption of RRWH remains limited due to financial, technical, behavioural, and institutional factors. Through comprehensive fieldwork, including focus group discussions and one-on-one interactions, we identified 17 critical factors hindering RRWH adoption. Based on these insights, we propose a tailored roadmap to promote RRWH implementation, incorporating strategies such as partnerships with local vendors, specialized training programs, subsidies, and targeted awareness campaigns. This study not only underscores the practicality of RRWH in offsetting the challenges posed by unsuitable groundwater but also provides a scalable model for enhancing water security through community-based initiatives and technological integration. Since the scenario of water scarcity and responses of residents change with the cultural and economic characteristics, it is suggested to update the factors while adopting the proposed framework. © The Author(s) 2025.