Science of the Total Environment最新文献

The work aims to estimate natural greenhouse gas emissions from soils in the Sibari Coastal Plain (Southern Italy), to understand (i) the contribution in terms of the total amount of CO₂ and CH₄ emitted in non-volcanic areas, (ii) the relationship among emitted gas, land use, organic matter and tectonic structures, and (iii) their potential environmental implications. Data were elaborated with statistical and geostatistical methods to separate the different populations and obtain prediction and probability maps. Methane fluxes had values consistently below the detection limit (0.032 g ∙ m^-2 ∙ d^-1) except for three measurement points randomly distributed along the plain. Statistical and geostatistical methods allowed to discriminate three main CO₂ flux populations: (i) high-flux population (Pop. B - mean value of 63.65 g ∙ m^-2 ∙ d^-1), located near the mouth of the Crati River and related to the massive presence of buried organic matter in the form of peat; (ii) medium-flux population (Pop. A2 - mean value of 8.37 g ∙ m^-2 ∙ d^-1) which is the result of soil respiration, and (iii) low-flux population (Pop. A1 - mean value of 1.85 g ∙ m^-2 ∙ d^-1) due to areas where low permeability or increases in saturated aquifer thickness may control the overall flux. In the study area, a total CO₂ emission of about 2671 t ∙ d^-1 was calculated, which, if compared to the average total flux expected for simple soil respiration (1284 t ∙ d^-1), represents a non-negligible value in the total Carbon balance. Finally, the comparison with representative normalized fluxes from volcanic and non-volcanic areas confirms the critical role of coastal plains in total atmospheric CO₂ emissions. The proposed approach can be applied to areas with comparable or different geological and climatic settings to trace their contribution in terms of greenhouse gas release to the atmosphere.

In the face of the climate change crisis, circular economy (CE) is put forward as a promising key to the sustainable development goals (SDGs) riddle. In this context that affects developed and developing countries alike, circular initiatives arise, such is the case for Morocco where an industrial synergy based on the CE concept of 'waste is food' can be envisioned between the local phosphate and cement industries. In order to support and guide this initiative, a life cycle assessment (LCA) was conducted to compare the environmental performance of the production of ordinary Portland cement (OPC), limestone calcined clay cement (LC3) and a phosphate waste-based cement known as calcined marl cement (CMC). In addition to a mass-based functional unit (FU), a performance-based FU was adopted to account for the 'longer service lives' concept of CE, which necessitated the estimation of cements' service lives and CO₂ uptake potentials. Results show that CMC and LC3 production respectively reduce impacts on global warming by 23 % and 60 %, while the country aims for a 18.3 % reduction by 2030; mineral resource scarcity is reduced by 30 % and 48 %; and other impacts by 10 % and 40 % compared with OPC. This is chiefly due to CMC and LC3's better durability performance and lower clinker content. Using LCA results, carbon tax was pre-estimated to drop by 9 and 18$/ton of cement for CMC and LC3. A life cycle costing and a social LCA must be conducted to comprehensively guide stakeholders in their decision-making process regarding a phosphate-cement synergy.

6-PPDQ is a new type of environmental contaminant contained in tire rubber. No studies have been reported on the potential targets and mechanisms of action of 6-PPDQ on renal tissue damage. In the present study, we used CKD as an example to explore the potential targets and biological mechanisms of renal injury caused by 6-PPDQ using Network toxicology and animal experiments. A total of 1361 6-PPDQ-related target genes were obtained from the CTD database. 17,296 CKD-related target genes were obtained through the GeneCards database. After intersecting the two, a total of 908 intersecting genes were obtained. Next, we constructed a PPI protein interaction network. Using different algorithms in Cytoscape software and "Logistic regression analysis", five key target genes were finally identified as NOTCH1, TP53, TNF, IL1B and IL6. We constructed a diagnostic model using five key target genes, and the ROC curves, calibration curves and DCA curves proved that the model has good diagnostic value. Molecular docking demonstrated high affinity between 6-PPDQ and five key target gene proteins. In animal experiments, repeated intraperitoneal injections of 6-PPDQ using different concentration gradients for 28 days revealed that the expression levels of five key target genes in renal tissues increased progressively with the increase of the concentration, and the damage to renal tissues was also aggravated. ssGSEA and animal experiments revealed a key role for activation of the MAPK signaling pathway. Finally, we also identified a significant correlation between five key target genes and the level of infiltration of multiple immune cells. In conclusion, these findings suggest that 6-PPDQ can cause damage to renal tissue and that the level of damage progressively increases with increasing concentration. Among them, NOTCH1, TP53, TNF, IL1B and IL6 may be its potential targets of action. Activation of the MAPK signaling pathway is a potential mechanism of action.

This study investigated the regenerability of anion exchange resins for per- and polyfluoroalkyl substances (PFAS), focusing on the interaction between regenerant composition and resin characteristics. The influence of salt type and concentration on PFAS solubility revealed a general decline in perfluorohexane sulfonate (PFHxS) solubility with increased salt concentrations, most strongly with KCl followed by NaCl and NH₄Cl. Mixed solubility results were observed for perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS). Three resins - A592E and USA291597EPF (strong base resins) and USA21107 (weak base resin) - were evaluated using aqueous and organic solvent regenerants across multiple cycles. Batch regeneration experiments demonstrated that regeneration effectiveness was higher for short chain perfluoroalkyl carboxylates (PFCA) compared to long chain PFCA, followed by n:2 fluorotelomer sulfonates (FtS) and perfluoroalkane sulfonates (PFSA). Chloride-based salts regenerants were more effective, while the type of cation had minimal impact. Organic solvent regenerants outperformed aqueous solutions, with effectiveness increasing at higher percentages. For low organic solvent percentages, acetone demonstrated higher effectiveness compared to ethanol and methanol. Resin regenerability ranked as follows: USA291597EPF > A592E > USA21107. Flow through column studies confirmed the dependency of regeneration effectiveness on PFAS structural characteristics, with shorter chain PFCA demonstrating higher efficiency. The Lin and Huang model's parameters, time to desorb 50% of resin-associated PFAS (τ) and the column constant (k_c), revealed two distinct desorption phases. The findings highlight the crucial role of regenerant composition in optimizing resin regeneration, offering valuable insights for developing more effective PFAS remediation strategies.

Human overexploitation contributed strongly to the loss of hundreds of bird species across Oceania, including nine giant, flightless birds called moa. The inevitability of anthropogenic moa extinctions in New Zealand has been fiercely debated. However, we can now rigorously evaluate their extinction drivers using spatially explicit demographic models capturing species-specific interactions between moa, natural climates and landscapes, and human colonists. By modelling the spatial abundance and extinction dynamics of six species of moa, validated against demographic and distributional inferences from the fossil record, we test whether their extinctions could have been avoided if human colonists moderated their hunting behaviours. We show that harvest rates of both moa birds (adults and subadults) and eggs are likely to have been low, varying between 4.0-6.0 % for birds and 2.5-12.0 % for eggs, annually. Our modelling, however, indicates that extinctions of moa could only have been avoided if Polynesian colonists maintained unrealistically expansive no-take zones (covering at least half of New Zealand's land area) and held their annual harvest rates to implausible levels (just 1 % of bird populations per annum). Although too late for moa, these insights provide valuable lessons and new computational approaches for conserving today's endangered megafauna.

Polyethylene nanoplastics (NPs) are widely diffused in terrestrial environments, including soil ecosystems, but the stress mechanisms in plants are not well understood. This study aimed to investigate the effects of two increasing concentrations of NPs (20 and 200 mg kg^-1 of soil) in lettuce. To this aim, high-throughput hyperspectral imaging was combined with metabolomics, covering both primary (using NMR) and secondary metabolism (using LC-HRMS), along with lipidomics profiling (using ion-mobility-LC-HRMS) and plant performance. Hyperspectral imaging highlighted a reduced plant growth pattern. Several vegetative indexes indicated plant toxicity, with 20 mg kg^-1 NPs significantly decreasing lettuce density and vegetation health (as indicated by NDVI and plant senescence reflectance indexes). Consistently, photosynthetic activity also decreased. At the biochemical level, metabolomics and lipidomics pointed out a multi-layered broad biochemical reprogramming of primary and secondary metabolism involving a decrease in sterols, sphingolipids, glycolipids, and glycerophospholipids in response to NPs. The reduction in phosphatidylinositol coincided with an accumulation of diacylglycerols (DAG), suggesting the activation of the phospholipase C lipid signaling pathway. Moreover, nanoplastic treatments down-modulated different biosynthetic pathways, particularly those involved in N-containing compounds and phenylpropanoids. Our mechanistic basis of NPs stress in plants will contribute to a better understanding of their environmental impact.

The oceanic dissolved organic matter (DOM) reservoir is one of Earth's largest carbon pools, yet the factors contributing to its recalcitrance and persistence remain poorly understood. Here, we employed ultra-high resolution mass spectrometry (UHRMS) to examine the molecular dynamics of DOM from terrestrial, marine and mixed sources during bio-incubation over weekly, monthly, and one year time spans. Using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), we classified DOM into three distinct categories (Consumed, Resistant and Product) based on their presence or absence at the start and end of the incubation. Our results show that molecular properties, such as hydrogen to carbon ratio (H/C), modified aromaticity index (AI_mod), and nominal oxidation state of carbon (NOSC), strongly influence DOM lability and its biogeochemical cycling. Interestingly, Product formulas identified in the short-term incubations were often reclassified as Consumed formulas in longer-term incubations, underscoring the importance of incubation time in determining the persistence of DOM formulas. Further, we introduced a Change Ratio (CR) to identify formulas with significantly altered relative abundances. The molecular characteristics of these Increase or Decrease formulas exhibited notable differences, reinforcing their role in determining lability. In seawater samples, Decrease formulas were more abundant than Increase formulas, supporting the dilution hypothesis, which suggests low concentrations contribute to biological recalcitrance. However, the instability of relative abundance differences between Increase and Decrease formulas when CR thresholds were altered, coupled with the robustness of AI_mod differences, highlights the dominance of molecular properties over concentration in determining DOM lability. Furthermore, the AI_mod distribution of these Increase and Decrease formulas mirrored deep-enriched and surface-enriched formulas in the open ocean, validating our incubation results with field investigations. Overall, our study demonstrates that combining laboratory incubation with UHRMS advances our molecular-level understanding of DOM recalcitrance and thus global carbon cycling.

Concentrated animal feeding operation facility in modern livestock industry is pointed out as a point site causing environmental pollution due to massive generation of manure. While livestock manure is conventionally treated through biological processes, composting and anaerobic digestion, these practices pose difficulties in achieving efficient carbon utilization. To address this, this study suggests a pyrolytic valorization of livestock manure, with a focus on enhancing syngas production. Hen manure was particularly chosen due to its abundance of calcium carbonate (CaCO₃) compared to other mammalian livestock, exhibiting distinctive thermolytic behaviours. The thermolysis of CaCO₃ in hen manure releases carbon dioxide (CO₂), simultaneously served as a partial oxidant for the carbon monoxide (CO) enhancement. To further evaluate the effectiveness of CO₂, hen manure was pyrolyzed under the presence of CO₂. The use of CO₂ demonstrated a gas-phase interaction with hen manure-derived volatiles, re-allocating the pyrogenic products into CO-rich syngas. To accelerate the reaction kinetics of CO₂, catalytic pyrolysis over a supported Ni catalyst was conducted, further enhancing CO-rich syngas. To assess the environmental advantages, the carbon footprints under various pyrolysis conditions were estimated by confirming the energy consumption and CO₂ mitigation potential of pyrogenic products. Therefore, this study highlights that the CO₂-mediated pyrolysis of hen manure globally generated offers a potential to mitigate 934.67 million tons of CO₂ in annual.

Microplastics (MP) are known to be ubiquitous. The pathways and fate of these contaminants in the marine environment are receiving increasing attention, but still knowledge gaps exist. In particular, the link between mass-based MP quantification and oceanographic parameters is often lacking. In this study, we aim to interconnect different parameters for the first time through in-situ measurements with an autonomous surface vehicle in the German Bight. It simultaneously sampled air, sea surface microlayer, and underlying water for analysis of MP and additionally, extracellular polymeric substances (only in water). These compounds, secreted by microorganisms, can interact with particulate matter, influencing their transport dynamics and aggregation behavior in the environment. During the entire sampling, a weather station and conductivity, temperature, and depth sensors were installed on the vehicle. Depth profiles were taken with an accompanying research vessel to learn more about the stratification and horizontal processes of MP in the marine environment. Additionally, an acoustic Doppler current profiler recorded water current velocities and flow direction. A relationship was found between wind direction and the presence of MP in the atmosphere. Furthermore, wind speeds may seem to increase heterogeneity in both the composition and concentration of MP in the water. A tentative correlation between extracellular polymeric substances and MP was documented. Investigating horizontal and vertical velocities of currents within the surface and the water column helped to explain the distribution of MP. Up- and downwelling processes corresponded to the accumulation of MP along density fronts and across depth profiles.

Assessing future snow cover changes is challenging because the high spatial resolution required is typically unavailable from climate models. This study, therefore, proposes an alternative approach to estimating snow changes by developing a super-spatial-resolution downscaling model of snow depth (SD) for Japan using a convolutional neural network (CNN)-based method, and by downscaling an ensemble of models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset. After assessing the coherence of the observed reference SD dataset with independent observations, we leveraged it to train the CNN downscaling model; following its evaluation, we applied the trained model to CMIP6 climate simulations. The downscaled mean ensemble reproduced the spatial distribution and seasonality of the reference observations. We found an average decrease in the snow-covered area by about 20 % in winter and 25 % in early spring, an altitude-dependent of the SD changes, and a delayed snow cover appearance by the middle of the 21st Century under a high emission scenario. Overall, the downscaling model captures physically plausible relationships, enables high-resolution assessments of future SD based on a multi-model ensemble, produces results consistent with regional climate models, and provides valuable insights into how future snow changes will affect winter tourism and water resources, highlighting its potential benefits for a wide range of adaptation studies.