Environmental Engineering for Ecosystem Restoration

This article examines and reports on the trends and environmental impact of paper consumption in India, with a focus on the period up to 2030. To forecast future levels of paper production and consumption across various industries, the research analyzes historical data patterns. The study finds that the paper industry is responsible for a significant amount of environmental damage, including deforestation, air and water pollution, and climate change. If measures are not taken to reduce our reliance on paper, the study predicts that paper production and consumption will continue to increase at an alarming pace, which could have detrimental effects on the environment. The report recommends encouraging sustainable practices such as recycling paper, using recycled paper, and decreasing overall paper consumption. Additionally, the study emphasizes the need for increased awareness among individuals and organizations about the environmental implications of paper use. The report proposes implementing legislation to ensure responsible paper production and use. Finally, the study highlights the importance of reducing paper dependence to protect the environment and preserve natural resources for future generations.

Currently, the building industry is focusing on the requirement for high energy utilization. It is critical to optimize energy use by utilizing renewable resources. The use of phase-change materials in thermal energy storage systems is gaining popularity in passive applications for green buildings due to their innovative approach. The proposed work focuses on the incorporation of MWCNT additive sodium poly acrylate as PCM materials into the walls, panels, and roofs of passive structures, as well as the assessment of optimal energy consumption in green buildings via indoor environmental quality (IEQ). A novel framework was developed using the response surface method and the hill climbing technique to identify the most efficient use of energy output, charging time, and heat transfer rate based on the input phase such as input air condition temperature (25–28 °C), air conditioner flow rate (100–600 cfm) and relative humidity (35–55%). According to the results, the optimal energy transfer rate of the PCM wall was found to be 53.86 during a charging duration of 39 min. The amount of thermal energy stored by the PCM wall to maintain the room temperature of 26 degrees Celsius was discovered to be 15,400 kJ. This energy is adequate to keep the room temperature stable for 3 days.

The study examines data collected over 7 years (2015–2021) from Delhi's National Ambient Noise Monitoring Network for atmospheric noise monitoring. This study looks at the psychological and physiological consequences of noise on health, including sleep disruption, decreased productivity, hearing loss, speech interference, and increased blood pressure. Five silence zones in Delhi were selected to investigate the noise exposure associated health risk study. None of these areas, according to the results, met the ambient noise standards, pointing to a pervasive problem. Long-term monthly average Ldn values varied widely among the locations, with values for Dilshad Garden ranging from 65.0 dB(A) to 79.0 dB(A), NSIT Dwarka from 60.7 to 66.2 dB(A), R K Puram from 61.6 to 81.6 dB(A), Mandir Marg from 57.9 to 93.2 dB(A), and DTU Bawana from 58.1 to 78.0 dB(A). The study also compares the Ldn values during the 7 years to observe the standards for health hazards set by the Netherlands' Health Council in 1994. According to the results, three of the study sites above the threshold of 70 dB (A) were linked to hypertension and ischemic heart disease, whereas all five sites exceeded the threshold of 42 dB (A) for annoyance. These findings bring to light the serious health issues connected to exposure to environmental noise.

Passive design strategies have gained increasing attention in recent years as a means of improving the energy efficiency and comfort of buildings. These strategies aim to reduce the energy consumption of buildings by utilizing natural resources such as sunlight, wind, and vegetation. This article provides a review of the literature on passive design strategies and their performance in buildings in cold and arid climate zones. Snow regions present unique challenges and opportunities for sustainable building design due to extreme cold temperatures, heavy snowfall, and the need for effective insulation. The review emphasizes about implementation of passive design strategies, including site analysis, building orientation, insulation, snow management, and efficient heating systems. Passive design of buildings in arid climates focuses on utilizing natural elements and strategies to maximize energy efficiency and thermal comfort without relying heavily on mechanical cooling systems.

Groundwater is one of the main sources of water for drinking purposes in the smart city of Bhubaneswar, Odisha, India. A geochemistry study of groundwater was conducted for the full year 2020.The aim of this study was to find out the quality of groundwater for drinking purposes. Prior to and during the monsoon season, samples from nine municipal bore wells were taken and their water was then examined for physico-chemical parameters such as pH, EC, TDS, TH, Ca2+, Mg2+, Na+, K+, CO2−3, HCO−3, Fe, Cl−, SO4 2−, NO3 2−, and F in accordance with APHA standards (1985). Arc GIS has been used to prepare geographic information system-based spatial distribution maps of different major elements. Next, the groundwater in the research region is evaluated using the water quality index (WQI) to determine if it is suitable for human consumption. The groundwater in the research area of the smart city region of Bhubaneswar (BMC) had a WQI that indicated it was generally suitable for drinking. With reference to BIS 10500: 2012 for Drinking Water, almost all of the parameters are found to be below the allowed limits, with the exception of Iron (Fe). TDS, TH, EC, and chloride are all shown to be strongly correlated with one another. It is clear from the data shown in the Hill-Piper diagram that the groundwater in the region of study does meet the “Indian Standard (IS)-10,500:2012” for potable water.

The present research analyzed spatial and temporal variability of short-term meteorological drought using Standardized Precipitation Index (SPI) and non-parametric trend tests for the semi-arid north Gujarat region, India. The SPI-6 indicating meteorological drought has been thoroughly examined considering drought characteristics such as intensity, duration, recurrence probability, and major drought years. The SPI-6 analysis along with non-parametric trend tests such as Mann-Kendall (MK) and Modified Mann-Kendall (MMK) for trend significance, Sen’s slope (SEN) and Linear Regression (LR) for trend magnitude and Lanzante’s test (LNZ) for change point detection were performed on Indian Meteorological Department (IMD) gridded rainfall data having time span 1951–2020 years. The analysis revealed major drought events for the years 1968, 1974, 1987, 1999, 2002, and recently in 2018 which were spatially distributed for the entire region using the IDW interpolation method in GIS-Environment. Based on the average SPI-6 values over the entire region, 1985–1987 and 1999–2002 time periods were observed to be severely dry spells in which 1987 was the extreme drought with intensity up to -4.24 in southern parts. The recurrence probability of extreme droughts was found to be highest (1 in 18 years) in northern and central parts. The trend analysis of SPI-6 values highlighted negative trends in about 17% of the grid points indicating drought-prone areas whereas about 83% of the grid points revealed positive trends indicating increasing wet spells. From the change point detection, significant changes in drought were observed for the year 2002 in most grid points. Present research outcomes will be helpful in crafting regional drought policies for the sustainable management of water resources in a changing climate.

Bagalkot and surrounding several villages have come under submergence due to the construction of Alamatti Dam under the Upper Krishna Project. Rehabilitation of the people had been done by authorities in Navanagar, a newly developed area. Apart from cities and villages large stretcthes of agricultural, barren and forest lands have come under submergence. It is of interest to study the impact of submergence on the city and its surrounding areas. The change in land-use/land-cover pattern with time is analyzed in this study using remote sensing images over the last three decades. The water storage upstream of the dam was started in the year 2001. The impact of water storage on Land-use/Land-cover pattern in the area is studied. LULC maps of Bagalkot taluk before (1991) and after this year (2001, 2011, and 2021) are prepared and analyzed for change detection. There is a drastic decrease in agricultural areas, with an increase in water bodies and built-up areas. Initially, the forest land decreases, but slowly re-gains due to the availability of water. Due to these changes, the weather and climate of the area is also affected.

A major obstacle to sustainable development is drought. India is an agricultural predominant country and a majority of the agricultural land is rainfed. After Rajasthan, Karnataka has the second largest geographical area which is prone to meteorological drought. For sustainable development, drought assessment is the first step in developing drought mitigation measures. Drought indices are used to assess drought, and research has shown that while certain dryness indices are better than others at describing drought, all drought indices are locally evolved. In this research, the Shimsha Basin is assessed for drought vulnerability using a meteorological drought index called percentage departure (PD). As the study area has a larger portion of agricultural land, it is very crucial to understand the drought characteristics to plan the agricultural activities. For this analysis, monthly rainfall data for 30 years from nine stations of IMD gridded data is used from 1989–2018. The study revealed that the study area is receiving decent amounts of rainfall across all the stations. The results reflect no drought condition in most of the years across all stations followed by mild drought, moderate, and severe drought conditions.

The Hill Tracts of Bangladesh experienced several landslides in recent years. The vulnerability to landslides is a major concern because of rising climatic and man-made impacts. Considering the river basin within these hill tracts with numerous small runoff channels, proper comprehension of the landslide vulnerability is essential for sustainable integrated water resources management (IWRM). The study seeks to evaluate the landslide vulnerability in the Sangu and Matamuhuri river basins using a two-step methodological framework. Firstly, the overlaying of six factors—rainfall, elevation, slope, soil characteristics (lithology), land use and land cover (LULC), and historical events was done to identify vulnerable areas, each of which has been weighted using a pairwise matrix of the analytical hierarchy process (AHP). Secondly, factors that accelerate vulnerability in the basin were explored qualitatively to understand the associated drivers. The investigation pinpointed Bandarban Sadar, Satkaniya, and Rowanchari with the highest vulnerability within the Sangu Basin and Alikadam and Lama within the Matamuhuri Basin. Alongside climate extremes such as heavy rainfall, development activities with unplanned hill cutting, tourism, and deforestation are increasing the basin’s vulnerability. The outcome of this study will aid policymakers in making informed decisions for sustainable and integrated watershed management.

Worldwide attention has increased on climatic variability, notably rainfall. As India is an agricultural developing country, thus it is crucial to evaluate how the monthly and annual rains are affected by the changing climate in order to determine what cropping practices would need to be modified. Based on annual and monthly rainfall data, this paper analyzes the rainfall trends in Gujarat, India's lower Mahi River Basin. Using data from the State Data Center from 1990 to 2020, the effect of a changing climate on rainfall has been evaluated. Sen's slope estimator (SS), the Mann–Kendall (MK) non-parametric statistical test, and linear regression analysis (LRA) have all been used to identify rainfall trends. IDW, or inverse distance weighting, has been used to spatially portray the trend. Both a monthly time period and an annual time period have been used to illustrate the spatial distribution of the rainfall trend. The month of August results in a strong increasing trend, according to Z-statistics and Sen's slope, while the month of June exhibits a negative trend across practically the whole research region. July, September, and October showed a non-significant increasing trend. The above analysis indicated that monsoon season tends to start late. The results will be helpful for cropping practices adapted to the study area.

The morphometric study of a basin in the context of morphological and hydrological parameters has been emphasized with the aid of geomatic tools. The conjugate of geological, geomorphological, hydrological, and fluvial parameters is analyzed to obtain the relationship between linear, relief, and aerial aspects of the Challakere watershed in Chitradurga district, South India. The drainage morphometric parameter is evaluated by DEM data in ArcGIS 10.3 version. The river Vedavathi and its tributaries flow on an undulated hard rock terrain comprising a chain of parallel mountains and narrow valleys. In the current study, drainage morphometric evaluation is carried out to a 4th order stream of the Vedavathi river of Challakere basin, its average elevation is 500 m MSL, and the drainage area of the basin is 1830 km2 (Table 1). Basin exhibits sub dendritic to dendritic drainage patterns. The stream order of the basin is exclusively driven by the influence of physiographic and lithology of the area. From the result, the basin comprises an irregularly increasing stream order, whereas the fifth order consists of 164 drainage networks, and the overall length of the stream is 701 km.

Dyes are the compounds used to impart color in various industries having an immense negative effect on the environmental and human wellness when it is discharged without adopting adequate treatment. In this research, oxidation of acidic (congo red, CR) and basic dye (crystal violet, CV) from synthetic effluent using different electro-chemical techniques i.e. Fenton (FT) and electro-Fenton processes (EF) has been carried out. Meanwhile, the consequence of operational parameters viz contacts time (0–180 min), dye concentration (25–300 mg/L), pH (3–11), voltage (5–25 V), FeSO4 + H2O2 dosage (100 + 50 − 500 + 250 mg/L), number of electrodes (2–6), electrode spacing (1–2 cm) and electrode combination (Fe-Al–Fe-Al and Al–Fe-Al–Fe) for dye degradation were examined. On the other hand, treatment of real-time textile effluent was investigated at optimum operating conditions obtained. First-order and second-order kinetic models were used to determine rate constants for degradation of dye compounds from effluents. From results, it was observed that EF process with Fe electrodes showed maximum dye degradation of 98.24% and 90.53% for CR and CV dye, respectively at natural pH. The removal CR was greater than the CV dye at optimum operating conditions i.e. 60 min, 20 V with four Fe electrodes at 1cm electrode distance. Subsequently, treatment of real-time textile wastewater performed at optimum conditions showed removal of ~97% with Fe-Al–Fe-Al electrodes combination in comparison with Fe (51%), Al (82%), and Al–Fe-Al–Fe (94%) electrodes. The removal of both dyes using Fe and Al electrodes from synthetic wastewater followed second-order kinetics. Meanwhile, kinetic constants for treatment of real-time textile effluent were found to be 0.016 min−1 for Fe electrodes, 0.013 min−1 for Al electrodes, 0.009 min−1 for Fe-Al–Fe-Al and 0.007 min−1 for Al–Fe-Al–Fe electrodes. While the energy consumption and electrical energy order were calculated, it turned out that Fe electrodes utilized less energy and had better electrical energy order (EEO) than Fe electrodes for both CR and CV dyes. In conclusion, EF technique can be effectively adopted for effective degradation of dyes from industrial effluents.

In this research, simultaneous adsorption of rhodamine B (RB) and methyl orange (MO) from mono-dye system (RB/MO) and multi-dye system (RB + MO) was analyzed for antagonistic/synergistic effect. Adsorbent characterization was performed using SEM, EDX, porosimetry, TGA, pHpzc and XRD analysis. Meanwhile, influence of operating conditions viz. contact time (0–3 h), pH (2–12), dye concentration (1–100 mg/L) and adsorbent dose (0.1–4 g/L) on dyes adsorption from mono-component system was evaluated. Subsequently, rate constants for dyes removal were determined using several kinetic models i.e., pseudo-first-order, intra-particle diffusion, pseudo-second-order, Elovich and liquid-film diffusion models. On the other hand, Langmuir, Freundlich, Elovich, Dubinin-Radushkevich and Temkin isotherm models adopted to explicate maximum adsorption ability and adsorption process mechanism. From results, it was noted that pseudo-second-order (K2: RB = 1.088 min−1; MO = 0.03 min−1) and Langmuir model best suited experimental data for both RB and MO dye removal. The maximum adsorption ability (mg/g) was found to be 77.52 and 47.84 for RB and MO, respectively at 60 min with dose 2 g/L at neutral pH. In contrast, maximum adsorption ability (mg/g) was found to be 71.9 and 81.3 for RB and MO, respectively from multi-component system. Furthermore, Langmuir competitive model facilitated in analysis of synergistic (cooperative) or antagonistic (competitive) effect for removing dyes from a multi-dye system (RB + MO) and synergistic effect was observed.

Fixed-bed column adsorption has been widely adopted for selective removal of pollutants from industrial effluents across the world. In the meantime, investigations on competitive (antagonistic) or cooperative (synergestic) adsorption analysis for simultaneous removal of multiple dyes from multi-pollutant mixture using fixed-bed adsorption column is scarce. Therefore, this study investigates removal of methyl orange (MO) and rhodamine-B (RB) dyes from mono-component (MO/ RB) and multi-component (MO + RB) system by using coconut shell activated carbon (CAC) in fixed-bed column. The influence of operating conditions viz. bed depth (D: 5–15 cm), flow rate (Q: 0.25–1 L/h) and dye concentration (Co: 25–100 mg/L) were examined. Subsequently, Thomas, Adams-Bohart and Yoon-Nelson models were used to model breakthrough curves. In addition, antagonistic (competitive) or synergistic (cooperative) nature of MO and RB dye removal in multi-component (MO + RB) system was elucidated. From results, it was observed that Thomas model better represented experimental data for sorption of MO and RB dyes from both mono-component and multi-component systems. Adsorption capacity of 19.51 and 15.54 mg/g for removal MO and RB using CAC. On other hand present adsorption capacity follows antagonistic nature in removal of MO and RB dye in multi-component system.

In recent years, salinity intrusion is a major concern in coastal regions due to the increase in demand for groundwater. However, monitoring and estimating the status of saltwater intrusion is a challenging task. Nowadays, the application of soft computing approaches gaining potential in engineering problems because of the rational structure and capable of analyzing non-linear problems. Saltwater intrusion is a key factor to assess the quality of groundwater, particularly in inland aquaculture areas. This paper presents aims to provide a detailed review study on the potential application of soft computing techniques to assess saltwater intrusion. Soft computing techniques such as artificial neural networks (ANN), support vector machine (SVM), random forest (RF), particle swarm optimization (PSO), fuzzy logic (FL), and genetic algorithm (GA), show desirable prediction results and to some extent replaces the tradition regression models. This paper also explores the case study on application of extreme learning machines (ELM) to predict salinity levels in the Upputeru watershed in Andhra Pradesh.

Spillways are the hydraulic structures used to destroy the surplus kinetic energy of floodwater downstream of the dam, having applications in flood mitigation, river engineering, and soil and water conservation. It is a concern over the past years that flood damages the dam structure due to overtopping, so it is important to reduce the impact of flooding over the structure by providing a safe passage of water. Steps provided over spillways improve the efficiency of energy dissipation from rapidly varied Cascades. In this research paper numerical simulation of flow over a rigid stepped spillway is performed using the CFD technique using the k-ε turbulence model with the Volume of Fluid (VOF) method to resolve the dynamics of free surface flow. Three models having three steps with fixed spillway heights of 30 cm and varied step dimensions (10 cm, 15 cm, 20 cm) of spillway were tested for flow characteristics. Five different discharges per unit width ranging from 0.020 to 0.95 m2 /sec were passed over each model. The conclusion from the result is that energy dissipation increases with an increase in step width and decreases with an increase in flow rate. The present study is in good agreement with the past studies.

One of the crucial factors in assessing the pond's intensive inland aquaculture water quality condition is ammonia. The excessive ammonia content will likely worsen water quality and result in the mass mortality of cultured individuals. For aquaculture management, it is therefore vital to accurately identify the ammonia nitrogen level of cultured water. However, the accuracy of technology for monitoring the ammonia content of aquaculture water currently needs to be improved to satisfy the demands of intensive aquaculture. This paper presents the prediction of the ammonia concentration of aquaculture water in real time using a hybrid intelligent soft computing algorithm. Radial basis function neural networks (RBFNN) and a hybrid model combining RBFNN, and particle swarm optimization (PSO) are used in this technique. Root mean square error (RMSE) and correlation coefficient (R2) were two separate statistical metrics used to compare the two methodologies and assess how well the soft computing strategies performed. The ammonia prediction results showed that the PSO-RBFNN method outperformed the RBFNN. The PSO-RBFNN model offers a real-time ammonia prediction value in inland farming waters that is moderately and generally accurate.

The rapid degradation of natural resources in chronically drought-prone areas is alarming, mainly due to increased biotic pressure on the fragile ecosystem, inappropriate management, and conservation practices. In the study area, hydrological boundaries serve as the unit of development, and all households are interconnected, not only in improving individually owned resources, but also in developing and managing common resources like grazing lands, tree cover, and groundwater. The authors identified the rural area of Kalugotla (V) to be in the south of Kurnool town. Since the total number of bore wells is estimated to be around 154, the density of wells indicates that part of the area is over-exploiting groundwater, especially along the stream course. An average area of 1294 acres of land has been irrigated under the bore wells at an average rate of 8.40 acres per well. The discharge of bore wells varies from 1400 to 4500 LPH. Based on field investigations, it is concluded that further drilling is not advisable to maintain groundwater balance.

The use of green materials in textile industries is a need for sustainable production. Life cycle assessment (LCA) of silk textile industry is performed from the manufacturing of silk, which starts from its extraction to the overall lifespan of the silk fiber. The LCA results will help to quantify the overall impacts related to resource depletion and major reduction of other adverse effects on the environment. The silk-based textile industries are one of the greatest sources of environmental degradation. To control this pollution, a subsection of silk industries came into existence known as spun silk which uses waste products from various stages at the time of production of silk which is referred to recycling of waste material of silk. Environmental contamination, low efficiency in production, wastage of material, and over usage of energy are some of the major issues with which spun silk sector is currently dealing. This review presents an eco-friendly approach for the production of mulberry spun silk fabric by the elimination of hazardous environmental impacts. Silk industry pollutes our natural ecosystem by discharging waste like dust, odors, gases, huge amount of material is wasted and production cost is also very high. The new process of utilizing silk waste reduces carbon emissions, material wastage, and also a lot of energy in the entire process which is a very big achievement in the production of spun silk fiber. In this paper, a comparative analysis is done between silk and cotton fiber to evaluate which fiber plays a more effective role in atmospheric degradation.

This paper presents a critical review of the existing research on the assessment of the carbon footprint of green concrete liners used in landfill construction. The review assesses the current understanding of the carbon footprint of green concrete liners and the key factors that affect the carbon footprint, including the materials and production processes used to manufacture these liners. The review is based on a systematic literature search, which identified and reviewed a total of 28 papers. The papers included studies that examined the carbon footprint of green concrete liners from the cradle-to-gate stage and from the cradle-to-grave stage. The review also identified potential areas for further research in order to improve the current understanding of the carbon footprint of green concrete liners. The results from the review indicate that the carbon footprint of green concrete liners depends on the materials used, their production process, and their service life. Furthermore, the review revealed that the current research on the carbon footprint of green concrete liners is limited, and further research focusing on the service life and the end-of-life stage of these liners is needed in order to develop a robust assessment of the carbon footprint of green concrete liners.

This paper investigates the effect of Fly Ash on the mechanical and thermal properties of concrete in order to address energy conservation and reduce carbon emissions in the building industry. The study shows that conductive heat transfer is responsible for energy consumption and carbon emissions in buildings. The conductive behavior of concrete is modified by using Fly Ash. The study finds that the inclusion of Fly Ash in the mass of cement significantly improves the compressive strength and toughness, and also increases its durability. Fly Ash can be used to partially replace cement and reduce the greenhouse effect, depending on the type of cement used. The paper presents the results of an experiment in which the compressive strength and thermal conductivity of concrete containing different percentages of Fly Ash were tested. The mix proportion was designed as per IS: 10,262–2009/IS: 456–2000 for M25 with OPC replacement by Fly Ash in percentages of 0, 15, 25, and 35. The study finds that the compressive strength of concrete increases up to 15% of Fly Ash, compared to conventional concrete strength whereas the thermal conductivity of concrete increases by the use of Fly Ash. The study concludes that the use of 15% Fly Ash in M25 concrete can improve its mechanical and thermal properties, making it a more sustainable building material that can help in addressing the issue of energy conservation and reducing carbon emissions, thus having significant implications for the building industry in terms of reducing its carbon footprint.

Construction and Demolition waste management in India is a critical issue due to the massive amount of waste generation and the environmental impact of improper disposal. The study reviews the current state of CWD management in India, including the policies and regulations, the challenges faced, and potential solutions for sustainable CDW management. The paper proposes the adoption of circular economy principles such as reuse, recycling, and redesign of CDW, to reduce the environmental impact and create economic opportunities. Moreover, the study highlights CDW management initiatives in India, such as the use of recycled CDW in road construction, the establishment of construction and demolition waste processing facilities, and the integration of CDW management. As per the survey, the waste material have applicable strength and might be used for construction work again. Most of the researchers suggest the use of recycled materials in construction. The paper emphasize the urgency of addressing the CDW management issue in India and the need for collaboration between the government, the private sector, and the community to achieve sustainable CDW management.

Rural India faces a massive waste disposal problem that will worsen in the coming years. With increasing population and economic inflation, the lifestyle of rural residents/households is changing. Thus, Solid Waste collection, disposal, and management have become a major rural problem, especially in populated cities. Three Gram panchayats (GP) were selected as study areas. The characterization study in these three villages is either non-existent or insufficient, with steps carried out in engineering ways from the collection, segregation at the source, transportation, and final disposal. Daily segregated waste collection, dry waste sorting, and wet waste processing data were captured in 3 g Panchayat for 3 months, based on the average of different data captured for 3-month average waste generation from households and commercials in the Gram Panchayat were calculated. All incoming unsorted waste will be stored temporarily at the unloading area near the SWM unit. EPR products like Tetra Pak and PET bottles will be moved immediately from the unloading area to their respective storage area. A segregated fraction of the waste like colored paper, tissue paper, cartons, plastic, and road waste will be stored. Reject waste will be stored in HDPE containers. Once the baling operation starts, items like Tetra Pak, PET, color paper, tissue paper, cartons, plastic, and road waste will be fed to the balers from their respective temporary storage location. The baled and un-baled segregated waste items will be stored at their respective allocated area. The result showed that the percentage of visual cleanliness will be drastically altered with the management of SW and inturn effects in the economic environmental aspects of the villages.

The increasing demand for greener approaches has made it critical for the industry to seize the opportunity, adopt new ways of thinking and set standards for the transition to a greener future. As the world strives to reduce greenhouse gas emissions, construction companies are playing an even bigger role. Green steel is a new concept aimed at reducing the environmental impact of steel production. Traditional methods of steel production rely heavily on fossil fuels, which lead to high carbon emissions. On the other hand, green steel is produced using renewable energy sources such as hydrogen and solar energy, which significantly reduces carbon emissions and overall environmental impacts. Green buildings have an opportunity to tap demand beyond geography and architecture. In fact, greener business models can attract sustainable investments. But by 2030, we can reduce fixed carbon in commercial buildings by 70%. In building construction, the use of green steel can help reduce the carbon footprint of buildings and contribute to the goal of achieving sustainable and environmentally friendly structures. Green steel can be used in a variety of architectural applications such as structural beams and columns, roof covering and cladding and reinforced concrete. Green steel also offers economic benefits such as reduced production costs and increased energy efficiency. With increasing demand for sustainable building materials, the use of green steel is expected to increase, creating new opportunities for the steel industry and promoting a more sustainable future for the building construction sector. This article details the benefits of green steel for manufacturing, structural support, its role in reducing carbon footprints and environmental protection opportunities.

The demand for cementless concrete in the construction sector is increasing by every day due to the global warming scenario of the world. In this study, industrial waste named GGBS along with Metakaolin has been utilized as the binders for the production of geopolymer concrete at varying proportions ranging from 0 to 100%. Another crisis that the world faces is the scarcity of river sand. To overcome the scarcity, the river sand is substituted with M-sand and Silica fume in various proportions. The optimum ratio of M-sand and SF was found to be 60:40, due to the performance in mechanical properties. The results show that the geopolymer concrete mix with 70% GGBS and 30% metakaolin has attained good mechanical properties when compared with conventional geopolymer concrete. The addition of metakaolin resulted in the acceleration in fresh concrete properties at a rate of 0.5% and 1% in workability and initial setting time, respectively.

An effort has been made to examine the flexural performance of ferrocement rectangular panels using geopolymer mortar consisting of fly ash and Ground Granulated Blast Furnace Slag as the base materials. River sand and M-Sand served as fine aggregates for the mortar. Hydroxides and Silicates of Sodium served as alkaline activators that polymerize the pozzolanic raw materials. For the designed mortar mix, the workability and compressive strength were determined using the standard test protocols. Ferrocement panels were cast using layers of fibreglass mesh and welded wire mesh (single, double and triple layers of the same type of mesh) and using hybrid layers (one type of mesh sandwiched between the other type) and subjected to the test under flexure. Characteristics like ultimate load, load versus deflection, ability to absorb energy and failure patterns were explored. Ductility enhancement is evident in welded wire mesh slabs in comparison to fibreglass slabs. Slabs with welded wire mesh have enhanced load-carrying capacities and energy absorption than the fibreglass mesh reinforced slabs. Irrespective of the type of sand and mesh, the ultimate load-carrying capacity increases with the number of layers of mesh. In the hybrid type, slabs with double welded wire mesh layers are superior with a higher load-carrying ability and ductility when compared to slabs reinforced with double fibreglass mesh layers.

A study was undertaken to ascertain the quality of water of borewells for human consumption in Tumakuru City Corporation limits utilizing Water Quality Index (WQI). 45 borewell samples were obtained from six wards during January–June 2022. The collected samples were tested for nine parameters, namely pH, Acidity, Alkalinity, Total Hardness, Calcium, Magnesium, Chloride, Sulphate and Nitrate as per IS code provisions. It was found that 35.5% samples are satisfying the BIS standards, and 64.5% samples are not meeting the standards as per WQI. Higher WQI was observed due to higher values of Alkalinity, Total hardness, Chloride, Calcium and Magnesium content present in the borewell water. The test results showed that the groundwater sources need to be treated before consumption and also sources have to be protected from contamination in future. This study helps protect groundwater sources and their management in future.

Groundwater resources are a critical constituent of the environment. The current article describes groundwater quality modelling based on WQI using ANN for drinking purposes in Madurai City. The primary objective is to design and develop an ANN-based model for predicting and simulating groundwater quality in Madurai. The model will be trained using water quality data; for carrying out the investigation, the data was collected from several parts of Madurai in the range of a 3.5 km radius, which represents 80 water samples in which qualitative parameters like TDS, SO4 2−, Cl−1, Mg2+, K+1, THS, pH, HCO3−1, Ca2+, Na+ , and WQI were estimated and modelled using the Levenberg–Marquardt algorithm (LMA) of ANN. It was observed that the ANN model values and the actual data fit well with statistical parameters like R2, MAE, and RMSE. The results indicate that the ANN models can predict very well. Such predictions could be beneficial in long-term planning to preserve the natural water table.

The supply of adequate quality and quantity of drinking water to the affected population in the relief camps is a significant post-disaster relief activity. Thus it is essential to keep the Water Treatment Plants (WTP) in a functional condition in the post-disaster scenario. Periodic Structural audit of WTP can ensure that the structural flaws and other non-structural defects, affecting the functionality of WTP are identified and rectified. A methodology for structural audit of WTP is developed in this paper shall be based on previous experience, an inspection of designs and drawings of WTP, use of visual tools such as photos, NDT methods, soil reports, electrical and mechanical designs, etc. to arrive at the inherent structural weakness, flaws in the WTP making it vulnerable to disaster. It is a questionnaire-based survey tool, to enlist all the salient information pertaining to the WTP. The survey is to be conducted only by expert surveyors having considerable exposure in the field of Water Supply Engineering. There are different types of WTP, the present exercise is focused on the conventional type of WTP which is the most popular and is located beside major rivers, and thus they are more prone to natural disasters. The expected outcome of the proposal is to improve the post-disaster response of the WTP structure to effectively ensure water supply to the affected population. This structural audit tool may be recommended to the water supply authorities to implement the process mandatorily by the imposition of bye-laws.

Andhra Pradesh's western Godavari Delta region is India's primary inland aquaculture zone, with a well-developed canal network. The Venkaya-Vayyeru canal is the most important canal stream depending on aquaculture catchment. It also serves as a drinking water supply for villages, aquaculture, and irrigation. As a result, the quality of the canal's water is essential. To determine the probable location as a pollution source, this study considered eight physicochemical water quality characteristics at three distinctive places along the canal for principal component analysis (PCA). Most parameters show significant geographical variation, indicating anthropogenic influence. According to PCA findings, the principal pollution sources are aquaculture ponds, processing businesses, and urban activities. Aquaculture intensively may contaminate canal water with salinity, ammonia, and Ca2+. Aquaculture effluents, soluble salts, nutrients, and organic matter were found to be the essential parameters responsible for changes in water quality using PCA and factor analysis. The study demonstrates the usefulness of multivariate statistical methods in understanding a pattern of feature variability and devising management techniques to enhance canal water quality by identifying prevailing characteristics that cause the most degradation in the water quality.

According to the composite water management index report of the National Institution of Transforming India (NITI) Aayog published in the year June 2018, India is facing extreme water stress crisis wherein, a figure close to 600 million people in the country are bereft of safe drinking water with nearly 70% of water being contaminated. There is a stern need of suitable-sustainable strategic water management programs considering the immense exertion of pressure on water resources due to increasing urban needs, climate changes and efforts to formulate within the framework of limited supply-to-growing demands. Some of the key features of proficient water-supply management are to ensure robust planning based on water consumption, harnessing the rainwater resource and implementation of plumbing networks with efficient fixtures. The present study focuses on computations of water consumption indices for a typical G + 3 residential building considering both conventional and rooftop rainwater as sources of water supply using respective plumbing layouts. Further, the water efficiencies are obtained for the cases of both conventional water fixtures and water-efficient fixtures. The results of the study showed a potential possibility of water-saving practice by 28% with the use of water-efficient fixtures and a water conservation index of 1.7 was obtained, a value close to the recommended range of 2–9 documented in several literature.

With the scarcity of fresh water all over the globe, wastewater can be cleaned using specific chemicals in sewage treatment plants, which aid in water recycling. This would increase the limited freshwater supply and postpone further investments in water treatment facilities. IoT sensors have been proven to be crucial for the STP to function effectively. It is employed to measure water’s alkalinity, acidity, pH, total hardness, dissolved oxygen, COD, chlorides, and other properties. These specifics will further aid in evaluating the water’s state to determine whether it may be recycled. Relays are used to link specific IoT sensors to the ESP-8266 microcontroller. Sensors like pH sensors, temperature sensors, chemical sensors, multi-parameter sensors, etc., can be used for this purpose. With adequate internet connectivity, these sensors will sense the parameters, send the data to a sensory node for processing, and then store the processed data in the cloud for later access. IoT sensors will find changes in various metrics at various purification processing phases. This information that will be kept in the cloud will provide specifics and statistics regarding pH levels, temperature, chemical reactions, and other factors, making it possible to monitor the STP from any location in the world.