It has been shown that chemical modification of chitosan with sulfur (S) functional groups could significantly enhance its chelating capability with heavy metals included Cd(II). However, a molecular level understanding has been lacking. Here, we carried out X-ray absorption fine structure (XAFS) and Fourier transformed infrared (FTIR) spectra studies to bridge this knowledge gap. The results indicate that both Cd–O/N and Cd–S bonds exist in the complex of Cd(II) with dithiocarbamate chitosan (DTC-CTS). S functional groups (dithiocarbamate) in DTC-CTS play the major role in complexation with Cd(II) and S content affects the adsorption mechanism. At low S content, Cd(II) is mainly adsorbed on DTC-CTS as an outer-sphere complex with two monodentate amino groups and two water molecules in tetrahedral configuration. At high S content, Cd adsorption dominantly occurs by formation of an inner-sphere complex with two bidentate mononuclear S ligands in tetrahedral configuration. This investigation provides information on the effectiveness and mechanisms of Cd(II) removal that is critical for evaluating modified chitosan applications for stabilization of Cd(II) in surface water, groundwater, soils and sediments.

Evaluation of the toxicity of pesticide residues on non-target organisms in the ecosystem is an important part of pesticide environmental risk assessment. Flupyradifurone is a new type of butenolide insecticide produced by Bayer, who claims it to be “low toxic” to non-target organisms in the environment. However, there is little evidence in the literature to show how flupyradifurone affects aquatic organism development. In the current study, zebrafish embryos were treated with 0.1, 0.15, and 0.2 mg/mL of flupyradifurone within 6.0–72 h past fertilization (hpf). We found that the half-lethal concentration (LC₅₀) of flupyradifurone for zebrafish embryos at 96 hpf was 0.21 mg/mL. Flupyradifurone decreases the heart rate, survival rate, and body length of zebrafish embryos. The flupyradifurone treatment also led to the failure of heart looping, and pericardial edema. Moreover, flupyradifurone increased the level of reactive oxygen species (ROS) and decreased the enzymatic catalysis of catalase (CAT) and superoxide dismutase (SOD). Alterations were induced in the transcription of apoptosis-related genes (bcl-2, bax, bax/bcl-2, p53 and caspase-9) and the heart development-related genes (gata4, myh6, nkx2.5, nppa, tbx2b, tbx5 and vmhc). In the current study, new evidences have been provided regarding the toxic effects of flupyradifurone and the risk of its residues in agricultural products and the environment.

Despite the increased attention for temporal aspects of stressor interactions and for effects of warming in ecotoxicological studies, we lack knowledge on how different exposure durations to warming may affect pesticide sensitivity. We tested how three types of exposure duration to 4 °C warming (acute, developmental and transgenerational exposure to 24 °C vs 20 °C) shape the effect of the pesticide chlorpyrifos on two ecologically relevant fitness-related traits of mosquito larvae: heat tolerance and antipredator behaviour. Transgenerational (from the parental generation) and developmental (from the egg stage) warming appeared energetically more stressful than acute warming (from the final instar), because (i) only the latter resulted in an adaptive increase of heat tolerance, and (ii) especially developmental and transgenerational warming reduced the diving responsiveness and diving time. Exposure to chlorpyrifos decreased the heat tolerance, diving responsiveness and diving time. The impact of chlorpyrifos was lower at 24 °C than at 20 °C indicating that the expected increase in toxicity at 24 °C was overruled by the observed increase in pesticide degradation. Notably, although our results suggest that transgenerational warming was energetically more stressful, it did reduce the chlorpyrifos-induced negative effects at 24 °C on heat tolerance and the alarm escape response compared to acute warming. Our results provide important evidence that the exposure duration to warming may determine the impact of a pesticide under warming, thereby identifying a novel temporal aspect of stressor interactions in risk assessment.

Air pollution is a complex process and is affected by meteorological conditions and other chemical components. Numerous studies have demonstrated that data-driven spatio-temporal prediction models of PM₂.₅ concentration are comparable with the model-driven model. However, data-driven models are usually depending on the statistical correlation between PM₂.₅ and other factors and have challenges in dealing with causality in complex systems. In this paper, we argue that domain knowledge should be incorporated into data-driven models to enhance prediction accuracy and make the model more physically realistic. We focus on the influence of dynamic wind-field on PM₂.₅ concentration distribution and fuse the pollution diffusion distance with the deep learning model based on a wind-field surface. In order to model spatial dependence between monitoring stations, which is dynamic and anisotropic because of the wind-field, we proposed a hybrid deep learning framework, dynamic directed spatio-temporal graph convolution networks (DD-STGCN). It expanded the ability to deal with space-time prediction in the continuous and dynamic wind-field. We used a directed graph time-series to describe the vertex state and topological relationship between vertices and replaced traditional Euclidean distance with wind-field diffusion distance to describe the proximity relationship between vertices. Our experiment results demonstrated that the DD-STGCN model achieved a better prediction ability than LSTM, GC-LSTM, and STGCN models. Compared to the best comparison model, MAPE, MAE, and RMSE were improved by 10.2%, 9.7%, and 9.6% in 12 h on an average, respectively. The performance of our model was further tested during a haze period. In the case that two models both considered the effect of wind, compared with the pure data-driven model, our model performed better in prediction distribution and showed the benefit of spatial interpretability provided by domain knowledge.

Motor vehicles emit a variety of pollutants including metals, petroleum hydrocarbons and polycyclic aromatic hydrocarbons (PAHs). The relationships between metals, petroleum hydrocarbons and PAHs, soil respiration and microbial diversity (fungi and bacteria) were studied using control (n = 3) and roadside soils (n = 27) with different exposure periods to vehicle emissions (2–63 years). Bacterial diversity was found to be higher than control sites (P = 0.002) but was the same across different categories of road age (P = 0.328). Significant (r = −0.49, P = 0.007) contrasting behaviour of fungal and bacterial diversity was reported, with diversity increasing across all road types for bacteria and decreasing across all road types for fungi compared to control soils. Analysis of the bacterial community identified three distinct clusters, separated on age of contamination, suggesting that roadside bacterial communities change over time with pollution from vehicles with the potential development of metal resistant bacteria in roadside soils. In contrast, for fungal communities, a reduction in diversity with time of exposure to roadside vehicle emissions was observed suggesting the potential for reduced ecosystem functionality and soil health in roadside soils. This is the first study in the published literature to include both bacterial and fungal responses from aged roadside soils. The results from this study suggest that normal functionality of soil ecosystem services is being affected in roadside soils, potentially globally.

The Yellow River Delta (YRD) wetland, the most important estuary wetland in eastern China, has an important ecosystem service function. Rapid and intensive development has inevitably led to the accumulation of potentially toxic elements (PTEs) in soils. Therefore, identifying quantitative sources and spatial distributions of PTEs is essential for soil environmental protection in the YRD. A total of 240 topsoil samples (0–20 cm) were collected in the Yellow River Delta Nature Reserve (YRDNR) and analyzed the PTE contents. To avoid the biases of the single receptor model, positive matrix factorization, factor analysis with nonnegative constraints, and maximum likelihood principal component analysis-multivariate curve resolution-alternating least squares were used for source apportionment of soil PTEs. To promote the efficiency of multivariate geostatistical simulation, a minimum/maximum autocorrelation factor-sequential Gaussian simulation was built to map the spatial patterns of PTEs. Three factors were derived by the three receptor models, and their contributions to the source explanation were similar. As, Cr, Cu, Mn, Ni, and Zn originated from natural sources, with contributions of 85.6%–96.4 %. A total of 61.5 % of Hg was associated with atmospheric deposition of coal combustion and wastewater from upstream. Agricultural activities and oil exploitation contributed 33.5 % and 15.9 % of the Cd and Pb concentrations. Spatial distributions of soil PTEs were controlled by sedimentary grain size. A total of 47.2 % of the total study area was identified as hazardous area for Cd, 10.3 % for As, and 5.4 % for Hg. This work is expected to provide references for soil pollution assessment and management of YRDNR.

It is possible for heavy metals in soils to be adsorbed by crop roots and then accumulated in crops, which eventually causes great health risk when the crops are ingested by humans. Thus, it is valuable to understand the enrichment model of heavy metals in crops. Diffusive gradients in thin-films (DGT) technique, as an in-situ passive sampling method, can be used to evaluate the bioavailable heavy metals contents in soils. In this study, data of the bioavailable cadmium (Cd) in soils determined by DGT and Cd contents uptake in rice and maize grains in Tianjin, Zhejiang and Guangxi provinces of China were collected from previous references in Web of Science. By comparing bioconcentration factors, it was found that the heavy metal concentrations accumulated in rice and maize followed a general order roots > stems or leaves > grains. An accurate and robust model for the prediction of Cd content in maize and rice grains was established based on bioconcentration factor (BCF) and the bioavailable Cd content determined by DGT method, with R² 0.986 and root mean square error (RMSE) 0.128. This result suggests that the DGT method can be good tool for predicting heavy metals uptake in crops.

Perfluorooctanesulfonic acid (PFOS) is a persistent environmental contaminant previously found in consumer surfactants and industrial fire-fighting foams. PFOS has been widely implicated in metabolic dysfunction across the lifespan, including diabetes and obesity. However, the contributions of the embryonic environment to metabolic disease remain uncharacterized. This study seeks to identify perturbations in embryonic metabolism, pancreas development, and adiposity due to developmental and subchronic PFOS exposures and their persistence into later larval and juvenile periods. Zebrafish embryos were exposed to 16 or 32 μM PFOS developmentally (1–5 days post fertilization; dpf) or subchronically (1–15 dpf). Embryonic fatty acid and macronutrient concentrations and expression of peroxisome proliferator-activated receptor (PPAR) isoforms were quantified in embryos. Pancreatic islet morphometry was assessed at 15 and 30 dpf, and adiposity and fish behavior were assessed at 15 dpf. Concentrations of lauric (C12:0) and myristic (C14:0) saturated fatty acids were increased by PFOS at 4 dpf, and PPAR gene expression was reduced. Incidence of aberrant islet morphologies, principal islet areas, and adiposity were increased in 15 dpf larvae and 30 dpf juvenile fish. Together, these data suggest that the embryonic period is a susceptible window of metabolic programming in response to PFOS exposures, and that these early exposures alone can have persisting effects later in the lifecourse.

Chronic exposure to potassium bromate (KBrO₃), a toxic halogen in the environment, has become a global problem of public health. The current study aims to elucidate for the first time the effect of Urtica dioica (UD) on behavioural changes, oxidative stress, and histopathological changes induced by KBrO₃ in the cerebellum, kidney, liver and other organs of adult rats.The rats were divided into four groups: group 1 served as a control received physiological serum, Group 2 received KBrO₃ (2 g/L of drinking water), group 3 received KBrO₃ and Urtica dioica (100 mg/kg), and group 4 received KBrO₃ and Urtica dioica (400 mg/kg). We then measured behavioural changes, oxidative stress, and biochemical and histological changes in the cerebellum, liver, kidney and others organs in these rats. After 30 days of treatment, the animals were sacrificed.We observed significant behavioural changes in KBrO₃-exposed rats. When investigating redox homeostasis in the cerebellum, we found that mice treated with KBrO₃ had increased lipid peroxidation and protein oxidation in the cerebellum. In addition, it inhibits hepatic and lipid peroxidation (malondialdehyde), advanced oxidation protein product (AOPP), attenuates KBrO₃-mediated enzyme depletion, catalase, superoxide dismutase, glutathione peroxidase enzymatic and antioxidant activities in the liver and kidney. Rats that were co-managed with Urtica dioica at the high portion of 400 mg/kg indicated a higher effect than that treated with the low dose of 100 mg/kg practically in all the tests carried out.Our results demonstrate that Urtica dioica is a potential therapeutic agent for oxidative stress associated with neurodegenerative diseases.

An integrated model of VOCs emission/sorption from/on dry building materials with a general boundary condition, variable air exchange rate and inlet concentration is developed. An analytical solution is obtained by using the generalized integral transform technique. Good agreements are obtained between the present model and the experimental data. The effects of environmental conditions on the emission are investigated. The emission from two surfaces can increase the concentration of hexanal in the air and decrease the initial emission rate at x=δ with the increase in mass transfer coefficient at x=0. Periodical inlet concentration can lead to the periodic variation of materials between a source and a sink. Ventilation can keep the concentration in the air at a low level and help to decrease the concentration of hexanal in materials. The present model is capable of simulating indoor air quality due to the VOCs emission and sorption.