1.1. Identification of the agent

1.2. Production and use

1.3. Measurement and analysis

1.3.1. Detection and quantification

Common standard methods to assay benzene in air are presented in Table 1.1, along with selected methods for measuring some biomarkers of exposure in urine.

Table 1.1

Representative methods for the analysis of benzene in air and its main urinary biomarkers.

Assays to monitor benzene in air were first developed to measure air concentration in the workplace, including personal exposure of workers, and to assess compliance with occupational limits. Typically, to measure 8-hour exposure, air is pumped through cartridges containing charcoal or other suitable sorbents for the duration of the entire work shift. In the laboratory, benzene is desorbed from sorbent using solvents such as carbon disulfide (NIOSH, 2003, method 1501) or high-temperature thermal desorption (NIOSH, 1996, method 2549), and analysed with either a gas chromatograph equipped with a flame ionization detector (NIOSH, 2003, method 1501) or a mass spectrometer (NIOSH, 1996, method 2549). As an alternative, passive samplers do not need a pump and allow benzene sampling via air diffusion through them; see EPA (2014) for a review of different assays using passive samplers for the determination of volatile organic compounds, including benzene. The sensitivity of both active and passive assays depends on sample volume, desorption method, and instrumental analysis; a higher sampling volume, the use of thermal desorption, and detection by mass spectrometer are associated with greater sensitivity (detection by mass spectrometer also offers high specificity). The design determines the sampling rate for passive samplers; radial geometry warrants a high flow rate and therefore larger sampling volume over a specific sampling time (Cocheo et al., 2000).

A real-time monitor can be used to check for benzene leaks and to measure short-term exposure, especially during critical operations, allowing the simultaneous sampling of air and detection of benzene. Benzene can be separated from other chemicals by portable gas chromatography and detected by photoionization detector (NIOSH 1994, method 3700), or can be measured by extractive Fourier-transform infrared spectrometry (NIOSH 2002, method 3800).

The alternative method of measuring benzene exposure by biomonitoring dates to the 1980s (Lauwerys, 1983); the first biomarkers, such as phenol, have been progressively abandoned in favour of biomarkers that are less abundant but more specific. The currently recommended biomarkers for assessment of benzene exposure in the workplace include urinary trans,trans-muconic acid (t,t-MA), urinary S-phenylmercapturic acid (SPMA), and urinary benzene (INRS, 2017).

t,t-MA is a urinary metabolite of benzene accounting for about 4% of the absorbed dose. Formed and excreted in urine with rapid kinetics with a half-life of about 5 hours (Boogaard & van Sittert, 1995), it is useful for assessment of recent exposure. It is measured using high-performance liquid chromatography with an ultraviolet detector (Lee et al., 2005), and standardized assays are present on the market. Its limitation is poor specificity, as t,t-MA is also produced by the metabolism of the preservative sorbic acid or sorbates contained in food and beverages (Ruppert et al., 1997; Weaver et al., 2000). t,t-MA is recommended when exposure is higher than 0.2 ppm (Kim et al., 2006a), depending on the amount of sorbic acid preservatives in the diet.

SPMA is a urinary metabolite of benzene accounting for less than 1% of the absorbed dose; it is formed and excreted in urine with rapid kinetics (half-life of ~9 hours; Boogaard & van Sittert, 1995). SPMA in urine is a specific biomarker, and is assayed using solid phase extraction followed by liquid chromatography coupled with tandem mass spectrometry (NIOSH, 2014, method 8326). The limitations of the use of this biomarker are the few standardized assays available and the high cost of the equipment to perform the assay. The variability associated with genetic polymorphism of glutathione S-transferase enzymes also affects urinary levels of SPMA (see Section 4.1).

Unmetabolized benzene is excreted in urine in a tiny proportion (< 0.1%) and with rapid kinetics (a half-life of a few hours). It is a specific biomarker, being uniquely indicative of exposure to benzene. It is assayed using online headspace sampling followed by gas chromatography or mass spectrometry (Fustinoni et al., 1999). A limitation in the use of urinary unmetabolized benzene is the lack of standardized assays; in addition, the volatility of benzene in urine may cause the loss of the analyte if no precautions are taken during sampling and in the storage of samples.

Both SPMA and urinary benzene are currently the biomarkers of choice to assess exposure to benzene in studies involving the general population (Fustinoni et al., 2005; Lovreglio et al., 2011; Andreoli et al., 2015).

1.4. Occurrence and exposure

1.4.1. Occupational exposure

Benzene is a ubiquitous pollutant that is present in several industries and occupations, including the production and refining of oil and gas, the distribution, sale, and use of petroleum products, coke production, the manufacture and use of chemical products, automobile repair, shoe production, firefighting, and various operations related to engine exhaust. Due to the high volatility of benzene, occupational exposure to benzene mainly occurs via inhalation. Benzene also penetrates skin, but the degree of dermal absorption of benzene will depend upon the exposure scenario. Dermal absorption will vary according to the tasks being performed (e.g. dipping machinery parts, immersion of hands, or using petroleum-based products as degreasing agents), the benzene content of the product, the composition of the product containing benzene, contact time, and the area of the body on which the chemical resides (Kalnas & Teitelbaum, 2000; Williams et al., 2011; Jakasa et al., 2015). In these scenarios, the exposure will not usually be to pure benzene.

The major industries and occupations in which workers are potentially exposed to benzene are reviewed in the following sections. This summary is not exhaustive, and the interested reader is referred to several reviews of occupational exposure to benzene across industries that have been published for Europe and North America (Runion & Scott, 1985; Nordlinder & Ramnäs, 1987; van Wijngaarden & Stewart, 2003; Capleton & Levy, 2005; Williams et al., 2008) and Asia (Kang et al., 2005; Liang et al., 2005; Navasumrit et al., 2005; Liu et al., 2009; Park et al., 2015). For some industries or applications, information in the literature is limited. For example, the use of pure benzene as a solvent and reagent in chemical laboratories is well known, but no report on exposure level of benzene was found for laboratory technicians apart from in the petroleum industry.

Although not exhaustive, Table 1.2 gives a summary of reported personal full-shift airborne benzene concentrations, while Table 1.3 summarizes biomonitoring data for the industries.

Table 1.2

Occupational exposure to benzene in air: personal measurements.

Table 1.3

Summary of selected studies on the biological monitoring of occupational exposure to benzene.

(a) Production, refining, and distribution of petroleum and petroleum-derived products

The petroleum industry can be divided into upstream and downstream segments. The upstream segment refers to conventional exploration, extraction, and production of crude oil and natural gas, described in the following section, as well as unconventional oil and gas development (UOGD). UOGD involves high-volume hydraulic fracturing, commonly referred to as “fracking”, which is coupled to (vertical or horizontal) drilling to extract oil and gas from shale formations (i.e. extraction of materials other than crude oil and natural gas). UOGD includes the process of injecting large volumes of water, proppants (often sand), and potentially hazardous chemicals into wellbores at high pressure, fracturing the rock and enabling the outflow of trapped oil or gas from shale formations (EPA, 2013). The downstream segment consists of refinery operations (production and ancillary operations within the refinery and distribution depots, e.g. tank dipping, pump repairs, filter cleaning), distribution (loading of ships, railcars and road tankers, delivery to service stations), and retail of the petroleum fractions (attendant or self-service filling of customer vehicles).

(i) Upstream petroleum industry (conventional oil and gas extraction)

During drilling, the revolving steel bit must be lubricated and cooled, the well requires pressure support, and the rock cuttings must be transported to the surface. Drilling fluid, a complex oil- or water-based mixture, is used for these purposes. The characteristics of the hydrocarbon base oils in the drilling fluids have changed over time. Diesel as a base oil for drilling was gradually replaced in the early 1980s in the United Kingdom and Norway by petroleum-mineral oils with a reduced aromatic content; non-aromatic mineral oils (aromatic content < 0.01%) were used after 1998 (Gardner, 2003; Steinsvåg et al., 2006, 2007; Bråtveit et al., 2012). The mud-handling areas were originally designed for water-based mud that did not generate vapours, with open flow lines and mud pits. Other than measurements of oil mist and oil vapour, there have been very limited attempts to characterize the exposure regarding its composition. Theoretically, however, hydrocarbon and benzene exposure can occur through contamination of the drilling fluid from the geological formation in which it is drilled, or from hydrocarbons that are added to the drilling fluid to improve drilling properties, as in diesel and drilling fluids containing aromatics in the 1980s (Verma et al., 2000; Steinsvåg et al., 2007). With the exception of eight area measurements made during drilling in Canada showing a full-shift concentration of 0.006 mg/m³ (with a highest measurement of 0.019 mg/m³ and one personal measurement of < 0.010 mg/m³), no information on this exposure scenario was available (Verma et al., 2000).

The separation and processing of crude oil and natural gas into crude oil, condensate, gas, and produced water before transport to shore via pipelines or tank ships takes place in a closed processing equipment and pipeline system. All four petroleum streams contain benzene, however, and the likelihood of exposure to benzene increases whenever the system is opened. The composition of crude oil and gas condensate varies between oil and gas fields and depends upon several factors, such as geological conditions in the reservoirs and the production age of the oil field, but typically lies within the range of < 0.01 and 3.0% by weight (Verma & des Tombe, 1999; Verma et al., 2000; Kirkeleit et al., 2006a), with benzene content in condensate being higher. The full-shift mean exposure in the production of oil and natural gas is usually well below 1 ppm [3.19 mg/m³] benzene, the 8-hour permissible exposure limit set by the Occupational Safety and Health Administration (OSHA, 2017), during ordinary activity (Glass et al., 2000; Verma et al., 2000; Kirkeleit et al., 2006a; Bråtveit et al., 2007; Steinsvåg et al., 2007) (Table 1.2). However, some specific tasks, such as cleaning and maintenance of tanks and separators, pipeline pigging operations, and storage tank gauging, may cause short-term exposures in excess of this (Runion, 1988; CONCAWE, 2000; Glass et al., 2000; Verma et al., 2000; Kirkeleit et al., 2006a; Esswein et al., 2014).

With technological advances and more efficient reservoir completion techniques, UOGD has grown in the past decades. The only study available for this segment indicates that the potential for exposure is higher than for conventional oil and gas extraction (Esswein et al., 2014; Table 1.2).

(ii) Downstream petroleum industry: refining

The full-shift exposure to benzene during ordinary activity in the refining petroleum industry tends to be higher than for upstream activities, but still with average values well below 1 ppm [3.19 mg/m³] (Nordlinder & Ramnäs, 1987; Verma et al., 1992, 2001; CONCAWE, 2000, 2002; Glass et al., 2000; Akerstrom et al., 2016; Almerud et al., 2017) (see Table 1.2). However, the range of exposure indicates potential for exceeding 1 ppm [3.19 mg/m³]; this is particularly true for refinery maintenance, laboratory technicians, and dock workers. Specific tasks such as sampling, opening of vessels for maintenance and cleaning, and loading of petrol may cause high short-term exposure (Runion, 1988; Hakkola & Saarinen, 1996; Vainiotalo & Ruonakangas, 1999; Davenport et al., 2000; Verma et al., 2001; Kreider et al., 2010; Widner et al., 2011). However, while workers before 2000 were likely to have been exposed to higher concentrations of benzene because of a higher content of benzene in reformate stream (Burns et al., 2017), the range of benzene exposures reported in recent studies is considerably reduced (Campagna et al., 2012; Akerstrom et al., 2016; Almerud et al., 2017; Burns et al., 2017). Some of the reported exposure levels are given in Table 1.2.

(iii) Downstream petroleum industry: distribution

In the petroleum transport chain there is a potential for exposure at each point where the products are stored and transferred, and the reported exposures tend to be higher than for production and refinery workers (Halder et al., 1986; Javelaud et al., 1998; CONCAWE, 2000, 2002; Glass et al., 2000). However, because of a lowered content of benzene in petrol (Verma & des Tombe, 2002; Williams & Mani, 2015), as well as the recent introduction of vapour recovery systems in the petroleum distribution chain in at least developed countries, the exposure to benzene for these groups of workers has declined over the years. Some of the reported exposure levels are given in Table 1.2.

Williams et al. (2005) reviewed the available industrial hygiene data describing exposure during the marine transport of products containing benzene (1975–2000). Although there were differences in sampling strategies and in the benzene content of the liquids being transported, air monitoring data revealed concentrations of 0.2–2.0 ppm [0.64–6.4 mg/m³] during closed-loading and 2–10 ppm [6.4–31.9 mg/m³] during open-loading operations. These estimates are somewhat higher than average values, but in line with the range of exposures reported in other reviews (CONCAWE, 2000, 2002; Verma et al., 2001).

(iv) Oil spill clean-up operations

The petroleum production and distribution scenario for which there is a lack of knowledge on exposure levels is the clean-up of an oil spill. In an oil spill field trial in the North Sea in 2016, full-shift measurements of benzene for personnel closest to the slick yielded a geometric mean exposure of 0.2 ppm benzene [0.64 mg/m³] (Gjesteland et al., 2017). No exposure to benzene was detected in personal samples collected during the Deepwater Horizon spill of light crude oil (Ahrenholz & Sylvain, 2011). In the Prestige and Nakhodka spills of heavy fuel oil, the measured benzene exposure was low because of the low content of volatile organic compounds (Morita et al., 1999; Pérez-Cadahía et al., 2007).

(v) Retail petrol stations

Averaged full-shift exposures of up to 0.65 mg/m³ (McDermott & Vos, 1979; Runion & Scott, 1985; Foo, 1991; Lagorio et al., 1993; CONCAWE, 2000, 2002; Verma et al., 2001; Chakroun et al., 2002; van Wijngaarden & Stewart, 2003; Fustinoni et al., 2005) and 59 µg/m³ [0.059 mg/m³] (Carrieri et al., 2006; Lovreglio et al., 2010, 2014; Campo et al., 2016) have been measured before and after 2000, respectively. Reported benzene exposure levels (Table 1.2 and Table 1.3) suggest that, in higher-income countries, at least, they have decreased with time. The decline is mainly ascribed to a decrease in benzene content in gasoline, as well as the installation of vapour recovery systems at retail gas stations capturing vapours during vehicle fuelling. The information on exposure for petrol station attendants in low- and middle-income countries is scarce, but available studies indicate somewhat higher concentrations of benzene for these workers compared with those reported from more developed countries (Navasumrit et al., 2005; Bahrami et al., 2007).

(b) Exposure from engine exhaust

Benzene from engine exhaust represents a potential exposure for professional drivers and urban workers, including taxi drivers, police, street workers, and others employed at workplaces with exposure to exhaust gases from motor vehicles (Nordlinder & Ramnäs, 1987). Reported exposure concentrations for these workers differ with region (Table 1.2). Reported median exposures for traffic police in Italy (2005) and Thailand (2006) were 6.1 µg/m³ and 38.2 µg/m³, respectively (Manini et al., 2008; Arayasiri et al., 2010). Cloth vendors and grilled-meat vendors in Thailand have been reported to have experienced mean exposures of 22.61 ppb [73 µg/m³] and 28.19 ppb [90 µg/m³], respectively (Navasumrit et al., 2005). Although the data for urban workers in low- and middle-income countries are scarce, the available information on both workers and outdoor air concentrations (see Section 1.4.2) indicates exposure to higher concentrations for these workers relative to the levels typical of higher-income countries.

(c) Automobile repair

Workers employed in automobile repair shops and recycling are potentially exposed to benzene through contact with gasoline vapour and engine products. Measured mean exposures before 2000 are typically less than 1 ppm (Nordlinder & Ramnäs, 1987; Foo, 1991; Hotz et al., 1997; Javelaud et al., 1998; Egeghy et al., 2002) (Table 1.2).

(d) Coke production

Benzene exposure is a potential hazard in the carbonization of coal to form coke used in the manufacture of steel, produced in the refining of the crude coke fractions and the by-products. China is currently the largest coke producer globally; average benzene exposure concentrations of 0.705 and 0.290 mg/m³ were measured during a survey of two plants, where charging and pushing activities accounted for almost 70% of the exposure at the topside (He et al., 2015). During the period 2005–2010 in Poland, median exposures of 0.09–0.37 mg/m³ according to job category were reported (Bieniek & Łusiak, 2012). Median exposure at a cokery in a shale oil petrochemical plant in Estonia was reported as 0.4 ppm [1.28 mg/m³] one decade earlier (Kivistö et al., 1997). Average exposure for coke oven workers in the USA during 1978–1983 was reported as 8.46 ppm [27.02 mg/m³] (van Wijngaarden & Stewart, 2003), while reported mean levels in the United Kingdom in 1986 ranged from 0.31 ppm [0.99 mg/m³] in coke oven workers to 1.32 ppm [4.22 mg/m³] in by-product workers (refining process of benzene) (Drummond et al., 1988).

(e) Rubber manufacturing

Benzene has historically been used in the manufacture of rubber, including the production of tyres and general rubber goods, and the process of retreading. It has also been used as a component in cement, glue, binding agents, and release agents, but has mainly been replaced by other agents (IARC, 2012). Some of the solvents used today still contain low benzene concentrations, however. From a pooled dataset on rubber manufacture workers in China used in a nested case–cohort study within the National Cancer Institute-Chinese Academy of Preventive Medicine (NCI-CAPM) cohort (n = 585), arithmetic and geometric means of 157.3 mg/m³ and 45.6 mg/m³ (geometric standard deviation, GSD, 6.4 mg/m³) were reported from 1949 until after 2000 (Portengen et al., 2016). Averages of 1.42 ppm [4.54 mg/m³] (n = 179) and 0.34 ppm [1.09 mg/m³] (n = 4358) for rubber manufacture and production of tyres and inner tubes, respectively, have been reported from the USA and Canada (Runion & Scott, 1985; van Wijngaarden & Stewart, 2003).

The exposure levels in a cohort of workers producing rubberized food-coating materials have been estimated several times (Rinsky et al., 1981, 1987; Paustenbach et al., 1992; Crump, 1994; Utterback & Rinsky, 1995). In the latest retrospective assessment, the highest exposures (involving the jobs of neutralizer, quencher, knifeman, and spreader) were typically 50–90 ppm during 1939–1946 (lower during 1942–1945) and 10–40 ppm during 1947–1976 at the 50th percentile (Williams & Paustenbach, 2003). These estimated exposure levels were two to four times as great as for other jobs in this same cohort.

Kromhout et al. (1994) performed an exposure assessment of solvents in 10 rubber-manufacturing plants in the Netherlands in 1988. The use of particular solvents varied widely, and those selected for the quantitative assessment of exposure were based on the individual solvents, cements, and release and bonding agents used in the plants included in the study. The final assessment was restricted to paraffins, aromatic compounds, chlorinated hydrocarbons, ketones, alcohols, and esters. Benzene was not included, suggesting that the products used in the European rubber industry did not contain benzene from the late 1980s (Kromhout et al., 1994).

(f) Shoemaking

Shoemaking consists of several steps, including: the cutting of the material (leather, rubber, plastic, etc.), fitting of parts, sewing and gluing the various parts together, and finally the trimming and buffing of the shoes (Wang et al., 2006). Benzene is used as a solvent in glues, adhesives, and paint in the shoe-manufacturing process. Dermal exposure to benzene has been reported as low, and does not significantly contribute to systemic exposure of benzene (Vermeulen et al., 2004). Although no longer as relevant in Europe and North America as in the past, this source of occupational benzene exposure is still of importance in some countries, notably in Asia.

In a recent Chinese study of shoe factory workers, mean exposures of 21.86 ppm [69.83 mg/m³] and 3.46 ppm [11.05 mg/m³] were reported for a small and large factory, respectively (Vermeulen et al., 2004). Benzene and toluene exposures were partly determined by the degree of contact with glues, the benzene and toluene content of each glue, air movement, and ventilation patterns. From a pooled dataset on workers in the shoemaking industry in China used in a nested case–cohort study within the NCI-CAPM cohort (n = 635), arithmetic and geometric means of 69.2 mg/m³ and 8.1 mg/m³ (GSD, 10.8 mg/m³) were reported for the period from 1949 to after 2000 (Portengen et al., 2016).

In a benzene exposure assessment in 12 Iranian shoemaking workshops (semiautomated, year not given) mean exposures (standard error) for three consecutive months were 1.10 (0.11) ppm [3.51 (0.35) mg/m³], 1.37 (0.14) ppm [4.38 (0.45) mg/m³], and 1.52 (0.18) ppm [4.86 (0.57) mg/m³] (Azari et al., 2012).

In the shoemaking industry in Spain, where benzene was unintentionally present in the adhesive as a contamination, the mean benzene exposure concentrations for the periods 2002–2003, 2004–2005, and 2006–2007 were 0.05 mg/m³, 0.07 mg/m³, and 0.05 mg/m³, respectively (Estevan et al., 2012).

(g) Firefighting

Because of the incomplete combustion and pyrolysis of organic and synthetic materials, respectively, firefighters are potentially exposed to benzene during firefighting (municipal and wildfire), overhaul, and training. The heterogeneity of types of fires, time spent at fires, and types of structure or material burning, as well as the limited collection of data due to the extreme conditions, have hampered the characterization of exposure to benzene by firefighters and data are scarce. However, the few reported data suggest that the full-shift exposure is much less than 0.5 ppm, and is higher for the knockdown of wildfires compared with structure fires (Reinhardt & Ottmar, 2004); the potential for short-term exposure much higher than 1 ppm [3.19 mg/m³] has also been reported (Bolstad-Johnson et al., 2000; Austin et al., 2001).

(h) Occupational use of products containing benzene

Benzene was formerly a common solvent and ingredient in a variety of products, including paint, printing inks, and glues, and is a natural component in products derived from petroleum. However, the benzene content in these products has either been replaced or reduced following regulations and other initiatives in the 1980s and 1990s.

(i) Application of paint

Benzene has been largely replaced as a solvent in paint, but is still used in some countries. Although this was a significant source of benzene exposure historically, data are lacking on benzene exposure during the use of paint that contains benzene as a constituent or contamination. In a review of benzene exposure in industries using paint in China, combining all the years during 1956–2005, relevant median exposures were reported for many activities, including: spray painting, 43.9 mg/m³ (maximum, 3212 mg/m³); brush painting, 58.2 mg/m³ (maximum, 3373.5 mg/m³); mixing, 53.6 mg/m³ (maximum, 139.4 mg/m³); immersion, 27.4 mg/m³ (maximum, 540.0 mg/m³); and paint manufacturing, 15.08 mg/m³ (maximum, 344.0 mg/m³) (Liu et al., 2009). From a pooled dataset on spray painting in China (n = 3754) used in a nested case–cohort study within the NCI-CAPM cohort, arithmetic and geometric means of 62.5 mg/m³ and 9.4 (GSD, 8.9) mg/m³ averaged over the period from 1949 to after 2000 were reported (Portengen et al., 2016). The corresponding exposure concentrations for painting (n = 1099) were 115.3 mg/m³ and 17.1 (GSD, 10.2) mg/m³. In a pilot study, eight painters in small car repair shops in Italy were reported to have experienced an arithmetic mean exposure of 9.8 mg/m³ (range, 0.4–53 mg/m³) over a period of 236–323 min (Vitali et al., 2006). The authors ascribed the benzene exposure mainly to fuel vapour and gasoline used for degreasing and paint dilution.

(ii) Printing industry

Benzene was withdrawn from its significant use as a solvent of printing inks in Europe in the 1950s, but was used in the USA in the rotogravure processes from the 1930s until the beginning of the 1960s (IARC, 1996). Reported mean exposures from the printing industry are 0.58 ppm [1.85 mg/m³] in the USA (van Wijngaarden & Stewart, 2003), and 0.017 ppm [0.0543 mg/m³] in the Republic of Korea (Kang et al., 2005), but it is still a concern in some low- and middle-income countries. From the pooled dataset from the NCI-CAPM cohort (n = 232), arithmetic and geometric means of 94.1 mg/m³ and 8.2 (GSD, 13.0) mg/m³ averaged over the period from 1949 until after 2000 were reported (Portengen et al., 2016).

(iii) Use of petroleum-based products containing benzene in small amounts

Benzene is a residual component (< 0.1%) in petroleum-based products such as mineral spirit, jet fuel, degreasing agents, and other solvents. There are insufficient data to draw any conclusions on air concentrations generated when using these products, but estimations and reported exposure after simulations and controlled testing performed in relation to lawsuits can be found in several publications (Fedoruk et al., 2003; Williams et al., 2008; Hollins et al., 2013). There have been some reports on exposure to benzene during handling of various types of jet fuel; although exposure concentrations vary between the studies, work tasks, and circumstances, the reported values indicate a potential for exceeding exposures of 1 ppm [3.19 mg/m³] (Holm et al., 1987; Egeghy et al., 2003; Smith et al., 2010).

(i) Biological monitoring of occupational exposure to benzene

Although the measurement of benzene in air is the most common method of investigating exposure in occupational settings, biomonitoring is considered the best technique as the characteristics of the individual and the use of protective equipment are taken into account. Moreover, when dermal exposure is a consideration, biological monitoring is the only system that can integrate both exposure routes.

A summary of selected studies on occupational exposure to benzene using biological monitoring is provided in Table 1.3. Investigated occupational settings include: the petrochemical industry (Boogaard & van Sittert, 1995, 1996; Kirkeleit et al., 2006b; Bråtveit et al., 2007; Hoet et al., 2009; Carrieri et al., 2010; Fustinoni et al., 2011; Hopf et al., 2012); cookery (Kivistö et al., 1997); and manufacturing, including chemical manufacturing (Boogaard & van Sittert, 1995, 1996; Kivistö et al., 1997), shoemaking (Kim et al., 2006a; Lv et al., 2014), adhesive production, and rubber and paint manufacturing (Waidyanatha et al., 2001, 2004). Exposure to gasoline vapours encountered by filling station attendants, tanker fillers, and fuel tanker drivers (Boogaard & van Sittert, 1995, 1996; Chakroun et al., 2002; Fustinoni et al., 2005; Bahrami et al., 2007; Lovreglio et al., 2010; Campo et al., 2016) and traffic exhaust exposure, such as that incurred by traffic police, and taxi and bus drivers (Fustinoni et al., 2005; Manini et al., 2006; Bahrami et al., 2007), were also investigated. A few studies have investigated exposure to benzene encountered by firefighters (Caux et al., 2002; Fent et al., 2014).

Benzene is present in a complex mixture of chemicals in the large majority of these settings, although this percentage can be small in the case of gasoline vapours and traffic exhaust fumes, for example.

In 1995 and 1996, Boogaard and van Sittert investigated 184 workers exposed to benzene in various occupational settings (natural gas production platforms, chemical manufacturing, oil refineries, fuel tank drivers, and gasoline attendants), measuring personal benzene exposure and two minor urinary metabolites (t,t-MA and SPMA) in urine samples collected at the end of shifts. Personal exposure ranged from less than 0.01 to 100 mg/m³. A group of 52 unexposed employees was also investigated as controls. It was estimated that about 4% and 0.1% of the inhaled dose was excreted in urine as t,t-MA and SPMA, respectively, with half-lives of about 5 hours and 9 hours. The correlation between personal benzene exposure and both biomarkers was very good, demonstrating their utility as biomarkers of exposure. Owing to the presence of background levels of t,t-MA in the urine of workers not exposed to benzene, this biomarker would be of limited use for assessing low benzene concentrations (Boogaard & van Sittert, 1995, 1996).

In later years, other studies in China investigated manufacturing workers exposed to high benzene concentrations in the rubber, adhesive, and paint production industries (up to 329 ppm [1051 mg/m³]) (Waidyanatha et al., 2004) and in factories manufacturing glue, shoes, and sporting goods (up to 107 ppm [342 mg/m³]) (Qu et al., 2003). Several benzene metabolites, such as urinary phenol, catechol, hydroquinone, t,t-MA, and SPMA, were investigated and all found to be correlated with personal benzene exposure. SPMA and t,t-MA demonstrated their superior ability as biomarkers of recent exposure, however; they were present in lower background concentrations in workers not exposed to benzene and they revealed a higher sensitivity in correlating with lower concentrations of occupational benzene. Urinary unmetabolized benzene was also measured, and demonstrated a very good correlation with personal benzene exposure and with the other urinary biomarkers (Waidyanatha et al., 2001).

Another study in China in 2000 applied urinary biomarkers to assess exposure in 250 shoemaking workers, using 139 clothes manufacturing workers as controls. Biomarkers were consistently elevated when the median benzene exposure level of the group was at or above 0.2 ppm for t,t-MA and SPMA, 0.5 ppm for phenol and hydroquinone, and 2 ppm for catechol (Kim et al., 2006a).

Much lower occupational exposures in fuel tanker drivers, filling station attendants, taxi and bus drivers, and traffic police were reported in Italy, with levels of up to 1017 µg/m³ [1.017 mg/m³] (Fustinoni et al., 2005; Manini et al., 2006; Lovreglio et al., 2010; Campo et al., 2016). Only the most specific biomarkers were measured in these studies, including urinary t,t-MA, SPMA, and unmetabolized benzene. These studies reported on the possibility of correlating very low benzene concentrations with both SPMA and urinary benzene, but not with t,t-MA. Moreover, these studies demonstrated the impact of tobacco smoking on the levels of biomarkers; smokers without occupational exposure to benzene had higher levels of benzene biomarkers than non-smoking filling station attendants (Fustinoni et al., 2005).

[The Working Group noted that, considered together, these studies showed that urinary SPMA and unmetabolized benzene are the most specific and sensitive biomarkers for the investigation of low occupational exposures, such as those found in most work settings. They are short-term biomarkers of exposure, and the best sampling time is at the end of the exposure or shift.]

1.4.2. General population exposure

Benzene is present ubiquitously in the environment, for example as a result of emissions from forest fires and volcanoes. However, the major environmental sources of benzene are anthropogenic. Such sources include industrial emissions, the burning of coal and oil, motor vehicle exhaust, and fuel evaporation. The primary route of environmental exposure to benzene is through inhalation, although exposure from ingestion of water and foods contaminated with benzene can also occur (ATSDR, 2007). Exposure to benzene can occur in microenvironments due to the evaporation of gasoline from parked cars in attached garages, while driving, or while pumping gasoline, or by spending time outdoors in close proximity to heavily trafficked areas or gasoline service stations. Benzene is a component of tobacco smoke; exposure therefore occurs when smoking or inhaling sidestream smoke (environmental tobacco smoke) (IARC, 2004).

(a) Outdoor air levels of benzene

Outdoor air concentrations of benzene vary widely throughout the world (see Table 1.4). In a review of air quality data from 42 European countries in 2014, the European Environment Agency reported no exceedances of the annual limit for benzene (5 μg/m³) (European Environment Agency, 2016). Earlier, Guerreiro et al. (2014) reported that very few (0.9%) monitoring stations in Europe in 2011 exceeded this annual guideline for benzene. Over the period from mid-2009 to November 2012, mean and median benzene levels in northern Italy (Mestre) averaged 1.8 and 1.1 μg/m³, respectively (Masiol et al., 2014). For a 5-year period from 2009 to 2013, benzene levels as measured at a single monitoring station in Edmonton, Canada, averaged 0.72 μg/m³ (Bari & Kindzierski, 2017). In 2013, average benzene levels across 343 monitoring stations in the USA ranged from 0 ppb carbon (equivalent to ppb multiplied by the number of carbon atoms) in Queen Valley, a sparsely populated town in southern Arizona, to 8.27 ppb carbon [~1.38 ppb = 4.41 μg/m³] in Steubenville, an industrial city in eastern Ohio (ATSDR, 2015). Based on data from seven continuous monitors in Tehran, Islamic Republic of Iran, in 2012 and 2013, annual benzene concentrations of 3.444 μg/m³ were reported (Miri et al., 2016). The highest reported levels were in China, where benzene levels averaged 6.81 ppb [21.75 μg/m³] over approximately 20 years, with city-specific averages from 0.73 ppb [2.33 μg/m³] (Hong Kong Special Administrative Region) to 20.47 ppb [65.39 μg/m³] (Ji’nan) (Zhang et al., 2017).

Table 1.4

Environmental monitoring of benzene.

There is evidence that benzene outdoor air concentrations have declined significantly over time in Europe (> 70% decline during 2000–2014) (European Environment Agency, 2016) and the USA (66% decline during 1994–2009) (EPA, 2010). In addition to long-term trends, levels may vary seasonally. Jiang et al. (2017) reported average benzene concentrations in outdoor air of 502.5, 116.8, 111.21, and 294.8 parts per trillion [1.61, 0.37, 0.36, and 0.94 μg/m³] in the spring, summer, autumn, and winter, respectively in Orleans, France. Similarly, outdoor air concentrations of benzene in the United Kingdom were reported to vary over the calendar year, with higher levels in the winter than during the summer (Duarte-Davidson et al., 2001).

Disasters may affect short-term air quality. After the Deepwater Horizon oil spill in the Gulf of Mexico in April 2010, mean benzene concentrations in air over the ensuing 5 months averaged 4.83 μg/m³ (min., 0.12 μg/m³; max., 81.89 μg/m³) and 2.96 μg/m³ (min., 0.14 μg/m³; max., 290 μg/m³) in regional and coastal areas of Louisiana, USA, respectively. These concentrations were higher than those measured from six urban areas in the state over the same period, which averaged 0.86 μg/m³ (min., 0.51 μg/m³; max., 2.33 μg/m³) (Nance et al., 2016).

(b) Personal exposures to benzene

A study published in 2008 reported on personal monitoring data for benzene collected in 12 European cities, with the lowest arithmetic mean concentration reported for residents of Helsinki, Finland (2.0 μg/m³), and the highest for residents of Thessaloniki, Greece (9.4 μg/m³) (Bruinen de Bruin et al., 2008).

(c) Benzene in drinking-water and food

Benzene exposure can occur due to ingestion of water and food contaminated with benzene (ATSDR, 2007). During 1985–2002, the United States Geological Survey detected benzene in 37 of 1208 (3.1%) domestic water well samples that were collected at sites across the country; all but one sample had concentrations that were less than 1 μg/L (Rowe et al., 2007). In 2015 and 2016, a small proportion of the samples from 116 drinking-water (domestic and public supply) wells in the Eagle Ford (9.3%), Fayetteville (13.3%), and Haynesville (2.4%) shale hydrocarbon production areas in Texas and Arkansas, USA, had detectable levels, and all concentrations were less than 0.15 μg/L (McMahon et al., 2017).

Based on a review of studies published during 1996–2013, relatively low concentrations were reported in carbonated beverages and other foodstuffs (< 1 ppb); the highest levels (18 ppb) were found in organ meats (Salviano Dos Santos et al., 2015). Over a 5-year period (1996–2006), the United States Food and Drug Administration evaluated 70 “table-ready” foods. Benzene was found in all of them except American cheese and vanilla ice cream; levels ranged from 1 ppb (in milk-based infant formula and raw strawberries) to 190 ppb (fully cooked ground beef) (Fleming-Jones & Smith, 2003). Medeiros Vinci et al. (2012) detected benzene in 58% of 455 food samples purchased and analysed from four supermarkets in Belgium in 2010, with the highest mean levels found in smoked (18.90 μg/kg) and canned (7.40 μg/kg) fish, as well as in fatty fish (3.1 μg/kg) and ready-to-eat salads (2.79 μg/kg). Mean levels were much lower in non-fatty (0.52 μg/kg) fish, raw meat (0.31 μg/kg), and eggs (below the limit of detection).

(d) Biomonitoring of benzene exposure

Nationally conducted surveys that include a biomonitoring component have documented benzene exposures in the general population (see Table 1.5). Based on data collected as part of the Canadian Health Measures Survey during 2012–2013 for people aged 12–79 years (n = 2488), geometric mean blood benzene concentrations were 0.036 μg/L (Haines et al., 2017). Based on the United States National Health and Nutrition Examination Survey (NHANES) in 2001–2002, 2003–2004, 2005–2006, and 2007–2008, median benzene blood concentrations for the United States population were 0.03 μg/L (n = 837), 0.027 μg/L (n = 1345), 0.026 μg/L (n = 3091), and less than the limit of detection (n = 2685), respectively (US Department of Health and Human Services, 2018). Using NHANES biomonitoring data, Arnold et al. (2013) reported differences in median blood benzene concentrations between those individuals who had pumped gasoline into a car or motor vehicle during the previous 3 days (0.029 μg/L) and those who had not (0.025 μg/L). Benzene concentrations were also higher for individuals who reported having inhaled diesel exhaust during the previous 3 days (0.039 μg/L) compared with those who had not (0.027 μg/L).

Table 1.5

Summary of selected studies with biological monitoring of environmental exposure to benzene^a.

Biomonitoring studies have also documented environmental exposure to benzene by measuring metabolites of benzene in urine. The Korean National Environmental Health Survey, which was conducted among adults aged 19 years and older during 2012–2014 (n = 6376), reported geometric mean levels of urinary t,t-MA of 58.8 μg/L (Choi et al., 2017). Among 336 adults (age, 35–69 years) living in central Italy who had cotinine levels less than 100 μg/g creatinine (the cut-off value above that was used to define a smoker), reported median urinary levels of t,t-MA and SPMA were 85.48 and 0.23 μg/g creatinine, respectively (Tranfo et al., 2017). Fustinoni et al. (2010) reported a urinary benzene level of 0.122 μg/L (median) in 108 Italian men and women.

A few studies have examined the exposure of adolescents and children to benzene using biomonitoring data. Geometric mean concentrations of urinary t,t-MA, adjusted for age, sex, smoking status, and creatinine concentrations in adolescents aged 14 and 15 years, were reported by the Flemish Environment and Health Study of 99 μg/L in 2003–2004 (n = 1586), 94 μg/L in 2007–2008 (n = 206), and 61 μg/L in 2013 (n = 204) (Schoeters et al., 2017). Based on urine samples collected from 396 Italian children (age, 5–11 years), Protano et al. (2012) reported mean levels of 127.59 and 0.62 μg/g creatinine for t,t-MA and SPMA, respectively.

In workers who are not exposed to benzene through their occupation, the combined effects of smoking and environmental tobacco smoke contribute, on average, 85% and 23% to total benzene exposure among smokers and non-smokers, respectively (Weisel, 2010). In a 2009–2011 nationally representative study of exposure to volatile organic compounds in Canada, statistically significant differences in indoor residential concentrations of benzene were detected between homes with and without smokers (difference, 1.12 μg/m³) (Zhu et al., 2013). Geometric mean benzene concentrations in blood were 0.136 and 0.024 μg/L for smokers and non-smokers, respectively, as assessed using biomonitoring data from the 2003–2004 NHANES survey (Kirman et al., 2012). Similarly, Tranfo et al. (2017) reported urinary levels of t,t-MA and SPMA of 141.32 and 1.83 μg/g creatinine in smokers, compared with 90.68 and 0.20 μg/g creatinine in non-smokers, respectively.

1.5. Regulations and guidelines

The International Labour Organization Benzene Convention (C136) Article 2(1) states: “Whenever harmless or less harmful substitute products are available, they shall be used instead of benzene or products containing benzene.” This convention was passed in 1971 and ratified by 38 countries (ILO, 1971). The European Union classified benzene as a category I carcinogen under Directive 67/548/EEC (European Commission, 1967). Benzene is not allowed to be placed on the market with the exception of fuel, or used as a substance or as a constituent of mixtures in concentration greater than 0.1% by weight (EU-OSHA, 2006). The USA withdrew benzene from consumer products in 1978 (IARC, 1982).

1.5.1. Occupational exposure limits

(a) USA

The 8-hour permissible exposure and short-term limits set by the Occupational Safety and Health Administration are 1 ppm [3.19 mg/m³] and 5 ppm [15.95 mg/m³], respectively (CFR 1910.1028) (OSHA, 2017) (Table 1.6).

Table 1.6

International occupational exposure limits for benzene.

Occupational exposure limit (OEL) recommendations for benzene have been made by the American Conference of Governmental Industrial Hygienists (ACGIH). ACGIH recommends a threshold limit value (TLV) during an 8-hour work shift of 0.5 ppm [1.6 mg/m³] and a short-term exposure limit (STEL) of 2.5 ppm [~8 mg/m³]. ACGIH also recommends a biological exposure index (BEI) for t,t-MA in urine of 500 µg/g creatinine and for SPMA in urine of 25 µg/g creatinine (ACGIH, 2012). The United States National Institute for Occupational Safety and Health (NIOSH) recommended exposure level (REL) for the time-weighted average is 0.1 ppm [0.32 mg/m³] (NIOSH, 2010) and the short-term limit value is 1 ppm [3.2 mg/m³].

(b) Europe

The European Union and most European countries have an OEL of 1 ppm, as does the Scientific Committee on Occupational Exposure Limits (SCOEL) (from 1991), but a few countries have opted for lower values (Table 1.6). The biological exposure limits set by the committee are 28 μg of benzene per litre of blood and 46 μg SPMA per gram of creatinine (SCOEL, 2014). The OEL set by the European Chemicals Agency (ECHA) is 1 ppm (3.25 mg/m³) (Annex III of Directive 2004/37/EC, European Commission, 2004).

In Germany, the Committee for Hazardous Substances has proposed a tolerable risk of 4 : 1000 and an acceptable risk of 4 : 10 000 (changing to 4 : 100 000), applicable over a working lifetime of 40 years with continuous exposure every working day. For benzene, the tolerable and acceptable risks correspond to 8-hour concentrations of 1.9 mg/m³ and 0.2 mg/m³ (0.02 mg/m³ by 2018), respectively (Bau, 2013).

1.6. Exposure assessment methods in epidemiological studies of cancer

1.6.1. Industry-based studies of occupational exposure

Selected epidemiological studies of cancer and occupational exposure are summarized in Table 1.7. The most common metrics of benzene exposure in these studies are the presumption of occupational exposure by duration (years), average exposure intensity (ppm or mg/m³), or cumulative exposure, which is the intensity of exposure multiplied by the number of years exposed (ppm-years or (mg/m³)-years). These metrics indicate that inhalation is the major route of entry, although some studies have also considered dermal exposure (e.g. Lewis et al., 1997; Schnatter et al., 2012; Rushton et al., 2014). The likelihood of peak exposure (using various definitions of peak) has also been examined in some studies (e.g. Lewis et al., 1997; Schnatter et al., 2012; Stenehjem et al., 2015).

Table 1.7

Exposure assessment method for selected occupational epidemiological studies of exposure to benzene.

The main sectors where exposure assessment for benzene has been carried out for epidemiological studies are the petroleum industry (e.g. Wong et al., 1993 ; Armstrong et al., 1996 ; Lewis et al., 1997 ; Glass et al., 2000; Steinsvåg et al., 2007, 2008; Bråtveit et al., 2011), the chemical industry (e.g. Wong, 1987a, b), and industries that use benzene in manufacturing processes (e.g. Rinsky et al., 1981; Yin et al., 1994; Utterback & Rinsky, 1995), including shoemaking (Seniori Costantini et al., 2003).

Exposure to benzene is often assessed by experts who group workers by job or facility (where appropriate) and then assign exposure to each person using a job–exposure matrix, which may have a time dimension. The exposure estimates in the job–exposure matrix may be quantitative, that is, based on personal and/or area benzene sampling (Rinsky et al., 1981), or they may be semiquantitative. Relative measures can later be translated into benzene concentration (e.g. ppm or mg/m³) (Guénel et al., 2002; Bråtveit et al., 2012). Very large studies where multiple experts examine different facilities can increase variability in assessments, but this can be mitigated by standardization across facilities (e.g. Portengen et al., 2016).

Most cohort studies and their nested case–control studies are retrospective, with some including participants from as early as 1910 (Wong, 1987a, b; Armstrong et al., 1996; Lewis et al., 1997). Because exposure data were sparse before 1970, the validity of exposure estimates extrapolated to earlier time periods may be uncertain (e.g. Rinsky et al., 1981; Utterback & Rinsky, 1995; Collins et al., 2015). Even for recent time periods, measured data may not be available or may be inadequate to describe exposures from all jobs. In some studies, data from one facility may be attributed to workers at a similar facility, for example offshore workers on different platforms (Bråtveit et al., 2012; Stenehjem et al., 2015). These differences in data availability may result in varying exposure assessments and outcomes (see Section 2.1.1).

Personal sampling data became more common from the 1970s onwards. Recent studies are therefore more likely to assess exposure using personal measurement data, from which more robust exposure estimates can be derived. It is preferable to assess a high proportion of the participants’ time at risk of exposure with contemporary exposure measurement data (Glass et al., 2000; Vlaanderen et al., 2010). When personal measurement data are available, temporal and between-worker exposure variability should be considered (Kromhout et al., 1993).

Changes in facilities over time have been considered in some studies listed in Table 1.7; for example, Dosemeci et al. (1994) and Wong (1987a) took production rate into account. Portengen et al. (2016) used a modelling process to consider several factors affecting exposure. Some studies incorporated factors to account for changes over time and between sites, for example due to changing technology and variations in products handled (Armstrong et al., 1996; Lewis et al., 1997; Glass et al., 2000).

Uncertainty is also introduced when exposure to benzene is based on modelling from total hydrocarbon exposure, as the proportion of benzene may vary with the source of the hydrocarbons (e.g. Smith et al., 1993).

Studies based mainly on grab or area sampling data (e.g. Rinsky et al., 1981; Dosemeci et al., 1994; Yin et al., 1994) have been used to derive average long-term exposure estimates, which can be less certain than those based on individual-level measurement data collected over longer periods (e.g. full work shifts).

Other exposures may have been incurred by participants in the studies listed in Table 1.7, for example, from other hydrocarbons for petroleum industry workers. Coexposures identified in these studies are listed in the limitations column. Some coexposures, for example styrene, have been associated with an increased risk of leukaemia (e.g. Guénel et al., 2002). Other exposures may not have been described, including low exposure to X-rays for some petroleum industry workers and possibly 1,3-butadiene for some refinery workers (Akerstrom et al., 2016; Almerud et al., 2017).

The application of validation methods can increase confidence in the exposure estimates. Such methods include the use of exposure estimation quality scores (e.g. Schnatter et al., 2012) and the assessment of interrater agreement (e.g. Steinsvåg et al., 2008).

1.6.2. General population studies

(a) Childhood cancer

Epidemiological studies focused on associations between benzene in outdoor air pollution and risks of childhood cancer in Denmark, France, Italy, and the USA. Primary methods to assess exposure to benzene are summarized for selected studies in Table 1.8, which provides a summary of the general approach and metric(s) that were used, along with strengths and limitations. All the studies used a geographical information system (GIS) to manage spatially referenced data from different sources in their benzene exposure assessments.

Table 1.8

Exposure assessment from selected environmental epidemiological studies of benzene exposure.

One investigation (Heck et al., 2014) used routine air monitoring data from 1990 to 2007 (collected every 12 days) from 39 monitors in the state of California (163 696 square miles or 423 970 km²), USA, and developed exposure estimates by linking maternal residences to the closest outdoor air monitor. However, not all monitors were operating throughout the study period; for example, in 2008 there were only 17 benzene monitors in operation (Cox et al., 2008). In addition, stationary monitors were often sited near heavy industry, busy freeways, or in agriculturally rich areas (Heck et al., 2014).

All other key studies relied on Gaussian dispersion models to predict outdoor benzene concentrations in air, for example: the California Line Source Dispersion model, version 4 (CALINE4) (Vinceti et al., 2012), the Danish Operational Street Pollution Model (Raaschou-Nielsen et al., 2001), or the EPA Assessment System for Population Exposure Nationwide (ASPEN) (Symanski et al., 2016; Janitz et al., 2017). Developed by the Department of Transportation in California, USA, CALINE4 is an air dispersion model for roads (and other linear air pollutant sources) used to estimate outdoor air concentrations of benzene and other contaminants at defined locations in a given area. The National-Scale Air Toxics Assessment (NATA) uses ASPEN, a dispersion model that relies upon a national inventory of emissions data for hazardous air pollutants, as well as other characteristics that affect the fate and transport of pollutants in the environment (e.g. the rate, location, and height of release of pollutants, and wind speed and direction).

The CALINE4 model used in the Italian study by Vinceti et al. (2012) used locally collected traffic flow data for a single year, but relied on vehicular emission factors over a longer period (1990–2007). One drawback in using the ASPEN model is that modelled estimates are only available for selected years (i.e. 1996, 1999, 2002, 2005, and 2011). Symanski et al. (2016) used all available estimates at the time of their study (until 2005) whereas Janitz et al. (2017) relied on data for a single year (2005). Because the NATA model inputs change over time, Symanski et al. (2016) conducted a sensitivity analysis by limiting the study population to cases and controls born within 1 year of a NATA release; estimated odds ratios were similar in magnitude, but less precise. Two investigations focused their assessments on exposures due to emissions from vehicular traffic: Raaschou-Nielsen et al. (2001) and Vinceti et al. (2012).

Houot et al. (2015) derived final estimates at geocoded locations using geostatistical methods that combined the dispersion modelled data for a 10 m² grid in the city of Paris, a 25 m² grid in the inner suburb, and a 50 m² grid in the outer suburb with available air monitoring data.

Studies based in the USA (Symanski et al., 2016; Janitz et al., 2017) used NATA estimates that were generated for all census tracts within the continent of North America. Census tract boundaries are drawn based on population size (average population size, 4000 people) and therefore vary by size and shape.

Because the exposure assessments in the reviewed studies relied on a records-based linkage to develop the exposure metrics, there was no response or recall bias in the exposure assessments. The study by Raaschou-Nielsen et al. (2001) offered an advantage over other studies because it addressed residential mobility in estimates of cumulative exposure; residential histories obtained from a national database, from 9 months before birth to the time of diagnosis, were used. All other studies relied on a single residence (either at birth or at the time of diagnosis) upon which to base the exposure assessment. The use of a single residence may have increased uncertainty in the exposure assessments, particularly in studies that included children diagnosed at older ages (e.g. 14–19 years) (Vinceti et al., 2012; Houot et al., 2015; Janitz et al., 2017).

A strength of the studies by Raaschou-Nielsen et al. (2001) and Heck et al. (2014) was their ability to construct temporally resolved estimates of exposure during pregnancy and childhood that allowed for an assessment of exposure at different life stages. However, none of the studies incorporated information on time spent away from the residence for the mother or the child and, by not accounting for exposures in other environments (e.g. maternal exposures at work), uncertainty in the exposure assessments was likely introduced.

Outdoor air includes multiple pollutants from diverse natural and anthropogenic sources; the air pollutant mixture can therefore vary both locally and regionally. Methods for addressing multiple exposures included the application of co-pollutant models (Symanski et al., 2016) and factor analysis (Heck et al., 2014). Information on indoor air sources of benzene (e.g. environmental tobacco smoke) was unavailable in all studies, as was information on housing characteristics (e.g. living in a residence with an attached garage); only one investigation had information about maternal smoking (Symanski et al., 2016).

In most of the studies, the control population (all of the investigations in Table 1.8 used a case–control study design) represented the source population and was therefore unlikely to be affected by exposure-related selection bias. However, some bias may have been introduced in the investigation by Heck et al. (2014) who excluded 2978 cases and 142 188 controls from the parent study because residences were not within defined buffers around a stationary air monitor (2 km for acute lymphoblastic leukaemia and 6 km for acute myeloid leukaemia). Vinceti et al. (2012) also excluded individuals living in mountainous areas (< 10% of the total population in the study area) because the CALINE4 dispersion model was not developed to incorporate rocky terrain in predicting air pollutant concentrations near roadways.

Vinceti et al. (2012) presented results from a validation study and, based on measurements collected at six monitoring stations, reported a modest correlation (Pearson correlation coefficient, 0.43) between the CALINE4 modelled estimates and outdoor air benzene levels. Raaschou-Nielsen et al. (2001) compared the results from their dispersion model with passive sampler measurements of benzene at various street locations in Copenhagen, Denmark and in rural areas. Pearson correlation coefficients of 0.62–0.68 were reported for urban locations (range in values based on differences in meteorological inputs); correlations were much lower for rural locations (0.15–0.19) where there is little variation in traffic levels. Regarding the NATA data, previous studies reported good agreement between the ASPEN modelled estimates and monitored levels of benzene in ambient air (Symanski et al., 2016).

(b) Cancer in adults

Studies on cancer risks associated with environmental benzene exposure have used a variety of approaches in their exposure assessments (see Table 1.8 for a summary).

In a nested case–control study of 82 cases and 83 controls among lifelong never-smokers of the Shanghai Cohort Study (a prospective cohort of 18 244 Chinese men, aged 45–64 years at enrolment) (Yuan et al., 2014), exposures to benzene were assessed using SPMA based on measured concentrations of stored urine samples collected at baseline. While SPMA is a specific biomarker for benzene exposure, its half-life in the body is relatively short; relying on a single urinary measurement of SPMA is problematic as it is not representative of average exposure.

Two drinking-water systems at the United States Marine Corps Base, Camp Lejeune, North Carolina were contaminated with tetrachloroethylene and other solvents, including benzene, from 1975 until February 1985. Bove et al. (2014) reconstructed monthly contaminant levels in the water distribution system using fate and transport models; these were linked to residential histories of marine and navy personnel living at the base to generate lagged (10-, 15-, and 20-year) and unlagged estimates of cumulative exposure. Exposures may have been misclassified due to errors in the reconstructed levels of benzene in the water distribution system, as well as inaccuracies in identifying units assigned to the base, in determining the location of the barracks or housing for marine/navy personnel with families, or in accounting for time spent away from the base for training or deployment.

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