퓨개시티 모델에 의한 유기오염물질의 분배예측

백종만, 박소진

충남대학교 공과대학 화학공학과

PPREDICTION OF DISTRIBUTION OF POLLUTED ORGANIC

COMPOUNDS BY USING FUGACITY APPROACH MODEL

Jong-Man Baek and So-Jin Park

Department of Chemical Engineering, Chungnam National University

INTRODUCTION

Understanding how polluted chemicals migrate thru the our environmental multimedia has became increasingly concerned with predicting fate and transport of chemicals which are subject to accumulation in environmental compartments where biota and human exposure is significant. Chemicals used industrially, commercially and domestically are discharged into environment. Among them toxic chemicals are our concern because they move through the food chain and have toxic effects on animal and human. It is necessary to understand and predict the sources, fates and effects of chemical substances in the environment for monitoring and assesment.

The environmental fates of organic chemicals are largely determined by their partitioning tendencies between atmospheric, aqueous, and organic phases. For this purpose there is an incentive to develop method of calculating or modeling, the multimedia environmental fate of toxic chemicals specially organic compounds. Several multimedia models such as ChemCAN(1), HAZCHEM(2), simple BOX(3), and Cohen et.al model(4) have been developed to produce a comprehensive picture of environmental behavior. Fugacity model which use physical-chemical properties, reactivity, transport characteristics and extent of release has been developed. It is also one of the developing methods which can be used to estimate prevailing concentration under steady state and unsteady state conditions. The fugacity concept has been applied to a variety of chemicals and environmental conditions.

In this paper we review a relatively simple four compartment fugacity model which reduced to a four immiscible phases (air, water, soil and bottom sediment) from the number of environmental media. These compartments are considered as assemblies of subcompartment, which consist of air, water, solid and biotic matter. Equilibrium is assumed to apply within each compartment. Partitioning, reaction, and diffusive and nondiffusive transfer process are generally considered. These transfer process are expressed in terms of D values. Each D value contains two terms, a Z value which is obtained form physical-chemical data and kinetics or transport rate terms such as mass-transfer coefficient, diffusivity or advective flow rate. By the way, In korea, spillage of phenol has occurred at the Nakdong river. In that case the remedy of the impacted areas are required. Detailed review assuming spillage in the region of lake Daechung was presented using fugacity approach.

The results of the model for assessing the fate of chemical, phenol in a four compartment system are presented and provide understanding about chemicals, their fate and environmental concentration.

THEORY

Fugacity is a thermodynamic quantity related to chemical potential or activity that characterizes the escaping tendency from a phase. It has units of pressure and can be related to concentration. At equilibrium, fugacities of each phase are equal. Partitioning of chemical between phases can be described by the equilibrium criteria of fugacity which can be considered to be the partial pressure of chemical in a phase and is related to concentration C (mol/m3) by the expression

C = fZ	(1)

where Z is the fugacity capacity. For phase we adopt another procedure exploiting partition coefficient. If we know Z for phase 1 and we can determine dimensionless partition coefficient K21 which is C2/C1, then since the fugacities of the solute are equal at equilibrium.

K12 = C1/C2 = Z1f/Z2f = Z1/Z2                                (2)

Chemicals move between phases by both diffusive and nondiffusive processes. The diffusive flux N (mol/h) between two phases, 1 and 2, can be described by

N = D(f1-f2)	(3)

where D (mol/hPa) is a transfer coefficient and f1 and f2 are the phase fugacities. The difference between f1 and f2 determines the direction of diffusive flux that take place from high to low fugacity. D is a function of Z values. Nondiffusive or one-way transfer process between phases can also be described by a transport parameter as

N = GC = GZ = Df                                        (4)

where G (m3/h) is the volumetric flow rate. First order reaction process in a phase can be described as

N = kRVZf = DRf	(5)

where kR is first order rate constant, V (m3) is the phase volume. In summary, all rates of chemical transport and transformation can be expressed as products of fugacities and D values.

RESULTS

Phenol, used in the production of phenolic resins, in a four compartment system is introduced. The result of model was reviewed with available data which were reported that concentration of trichloethylene (TCE) was in reasonable agreement with the available field measurements. Table 1 shows the calculated and reported concentration and fugacities for the four bulk phases.  The order of magnitude of fugacity in air, water, soil and sediment are fairly similar. Utilizing this model specific calculation in the area of lake of Daechung was performed with the utilized compartment values given in tables 2 and 3.  A  problem is estimation of reasonable

Table 1. Calculated and reported concentration and phase fugacities for the four bulk phases

	air ng/□	water ng/l	soil mg/kg	sediment ng/g	fugacities
					air	water	soil	sediment
calculated	48715	1095	2.4e-5	2.410	0.00009	0.0098	0.00087	0.0080
reference5)	11000	270	3.7e-5	0.6	0.00021	0.0025	0.00021	0.0025

emission rates.

The model results shown in figure 1 for the phenol were based on the partition and transport coefficient shown in table 4 and 5. The overall persistence is 279hrs and total mass is 95.6kg.

Figure 1. Emission to three media

Table 2. Physical-chemical properities of lake Daechung

temperature (℃)	20
molecular weight (g/mol)	94.1
aquous solubility (g/□)	1.05e+5
vapor pressure (Pa)	38.7
octanol water partition coefficient (Kow)	1.45

Table 3. Characteristic of the environment of lake Daechung

total surface area (K□)	482
surface covered by water (% total)	15
average air height (Km)	1
average water depth (m)	29
average soil depth (cm)	10
average sediment depth (cm)	5
environmental temperature (℃)	20

Table 4. Phase properties, compositions

phase	air	water	soil	sediment
bulk □	4.8e+14	2.1e+9	4.1e+7	7.2e+5
density Kg/□	1.206	1000	1500	1420
bulk Z value	4.1e-4	28.8	16.6	29.7
emmision Kg/y	1000	1000	1000	0
fugacity Pa	9.81e-8	3.15e-10	8.11e-8	3.07e-10
concentration g/□	3.79e-3	0.853	127	0.858
amount Kg	1.826	1.788	5.202	6.02e-4

Most phenol is founded in soil and water. The actual relative emission to the air, water and soil can be known. Environmental condition vary in time and space and few reliable data are usually available. Reaction rate, constant are vary seasonally. phenol degradation in the water and air compartment was assumed to follow first order kinetics.

Table 5. Intermedia transport data

	half time (h)	equv.flow (□/h)	D value (mol/pah)	rates (mol/h)
air to water	407	7.31e+6	3001	1.61e-3
air to soil	50.7	8.25e+6	3387	1.81e-3
water to air	407	3.54e+6	295	0.499
water to sediment	7016	9645	8.157	1.36e-3
soil to air	50.7	5.6e+5	3352	0.841
soil to water	9789	2900	17.4	4.36e-3
sediment to water	1163	2137	6.277	1.01e-3

From the results several important thing can be drawn from these depiction of chemical fate. When emissions to all three media occur simultaneously, the fate is sum of the weighted individual emissions due to linear equation used in the model. Overall environmental persistence depend on how chemical is discharged to the environment.

From this model it is possible to predict the behavior of new chemical and to estimate order of magnitude concentration, the dominant reaction, role of advective loss and the intermedia transport characteristics.

CONCLUSIONS

The model provides a relatively simple, rapid methods of establishing the relative importance of environmental fate process for specific chemical using minimum data. The primary advantage of this modeling is that it provides the general  behaviour profile of specified chemicals. This simple fugacity model serves to illustrate and reinforce the concept of multimedia approach. Future work should be concentrated on the extension of fugacity model to more specific situation.

ACKNOWLEDGEMENTS

The authors thank " Korea Science and Research Foundation and Green environment Co. Ltd." for financial support.

REFERENCES

(1). Mackay, D. et al. ChemCAN: A Regional Level III Fugacity Model for              Assessing Chemical Fate in Canada

(2). ECETOC, HAZCHEM: A Mathematical Model for Use in Risk Assesment

of Substance; Brussels, Belgium (1994)

(3). van de Meent, D. SimpleBOX: A Generic Multimedia Fate Evaluation

Model; RIVM: Biltoben, Netherlands (1993)

(4). Cohen, Y. et al., Environ. Sci. Tech., 24, 1549-58 (1990)

(5). Mackay, D. and S. Paterson., Environ. Sci. Tech., 25, 427-436 (1991)