Ecological Modelling 47 (1989) 115-130 115 Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands

EXPOSURE AND ECOTOXICITY ESTIMATION FOR ENVIRONMENTAL CHEMICALS (E4CHEM): APPLICATION OF FATE MODELS FOR SURFACE WATER AND SOIL

M. MATTHIES, R. BRUGGEMANN, B. MUNZER, G. SCHERNEWSKI and S. TRAPP

Gesellschaft ]'fir Strahlen- und Umweltforschung Miinchen, Projektgruppe Umweltgefiihrdungspotentiale yon Chemikalien, Ingolstiidter Landstrasse 1, D-8042 Neuherberg (Federal Republic of Germany)

ABSTRACT

Matthies, M., Briiggemann, R., Miinzer, B., Schernewski, G. and Trapp, S., 1989. Exposure and ecotoxicity estimation for environmental chemicals (E4CHEM): application of fate models for surface water and soil. Ecol. Modelling, 47: 115-130.

The E4CHEM (Exposure and Ecotoxicity Estimation for Environmental CHEMicals) model system was developed for exposure and hazard assessment of environmental chemicals. Two E4CHEM fate models, EXWAT and EXSOL, for surface waters and soil, respectively, are tested and validated by comparing experimental with calculated results.

The concentrations of a volatile compound (tetrachloroethene) in the river Main can be predicted by EXWAT, taking into account the average consumption values along the river and an empirically derived proportionality factor for the release rate (0.6% for tetrachloroethene). A sensitivity analysis shows the dominance of volatilisation over dilution.

The transport and fate of the herbicide, 2,4,5-trichlorophenoxyacetic acid, are simulated for four German soils under various climatic conditions. Downward movement is underesti- mated by laboratory sorption measurements. Sorption coefficients derived from field trials have lower values and lower variabilities than those from laboratory sorption studies.

INTRODUCTION

Monitoring studies and recent findings from various countries show that many of the chemicals of different structure classes have been observed in various environmental media, i.e. air, water, soil, or biological materials. Once released into the environment, chemicals can enter almost all environ- mental compartments. However, for most chemicals released into the en- vironment only fragmentary knowledge exists about their environmental exposure which is, beside the toxicity and ecotoxicity assessment, the other part of the hazard-assessment process.

0304-3800/89/$03.50 © 1989 Elsevier Science Publishers B.V.

M. M A T T H I E S ET AL. 116

T A B L E 1

Characteristics and major input data categories for E4CHEM exposure models

Model Characteristics Input data categories

RLTEC release rates from manufacturing, production quantities, use pat tern, processing, uses and disposal of dispersivity, pathways to the environ- chemicals ment

EXAIR analytical box model for atmospheric physico-chemical data, meteorologi- transport cal statistics, deposition rates

steady-state compartment model for physico-chemical data, hydrological transport and fate in surface waters characteristics, meteorological data

multi-layer soil model for transport physico-chemical data, soil character- and fate in the unsaturated soil zone istics, climatological data

thermodynamic equilibria between volumes, interfaces, densities, physi- air, water and soil co-chemical data

model to combine results from RLTEC, see RLTEX, EXAIR, EXWAT, and EXSOL EXAIR, EXWAT, and EXSOL

compartment model for global atmo- spheric dispersion

EXWAT

EXSOL

EXTND

EXINT

EXATM tropospheric/stratospheric transfer rates, photodegradation

The E4CHEM (Exposure and Ecotoxicity Estimation for Environmental CHEMicals) model system is developed for the exposure and hazard assess- ment of environmental chemicals (Rohleder et al., 1986). E4CHEM comprises a set of combined models and methods which are briefly characterised in Table 1. One model, RLTEC, is a source-assessment model and estimates the release rate and the release medium. The six environmental fate models EXAIR, EXWAT, EXSOL, EXTND, EXINT, a n d EXATM are e n v i r o n m e n t a l -

medium-related models, mainly compartment models with intramedium transport and intermedia transfer processing (Matthies et al., 1986). For the ranking, comparison and selection of chemicals from a substance list, descriptors are defined and statistically evaluated (Rohleder et al., 1986; Halfon and Bri~ggemann, 1989).

E4CHEM has been developed on a Siemens BS2000 mainframe. The microcomputer version allows a wider distribution of the program with a minimum of implementation efforts. The current version uses only those DOS features accessible from standard Fortran, such as support of ANSII control sequences, access to line printer and console via file-names and an ASCII output option as a link to other programs (Lotus, Minitab, etc.).

The menus can be customised for special applications. The advanced user, however, will appreciate the full flexibility of the E4CHEM command lan- guage.

EXPOSURE AND ECOTOXICITY ESTIMATION FOR ENVIRONMENTAL CHEMICALS 117

An important part of the modelling process is the testing and validation by comparing experimental with calculated results in order to obtain confi- dence in model calculations. The limits of applicability of laboratory data for field situations and the sensitivity of model processes and parameters should be known. As an example of application of E4Cr[EM two fate models will be presented and discussed: the surface-water fate model EXWAT is applied to the fate of the chloro-organic compound, tetrachloroethene, in the river Main, and the soil fate model EXSOL is applied to the transport and fate of a herbicide, 2,4,5-trichlorophenoxyacetic acid (2,4,5-T), in different Ger- man soils.

The main purpose of the paper is to show how well predictions for environmental exposure can be made if only a limited set of substance parameters is available.

E N V I R O N M E N T A L F A T E M O D E L S E X W A T A N D E X S O L

EXWAT. The model EXWAT (EXposure of surface WATer bodies) (Briigge- mann and Miinzer, 1987) was developed for the characterisation of the chemicals' fate in surface water bodies with emphasis on comparative aspects for which steady-state conditions are considered. EXWAT is a box model with two compartments per box (Fig. 1): fluid and sediment. The following processes are considered: deposition and resuspension of sus- pended matter; partitioning of chemicals between water and suspended matter in the fluid and between pore water and benthic sediment solids; ionisation equilibrium; exchange between pore and fluid water as driven by dispersion; sediment burial; volatilisation; degradation; bioconcentration. The approach is similar to Mackay's model QWASI (Mackay et al., 1983a,

VOLATILITY

FLUID

SUSPENDED W~ FLO__WIX~ MATTER WATER FLO WATER

/

DEGRADATION N'T I I--:-

SEDIMENT BURIAL

Fig. 1. EXWAT model s t ruc ture and cons idered processes .

118 M. MA'VI'HIES ET AL.

b). The relations are described by two mass-balance equations which are explicitly solved analytically and which lead to steady-state concentrations (Briiggemann and Miinzer, 1987; Briiggemann and Trapp, 1988). By linking a number of (not necessarily identical) boxes, a concentration profile along the river can be estimated.

There are some limitations to be considered: the conditions of steady state have to be fulfilled and the transient behavior cannot be studied; stratified lakes or ponds are not considered; sedimentation and resuspension are modelled, taking into account a mass-balance concept for the suspended matter and particles of the benthic sediments, respectively; the influence of temperature is neglected; the fate of transformation products is not consid- ered. The deposition of pollutants from air to water is not considered in EXWAT, but is estimated by the model EXINT which integrates the air, soil, and water models.

EXSOL. The EXSOL model (Matthies et al., 1987) is a one-dimensional vertical dynamic multi-layer model and considers the following processes within the unsaturated soil zone (Fig. 2): advection with pore water flow; hydrody- namic dispersion; partitioning between soil water and soil air; sorption on organic matter; ionisation equilibrium; gaseous diffusion in soil air; vola- tilisation; biotic and abiotic degradation; root uptake. Up to ten horizons with 77 sub-layers can be defined. The transport in soil layers of variable thickness after continuous, intermittent or single initial deposition, applica- tion, or contamination can be studied. The water flow is estimated by a

DEPOSITED OR APPLI ED SUBSTANCE VOLATILITY

LAYER I SORBED ~ ,'DISSOLVED',,- ",-fiASEOUS SO~L

LAYER 2

T T ¥

LAYER 3

. . . . . . . _ . t _ T L - _ _ , . . . . .

I ' IN GAS I . . . . . . ' . . . . . . ~ . . . . . . I'~PLANT UPTAKE I t

I DIFFUSION f I

L~ERN ~

LEACHING D~FFUSION

Fig. 2. EXSOL model structure and considered processes.

E X P O S U R E A N D ECOTOXICITY ESTIMATION FOR E N V I R O N M E N T A L C H E M I C A L S 119

simple water-balance approach taking into account averaged or time-depen- dent data for precipitation, evapotranspiration, and surface runoff. A numerical solution of the differential equations is applied using a predictor-corrector method. The limitations of the method relate to the simplifications in describing the complex interactions in the soil environ- ment. The current version does not consider single rain or storm events, transient water flow, remobilisation of bound residues, root distribution, or non-equilibrium adsorption.

RESULTS AND DISCUSSION

Application of EXWAT to the transport and fate of tetrachloroethene in the river Main

The transport and fate of organics in rivers are determined by the interactions of physical, chemical and hydrological processes and by climatic influences. The river Main in Central Europe, which has a length of about 500 km, is taken as an example. Some towns and cities are located along a 310-km section of the river with a multitude of industrial activities and releases from municipal waste-water treatment plants. The geographical situation is shown in Fig. 3.

Field studies concerning volatile chemicals have been done during Oc- tober 1982 (Hellmann, 1984). Here, the chemical tetrachloroethene is used as an example. The following questions arise: - Is the input into the river related to the consumption of the chemical? Is it

possible to estimate one proportionality factor R between annual con- sumption values and input rates?

- What are the main factors influencing the concentrations? To simulate the transport of tetrachloroethene in the river Main, eight different segments were introduced according to the varying hydrological properties of the river (Bayerisches Landesamt fiir Wasserwirtschaft, 1985).

Fig. 3. Map of the river Main krn 67-385; A-E , urban-industrial areas; 1-9, locations of measurements October 1982 (Hellmann, 1984)

120 M . M A T T H I E S ET A L .

10004 r//,,I ~ 800

600

400

o 200

O ~

I I ~ ~ ~ ~ 3 ,o o ~/- /X / / / / / /

400 O

300 c .9

200 E

c 0

-100 o

Fig. 4. Annual and averaged daily consumption of tetrachloroethene in the catchment area of the river Main (Atri, 1985).

The general results of EXWAT are described as follows:

c(x)=f(Co, RI(x)) where C o is the concentration of tetrachloroethene which is transported to the first considered segment of the river Main. I(x) is the discrete function of the usage of tetrachloroethene at the segment x and is shown in Fig. 4.

The proportionality factor R, which is needed to calculate the release into the river at different sites, is estimated by fitting the calculated to the measured concentrations. Note that only one factor is used for all the different locations!

In Fig. 5 the measured concentrations are shown which may have some uncertainties due to site- and time-specific effects. The measured concentra-

b

2,

o

i 1 8 o

3 0 0 2 0 0

Kilometer of t he River 0 measured

Exwot - Conservative

100

Fig. 5. Measured and calculated concentrations of tetrachloroethene in the river Main.

EXPOSURE AND ECOTOXICITY ESTIMATION FOR ENVIRONMENTAL CHEMICALS 121

tions are rather well approximated by the calculated concentrations. There- fore it can be deduced: - One typical background concentration C O is consistent with EXWAT esti-

mations. - Only one value of R is necessary to describe satisfactorally the measured

concentration profile. The low value of R(0.6%) shows that only a minor part of the consumed

tetrachloroethene is emitted into the river Main. This may be a consequence of effective waste-water treatment and avoidance of emissions directly into the river.

In addition, Fig. 5 represents the results of a more simplified model which considers only the dilution (dotted curve) and which may be regarded as conservative. The same R-factor and the same background concentration C O are assumed as in the EXWAT model. Fig. 5 shows that the dilution model cannot explain the concentration profile by using only the fit-parameters R and C 0. One physical difference between the EXWAT model and the dilution model is volatilisation. It is therefore concluded that the main process which determines the fate of tetrachloroethene is volatilisation. This obviously can be deduced from the rather high Henry's Law coefficient (1.4 × 10 3 Pa m 3 mol-1). Nevertheless, it should be emphasized that the dilution along the river only had the factor 2 at the time of the measurements.

Sensitivity study

Volatilisation is modelled by the equation derived by Southworth (1979). The environmental data needed are average wind velocity, current velocity, and depth of the river. In Fig. 6 the results of a sensitivity study are shown. The following cases are considered: (A) The standard case. The depth of the river varies between 2.5 and 4 m.

Wind velocity is assumed to be zero (velocities smaller than 3.8 m s -1 have no influence).

(B) The depth is constant (3 m). The wind velocity is zero. (C) The depth varies exactly as in case (A), but the wind speed (at 10 m

height) is now 5 m s-1. The following results are obtained:

- A slight variation of depth (A) leads to no significant differences com- pared with the case of a constant average depth of 3 m (B). (A realistic assumption, because the river Main as a navigable waterway has a rather constant depth.)

- Curve C always shows smaller values than curves A and B, which certainly comes from the higher volatility at a higher wind speed (1.37 times the volatility of curve A).

122 M, M A T T H I E S ET AL.

5 '

._b 4. E

c)

~6 2, g o

c

3 g 0 c ) 300 200 100

Ki lometer of the River ¢' meosured

J curve A . curve [3 ~ / curve C

Fig. 6. Sensitivity study: (A) wind velocity 0 m s-l; river depth: 2.5-4 m; (B) wind velocity 0 m s-l; river depth: 3 m; (C) wind velocity 5 m s-l; river depth: 2.5-4 m.

- Comparing case (A) and (B): there are intersections between the curves due to different weight of volatilisation according to different depths.

Summary EXWAT

The application of the model EXWAT to tetrachloroethene has shown: - that releases into the river are related to the consumption in the catch-

ment area; - that simple dilution models describing the fate of volatile chemicals in the

river Main may not be adequate; - that volatilisation is the dominating fate process of tetrachloroethene and

similar chemicals in the river Main; - that for wind velocity and river depth, average values are sufficient; - that simple steady-state models can be useful tools to interpret measured

concentrations if the conditions of stationarity are fulfilled.

Application of EXSOL to the transport and fate of 2,4,5-T

The behavior of 2,4,5-trichlorophenoxyacetic acid was investigated in German soils with different properties and under different climatic condi- tions (Blume et al., 1983; Litz, 1985; Litz and Blume, 1985). The herbicide was applied in quantities of 1 and 10 g m -2 in June 1980 and of 2 g m -2 in December 1980, and the concentrations were measured at various soil depths after specific time intervals. Water movement was recorded for the winter studies by simultaneous determination of tritiated water movement. Laboratory studies on adsorpt ion/desorpt ion, percolation and degradation were carried out in order to predict the transport and fate from laboratory

EXPOSURE AND ECOTOXICITY ESTIMATION FOR ENVIRONMENTAL CHEMICALS

TABLE 2

Properties of different German soils (after Litz et al., 1987)

123

Soil Depth Density Field Corg pH Clay horizon a (cm) (g cm -3) capacity (%) (%) (CaC12) (%)

Luvisol (Pb) from boulder marl under arable land Ap 0-20 1.60 26 1.6 6.4 8 AI 20-65 1.65 19 0.18 6.5 5 Dystric Cambisol (Ro) from boulder sand under forest Aeh 0-15 1.05 28 9.6 3.3 3 Bv 15-50 1.65 20 1.6 4.0 2 Cambisol (RiBe) from boulder sand under waste water irrigation Ap 0-32 1.20 27 2.6 5.3 9 Bv 32-65 1.67 16 0.16 5.5 6 Gleysol (PaG1) from river sand forest Ah 0-20 0.85 31 2.4 5.0 2 Gor 20-80 1.06 4 0.11 6.5 2

a German nomenclature.

data. A detailed description of the applied experimental methods and a discussion of the obtained results are reported in Litz (1985).

The model EXSOL was used to simulate the transport and fate of 2,4,5-T under field conditions (Schernewski and Matthies, 1988). Concentrat ion profiles were calculated by using only the frequently available soil and climatic data. The results were compared with observed concentrations in various soil depths. Four soils (from 15 investigated soils) were selected, for which the most results were reported. The properties of the four selected soils are given in the Table 2.

The purpose of this s tudy is to evaluate the applicability and validity of the EXSOL model structure and parameters. The modelling goal is not the prediction of any specific situation but rather the representation of the general behavior of organics in soil for screening purposes. Furthermore, the use and limits of laboratory data for field predictions are tested and the variability of key parameters for transport and fate (water flow, sorption, and degradation) under field conditions is estimated.

Elimination

Chemicals can be eliminated from the soil by runoff (surface, interflow), leaching, root uptake, volatilisation, and degradation. The dominating pro- cess of 2,4,5-T elimination is aerobic microbial degradation (Rosenberg and Alexander, 1980; Litz, 1985). Litz (1985) measured the decomposi t ion of 2,4,5-T under aerobic and anaerobic conditions for 2 4 ° C and 5°C . The

124 M. MATTHIES ET AL.

TABLE 3

Degradation rate constants (d-1) for 2,4,5-T from laboratory measurements (after Litz, 1985) and elimination rate constants (d-1) from field observations assuming first-order kinetics

Soil Laboratory Field horizon a 24 ° C 5 ° C Summer Winter

Luvisol (Pb) Ap 0.016 0.001 0.038 0.017 Dystric Cambisol (Ro) Aeh 0.008 0.0007 0.016 0.003 Cambisol (RiBe) Ap 0.023 n.m. 0.045 0.007 Gleysol (PaG1) Ah 0.015 n.m. 0.043 0.005

a German nomenclature. n.m., not measured.

corresponding rate-constants for the dominating aerobic degradation are given in Table 3. From the remaining quantities of the applied 2,4,5-T in field after various time intervals 'elimination rate constants' can be esti- mated assuming first-order kinetics. Table 3 shows that the elimination-rate constants in the field are in general higher than the degradation rates measured in the laboratory for the upper horizon. The eliminated quantities vary with temperature, soil properties, and application amounts. The higher elimination observed in field experiments can be explained by the different methods used. In the field, the disappearance of 2,4,5-T over time was measured and not the 14CO2 evolution as in the laboratory experiments. Therefore, the primary degradation (plus the other elimination processes) were recorded in the field in contrast to the total decomposition of the parent compound in the laboratory test system.

Except in one case, surface runoff of 2,4,5-T could be neglected because of the field trial conditions. The uptake of 2,4,5-T by the roots of perennial ryegrass (Lolium perenne) was less than 1% of the applied quantity. EXSOL estimates the uptake in plants by concentration factors derived from various independent studies (Matthies et al., 1987). Taking into account the quanti- ties which moved into the root zone, the concentrations in plants were estimated for two soils with an accuracy between 5 and 30% (Schernewski and Matthies, 1988). Vapor losses due to volatilisation of 14C-compounds were observed up to 4% in summer and below 1% in winter. Because of the unknown chemical nature of the vapor losses, a comparison with model calculations is not possible. Lateral interflow and transversal dispersion further reduce the concentration in the soil subsurface. Simulation of these

E X P O S U R E A N D E C O T O X I C I T Y E S T I M A T I O N F O R E N V I R O N M E N T A L C H E M I C A L S 125

processes requires knowledge about the three-dimensional water and solute flow, which was not available for this study. Therefore, the elimination-rate constants are used for all soil depths.

Transport

The transport of solutes in soil depends on the water movement in the unsaturated zone. The average drainage-water rate can be calculated from the water balance. Neglecting the surface-water runoff and assuming only small changes of the water content, the pore-water velocity is determined from the difference between precipitation and evapotranspiration divided by the water content. Since the volumetric water content varies with the soil, depth and time, the water movement is not constant. This approach is applicable if the soil is normally wet and no drastic drying is observed. Precipitation was recorded weekly. Evapotranspiration is calculated by the equation of Thornthwaite (SchriSdter, 1985). Volumetric water constants are calculated from the texture, water content at field capacity, and water tension (Scheffer and Schachtschabel, 1984). The resulting drainage rates (daily averages) and the volumetric water contents (weekly averages) are

TABLE 4

Hydrological model parameters

Soil Summer 1980 Winter 1980/81

horizon" Drainage Volumetric Drainage Volumetric water b water content water c water content (mm d -1) (%) (mm d -x) (%)

Luvisol (Pb) Ap AI Dystric Cambisol (Ro) Aeh Bv Cambisol (RiBe) d Ap Bv Gleysol (PaG1) Ah Gor

2.6/2.2/0.0 32 /30/30 2.5/4.3 30/29 22 /22/22 22/22

12.1/6.3/0.0 17/24/21 3.9/3.2 39/30 15/15/15 29/29

5.6/27.4/0.0 21/21/21 3.4/5.9 47/45 16/16/16 16/16

2.9/3.4 50/50 60/60

a German nomenclature. b Values are given for 1, 2 and 4 weeks after application. c Values are given for 2 and 5 weeks after application. 0 Waste water irrigation included.

126 M. M A T r H I E S E T AL.

0 2

i

10

20 4:

30 - '

4 0

~ o ] ~

concentration of 2,4,5 - T (mg / I soil)

4 6 8 10 12 14 16

iuvisol (Pb) winter 1980/81

EXSOL EXSOL')

/ ~ field data

18

concentrat ion of 2,4,5 - T ( m g / I soil)

0 2 4 6 8 10 12 14 16 0 2 _ _ ~

lO

2 0 dystric camblsol (Ro) winter 1980/81

x~ 30 -

o ~ EXSOL EXSOL*)

4 0 field data

5O

concentration of 2,4,5 - T (mg / I soil)

0 2 4 6 8 10 12 14 16 0

1° I ~ 2 0 c a m b i s a l (RiBe) 1 winter 1980/81

-a 30 • ~ / / EXSOL

EXSOL') 40 / / field data

50

18

10-

20

"o 30

40

50

concentration of 2,4,5 - T ( m g / I soil)

2 4 6 8 10 12 14 16

gleysol (PaGI) winter 1980/81

J EXSOL EXSO~) field data

18

Fig. 7. Concentration of 2,4,5-T, 5 weeks after application in winter, comparison of measured and calculated depth profile, all data referring to 2-g m -2 application, field data from Litz (1985), *) averaged for horizontal layers.

given in Table 4 for the two upper horizons of the four investigated soils. The dispersion length (or longitudinal dispersivity) varies between 0.5 and 12 cm and is used as a fit parameter. (For a detailed discussion see Schernewski and Matthies, 1988).

Sorption plays a decisive role in the behavior of chemicals in soil and influences percolation, leaching, degradation, volatilisation, and plant up- take. Sorption is described by a linear equilibrium-distribution coefficient K d. The K d values are used to simulate the percolation of 2,4,5-T. Simulated K d values from field studies are compared with sorption constants from laboratory batch studies. Figures 7 and 8 show the results of model calcula- tions and the comparison with field trials for the four soils in winter and for two soils in summer. The curves represent the concentrations as a function of soil depth 4 weeks after application in summer and 5 weeks after application in winter. For the gleysol, field trials were carried out only in winter. For the luvisol, model calculations cannot be fitted to the experimen- tal results in summer. This is presumably due to the initial infiltration and percolation into deeper soil depths. Unfortunately, the tritium water studies were not successful in summer so that the water flow cannot be simulated.

EXPOSURE AND ECOTOXICITY ESTIMATION FOR ENVIRONMENTAL CHEMICALS 127

concentration of 2,4,5 - T (mg/ t soil)

2 4 6 8 10 12 14 16 18 0 ' ~ '

T 1 0 t r /

~u 20- dystric cambisol (Ro) .c summer 1980

"~ 30- • ~ / EXSOL

EXSOL') 40- .-~ field data

50

concentration of 2,4,5 - T (mg/ I soil)

0 2 4 6 8 10 12 14 16 18

10

20 combisol (RiBe) ~: summer 1980

50 1 I -t • ~ / EXSOL EXSOL')

4 0 ~ , ~ field data

5O

Fig. 8. Concentration of 2,4,5-T, 4 weeks after application in summer, comparison of measured and calculated depth profile, all data referring to 1 - g m -2 application, field data from Litz (1985), *) averaged for horizontal layers.

TABLE 5

Adsorption constants for the upper horizon from Freundlich's adsorption isotherms and K d values derived from field experiments

Soil Laboratory Field

horizon a Litz (1985) Welp (1987) Summer Winter WB b

W B b T H O c

Luvisol (Pb) Ap 1.18 0.84 n.a. 0.35 Dystric Cambisol (Ro) Aeh 68.5 41.7 2.10 2.03 Cambisol (RiBe) Ap 2.25 n.m. 1.23 0.98 Gleysol (PaGI) Ah 4.46 n.m. n.m. 1.97

0.24

2.23

n.a.

1.97

a German nomenclature. b Water flow from water balance approach. c Water flow from tritriated water movement. n.a., = not applicable. n.m., = not measured.

1 2 8 M. MATTHIES ET AL.

Table 5 summarizes the results of the percolation experiments and shows the comparison of sorption constants (K d) from the laboratory batch studies with those fitted to the field data. The general tendency to higher sorption values for soils with higher organic matter content is confirmed with the field studies. However, the K d values from field studies are, in general, lower than those measured in the laboratory. This is presumably due to the experimental conditions for the sorption test which favor sorption to soil surfaces. The 'field' Ko values are similar for the winter and summer field experiments. Furthermore, only minor differences are obtained when the water flow is calculated from the tritium water flow measurements, confirm- ing the applicability of the simple water balance approach.

Using sorption coefficients from batch experiments the downward move- ment of 2,4,5-T is underestimated for all investigated soils and both seasons. Furthermore, the variability of the 'field' K d values is lower than that from batch experiments. These findings indicate that the use of sorption coeffi- cients from laboratory experiments must be carefully evaluated in order to avoid misinterpretations.

CONCLUSIONS

The application of two fate models from the E4CHEM model system shows the validity and limits of predictions for the environmental behavior of chemicals. From the comparison of calculated with experimental results from field studies the applicability of laboratory data and the use limits of the generalised model approach can be elaborated. One of the major constraints for all E4CHEM models is the restricted availability of data. The models are therefore limited within their description of processes.

As partially pointed out in earlier sections the main limitations in EXWAT are: - The conditions of stationarity have to be fulfilled. This includes immis-

sion and hydrological properties. - Tributaries are not explicitly considered. - The underlying geometry of the boxes themselves and their linear se-

quence may be too simple, for example, if dead-zone areas have to be taken into account. Concerning the limitations of EXSOL, transient water-flux simulations

require a lot of meteorological, hydrological, and soil data. However, con- stant-flux models are appropriate for predicting solute transport through field soils with their inherent spatial variability in physical and chemical properties (Beese and Wierenga, 1980). The example of 2,4,5-T has shown the validity of the EXSOL structure for most of the studied soils. Deviations

E X P O S U R E A N D E C O T O X 1 C I T Y E S T I M A T I O N F O R E N V I R O N M E N T A L C H E M I C A L S 129

of p r ed i c t ed f r o m the obs e rved b e h a v i o r are m a i n l y due to the u n c e r t a i n t y of

e x t r a p o l a t i o n of l a b o r a t o r y d a t a to the field.

T h e exper ience ga ined wi th we l l -known chemica l s is useful for the assess-

m e n t of less s tud ied or new chemicals . E4CHEM m o d e l s the re fo re are sup-

p o r t e d b y rou t ines for e s t ima t ion of phys i co -chemica l subs t ance proper t i es .

F u r t h e r s tudies are in p rogress in o rde r to ob t a in con f idence in the genera l app l i cab i l i ty of the E4CHEM m o d e l sys t em for exposu re a n d h a z a r d assess-

men t s .

ACKNOWLEDGEMENT

W e t h a n k Dr . N. Litz, B undes ges undhe i t s amt , Ins t i tu t fiir Wasser - , Boden- u n d Luf thyg iene , Berlin, for da t a s u p p o r t a n d m a n y he lpfu l discussions.

REFERENCES

Atri, F.R., 1985. Chlorierte Kohlenwasserstoffe in der Umwelt, Fischer, Stuttgart, 411 pp. Bayerisches Landesamt fiir Wasserwirtschaft, 1985. Deutsches Gew~isserkundliches Jahrbuch.

Rheingebiet, Teil II: Main. Anhang: Bayerisches Elbegebiet. Abflussjahr 1982. Miinchen, 164 pp.

Beese, F. and Wierenga, P.J., 1980. Solute transport through soil with adsorption and root water uptake computed with a transient and a constant-flux model. Soil Sci., 129: 245-252.

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