Environmental Science: Processes & Impacts最新文献

Recently developed multi-element methods for filtered and unfiltered river water enable the analysis of 67 elements in a single analytical run, facilitating the assessment of multi-element fingerprints in monitoring programs. To elucidate the occurrence and possible pathways of emerging contaminants, it is essential to have baseline data for as many elements as possible to detect anomalies at specific environmental events. However, the variability of element concentrations in river water on the temporal and spatial scale is only poorly understood, causing considerable uncertainty for river water monitoring. Therefore, we conducted comprehensive sampling campaigns to assess the spatiotemporal variabilities of element concentrations in the river Rhine (Germany) at different discharge levels. Both, the long-term temporal (one-year data) and the spatial variability data revealed a distinct behavior of two element groups in relation to the discharge: elements showing a dilution effect (e.g.: B, Mg, S, K, Ca, Br, Sr, Mo, and U) or a co-rising effect (e.g.: Al, Si, P, Ti, V, Mn, Fe, Ni, Cu, Ga, As, Rb, Y, Cs, Ba, La, Ce, Pr, Nd, Sm, Gd, Pb, and Th) with higher discharge in the unfiltered river water. However, certain elements such as K, Ba or Gd displayed a variable behavior throughout the dataset, underlining the importance of collecting enough baseline data from various locations and conditions to detect anomalies. The analysis of unfiltered water samples in comparison with the filtered fraction allowed us to detect opposite behavior between the dissolved and particulate fractions for Co, Ni, As, Rb, Cs, and Gd. Cross-profile measurements were conducted to investigate spatial variabilities, revealing that lateral spatial gradients in element concentrations (up to a factor of 4) are more pronounced than depth gradients, likely caused by insufficient mixing of river influents or point-sources. Thus, fixed monitoring stations or single-point sampling for long-term data acquisition might not be able to capture the whole picture regarding element behavior in rivers.

Microplastics have become a major focus of research in environmental chemistry; over the past decade, microplastic sampling has shifted from marine and large lake settings to areas such as wastewater treatment plants, inland lakes, and rivers, which present various environmental sampling challenges due to more enriched and complex sample matrices. This study highlights the various methods that are used in microplastic sample processing, tests a new methodological approach to address the matrices found in a series of inland lakes in Minnesota, United States, and investigates the FTIR spectra and potential library misidentification of natural matrix materials, such as plant waxes and bird feathers that sometimes survive oxidative treatments. Specifically, the new methodological approach incorporates the use of ethanol to address lipid-rich organic materials and an additional filtering step following Fenton oxidation to separate the retained plastics from smaller clay matrix materials and avoids the use of enzyme digestion. This method was validated through a series of particle recovery tests and method blanks, which highlighted minimal to no particle loss and small amounts of fragmentation/discoloration. Further testing confirmed that the method exhibits low to negligible contamination levels. We determined that plant wax materials are not removed in sample processing and are often misidentified as plastic polymers within library searches. However, we identified distinguishable, albeit small, spectral differences from plastics, which may require adjusting libraries and adding to training sets for AI identification of plastics. Overall, this study has resulted in an adaptable sample processing workflow to ensure robust and accurate assessment of microplastic contamination in a variety of environmental compartments.

Polyethylene nanoplastics (PENPs) accumulate in soil, presenting significant environmental risks. However, research on the transport behavior of PENPs in soils remains limited. In this study, we employed saturated column experiments to systematically examine the transport of PENPs in two contrasting soil types, black soil (BS) and brown earth (BE), while evaluating the critical effects of ionic strength (IS), pH, and flow velocity. The results indicated that PENP mobility increased with higher flow velocity (1–5 mL min⁻¹), lower IS (1–10 mM NaCl/CaCl₂), and higher pH (5–9) in both soils. Notably, PENPs exhibited significantly greater transport capacity in BS compared to BE. Under identical IS and pH conditions, BS exhibited higher surface negative charges and more negative zeta potential than BE. DLVO theory calculations confirmed stronger electrostatic repulsion between the negatively charged PENPs and BS, resulting in significantly enhanced transport capacity and reduced deposition compared to BE. These findings demonstrate that soil surface charge critically governs PENP transport and provide a mechanistic foundation for assessing the mobility and ecological risks of nanoplastics in soils with distinct physicochemical properties.

The atmospheric particulate matter (PM) and bioaerosol concentration in agricultural sites varied with agricultural activities and plantation type. In this study, the mass and elemental and ionic composition of PM₁₀ and PM_2.5 were examined at three agricultural sites cultivating Andrographis paniculata, Ocimum basilicum and Ocimum sanctum. The bacterial colony-forming units (CFU) and dominant bacterial species present in PM₁₀ were also examined at three sites. PM₁₀ concentrations ranged from 138.20 to 309.60 μg m⁻³, while PM_2.5 varied between 50.05 and 165.15 μg m⁻³. Elemental analysis revealed the dominance of crustal elements (Ca, Al, and B) along with trace levels of heavy metals (Pb, Cr, and Cd), while the ionic composition was dominated by Ca²⁺, K⁺, NH₄⁺, Cl⁻, SO₄²⁻, and NO₃⁻, indicating agricultural and combustion-related sources. Source apportionment analysis revealed that PM_2.5 was more influenced by secondary aerosols and combustion-related emissions, while PM₁₀ was associated with biological and crustal components. Bioaerosol concentrations ranged from 5.87 to 7.11 log CFU m⁻³, with Bacillus sp., Pantoea sp., and Pseudomonas sp. identified as the dominant bacterial species. A significantly lower load of these bacterial species in bioaerosols at the site cultivating Ocimum sanctum was observed. Overall, the source apportionment demonstrates that agricultural activity is a key source of particulate matter and regulates the concentration of particulate matter in the air.

Organophosphate esters (OPEs) are ubiquitous endocrine-disrupting chemicals that have been frequently detected in metropolitan river systems. However, the distinctions in OPE sources and water–sediment dynamics between urban and suburban rivers remain poorly understood. In this study, the occurrence of 5 alkyl organophosphate esters (alkyl-OPEs), 4 aryl organophosphate esters (aryl-OPEs), 3 chlorinated organophosphate esters (Cl-OPEs), and 2 oligomeric organophosphate esters (oligomeric-OPEs) was investigated in water and sediments of 4 urban rivers and 2 suburban rivers in the Pearl River Basin, South China. All these compounds were found in both types of rivers. In the water phase, OPE occurrence was primarily influenced by dissolved oxygen and chemical oxygen demand, while in the sediment phase, it was mainly associated with total organic carbon. Sediment density was another dominating factor in only suburban rivers. Additionally, log K_ow largely governed the OPE partitioning behaviors in both rivers. The source attribution analysis revealed domestic emissions as the primary source for urban rivers and industrial emissions for suburban rivers. Furthermore, triphenyl phosphate (TPHP), tris(chloro-2-propyl)phosphate (TCIPP), and tris(1,3-dichloro-2-propyl)phosphate (TDCIPP) had high ecological risks in sediments of certain sites, highlighting the necessity of OPE management in sediments. These results will deepen our understanding of the OPE contamination in metropolitan river systems.

Pharmaceutical contamination in the environment poses a global concern, raising questions about potential implications for both ecology and human health. Unravelling the fate and exposure of these contaminants is crucial, as it depends on various factors, including their physicochemical properties, metabolic pathways, breakdown processes (e.g., oxidation and hydrolysis), and environmental conditions. Applying model-based approaches to assess the fate and exposure of pharmaceuticals is essential for evaluating their potential risks and impacts on the environment and public health. This paper reviews the state-of-the-art models used to predict the environmental fate and exposure of pharmaceuticals, focusing on sources, theoretical frameworks, comparative analyses of existing models, and factors such as polarity, metabolism, and breakdown processes. Additionally, the paper identifies current challenges and outlines future directions in this field.

Understanding oil spill behavior in estuarine and coastal systems requires knowledge of oil–mineral aggregate (OMA) formation, as this process significantly governs the transport of floating oil. Current understanding of OMA formation remains superficial, lacking in-depth analysis of underlying micromechanisms. Moreover, existing models rely solely on mineral concentration, resulting in limited applicability. In this study, the aggregation between moderately dispersed oil and various minerals was investigated through mesoscale simulation experiments conducted in a wave tank. Physicochemical and morphological analyses confirmed the van der Waals, electrostatic, and impact forces between oil droplets and minerals. Their relative contributions under varying conditions were qualitatively assessed. Furthermore, a new oil-attenuation equation under particle intervention was proposed, and the coupling of the oil spill dispersion model and the OMA density prediction model was achieved. Based on the experimental data, the expression of the integrative coefficient (α) in relation to the key characteristics of minerals was derived. The new model can accurately predict the time-dependent oil sedimentation at high mineral concentrations. These results can offer technical support for maritime management and marine environmental protection departments to quantitatively evaluate the settlement degree and hazard scope of coastal oil spills.

Valvular heart disease (VHD) is a common cardiovascular disease, particularly among the elderly, and its social burden is increasing with the aging population in China. Numerous studies have shown that trace element imbalances and exposure to metals and metalloids may negatively affect the cardiovascular system. However, studies on the effects of exposure to mixed metals and metalloids on VHD are limited, and the existing evidence is inconsistent. Therefore, we investigated the concentrations of 12 metals and metalloids in the urine of VHD patients and healthy adults from China based on a case–control study, while also exploring the single and combined effects of these metals and metalloids on VHD. The results showed that zinc (Zn) and strontium (Sr) concentrations were the highest in both case and control groups. Compared to controls, VHD patients had significantly higher urinary concentrations of manganese (Mn), cobalt (Co), Zn, cadmium (Cd), mercury (Hg), and lead (Pb), along with lower concentrations of lithium (Li), copper (Cu), and thallium (Tl) (P < 0.05). Furthermore, logistic regression analyses showed that urinary concentrations of Li, Mn, Cu, Zn, Sr, Hg, Tl, and Pb were positively associated with the heightened risk of VHD. The Bayesian Kernel Machine Regression model further revealed a strong positive correlation between multiple metal and metalloid exposure and the incidence of VHD. Notably, Pb and Hg were potential risk factors for VHD, while Li and Cu may be protective factors. More epidemiologic investigations and toxicological studies are needed in the future to explore and validate the negative effects of metals and metalloids on VHD.

Biochar is widely used in agriculture and pollution remediation, but its effect on soil carbon cycling balance remains uncertain. Due to the growing interest in biochar-induced priming effects, which can inhibit or promote mineralization that affects carbon cycling, assessing its carbon stabilization and mechanisms is essential. This carbon-rich byproduct of biomass pyrolysis enhances carbon sequestration and reduces CO₂ emissions through its stable aromatic structure and soil interactions, though its efficiency is limited by environmental, physicochemical and technological thresholds. Discrepancies among short-term experimental/model predictions and natural conditions suggest that current research may underestimate carbon oxidation risks by over-reliance on laboratory conditions and neglecting the complexity of natural environments. Negative priming effects arise only under specific conditions. Furthermore, the trade-off between biochar pyrolysis technology and energy recovery poses a significant challenge. This review critically analyzes the key mechanisms through which biochar stabilizes soil organic carbon, in accordance with the bidirectionality of priming effects. Key mechanisms include: (i) physical protection of organic–mineral complexes and soil aggregation; (ii) chemical stability of aromatic polymer condensation and oxidized biochar; and (iii) microbial metabolism and transformations of plant-derived carbon. Future research should clarify the molecular transformation mechanisms of soil carbon from various sources after biochar application, using diverse analytical techniques. Additionally, it should focus on developing biochar application systems tailored to different field conditions and regional soil characteristics. This review provides a theoretical framework for optimizing biochar's carbon sequestration pathways and establishes a scientific foundation for the development of technologies for carbon reduction.

Groundwater salinisation in inland water-scarce areas exacerbates various ecological, environmental, and social issues. To obtain a comprehensive understanding of the primary mechanisms driving groundwater salinisation and the baseline water quality in the Ulungur River Basin (URB), this study integrated hydrochemical analysis, geostatistical methods, and multivariate statistical techniques. In addition, rational recommendations for the sustainable exploitation and protection of water resources were proposed. Analysis of the dissolved components revealed that groundwater chemistry was predominantly influenced by Na⁺ (365.62 mg L⁻¹), Ca²⁺ (205.91 mg L⁻¹), Mg²⁺ (62.18 mg L⁻¹), Cl⁻ (276.96 mg L⁻¹), and SO₄²⁻ (817.45 mg L⁻¹). Groundwater in the Low Mountain region was categorised as freshwater, which gradually turned to saline water in the Lacustrine Plain along the flow direction, with hydrochemical types evolving from HCO₃·SO₄–Na·Ca and SO₄·HCO₃–Na·Ca (Mg) to SO₄–Na·Ca and SO₄·Cl–Na·Ca. Principal component analysis identified four principal components (PCs) that collectively accounted for 80.53% of the total cumulative variance in the key determinants of groundwater salinisation. PC1 represented water–rock interactions (which included carbonate and evaporite dissolution or precipitation and cation exchange). PC2 represented the degradation of organic matter and the application of farm manure. PC3 was associated with the return flow of irrigation water and lateral recharge. PC4 involved domestic sewage discharge and fertiliser application. The calculated values of the water quality index indicated that 47% of the samples, classified as having either excellent or good water quality, were suitable for drinking. Furthermore, the results of the permeability index, sodium adsorption ratio, residual sodium carbonate, and potential salinity indicated that both river water and groundwater within the riparian zone were safe and suitable for irrigation purposes. Overall, reducing river water extraction, upgrading agricultural production technologies, and enhancing domestic sewage treatment capacities are key strategies for protecting water resources in the URB.