The degradation of polylactic acid face mask components in different environments.

The disposal of fossil fuel-based plastics poses a huge environmental challenge, leading to increased interest in biodegradable alternatives such as polylactic acid (PLA). This study focuses on the environmental impact and degradation of PLA face mask components under various conditions (UV (Ultraviolet) radiation, DI water, landfill leachate of various ages, seawater, and enzyme). Under UV exposure, notable changes in physicochemical properties were observed in the PLA masks, including increased oxidation over time. Degradation rates varied across environments, with old landfill leachate and enzyme degradation having a notable impact, especially on meltblown layers. Furthermore, it was found that seawater conditions hampered the degradation of PLA masks, likely due to the inhibitory effect of high salt concentrations. The pathways of chemical group changes during degradation were elucidated using 2D-COS (Two-Dimensional Correlation Spectroscopy) maps. The investigation into the release of microparticles and oligomers further revealed the degradation mechanism. Moreover, PLA masks were found to release fewer microparticles when degraded in studied environments when compared to traditional polypropylene masks. Furthermore, correlation analysis highlighted the influence of factors such as carbonyl index and contact angle on degradation rates, underscoring the complex interplay between environmental conditions and PLA degradation. This comprehensive investigation advances the understanding of PLA degradation pathways, which are crucial for mitigating plastic pollution and promoting the development of sustainable products.

Revealing the Freezing-Induced Alteration in Microplastic Behavior and Its Implication for the Microplastics Released from Seasonal Ice.

Ice can serve as a significant temporary repository and conveyance mechanism for microplastics (MPs). MPs present in the water column can become entrapped within developing ice formations, subsequently being sequestered and transported by ice floes. With changing temperatures, MPs stored in ice can be released back into the environment, while freezing conditions can alter the properties of MPs, ultimately affecting the fate of MPs in the environment. Freezing of MPs in freshwater ice results in the aggregation of MP particles due to physical compression, leading to an increase in particle size once the MPs are released from the ice. The freezing-induced aggregation enhances buoyancy effects, accelerating the settling/rising velocity of MPs in water. Additionally, freezing can lead to enhanced surface wetting alterations, thus improving the dispersion of hydrophobic MPs. The presence of salt in the water can mitigate the effect of freezing on MPs due to the formation of a brine network within the ice structure, which reduces the pressure on MPs entrapped by ice. In cold regions, numerous MPs undergo freezing and thawing, re-entering the water column.

Effect of nanobubbles on the mobilization of microplastics in shorelines subject to seawater infiltration.

The widespread presence of microplastics (MPs) in the ocean has varying degrees of impact on ecosystems and even human health. Coastal tidal zones are crucial in controlling the movement of MPs, which are influenced by waves and tidal forces. Meanwhile, natural nanobubbles (NBs) in the ocean can affect the hydrodynamic properties of the tidal zone. The mobilization of MPs in coastal tidal zones under the effect of NBs has been less studied. In this study, we explored natural NBs' influence on the mobilization of MPs in shorelines subject to seawater infiltration. Using glass beads as a substrate, a coastal porous environment was constructed through column experiments, and the pump-controlled water flow was used to study the transport of MPs subject to seawater movement within the substrate. The infiltration of MPs under continuous and transient conditions, as well as the upward transport induced by flood tide, were considered. The role of salinity in the interactions between NBs, MPs, and substrates was evaluated. Salinity altered the energy barriers between particles, which in turn affected the movement of MPs within the substrate. In addition, hydrophilic MPs were more likely to infiltrate within the substrate and had different movement patterns under continuous and transient flow conditions. The motion of the MPs within the substrate varied with flow rate, and NBs limited the vertical movement of MPs in the tidal zone. It was also observed that NBs adsorbed readily onto substrates, altering the surface properties of substrates, particularly their ability to attach and detach from other substances.

Poly (Vinylidene Fluoride-Hexafluoropropylene)-Lithium Titanium Aluminum Phosphate-Based Gel Polymer Electrolytes Synthesized by Immersion Precipitation for High-Performance Lithium Metal Batteries.

Gel polymer electrolytes (GPEs) have high safety and excellent electrochemical performance, so applying GPEs in lithium batteries has received much attention. However, their poor lithium ion transfer number, cycling stability, and low room temperature ionic conductivity seriously affect the utilization of gel polymer electrolytes. This paper successfully synthesized flexible poly (vinylidene fluoride-hexafluoropropylene)-lithium titanium aluminum phosphate (PVDF-HFP-LATP) gel polymer electrolytes using the immersion precipitation method. The resulting GPE has a porous honeycomb structure, which ensures that the GPE has sufficient space to store the liquid electrolyte. The GPE has a high ionic conductivity of 1.03 ×10-3 S cm-1 at room temperature (25 °C). The GPE was applied to LiFePO4/GPE/Li batteries with good rate performance at room temperature. The discharge specific capacity of 1C was as high as 121.5 mAh/g, and the capacity retention rate was 94.0% after 300 cycles. These results indicate that PVDF-HFP-LATP-based GPEs have the advantage of simplifying the production process and can improve the utility of gel polymer lithium metal batteries.

Spotlight on the vertical migration of aged microplastics in coastal waters.

Coastal waters are complex and dynamic areas with unique environmental attributes that complicate the vertical migration of microplastics (MPs). The MPs that enter coastal waters from diverse sources, including terrestrial, riverine, oceanic, and shoreline inputs undergo various aging pathways. In this study, the variations in the physiochemical characteristics of MPs undergoing various aging pathways and their vertical migration under dynamic conditions subjected to the effects of different MP characteristics and coastal environmental features were comprehensively explored. Opposite effects of aging on the vertical migration of hydrophobic and hydrophilic MPs were observed, with aging appearing to promote the dispersion of hydrophobic MPs but enhance the vertical migration of hydrophilic ones. The positive role of salinity and the negative role of humic acid (HA) concentrations on MP vertical migration were identified, and the mechanisms driving these effects were analyzed. Notably, intense turbulence not only promoted the floating of positively buoyant MPs but also reversed the migration direction of negatively buoyant MPs from downward to upward. Aging-induced changes in MP characteristics had a limited effect on MP vertical migration. The inherent characteristics of MPs and the surrounding environmental features, however, played major roles in their vertical migration dynamics. ENVIRONMENTAL IMPLICATION: Microplastics (MPs) have emerged as a significant global environmental concern and the coastal zones are the hotspots for MP pollution due to their high population density. This study comprehensively investigated the variations in the physiochemical characteristics of MPs undergoing various aging pathways. Their vertical migration patterns under dynamic conditions subjected to the effects of different MP characteristics and coastal environmental features were revealed. The roles of turbulence and MP density in their migration were identified. The findings of this study have important implications for understanding the transport and determining the ecological risks of MPs in coastal waters.

Preparation and Properties of Gel Polymer Electrolytes with Li1.5Al0.5Ge1.5(PO4)3 and Li6.46La3Zr1.46Ta0.54O12 by UV Curing Process.

Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP)-based gel polymer electrolytes (GPEs) are considered a promising electrolyte candidate for polymer lithium-ion batteries (LIBs) because of their free-standing shape, versatility, security, flexibility, lightweight, reliability, and so on. However, due to problems such as low ionic conductivity, PVDF-HFP can only be used on a small scale when used as a substrate alone. To overcome the above shortcomings, GPEs were designed and synthesized by a UV curing process by adding NASICON-type Li1.5Al0.5Ge1.5(PO4)3 (LAGP) and garnet-type Li6.46La3Zr1.46Ta0.54O12 (LLZTO) to PVDF-HFP. Experimentally, GPEs with 10% weight LLZTO in a PVDF-HFP matrix had an ionic conductivity of up to 3 × 10-4 S cm-1 at 25 °C. When assembled into LiFePO4/GPEs/Li batteries, a discharge-specific capacity of 81.5 mAh g-1 at a current density of 1 C and a capacity retention rate of 98.1% after 100 cycles at a current density of 0.2 C occurred. Therefore, GPEs added to LLZTO have a broad application prospect regarding rechargeable lithium-ion batteries.

A stochastic resonance etection algorithm based on orthonormalized basis function for magnetic anomaly detection.

To address the problem that the performance of the detector in airborne magnetic anomaly detection (MAD) is terrible, a stochastic resonance (SR) detection algorithm based on orthonormalized basis function (OBF-SR) is proposed for MAD under low signal-to-noise ratio conditions. The signal contaminated by noise is first preprocessed by the OBF method, where the sum of the three components in the OBF space is selected as the SR system input. Then, a parallel SR system with different initial states is designed to detect the signal. Finally, the simulation analysis of MAD methods is performed to draw a comparison between the OBF-SR method, the typical SR method, and the OBF method. The results show that the OBF-SR method outperforms the SR and OBF methods in the detection probability and detection range under the same conditions.

Toxic elements pollution risk as affected by various input sources in soils of greenhouses, kiwifruit orchards, cereal fields, and forest/grassland.

Increasing food demand has led to more intensive farming, which threatens our ecosystem and human health due to toxic elements accumulation. This study aimed to estimate the vulnerability of different agricultural systems with unequal high fertilizer input practices regarding toxic element pollution in the greenhouse, kiwifruit orchard, cereal field, and forest/grassland. Soil samples were collected from 181 sites across Shaanxi Province, China, and analyzed for selected characteristics and toxic elements (As, Cd, Cr, Cu, Hg, Pb, and Zn). The contamination factor (CFx) represents the ratio of the measured value of the toxic element in the soil over the soil background values. The CFx values of all the toxic elements were above background values, while Cd and Hg contamination levels were more severe than those of Zn, Cu, As, Cr, and Pb. Kiwifruit orchards and greenhouse soils were contaminated with Cd, Hg, Cu, and Zn, but cereal fields and forest/grassland soils were contaminated with As, Cd, Hg, and Hg. Overall, the cumulative pollution load (PLI) of toxic elements indicated moderate contamination. The cumulative ecological risk (RI) results indicated that greenhouse (178.81) and forest/grassland (156.25) soils were at moderate ecological risks, whereas kiwifruit orchards (120.97) and cereal field (139.72) soils were at low ecological risks. According to a Pearson correlation analysis, Cd, Hg, Cu, and Zn were substantially linked with soil organic matter (SOM), total nitrogen (TN), total phosphorous (TP), and total potassium (TK). The primary sources of toxic elements were phosphate and potash fertilizers, manure, composts, and pesticides in a greenhouse, kiwifruit orchards, and cereal fields, whereas, in forest/grassland soils parent material and atmospheric deposition were the sources identified by positive matrix factorization (PMF). Furthermore, the partial least square structural equation model (PLS-SEM) demonstrated that agriculture inputs largely influenced toxic elements accumulation. We conclude that high fertilizer inputs in greenhouse soils should be considered carefully so that toxic element pollution may be minimized.

Promoting Cross-Regional Integration of Maritime Emission Management: A Euro-American Linkage of Carbon Markets.

Reducing greenhouse gas emissions from maritime transport is an urgent topic. Some regional emissions trading systems (ETSs), buoyed by the globalized market-based measures (MBMs) plan of the International maritime organization, have initially assessed the feasibility of including maritime emissions under compliance obligations. However, including maritime emissions (which are interjurisdictional) in the existing ETSs is controversial, and globalized maritime MBMs remain elusive. Therefore, this study designed a joint bilateral maritime carbon market (BMCM) model based on the European ETS (EU-ETS) and Quebec ETS (QC-ETS). The carbon costs, speed optimization, and marginal abatement costs of three container routes under BMCM were analyzed. The results show that this Euro-American linkage achieves adequate emission coverage on specific routes and generates acceptable carbon costs for charterers. This study yields a positive result for the equal division of ETSs' exercising competence in cross-regional maritime transport and provides evidence for sector-specific ETS links based on quantitative analysis.

A Lightweight Detection Method for Remote Sensing Images and Its Energy-Efficient Accelerator on Edge Devices.

Convolutional neural networks (CNNs) have been extensively employed in remote sensing image detection and have exhibited impressive performance over the past few years. However, the abovementioned networks are generally limited by their complex structures, which make them difficult to deploy with power-sensitive and resource-constrained remote sensing edge devices. To tackle this problem, this study proposes a lightweight remote sensing detection network suitable for edge devices and an energy-efficient CNN accelerator based on field-programmable gate arrays (FPGAs). First, a series of network weight reduction and optimization methods are proposed to reduce the size of the network and the difficulty of hardware deployment. Second, a high-energy-efficiency CNN accelerator is developed. The accelerator employs a reconfigurable and efficient convolutional processing engine to perform CNN computations, and hardware optimization was performed for the proposed network structure. The experimental results obtained with the Xilinx ZYNQ Z7020 show that the network achieved higher accuracy with a smaller size, and the CNN accelerator for the proposed network exhibited a throughput of 29.53 GOPS and power consumption of only 2.98 W while consuming only 113 DSPs. In comparison with relevant work, DSP efficiency at an identical level of energy consumption was increased by 1.1-2.5 times, confirming the superiority of the proposed solution and its potential for deployment with remote sensing edge devices.

Multilevel spatial confinement of transition metal selenides porous microcubes for efficient and stable potassium storage.

Recently, potassium-ion batteries (PIBs) have been considered as one of the most promising energy storage systems; however, the slow kinetics and large volume variation induced by the large radius of potassium ions (K+) during chemical reactions lead to inferior structural stability and weak electrochemical activity for most potassium storage anodes. Herein, a multilevel space confinement strategy is proposed for developing zinc-cobalt bimetallic selenide (ZnSe/Co0.85Se@NC@C@rGO) as high-efficient anodes for PIBs by in-situ carbonizing and subsequently selenizing the resorcinol-formaldehyde (RF)-coated zeolitic imidazolate framework-8/zeolitic imidazolate framework-67 (ZIF-8/ZIF-67) encapsulated into 2D graphene. The highly porous carbon microcubes derived from ZIF-8/ZIF-67 and carbon shell arising from RF provide rich channels for ion/electron transfer, present a rigid skeleton to ensure the structural stability, offer space for accommodating the volume change, and minimize the agglomeration of active material during the insertion/extraction of large-radius K+. In addition, the three-dimensional (3D) carbon network composed of graphene and RF-derived carbon-coated microcubes accelerates the electron/ion transfer rate and improves the electrochemical reaction kinetics of the material. As a result, the as-synthesized ZnSe/Co0.85Se@NC@C@rGO as the anode of PIBs possesses the excellent rate capability of 203.9 mA h g-1 at 5 A g-1 and brilliant long-term cycling performance of 234 mA h g-1 after 2,000 cycles at 2 A g-1. Ex-situ X-ray diffraction (Ex-situ XRD) diffraction reveals that the intercalation/de-intercalation of K+ proceeds through the conversion-alloying reaction. The proposed strategy based on the spatial confinement engineering is highly effective to construct high-performance anodes for PIBs.

Entrainment and Enrichment of Microplastics in Ice Formation Processes: Implications for the Transport of Microplastics in Cold Regions.

Sea ice can serve as a temporary sink for microplastics (MPs), and thus, it too can function as a secondary source of and transport medium for MPs. This study aimed to explore the effect of various MP properties and environmental characteristics on the entrainment and enrichment of MPs in ice under varying turbulence conditions. It was found that high rotation speed in freshwater distinctively enhanced the entrainment of hydrophobic MPs in ice, this being attributable to the combined effects of frazil ice and air bubbles. The hydrophobic nature of these MPs caused them to be attracted to the water/air or water/ice interface. However, in saline water, high turbulence inhibited the entrainment of all of the MP types under study. The ice crystals formed a loose structure in saline water instead of congealing, and this allowed the exchange of MPs between ice and water, leading to the rapid expulsion of MPs from the ice. The enrichment factors of all the MPs under study increased in calm saline water compared to in calm freshwater. The results revealed that the entrainment and enrichment of MPs in ice can be critical pathways affecting their fate in cold regions.

Impact from the evolution of private vehicle fleet composition on traffic related emissions in the small-medium automotive city.

Understanding the emission characteristics in the evolution of private vehicle fleet composition has become a key issue to be addressed to develop appropriate emission mitigation strategies in transportation sector. In this study, the influence of such evolution on on-road emissions was investigated based on a comprehensive dataset encompassing vehicle fleet composition, demographic, economic, and energy features from a representative small-medium automotive city in North America. The decoupling analysis was carried out to assess the dynamic linkage between environmental pressure exerted by the transportation sector and economic growth at both city level and national level in North America. We also developed an approach that supports the long-term traffic-related air pollutant prediction and investigated the potential influence on urban air quality. A sharp upward trajectory was observed in the quantity of SUVs from 2001 to 2018, gradually replacing the dominance of the quantity of four-door cars. There was a significant shift in the GHG emissions emitted from vehicle types used for passenger transport: emissions from SUVs and trucks rose by 374.0% and 69.3%, respectively, whereas emissions from four-door cars, two-door cars, station wagons, and vans all decreased. The changes in vehicle composition, along with the steady trend in GHG emissions from private fleet and decrease in on-road air pollutant concentrations found in Regina, were a response to the establishment of federal fuel economy standards and improved fuel economy. Relative decoupling was observed in aggregate for Regina and Canada in most of the years while both experienced economic downturns and increases in environmental pressure in the form of emissions from 2014 to 2015. The predicted results also demonstrate the high capability of XGboost machine learning algorithm in predicting on-road air pollutant concentrations of CO, PM2.5, and NOX.

Sources, behaviors, transformations, and environmental risks of organophosphate esters in the coastal environment: A review.

The rapid growth in the global production of organophosphate esters (OPEs) has resulted in their high environmental concentrations. The low removal rate of OPEs makes the effluents of wastewater treatment plants be one of the major sources of OPEs. Due to relatively high solubility and mobility, OPEs can be carried to the coastal environment through river discharge and atmospheric deposition. Therefore, the coastal environment can be an important OPE sink. Previous studies have shown that OPEs were widely detected in coastal atmospheres, water, sediments, and even aquatic organisms. OPEs can undergo various environmental processes in the coastal environment, including adsorption/desorption, air-water exchange, and degradation. In addition, bioaccumulation of OPEs was observed in coastal biota but current concentrations would not cause significant ecological risks. More efforts are required to understand the environmental behaviors of OPEs and address resultant environmental and health risks, especially in the complicated environment.

DACFL: Dynamic Average Consensus-Based Federated Learning in Decentralized Sensors Network.

Federated Learning (FL) is a privacy-preserving way to utilize the sensitive data generated by smart sensors of user devices, where a central parameter server (PS) coordinates multiple user devices to train a global model. However, relying on centralized topology poses challenges when applying FL in a sensors network, including imbalanced communication congestion and possible single point of failure, especially on the PS. To alleviate these problems, we devise a Dynamic Average Consensus-based Federated Learning (DACFL) for implementing FL in a decentralized sensors network. Different from existing studies that replace the model aggregation roughly with neighbors' average, we first transform the FL model aggregation, which is the most intractable in a decentralized topology, into the dynamic average consensus problem by treating a local training procedure as a discrete-time series.We then employ the first-order dynamic average consensus (FODAC) to estimate the average model, which not only solves the model aggregation for DACFL but also ensures model consistency as much as possible. To improve the performance with non-i.i.d data, each user also takes the neighbors' average model as its next-round initialization, which prevents the possible local over-fitting. Besides, we also provide a basic theoretical analysis of DACFL on the premise of i.i.d data. The result validates the feasibility of DACFL in both time-invariant and time-varying topologies and declares that DACFL outperforms existing studies, including CDSGD and D-PSGD, in most cases. Take the result on Fashion-MNIST as a numerical example, with i.i.d data, our DACFL achieves 19∼34% and 3∼10% increases in average accuracy; with non-i.i.d data, our DACFL achieves 30∼50% and 0∼10% increases in average accuracy, compared to CDSGD and D-PSGD.

Variations in lignin monomer contents and stable hydrogen isotope ratios in methoxy groups during the biodegradation of garden biomass.

Lignin, a highly polymerized organic component of plant cells, is one of the most difficult aromatic substances to degrade. Selective biodegradation under mild conditions is a promising method, but the dynamic variations in lignin monomers during the biodegradation of lignocellulose are not fully understood. In this study, we evaluated the differences in lignin degradation under different microbial inoculation based on the lignin monomer content, monomer ratio, and stable hydrogen isotope ratio of lignin methoxy groups (δ2HLM). The weight loss during degradation and the net loss of lignocellulosic components improved dramatically with fungal inoculation. Syringyl monolignol (S-lignin), which contains two methoxy groups, was more difficult to degrade than guaiacyl (G-lignin), which contains only one methoxy group. The co-culture of Pseudomonas mandelii and Aspergillus fumigatus produced the greatest decrease in the G/S ratio, but δ2HLM values did not differ significantly among the three biodegradation experiments, although the enrichment was done within the fungal inoculation. The fluctuation of δ2HLM values during the initial phase of biodegradation may be related to the loss of pectic polysaccharides (another methoxy donor), which mainly originate from fallen leaves. Overall, the relative δ2HLM signals were preserved despite decreasing G/S ratios in the three degradation systems. Nevertheless, some details of lignin δ2HLM as a biomarker for biogeochemical cycles need to be explored further.

Construction, renovation, and demolition waste in landfill: a review of waste characteristics, environmental impacts, and mitigation measures.

With the increase in global population, industrialization, and urbanization, waste from construction, renovation, and demolition (CRD) activities has grown rapidly. There are some issues associated with the disposal of CRD waste in landfills. Depositing in landfills is still the main method for CRD waste disposal from the global perspective. The objective of this study is to comprehensively review the environmental impacts and management technologies for CRD waste in landfills. It includes the overview of the current CRD waste flow and relevant policies worldwide. The main environmental problems caused by CRD waste in landfills include leachate and H2S gas emission. This paper summarizes the primary environmental impacts caused by landfilling CRD waste and the available mitigation technologies. It also includes the use of CRD waste as an alternative material in landfill barriers. Although many technologies can help mitigate the environmental impacts caused by landfilling CRD waste, the optimal solution is to divert the waste flow from landfills using the "3R" principle. In the end, the existing research gaps in CRD waste and landfill management are also discussed.

Cleanup of oiled shorelines using a dual responsive nanoclay/sodium alginate surface washing agent.

Oil spills may affect ecosystems and endanger public health. In this study, we developed a novel and dual responsive nanoclay/sodium alginate (NS) washing fluid, and systematically evaluated its application potential in oiled shoreline cleanup. The characterization results demonstrated that sodium alginate combined with nanoclay via hydrogen bonds, and was inserted into the interlayer spacing of nanoclay. Adding sodium alginate reduced surface and interfacial tensions, while increasing the viscoelasticity of the washing fluid. Batch experiments were conducted to investigate oil removal performance under various conditions. Additionally, the factorial design analysis showed that three single factors (temperature, oil concentration, and salinity), and two interactive effects (temperature/salinity; and oil concentration/HA) displayed significant effects on the oil removal efficiency of the NS washing fluid. Compared to the commercial surfactants, the NS composite exhibited satisfactory removal efficiencies for treating oily sand. Green materials-stabilized Pickering emulsion can potentially be used for oil/water separation. The NS washing agent displayed excellent pH- and Ca2+- responsiveness, generating transparent supernatants with low oil concentration and turbidity. Our work opens an interesting avenue for designing economical, high performance, and green washing agents.

A green initiative for oiled sand cleanup using chitosan/rhamnolipid complex dispersion with pH-stimulus response.

The released oil can affect the vulnerable shoreline environment if the oil spills happen in coastal waters. The stranded oil on shorelines is persistent, posing a long-term influence on the intertidal ecosystem after weathering. Therefore, shoreline cleanup techniques are required to remove the oil from the shoreline environment. In this study, a new shoreline cleanup initiative using chitosan/rhamnolipid (CS/RL) complex dispersion with pH-stimulus response was developed for oiled sand cleanup. The results of factorial and single-factor design revealed that the CS/RL complex dispersion maintained high removal efficiency for oiled sand with different levels of oil content in comparison to using rhamnolipid alone. However, the increase of salinity negatively affected the removal efficiency. The electrostatic screening effect of high ionic strength can hinder the formation of the CS/RL complex, and thus reduce removal efficiency. The pH-responsive characteristic of chitosan allows the easy separation of water and oil in washing effluent. The chitosan polyelectrolytes aggregated and precipitated due to the deprotonation of amino groups by adjusting the pH of the washing effluent to above 8. The microscope image demonstrated that the chitosan aggregates wrapped around the oil droplets and settled to the bottom together, thus achieving oil-water separation. Such pH-stimulus response may help achieve an easy oil-water separation after washing. These findings have important implications for developing the new strategies of oil spill response.