Hasil untuk "Hazardous substances and their disposal"

Yulong Chen, Jim Griffin, Francisco Javier Rubio

The proportional hazards (PH) and accelerated failure time (AFT) models are the most widely used hazard structures for analysing time-to-event data. When the goal is to identify variables associated with event times, variable selection is typically performed within a single hazard structure, imposing strong assumptions on how covariates affect the hazard function. To allow simultaneous selection of relevant variables and the hazard structure itself, we develop a Bayesian variable selection approach within the general hazard (GH) model, which includes the PH, AFT, and other structures as special cases. We propose two types of g-priors for the regression coefficients that enable tractable computation and show that both lead to consistent model selection. We also introduce a hierarchical prior on the model space that accounts for multiplicity and penalises model complexity. To efficiently explore the GH model space, we extend the Add-Delete-Swap algorithm to jointly sample variable inclusion indicators and hazard structures. Simulation studies show accurate recovery of both the true hazard structure and active variables across different sample sizes and censoring levels. Two real-data applications are presented to illustrate the use of the proposed methodology and to compare it with existing variable selection methods.

Haichao Zhu, Zhaorui Yang, Qian Zhang

Spatial perception aims to estimate camera motion and scene structure from visual observations, a problem traditionally addressed through geometric modeling and physical consistency constraints. Recent learning-based methods have demonstrated strong representational capacity for geometric perception and are increasingly used to augment classical geometry-centric systems in practice. However, whether learning components should directly replace geometric estimation or instead serve as intermediate modules within such pipelines remains an open question. In this work, we address this gap and investigate an end-to-end modular framework for effective spatial reasoning, where learning proposes geometric hypotheses, while geometric algorithms dispose estimation decisions. In particular, we study this principle in the context of relative camera pose estimation on RGB-D sequences. Using VGGT as a representative learning model, we evaluate learning-based pose and depth proposals under varying motion magnitudes and scene dynamics, followed by a classical point-to-plane RGB-D ICP as the geometric backend. Our experiments on the TUM RGB-D benchmark reveal three consistent findings: (1) learning-based pose proposals alone are unreliable; (2) learning-proposed geometry, when improperly aligned with camera intrinsics, can degrade performance; and (3) when learning-proposed depth is geometrically aligned and followed by a geometric disposal stage, consistent improvements emerge in moderately challenging rigid settings. These results demonstrate that geometry is not merely a refinement component, but an essential arbiter that validates and absorbs learning-based geometric observations. Our study highlights the importance of modular, geometry-aware system design for robust spatial perception.

Jonathan W. Bartlett, Dominic Magirr, Tim P. Morris

The hazard ratio, typically estimated using Cox's famous proportional hazards model, is the most common effect measure used to describe the association or effect of a covariate on a time-to-event outcome. In recent years the hazard ratio has been argued by some to lack a causal interpretation, even in randomised trials, and even if the proportional hazards assumption holds. This is concerning, not least due to the ubiquity of hazard ratios in analyses of time-to-event data. We review these criticisms, describe how we think hazard ratios should be interpreted, and argue that they retain a valid causal interpretation. Nevertheless, alternative measures may be preferable to describe effects of exposures or treatments on time-to-event outcomes.

Ting Su, Huasheng Wang, Xiangyu Gu et al.

Microplastics have been discovered in the solid residuals from municipal solid waste (MSW) incineration plant, posing potential risks to the surrounding environments. However, there exists a lack of evidence on the presence and characterizations of atmospheric microplastic emission from MSW incineration, which is considered more hazardous due to size reduction. Hence, we collected particles from flue gas emitted by a circulating fluidized bed incinerator, to investigate the morphology, chemical structure, and emission abundance of microplastics. Further, particles from different stream locations were collected to identify the effects of air pollution control devices on the microplastic abundance and chemical structures. Results indicate the predominant length of the microplastics in the flue gas ranged from 10 to 40 μm at different locations. The major polymer types of microplastics were polyvinyl chloride and polyacrylamide, resulting from inherent Cl elements and selective non-catalytic reduction in MSW, respectively. Based on the field data, the atmospheric microplastic emission was estimated at 2.1 × 1012 pieces/yr, turned out to be a pivotal contributor to the atmospheric microplastics. Notably, the unique microplastic chemical properties pose a higher threat to human health than conventional plastics. Our work prioritizes an alternative source of microplastic emissions and calls for further research endeavors.

Мамонтов, А.А., Мамонтова, Е.А., Фереферов, Е.С.

Представлены результаты исследований Солзанского полигона БЦБК на предмет содержания стойких органических загрязнителей в шлам-лигнине, золе из 10 карт накопителей, почвах полигона и окружающих его территорий. Отбор проб произведен в августе-октябре 2024 г. Анализ выполнен в Институте геохимии им. А.П. Виноградова СО РАН с использованием метода ГХ/МС на приборе «Кристалл-5000». Максимальные концентрации были найдены для полихлорированных бифенилов (ПХБ) (до 3900 мкгƩ32ПХБ/кг почвы и до 481 мкгƩ32ПХБ/кг шлам-лигнина). Впервые на территории центральной экологической зоны Байкальской природной территории обнаружен столь значительный источник стойких органических загрязнителей.

masoud fazlalipour, mohamad khalediyan, mehdi salehi

Background: Reality therapy aims to foster responsibility-taking and help individuals establish a successful identity. This study investigates the effectiveness of group reality therapy on students' psychological well-being.  Methods: The study population comprised all Payame Noor University students enrolled at Ghorveh branch during 2022. The research employed an experimental design with both experimental and control groups. A random sample of 30 students was selected, with 15 participants assigned to the experimental group, which received nine 90-minute sessions of group reality therapy. The remaining 15 students formed the control group. Data were collected using Carol Ryff's Psychological Well-Being Scale. Results: The findings showed descriptive information regarding psychological well-being in pretest and posttest for both control and experimental groups. Psychological well-being mean value of students in experimental group in pretest was 308.01 ± 9.38, while posttest mean value for the same group was 317.73 ± 8.99. In contrast, psychological well-being mean value of students in control group in pretest was 309.93 ± 8.84, with posttest mean value for this group being 310.46 ± 8.96. The findings revealed that group reality therapy significantly improved the students' psychological well-being (p < 0.05). Conclusion: Group reality therapy is an effective intervention for enhancing students' psychological well-being, Therefore, this method can be used to improve the psychological well-being of students.

Yurika Tokunaga, Kosuke Tanaka, Go Suzuki et al.

Nanoplastics (NPs) are cause for increasing concern due to their ability to cross biological barriers, enhanced reactivity, and potentially greater toxicity than microplastics. However, their quantification in biological samples such as animal tissues remains challenging, primarily due to complex matrix interference and contamination risks. Reliable quantification of NPs in tissues is critical for understanding their bioavailability, bioaccumulation, and associated toxicological risks to animals, as well as their potential ecological risks. Here, we developed a simple yet robust method for quantifying polystyrene (PS) NPs in animal tissues using silica gel column chromatography coupled with pyrolysis–gas chromatography/mass spectrometry. Tissue samples were homogenized in dichloromethane (DCM) to extract and dissolve PS NPs in DCM and then subjected to alkaline digestion. The extract was subsequently purified using pre-heat-treated silica gel columns. The method showed high recovery rates (102.0 % and 91.2 % at 0.3 and 1.7 µg g⁻¹, respectively), with limits of detection and quantification of 3.0 ng and 7.8 ng, respectively. Validation with liver samples from Japanese quail orally exposed to 50 nm PS NPs revealed significantly elevated levels of PS NPs on Days 1 and 3 post-exposure (33.8 ± 1.5 and 34.1 ± 5.2 ng g⁻¹) compared to controls (13.2 ± 0.3 and 14.5 ± 2.0 ng g⁻¹) (p < 0.005). This method demonstrates effective removal of biological matrix components, enabling accurate and reproducible quantification of PS NPs in avian liver tissues. While the application to other biological samples will be explored in future studies, the method’s simplicity and minimal contamination make it a valuable tool for advancing risk assessments of NPs in biological systems.

Sakineh Gerayllo, Mohammad taghi Badeleh, Somayeh Ghorbani et al.

Background: Performing health-promoting behaviors is the most important and effective factor in maintaining the health of the elderly. Therefore, this study investigated health promotion behaviors and their related factors among the elderly population in Gorgan city. Methods: This cross-sectional descriptive-analytical study was conducted in 2023. Using a multistage sampling method, four comprehensive health centers in Gorgan city, Iran, were randomly selected, and a total of 170 elderly individuals aged over 60 years were conveniently recruited into the study. Data were collected using the standardized Health-Promoting Lifestyle Profile II (HPLP–II) questionnaire. After data collection, the data were analyzed and reported using SPSS version 26 software and parametric statistical tests, including t-test, ANOVA, and Pearson correlation coefficient, at a significance level of less than 0.05. Results: In this study, 44.1% of the elderly were male and 55.9% were female. The mean age of the participants was reported as 66.70 ± 7.23 years. A statistically significant difference was observed between the mean score of health promotion behaviors and demographic variables, including education level, economic status, and presence of underlying diseases (p < 0.05). Pearson correlation results indicated a positive correlation between health promotion behaviors and their subdomains (p < 0.05). The highest mean score was related to the interpersonal relations domain (32.28), while the lowest score belonged to the physical activity domain (13.52). Conclusion: Considering the results and the importance of health-promoting behaviors, particularly the low average scores in physical activity and stress management, it is necessary to emphasize these areas. Implementing continuous education programs based on elderly surveys, alongside strategic planning to encourage their active participation in health-related matters, can enhance health promotion among the elderly population.

Maryam Dehghanian, Simin Tahmasbi

Background: HIV/AIDS can be transmitted in healthcare settings including dentistry. Therefore, specific strategies are necessary to prevent its spread. This study aims to examine the for Knowledge Attitude and Practice of dentists and dental assistants regarding HIV infection and their knowledge of the oral manifestations of AIDS in public and private dental centers in Shahrekord. Methods: A cross-sectional survey was conducted in 2021 in Shahrekord, Iran, involving 108 dentists and 104 dental assistants through a census sampling method. Data were collected using validated questionnaires assessing knowledge, attitude, and performance regarding HIV/AIDS, as well as awareness of oral manifestations. Data analysis was performed using SPSS software, version 20 Results: According to the results, the mean scores for Knowledge Attitude and Practice of dentists were 16.18 ± 2.06, 53.73 ± 7.19, 70.04 ± 5.13, respectively. The average knowledge, attitude, and practice scores for dental assistants were 14.77 ± 2.1, 50.2±6.10, and 62.96 ± 5.11. There was no significant relationship between the knowledge and practice of dentists and dental assistants regarding HIV infection.) P > 0.05(. However, there was a significant relationship between dentists' knowledge of HIV infection and their knowledge of oral AIDS manifestations (p < 0.001). Conversely, no significant relationship was found between dentists' attitudes and practice and knowledge of oral AIDS manifestations (p < 0.05). Among the demographic data, only the age and work experience of dentists with knowledge of AIDS were significant (p < 0.05).                              Conclusion: The knowledge of dentists and dental assistants regarding AIDS is moderate, emphasizing the need for continuous training. Dentists scored higher in knowledge, attitude, and practice compared to dental assistants. However, the lack of a significant relationship between knowledge and practice suggests that theoretical education alone is insufficient, highlighting the importance of practical training.

Roya Botshekanan, Simin Tahmasbi

Background: Inter-professional collaboration (IPC) is vital in enhancing the quality of healthcare. Hence, this study aims to evaluate the attitudes of healthcare staff towards interprofessional cooperation. Methods: The study utilized a descriptive-analytical method. The medical teams from two hospitals of Shahrekord University, constituted the study population. Using stratified sampling, 325 individuals were selected.on 2020  Data were gathered by Jefferson Interprofessional Attitude Questionnaire, consisting of demographic information and IPC questions (20 items.. SPSS (20) was used for data analysis, and variables were assessed by descriptive tests, one-sample t-tests, t-student tests, Levene tests, and ANOVA. Results: The mean scores for attitudes towards IPC were as follows: general practitioners (4.54 ± 0.31), specialists (4.94±0.37), nurses (4.84±0.40), midwives (4.86±0.36), radiologists (4.86±0.43), nutritionists (4.69±0.46), laboratory staff (4.97±0.38), pharmacists (4.99±0.49), operating room anesthesiologists (5.09 ±0.38), environmental and occupational health experts (5.07±0.35), and psychologists (5.19±0.34). There was a significant difference (p < 0.05) between general practitioners and anesthesia and operating room experts. The relationship between demographic data with mean score of IPC was not significant, but it was significant forjob experience of 15-20 years (sig = 0.001 and F = 8.81). Conclusion: Managers should promote a positive attitude towards IPC within the healthcare team. By implementing an educational strategy, cooperation and performance among healthcare staff can be enhanced.

Seyedeh Nahid Seyedhasani, Afrooz Arzehgar, Mohamad Amin Bakhshali et al.

Background: Artificial intelligence (AI) and data science have transformed healthcare by enabling advanced analytical techniques. AI-driven solutions rely on sophisticated algorithms that require specialized programming languages. Understanding the most commonly used programming languages is essential for healthcare data scientists in order to navigate this domain effectively. This study explores the trends and applications of programming languages in healthcare data science, highlighting their roles in machine learning (ML) and related methodologies. Methods: A systematic search was conducted in PubMed/MEDLINE, Scopus, and Web of Science (WoS) covering the period 2010–2023. Keyword combinations included artificial intelligence, machine learning, programming languages, healthcare, and medical informatics. After screening, 174 studies that explicitly mentioned programming languages in their abstracts were included for analysis. Results: Public health accounted for 50.6% (n=88/174) of the reviewed studies, followed by medicine at 25.9% (n=45/174) and genomics at 14.4% (n=25/174). Python emerged as the most widely used programming language, appearing in 37.47% (n=65) of the articles, followed by R at 29.6% (n=51) and MATLAB at 17.8% (n=31). Machine learning methods were predominant in genomics and epidemiology. The temporal trend showed an increasing preference for Python, while MATLAB use declined in recent years. Conclusion: The selection of programming languages in healthcare data science is influenced by technical needs, application-specific requirements, and collaboration dynamics. Python’s versatility has made it a dominant choice, while R’s statistical focus and MATLAB’s specialized toolkits remain significant in specific domains. The findings provide a framework for educational strategies, guiding data scientists in making informed decisions about language proficiency. Future research should evaluate the long-term implications of programming language adoption on healthcare analytics.

Mintaek Oh, Chan Kim, Seung-Woo Seo et al.

Robots operating in human-centric or hazardous environments must proactively anticipate and mitigate dangers beyond basic obstacle detection. Traditional navigation systems often depend on static maps, which struggle to account for dynamic risks, such as a person emerging from a suddenly opening door. As a result, these systems tend to be reactive rather than anticipatory when handling dynamic hazards. Recent advancements in pre-trained large language models and vision-language models (VLMs) create new opportunities for proactive hazard avoidance. In this work, we propose a zero-shot language-as-cost mapping framework that leverages VLMs to interpret visual scenes, assess potential dynamic risks, and assign risk-aware navigation costs preemptively, enabling robots to anticipate hazards before they materialize. By integrating this language-based cost map with a geometric obstacle map, the robot not only identifies existing obstacles but also anticipates and proactively plans around potential hazards arising from environmental dynamics. Experiments in simulated and diverse dynamic environments demonstrate that the proposed method significantly improves navigation success rates and reduces hazard encounters, compared to reactive baseline planners. Code and supplementary materials are available at https://github.com/Taekmino/LaC.

Graciela Camacho-Fidalgo, Blain Judkins, Kylee Friederichs et al.

Augmented Reality Head-Mounted Displays (AR-HMDs) have proven effective to assist workers. However, they may degrade their Safety and Situational Awareness (SSA), particularly in complex and hazardous industrial settings. This paper analyzes, objectively and subjectively, the effects of AR-HMDs' on workers' SSA in a simulated hazardous industrial environment. Our evaluation was comprised of sixty participants performing various tasks in a simulated cargo ship room while receiving remote guidance through one of three devices: two off-the-shelf AR-HMDs (Trimble XR10 with HoloLens 2, RealWear Navigator 520), and a smartphone (Google Pixel 6). Several sensors were installed throughout the room to obtain quantitative measures of the participants' safe execution of the tasks, such as the frequency in which they hit the objects in the room or stepped over simulated holes or oil spills. The results reported that the Trimble XR10 led to statistically highest head-knockers and knee-knocker incidents compared to the Navigator 520 and the Pixel 6. Furthermore, the Trimble XR10 also led to significantly higher difficulties to cross hatch doors, lower perceived safety, comfort, perceived performance, and usability. Overall, participants wearing AR-HMDs failed to perceive more hazards, meaning that safety-preserving capabilities must be developed for AR-HMDs before introducing them into industrial hazardous settings confidently.

S. Padmanabhan, C. Joel, S. Mahalingam, J. R. Deepak, T. Vinod Kumar and Deborah Raj

Batteries are a widely utilized and simple method for powering electronic devices, particularly given the prevalence of individuals traveling to all gadgets. The escalating adoption of electric vehicles and portable electronic devices has led to a surge in the demand for lithium-ion batteries. Consequently, this has given rise to supply uncertainties in acquiring essential minerals such as lithium and cobalt, along with concerns about the proper disposal of dead batteries. The existing methods for battery recycling exhibit variations based on the individual chemistries of the batteries, hence influencing both cost factors and greenhouse gas emissions. Simultaneously, there exists a possibility for repurposing depleted batteries for low-tier energy storage applications. The absence of legislation pertaining to the secure storage and handling of waste streams contributes to the accumulation of refuse in exposed environments and the release of hazardous substances from landfills. In addition, contemporary battery manufacturing methods necessitate the utilization of innovative substances, such as ionic liquids for electrolytes and nanostructures for cathodes, to enhance the energy characteristics and longevity of batteries. The presence of uncertainties regarding the accurate assessment of the environmental consequences associated with novel battery chemicals has the potential to impede efforts aimed at recycling and containment. The objective of this analysis is to consolidate the existing knowledge regarding battery pollutants, both those that are recognized and those that remain uncertain, and to assess their potential environmental impacts. Additionally, this research aims to examine the current strategies and methods employed for the recycling of batteries in the circular economy.

Shilpi Goenka

Bisphenol A (BPA), bisphenol F (BPF), and bisphenol S (BPS) are contaminants of emerging concern (CECs) that humans are exposed to. In silico and zebrafish studies have linked BPA, BPF, and BPS exposure to pigmentation abnormalities, but no studies have examined their impact on primary human melanocytes. Herein, we examined the effects of BPA, BPF, and BPS exposure using human epidermal neonatal melanocytes. BPA induced the greatest cytotoxicity, followed by BPS, whereas BPF did not affect viability. BPA did not alter cellular melanin, whereas BPF and BPS diminished it at 100 µM. BPA decreased dendricity, as did BPF and BPS, although BPF was a potent suppressor of dendricity than BPS. BPA inhibited tyrosinase activity, followed by BPF, while BPS weakly suppressed tyrosinase activity. The tyrosinase activity was mostly recovered after the cessation of bisphenol treatments, although it remained lower for BPA and BPF. All bisphenols elevated cellular ROS production, although BPA and BPS showed non-monotonic dose responses. BPA and BPS augmented IL-6 cytokine secretion in melanocyte cultures treated with lipopolysaccharide, but BPF did not, suggesting that they exacerbate melanocyte inflammation. Collectively, these findings indicate BPA, BPF, and BPS, may impair melanocyte function and pose health hazards, warranting more study.

Sehar Razzaq, Beibei Zhou, Zakir Ullah et al.

Objectives: This study addresses the critical issue of Cd contamination in agricultural soils, posing substantial risks to crop productivity and food safety. While prior pot experiment has undertook this issue on a small scale, this study aims to evaluate the efficacy of selected best soil amendments, at a large-scale field experiment. Methodology: Press mud and humic acid were applied at 0.5%, while gypsum and Fe2O3 were applied at 5 mg/kg alone and with foliar application of Fe nanoparticles at 5 mg/L. Analysis: Comparative analysis with control revealed the immobilization efficiency of all amendments in descending order of effectiveness as follows: 100, 102, 104, 104, 105, 102, 105, and 105% for PM, HA, GYP, Fe, PM + Fe Nps, HA + Fe Nps, GYP + Fe Nps, and Fe + Fe Nps. Additionally, reduced growth, photosynthetic activities, and elevated levels of malondialdehyde and hydrogen peroxide, indicative of oxidative damage in control plant. Findings: Application of these amendments with foliar spraying of Fe Nps effectively mitigates Cd toxicity in maize crops, leading to improved growth, biomass, photosynthetic pigments, and antioxidant enzyme activities. Novelty/Improvement: These findings highlight the significance of exploring innovative approach of combining different amendments with foliar application of nanoparticles to mitigate Cd contamination and enhance soil health, thereby contributing to global efforts in ensuring food safety and security.

Nastaran Ahmadi, Parvane Rashidpour, Mohammadreza Mohammadi et al.

Background: Considering that personality disorders and parents' social capital are two important factors that can affect the social health of children and adolescents, therefore, the present study aims to examine the relationship between personality disorders and parents' social capital with the social health of children and adolescents in Yazd. Methods: This is a descriptive_ correlational study that was done in the province of Yazd in which 1035 children and adolescents between the ages of 6 to 18 participated. These participants were selected on the base of multi-stage random cluster sampling. The social capital questionnaire and parents' personality disorders (Millon Clinical Multiaxial Inventory - Third Edition (MCMI-III) which parents completed and the lifestyle questionnaire was completed by children and adolescents. Data analysis was done by applying descriptive statistics and calculation of odds ratio with a 95% confidence interval. Results: A total of 1035 parents children and adolescents were enrolled, participants (44.1%) were males and (55.9%) were females. Millon's test of fathers demonstrates a significant correlation with the average scores of structural social capital, cognitive social capital, communicative social capital, and total social capital (P-value < 0.001). Millon’s test of fathers had a significant relationship with total social capital in all age groups (P-value < 0.05). On the other hand, Millon’s test of mothers had a significant relationship with total social capital in fathers aged 19-34 years (P-value < 0.001). Conclusion: Family social capital improves children and adolescent’s social health. Consequently, caregivers have a significant impact on the social and psychological well-being of young individuals. Enhancing the level of social capital and promoting mutual understanding among parents is imperative to achieve this goal. It is necessary to strengthen the level of social capital,  and mutual understanding between parents. In addition, it can be suggested to pay more attention to the psychological characteristics of parents in the process of diagnosis and therapeutic intervention of children and adolescents.

Leah London Arazi, Amir Shpilka

This paper studies the hazard-free formula complexity of Boolean functions. Our first result shows that unate functions are the only Boolean functions for which the monotone formula complexity of the hazard-derivative equals the hazard-free formula complexity of the function itself. Consequently, they are the only functions for which the hazard-derivative approach of Ikenmeyer et al. (J. ACM, 2019) yields optimal bounds. Our second result proves that the hazard-free formula complexity of random Boolean functions is at most $2^{(1+o(1))n}$. Prior to this, no better upper bound than $O(3^n)$ was known. Notably, unlike in the general case of Boolean circuits and formulas, where the typical complexity is derived from that of the multiplexer function with $n$-bit selector, the hazard-free formula complexity of a random function is smaller than the optimal hazard-free formula for the multiplexer by an exponential factor in $n$. We provide two proofs of this fact. The first is direct, bounding the number of prime implicants of a random Boolean function and using this bound to construct a DNF of the claimed size. The second introduces a new and independently interesting result: a weak converse to the hazard-derivative lower bound method, which gives an upper bound on the hazard-free complexity of a function in terms of the monotone complexity of a subset of its hazard-derivatives. Additionally, we explore the hazard-free formula complexity of block composition of Boolean functions and obtain a result in the hazard-free setting that is analogous to a result of Karchmer, Raz, and Wigderson (Computational Complexity, 1995) in the monotone setting. We show that our result implies a stronger lower bound on the hazard-free formula depth of the block composition of the set covering function with the multiplexer function than the bound obtained via the hazard-derivative method.

Pradeep Dewapriya, Lachlan Chadwick, Sara Ghorbani Gorji et al.

While several sources of per- and polyfluoroalkyl substances (PFAS) are known, their use in consumer household products is far less explored. The aim of this study was to provide comprehensive bottom-up analysis of the types and concentrations of PFAS reported in the literature over the past decade. A total of 52 studies revealed 107 PFAS belonging to 15 different categories in 1040 consumer products. The highest number of products tested were from the USA (n = 389) followed by the Czech Republic (n = 111). Mean PFAS concentrations were highest in household firefighting products, followed by textile finishing agents and household chemicals. The highest diversity of PFAS was reported in textiles (72 PFAS). Fluorotelomer alcohol (FTOH), polyfluoroalkyl phosphate esters (PAPs), perfluorocarboxylic acid (PFCA) and perfluorosulfonic acid (PFSA) are the classes of PFAS of high interest. Eight out of 52 studies used High-Resolution Mass Spectrometry techniques. Highlighted knowledge gaps included (i) the development of analytical methods for detecting a range of PFAS in consumer products, (ii) method validation and QA/QC approaches, (iii) application of suspect and non-target analysis, and (iv) an understanding of human exposure risk. This review highlights that the presence of PFAS in consumer products is of concern and remains underexplored.

Laura M. Hernandez, Joel Grant, Parvin Shakeri Fard et al.

Many environmental factors affect the breakdown of plastics in aquatic environments, including exposure to ultraviolet (UV) irradiation and elevated environmental temperatures. More studies are needed to understand how these stressors contribute to plastic degradation, resulting in the release of smaller plastic particles. We studied the impact of environmentally relevant UV and temperature (37 °C) weathering of four high-production volume plastics (polystyrene, polypropylene, low-density polyethylene, and high-density polyethylene) suspended in water. Particle release was detected, characterized by scanning electron microscopy (SEM), and nanoparticles were quantified by nanoparticle tracking analysis (NTA). Weathering resulted in the release of micro- and nanoparticles that exhibited a plastic signature corresponding to the parent microplastic. Nanoparticle release is broadly correlated with an increase in the carbonyl index of the parent microplastic. Aged microplastics were characterized for physical and chemical changes. The impact of weathering on microplastic surface hardness and polymer oxidation depended on material type and environmental factors. Few to no particles were observed in controls, including controls that contained microplastics at 4 °C in dark conditions, highlighting the importance of weathering stimuli in particle release. These results show that plastic degradation needs to consider both the parent microplastic and the smaller particles that are formed.