Document k94m28MbJ5gLeZ5EGvaBa9ejE

- Environmental Health Perspectives Supplements 101 ( S U ~ P L6): 13-21 (1993) Health Effects of Gasoline Exposure. 1. Exposure Assessment for U.S. Distribution Workers by Thomas d. Smith,' S. Katharine Hammond,' and --_ --- Otto Wong' I Personal exposures were estimated for a large cohort of workers in the U.S.domestic system fordistributing gasoline by trucks and marine vessels. This assessment included development of a rationale and methodology for extrapolating vapor exposures prior to the availability of measurement data, analysis of existing measurement data to estimate task andjob exposures during 1975-1985, and extrapolation of truck and marine job exposures before 1975. A worker's vapor exposure was extrapolated from three sets of factors: the tasks in his or her job associated with vapor sources, the characteristics of vapor sources (equipment and other facilities) at the work site, and the composition of petroleum products producingt9pors Historical data were collected on the tasks in job definitions, on work-site facilities, and on product composition. These data were used in a model to estimate the overall time-weighted-average vapor exposure for jobs based on estimates of task exposures and their duration. 'hsk exposures were highest during tank filling in trucks and marine vessels. Measured average annual, full-shift exposures during 1975-1985 ranged from 9 to 14 ppm of total hydrocarbon vapor for truck drivers and 2 to 35 ppm for marine workers on inland waterways. Extrapolated -past average exposures in truck operations were highest for truck drivers before 1965 (range 140 220 ppm). Other jobs in truck operations resulted in much lower exposures. Because there were few changes in marine operations before 1979, exposures were assumed to be the same as those measured during 1975-1985. Well- defined exposure gradients were found acrossjobs within time periods, which were suitable for epidemiolo~c analyses. Introduction An individual's exposure to an airborne agent is the time of the air concentrationin his or her breathing zone. -sure,exposure profile is processed to formulate epi- a d o g i c exposure variables such as ever exposed, years and cumulative exposure for an agent. Epi- denrdogic studies of cancer risk from inhaled agents h a y require the evaluation of exposure acrosslarge toberpas of time, much of it before the collection of expo- measurements.The central problem for retrospective estimationin this type of study is how to infer the c.r$onmental conditions without direct measurements. Problem may be divided into two subproblems: a) bt factors and emission mechanism determine the presence of the agent in a work location? b) If an agent is present, what factors affect its concentration in the workers' breathing zones? A strategy was developed to answer these questions for an epidemiologic study of cancer risk for workers in the U.S. domestic gasolinedistribution system,both truck and marine operations. The objectives of the exposure assessment were a) to develop a rationale and methodology to estimate historic marketing and marine distribution worker exposures to gasoline,b)to apply these methods to the U.S. gasoline distribution workers cohort, and c) to classify this cohort into groups with substantially different histories of gasoline exposure,suitable for an epidemiologic analysis of cancer risks. I nt of Family and Commu- Rationale I Medical Center, 55 Lake ond Avenue, sujte628, Po. B~ to T.J. Smith, Occupational Health pro- 665 s presented at the International Symposiumon the oline held 5-8 November 1991in Miami,FL. Determining the presence or absence of an agent iS easier generally than estimating its air concentration. A mechanistic model of exposure was developed for gasoline vapor, which is sh0N-n in Figure 1 (I). At its simplest, the model I-eqUireS three elements: a source of Vapor emissions, a worker in the area of the source, and transport of fb! f< + , I. .. , .. 14 -Liquid Gasoline from Tank rr (Truck ~ Tank ' SMITH ET AL. Worker (on top truck loadlng) Job title Tasks Work location estimate approximate exposure intensities and sort potentially exposed into subgroups by approximate i n h sity in an epidemiologicallyuseful way. Potential Agents 5* (dirplacod vaporr) Emission rate Composition An exposure classification for epidemiology ~ e ~ u i r e s selection of a hypothetical agent whose potential e f f e are to be examined in the epidemiologic analysis. For & present study,total hydrocarbons (THC)was the hypothesized agent. However, THC was also a reasonable e m gate for one or more of the major hydrocarbon components in the vapor mixture from gasoline based on an asseag ment of the scientific literature and the sampling dots, which showed that after approximately 1969 there relatively little change in the amounts of the meas- components of gasoline (2-5). Benzenewas an exceptiato this because the benzene content of gasoline has v m over time as a result of changes in gasoline blm* practices by the refineries. THC also may not be a surrogate for the minor components of gasoline vapor because they appear to be more variable than the maja components. FIGURE 1. Source-receptor model representation of a worker (the receptor) loading a tanker truck with gasoline. (The open hatch is the emission source.) Methods the vapor emissions into the worker's breathing zone. An industrial hygiene analysis of each work situation can determine if sources of gasoline vapor emissions are pre- sent. An analysis of tasks and work locations for each job title can identifythose that put a worker in closeproximity to an emission source where emissions might reasonably be transported into the breathing zone (the factors are shown in ?'able 1).Because historical work situations and \ 1 job titles can be evaluated by interviewing long-term I workers, it is possible to determine with a high degree of certainty which job titles and work situations have been historically associated with gasoline vapor exposure. .Estimating exposure intensity without exposure mea- s u r e a s is more difficult. The goal of exposure assess- ment for epidemiologic studies is not precise estimates of individuals' exposureintensity,but to identify groups with clearly different exposure intensities so their risks of disease may be compared. Therefore, exposure groups based on differences in sources of exposure (e.g., exposure situations with different emission rates) and/or large dif- ferences in potential contact with emissions are likely to produce different averageexposureswen if it is difficult to make precise estimates of the average per se. It also is relatively easy to identify exposure situations that repre- sent the extremes: those with minimal exposure and those with a high likelihood for intense exposures. These situa- tions represent the boundaries of the intensity continuum for a population. The mechanistic model of exposure pro- vides a means of assessing the quantitative effects of historic changes in factors affecting exposure. One such model is elaborated below. The combined mechanistic model and industrial Wgiene analysis approach can both An individual's exposure to gasoline vapors was de&^ mined by a)the tasks in his or her job definition,b)chantteristics of vapor sources associated with work-& facilitiesfor handling petroleum products, and c) the cam- position of the products handled. The source-receptm model shown in Figure 1 was developed to express the relationship between exposure and work-site factors (5,d). "bo types of emission sources for vapors were identified: displacement of vapors from a tank during filling and evaporation from open liquids, such as spillsor open tanka The job tasks that bring a worker in contact with the vapors from these sources and the site factors that &ect exposure intensity were identified through an industrial hygiene analysis ('Pdble 1).Exposure measurements were used to quantify exposure intensities associatedwith spp- cific combinations of job tasks, types of work sites, and types of products, although only common combination- had been measured. Task-TWAExposure Motlel. Given an estimate of avw- age exposure intensity for each task with exposure by work-site type and time spent on the tasks, a timeweighted average (TWA) exposure could be estimated for each job title and work-site type. task-TWA all tasks '2 '=1 = [(task mean)Jtask thdd all tasks 2 j=l (task time)y This is the task-TWAexposure model. The task-TWAf*' job title is an estimate of the arithmetic mean, W F needed to calculate the cumulative exposure do* EXPOSURE OF GASOLINE WORKERS - ~ 15 - W l e L Source of gasoline vapor emissions and factors affecting exposure intensity. Factors Dbplaced vapors (loeding and delivery) Si and venting of space (open area v s confined area) Proximity to source (immediatework area or general area) Pump rate (relatedto truck size)' Splash vs. submerged loading" Vapor recovery system' Top or bottom truck loading' Marine loading at site" Tight connection and remote tank vent at delivery site' Spills Volume spilled (overfillvs. drips) Proximity (immediatework area vs. general area) Frequency (rare vs. common) Size and venting of space Overfill controls (preset meters)" aothing contamination (contactkplashes) Frequency (rare vs. common) Length of delivery route (affects duration of exposure to volatilized %actors that are part of the equipment configuration at a terminal or ddivery site. ( b e d below). The advantage of this approach is it d h s back extrapolation of the TWA mean based on btmical data on tasks. h t exposures of gasoline distribution workers were gh.apolated with the task-TWA exposure model based on Is3ol. changes in job definitions and work-site charac- kbtics that had occurred across the industry. Changes b w k e r behavior over time also were used to modify rpoWrre, such as care in the prevention of small spills and Cpacern about inhaling vapors. nts. Exposure data had ng companiesover the were generally comPetroleum Institute recomompounds and the total measure task exposures, fixed location area sam- olated by the task-TWA making deliveries, and other nonexposed tasks. Most of their exposurewas received during loading and deliveries. Loaders performed only truck loading or nonexposed tasks. Terminal operators performed some loading, a variety of mechanical and maintenance tasks with some exposure potential and nonexposure tasks.This group included a wide range of job titles with variable potential for exposure but generally less than truck drivers. Other terminal job included all jobs with no potential for direct contact with emission sources. These workers were exposed only to background levels of vapor in the terminal area, such as clerks and managers. A similar process was followed for the marine operations, which consist of inland barges and domestic seago- ing tankers. Although there are important diffgi-eeces between these two types of marine operations,two genenjob groups were identified for both: deck personnel and other shipboard job. The deck personnel are all workers 1involved with the loading and discharge of cargo, which 1 are the major sources of vapor emissions.Other shipboard job tasks are involved only with indirect exposures to gasolinevapors. Companiesassigned alljob titles to one of the generic groups or a third category for land-based, predominantly office jobs. Historic W d i n g Conditions. Extensive information on recent and past truck and marine operations was collected by site visits, interviews of long-term employees and annuitants from each of the participating companies, and company completion of facilitiesquestionnaires on the history of equipment and operations at specific terminal sites and on selected marine vessels. These data were blended with published reports of industry-wide activities to developjob descriptions of tasks, work-site descriptions of typical operations, and historical changes across the industry. For facilities at truck terminals, four factors were obtained: splash or submerged top loading,metered or valved top-loading controls, bottom loading, and presence of a vapor recovery system. For marine vessels, four types of data were obtained: loading with hatches open or with remote venting, voyage frequency, percentage of gasoline in cargo, and area of operations. These data on individualterminals and vessels allowed the individualization of exposure estimates for subjects who worked at these sites and improved exposure classification. A matrix for assigning TWA exposures by type of truck operations and generic jobs (shown in n b l e 5 )was calculated for the four time periods. The task-TWA model was used to estimate driver exposures by type of loading and delivery facilities using measured or extrapolated exposure intensities for each task (loading, driving, delivery, and other). Intensities for tasks measured during 19751985 were adjusted to estimate earlier time periods by compensating for decreased concern about small spills, leaks, and minor clothing contamination, which will all contribute to inhalationexposure.Durations of tasks were adjusted based on interview reports and changes in truck size, pumping rates, and frequency of small deliveries. Annualized TWA exposures were calculated for deck personnel on barges using regionalized task exposuresfor loading and discharging cargo, duration of loading and i 16 Job title Truck and/or marine terminal jobs Driver Loader Terminal operator without marine facilities" Terminal operator with marine facilities" Other terminal job SMITH ET AL. lsble 2. Generic job gmups for petroleumdistribution operations Description - -4 Positions truck at filling rack; loads truck (if no loader);drives transport truck to/from d- asites; unloads gasoline at delivery site; performs clerical work as needed to record a c t i v i h transactions mwet-.Primarily loads gasoline trucks; may perform some plant maintenance; remains on the (makes no deliveries) (Plant worker, maintenance worker, auto mechanic, and may include yard worker); skilled person whose primary responsibility is to maintain and repair equipment at a de may also include inventory-controlprocedures, pipeline transfers of products gauging-s sampling and testing products (includingpipeline product@, and occasional truck loading (e.0- monthly) (Plant worker, maintenance worker, auto mechanic, or dock worker); same as terminal o m above but also performs any combination of tasks on dock, including position vessel and u b during docking and undocking; connect hose couplings to enable gasoline to be pumped pnd barges and tankers; use tape and thermometer to measure depth and temperature of pro&& Category includes supervisor, clerk, and other support personnel with occasional (e.g, incidental exposure outdoors or during plant duties, as well as laborer, yard worker, dock arorlpr (truck or warehouse loading dock at terminals without marine facilities) who are pred- exposed to background concentrationsfrom plant operations Seagoing tanker and inland barge operations Deck personnel (Ordinary seaman; able-bodied seaman; first, second, and third mates, etc.); COM~CV- hose couplings and/or activate pumps for cargo transfer operations;gauging during loadin& unloading; tank washing and cleaning (seagoingtankers only); tank stripping and inspection; watches and perform variety of underway activities, including watching for obstructions in the vessel's path, measuring water depth, repairing and stowing gear, handling mooring lines, maintenance, lubricatingmachinery, assisting officers in loading/unloading cargo, etc. Other marineharge shipboadjob Engineering department: captain, pilot, navigator, and engine room personnel. Steward depuhaart: cook, etc. Nonshipboard marine job Supervisory, clerical, technical, etc. Inland waterway barge operations Same breakdown as for tankers above, except the captain is placed in the deck group for eg#rpra reasons 'At a small terminal, terminal operators also perform loading. t discharging, watch duration and time onboard, each vessel's annual number of voyages, percentage of gasoline in cargo, and region of operations. TWA estimates were annualizedto a 2000-hrwork year to permit comparison to truck operation exposures. There were not enough data to estimate seagoing tanker exposures. I' Dose Indices Two dose indices for the epidemiologic analyses were calculated from the exposure assessment and job histories: cumulative exposure and annual fre- quency of peak exposures. Cumulativeexposurewas calculated by multiplying the TWA exposure for each job in a --subje$s' job history by the duration in the job and summing across all jobs. For truck operations, exposure assignments were based on the generic job assigned to each job title in a subject's work history. The truck terminals listed in the work history were used to identify type of facilities at the subject's work site so the appropriate exposure for each generic job could be drawn from the terminal exposure matrix. The marine subjects' cumulative exposures were calculated similarly for inland barge operations: the subjects' job history identified their job titles and vessels on which they served, titles were converted to generic jobs, and an annualized TWA for each genericjob was assigned based on the job TWA estimated for each vessel listed in their history. The annual frequency of peak exposures was deter- mined by identifymg the tasks with potential to produce peaks, estimating the annual number occurrences of the task, and then using the frequency distribution of expo- sure intensities for the tasks to estimate the fraction oft& total occurrences that exceed the minimum criteria faa peak. A peak exposure was defined as at least 500 ppa THC averaged over 15-90 min. The number of oceunwrer of a task was determined from the historical data The frequency distributions had been measured for all of the truck driver and barge tasks associated with potential peaks during 1975-1985. For past truck operations,it wa8 assumed that the frequency distributions would have the same general shape (lognormal with an approximately constant geometric standard deviation),but the geometric mean of the distribution would be shifted upward p r o p tionally to the change in arithmetic mean exposures. It was not possible to estimate peak exposures of terminai operators, although it is likely that they had some pal\ exposures. Findings and Conclusions Measured Exposures in 'buck Operations Measurement data were available for 1975-1985, wbkb were analyzed to estimate task and full-shift TWA sures. These findings then became the basis for theb d - ward extrapolation of historical exposures. lhsk Sample& Truck loading was a major SUUW1 exposure for drivers, loaders, and some terminal 0- (Table 3). 'hsk samples for drivers showed an 8-fd EXPOSURE OF GASOLINE WORKERS 139 130 14.2 7-60 103 120 15.4 7-60 36 157 32.4 8-60 Tup loading (1 company, 1 site) &xtmloading ('7 companies,6 sites) 81 17 2.8 8-60 42 11 1.1 8-60 39 24 5.6 15-40 , ~ dekliveries Large deliveries: remotely vented, large underground tanks using tight connections (1 company, 7 sites)" 32 9 1.8 of these samples was estimated from the sampling time specified in the methods. sure was rounded to one significant figure to represent the probable level of precision for our application of these data. I between loading without a vapor recovery OX) 30ppm) and with a VR system (17 ppm). Bottom wsus top loading of trucks showed no evidenceof kpendent of VR systems, but this was difficultto because there were few samples for top loading md bottom loading without VR. Terminal operaiona ally load trucks and were assumed to have exposure as drivers during this task. '8had been measured only at one site,where they 30 ppm for partial-shift samples. They showed pure than drivers using the same type of equipbably because the samples were longer than the mples (longer samplesincludemore time with low $ and because the loaders generally did not ib 8 truck while it filled, whereas the drivers did. uring truck fillingwas estimated by erved short-task samples of drivers' onger task samples of loaders d lower boundaries, respectively, the true mean was approximately eliveries, and exposures during f Were substantially different for small-volume F e e customer sites.Small-volume customers b had small above-ground tanks (500 gal) that gh an opening at eye level (where disalsovented) with a hand-held nozzle that within the tank. 'Panks for large-volume measurements of liquid levels in storage tanks. Other terminal jobs had no direct contact with emission sources through their task activities,and consequentlythere were no measurements for any of these tasks. The driver task data showed common opportunities for high short-term exposures(peaks) during loading without VR and small deliveries.Terminal operators perform some tasks that may produce peak exposures, but they were rarely measured. Full-Shift Job Exposure. Full-shift TWA samples (Eible 4) also showed differences in exposure by types of terminal equipment: Drivers averaged 14 ppm for terminals without VR systems and 9 ppm for those with VR. These samples were obtained from drivers making only large deliveries. Although loading exposures were varied more than this, only a smallfraction of a driver's work time is spent loading. Full-shift exposures of terminal operators were less than drivers at terminals with the same types of facilities:approximately 9 and 5 ppm without VR and with VR, respectively. There were few samples for other terminal jobs, but they were all very low (5 ppm). Thus, a gradient in job exposures was found in the fullshift data that was consistent with each job's potential for exposure. The 1975-1985 data showed a 7-fold range in exposures across the major jobs. Extrapolation of Historical Exposure for Tkuck Operations Four time periods with distinct characteristics were identified for truck operations: pre-1950,1950-1964,19651974, and 1975-1985. The characteristics of and differences among the time periods are summarized in Bble 5. Although sharp transition dates are given, they represent median dates of changes, and some parts of the distribution system changed earlier and some later. I f! t 1. I. - .. , -1. ,- .J . 1. I' c-- -I - G 18 SMITH ET dL. lsble 1.Time-weighted average, full-shift exposures for truck operation jobs by type of facilities, 1975-1985. Generic job/ THC arithmetic terminal loading facility N mean,ppm SE Driver No vapor recovery TODloadina i3 companies, 12 sites) Bottom loading (2 companies, 2 sites) Vapor recovery Top loading (1company, 1 site) Bottom loading (3companies, 1'7 sites) 98 90 8 94 7 87 14 1.5 14 1.5 18 2.4 9 1.6 10" 1.5 9 1.6 Terminal operatorb Top load, no vapor recovery (3companies, 12 sites) Vapor recovery (3companies,41 sites) 37 112 9 1.3 5 0.8 Other terminal jobs' 14 5 1.3 THC, total hydrocarbons. There were no THC data, so THC was extrapolated from benzene va r level assuming THC vapor contains 1% benzene. 'Terminal operator" job also includes plant worker, yard worker (depending on job definition), maintenance worker, and auto mechanic. '"Other terminaljobs" includes clerk, foreman, supervisor, warehouse worker, etc. Past exposures were extrapolated with the task-TWA model using exposure data from1975-1985, data from task simulations, and information on past operations and jobs. The accuracy of the model was checked by comparing the 1975-1985 task-TWA estimate for drivers at the two most common terminal configurations,top loading without VR +a%and bottom loadingwith VR,relative to the measuredfpn- shift exposures. The extrapolationswere within to -27" of the observed mean THC concentrations. Drivers. There were several important changes fa earlier periods that affected exposures: use of splash loading (the filling spout is above the level of liquid in tank, so gasoline splashes within the tank, creating aero. asol and rapid evaporation), small deliveries (splasilaftlrrpl of small above-ground tanks without remote ventingh less concern about small spills, leaks, or minor ci- contamination. Based on simulations, splash loading estimated to be 200ppm during 1965-1985. Loading s u e s before 1965were assumed to be 50% higher there were reports of more small spills and less concgll about contact with gasoline. Driving exposures increased in the past tamination, which is a because of increased clothing vapor source within the truck &,. Factoring these into the task-TWA extrapolation res- in substantially higher THC exposures for the three time periods preceding 1975, as shown in Table 6. Drivers at small terminals had consistently the exposures, averaging approximately 200 ppm, 1950-1965. Drivers at large terminals showed a pr- sive reduction in exposure from the high values of 16O-a ppm in 1950-1965 down to the low values measured in 1975-1985. In the earlier time periods, exposures during small deliveries were the most important sourcesof expo- sure, which is consistent with the relatively large fraction of time spent on this activity, about one-third of total time, and the high potential for exposure for this task. We concluded that earlier time periods had much higher potential for driver exposures and estimated a 10-to 37- fold increase depending on the type of terminal rad delivery operations. W l e 5. Historical changes affecting driver exposures to total hydrocarbons from gasoline during periods of m z k industry-wide changa' Loading \ ' 1975-1985 J ~ itiml e,~20 min; 1 0 , ~trugck~s; 500-gaVmin pump rates; spill controlsb Driver task Driving Rubber gloves (lessvapors in cab); clothing contamination rare; long delivery routes (70 min per trip) Delivery Delivery time, 40 min; small terminals discontinued; most large deliveries;tight delivery connections; remote stack vents fa tanks "---\ 1965-19'74 Fill time, 30 min; 8,OOO-gal trucks; 2jO-gaVmin pump rates; spill controlsb Leatherkanvas gloves; occasional clothing contamination; mixed-route length (50 min per trip) Delivery time, 50 min; mixed terminal size. mixed delivery size; tight delivery connections; remote stack vents for tank. 1950-1964' Fill time, 40 min; 6,000-gal trucks; 150-gaVminpump rates; limited spill controls Leatherkanvas gloves; limited concern about clothing contamination; many short routes (50 min per trip) Delivery time, 50 min; mixed terminal size. many small deliveries; tight delivery connections; limited remote tank venting Pre-1950 Fill time, 40 min; 2,OOO-gal trucks; 5co0n-gtraoVlsmin pump rates; limited spill Leatherfcanvas gloves; limited concern about clothing contamination; most short routes (50 min per trip) Delivery time, 50 min; most small terminrh; most small deliveries; loose delivery connections; remote tank venting These are based on median dates of changes and median conditions: Specific companies and regions may have changed factors at differentthO4d loading and delivery times may have been somewhat longer or shorter depending on equipment. This does not include changes in factors identified for work sites that are known to affect exposures,e.g, vapor recovery and type of loading. bSpill controls included changes in operating practices and, in later years, equipment modifxations such as high-level cutoff and preset %ansition time of major post-war expansion of delivery system. EXPOSURE OF GASOLINE WORKERS - 19 'hble 6. Summary of extrapolated, full-shift, time-weighted average exposures to total hydrocarbons (ppm) from gasoline for generic jobs and specific site types by time periods. Terminal size Large Small *and load type Driver DriverAoader Loader TO Driver TO c Both Other Submerged Splash Vapor recovery 1965-1974 Submerged Splash Vmor recovery 1iiiiilw Submerged Splash GS1&9s5h0 14" - 9" 64 79 41 190 220 170 7 - 6 41 42 39 150 150 140 --98 72 - - 5 9 150 80 210 80 28 ---- 75 68 170 68 1- Tcr,terminal operator. %served values, not extrapolated. % .recovery introduced in this time period, associated with frequent malfunctions and maintenance. I I I Loadenr.The task-TWA model was used to extrapolate ~ p o s u r eosf loaders. However, the data availablefor these the broad mix of job it was difficult to was consistent for all of the oup, such as yardman and del was divided into loading ing component was taken from e same equipment.The other tasks comporough estimates and multipliers based ts of changes in work activities and the inor sources, such 1Comparison among Tkuck Job 8 mduded that there was a substantial 10-fold graB S s the generic jobs: driver > loader > terminal P other terminal job that was consistent within time periods and for workers at the same types of teiminals. This gradient was consistent with qualitative assessment of contact with sources of gasoline vapor exposure. However, the quantitative estimates showed that the gradient was not consistent for job comparisons across time periods: for example, early-period terminal operators were as highly exposed as drivers in 1975-1985. The gradient also was not consistent across terminal types: Drivers at terminals with vapor recovery were less exposed than terminal operators at terminals with splash loading. Thus, care must be used in comparing workers classified by qualitative differences in generic job title alone. Marine Exposures and Historical Extrapolations Fewer data were available on marine exposures than on truck operations; the majority was obtained on barge operations on inland waterways. Marine operations were subdividedintovessel loading,underway,cargo discharge, and other activities. Exposure estimates are summarized by operation activity and region in Table 7. Most sampling data had been gathered on deck personnel to assess vessel loading because it presents the highest potential for exposure. Regional differences were observed in the average exposures during full-shift personal samples while loading: 250 ppm THC during loading several barges simul- taneously in the western rivers region and EO ppm during single-barge loadingin the East Coast region. Topping-off the tanks (thefinal stage of filling)was associated with the highest task cqosures observed: over 1500ppm THC for 15-30 min per tank. Discharging cargo was associated with much lower exposures because vapors are not being forced out of the tank (16 ppm for a full shift). Marine operations have very different work patterns from land-based operations. Marine workers are on-watch for 6 hr and off-watch for 6 hr continuously, 24 h r per day, while they are onboard a vessel. They also are onboard a 20 SMITH ET .4L. "hble 7. Estimated time-weighted exposures for 1940-1985 for inland barge operations handling gasoline by loading configuration and region.' Full-shift TWA euposures, pprn THC Deck personnelh Other vessel jobs 'Pdsk/operation Openhatch venting Remote venting All loading t"YPes Loading East Coast Western rivers and Gulf Coast UnWdeesntvCavoa+stwait ~~ Discharging 120 2 32 250 2 33 NA 1 2 0.2 16 ? 6 NA NA 2 2 0.3 Id 1 t 0.2 1' NA NA NA Id '1 NA, not applicable for the epidemiologic study. "Mean -c SE is given for those cases with measured data; the mean was rounded to two sigmficant figures. ?he captain is included in the deck personnel group for some companies. 'Loading exposures for nondeckcrewjobs were assumed to be approximately equal t o the underway level. dUndenvayandwaiting exposureswere assumedto be the same for all exposure groups. eDischargingexposures were assumed to be the same for all on-board personnel during discharging with remote venting. vessel for different time periods depending on the region, such as onboard for 40 days and on-shorefor 20 days in the western rivers region, and 1week onboard and 1week onshore in the East Coast region. Marine operations also tend to require more time than equivalent truck operations. For example, loading a barge requires 9-18 hr. As a result, loading and discharging cargo are full-shift operations (6-hr) for deck personnel and short-term tasks for truck drivers. To account for this difference and permit comparison of marine and truck exposures, an annualized , W A for a 2000-hr annual work period (8hr per day,5days per week and 50 work weeks per year) was calculated. It was assumed that while marine personnel are onboard I they are exposed to background vapor concentrations, even off duty. The 1978-1985 annualized TWA for 2000 hr for deck -pas_onnel handling gasolineranged from 2to 35ppm THC for l o a n g with open-hatchventing of vapors. The lowest TWA was observed for barge operationswith longvoyages and the highest for those with short voyages and frequent loading. These levels of exposure are comparable to those seen for drivers during 1975-1985. Exposures for deck personnel on barges with remote venting of vapors during loading and cargo discharging were low, averaging 2 ppm in the few samples available. Historical exposures in barge operations before 1978 were judged to be the same as those measured for barges with open-hatch venting. The work practices and equip- ment had not changed in any significant manner that would affect exposures. One company had used barges with remoteventing since the 1940%and its deck personnel were assigned the low value observed in the samples. Other shipboardjob groupwas assigned 1ppm, which was the background level for all barge operations. Due to the limited exposure data for seagoing operations, quantitative exposures could not be e s w However, deck personnel have potential for high vapa exposures on tankers transporting gasoline that open-hatchventing during loadingand discharging ca%o These workers also have potential exposures to a v a i of other materials that have been routinelytransportedb tankers, such as crude oil and intermediate refinery plea- ucts. Consequently,their exposurehistories aremmcg plex than those of the truck or inland barge w o r k Dose Indices Cumulative Exposures. The cumulative exporrpre index was calculated for the truck and inland barge workers based on their personal job histories and assigned exposures for the generic jobs. It ranged 2 to 8000 ppm* year. Long-term drivers at small had the highest values; short-term workers in other-- nal jobs were lowest. Inland barge deck personnelhad to intermediate cumulativeexposures. The wide rangeand relatively large numbers of workers with high provided a suitable population for a reasonable test o f h association of gasoline exposure with cancer risk, under the assumption of a linear relationshipbetween ppm+year and risk. Lifetime Frequencg o f Peak Exposurea The liffrequency of peak exposures index should be useful epidemiologically for detecting cancer risk associated peak exposures above 500 ppm; however, because of& correlationbetween the frequencyof peaks and cumulative exposure, it may be difficult to distinguish their separ&e effects. Peak exposures were calculated for truck and inland barge workers. They ranged from 0 to 24,000 peak exposures greater than 500 ppm lasting 15-90 min. Drivers at small terminals had the highest long-term frequencies because of the high frequency of peaks during loading and small deliveries.Although the peak exposures of barge deck personnel during topping-off reach higher concentrations and last longer than those of drivers, t h y are less frequent because of the much lower loading frequencies for barges. Consequently,deck personnelhandling gasoline had generally lower lifetime frequencies of peak exposures than truck drivers. Seagoing Tanker Exposures. Because quantitativch exposures could not be estimated for seagoing tankers. 11 u-as not possible to calculate cumulative exposure or pt*:ih frequency for these workers.Years of work in deck pei-s~~fi ne1jobs on ships carrying gasoline was used as an inde\ (11 potential exposure. Before 1980, nearly all ships u d open-hatch venting, so no date criterion was used in thv index. Again, a wide range in years of potential e.Qo~l~*~. was found (0-30 years), and there was a large p u p w t h many years of potential exposure. This also should proyide a suitable test of the possible associationwith cancer ri8k. Limitations and Uncertainties eThe few exposure data forlow-exposurejobs and tic seagoing tanker operations, and the limited a v a t y of data (only 1975-1985) were major limitations of EXPOSURE OF GASOLINE WORKERS - - 21 shdy. To deal with these limitations, an extrapolation approach was developed. There were many sources of uncertainty in the quantitative extrapolation. The largest uncertainties are in the lowest exposure estimates. Although the absolute magnitude of the extrapolated past exposures is imprecise, there were large differences in exposure across thejob groups, and the relative ranking of these exposures is well supported by the assessment of potential contactwith emission sources and tasks associated with eachjob group. Loader ex-posureswere very uncertain, but this was a small group with little influence on the epidemiologic analysis. Overall, it was unlikely that the uncertainty in the past exposure estimates would obscure the apparent differences in dose indices or job groups. This project was funded by the American Petroleum Institute. The authors gratefully acknowledgethe extensive contributions of the American Petroleum Institute's OH-38D Task Force and the specificcontributions of Norman Zeiser, Wayne Skocypec, Jerry Ransdell, Terri Colangelo, Stephen Killiany, Jr., James Branham, Jr., and Dr. Melvin First. We especially acknowledge the contributions of Robert Diakun, who passed amyay during the project; he gave unselfishly of his extensive knowledge and expertise, and we miss his warmth and generosity. REFERENCES 1.Smith, T.J, Hallock, M, and Hammond, S. K. Retrospective exposure assessment for epidemiology: vapor exposures of gasoline transport workers. 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Evaluation of Four Air Sampling Methods Used for Monitoring Worker Exposure to Gasoline Vapors. iAPI project No. IH-34-BI, American Petroleum Institute, Wash ington, DC, 1984. 8. OPA, Ontario Petroleum Association. Hydrocarbon exposure study a petroleum bulk terminals and ageneies in Ontario. Ontario Petroleum Association, Ontario, Canada, 1988,pp. 1-70.