Advances in Environmental Sustainability, Energy and Earth Science

Segregation of waste is a key component of the waste management system. To attain high-quality recycled plastics, reduce pollution, and for a cleaner environment, sorting waste is vital. Manual sorting of waste can be inefficient due to human error and difficulty in separating different plastic types. It also causes several health issues for the workers. In medium- to high-volume factories, automated technology plays a critical role in the sorting of plastic materials. Accordingly, in this chapter, we have focused on different types of automated sorting techniques like direct and indirect sorting of plastics from municipal solid waste. The use of robots in sorting materials, such as plastic, paper, metals, glass, etc., from municipal solid waste can reduce manufacturing costs and energy consumption while facilitating the creation of secondary raw materials. This chapter is set forth by critically evaluating the different types of segregation technologies and their efficiency. By combining artificial intelligence (AI), deep learning, and robotics, we’re creating a more automated and eco-friendly way to manage waste, ensuring a healthier future for generations to come.

A fluidized bed reactor is employed for three-phase interactions for the treatment of wastewaters using the inversed bed. Specific parameters like gas holdup, bed heights, gas velocities, and spargers are investigated in an experimental setup. The bubble movements governing the flow patterns across the entire process contributed to fabricated wastewater that mimicked the textile effluent (initial value of 1110 ppm) for its aerobic digestion. The purpose of the current study is to reduce chemical oxygen demand (COD) by employing four gas spargers specifically designed as per open percentage area. This inverse phase bioreactor (solid media particle density lower than water) was investigated for its influence by the static bed heights (H) of 4.85 cm and 2.43 cm, which was accompanied by the low gas velocities of the range of 0.343 cm/s and 0.4068 cm/s. εg = 0.0062 Ug 0.995 was the deduced correlation for the gas holdup. The accuracy in the measurements of COD was supported by the statistical values of regression coefficient and standard errors. Attainment of up to 96.9% COD reduction is achieved for synthetic wastewater.

Globally, annual coconut production for domestic and commercial purposes is estimated at 62.41 million metric tonnes. The coir is a naturally available elastic fibre, which is abundantly available and unhandled coir waste (i.e., short fibre/peat/dust) has significant potential to maintain the economy and ensure sustainability through an effective waste-to-energy recovery perspective. The primary energy demand in India is predicted to climb up to around 1500 Mtoe. The Indian coir industry is considered a significant energy-intensive under micro, small, and medium enterprises (MSME). The 3 M management conception has transformed into the 4 M management conception, emphasizing energy management as its key focus. The coir industry is an intermittent/interlinked process; supply chain optimization and energy management must join to maintain overall energy efficiency. The manuscript aims to carry out a detailed systematic energy analysis focusing on supply chain and power quality optimization with significant scope for implementing resource recycling measures in the Indian rural coir industry of capacity LTCT 109.9 kW with an average energy consumption of 3500 kWh/billing cycle. Power quality optimization and recommendations were proposed based on the power quality analyser and infrared thermography results to achieve better energy efficiency. Coir industries produce coir dust as bioresidues, which should be treated effectively; otherwise, it will settle over the land, preventing the locking of water bodies and creating environmental degradation. As resource recycling, the above coir industry roughly produces 75–100 kg of coir dust daily, which will be used as feedstock for a gasifier that produces 15 kW_e and 45 kW_th. This reduces the grid dependency and is self-sufficient in the power generation of the coir industry. The techno-economic feasibility study is also reported in this manuscript.

Microcrystalline cellulose (MCC) is a natural biopolymer derived from partially depolymerized and purified cellulose, produced by treating alpha cellulose with a large quantity of mineral acids. MCC has a large surface area, is biodegradable, renewable, nontoxic, biocompatible, and has appreciable mechanical properties and economic value. The heavy metal intrusion from various industrial activities like dyeing industries, textiles, chemical industries, manufacturing industries, atomic power plants, etc., into the soil not only contaminates the soil but also pollutes the groundwater. The properties of the soil are adversely affected by heavy metal contamination. In this study, MCC is used to modify soil properties such that it attenuates heavy metal incursion into soil. Lead iron-oxide (Pb₂O₃) is selected as synthetic leachate for the study. The heavy metal removal was observed by adding 2% MCC by weight of dry soil at pH of 4, 6, 8, and 10. The dosage of MCC was selected based on its capacity to enhance the geotechnical properties of the soil. The contact time varied between 0 and 8 h. The investigation showed that the maximum adsorption capacity of 2% MCC at a pH of 10 is 48.46 mg/L while that of soil was 24.13 mg/L. The adsorption increased by nearly two times by treating the soil with 2% MCC. The results of the study show that MCC can be employed to control soil pollution.

Personal protective equipment’s (PPEs) waste is one of the hazardous wastes, which includes surgical gowns, head covers, surgical masks, shoe covers, etc. During COVID-19, a large amount of PPEs waste was generated and was disposed into oceans and surrounding environments (landfill or incineration). PPEs are generally made up of nonwoven fabrics which have been used widely in numerous applications like geotextiles, medical, etc., and they consist of many polymers like polypropylene, polyacrylonitrile, polyurethane, etc. This kind of waste leads to different kinds of environmental pollution like water pollution, air pollution, etc. This paper presents a study on generating construction material (brick) composites from PPEs waste and fly ash. The work (manufacturing of brick) has been carried out with a proportion of PPEs waste (40%) and fly ash (60%). Different properties such as compressive strength, water absorption, efflorescence, and soundness were investigated through standard tests suggested by IS: 3495 (1992). A comparison between the properties of the proposed brick with a standard clay brick reveals that the brick prepared from the PPEs waste may be used in the construction of temporary structures, non-load-bearing walls, and partition walls with satisfactory performance.

In modern trends in construction industries, the paradigm shift towards Integrated Project Delivery (IPD) methodologies and the increasing reliance on Building Information Modeling (BIM) for project execution are transforming the industry. Studies have found the wide use of BIM technology for IPD risk management. In India, a rapidly growing economy with a burgeoning construction sector, the adoption of IPD and BIM presents both opportunities and challenges, influenced by unique socioeconomic dynamics and regulatory landscapes. Despite a growing body of literature emphasizing the positive impact of IPD and BIM on project outcomes, there remains a distinct gap in understanding the specific financial risks associated with IPD projects executed through BIM. This research seeks to address this gap by identifying and assessing the financial risks inherent in the execution of IPD projects using BIM. The objectives include conducting a comprehensive study to identify key risk parameters in IPD, developing a BIM model with various layers for clash detection, validating simulation results, and comparing financial outcomes with conventional building projects. The research aims to contribute valuable insights into the financial risk landscape of IPD projects, aiding stakeholders in making informed decisions for successful project delivery in the dynamic construction industry. To achieve this objective, case studies of residential projects from Pune city, India, are taken to assess the financial risk using BIM with reference to the framework mentioned in previous studies.

The disposal of municipal solid waste is a critical issue in urban environments. In recent times, waste-to-energy plants have been installed and operated across the globe to reduce the volume of trash. In Hyderabad, India, there are currently five such waste-to-energy plants operating in Dundigal, Jawaharnagar, Bibinagar, Pyaranagar, and Yacharam. These energy production units produce incinerated ash as a by-product. In the current study, an attempt was made to determine the feasibility of using incinerated ash from domestic waste to mitigate the swell-shrink behavior of locally available expansive soil. Domestic waste was collected from a municipal solid waste dump yard, and ash was made by burning it. Tests such as shrinkage limit test, free swell index test, and oedometer tests were performed as per IS 2720 to study the swell–shrink and consolidation characteristics of locally available soil and the soil treated with incinerated ash. The shrinkage limit of virgin soil, which was initially 15%, increased to 38%, 52%, and 55% by the inclusion of 20%, 30%, and 50% of incinerated ash by weight of soil, respectively. By incorporating 25% of burned ash into the soil mass, the free swell index of virgin soil was dropped by 23%, which was 30% initially. Consolidation characteristics were found for virgin soil, incinerated ash, and soil mixed with the optimum quantity of ash. An increase of 75% in the rate of consolidation was observed for the soil mixed with the optimum quantity of ash. Based on the test results, the ideal amount of incinerated ash required to mitigate swell-shrink and settlement characteristics of expansive soil can be determined.

Bituminous surface roads are rapidly degrading due to growing traffic loads and climate change. Therefore, the management of fracture and permanent deformations in flexible pavements has been the subject of research in recent years. Various polymer modifiers are used to alleviate fatigue, rutting, and low-temperature cracking concerns. One kind of substance that has a lot of fine glass fibres in it is called glass powder. A key component in enhancing the performance of flexible pavements is additive. Glass powder has been used to improve asphalt mixture performance by preventing fatigue cracking and permanent deformation, as well as improving automatic characteristics. Compared to previous methods, it was discovered that adding glass powder to the bituminous pavement mix as a low-cost modifier improved performance. To assess the performance characteristics of a bitumen mixture, a combination of glass powder and rice husk ash (RHA) is introduced in this study.

The global construction sector stands at a crucial juncture, necessitating eco-conscious practices to minimize environmental impact and enhance resource efficiency, with highway construction playing a significant role. In the Indian context, the urgency to adopt sustainable supply chain management practices in highway construction is pronounced, given the country’s vast infrastructure projects and environmental challenges. India’s ambitious infrastructure goals necessitate innovative approaches to ensure sustainability and resilience in highway construction projects. This study explores integrating sustainable supply chain management into highway construction, focusing on material demand forecasting. Leveraging machine learning techniques, specifically random forest regression, the research aims to transform material demand forecasting in highway construction, addressing issues such as overstocking and stockouts. By providing stakeholders with valuable insights into material demand forecasting, the study seeks to contribute to the timely completion and sustainable development of highway infrastructure projects, fostering environmentally conscious and resilient transportation networks worldwide.

Liquefaction phenomenon occurs in completely saturated, cohesive-less and loose soils that are subjected to periodic loading in undrained conditions. Because of the gradually rising pore pressure during liquefaction, the soil loses its shear strength when the effective stress resulting to zero. Even if a structure is intended to resist earthquakes, liquefaction may lead to foundation failure and subsequent structure collapse. Liquefaction is dependent on the properties of the soil below the ground surface. This paper presents the methods for the analysis of liquefaction potential and aims at the comparison of stress and energy-based methods, which rely mainly on Standard Penetration Test (SPT) values. This paper reviews some of the liquefaction hazards from previous earthquakes as well as case data from field research. This paper also studies remedial strategies employing different soil mitigation techniques that might be applied based on soil conditions at that site to reduce the severe damage caused through liquefaction.

A paradigm shift towards Siddha medicines was rapidly increasing due to several health benefits. The utilization and demand for natural medicines to cure diseases has been increased rapidly. Natural medicines require conditioning and preprocessing (i.e., removal of moisture content) to maintain the quality and consistency of the medicine. A sustainable drying process is essential to maintain an effective supply chain. The sustainable solar drying process is improving the shelf life and quality of medicinal plants. Also, it promotes density reduction of the medicinal plants and supports competitive positions through value addition. Sirumalai is a mountain range situated in the Dindigul district in Tamil Nadu. It is known for its rich biodiversity and unique medicinal herbs. Many of these herbs have been traditionally used in Ayurvedic and Siddha medicine for their therapeutic properties. This paper attempts to analyze a passive solar dryer integrated with a solar water heater based on 24×7 drying of herbs to improve the quality of herbs. Solar PV-based force circulation fan with air heat exchanger has been employed for backup heating during night time. The performance analysis has been carried out and reported. Also, the socioeconomic analysis has been carried out and reported in this paper.

In recent years, fly ash and slag, both industrial by-products, have been integral to sustainable geopolymer concrete, but their fire resistance lacks clarity. The complex interaction between its composition and elevated temperatures has a significant impact on its resulting mechanical properties, thereby suggesting the need for precise predictive models. This significant knowledge gap can be bridged by using advanced machine learning methods to accurately forecast the compressive strength of sustainable geopolymer concrete under high-temperature conditions. In this study, an experimental dataset consisting of over 200 data points is collected from literature. Several machine learning techniques, encompassing linear regression, decision trees, support vector machine, Gaussian process regression, ensemble methods, neural networks, and kernel-based algorithms, are employed to forecast the compressive strength. Statistical and performance metrics for all machine learning models are tabulated to examine their efficiency. It is observed that the trilayered neural network model outperformed other algorithms, achieving an R² value of 0.95 and MSE of 37.55. The study provides structural designers with a reliable computational tool for assessing the strength of green concrete exposed to elevated temperatures.

The large-scale fly ash and slag integration in concrete has not only aided in reducing the environmental impact of cement, but also contributed to economic development by reducing waste, cutting carbon emissions, conserving resources, and offering cost-effective, sustainable construction solutions. This aligns with the global shift towards green building practices. However, the optimal mix design of such green concrete continues to remain a significant challenge since it requires optimizing component proportions to achieve several desired attributes of concrete. This study focuses on optimizing concrete mix design by forecasting a crucial variable: 28-day compressive strength. It is analyzed using seven input factors: cement, slag, fly ash, water, superplasticizer (sp), coarse aggregate, and fine aggregate. A dataset comprising 103 data points from the literature is employed to investigate the chosen input and output variables. Various machine learning methods, such as linear regression, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, k-means clustering, neural networks, and Gaussian process regression, are evaluated on the gathered dataset. The performance metrics from all machine learning models are compared to evaluate their efficiency. The results from the analysis indicate that Gaussian Process Regression (GPR) demonstrates exceptional accuracy in forecasting 28-day compressive strength, making it a robust choice for precision–critical applications in concrete mix design.

Solid waste management stands as a significant municipal service vital for urban cleanliness worldwide. Amidst the conveniences of modern civilization, there emerges a pressing issue: the proliferation of solid waste, necessitating meticulous disposal efforts. The efficacy of waste disposal hinges upon judicious site selection, influenced by various factors. Recent years have seen notable strides in employing advanced techniques like remote sensing and Geographic Information Systems (GIS) to address regional waste management challenges. These technologies expedite the acquisition, processing, and dissemination of pertinent data crucial for effective waste management strategies. This paper presents a comprehensive examination of leveraging remote sensing and GIS methodologies integrated with the Analytical Hierarchy Process (AHP) to tackle environmental concerns associated with waste disposal. The study underscores the potential of remote sensing and GIS techniques in optimizing waste management systems. A geospatial multi-criteria analysis, employing weighted overlay technique, integrates diverse parameters encompassing physical, social, and demographic dimensions of urban landscapes to identify suitable solid waste disposal sites. The Land Suitability Index (LSI) aids in quantifying site suitability based on environmental considerations. Employing an equal interval classification method, the resultant index model categorizes sites into four distinct suitability tiers: “unsuitable,” “less suitable,” “moderately suitable,” and “suitable.”

The integration of Remote Sensing and Geographical Information System (GIS) provides extensive opportunities for monitoring and overseeing natural resources with capabilities spanning multi-temporal, multi-spectral, and multi-spatial resolutions. There is an immediate imperative to comprehend the specialized functionalities of a continuously expanding range of image sources and analytical techniques, particularly for those involved in natural resource management. This comprehensive study compiles diverse applications of remote sensing and GIS tools relevant to the management of natural resources, including agriculture, water, forests, soil, and natural hazards. The major applications of remote sensing and GIS in natural resource management are resource management, change detection, impact assessment, suitability analysis, biodiversity, and forest management, etc. The collaborative effort is essential for the effective use and application of remote sensing techniques for monitoring and assessment of natural resource management. Remote Sensing (RS) proves to be an efficient instrument for monitoring spatial and temporal changes in the landscape, by facilitating land use and land cover mapping. When integrated with on-site ecosystem assessments and other relevant biophysical and socio-economic data, the resulting land cover and land use maps offer crucial insights. By integrating and modifying spatial data in a Geographic Information System (GIS), it is possible to carry out analyses that improve understanding of the dynamics and processes associated with land use changes.

The escalating threat of climate change demands urgent action to achieve net-zero greenhouse gas emissions. This paper explores the critical role of carbon sequestration in this global endeavor. We are specifically evaluating the potential of afforestation vs. Engineered techniques, analyzing the economic feasibility of large-scale implementation, or examining the social and environmental impacts of various methods. Through comparative analysis of existing data, and case studies of specific projects especially from Africa and Asia, we uncover that more effort is still needed in these continents since both continents have growing economies and populations, leading to rising carbon dioxide emissions, they are particularly vulnerable to climate change impacts and investing in carbon sequestration can offer economic opportunities (e.g., new jobs, green technologies), support sustainable development, and protect vulnerable communities. Our findings illuminate identifying promising pathways, informing policy decisions, and suggesting areas for further research and development. By examining the potential and challenges of carbon sequestration, this paper enhances the understanding of this vital strategy in combating climate change.

Groundwater potential zone identification is necessary for administrating each subsurface and surface water resource. Groundwater is vital to maintaining human health and the health of various aquatic and land-based organisms and their environment. The area of interest is the Wyra River basin of the lower Krishna catchment area, encompassing an area of 3443 km² and located between latitudes 16⁰14^′ 00“ N and 17⁰ 35^’ 00^’‘ N and 80⁰ 05’ 00” E and 80⁰ 55′ 00″ E longitude. A geographical information system (GIS) is used to generate thematic maps and identify groundwater potential zones. The multi-criteria decision analysis method and GIS were used to develop thematic maps. These thematic maps are ranked by Satty’s analytic hierarchy processes. To identify possible zones for groundwater, a total of eight thematic layers of the specified kind of digital elevation model, land use and land cover, soil map, slope, rainfall, geology, lineament density, and drainage density were planned during the analysis. The GIS platform is used to convert each of the thematic layers into a raster. Utilizing weighted overlay techniques entire Wyra basin is divided into four major classes from poor to very good. Corresponding percentages are 5.05%, 73.40%, 21.45%, and 0.08% of the study region. According to this research, groundwater planning and management can be done more effectively and economically by integrating GIS.

Wastewater is a major threat to the natural water streams, damaging their ecological balance and aquatic environments. Untreated wastewater streams from both domestic and industrial effluents pollute natural streams, which further causes several health and environmental concerns for human society. This study explores the efficacy of the Vertical Flow Constructed Wetland (VFCW) system for the benefit of recovering the Panchaganga river passing through the city of Kolhapur, Maharashtra, India. Jayanthi Nallah is the major contributor to stream pollution. Hence, the pollution load has been evaluated for the grab integrated samples from six different sampling locations by analyzing physicochemical parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), total phosphorus (TP), and total Kjeldahl nitrogen (TKN) in this study. A lab-scale model of VFCW with the dimensions of 0.62 m*0.70 m*0.45 m was developed for phytoremediation using three different combinations of locally available plant species (Canna indica, Canna indica & Typha, and Canna indica & Cyperus rotundus) and their treatment efficiencies were evaluated for three different hydraulic loading rates of 0.12 m³/m²/hr., 0.18 m³/m²/hr., and 0.24 m³/m²/hr. The treated water from all three plant combinations had all the parameters well below the regulating standards when the hydraulic loading rate was fixed at 0.18 m³/m²/hr. The VFCW balances treatment efficiency and cost, making it a sustainable wastewater treatment technology.

Hydrogeochemical methods have been carried out in Dubbak (M) of Siddipet district, Telangana, to understand the limitations of major cations viz., sodium (Na⁺), potassium (K⁺), calcium (Ca²⁺), magnesium (Mg²⁺), and major anions carbonate (CO₃⁻), bicarbonates (HCO₃⁻), chloride (Cl^¯) fluoride (F¯), nitrate (NO_3¯), and sulfate (SO₄^2¯) present in the groundwater. Groundwater sampling has been done from the 14 borewell locations in the study area and examined at TSGWD, Hyderabad. The analysis has been done based on BIS 2012. The highest concentrations of fluoride have been recorded in Thimmapur (1.9 ppm), Dubbak (1.81 ppm), Lachhapet (1.65 ppm), and Boppapur (1.54 ppm) whereas the highest concentrations of nitrate were marked at Akaram (125 ppm) and Thimmapur (55 ppm). Higher concentrations of F and N are due to weathering of fluoride-bearing minerals and anthropogenic sources, respectively. The US Salinity diagram depicts the C3-S1 zone. Gibbs’s plot indicates that rock-weathering processes control the geochemistry of the study region. Wilcox’s plot showed that 57% of the total samples belong to the good to permissible, whereas 43% belong to the excellent to good category. The Water Quality Index (WQI) represents 35% of the total samples belonging to a very poor category, 57% belonging to an unsuitable category, and 0.07% belonging to the poor category.

Accessing clean, safe drinking water is still a problem for many people worldwide. Numerous technologies for filtering and purifying water demand more electricity, energy, or resources. As the environment continues to change, these difficulties will only get worse. Due to the depletion of water supplies and the fear mongering surrounding environmental degradation, water treatment is currently one of the main research areas. This has forced the upgrading of conventional water treatment technologies toward recycling and reuse. They function by neutralizing the charge by polymeric bridging, an adsorption process. The work offers particular information about the coagulation properties of natural coagulants, fabricating a solar powered water purification system at lower maintenance cost, where sand, pebbles, and charcoal are used for physical impurity filtration, water is preheated using heating coils, where moringa seeds act as a natural coagulant and solar energy is used to power the heating coils and UV light source. Total Coliform bacteria causing illness were completely absent and parameters like TDS, pH, and Turbidity have reduced from 309.6 mg/L, 7.4, 10.8 NTU to 274.4 mg/L, 7.2, 1.2 NTU, respectively. This is the cheapest water purification system that can be used in rural areas with household containers, Moringa (drumstick) seeds, and solar panels. The use of natural coagulants, which are widely accessible, affordable, simple to use, biodegradable, non-toxic, environmentally friendly, efficient, and produce less volumes of sludge, is a sustainable substitute.

The most frequent issues with combined sewer distribution systems in urban areas are the ones related to water surcharges. Rapid urbanization leading to an increase in impervious areas, high-intensity rainfall, and clogging of drains due to improper maintenance of sewer systems are the most common causes of surcharge. The main objective of the study is to measure and assess the overflow conditions and locate the potential flood-effected areas in a part of Pragathi Nagar of Hyderabad city, considering the existing sewer drainage system and with the inclusion of Low Impact Development (LID) techniques. To model the scenario for the study area, a computational SEWERGEMS was developed. SEWERGEMS model was developed with and without consideration of LID approaches for various design rainfall intensities for 2-, 5-, 10-, and 30-year return periods. The outcomes implied the effectiveness of the computational model in explaining multiple scenarios and can support the municipal authorities in effectively managing the combined sewer distribution network.

Saltwater intrusion is a global issue that affects the coastal areas worldwide. Due to this intrusion, it will affect the growth of crops, soil fertility, and human health. The current study estimates parameters such as Water Quality Index (WQI), Human Health Risk Assessment (HHRA), Seawater Mixing Index (SMI), and Irrigation efficiency (IE) in order to examine the groundwater quality of Kanchipuram district, Tamil Nadu coastal area. A total of 60 sampling stations were considered to examine groundwater quality. For the groundwater analysis, the physicochemical parameters were taken into account. Q-GIS has been used in mapping the sampling locations and affected areas. WQI was calculated for the Kanchipuram based on the physicochemical characteristics of water namely pH, Electrical Conductivity, Total Dissolved solids, Total Hardness, Calcium, Magnesium, potassium, chlorides, fluorides, nitrates, and sodium. From the WQI results it is observed that out of 60 stations, it was observed that around 30% of groundwater is above good quality and around 42% is very poor and not suitable for consumption. The WQI states that groundwater in Kanchipuram district was moderately polluted. SMI was also calculated, it was observed that out of 60 stations SMI values of 23 stations were above 1, i.e., in 38% of stations SMI value was observed to be high. Also calculated HHRA, it was observed in 13% of stations fluoride content is greater than 1 in children. The analysis shows that the impact of fluoride content in children is higher than in adults. Irrigation Indices conclude that 65% of sampling stations have SAR values greater than 10 mEq/L and 58 stations have Na% less than 80%.

Surface water and groundwater were analyzed as individual components in the past in a hydrological cycle, though they are interconnected throughout the process. Overutilization of aquifer water and surface water has attracted attention to their recent interaction studies. Both lateral and longitudinal flows are present in this interaction. Surface water seeps into the earth, replenishing subterranean aquifers, while groundwater seeps to the surface, providing stream base flow. It is essential to comprehend and measure the interchange occurring between stream water and groundwater from the perspective of sustainable water resource management. A fundamental grasp of these interactions is crucial in developing effective strategies for disaster and risk management studies. Comprehending how surface water and groundwater connect is essential for creating numerical models that effectively simulate scenarios. The present review emphasizes various numerical coupling models and strategies for estimating fluidities in the surface water and groundwater interface. The review underlines the limitations and advantages of fully coupled and loosely coupled models in understanding interactions on a regional scale.

For the betterment of public health and environmental preservation, technological advancements in leachate leakage monitoring and detection in landfill regions are becoming more and more important. The liquid that results from water interacting with waste products in landfills is known as leachate, and it may include toxic compounds and other contaminants. In order to stop groundwater pollution and environmental deterioration, leachate leak detection and monitoring are crucial. Although landfills are essential locations for disposing of trash, there are serious environmental dangers associated with them because of the possibility of leachate leaks, which can damage soil and water supplies. In order to reduce these environmental risks, leachate leakage must be effectively detected and monitored. The primary technique used in traditional leachate detection methods was manual sampling and analysis, which frequently had drawbacks in terms of accuracy, efficiency, and real-time monitoring capabilities. But as more sophisticated technologies have become available, such as remote sensing, geophysical surveys, and sensor networks, the way that leachate leakage is found and tracked has changed dramatically. The technical advancements in leachate leak detection and monitoring in landfill regions are highlighted in this abstract.

This study investigates the performance of agrovoltaic systems by analyzing module efficiency, energy yield, microclimate conditions, and crop productivity. A field experiment was conducted to compare the parameters between agrovoltaic systems and traditional agricultural practices. Module efficiency and energy yield were measured to assess the solar panels’ performance under co-located crop cultivation. Microclimatic conditions, including temperature, humidity, and wind speed, were monitored to understand their influence on both crop growth and solar module efficiency. Crop yield was evaluated to determine the agricultural productivity of the agrovoltaic system compared to conventional farming practices. The study outcome provides a deep insight into the feasibility and benefits of integrating agriculture and solar energy production, highlighting opportunities for maximizing land use efficiency and promoting sustainable farming practices.

The major global issues are the scarcity in availability of freshwater resources, diminishing environmental pollution, constant increase in the population density, and diminishing fertile land resources for crop cultivation. The availability of land for agriculture in urban and peri-urban is impassable due to dense population. Hydroponic systems are a one-stop solution for dealing with water pollution, water scarcity, and feeding a growing population. In hydroponics, crops are cultivated without soil under controlled environment with constant supply of nutrients and for faster growth rate. In the study, Hydroponic Cropping System (HCS) under saline and inorganic dye concentrations was carried out. The species used for the study was Mentha genus, enclosed in a chamber under controlled environment. Mentha sp. were spiked with salinity of 0 to 3000 mg/L and dye concentrations (methylene blue) of 0 to 15 mg/L. The study found that under saline circumstances, the plants grew unhindered; however under dye concentrations, they displayed hindrance in their growth. At a concentration of 15 mg/L of dye the plant leaf turned into pale yellow colour and gradually the wilting stage is reached. In addition, the risk assessment of pollutants on plant growth was evaluated. The study concludes that possible health risk due to salinity was very less. As clearly indicated, the health risk index (HRI) and targeted hazardous quotient (THQ) values under saline conditions are less than 1 implies less risk associated, but with dye contaminant the risk assessment was on higher side with HRI and THQ values are more than 1. Hence the study concludes that hydroponic crop production is possible in saline water, but suitable pre-treatment needs for dye-containing wastewater for crop growth.

The contribution of women to the advancement of agriculture has grown significantly. Women play a crucial role in guaranteeing food security and conserving local agro-biodiversity. Agriculture sector employs 80% of all economically active women; they comprise 33% of the agricultural labor force and 48% of self-employed farmers. Despite playing a significant role in various aspects of agriculture and food production, yet their contributions are often undervalued and underrepresented. As women are the primary participants in all stages of agricultural production, including pre-harvest, post-harvest processing, packaging, and marketing, it is crucial to implement gender-specific interventions to enhance agricultural productivity. Empowering women in agri-startups not only promotes gender equality but also has the potential to significantly enhance food security. This paper explores the crucial role of women in agri-startups for achieving sustainable food security, challenges faced by women in agri-startups, the benefits of their empowerment, and strategies for fostering their leadership in this sector. By addressing these issues, we can create a more inclusive and sustainable agricultural landscape, ultimately leading to improved food security for communities worldwide.

The removal of forest resources, driven by increased human demand for timber, fuelwood, and other natural commodities, has significant repercussions on forest ecosystems and their inhabitants. Katarniaghat (400 sq.km.) and Kaimoor (500 sq.km.) Wildlife Sanctuaries situated in Utttar Pradesh were selected to carry out the study. Depending on the reconnaissance survey regarding the anthropogenic disturbance variables such as human trails, grazing cover, weed cover, lopping density, and fire, the protected area was categorized into high, medium, and low disturbed sites. For data collections, line transect method (direct sighting) and pellet group method (indirect evidence) were used to record mammals. Circular plot of 10 m radius was used to evaluate and quantify habitat variables. The data were analyzed using Kruskal-Wallis test using SPSS comparing density, abundance, area preference, mean group size, and encounter rate of the species. The low disturbed areas of Katarniaghat and Kaimoor showed higher values for overall mean pellet group density (13.26 ± 2.01 and 17.84 ± 1.6), abundance (0.007 ± 0.001 and 0.008 ± 0.001), area preference (0.52 ± 0.07 and 0.25 ± 0.01), encounter rate (2.9 ± 0.43 and 1.26 ± 0.22), and mean group size (2.9 ± 0.43 and 2.6 ± 0.5) of mammals, respectively. However, some species showed affinity toward human disturbance, for example, Nilgai, Jackal, and Langur, which showed their coexistence with human interference. The present study aims to contribute to a better understanding of the complex interactions between forest resource extraction and mammalian communities, offering insights to inform sustainable management practices, conservation efforts, and policy formulation in forested landscapes.