Besides adsorption rate constant, the half-life was also a basic factor that described the characteristics of adsorption kinetics. However, the direct prediction of the half-life was still a problem to be addressed urgently. In this work, the parameter τ was introduced into the pseudo-first-order (PFO), pseudo-second-order (PSO), pseudo-nth-order (PNO), and the corresponding fractal-like kinetic models (fractal-like PFO, fractal-like PSO, and fractal-like PNO) to directly predict the half-life by changing the boundary condition, i.e., the replacement of qₜ = 0, t = 0 by qₜ = qₑ/2, t = τ. The fitting performance of these kinetic models after modification was evaluated by nitrate adsorption on polyaniline-modified activated carbon (PAN/AC) and phosphate adsorption on zirconium-loaded Ca-montmorillonite. The results indicated that this type of model modifications did not influence the fitting performance and that the half-life was easily obtained only by the curve fitting. The practical significance of this work was to simultaneously predict the adsorption rate constant and half-life using the modified kinetic models.

Rapid population growth and agricultural development are generating a considerable amount of effluents, which poses threats to the quality of rural water resources as well as sanitary conditions. However, with a range of rural wastewater treatment (WT) technologies available, one major problem facing the practitioners is which to choose as the most favorable option suited to specific areas. In this study, a novel decision-making framework is proposed to evaluate and select the optimal alternative in rural areas of Xi’an within multiple consecutive time periods. Firstly, an evaluation index system is constructed and picture fuzzy numbers (PFNs) are used to represent both evaluation levels and experts’ refusal due to limitation of knowledge. Secondly, fuzzy analytical hierarchy process (FAHP) is applied to derive weights of criteria, which enables experts to assign fuzzy numbers to express their preferences for comparison judgments. Thirdly, evidence theory is utilized to obtain the aggregated values from multiple time periods. Finally, based on the belief intervals obtained, sequencing batch reactor (A₄) is determined as the optimal rural WT technology in Xi’an from 2006 to 2020, whereas the membrane bio-reactor (A₂) is the last option. The effectiveness of the proposed framework is further validated by comparative analysis. This research can hopefully serve as useful guidance for the assessment of rural WT technologies in various regions.

Epidemiological studies have proven that children mental health can be affected by environmental pollutants which are believed to be visible in the form of psychological disorder later in their childhood. Moreover, the effects of children mental health are evidently clear in the case of phthalates which have been observed to increase psychological disorder, specifically attention-deficit hyperactivity disorder (ADHD). Hence, the present study aims to conduct a systematic review and provide an overview of the existing literature on the association between urinary phthalate metabolite concentrations and ADHD symptoms among children by emphasizing the confounding factors and limitations. Additionally, this review addressed the possible phthalate mechanism insights in human body including its impact on ADHD symptoms. In this case, 16 epidemiological studies (five cross-sectional, nine cohort and two case control studies) that met all the inclusion criteria were selected out of the total of 427 papers screened to show varying quantitative associations between phthalate exposure and ADHD symptoms among children with confounding factors and limitations in the existing studies in regard to the exposure and outcomes. This review also attempted to present possible explanation on phthalate mechanism in children body and its connection on neurodevelopment and ADHD symptom development which remains unclear in most of the studies. Finally, it is highly recommended for further research to carefully design cohort studies from prenatal to later childhood development with a complete sample size in order to understand phthalate impacts on children health.

Lake water-level fluctuation is a complex and dynamic process, characterized by high stochasticity and nonlinearity, and difficult to model and forecast. In recent years, applications of machine learning (ML) models have yielded substantial progress in forecasting lake water-level fluctuations. This paper presents a comprehensive review of the applications of ML models for modeling water-level dynamics in lakes. Among the many existing ML models, seven popular ML model types are reviewed: (1) artificial neural network (ANN); (2) support vector machine (SVM); (3) artificial neuro-fuzzy inference system (ANFIS); (4) hybrid models, such as hybrid wavelet-artificial neural network (WA-ANN) model, hybrid wavelet-artificial neuro-fuzzy inference system (WA-ANFIS) model, and hybrid wavelet-support vector machine (WA-SVM) model; (5) evolutionary models, such as gene expression programming (GEP) and genetic programming (GP); (6) extreme learning machine (ELM); and (7) deep learning (DL). Model inputs, data split, model performance criteria, and model inter-comparison as well as the associated issues are discussed. The advantages and limitations of the established ML models are also discussed. Some specific directions for future research are also offered. This review provides a new vision for hydrologists and water resources planners for sustainable management of lakes.

2,4-Dichlorophenoxyacetic acid (2,4-D) is one of the most commonly used herbicides worldwide. While the effects of 2,4-D in target organisms are well known, its consequences in nontarget organisms are not fully explained. Therefore, the purpose of this study was to investigate the effects of the herbicide on mitochondrial energy metabolism, oxidative status, and exploratory behavior in adult zebrafish. Animal exposure to 2,4-D increased cytochrome c oxidase and catalase activities and reduced SOD/CAT ratio, moreover, increased the total distance traveled and the number of crossings. Finally, animals exposed to 2,4-D spent more time in the upper zone of the tank and traveled a long distance in the upper zone. Overall, our results indicate the 2,4-D can provoke disabling effects in nontarget organisms. The obtained data showed that exposure to 2,4-D at environmentally relevant concentrations alters mitochondrial metabolism and antioxidant status and disturbs the zebrafish innate behavior.

Biodiesel is a mixture of fatty acid methyl esters (FAME) from either vegetable oils or animal fats. Although biodiesel biodegrades faster than diesel fuel, the impacts of this biofuel in environment throughout its biodegradation process should be investigated. For this reason, the objective of the present study was to evaluate the microbial activity, the phytotoxicity, and the formation of metabolites during biodegradation of the contaminated soil with biodiesel. Microbial activity was evaluated using culture-dependent methods in soil samples artificially contaminated with biodiesel—followed by pH adjustments. The formation of metabolites during biodegradation was identified using gas chromatography coupled with mass spectrometry (GC/MS). Respirometric method was also applied to evaluate total microbial activity. Seeds of Cucumis sativus were sown in soil samples before and after biodegradation to expand our knowledge on the impacts of such metabolites in a eukaryotic test-organism. Culture-dependent assays successfully allowed the quantification of microorganisms during biodegradation. According to CO₂ production, biodiesel initially acted as a biostimulation agent increasing microbial activity. Indigenous microbiota degraded biodiesel into smaller compounds such as pentane, free fatty acids, and methanol. Soil pH significantly dropped from 5.4 to 3.0 after 120 days of biodegradation as a result of high concentration of free fatty acids. These free fatty acids inhibited further microbial growth after biodegradation. It was proposed that correcting soil acidity during biodegradation would be enough to sustain microbial growth. However, pH decrease was just one of the factors that inhibited microbial growth and plant root development. It was proposed that biodegradation yielded toxic metabolites such as methanol. These metabolites contributed to impair the root elongation due to alcohol-specific properties to solubilize a wide variety of lipids within the seed. Therefore, the present study draws attention to metabolites from biodegradation of biodiesel and their potentially harmful environmental impacts.Biodegradation of biodiesel changes soil pH, as it generates metabolites that are phytotoxic, and reduces microbial counts (CFU g⁻¹ dry soil).

The leaching process and drainage chemistry of acid rock drainage is mainly controlled by geochemical reactions and how water carries soluble reaction products in waste rock piles. This paper studied how water flows through a full-scale waste rock pile at the Equity Silver mine site in British Columbia, Canada and elaborated on their effects on the leaching process and drainage chemistry. A revised dual-permeability model coupled with mass transport was adopted to investigate preferential flow and matrix flow in the pile simultaneously while considering water and geochemical products leaching/exchange between them. Furthermore, a particle-level water film model and also the effects of air flow, oxygen transport, and heat transfer in pile scale were integrated to account for geochemical reactions. Simulation results of full-scale iron discharge showed that aqueous concentrations in drainage water did not vary significantly relative to variations in drainage flow rate, which was confirmed by 12 years of field monitoring data. In addition, the comparison of pre- and post-cover simulations with measured lime consumption during ARD treatment, and mass-balance/dilution calculations for the entire pile, indicates that roughly 15–20% of total precipitation passes through the cover.

Activated carbon adsorption has been considered the most efficient technology toward VOC removal. The waste biomass as alternates solved the problems of high price and nonrenewable of traditional raw materials. The waste Zanthoxylum bungeanum branches were firstly selected as raw materials to prepare activated carbons. Interestingly, the pore structure and surface chemistry can be successfully controlled by adjusting the heating rate. The hierarchical porous carbons exhibited great potential for toluene adsorption. The micro-mesopore structure possessed unique spatial effect; micropores played a dominant role in adsorption process, especially narrow micropores (pore size ≤ 1.0 nm) emerged stronger adsorptive force toward toluene molecules due to overlapping attractive forces from neighboring pore walls. And mesopores not only displayed excellent transport diffusion but also provided adsorption sites. Additionally, the high graphitization degree enhanced the interaction between graphene layer equipped electron-rich regions and π-electrons on the aromatic ring by the π-π conjugated effect. The hydroxyl and carbonyl functional groups served as chemisorption sites and led to higher adsorption amounts. Fortunately, the regeneration can be achieved by thermal treatment at the low temperature (≤ 150 °C) or even gas purging at room temperature (20 °C), which avoided an explosion accident in the process of high-temperature regeneration.

This paper employs a recently constructed consumption-based carbon dioxide emissions data in which emissions computations are made based on fossil fuel usage domestically, in addition to emissions emanating from imports minus exports. We contrast this measure with the commonly measured territory-based carbon dioxide emissions data and examine how trade performance (split into imports, exports, and total trade) impacts these two measures of carbon dioxide. We focus on 22 sub-Saharan African countries over the period 1995–2014. Employing the system generalized method of moments, we find trade to generally have positive effect on emissions. The results are consistent across the different measures of trade and carbon dioxide emissions. The results of the paper allow us to give some policy suggestions regarding carbon dioxide emissions in sub-Saharan Africa.

This work investigated the impact of a clay mineral on toxic waste. The Ivorian Anti-pollution Center discovered the toxic waste from Probo Koala boat on 21 August 2006. This boat had been used to refine oil named naphtha of cokéfaction by Trafigura firm in the sea. The process of refining consists of caustic sodium carbonate washing and produced toxic waste. These toxic wastes have been unloading in 13 zones of the Abidjan district: Akouédo, Abobo, Abobo Alépé road (Djibi village), civile prison road (MACA), industrial zone of Koumassi, Port-Bouët - Vridi CAP Logistic (Rue Saint-Sylvestre)… This situation caused a socio-political crisis and generated the death of many people. To solve this problem, one first part has been excavated and sent to France to be incinerated. A second part is used to be a biopile for bioremediation. After these two processes, the rest of toxic waste remained in the place where they have been unloaded. The analyses of these toxic wastes show that polycyclic aromatic hydrocarbons (PAHs), oxygenated polycyclic aromatic compounds (O-PACs), volatile aromatic compound (VAC), mercaptan and sulfur molecules, and also heavy metal and organometallic are the principal polluters of these contaminated soils. From a mineralogical viewpoint, the tropical climate soils of Ivory Coast in general and district of Abidjan in particular constituted of about 50% of kaolinite, 30 to 40% of smectite, and 10 to 20% of illite (OSTROM 1993). In this study, we want to show the impact of this local clay on toxic waste.