Soil is one of the largest carbon reservoirs sequestering more carbon than vegetation and atmosphere. Due to the enormous potential of soil to sequester atmospheric CO2, it becomes a feasible option to alleviate the current and impending effects of changing climate. Soil is a vulnerable resource globally because it is highly susceptible to global environmental problems such as land degradation, biodiversity loss, and climate change. Therefore, protecting and monitoring worldwide soil carbon pools is a complicated challenge. Soil organic carbon (SOC) is a vital factor affecting soil health since it is a major component of SOM and contributes to food production. This review attempts to summarize the information on carbon sequestration, storage, and carbon pools in the major terrestrial ecosystems and underpin soil carbon responses under climate change and mitigation strategies. Topography, pedogenic, and climatic factors mainly affect carbon input and stabilization. Humid conditions and low temperature favor high soil organic carbon content. Whereas warmer and drier regions have low SOC stocks. Tropical peatlands and mangrove ecosystems have the highest SOC stock. The soil of drylands stores 95% of the global Soil Inorganic Carbon (SIC) stock. Grasslands include rangelands, shrublands, pasturelands, and croplands. They hold about 1/5th of the world’s total soil carbon stocks.

This research was conducted in the waters of Malili River, East Luwu Regency, with 4 observation points in Malili River East Luwu Regency, namely: (a) Southeast Sulawesi Sub Das (Point 1) namely Pongkeru village bridge, Coordinate point 12126.69’8°” E; (b) Larona Sub Das Karebbe basin bridge (Point 2), Coordinate point 12115.09’9°” E; (c) The meeting point of Larona sub-dash and Pongkeru sub-dash (Point 3), coordinate point 12159.64’8°” E; (d) Upper Malili River, Malili village, Malili bridge (Point 4), Coordinate point 12147.20’5°” E. Metal concentration and distribution were analyzed descriptively with the help of images (maps), graphs, and tables. Differences in Pb, Cd, and Hg metal concentrations in sediments between point locations were tested using analysis of variance (ANOVA) through the SPSS version 22 program. The relation between grain size, organic matter, and Pb, Cd, and Hg metal concentrations was tested using linear correlation. The results showed that the sediment content of Pb and Cd metal concentrations at each point location did not exceed NOAA (1999) quality standards. In the sediment, Hg metal concentration exceeds the quality standards of NOAA (1999) at each point, namely point 1. Pongkeru 0.590 μg.g-1, point 2. Karebbe 0.229 μg.g-1, point 3. Kawasule 0.514 μg.g-1 and point 4. Malili 0.358 μg.g-1. The relation between sediment size and Pb, Cd, and Hg metal concentrations at each point location has a weak correlation. The relation does not significantly affect the content of heavy metals in the sediment. It may be due to other factors, such as the source of heavy metal pollutants in each different point location. The relation between organic matter and the concentration of Pb, Cd, and Hg metals at each point location has a weak correlation. The relation does not significantly affect the content of heavy metals in the sediment because it may be due to other factors, such as different sources of heavy metal pollutants in each point location.

The Rumei Hydropower Station is a typical cascade hydropower development project in a plateau area. The dam site is located in an area with complex topography, lithology, and geological structure. Geological disasters are developed in the area, mainly debris flow. Thus, taking the dam site and the surrounding areas as key evaluation objects, the engineering geological characteristics, geological environment characteristics, and the susceptibility and risk of geological disasters that may be caused are predicted and evaluated. The main methods used in this assessment are the binary logistic regression model and expert evaluation. The results show that the susceptibility to geological disasters is small and medium. The results of this study could provide a scientific basis for the rationality of the general layout and site selection of the project construction in the plateau water elevator level development reservoir area.

Characterization and treatment of greywater are major environmental issues in most nations of the world. The research aims to characterize and evaluate recycling technologies using an analytical hierarchical process for Afe Babalola University Ado-Ekiti (ABUAD) community. A survey was conducted around ABUAD to determine the number of functioning boreholes and active water systems in the area, the total population of students was derived from the total head count of each room and student in each hostel, and a population projection for the next 3 years was conducted to determine the rate at which the student body will grow in terms of future water demands, and daily water volume and questionnaires were used to collect data. Before developing the small-scale model of the greywater filter system (consisting of activated carbon, shaft sand, pebbles, cotton fiber, and gravel), water grey samples were gathered from several ABUAD locations to evaluate the pollution level of each greywater source. A total of 88 students (43 males and 45 females) replied to the survey, revealing their high need for clean water and their dissatisfaction with the water supply in their respective hostels. The water quality tests conducted in the various locations of ABUAD reveal high levels of total dissolved solids (TDS) and turbidity, particularly in the girl’s hostels, and the water was discovered to be predominantly alkaline. After passing a sample of greywater through the small-scale greywater filtering device, it was determined to be effective, since it produced clear, reusable water and a greywater filtration system in ABUAD will yield favorable outcomes.

Environmental pollution is a serious concern nowadays with its disastrous impact on living organisms. In several types of pollution, Air pollution takes on a crucial role by directly affecting the respiratory system and causing fatal diseases in humans. Air pollution is a mixture of gaseous and particulate matter interweaved by different sources and emanating into the atmosphere. In particular, particle pollutants are critical in growing air pollution in India’s main cities. Forecasting the particulate matter could mitigate the complications caused by it. The employment of a model to predict future values based on previously observed values is known as time series forecasting. In this paper, the PM2.5 pollutant emission data recorded at the Kodungaiyur region of Chennai city were forecasted using three-time series models. The standard ARIMA model is compared with the deep learning-based LSTM model and Facebook’s developed Prophet algorithm. This comparison helps to identify an appropriate forecasting model for PM2.5 pollutant emission. The Root Mean Squared Error (RMSE) acquired from experimental findings is used to compare model performances.

The availability of land for proper waste disposal is one of the most important and emerging potential challenges in most big cities. Although some attempts are being made to minimize and recover garbage, landfill disposal continues to be the dominant method of waste disposal. An improper landfill site can negatively impact the environment, the economy, and the environment. Thus, it should be carefully chosen, taking into consideration both rules and standards from other sources. To examine all aspects of this study, an integration of the “Geographic Information System (GIS)” and the “Analytic Hierarchy Process (AHP)” was incorporated for land-fill site selection. Various parameters were examined to make decisions about landfill site selection. These parameters included slope, elevation, soil texture, LULC, surface water, groundwater table, road network, historical areas, and residential areas. An analytic-hierarchy process was used to determine the relative importance of each parameter, and a final site suitability map was created. With an equal interval classification method, the final index model was categorized into four categories, which included “unsuitable”, “less suitable”, “moderately suitable” and “suitable”. As a result, 30.28% of the study area was less suitable, 28.49% was moderately suitable, 12.39% was suitable, and 28.84% of the study area was unsuitable for landfilling.

Climate change and global warming are two of the world’s most pressing environmental issues. With CO2 being one of the most significant greenhouse gases released into the atmosphere, and cement and concrete manufacturing accounting for roughly 10% of worldwide CO2 emissions, the construction sector must employ an environmentally sustainable substance as a substitute for cement. The CO2 emissions, energy factor, and strength qualities of concrete were investigated. Those negative reaction of conventional cementitious substances is reduced by the development of binary and ternary cementitious systems. In this study, two mineral admixtures obtained from industrial waste substances, red mud (RM) and silica fume (SF), had been used as the alternatives for cement and fine aggregate was fully replaced by manufactured sand (M-sand). An experimental examination of the compressive strength, water absorption, density of concrete, equivalent CO2 emission, and energy factor for environmental benefits with the comparison of RM on SF-based eco-friendly concrete mix of M30 grade was used. A binary and ternary blended cementitious system with RM and SM was created with twelve various mix proportions, varying from 0-20% by 5% increases. From the binary blended cementitious system (BBS), based on the observed mechanical characteristic of concrete it was found that the optimum level of RM was 15% and SF was 10 % by the volume of cement. Similarly, for the ternary blended cementitious system (TBS), the level of 10% RM and 10% SF in the cement mixture provides a much higher improvement in compression strength compared to the alternative trials. The negative sign implies that replacing cement with RM and SF reduces energy consumption (-1.91% to -6.97%) and CO2 emissions (-4.52% to -16.16%). The use of mineral admixtures such as RM and SM in supplementary cementitious materials results in a significant outcome and potential impact on the production of sustainable concrete that addresses environmental issues.

As China’s natural resource governance has turned to high-quality management, establishing reasonable and ecological land-use patterns is an effective means of promoting natural resource utilization and improving the quality of the ecological environment. Therefore, this study used ecological land as the expansion source to construct an ecological land-use pattern with the minimum cumulative resistance model in Haixing County, China, based on regional food security, ecological security, and construction land expansion patterns. This work also involved designing ecological corridors, radiation channels, strategic nodes, and other ecological components. The results demonstrate that (1) the ecological land source is 7976.93 hm2, accounting for 9.19% of the total area. It is mainly distributed in the southeast of the county, mainly in the river system and woodland; (2) the food security situation of Haixing County can be divided into four zones, most of which are agricultural adjustment areas, indicating that the ecological security of cultivated land in this area needs to be improved; (3) the ecological security level of Haixing County is divided into four areas, and the ideal safety zone accounts for the smallest area, indicating that the regional ecological situation is very unstable; (4) construction land expansion zone is divided into four parts. A suitable construction zone occupies the largest area and is mainly distributed around the current construction land; (5) the expansion of the ecological land-use pattern of Haixing County includes four zones, 15 ecological corridors, 12 radiation channels, and 35 strategic nodes, which is conducive to optimal land allocation from an ecological security perspective. This paper puts forward some suggestions for ecological protection and intensive urban development.

Mathematical Modeling of the activated sludge process (ASP) enhances the understanding of the process and improves the quality of the effluent released. However, as the process is complex and nonlinear, mathematical modeling of the process has been a challenge. In this study, multi-layer perceptron neural networks (MLP-ANN) are investigated to predict water quality parameters for better control of wastewater treatment plants employing an activated sludge process. The study area selected was in a central district of the southern state of India. The parameters to be investigated are biochemical oxygen demand (BOD), suspended solids (SS), and pH. The model is evaluated based on statistical parameters of correlation coefficient R and mean square error (MSE). The neural network toolbox of MATLAB 2015b is used for modeling and simulation study. It has been found that effluent biochemical oxygen demand was predicted with a maximum correlation coefficient of 0.927 and minimum mean square error of 0.0022, effluent suspended solids were predicted with a maximum correlation coefficient value of 0.947 and minimum mean square value of 0.0058, effluent pH was predicted with a maximum correlation coefficient value of 0.8299 and minimum mean square value of 0.0132.

An ecological vitrimer is being developed using activated carbon pyrochar from municipal mixed plastic waste pyrolysis into an epoxy composite. Durable vitrimeric materials may be created by adding pyrochar to polymeric composites. Due to their ductility, reusability, and recyclability, vitrimeric materials have become popular and reliable materials. As a result, the self-healing temperature of composite vitrimers is lower via disulfide exchanges than that of virgin epoxy vitrimers. Additionally, compressive studies have been used to study self-healing capacities, and modulus variations have been used to highlight changes in the healing efficiency of the materials.