The research aims to develop artificial intelligence (AI)-based model to predict the adsorptive removal of 2-chlorophenol (CP) in aqueous solution by coconut shell carbon (CSC) using four operational variables (pH of solution, adsorbate concentration, temperature, and contact time), and to investigate their effects on the adsorption process. Accordingly, based on a factorial design, 640 batch experiments were conducted. Nonlinearities in experimental data were checked using Brock–Dechert–Scheimkman (BDS) statistics. Five nonlinear models were constructed to predict the adsorptive removal of CP in aqueous solution by CSC using four variables as input. Performances of the constructed models were evaluated and compared using statistical criteria. BDS statistics revealed strong nonlinearity in experimental data. Performance of all the models constructed here was satisfactory. Radial basis function network (RBFN) and multilayer perceptron network (MLPN) models performed better than generalized regression neural network, support vector machines, and gene expression programming models. Sensitivity analysis revealed that the contact time had highest effect on adsorption followed by the solution pH, temperature, and CP concentration. The study concluded that all the models constructed here were capable of capturing the nonlinearity in data. A better generalization and predictive performance of RBFN and MLPN models suggested that these can be used to predict the adsorption of CP in aqueous solution using CSC.

The lack of water is the most serious threat to humanity that leads to more efficient water and sewage treatment. Currently, many scientists are looking for new coagulants, flocculants and physicochemical methods allowing for sufficient removal of pollutants from water. The presence of various types of pigments, including chromium (III) oxide, poses the major problem. Even small amounts of these substances inhibit life processes in water. In this paper, the stability of Cr₂O₃ suspension in the absence and the presence of polyacrylic acid (PAA) was determined. To explain the changes in the system stability, the adsorption and electrokinetic measurements were performed. The chromium (III) oxide suspension not containing PAA is the most stable at pH = 3. Under these conditions, each positively charged solid particle is surrounded by a negatively charged diffusion layer which protects from particle collision and aggregates formation (electrostatic stabilization). In turn, the Cr₂O₃ suspension containing the PAA is most unstable also at pH = 3. In this case, the polymer causes destabilization of the colloidal suspension, which results from charge neutralization of solid particles by adsorbed PAA.

Although generally misunderstood, the p value is the probability of the test results or more extreme results given H₀ is true: it is not the probability of H₀ being true given the results. To obtain directly useful insight about H₀, the positive predictive value (PPV) and the negative predictive value (NPV) may be useful extensions of null hypothesis significance testing (NHST). They provide information about the probability of statistically significant and non-significant test outcomes being true based on an a priori defined biologically meaningful effect size. The present study explores the utility of PPV and NPV in an ecotoxicological context by using the frequently applied Daphnia magna reproduction test (OECD guideline 211) and the chemical stressor lindane as a model system. The results indicate that especially the NPV deviates meaningfully between a test design strictly following the guideline and an experimental procedure controlling for α and β at the level of 0.05. Consequently, PPV and NPV may be useful supplements to NHST that inform the researcher about the level of confidence warranted by both statistically significant and non-significant test results. This approach also reinforces the value of considering α, β, and a biologically meaningful effect size a priori.

Samples of gas- and particle-phase polycyclic aromatic hydrocarbons (PAHs) were collected at three sampling stations (Xiaomai Island, Laohutan, and Zhangzi Island) in the north Yellow Sea, China during November 2008 and September 2009 to study their atmospheric transport potential and the gas/particle distributions. The composition of PAHs was dominated by gaseous compounds. The percentages of the particle-phase PAHs to the total concentrations were found to be higher during the heating period than the non-heating period. The ratios of naphthalene and acenaphthene to phenanthrene, chrysene and dibenzo(a,h)anthracene showed an increasing trend from Xiaomai Island to Zhangzi Island, which can be called as the local atmospheric distillation of PAHs. Gas/particle partitioning coefficients (K ₚ) and their relationship with the sub-cooled liquid vapor pressures (pºL) of PAHs were investigated. The regressions of logK ₚ versus logpºL gave significant correlations for all samples of the three sites with r ² values in the range 0.56–0.66 (p < 0.01). Both Junge–Pankow adsorption model and octanol–air partition coefficient absorption model tended to underestimate the sorption for most PAHs, but the absorption model appeared to be more suitable for predicting the particle fraction of PAHs than the Junge–Pankow model.

INTRODUCTION: A biosorbent was developed by simple dried Agaricus bisporus (SDAB) and effectively used for the biosorption of cationic dyes, Crystal Violet and Brilliant Green. MATERIALS AND METHODS: For the evaluation of the biosorbent system, all the batch equilibrium parameters like pH, biomass dose, contact time, and temperature were optimized to determine the decolorization efficiency of the biosorbent. The maximum yields of dye removal were achieved at pH 4.0 for Crystal Violet (CV) and pH 5.0 for Brilliant Green (BG), which are closer to their natural pH also. RESULT AND DISCUSSION: Equilibrium was established at 60 and 40 min for CV and BG, respectively. Pseudo first-order, pseudo second-order, and intraparticle-diffusion kinetic models were studied at different temperatures. Isotherm models such as Freundlich, Langmuir, and Dubinin–Radushkevich were also studied. Biosorption processes were successfully described by Langmuir isotherm model and the pseudo second-order kinetic model. CONCLUSIONS: The biosorption capacity of A. bisporus over CV and BG were found as 21.74 and 12.16 mg gm⁻¹. Thermodynamic parameters indicated that the CV and BG dye adsorption onto A. bisporus is spontaneous and exothermic in the single and ternary systems. Scanning electron microscopy, X-ray diffraction, and Fourier transform infrared spectroscopy were used for the surface morphology, crystalline structure of biosorbent, and dye–biosorbent interaction, respectively. This analysis of the biosorption data confirmed that these biosorption processes are ecofriendly and economical. Thus, this biomass system may be useful for the removal of contaminating cationic dyes.

Arsenic contamination of groundwater has been called the largest mass poisoning calamity in human history and creates severe health problems. The effective adsorbents are imperative in response to the widespread removal of toxic arsenic exposure through drinking water. Evaluation of arsenic(V) removal from water by weak-base anion exchange adsorbents was studied in this paper, aiming at the determination of the effects of pH, competing anions, and feed flow rates to improvement on remediation. Two types of weak-base adsorbents were used to evaluate arsenic(V) removal efficiency both in batch and column approaches. Anion selectivity was determined by both adsorbents in batch method as equilibrium As(V) adsorption capacities. Column studies were performed in fixed-bed experiments using both adsorbent packed columns, and kinetic performance was dependent on the feed flow rate and competing anions. The weak-base adsorbents clarified that these are selective to arsenic(V) over competition of chloride, nitrate, and sulfate anions. The solution pH played an important role in arsenic(V) removal, and a higher pH can cause lower adsorption capacities. A low concentration level of arsenic(V) was also removed by these adsorbents even at a high flow rate of 250–350 h⁻¹. Adsorbed arsenic(V) was quantitatively eluted with 1 M HCl acid and regenerated into hydrochloride form simultaneously for the next adsorption operation after rinsing with water. The weak-base anion exchange adsorbents are to be an effective means to remove arsenic(V) from drinking water. The fast adsorption rate and the excellent adsorption capacity in the neutral pH range will render this removal technique attractive in practical use in chemical industry.

The aims of this paper were to quantify the heavy metal concentrations in street dust of small towns in Shanghai suburban area compared with those in urban area, and examine their seasonal and spatial variations, and to assess their risks to water environment and local populations. Street dust samples were collected from three small towns and urban area in Shanghai in different seasons. Levels of heavy metals were determined by atomic adsorption spectrophotometer analyzer. The method of potential ecological risk index and the health risk assessment model were used to evaluate the potential risks to water bodies and local residents, respectively. The mean metal concentrations in street dust of small towns were far above soil background values but still lower than those in the urban area. No significant seasonal change was observed except for Cr, Ni, and Zn concentrations. Higher metal concentrations tended to be located in central area of towns and township roads. The integrated metal contamination was high and posed a strong potential ecological risk. Children had greater health risk than adults. The carcinogenic risk probabilities were under the acceptable level. The hazard index values to children were close to the safe level. Street dust from the studied area has been contaminated by heavy metals. The contamination of these elements is related more to the pollution source than seasonal change. The combination of the six metals may threaten the water environment and has non-cancer health risk to children, but not to adults.

Discharges of saline effluents into rivers can lead to risks for local aquatic ecosystems. A specific ecological risk assessment methodology has been developed to propose a management tool to organisations responsible for managing rivers and industrial companies producing saline effluents. This methodology involves the detailed description of the spatiotemporal system concerned, the choice of ecological targets to be preserved, and the performance of bioassays adapted to each of the compartments of the river. Following development, it was applied to an industrial effluent in eastern France. For the scenario studied, results obtained suggest a high risk for the organisms of the water column and a low risk for the organisms of the periphyton. This difference can be explained by the structure of the latter which integrate extracellular polymers secreted by the organisms of the biofilm, forming a gel with a porous structure that acts as a barrier to diffusion. The methodology formulated permitted identifying the critical points of the spatiotemporal system studied and then using them as the basis for making well-grounded proposals for management. Lastly, proposals to improve the methodology itself are made, especially concerning the integration of the sediment compartment in the version formulated initially.

Fourteen and 17 sediment samples were collected from three main rivers of Shanghai in July and November, respectively. Eight polybrominated diphenyl ether (PBDE) congeners (BDE-28, BDE-47, BDE-99, BDE-100, BDE-153, BDE-154, BDE-183, and BDE-209) were detected in these samples to clarify the pollution status in the metropolis. Instrumental analyses showed that the concentrations of ∑₈PBDEs ranged from 10.97 to 64.05 ng/g dry weight (dw), with an average value of 29.71 ng/g dw. BDE-209 was the predominant congener accounting for more than 97 % of total PBDEs, followed by BDE-47 and BDE-99. Remarkable spatial and seasonal distributions of PBDE concentrations were observed, suggesting that local sources, seasonal climates, and hydrologic conditions might be the influencing factors. Moderate correlations (r ² = 0.28–0.51, p < 0.05) were found between total organic carbon and PBDEs, which indicated that organic carbon content influenced the distributions of PBDEs in sediment of Shanghai at some extent. Hazard quotients revealed PBDEs posed no potential risk to benthic organisms in the study area at present.

A battery of biochemical and immunological biomarkers used for pollution assessment were measured for first time in the clams Venus verrucosa and Callista chione and were compared with those of the mussel Mytilus galloprovincialis, a well-established indicator organism utilized in numerous environmental monitoring programs. Clams and mussel were transplanted at a polluted and a reference site or maintained at the laboratory. Among biochemical biomarkers, acetylcholinesterase did not differ at the polluted site in all species, but there was a significant difference between the mussel and the clams, glutathione S-transferase showed a clear inhibition at the polluted site in all species and a significant difference between the two clams was also indicated, while catalase activities were increased only in V. verrucosa at the polluted site and not in mussel or the other clam. Immunological biomarkers responses were also pronounced at the polluted site. Lysozyme activity was species-dependent whereas respiratory burst activity measured as luminol-dependent chemiluminescence (CL) was site and stimulus dependent, and it was evident in M. galloprovincialis and V. verrucosa and not in C. chione. Further investigation focused on biochemical and immunological biomarkers related with the oxidative mechanisms in clams will strengthen and expand their use as bioindicators for pollution assessment.