Environmental science. Advances最新文献

During the recycling of polyethylene (PE)-based agricultural film waste, the presence of small amounts of polypropylene (PP)-containing films can significantly deteriorate the mechanical properties of the recycled material. This is primarily due to the immiscibility between PE and PP in such complex multiphase systems. Physical compatibilization is widely regarded as the most efficient and practical method for improving mechanical performance and interfacial adhesion in such mechanically recycled multiphase waste systems. In this study, propylene–ethylene elastomer (EPR) and ethylene–octene copolymer (EOC) were selected as physical compatibilizers for both binary model PE/PP blends and quaternary model recycled PEs/PPs blends. The blends consisted of virgin LLDPE, LDPE, and their mixtures as the major phase, combined with 10 wt% PP as the minor phase and 7% compatibilizer. The specific research strategy was to enhance mechanical performance in the presence of physical compatibilizers by inducing and/or modifying the morphological structures within the blends, supported by rheological analysis. The compatibilization effects were initially investigated through rheological and morphological analyses. A decrease in complex viscosity and storage modulus, particularly at lower frequencies, was found in small-amplitude oscillatory shear (SAOS) rheology, indicating improved interfacial compatibility between PE and PP. These findings were further supported by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), which revealed finer morphologies and significantly reduced dispersed domain sizes in both compatibilized systems. As a result of enhanced interfacial adhesion and the elastic features of the compatibilizers, notable improvements in impact resistance, tear resistance, and elongation at break were achieved. In summary, compared to EPR, EOC demonstrated superior compatibilization performance in the recycled blends, likely due to its ethylene/octene segmental structure, which exhibits greater chemical affinity with polyethylene. The ultimate target is to guide the mechanical recycling of contaminated plastic waste through establishing rheology-morphology-property relationships in complex multiphase systems. This study offers valuable insights into effective compatibilization strategies for complex multiphase polymer recycling systems.

The banning of single-use plastic food service items has led to a shift towards single-use, compostable alternatives. Globally, decision-makers are grappling with balancing the largely uncharacterised risk of compostable single-use food service items with the potential benefits of diverting additional food waste from landfills. To help close this gap in regulatory understanding, food service items were collected from semi-closed locations that only allow compostable items and analysed for their physical and chemical properties. Collected items represented the broad range of material and item types associated with ‘compostable’ single-use food service items, including food service vessels, straws, cutlery, napkins, sandwich bags and wraps. Analysis determined the likely systematic inclusion of perfluoroalkyl and polyfluoroalkyl substances (PFAS) across a range of sugarcane bagasse samples with a maximum detected concentration of 86 200 μg kg⁻¹. Additionally, food service item components such as plastic linings and lids were often found to contain common, non-compostable plastics. Findings indicate that at present, single-use plastic item bans have shifted manufacturers of single-use food service items towards material choices that do not possess viable resource recovery pathways. This paper emphasises the need for policymakers to consider likely market shifts and the risks associated with likely alternative materials prior to taking action on single-use plastic items.

Ether-based per- and polyfluorinated alkyl substances (PFAS) are increasingly used as alternatives to legacy PFAS due to their higher tendency to break down in natural settings. Among these, ADONA – a carboxylate ether-PFAS replacement species – is a prominent substitute for PFOA. However, despite its intended decrease in toxicological behavior, ADONA has been associated with some adverse effects in biological systems and is considered an emerging contaminant. Subsequent to employing ADONA for nearly two decades, these molecules are increasingly detected in environmental matrices, particularly near industrial sites. Consequently, there is an increased risk for human exposure through water sources. At the same time, soil minerals could play a central role in governing the leaching of ADONA from surface environments to groundwater. In this study, the influence of soil mineral components on the distribution and transport of ADONA in terrestrial environments has been investigated using molecular dynamics (MD) simulations. Three common clay minerals were chosen as models due to their distinct variations in both charge distribution and magnitude at their basal surfaces. The interfacial adsorption structures and dynamic properties of ADONA vary substantially between different mineral surfaces, and the adsorption mechanism strongly depends on the surface charge of the minerals examined.

Bisphenol A (BPA), a ubiquitous industrial material, is widely employed as a starting material in preparing epoxy resins and polycarbonate plastics. This compound is utilized on a very large scale around the globe. As this compound has been classified as one of the EDCs, substantial evidence has demonstrated a positive correlation between BPA exposure and developmental disorders in the fetal central nervous system as well as fetal neurodevelopment. Its exposure also affects memory formation and the normal functioning of the pituitary gland. Bisphenol has adverse effects on thyroxine, alternatively affecting fetal physical development. BPA also affects sexual behaviors and causes hypersexuality. In addition, BPA exposure leads to certain epigenetic and transgenerational effects. The main aim of our review is to highlight the impact of BPA on fetal neurodevelopment and mental behavior. It is essential to completely understand the mechanism of action of BPA on the molecular structure of interneurons and other neurons during fetal development due to BPA exposure. This will help in the evaluation of interneuron linkage and other neural activities along with brain development from the fetal stage to mature life. This review encompasses the literature available on the abnormal impacts of BPA on fetal development due to maternal exposure to BPA. We have surveyed the relevant literature to disseminate the information obtained through research carried out to reveal these impacts.

The quality of surface and drainage water is key for the health of nature; therefore, their contamination levels should be maintained under safe limits. This study focuses on water sampled from the Říčka tSream in the Czech Republic, which is contaminated mainly by nitrates and phosphates originating from fertilizers. Additionally, the content of heavy metals was monitored. The measured concentrations of Cd and Zn were below the limit of detection, while Cu and Pb remained below safe limits except during summer, likely due to the dry season. Concentrations of nitrates and phosphates exceeded the limiting values in all cases. Batch adsorption experiments using lignite were performed with both model solutions to determine adsorption capacity, which decreased in the order Pb > Cu > nitrates > phosphates. The experiments with real water samples from the Říčka Stream showed that lignite can effectively immobilize the studied pollutants. The adsorption efficiency was higher than 70% in all cases. The majority of the adsorbed pollutants remained in the immobilized forms both in the experiments with the model solutions and real water samples. An increased leachability was observed for nitrates; however, the equilibrium concentrations of nitrates after adsorption as well as their leachable form were under safe limits. Lignite can be considered an effective and low-cost adsorbent for the removal of pollutants from real water.

Pollution with PFASs is found in several types of environmental matrices across the globe. In groundwater, the occurrence is usually attributed to point sources like firefighting training areas, landfills or direct industrial use. During the last 15 years it has become clear that some PFASs are highly preconcentrated in sea spray aerosols and recently this was proposed to be a significant source of PFASs on land. To see if such a source is strong enough to affect groundwater, we analysed a nationwide dataset for PFASs in shallow wells. By focusing on wells located in forests or other nature areas, it became clear that groundwater within 5 km of the 400 km long Danish west facing North Sea coast is clearly affected by a diffuse PFAS source, most likely sea spray aerosols. PFOA dominated, but PFHxS was detected almost as frequently and the concentration ratio between these two PFASs was relatively constant. Four very shallow monitoring wells with 2–21-year-old groundwater were repeatedly sampled over 3–5 years, and all showed an almost constant concentration of PFOA, PFHxS, PFOS and PFBS. A screening of 60 PFASs showed that legacy PFAAs dominated wells affected by sea spray aerosols. The observed diffuse PFAS pollution in groundwater is most likely a world-wide coastal phenomenon, but additional studies are needed to achieve sufficient understanding of the drivers.

This study presents a comprehensive life cycle analysis of potential synthetic graphite battery anode material (BAM) production in the U.S. based on industrial-scale data. The analysis focuses on three impacts: greenhouse gas (GHG) emissions, total energy use, and water consumption. We also conducted sensitivity analyses to evaluate the effect of variation in process parameters and energy sources used for synthetic graphite BAM production on its life cycle GHG emissions. A detailed supply chain analysis of graphite BAM in the U.S. was also undertaken, along with a study of its associated GHG emissions. The results show GHG emissions of 29.7 kg CO₂-eq. per kg BAM, total energy use of 580 MJ kg⁻¹ BAM, and water consumption of 121 L kg⁻¹ BAM for the baseline condition. The graphitization step is a major process hotspot, contributing to over 74% of all impacts. This is attributed to the energy and material input requirements for this step, particularly through the use of crucibles. Across the entire synthetic graphite production process, electricity is the primary contributor, followed by crucibles used in graphite block production, and then calcined petroleum coke. Sensitivity analyses indicate that improvement in micronization yield, reuse of crucibles, and use of low-carbon nuclear energy can significantly reduce GHG emissions of potential domestic graphite production (by ∼70%). Supply chain analysis identified major graphite BAM sources in the U.S. and showed that the U.S. has a competitive advantage in domestic production of synthetic graphite BAM in terms of reduced life cycle GHG emissions compared to present-day imported sources (by ∼20%).

Environmental pollution from heavy metals and untreated wastewater poses significant risks to ecosystems and human health, highlighting the urgent need for innovative remediation strategies. Bioremediation employs microorganisms to break down contaminants and presents a sustainable and economical solution. However, conventional techniques such as bioaugmentation and bio-stimulation face challenges due to inefficiencies and the absence of real-time monitoring. This narrative review consolidates the latest developments in AI-driven bioinformatics aimed at enhancing microbial bioremediation, with an emphasis on the degradation of heavy metals and wastewater pollutants. Advanced computational models such as random forest, artificial neural networks, and support vector machines demonstrate high predictive accuracy (R² > 0.99) in analysing microbial behaviour and pollutant dynamics and optimizing processes. Bioinformatics tools such as AlphaFold2 and I-TASSER and metagenomic platforms such as QIIME and MG-RAST facilitate accurate identification of microbial communities, genes, and degradation pathways. AI-powered biosensors and advanced deep learning enable the continuous observation of enzymatic activity and the effectiveness of treatments. The combination of AI, metagenomics, and gene editing techniques, such as CRISPR, presents scalable approaches for achieving sustainable bioremediation. The present work emphasizes innovative tools, practical applications such as ANN-RF hybrid models, and prospective pathways, highlighting the significant impact of computational intelligence on ecological restoration.

Antibiotics are poorly absorbed and largely excreted through feces and urine, entering the environment. Although previous research focused on the adsorption of cefuroxime (CFX), amoxicillin (AMX) and azithromycin (AZM) onto soils and bio-adsorbents, the effect of the simultaneous presence of these antibiotics was not investigated, although being common in the environment. Hence, this work studied the adsorption of these antibiotics when added together to six soils and to three bio-adsorbents (oak ash, pine bark and mussel shell), and compared the results with those obtained for each antibiotic individually in previous studies. AZM exhibited the highest adsorption on soil. AMX adsorption by soils increased in the presence of CFX and AZM (from 76% to 88%). However, the adsorption of the other two antibiotics decreased in ternary systems: CFX dropped from 99% to 96%, and AZM from 100% to 42%. Regarding bio-adsorbents, oak ash demonstrated the highest adsorption efficiency for the three antibiotics, exceeding 90% in the ternary system. Pine bark and mussel shell showed lower adsorption efficiencies. The Freundlich model best described adsorption in soils, while only mussel shell fits well this model among the bio-adsorbents. Desorption from soils increased when antibiotics were applied simultaneously, with AMX showing the highest desorption. For bio-adsorbents, desorption was higher in the single-compound systems. Overall, AMX adsorption was enhanced by the presence of CFX and AZM, while both CFX and AZM adsorption were negatively affected by the presence of other antibiotics, suggesting competitive interactions.

Heatwaves are extreme weather events characterized by prolonged periods of unusually high temperatures, often leading to severe impacts on health, economy, and infrastructure. Global numerical weather prediction (NWP) models are useful for heatwave prediction, but they often underestimate the intensity due to their coarse resolution. To address this, experiments with high-resolution NWP models are required to better capture the intensity of heatwaves. In this study, we conducted an experiment using the National Centre for Medium Range Weather Forecasting (NCMRWF) Global Unified Model (NCUM-G) in two configurations: 12 km (Exp12) and 6 km (Exp06) resolutions, both initialized with identical conditions. To assess their performance, forecasts from the two versions were evaluated against the India Meteorological Department's (IMD) gridded observations using the mean error (ME) for the extreme heatwave over eastern India during 14–19 June 2023. The observed maximum temperature (T_max) during this event reached 42–46 °C, well above the climatological 32–36 °C, mainly due to a ridge over eastern India and delayed monsoon onset from cyclone Biparjoy. Results show that Exp06 provided superior accuracy at shorter lead times (Day 1 and Day 3), closely capturing the observed heatwave intensity, while Exp12 outperformed Exp06 at longer lead times (Day 5). Regional verification revealed that Exp06 forecasts aligned particularly well with observations over Uttar Pradesh and Bihar, while both models showed comparable performance over Jharkhand and Odisha. These findings highlight the trade-offs between the resolution and forecast range in global models and demonstrate that high-resolution experiments can substantially improve short-range predictions of extreme heatwaves in India.