Environmental Research最新文献

Heavy metal adsorption by soil particles significantly influences its pollution risk in global soil. However, the global distribution of soil adsorption ability is still lacking due to the difficulty of obtaining large-scale adsorption data. Here, we proposed a novel method to evaluate the adsorption ability in a global scale through predicting the distribution coefficient (K_d) of HMs in soil via machine learning and big data. Based on the data selected, which included soil properties, adsorption properties, and mineral contents, the Random Forest (RF) achieved prediction accuracies of 0.91, 0.85, 0.90, and 0.87 for K_d values of As, Cd, Cr, and Pb, respectively. The main factor influencing K_d values was found to be the mineral content. The corresponding contents of Fe_oxide, chlorite, and kaolinite exhibited significant positive correlations with As, Cd, and Cr, respectively. The pollution risk areas were further delineated based on the U.S. EPA metrics of K_d. It is noteworthy that the environmental risk areas of farmland on each continent exceed 20%, with Asia had 72%, 64% and 58% of the risk areas for As, Cd and Cr, which are obviously larger than those on other continents. Moreover, the distributions of these high - risk areas were consistent with those of the corresponding minerals below or close to the global mean contents. The approach proposed in this study enables the prediction of K_d values and pollution risk assessment of soils globally, revealing the impact of mineral heterogeneity on K_d values. These results are valuable for evaluating environmental risks and formulating soil remediation strategies.

This study presents an integrated co-exposure assessment of toxic metals and microplastics in 30 commercially available sports protein supplements in China by combining targeted analytical measurements with scenario-based and probabilistic health-risk modeling. Arsenic (As), cadmium (Cd), lead (Pb), and mercury (Hg) were quantified via closed-vessel microwave digestion and inductively coupled plasma mass spectrometry (ICP-MS), validated through duplicate analyses and reference materials. While all samples contained at least one target metal, plant-derived products exhibited higher mean Pb (0.18 mg/kg) and Cd (0.05 mg/kg) levels compared to dairy-derived products (0.06 and 0.01 mg/kg, respectively; P < 0.01). Notably, a brown rice and cocoa-flavored product emerged as an outlier (Pb 0.60 mg/kg; Cd 0.15 mg/kg; As 0.30 mg/kg), whereas Hg concentrations were predominantly <0.01 mg/kg, except for one collagen sample (0.02 mg/kg). Microplastic particles were isolated via peroxide-alkali digestion and identified by micro-Fourier transform infrared (μFTIR) and micro-Raman spectroscopy (μRaman). Microplastics were detected in all samples, ranging from 2 to 19 particles per 30 g serving (mean 8 ± 5); these were predominantly comprised of fibers (40-50%) and fragments (∼30%), with typical sizes of 100-500 μm and polymers including polyethylene, polypropylene, and polyethylene terephthalate. ** regarding exposure risks**, deterministic modeling yielded a hazard index (HI) of 0.45 for 30 g/day and 0.90 for 90 g/day (driven primarily by As and Cd), while Monte Carlo simulation (10,000 iterations) indicated a 95th-percentile HI of 1.28 under high-use conditions; predicted blood Pb increments remained <3 μg/dL. Collectively, these results offer a quantitative basis for prioritizing contaminant control in high-consumption scenarios and for informing athletes, manufacturers, and regulators about combined contaminant burdens. These findings align with emerging evidence of ubiquitous microplastic presence in protein products and underscore the necessity for consumption-scenario-based risk evaluation regarding heavy metals.

Prussian blue analogs (PBAs) worked well as activators for peroxymonosulfate (PMS). However, PBAs tended to fall short in electron transfer efficiency and degradation performance, which to a certain extent limited their practical use. In this study, Ni-Co-P, Ni-Co@Fe-P and Ni-Co@Fe-Co-P were synthesized by a combination of coprecipitation methodology and a phosphorylation procedure mediated by an interface-induced contraction mechanism. Ni-Co@Fe-Co-P enabled the degradation of tetracycline (TC) by PMS activation. Experiments showed that in the Ni-Co@Fe-Co-P/PMS system, the degradation efficiency of TC hit 96.4% within 20 min. Employing multiple techniques to characterize the physicochemical properties and catalytic performance of Ni-Co@Fe-Co-P, while also clarifying the reaction mechanism and assessing the catalyst's adaptability to different aquatic environments. In the Ni-Co@Fe-Co-P/PMS system, SO₄^•- and ^•OH were the main reactive species. Using HPLC-MS and T.E.S.T., this research analyzed and predicted the intermediate substances during TC's degradation and their biological toxicity. This research provided guidance for the development of efficient, stable and economically viable catalytic materials for PMS activation to support environmental purification efforts.

The accumulation of microplastics in marine environments poses a significant ecological threat. This study reports the isolation and characterization of a marine-derived fungus, Cladosporium oxysporum SCSIO 81042, capable of degrading polyurethane (PU) under seawater conditions. Through tiered screening, the strain was selected based on its superior hydrolysis activity against Impranil® DLN and solid poly(1,4-butylene adipate) PBA-based PU (PBA-PU). The strain demonstrated exceptional adaptability to seawater conditions, with optimal growth at 15-28 °C, ∼3% salinity, and pH 7.5-8.0. Under simulated seawater salinity, it degraded 94.5% of Impranil® DLN within four days in simulated seawater while maintaining sustained activity over two successive cycles. In natural seawater, near-complete degradation of 0.1% Impranil® DLN was achieved within 7 days, and the degradation products showed negligible developmental toxicity to zebrafish. Notably, this efficiency successfully translated to a 10-L seawater mesocosm, where most Impranil® DLN was degraded within 7 days. The strain also caused structural damage to solid PBA-PU films and PU foam under simulated seawater salinity after 14 days, although no significant weight loss was observed. Metabolite analysis confirmed its ability to hydrolyze both ester and urethane bonds in PBA-PU. Furthermore, chitosan nanoparticle (CS-NP) was introduced as an adhesion adjuvant, enhancing degradation across all tested PU substrates, potentially through facilitated microbial adhesion and substrate contact. While challenges remain regarding degradation of complex PU foams, CS-NP environmental fate, and microbial competition, this work establishes C. oxysporum SCSIO 81042 and the CS-NP adjuvant strategy as promising tools for the bioremediation of marine PU pollution.

The accessibility of surface water renders it vulnerable to contamination, particularly in alpine rivers characterized by high environmental sensitivity and eco-fragility. The Yarlungzangbo River (YR) is the largest-scale regional catchment in the southern Tibetan Plateau. River water quality is becoming an imperative issue that needs to be ascertained with increased human activities in recent decades. In this study, natural background levels (NBLs), novel water quality indices, and machine learning approaches were used to comprehensively evaluate the suitability of alpine surface water. The results of NBLs have revealed that the discrepancy of each hydrochemical indicator resulted from both natural processes and human activities. The novel irrigation water quality index (IWQI) has demonstrated that 64% in the upper reach (UR), 85% in the middle reach (MR), and 48% in the lower reach (LR) are deemed suitable for agricultural irrigation. Notably, the concentration of Na⁺ holds a predominant influence on the IWQI in both UR (7.82%) and LR (10.01%). Conversely, in MR, the Sodium Adsorption Ratio emerges as the primary factor, contributing 4.53% to the IWQI. The novel drinking water quality index (DWQI) demonstrated that 95% of samples are excellent for drinking. NO₃^- concentration is the most influential factor determining the DWQI in UR (9.63%), MR (8.25%), and LR (8.96%). Among four machine learning models, the convolutional neural network (CNN) was recognized as the robust algorithm to predict the IWQI (R²=0.9358) and DWQI (R²=0.9993) in the YR catchment. The research findings indicate that anthropogenic activities significantly contribute to water quality degradation in MR. This research presents an extensive suitability assessment of a typical alpine catchment at a large scale, serving as valuable information for water management in the Tibetan Plateau (Asian water tower).

The Northern Sandstorm Belt (NSbelt) of China is a key dust source region. Its dust activity directly affects regional ecological security and human settlements. Large-scale ecological restoration projects have significantly mitigated dust activity. However, the driving mechanisms of dust evolution under different precipitation backgrounds remain unclear. This study aims to systematically reveal PM10 evolution characteristics and dust activity driving mechanisms in the NSbelt from 2000 to 2023. The study first divided the NSbelt into four sub-regions: East, Central, Northwest, and Southwest. This division was based on geospatial location, desert distribution, hydrothermal conditions, and surface cover differences. Next, the study used the Mann-Kendall test and Sen's slope estimator to analyze PM10 evolution trends. A dust pollution identification method distinguished between dust-affected and dust-free days. Finally, a contribution attribution method quantified the relative contribution of fractional vegetation cover (FVC), precipitation (Pre), wind speed (Wind), and temperature (T) to dust activity. The results indicate: (1) PM10 across the entire region followed a significant fluctuating downward trend. The Central showed the most significant improvement (Sen's slope = -1.83). (2) The Southwest was an extreme dust pollution zone. It recorded 2,487 cumulative dust-affected days. The East was the least affected region. It maintained over 345 dust-free days annually. (3) Precipitation strictly constrained the driving mechanisms. In the 400-600 mm zone, dust was most sensitive to vegetation (-0.31). In the 50-100 mm hyper-arid zone, dust was most sensitive to wind speed (0.20). (4) Increased FVC was the dominant factor in regional dust reduction (relative contribution: 44.26-77.51%). This study reveals differentiated driving mechanisms of environmental factors under various hydrothermal backgrounds. These findings provide a vital scientific basis for future regional dust prevention and control strategies.

Seagrass beds are key blue-carbon ecosystems, yet their resilience is increasingly challenged by microplastic (MP) pollution and marine heatwaves (MHWs). We experimentally tested how these stressors, alone and combined, affect the seagrass Zostera marina (eelgrass) using a controlled mesocosm experiment grounded in multiple-stressor and trait-based ecological theory. Plants were grown for 43 days in sediments with or without polyethylene/polypropylene MPs and a simulated MHW, (+5°C for 15 days) was imposed in the final phase. MP exposure significantly reduced rhizome elongation (-35%), total root length (-65%), and below-ground biomass, and depleted non-structural carbohydrates (NSC) in leaves and rhizomes (-35% to -40%). Warming alone stimulated leaf growth but further reduced NSC, while the MP × MHW interaction produced the lowest below-ground growth and carbohydrate reserves, consistent with synergistic stress predicted by multiple-stressor theory. MP exposure also reshaped the microbiome enriching putative sulfur-cycling taxa in the rhizosphere and indicating more reducing sediment conditions. With a carbon-balance and holobiont framework, MPs appear to constrain resource supply (oxygen and nutrients) and increase maintenance costs, whereas warming amplifies metabolic demand. The resulting carbon deficit limits below-ground growth, traits that underpin restoration success and blue-carbon function. These findings show the importance of incorporating microplastic monitoring into seagrass management to anticipate cumulative stress under a warming ocean.

This study investigates sediment contamination related to emerging contaminants (ECs) in the marine environment of the Red Sea, a cornerstone of the Kingdom of Saudi Arabia's economic development. Sediment samples were collected throughout the Red Sea coastal and deep areas, to assess the occurrence, distribution, possible sources, and transport pathways of ECs. This is the first geographically comprehensive study of ECs in the Saudi Arabia's coastal and deep Red Sea marine environment, including the most important coastal hotspots and employing cutting-edge novel analytical techniques. This work provides useful insights to legislative parties in the framework of the Marine and Coastal Environment Protection Initiative (MCEP) for the assessment of the marine environment of the Red Sea. Generic sample preparation protocols were applied to extract a broad range of LC-amenable semi-polar to polar ECs and a hybrid trapped ion mobility tandem high resolution mass spectrometric technique was utilized. Subsequently, wide-scope target screening of more than 3100 ECs was conducted. In total, 55 ECs were determined belonging to 7 distinct chemical classes, including pharmaceuticals, pesticides, per- and polyfluorinated alkyl substances (PFAS), industrial chemicals, etc. The highest contaminant concentrations were found in Jeddah Mena and Jeddah Lagoon regions, with cumulative concentrations of ECs reaching up to 3.96 mg/kg d.w. and 10.77 mg/kg d.w., respectively, while some specific contaminants (e.g. PFOS, phthalates) were detected in the deep sediments of the Red Sea. Risk assessment showed that 12 compounds were at high ecological risk, highlighting the need for comprehensive monitoring of the coastal area.

Pesticide contamination poses a substantial threat to human health. Existing evidence has linked exposure to imidacloprid (IMI) with lipid metabolism disorders. Nevertheless, the mechanisms mediating IMI-induced aberrations in hepatic lipid metabolism and hepatocyte senescence remain incompletely elucidated-particularly the long-term impact effects of exposure at human-relevant doses, which are even less well characterized. To fill this research gap, we conducted a 24-week drinking water exposure experiment in mice using human-relevant doses of IMI (0, 0.015 μg/mL, 0.52 μg/mL, 0.033 mg/mL) to investigate the resulting hepatic lipid metabolism abnormalities and the regulatory role of hepatocyte senescence in this pathological process. Toxicological analyses showed that IMI exposure led to liver function impairment and histopathological changes in mice, induced abnormal hepatic lipid metabolism (p<0.05), and upregulated the expression of senescence-associated proteins in mice (p<0.05). Mechanistic investigations further revealed that the cGAS-STING pathway may mediate hepatocyte senescence, and inhibition of this pathway in HepG2 cells markedly alleviated cellular lipid metabolic disorders and senescence (p<0.05). The findings of this study demonstrate that IMI exhibits chronic hepatotoxicity at human-relevant exposure levels, emphasizing an urgent need for additional toxicological investigations based on human-relevant exposure levels to comprehensively evaluate the toxicity profile of neonicotinoids.

Using metakaolin (MK) as a supplementary cementitious material (SCMs) to enhance the early strength of supersulfated cement (SSC) is a feasible strategy. The effects of 0-30 wt% MK on the hydration thermodynamics, flowability, setting time, and mechanical properties of supersulfated cement (SSC) were evaluated. Characterization techniques, including ICC, XRD, FTIR, TG-DTG, and SEM-EDS, provided insight into how MK influences the performance and microstructural evolution of metakaolin-supersulfated cement (MSSC). The results indicate that MK accelerates the early hydration rate of MSSC by providing additional nucleation sites. The optimal MK content was found to be 25 wt%, with compressive strengths reaching 18.7 MPa at 3 d and 42.4 MPa at 28 d, reaching 122.22% and 208.87% of the MK0, respectively. Additionally, the pozzolanic activity of MK facilitated the formation of ettringite (AFt) and calcium aluminosilicate hydrate (C-(A)-S-H) in MSSC. By adjusting the Ca/Si and Al/Si ratios, the C-(A)-S-H structure was optimized, resulting in a denser matrix pore structure. These findings were further supported by phase composition and microstructure analyses. However, when the MK content reached 30 wt%, its excessive addition limited its reactivity due to insufficient portlandite in MSSC, leading to reduced compressive strength. This study identifies 25 wt% MK as the optimal dosage for enhancing SSC performance, improving early strength, and maintaining environmental sustainability.