Comprehensive efficiency analysis of wastewater treatment plants (WWPTs) in the alpine region with harsh environment and poor techniques as well as managing experience could provide targeted and effective improvement evidences for local wastewater treatment industry and help to improve the water quality of downstream reaches. In this paper, slack–based data envelopment analysis (SBM–DEA) was adopted to assess the operating efficiencies of WWPTs in northeast Qinghai–Tibet Plateau (QTP). Results showed that the average efficiency score for all WWPTs was 0.608, and 32.5% of WWPTs were efficient. Some WWPTs had large improvement potentials in operating costs and pollutant removal rates. Lowering expenditures and promoting facility construction for WWPTs to overcome the climate difficulties and improve management level was necessary according to their improvement potentials. In addition, the relative importance of the quantitative influential factors to efficiencies scores calculated by random forest regression (RFR) indicated that design capacity and temperature were important quantitative factors affecting the performance of WWPTs. Furthermore, geographical location and design capacity also had significant influence on the comprehensive efficiency of WWPTs verified by Kruskal–Wallis test. Our results highlight the importance of facilities upgrading, scientific management for WWPTs. And the relative improvement suggestions on overcoming the high and cold environment should also be considered for the efficient operations of WWTPs as well as the protection the aquatic environment.

The theory-guided air quality model solves the mathematical equations of chemical and physical processes in pollution transportation numerically. While the data-driven model, as another scientific research paradigm with powerful extraction of complex high-level abstractions, has shown unique advantages in the PM₂.₅ prediction applications. In this paper, to combine the two advantages of strong interpretability and feature extraction capability, we integrated the partial differential equation of PM₂.₅ dispersion with deep learning methods based on the newly proposed DPGN model. We extended its ability to perform long-term multi-step prediction and used advection and diffusion effects as additional constraints for graph neural network training. We used hourly PM₂.₅ monitoring data to verify the validity of the proposed model, and the experimental results showed that our model achieved higher prediction accuracy than the baseline models. Besides, our model significantly improved the correct prediction rate of pollution exceedance days. Finally, we used the GNNExplainer model to explore the subgraph structure that is most relevant to the prediction to interpret the results. We found that the hybrid model is more biased in selecting stations with Granger causality when predicting.

Chemical sensors that can detect volatile organic compounds (VOCs) are the subject of extensive research efforts. Among various sensing technologies, molecularly imprinted polymers (MIPs) are regarded as a highly promising option for their detection with many advantageous properties, e.g., specific binding-site for template molecules, high recognition specificity, ease of preparation, and chemical stability. This review covers recent advances in the sensing application of MIPs toward various types of VOCs (e.g., aliphatic and aromatic compounds). Particular emphasis has been placed on multiple approaches to the synthesis of MIP-based VOC sensors in association with their performance and sensing mechanisms. Current challenges and opportunities for new VOC-sensing applications are also discussed based on MIP technology.

Studies have confirmed that PM₁₀, defined as respirable particles with diameters of 10 μm and smaller, has adverse effects on human health and the environment. Various estimation methods are employed to determine the PM₁₀ concentration using historical data on controlling PM₁₀ air pollution, early warning, and protecting public health and the environment. The present study analyses different Long Short-Term Memory (LSTM) models that can predict hourly PM₁₀ concentration. In parallel, the study also investigates the effectiveness of the data preprocessing and feature selection (DPFS) process on the prediction accuracy of the LSTM models. For this purpose, three different LSTM models, namely Vanilla, Bi-Directional, and Stacked, were developed. Then, a comprehensive data preprocessing stage is used to eliminate missing and erroneous data and outliers from real-world raw data, and a feature selection process is applied to extract unnecessary features. The LSTM models consider three air quality parameters, including SO₂, O₃, and CO, and three meteorological factors, including relative humidity, wind direction, and wind speed. The prediction performances of the LSTM models are compared using the RMSE, MAE and R² performance index according to whether DPFS is used in the models or not. As a result, when the DPFS process was applied, the proposed LSTM models achieved high prediction performance and can be used to predict hourly PM₁₀ concentrations. Overall, the DPFS process significantly enhanced the developed LSTM models’ prediction performance. Furthermore, the proposed model might be a useful tool for city administrators to make decisions and improve air quality management efforts.

Plastic film mulch (PFM) is a double-edged-sword agricultural technology, which greatly improves global agricultural production but can also cause severe plastic pollution of the environment. Here, we characterized and quantified the amount of macro- and micro-plastics accumulated after 32 years of continuous plastic mulch film use in an agricultural field. An interactive field trial was established in 1987, where the effect of plastic mulching and N fertilization on maize yield was investigated. We assessed the abundance and type of macroplastics (>5 mm) at 0–20 cm soil depth and microplastic (<5 mm) at 0–100 cm depth. In the PFM plot, we found about 10 times more macroplastic particles in the fertilized plots than in the non-fertilized plots (6796 vs 653 pieces/m²), and the amount of film microplastics was about twice as abundant in the fertilized plots than in the non-fertilized plots (3.7 × 10⁶ vs 2.2 × 10⁶ particles/kg soil). These differences can be explained by entanglement of plastics with plant roots and stems, which made it more difficult to remove plastic film after harvest. Macroplastics consisted mainly of films, while microplastics consisted of films, fibers, and granules, with the films being identified as polyethylene originating from the plastic mulch films. Plastic mulch films contributed 33%–56% to the total microplastics in 0–100 cm depth. The total number of microplastics in the topsoil (0–10 cm) ranged as 7183–10,586 particles/kg, with an average of 8885 particles/kg. In the deep subsoil (80–100 cm) the plastic concentration ranged as 2268–3529 particles/kg, with an average of 2899 particles/kg. Long-term use of plastic mulch films caused considerable pollution of not only surface, but also subsurface soil. Migration of plastic to deeper soil layers makes removal and remediation more difficult, implying that the plastic pollution legacy will remain in soil for centuries.

Zero valent iron-loaded biochar (Fe⁰-BC) has shown promise for the removal of various organic pollutants, but is restricted by reduced specific surface area, low utilization efficiency and limited production of reactive oxygen species (ROS). In this study, iron carbide-loaded activated biochar (Fe₃C-AB) with a high surface area was synthesized through the pyrolysis of H₃PO₄ activated biochar with Fe(NO₃)₃, tested for removing bisphenol A (BPA) and elucidated the adsorption and degradation mechanisms. As a result, H₃PO₄ activated biochar was beneficial for the transformation of Fe⁰ to Fe₃C. Fe₃C-AB exhibited a significantly higher removal rate and removal capacity for BPA than that of Fe⁰-BC within a wide pH range of 5.0–11.0, and its performance was maintained even under extremely high salinity and different water sources. Moreover, X-ray photoelectron spectra and density functional theory calculations confirmed that hydrogen bonds were formed between the COOH groups and BPA. ¹O₂ was the major reactive species, constituting 37.0% of the removal efficiency in the degradation of BPA by Fe₃C-AB. Density functional reactivity theory showed that degradation pathway 2 of BPA was preferentially attacked by ROS. Thus, Fe₃C-AB with low cost and excellent recycling performance could be an alternative candidate for the efficient removal of contaminants.

Fluorinated pesticides acquired a significant market share in the agrochemical sector due to the surge of new fluoroorganic ingredients approved in the last two decades. This growing trend has not been accompanied by a comprehensive scientific and regulatory framework entailing all their potential negative impacts for the environment, especially when considering the hazardous properties that may result from the incorporation of fluorine into organic molecules. This review aims to address the safe/hazardous dichotomy associated with fluorinated pesticides by providing an updated outlook on their relevancy in the agrochemical sector and how it leads to their role as environmental pollutants. Specifically, the environmental fate and distribution of these pesticides in the ecosystems is discussed, while also analysing their potential to act as toxic substances for non-target organisms.

Across the planet, winter de-icing practices have caused secondary salinization of freshwater habitats. Many amphibians are vulnerable because of permeable skin and reliance on small ponds, where salinity can be high. Early developmental stages of amphibians are especially sensitive to salt, and larvae developing in salt-polluted environments must osmoregulate through ion exchange in gills. Though ionoregulation in amphibian gills is generally understood, the role of gill morphology remains poorly described. Yet gill structure should affect ionoregulatory capacity, for instance in terms of available surface area. As larval amphibian gills also play critical roles in gas exchange and foraging, changes in gill morphology from salt pollution potentially affect not only osmoregulation, but also respiration and feeding. Here, we used an exposure experiment to quantify salinity effects on larval gill morphology in wood frogs (Rana sylvatica). We measured a suite of morphological traits on gill tufts—where ionoregulation and gas exchange occur—and on gill filters used in feeding. Larvae raised in elevated salinity developed larger gill tufts but with lower surface area to volume ratio. Epithelial cells on these tufts were less circular but occurred at higher densities. Gill filters showed increased spacing, likely reducing feeding efficiency. Many morphological gill traits responded quadratically, suggesting that salinity might induce plasticity in gills at intermediate concentrations until energetic demands exceed plasticity. Together, these changes likely diminish ionoregulatory and respiratory functionality of gill tufts, and compromise feeding functionality of gill filters. Thus, a singular change in aquatic environment from a widespread pollutant appears to generate a suite of consequences via changes in gill morphology. Critically, these changes in traits likely compound the severity of fitness impacts in populations dwelling in salinized environments, whereby ionoregulatory energetic demands should increase respiratory and foraging demands, but in individuals who possess structures poorly adapted for these functions.

Perfluorooctanoic acid (PFOA) is abundant in environment due to its historical uses in consumer products and industrial applications. Exposure to low doses of PFOA has been associated with various disease risks, including neurological disorders. The underlying mechanism, however, remains poorly understood. In this study, we examined the effects of low dose PFOA exposure at 0.4 and 4 μg/L on the morphology, epigenome, mitochondrion, and neuronal markers of dopaminergic (DA)-like SH-SY5Y cells. We observed persistent decreases in H3K4me3, H3K27me3 and 5 mC markers in nucleus along with alterations in nuclear size and chromatin compaction percentage in DA-like neurons differentiated from SH-SY5Y cells exposed to 0.4 and 4 μg/L PFOA. Among the selected epigenetic features, DNA methylation pattern can be used to distinguish between PFOA-exposed and naïve populations, suggesting the involvement of epigenetic regulation. Moreover, DA-like neurons with pre-differentiation PFOA exposure exhibit altered network connectivity, mitochondrial volume, and TH expression, implying impairment in DA neuron functionality. Collectively, our results revealed the prolonged effects of developmental PFOA exposure on the fitness of DA-like neurons and identified epigenome and mitochondrion as potential targets for bearing long-lasting changes contributing to increased risks of neurological diseases later in life.

Environmental pollution by metals has repercussions on wildlife health. It is known that some metals can have an influence on the neuroendocrine stress response, and at the same time, metals have pro-oxidant effects that can overwhelm the antioxidant system and cause oxidative stress. This study evaluates the association of metals with neuroendocrine stress activity and biomarkers of oxidative stress in 42 captive female Morelet's crocodiles (Crocodylus moreletii). We measured five metals of ecotoxicological importance (Hg, Cd, Pb, Cu and Zn), and three biomarkers of the oxidative stress response in the liver: glutathione (GSH) and glutathione disulfide (GSSG) as markers for antioxidant system and thiobarbituric acid reactive substances (TBARS) for oxidative damage. We also measured one biomarker of the neuroendocrine response to stress: corticosterone (B) in blood plasma. The mean ± SD concentrations of metals in the liver expressed in μg/g (dw) were: Cd: 0.004 ± 0.003, Hg: 0.014 ± 0.019, Cu: 0.017 ± 0.013, Zn: 0.043 ± 0.035, Pb: 0.16 ± 0.256. The mean ± SD of GSH was 0.42 ± 0.35 nmol/mg protein, the mean ± SD of GSSG was 0.24 ± 0.20 nmol/mg protein, the mean ± SD concentrations of TBARS were 0.36 ± 0.21 nmol/mg protein, and the mean ± SD of B was 393.57 ± 405.14 pg/mL. Hg presented a significant negative relationship with corticosterone. Cd had a negative relationship with both GSH and GSSG; meanwhile, Zn showed a negative relationship with TBARS levels, could be a protective element against hepatic oxidative damage. Finally, B had negative relationship with oxidative damage. The connection found between Hg and the neuroendocrine stress response, as well as the correlations of Cd and Zn with oxidative damage and antioxidant activity should be studied further, given their toxicological importance and implications for the conservation of C. moreletii and other crocodilians.