Daniel H. Chen and Carl L. Yaws Lamar University, Beaumont, Texas ABSTRACT
Results for soil sorption coefficient KOC are presented for 336 hydrocarbon and organic chemicals.
The chemicals include hydrocarbon, oxygen, nitrogen, halogen, sulfur and phosphorus compounds.
Representative results for soil adsorption coefficient [(mg sorbed / kg organic carbon in soil) / ( mg/L aqueous concentration) or abbreviated as L/kg] are 4300 for trifluralin (C10H9F3N3O4), 3910 for hexachlorobenzene (C6CL6), 1300 for naphthalene (C10H8) and 27 for phenol (C6H6O) in a normal soil environment (20 C, pH 4-8, carbon exchange capacity greater than 7 MEQ/100 g, sand composition less than 70%, etc.). The melting point (MP) and molecular weight (MW) data are also provided as they are needed in many environmental property data correlations.
INTRODUCTION
The soil sorption coefficient KOC , which determines the partitioning of an organic chemical between the soil/sediment and the aqueous solution, is an important environmental parameter. KOC affects the physical movement of pollutants, chemical degradation (photolysis and hydrolysis), biodegradation, acidity and buffered solution-phase concentration. As a result, the soil sorption coefficient is widely used in river, runoff and soil/ground water models for the assessments of the fate and transport of chemicals (5,24,28,36).
KOC is also known as "soil organic carbon partition coefficient" or "soil sorption coefficient standardized with respect to organic carbon." With the value of KOC known, the partition uptake of water contaminants for a particular soil/sediment or the degree of leaching of the pollutants into the ground water can be estimated.
A compilation of the soil sorption coefficient data for 336 compounds is provided in an easy-to-use tabular format that is especially applicable for rapid engineering use with the personal computer or hand calculator.
SOIL SORPTION COEFFICIENT
The amount of chemicals sorbed onto a soil or sediment depends on the concentration of chemicals and their equilibrium distribution coefficient (i.e., KOC). For dilute aqueous solutions, the distribution coefficient can be adequately expressed with the Freundlich equation with 1/n equal to one (8,11,24,25,38):
x / m = KOC C (20-1)
where x = weight of solute sorbed, mg
C = equilibrium concentration of solute in aqueous phase, mg/L m = weight of sorbent (organic carbon in soil), kg
KOC = soil sorption coefficient
From the above equation, KOC can be interpreted as the ratio of the solid phase concentration (normalized for the organic carbon content) to the solution phase concentration of the chemical at equilibrium. Therefore, in commonly used units, KOC is:
mg sorbed/ kg organic carbon KOC = _________________________________________
(20-2) mg/L aqueous concentration
The unit of KOC can be abbreviated as L/kg. The average organic carbon content of a typical soil is from 0.5% to 3.5%. By basing the sorption coefficient on soil (or sediment) organic carbon, one can eliminate much of the variation between soils due to organic carbon content. Note that the cited experimental or predicted KOC values are intended for a normal environment as stated above. Attempts to extrapolate far beyond these conditions may incur considerable errors (10-12,15,24). In case that the coefficient is expressed in terms of soil organic matter, Kom, the following equivalence can be used to obtain KOC:
KOC = 1.72 Kom (20-3)
This assumes that the organic matter contains about 58% C (8).
The results for the soil sorption coefficient for organic chemicals in water are given in Table
20-1. The melting point (MP) and molecular weight (MW) are also provided to facilitate predictions for other
environmental properties. The tabulation is applicable to a wide variety of organic chemicals in contact with water at normal ambient conditions. The wide variety of substances includes hydrocarbons, acids, alcohols, esters, ethers, ketones, fluorides, chlorides, bromides, amines, sulfones, nitros, amides, sulfides and phosphates. The tabulation is arranged by carbon number (C, C2, C3, .... C21). This provides ease of use in quickly locating data using the chemical formula.
In preparing the tabulation, a literature search was conducted to identify data source publications (1-40). The publications were screened and copies of appropriate data were made. These data were then keyed into the computer to provide a database.
The nonlinear group contribution method (3,13,21) has been used for the estimation of the soil sorption coefficient when experimental KOC values are not available. The method is based on comprehensive (225 compounds) and updated data. Comparison with literature methods yields favorable results (2,3,13,19,32,33). In general, the prediction errors are within ± 0.82 order of magnitude (95%
confidence limit). A comparison of calculated and data (experimental) values for the soil sorption coefficient is shown in Figure 20-1. The graph discloses general agreement of calculated and data values for different organic chemicals.
The compilation for the soil sorption coefficient maybe used in engineering and environmental impact studies involving organic compounds in water.
EXAMPLES
The tabulation may be used for determining the soil sorption coefficient for the compound in water.
The use of the soil sorption coefficient in environmental applications involving organic chemicals in water is illustrated below.
Example 1 For an aqueous concentration of benzene (C6H6) in contaminated river water of 10 ppm by weight, what will be the maximum uptake of benzene by the bottom sediment? The average organic carbon content of the bottom sediment is 3%.
The equation x/m = KOC C is used in determining the solution. First, calculate the amount of organic carbon per ton (metric) of bottom sediment: m = 1000 * 3% = 30 kg organic carbon. Then substitute the soil sorption coefficient of benzene from the tabulation
KOC = 83 (mg sorbed/kg org carbon) / (mg/L aqueous conc) = 83 (mg sorbed/kg org carbon) / (ppm aqueous conc) and the aqueous concentration C = 10 ppm into the equation for x/m to obtain:
x /30 = 83 * 10 mg
x = 30*83*10 mg = 2.5E04 mg = 0.025 kg
Example 2 Atrazine (C8H14CLN5) is uniformly applied to a field and incorporated into the soil. The soil has a bulk density of 1.25 kg/L, 2 % organic carbon and 25 % each air and water by volume. Estimate the equilibrium distribution of the pesticide resulting from a 1 kg/hectare (1 hectare = 10,000 m2) application incorporated to 10-cm depth. Volatilization into the air is assumed to be negligible.
The amount of organic carbon in soil per hectare is m = 10,000 *.1 * 1000 * 1.25 * 2% = 25,000 kg of org carbon. From the tabulation, the soil sorption coefficient of atrazine is
KOC = 149 (mg sorbed/kg organic carbon) / (mg/L aqueous conc)
Determination of the amount of atrazine in the soil phase per hectare requires a trial and error procedure.
Trying x = .94 kg = 940000 mg in the equation x/m = KOC C and solving for C gives:
C = (940000 /25,000)/149 = .252 mg/L
The amount of atrazine in the aqueous phase per hectare is .252 * 10,000 * .1 * 1,000 * 25% = 63000 mg = .063 kg
The total amount of atrazine is 1.003 kg/hectare. This is close enough to the application (1.003 vs 1 application).
The equilibrium distribution of atrazine is estimated to be:
.063/(.94 + .063) = 6.3 % in water .94/ (.94 + .063) = 93.7 % in soil
Portions of this material appeared in Pollution Engineering, 24, 54 (June 15, 1992) and are reprinted
by special permission.
REFERENCES – ORGANIC COMPOUNDS
1. Boyd, S. A., Mikesell, M. D., and Lee, J. F., Chlorophenols in soil. Sawhney, B. L. and K. Brown (eds.), REACTION AND MOVEMENT OF ORGANIC CHEMICALS IN SOILS , Soil Science Society of American and American Society Agronomy, SSSA Special Publication no. 22, 209 (1989).
2. Briggs, G. G. J. Agric. Food Chem. 29(5), 1050 (1981).
3. Chen,T. L., D. H. Chen, and C. L. Yaws, Predicting soil adsorption with molecular structure, paper 54b, AIChE National Meeting, August 19-22, 1990, San Diego, California.
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10. Hamaker, J. W. and J. M. Thompson, Adsorption. Goring C.A.I. and Hamaker J.W.(eds.), ORGANIC CHEMICALS IN THE SOIL ENVIRONMENT, Vol. 1, Marcel-Dekker , New York, NY (1972).
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41. Chen, D. H., C. L. Yaws and others, Pollution Engineering, 24, 54 (June 15, 1992).
Chapter 21 VISCOSITY OF GAS
Carl L. Yaws, Xiaoyan Lin and Li Bu Lamar University, Beaumont, Texas ABSTRACT
Results for gas viscosity as function of temperature are presented for a wide range of organic and inorganic chemicals. The major chemicals include many compound types. The results are provided in easy-to-use tables that are especially applicable for rapid engineering usage with the personal computer or hand calculator. The agreement of correlation and data is quite good.
INTRODUCTION
Gas viscosity data are important in many engineering applications in the chemical processing and petroleum refining industries. The objective of this article is to provide the engineer with such viscosity data.
The compilation of data is presented for a wide temperature range to enable the engineer to determine values at desired temperatures of interest.
GAS VISCOSITY CORRELATION
The correlation for gas viscosity as a function of temperature is given by the equation shown below:
ngas = A + B T + C T2 (21-1) where ngas = viscosity of gas, micropoise
A, B and C = regression coefficients for chemical compound T = temperature, K
The results for gas viscosity at low pressure are given in Tables 21-1 and 21-2. The tabulations are arranged by chemical formula carbon number to provide ease of use in quickly locating data.
In preparing the compilation, a literature search was conducted to identify data source publications for organics (1-37) and inorganics (1-62). Both experimental values for the property under consideration and parameter values for estimation of the property are included in the source publications. The publications were screened for appropriate data. The compilation resulting from the screening is based on both experimental data and estimated values. In the absence of experimental data, estimates were primarily based on modified Chapman-Enskog method (29, Chung et al equation, intermolecular forces, collision diameter) and Reichenberg equation (29, corresponding state, group contribution). Experimental data and estimates were then regressed to provide the same equation for all compounds.
Very limited experimental data are available for highly polar and high molecular weight compounds.
Thus, the values for these compounds should be considered rough approximations.
A comparison of correlation and experimental data is shown in Figure 21-1 for a representative chemical. The graph discloses good agreement of correlation and data.
EXAMPLES
The correlation results maybe used for prediction and calculation of gas viscosity. Examples are given below.
Example 1 Calculate the gas viscosity of n-hexane (C6H14) at a temperature of 300 K.
Substitution of the coefficients from the table and temperature into the correlation equation yields:
ngas = - 8.2223 + 2.6229E-01*300 - 5.7366E-05*3002 ngas = 65.3 micropoise
The calculated and data values compare favorably (65.3 vs 66.6, deviation = 1.95%).
Example 2 Calculate the gas viscosity of carbon tetrachloride (CCl4) at a temperature of 520 K.
Substitution of the coefficients from the table and temperature into the correlation equation yields:
ngas = - 7.7453 + 3.9481E-01*520 - 1.1150E-02*5202 ngas = 169.3 micropoise
The calculated and data values compare favorably (169.3 vs 167.0, deviation = 1.36%).
REFERENCES – ORGANIC COMPOUNDS
1-34. See REFERENCES - ORGANIC COMPOUNDS in Chapter 1 CRITICAL PROPERTIES AND ACENTRIC FACTOR
35. Golubev, I. F., VISCOSITY OF GASES AND GAS MIXTURES, translated from Russian, US Dept. of Commerce, Springfield, VA (1970).
36. Stephan, K. and K. Lucas, VISCOSITY OF DENSE FLUIDS, Plenum Press, New York, NY (1979).
37. Yaws, C. L., HANDBOOK OF VISCOSITY, Vols. 1, 2 , 3 and 4, Gulf Publishing Company, Houston, TX (1995, 1995, 1995, 1997).
REFERENCES – INORGANIC COMPOUNDS
1-56. See REFERENCES - INORGANIC COMPOUNDS in Chapter 1 CRITICAL PROPERTIES AND ACENTRIC FACTOR
57. Golubev, I. F., VISCOSITY OF GASES AND GAS MIXTURES, translated from Russian, US Dept. of Commerce, Springfield, VA (1970).
58. Lyon, R. N., ed., LIQUID-METALS HANDBOOK, Atomic Energy Commission and Dept. of Navy, Washington, DC (1954).
59. Emsley, J., THE ELEMENTS, 2nd ed., Clarendon Press, Oxford University Press, New York, NY (1991).
60. Perry, D. L. and S. L. Phillips, HANDBOOK OF INORGANIC COMPOUNDS, CRC Press, New York, NY (1995).
61. Stephan, K. and K. Lucas, VISCOSITY OF DENSE FLUIDS, Plenum Press, New York, NY (1979).
62. Yaws, C. L., HANDBOOK OF VISCOSITY, Vol. 4, Gulf Publishing Co., Houston, TX (1997).
Chapter 22 VISCOSITY OF LIQUID
Carl L. Yaws, Xiaoyan Lin and Li Bu Lamar University, Beaumont, Texas ABSTRACT
Results for liquid viscosity as function of temperature are presented for a wide range of organic and inorganic chemicals. The major chemicals include many compound types. The results are provided in easy-to-use tables that are especially applicable for rapid engineering usage with the personal computer or hand calculator. The agreement of correlation and data is quite good.
INTRODUCTION
Liquid viscosity data are important in many engineering applications in the chemical processing and petroleum refining industries. The objective of this article is to provide the engineer with such viscosity data.
The compilation of data is presented for a wide temperature range to enable the engineer to determine values at temperatures of interest.
LIQUID VISCOSITY CORRELATION
The correlation for liquid viscosity as a function of temperature is given by the equation shown below:
log10 nliq = A + B/T + C T + D T2 (22-1) where nliq = viscosity of liquid, centipoise
A, B, C and D = regression coefficients for chemical compound T = temperature, K
The results for liquid viscosity are given in Tables 22-1 and 22-2. The tabulations are arranged by chemical formula to provides ease of use in quickly locating data. Many of the values for the liquid cover the full range from melting to critical point.
In preparing the compilation, a literature search was conducted to identify data source publications for organics (1-40) and inorganics (1-126). Both experimental values for the property under consideration and parameter values for estimation of the property are included in the source publications. The publications were screened for appropriate data. The compilation resulting from the screening is based on both experimental data and estimated values.
For organic compounds, liquid viscosities at low temperatures were primarily estimated using the Van Velzen method (29, group and structural contributions). The Przezdziecki and Sridhar equation (29, corresponding states) and boiling point method (empirical) were also used for selected compounds. For liquid viscosities at high temperatures, both experimental data and estimates were extended using a modified Letsou and Stiel equation (29, corresponding states) for saturated liquids. Experimental data and estimates were then regressed to provide the same equation for all compounds.
For inorganic compounds, liquid viscosities for metals were primarily estimated using the Grosse method (64, melting point, liquid volume). For inorganics that are solids at ambient conditions, a modified Letsou and Stiel method (29, corresponding states, melting point, boiling point) was used. For inorganics that are gases and liquids at ambient conditions, a modified Letsou and Stiel method was also used.
Experimental data and estimates were then regressed to provide the same equation for all compounds.
For gas and liquid viscosities, the experimental data for inorganics is very limited or scarce when compared to that available for organics. The estimation methods for inorganics are also very limited or scarce in comparison to organics. Thus, in the absence of experimental data and the scarcity of estimation methods, the estimates for inorganics should be considered as very rough approximations.
Very limited experimental data for liquid viscosities are available at temperatures in the region of the melting and critical point temperatures. Thus, the values in the regions of melting and critical point temperatures should be considered rough approximations. The values in the intermediate region (above melting and below critical point) are more accurate.
A comparison of correlation and experimental data for liquid viscosity is shown in Figure 22-1 for a representative chemical. The graph discloses good agreement of correlation and data.
EXAMPLES
The correlation results maybe used for prediction and calculation of liquid viscosity. Examples are given below.
Example 1 Calculate the liquid viscosity of cyclohexane (C6H12) at a temperature of 353.85 K (80.7 C).
Substitution of the coefficients from the table and temperature into the correlation equation yields:
log10 nliq = + 4.7423 - 2.5322E+02/353.85 - 1.6927E-02*353.85 + 1.2472E-05*353.852 = -.4012 nliq = 10-.4012
nliq = 0.397 centipoise
The calculated and data values compare favorably (0.397 Vs 0.413, deviation = 3.87%).
Example 2 Calculate the liquid viscosity of benzene (C6H6) at a temperature of 343.35 K (70.2 C).
Substitution of the coefficients from the table and temperature into the correlation equation yields:
log10 nliq = - 7.4005 + 1.1815E+03/343.85 + 1.4888E-02*343.85 - 1.3713E-05*343.852 = -.4647 nliq = 10-.4647
nliq = 0.343 centipoise
The calculated and data values compare favorably (0.343 Vs 0.3507, deviation = 2.2%).
Portions of this material appeared in Chem. Eng., 101 (4), 119 (April, 1994) and is reprinted by special permission.
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