Phytoextraction and phytostabilization are the most consistent patterns or mechanisms of action of phytoremediation. One of the elements influencing the mechanism of action of heavy metal absorption by plant species is Ethylene Diamine Tetraacetic Acid (EDTA). Therefore, this study aimed to determine the pattern of phytoremediation in water spinach and spinach due to the addition of EDTA in the soil. The treatments tested by factor 1 were water spinach (T1) and spinach (T2), and factor 2 was the concentration of EDTA consisting of 3 levels, 0, 3, and 6 g/polybag. Each treatment was repeated three times on five sample plants. Furthermore, growth evaluation was carried out in the first six days after planting and conducted every 3 days. It was carried out on variables such as changes in plant height, leaves area, total root length, Pb content in the soil, fresh and dry weight of shoots and roots, shoot, seeds, and Translocation Factor (TF). The results showed that water spinach and spinach had different mechanisms of action due to the application of EDTA in Pb-contaminated media. Furthermore, water spinach and spinach have a mechanism of phytoextraction and phytostabilization, respectively. Therefore, spinach is safer than water spinach when grown in Pb-polluted land.

The heavy metal speciation analysis in sediments helps us understand and evaluate essential and unavoidable issues in terms of both health and environmental hazards imposed by these metals in our lives. Analyzing the total content of heavy metals enables us to understand only the quantity of the contaminants. To understand the different species or the chemical forms of heavy metals available in the sediments, we must study their speciation. Speciation studies help us determine their possible sources as well as their environmental stability in terms of availability to plants and other organisms. The heavy metals in this study were specified using four-stage sequential extraction, also known as the BCR technique. This study mainly highlights the quantification of metal contamination of Cu, Zn, Pb, Ni, Cd & Cr, and chemical forms as species in sediment samples collected from different Pune District, Maharashtra sites. Heavy metal contamination from the collected samples was analyzed with the use of flame atomic absorption spectrometry. This study indicated that Zn and Ni are among the most abundant metals in the sediment samples; however, Cu and Cd belong to the least abundant category. The oxidizable and residual forms (immobile and cannot be used by the organisms readily) appeared dominant for most heavy metals. Very significant differences were observed in the speciation of heavy metals from sample to sample, which was probably due to differences in water/soil composition and the agrochemicals like pesticides, weedicides, and fertilizers used in agricultural practices; the wastewater generated from different pharmaceuticals, chemical processing and manufacturing industries as well as the improper wastewater treatment methods.

In this paper, greywater samples are collected from the kitchens of different types of buildings (residential and commercial) located in different districts within the city of Jeddah, Saudi Arabia. The collected samples are analyzed and compared with the potable water from the same region. The parameters investigated are pH, conductivity, total solids (TS), total dissolved solids (TDS), total suspended solids (TSS), total hardness, temporary hardness, permanent hardness, alkalinity, chloride, and biochemical oxygen demand (BOD). It was found that the amount of total suspended solids is very high in the greywater samples. It shows the presence of both temporary and permanent hardness. Their alkalinity values are greater than hardness. It may be due to the number, lifestyle, age of the occupants, presence of children, and social and cultural behavior of residents. The concentration of BOD level is very low, which shows that the greywater samples have lower concentrations of organic compounds. Design details of the greywater treatment plant are suggested based on the results of the analysis. This includes a screening chamber, grit chamber, settling tank, and filtration unit. The treated greywater is recommended for reuse for gardening, landscaping, and toilet flushing purposes.

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.

Over the past decades, energy forecasting has attracted many researchers. The electrification of the modern world influences the necessity of electricity load, wind energy, and solar energy forecasting in power sectors. Energy demand increases with the increase in population. The energy has inherent characteristics like volatility and uncertainty. So, the design of accurate energy forecasting is a critical task. The electricity load, wind, and solar energy are important for maintaining the energy supply-demand equilibrium non-conventionally. Energy demand can be handled effectively using accurate load, wind, and solar energy forecasting. It helps to maintain a sustainable environment by meeting the energy requirements accurately. The limitation in the availability of sufficient data becomes a hindrance to achieving accurate energy forecasting. The transfer learning strategy supports overcoming the hindrance by transferring the knowledge from the models of similar domains where sufficient data is available for training. The present study focuses on the importance of energy forecasting, discusses the basics of transfer learning, and describes the significance of transfer learning in load forecasting, wind energy forecasting, and solar energy forecasting. It also explores the reviews of work done by various researchers in electricity load forecasting, wind energy forecasting, and solar energy forecasting. It explores how the researchers utilized the transfer learning concepts and overcame the limitations of designing accurate electricity load, wind energy, and solar energy forecasting models.

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).

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.

The quality of surface water has a significant impact on human health and the entire ecological system. Sewer spillages from the surrounding informal settlements discharging into the river, carrying high concentrations of fecal coliforms, are one of the major causes of extreme pollution in the rivers of South Africa. These informal settlements are common in many developing countries, and they are usually located near waterways to compensate for basic demands for water, sanitation, and recreational space, where municipal infrastructure lags behind urban growth. One major problem has been poor sanitation and poor waste disposal practices in the informal settlements, which has led to the contamination of water resources. This study aims to assess the extent to which poor sanitation in informal settlements impacts the water quality of South African rivers, given the rapid rise in population and unemployment rate. The study also highlights health and environmental issues in the local regions caused by poor sanitation. Contamination of water bodies is associated with serious health problems and fatalities. Therefore, there is a need for frequent monitoring and management of waste products discharged into the neighboring aquatic environments.

The expanding nuclear industry has led to increasing radioactive waste in the environment. Exposure to these wastes causes considerable irreversible damage to the organisms, some of them being even lethal. Conventional methods like incineration, wet oxidation, and acid digestion have been used for radwaste treatment to control this. Apart from them, other organic methods like bioremediation are being widely applied by scientists. Many bacteria, fungi, algae, and plants are observed to possess remediating properties. Hence, these are now used on a large scale to treat the radioactive matter as quickly and effectively as possible. Techniques like bioaccumulation, enzymatic reduction, bioprecipitation, or phytoremediation methods such as phytoextraction and phytostabilization involving such organisms with remedial abilities have successfully removed the radioactive matter to an extent from the contaminated site. Further research is needed to increase the efficiency of the techniques and help remove radionuclides in an environment-friendly manner.

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).