Residential coal combustion is a prominent source of brown carbon (BrC) aerosols, but knowledge of their molecular structures and optical absorption were limited, which have notable used in ambient BrC source identification and radiative forcing calculation. In this study, the Fourier transform–ion cyclotron resonance mass spectrometry combined with partial least squares regression analysis as well as Fourier transform infrared spectroscopy analysis were used to insight the molecular compounds and structures of BrC from anthracite and bituminous coal combustions between traditional and improved stoves. The absorption Ångström exponents (AAE) and mass absorption efficiency (MAE) values for the BrC emitted from the combinations of bituminous were both 1.2–2.5 times lower than those of anthracite, interpreting that the BrC from the anthracite emissions had greater light-absorbing capacity. In contrast, the emission factor of light absorption (EFAbₛ) at 365 nm for the bituminous coal combusted in the traditional stove was the highest among all the tested scenarios, which revealed that the incomplete combustion of bituminous coal could emit more BrC. It was noted that primary BrC emitted from the coal combustion with traditional stoves contains higher aromaticity groups of C–C and C＝O and higher S containing organics, whereas more aliphatic groups were found in BrC using the improved stoves. N-containing (CHON and CHONS) compounds were dominated in the total molecular formula of BrC, whereas the sum of CHON and CHO groups had high double-bond equivalent (DBE) values contributed 53.5%–87.1% to the total BrC absorption. Moreover, for CHOS, the lowest of estimated molecular absorption, DBE, and DBE/C should attribute to the non-chromophoric or weak absorptive S-containing compounds. This study supplied an effective evaluation method to compare BrC emissions and their absorption for coal combustion on regional scale.

The existence of heavy metals and emerging organic contaminants in wastewater produces serious toxic residues to the environment. Developing cheap and efficient materials to remove these persistent pollutants is crucial. Iron-based materials are cost-effective and environmentally friendly catalysts, and their applications in the environmental field deserve attention. This paper critically reviewed the removal mechanisms of heavy metals and emerging organic pollutants by different influencing factors. The removal of pollutants (heavy metals and emerging organic pollutants) in a multi-component system was analyzed in detail. The mechanisms of synergism, antagonism and non-interference were discussed. This paper had a certain reference value for the research of wastewater remediation technology which could simultaneously remove various pollutants by iron-based materials.

Aquaculture ecosystem is a hot-spot for antibiotic resistance genes (ARGs). Rice-crayfish co-culture was considered an eco-friendly aquaculture model and has been widely adopted in China. However, it is unclear whether rice-crayfish co-culture is one of the most eco-friendly models from the perspective of antibiotic resistance profiles. In this study, we evaluated the eco-friendliness of rice-crayfish co-culture, and compared this model with other aquaculture models, from the perspectives of antibiotics and ARG patterns, based on multi-omics and antibiotic profiles. Results showed that the nutrient levels, antibiotic concentrations, dominant microbial genera and ARG patterns in the rice-crayfish co-culture model were profoundly different from the other three aquaculture models (crab only aquaculture model, crayfish only aquaculture model, and crab-crayfish co-culture models). Specifically, the rice-crayfish co-culture model has significantly lower diversity of ARGs and lower potential risks of ARGs when compared to the other aquaculture models. Nutrient and antibiotic concentrations were the important environmental factors for shaping ARG patterns, but compared with environmental factors, the effects of mobile genes and bacteria community on the proliferation and transmission of ARGs were stronger. This study has deepened our understanding of ARGs in freshwater aquaculture ecosystem, and suggested that rice-crayfish co-culture model is a relatively eco-friendly aquaculture model when compared with the other aquaculture models.

Selenium is an indispensable trace element for humans and other organisms; however, excessive selenium in water can jeopardize the aquatic environment. Investigations on the biogeochemical cycle of selenium have shown that anthropogenic activities such as mining, refinery, and coal combustion mainly contribute to aquatic selenium pollution, imposing tremendous risks on ecosystems and human beings. Various technologies thus have been developed recently to treat selenium contaminated water to reduce its environmental impacts. This work provides a critical review on the applications, characteristics, and latest developments of current treatment technologies for selenium polluted water. It first outlines the present status of the characteristics, sources, and toxicity of selenium in water. Selenium treatment technologies are then classified into three categories: 1) physicochemical separation including membrane filtration, adsorption, coagulation/precipitation, 2) redox decontamination including chemical reduction and catalysis, and 3) biological transformation including microbial treatment and constructed wetland. Details of these methods including their overall efficiencies, applicability, advantages and drawbacks, and latest developments are systematically analyzed and compared. Although all these methods are promising in treating selenium in water, further studies are still needed to develop sustainable strategies based on existing and new technologies. Perspectives on future research directions are laid out at the end.

The link between zinc exposure and glucose metabolism or the development of type 2 diabetes (T2D) is controversial, and underlying mechanisms are unclear. This study aimed to explore the associations of zinc exposure with glucose-insulin homeostasis traits and the long-term effects of zinc on the development of T2D, and further to estimate the potential roles of inflammation and oxidative damage in such relationships. We investigated 3890 urban adults from the Wuhan-Zhuhai cohort, and followed up every three years. Mixed linear model was applied to estimate dose-response associations between urinary zinc and glycemia traits [fasting plasma insulin (FPI), fasting plasma glucose (FPG), insulin resistance (homeostasis model assessment of insulin resistance, HOMA-IR), and β-cell dysfunction (homeostasis model assessment of β-cell function, HOMA-B)], as well as zinc and biomarkers for systemic inflammation (C-reactive protein) and oxidative damage (8-isoprostane and 8-hydroxy-2′-deoxyguanosine). Logistic regression model and Cox regression model were conducted to evaluate the relationships between urinary zinc and prevalence and incidence of T2D, respectively. We further performed mediation analysis to assess the roles of inflammation and oxidative damage biomarkers in above associations. At baseline, we observed significant dose-response relationships of elevated urinary zinc with increased FPI, FPG, HOMA-IR, and T2D prevalence and decreased HOMA-B, and such associations could be strengthened by increased C-reactive protein, 8-isoprostane, and 8-hydroxy-2′-deoxyguanosine. Elevated C-reactive protein significantly mediated 9.09% and 17.67% of the zinc-related FPG and HOMA-IR increments, respectively. In longitudinal analysis, a significantly positive association between urinary zinc and T2D incidence was observed among subjects with persistent high urinary zinc levels when compared with those with persistent low zinc levels. Our results suggested that high levels of zinc exposure adversely affected on glucose-insulin homeostasis and further contributed to increased risk of T2D cross-sectionally and longitudinally. Moreover, inflammatory response might play an important role in zinc-related glucose metabolic disorder.

The decay of algal biomass and aquatic plants in freshwater lakes leads to the overproduction of autochthonous organic matter (OM) and the exhaustion of dissolved oxygen, impacting the microbial community and subsequent biodegradation of emerging contaminants in sediment. This study explored how the microbial processing of aquatic plant- and algal-derived OM (POM and AOM) mediates 17α-ethinylestradiol (EE2) biodegradation in the anoxic sediments of Lake Taihu in China. In four months of microcosm incubations, the increased concentrations of protein-like substances in AOM and POM exhibited temporary activation on microbial metabolic enzyme activity (fluorescein diacetate hydrolase and dehydrogenase) and significantly promoted the carbon mineralization with iron reduction (P < 0.001). These in turn increased the EE2 biodegradation efficiency to 77–90 ng g⁻¹ in the anoxic sediment. However, a higher EE2 biodegradation of 109 ng g⁻¹ was achieved with the humic acid augmentation containing more quinone-like compounds, showing a weaker substrate-priming effect but accelerated redox cycling of iron and organic substrates in the later period of incubation. The microbial analysis further revealed that the quinone-like compounds in OM were more closely associated with microbial electron transfer and strengthened their interspecies syntrophic cooperation favorable to contaminant biodegradation, even though the connective members exposed to protein-like components upregulated more functional genes related to organic carbon and xenobiotics metabolism and biodegradation. Our findings will help predict the fate of estrogens in various sedimentary environments under increasing eutrophication and further climate change scenarios.

Total suspended particulate (TSP) and PM₁₀ filters collected from two ambient air monitoring stations in Port Pirie were analysed to determine the impact of a lead (Pb) smelter redevelopment on air quality parameters including total elemental concentration, Pb isotopic ratio, Pb bioaccessibility and Pb speciation. Filters from 2009 to 2020 were analysed with a focus on samples from 2017 (immediately prior to smelter redevelopment) and 2020 (post-smelter redevelopment). Lead concentration in 2009–2020 TSP was variable ranging up to 6.94 μg m⁻³ (mean = 0.57 μg m⁻³), however, no significant decrease in Pb concentration was observed at either Port Pirie West (p = 0.56, n = 34) or Oliver Street (p = 0.32, n = 28) monitoring stations when 2017 and 2020 TSP values were compared. Similarly, no significant difference (p = 0.42) in PM₁₀ Pb concentration was observed in 2017 (mean = 0.80 μg m⁻³) and 2020 (0.60 μg m⁻³) Oliver Street filters. Although no change in percentage Pb bioaccessibility was observed when 2017 and 2020 Port Pirie West TSP samples were compared (mean of 88.7% versus 88.0%), Pb bioaccessibility was lower (p < 0.005) in both 2020 TSP (mean of 83.9% versus 62.9%) and PM₁₀ (mean of 70.8% versus 58.3%) Oliver Street filters compared to 2017. While scanning electron microscopy, energy dispersive x-ray spectroscopy identified a number of Pb phases within filters (galena, anglesite, cerussite, conglomerates), differences in Pb speciation between 2017 and 2020 filters could not be identified although it was presumed that this influenced Pb bioaccessibility outcomes at Oliver Street. Data from this study suggests that recent smelter redevelopments have not significantly decreased the concentrations of airborne Pb in Port Pirie although re-entrainment of soil-Pb from historical impact may also be a contributing Pb source.

Evaluating ozone levels at high resolutions and accuracy is crucial for understanding the spatiotemporal characteristics of ozone distribution and assessing ozone exposure levels in epidemiological studies. The national models with high spatiotemporal resolutions to predict ground ozone concentrations are limited in China so far. In this study, we aimed to develop a random forest model by combining ground ozone measurements from fixed stations, ozone simulations from the Community Multiscale Air Quality (CMAQ) modeling system, meteorological parameters, population density, road length, and elevation to predict ground maximum daily 8-h average (MDA8) ozone concentrations at a daily level and 1 km × 1 km spatial resolution. The model cross-validation R² and root mean squared error (RMSE) were 0.80 and 20.93 μg/m³ at daily level in 2013–2019, respectively. CMAQ ozone simulations and near-surface temperature played vital roles in predicting ozone concentrations among all predictors. The population-weighted median concentrations of predicted MDA8 ozone were 89.34 μg/m³ in mainland China in 2013, and reached 100.96 μg/m³ in 2019. However, the long-term temporal variations among regions were heterogeneous. Central and Eastern China, as well as the Southeast Coastal Area, suffered higher ozone pollution and higher increased rates of ozone concentrations from 2013 to 2019. The seasonal pattern of ozone pollution varied spatially. The peak-season ozone pollution with the highest 6-month ozone concentrations occurred in different months among regions, with more than half domain in April–September. The predictions showed that not only the annual mean concentrations but also the percentages of grid-days with MDA8 ozone concentrations higher than 100/160 μg/m³ have been increasing in the past few years in China; meanwhile, majority areas in mainland China suffered peak-season ozone concentrations higher than the air quality guidelines launched by the World Health Organization in September 2021. The proposed model and ozone predictions with high spatiotemporal resolution and full coverage could provide health studies with flexible choices to evaluate ozone exposure levels at multiple spatiotemporal scales in the future.

Indoor dust has been postulated as an important matrix for residential pesticide exposure. However, there is a lack of information on presence, concentrations and determinants of multiple pesticides in dust in residential homes close to treated fields. Our objective was to characterize the spatial and temporal variance of pesticides in house dust, study the use of doormats and floors as proxies for pesticides in indoor dust and identify determinants of occurrence and concentrations. Homes within 250 m from selected bulb fields were invited to participate. Homes within 20 km from these fields but not having agricultural fields within 500 m were selected as controls. House dust was vacuumed in all homes from floors (VFD) and from newly placed clean doormats (DDM). Sampling was done during two periods, when pesticides are used and not-used. For determination of 46 prioritized pesticides, a multi-residue extraction method was used. Most statistical analyses are focused on the 12 and 14 pesticides that were detected in >40% of DDM and VFD samples, respectively. Mixed models were used to evaluate relationships between possible determinants and pesticides occurrence and concentrations in DDM and VFD. 17 pesticides were detected in more than 50% of the homes in both matrixes. Concentrations differed by about a factor five between use and non-use periods among homes within 250 m of fields and between these homes and controls. For 7 pesticides there was a moderate to strong correlation (Spearman rho 0.30–0.75) between concentrations in DDM and VFD. Distance to agricultural fields and air concentrations were among the most relevant predictors for occurrence and levels of a given pesticide in DDM. Concentrations in dust are overall higher during application periods and closer to fields (<250 m) than further away. The omnipresence of pesticides in dust lead to residents being exposed all year round.

The disruption of the Fundão dam released 43 million m³ of mine tailings into the Doce River until it flowed into the ocean through the estuary. The mine tailing changed the composition of metals in water and sediment, creating a challenging scenario for the local biota. We used multivariate analyzes and the integrated biomarker response index (IBR) to assess the impact of mine tailings on the bioaccumulation profile (As, Cd, Cr, Cu, Fe, Mn, Pb and Zn) as well as the biomarkers response in gills, hepatopancreas and muscle of shrimps sampled from different sectors during two dry seasons (dry1 and dry2) (Sep/Oct 2018; 2019) and two wet seasons (wet1 and wet2) (Jan/feb 2019; 2020). There was seasonal and local effect under bioaccumulation and biomarker response revealing that the pattern responses seen in each sector sampled changed according to the season. The greater IBR added to the strong association among the most metals tissue content (Cd, Cr, Cu and Mn) and sectors sampled during dry 1 suggests greater bioavailability of these metals to the environment in this period. Estuarine sectors stand out for high Fe bioavailability, especially during wet1, which seems to be associated with greater metallothionein content in hepatopancreas of shrimps. Native species of marine shrimps proved to be successful indicators of sediment quality besides being sensitive to water contamination by metals. The multi-biomarkers approach added to multivariate analysis supports the temporal and seasonal effects, signalizing the importance of continuous monitoring of the estuarine region to better know about the bioavailability of these metals, mainly Fe, and their long-term effects on the local biota.