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Polycyclic aromatic hydrocarbon (PAH) exposures in aluminum smelter and offshore industry

A dissertation submitted to the

Division of Research and Advanced Studies

of the University of Cincinnati

In partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

In the Department of Environmental Health of the College of Medicine

November 2008

By

Nancy Brenna Hopf

M.Sc. University of Oslo, 1996

Committee Chair: Glenn Talaska, Ph.D.

1 Abstract

Exposures to polycyclic aromatic hydrocarbons (PAHs) may cause lung and bladder cancer. Exposure monitoring programs have been used in the aluminum smelter industry for decades to decrease the risk of cancer from exposure to PAHs, while other industries such as the offshore industry has never been monitored. Biological monitoring of PAHs incorporates all routes of exposure. Measuring post-shift urinary 1-hydroxypyrene (1OHP), a metabolite of pyrene, is a surrogate for workers’ daily PAH exposures, while DNA adducts detected in white blood cells or urothelial cells can reflect chronic exposures to PAHs.

In the first study, we reviewed the scientific literature to identify changes over time in (1) 1OHP levels, (2) DNA-adduct levels, and (3) other contributing factors associated with 1OHP and DNA-adduct levels in the aluminum smelter industry. No trends were observed in 1OHP and DNA-adduct levels. This could be due to variable selection of study populations and poorly identified job tasks which prevent comparison of jobs across plants and times, unassessed worker exposure variability, and the impact of cumulative exposures. Inconsistent findings were also observed in the analysis of CYP1A1, GSTM1 and GSTP1 polymorphisms and their effect on biomarker levels. Future studies should be aimed at follow-up in workplaces where dermal and inhalation exposure interventions have been employed.

In the second study, we explored the possibility of exposure to PAH derivatives in aluminum smelters such as fluorine-substituted PAHs (F-PAHs). Coal tar is used as an anode and cryolite (Na3AlF6) is the solvent in the electrochemical reaction in a smelter. The aim of this study was to determine whether F-PAHs were actually formed in aluminum smelters. Settled dust samples (n = 5) were extracted using established PAH extraction methods. Detection methods were reverse phase high performance liquid chromatography with photodiode array ultraviolet detection (HPLC/PDA), and gas chromatography with mass spectroscopic detection (GC/MS). F-PAHs were not found in any of these samples, but only unsubstituted analogs; however the sample size was too

2 small to state unequivocally that F-PAHs were not present. Thus, the need for further characterization of the complex chemical mixtures to which aluminum smelter workers are exposed is still needed.

In the third study, we studied PAH exposures in offshore workers (n=42). Our objectives were to: (1) Compare differences in mean post- and pre-shift urinary 1OHP levels between exposed and non-exposed workers, after including covariates such as smoking, job, and age; and (2) Compare differences in post-shift urinary 1OHP levels between exposed workers, after controlling for pre-shift 1OHP levels, smoking, job, and age. Analysis of covariance was used and models included pre-shift values and covariates. We found that (1) Post-shift 1OHP levels were significantly higher in the exposed workers compared to the controls, after controlling for age and pre-shift 1OHP levels; and (2) Tank workers and process operators did not show statistically significant different post- shift 1OHP levels, after controlling for age and pre-shift 1OHP levels. Altogether, this study indicates the presence of a low level PAH exposure among offshore production workers.

3 4 Acknowledgements

I earnestly thank my advisor Dr. Glenn Talaska for his guidance and mentoring. He is a person encouraging independent work, giving me a chance to become autonomous. I also want to thank him for emphasizing that ultimately the workers should benefit from our research.

Thank you to my committee members: Dr. Tania Carreòn, a senior researcher at National Institute for Occupational Safety and Health (NIOSH) and an assistant professor at the University of Cincinnati (UC) in molecular epidemiology, for careful guidance in epidemiology and especially for being patient with delays in our molecular epidemiology project due to my pregnancy. Dr. Mary Beth Genter, a professor in toxicology at UC, for fundamental discussions of toxicological methods and articles. Dr. Paul Succop, a professor in statistics at UC, for thoughtful guidance in experimental design, SAS programming, and interpretation of outputs. Dr. James Mack, a professor in organic chemistry at UC, for discussions and updates on new and existing chemical analytical methods, and giving me chemicals to complete my projects when the funds ran out.

I thank my co-authors: Dr. Jorunn Kirkeleit, a post-doc at the University of Bergen, Norway, for making my project feasible and trusting me with the urine samples. Dr. Marin Harper, a branch chief at NIOSH, and Dr. Yngvar Thomassen, a branch chief at the Norwegian Institute for Occupational Safety and Health (STAMI), for valuable discussions and criticisms.

Thank you to the Division of Environmental and Occupational Hygiene faculty in the Department of Environmental Health: Dr. Amit Bhattacharya for helpful guidance with the ERC project, Dr. Scott Clark for reviewing a class project becoming a manuscript, Dr. Kermit Davis for allowing me to invite speakers to Friday seminars, Dr. Sergey Grinshpun for serving on my qualifying exam committee, and Dr. Tiina Reponen for careful guidance on how to teach student laboratories. I wish to single out Dr. Rice for keeping me informed about requirements and encouragement in both completing my PhD and seeking a job. Thank you to Dr. Howard Shertzer, professor in the Division of Environmental Genetics and Molecular Toxicology, for giving me the opportunity to use his laboratory and equipment.

Thank you to Amber Twitty for helping me get through the ERC research pilot project requirements and forms, and to Stephanie Starkey for making sure all forms for UC have been completed. Thanks to Elizabeth Kopras for English editing.

Thanks to current and past students in the Department of Environmental Health.

Thank you to Brenda Schumann for training me in DNA adduct labeling with 32P, radiation safety, and most importantly, being my friend.

Thank you to my wonderful husband, Pierre, who made it all possible with constant love and support. My thanks are sent to my daughter, Emma Sophie, for sleeping through the night, and to my family in Norway and Switzerland for constant encouragement.

Cincinnati November 18 2008

Nancy Brenna Hopf

5 TABLE OF CONTENTS

Polycyclic aromatic hydrocarbon (PAH) exposures...... 1 in aluminum smelter and offshore industry ...... 1 Acknowledgements...... 5 Introduction...... 12 Chapter 1 Background...... 16 1.1 General...... 16 1.2 Sources and population of exposure ...... 16 1.3 Toxicokinetics - toxicodynamics ...... 17 1.4 Metabolism and activation...... 17 1.5 Exposure monitoring...... 18 1.5.1 Air monitoring ...... 19 1.5.2 Biological monitoring...... 20 1.5.3 Occupational Exposure Limits...... 21 1.5.4 Biological Exposure Index (BEI)...... 21 1.6 Specific aims...... 22 Chapter 2 Biological markers of carcinogenic exposure in the aluminum smelter industry, a systematic review...... 25 2.1 Introduction...... 25 2.2 Biomarkers of exposure in aluminum smelters ...... 30 2.3 Rationale and approach...... 34 2.4 Factors influencing biomarker levels reported in the scientific literature ...... 40 2.4.1 Study design...... 41 2.4.2 Metabolic polymorphisms ...... 42 2.4.3 PAH mixtures...... 46 2.4.4 Target organ...... 47 2.4.5 Non-occupational PAH exposures...... 49 2.5 Conclusion ...... 50 2.5.1 Acknowledgements...... 52 Chapter 3 Determination of fluorine substituted polycyclic aromatic hydrocarbons (F- PAHs) in aluminum smelter dust...... 63 3.1 Introduction...... 63 3.2 Materials and Methods...... 66 3.2.1 Dust samples ...... 66 3.2.2 Dust sample analysis...... 66 3.3 Results...... 68 3.4 Discussion...... 69 3.5 Conclusion ...... 72 Chapter 4 Urinary 1-hydroxypyrene levels in offshore workers...... 76 4.1 Introduction...... 76 4.2 Methods...... 78 4.2.1 Study population...... 78 4.2.2 Urine samples...... 81 4.2.3 Laboratory analysis...... 81

6 4.2.4 Statistical analysis...... 82 4.3 Results...... 83 4.4 Discussion...... 85 4.5 Conclusion ...... 88 4.5.1 Acknowledgement ...... 89 Chapter 5 Conclusion ...... 93 References...... 97

7 List of Figures

Figure 1 Stepwise biomarker process from exposure to disease (1)...... 19

Figure 2 Flow-chart of the selection process of articles ...... 55

Figure 3 Mean urinary 1-hydroxypyrene (1OHP) levels found in aluminum smelter workers over time. Circle sizes indicate the relative number of samples...... 56

Figure 4 Mean DNA adduct levels in blood found in aluminum smelter workers over time. Circle sizes indicate the relative number of samples...... 57

Figure 5 Chromatogram using HPLC with Supelco column (Supelcosil TM LC18 30cmx4.0mm, 5um) and PDA detector (254 nm) showing relative F-PAH [0.1 μg/μl in toluene (RT=5.8 min)] RT and intensity. Inserted table gives F-PAH RT and max absorbance in UV...... 73

Figure 6 UV and structures of F-PAH standards used to identify possible F-PAHs in dust samples from aluminum smelters ...... 74

Figure 7 Settled dust samples from a) ducts in the Soderberg potroom (Karmøy), b) ducts in the Søderberg potroom (Karmøy), c) filters in the prebake potroom (Karmøy), d) used anodes processing area (Sunndalsøra), and e) carbon recovered from used anodes (Sunndalsora), analyzed by GC (labeled #1a-e) and HPLC (labeled #2a-e)...... 75

Figure 8 Urinary 1OHP (μg/g creatinine) by exposure group (controls, tank workers, and process operators) and shift (pre-and post-shift). Horizontal lines indicate the median. . 92

8 List of Tables

Table 1 PAH levels (μg/m3) determined from personal air sampling of jobs performed in aluminum smelters...... 53

Table 2 Urinary 1OHP levels in aluminum smelters reported in the literature ...... 58

Table 3 DNA adduct levels in aluminum smelters reported in the literature ...... 61

Table 4 Descriptive Statistics by Exposure Group ...... 90

Table 5 Descriptive urinary 1OHP (not log-transformed, creatinine adjusted given in μg/g creatinine and un-adjusted values given in μg /L of urine) statistics by exposure group. 91

9 Table of Abbreviations

1OHP 1-Hydroxypyrene ACGIH American Conference of Governmental Industrial Hygienists APR Air purifying respirators BaP Benzo[a]pyrene BEI Biological exposure index FID Flame ionization detector CYP Cytochrome P450 DNA Deoxyribonucleic acid F-PAH Fluoro substituted polycyclic aromatic hydrocarbons EPA Environmental Protection Agency GC Gas chromatography GST Glutathione S-transferase GM Geometric mean HPLC High performance liquid chromatography MS Mass spectroscopy NAICS North American Industry Classification System NIOSH National Institute for Occupational Safety and Health NMAM NIOSH Manual of Analytical Methods OSHA Occupational Safety and Health Administration OV Organic vapor cartridge PAH Polycyclic aromatic hydrocarbon PDA Photodiode array PEL Permissible exposure limit PPE Personal protective equipment PTFE Polytetrafluoroethylene SD Standard deviations SEF Selective electrochemical fluorination TLV Threshold limit value TWA Time weighted average UBC Urinary bladder cancer

10 UV/Viz Ultraviolet and visible wavelength WBC White blood cells

11 Introduction Polycyclic aromatic hydrocarbons (PAHs) and their derivatives are ubiquitous

occupational and environmental agents, emitted when organic matter is burned. Human

exposures to PAHs are therefore unavoidable. Epidemiologic studies of PAH exposed

workers, especially in coke ovens and aluminum smelters, have shown clear excess of

lung cancer and highly suggestive excess of bladder cancer.(2-4) Although the cancer risk has been established from historical air concentration data, the exposure–response

relationship is still unclear because the exposure assessments are generally poor. Today’s

exposures appear to be lower than in the past, and while this is good for the workers, it tends to increase the uncertainty in the relationship between exposure and disease

causality. Information on the exposure-response relationship is important for setting

occupational and environmental standards. To clarify this relationship further, three

exposure assessments were studied: (1) we conducted a systematic review of articles

from aluminum smelter industry quantifying exposures by PAH internal dose, which is a

more sensitive tool than measuring air concentrations because it takes into account all

routes of exposure (inhalation, dermal, and ingestion); (2) we analyzed dust samples

collected in aluminum smelters for novel PAH-derivatives, potentially adding to already

known cancer risks; (3) we determined internal PAH doses in offshore workers exposed

to PAHs in crude oil, which had yet to be assessed for these carcinogens.

PAHs - a mixture of more than 100 different chemical compounds characterized by two

or more fused aromatic rings of carbon and hydrogen atoms - pose health risks to

humans. PAHs are formed during the incomplete burning of coal tar, oil and gas, or

other organic substances like tobacco or charbroiled meat.(5) Seven PAH compounds,

12 including benzo[a]anthracene, benzo[b]fluoranthene, benzo[j]fluoranthene,

benzo[k]fluoranthene, benzo[a]pyrene, dibenz[a,h]anthracene, and indeno[1,2,3-

c,d]pyrene, are considered to be human carcinogens. (4)

PAHs may be airborne during the burning or heated processes, or adsorbed onto

particulate matter. In occupational settings, airborne PAHs are inhaled, and dermal

uptake may occur from touching PAH contaminated surfaces and dust. Non-occupational

PAH exposures are usually associated with smoking and eating charbroiled meat.

The inhaled PAHs may enter the body through the pulmonary tract or gastrointenstinal

tract. Dermal exposure may lead to percutaneous absorption due to the lipophilicity of

many PAHs. After entering the body, PAHs are widely distributed, especially to organs

rich in lipids. The systemic distribution of PAHs from the pulmonary tract and gastrointestinal tract are faster than from percutaneous absorption.

Metabolism of PAHs is complex. Parent compounds are converted via intermediate epoxides to phenols, diols, and tetrols, which are conjugated with glucuronic acids or

with glutathione. Detoxification is the main result; however, some PAHs are activated to

DNA-binding species, initiating tumors. Excretion of metabolites is fairly rapid mainly

via feces; only about 10% are excreted in the urine (6).

Large epidemiologic studies of aluminum production workers have been conducted to determine the relationship of PAH exposure to the elevated cancer rates in this

13 population. (2, 7). Exposures in aluminum smelters are of great health concern, especially with regard to lung and bladder cancer(8, 9).

Currently, 443,500 workers are employed in the alumina and aluminum production and processing (North American Industry Classification System (NAICS) code: 3313) industry, and almost 79% (349,000) are production workers (www.bls.gov accessed on

07/07/08) PAH exposures in aluminum smelters are common (10, 11), and therefore workers in this industry have been monitored for PAH exposures.

The aluminum industry relies heavily on electrical energy, and the costs of this energy are central to the operation. Changes in this industry are often driven by electrical energy reduction demands, production cost reductions, and environmental considerations such as the increasing cost of compliance with existing fluoride regulations.(12) Change in production may lead to unknown physical and chemical exposures to the workers.

Therefore, in addition to monitoring for PAH exposures, the occupational health professional must always be on the lookout for possible exposures to unknown hazards.

One such example is combining the exposure to PAHs formed in aluminum smelters with other chemicals used in this process, such as fluorides, which can result in new chemical compounds e.g. fluorine substituted PAHs (F-PAHs).

It is useful to use the knowledge acquired regarding PAH exposure monitoring and apply it to other workplaces that could potentially have PAH exposures. Crude oil contains

PAHs to a variable degree depending on the geographic source of the oil. The amount of

14 PAH in crude oil is generally low, but the crude oil residues in sand/clay (slag) contain higher amounts of PAHs (13). Fossil water that has been trapped with oil and gas in the geologic reservoir and pumped up with the oil that also contains PAHs(14, 15) . Most of the processes on offshore installations are performed in closed systems during ordinary operations; however, as in today’s aluminum industry, the petroleum workers may be at risk of PAH exposure whenever the system is opened for surveillance of the production, cleaning, inspection, or maintenance. In the US, 165,900 workers are employed in the oil and gas extraction industry (NAICS 2111), and 93,400 of these are production workers with unknown levels of exposure to carcinogens such as PAHs.

This dissertation will begin with an overview of methods of PAH monitoring, followed by a review of the biomonitoring performed in aluminum smelters. In order to detect unknown hazards of novel exposures, we analyzed dust samples for fluorinated PAHs from aluminium smelters. Finally, biomonitoring of off-shore workers was performed in order to assess PAH exposures in this previously unstudied population. This knowledge will provide a better understanding of PAH exposures and novel PAH-derivatives. Using the acquired understanding in order to well developed exposure monitoring programs.

Implementing exposure reduction programs will ultimately lead to a reduction in human disease.

15 Chapter 1 Background

1.1 General

Polycyclic aromatic hydrocarbons (PAHs) are a large group of organic compounds with

two or more fused aromatic rings. They are highly lipophilic; hence have relatively low solubility in water. In air, PAHs are mainly found adsorbed on particles.(16)

1.2 Sources and population of exposure

PAHs are formed mainly as a result of pyrolytic processes, especially the incomplete

combustion of organic materials during industrial processes, such as processing of coal and crude oil derived products (coal tar, pitch, creosote, bitumen), and in non-industrial

processes, such as tobacco smoking, grilled meat, or medications containing tar. PAHs

are byproducts of industrial processes. There are several hundred PAHs; the best known

are naphthalene used in mothballs and benzo[a]pyrene (BaP), which has been well characterized for its carcinogenic effect. Also, there are sources of PAH derivatives, such as nitro- and thio-PAHs, that are not fully characterized, and other PAH derivatives not yet identified. For example, aluminum smelters’ contaminations include not only with

PAHs, but an array of other hazardous chemicals, including fluoride, alumina, sulphur dioxide, and carbon monoxide. Processes involving mixtures of chemicals may produce novel or uncharacterized chemicals. The examination of one such chemical, fluorine- substituted PAHs (F-PAHs), is described in Chapter 3.

In the past, chimney sweeps and tar workers were dermally exposed to substantial amounts of PAHs, and there is sufficient evidence that skin cancer in many of these

16 workers was caused by exposure to PAHs. (3) Epidemiological studies in coke-oven workers, coal-gas workers and employees in aluminum production plants provide sufficient evidence of the role of inhaled PAHs in the induction of lung cancer. (3) There are other workers at risk for PAH exposures who have not been monitored, such as oil

production workers exposed to PAHs in crude oil (Chapter 4). In the general

population, psoriasis patients treated with coal tar(17), smokers, or people who must

work or live in conjunction with environmental tobacco smoke, have exposures to

PAHs.(18)

1.3 Toxicokinetics - toxicodynamics

PAHs are readily absorbed from the lung, gut and skin of humans. The liver is the major

organ of biotransformation (first-pass effect) (3), and lungs and skin contribute to a lesser

extent. Mammary and other fatty tissues are storage depots for PAHs.(19) Independent

of the route of exposure, the major route of PAH excretion is hepatobiliary excretion and elimination through the feces.(20). Urine is the other major excretory route, although quantitatively less of the PAHs are excreted via this path.(21)

1.4 Metabolism and activation

The microsomal cytochrome P450 enzyme system is largely responsible for PAH

metabolism, converting the non-polar PAHs into polar hydroxy and epoxy derivatives.

((22) Epoxides are reactive, and are metabolized readily to other compounds such as diol

epoxides and phenols. PAHs, such as the potent BaP, exert their mutagenic and

carcinogenic activity through these reactive intermediates, which can bind covalently to

17 DNA. Some PAHs, such as pyrene, are not metabolized into reactive species, and therefore are not genotoxic.(3) The metabolites are excreted through bile and urine.

1.5 Exposure monitoring

Exposure monitoring is used to measure the amount of pollutants in order to implement

monitoring programs, leading to appropriate exposure controls and, ultimately, reduction

in human disease.

In a workplace, “exposure monitoring program” has a two-fold meaning; first to have

developed a plan to assist in selecting effective procedures, equipment, personal protective equipment (PPE) and work practices to protect workers from the health

hazards presented by hazardous chemicals used in that particular workplace as defined by

Occupational Safety and Health Administration (OSHA), and second to implement the plan.

Exposure monitoring is often referred to as the monitoring of air, skin, and surface exposures; however, internal exposure/dose, effective dose, and early effects are also aspects of exposure monitoring, often referred to as biological monitoring. Biomarkers are substances, structures, or processes that are measured to characterize an exposure or susceptibility, or that predict the incidence or outcome of disease.(23) Figure 1 shows the steps from exposure to disease. The goal is early detection, using exposure markers as

far away from disease as possible, to implement early interventions, and prevent the

development of disease.

18

Figure 1 Stepwise biomarker process from exposure to disease (1)

Exposure monitoring programs have been used in aluminum smelters for decades to

monitor PAH exposures in the workplace. The purpose of such a program is to lower

worker exposure. We wanted to investigate whether aluminum smelter workers have had

a reduction in PAH exposures over the years, by reviewing available information in the

literature (Chapter 2).

1.5.1 Air monitoring

Monitoring for PAHs in ambient air includes collection of air and particulates; PAHs

adsorb onto particulates. The methods for collection and analysis of PAHs have been

refined over the years, and today PAHs are collected using a filter

(polytetrafluoroethylene or PTFE) and analyzed with High Performance Liquid

Chromatography (HPLC) with fluorescence or ultra violet (UV) detection, Gas

19 Chromatography (GC) with Flame Ionization Detector (FID), or GC with Mass

Spectroscopy (MS) detection.

1.5.2 Biological monitoring

It is advantageous to use biological monitoring of PAH exposure because internal dose from all routes of exposure (dermal and inhalation) can be estimated, (24)as can the effectiveness of exposure interventions.

A number of techniques have been developed for the biological monitoring of human exposures to PAHs. The methods most commonly used are: PAH concentrations and their metabolites in blood and urine, and determination of DNA and protein adduct formation in tissues.(25)

The 32P-postlabelling assay is highly sensitive for quantification of carcinogen-DNA adducts.((26) 32P-Postlabelling analysis has been used to detect the formation of DNA adducts in skin samples from humans exposed to components of complex mixtures of

PAHs in coal-tar, creosote, bitumen, used engine oils and fuel exhaust condensates.(27).

This method has been used to investigate DNA adduct levels in workers known to have high PAH exposures. DNA adduct levels in blood cells from aluminum smelter workers

(28) and coke oven workers, (29) and in urothelial cells in rubber workers (30) have been determined.

Urinary 1-hydroxypyrene, a major metabolite of pyrene, is increasingly used as a marker of exposure to PAHs. Pyrene is normally abundant in complex PAH mixtures, and

20 increased urinary levels of 1-hydroxypyrene have been found in workers exposed to creosote oil, coal tar distillery workers, road-surfacing workers, coke-oven workers, and workers exposed to bitumen fumes. We have used this biomarker in a currently unsurveyed population, offshore workers exposed to crude oil, which contain PAHs

(Chapter 4).

1.5.3 Occupational Exposure Limits

In the US, the Occupational Safety and Health Administration (OSHA) has set a

Permissible Exposure Limit (PEL) of 0.2 milligrams of PAHs per cubic meter of air (0.2 mg/m3). Mineral oil mist that contains PAHs has a PEL of 5 mg/m3 averaged over an 8- hour exposure period.

The National Institute for Occupational Safety and Health (NIOSH) recommends that the average workplace air levels for coal tar products not exceed 0.1 mg/m3 for a 10-hour workday, within a 40-hour workweek.

The Norwegian occupational exposure limit (administrative norm) is set to 0.04 mg/m3.

1.5.4 Biological Exposure Index (BEI)

The American Conference of Governmental Industrial Hygienists (ACGIH) has recommended a benchmark of 1 μg of 1-hydroxypyrene per liter of urine instead of a

Biological Exposure Index (BEI) for 1-hydroxypyrene because data are not sufficient in supporting a numerical BEI based on health outcome or upon an airborne exposure

21 threshold limit value (TLV). However, the presence of 1-hydroxypyrene above this

benchmark is evidence of occupational exposure to PAHs.

1.6 Specific aims

In this dissertation, we identified knowledge gaps in three areas of PAH exposure

research, and investigated these areas guided by our three questions:

1. Does the exposure monitoring program for reducing PAH exposures in aluminum

smelters work?

To answer this first question, we performed a systematic review of the scientific literature, extracting results on biological monitoring of workers in United States aluminum smelters. The objectives of this review were: (1) to identify changes over time in 1-hydroxypyrene levels in aluminum smelter workers in the scientific literature, (2) to identify changes over time in DNA-adduct concentrations in aluminum smelters in the scientific literature, and (3) to identify other contributing factors associated with 1OHP and DNA-adduct levels such as polymorphisms in genes involved in PAH metabolism, when listed in the scientific literature. (Chapter 2)

2. Do unidentified fluorinated PAHs (F-PAH) exist in aluminum smelters, posing

additional health hazards to these workers?

To answer this second question, we collected five dust samples in an aluminum smelter, and obtained F-PAH standards to run our chemical analysis. The objective was to

22 compare reverse phase high performance liquid chromatography with ultraviolet and

visual wavelength (UV/VIS) photodiode array absorbance detection (HPLC/PDA) and

gas chromatography with mass spectroscopy detection (GC/MS) of settled dusts obtained

from various operations in primary aluminum smelters, with HPLC/PDA and GC/MS

spectra from available F-PAH standards (Chiron, Norway). (Chapter 3)

3. Do the PAHs in crude oil give rise to occupational exposures in offshore workers?

Are offshore workers exposed to PAHs in crude oil as part of their occupation?

To answer this third question, we collected urine from offshore workers, and analyzed urinary 1-hydroxypyrene levels. This study had three specific aims. The first aim was to compare the difference in post-shift urinary 1OHP levels between exposed and non- exposed workers (controls), after controlling for smoking, age, and pre-shift urinary

1OHP levels. The exposure group for this specific aim included two jobs: tank workers

and process operators. The second aim was to compare the difference in post-shift urinary

1OHP levels between the two exposed groups (process operators, tank workers), after

controlling for smoking, age, and pre-shift 1OHP levels. Since the workers had been

working before this study was performed, the third aim was to compare pre-shift urinary

1OHP levels between exposed and non-exposed workers (controls), after adjusting for

smoking status and age. (Chapter 4)

To summarize, this dissertation describes three studies on worker exposures to PAHs. A

better understanding of these exposures, including historical exposures, characterization

23 of novel chemicals, and previously uncharacterized worker populations, will enable us to implement exposure monitoring programs to reduce PAH exposure, and ultimately reduce human disease.

24 Chapter 2 Biological markers of carcinogenic exposure in the aluminum smelter industry, a systematic review

Nancy B. Hopf, Tania Carreón, and Glenn Talaska

Department of Environmental Health, University of Cincinnati

2.1 Introduction Today, the aluminum industry employs more than 15,000 workers in 14 United States

aluminum industrial plants. There are about 300 aluminum plants worldwide. (31) Large

epidemiologic studies of aluminum production workers have been conducted to determine the impact of polycyclic aromatic hydrocarbon (PAH) exposure on cancer rates in this population since some PAHs are known or suspected carcinogens. (4) In a comprehensive review (2), wide variability in cancer risk estimates among studies of aluminum workers was found. However, the most informative study found a dose- response effect between benzene soluble matter and benzo[a]pyrene (BaP) estimated exposure and lung cancer. A more recent review (7) did include the aforementioned data

(2), but reported no excess risk for lung cancer in aluminum workers, when taking other studies into account. However, a modest excess risk for urinary bladder cancer (UBC) was reported pooling results from 15 published papers (1997-2005), including workers employed up to 1990 on nine aluminum production cohorts. The authors found that UBC was statistically significantly increased in aluminum production workers (pooled relative risk (RR)=1.29 and 95% confidence interval (CI) 1.1-1.5). Some of these aluminum

25 smelter plants started production as early as 1920; and the review included workers up to

1990 (7).

Aluminum is produced by electrolysis of bauxite. This takes place in large carbon-lined steel vessels called pots. Hundreds of these pots may be housed in a "potroom". Pots have an anode (made of petroleum coke bound with a coal-tar pitch binder) and a cathode. There are two types of aluminum smelter technologies: prebake and Søderberg anode cell (horizontal and vertical stud). Anodes are consumed in the reaction. Anode production starts with crushing and grinding coke, which is then mixed with pitch binder.

Pitch is a residue from the distillation of coal tar. A steam jacketed mixer is used to create a paste. This paste is added directly to the anode casings of the Søderberg cells, as opposed to the prebaked anode cells where this paste is first baked in a furnace, which may be off site. The production of anodes in the prebake process is distinct from the potrooms.

The most important PAH sources in aluminum smelters are emissions from heated coal tar and pitch. Data indicate that prebaked anode cells are preferred because they are more efficient electrically and they emit less PAHs, than Søderberg smelters.(32)

Although prebake aluminum smelters emit less PAHs than the old technology Søderberg smelters, the prebake anode plants still release significant amounts of PAHs. In a historical review of exposures in the aluminum smelter industry (33), Benke et al. report chemical emissions including PAHs measured in aluminum smelters worldwide. The minimum and maximum PAH levels (μg/m3) reported from personal air samplings are

26 given in Table 1. As expected, the PAH levels reported for prebake are far lower than for

Søderberg smelters with ranges 0.52-120.6 μg/m3 and 3-2790 μg/m3, respectively. Even though air concentrations of PAHs reported in the literature for aluminum smelters have used different air sampling methods for PAHs (Table 1), there is little doubt that PAHs were, and are still present in the work atmosphere. PAHs may exist in either the vapor phase or adsorbed onto particulates.

PAHs are fused aromatic rings, formed by the incomplete combustion of organic matter and fossil fuels. The formation of specific PAH mixtures depends upon the conditions of combustion, which are highly variable, and therefore produce mixtures of variable composition. PAH carcinogenicity is very structurally dependent since the metabolism of these materials within the host produces the active carcinogen. The most important example is the potent benzo[a]pyrene (BaP). The excess risk of cancer found in aluminum smelters due to PAH exposures has in some instances been attributed to BaP and certain other components of this complex exposure mixture. BaP has been widely studied because of its carcinogenic properties and it serves as a good model for the activation and DNA binding of most or all carcinogenic PAHs. BaP is metabolized to benzo[a]pyrene diol epoxide, which covalently binds to DNA, distorting the DNA structure, reducing the fidelity and inducing mutations by DNA polymerases during cell replication.(5) To determine the overall carcinogenicity of the PAH mixture, the U.S.

Environmental Protection Agency (EPA) recommends converting concentrations of individual PAHs into BaP equivalents based on the compounds’ concentration and its activity relative to BaP (34).

27 BaP air concentrations in Søderberg plants are reported to be: 0.18-116.3 μg/m3 (10, 33,

35-39), in prebake plants 0.03-4.88 μg/m3 (10, 40-42) and in plants where the process

was not specified 0.8-3.5 μg/m3.(43, 44) Similar to PAHs in general, BaP air

concentrations were higher in Søderberg plants than in prebake plants. Exposure to BaP

was reported as the causative factor in the first epidemiologic study reporting excess risk

of UBC (RR=2.4; 95%CI 1.3-4.3) among aluminum smelter workers.(45) However, in

addition to PAHs and BaP, other risk factors are found in both air and coal tar pitch used in Søderberg smelters such as the UBC carcinogen 2-naphthylamine, an aromatic amine.(46) In fact, the dye industry has utilized aromatic amines widely and is best identified with excess of UBC.(47)

In the previously mentioned epidemiological review of aluminum workers, Bosetti et al. found only two epidemiologic studies allowing further analysis of standardized mortality ratios (SMRs) within jobs. These studies found that 1) bladder SMRs increased from 1.8 to 2.2 for “jobs with more probable exposure to PAH”, and 2) maintenance workers had a

SMR of 2.0 for both lung and bladder as opposed to production workers with a SMR of

1.0.(7)

PAHs can enter the body via inhalation or dermal uptake. Potroom workers experience

exposures to PAHs particularly when tending the pot, i.e. stirring the coal lined pot

containing molten cryolite (>700 °C) (Table 1).(37, 38, 48) This task, breaking the crust

forming on top of the melting rock, brings the worker very close to the open pot.

Potroom workers often perform pot-linings (dismantling pot structures, digging spent pot-

28 linings and refractory, rebuilding the pot-lining and structure).(49) With high levels of

PAHs in the working atmosphere, inhalation of PAH emissions, especially from the pot tending, are common. PAH exposures through the skin are especially common in workers performing potlining. The relative contribution of dermal and inhalation PAH exposures in aluminum smelter jobs has not been estimated; however, in other industries, it has been shown to vary depending on jobs performed.(50) Some workers use personal protective equipment (PPE) such as respirators or gloves to reduce exposures. Proper use

of these devices can dramatically lower exposure. Unfortunately, reliance on these

devices is often fraught with error and workers frequently handle PAH contaminated

equipment and wear contaminated gloves, and do not use correct respirator for the

exposure and/or are not fit-tested for the respirators they use. So, in addition to

determining that workers are using gloves and respirators, researchers should take care to determine if they are using them properly. Description of the use of these devices in studies is often sketchy or not usually considered, and thus may confound a potential relationship between PAH exposures, internal dose, and cancer.

To decrease the cancer risk among aluminum smelter workers, it is essential to monitor the exposures to carcinogenic and mutagenic agents such as PAHs, identify subpopulations of workers that have high exposures to PAHs, and then reduce these workers’ PAH exposures. Monitoring programs of workers in aluminum smelters have traditionally consisted mainly of measuring the concentration of PAHs in ambient air

(Table 1). It is advantageous to use biological monitoring of PAH exposure in

conjunction with environmental monitoring in aluminum workers because internal dose

29 from all routes of exposure (dermal and inhalation) can be estimated(24) as can the

effectiveness of exposure interventions. Biomarkers of internal dose can be used to

quantify an individual's exposure to and uptake of environmental agents potentially

related to disease, and metabolic activation and detoxification parameters that may be

related to disease susceptibility.

Biological monitoring has been performed for aluminum smelter workers since 1988.(28)

We wanted to know if the aluminum smelter workers’ PAH exposures have been reduced

since the biological monitoring programs were begun in this industry.

2.2 Biomarkers of exposure in aluminum smelters Currently, there are three biological markers commonly used to estimate PAH exposures

in workers are: urinary 1-hydroxypyrene (1OHP) and urinary 1- and 2-naphthol for

internal dose and DNA-adducts for effective dose.

The internal dose biomarkers 1- and 2-naphthols, are metabolites of naphthalene, the

most volatile compound of the PAH mixture and a carcinogen.(51) Naphthalene

measured in air samples from aluminum smelters ranged from 4 to 311 μg/m3.(10)

Urinary 1- and 2-naphthols have not been measured in aluminum smelter workers, and

because of this, no further naphthol details are provided in this review. The industries where naphthols have been used as biomarkers for PAH and naphthalene exposures have been summarized.(52) Measurement of 1- or 2- naphthol levels can be considered a

useful addition to a biological monitoring program where, as in the aluminum industry,

30 PAHs are heated. These markers would provide an estimate of the more toxic, but less

carcinogenic volatile PAHs likely to be in the vapor phase.

The internal dose biomarker 1OHP; is a metabolite of pyrene, a major compound present

in almost every PAH mixture. Pyrene is metabolized via oxidation by cytochrome 450

(CYP) isozymes in the liver predominately to 1OHP, which is glucuronidated and

excreted in the feces and urine. 1OHP urinary elimination in humans is triphasic with

half-lives of 5 hours, 22 hours, and 17 days.(6) Measuring the concentration of 1OHP in

urine is reliable and easy to do, and hence is a preferred biomarker for quantifying an

individual’s PAH exposure.(6) The American Conference of Governmental Industrial

Hygienists (ACGIH) has found that 1OHP in post-shift urine samples increases during

the workweek, and on a week-to-week basis for several months.(6) It appears that pyrene

is distributed to a long-lived body compartment and continues to rise for approximately

four months, thus contributing to an increasing amount in the pre-exposure samples.

Therefore, urinary 1OHP levels in post-shift – pre-shift urine samples reflect an

individual’s daily variable PAH exposure, while a pre-shift, before work-week, level of

1OHP reflect chronic exposures.

The 1OHP biomarker has successfully been used in studies (53-55) assessing the effectiveness of personal protective equipment (PPE) (56) and ventilation, and evaluating exposures associated with different aluminum smelter tasks.(29) In addition, the method of analysis for 1OHP has been very consistent since 1988, and the same method is used by almost all investigations.

31 However, pyrene as a biomarker for PAH exposures have been criticized. In an

experiment with human liver microsomes, Grimmer (1990)(57) reported that 1OHP was

not necessarily the major metabolite, and that the metabolite profile of pyrene varied

among individuals. However, these results have not been corroborated, but it may be that

levels of 1OHP may potentially be affected significantly by genetic polymorphisms of

CYP and GST enzymes.(58) Others have noted correctly that pyrene is not a carcinogen

and therefore, the internal dose of 1OHP cannot be directly related to cancer risk.

Quantification of DNA adducts is a biomarker of exposure measuring the biologically

effective dose. PAH compounds are metabolized to highly reactive PAH diol epoxides

that can bind covalently to cellular proteins and DNA, forming adducts predominantly with adenine and guanine. The DNA repair rate of adducts of various compounds is determined by their structures, thus representing differences in their impact on the

regulatory mechanisms governing the replication of cells and their potential

transformation into cancerous clones.(59) Measurement of DNA adduct levels is

currently used to assess the biologically active fraction of PAHs, which is capable of interacting with DNA, preferably in the target site. DNA adducts can reflect cumulative dose in either exfoliated bladder cells in urine (100 days cumulative dose) or in blood lymphocytes (one to five day cumulative dose).

Correlations between DNA adduct levels in blood leukocytes and external or internal

PAH exposure (as measured by urinary levels of 1OHP) have often been poor (28, 60-62) suggesting either that genetic and environmental susceptibility factors may affect the

32 individual response to PAH exposure or that there is significant day-to-day variability in

PAH exposures. DNA adducts have long half-lives in some target tissues and would naturally correlate less well with biological markers with short half-lives if there was significant day-to day variability in exposure. Biomarkers with similar half-lives would be expected to correlate well. For example, in a study of benzidine-exposed workers, urinary mutagenicity was found to correlate well with urinary metabolites of benzidine

(r=0.88), both of which have short half-lives, while the correlation with DNA-adducts in exfoliated bladder cells with a lifespan of about 100 days, was lower (r=0.59).(63)

Tobacco smoking can confound the interpretation of urinary 1OHP and DNA adducts because tobacco smoke contains pyrene and other PAHs.(6) Smoking and occupational exposures can combine to produce elevated urinary 1OHP levels (6), although some aluminum smelter PAH exposure appears to vastly overwhelm the effect of smoking. A recent meta-analysis (64) tested whether “the presence of a high level of bulky DNA adducts in tissues is associated with an increased risk of cancer in humans”, and the authors concluded that current smokers with high levels of adducts have an increased risk of lung and bladder cancers. Among factors that may modify the levels of individual

PAH-DNA adducts are inducibility of PAH-metabolizing enzymes and polymorphisms in genes for these enzymes. However, current data indicate these polymorphisms are effect modifiers rather than confounders and do not often have significant biological impact.(65)

33 The objectives of this review are: (1) to identify changes over time in 1OHP levels in aluminum smelters in the scientific literature, (2) to identify changes over time in DNA- adduct concentrations in aluminum smelters in the scientific literature, and (3) to identify other contributing factors associated with 1OHP and DNA-adduct levels such as polymorphisms in genes involved in PAH metabolism, when listed in the scientific literature.

2.3 Rationale and approach Studies published in peer-reviewed journals were identified through the search engine

Scopus (http://www.scopus.com/scopus/home.url), which covers life sciences, health

sciences including Medline, physical sciences, and social sciences. No restrictions on

dates or document type were given. Aluminum is spelled differently in British English

and American English journals. Both spellings were included in all the searches

performed. First, the following keywords were used: “aluminium” OR “aluminum”

AND “smelter” OR “industry”. This search resulted in 15,359 articles. Second, we

searched within the resulting 15,359 articles for keyword “DNA adduct”, and this search

narrowed the number of articles to 36. Third, we excluded all articles with animal,

laboratory or occupational data, overlapping studies, epidemiologic studies, and studies

not using post-labeling methods. These exclusions resulted in six studies. Through their

references we found three additional studies that fit the criteria and were included, which

left us with nine studies total for this review. Fourth, searching for 1-hydroxypyrene

within the combination “aluminium/aluminum AND smelter/industry” articles resulted in

28 articles. After excluding epidemiologic, overlapping, non-occupational, non-English

34 studies and reviews, we were left with seven studies. Through their references we

identified eight studies that fit our criteria, and a total of 15 studies were included in our

review. The total number of articles included in this review for DNA and 1-

hydroxypyrene was 19 articles. See for the flowchart of this search.

We reviewed research papers we had found up to April 2007 and present the results in two tables (Table 2 and Table 3 ). Most of these studies were undertaken in the 1980s and were limited to a few countries: Norway, Sweden, Hungary, Germany, the

Netherlands, and Canada.

While methods for 1OHP analysis were similar across studies, the units reported varied.

Some studies reported 1OHP as μg/L, not adjusting for creatinine, and others reported total 1OHP (μg/day) in 24-hour urine samples. The vast majority reported 1OHP levels

adjusted for urinary levels of creatinine (μmol/mol creatinine). We computed non-

adjusted 1OHP levels, assuming a constant creatinine level (13 or 14 µmol creatinine per

liter urine or 1.47 mg creatinine/L).(66) The 1OHP analysis in all the studies included in

this review were performed using the method developed by Jongeneelen et al.(55), i.e.

enzymatic hydrolysis using β-glucuonidase and arylsulfatase. Other hydrolysis methods

used to obtain the free un-conjugated 1OHP are: acids, only sulfatases or only

glucuronidases.(67) These methods will likely give slightly different 1OHP levels.

A total of 15 articles have been included in this review of 1OHP (Table 2) and 9 articles

for DNA-adducts (Table 3). Some aluminum smelters have an anode pre-bake area as

35 part of their process; articles that report workers in the anode pre-bake have been

included in this review.

Fifteen studies reported urinary 1OHP levels in aluminum smelters (Table 2). Most of

the studies were conducted in Søderberg aluminum plants in different countries (Norway,

Sweden, Hungary, and Germany). The study design varied across studies, resulting in

study subjects with different levels of PAH exposures; six studies (28, 37, 58, 60, 68, 69)

focused on high exposed workers (potroom workers), while other studies (38, 42, 70-75)

describe different PAH exposures across jobs performed at the plant.

Some studies focused on repeated measures (68, 72), the influence of genetic

polymorphisms on urinary 1OHP levels (69), or the relative contribution of dermal

exposure to total PAH exposures.(74) The influences of smoking and respiratory

protection on urinary 1OHP levels have been discussed in multiple studies; however,

control of confounding by these factors is not consistent across studies. Information on

smoking status’ effect on urinary levels of 1OHP has been reported to be: 1.5 times

higher than nonsmokers in the same job(68), more than 30 cigarettes per day may when

combined with occupational exposure bring the urinary 1OHP to levels as high as 1 μg/L

(76), and former-smokers are more similar to smokers than non-smokers with respect to

urinary 1OHP levels.(71) These data suggest that smoking is a significant confounder, especially when occupational exposure is relatively low. Therefore, smoking status should be ascertained as accurately as possible in studies of smelter workers.

36 Bosetti et al.(7) noted in their meta-analysis of aluminum workers that the observed

excess risk of urinary bladder cancer may not be real because some other bias or confounding cannot be completely ruled out. For example workers may have been exposed to other occupational carcinogens, as well as tobacco smoking. However, no other specific carcinogens have been studied in this context.

Nine studies reported DNA-adduct levels in aluminum smelters (Table 3). DNA adduct

levels were all reported in adducts per 108 nucleotide. There are two methods widely

used to measure DNA-adducts, ELISA and 32P-postlabelling. To be able to compare across studies we only included studies measuring DNA-adduct levels using the 32P-

postlabeling method (Table 3). One of the studies included here compared the two DNA-

adduct analysis methods.(69) Study subjects included in these eight 32P-postlabeling adduct studies were high PAH exposed workers (potroom workers) (28, 61, 62, 69), while other studies recruited workers for other purposes. DNA-adduct levels by jobs were explored by Schoket et al.(77) and Van Delft et al.(73) Longitudinal studies were conducted by Øvrebø et al.(28) and Schoket et al.(77, 78) All the DNA-adduct studies used DNA from blood, obtained from white blood cells, peripheral lymphocytes, or lymphocytes.

Whenever possible, information about gender and smoking status has been included.

Some workers may have participated in several studies and therefore their urinary 1OHP and DNA-adduct levels may have been reported more than once in Table 2 and Table 3.

37 Unfortunately, it is difficult to determine when there are multiple reports on the same sample or if several samples are from the same person at a different time.

Levels of metabolites in biological samples may or may not be normally distributed. A log-normal distribution appears to be most common. This is consistent with most other occupational exposure metrics. Authors have reported central tendency measures such as arithmetic means, medians, geometric means with corresponding standard deviations, geometric standard deviations, and ranges based on their analysis and interpretations.

One of the questions posed for this review was: Have urinary 1OHP and DNA-adduct levels changed over time? Unfortunately, it became clear that this is a difficult question to answer with the current data set, because of differences in study design. Many studies were focused on the highest exposed workers, usually potroom workers, while others were on a random sampling of workers from all workers in smelters. In this review, if the year of the urine collection was not reported – as in most cases, we have assumed the collection year of the samples being equal to the year of publication. Plotting the urinary

1OHP data from Table 2 showed a slight statistically significant increase (0.11, p<0.001) in the reported 1OHP levels over time (figure 2). Limiting the results to only potroom workers (including potlining) gave a slight statistically significant increase (0.13, p<0.001) (data not shown). However, caveats were detected, and are discussed later in this review. Plotting the DNA-adduct data from Table 3 showed a not statistical significant increase (0.009, p<0.09) in DNA-adduct levels in 2002 (figure 3).

38 To be able to compare exposure groups with the greatest accuracy, the variability in these

groups must be equal or taken into account. Because between- or inter-worker exposure

variability is high, some studies have stratified the workers into groups of jobs, or in

specific jobs. Often, correlations between pyrene concentrations measured in personal air

samples and urinary 1OHP medians or means are significant on a group level but not

significant on individual levels. To explain worker variability, recent studies have

focused on the effect of possible polymorphisms such as GSTM1, GSTP1, and on urinary

1OHP levels (see Table 2 1).(58)

Process temperatures determine the fraction of airborne PAHs in the vapor phase or adsorbed onto particulates.(10) Dermal uptake appears to be a significant contributor to internal dose(74), and may explain some of the variability of urinary 1OHP levels seen in workers. Dermal exposures depend not only on processes the performed, but also type and use of PPE, work practices, and personal hygiene. Van Rooij et al. (74) have made a significant contribution to quantify dermal exposure to pyrene in aluminum smelter workers. In this study, using skin patches underneath the workers regular clothing and

PPE to determine dermal exposures, the authors estimated that 75% of the urinary 1OHP level was due to skin exposures. This may be regarded as an overestimate since the

authors did not adjust estimates for baseline urinary 1OHP values. Qualitative assessments of dermal exposures have been performed; however, these dermal assessments were not included as covariates in statistical models of urinary 1OHP excretion.(28, 37, 73) For example, Petry et al.(42) found that a worker with overseeing responsibilities had a better correlation between pyrene in air and urinary 1OHP than a

39 worker with hands-on work practice. Workers’ personal hygiene such as showering after

work was noted in one study.(60) Several studies attributed a poor correlation between measured pyrene air levels and corresponding urinary 1OHP levels (42, 60, 68, 70) to dermal exposures; however, the extent of the dermal contribution was either not measured, or not estimated. Future studies need to address the contribution of dermal exposure in explaining worker variability seen in urinary 1OHP levels. This would best be done by intervention studies where reduction in urinary 1OHP levels is quantified after quantitatively reducing either inhalation or dermal exposures.

From studies with repeated measures of urinary 1OHP (68, 72) it is known that the workers’ urinary OHP levels increase not only from pre-shift to post-shift but also over a

5-day workweek if the PAH air concentrations are about the same every day.(6)

However, the PAH levels have been shown to fluctuate throughout the day and between days, and this could potentially explain the variable urinary 1OHP levels seen in workers.

Therefore it is pertinent to quantify the variability in daily PAH exposures by measuring

PAH air levels, and combining these with dermal and urine 1OHP levels, to avoid contributing the flux in urinary 1OHP to the workers metabolism.

2.4 Factors influencing biomarker levels reported in the scientific literature In this review we investigated changes over time in 1OHP and DNA-adduct levels in

aluminum smelters in the scientific literature, and have recorded other contributing

factors associated with 1OHP and DNA-adduct levels (genetic polymorphisms,

dermal/inhalation exposure ratio, use of PPE and respirators, variable PAH air levels,

40 variation in job tasks, and smoking). Next we will investigate these potential sources of

variations in studies more fully with the goal of improving future study design and data

collection.

2.4.1 Study design Comparing studies is complicated due to varying sampling strategies, including

participant selection, purpose, and the measurements made. The choice of study

participants has been either “high” exposed workers (i.e. potroom workers), random

selection of all workers, or selection of workers by jobs. Potroom workers are considered

the highest PAH-exposed workers in an aluminum plant, and were the study population

in seven publications.(37, 58, 61, 62, 69, 77, 79) Workers randomly selected in the

aluminum plant were the study population in five publications.(38, 41, 68, 71, 80)

Lastly, four publications chose a group of workers in specific jobs such as graphite-

electrode producing workers (70), operator, maintenance, and supervisors from the same

crew (42), anode bake area (72), and cathode relining workers.(28) The workers in the

studies reviewed were from European countries (Norwegian, Dutch, Hungarian, German,

and Swedish). This publication bias limits to some extent the genetic diversity, and minimizes social/cultural differences.

Changes in 1OHP levels in aluminum smelters over time were identified by plotting the

urinary 1OHP data from Table 2, which showed an increasing trend (Figure 3). The size

of the circle in this plot (Figure 3) indicates the size of the study population. A separate

time dependent plot of only potroom workers’ 1OHP and DNA adduct levels, gave flat

41 trendlines (r-squared of 0.0008 and 0.0035, respectively). Unfortunately, these plots are misleading because (a) earlier studies measured workers in random jobs in an aluminum smelter for an overview of the 1OHP levels among the workers at the plant, and (b) later

studies focused on a subgroup or subgroups of high PAH exposed workers within a plant.

Furthermore, the focus of more recent studies has been narrowed down to jobs/tasks

performed within the aluminum smelters. Earlier studies were often cross sectional,

encompassing many job titles. These studies identified potroom workers as having the

most exposure. Subsequent studies were more likely to focus on potroom workers.

Therefore, our original question regarding aluminum smelter workers’ exposures to

PAHs to have decreased over time cannot be answered with current knowledge.

However, it may be possible to determine if potroom workers’ exposures are increasing

or decreasing. This will require either a large number of studies or a re-sampling of those

previously published.

2.4.2 Metabolic polymorphisms Our third aim for this review was to investigate whether genetic polymorphisms

contribute to the variability seen in urinary 1OHP and/or DNA-adduct levels. With

regard to DNA adduct levels, a strong case can be made to investigate polymorphisms in enzymes: (I) belonging to the CYP450 superfamily, which are known to activate PAHs;

or (II) belonging to mutated alleles of the glutathione-S-transferase family (GST), known to detoxify the most DNA reactive of the activated PAH species. The impact of CYP450 variants has been complicated recently: complete abrogation of the specific CYP isozymes activity shown to be most active in the in-vivo activation of BaP through

42 genetic knockout in mice, did not reduce the levels of DNA adducts following BaP exposure.(81) To date, the results of these studies have not borne out that these polymorphisms impact the levels of DNA adducts in smelter workers. Since these polymorphisms are much more likely to be effect modifiers that confounding variables(82), it is important that investigations be made with groups that have very closely matched exposures, something that is extremely difficult to do in occupational studies, while maintaining sufficient power to see if a difference exists.

Making a case for these same activities to have an impact on the levels of 1OHP is even more challenging. The major phase II enzyme responsible for the elimination of 1OHP is glucuronyl transferase, not GST(83); although some fraction of 1OHP is eliminated as a thiol.(57) Nonetheless, investigators have made measurements of GST activity relative to 1OHP elimination in smelter workers. For example, inter-worker variability observed for urinary 1OHP was explained with genetic polymorphisms by Schoket et al.(69), where the GSTM1 null individuals had a significantly lower (p=0.05) urinary 1OHP level than the GSTM1 positive individuals in the presence of the GSTP1 Ile105 allele. GST null persons might be expected to excrete more 1OHP glucuronide since it would be the equivalent of removing a competing detoxification pathway, so this result is puzzling.

Schoket et al.(69) also found a positive linear correlation between DNA adducts in white blood cells and 1OHP levels in potroom workers with the GSTM1 null genotype. The explanation offered by the authors was an interaction between the GSTM1 and GSTP1 alleles in modulation of 1OHP levels and DNA adduct levels in the PAH-exposed workers. This result has also been seen in coke oven workers where a significant

43 relationship between 1OHP and DNA adducts in high PAH exposed Italian coke-oven

workers with GSTM1 null genotypes was found.(84) The variability in urinary 1OHP

levels explained by the GST polymorphism as seen by Schoket et al. has been

corroborated in a cohort of aluminum smelter workers with combined GSTM1 null-

CYP1A1 Ile462Val heterozygous genotype, which had substantially higher 1OHP levels

compared with other genotype combinations.(58) Neither of these studies offered a

metabolic explanation of why the GST polymorphism would have an impact on the

excreted amount of 1OHP. However, it can be appreciated that the relationship between internal dose and DNA adduct levels could be simplified if the influence of GST could be eliminated as it is in the nulls. In an earlier study, Øvrebø et al. did not find a significant effect of GSTM1 and GSTP1 on urinary 1OHP levels.(85) These questions remain for future studies on how GST alters pyrene metabolism in humans. Also, polymorphism interactions have to be biologically explained such as the interaction between GSTM1,

GSTP1, and CYP1A1. Nonetheless, current data do not indicate that either CYP or GST variants significantly modify the impact of PAH exposure on DNA adduct levels.

Recently, this divergence in results was not explained by polymorphisms alone but rather by gene–environmental interactions magnifying polymorphic variability in bioactivation/detoxification capacity. Elovaara et al.(86) found that human lung specimens, which can metabolize pyrene, treated with PAHs increased GST activity (4.4- fold), and the authors concluded that the PAH-metabolizing pathways are mainly induced by BaP-type minor constituents. Future studies need to address not only the polymorphisms of the individuals but control for variations in PAH exposures, and

44 include measurements of BaP-type constituents(86), which may act as coinducers of enzymes that activate/detoxify procarcinogens in PAH mixtures. Other co-inducers may

be found in a worker’s medication use. Some medications(87) are metabolized by uridine diphosphate glucuronyltransferase (UDPGT), the same pathway involved in the metabolism of 1OHP.(88) Age, disease state, exposure to medications / PAHs or genetic background may be related to UDPGT activity, and how this alters the metabolism has

yet to be determined.(87) Future studies should incorporate medication use in their

statistical analysis.

In repeated measures of urinary 1OHP in workers, day-to-day variations (intra-worker

variability) in PAH exposures may obscure possible relationships between 1OHP and polymorphisms. Analyses using groups of workers, inter-worker variability such as work tasks, individual hygiene, and use of PPE, may obscure possible relationships between

1OHP and the polymorphism studied.

From an earlier study by Petry et al.(42), worker variability was minimized by repeated measurements (pre- and post-shift for five consecutive days), and by measuring pyrene levels in the working atmosphere to confirm the fluctuations seen in urinary 1OHP levels.

Petry et al.(42) found that pyrene in air correlated well (Spearman correlation rs) with

1OHP post-shift urine samples (rs =0.56, significance level not recorded), and less with

1OHP pre-shift samples (rs =0.48, significance level not recorded). This finding is not

surprising because one of pyrene’s triphasic elimination half-lives is 5 hours (6), and

collecting urine samples post-shift captures the daily pyrene exposures, which the air

45 samples also represent. Pre-shift samples reflect cumulative exposure from urinary elimination of pyrene with half-lives of 22 hours and 17 days.(6) Cumulative exposure of pyrene measured as urinary 1OHP levels in pre-shift samples, would not necessarily correlate well with daily exposures measured as pyrene air levels if there is substantial day-to-day variability. Workers’ cumulative exposure is captured as urinary 1OHP levels in pre-shift, before work-week urine samples, and workers’ daily exposure is measured post-shift, end-of-work week urine sample.(6)

DNA adducts represent the cumulative exposure and metabolism to a genotoxic species over the lifespan of the sampled cells. To understand the fluctuation of 1OHP and DNA- adduct levels seen in workers within a plant or across plants, it is necessary to identify and summarize the daily variation in workers’ tasks and exposures in addition to polymorphisms in future studies. This knowledge might help to explain the differences seen between workers in the same job but also explain fluctuations of 1OHP levels seen within a worker (inter-worker variability) in repeated measurements.

2.4.3 PAH mixtures The major disadvantage of measuring urinary 1OHP levels is that urinary 1OHP is an estimate of exposure to a single compound in a complex mixture and not of carcinogen exposure, directly. One of the major questions identified by ACGIH regarding this marker is whether there is a relationship between 1OHP and health effects or markers of carcinogenesis. As mentioned earlier, the ACGIH recommends comparing levels of pyrene to BaP to adjust for mixtures that are dilute in carcinogenic PAHs (e.g. asphalt

46 versus coal tar pitch). This is echoed by Petry et al.(42) who recommended that air levels

of BaP be monitored as well as air levels of pyrene when urinary 1OHP levels are

determined in future studies. Petry et al. (42) found that BaP in air correlates well with urinary 1OHP post-shift levels (rs =0.56) and less with pre-shift levels (rs =0.41).

However, the link between urinary 1OHP and pyrene and BaP in air was not so straightforward in other studies in other plants. Bentsen-Farmen et al.(68) found no correlation between 1OHP and pyrene air levels. However, the authors suggest that skin exposure is an important route of pyrene exposure at the plant where they performed their study.

2.4.4 Target organ DNA adducts are often measured in white blood cells (WBC). A problem associated with

measuring DNA-adduct levels in blood is that this biomarker may not reflect the DNA-

adduct levels in the target tissues (lung, skin and bladder). Currently, peripheral WBC

are the most widely used cells in the detection of DNA adducts in humans exposed to

carcinogens from occupational and environmental sources because of the relative ease in

which they can be obtained, the amount of DNA available, and their position in the

central body compartment. PAHs and metabolites affect the human urinary bladder by

DNA damage in the epithelial cells, suggesting that metabolism and distribution factors

of these compounds are critical to bladder and lung. Monitoring of a surrogate tissue like

WBC might not be in proportion to events occurring in the target organ. Thus, all DNA

samples may not be equal for biomarker purposes.(82)

47 Detection of carcinogen-DNA adducts in exfoliated urothelial cells (89) is a promising assay that can be used to monitor exposure to bladder carcinogens. Measurement of DNA adducts in exfoliated urothelial cells is motivated by the evidence that these cells have long been used for cytological studies to detect the presence of malignant phenotype.

DNA adduct levels have been measured in exfoliated urothelial cells, which are biological indicators that reflect: I) exposure to carcinogens at the target organ (bladder),

II) DNA-adduct level, and III) the individual differences in carcinogen biotransformation, cell turnover, and DNA repair rates.(90) Identification of DNA adducts in exfoliated urothelial cells could therefore be a useful indicator to: 1) elucidate the toxicodynamics regarding how the PAH mixture gets from the liver to the bladder, and 2) identify the potential health hazard associated with exposures in this industry, in addition to industries where exposure has been related to UBC.

DNA-adduct levels in urothelial cells have yet to be measured in aluminum smelters but have been successfully performed in other PAH-exposed workers such as non-smoking rubber workers (n=52), and a relationship between high PAH exposure processes and increased DNA-adduct level was found.(30, 91) Further analysis of the processes in this study could not be performed due to the limited number of workers in each job. However; the authors identified several different types of DNA-adducts relevant to non-smoking rubber workers, and concluded that the combination of these types of DNA-adducts represented the production function.

48 Another difference between blood and urothelial cell DNA-adduct levels is that they integrate an individual’s PAH exposures over different time periods. Measuring DNA- adduct levels in WBC represents PAH exposures from hours up to four or five days since this is the lifespan of WBC. Urothelial cells live for approximately 100 days and reflect

PAH exposures for this time period. If both tissues were equally exposed and at steady state, the adduct levels in the exfoliated urothelial cells would be higher than the WBC.

This should reduce the number of samples under the limits of detection and quantitation.

Therefore a better estimate of cumulative risk than for blood is obtained, i.e. levels averaged over 100 days instead of just a few days. This means that short duration increases or decreases of pyrene exposure will not affect DNA adducts measured in urothelial cells. The disadvantage is that the method for determining DNA-adducts in urothelial cells requires a lot of urine (>0.2 L) to isolate sufficient cells to obtain sufficient DNA. This adds to the time and resources needed in the laboratory, in addition to logistics in urine collection.

2.4.5 Non-occupational PAH exposures Complicating the PAH exposure picture is PAHs ingested from diet and in inhaled cigarette smoke, which give rise to urinary 1OHP. From a literature review, ACGIH found that the ranges of urinary 1OHP of the non-occupationally exposed population for non-smokers and smokers were: 0.1-1.8 μg/L and 0.1-2.8 μg/L, respectively.(6)

However, only a very small fraction of smokers will have 1OHP levels greater than 1

μg/L due to their smoking alone.(6) This has also been seen by Huang et al.(92), using data from the National Health and Nutrition Examination Survey (NHANES). They found an overall geometric mean concentration for 1OHP for smokers and non-smokers

49 combined of 0.08 μg/L, with a 95% confidence interval (CI) of 0.07–0.09 μg/L. Urinary

1OHP levels by smoking status gave a median for non-smokers and smokers (number of

individuals measured) of 0.025 (1,713) and 0.080 (319) μmol/mol creatinine,

respectively. The three times higher urinary 1OHP levels in smokers than non-smokers

were statistically significant. The impact of smoking increases when occupational

exposures produce 1OHP levels that are in this lower range, as determined in the

exposed, non-smoking population.

Several studies have found that smoking does not influence occupational 1OHP levels(76) while others have found the opposite.(28) Reasons offered for the conflicting evidence were that smoking interferes with using a protective mask leading to less

frequent use of protective respirators among smokers.(28) However, smoking and

occupational exposures can combine to produce elevated 1OHP levels; therefore it is

necessary to investigate how smoking and exposure might interact in an individual.

2.5 Conclusion Benke et al.(33) identified four aspects of future research needed in the aluminum

industry, and one was to quantify the decrease in BaP levels over time. The authors

concluded that this could not be determined at present because of measurement errors,

differences in analytical techniques and other factors in the published literature. We have

chosen to explore the trend in the quantitative PAH exposure levels using biomarkers for

PAH: 1OHP and DNA-adducts; however, the conclusion for this systematic review is the

same as that of Benke et al.(33) regarding BaP over time: We could not determine the

decrease in biomarker levels, but for different reasons.(33)

50

We were not able to determine a trend in biomarker levels due to variable selection of

study populations, poorly defined job tasks to compare jobs across plants and times,

worker variability not identified, and lastly, the failure to consider cumulative exposures.

These are all shortcomings in current studies that should be addressed in future studies of aluminum workers as well as other cohorts studying PAH exposures and their biomarkers.

Future exposure studies would benefit from having repeated measures on each worker

(worker variability), determining urinary 1OHP in pre-shift samples after at least 48- hours of non-exposure (cumulative exposure) and post-shift (daily exposures) samples, determining DNA-adducts in urothelial cells (target organ), determining the pyrene concentration in the specific PAH mixture used at the plant, describing the workers’ job tasks and work practices in detail (to avoid misclassification of workers in epidemiological studies and to understand the fluctuation of 1OHP and DNA-adduct levels seen in workers within a plant or across plants), and documenting use of PPE and amount of smoking. Other bladder carcinogens (2-naphthylamine)(46) exist in coal tar,

and concentrations of these materials should be monitored, as well.

Our last aim was to report on the impact of polymorphisms associated with metabolism

of PAHs on urinary 1OHP and DNA-adduct levels in aluminum smelter workers.

Currently, only three polymorphisms in aluminum smelters have been explored: CYP1A1

Ile462Val heterozygous genotype, GSTM1 and GSTP1. Reasons for the discrepant

51 results observed in this type of study may be because a single polymorphism may only

have a weak effect while susceptibility may depend on many polymorphisms at multiple

gene loci (93), and the gene-environment interactions may magnify polymorphic variability in detoxification capacity.(86) Effect of polymorphisms on PAH exposure- related biomarkers have been reported in other industrial processes such as the coke

oven.(94) Using polymorphisms to explain differences seen in aluminum smelters should

still be encouraged; however, the primary goal should be a larger biological monitoring

study to determine and reduce workers with excessive exposures and to control the

working environment for carcinogens such as PAHs.

2.5.1 Acknowledgements We thank Dr. Martin Harper at the National Institute for Occupational Safety and Health

(NIOSH) in Morgantown WV, for financial support and for insightful discussions.

52

Table 1 PAH levels (μg/m3) determined from personal air sampling of jobs performed in aluminum smelters Author Type of aluminum plant Jobs (n=number of workers) Collection and analysis of PAHs μg PAH/m3 Bjørseth 1978, 1981 (10), Norwegian Søderberg Coke packer, pitch bin worker, hydraulic Collection of particulate PAHs using 37.7 2790 (11) smelters press operator, pitch dust sweeper (18 Acropore filter. Collection of vapor-phase jobs, 5 consecutive days). PAH acropore filter and two cooled bottles with ethanol Norwegian prebake plants Tapper, coke puller, crust breaker (n=28) 0.52 2.0 Becker 1984 (48) Norwegian Søderberg Potroom workers (n=15) Collection of airborne particulate PAH 51.8 268 smelters using a 37mm polyamide membrane filter. Analyzed by HPLC with fluorescence detector. Levin 1995 (38) Swedish Søderberg smelter Potroom workers including crane Collected on glass fiber filter followed by 20 480 operators, potmen, and electrode men sorbent tubes (XAD2) and spectrofluoro (n=10) monitor. Seven PAHs analyzed by LC. Ny 1993 (37) Søderberg smelter Point crew, crucible cleaners, samplers, Collected on glass fiber filters backed by 8.8 840 grinder, spike quality controllers, a silver membrane followed by an XAD2 foreman, contractors, potmen, crane tube for vapor-phase PAHs. operators, tappers (n=48) Tolos 1990 (72) Dutch prebake smelters Liquid pitch and coke pressed and heated Collected on Teflon filter followed by 9.5 95 into a block (green block). Packer-pullers sorbent tubes. Teflon filters analyzed for (n=7) and crane operators (n=9) (cover coal tar pitch volatiles (benzene solubles) block with pitch), equipment operator and sorbent tubes analyzed for 17 PAHs (n=2) using GC.

Van Schooten 1995(41) Dutch prebake smelters Anode factory (mixing and shaping of the Collected on teflon filters. Sonication 3 107 extract analyzed for 12 PAHs by HPLC anode) (n = 16); (Vydac C18 column)/fluorescence detector. bake oven (baking of the anode) (n = 20); pot-relining department (n = 13); and

53 electrolysis department (n = 24).

Control group, (n=32)

workers in foundry department in same aluminum plant.

Petry 1996 (42) prebake smelters Carbon anode plant workers (n=6): truck 26 PAHs determined. PAH particulates 3.99 120.6 driver, crane operator, floor worker, collected with glass fiber filters followed forman/maintenance by a silver membrane and volatile PAHs collected with XAD2 absorbent tube in line. Analyzed with GC/MS

Øvrebø 1995 (28) Norwegian Soderberg Pot relining of cells using hot ramming Collected on filter. Analyzed with 5 130 smelter paste, anode paste plant workers, GC/FID for 16 PAHs. industrial health workers (n=165)

54

Figure 2 Flow-chart of the selection process of articles

55

Figure 3 Mean urinary 1-hydroxypyrene (1OHP) levels found in aluminum smelter workers over time. Circle sizes indicate the relative number of samples.

56

Figure 4 Mean DNA adduct levels in blood found in aluminum smelter workers over time. Circle sizes indicate the relative number of samples.

57 Table 2 Urinary 1OHP levels in aluminum smelters reported in the literature Urinary 1OHP (µmol/mol creatinine) Study Aluminum smelter job Year N Sex 24h Mean GM Median SD Range Methods (pre- or post shift urine sample) (μg/day) (study population, demographics, plant information, purpose) Alexandrie Potroom workers (preshift) 2000 94 M 3.43 0.07-26.6 Highest exposure (potroom workers), 32% 2000 (58) Potroom workers (post shift) 97 4.31 0.09-17.7 smokers, Søderberg plant, Sweden Angerer Graphite electrode producing plant – All (postshift) 1997 67 M 4.0 0.4-42.9 Investigat e workplace exposures, Germany 1997 (70) Graphite electrode producing plant - by job (postshift): crushing 2 NR 9.6 baking 30 NR 23.4 impregnation 9 NR 22.0 graphitization 24 NR 1.8 conditioning 2 NR 2.3 Bentsen-Farmen Primary Aluminum Anode Paste plant – preshift 1999 34 NR 3.93 2.57 3.20 17 workers sampled several times during a 1999 (68) Primary Aluminum Anode Paste plant – postshift 1999 34 NR 10.2 8.94 6.58 normal workweek, electrode paste for Søderberg smelters, Norway Carstensen Potroom workers (post shift) 1999 96 M 4.31 0.09-17.7 Recruited from 167 current potroom 1999 (61) workers, Søderberg plant, Sweden Goen Aluminum smelter workers 25 NR 8.07 0.1-126.2 Employees with known or suspected PAH 1995 (71) Carbon electrode production – plant 1 6 NR 11.25 exposures in different industries. Only Carbon electrode production – plant 2 3 NR 24.50 Aluminum Production factory, Germany, Carbon electrode production – plant 3 14 NR 16.15 included in review. Levin Potroom workers – all 1995 9 M 1.97** 2.00** 1.07 0.005-6.88 Investigate correlation of [PAH] in air with 1995 (38) Potroom workers – by job: [1OHP] in urine in different pot anode 1995 4 M 1.99 2.12 0.85 industries, vertical stud (262 pots) cathode 3 M 2.43 2.87 1.40 Søderberg plant, Sweden. Non-smokers crane 2 M 1.22 1.22 1.11 except for crane worker. No correlation between BaP air and 1OHP possibly due to respiratory protection used. Ny Group1^ (bow$) 1993 5 NR 0.56 0.51 Investigate correlation of exposure to 1993 (37) Group 1^ (eow$$) 1.00 0.69 cumulative PAHs air and 1OHP, Group 2^^ (bow) 4 NR 0.93 0.88 vertical stud Søderberg plant, two potrooms Group 2^^ (eow) 3.00 2.60 w/ 39 pots each, tropics. Group 3^^^ (bow) 8 NR 1.20 0.91 Random selection of workers in potroom Group 3^^^ (eow) 18.00 14.00 Potmen (bow) 9 NR 2.2 1.60 Potmen (eow) 35.00 31.00 Electrodemen (bow) 4 NR 2.10 1.90 Electrodemen (eow) 43.00 40.00 Øvrebø Primary Aluminum – cathode relining by year: 1988 13 11M,2F 2.44 1.57 Biological survey of workers w/ high 1995 (28) 1989 12 11M,1F 2.29 1.43 exposure jobs in potrooms: cathode 1989 17 15M,2F 0.36 0.17 relining. Survey time: 2.5 years. 1989 23 17M,6F 1.58 0.94 1990 24 22M,2F 0.83 0.78 44-74% of workers were smokers 1990 26 20M,6F 1.38 1.41 1990 24 20M,4F 1.08 0.84 Petry Carbon plant workers (making carbon anodes for aluminum 1995 6 NR 9.20 3.15 13.5 0.5-61.0 Evaluate suitability of 1OHP to 1995 (42) pre-bake plants) – postshift 5 consecutive days characterize respiratory exposure to PAHs. Low sign correlation between pyrene and 1OHP. 58 Urinary 1OHP (µmol/mol creatinine) Study Aluminum smelter job Year N Sex 24h Mean GM Median SD Range Methods (pre- or post shift urine sample) (μg/day) (study population, demographics, plant information, purpose) Schoket Potroom workers GSTM1 postive 2001 21 M 26.1 15.9 Evaluate genetic polymorphisms’ influence 2001 (69) Potroom workers GSTM1 null 18 M 20.1 13.3 on 1OHP excretion Potroom workers GSTP1 aa 20 M 26.3 15.9 Highest PAH exposures: potroom workers Potroom workers GSTP1 ab 10 M 24.9 14.4 in two plants, Hungary Potroom workers GSTP1 bb 9 M 14.9 10.5 Potrroom workers GSTM1 positive + GSTP1 aa 9 M 32.2 15.9 Potrroom workers GSTM1 null + GSTP1 aa 11 M 21.4 14.8 Potrroom workers GSTM1 positive + GSTP1 aa and ab 15 M 31.8 14.8 Potrroom workers GSTM1 null + GSTP1 aa and ab 15 M 19.7 13.3 Potrroom workers GSTM1 positive + GSTP1 aa and bb 12 M 21.4 14.8 Potrroom workers GSTM1 null + GSTP1 aa and bb 7 M 18.0 11.3 Potroom workers GSTM1 positive + GSTP1 bb - M - - Potroom workers GSTM1 null + GSTP1 bb 1 M 11.9 - Tolos Primary Aluminum Anode Bake area stratified by job, day 1990 28 26M,2F Analyze the relationship between urinary 1990 (72) and shift: 1OHP and Crane operator day 1 preshift 1990 9 NR 0.64 0.14 8-TWA coal tar pitch volatiles (CPTV), Crane operator day 3 preshift 9 0.72 0.12 pyrene, 17 PAHs Crane operator day 1 postshift 9 2.87 0.21 Crane operator day 3 posthift 9 2.72 0.68 Packer puller day 1 preshift 1990 9 NR 0.57 0.23 Packer puller day 3 preshift 9 0.77 0.12 Packer puller day 1 postshift 9 2.41 0.52 Packer puller day 3 posthift 9 3.01 0.80 Equipment operator day 1 preshift 1990 1 NR 0.68 Equipment operator day 3 preshift 2 0.56 Equipment operator day 1 postshift 1 2.50 Equipment operator day 3 posthift 2 2.55 Gas furnace operator day 1 preshift 1990 3 NR 0.43 0.29 Gas furnace operator day 3 preshift 3 0.57 0.36 Gas furnace operator day 1 postshift 3 3.60 Gas furnace operator day 3 posthift 3 3.10 0.71 Mechanic day 1 preshift 1990 1 NR 0.76 Mechanic day 3 preshift 1 0.65 Mechanic day 1 postshift 1 2.00 Mechanic day 3 posthift 1 2.30 Brick layer day 1 preshift 1990 4 NR 0.56 0.25 Brick layer day 3 preshift 4 0.68 0.13 Brick layer day 1 postshift 4 1.93 0.21 Brick layer day 3 posthift 4 2.05 0.17 Van Delft Carbon electrode manufacturing plant – carbon anode 1998 17 NR 13.2 2.15*** All workers at the plant were divided into 1998 (73) Carbon electrode manufacturing plant – maintenance 1998 19 NR 5.66 0.93 high medium and low exposure jobs prior Carbon electrode manufacturing plant – lab/office 1998 19 NR 1.59 0.26 to sampling. Age range 27-59. 21 smokers and 34 non-smokers Van Rooij Primary Aluminum Paste Plant – preshift 1992 8 NR 0.58 0.17-1.71 Determine relative contribution of PAH 1992 (74) Primary Aluminum Paste Plant – postshift 3.04 1.58-7.40 contamination of skin to Primary Aluminum Bake Oven – preshift 1992 5 NR 0.94 0.56-2.42 total PAH exposure by job area Primary Aluminum Bake Oven – postshift 4.40 0.98-13.1 59 Urinary 1OHP (µmol/mol creatinine) Study Aluminum smelter job Year N Sex 24h Mean GM Median SD Range Methods (pre- or post shift urine sample) (μg/day) (study population, demographics, plant information, purpose) Primary Aluminum Pot relining– preshift 1992 7 NR 0.53 0.23-1.33 Primary Aluminum Pot relining– postshift 5.96 1.90-12.2 Van Schooten Bake oven (preshift) (Day 1) 1995 5 NR 1.0* Exposed workers recruited from four PAH 1995 (41) Bake oven (postshift) (Day 1) 3.0 exposure level jobs, Bake oven (preshift) (Day 2) 5 NR 1.9 average age 41 years, Prebake anode plant, Bake oven (postshift) (Day 2) 3.9 synergistic effects of Bake oven (preshift) (Day 3) 5 NR 1.95 occupational PAH exposure and cigarette Bake oven (postshift) (Day 3) 6.0 smoking. Bake oven (preshift) (Day 4) 5 NR 2.1 Bake oven (postshift) (Day 4) 7.1 Bake oven (preshift) (Day 5) 5 NR 2.9 Bake oven (postshift) (Day 5) 6.2 Aluminum smelters Smokers High Exp (preshift) 14 NR 0.97 0.47 Aluminum smelters Smokers High Exp (postshift) 14 NR 7.19 4.00 Aluminum smelters Nonsmokers High Exp (preshift) 18 NR 0.47 0.28 Aluminum smelters Nonsmokers High Exp (postshift) 16 NR 3.87 2.99 Aluminum smelters Smokers Low Exp (preshift) 29 NR 0.52 0.34 Aluminum smelters Smokers Low Exp (postshift) 30 NR 0.74 0.38 Aluminum smelters Nonsmokers Low Exp (preshift) 27 NR 0.33 0.26 Aluminum smelters Nonsmokers Low Exp (postshift) 24 NR 0.47 0.22

*Read from graph **Converted from ng/ml to µmol/mol creatinine by assuming 13 mmol creatinine per liter urine *** Assuming average creatinine concentration in the urine is 14 mmol/L (van Rooij et al 1994) and urine production of 2L urine/day.

Abbreviations: N = number of urine samples included in the study (not the number of subjects in the study) Sex: M = male, F = female, and NR = not recorded GM = geometric mean SD = standard deviations

60

Table 3 DNA adduct levels in aluminum smelters reported in the literature PAH-DNA adducts (per 10E8 nucleotides) Study Aluminum smelter job Year N Sex Source Mean GM MedianSD Range Methods (pre- or post shift urine sample) (study population, demographics, plant information, purpose) Carstensen Potroom workers 1999 88 M Blood 2.62 1.44-6.67 Recruited from 167 current potroom 1999 (61) workers, Søderberg plant, Sweden Kriek Primary aluminum – all 1993 15 NR WBC 4.6 6.9 0.1-22.0 Demonstrate DNA-adducts in aluminum 1993 (80) After vacation 14 WBC 2.2 3.0 0.1-10.0 smelters Ref therein Day 1 11 WBC 2.7 4.4 0.1-15.0 Day 3 11 WBC 9.6 29.0 0.1-97.0 Day 5 11 WBC 6.5 11.0 0.1-30.0 Plant 1 25 PBL 1.48 0.96 0.3-4.1 Plant 2 21 PBL 3.08 1.69 0.4-7.1 Øvrebø Primary Aluminum – cathode relining by year: 1988 6 NR WBC 12.0 Biological survey of workers w/ high 1995 (28) 1989 17 15M,2F WBC 10.8 exposure jobs in potrooms: cathode relining. Survey time: 2.5 years.

44-74% of workers were smokers Schoket Primary Aluminum – plant 1 1989 25 M PBL 1.5 1.0 0.3-4.1 aluminum industry workers, 2 plants, 1993 (78) Primary Aluminum – plant 2 1989 21 M PBL 3.1 1.7 0.4-7.1 Hungary, Compare DNA adduct methods: Primary Aluminum – follow-up 1990 127 M PBL 3.1 1.8 0.5-9.2 32P postlabelling and ELISA Primary Aluminum – follow-up 1990 45 M PBL 3.0 1.7 0.9-9.6 Schoket Primary Aluminum – busbar operator Btw 7 M PBL 5.2 1.9 aluminum industry workers, 2 plants; plant 1995 (77) Primary Aluminum – anodeman 1989 11 M PBL 4.2 2.0 1-horizontalstud Søderberg; plant 2 – Primary Aluminum – potbuilder and 20 M PBL 2.8 2.1 horizontal- and vertical Søderberg, Primary Aluminum – potman 1992 73 M PBL 2.7 1.4 Hungary. Mean age of workers plant 1:42, Primary Aluminum – tapper 5 M PBL 3.5 1.2 37, 45yrs, plant2:40, 36, 38yrs in study Primary Aluminum – maintenance and crewleaders 11 M PBL 3.9 2.0 1,2,3 respectively. Employment duration Primary Aluminum – studpuller 2 M PBL 3.8 0.9 between 10-18 years. Give a Primary Aluminum – flex raiser 6 M PBL 2.7 0.9 comprehensive overview of the Primary Aluminum – potman 29 M PBL 3.0 1.0 longitudinal biomonitoring study during Primary Aluminum – stud cleaner 8 M PBL 3.2 1.6 normal operations and after close-down. Schoket Potroom workers GSTM1 postive 2001 79 M PBL 3.2 1.8 High exposed potroom workers, Explore 2001 (69) Potroom workers GSTM1 null 82 M PBL 2.9 1.7 correlation between DNA-adducts and 1OHP, metabolic genotypes of phase 1 and phase 2 enzymes. Tuominen Potroom workers 2002 91 M Lymphoc 6.71 <0.1-39.5 Continuum of Carstensen et al. 1999, 2002 (62) ytes Potroom workers, Swedish Søderberg plant, smokers and non-smokers included. Explore individual PAH-DNA adducts and the genetic factors potentially influencing them. Van Delft Carbon electrode manufacturing plant – carbon anode 1995 13 NR Lymphoc 5.1 2.6-17.0 All workers at the plant were divided into 1998 (73) Carbon electrode manufacturing plant – maintenance 1995 14 NR ytes 5.0 2.6-15.0 high medium and low exposure jobs prior Carbon electrode manufacturing plant – lab/office 1995 15 NR 6.5 3.4-25.0 to sampling. Age range 27-59. 21 smokers and 34 non-smokers. Exploring occ exp to PAHs with three methods: air PAH, 1OHP and DNA adducts.

61 Abbreviations: N = number of blood samples included in the study (not the number of subjects in the study) Sex: M = male, F = female, and NR = not recorded Source: PBL = periphery blood lymphocytes, WBC = white blood cells GM = geometric mean, SD = standard deviations

62

Chapter 3 Determination of fluorine substituted polycyclic aromatic hydrocarbons (F-PAHs) in aluminum smelter dust

Nancy B. Hopf1, James Mack2, Martin Harper3, Yngvar Thomassen4, Glenn Talaska1

1 Department of Environmental Health, University of Cincinnati, 3223 Eden Ave., P.O. Box 670056 Cincinnati, OH 45267. 2 Department of Chemistry, University of Cincinnati, 404 Crosley Tower, PO Box 210172 Cincinnati, OH 45221. 3 Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, 1095 Willowdale Road, Morgantown, WV 26505 4 Norwegian National Institute of Occupational Health, PB 8149 Dep, N-0033 Oslo, Norway

3.1 Introduction

Exposures in aluminum smelters are of great health concern. In earlier years, fluorosis was the

main health concern; however today cancer of the lung and bladder (8, 9), and respiratory

morbidity commonly named “potroom” astma are especially concerning. Exposure studies in the

past have been concerned with contaminants such as polycyclic aromatic hydrocarbons (PAHs),

fluoride, alumina, sulphur dioxide, and carbon monoxide. In addition to these chemical

exposures, smelter workers also encounter physical exposures, such as magnetic fields from

electric currents (50,000-280,000 amperes), and heat (pots > 980°C) (33, 95). Beside the direct

effect on the workers, these physical and chemical hazards could potentially introduce new and

unknown exposures in this workplace.

Aluminum smelting is an electrochemical process producing pure metal from its ore (bauxite,

bauxitt). Electric current flows between a carbon anode (positive), made of petroleum coke and

63 pitch, and a cathode (negative), provided by the thick carbon or graphite lining of the pot. The

source of PAHs in aluminum smelters is the coal tar pitch that forms the anodes, and the largest

quantities are emitted from the anodes used in the Søderberg process. Fluoride is used as a

solvent in the reduction process in the form of cryolite (Na3AlF6), with additional components

such as aluminum and calcium fluoride (33, 95).

Fluorine-substituted PAHs (F-PAHs) can be formed through a variety of mechanisms. PAHs and

fluorides may come into intimate contact during aluminum extraction, which requires a high

electrical current potentially driving F-PAH formation. Direct fluoride substitution of aromatic

rings requires a high activation energy (Gibbs free energy, ΔG‡), which can be supplied in

aluminum smelters as thermal or electric energy. Fluorine free radicals may be formed (via heat

or electrolysis) producing hydrogen fluoride (HF) and thus R-F (R being an aliphatic moiety)

may be followed by ring closure. F-PAHs can be synthesized by reacting fluorides with an

organic compound, followed by ring closure under very low temperatures in the presence of a

catalyst(96). The most recent trend in the synthesis of organofluorine compounds is the use of

selective electrochemical fluorination (SEF). This process involves electrochemical partial

fluorination in ionic liquids, such as fluoride salts, and proceeds via a (radical) cation

intermediate.(97) The result is a highly selective fluorination whose stereoselectvity is

determined by the presence, or absence of solvents. Using this method, triethylamine*HF salts

in the absence of solvents produced tetrafluorobenzene derivatives(98) . Fluorinated aromatic

compounds of caffeine, flavones, and quinoline have been synthesized using SEF(99). Based on the high-energy conditions in aluminum smelters, processes of this kind may also occur in aluminum smelting.

64

Today, the aluminum industry employs more than 15,000 workers in 14 United States plants.

There are about 300 aluminum plants worldwide

(http://minerals.usgs.gov/minerals/pubs/commodity/aluminum/alumimcs04.pdf, accessed

07/07/08). PAH exposures in aluminum smelters are common (10, 11). Cancer rates in this population are elevated (2, 7), consistent with the knowledge that some PAHs are known or suspected carcinogens (4). As opposed to the case of PAHs, very little is known about F-PAH

exposure-associated hazards. In a study conducted in mice, the extent of formation of epidermal

DNA adducts following exposure to two F-PAHs; 9-fluoro-7,12-dimethylbenz[a]anthracene (9-

F-DMBA) and 10-fluoro-7,12-dimethylbenz[a]anthracene (10-F-DMBA), was compared to that

for 7,12-dimethylbenz[a]anthracene (DMBA). 9-F-DMBA was equipotent to, whereas 10-F-

DMBA was more potent than DMBA for skin tumor initiation (100).

Based on the high-energy conditions in aluminum smelters and the plausible mechanisms for

forming F-PAHs, we hypothesized that F-PAHs may be produced during the primary aluminum

smelting processes, and that these compounds might therefore be found in dusts from these

facilities. This study is the first attempt to detect F-PAHs in dusts in aluminum smelters. Our

specific aim was to compare reverse phase high performance liquid chromatography with

UV/VIS photodiode array absorbance detection (HPLC/PDA) and gas chromatography with

mass spectroscopy detection (GC/MS) of settled dusts from ducts obtained from various

operations in primary aluminum smelters, with HPLC/PDA and GC/MS spectra from available

F-PAH standards (Chiron, Norway).

65 3.2 Materials and Methods

3.2.1 Dust samples

Five dust samples were obtained from Norwegian primary aluminum smelters. Two settled dust

samples were obtained from ducts in the Søderberg potroom at a plant in Karmøy and one settled

dust sample from a filter in the prebake potroom. One sample was collected at a prebake smelter

potroom in Sunndalsøra, from an area processing used prebake anodes for Al2O3 residue and one

sample was of the carbon recovered in this process. These dust samples were grab samples and

the bulk material was put in a plastic tube and shipped overnight from Oslo, Norway to

Cincinnati, Ohio. The samples were stored at 4˚C.

3.2.2 Dust sample analysis

F-PAHs behave similarly to PAHs (101) in their chemical and physical properties, therefore

established and validated extraction methods for PAHs in dust samples were utilized: 1)

Environmental Protection Agency (EPA) method TO-13A (102) and 2) National Institute for

Occupational Safety and Health (NIOSH), NIOSH Manual for Analytical Methods (NMAM)

number 5506 for PAHs (103).

For the EPA (TO-13A) extraction method, each dust sample (3.5-4.0 g) was extracted in 200 ml ethylacetate:hexane (v/v 10:90) using a Soxhlet apparatus. Extraction was carried out for 18

hours, and the solvent evaporated using a vortex rotavapor (Büchi Rotavapor-R). The samples

were re-suspended in methanol (6 mL), and filtered (syringe filters, 0.45 um, 25 mm,

Nalgene™).

66 Extraction was also performed using sonication (103). Each dust sample (0.5 g) was extracted in

acetonitrile (20 ml) with sonication (Model FS60, Fisher Scientific, Pittsburgh, PA, USA) for 10

minutes. The samples were solid phase extracted (SPE) using C18 cartridges (SepPakR

Cartridges, Waters Corporation, Milford, MA, USA) and the F-PAHs eluted with acetonitrile.

The solvent was evaporated using an analytical nitrogen evaporator (N2-evapR Model no. 111,

Organomation Associates Inc., Northborough, MA, USA). The samples were re-suspended in

methanol (2 ml) and filtered (syringe filters, 0.45 um, 25 mm, Nalgene™). F-PAH recovery

studies were performed using both extraction methods. Two dust samples were spiked with F-

PAHs (100 μl of 0.1 μg/μl solution of each F-PAH standard in toluene) and Soxhlet extracted

(EPA method). Two other F-PAH spiked dust samples (100 μl of 0.1 μg/μl solution of each F-

PAH standard in toluene) were extracted using the sonication techniques (NMAM method).

Filtered samples were analyzed by HPLC/PDA and GC/MS. The HPLC system consisted of a

Waters 2695 separation module with integrated solvent degasser, autosampler and two constant flow syringe pumps, and a Waters 996 Photodiode Array Detection (PDA) detector (Waters

Corporation, Massachusetts, USA). A Supelcosil™ (30 cm x 4.0 mm, 5 μm LC-18, Supelco Inc,

Bellafonte, PA, USA) column was used for the dust analysis at 30˚C. The mobile phase was a

water:acetonitrile gradient (60 to 100 acetonitrile using curve 9 in 12 min, hold 11 min, back to

initial concentration) at a flow rate of 0.5 ml/min. Injection volume was 35 μl. Data acquisition

was performed with Empower Pro 2.0.

In the GC/MS method, the GC column was a Zebron-ZB- 15m x 0.25 mm x 0.25mm capillary

column. The F-PAH standards were used to validate the length of the column. The column was

67 operated under the following conditions: injection volume 4 μL; splitless injection temperature

250 ˚C; oven temperature increasing rate 10 ˚C/min from 70 ˚C to 200 ˚C; once the temperature reached 200˚C the temperature was increased at a rate of 15 ˚C/min from 200 ˚C to 300 ˚C. The

GC/MS interface temperature was maintained at 280 ˚C. A Hewlett-Packard HP6890 Series quadropole mass selective detector was used, and operated in electron impact (EI) ionization mode with electron energy of 70 eV, and scan range from 40 to 400 m/z.

The following standards (0.1 mg/mL in 1 mL toluene) were purchased from Chiron (Norway): 1- fluoronaphthalene, 5-fluoroacenaphthylene, 3-fluorophenanthrene and 2-fluorophenanthrene, 3- fluorochrysene, 1-fluoropyrene, 2-fluorofluorene, 3-fluorofluoranthene, and 9- fluorobenzo[k]fluoranthene.

3.3 Results

The F-PAH standards had retention times between 7 and 14 minutes in the chromatograms under

the HPLC/PDA conditions described in methods (Figure 5). The F-PAH standards’ structures

and UV spectra are shown in Figure 6. Standard curves using HPLC/PDA for the F-PAH

standards were developed separately, and correlation coefficients were 0.99 for all individual F-

PAH. The F-PAH peak intensities in the chromatograms varied considerably. To visualize the

relative F-PAH peak intensities, a mixture of each F-PAH standard in equal concentration (0.1

μg/μl in toluene), was separated on the Supelcosil™ column (30 cm x 4.0 mm, 5 μm LC-18,

Supelco Inc, Bellafonte, PA, USA) (Figure 5).

The recoveries for both extraction methods were >100% using HPLC/PDA. The recoveries were

extremely high because the F-PAH standards could not be separated from their analogous PAHs

68 found in the samples. The F-PAHs could not be separated in the GC either, therefore we could not quantify the amount of F-PAHs in the spiked samples.

The dust samples had multiple peaks with retention times equal to the F-PAH standards. Dust found in the prebake potroom dry filter did not show any UV absorbance in the aromatic region

(230-260 nm) as opposed to the other dust samples and F-PAH standards. Several of the peaks in the HPLC/PDA chromatograms of the dust samples had absorbance spectra similar to the F-

PAH standards. From the recovery study, we knew that PAH analogues of the F-PAHs could not be differentiated in the HPLC/PDA system, therefore determination of possible F-PAHs present in the sample was attempted with MS. Each of the dust sample peaks in the GC chromatograms was analyzed separately with MS to obtain a MS fragmentation pattern for each peak. To collect fragmentation data on all possible F-PAHs in the samples, the MS was set to full scan mode, i.e. broad range of mass fragments was monitored for m/z 50 to m/z 400. None of the dust MS spectra showed M+ of any of the F-PAH standards or a loss of m/z 19 or m/z 20 as would be expected for fluorine and HF, respectively. GC chromatograms of each dust sample (n=5) are shown in Figure 7.

3.4 Discussion

The aim of this study was to determine whether F-PAHs could be formed in environments within

the aluminum smelters (Søderberg or prebake) environments, and detected by modern chemical

analysis. It was hypothesized that C-F bonds could form by either of two mechanisms: thermal

(including pyrolysis) and SEF. F-PAHs may subsequently form by condensation, which is the

mechanism by which PAHs are formed in the environment. We hypothesized that the high

currents (50,000-280,000 amps) and intense heat (980ºC) would provide sufficient activation

69 energy (ΔG‡) for aromatic fluoride substitution to occur. We did not detect F-PAHs in any of the

dust samples collected in these facilities. However, the sample size was too small to state

unequivocally that F-PAHs do not exist in settled dusts from aluminum smelters. It is possible

that F-PAHs are formed in the aluminum reduction environment, but not in the areas where the

dust samples were collected.

Failure to find F-PAHs might also have been a consequence of less than optimal extraction

methods (Soxhlet and sonication). Trifluoroethane or trifluoroethanol, which selectively extract

fluoro-substituted materials, could have been better solvents for F-PAHs. The HPLC / PDA

chromatograms suggested that the organic material was efficiently extracted from the settled dust

samples, however.

The physicochemical properties of monofluorinated PAHs are very similar to that of their un-

substituted analogs (104). They have often been used as internal standards (IS) in PAH analyses

and determination of extraction recovery efficiencies from environmental samples (104). From

the recovery study it was clear, with apparent recoveries far above 100%, that the HPLC/PDA

method could not differentiate between F-PAHs and analogous hydrocarbons. Retention times

were practically the same, as were UV-spectra. From this, analogous PAHs were clearly present

in the samples, even though they were not quantified. A separation between F-PAHs and their

analogous PAH in GC also failed, and recoveries could not be calculated for the GC/MS method.

Using F-PAHs as internal standards in the quantitation of PAHs in environmental samples was not useful using HPLC/PDA or GC/MS. This is in contrast to Luthe and Brinkman (104), who

70 used F-PAHs as internal standards in a metabolic study. In their study, the F-PAHs had slightly higher retention times in comparison with their hydrocarbon analogues using LC and UV/VIS detection. They found, as we did, that the UV-VIS absorbance spectra of the F-PAHs and PAHs are practically identical. To distinguish the F-PAHs from the non-fluorinated compounds these authors(104) used Shpol´skii spectroscopy, a qualitative detection technique requiring special equipment and very low temperatures (40˚K). We deemed F-PAH not useful as internal standards in extracting organic materials from dust samples and analyzing them using

HPLC/PDA or GC/MS. To be able to use F-PAHs as internal standards in extraction of organic material in environmental samples a large amount of F-PAHs would be necessary to distinguish these peaks from all other PAH peaks present in the dust.

One of the major limitations of using a PDA detector is its sensitivity, and its variable sensitivity across different F-PAH species (Figure 5). Some PAHs are often detected using a fluorescence detector instead of a PDA detector. This is because the fluorescence detector is more sensitive. In our case, we wanted to detect several F-PAHs in a single sample. It is more convenient to use a

PDA to detect several F-PAHs at one time in one run because all the F-PAHs absorb at 254 nm.

Using a fluorescence detector involves a specific absorption and emission wavelength for each

F-PAH structure, because a single absorption and emission wavelength common to all these structures does not exist. Therefore the use of fluorescence is impractical in the case of multiple

F-PAHs, unless the fluorescence detector can be programmed for each sample run.

71 3.5 Conclusion

Even though F-PAHs were absent in the few dust samples we collected, we cannot rule out the

possibility that these compounds may exist in the potroom air. The F-PAHs may be a source of

worker exposure by both inhalation and dermal routes to carcinogens and potentially other health risks. Future studies should focus on fully characterizing the air and dust in aluminum smelters.

Disclaimer.

The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.

Acknowledgment:

MS/GC spectra were obtained with help from Andrew Hughett, who carried out the analysis of the dust samples, and Darius Criswell, who performed the analysis of F-PAH standards.

72

Figure 5 Chromatogram using HPLC with Supelco column (Supelcosil TM LC18 30cmx4.0mm, 5um) and PDA detector (254 nm) showing relative F-PAH [0.1 μg/μl in toluene (RT=5.8 min)] RT and intensity. Inserted table gives F-PAH RT and max absorbance in UV.

73

Figure 6 UV and structures of F-PAH standards used to identify possible F-PAHs in dust samples from aluminum smelters

74

Figure 7 Settled dust samples from a) ducts in the Soderberg potroom (Karmøy), b) ducts in the Søderberg potroom (Karmøy), c) filters in the prebake potroom (Karmøy), d) used anodes processing area (Sunndalsøra), and e) carbon recovered from used anodes (Sunndalsora), analyzed by GC (labeled #1a-e) and HPLC (labeled #2a-e).

75 Chapter 4 Urinary 1-hydroxypyrene levels in offshore workers

Nancy B. Hopf1, Jorunn Kirkeleit2, Stacy Kramer1, Bente Moen2, Paul Succop1, Mary Beth Genter1, Tania Carreón1, James Mack3, Glenn Talaska1

1 University of Cincinnati, Department of Environmental Health, 3223 Eden Ave., P.O.Box 670056 Cincinnati Ohio 45267 2 University of Bergen, Department of Public Health and Primary Health Care, P.O.Box 7804, N-5020 Bergen Norway 3 University of Cincinnati, Department of Chemistry, CROSLEY 502 P. O. Box 210172 Cincinnati OH 45221

4.1 Introduction

Crude oil contains carcinogenic polycyclic aromatic hydrocarbons (PAHs) (4) to a

variable degree depending on the geographic source of the oil. After arriving at an

offshore production facility, crude oil is piped through a closed system where it is separated into oil, gas, water and solid waste (sand and sediment). The amount of PAHs in crude oil is generally low, but the crude oil residues in sand/clay (sludge) may contain

higher amounts of PAHs (13). Fossil water trapped with oil and gas in the geologic

reservoir and pumped up with the oil also contain PAHs(14, 15). Although most of the

processes on offshore installations are performed in closed systems during ordinary

operations, the petroleum workers offshore may be at risk of exposure to PAH and other

aromatic hydrocarbons whenever the system is opened for surveillance, cleaning,

inspection, and maintenance. Exposure to other aromatic hydrocarbons has been

demonstrated among oil production workers(105, 106), but exposure to PAHs in this

work environment has not been published.

76 PAHs can enter the body through ingestion, inhalation, and percutaneous absorption. It is therefore advantageous to use biological monitoring of PAH exposure over

environmental monitoring to estimate the internal dose from all routes of exposure (24).

The internal dose can be estimated using urinary 1-hydroxypyrene (1-OHP) as a surrogate for PAH exposure. 1OHP is a metabolite of pyrene, which is one of many compounds in the PAH mixture. The pyrene metabolite 1OHP is easily detected and has been extensively studied as a biomarker for monitoring PAH exposure (53-55). In spite of PAH being a known constituent of crude oil, internal PAH exposures in offshore workers have not been investigated.

Petroleum workers on the Norwegian continental shelf have an extended work schedule:

12 hour shifts 7 days a week for 2 weeks with 28 days of leave between the tours. In addition, the potential hydrocarbon exposure for some workers during some tasks (e.g. tank work) coexists with a high physiologic strain that presumably increases a potential chemical uptake.

This study had three specific aims. The first aim was to compare the difference in post- shift urinary 1OHP levels between exposed and non-exposed workers (controls), after controlling for smoking, age, and pre-shift urinary 1OHP levels. The exposure group for this specific aim included workers in two jobs: tank workers and process operators. The second aim was to compare the difference in post-shift urinary 1OHP levels between the two exposed groups (process operators, tank workers), after controlling for smoking, age, and pre-shift 1OHP levels. As some of the workers might have been exposed to PAH

77 through their work prior to this study was performed, the third aim was to compare pre- shift urinary 1OHP levels between exposed workers and controls, after controlling for smoking status and age. From these specific aims, this study had three hypotheses:

1. Mean post-shift urinary 1OHP levels are statistically significantly different between

the exposed and unexposed workers, after controlling for smoking, age, and pre-shift

urinary 1OHP levels.

2. Mean post-shift urinary 1OHP levels are statistically significantly different between

tank workers and process operators, after controlling for smoking, age, and pre-shift

urinary 1OHP levels.

3. Mean pre-shift urinary 1OHP levels are statistically significantly different between

the exposed and unexposed workers, after controlling for smoking and age.

4.2 Methods

4.2.1 Study population

The study population of offshore oil platform workers (N=42) located on the Norwegian continental shelf consisted of two exposure groups with different jobs and locations.

Tank workers (n=13) were recruited from a crude oil production vessel, while process operators were recruited from a fixed oil and gas installation (n=12). The study also included a presumably unexposed control group recruited from the same installations as the exposed workers (n=17).

78 The tank workers in the present study performed maintenance work in crude oil cargo tanks (volume 5000-7800 m3) to mend leaks due to corrosion and cracks. These tasks included tank cleaning, tank inspection, scaffold construction, and welding. Before maintenance work started, the tanks were cleaned with hot crude oil and sea water and purged with inert gases and fresh air. However, the empty storage vessels ready for inspection and maintenance had sludge lining the inside and covering the bottom. The tanks were continuously ventilated with forced air.

The process operators included in the study ran the day-to-day operations on the oil and gas installation. Tasks associated with potential PAH exposures were: 1) sampling and analysis of crude oil, condensate and produced water, 2) sending and receiving pipeline cleaning devices (referred to as “pigs”) to clean out the sludge lining the inside of the vessels and 3) inspection of and work on the flotation package (handling of produced water) (105).

For both exposure groups, a control group matched on shift was selected. All controls worked in the living quarters; two controls surveyed the production from a central control room, while the remaining controls worked in catering or housekeeping. Although a few of the controls might have been exposed to PAH during cleaning of dirty suits, none of the controls were in the area where crude oil or produced water was present.

Use of half-mask air-purifying respirators (APR) with a combination particle filter and organic vapor cartridge (OV) was mandatory during tank work. The process operators

79 were recommended, but not required to use APRs with OV cartridges during tasks associated with open systems (e.g. maintenance, analysis etc). Tank workers used protective suits (Tyvek ®) during cleaning and inspection. These protective suits were worn over the cotton coveralls and discarded twice during each shift (before lunch and after the shift). All exposed workers used cotton coveralls during work hours.

The participants completed a self-administered questionnaire including questions on age, gender, and whether they were current smokers (yes/no) during the study period.

Smoking can give rise to urinary 1OHP levels. On offshore installations, smoking is prohibited except for designated smoking areas in the living quarters. Therefore, smoking status was included as a covariate when modeling occupational urinary 1OHP levels.

Information on grilled food was not included in the questionnaire, therefore, we were unable to account for possible food-related PAH exposures. However, all participants ate in the same cafeteria and may have eaten approximately the same type of food, but we do not know any details about this.

Informed written consent was obtained from all participants. All subjects were informed about their own results. The study protocol was approved by the Western Norway

Regional Committee for Medical Research Ethics, the Norwegian Social Science Data

Services, and the Institutional Review Board of the University of Cincinnati. The

Ministry of Health and Care Services in Norway gave permission to transfer urine samples to the University of Cincinnati for analysis.

80 4.2.2 Urine samples

Urine samples (n=81) used for this analysis were collected as part of another study

conducted in July 2004 (tank workers), April 2005 (tank workers) and October 2005

(process operators) (105-107). The reason for several collection times was due to

practicalities (a limited number of workers included in tank work each time and transport

of samples and helicopter flights).

The sampling of urine is described in detail in Kirkeleit et al. 2006(106, 107) and Bråtveit

et al. 2007)(105). In short, two urine samples were collected from each participant at two

points in time: 1) Pre-shift: the morning void before the tank workers entered the tank

and in the morning at the helioport before departure to the oil- and gas installation for

process operators, and 2) Post-shift, collected immediately at the end of the 12-hour shift

on the third day of tank work for tank workers, and immediately after work on the 13th

day of the offshore work period for process operators. Urine collection times for the

controls were the same as for their matched exposed subjects. Pre-shift urine samples

were not collected from two process operators due to late enrollment into the study.

4.2.3 Laboratory analysis

The laboratory analyst was blinded to the exposure category and previous results for each

individual until the analysis was completed. Urinary 1OHP was analyzed by high performance liquid chromatography (HPLC) (Waters 680 Automated Gradient

Controller) with fluorescence detection (Waters 730 Data Module), after enzymatic

hydrolysis according to the method of Jongeneelen et al.1987 (55). The excitation

81 wavelength of the fluorescence detector was set to 242 nm and the emission wavelength to 388 nm. Creatinine was measured in urine samples using a creatinine kit (Stanbio

Direct Creatinine LiquiColor Procedure No. 0420) and a spectrophotometer (Beckman

Coulter DU800).

4.2.4 Statistical analysis

In the statistical models, the limit of detection (LOD) divided by the /√2 was used for results below the LOD (108). To account for differences in urine volume between study participants, urinary 1OHP values were creatinine-corrected by dividing the raw 1OHP values by the creatinine level, resulting in 1OHP μg per gram creatinine (μg/g creatinine).

Creatinine-corrected urinary 1OHP levels were not normally distributed (Shapiro-Wilks p-value <0.0001), and therefore we used a log-transformation using the natural log.

Although log-transformed 1OHP levels also failed the Shapiro-Wilks test, the symmetry of this variable’s distribution greatly improved. The Studentized residual test was used to detect possible outliers. No statistical outliers were observed when the magnitude of the

Studentized residuals were compared to the Bonferroni adjusted value. For two hypotheses, the outcome variable was post-shift urinary 1OHP and for the third hypothesis it was pre-shift urinary 1OHP. The main independent variable of interest was exposure group (tank worker, process operator, or control). For hypothesis 1 and 3, tank workers and process operators were grouped into a single exposed group for comparison with the controls. For hypothesis 2, controls were excluded from the analysis, and the tank worker and process operator groups were compared to each other. Because smoking increases urinary 1OHP, it was included as a dichotomous covariate (current vs. never or

82 former smokers) in the statistical model. Additional covariates included in the model were age, a continuous variable, plus pre-shift urinary 1-OHP. Similar to post-shift urinary 1OHP levels, pre-shift urinary 1OHP levels were creatinine-corrected and log-

transformed.

Analysis of covariance (ANCOVA) was performed using the PROC MIXED procedure

in SAS (109) to account for repeated urine measurements collected for each study

participant. All covariates and interactions of interest were included in the initial models

(e.g., smoking*exposure group, age*exposure group). Covariates and interaction terms

that were not significant (p-values > 0.05) were removed in a stepwise fashion, beginning

with the most complex interaction term. To test the assumption of equal variances

among the three exposure groups, the Brown-Forsythe test was performed. No

statistically significant variance heterogeneity between the three groups (p-values > 0.05)

was found.

4.3 Results

Tank workers were both contractors and permanent employees. While the permanent

employees did not perform tank work prior to our study, we do not have information regarding the work that contractors performed before participating in our study.

However, the contractors would not perform tank work three days prior to the pre-shift urine sample because it would take one day to get to the installation and two days offshore to plan the tank work.

83 The controls were older than both process operators and tank workers (Table 4), and had

lower 1OHP levels at both their pre-shift and post-shift voids. Controls and tank workers

reported similar smoking percentages, while process operators reported a lower

percentage of current smoking.

Two workers have visibly higher 1OHP levels than the rest (Figure 8); however, after

their levels were transformed to the logarithmic scale, they did not meet statistical criteria to be considered outliers. The tank worker with the highest post-shift urinary 1OHP level was a non-smoker. He had performed miscellaneous tasks in the tank such as scaffold building and being a fire watcher/safety guard for approximately 6-7 hours on the last day with minimal use of respiratory protection. The process operator with the highest post-

shift urinary 1OHP level was a smoker performing usual process work, but was not

reporting any task with a potential for hydrocarbon exposure.

The initial model for hypothesis 1 did not show any statistically significant terms. After

removing non-statistically significant terms (p-values > 0.05) in a step-wise fashion, the

final model consisted of exposure group (p -value ≤ 0.014), age (p -value ≤ 0.014), pre-

shift 1OHP level (p -value ≤ 0.008), and the interaction of age and exposure group (-0.16

p -value ≤ 0.0004). Based on these results, mean post-shift 1OHP levels were

statistically significantly higher in the exposed workers compared to the controls, after

controlling for age and pre-shift 1OHP levels.

84 For hypothesis 2, no statistically significant effects were observed in the initial model.

After removing non-statistically significant terms (p-values > 0.05) in a step-wise fashion, the final model consisted of the non-significant exposure group (p ≤ 0.827), age

(p ≤ 0.007), and pre-shift 1OHP level (p ≤ 0.026). In this model, tank workers and process operators did not show significantly different post-shift 1OHP levels, after adjusting for age and pre-shift 1OHP levels.

For hypothesis 3, no statistically significant effects were observed in the initial model.

Again, after removing non-statistically significant terms (p-values > 0.05) in a step-wise fashion, the final model consisted of the non-significant exposure group (p ≤ 0.18) and significant smoking (p ≤ 0.02). In this model, pre-shift 1OHP levels were only associated with smoking; not the exposure group (control, process operator, or tank worker).

Three of the tank workers were scheduled to perform tank work for all three days, but only performed tank work on the first of these three days. These workers’ urinary 1OHP levels did not reflect possible PAH exposures associated with tank work because most of

1OHP would have been excreted post-shift the first day. Excluding these three tank workers from the statistical analysis did not change the results (data not shown).

4.4 Discussion

Exposed workers had statistically significantly higher urinary levels of urinary 1OHP than the control group. The two exposure groups, process operators and tank workers, did not show differences in 1OHP urinary levels. The internal exposure of PAH,

85 measured as urinary 1OHP not corrected for creatinine, was low (0.03 ug/L) compared to

the biological exposure index (BEI) for urinary 1OHP (1 μg/L) (6) both in process

operators and tank workers. The urinary 1OHP levels were 1.6-5.9% of the BEI.

All of the offshore-workers’ exposure levels were well below what has been reported for

many other occupational groups exposed to PAH (18). The controls had similar urinary

1OHP levels as those reported in a general population in Germany recently surveyed

(110), while tank workers’ mean post-shift levels corresponded to levels reported for a general population of smokers(111).

Urinary 1OHP elimination in humans is triphasic with half-lives of 5 hours, 22 hours, and

17 days (6). In our study, post-shift urine samples were collected three days after the

collection of the pre-shift samples for tank workers, which would presumably maximize

the urinary 1OHP concentrations. The time of the peak urinary 1OHP levels are relative

to the time of the tank work performed during the shift. If tank work was performed

earlier in the shift, then peak 1OHP excretion would be during mid-day and we could

have possibly underestimated their exposure. However, due to the ambient temperatures and low vapor pressure of PAH, dermal exposure probably predominates and this is

associated with a slower appearance of urinary 1OHP (21).

Peak exposures would also depend on personal protective equipment (PPE) worn by the

worker. The use of respirators varied among the workers, and the workers replaced the

filter/cartridge with varying frequency. The extent of respirator use was not recorded

86 quantitatively, as was true for glove (goatskin, leather, nitrile, surgical) use.

Unfortunately, we did not have information on the individual’s change-out schedules of respirators, suits or gloves. This information could potentially be a significant factor in modeling urinary 1OHP post-shift levels, and collecting PPE information is of vital importance in modeling this type of exposure. At the oil installations under study, PPE were made available at no cost and in unlimited supply to the workers, which might not be the case at other oil installations. Future studies among offshore workers should include information on personal protective clothing (type, duration, frequency, change- out schedules).

Age played a significant role in both models. An earlier study (112) showed that offshore workers are an aging workforce. It is not known if the metabolism of pyrene to 1OHP significantly decreases with age. Therefore, the importance of age may be better explained by jobs performed: 1) older workers are experienced workers, knowing how to control their PAH exposures or 2) younger workers perform the dirtiest jobs. The age relationship could not be further explored due to the small sampling size.

No correlation was found between log transformed post-shift urinary 1OHP levels and smoking (Pearson correlation: 0.21, p=0.18), implying that post-shift urinary 1OHP

levels are related to occupational exposures and not to smoking. Smoking is strictly regulated offshore, and smoking is only allowed in designated areas. Pre-shift urinary

1OHP levels were correlated with smoking (Pearson correlation 0.34, p=0.04), as

expected from hypothesis 3. One explanation for this relationship might be that smokers

87 among process operators and controls had unlimited access to cigarettes before collection

of the pre-shift urine samples prior to the departure to the installations (between tours).

Sampling urine is an efficient and very reliable way of assessing exposure to PAHs, and

this method may be an effective way of assessing internal exposure to crude oil derived

PAH in this industry. Importantly, the internal dose of pyrene reflects all routes of PAH-

exposures, extended work schedules, increased uptake due to physical activity, as well as

the inter-individual variations in absorption, metabolism, and excretion of this PAH compound.

4.5 Conclusion

Significant covariates in the model for post-shift urinary 1OHP were exposure group

(control, tank worker, process operator), 1OHP preshift levels, and age*exposure group

interaction term. Mean post-shift 1OHP levels were significantly higher in the exposed

workers compared to the controls, after controlling for age and pre-shift 1OHP levels.

Tank workers and process operators did not show significantly different post-shift 1OHP

levels, after controlling for age and pre-shift 1OHP levels. This study indicates the

presence of a low level PAH exposure among offshore production workers. Future

studies among offshore workers should include information on personal protective

clothing (type, duration, frequency, change-out schedules), diet, PAH concentrations in

air, crude oil and sludge.

88 4.5.1 Acknowledgement

We wish to thank Brenda Schumann for assistance in the laboratory and Dr. Howard

Shertzer for access to laboratory instruments. Funding was received by the National

Institute for Occupational Safety and Health (NIOSH) and the Health Pilot Research

Project Training Program of the University of Cincinnati Education and Research Center

Grant #T42/OH008432-03.

89 Table 4 Descriptive Statistics by Exposure Group Exposure N Current Median Age % Male Group Smokers (Range) (%) º Controls 17 5 (29.4) 45.0 (29.0-60.0) 62.5 Tank Workers 13 4 (30.8) 35.0 (27.0-55.0) 100 Process Operators 12 3 (25.0) 44.5 (22.0-59.0) 66.7 º Versus former or never smokers

90 Table 5 Descriptive urinary 1OHP (not log-transformed, creatinine adjusted given in μg/g creatinine and un-adjusted values given in μg /L of urine) statistics by exposure group 1OHP Controls (N=17) Process Operators (N=12) Tank Workers (N=13) Creatinine Variable n % >LOD GM GSD n % >LOD GM GSD n % >LOD GM GSD Pre-shift Adjusted 0.058 0.101 0.068 0.123 0.137 0.265 16 71 10 67 13 69 Un-adjusted 0.014 0.009 0.031 0.038 0.034 0.042

Post-shift Adjusted 0.034 0.059 0.201 0.608 0.281 0.872 17 53 12 17 13 69 Un-adjusted 0.016 0.022 0.027 0.041 0.059 0.069 N= number of workers, n = number of urine samples analyzed, GM = geometric mean, GSD = geometric standard deviations

91 4.5

4

3.5

3

2.5

2

1.5 urinary 1OHP (ug/g creatinine)

1

0.5

0 Controls Tank workers Process operators

Figure 8 Urinary 1OHP (μg/g creatinine) by exposure group (controls, tank workers, and process operators) and shift (pre-and post-shift). Horizontal lines indicate the median.

92 Chapter 5 Conclusion In this dissertation we have described three studies on worker exposures to PAHs in aluminum smelters and in the offshore industry. A better understanding of PAH exposures, including historical exposures, characterization of novel exposures, and previously uncharacterized worker populations, will enable us to implement exposure monitoring programs to reduce PAH exposure, and ultimately reduce human disease.

Historical exposures were investigated in the primary aluminum industry by systematically reviewing the scientific literature for results on biological monitoring of workers in United States aluminum smelters, especially for carcinogenic biomarkers. We explored the trend in the quantitative PAH exposure levels using two biomarkers for

PAH: 2-hydroxypyrene (1OHP) and DNA-adducts. We were not able to determine a trend in biomarker levels due to variable selection of study populations, poorly defined job tasks to compare jobs across plants and times, worker variability not identified, and lastly, cumulative exposures not considered.

We also investigated the impact of genetic polymorphisms associated with metabolism of

PAHs on urinary 1OHP and DNA-adduct levels in aluminum smelter workers.

Currently, only three polymorphisms in aluminum smelters have been explored: CYP1A1

Ile462Val heterozygous genotype, GSTM1 and GSTP1. Reasons for the discrepant results observed in these types of studies may be due to the weak effects of a single polymorphism, while susceptibility may depend on multiple gene loci (93), and the gene-

93 environment interactions may magnify polymorphic variability in detoxification

capacity.(64) (Chapter 2)

We attempted to characterize novel aluminum smelter exposures such as fluorinated

PAHs (F-PAHs) that may pose an additional health hazard to these workers. F-PAHs are

carcinogens and have similar physical and chemical properties as PAHs. We analyzed

dust samples from ducts in three Norwegian aluminum smelters. The samples were

soxhlet and sonication extracted. Separation was performed using high performance

liquid chromatography (HPLC) with the most powerful UV/Vis absorbance detection: a

photodiode-array (PDA), and gas chromatography with mass spectroscopy (GC/MS).

Our analysis showed no presence of F-PAH; however, we only had five dust samples,

and, therefore, we cannot rule out the possibility that these compounds may exist in the

potroom air or in other areas of the plant that were not sampled. (Chapter 3)

We studied PAH exposures in a previously uncharacterized worker population: Offshore

workers. Crude oil contains PAHs. We determined the internal PAH dose in these

workers by quantifying urinary 1-hydroxypyrene (1OHP). Urine samples were collected

pre- and post shift from offshore workers performing three jobs: 1) tank workers –

cleaning and repairing the inside of crude oil storage tanks, 2) process operators –

controlling processes onboard permanent oil installations, and 3) controls - catering and cleaning living quarters. Modeling post-shift urinary 1OHP levels, we found several significant covariates: exposure group (control, tank worker, and process operator),

1OHP preshift levels, and the age*exposure group interaction term. Comparing post-

94 shift 1OHP levels between exposed and non-exposed workers, the model showed that the internal PAH dose was significantly higher in the exposed workers compared to the controls, after controlling for age and pre-shift 1OHP levels. Tank workers and process operators did not show significantly different post-shift 1OHP levels, after controlling for age and pre-shift 1OHP levels. This study indicated low level of PAH exposure among offshore production workers. (Chapter 4)

Based on our findings, the primary goal of future studies should be to conduct larger biological monitoring studies to determine and reduce excessive exposures of workers, and to control the working environment for carcinogens such as PAHs. To explain differences seen between and within workers in the same industry, we encourage the inclusion of covariates such as genetic polymorphisms, use of personal protective clothing (type, duration, frequency, change-out schedules), diet, and PAH concentrations in air, dust, and other surface areas. Therefore, future exposure studies will gain specificity by incorporating repeated measures on each worker (worker variability), determining urinary 1OHP in pre-shift samples after at least 48-hours of non-exposure

(cumulative exposure) and post-shift (daily exposures) samples, determining DNA- adducts in urothelial cells (target organ), determination of pyrene concentrations in the specific PAH mixture used at the plant, description of the workers’ job tasks and work practices in detail (to avoid misclassification of workers in epidemiological studies and to understand the fluctuation of 1OHP and DNA-adduct levels seen in workers within a plant or across plants), and documentation of PPE use, as well as worker tobacco use and exposure. Since PAHs can cause lung, skin and bladder cancer, other carcinogenic (e.g.

95 bladder carcinogen 2-naphthylamine exist in coal tar) concentrations of these materials

should be monitored.

Scientific investigations always lead to new questions, and other knowledge gaps

identified include: 1) the relationships between biological monitoring and air monitoring

of PAHs are not characterized, e.g. correlations between PAH air levels and DNA adducts or 1OHP levels have been inconsistent, and may be related to the fact that biomonitoring data often represent only a single point in time for an individual (Angerer et al 2006). 2) the impact of PAH exposures from confounding environmental sources on estimated internal dose from occupational exposures have not been quantified, e.g.

tobacco smoking can confound the interpretation of urinary 1OHP and DNA adducts

because tobacco smoke contains pyrene and other PAHs.(6) Smoking and occupational

exposures can combine to produce elevated urinary 1OHP levels(6).

Studies of occupational groups remain an important component of the current effort to

identify the causes of human cancer. Translating acquired knowledge of exposures to

carcinogens to enforcing control of such exposures, will reduce the incidence of future

occupationally induced cancers.

96 References

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