Environmental Risk Evaluation Research Articles

Evaluation of environmental risks by heavy metals pollution and algae accumulations in two alpine lakes

ABSTRACT This research assessed the environmental changes occurring in two alpine lakes in Mexico, namely Lake El Sol and Lake La Luna. The investigation was based on the analysis of lakes sediment composition, organic matter content, algae predominance, levels of heavy metals and assessment of environmental risks. Sediment composition analysis revealed angular form as a primary particle, increase in the concentration of gravel particles, and decrease of the concentration of silt and sand particles. The dry season and central areas of the lakes showed the highest concentration of organic carbon (<12%). In addition, Lake El Sol showed the largest alterations in algae predominance, resulting from eutrophication changes. The concentration of Pb, Cd and Ni in sediments and algae was variable. The largest contribution was observed in algae from Lake La Luna; however, sediments from Lake El Sol showed the highest concentration of Pb with the maximum affectation in dry and wet seasons. The ecological risks posed by heavy metals indicated intermittent effects of Pb and Cd on organisms, and minor impacts of Ni. The data will be important in assessing the changes observed in Lakes El Sol and La Luna, in establishing future monitoring practices, and in implementing conservation strategies for ecosystems.

Evaluation of Environmental Risk from Heavy Metals in Sediments in Port Areas

This research aims to evaluate the concentration and distribution of heavy metals in sediment in the Port area of ​​PT Pelindo Dumai Branch, which is one of the main ports in Riau Province, Indonesia. Heavy metals such as cadmium, copper, lead, mercury and zinc are known to have significant toxic effects on maritime ecosystems and can accumulate in the food chain, potentially endangering aquatic life and human health. The research methodology involves taking sediment samples from various points around the port area, which are then analyzed using spectroscopic techniques to determine heavy metal concentrations. The results showed that the concentration of heavy metals in sediments varied, with zinc having the highest concentration (average 0.019724 mg/L), followed by copper, lead, cadmium, and mercury. This variation indicates the existence of diverse sources of pollution and uneven distribution in the port area. Although cadmium and mercury concentrations are relatively low, they still raise concerns due to their high toxicity and potential accumulation in the food chain. These results emphasize the need for more intensive environmental monitoring and targeted risk management to reduce the negative impacts of heavy metals on maritime ecosystems and human health. This research provides an important scientific basis for mitigation efforts in port areas, which are crucial to ensuring the sustainability of ecosystems and the well-being of communities that depend on marine resources.

Steering authority allocation strategy for human-machine shared control based on driver take-over feasibility

Misoperation when a driver is distracted, e.g., turning the steering wheel unconsciously, preventing the machine from turning the steering wheel, etc., can lead to a false take-over of the vehicle, which poses a danger to shared control. Therefore, it is essential to evaluate the feasibility of driver take-over in distraction status. This paper proposes a steering authority allocation strategy based on driver take-over feasibility to reduce the interference of distracted driver behavior on shared control. First, a driver take-over feasibility framework is established based on quantified driver distraction levels and take-over intention. Then the shared control system is established based on a linear parameter-varying vehicle model and non-cooperative game theory to suppress the interference of time-varying speed and parameter uncertainty on shared control. Subsequently, the steering authority allocation strategy is constructed in conjunction with driver take-over feasibility and environmental risk evaluation. The proposed sigmoid-based mapping function ensures fast and smooth authority allocation. Finally, a series of driver-in-the-loop experiments are conducted to validate the effectiveness of our proposed strategy across various driving scenarios, and the results demonstrate that our strategy has superior performance than other advanced shared control schemes in reducing steering burden, improving driving safety, and enhancing vehicle stability, etc.

Age of neutering contributes to risk of cruciate ligament rupture in Labrador Retrievers.

Cruciate ligament rupture (CR) in Labrador Retrievers is a complex polygenic disease with high heritability. The environmental contribution to CR risk remains poorly characterized. An accurate genetic risk test for CR in the Labrador Retriever has been developed. This enables evaluation of environmental risk with knowledge of genetic disease predisposition through study of dogs with phenotypic disease status that is discordant with their genetic risk. The objective of this study was to identify environmental factors that contribute to CR in Labrador Retrievers through evaluation of dogs with clinical phenotypes that are discordantly predicted with the use of genetic markers. Dogs were prospectively recruited between January 2013 and December 2022. To study discordant subjects, case dogs with a posterior risk probability value < 0.75 and control dogs with a posterior risk probability of > 0.25, determined with the use of an average of 8 statistical models, were selected. The environmental factors investigated were neuter status, age of neuter, withers height measured at the dorsal-most ridge between the scapulae, weight, body mass index, and athletic activity. Ninety three dogs were discordant: 58 dogs were discordant CR cases, and 35 dogs were discordant CR controls. Neutering before 12 months of age was a significant risk factor for CR development. Sex, neuter status, or status as an athlete was not associated with CR risk. Neutering before 12 months of age influences risk of CR in Labrador Retrievers. This information can inform management decisions about Labrador Retrievers regarding age of neutering, body condition, and athletic activity. The primary factor influencing CR development in Labrador Retrievers is polygenic intrinsic genetic risk.

Derivation of ecological safety thresholds and risk assessment of new SDHI fungicides in farmland system

Succinate dehydrogenase inhibitor (SDHI) fungicides have become some of the top-selling fungicides in recent years. As the utilization of these fungicides intensifies, the corresponding potential risks to the environment proportionately increase. However, there is still limited knowledge about their toxic effects on ecosystems. In this study, acute toxicity data from laboratory assessments of the springtail Folsomia candida, alongside collected data from terrestrial and aquatic non-target species, were utilized to construct a species sensitivity distribution (SSD) model for both terrestrial and aquatic non-target organisms. Subsequently, we derived ecological baseline values for diverse scenarios within ecosystems. The results indicated that benzovindiflupyr exhibited the highest 7-day median lethal concentration (7d-LC50) to Folsomia candida at 2.0 μg cm−2, while the toxicity levels of other SDHI fungicides varied, ranging from 99 to 304 μg cm−2. In agricultural environments, the Hazard Concentration for 5 % of species (HC5) values for fluxapyroxad, boscalid, sedaxane, and isopyrazam were determined to be 8.0, 1240, 12.97, and 25.37 g ha−1, respectively. In aquatic environments, the HC5 values for benzovindiflupyr, fluxapyroxad, boscalid, sedaxane, isopyrazam, and carboxin were 0.0013, 0.022, 1.76, 0.372, 0.013, and 0.161 mg L−1, respectively. In an evaluation of typical agricultural scenarios within China, SDHI fungicides were found to exert substantial ecological risks to terrestrial non-target fauna and aquatic ecosystems around agricultural fields. Specifically, isopyrazam and fluxapyroxad were identified as posing heightened ecological risks to Typhlodromus pyri and Aphidius rhopalosiphi. Moreover, the application of benzovindiflupyr, carboxin, isopyrazam, and fluxapyroxad in paddy field environments is associated with unacceptable risks to groundwater. The findings of this study contribute significantly to the environmental risk evaluation of SDHI fungicides within farmland system, thereby informing the development of policy frameworks for their scientifically grounded application.

Research on the group effect of new energy vehicles from different policy perspectives

Abstract Policies play a pivotal role in fostering the growth of new energy vehicles. This paper delves into the benefits and risks associated with the development of new energy vehicles under varying policy landscapes. Firstly, the intricate relationship between the competition and growth of new energy vehicles and internal combustion engine vehicles is captured through the application of the extended Lotka-Volterra model. Secondly, a simulation flow diagram is constructed, taking into account the actual mediums of policy impact and drawing insights from diverse research methodologies. This flow diagram enables a comprehensive evaluation of environmental benefits, health risks, and traffic pressure. Finally, a critical evaluation of the actual impact of policies on new energy vehicles is conducted, along with an exploration of the root causes of potential policy paradoxes. The findings reveal that a standalone infrastructure support policy, research and development support policy, or carbon tax policy can, in certain periods, lead to an increase in carbon emissions and traffic pressure. Although the driving restriction policy does not exert negative impacts on the environment, health, and traffic at the national level, it can result in a surge in the total vehicle population. Therefore, it is imperative to adopt a combination of policies to mitigate the potential risks associated with any single policy.

Environmental risk evaluation for radionuclide transport through natural barriers of nuclear waste disposal with multi-scale streamline approaches

Natural barriers, encompassing stable geological formations that serve as the final bastion against radionuclide transport, are paramount in mitigating the long-term contamination risks associated with the nuclear waste disposal. Therefore, it is important to simulate and predict the processes and spatial-temporal distributions of radionuclide transport within these barriers. However, accurately predicting radionuclide transport on the field scale is challenging due to uncertainties associated with parameter scaling. This study develops an integrated evaluation framework that combines upscaled parameters, streamline transport models, and response surface techniques to systematically assess environmental risk metrics and parameter uncertainties across different scales. Initially, upscaling methods are established to estimate the prior interval of critical transport parameters at the field scale, and streamline models are derived by considering the radionuclides transport with a variety of physicochemical mechanisms and geological characterizations in natural barriers. To assess uncertainty ranges of the risk metrics related to upscaled parameters, uncertainty quantification is performed on the ground of 5000 Monte Carlo simulations. The results indicate that the upscaled dispersivity of fractured media (αLf) has a relatively high sensitivity ranking on release dose for all nuclides, and upscaled matrix sorption coefficient (Kd) of Pu-242 strongly affects breakthrough time and release dose of Pu-242. Facilitated by robust response surface with the lowest R2 of 0.89, it is shown that the release doses of Pu-242 and Pb-210 increase under conditions of low Kd and αLf, respectively. Furthermore, statistical analysis reveals that employing limited laboratory-scale parameters results in narrower confidence intervals for risk metrics, while upscaling methods better account for the highly heterogeneous properties of large-scale field conditions. The developed risk evaluation framework provides valuable insights for utilizing upscaled parameters and modeling radionuclide transport within natural barriers under various scenarios.

Plasmon-enhanced photoelectrochemical-SERS simultaneous dual-read-out determination of enrofloxacin based on bifunctional Bi2S3 quantum dots/triangular Ag nanoparticles/Ti3C2 MXene heterojunction

The exploration of high-efficiency detection technologies of antibiotic residues plays vital roles for the evaluation of food quality and environmental safety risks owing to the adverse effects of antibiotics, which could accelerate the emergence of antibiotic-resistant genes. Herein, an integrated complementary dual-mode sensor was developed based on Bi2S3 quantum dots/triangular silver nanoparticles/Ti3C2 MXene (Bi2S3 QDs/T-Ag NPs/Ti3C2) heterojunction by in-situ coupling photoelectrochemical (PEC) analysis with surface-enhanced Raman spectroscopy (SERS) method. The bifunctional heterojunction could enhance light absorption, boost the generation of the electron-hole pairs, and facilitate the light-matter interactions, resulting in increased photoelectric conversion efficiency and enhanced Raman scattering for sensing applications. Moreover, the unique triangular shape and strong surface plasmon resonance effect of T-Ag NPs were conducted to further enhance the output signals of the dual-mode sensing platform. Such as-fabricated PEC/SERS detection system offered good complementarity and achieved mutually check via the combination of the inherent characteristics of two individual modes, which provided more accurate measurement results and more convincing information. Further, aptamer was adopted to recognize enrofloxacin molecules, which could achieve selective and sensitive detection of target. The detection limit of PEC and SERS was calculated as 0.61 fM (S/N = 3) and 0.21 fM (S/N = 3), respectively. Besides, the dual-mode aptasensor exhibited excellent stability and reproducibility, showing a promising prospect to detect enrofloxacin in real samples.

Multivariate ocean waves dynamics in North Sea and Norwegian Sea by Gaidai reliability method

Current study presents state-of-the-art approach for evaluating spatiotemporal multivariate environmental risks, especially suitable for complex environmental systems that have been either numerically simulated or physically observed. Advocated methodology provides accurate hazard risk forecasts, based on real-time in situ environmental data. Design of offshore structures requires multivariate risk assessment – offshore and naval operations require both short- and long-term risk and reliability analyses. Contemporary risk evaluation techniques often struggle with raw timeseries multivariate data due to intrinsic multidimensionality and nonlinear interconnections among critical system’s dimensions/components. In the current study effectiveness of the Gaidai multivariate risk evaluation method is illustrated by utilizing significant wave heights dataset, measured within two offshore zones: Heidrun and Troll Norwegian oil fields. Analyzing offshore waves being particularly challenging due to their complexity, high nonlinearity, multidimensionality, yet dynamic inter-correlations. Global warming being among several significant factors, affecting ocean and sea wave heights. For naval, offshore and marine structures operating in harsh weather conditions, robust multivariate environmental risk evaluation methods being crucial for both design and safe operations. Current study aims to validate and benchmark state-of-the-art methodology, enabling extraction. Advocated approach allows for efficient yet accurate assessment of global damages, failures or hazard risks for a wide range of complex nonlinear multivariate environmental and energy systems. Primary advantage of presented multivariate reliability methodology lies within its ability to treat complex systems with practically unlimited number of dimensions, while existing reliability methods being mostly limited to univariate and bivariate analyses.

Characterization and Source Analysis of Heavy Metal(loid)s Pollution in Soil of an Industrial Park in Kunming, China

This study investigated the characteristics and sources of heavy metal(loid) pollution in the soil of a key industrial park in Kunming, China. In total, 60 soil samples (40 from agricultural land and 20 from construction land) were collected from and around the park. The soil pH and contents of Arsenic (As), lead (Pb), copper (Cu), zinc (Zn), cadmium (Cd), mercury (Hg), nickel (Ni), and chromium (Cr) were measured. The contents of the eight heavy metal(loid)s were analyzed using the background values of heavy metal(loid)s in the Kunming soil. The pollution load, geoaccumulation, and Nemero Comprehensive Pollution Indices were used for environmental risk evaluation. Cluster and principal component analyses were used to resolve heavy metal(loid) sources. Cd was enriched in construction and agricultural soils. As, Hg, Cd, Pb, Cu, and Zn exhibited large spatial differentiation and were significantly affected by the external environment. A regional pollution load index of 3.02 indicated overall heavy pollution. The pollution load index for each heavy metal(loid) indicated light pollution. The geoaccumulation index indicated relatively severe As, Cd, Cu, Pb, and Zn pollution. The Nemero Composite Pollution Index value showed that the study area was heavily polluted, with construction land being mildly polluted by Cd, and agricultural land being moderately polluted. The results of the spatial distribution show that there were high levels of contamination in the center. Correlation and principal component analyses showed that the pollution sources of the eight heavy metal(loid)s varied. Hg, Cd, and Pb originate primarily from industrial and agricultural pollution. Traffic sources significantly impacted Cu, Pb, Cd, and Cr. Natural sources are the main sources of Cr, Ni, and Cd. Ni is also affected by industrial sources, whereas Zn and Cu are affected by agricultural pollution. The influences of As, Cd, and Pb on the surface soil in the study area were more serious. Cd is more widely polluted and should be a priority in controlling soil heavy metal(loid)s.

Medical Intelligence And Public Health In The Complexities Of Contemporary Societies The Role Of FBI In The United States

The term Medical Intelligence (Medint) defines the activities of collection, evaluation, analysis and interpretation of medical, bio-scientific and environmental information, regarding a specific country or geographical area, carried out mainly by military or intelligence agencies and carried out abroad, and useful for military or humanitarian strategic planning. It is of interest to Medint to know the potential of local health facilities, both civil and military, in the diagnostic evaluation, in case of infectious pathologies and in the evaluation of environmental risks as well as the "state of the art" of the development of computerized diagnostic technology and of biotechnology. The SMI (Strategic Medical Intelligence) is instead institutionally delegated to the intelligence agencies that deal with territorial control (counter-terrorism). In the United States, the SMI bioterrorism experts depend on the FBI. According to the definition offered by the FBI, Strategic Medical Intelligence (SMI) deals with all the management activities of a medical or health crisis situation following a terrorist act.

Comprehensive Evaluation of Health, Safety, and Environmental Risks in Railway Construction Project Management

Comprehensive Evaluation of Health, Safety, and Environmental Risks in Railway Construction Project Management

ChemFREE: a one-stop comprehensive platform for ecological and environmental risk evaluation of chemicals in one health world.

Addressing health and safety crises stemming from various environmental and ecological issues is a core focus of One Health (OH), which aims to balance and optimize the health of humans, animals, and the environment. While many chemicals contribute significantly to our quality of life when properly used, others pose environmental and ecological health risks. Recently, assessing the ecological and environmental risks associated with chemicals has gained increasing significance in the OH world. In silico models may address time-consuming and costly challenges, and fill gaps in situations where no experimental data is available. However, despite their significant contributions, these assessment models are not web-integrated, leading to user inconvenience. In this study, we developed a one-stop comprehensive web platform for freely evaluating the eco-environmental risk of chemicals, named ChemFREE (Chemical Formula Risk Evaluation of Eco-environment, available in http://chemfree.agroda.cn/chemfree/). Inputting SMILES string of chemicals, users will obtain the assessment outputs of ecological and environmental risk, etc. A performance evaluation of 2935 external chemicals revealed that most classification models achieved an accuracy rate above 0.816. Additionally, the $Q_{F1}^2$metric for regression models ranges from 0.618 to 0.898. Therefore, it will facilitate the eco-environmental risk evaluation of chemicals in the OH world.

Field evaluation of spray quality and environmental risks of unmanned aerial spray systems in mango orchards

Unmanned Aerial Spraying Systems (UASS) have garnered substantial market attention as efficient tools for applying Plant Protection Products (PPPs). However, their application has primarily focused on low-growing crops such as rice and wheat. This study emphasizes the need for additional UASS field trial data, specifically addressing spray quality and environmental risks associated with 3D fruit trees. The research aims to quantitatively assess the impact of canopy structure characteristics of mango trees and droplet size on spray quality. Simultaneously, it explores the exposure risks of UASS spraying in orchards to applicators, bystanders, and machine residue, comparing these risks with traditional ground machinery. Research findings reveal substantial differences in the distribution of UASS among mango tree canopies, with variations linked to the size of the canopy. Contrary to expectations, as tree volume increases, droplet deposition does not exhibit exponential growth. More droplets are deposited in the upper part of the canopy rather than the bottom. Altering droplet size significantly influences the deposition and distribution of droplets within the mango tree canopy. Notably, the coverage effect of fine droplets at the bottom of the canopy is 2.5 times that of coarse droplets. The ground loss from ground spray guns was lower than that of UASS, but the exposure risk was higher. Specific body parts with elevated operator exposure risks are identified as the legs and chest. UASS operators are advised to remain vigilant regarding the risk of pesticide adhesion on the equipment rack.

Assessing the dyeing efficacy and environmental impact of cotton fabric dyed with sawmill bio‐waste extracts and metal salts

AbstractTextile coloration is a complex process involving the interaction of dye molecules with fibers in a dye bath. Synthetic dyes pose environmental hazards, leading to increased interest in natural dyes sourced from plants, animals, and minerals. However, natural dyes often require mordants for application to textiles. Despite their eco‐friendliness, natural dyes can exhibit poor wash fastness on fabrics, necessitating further research to enhance their performance. This study investigates the use of mahogany sawdust extract as a natural dye for cotton coloration, focusing on the enhancement of fastness properties through metallic mordants and associated environmental risks. Mahogany sawdust, rich in flavonoids and tannins, shows promise as a sustainable alternative to synthetic dyes. The dyeing process involves the extraction of natural dyes from sawmill bio‐waste and subsequent application onto cotton fabrics using various metallic mordants. Evaluation of colorfastness properties, color strength, color coordinates, tensile strength, FTIR, and SEM analysis provides insights into the dye‐fiber interactions and fabric properties. Environmental risk assessment considers metal exhaustion onto fabric surfaces, residual metal concentrations in mordant baths, and metal content in dyeing wastewater. Overall, this study contributes to the development of sustainable dyeing processes and highlights the importance of environmental considerations in textile coloration.Highlights Mahogany sawdust extract: potential natural dye for sustainable cotton coloration. Metallic mordants enhance colorfastness and fabric durability in dyeing processes. Comprehensive analysis reveals the intricate dynamics of dye‐fiber interactions. Environmental risk evaluation guides sustainable textile manufacturing practices. Research paves the way for greener, more sustainable textile industry practices globally.

Environmental concerns on the use of the electrospinning technique for the production of polymeric micro/nanofibers

The production of micro and nanofibers through the electrospinning technique is a well assessed technology that finds application in a variety of fields. Indeed, the specific features of electrospun fibers, as well as the possibility to be modelled and functionalized, ensure their great versatility. In the last decades, the widespread use of electrospun fibers promoted studies related to the evaluation of both human health and environmental risks associated to their handling and exposure. However, to date, the environmental impact strictly related to the use of the manufacturing process has been barely considered. Therefore, the present work aims to assess the environmental impacts of the electrospinning technology used to produce micro and nanofibers. To this purpose, a model polymer was systematically electrospun, varying the main system, process and external parameters, that control the electrospinning technique. A simplified life cycle assessment analysis was finally used to evaluate how the fibrous morphology, closely linked to the choice of the technological parameters, intrinsically affected the environmental impacts.

Cohort profile: the PERSIAN Dena Cohort Study (PDCS) of non-communicable diseases in Southwest Iran

PurposeThis study conducted in Dena County is a population-based cohort study as part of the Prospective Epidemiological Research Studies in Iran (PERSIAN). The specific objectives of this study were to...

Environmental Risk Assessment of a Hydrocracker Unit in Abadan Oil Refinery Using the EFMEA Analysis

Background: The aim of risk assessment is to use a rational method to analyze risks and to identify the possible hazards and outcomes for people, equipment, materials, and the environment. Methods: The criteria and indices for assessing the environmental, health, and safety risks of the hydrocracker unit were determined by a Delphi questionnaire in this study. Then, an Environmental Failure Mode and Effects Analysis was applied to evaluate, score, and rank the risks based on their probability of occurrence, severity, probability of detection, extent of pollution, and potential of recycling. Results: According to the results of the Delphi process, 19 out of the 22 items were identified as the main criteria in the environmental, health, and safety risk evaluation of the hydrocracker unit at the Abadan Oil Refinery. However, the results indicated that 67% of the risks associated with the life cycle operation were low while 33% of them were high in terms of intensity. In contrast, 75% of the risks associated with control room operators were low and 25% were high in terms of intensity. On the other hand, 64, 7, and 29% of the risks associated with the activities of site employees were low, moderate, and high in terms of intensity, respectively, while the corresponding figures were 14, 29, and 57% in the case of risks associated with repairs. Conclusion: Based on the results of techniques of environmental failure modes and effects analysis (EFMEA) and Delphi, appropriate methods can be used to identify and reduce risks in similar industries.

Pacific Ocean Windspeeds Prediction by Gaidai Multivariate Risks Evaluation Method, Utilizing Self-Deconvolution

Abstract The current study advances research on the consequences of global climate change by utilizing the novel Gaidai multivariate risks evaluation methodology to conduct spatiotemporal analysis of areal windspeeds. Multidimensional structural and environmental dynamic systems that have been either physically observed or numerically simulated over a representative time-lapse are particularly suitable for the Gaidai risks evaluation methodology. Current research also presents a novel non-parametric deconvolution extrapolation method. As this study has shown, given in situ environmental input, it is possible to accurately predict environmental system hazard risks, based even on a limited underlying dataset. Furthermore, because of their complex nonlinear cross-correlations between various environmental system-critical dimensions or components and large dimensionality, environmental dynamic systems are difficult to handle using traditional methods for evaluating risks. In the North Pacific, close to the Hawaiian Islands, NOAA buoys gathered raw in situ wind speed data, which has been utilized in the current study. Areal ocean wind speeds constitute quite a complex environmental dynamic system that is challenging to analyze because of its nonlinear, multidimensional, cross-correlated nature. Global warming had impacts on ocean windspeeds in the recent decade. Developing novel state-of-the-art environmental system risk evaluation methods is a principal component of modern offshore structural analysis in light of adverse weather. The advocated novel risk/hazard assessment approach may be used for resilient island cities design, especially those that are near ocean shore and hence exposed to extreme weather.

Understanding the importance of atmospheric transformation in assessing the hazards of liquid crystal monomers.

Liquid crystal monomers (LCMs), a group of synthetic chemicals released from liquid crystal devices such as televisions and smartphones, have recently been recognized as emerging contaminants due to their widespread occurrence in the environment and potential negative impacts on human health. Airborne LCMs can undergo atmospheric oxidation reactions to form various transformation products. Despite the certainty of atmospheric transformation chemistry, the knowledge about the hazard properties of transformation products remains largely unknown. Here, we perform an in silico model-based evaluation of the persistence, bioaccumulation potential, mobility, and toxicity of two representative LCMs, namely, 1-ethyl-4-(4-(4-propylcyclohexyl)phenyl)benzene and 4''-ethyl-2'-fluoro-4-propyl-1,1':4',1''-terphenyl, and their transformation products. We found that, among the investigated transformation products, 38% have overall persistence greater than the minimum of 331 days among the persistent organic pollutants regulated by the Stockholm Convention, 62% meet the bioaccumulation threshold of 1000 L kg-1 used by the United States Environmental Protection Agency, 44% are classified "mobile" according to the criterion used by the German Environmental Agency, and 58% have the potential to induce unacceptable toxic effects in aquatic organisms. Furthermore, we identified several transformation products with increased persistence, bioaccumulation potential, and mobility compared to their parent compounds. These findings not only offer insights for prioritizing LCM transformation products for future risk assessment, but also underscore the significance of considering atmospheric transformation in the evaluation of environmental risks posed by emerging contaminants, including LCMs.