# Low-Dose Benzene Exposure Monitoring of Oil Refinery Workers: Inhalation and Biomarkers
## 1 Introduction
While _t,t_-MA could be a sensitive biomarker due to benzene's relatively high biotransformation rate (>4%), it presents significant disadvantages [6]. Firstly, benzene's _t,t_-MA biotransformation rate varies greatly between individuals (from <0.1 to 58%) due to exposure conditions [7]. Furthermore, _t,t_-MA is not a specific biomarker of low-dose exposure; it shows high variability in background levels since it is also a metabolite of _t,t_-sorbic acid (_t,t_-SA) [8]. Sorbic acid (SA) and its salts are used as preservatives in food and beverages, as well as in many drugs and cosmetics. Daily intake of SA and its salts has been reported to be on the order of tens of mg [9; 10]. The biotransformation rate of SA into _t,t_-MA was estimated to vary between 0.05 and 0.51% [8]. Therefore, the _t,t_-MA suitability as a biomarker for low-dose exposure of benzene is being questioned. According to some authors [11], only a small percentage of background _t,t_-MA values can be imputed to the benzene, with the rest being due to food intake. [PERSON] et al. [12] noticed a correlation between _t,t_-MA and SA in urine, but this was modestly related to blood benzene. Currently, ACGIH recommends a BEI of 500 \(\mathrm{\SIUnitSymbolMicro g}/\mathrm{g}\) creatinine per _t,t_-MA (end of shift), based on a TLV-TWA of 0.5 ppm. Due to the uncertainties related to _t,t_-MA, urinary benzene is considered the most specific indicator; however, SPMA can be used with U-B as a specific bio-indicator of exposure, since its only source is benzene [13]. The conversion rate of SPMA is low, but no other metabolic pathways from which SPMA originates are known. Some authors, although, have demonstrated the role of genetic polymorphisms on SPMA urinary levels as sensitive to \"null\" GSTT1 allele genotypes of glutathione transferses (GST), which reduce urinary elimination [14; 15]. Nevertheless, analytical issues must be treated. Compared to _t,t_-MA, U-B and SPMA are quite low; thus, highly sensitive and precise analytical methods are needed [16; 17]. These methods require sophisticated instruments and skilled technicians, both in sampling and analysis phases. Currently, pre-analytical and analytical factors limit the routine application of U-B [18]. In addition, SPMA, _t,t_-MA, and U-B are affected by smoking habits due to the direct inhalation of significant amounts of benzene in tobacco products; these doses might be of the same magnitude as low occupational exposure [19]. Thus, urinary cotinine (U-C) analyses are necessary to evaluate the smoking habits impact on occupational exposure measurements [20]. Dermal absorption of benzene is a further potential factor that must be factored in. However, it is generally considered less impactful than inhalation since benzene evaporates quickly from the skin. Furthermore, dermal exposure is prevented by the correct use of personal protective equipment. Nevertheless, our study monitored this by inspecting the internal part of workers' gloves at the end of their shift [21]. This study presents a fully automated analytical methodology that allows a robust and traceable assessment of occupational exposure to airborne benzene. In addition, the analysis, and the correlation between personal environmental sampling and biomarkers of benzene exposure, carried out with oil refinery workers employed in petroleum refining activities is shown. This evaluation aims to analyze the ability of U-B, _t,t_-MA, and SPMA to estimate occupational exposure at low airborne benzene concentrations, considering the effect of known confounding factors and assessing the internal dose that may derive from dermal exposure.