A Dual-Level Rubric Design for Chemical Hazard Evaluation in Research Laboratories
DOI:
https://doi.org/10.11113/ijic.v16n1-2.704Keywords:
Chemical hazard evaluation, Rubric design, Laboratory Safety, Risk AssessmentAbstract
Evaluation of chemical hazards in research laboratories must balance the requirements of regulatory frameworks with the need for tools that are usable by frontline staff. Systems such as the Globally Harmonized System (GHS), the European Union’s CLP Regulation, OSHA’s Hazard Communication Standard, and Malaysia’s CLASS Regulations provide a common language for hazard communication but do not in themselves identify which chemicals in a laboratory inventory should be considered highest priority [3], [24]. This study introduces a dual-level rubric that combines a simplified tool for everyday use with a more detailed scoring framework for deeper analysis. Both rubrics feed into an Environmental Hazard Index (EHI) that integrates hazard categories with exposure-related dimensions such as quantity and frequency of use. The framework was applied to more than 500 records representing nearly 700 unique chemicals across research laboratories at Universiti Teknologi Malaysia (UTM) Kuala Lumpur. Results include a ranked list of Top 20 chemicals, per-laboratory profiles, distribution analyses, and hazard-type composition. The outputs not only enhance chemical safety management but also generate structured, auditable data suitable for AI-driven governance in laboratory safety.
References
Barr, D. (2019). Mercury spills in academic laboratories: Incidents and responses. Journal of Chemical Health & Safety, 26(4), 22–28. https://doi.org/10.1016/j.jchas.2019.04.005
Denlinger, K. L., Riddell, N., & Jacobs, D. (2018). Hazard assessment in research laboratories. Journal of Chemical Health & Safety, 25(2), 9–13. https://doi.org/10.1016/j.jchas.2017.12.001
Department of Occupational Safety and Health (DOSH) Malaysia. (2018). A manual of recommended practice on assessment of the health risks arising from the use of chemicals hazardous to health at the workplace (3rd ed.). Putrajaya: DOSH.
ECHA. (2017a). Guidance on the application of the CLP criteria (Version 5.0). European Chemicals Agency.
ECHA. (2017b). Guidance on labelling and packaging (Version 3.0). European Chemicals Agency.
Fatemi, F., Ghaffari, M., & Golbabaei, F. (2022). Implementation of chemical health, safety, and environmental risk assessment in academic laboratories. Safety and Health at Work, 13(3), 274–283. https://doi.org/10.1016/j.shaw.2022.03.001
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., … & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5
Gharibi, V., Dianat, I., & Moussavi Najarkola, S. A. (2018). Semi-quantitative risk assessment of occupational exposure to hazardous chemicals in university health laboratories. Safety and Health at Work, 9(3), 281–285. https://doi.org/10.1016/j.shaw.2017.09.005
Hua, M., Dawson, D. A., & Hayes, S. (2025). U.S. EPA’s hazard index approach for PFAS mixtures: Policy and science perspectives. Critical Reviews in Toxicology, 55(1), 1–22.
ISO/IEC. (2023). ISO/IEC 23894:2023 Artificial intelligence—Risk management. International Organization for Standardization.
Itumoh, E. J., Abah, J., & Omaka-Amari, L. (2024). Persistence, bioaccumulation, and toxicity of PFAS: A tutorial review. Sustainable Chemistry, 4(2), 111–145.
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2
Jankowska, E., Oczkowski, A., & Skowroń, J. (2023). Control banding-based methods for nanomaterial risk assessment: A review. Nanotoxicology, 17(10), 1255–1277. https://doi.org/10.1080/17435390.2023.2257912
Kemsley, J. (2016). Laboratory safety lessons from the UCLA fire case. Chemical & Engineering News, 94(4), 18–20.
McCarthy, J. F., Dols, J., & Smith, J. (2022). Balancing safety and efficiency in laboratory ventilation: A control-banding perspective. ACS Chemical Health & Safety, 29(4), 346–357. https://doi.org/10.1021/acs.chas.2c00045
Nasrallah, I., Al-Majali, S., & Al-Khalidi, H. (2023). Evaluating safety in academic laboratories using FMEA. Scientific Reports, 13, 19161. https://doi.org/10.1038/s41598-023-45678-9
NIST. (2023). Artificial intelligence risk management framework (AI RMF 1.0). National Institute of Standards and Technology.
Papadopoli, R., De Luca, V., & Giorgianni, C. (2020). Chemical risk awareness among academic laboratory workers: A cross-sectional study. Journal of Occupational Medicine and Toxicology, 15, 23. https://doi.org/10.1186/s12995-020-00286-3
Ramos, D., Lopes, S., & Fernandes, A. (2023). Managing engineered nanomaterials through control banding: An updated review. International Journal of Environmental Research and Public Health, 20, 5663. https://doi.org/10.3390/ijerph20095663
Rashid, N. N., Azmi, S. N., & Hamzah, A. (2021). Chemical hazard risk assessment in Malaysian university laboratories using HIRARC. International Journal of Advanced Research in Education and Society, 3(1), 89–99.
Schmidt, C. W. (2017). Beyond the bottle: Improving chemical inventory management. Environmental Health Perspectives, 125(9), 095001. https://doi.org/10.1289/EHP2387
Schröder, I., Riedel, M., & Grobe, N. (2020). Laboratory safety workshop proceedings: Hazard identification and risk analysis in academic labs. ACS Chemical Health & Safety, 27(5), 363–370. https://doi.org/10.1021/acs.chas.0c00025
Stahl, B. C., Wright, D., & Gallo, P. (2021). Responsible artificial intelligence: Rethinking AI ethics and governance. AI & Society, 36(1), 1–14. https://doi.org/10.1007/s00146-021-01108-5
UNEP. (2019). Global monitoring report on persistent organic pollutants under the Stockholm Convention. United Nations Environment Programme.
Whittlestone, J., Nyrup, R., Alexandrova, A., & Cave, S. (2019). The role and limits of principles in AI ethics: Towards a focus on tensions. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (pp. 195–200). https://doi.org/10.1145/3306618.3314289
Zalk, D. M., & Swuste, P. (2020). Barrier banding: Control banding principles for hazard prevention. ACS Chemical Health & Safety, 27(3), 219–228. https://doi.org/10.1021/acs.chas.9b00084
Downloads
Published
Issue
Section
License
Copyright (c) 2026 International Journal of Innovative Computing
This work is licensed under a Creative Commons Attribution 4.0 International License.
