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Review

Setting occupational exposure limits (OELs) for carcinogens: a focus on benzene

Jul 2026 · Critical Reviews in Toxicology · Vol 56, pp. 409 - 424 · 0 citations · 111 references
Medicine

TL;DR

A narrative review compares two approaches for setting Occupational Exposure Limits (OELs) for carcinogens, focusing on benzene, and supports the establishment of a more realistic OEL for benzene and minimizing the likelihood of over- or underestimating the associated risks.

Abstract

Abstract Since the 1950s, regulation of occupational carcinogen exposure has progressed from hazard identification to quantitative evaluation, driven by advances in cancer biology. This narrative review compares two approaches for setting Occupational Exposure Limits (OELs) for carcinogens, focusing on benzene. The first one applies a mode of action (MOA)-based approach to genotoxicity stratification, using linear extrapolation for direct genotoxicants and non-linear extrapolation for indirect genotoxicants. The second approach quantifies in vivo genotoxicity data, employing mathematical modeling to define the point of departure (POD) for non-linear extrapolation, regardless of the MOA. As benzene is an indirect genotoxicant, it is considered to have a threshold value. Applying the MOA-based approach to genotoxicity stratification, different European institutions and commissions have proposed OELs ranging from 0.05 to 0.25 ppm. The ACGIH has recommended a TLV-TWA of 0.02 ppm (skin notation). Based on a quantitative genotoxicity approach, the proposed OELs range from 0.021 to 0.07 ppm for benzene. Current evidence indicates that workplace benzene concentrations above 0.3 ppm do not adequately protect the health of exposed workers. Extending follow-up of existing cohorts and conducting robust quantitative genotoxicity assays in well-designed epidemiological and experimental studies are essential to reduce uncertainties and to confirm the most sensitive toxic effect, thereby supporting the establishment of a more realistic OEL for benzene and minimizing the likelihood of over- or underestimating the associated risks.

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