Elevated nano-α-Fe2O3 enhances arsenic metabolism and dissolved organic carbon release of Microcystis aeruginosa under a phytate environment.

Little information is available on the effects of nano-α-Fe2O3 on arsenic (As) metabolism of algae and potential associated carbon (C) storage in As-contaminated water with dissolved organic phosphorus (DOP) as a phosphorus (P) source. In this study, Microcystis aeruginosa (M. aeruginosa) was used to investigate impacts of nano-α-Fe2O3 on cell growth and As metabolism of algae under a phytate (PA) environment as well as potential associated C storage. Results showed that nano-α-Fe2O3 had a subtle influence on algal cell growth in a PA environment. Herein, algal cell density (OD680) and chlorophyll a (Chla) were inhibited at elevated nano-α-Fe2O3 levels, which simultaneously limited the decrease of Yield. As suggested, the complexation of PA with nano-α-Fe2O3 could alleviate the negative influence on algal cell growth. Furthermore, the elevated nano-α-Fe2O3 increased As methylation in the PA environment due to higher monomethylarsenic (MMA) and dimethylarsenic (DMA) concentrations in the test media. Additionally, microcystins (MCs) in the media changed consistently with UV254, both of which were relatively lower at 10.0 mg·L-1 nano-α-Fe2O3. Enhanced As(V) methylation of algal cells was found to simultaneously reduce the release risk of As(III) and MC while increasing dissolved organic carbon (DOC) content in media, suggesting unfavorable C storage. Three-dimensional fluorescence analysis revealed that the main DOC constituent was the tryptophan-like component in aromatic proteins. Correlation analysis showed that decreases in pH and the zeta potential and an increase in Chla may lead to metabolic As improvements in M. aeruginosa. The obtained findings highlight the need for greater focus on the potential risks of DOP combined with nano-α-Fe2O3 on algal blooms as well as the biogeochemical cycling processes of As and C storage in As-contaminated water with DOP as the P source.

Enhancing arsenate metabolism in Microcystis aeruginosa and relieving risks of arsenite and microcystins by nano-Fe2O3 under dissolved organic phosphorus conditions.

Little information is available on how nano-Fe2O3 substituted iron ions as a possible iron source impacting on algal growth and arsenate (As(V)) metabolism under dissolved organic phosphorus (DOP) (D-glucose-6-phosphate (GP)) conditions. We investigated the growth of Microcystis aeruginosa and As(V) metabolism together with their metabolites in As(V) aquatic environments with nano-Fe2O3 and GP as the sole iron and P sources, respectively. Results showed that nano-Fe2O3 showed inhibitory effects on M. aeruginosa growth and microcystin (MCs) release under GP conditions in As(V) polluted water. There was little influence on As species changes in GP media under different nano-Fe2O3 concentrations except for obvious total As (TAs) removal in 100.0 mg L-1 nano-Fe2O3 levels. As(V) metabolism dominated with As(V) biotransformation in algal cells was facilitated and arsenite (As(III)) releasing risk was relieved clearly by nano-Fe2O3 under GP conditions. The dissolved organic matter (DOM) in media exhibited more fatty acid analogs containing -CO, -CH2 =CH2, and -CH functional groups with increasing nano-Fe2O3 concentrations, but the fluorescent analogs were relatively reduced especially for the fluorescent DOM dominated by aromatic protein-like tryptophan which was significantly inhibited by nano-Fe2O3. Thus, As methylation that was facilitated in M. aeruginosa by nano-Fe2O3 in GP environments also caused more organic substances to release that absorb infrared spectra while reducing the release risks of As(III) and MCs as well as protein-containing tryptophan fractions. From 1H-NMR analysis, this might be caused by the increased metabolites of aromatic compounds, organic acid/amino acid, and carbohydrates/glucose in algal cells. The findings are vital for a better understanding of nano-Fe2O3 role-playing in As bioremediation by microalgae and the subsequent potential aquatic ecological risks.

Effect of montmorillonite biochar composite amendment on thallium bioavailability in contaminated agricultural soils and its mitigated health risk.

Little information is available on the effect of clay minerals and biochar composite on the remediation and bioavailability of thallium in agricultural soils. This study thus investigated the influence of montmorillonite biochar composite (Mnt-BC) amendment on the remediation of agricultural soil contaminated artificially by Tl and its potential health risks. Herein, bok choi was cultured to estimate the efficiency of soil Mnt-BC amendments through the bioavailability of Tl of the vegetable. Results showed that Tl bioavailability was significantly reduced in Mnt-BC-amended soils, mainly ascribed to the elevated soil pH and other improved soil properties of high functional groups (-OH, -COOH), negative charges, and exchangeable cations after amendment. Specifically, the highest immobilization efficiency of Tl in soils was observed in 2.5% treated soils with 79.11%, while in plant leaves the highest reduction of Tl was estimated to be 75.1% compared to the control treatment. Hence, the amendment dosage improved the immobilization of Tl in soil and subsequently reduced Tl uptake by the vegetable. Furthermore, from target hazard quotient (THQ) estimation, Mnt-BC amendment can lower the potential health risk while consuming such cultured bok choi in Tl-contaminated soils. Considering the environmental friendliness and high efficiency of Mnt-BC, it could be used as a potential soil amendment to remediate agricultural soils contaminated by Tl.

Machine learning application in forecasting tire wear particles emission in China under different potential socioeconomic and climate scenarios with tire microplastics context.

Little information is available on different contribution of TMPs from tire wear particles (TWPs), recycled tire crumbs (RTCs) and tire repair-polished Debris (TRDs) in the environment at national scale and their potential tendency. In this study, the TWPs were predicted using machine learning method of CNN (Convolutional Neural Networks) algorithms under different potential socioeconomic and climate scenarios based on the estimation of TMPs in China. Results showed that TWPs emission exhibited the most important part of TMPs, followed by RTCs and TRDs in China. The three mentioned tire microplastics largely distributed in Chinese coastal provinces. After machine learning applied in CNN using the dataset of estimated emission of TWPs from 2008 to 2018, the express delivery volume and education funding at the current increased rate would not have significant impacts on TWPs emissions; Additionally, TWPs emissions were also sensitive to changes of economic and transportation development; Low temperature conditions would further promote TWPs emissions. Accordingly, the rational development of logistics and green economy, the equilibrium improvement of education quality, and the increase of public traffic with new energy would be helpful to mitigate TWPs emissions. The obtained findings can enhance the understanding TMPs emission at particular scale and their corresponding precise management.