A new adsorption material from fly ash (FA) was prepared by a two-step surface modification process, which showed higher ability for the removal of both inorganic and organic cationic pollutants from aqueous solution, i.e., Cu²⁺ and methylene blue (MB). Firstly, FA was modified by hydrothermal method in alkaline solution at 80 °C (FA80) to have a larger BET surface area. Afterwards, FA80 was further modified by sodium dodecyl benzene sulfonate (SDBS), of which a layer of anionic functional groups were grafted on the surface. The adsorption performance of SDBS@FA80 for removal of Cu²⁺ and MB were detailedly investigated. The results showed that SDBS@FA80 presented the optimal adsorption capacity at pH 7.0. Additionally, the maximum adsorption capacities of SDBS@FA80 for the removal Cu²⁺ and MB were up to 227.3 and 50.76 mg g⁻¹ at 70 °C, respectively, as well as being about three times higher than that of FA. When the initial concentrations of Cu²⁺ and MB were lower than those of 20 and 10 ppm, their removal efficiencies were as high as 99.75 and 96.4%, respectively. The pseudo-second-order model was well applied to describe the adsorption kinetics, indicating that chemisorption was taking place. Furthermore, a plausible mechanism is proposed by XPS studies, where the high adsorption capacity is mainly contributed to the electrostatic attraction and π–π stacking interaction between the cationic Cu²⁺/MB and anionic functional groups of SDBS. Due to the low-cost and high adsorption capacity, SDBS@FA80 is regarded as a promising adsorbent for the removal of cationic pollutants.

We studied the effect of electron competition on chromate (Cr(VI)) reduction in a methane (CH₄)-based membrane biofilm reactor (MBfR), since the reduction rate was usually limited by electron supply. A low surface loading of SO₄²⁻ promoted Cr(VI) reduction. The Cr(VI) removal percentage increased from 60 to 70% when the SO₄²⁻ loading increased from 0 to 4.7 mg SO₄²⁻/m²-d. After the SO₄²⁻ loading decreased back to zero, the Cr(VI) removal further increased to 90%, suggesting that some sulfate-reducing bacteria (SRB) stayed in the reactor to reduce Cr(VI). However, a high surface loading of SO₄²⁻ (26.6 mg SO₄²⁻/m²-d) significantly slowed down the Cr(VI) reduction to 40% removal, which was probably due to competition between Cr(VI) and SO₄²⁻ reduction. Similarly, when 0.5 mg/L of Se(VI) was introduced into the MBfR, Cr(VI) removal percentage slightly decreased to 60% and then increased to 80% when input Se(VI) was removed again. The microbial community strongly depended on the loadings of Cr(VI) and SO₄²⁻. In the sulfate effect experiment, three genera were dominant. Based on the correlation between the abundances of the three genera and the loadings of Cr(VI) and SO₄²⁻, we conclude that Methylocystis, a type II methanotroph, reduced both Cr(VI) and sulfate, Meiothermus only reduced Cr(VI), and Ferruginibacter only reduced SO₄²⁻.

Furanic and phenolic compounds are problematic compounds resulting from the pretreatment of lignocellulosic biomass for biofuel production. Microbial electrolysis cell (MEC) is a promising technology to convert furanic and phenolic compounds to renewable H₂. The objective of the research presented here was to elucidate the processes and electron equivalents flow during the conversion of two furanic (furfural, FF; 5-hydroxymethyl furfural, HMF) and three phenolic (syringic acid, SA; vanillic acid, VA; 4-hydroxybenzoic acid, HBA) compounds in the MEC bioanode. Cyclic voltammograms of the bioanode demonstrated that purely electrochemical reactions in the biofilm attached to the electrode were negligible. Instead, microbial reactions related to the biotransformation of the five parent compounds (i.e., fermentation followed by exoelectrogenesis) were the primary processes resulting in the electron equivalents flow in the MEC bioanode. A mass-based framework of substrate utilization and electron flow was developed to quantify the distribution of the electron equivalents among the bioanode processes, including biomass growth for each of the five parent compounds. Using input parameters of anode efficiency and biomass observed yield coefficients, it was estimated that more than 50% of the SA, FF, and HMF electron equivalents were converted to current. In contrast, only 12 and 9% of VA and HBA electron equivalents, respectively, resulted in current production, while 76 and 79% remained as fermentation end products not further utilized in exoelectrogenesis. For all five compounds, it was estimated that 10% of the initially added electron equivalents were used for fermentative biomass synthesis, while 2 to 13% were used for exoelectrogenic biomass synthesis. The proposed mass-based framework provides a foundation for the simulation of bioanode processes to guide the optimization of MECs converting biomass-derived waste streams to renewable H₂.

In this study, sewage sludge-derived activated carbon (SDAC) was synthesized, characterized, and tested for its potential as an adsorbent of methyl tert-butyl ether (MTBE). The SDAC was produced by activating the sludge with zinc chloride and subsequently subjected to various ranges of pyrolytic temperatures. It was then characterized using SEM/EDX, BET, and TGA. The SEM-EDX analyses showed that impurities like Fe, Al, Mg, Mn, Ca, and Na of the raw sludge were removed by the higher pyrolytic temperature and acid-washing procedures. TGA showed the thermal stability of the produced material. Results of the BET revealed a significant increase in surface area of the sludge from 1.5 m²/g to 385 m²/g after acid washing. The MTBE removal efficiency of 70% was achieved after 60 min with 2 g/L of SDAC at pH 6, and initial MTBE concentration of 1 ppm. The adsorption kinetics of SDAC fitted into pseudo-second-order reactions. This work demonstrated a beneficial use of a bio-waste material (sewage sludge) in water treatment technologies.

This study is concerned with the impact factors of electric carbon productivity change in China. Some influencing factors are identified by examining the time series decomposition of electric carbon productivity based on data from 2003 to 2015, where the usual Logarithmic Mean Divisia Index (LMDI) method is used but with the regional dimension taken into consideration. Moreover, this study analyzes the driving factors of electric carbon productivity change from the perspective of production and consumption in China’s power industry, where the influences of power transfers among provinces, imports and exports, and transmission losses are considered. Based on the decomposition analysis of existing data in 30 provinces (including province-level municipalities), from the perspective of production, regional actual electric carbon productivity, and per capita GDP are the main influencing forces for the growth of electric carbon productivity, and the reciprocal of per capita electric carbon emissions, energy intensity, and energy emission intensity play dominate roles in the decline of electric carbon productivity. From the perspective of consumption, the main impact factors to improve electric carbon productivity are power transfers among provinces, imports and exports, the reciprocal of emission intensity of power consumption and regional electric carbon productivity, and the impact of energy consumption on thermal power generation, the proportion of thermal power to total electricity generation, and the effect of transmission losses. Finally, several conclusions are drawn that might be meaningful for the Chinese government to improve China’s electric carbon productivity.

Monitoring exposure to xenobiotics by biomarker analyses, such as a micronucleus assay, is extremely important for the precocious detection and prevention of diseases, such as oral cancer. The aim of this study was to evaluate genotoxic effects in rural workers who were exposed to cigarette smoke and/or pesticides and to identify possible classification patterns in the exposure groups. The sample included 120 participants of both sexes aged between 18 and 39, who were divided into the following four groups: control group (CG), smoking group (SG), pesticide group (PG), and smoking + pesticide group (SPG). Their oral mucosa cells were stained with Giemsa for cytogenetic analysis. The total numbers of nuclear abnormalities (CG = 27.16 ± 14.32, SG = 118.23 ± 74.78, PG = 184.23 ± 52.31, and SPG = 191.53 ± 66.94) and micronuclei (CG = 1.46 ± 1.40, SG = 12.20 ± 10.79, PG = 21.60 ± 8.24, and SPG = 20.26 ± 12.76) were higher (p < 0.05) in the three exposed groups compared to the GC. In this study, we considered several different classification algorithms (the artificial neural network, K-nearest neighbors, support vector machine, and optimum path forest). All of the algorithms displayed good classification (accuracy > 80%) when using dataset2 (without the redundant exposure type SPG). It is clear that the data form a robust pattern and that classifiers could be successfully trained on small datasets from the exposure groups. In conclusion, exposing agricultural workers to pesticides and/or tobacco had genotoxic potential, but concomitant exposure to xenobiotics did not lead to additive or potentiating effects.

This study examines the relationship between energy consumption and economic growth based on three models in China covering the period of 1982–2015. From the Ng-Perron (NP) and Zivot-Andrews (ZA) unit root test, each variable has no unit root in the first difference. Based on Johansen multivariable co-integration test and autoregressive distributed lag (ARDL) bounds test, the co-integrating relationship existed between selected variables. Moreover, dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and ARDL estimates are used to estimate the coefficients of each variable, which presents that any increasing of each kinds of energy sources can increase China’s economic growth in the long term. Additionally, the vector error correction model (VECM) Granger causality test based on three models is investigated. Some implications based on the empirical results are given.

The success of bioaugmentation processes for the remediation of groundwater contamination relies on effective transport of the injected microorganisms in a subsurface environment. Biosurfactants potentially affect bacterial attachment and transport behavior in porous media. Although saponins as biosurfactants are abundant in nature, their influence on bacterial transport in groundwater systems remains unknown. In this research, tank visual-transport experiments, breakthrough curve monitoring, and surface property measurement were performed to evaluate the effects of saponins on the transport of Pseudomonas migulae AN-1 cells, which were used as a model bacterium in saturated sand. Results show that the 0.1% saponins could effectively facilitated the AN-1 secondary transport and the addition of saponins decreased the hydrophobicity of AN-1 and sand. The role of the promotion of saponins was more dominant than that of the inhibition of ions on AN-1 transport in a saturated porous medium when ions and saponins coexisted. The interactions between AN-1 and sand grains with saponins and ions were explained in accordance with the Derjaguin–Landau–Verwey–Overbeek theory.

Hexavalent chromium is a highly toxic metal that can enter drinking water sources. Chitosan, which contains amino and hydroxyl functional groups, is considered an appropriate candidate to remove heavy metals through absorption. In this study, a novel adsorbent, magnetic nanoparticles of chitosan modified with polyhexamethylene biguanide (Ch-PHMB NPs) was synthesized and was used to successfully remove chromium from aqueous solution. Quadratic models with independent variables including pH, adsorbent dosage, time, and the initial concentration of chromium were proposed through RSM to describe the behavior of both magnetic chitosan (M-Ch) and Ch-PHMB NPs in Cr(VI) removal. Optimized models with adjusted R² values of 0.8326 and 0.74 for M-Ch and Ch-PHMB NPs were developed. Cr(VI) removal from aqueous solution by both absorbents followed pseudo-second-order kinetics. The experimental data were best fitted to the Temkin and Freundlich models for M-Ch and Ch-PHMB NPs, respectively. M-Ch and Ch-PHMB NPs can effectively remove the hexavalent chromium from aqueous solution with pH above 7. Ch-PHMB NPs have higher removal efficiency than M-Ch, removing up to 70% of Cr(VI) from aqueous solution. However, toxicity evaluation on Daphnia magna revealed that Ch-PHMB NPs was more toxic than M-Ch nanoparticles.

Aquatic organisms of inland waters are often subjected to a combination of stressors. Yet, few experiments assess mixed stress effects beyond a select group of standard model organisms. We studied the joint toxicity of reference toxicants and increased temperature on the turquoise killifish, Nothobranchius furzeri, a promising model for ecotoxicological research due to the species’ short life cycle and the production of drought-resistant eggs. The acute sensitivity of the larval stage (2dph) to three compounds (cadmium, 3,4-dichloroaniline and chlorpyrifos) was tested in combination with a temperature increase of 4 °C, mimicking global warming. Dose-response relationships were used to calculate 96h-LC₅₀ of 0.28 mg/L (24 °C) and 0.39 mg/L (28 °C) for cadmium, 96h-LC₅₀ of 9.75 mg/L (24 °C) and 6.61 mg/L (28 °C) for 3,4-dichloroaniline and 96h-LC₅₀ of 15.4 μg/L (24 °C) and 14.2 μg/L (28 °C) for chlorpyrifos. After 24 h of exposure, the toxicity of all tested compounds was exacerbated under increased temperature. Furthermore, the interaction effect of cadmium and temperature could be predicted by the stress addition model (SAM). This suggests the applicability of the model for fish and at the same time indicates that the model could be suitable to predict effects of temperature-toxicant interactions.