Wayne R. Ott W c e of Research and Development Environmental Proteoreaion Agency Whinaton, D. C. 20460 A newly emerging research field in the environmental sciences provides data on total human exposure to environmental pollutants. Instead of focusing purely on the sources of pollution or their transport and movement through the environment, this research focuses on humans as the receptors of these pollutants; people and their daily activities become the center of attention. This research addresses the qnestions of whether the population is exposed to chemicals, and, if so, how many persons are exposed and to what degree. The methodology measures pollutant concentrations found at human physical boundaries, regardless of whether the 880 Envimn. Sci.Technol..MI. 19. No. 10. 1985
pollutants arrive through the air, water, food, or skin. Its purpose is to characterize quantitatively the effect of pollution on humans by determining whether an environmental problem exists at the human interface and, if so, to determine its sources, nature, extent, and severity (The human interface is a threedimensional surface enclosing the person, including the skin, lungs, and other organs.) Determining the risk posed by environmental pollution to public health requires a knowledge of five fundamental components: the soums of pollutants, the transport of pollutants from sources to humans, the exposures of humans to pollutants, the doses received by those who are exposed, and the adverse health effects resulting from the doses.
These components may be viewed as links in the chain-from source to effect-that makes up the full risk model (pipure 1). Although each component is important in determining the public health risk associated with environmental pollution, our scientific knowledge a b u t them is not b a l a n d . Usually, environmental pollution comes to the attention of public of& cials because sources such as smoke stack plumes or leaking toxic waste drums provide obvious evidence of chemical releases into the environment. This has led to an overemphasis on the outdoor source component of the model; the consequence is that there is extensive understanding of outdoor s o u ~ c eabatement and control but little knowledge about the other kinds of
sources. Once a source of environmental pollution is identified, interest often shifts to the manner in which the pollutant This article not subjsn UI US. copyright. Published 1985 American Chemical Sociely
FIGURE 1
Components of a Conceptual risk model
I-
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moves through the environment-its fate and transport-until it is ultimately assimilated by ecosystems or reaches humans. As with the source component of this conceptual risk model, the fate and transport component has received extensive research attention. The study of meteorology has led to development of a number of atmospheric dispersion models, and other fields have developed models for the movement of pollutants through streams, soil, and the food chain (1,2). As with the first two components of the model, the fifth component-the effects of pollutants on humans-has received considerable research attention. Numerous studies have related various exposures and doses to identifiable effects on animals and humans, as can be seen in any of the published air quality criteria documents (3-5).However, our knowledge of two important components of the risk model-exposure and dose-is rudimentary for most pollutants of concern. The environmental risk model is serial in structure: The output of each component serves as input to the next. Thus, the absence of valid information on any component seriously impairs our ability to make accurate assessments of public health risk, and the absence of valid human exposure data has serious adverse implications for regulatory policies designed to protect public health. As our knowledge about three components of the risk model-sources, fate and transport, and effects-has increased as a result of formal research programs in these areas, the need for valid data on exposures and doses has become more critical. More than a dozen government research reports and technical papers have been written over the past decade proposing schemes for calculating population exposures to air pollution (6). These methods are imperfect because they rely on the limited data available from fixed air monitoring stations and they produce estimates of “potential exposures” with unknown accuracy. Until the 1980s, we possessed few accurate field data on the actual exposures of the population to important environmental pollutants. Virtually noth-
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r
fer. How are the exposure profiles for the population of an entire city to be characterized? From a public health standpoint, interest must focus on the frequency distribution of exposures to the entire population. To illustrate this concept using an air pollutant for which a National Ambient Air Quality Standard (NAAQS) exists, such as carbon monoxide (CO), imagine a city of 200,000 residents. The running 8-h average CO exposure is of particular interest, because EPA’s NAAQS of 9 ppm for 8 h is designed to protect public health. If the 24-h exposure profile on a given date were known for every person, we could calculate each person’s maximum 8-h running average CO exposure. If we then plomd the resulting values on a histogram in which the vertical bars denote the number of persons Defining exposure falling into selected concentration interBefore discussing the recent progress vals, it might resemble a bell-shaped made toward solving these problems, it curve (Figure 2). The area under this is necessary to arrive at a uniform defi- curve, to the right of the 9-ppm nition of exposure to avoid confusion. NAAQS, represents the city’s populaA recent paper used statisticians’ termi- tion that is exposed to more than 9 ppm nology to define exposure as the event COin8h. The cumulative frequency distribuduring which a person comes into contact with a pollutant (6). That is, if the tion (Figure 2) is derived from the hispollutant concentration is a random togram (top curve) by adding the provariable C, then we say that a person is portions from left to right. For this exposed to concentration C = c of that example, 58% of the population of the pollutant at a particular instant of time city was below the NAAQS on this when the pollutant and the person are date. The result allows a precise statepresent at the same location. Then, an ment about the level of protection afforded by the standard: On this date, exposure becomes the intersection, or joint occurrence, of two events: the the probability that any person’s 8-h person is present, and the concentration maximum exposure exceeded the 8-h standard was Q = 1 - 0.58 = 0.42. c i s present. It is clear that a protection probability In general, a pollutant is transported by some carrier medium (air, water, or of P = 1 - Q = 0.58 does not seem food). If we represent the physical very high. As a public policy decision, boundary of the person as an envelope the goal might be a probability of P = (e.g., the skin and surface membranes 0.95, P = 0.99, or 0.999 as the desired of the lung), then a dose occurs only if level of protection. A level of protecthe pollutant actually crosses the enve- tion of P = 0.999 corresponds to the lope; exposure occurs merely if the pol- probability of one person’s exposure lutant comes into contact with the enve- exceeding the NAAQS on a given date lope. Consequently, there can be an of Q = 1 - P = 0.001, or 1 in 1ooO. Note that such an approach is less exposure without a dose, but there canconcerned with the exposures of a parnot be a dose without exposure. The record of a person’s exposure as ticular identifiable person than it is with a function of time throughout the day is the representative exposure distribution called an exposure profile. Because of the population as a whole. Despite daily activities differ from one person the importance of such an exposure freto the next, exposure profiles also dif- quency distribution, until recently we
ing was known about the variation in exposure to a given pollutant from one person to another, the reasons for these variations, or the differences in the exposures of subpopulations of a given area. Furthermore, a variety of field studies undertaken in the 1970s and early 1980s showed that the concentration experienced by those engaged in various activities (driving, walking on sidewalks, shopping in stores, working in buildings) did not correlate well with the simultaneous readings observed using existing monitoring networks (& 22). Finally, no scientifically defensible, uniform methodology was available for predicting future exposures of a population or for estimating how population exposures might change in response to different regulatory actions.
Environ. SCi.Technol., Vol. 18. No. 10, 1985 881
FIGURE 2
Hypothetical frequency distribution of Eh maximum CO exposures.
Bh Maximum CO exposure. c (ppm)
Cumulative frequencydilnrlbution of expoa
O
0
L 1 -
~
~
. 6 7 8
910111213141516171819X)21~224
8.h Maximum CO exposure, c (ppm) .Ulb*" pOpviatiDn Of 2 m . mp e r m s On B PB'IiCYlW m e
a.m. .Measured with a personal exposure monitor June 28. 1979
882 Envimn. Sci.Tednol., vol. 19. No. 10, 1985
Time
had little information about the actual exposures of the population to most of the pollutants of concern in the environment. Recent progress has been made in providing this information. As described by Duan, two basic approaches exist for developing a frequency distribution of exposures of a population (23). The first, or direct, a p proach is to measure the 24-h exposure profiles of a large sample of persons statistically chosen to allow extrapolation of the results to the entire population. The other, indirect, method calculates exposure profiles by combining information on the time spent in particular activities with the concentrations associated with those activities. EPA's research program on total human exposure has employed both approaches.
Direct approach This method seeks to measure a person's exposures directly by measuring concentrations of a given pollutant in the air breathed, the water drunk, and the food eaten. To characterize a population's exposures, it is necessary to monitor a relatively large number of persons and to select them in a manner that is statistically representative of the larger population. This approach marries the survey de-
p.m.
sign techniques of the social scientist to the latest measurement technology of the chemist and engineer, combining both statistical survey methodology and environmental monitoring in one field survey. The same survey research methods have been used for many years to determine public opinions and attitudes. For the air exposure route, this method uses miniaturized personal exp u r e monitors (PEMs), which have become available over the past decade (24-26). Major field survey programs have been conducted by EPA to test and develop this new methodology for two pollutants, carbon monoxide (CO) and volatile organic compounds (VoCs). Carbon monoxide. CO was selected as one pollutant for demonstrating this new monitoring methodology because much is known about its sources and health effects: NAAQS have been promulgated for CO, a continuous PEM for CO is available, and human activity exposure d m models have been developed for calculating human CO exposures and blood carboxyhemoglobin profiles. Because CO’s only route of exposure is by air, it is not necess.lIy to monitor its presence in food or drinking water. On June 28,1979, an EPA employee was asked to carry one of the newly developed CO PEMs (Energetics Science Model 9ooo Ecolyzer) to work on the following day and to maintain a log of her activities to see whether the PEM could generate a CO exposure profile (27). She Lived in Manassas, Va., some 30 miles from EPA’s buildings in Southwest Washington, D.C. Before she left her home at 606 a.m. her CO exposure was negligible, but it began to increase as she entered her normal highway commuting pattern (Figure 3). The CO exposures she experienced along the Washington area’s large freeways (I-395 and 1495) soon exceeded 9 ppm, and her exposure in EPA’s garage reached 27 ppm, although it lasted only a few minutes. Once she was inside the office, which is free of
smokers, her exposure dropped to about 2 ppm, and remained fairly constant with time. Her return commute showed a pattern similar to her morning commute, in reverse order. The highest exposure, 50 ppm, occurred inside the EPA garage; levels in traffic ranged from 10 ppm to 20 ppm. We later found this CO exposure profde to be fairly typical. It shows the importanct of one’s activities (driving on a highway, walking in a garage) in contributing to exposures. This profile suggests two questions: How do profiles differ from person to person? what proportion of the population experiences a profde in which the 8-h exposure exceeds 9 ppm? In 1980, a pilot field study was undertaken by Ziskind, Fite, and Mage under an EPA contract to determine further the feasibility of using several different miniaturized PEMs to measure 24-h CO exposure pmfdes of nine persons for about 45 days each (2s). Although the study demonstrated the validity of this technique, improvements were needed in the data-logging capability of the PEMs because these continuous instruments generated too with much data for reswndents to CODY _. a pen on paper. A soeciallv desimed PEM was develop&, bas& on h e General Electric carbon monoxide detector (model 15ECS3CO3). It contained a built-in data logger that could record and store CO concentrations with a time resolution of 1 min or less (29). In the winter of 1982-83, EPA conducted large-scale urban field studies using these PEMs to measure the CO exposures of the populations of Denver, Colo., and Washmgton, D.C. (30-37). A multistage sampling design was used in which a random sample of the population was telephoned (approximately 3200 households in Denver and 5800 households in Washington) and asked about their smoking habits, commuting times, and other factors. This telephone questionnaire enabled a strat-
ified sample to be assembled that included nonsmokers and a disproportionate number of persons who commute long distances and have other characteristics of importance (such as homes with gas appliances) for their CO exposure. Each person selected in the final sample was visited at home by an interviewer who left a calibrated PEM and instructions for its use, along with a diary. The diary approach was patterned after the time budget studies of Szalai (38). During the following day, the respondents carried their PEMs as they went about their normal daily activities, depressing a data-logging button on the PEM each time they changed activities. A questionnaire was administered to obtain information about each respondent’s home, workplace, and commuting habits. From these data, it was possible to construct CO exposure profdes for each person in the sample. It also was possible to determine the CO concentrations present in hundreds of locations. The survey design for both cities a p pears in a report by Whitmore, Jones, and Rosenzweig (31). Details of the survey’s design are presented in the contractor’s final reports (32,33).Field studies have demonstrated the effectiveness of a large-scale, statistically designed field survey of CO exposures using the direct approach with PEMs. Their findings are summarized in shorter papers by Johnson (359, Hartwell et al. ( 3 9 , Wallace et al. (36), and Akland et al. (37). Vohtlle organic compounds.--The other program to develop and apply this new exposure measurement methodology in the field deals with organic compounds. Those organics that ordinarily form vapors, the VOCs, include many carcinogens and mutagens. From 1980 to 1984, the Total Exposure Assessment Methodology (TEAM) program was under wav in eieht cities in the US. (Table 1): As in the CO exposure field studies, 1
Envimn. Sci. Technol., MI. 19. No. 10, 1985 883
a statistically designed representative random sample of the population was selected. The largest TEAM surveys were conducted in two New Jersey cities: Bayonne, where 1788 persons participated in an initial screening survey, and Elizabeth, where 2638 persons participated in the survey. The data from the survey permitted selection of a smaller target population with appropriate characteristics with regard to possible VOC exposure (persons living close to major industries or in special occupational categories). This two-stage sampling process reduces the final target population to a manageable size, and the findings can still be generalized to the entire population of the city. The final sample consisted of a total of 355 residents for Bayonne and Elizabeth combined. Because VOC exposure can occur through routes other than exposure to air, the survey included measurement of drinking water and breath levels of VOCs. Initially, food also was included. Each person participating in the survey was given a diary and a specially designed, miniaturized pump connected to a six-inch Tenax cartridge, which were to be carried throughout the day. The cartridge and pump operate for 12 h and collect a great variety of organic compounds that can be analyzed by gas chromatography-mass spectrometry (GS/MS). Several hundred compounds can be identified and about 50 can be quantified; the TEAM study concentrated on about 20 target compounds. VOCs on the breath of respondents were measured by having each person breathe into a specially designed spirometer. The contents of the spirometer were then analyzed by GUMS. Although the large data base collected in these field surveys is still being ana-
lyzed, these data are leading to many discoveries about actual human exposures of the population through all environmental media (air, food, and drinking-water pathways; breath as a measure of body burden). Wallace et al. describe the measurement technique and the findings from initial pilot studies in Chapel Hill, N.C., and Beaumont, Tex. (39).and Zweidinger et al. present the data in greater detail (40). Initial analyses of the TEAM data from New Jersey appear in a paper by Wallace et al. (44,and the data are presented in greater detail in a contractor’s report by Pellizzari et al. (42) and in papers by Pellizzari et al. (43), Hartwell et al. (44),and Wallace et al. (45,46). Because the VOC personal monitor was indoors during evening hours, and a similar monitor was operated outdoors, it is possible to compare indoor and outdoor air quality levels. An important finding of the TEAM study is that levels of 11 important organic compounds, some of which are regarded as potential carcinogens, were found to be significantly higher indoors than outdoors. These chemicals included chloroform, 1,1, l-trichloroethane, benzene, carbon tetrachloride, trichloroethylene, tetrachloroethylene, styrene, metu- and paru-dichlorobenzene, ethylbenzene, and zylene isomers. The sources appear to be inside the home, probably in furniture, paint, solvents, drapes, carpets, spray cans, clothing, and construction materials. Additional exposure-monitoring studies are needed to determine their exact nature. Indirect approach Rather than measuring the exposure profile directly, the indirect approach seeks to construct the exposure profile
mathematically by combining information on the times people spend in particular locations (homes, automobiles, and offices) with the concentrations expected to occur there. This requires a mathematical model, information on human activity patterns, and statistical information on the concentrations likely to occur in selected locations, or microenvironments. Fugas was the first to compute air pollution exposures by considering both the concentration at different locations in a day and the movement of p e e ple to these locations (47).Lead, manganese, and sulfur dioxide were measured in Zagreb, Yugoslavia, in 1972-73 at several official air-monitoring stations and in several streets during business hours, indoors close to streets, and in the countryside. Fugas calculated the weighted weekly exposures by estimating the time city dwellers spent in five locations-at home, at work, in two streets, and in the countryside. Although intended only as an example, Fugas’s approach is the same as that used in most exposure models developed subsequently (46).Hone and Eldon, who proposed the same concept independently, call it component monitoring (48).Duan has developed this approach formally in mathematical expressions of the combination of microenvironmental concentrations and time spent in them (23). In its simplest form, the problem is to compute the integrated exposure as the sum of the individual products of the concentrations encountered by a person in a microenvironment and the time the person spends there. The integrated exposure permits computation of the average exposure for any averaging period by dividing the integrated exposure by the duration of the averaging period. If the concentration within microenvironmentj is assumed to be constant during the period that person i occupies microenvironment j, then the integrated exposure E, for person i will be the sum of the product of the concentration c, in each microenvironment, and the time spent by person i in that microenvironment will be as follows: J
E, =
E
cjto
i= I
~
884 Envimn. Sci. Technol., MI. 19, No. 10, 1985
where E, is the integrated exposure of person i over the time period of interest, cj is the concentration experienced in microenvironment j , to is the time spent by person i in microenvironment j, and J is the total number of microenvironments occupied by person i over the time period of interest. To compute the integrated exposure E, for person i, it obviously is necessary to estimate both cj and t+ If T is the averaging time, the average expo-
sure Ej of person g s obtained by dividing by T: that is, Ej = Ej/T Several models and computer programs have been developed that are based conceptually on the above equation (45-51). Moschandreas and Morse computed exposures to ozone by considering the mobility patterns of six subgroups of the population: house wives, ofice.workers, industrial workers, outdoor workers, elderly and infum persons, and students (49). A computer program called the NAAQS Exposure Model (NEM) generates the hour-by-hour movements of representative population groups through the districts of a city and through selected microenvironments within each district, accumulating the resulting CO exposure over a year (50). Another computer model, called Simulation of Human Air Pollution Exposures (SHAPE), uses Monte Carlo simulation techniques to combine data on activity patterns of the population with statistical descripions of concentrations of pollutants in specific microenvironments (51). Monte Carlo techniques use a computer to generate variables with known statistical properties that are under the control of the modeler The variables then are combined using equations, and the computer generates a frequency distibution of the predictedvariable of interest. SHAPE uses 14 microenvironments, and exposures are computed on a person-by-person basis with a time resolution of 1 min. The resulting 24-h exposure profile is then computed for each person, and the program stores the maximum hourly exposure, the maximum 8-h exposure, and the highest hourly blood carboxyhemoglobin level for each person. From these profdes, SHAPE generates a frequency distribution of the exposures of a population. Although the SHAPE and NEM models are now in operation, they need more development and should be validated with real data to represent expo-
sure microenvironments more realistically. Models similar to SHAPE can be constructed for N Q , respirable suspended particulates (RSP), and other pollutants. Such models provide a great deal of information about the exposure process and are useful in developing field survey protocols. A timeweighted model for RSP has been constructed by Sexton, Spengler, and k i t man (52). Field data similar to those reported for CO and VOCs have been reported showing important differences between indoor and outdoor RSP concentrations (53-55).
Better risk estimates ?\Ho complementary approaches for determining the frequency distribution of exposures of a population to environmental pollution have been developed. The first directly measures a statistically representative cross section of the population; the second constructs each person's exposure profile by combining information on human activities with microenvironmental field data. Early evidence suggests that the direct approach is well suited to answering the question of whether there is actually an environmental exposure problem resulting from a given pollutant. Thus, when limited exposure data are available on a pollutant, this a p proach may be the best one to choose. The indirect approach requires investigators to model each microenvironment a person visits, so it requires a greater knowledge of the concentrations prevailing in these microenvironments and in the microenvironments of importance. For each pollutant, the microenvironments differ. For CO, typical microenvironments are buses, automobiles, parking garages, sidewalks, houses with gas stoves, and ofices with smokers. For VOCs, typical microenvironments are gas stations, dry cleaning stores, freshly painted rooms, and households with solvents stored indoors. The direct approach should be used fmt to determine whether an ex-
posure problem exists for a given pollutant. If it does, then the indirect method can be used to characterize the sources in the microenvironment responsible for the problem. The data obtained from the total human exposure field studies have many uses. Because they ffl an important gap in the public health risk model (Figure l), they greatly improve the accuracy of our estimates of the risk to human health posed by environmental pollutants. For air pollutants, such exposure information enables us to assess the margin of safety incorporated into the NAAQS more accurately than has ever before been possible. Also,by comparing exposure data with measurements from conventid monitoring stations, it is now possible to evaluate the adequacy of existing monitoring networks in terms of actual human exposures. These comparisons may help us to develop improved criteria for siting airmonitoring stations. The total human exposure methodology has important implications for the emerging field of indoor air quality research In a single field study, it becomes possible to characterize indoor, outdoor, and in-transit contributions to total exposures, which in turn leads to discovery of pviously unknown indoor sources. For example, the TEAM study has revealed surprisingly high indoor exposures to a number of important organic compounds, apparently as a result of materials found in common household furnishings and other items. From these studies, we also may discover a variety of new procedures for reducing exposures. For example, removing solvents from homes is one a p proach that may be relatively inexpensive and easy to implement. Exposure studies also can help us to understand the influence of human activities, lifestvles, . and occuoations on uollutant exposures. F d v . the data from these studies can be I&to develop and validate new exposure models such as SHAPE and ~~~
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Environ. SCI. Technol., &I. 19, NO.IO. 1985 885
NEM. Using such models, it may be possible to estimate the effect of different regulatory strategies on exposures and even to project exposure distributions in urban areas under study or in urban areas where limited data are available. Studies of total human exposure and the techniques evolving from them provide a powerful new methodology for filling basic gaps in the environmental risk model. The findings from these studies help us characterize the sources, nature, and extent of environmental problems with an accuracy never before attainable, and such information is essential for formulating intelligent and effective regulatory programs. In 1985, EPA is adapting the total human exposure methodology to the pesticides problem and is conducting a TEAM study of human exposures to pesticides. As measurement techniques improve, the total human exposure methodology can be applied to other pollutants, such as NO2, particulates. RSP, trace metals, pesticides, and semivolatile organic compounds. In addition, the methodology for CO and VOCs can be applied easily to other locations to compare the results obtained elsewhere with the data already collected.
Acknowledgment Before publication, this article was reviewed for suitability as an ES&T feature by John D. Spengler. Harvard University, School of F’uhlic Health, Boston. Mass. 02115; Ken Sexton, Health Effects Institute, Cambridge. Mass. 02142; and Paul 1. Lioy, New York Medical Center, Institute of Environmental Medicine, New York.
N.Y. 10016.
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