Resupply, diffusion, and bioavailability of Hg in paddy soil-water environment with flood-drain-reflood and straw amendment.

Mercury (Hg) poses a significant risk in paddy fields, particularly when it is converted to methylmercury (MeHg) and accumulates in rice. However, the bioavailability and resupply kinetics of Hg in the paddy soil-water environment are not well understood. In this study, the diffusive gradients in thin films (DGT) and the 'DGT-induced fluxes in sediments' model (DIFS) were first adopted to investigate the Hg resupply kinetics, diffusion fluxes and bioavailability in a paddy environment subjected to flood-drain-reflood treatment and straw amendment. Our results show that although the straw amendment limited the bioavailability of Hg (38.2%-47.9% lower than control) in porewater by decreasing its resupply capacity, especially with smaller straw particles, the net production of MeHg in paddy fields was significantly increased after straw amendment (73.5%-77.9% higher than control). The results of microbial sequencing indicate that enhanced methylators (e.g., family Geobacter) and non-Hg methylators (e.g., Methanosarcinaceae) played a crucial role in MeHg production following straw amendment. Moreover, Hg-containing paddy soils generally tend to release Hg into the overlying water, while drain-reflood treatment changes the direction of Hg diffusion fluxes in the paddy soil-water interface. The drainage-reflooded treatment decreases the Hg reactive and resupply capacity of the paddy soil, thereby hindering the release of Hg from soil into overlying water during the early stages of reflooding. Overall, this study provides novel insights into the behavior of Hg in paddy soil-water surface microlayers.

Adsorption of lead ions by activated carbon doped sodium alginate/sodium polyacrylate hydrogel beads and their in-situ recycle as sustainable photocatalysts.

In this study, sodium alginate (SA), sodium polyacrylate (PAAS) and powdered activated carbon (PAC) were cross-linked by calcium ions [(Ca(II)] to form SA/PAAS/PAC (SPP) hydrogel beads. The hydrogel-lead sulfide (SPP-PbS) nanocomposites were successfully synthesized by in-situ vulcanization after the lead ions [(Pb(II)] adsorption. SPP showed an optimal swelling ratio (600% at the pH value of 5.0) and superior thermal stability (206 °C of heat-resistance index). The adsorption data of Pb(II) was compatible with the Langmuir model, and the maximum adsorption capacity of SPP was 391.65 mg/g after optimizing the mass ratio of SA to PAAS (3:1). The addition of PAC not only enhanced the adsorption capacity and stability, but also promoted photodegradation. The significant dispersive capacity of PAC and PAAS resulted in PbS nanoparticles with particle sizes of around 20 nm. SPP-PbS showed good photocatalysis and reusability. The degradation rate of RhB (200 mL, 10 mg/L) was 94% within 2 h and maintained above 80% after 5 cycles. The treatment efficiency of SPP was more than 80% in actual surface water. The results of quenching experiments and electron spin resonance (ESR) experiments revealed that the superoxide radicals (O2-) and holes (h+) were the main active species in the photocatalytic process.

A spectral learning path for simultaneous multi-parameter detection of water quality.

Water quality parameters (WQP) are the most intuitive indicators of the environmental quality of water body. Due to the complexity and variability of the chemical environment of water body, simple and rapid detection of multiple parameters of water quality becomes a difficult task. In this paper, spectral images (named SPIs) and deep learning (DL) techniques were combined to construct an intelligent method for WQP detection. A novel spectroscopic instrument was used to obtain SPIs, which were converted into feature images of water chemistry and then combined with deep convolutional neural networks (CNNs) to train models and predict WQP. The results showed that the method of combining SPIs and DL has high accuracy and stability, and good prediction results with average relative error of each parameter (anions and cations, TOC, TP, TN, NO3--N, NH3-N) at 1.3%, coefficient of determination (R2) of 0.996, root mean square error (RMSE) of 0.1, residual prediction deviation (RPD) of 16.2, and mean absolute error (MAE) of 0.067. The method can achieve rapid and accurate detection of high-dimensional water quality multi-parameters, and has the advantages of simple pre-processing and low cost. It can be applied not only to the intelligent detection of environmental waters, but also has the potential to be applied in chemical, biological and medical fields.

Enhanced removal of diclofenac via coupling Pd catalytic and microbial processes in a H2-based membrane biofilm reactor: Performance, mechanism and biofilm microbial ecology.

Diclofenac (DCF) is a most widely used anti-inflammatory drug, which has attracted worldwide attention given its low biodegradability and ecological damage, especially toxic effects on mammals including humans. In this study, a H2-based membrane biofilm reactor (H2-MBfR) was constructed with well-dispersed Pd nanoparticles generated in situ. The Pd-MBfR was applied for catalytic reductive dechlorination of DCF. In batch tests, DCF concentration had significantly effect on the rate and extent DCF removal, and NO3- had negative impact on DCF reductive dechlorination. Over 67% removal of 0.5 mg/L DCF and 99% removal of 10 mg/L NO3--N were achieved in 90 min, and the highest removal of 97% was obtained at 0.5 mg/L DCF in the absence of NO3-. Over 78 days of continuous operation, the highest steady-state removal flux of DCF was 0.0097 g/m2/d. LC-MS analysis indicated that the major product was 2-anilinephenylacetic acid (APA). Dechlorination was the main removal process of DCF mainly owing to the catalytic reduction by PdNPs, microbial reduction, and the synergistic reduction of microbial and PdNPs catalysis using direct delivery of H2. Moreover, DCF reductive Dechlorination shifted the microbial community in the biofilms and Sporomusa was responsible for DCF degradation. In summary, this work expands a remarkable feasibility of sustainable catalytic removal of DCF.

Long-term effects of Cu(II) on denitrification in hydrogen-based membrane biofilm reactor: Performance, extracellular polymeric substances and microbial communities.

Divalent copper (Cu(II)) frequently coexists with nitrate (NO3-) in industrial wastewater and the effect of Cu(II) on the autotrophic denitrification system using H2 as the electron donor remains unknown. In this study, the hydrogen-based membrane biofilm reactor (H2-MBfR) was operated continuously over 150 days to explore the effect of Cu(II) on the performance of autotrophic denitrification system and understand the key roles of EPS and microbial community. More than 95% of 20 mg-N/L NO3- was removed at 1-5 mg/L Cu(II), and the removal rate of NO3--N was stabilized to 82% at 10 mg/L Cu(II) after a short period, while NH4+ and NO2- in effluent were hardly detected, indicated that high concentration of Cu(II) did not permanently inhibit the denitrification performance in H2-MBfR. Colorimetric determination showed that Cu(II) stimulated the secretion of EPS, in which the protein (PN) content was much higher than polysaccharide (PS). The PN/PS ratios increased from 0.93 to 1.99, and the PN was more sensitive to copper invasion. The results of three-dimensional excitation-emission matrix illustrated that tryptophan was the main component of EPS chelating Cu(II) to reduce toxicity. The results of Fourier-transform infrared demonstrated that hydroxyl, carboxyl, and protein amide groups bound and reduced Cu(II). Furthermore, Cu(II) was effectively removed (>80%), and the results of distribution and morphology analysis of Cu(II) show that the electron-dense deposits of monovalent copper (Cu(I)) were found in EPS and biofilms and the reduction of Cu(II) to Cu(I) was an obvious self-defense reaction of biofilm to copper stress. The microbial richness and diversity decreased with the long-term exposure to Cu(II), while the relative abundance of denitrifiers Azospira and Dechloromonas increased. This study provides a scientific basis for the optimal design of treatment system for removal of nitrate and recovery of heavy metals simultaneously.

Carboxymethyl cellulose stabilized ferrous sulfide@extracellular polymeric substance for Cr(VI) removal: Characterization, performance, and mechanism.

Iron-based materials, especially ferrous sulfide (FeS), effectively remediate chromium pollution. However, the agglomeration of FeS reduces its reactivity to chromium. Herein, carboxymethyl cellulose stabilized ferrous sulfide@extracellular polymeric substance (CMC-FeS@EPS) was developed to remove hexavalent chromium (Cr(VI)) from water. CMC-FeS@EPS (98.00%) exhibited excellent removal efficiency of 40 mg/L Cr(VI) than those of FeS (57.35%) and CMC-FeS (68.60%). CMC-FeS@EPS showed good removal efficiency of Cr(VI) in wide pH range (from 4 to 9) and the co-existence of ions. FTIR and XPS results demonstrated that EPS functional group accelerated the process of adsorption and precipitation. Electrochemical results showed that CMC-FeS@EPS transferred electrons to Cr(VI) faster than CMC-FeS. In total, this study started from a new idea of using EPS to improve the performance of CMC-FeS, and provided a simple and effective way to remediate chromium pollution without secondary pollution.

Image learning to accurately identify complex mixture components.

The study of complex mixtures is very important for exploring the evolution of natural phenomena, but the complexity of the mixtures greatly increases the difficulty of material information extraction. Image perception-based machine-learning techniques have the ability to cope with this problem in a data-driven way. Herein, we report a 2D-spectral imaging method to collect matter information from mixture components, and the obtained feature images can be easily provided to deep convolutional neural networks (CNNs) for establishing a spectral network. The results demonstrated that a single CNN trained end-to-end from the proposed images can directly accomplish synchronous measurement of multi-component samples using only raw pixels as inputs. Our strategy has some innate advantages, such as fast data acquisition, low cost, and simple chemical treatment, suggesting that it can be extensively applied in many fields, including environmental science, biology, medicine, and chemistry.

Do perfluoroalkyl substances aggravate the occurrence of obesity-associated glucolipid metabolic disease?

BACKGROUND: Since 2016, more and more studies have been conducted to explore the combination of obesity and perfluoroalkyl substances (PFASs) exposure, and the results indicate that PFASs may be connected with the occurrence of obesity-associated glucolipid metabolic disease (GLMD). OBJECTIVES: This article summarizes the epidemiological studies on PFASs and obesity-related GLMD, as well as relevant experimental evidence. RESULTS: (i) Both obesity and PFASs exposure can cause disorder of glucose and lipid metabolism (GLM). (ii) Obesity is a pivotal factor in the high incidence of GLMD induce by PFASs. (iii) PFASs are aggravating the occurrence of obesity-associated GLMD [e.g., diabetes, cardiovascular disease (CVD), and liver disease]. CONCLUSION: The paper fills the gaps among environmental chemistry/epidemiology/toxicology area research. More importantly, PFASs should be taken into account to explain the high-prevalence of obesity-related GLMD. FUTURE DIRECTION: Three research programs are proposed to explore the synergistic mechanism of PFASs and obesity. In addition, three suggestions are recommended to solve the harm of PFASs pollutants to human beings.

Insight the roles of loosely-bound and tightly-bound extracellular polymeric substances on Cu2+, Zn2+ and Pb2+ biosorption process with Desulfovibrio vulgaris.

The aim of this study is to explore the fate and mechanism of metal cations of biosorption in the Desulfovibrio vulgaris system (including bacterial cells and secreted loosely-bound extracellular polymeric substances (LB-EPS) and tightly-bound extracellular polymeric substances (TB-EPS)). The relative contribution of EPS (TB-EPS and LB-EPS) to the adsorption of three metal cations is much greater than that of bacterial cells, and the adsorption capacity of Pb2+ on EPS (TB-EPS and LB-EPS) is much greater than that of Cu2+ and Zn2+ (Pb2+ > Cu2+ > Zn2+). The order of absorption capacity was as follows: LB-EPS > TB-EPS > bacterial cells, the adsorption contribution of EPS (including TB-EPS and LB-EPS) to Cu2+, Zn2+ and Pb2+ accounted for total adsorption capacity was 82%, 83% and 86%, respectively. It was suggested that LB-EPS was the first reaction barrier of immobilization metal cations before metal cations was able to pass through EPS and react with cells. The adsorption process was dominated by complexation and electrostatic interaction. The three-dimensional excitation-emission matrix (3D-EEM) identified two main fluorescence peaks of the aromatic and tryptophan protein-like substances in EPS. According to the synchronous fluorescence spectra, the tryptophan protein-like substances were gradually quenched with increased metal cations concentrations, which the quencher mechanism is dynamic quenching. The findings of this work are significant to reveal the fate of Cu2+, Zn2+ and Pb2+ during its sorption process onto Desulfovibrio vulgaris, and provide useful information of the interaction between Desulfovibrio vulgaris and its secreted EPS with metal cations.