Annals of Occupational Hygiene Advance Access originally published online on May 17, 2004
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Ann. occup. Hyg., Vol. 48, No. 4, pp. 369-376, 2004
© 2004 British Occupational Hygiene Society
Published by Oxford University Press
Occupational Exposure to Diesel Exhaust Fumes
Institute of Occupational Health, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
Received 20 May 2003; in final form 23 October 2003; published online on 17 May 2004
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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There is currently no OEL for diesel fumes in the UK. This study reports parallel measurements of airborne levels of diesel fume pollutants in nine distribution depots where diesel powered fork-lift trucks (FLTs) were in use. Correlations between individual pollutants are assessed as well as their spatial distribution. Samples were collected on board FLTs and at background positions at nine distribution depots. Substances measured and the range of exposures by site were: respirable dust (n = 76) GM
80–179 µg/m3; elemental carbon (n = 79) GM = 7–55 µg/m3; organic carbon (n = 79) GM = 11–69 µg/m3; ultrafine particles (n = 17) range = 58–231 x 103 particles/cm3; selected particulate phase polycyclic aromatic hydrocarbons (PAHs) (n = 14) range = 6–37 ng/m3. In addition, a tracer method based on ultrafine particle measurements was used to estimate the spatial distribution of total carbon and PAHs at the sites monitored. The spatial distribution was found to be reasonably uniform. Major diesel fume aerosol components were, in general, well correlated (r = 0.62–0.97). CO2 measurements were also made and found to be below the HSE guideline of 1000 p.p.m., with most levels below 600 p.p.m.
Keywords: diesel exhaust fumes; elemental carbon; fork lift trucks; polycyclic aromatic hydrocarbons; ultrafine particles
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Diesel exhaust fumes are a complex mixture of particulate and gas phase pollutants. The highly respirable particles consist mainly of a carbonaceous core and adsorbed organic compounds. Gas phase components, particularly SO2, may subsequently undergo gas to particle reactions and form secondary particulate. The carbon core is defined as elemental carbon (EC) and adsorbed organics as organic carbon (OC). Total carbon (TC) is the sum of these fractions. The most important adsorbed organics are n-alkanes and polycyclic aromatic hydrocarbons (PAHs). Oxides of nitrogen in the exhaust gas may react with PAHs to form highly carcinogenic nitro-PAHs.
Major variables that influence emissions of particulate matter and PAHs from diesel engines are engine speed and load, air:fuel ratios, fuel density and aromatic content, agedness of lubricating oil, engine design [direct injection (DI) or indirect injection (IDI)] and maintenance status, particularly the condition of injection pumps and piston ring seals (Schuetzle and Frazier, 1986; Williams et al., 1989).
Much attention has been focused on particulate phase components of diesel fumes due to possible acute and chronic respiratory effects. The IARC have designated diesel exhaust fumes class 2A carcinogens, defined as ‘probably carcinogenic to humans’ (IARC, 1989). Some studies suggest that exposure is also associated with excess respiratory morbidity (Gamble et al., 1987; Purdham et al., 1987; Ulfvarson and Alexanderson, 1990; Jepson and Beach, 1993).
There is currently no OEL for diesel fumes in the UK. Current guidance from HSE is that adverse health effects are unlikely if exposure to CO2 from emissions is <1000 p.p.m. (HSE, 1999). In Germany, however, a limit of 100 µg/m3 EC applies, except where OC > EC, when the limit is 150 µg/m3 TC. The ratio EC:OC may therefore be significant in respect of compliance.
The main aims of this study were to determine: (i) parallel levels of pollutants for which occupational exposure limits or guidelines exist (i.e. respirable dust, EC, OC and CO2); (ii) levels of key unregulated pollutants (ultrafine particles and PAHs); (iii) correlations and regression models for measured individual pollutants; (iv) the spatial distribution of the pollutants of interest; (v) the role of operational factors in emissions and the relationship between pollutants, particularly in respect of EC/OC.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Work activities
Exposure to diesel fumes was measured in nine distribution depots engaged in the supply of drinks to the licensed trade. Diesel fork lift trucks (FLTs) were used to receive incoming stock and assemble orders. All FLTs were Lansing Linde model H300D-03, rated at 3000 kg, and entered service during 1997–1998. FLTs used red derv, a duty exempt diesel fuel with a colourant additive. Larger depots had an in-house engineer while smaller depots had access to a contract engineer as required. The number of workers present and the intensity of activity varied widely through a shift. Neither local exhaust ventilation (LEV) nor mechanically assisted dilution ventilation was present at any of the depots investigated.
Sampling was conducted between June and September, periods of relatively high activity. Smoking was not permitted at any depot and no sources of heating were in use, hence confounding sources of pollutants of interest were excluded as far as possible.
Respirable dust
Respirable dust was monitored according to MDHS14/3 (HSE, 2000). Filters (25 mm quartz fibre) (Whatman, Maidstone, UK) were pre-weighed on a Cahn 25 microbalance and loaded in Higgins and Dewell cyclones. These were connected to personal sampling pumps calibrated to a flow rate of 2.2 l/min before and after sampling using a rotameter. The rotameter was calibrated against a primary standard (Gilibrator 2; Gilian Instruments, Clearwater, FL). Filters were removed to clean cassettes after sampling and allowed to equilibriate at the laboratory prior to gravimetric analysis. Control filters, calculated as the mean plus two standard deviations, were used for baseline correction and to establish the limit of detection.
Elemental and organic carbon
After gravimetric determination of respirable dust, EC and OC were determined by two-stage thermal analysis with coulometric detection. This method is described in detail elsewhere (Groves and Cain, 2000).
Polycyclic aromatic hydrocarbons
Particulate phase PAHs were collected onto 70 mm diameter Teflon-coated glassfibre filters (Pallflex T60A20; Pallflex Corp., Putnam, CT) pre-extracted in HPLC grade dichloromethane. These were loaded into borosilicate glass filter holders with a fritted support. Total suspended particulate (TSP) was sampled at a flow rate of 20–25 l/min using a medium flow pump with dry gas meter (Universal Stack Sampler; Andersen Instruments, Atlanta, GA). Sample volumes ranged from 10 to 13 m3.
Filters were stored in a freezer prior to analysis. Desorption was performed by sonication in 2 cm3 dichloromethane for 2 h. The extracts were filtered and internal standards added (perylened12 and chrysened12). Extracts were then analysed by gas chromatography–mass spectrometry. The following PAHs were quantified: phenanthrene, fluoranthene, pyrene, benz[a]anthracene, chrysene, benzofluoranthenes (as the sum of the isomers), benzo[a]pyrene, indeno[123cd]pyrene and benzo[ghi]perylene.
Ultrafine particles
Ultrafine particles were measured using a P Trak condensation particle counter model 8525 (TSI, Shoreview, MN). An integral pump draws a sample through the instrument probe at a flow rate of 100 ml/min. Larger particles are removed by filtration and ultrafine particles grow by condensation in a saturated alcohol vapour. Particles in the range 0.02–1 µm are counted. Counts were integrated over a period of 1 min.
Carbon dioxide and carbon monoxide
CO2 was measured using long-term detector tubes (Drägar, Lübeck, Germany). These were operated using low flow sampling pumps calibrated using a bubble flow meter to 15–20 ml/min. Parallel measurements of CO2, together with carbon monoxide (CO), temperature and relative humidity, were taken using a Q Trak detector (TSI). This instrument uses a non-dispersive infrared cell (NDIR) to measure CO2 and CO.
Monitoring strategy
Samples were collected continuously over periods of 7–10 h as follows. At most depots parallel samples of CO2, EC, OC, PAHs and ultrafines were collected at a position referred to henceforth as the reference position. Depending on the layout of the depot, the reference position was close to the loading bay area where overall FLT activity was highest and where maximum levels of pollutants might be expected. In addition, parallel samples of EC, OC and CO2 were collected at a second position within the depot, mostly in the keg storage area, where FLTs were also in frequent use.
Samples of EC, OC and CO2 were also collected on board FLTs by attaching cyclones to the overhead crossbeam close (
30 cm) to the driver’s breathing zone. CO2 detector tubes were fixed close to the cyclones but outside the windscreen and were therefore not directly impacted by the driver’s exhaled breath.
Levels of ultrafine particles around each depot were mapped using an additional P Trak detector. Spot measurements were taken repeatedly over 2 min periods at 6–10 monitoring positions covering the area of the depot. The ratio of each spot measurement to the corresponding measurement at the reference position within the same time frame (30 min) was calculated in each case. This is denoted as Rspot/ref. TWA estimates at individual monitoring positions were calculated as the product of the mean value for Rspot/ref and the TWA ultrafine level at the reference position: estimated TWA concentration at the spot measurement position = Rspot/ref x TWAref.
The standard error was calculated as an estimate of the uncertainty associated with these estimates. The same equation was used to predict TC concentrations at the second sampling position by assuming that the ratio of TC at the second and reference positions was the same as the ratio of ultrafine particles. Here, Rspot/ref refers specifically to the second and the reference positions, respectively: predicted TWA TC at the second sampling position = Rspot/ref x TCref. The predicted values were then plotted against the measured value at the second position.
Statistical analysis was performed using Microsoft Excel 2000 and Minitab 13 (Minitab Inc.). In regression analysis, the distribution of residuals was checked by graphical means. Values below the limit of detection (LOD) were assigned a value equal to half the LOD.
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RESULTS |
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Results for respirable dust, EC, OC and CO2, expressed as geometric means (GMs), are shown in Table 1. All TWAs reported are for the sampling period of 7–10 h. EC was approximately log-normally distributed and the distribution of respirable dust, OC and TC was also slightly skewed. A few respirable dust results were clearly anomalous in that the blank corrected concentrations were less than the corresponding result for TC. A similar finding was reported by Groves and Cain (2000) and attributed to handling losses of fibres from the quartz fibre filters.
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The highest levels of EC and OC were recorded at depots 1, 2 and 7. These depots suffered from a combination of intensive FLT usage and architecture which impeded natural ventilation. In addition, lorries were loaded internally at depot 1. The majority of FLT samples (88%) at these depots were >50% of the corresponding German limit, although only one exceeded the limit (depot 1, EC = 117.9 µg/m3). GMs for EC in FLT samples were
10–70% higher than the background levels at most locations except depots 5 and 6, where FLT and background levels were similar. GMs for respirable dust ranged from <80 to 179 µg/m3. Several samples were below the limit of detection of 80 µg/m3. GM CO2 levels ranged from 436 to 535 p.p.m. The highest level measured was 828 p.p.m. (depot 2), with all but two results <600 p.p.m., considerably below the HSE guideline of 1000 p.p.m. CO2 measurements using long-term detector tubes were marginally, but consistently, higher than parallel NDIR results. CO levels ranged from mostly not detected to 1–2 p.p.m., consistent with previous reports (Purdham et al., 1987; Ulfvarson and Alexanderson, 1990).
Results for PAHs and ultrafines at the reference positions are shown in Table 2. Concentrations of the particulate phase PAHs measured ranged from 6.2 to 34.7 ng/m3. The lower end of this range is approaching the expected urban summertime background for the UK (Smith and Harrison, 1996) and was found in a depot with little FLT activity. The mean ratio of PAHs to TC was 0.035% (range 0.016–0.044%). Despite differences in experimental methods, these values are comparable to similar ratios derived from source sampling of a current technology heavy goods vehicle (HGV) of 0.056% (range 0.036–0.074%) at 1600 r.p.m. and 0.039% (range 0.034–0.049%) at 2600 r.p.m. (Shi et al., 2000). A slightly more extensive suite of PAHs was measured in this study, accounting for the marginally higher ratios reported.
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Ultrafine levels also varied widely, with a maximum of 2.3 x 105 particles/cm3 (depot 7). Wide temporal variation in ultrafine levels was apparent, with peak concentrations of 4–5 x 105 particles/cm3 over the integration period of 1 min. It is also noted that off-scale (>5 x 105 particles/cm3) transient exposure peaks sometimes occurred when the monitoring position was directly impacted by the plume from a passing FLT. These peaks were generally of less than 1 min duration.
The highest value for respirable dust (278 µg/m) had an anomalously low corresponding EC value. Eliminating this point and restricting the data set to a respirable dust limit of 250 µg/m3, correlation coefficients for the substances measured were calculated. These are shown in Table 3. Most substances were reasonably well correlated (r = 0.62–0.97, P < 0.05 for all particulate phase components). EC and OC were highly correlated in FLT and static samples (Fig. 1, r = 0.88–0.91). The slopes are similar, although there is a suggestion that OC is slightly enriched in FLT samples. PAHs were unexpectedly highly correlated with both respirable dust (r = 0.90) and carbon fractions (r = 0.93).
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The spatial distribution of ultrafines was measured and the ultrafine tracer measurements were used to predict TC at the second sampling position as described above. A reasonable correlation between measured and predicted values was found. This is shown in Fig. 2 (r = 0.80). This method therefore provides, within limits, a useful estimate of the spatial distribution of TC and an indication of the extent to which values measured at a selected position(s) are representative of exposures across the workplace.
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Given the strong correlation between ultrafines and PAHs, the use of this method for estimation of PAHs should be of comparable accuracy to its use for TC. Predicted mean TWA levels of TC and PAHs, together with the corresponding range of TWAs expected within each depot, are shown in Table 4. Mean concentrations of ultrafines at four depots were in the range 180–192 x 103 particles/cm3. The range of predicted daily TWA levels suggests that ultrafine TWA values at points within five depots were in excess of 200 x 103 particles/cm3. It should be noted that these estimates do not represent actual TWA personal exposures but predicted concentrations at defined locations.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Comparison of exposure levels with other studies
Comparisons of exposure levels between studies is problematical due to differences in sampling and analytical methods (e.g. Zaebst et al., 1991; Hammond et al., 1993). The EC and OC fractions are essentially a function of the thermal programme employed. Recent UK exposure data have been reported by Groves and Cain (2000) (these data were analysed using the method employed in this study). The highest TC exposures were found at workplaces where FLTs were used (GM = 104–509 µg/m3), generally higher than the FLT data in this study (GM
113 µg/m3). Similarly, respirable dust exposures for FLT workplaces (GM = 248–873 µg/m3) and the ‘overall personal exposure value’ for CO2 (650 p.p.m.) were also higher than the FLT data presented here (GM = 104 µg/m3 and 509 p.p.m., respectively). It is therefore apparent that relatively high levels of exposure to pollutants can occur in workplaces where FLTs are used, although there is considerable variation between sites. In contrast to the data reported here, Groves and Cain found that respirable dust, EC, OC and TC were poorly correlated. This inconsistency may be partly due to differences in sampling methods. It is noted that the data reported here for particulate matter were collected using a flow rate of 2.2 l/min (HSE, 2000), in conformance with the revised CEN protocol (BSI, 1993). This lowers the cut points for the collection of fractions within the respirable range. While this may have introduced some bias in respirable dust measurements, collection of diesel fume carbon fractions should be unaffected given the particle size distribution of diesel fumes. However, the fact that levels of both particulate phase pollutants and CO2 were elevated in the data reported by Groves and Cain suggests that there were indeed real differences in the level of fumes and these inconsistencies were not merely a sampling artefact. We have also recorded higher levels elsewhere (see discussion below). Nevertheless, respirable dust levels collected using a flow rate of 1.9 l/min may have been elevated to some extent by the collection of some relatively coarse, extraneous particulate. The revised method should make gravimetric measurements somewhat more selective in respect of diesel fumes and may partly account for the correlations between respirable dust and other pollutants reported here.
Another reason for the high correlation of pollutants reported here may be the unusual homogeneity applying in this study, principally the use of identical vehicles and similar premises, maintenance regimes and activities.
Models for exposure to unregulated pollutants
Given the correlation coefficients reported in Table 3, multiple regression was used to determine whether it was possible to use regulated pollutants (respirable dust and CO2) and other relevant parameters (temperature and relative humidity) to predict levels of unregulated pollutants. A combination of respirable dust and CO2 provided an improved model for TC (r = 0.77, respirable dust P < 0.0005, CO2 P = 0.012). This is plotted in Fig. 3. Given that CO2 production by exhalation was considered minimal, excess CO2 (i.e. above background levels for the location) is a volumetric measure of fuel consumption and is therefore directly relevant to pollutant concentrations. It is stressed that this model may not be applicable in other circumstances, for reasons discussed above, and it is not intended for more general use without prior confirmation through collection of experimental data.
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Operational factors influencing TC/EC/OC
Differences in EC:OC ratios by depot suggest that site-specific operational factors may be a factor in the partitioning of particulate carbon. Management at depot 2 were actively engaged in an effort to reduce emissions from idling FLTs. Consequently, the number of FLTs in use at a given time was capped. The EC:OC ratio at this depot was the highest of any depot (n = 12, mean ± SD = 1.01 ± 0.12). Conversely, considerable engine idling, particularly from unattended vehicles, was observed at depot 7, where the EC:OC ratio was the lowest observed (n = 8, mean ± SD = 0.63 ± 0.08). Corresponding values for other depots ranged from 0.64 to 0.99. This suggests that low EC:OC ratios (high OC values) arise from idling, probably due to inefficient combustion of fuel.
The relationship between the EC:OC ratio and TC for data from this study and also for measurements made previously in a HGV repair workshop and a bus garage (Institute of Occuational Health, unpublished data) are shown in Fig. 4. With a single exception, EC:OC ratios from the present study were in the range 0.3–1.2 (Fig. 4a).
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Generally, higher levels of TC were found in the other workplaces, with two samples in the bus garage in excess of 1000 µg/m3 (Fig. 4b). It is noticeable that the lowest TC results in Fig. 4b correspond to EC:OC ratios in the same range as the FLT data (i.e. 0.3–1.2). These were recorded in the main area of the HGV workshop where exhaust mounted LEV units were used and consequently engine idling or revving contributed little to airborne pollutant levels. In contrast, values of EC:OC > 1.2 were recorded for samples in an adjacent area where there was no LEV and hard revving was performed during smoke tests.
Samples from the bus garage, where no LEV was in use, were collected either during periods of peak or moderate activity. Excessive idling during start-up and repairs contributed heavily to pollutant levels. With one exception, all samples had very high OC content (EC:OC < 0.4). The single sample with EC:OC > 1.5 was recorded for a mechanic working in the exhaust plume of a vehicle while it was being revved to diagnose a fault. This finding is consistent with the smoke test data for the HGV workshop.
Reports in the literature suggest that EC:OC ratios appear to increase with revs and decrease with idling (Yamaki et al., 1986; Groves and Cain, 2000). The EC:OC ratios for both hard revving of stationary vehicles and excessive idling in Fig. 4b, together with the above discussion of the FLT data, are consistent with these findings. In summary, high TC levels appear to be associated with a perturbance of the EC:OC ratio, the magnitude and direction of which may serve as a diagnostic tool in respect of vehicle and operational variables.
Exposure to ultrafine particles
Currently there are conflicting reports concerning the significance of ultrafine particles in the aetiology of respiratory morbidity in non-occupationally exposed groups (Peters et al., 1997; Osunsanya et al., 2001). We are unaware of other reports of occupational exposure to ultrafines from diesel exhaust emissions, although levels of ultrafines occurring in metal and associated industries (fettling, welding and soldering), also measured with a P Trak detector, have been reported (Wake et al., 2002). These range widely from 100 to >500 x 103 particles/cm3. Measured and predicted exposures from diesel FLTs reported here are mostly within, or slightly below, this range. However, these comparisons are highly dependent on operational factors: where the use of diesel powered vehicles is more continuous and more intensive than was found in this study, higher pollutant levels will occur, as indicated by other data for EC and OC cited above.
Although there is no regulatory definition of ultrafine particle size, the range measured using the P Trak (0.02–1.0 µm) is larger than the consensus definition of <0.1 µm. Measures of particle number reported in this study span the nucleation and accumulation modes and are likely to underestimate particle number at the lower end of the ultrafine range and overestimate at the upper end relative to levels reported elsewhere. However, the most meaningful definition remains uncertain. In practice, however, the significance of these differences is likely to be limited in respect of exposure to diesel fumes. The particle number in freshly generated fumes is concentrated predominantly in the 0.02–0.1 µm range (Shi et al., 2000) but is likely to shift upwards in the workplace context due to particle agglomeration; median diameters of EC- and PAH-containing particles collected in a road tunnel in California were 0.11–0.15 and 0.06–0.26 µm, respectively (Venkataraman and Friedlander, 1994). Hence, the sampling efficiency of the P Trak with respect to particle size appears to be appropriate.
Acknowledgements—The authors would like to thank Mr Dave Dabill and colleagues at HSL Sheffield for their analytical work.
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FOOTNOTES |
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* Author to whom correspondence should be addressed. E-mail: s.sadhra{at}bham.ac.uk
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