Environmental Geochemistry and Health最新文献

Aquaculture operations produce large amounts of wastewater contaminated with organic matter, nitrogenous compounds, and other emerging contaminants; when discharged into natural water bodies, it could result in ecological problems and severely threaten aquatic habitats and human health. However, using aquaculture wastewater in biorefinery systems is becoming increasingly crucial as advancements in valuable bioproduct production continue to improve economic feasibility. Research on utilising microalgae as an alternative to producing biomass and removing nutrients from aquaculture wastewater has been extensively studied over the past decades. Microalgae have the potential to use carbon dioxide (CO₂) effectively and significantly reduce carbon footprint, and the harvested biomass can also be used as aquafeed. Furthermore, aquaculture wastewater enriched with phosphorus (P) is a potential resource for P recovery for the production of biofertiliser. This will reduce the P supply shortage and eliminate the environmental consequences of eutrophication. In this context, the present review aims to provide a comprehensive overview of the current state of the art in a generation, as well as the characteristics and environmental impact of aquaculture wastewater reported by the most recent research. Furthermore, the review synthesized recent developments in algal biomass cultivation using aquaculture wastewater and its utilisation as biorefinery feedstocks for producing value-added products, such as aquafeeds, bioethanol, biodiesel, biomethane, and bioenergy. This integrated process provides a sustainable method for recovering biomass and water, fully supporting the framework of a circular economy in aquaculture wastewater treatment via resource recovery.

A tremendous amount of recent work has been done on different metal oxide nanomaterials for biological activities and photocatalytic dye degradation. This work used the Cissus quadrangularis leaf extract to prepare TiO₂, CdO, Mn₂O₃, and ZnO nanoparticles using a green synthesis approach. To ascertain the physicochemical characteristics of the generated metal oxide nanoparticles, various characterisation techniques were used. The X-ray diffraction technique was used to determine the composition of the crystal and phase. Metal oxide nanoparticles have been proven to be present through surface morphological investigations using a scanning electron microscope and energy dispersive spectroscopy analysis. UV-Vis and Fourier transform infrared spectra were used for spectroscopic analysis. X-ray photoelectron spectroscopy can determine a material's elemental composition in addition to the electronic and chemical states of its atoms. The nanomaterial's distinct morphology, which resembles rods, rose petals, platelets, and spheres, was discovered by scanning electron microscope. Synthesized metal oxide nanoparticles have demonstrated a remarkable efficiency of 87.5-90.6% when utilized as a catalyst towards the removal of the malachite green dye under UV light irradiation. Additionally, we use the disc diffusion method to assess antibiotic efficacy against Bacillus subtilis, Candida tropicalis, and Escherichia coli. ZnO nanoparticles had the greatest zones of inhibition for 80 μL doses, measuring 26.99 mm for Bacillus subtilis, 27.57 mm for Escherichia coli, and 25.28 mm for Candida tropicalis. The antimicrobial activity was strongly impacted by the size of the nanoparticles and increased with decreasing particle size. Overall, our research demonstrates that metal oxide nanoparticles are a promising photocatalytic agent for wastewater treatment and biological applications.

The construction of dams has caused disruptions to river connectivity, leading to alterations in the deposition of hydrophobic organic contaminants in reservoir sediments. Further investigation is warranted to explore the impact of cascade reservoirs with differing hydrological characteristics on polycyclic aromatic hydrocarbons (PAHs) distribution in sediment. This study examines the presence of 30 PAHs in the sediments collected from six cascade reservoirs situated in the Wujiang River basin during January and July 2017. The results showed that Σ30 PAHs ranged from 455-3000 ng/g dw (mean 1030 ng/g dw). Anthropogenic activities and reservoir hydrology determined the distribution trend of PAHs in sediments, with an overall increase from upstream to midstream and then a decrease downstream. The PAH levels were highly linked to the secondary industry (P < 0.05). This was further supported by the relationship between the PAH emissions from coal combustion and traffic sources analyzed by the positive matrix factorization model and economic parameters in the wet season (P < 0.01). At the same time, reservoir age (RA) showed a positive correlation with PAH concentrations (P < 0.05), while hydraulic retention time (HRT) exhibited a negative correlation with PAH levels (P = 0.03). The relationship between total organic carbon (TOC) and PAHs in stream sediments worldwide was nonlinear (P < 0.01), with PAH concentrations initially rising and then falling as TOC levels increased. Concerns regarding carcinogenic risk were raised due to contributions from coal and vehicular sources, with the risk increasing with RA.

Bacterial drug resistance is becoming increasingly serious, this study aims to investigate the relationship between the resistance rate of erythromycin-resistant Streptococcus pneumoniae (SP) and reasons for the epidemic under complex geographical and climatic factors in China. Data spanning from 2014 to 2021, including drug resistance rates, isolate rates, meteorological variables, and demographic statistics, were collected from the China Antimicrobial Resistance Monitoring System, the China Statistical Yearbook and China Meteorological Website. Our analysis involved nonparametric tests and the construction of multifaceted regression models for rigorous multivariate analysis. Single-factor analysis revealed significant differences in the resistance rate and isolate rate of erythromycin-resistant SP across different regions characterized by Hu Huanyong lines or different climate types. Multivariate regression analysis indicated positive correlations between the drug resistance rate and temperature, Subtropical climate, Gross Domestic Product (GDP), Hu Huanyong line, and the highest temperature in the past period (Tm); the isolate rate showed a positive correlation with regional GDP and a negative correlation with monsoon climate. The model developed in this study provides valuable insights into the resistance rate and potential relationships of erythromycin-resistant SP under complex meteorological conditions in China.

Identifying the source-specific health risks of potentially toxic elements (PTE) in urban park soils is essential for human health protection. However, previous studies have mostly focused on the deterministic source-specific health risks, ignoring the health risk assessment from a probabilistic perspective. To fill this gap, we developed a hybrid model that incorporated machine learning (ML) interpretability into positive matrix factorization (PMF) and probability health risk assessment (PHRA) based on the Monte Carlo simulation. The results indicated that concentrations of soil PTEs except for Mn and Sb were significantly higher than their corresponding background values. Random forest (RF) was regarded as the best ML model to identify key drivers for As, Cd, Cr, Cu, Ni, Pb, and Zn, with R² > 0.60, but was less effective for other soil PTEs (R² < 0.49). Specifically, the contributions of the four potential pollution sources were mixed sources, traffic emission, fuel combustion, and building materials, with contribution rate of 24.88%, 30.56%, 28.99%, and 15.56%, respectively. Fuel combustion contributed the most to non-carcinogenic for children (39.45%), male (43.84%), and female (43.76%), and the non-carcinogenic risk could be considered negligible for human. However, building materials was the major contributor to carcinogenic risk for children (36.1%), male (44.9%), and female (43.2%). The integration of the RF model with PMF and PHRA improved the accuracy of the results by identifying and quantifying the specific sources of each soil PTE using the relative importance analysis from the RF model. The results of this study assisted in providing efficient strategies for risk management and control of soil PTEs in Beijing parks.

Assessing local air quality using traditional methods, such as analyzing precipitation composition, is often difficult due to the complex data, which is influenced by a variety of chemical elements from distant atmospheric sources and cyclone formation areas. This study presents a new approach to overcome these challenges: a multi-elevation sampling method that improves the accuracy of local air quality measurements. By collecting precipitation samples at different ground elevations, the technique takes advantage of the natural process where raindrops and snowflakes collect more elements as they fall through the air. This method helps to distinguish local air quality from background levels found at higher, non-industrial elevations. The primary goal was to isolate and identify the elemental fingerprints of marine influences, while excluding contributions from cyclones. In February 2023, 51 meltwater samples were collected from 17 observation points in the city of Sochi under southeast wind conditions. These samples revealed a spectrum of chemical elements, predominantly of marine origin (Mg > Na > Sr > Ca > K > Ce > Mn). The results showed significant differences in elemental concentrations between upland and coastal areas. The Geochemical Indicator of Marine Origin (GIM) ranged from 22 to 3235, confirming the strong influence of marine aerosols in the area. These findings demonstrate the effectiveness of the multi-elevation sampling method in providing robust environmental assessments. This approach, combined with the GIM index, offers valuable insights for improving environmental policies and public health, particularly in coastal regions affected by marine aerosols.

Herbicides are widely recognized as the most cost-effective solution for weed control, but their extensive use in both urban and agricultural settings raise serious concerns about nontarget effects. We assessed the possible hazards associated with pre-emergence herbicides such as dimethenamid-P, metazachlor, and pyroxasulfone, which are frequently applied in both urban and agricultural soils. The dissipation rate constant values (k day^-1: 0.010-0.024) were positively linked to total organic carbon (TOC), silt, clay, soil pH, and Al and Fe oxides, but negatively correlated with sand content. In contrast, half-life values (DT₅₀: 29-69 days) of the herbicides showed negative correlations with TOC, clay, silt, soil pH, and Fe and Al oxides, while sand content showed a positive impact. The selected herbicides showed minimal impact on soil dehydrogenase activity (DHA). Mostly, soils with higher organic matter (OM) content exhibited increased DHA levels, highlighting the role of OM in influencing this soil enzyme across different soils. Assessment of environmental indicators like groundwater ubiquity score (GUS:1.69-6.30) and leachability index (LIX: 0.23-0.97) suggested that the herbicides might reach groundwater, posing potential risks to nontarget biota and food safety. Human non-cancer risk evaluation, in terms of hazard quotient (HQ < 1) and hazard index (HI < 1), suggests minimal or no risks from exposure to soil containing herbicide residues at 50% of the initial concentrations. Our data thus help the stakeholders and regulatory agencies while applying these pre-emergence herbicides in soils and safeguarding human and environmental health.

Molybdenum (Mo) plays an important role in maintaining plant growth and human health. Assessment studies on the driving factors of Mo migration in soil-crop systems are crucial for ensuring optimal agricultural and human health. The Mo bioconcentration factor (BCF-Mo) is a useful tool for evaluating Mo bioavailability in soil-crop systems. However, the influence pathways and degrees of different environmental factors on BCF-Mo remain poorly understood. In this context, 109 rhizosphere and maize grain samples were collected from the Longitudinal Range-Gorge Region (LRGR) in Linshui County, Sichuan Province, China, and analyzed for the contents of Mo and other soil physiochemical parameters to explore the spatial patterns of BCF-Mo and its driving factors. Areas with the highest BCF-Mo values were mainly observed in the southern and northern parts of the Huaying and Tongluo mountains. The influence degrees of the selected environmental factors in this study followed the order of normalized difference vegetation index (NDVI) < elevation (EL) < mean annual humidity (MAH) < slope (SL) < mean annual temperature (MAT). The MAH and NDVI directly influenced the BCF-Mo values. The EL and MAT mainly indirectly affected the BCF-Mo values by influencing the rhizosphere organic matter (OM) contents, while the SL mainly affected the BCF-Mo values by influencing the rhizosphere pH. Therefore, OM and pH of the rhizosphere were the main influencing factors of BCF-Mo in the study area. In summary, the selected environmental factors mainly exhibited indirect influences on BCF-Mo by directly affecting the physicochemical properties of the rhizosphere.