Water, Air, & Soil Pollution最新文献

Lead–zinc mine tailings are characterized by high heavy metal content, low enzyme activity, and poor nutrient content, which make it difficult for most plants to colonize and significantly hinder the restoration of the tailings. Therefore, selecting pioneer plants capable of effectively improving the physicochemical properties of the tailings is crucial. In this study, a pot experiment was conducted to compare the effects of four plants—Bassia scoparia, Agropyron elongatum, Suaeda glauca, and Sorghum sudanense—on the physicochemical properties of tailings. The results showed that these pioneer plants improved the physicochemical properties of the tailings. Specifically, they increased the activities of urease, invertase, and alkaline phosphatase in the tailings by 0.25% to 12.7%, 19.0% to 746.5%, and 16.9% to 113.1%, respectively, while reducing the available concentrations of Cd, Pb, and Zn by 1.62% to 19.4%, 9.17% to 42.4%, and 13.9% to 24.9%, respectively. Among the plants tested, S. sudanense exhibited the largest biomass, the highest root activity, and the most significant improvements in pH and cation exchange capacity (CEC) of the tailings. It also demonstrated the most effective control over the available states of Cd, Pb, and Zn, and substantially increased the activities of urease, invertase, and alkaline phosphatase. Furthermore, S. sudanense showed a higher proportion of heavy metals in its roots, suggesting that it can effectively immobilize heavy metals and reduce the risk of leaching. A grey comprehensive evaluation confirmed that S. sudanense is an ideal pioneer plant for the ecological restoration of tailings ponds.

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Occurrence, spatial distribution, influencing factors and ecological risks of 15 Phthalate esters (PAEs) in the sediments of Poyang Lake and its tributaries were investigated. The concentrations of total PAEs (Σ₁₅ PAEs) in the sediments of Poyang Lake ranged from 9.8 to 3765.6 ng/g dry weight and Σ₁₅ PAEs of the tributaries ranged from 32.7 to 590.9 ng/g. Di-(2-ethylhexyl) phthalate was the dominant PAE in the sediments of Poyang Lake, which accounted for approximately half of the Σ₁₅ PAEs. The spatial distribution patterns of most PAEs exhibited a fan shaped pattern, with high concentrations of PAEs locating in the northern part of the lake based on continuous spatial distribution patterns. The PAE distributions were associated with anthropogenic activities and influenced by inputs from tributaries and backflow from the Yangtze River. The correlations between PAEs and environmental factors exhibited region-specific differences according to redundancy analysis and Pearson correlation analysis. Di-iso-butyl phthalate posed a high risk to sensitive fish according to the risk quotients. The results of this study could provide innovative insights into the behaviors of PAEs in the large river-connecting lakes.

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In hot-arid urban environments such as Riyadh, Saudi Arabia, indoor air quality (IAQ) has emerged as a critical public health issue due to the widespread use of airtight residential buildings and reliance on mechanical ventilation. This study investigates the effectiveness of indoor vegetation in improving indoor environmental quality (IEQ) by reducing formaldehyde (HCHO) concentrations and stabilizing thermal and humidity conditions. Full-scale laboratory experiments were conducted in simulated apartment units configured to reflect standard Riyadh construction practices. Across three experimental phases—baseline (no vegetation), plant placement, and plant placement with mechanical ventilation—HCHO, temperature, and humidity were continuously monitored for 5 days. The results indicate that indoor plants significantly reduced HCHO concentrations in vegetated zones (by 0.312 ppm on average) compared to control zones, while also moderating temperature fluctuations and maintaining humidity between 75 and 87%. Introducing mechanical air circulation between zones extended the benefits to adjacent living spaces, demonstrating that even passive or forced airflow can enhance the spatial effectiveness of plant-based purification strategies. In contrast, non-vegetated zones maintained high HCHO levels and exhibited greater environmental instability. These findings highlight the synergistic potential of combining biophilic design with low-energy mechanical systems to achieve healthier indoor environments. The study provides empirical evidence for integrating vegetation into residential design strategies aligned with Vision 2030 and the Saudi Green Initiative. It also underscores the need for long-term IAQ monitoring and construction quality controls to optimize occupant health and building sustainability in the Gulf region.

Copper (Cu) is a heavy metal found in waters from regions impacted by mining. This type of contamination can present a significant challenge to the efficiency of biological nitrogen removal processes. This study investigated the impact of Cu on two anaerobic ammonium oxidation pathways: Feammox (ammonium oxidation coupled to iron reduction) and Anammox (anaerobic ammonium oxidation). Batch experiments using enriched cultures from both processes were conducted under controlled Cu concentrations (0, 4, 8, and 10 mg/L), and Feammox was analyzed under two carbon sources (acetate and bicarbonate). Anammox showed stable NH₄⁺ removal (~ 50%) at all Cu concentrations, although NO₂⁻ accumulation at higher Cu levels indicated potential stress. In contrast, Feammox was more sensitive to Cu, particularly in terms of Fe³⁺ reduction and Fe²⁺ accumulation, where acetate promoted greater activity than bicarbonate. Molecular analyses revealed the presence of key microorganisms associated with Feammox processes, such as Albidiferax ferrireducens, Acidimicrobium, Geobacter spp., Shewanella spp., as well as Anammox bacteria. Similarly, nitrogen cycle-related genes also remained detectable under moderate copper concentrations. These results indicate that while both processes can operate under moderate copper concentrations, Feammox was more susceptible to inhibition. These findings contribute to understanding the resistance and limitations of biological N removal in Cu-contaminated wastewater, allowing for the development of more robust and efficient treatment strategies.

Locating atmospheric pollution sources is essential for protecting the environment and public health. It enables identification and control of pollution sources, reduces the impact of pollutant emissions on the environment, and holds significant practical importance. This study proposes a method that integrates sensor networks with machine learning to identify pollution sources. By monitoring sensor data, we track pollutant dispersion and apply models including support vector machines (SVM), deep neural networks (DNN), and hierarchical DNNs (HI-DNN) for source classification. To overcome the limitations of numerical simulations, we collected real-world diffusion data through field measurements. We partitioned the monitoring area into grids and transformed the localization task into a multi-class classification problem. We trained and evaluated models based on DNN, SVM, and HI-DNN architectures. The SVM model with an RBF kernel achieved an accuracy of 89.5%, the basic DNN model reached 95.2%, and the HI-DNN model achieved 96.7%, successfully identifying the most likely source among 17 candidates. Most misclassified predictions were near the actual source, providing useful reference for practical localization.

Global production and consumption of plastics have dramatically increased in recent decades. While social benefits of plastic products are undisputed, plastics have resulted in negative environmental impacts. Through physical, chemical, and biological degradation processes, plastic fragments are formed, gradually breaking down into microscopic-sized particles over time. These tiny particles, known as microplastics (MPs, < 5 mm), have gained considerable attention due to their small size, widespread presence, bioavailability, and adverse effects on human and ecosystem health. MPs have been detected globally in all environments, including the human body, becoming a pressing global concern. Recently, regional, national, and international efforts have been made to study and quantify environmental impacts of MPs. This review provides an overview of the current state of MP studies, focusing on different sample types while specifically analyzing their characteristics including color, shape and chemical composition in Canada. For this review, a specific set of keywords separated by Boolean operators was used to collect relevant research on MPs in Canada. The most prevalent shapes in Canadian environmental samples were fibers and fragments, while blue, black, and clear are the most common colors. Polyethylene (PE), Polyethylene terephthalate (PET), and Polypropylene (PP) are the most frequently encountered polymers in water, wastewater, biosolids, and sediment samples. Although there has been advancement in the examination of MPs in Canada, there is still a considerable knowledge gap, including uneven spatial coverage, inconsistent methods and reporting, scarse polymer/additive data, and a few long-term time series studies. Filling these knowledge gaps will help improve our understanding of the prevalence, origins, and impacts of MPs in Canada's varied ecosystems. Future research needs to include the creation of uniform data collection techniques and the introduction of long-term monitoring programs to measure MPs across varied ecosystems. This will help development of effective mitigation strategies to manage the increasing problem of plastic and MP pollution.

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Electrokinetic soil remediation (EKR) is a promising in-situ technique that could be suitable for the removal of high salt ions content from soil. However, the presence of carbonate ions and calcite in saline soil presents additional challenges for this remediation approach. This study investigates the efficacy of EKR on a real calcareous and highly saline soil by following the removal efficiency of key salt ions (6 anions: NO₂⁻, NO₃⁻, HCO₃⁻, CO₃²⁻, Cl⁻, SO₄²⁻, and 4 cations: Na⁺, K⁺, Mg²⁺, Ca²⁺). The focus is on optimizing carbonate ion decomposition to enhance soil decontamination. Four experiments were conducted under varying conditions, including constant and cycled DC voltage applications. The results showed that experiment 3, which involved pre-EKR neutralization of soil carbonates ions and controlled pH levels of the anolyte and catholyte, achieved the highest removal efficiency for ions, including over 60 % of carbonate ions. Additionally, this treatment reduced soil electrical conductivity from 18.56 dS/m to 1.89 dS/m. The cycled voltage application in experiment 4 demonstrated a slight reduction in energy consumption while maintaining ion removal efficiency. These results highlight the importance of managing carbonate ion concentrations and pH levels to enhance the efficiency of EKR in calcareous highly saline soil remediation.

It is urgent to control the excess growth of alga. Thus, a novel photo-electric synergistic treatment (PEST) system was designed for effective algae removal in this study. The results indicated that PEST achieved the removal of 67.6% for Microcystis aeruginosa (M. aeruginosa), 83.1% for chlorophyll a and 90.7% for microcystin–LR after 100 min, respectively, which were higher than those of photocatalysis and electrocatalysis. The photocatalyst of PEST (MoS₂/WO₃/CF-5%) demonstrated an excellent reusability and stability. Additionally, the inactivation mechanism of the PEST on M. aeruginosa was explored. Reactive oxygen species generation during the PEST were able to damage the cell membrane, DNA and protein, leading to cellular function disruption and algal cells apoptosis. An all–weather photo–electric synergistic reactor (AWPESR) was developed based on the PEST to achieve continuous removal of algae under natural conditions. The AWPESR demonstrated a high removal (78.4%) of M. aeruginosa, with a treatment load of 5.51 × 10⁸ cells•(m^–2•d^–1). Moreover, the operation of the AWPESR is simple and relies solely on solar irradiation. The demonstration of algal removal in the novel PEST and AWPESR systems under natural conditions provides a potential green strategy for algal blooms control.

In this study, to mitigate the ecological risks associated with ofloxacin residues in the environment, two drug-resistant strains, Aerococcus sp. DORC01 and Aspergillus sp. DYN01, were isolated and acclimatized from chronically exposed cow dung. Their efficacy in removing ofloxacin was optimized using both single-organism and mixed-co-culture systems, in conjunction with response surface methodology. Under optimal conditions for single-organism systems, DORC01 and DYN01 achieved 68.7% and 51.8% removal of 100 mg/L ofloxacin over a 7-day period, respectively. The optimal conditions for DORC01 were 29.61 °C, 70.05 mg/L substrate concentration, and 0.46% bacterial load, while for DYN01, they were pH 5.97, 72.99 mg/L substrate concentration, and 0.50% bacterial load. The mixed mycelium spheres were further prepared using a co-culture method with a 3:1 ratio, resulting in an enhanced predicted maximum removal rate of 93.91% under conditions of 33.50 °C, pH 7.45, 0.37% bacterial volume, and a substrate concentration of 74.96 mg/L. This represents a 45% improvement over the efficiency observed with single bacterial cultures. Inactivation experiments demonstrated that live bacteria facilitated degradation primarily through biosorption, with degradation being the dominant process. After 7 days, the removal rate achieved by live bacteria was significantly higher than that of inactivated bacteria. This study is the first to establish a synergistic system involving Aerococcus and Aspergillus, offering a novel strategy for the efficient bioremediation of antibiotic contamination in livestock and poultry environments.