Arsenic, aluminum, iron, lead, chromium, copper, zinc, manganese, and cadmium are some of the heavy metal pollutants in the air that cause severe impacts on the biotic and abiotic environment. This study intended to find the accumulation capacity of the heavy metals on the leaves of tree species such as Terminalia catappa, Syzygium cumini, Saraca asoca, Pongamia glabra, and Ficus religiosa and predict their accuracy by comparing different machine learning (ML) models. The samples were collected at six different locations (likely Vellagate, Cancer Institute, CSI hospital area, Moongilmandapam, Collectorate, and Pallavarmedu) and distributed in a manner within Kanchipuram town, Tamil Nadu, in February and March of 2018 and 2019, respectively. Six ML methods were selected, such as KStar (K*), Lazy IKB, Logistic Regression Algorithm (LR), LogitBoost Classifier (LB), Meta Randomizable Filtered Classifier (MRFC), and Random Tree (RT), for prediction and to compare the efficiency of their predictions. Out of six models, Logistic functions perform well in terms of TP rate when compared to other classifiers (93.21%-99.81% TPR– 0.93–0.99) and Logitboost attained a low TP rate that ranged from 0.76 to 0.82. This study indicates the feasibility of different ML methods in the prediction of species capabilities toward the accumulation of heavy metals.

Environmental sustainability encompasses various problems, including clean air, renewable energy, climate change, safe environments, and the capacity to live in a healthy community. One possible strategy for addressing these global problems is the circular bio-economy. Cleaner and lower-carbon environments may be fostered via the production of bioenergy and biomaterials, which can also help to maintain the energy-environment connection. To improve sustainability and the state of the planet, scientists are looking at renewable energy sources like ethanol. Compared to gasoline, ethanol has a reduced carbon footprint and a greater energy density, making it a viable alternative fuel. This study gives an overview of ethanol as a possible alternative fuel for flex-powered power generators in India to meet the goals of the circular bio-economy. This paper details the results of flex-fuel testing conducted on a light-duty power generator using an ethanol-gasoline mix. The findings reveal improved thermal efficiency and lower fuel consumption rates than basic fuel. The emissions of both carbon monoxide and unburned hydrocarbons were shown to be reduced.

In the present work, degradation of the herbicide metribuzin (C8H14N4OS) has been performed. A novel metribuzin-degrading bacterium, Olivibacter oleidegradans strain SP01, was isolated from the metribuzin-contaminated soil by an enrichment technique. To investigate the effect of various parameters on metribuzin degradation, various experiments were performed at an initial concentration in the range of 20-100 mg.L-1, a pH of 5-9, and a temperature of 25-40°C. Around 85% of the highest percentage degradation of metribuzin was obtained at a concentration of 20 mg.L-1 in 120 h under optimized conditions. The current work for the Metribuzin degradation study fits well with first-order reactions. Also, at higher concentrations, i.e., 100 mg.L-1, only 40.3% degradation of metribuzin was observed. The Olivibacter oleidegradans strain SP01 has the potential to be extremely beneficial in the removal of Metribuzin from the environment.

A common heavy metal pollutant of water resources, copper (II), can cause serious health problems or even death. Over the past few years, several filamentous fungi strains have been isolated, identified, and tested for their ability to bio-adsorb heavy metals for potential use in the bio-remediation of copper from wastewater. In this study, variables, including the dosage of fungal pellets, temperature, pH, time, initial copper concentration, and agitation rate, were assessed to select the best conditions for the adsorption of copper by Dictyuchus sterile pellets. To identify the active groups responsible for metal adsorption, microscopic observations were made using a light microscope and scanning electron microscope. The copper adsorbent was then analyzed before and after adsorption using an atomic adsorption spectrophotometer and Fourier transform infrared spectroscopy. The ideal adsorption conditions were: fungal pellets with a wet weight of 1 g.L-1 at a temperature of 25°C, pH 5.5, the initial copper concentration of 100 ppm, and shaking at a speed of about 250 rpm for 72 h to achieve a removal efficiency rate of 95%. Copper adsorbed with the biomass of the fungal pellets was 57 mg.g-1. The use of fungal pellets would be a method that can be used to increase the surface area of adsorption and also is thought to be one of the most cost-effective ways to remove trace metals from polluted water.

Heavy metal contamination is one of the significant concerns of environmental pollution. The present study was conducted to find out the correlation between soil and crop/food matrices grown at the exact location for Al, As, Ca, Cd, Cr, Cu, Fe, Hg, K, Mg, Mn, Ni, Na, P, Zn, and Pb elements near the industrial areas of Narol, Changodar, Vatva, Makarpura, Nandesari, and Ankleshwar in Gujarat, India. Soil samples were collected from 64 sampling sites in an industrial area. Twenty of these sites contained crop/food matrices used for the correlation study. The ranges of concentration of Cr (17-74.4 mg.kg-1), Cu (9.6-82.4 mg.kg-1), Ni (10.6-55.9 mg.kg-1), Pb (4.5- 20.7 mg.kg-1), Zn (21.5-112.4 mg.kg-1), and Al (7075-44557.5 mg.kg-1) for Soil and for crop Cr (0.3-0.6 mg.kg-1), Cu (0.3-8.6 mg.kg-1), Zn (1.1-43.5 mg.kg-1), Fe (12.6-69.4 mg.kg-1), and Al (5.8-102.2 mg.kg-1). According to the study, there is a strong correlation between the soil and crop/food matrices at the different locations, like 0.97 for Fe and Ni, 0.94 for Mg, 0.95 for Mn, and 0.55 for Pb and Zn, and very little correlation between K, P, and Ca, while a negative correlation between Al, Cr, Cu, and Na. The DTPA extractable method was used for the elemental analysis, and analysis was done using the ICP-OES instrument following microwave-assisted digestion. The results show that metal contamination transforms from soil to crop/food matrices, which represents a serious concern and requires action to address the metal contamination by industrialization.

In the current research work, the authors proposed a list of tactics to eliminate Cr (VI) with the help of pig bone biochar. The Cr (VI) was adsorbed in batches onto pig bone biochar to scrutinize the adsorption data. The studies determine the impact of adsorption dose, pH, and concentration. From the results, it was inferred that the optimum pH level was 7 for the removal of metal. The study calculated the adsorption isotherms in terms of affinity and adsorption capacity by leveraging Temkin, Langmuir, and Freundlich equations. According to the reports, the Langmuir model is suitable for the adsorption data, followed by Temkin and Freundlich equations. In this model, rapid adsorption kinetic rates were observed, whereas the equilibrium state was achieved after two hours. There seems to be a perfect collation between the kinetic adsorption data and the pseudo-second-order equation. The researchers determined both Lagergren and Ho’sconstants. When biochar was characterized with SEM (Scanning Electron Microscope), EDX (Energy Dispersive X-ray spectrometer), and FTIR (Fourier Transform Infrared spectrometer), it was revealed that the Cr (VI) ions interacted with the isolated aggregates formed on the biosorbent surface. From the results, it can be understood that the pig bone biochar can be effectively used to eliminate chromium ions from an aqueous solution.

As urbanization and population increase in the megacity, there is a need for engineering intervention and strategic monitoring of groundwater around landfills for environmental sustainability, pollution reduction and public health. This study evaluated water’s physical and chemical parameters in wells and boreholes near the Olusosun landfill in Lagos State to determine how they impact groundwater quality. An Atomic Absorption Spectrometer (AAS) was used to evaluate groundwater samples obtained from five locations within the dump site. Some water parameters, such as dissolved oxygen (DO), iron (Fe), lead (Pb), manganese (Mn), and magnesium (Mg), had concentrations that were higher than the WHO, NESREA, and Nigerian Standard for Drinking Water Quality (NSDWQ) standard limits in some sampling sites, with mean concentrations of 0.33 mg.L-1, 0.04 mg.L-1, 0.74 mg.L-1, and 0.74 mg.L-1, respectively. A small amount of lead was identified in the groundwater of the study area. A major source of air and groundwater pollution, the Olusosun landfill has a detrimental impact on the health of those who live there. Solid waste, groundwater interactions, and contaminated migration into the nearby neighbourhood were studied. It was observed that the degradation of waste products in dump sites releases harmful leachate into the groundwater. Even though some heavy metal concentrations in the study area are still within WHO, NESREA, and NSDWQ standard limits, investigations and further monitoring should be conducted regularly to assess the concentrations of heavy metals in groundwater.

Scientifically delineating ecological function zones is essential for national territory spatial planning and comprehensive management. In this study, we evaluated five ecosystem services, habitat quality, water yield, carbon sequestration, soil conservation, and food production, in Fuping County, China, and introduced the application of the topographic position index in exploring the topographic gradient effect of each service. We next applied the K-means clustering algorithm to identify the ecosystem services bundles and analyze the dominant type of ecosystem service in these bundles. A particle swarm optimization-support vector machine model was also constructed to identify the boundaries of ecological function zones and complete the ecological function zoning. The results are as follows: (1) In Fuping County, the high-value areas of habitat quality are distributed in the west, north, and southeast; those of soil conservation are in the northwest, northeast, and southwest; those of water yield are in the east and south; those of carbon sequestration are in the west, and those of food production is in the east. (2) The habitat quality first decreases and then increases with an increasing topographic gradient; food production and water yield decline with increasing topographic gradient; carbon sequestration and soil conservation increase with increasing topographic gradient. (3) Four types of ecosystem services bundles were identified. The dominant ecosystem functions of Type I, II, and III bundles are food production and water yield, carbon sequestration, and soil conservation, respectively. Type IV bundles generally have low levels of ecosystem services in the study area. (4) Four ecological function zones were delineated: food production zone, ecological conservation zone, potential restoration zone, and critical restoration zone. The research findings can provide a theoretical and practical basis for formulating and implementing ecological spatial management policies in the Taihang Mountains of China.

Malabar Giant Squirrel (Ratufa indica indica) is one of the four subspecies endemic to India (Abdulali 1952), common to northern and central Western Ghats among species Ratufa indica belonging to Subfamily Ratufinae. The study was designed to analyze the nest tree preferences of animals in the dry deciduous forests of the Umblebyle range, Shimoga, Karnataka (South India) during February, March, and April 2021, surveying 20 transects covering a distance of 47.7 km. Nest tree preferences were assessed by observing 406 dreys (nests) on 385 trees covering an area of 8350.89 ha. The nest trees came from 20 families and 41 species, with 12 tree species in the Family Fabaceae and 84 trees in the Terminalia paniculata having the highest preference. The Squirrels showed the highest preference for deciduous trees over semi-evergreen and evergreen trees. The most preferred tree height and nest height ranged between 11-20m, including 87.53% of nesting trees and 83.89% of nests, respectively. The average nest height was estimated to be 14.73 (±3.311) m, with a minimum and maximum height of 7 m and 28 m, respectively. The difference between average tree height and average nest height was 1.512m.

The COVID-19 first case was reported in India on January 30, 2020, and in Chhattisgarh on March 19, 2020, and since then a sharp surge has been noticed. The government of India imposed a nationwide lockdown on March 25, 2020, a complete suspension of human activities, viz., industry, construction, transport, academic institutions, etc., which resulted in an improvement in air quality (a decrease in PM2.5 and PM10, alteration in NO2 and an increase in O3). But the rate of cases of COVID-19 has increased sharply, and eventually, under economic pressure, the lockdown was withdrawn on June 1, 2020, which further accelerated the exponential growth of COVID-19 cases. We noticed that in the Chhattisgarh State of India, the alteration in the air quality index during the lockdown period is continuing even after the restoration of anthropogenic activities. Among PM2.5, PM10, NO2, and O3, the behavior of NO2 was found to be different than others; it was found to increase during the lockdown period but further decreased with the resumption of anthropogenic activities. We conclude that the air quality index has an insignificant impact on COVID-19 infection.