Biodiesel production from Pongamia pinnata, a tree-based oil using healthcare industrial waste dolomite as a catalyst, was studied. The studies aimed to establish the ideal parameters for producing biodiesel, such as temperature, the ratio of methanol to oil, and the weight percentage of the catalyst. The healthcare industrial waste was procured and characterized. With the operating conditions, temperature maintained at 75°C, methanol to oil molar ratio of about 20:1, and a catalyst weight of 5%, the optimum yield of 92.3% was obtained. The tree-based nonedible oil source for biodiesel production was suggested widely due to its ability to achieve sustainable development goals (SDGs). The Pongamia Pinnata cultivation on barren land supports the afforestation projects with economic and environmental values; further biodiesel from renewable bioresources reduces emissions, and livelihood development to eradicate unemployment are the primary objectives for achieving the SDGs. The tree-based biodiesel production and adaptation of dolomite as a heterogeneous catalyst have proven to be a recent attraction among scientists. The present study is the first report on Pongamia pinnata for biodiesel production catalyzed by dolomite.

Climate change is a worldwide phenomenon that significantly impacts the area, production, and yield of crops. Changes in climate conditions have diverse effects on farming globally. For instance, an increase in temperature can make specific crops more vulnerable to pests. Similarly, a decrease in rainfall reduces water availability, affecting both irrigated and rainfed farming practices. This study aims to investigate climate change effects on crop area dynamics in the Cachar district of Assam, India, for a period spanning from 1981 to 2017. The time series ARDL (Autoregressive Distributed Lag) model is employed to analyze the relationship between climate factors and areas under different crops. As a pre-requisite condition for ARDL, the Augmented Dickey-Fuller (ADF) test is employed to check the order of integration of area under selected crops. The research reveals that the annual average temperature negatively affects the area dedicated to chickpeas, while annual average rainfall negatively impacts the areas allocated to rice and chickpeas. Conversely, annual average relative humidity has a significant positive impact on the area of these crops in the study region. Policymakers may consider strategies and policies for agriculture by encouraging the cultivation of crop varieties that are more resilient to climate change.

Smart grids are modernized, intelligent electricity distribution systems that integrate information and communication technologies to improve the efficiency, reliability, and sustainability of the electricity network. However, existing smart grids only integrate renewable energies when it comes to active demand management without taking into consideration the reduction of greenhouse gas emissions. This paper addresses this problem by forecasting CO2 emissions based on electricity consumption, making it possible to transition to renewable energies and thereby reduce CO2 emissions generated by fossil fuels. This approach contributes to the mitigation of climate change and the preservation of air quality, both of which are essential for a healthy and sustainable environment. To achieve this goal, we propose a transformer-based encoder architecture for load forecasting by modifying the transformer workflow and designing a novel technique for handling contextual features. The proposed solution is tested on real electricity consumption data over a long period. Results show that the proposed approach successfully handles time series data to detect future CO2 emissions excess and outperforms state-of-the-art techniques.

The rapid global plastic production of 348 million tonnes in 2018 has led to widespread environmental pollution, especially in terrestrial ecosystems. This study examines microplastics in agricultural soils, coming alarmingly. Particles ≤5 mm, which are defined as microplastics, have detrimental effects on the earth’s environment. Because of its ecological importance, soil acts as an important microplastic sink, affecting soil and plant health and microbial activity. A variety of factors contribute to microplastic pollution in agricultural soils, including plastic mulching, manure, agricultural products (silage nets, twine), sewage sludge, weathering, and other indirect processes. These microplastics migrate, threatening soil integrity and biodiversity. Soil microplastics are analyzed for size, volume fraction, and polymer. Common materials include polyethylene, polypropylene, polyamide, polystyrene, polyvinyl chloride, and polyesters. Techniques, including optical microscopy and spectroscopy, extract and analyze microplastics. This comprehensive review calls for increased concern about the ecological effects of microplastics in agricultural soils. It emphasizes the importance of managing plastics to solve environmental challenges. The integrated environmental assessment highlights the complex relationship between microplastics and soil ecosystems, providing insights into potential risks and suggesting strategies to combat this looming environmental threat.

The issues of human impact on the environment are evident and pose a threat to the health and well-being of future generations. Technogenic disturbances in coal mining sites, such as open pits, excavations, and industrial waste, pose risks to both human health and the environment. Open-pit coal mines not only frequently cause the destruction of natural ecosystems, including landscapes, vegetation, and biodiversity, but they also significantly contribute to greenhouse gas emissions into the atmosphere. Addressing the carbon footprint necessitates not only the use of renewable energy but also the restoration of disturbed landscapes and vegetation, including trees and shrubs. All of this is achieved by implementing biological remediation within technogenically disturbed territories. This process fosters a return of biological balance and establishes favorable conditions for plant and animal life, while at the same time reducing carbon footprint indicators. The biological remediation of areas affected by the mining activities of coal mines can create new economic opportunities. The reclaimed land can be utilized for various purposes such as agriculture, forestry, park development, and tourism, thereby contributing to local economic growth and job creation. When planning measures for land bioremediation, it is essential to analyze all quality indicators of the land. In this case, the selection of technologies such as plants, fertilizers, and microorganisms can effectively restore territories.

The mountainous region of the Hunza River watershed basin, especially along the Karakorum highway, and also known as a third pole for the high accumulation of glaciers, which leads to huge devastating landslides occurring every year. Landslide susceptibility mapping was carried out using two deep machine learning techniques (DeeplabV3+ & universal network U-Net) and two statistical models (Intuitionistic Fuzzy divergence IF-D & Frequency ratio FR). The landslide susceptibility mapping is conducted using landslide inventory data and twelve conditional factors. The landslide susceptibility maps obtained from the two statistical models were compared with those generated by two deep machine learning models based on prediction accuracy measures, such as the Area Under the Curve (AUC) and Seed Cell Area Index (SCAI). The Success Rate Curve (SRC) was obtained using the training dataset, and the AUC values for the four models were as follows: 76.9% for IF-D, 76.9% for FR, 80.4% for DeeplabV3+, and 76.3% for U-Net. In terms of the Prediction Rate Curve (PRC) obtained from the validation dataset, the AUC values were found to be 80.8% for IF-D, 80.8% for FR, 81% for DeeplabV3+, and 77.8% for U-Net. To assess the classification ability of the models, the Seed Cell Area Index (SCAI) test was conducted. The results indicated that the SCAI (D-value) was 7.3 for U-Net, 10 for DeeplabV3+, 7.6 for IF-D, and 9.1 for FR. Overall, the findings revealed that DeeplabV3+ exhibited the highest prediction accuracy and classification ability, making it the most suitable choice for landslide susceptibility mapping in the relevant study area.

This study was conducted to determine strategies to enhance the sustainable forest management practices of the Tagbanua tribe. Specifically to describe the biodiversity and soil characteristics of the ancestral domain. The modified belt-transect method for biodiversity assessment developed by B+WISER (2014), further modified by the Department of Environment and Natural Resources (DENR) in the assessment, was used in this study. Results of soil chemical analysis showed significant variations among various land uses. The ancestral domain had at least 73 plant species belonging to 34 families and 59 genera. Four (4) taxa whose SN/families were still undetermined and another three (3) genera under families Annonaceae, Meliaceae, and Sapindaceae were unidentified. It had 12 plant species that are threatened with one critically endangered based on the list of threatened Philippine plants of the DENR. On the other hand, a total of 372 birds representing 61 species from 29 families were recorded. The high Shannon-Weiner Diversity Index (H’=3.69) and Shannon’s Evenness (HE=0.90) values indicate high avifaunal diversity and equitable distribution among the detected species. Most of the conservation priority species recorded in the area are Palawan endemic species. The survival of these birds is threatened by extinction due to habitat loss. This observation emphasized the importance of the ancestral domain as a refuge for these endemic species and conservation priority areas.

Urban xenobiotics are a vital contamination phenomenon of urban plants in the overall country. They are a result of human activity due to growing urbanization and population growth. There are extensive sources of both natural (soil or rock erosion, fires, biodegradation, and volcanic eruptions) and anthropogenic (soil pollution, air, and herbicides). Currently, the demand for pharmaceuticals, compared to the growing population, has placed a risk on the urban plant. Additionally, the production of illegal drugs has caused the release of dangerous carcinogens into fungal activities, which will have an impact on plant health, microbial structure, and fungal interaction. Because of the harsh environment, higher temperatures, heavy metals, and higher N deposition, most urban trees suffer from stress conditions, and mycorrhiza is negatively impacted by plant conditions. Some mycorrhiza fungi are unable to sporulate and hyphal at higher xenobiotic concentrations in urban areas. This chapter takes a look at the sources and compounds of xenobiotics and their harmful impact on mycorrhiza; and its association with the urban plants.

Soil stabilization is a very important method of science and engineering for improving the properties of soil. This paper aims to stabilize expansive black cotton soil through a biological approach involving plant extracts, plant waste materials, and microorganisms. While chemical methods exist, i.e., lime stabilization, geotextiles, etc., they are not economically feasible for large-scale applications. The primary issue with black cotton soil is due to the presence of montmorillonite clay mineral, which makes it unsuitable for the construction of roads and airfields. The cation exchange capacity (CEC) can be defined as the ability of soil to absorb and exchange positively charged ions; thus, if free positively charged ions are not available, the soil will not exchange them with others. The CEC of the soil is diminished, and ultimately, the soil is stabilized to some extent. This paper explores the preparation of plant extract, which contains a high number of anions, and directly inoculates it with soil, which nullifies the positive charge of the soil and diminishes the CEC. The use of cellulose and lignin-degrading microorganisms as an energy source and other minerals that are needed for their growth will be utilized from the soil to reduce CEC, i.e., Mg required for DNA replication and Ca required for their growth and maintenance. Another approach to diminishing the CEC is to use the microorganisms that produce EPS, which require Ca and Mg as adhesions for the formation of biofilm, i.e., Pseudomonas aeruginosa, Bacillus subtilis, and Escherichia coli. The use of microorganisms that have specific enzymes is also used in the diminishing soil CEC, i.e., by using ureolytic enzyme-producing bacteria like Sporosarcina pasteurii, Bacillus paramycoides, Citrobacter sedlakii, and Enterobacter bugadensis.

Groundwater, an invaluable resource crucial for irrigation and drinking purposes, significantly impacts human health and societal advancement. This study aims to evaluate the groundwater quality in the Mnasra region of the Gharb Plain, employing a comprehensive analysis of thirty samples collected from various locations, based on thirty-three physicochemical parameters. Utilizing tools like the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Irrigation Water Quality Index (IWQI), as well as Multivariate Statistical Approaches (MSA), and the Geographic Information System (GIS), this research identifies the sources of groundwater pollution. The results revealed Ca2+ dominance among cations and Cl− as the primary anion. The Piper and Gibbs diagrams illustrated the prevalent Ca2+-Cl− water type and the significance of water–rock interactions, respectively. The PIG values indicated that 86.66% of samples exhibited “Insignificant pollution”. NPI showed notable nitrate pollution (1.48 to 7.06), with 83.33% of samples rated “Good” for drinking based on the WQI. The IWQI revealed that 80% of samples were classified as “Excellent” and 16.66% as “Good”. Spatial analysis identified the eastern and southern sections as highly contaminated due to agricultural activities. These findings provide valuable insights for decision-makers to manage groundwater resources and promote sustainable water management in the Gharb region.