Yoram Cohen universiry of California, os Angeles Los Angeles, calif: 9oM4 Pollutants released to the environment are distributed across environmental media (the atmosphere, soil,and water) and among biota as the result of cornplex physical, chemical, and biological processes. The potential hazards of these pollutants depnd on the degree. of exposure of human and ecological receptors to these chemicals and the health effects associated with such exposures (pipure 1). To assess these threats, it is necessary to understand 638 Envimn. Sci. Technol.. Vol. 20, No. 6. 1986
how pollutants tend to behave in varimedia. Interest in the nature of environmental pollution in different media is gaining momentum. Detailed experimental evaluation of the effect of each pollutant on all environmental media, however, is almost impossible because of the large number of known and potential pollutants. Mathematical models of the fate and transport of pollutants in a multimedia environment are attractive because they offer a relatively rapid and inexpensive way to assess potential environmental hazards during the early stages of chemical production or process development. Furthermore, in the
absence of monitoring data, mathematical models often provide the only means of predicting complex environmental events. Because multimedia monitoring studies are suuce, data required for model validation are lacking. Nonetheless, researchers continue to develop models that take into account cross-media aspects of environmental transport (1).
Models must be adaptable Environmental multimedia fate and transport models can be generic or site specific. The complexity of the model and its input and output data depend on the spatial and temporal scales of interest-the pollutant release scenario, the lifetime of the chemical (the length of time it persists in the environment), and the rates of environmental transport. Short-lived chemicals that are rapidly msformed into other chemicals or transferred to media adjacent to the area in which the release or emission has occurred may require the use of site-specific scales. This gives rise to the need for models that can predict short-term fluctuations in field concentrations. Long-lived or slowly transported chemicals require the modeling of long-range vansport and accumulation. On the basis of source characteristics and environmental transport and transformation processes, it may be more appropriate to predict either longterm average exposures or short-term fluctuations in exposures to specific targets or receptors. In either case, the model must be adapted to mimic the characteristicsof the problem. Numerous models of pollutant fate and transport incorporate various intermedia transport processes, but they emphasize single-medium transport (2,3). For example, models that deal with air pollutants neglect complex interactions with the water or soil compartments or phases. S i a r l y , transport models that are concerned with chemicals applied directly to soil focus on transport in the soil. And it is usually assumed that chemicals discharged directly into water bcdies are unlikely to cause significant global air pollution problems. Thus, volatilization and aerosol transport back to the atmosphere are commonly neglected.
A workshop on multimedia modeling P ~ l l b , , ~ds, , a multimedia problem was the subject of a workshop, "Pollutant Transport and Accumulation in a Multimedia Environment," held in Santa Monica, Calif., Jan. 21-24, 1986. The workshop was sponsored by the National Center for Intermedia Transport Research and the California Toxic Substances Research and Training Program. It was devoted to reviewing advances in the development and use of environmental multimedia fate and transport models and in the design and interpretation of experimental studies of multimedia pollutant partitioning. Three principal conclusions were drawn: First, no single model is useful for multimedia exposure and risk assessment. Simple cornpartmental models are merely the first step in conducting a multimedia exposure and risk analysis. Such models can be evaluated easily by means of standard sensitivity analysis techniques. Given the current state of knowledge of intermedia transport and transformation,it is unlikely that sophisticated spatial models will emerge as the standard in this field. It is more probable that classes of models with specific applications will emerge in the next several years. Second, the evaluation of multimedia risk will have to rely on realistic estimates of exposure. Current techniques for evaluating multimedia exposure treat the human body essentially as a sink for the various chemicals under consideration. New multimedia models that carefully consider fate and transport in the human body, analogous to methods used in pharmacokinetics, will have to be developed. Finally, although outdoor exposure has been the major area of concern for many years, it is now apparent that indoor pollution and its resulting exposure require thorough evaluation.The data base in this area is limited, and predictive methodologies are virtually nonexistent. More information in this field is essential for a comprehensive analysis of multimedia exposure and risk.
It is important to understand that the main force in any multimedia model is the source input of the chemical under consideration. Therefore, meaningful predictions require the identification and quantification of all sources of the chemical. The pertinent information for each source should include the total emission rate of the chemical to the particular environmental medium, the physical state of the chemical (dissolved, particulate, or gaseous), and the chemical's specific molecular form or speciation. These data are needed for all stages of introduction of the chemical into the environment, including losses during production, distribution, use, and disposal. Given the above information, transport equations for individual environmental media are formulated and coupled through the appropriate mathematical boundary conditions. Such boundary conditions, for example, may Modeling approach specify the mass flux or concentrations The global scheme for the multime- at the boundary between adjacent comdia modeling approach is shown in Fig- partments. The standard output from ure 1. The input variables include me- the model is in the form of transient concentration profiies for each of the dia properties, physicochemical and thermodynamic properties of the pollu- environmental compartments under tant under consideration, climatic con- consideration. The resulting concentraditions, and initial background concen- tion profiies, for example, can be coutrations. Intermedia transport and pled with exposure and risk assessment transformation processes are specified models (Figure 1). as well. The construction of a multimedia
model depends largely on the specific region under consideration and the judgment of the modeler. For example, the multimedia system shown in Figure 2 consists of three macrocompartments-atmosphere, water, and soil. These are further divided into a total of nine subcompartments, five of which are subdivided into a total of sixteen microcompartments to make a total of twenty compartments. An even larger number of compartments would result from the division of the sediment, saturated soil zone, and lower unsaturated soil zones into subcompartments. This compartmental system is by no means the most general one. It is apparent, however, from the large number of possible transport and transformation pathways, that even in a relatively simple compartmental system a great deal of information is required to describe pollutant transport across compartmental boundaries and to explain the various chemical transformations within the compartments themselves. But there is still a serious deficiency in our understanding of various intermedia transport processes (3-7). Multimedia models can be formulated with different degrees of detail with regard to both the model structure and the various physical and chemical processes. These models can be formulated as a collection of uniform (wellmixed) compartments, each of which represents a differentsector of the enviEnvimn. Sci. Twhnol.. MI. 20, No. 6. 1986 539
iental system
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ronment, as a detailed portrayal of temporal and spatial variations, or as a combmation of both characteristics. When a site-specific predictive capability is required, spatial models are neeswy. These call for the solution of complex, four-dimensional partial differential equations of spgce and time by appropriate numerical techniques. They also require a considerable amount of meteorological and hydm logical information. In contrast, the m lution of the well-mixed compartmental models requires only a modest amount of input data and the solution of time. dependent ordinary differential q u a .
tions (8-10). One of the main difficulties in multi . media transport modeling arises from the difference in time scales associated with the different intermedia transport processes. For example, the.time scale for the atmospheric compartment may be dictated by the intervals at which meteorologicaldata are available. S i . larly, the solution of the transport equa . tions for the aqueous and terntrial en. vironments may require time scales that are different from those of the atmospheric compartment. Because the atmospheric, aqueous, and terrestrial environmental compartments are connected with one another Y O Envimn. Sci. Technol.. Vol. 20, No. 6. 1986
.
Release of chemicals to the environment To the atmosphere Stack emission during manufacturingprocesses Fugitive volatilization from source including leaks, storage tank vent and waste disposal and treatmenl sites Losses during use and dispoenl To water Treatment of effluents at manufacturing and formulating plants Spills during manufacturingand distribution Losses during transportation Disposal after use
To soil
Direct applications of agricultural chemicals such as pesticides or fertilizers Land disposal for landfilling or cultivation operations Spills
through processes such as wet and dry deposition, volatilization, and resuspension, there may be an incompatibility of time scales that leads to instability in the solution of the equations. Consequently, it may be difficult to link individual compartmentsthrough all the intermedia l i i g e s . This problem may be overcome in part with models that are capable of stochastic generation of the required meteorological data (11).
Uniform compartmental system Models of uniform compamnental systems make use of well-mixed compartments to describe events in the various parts of the environment. The compartments correspond to environmental media, such as air, water, and soil, for example, or to abstract mathematical constructs designed for modeling convenience (12). Although spatial resolution is sacrificed somewhat in these models, quantitative estimates of the overall behavior of the system can be obtained. For example, the results from a uniform compartment model simulate the steady-state concentrations of trichloroethylene in the area of San Diego (10) and the relative distribution of benzo[u]pyrene in southeastern Ohio (13). These are presented in Tables 1 and 2, respectively.
Examples of compartmental models include site-generic equilibrium fugacity-type models (8, 1&16), the ADL models (13, the kinetic-type models ( I @ , and the GEOTOX model (19). These models lack detailed descriptions of intermedia transport processes and are restricted to nonparticulate pollutants. Nonetheless, they are attractive because of their simplicity and modest requirements for input data. The fugacity models, in particular, are useful for estimating the partitioning of gaseous and liquid pollutants in generic model environments (9).The modeler adjusts the sue of the air, water, soil, and biota compartments to mimic the global environment. These models consider the environmental compartments to be in equilibrium, or they may be formulated in terms of the transport of fugacity within or between compartments. The fugacity models, however, are cumbersome when pollutant transport occurs by processes that are not restricted by equilibrium driving forces (chemical potential or fugacity). For example, the removal from the atmosphere of organic pollutants that are primarily in the particulate phase is governed by physical processes, such as interception and impaction, that are not restricted by thermodynamic equilibrium processes. Therefore, in such cases there is no advantage in writing the transport equations in terms of fugacity rather than concentration. The fugacity approach breaks down when spatial transport equations must be used. They are needed when nonnniform compartments are present in the compartmental system and when convection as well as dispersion must be considered (10). Recently, a hybrid spatial-multimedia-compartmental (SMCM) model that uses well-mixed and nonuniform compartments was presented (10). The SMCM model describes spatial transport in the soil and sediment compartments by a one-dimensional time&pendent diffusion process. The air, water, suspended solids, and biota are approximated by uniform compartments. The resulting system of partial and o r d i i y differential equations is then solved simultaneously.
Spatial models Spatial multimedia models are designed to provide a one-, two-, or three-dimensional spatial resolution of pollutant concentration-time profdes. The models involve a series of coupled partial differential equations that must be solved numerically. Currently, there is a limited number of spatial models to deal with multimedia transport and transformation of organic pollutants.
1
Transport and transformation of organic pollutants
Atmosphere Transport from the atmosphere to land and water Dry deposition of particulate and gaseous pollutants Precipitation scavenging of gases and aerosols Adsorption onto particulate matter and subsequent wet and dry deposition Transport within the atmosphere Turbulent mixing and convection within the atmosphere Diffusion to the stratosphere Atmospheric transformation Photochemical degradation by direct absorption of light, by accepting energy from excited donor molecules, or by reacting with another chemical that has reached an excited state Oxidation by ozone Reaction with free radicals Reactions with other chemical contaminants
I
Water Transport from water to atmosphere, sediment, and organisms Volatilization Sorption by sediment and suspended solids Sedimentation and resuspension of solids Aerosol formation at the air-water interface Uptake and release by biota Transport within water bodies Turbulent dispersion and convection because of currents, wind shear, an( waves in the upper mixed layer Turbulent mixing and dispersion in confined flows (mixing and dispersion rivers) Diffusionbetween the upper mixed layer and the bottom layer Transformation Biodegradation Photochemical degradation Degradation by chemical processes such as hydrolysis and free-radical oxidation Soil
Transport from soil to water, sediment, atmosphere, or biota Solution in rainwater Adsorption onto soil particles and transport by runoff or wind erosion Volatilization from soil or vegetation Leaching into groundwater Resuspension of contaminated soil particles by wind Uptake by microorganisms, plants, and animals Transformations Biodegradation Photodegradation at plant and soil surfaces
The Tox-Screen multimedia screening model assumes a fixed geometry (20). Consequently, it is inadequate for forecasting pollution problems at specific sites. In the UTM-TOX model (Unified Transport Model for Toxic Materials) (21, 22) single-medium modules share information that serves to determine pollutant input from one medium to the next. The single-medium modules are not coupled through the physical boundary conditions at the soil-air and water-air interfaces. Consequently, there is no proper treatment of the mechanisms of transport from water and soil to the air.
Another multimedia model that involva the linkage of single-medium models is the ALWAS (Air, Land, Water Analysis System) (23). Unlike the UTM-TOX model, the ALWAS model uses uniform compartments to describe the aqueous medium. In the ALWAS computer model, the modules for air, land (runoff), and aquatic compartments are run independently with output from one module serving as input to the next. As in the UTM-TOX model, the modeling approach neglects feedback mechanisms such as volatilition from soil and water back to the atmosphere as well as the resuspension of Environ. Sci. Technol.. Vol. 20, No. 6, 1986 541
Environmental and predictedconcentrations of TCE,. nglm Llverpool
Air
Water (sea) Water (fresh)
104
3 x 104 3 x lW 6 x lo" 9 x lo" 6 x lo5
6.4 x 103
3 6
x 105 x W(maxp
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*TCE P trichloroethylene aThe reprted environmental wncenlrations are average values except far maximum concentrations denoted by ( m a ) Source: Reference IO. Reprintedwith permission tram ES&T Copyright 1985. American Chemical
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aerosol-bound organic pollutants. The spatial multimedia models described above provide a reasonable theoretical representation of the transport of contaminants in runoff, water streams, and sediment. Atmospheric transport also is reasonably well described, although the treatment of wet and dry deposition is approximate. Volatilization from water bodies, however, is described by inaccurate expressions that do not reflect the state of the art in modeliig ai-water mass transfer. Although these deficiencies can be corrected easily, several other deficiencies in the existing formulations of spatial multimedia models remain. The transport equations for the different ~ ~ the media are not C O M ~ C through physical boundary conditions; hence, the model equations are not solved simultaneously. The result is that generation of time-series data with such models requires a large number of computer operations. Existing multimedia models are inadequate for describing intermedia transport across the soil-air and unsaturated soil-saturated soil zones. This deficiency is attributable to the lack of a workable theory for multiphase transport through the multiphase soil matrix (24, 25). Therefore, existing models are incapable of providing a multimedia description of the pollutant migration that is associated with hazardous chemical waste sites. The soil environment is a multiphase system consisting of a solid phase, an organic phase, and an air or a water 542 Envlron. Sd. Technol., Vol. 20. No. 6. 1888
phase (Figure 3). A biotic phase is often present, and a water-immiscible contaminant phase may be present in the vicinity of hazardous waste sites. Pollutant transport in the soil matrix constitutes an unusual local multimedia transport problem, the understanding of which has advanced only minimally in recent years. There has been a great deal of study of contaminant migration associated with groundwater movement in the saturated zone (26-31). and this knowledge base is expanding (32). In contrast, an accurate theoretical formulation of multiphase pollutant transport in the multiphase unsaturated soil zone is still lacking (24.25). Many empirical treatments exist, but these usually require model calibration against laboratory or field data, which then casts doubts on the usefulness of the model as a rmly predictive tool. Existing models do not take into account the transport processes occurring in the soil-water, soil-air, and soil-solids compartments of the unsaturated soil zone or the detailed interaction of these compartments with the atmospheric phase above the soil or the underlying water table. Existing unsaturated soil zone transport models fail to consider mass transfer liitations associated with adsorp tion and desorption and with absorption and volatilization processes. Most of the models are approximate; they assume that equilibrium conditions prevail among the soil-air, soil-solids, soil-water, and soil-contaminant phases (33-37). Extreme temperature
and moisture gradients exist near the surface of the soil phase, yet none of the models consider the effect of their temporal variation. Therefore, current transport models for the unsaturated soil zone are inadequate for incorporation into a multimedia framework of contaminant transport.
Uncertaintiesmust be quantified Environmental models designed to assess the presence, distribution, and
effect of chemicals in the environment
are extremely complex problems involving numerous variables. Irrespective of the mathematical complexity of the model, the ability to forecast accurately can be achieved only through accurate description of physical, chemical, and biological intermedia and transformation processes. In particular, the use of multimedii models in risk assessment will require a quantitative evaluation of modeling uncertainties (38). These uncertainties arise from a combination of uncertainties in the values of model parameters and a lack of understanding of the physicochemical processes that govern pollutant transport and transformations. If multimedii models are to become useful in risk assessment, an effective methodology will have to be developed to quantify the effect of uncertainties. It is unlikely that a single comprehensive model could be developed in the near future to predict the transport, transformation, and accumulation of every toxic chemical that has been introduced or will be introduced into the environment. Although existing models are a step in the right direction, they are oversimplified and only approximate the treatment of intermedia transport processes. Available models consist of spatial models that link individual-medium modules or those that make use of wellmixed compartmental systems. Spatial models requirethe input of a considerable amount of meteorological and hydrological information, whereas the well-mixed compartmental models have only modest input requirements. Finally, the selection of a multimedia model for a particular application calls for a careful consideration of the required temporal and spatial scale, the complexity of the model in relation to available model input, interpretation of the model, and validation by laboratory and field measurements. Any theoretical or experimental multimedia program must first be used to consider the role of each environmental compartment in an overall multimedia scheme. Currently, such programs are in an embryonic stage. Despite the intensive effort d e v d to the development of new models, it appears that lit-
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tle attention has been given to their verification through laboratory and field studies. This deficiency stems principally from the lack of adequate multimedia monitoring data. The coordination and amplification of multimedia monitoring and modeling activities is most essential for progress toward assessing the environmental effect of emerging technology and hazardous waste treabnent and disposal practices.
Acknowledgment This work was supported in p a n by EPA Grant CR-807861-03. This article has been reviewed for suitability as a n ES&TfeaNre by Donald Mackay, University of Toronto, Toronto, Ont. M5S 1A4, Canada, Bruce Wiersma, Idaho Falls National Engineering Laboratory, Idaho Falls, Idaho 83415; and L. Tbibcdeaux, Louisiana State University, Baton Rouge, La. 70803.
References (1) Hill, A. A. “Report on Long-Term Envi-
ronmental Research and Development”; Council on Environmental Quality, Interagency Subcabinet Committee on LongTerm Environmental Research and Develop ment: Washington, D.C., 1985.
(2) Fare of Chemicals in the Environment; Swann, R. L.; Eschenroeder, A., Eds.; ACS Symposium Series 225; American Chemical Society: Washington, D.C., 1983. (3) Cohen, Y. In Conference on Gcochcmicol and Hydrologic Processes and Their Proteelion; Council on Environmental Quality: Washington, D.C., 1984. (4) Proceedings of the Workshop on Transporr and Fare of Toxic Chemicals in the Environment; Haque, R., Ed.; Office of Research and Development, EPA: Washington, D.C., 1978. (5) “Report of the Workshop on Research Needs in Intermedia Transport Processes”; Friedlander, K. E; Pmppacher H. R., Eds.; National Center for Intermedia Transport Research, University of California: Los Angeles, 1981. (6) Lyman, W. 1.; Reehl, W. E; Rosenblatt, D. H.Handbook of Chemical Properry Esrirnation Merhodr: Environmenral Behavior of Organic Compoundr; McGraw-Hill: New York, 1982. (7) Environmenral Risk Analysis for Chemicals; Conway, R.A., Ed.; Van Nostrand Reinhold New York, 1982. (8) Neely, W. B. Chemicals in the Environmenr; Marcel Dekker: New York, 1980. (9) Mackay, D.; Patenon, S.;Joy, M. In Fare of Chemicals in the Environmenr; Swann, R. L.; Eschenrceder, A,, Eds.; ACS Symposinm Series 225; American Chemical Society: Washington, D.C., 1983; pp. 175-96. (IO) Cohen. Y.; Ryan, P.A. Environ. Sci. Technol. 1985, 19,412.
(11) Onishi, Y.; Whelm, 0 . ; Skaggs, R.L.
“Development of a Multimedia Radionuclide Exposure Assessment Methodology for Low-Level Waste Management,” PNL3370 Battelle Pacific Northwest Laboratory: Richland, Wash., 1982. (12) Gillett, J. W. et al. “A Conceptual Model for the Movement of Pesticides through lhe Environment,” EPA-6OOl3-74.024. Ecological Research Series, EPA: Washington, D.C., 1974. (13) Ryan, P. A,; Cohen, Y. Chemosphere 1981,15, 21-47. (14) Mackay, D.; Paterson, S . Environ. Sci. Technol. 1981,15, 10613. (15) Mackay, D.; Paterson, S . Environ. Sei. Technol. 1982,16. 654-6OA. (16) Hedden, K. E J. Toxicol. Clin. Toxicol. 1984.21, 65-95. (17) Lyman, W. 1. “Prediction of Chemical Partitioning in the Environment: An Assessment of lbo Screening Models”; prepared under Contract 68-01-5949; EPA Washington, D.C., 1981. (18) Wiersma, 0. B. “Kinetics and Exoosure Commitment Analyses of Lead Bchavioor in a Biosphere Reserve,” Tcchnrcal Report. Montiorrng and As\ersmcnl Research Ccnler. Chelsea Collcec. Unwersm of London London, 1979. (19) McKone, T. E. “The Use of Environmental Health-Risk Analysis for Managing Toxic Substances.” UCRL-92329: Lawrence ~ ~ Livermore ‘National Laboraiory : Livermore, Calif., 1985. (20) McDowell-Boyer, L. M.;Hetrick, D. M. I
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Envim. Sci. Technol.,Val. 20. No. 6, 1986 543
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One-page reviews packed with data on the current economic status and short-term outlook for 46 largevolumechemical industry products. The 46 produas are:
“A Multimedia Screening-Level Model for Assessing the Potential Fate ofChemical Releases t o the Environment,” ORNLI TM8334; Oak Ridge National Laboratory: OakRidge, Tenn.. 1982. (21) Patterson, M. R. et al. A Userk Manual for UTM-TOX:A U+d Transpon Model. ORNL-6064; Oak Ridge National Laboratory: Oak Ridge, Tenn., 1984. (22) Browman, M. G.; Patterson, M. R.; Sworski, T J. “Formulation of the Physicochemical Processes in the ORNL Unified Transport Model for Toxicants (UTM-TOX) Interim Report,” ORNLITM-8013; Oak Ridge National Laboratory, Oak Ridge, Tenn., 1982. (23) ’hcker, W. A.; Eschenrceder, A. 0.;Magd, G. c. “Air, Land, Water Analysis System (ALWAS): A Multimedia Model for Assessing the Effect of Airborne Toxic Substances on Surface Quality,” first drafl report, prepared by Arthur D.Little for Environmental Research Laboratory, EPA: Athens, Ga., 1982. (24) Thibodeaux, L. J. Presented at CEQ Conference on Geochemical and Hydrologic Processes and Their Protection, September 1984. Council on Environmental Quality: Washington, D.C., 1984. (25) Bonazountas, M. In Fare of Chemicals in rhe Environmenr; Swann, R. L . ; Eschenrceder, A., Eds.; ACS Symposium Series 225, American Chemical Society: Washington, D.C., 1983; pp. 41-66. (26) McCarty, F! L.; Roberts, I! V.; Bouwer, E. 1. Water Forum 1981, 1, 606-15. (27) Enfield, C . 0 . et al. Ground Wnrer 1983, 20,711-22. (28) Pinder, G. F. Environ. Sci. Technoi. 1984,18, 108-14A. (29) lavandei, I.; Doughty, C.; Tsang, C-F. Groundwater Transport: Handbook of Mathematical Models,” EPA-MW)/1-84-051; EPA Washington, D.C., 1984. (30) Aribola, L. M.; Pinder, G. F. Worer Resou): Res. 1985,21, 11. (31) Aribola, L. M.; Pinder, 0. F. Warer ReSOUI: Res. 1985,21, 19. 544
Environ. Sci. Technol.. h i . 20,NO. 6, 1986
Acetone Nylon Acrylics Oxygen Ammonia Phenol Benzene Phenolica Butadiene Phosphoric acid Carbon black Phosphorus Carbon dioxide Polyester Caustic soda Polyesters Chlorine Polypropylene Cyclohexane Polystyrcnc DMTIPTA Polyvinyl Epoxies chloride Ethanol Potarh Ethylene Propylene (32) Mackay, D. M.; Roberts, F! V.; Cherry, Ethylene oxide Soda ash I. H. Environ. Sci. Technol. 1985, 19, 384. Formaldehyde Styrene (33) Bomberger, D. C. et al. I n Fore of ChemiHigh-density Sulfur cals in the Environment: Swann. R. L.: Eachenroeder, A,, Eds.: ACS Svmvosium Sepolyethylene Sulfuric acid ries 225; American Chemicd Society: Hydrogen Titanium dioxide Washington, D.C., 1983; pp. 197-214. Lime Toluene (34) Enfield. C. 0. “Chemical ’Ranroort Fa~~~~~~. r . ~ ~Low-density diiMCYanate dlitated by Multiphase Flow Systems”; polyethylene (IOU Robert Kerr Environmental Research L a b Methanol Urea ratory, EPA: Ada, Okla., 1984. Methylene Vinyl acetate (35) Jury, W. A.; Spencer, W. E ; Farmer, chloride Vinyl Chloride W. 1. 3. Environ. Qual. 1984, 13, 573. (36) Jury, W. A.; Spencer, W. E ; Farmer, Nitrogen pXylene W. I. 3. Environ. Qual. 1984, 13, 567. (37) Jury, W. A.; Spencer, W. E ; Farmer, 13. 580. W. 1. 3. Environ. Ounl. 1984. ~~. Chemical h Engineering Nnxr (38) Doniaian. A. ST Ir. In Fare of Chemicals Distribution Dept. in rhe &Environmenr; Swann, -R. L.; Es1155-16thSt.. N.W. chenroeder, A., Eds.; ACS Symposium seWashington, D.C. Po036 ries 225; American Chemical Society: Please send __copies Of Key Washington, D.C., 1983; pp. 153-74. Chmicals h Polymers (7th Edition) at $5 w Per copy ($4.00 per copy for orders of more than 10). On orders of $20or less Piease send payment With order. California residents add 6% $ales tax.
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Y o m Cohen received his B.A.Sc. and M.A. Sc. in chemical engineering from the University of Toronto, Canada. He received his Ph.D. from the University oj Delaware. He is on the chemical engineering faculty at the University of California, Los Angeles, where he is also a member oj the National Center for Intermedia Transport Research. Cohen has published man) articles on transport phenomena.
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