Journal of chemical health & safety最新文献

There is a mental health crisis in academia affecting researchers and students at all levels. Reports today continue to highlight a problem that was raised nearly 30 years ago. That is not to say significant progress has not been made; simply having the topic on the minds of institutions is an achievement. However, there are costs associated with not proactively addressing this issue using all the tools we faculty have, just as strides have been made over the last 30 years in physical safety. I argue that these issues are interconnected and that physical and emotional safety are equally essential. It is our collective responsibility─faculty, students, staff, and bystanders─to actively foster a culture of safety. Here, I introduce the framework, STEM (Safely Teaching Empowerment Mentorship), which I use to intentionally address this challenge and offer suggestions for others to develop their own approaches.

As the demand for sustainable recycling of fibrous and polymeric waste increases, university laboratories play a crucial role in developing new technologies while training future professionals. This study presents a practical model for conducting safe, student-led laboratory research on the chemical recycling of textile waste with a focus on silk and cotton materials. It outlines safety measures for managing chemical and biological hazards including waste classification, disinfection protocols, and risk assessment procedures adapted for educational settings. Key innovations include the use of express tests for verifying bacterial decontamination, tailored workspace organization, and the application of solvent-based cleaning for material purity, a general approach to laboratory management that emphasizes student and staff responsibilities to health and safety. The study also reviews regulatory compliance and engineering controls specific to Russian and Uzbekistan academic settings. The proposed approach, supported by case studies, demonstrates the safe engagement of students in meaningful recycling research while mitigating risks associated with fibrous waste handling and chemical processing under the guidance of staff members who are not specialist health and safety professionals.

The intensive use of chemicals in laboratory work and pharmaceutical research generates a significant amount of hazardous waste, requiring rigorous management to protect the health of users (students, teachers, and technicians). Effective management is critical to minimize environmental contamination and occupational hazards in academic laboratories. Chemical waste from laboratory work is often discharged into sewers, threatening the water table. Sorting and collecting chemical waste are therefore a solution to reduce the risks associated with these substances. In this context, we conducted a study to determine the type of chemical waste generated by practical works of four teaching units at the Faculty of Pharmacy of Monastir in Tunisia: medicinal chemistry, organic chemistry, general chemistry, and pharmacognosy. In 70% of cases, waste revealed to be hazadous. In general, slightly more than half of the waste (55.3%) can be treated by neutralization, while the remaining 44.7% must be stored due to its hazardous or non-neutralizable nature. Once the waste was identified and classified, we sought treatment solutions to ensure its sorting at the source, inert, or secure storage, pending collection by an approved company. The aqueous residues must be chemically neutralized before being drained. This is only applicable to diluted mineral acids and bases C < 1 mol/L that are free of organic solvents, heavy metals, or persistent pollutants. Final pH control (6–8) and compliance with regulatory threshold are also required. Special containers made of high-density polyethylene are needed for contaning halogenated solvents, organometallic complexes, mercury, or chromium. This methodical approach aims to reduce health and environmental risks while educating university stakeholders about appropriate laboratory procedures. In conclusion, this study highlights the importance of a systematic approach to waste management as a crucial step toward safer and more responsible academic practices.

Evaluating the population pharmacokinetic parameters, biological half-life (HL), and apparent volume of distribution (V_d) is important for identifying potential risks of chemicals. In this study, we developed a framework of stacking machine learning models for predicting the two parameters, providing more generalized prediction methods for data from diverse sources. We built a larger database containing experimental data for 2934 and 1787 substances for HL and V_d, respectively, and considered two different chemical featurization methods. We employed five individual algorithms (Support Vector Regression, Random Forest, Gaussian Process, Artificial Neural Network, and Extreme Gradient Boosting) to construct the base models, and then combined predictions using Multiple Linear Regression to obtain 4 stacking models. Our stacking models performed well and outperformed the corresponding base models, with the extended connectivity fingerprint-based stacking model achieving the best predictive performance. The accuracy of the models, as defined by the applicability domain, was further improved, retaining more than 60% of the test data. Finally, we developed a publicly accessible online Web site (http://tkpara.hhra.net), where users can easily and quickly utilize our models. Our work provides data support for human health risk assessment of chemicals and for the use and management of chemicals or industrial products.

The rapid and accurate localization of hazardous chemical leak sources is critical for mitigating environmental damage, protecting public health, and ensuring an effective emergency response. However, the conventional source localization method can be slow and inefficient. To address this challenge, this research proposes and develops a novel integrated system leveraging computational fluid dynamics (CFD), sensor network optimization, and artificial neural networks (ANN) for the precise localization of chemical sources, focusing on ethanol leaks within a laboratory environment. The dispersion of ethanol gas was simulated using CFD, and the simulation data were used for sensor optimization. The sensor system, consisting of 10 sensors at vital locations, is the foundation for the development of the ANN-based source localization method. The environmental factors related to gas dispersion considered were wind speed, wind direction, and temperature, as well as the presence of exhaust and air supply systems. A total of 4 leakage points were studied. The concentration data measured by the sensor system were used to train the ANN to identify the most probable location of the ethanol leak. The model achieved a validation percentage of 87.5% and an average error of 0.0001% in determining the ethanol leak location of four release points in the study area. The findings demonstrate that this combined CFD-ML approach offers a powerful and efficient tool for improving emergency response protocols, enhancing safety measures, and mitigating potential financial losses during chemical incidents.

Institute of Science Tokyo has been actively conducting safety and health risk assessments (RA) across its science and engineering laboratories. Prior studies indicated a negative association between RA implementation rates and accident occurrence, suggesting that thorough RA practices can effectively reduce risks. Notably, hazards such as glassware and cutting tools were associated with higher accident rates, primarily resulting in cuts and puncture wounds. Effective RA requires concrete damage scenario assumptions and prioritization of engineering controls over worker-dependent measures. In August 2024, a chlorine gas leak incident occurred on campus due to a valve malfunction in an unused and uninspected gas cylinder. Despite the absence of injuries, the incident highlighted the need for enhanced preventive strategies. This study analyzes the high-pressure gas accidents that occurred over the past 20 years and assesses whether current RA practices adequately address these risks, with the goal of enhancing future safety strategies. During this time, seven high-pressure gas accidents were reported (five leaks, two ruptures), averaging 0.4 cases per year─significantly fewer than chemical-related incidents (285 cases, 14.3/year). In 2024, 49% of laboratories possessing gas cylinders conducted RA. Laboratories assessing toxic gases and predicting poisoning implemented more countermeasures, with a notable focus on engineering controls, reflecting greater hazard awareness. However, incomplete RA, as seen in the 2024 incident, may hinder the goal of zero accidents. The lack of regular inspections and aging infrastructure (pipes, valves, flanges) emerged as critical issues. These findings offer valuable insights for global institutions seeking to improve high-pressure gas safety and risk management.

Chemical Health Risk Assessment (CHRA) and Indoor Air Quality (IAQ) assessments are important aspects of assessment to be conducted in chemical laboratories. A local higher education institution was selected for the purpose of this study. The objective of this study is to propose an integrated approach that combines IAQ monitoring with CHRA to enhance the accuracy and effectiveness of chemical risk assessments in Malaysian academic laboratories under the provision of the OSHA 1994. 79 laboratories had undergone a thorough chemical health risk assessment based on the requirements of the Use and Standards Exposure of Chemicals Hazardous to Health Regulation (2000). Thirty-four laboratories were later selected and underwent further analysis using an Indoor Air Quality assessment based on the Malaysian Industrial Code of Practice on Indoor Air Quality (2010). Parameters such as relative humidity and ventilation indicator (carbon dioxide) were found to be significantly associated with Action Priority (AP-risk level) using the CHRA methodology at a 5% significance level. Integrating IAQ parameters with CHRA offers a more comprehensive, data-driven approach to identifying and managing chemical exposure risks in Malaysian academic laboratories.

Purpose: exposure to cleaning work has been associated with adverse effects on skin and the respiratory tract. However, quantitative data on exposure to chemicals among cleaning personnel are limited. We aimed to develop a new approach for cleaning chemical exposure quantification and to characterize cleaning personnel’s work environment. Methods: cleaning personnel (n = 12) from three workplaces participated. Personal air samples were collected with a 25 mm filter cassette containing an active adsorbent sample disc. Samples were analyzed with Gas Chromatography–Mass Spectrometry (GC–MS) in two ways, a fingerprint-based quantification and a nontarget screening to identify the range of chemicals. DataRAM pDR 1000AN was used to monitor particle peaks (1–10 μm). Additional information, such as glove use and health symptoms, was collected via questionnaires, diaries, and observations. Nasal patency was assessed using peak nasal inspiratory flow (PNIF) pre- and postshift. Results: Chemical exposures varied within and between cleaning personnel and between workplaces. Fifty-five chemicals were identified across the air samples, 21 of which were also found in analyzed products. Constituents from spray products were more often detected than from nonspray products. Peak exposures to particles were identified during bathroom cleaning or spray use. Cleaning personnel with self-reported respiratory allergies had lower PNIF values than other cleaners (p = 0.016). Workplace observations indicate an extremely long duration of glove use. Conclusion: This study successfully implemented a GC–MS-based chemical analysis, showing high variation in both amounts and chemical ranges between cleaning personnel. Estimated air concentrations were low compared to the Swedish occupational exposure limits. Use of occlusive gloves was high.

Billions of plastic bags (PBs) are consumed per day and are discarded after use. One way to reduce PB waste is distributed recycling and conversion into filament for 3-D printing as part of a circular economy, though little is understood about emissions during these processes. Herein, a “green” method was used to mix high-density polyethylene (HDPE) PBs from South Africa or the United States with virgin HDPE and extrude into filaments that were used to 3-D print tensile test specimens. Particle- and gas-phase emissions were measured throughout processing. On a particle number basis, during filament production, emissions mostly had sizes 1.2–5.2 nm, whereas during 3-D printing, emissions were mostly 5.6–560 nm. Particle yields (no./g plastic processed) were significantly (2–3 orders of magnitude) higher during 3-D printing compared with filament making. Acetone (range: 1.4–39.4 μg/g printed) and formaldehyde (range: 9.9–16.1 μg/g printed), the latter a potential occupational carcinogen, were released during 3-D printing. The Young’s modulus of test specimens was comparable to literature values for 3-D-printed virgin and recycled HDPE. Recycling waste PBs into filament for 3-D printing has myriad sustainability benefits, though the potential for human exposures to particles and gases is an important consideration for future life cycle analyses.

A novel electrochemical sensor based on aminobenzenesulfonate-functionalized silicon carbide (SiC) nanoparticles and graphene on a glassy carbon electrode (denoted as GC/Gr/SiC@ABS) was developed for the sensitive detection of nitroaromatic explosives, such as p-nitrophenol (p-NP), 2,4-dinitrophenol (2,4-DNP), 2,4-dinitrotoluene (2,4-DNT), and 2,4,6-trinitrotoluene (TNT). The high electron mobility in graphene, chemical stability of SiC nanoparticles, and modification with aminobenzenesulfonate have a synergistic effect to facilitate and enhance the electrocatalytic reduction of nitroaromatics at acidic pH (1.0). Using cyclic voltammetry, differential pulse voltammetry, and hydrodynamic amperometry, a detection limit of 95 nM, a sensitivity of 1.31 μA μM^–1 cm^–2, and a linear range of 0.5–20 μM for TNT were achieved. The superior sensitivity and selectivity of the designed sensor make it an expandable, cost-effective option for environmental and safety monitoring of nitroaromatic explosives.