It is extremely difficult to clean up accidental oil spills in water since conventional oil sorbents absorb much more water in addition to the oil. Alternatively, cleanup techniques might lead to secondary contamination. This study examines and measures the oil absorption capacities of two hydrophobic natural fibers: water hyacinth (Eichhornia crassipes) and lotus (Nelumbo nucifera). At the laboratory scale, the absorption of engine oil, vegetable oil, and diesel oils onto various dry biomass materials, including water hyacinth and lotus with different particle sizes (BSS-44, BSS-60, BSS-100, BSS-120, BSS-160, and BSS-200), was investigated. Water hyacinth shows a higher absorption efficiency for all samples as compared to the lotus.

This study aimed to conduct a systematic review to analyze heavy metals seasonal concentrations in Uttarakhand tourist hotspot cities (Almora, Nainital, Ranikhet, Mussoorie, and Dhanaulti). A total of 45 samples of liverwort Dumotiera hirsuta were collected from five different cities during winter (Dry deposition) and monsoon (Wet deposition) in the year 2021. The concentrations of Zn, As, Cd, and Pb due to anthropogenic pollution load in the selected locations were analyzed by active biomonitoring using Inductive Coupled Plasma Mass Spectrometry (ICP-MS). Concentration loading of zinc, arsenic, cadmium, and lead was observed to be 79%, 71%, 48%, and 33%, respectively, higher during the dry (winter) season when compared with the monsoon dataset. Multivariant data were analyzed using Principal Component Analysis (PCA) with three components explaining maximum variation in data by factor loading through varimax rotation. The rapid growth and development have connected tourists to the mountain of the western Himalayas. Thus, a monitoring program is needed in these areas for further assessment. So that necessary action can be taken to conserve the eco-sensitive zones of Uttarakhand.

Sustainable clinical trials involve conducting trials in a socially conscious and environmentally responsible manner. This involves considering the effects of clinical trials on the environment and the populations engaged in the studies. The pharmaceutical sector, particularly clinical research, is a large contributor to greenhouse gas emissions. The need for a legal framework considering the environmental impact of hundreds of global clinical trials cannot be overstated. Clinical trials’ carbon footprint is a complex subject that calls for cooperation from various parties, including researchers, trial sponsors, healthcare providers, and regulatory organizations. The waste generated during clinical trials, including packaging materials, laboratory supplies, and hazardous waste from the disposal of clinical samples, can adversely affect public health and the environment. Therefore, addressing this issue is essential to ensure that clinical trials are conducted in an environmentally and socially responsible manner. The purpose of this study is to discuss potential strategies to cut down on carbon emissions, discuss the challenges in setting up clinical trials in an environmentally sustainable way, and highlight the importance of a precautionary approach during the various phases of conducting clinical trials. Although there is limited research on greenhouse gas emissions generated by clinical trials, it is evident that more work needs to be done in this field.

The current study is about detoxifying soil and water contaminated with toxic Cr(VI). To ensure that DAS1 could develop as well as possible, the pH was changed between 4 and 10. DAS1 showed its highest growth at pH 8, and at the same pH, it had an 85% potential to remediate by converting Cr(VI) to Cr(III). Immobilized bacteria increased the reduction of Cr(VI) to Cr(III) from the culture medium to 90.4%. The impact of glucose concentrations between 0.5 and 2.5 g.L-1 was examined. The greatest development was seen at pH 8 and 2 g.L-1 glucose concentration. The remediation potential was improved by up to 96% when the growing medium contained 200 mg.L-1 Cr(VI). The value of ks (0.434 g.L-1) demonstrated the substrate’s affinity for bacteria in accordance with the Monod equation, while μ max (0.090 h) demonstrated that DAS1 required 11.11 h for maximal growth. The multifactor experimental design was used to analyze mixed cultures of DAS1 and DAS2 in a 1:1 ratio, and it was determined that the X3Y2Z1 experiment design was best for completely removing Cr(VI) from the growing medium. By making pores using Na2EDTA, it was determined that the cell membrane’s impermeability did not cause Cr(VI) resistance in DAS1. The delayed lag phase indicated that the enzyme activity was inductive rather than constitutive.

A strategic shift towards sustainable, appropriate supply chain networks and data-driven decision-making in solid waste management in rural and urban areas can drastically reduce environmental pollution. This study utilizes a hybrid strategy of genetic algorithms and fuzzy logic to improve the supply chain network in solid waste management in Lagos State. In this research, four local governments in Lagos State are taken as a case study to help Identify solid waste in those selected areas, acquire data to better understand the supply chain network in solid waste management, and use the data acquired to model for the algorithm. A series of 30 iterations were carried out using a fitness parameter of frequency, price range, and means of disposal to determine who should be given utmost importance in the chain. Supply chains often exhibit inadequacies that may be enriched using Artificial Intelligence (AI) tools. The optimization model is flexible and useful, so everyone involved in the chain can coexist harmoniously. One of the reasons causing these inadequacies in proper waste management is a poorly planned supply chain network. It was concluded that the scavengers must be recognized as major participants in the movement of waste from houses to these provided refuse bins, with their frequency increased to 6 times daily with dustbins ranging from 9-20 be provided on each street which the private service participants (PSP).

Water pollution in the Vam Co River basin is becoming more complicated due to untreated wastewater being directly discharged into rivers and canals from agricultural, industrial, and domestic activities. To assess the water quality in this area, this study conducted monitoring at ten sampling locations (S1-S10) from 2018 to 2022, calculated the Water Quality Index (WQI) for each parameter, and simulated water quality in 2022 using the 1D- MIKE 11 model developed by DHI with two main modules including HD and AD. The findings showed that most parameters did not surpass the allowable limits per QCVN 08-MT:2015/BTNMT on Vietnam National Technical Regulation on Surface Water Quality. However, organic and microbial pollution led to certain parameters, such as BOD5, COD, and Coliform, exceeding the limits. The lowest water quality was recorded in Long An province, especially at sampling locations S3, S4, and S6, with the average WQI for nine water quality parameters from February to July 2022 being 58.4, 67.8, and 21.1, respectively. Additionally, the simulation outcomes of the MIKE 11 model salinity, BOD5, DO, and NH4 aligned with the real measurements taken. It has been observed that the southern area of the Vam Co River Basin possesses poorer water quality than the northern part, with Long An province located downstream of the Vam Co River basin being the primary source of pollution. The development of this hydraulic model signifies a crucial milestone in comprehending and regulating the effects of pollution in monitoring and managing water management systems, controlling saline intrusion, and ensuring water supply for agricultural production and daily use in the Vam Co River basin.

In this study, we summarized our own and literature data on the helminth fauna in amphibians, reptiles, birds, and mammals inhabiting the Mordovia Nature Reserve (European Russia). The history of research on parasitic worms in vertebrates has more than 70 years here. Nowadays, 242 species of helminths have been identified in vertebrates in this protected area: 54 cestodes, 87 trematodes, 98 nematodes, and 3 acanthocephalans. Of these, 169 helminth species have an indirect life cycle, while 73 develop directly. 217 revealed parasite species use vertebrates as definitive hosts and 21 as intermediate and/or parathenic hosts. Three species of trematodes, Gorgoderina vitelliloba, Haplometra cylindracea, and Opisthioglyphe ranae combine the larval and mature lifestyle stages in amphibians. The most diverse helminth fauna is in rodents (41 species), birds (38), artiodactyls (37), and insectivores (35). Less rich in amphibians (32), bats (32), reptiles (26), and carnivores (19). Only six parasite species are found in hares. Most of the helminth species recorded in the vertebrates of the Mordovia Nature Reserve belong to the Palearctic faunistic complex – 107 species. Fifty-eight species are cosmopolitan. The range of 39 species covers the Holarctic. The distribution of 37 species of helminths is limited to Europe. Seventy-three of 242 species found in the nature reserve’s vertebrates have medical and veterinary importance as potential pathogens of dangerous zoonoses.

Lipases are utilized in biodiesel production utilizing various types of substrates. The use of lipase in bioenergy production aims to reduce energy crises and environmental pollution. Lipase-producing indigenous bacteria Bacillus licheniformis (Accession no. OP56979) and Bacillus rugosus (Accession no. OP56980) were isolated from various oil-contaminated sites. The isolated potential lipolytic bacteria were screened for maximum lipase production. Then, the bacteria showing the highest lipolytic activity were subjected to identification using the 16s rRNA technique while other isolated were identified biochemically. Lipase [LipBL-WII(c)] from Bacillus licheniformis having the highest lipolytic activity expressed various characteristics. Characterization of crude LipBL-WII(c) expressed that it showed stability in a wide range of pH (4 to 10) with optimum lipolytic activity observed at pH 8. It was then found to be active at a temperature range from 20°C to 80°C with optimal at 50°C. Lipase activity was also stimulated in metal ions such as Ca+1, Mg2+, and Zn2+ the most. Furthermore, LipBL-WII(c) retained lipolytic activity in the presence of various organic solvents and surfactants. The kinetic parameters (Km and Vmax) for LipBL-WII(c) were ascertained using Lineweaver- Burk plot. LipBL-WII(c) showed a potential for biodiesel production using olive oil as a source. Lipase gave 84% yield of biodiesel production from olive oil. Thus, it could be employed as a potential candidate for green biodiesel production using oil sources.

The neurotoxic effects of exposure to low levels of the pesticide imidacloprid (IMI) and the effect of curcumin are of current interest when exposure occurs during early development. Male weanlings of Swiss albino mice (21 days old) were given 1 mg.kg-1 body weight (1/130 of LD50 and 2 mg.kg-1 body weight (1/65 of LD50) of imidacloprid and Curcumin (100 mg/kg body wt.) by oral gavage from postnatal day 21 to postnatal day 60. Young adult offspring were studied for behavioral parameters and learning ability using open field and Morris water maze. After completing the behavioral test, brains were processed for acetylcholine esterase activity and antioxidant enzyme estimation. The level of lipid peroxidation and activity of catalase, superoxide dismutase, and glutathione were assayed. In the present study, parameters such as locomotor activities and cognitive skills were not affected compared to lower doses of imidacloprid in the open field and Morris water test. However, activities and levels of antioxidant enzymes such as catalase and lipid peroxidation were found to be altered. In contrast, superoxide dismutase, acetylcholine esterase activity, and glutathione remained unchanged compared to the control. This suggests that subchronic exposure to low doses of IMI can lead to significant alterations in the enzymes of antioxidant protective systems such as catalase and lipid peroxidation. Co-treatment with curcumin was able to restore the activities of the affected enzymes in comparison with the control.

Environmental issues have continued to spur discussions, debates, public outrages, and awareness campaigns, inciting interest in emerging technologies such as Artificial Intelligence. Its usage is spread across many environmental industries, including wildlife protection, natural resource conservation, clean energy, agriculture, energy management, pollution control, and waste management. In 2017, at the United Nations Artificial Intelligence Summit in Geneva, the UN acknowledged that AI could be an enabler in the sustainable development process towards peace, prosperity, and dignified life for humankind and proposed to refocus on the application of AI in assisting global efforts on sustainable development to eradicate poverty, hunger and to protect the environment as well as to conserve natural resources. It is vital to address environmental sustainability concerns; however, with the advent of AI, most common environmental issues are now solvable by prioritizing human interests. Sustainability encompasses the interrelated areas of the environment, society, and economy. According to the United Nations’ “Our Common Future,” also known as the “Brundtland Report,” it is defined as “development that satisfies current needs without compromising the ability of future generations to meet their own needs.” Unfortunately, the Earth is currently facing serious consequences from global warming and climate change, and immediate action is required to encourage the use of environmentally friendly and sustainable products to address these issues. Environmental degradation and climate change are numerous environmental concerns requiring novel and intelligent artificial intelligence solutions. The literature on AI and environmental sustainability encompasses various domains. Notably, AI is being used to address the bulk of regional and global environmental concerns, including energy, water, biodiversity, and transportation, even though many of these sectors have permeated and evolved. However, there is a need to combine current literature on the application of AI, particularly in relation to environmental sustainability in areas such as energy, water, biodiversity, and transportation. There is a significant lack of research on how AI can promote environmental sustainability. This research aims to explore how AI can be applied to address environmental issues in various sectors to achieve the Sustainable Development Goals (SDGs).