A quantitative method for estimating dermal benzene absorption from benzene-containing hydrocarbon liquids.

This study examines a method for estimating the dermal absorption of benzene contained in hydrocarbon liquids that contact the skin. This method applies to crude oil, gasoline, organic solvents, penetrants, and oils. The flux of benzene through occluded skin as a function of the percent vol/vol benzene in the liquid is derived by fitting a curve to experimental data; the function is supralinear at benzene concentrations < or = 5% vol/vol. When a liquid other than pure benzene is on nonoccluded skin, benzene may preferentially evaporate from the liquid, which thereby decreases the benzene flux. We present a time-averaging method here for estimating the reduced dermal flux during evaporation. Example calculations are presented for benzene at 2% vol/vol in gasoline, and for benzene at 0.1% vol/vol in a less volatile liquid. We also discuss other factors affecting dermal absorption.

Predicting benzene vapor concentrations with a near field/far field model.

Published data on benzene vapor concentrations in work simulation settings were used to examine the predictive ability of a near field/far field vapor dispersion model with an exponentially decreasing vapor emission rate. A given simulation involved two 15-min periods of applying a known volume of benzene-containing liquid to equipment on a worktable in a room with a measured air exchange rate. Replicate personal breathing zone (15-min time-weighted average, TWA) and room area (1-hr TWA) air samples were collected. In our modeling, the benzene vapor concentration in the near field zone (at the worktable) represented the personal breathing zone exposure level, and the benzene vapor concentration in the far field zone represented the room area concentration. Across 10 simulation combinations of two factors (the mass of benzene applied and the room air exchange rate), the mean of the personal breathing zone exposure levels ranged from 0.2 to 9.9 mg m(-3), and the mean of the room area concentrations ranged from 0.05 to 5.05 mg m(-3). Our model provided reasonably accurate estimates of the measured benzene vapor concentrations. Linear regression of the mean measured personal breathing zone exposure versus the predicted near field concentration yielded slope = 0.93 and r(2) = 0.94; the null hypothesis that the true slope equals one was not rejected (p-value = 0.39). Linear regression of the mean measured room area concentration versus the predicted far field concentration yielded slope = 0.90 and r(2) = 0.94; the null hypothesis that the true slope equals one was not rejected (p-value = 0.20). Other statistical tests showed no significant differences between measured and predicted values. In addition, most predicted concentrations fell within an approximate range of one-half to twofold the respective measured concentrations.

Estimating benzene exposure at a solvent parts washer.

A mathematical model is described for estimating benzene exposure at a parts washer using petroleum distillates solvent containing benzene. The basic assumptions are that the benzene mass emission rate exponentially decreases over time, and that the air above the parts washer basin to which a worker is exposed is part of a well-mixed air zone termed the near field (relative to the source location). Two previously conducted simulations of the parts washer process are described. A single 1-hour time-weighted average (TWA) benzene concentration was measured during Simulation #1, and two 4-hour TWA benzene concentrations were measured during Simulation #2. The initial benzene concentrations in the solvents were known, and the exponential loss rate constants were estimated from subsequent determinations of the benzene concentrations. Values for the interzonal airflow rate were estimated based on the conceptual geometry of the near field zone and sparse information on air speed near the parts washers. Minimum values for the room supply/exhaust air rate were estimated based on the room volumes and ventilation conditions. The modeled benzene concentrations were within a multiplicative range of one-half to twofold the measured concentrations. Uncertainty in a model estimate was quantified by Monte Carlo analysis; the distributions of model estimates exhibited coefficients of variation of approximately 40%. Issues related to uncertainty in exposure estimates made by mathematical modeling are discussed.

Estimating methyl bromide exposure due to offgassing from fumigated commodities.

Methyl bromide (MB) is used to fumigate diverse commodities. During fumigation, the commodity can sorb a substantial mass of MB, which does not chemically react and is termed a residue. During subsequent commodity handling, the residue offgasses and can lead to MB inhalation exposure among processing workers. Although MB has a low 1 ppm 8-hr TLV-TWA as recommended by the American Conference of Governmental Industrial Hygienists (ACGIH(R)) and is considered a potential occupational carcinogen by the National Institute for Occupational Safety and Health, the recent industrial hygiene literature contains no pertinent exposure data. Limited measurements made in 1992 by the California Department of Pesticide Regulation are summarized here, but associated information on exposure determinants is lacking. In this article, mathematical models are used to integrate data on MB residue offgassing with several processing scenarios to estimate potential exposure levels. The main finding is that if a large volume of commodity rapidly offgasses MB and is handled under conditions of low ventilation, the potential exists for MB exposures above the 1 ppm TLV-TWA value. However, the combination of handling a smaller commodity volume and less rapid offgassing may be the more typical scenario. It is recommended that a pilot study be conducted to measure current MB exposure levels, test the validity of the mathematical models, and collect industry-wide data on exposure determinants. By using the latter data as inputs for validated models, public health scientists could estimate the distribution of MB exposure levels across the commodity processing industry.