Environ. Sci. Technol. 2000, 34, 266-273
Modeling Polydimethylsiloxane Degradation Based on Soil Water Content U . B . S I N G H , † S . C . G U P T A , * ,† G. N. FLERCHINGER,‡ J. F. MONCRIEF,† R. G. LEHMANN,§ N. J. FENDINGER,| S. J. TRAINA,# AND T. J. LOGAN# Department of Soil, Water, and Climate, University of Minnesota, St. Paul, Minnesota 55108, USDA-ARS, Boise, Idaho, Dow Corning Corporation, Midland, Michigan, The Procter and Gamble Co., Cincinnati, Ohio, and The Ohio State University, Columbus, Ohio
Polydimethylsiloxane (PDMS) is a widely used silicone polymer that is introduced into wastewater treatment systems where it is removed with sludge. PDMS subsequently enters the terrestial environment as a result of sludge amendment to soil. Laboratory studies have shown that PDMS extensively breaks down into monomeric units when in contact with dry soils. The byproducts of hydrolysis eventually biodegrade or evaporate. The objective of this study was to develop a computer model that can predict the degree of PDMS breakdown based on level and duration of soil drying under different climatic conditions. The framework of the model was the SHAW (Simultaneous Heat and Water) model that predicts daily water content distribution in soil over the course of a year. The soil water contents predicted from the SHAW model were then linked to PDMS degradation rate data for various soils to predict soil and climate impacts on PDMS losses. Field testing of the model at Columbus, OH showed that the model was able to predict the general trends in PDMS degradation over 2 years. Predicted PDMS concentrations remaining in the 0-10 cm depth 2 years after sludge addition were 19.8 mg/kg of soil compared to the measured values of 23.0 mg/ kg of soil. The sensitivity analysis of the model showed that >95% of PDMS degraded at the soil surface in Bayamon sandy clay loam (San Juan, PR), Miamian loam (Columbus, OH), and Wedowee sandy clay loam (Athens, GA) soils within 365 days after application. However in some years, >50% of applied PDMS was still remaining at 2.5-cm depth 365 days after its application. At any given day, there was less PDMS remaining in soil at San Juan, PR, and at Athens, GA, than at Columbus, OH. This is because of (1) higher rates of PDMS degradation in Bayamon and Wedowee soils than in Miamian soil and (2) better soil drying conditions in Puerto Rico and Georgia than in Ohio.
Introduction Polydimethylsiloxane (PDMS) is a silicone polymer that is widely used in many industrial and consumer applications. * Corresponding author phone: (612)625-1241; fax: (612)625-2208; e-mail:
[email protected]. † University of Minnesota. ‡ USDA-ARS. § Dow Corning Corporation. | The Procter and Gamble Co. # The Ohio State University. 266
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Approximately 14% of the PDMS manufactured is disposed of down the drain and enters wastewater treatment systems where it is sorbed on and then removed with sludge (1, 2). Approximately 1/3 of the sludge produced in the U.S. is used to amend soils for beneficial purposes (Standard for the Use and Disposal of Sludge. Fed. Reg. 1993, 58, 9257). The practice of sludge addition to land results in the introduction of PDMS in the soil environment. PDMS is resistant to biodegradation, hydrolytic, or oxidative breakdown during wastewater treatment (3). However, PDMS hydrolyzes to water soluble dimethylsilanediol [(CH3)2Si(OH)2] when it comes in contact with dry soils (2, 4):
(CH3)3SiO-[Si(CH3)2O]n-Si(CH3)3 + (n+1)H2O f n(CH3)2Si(OH)2 + 2(CH3)3SiOH It is postulated that the presence of clay in soil promotes degradation of these silicone polymers (5). The PDMS hydrolysis is thought to be catalyzed by surface Bronsted and Lewis acidities associated with clay minerals (6). The main hydrolysis product, dimethylsilanediol, is removed from soil by both biodegradation to CO2 (7) and volatilization to the atmosphere where it is oxidized by OH radicals generated in the presence of sunlight (8). Laboratory studies have shown that the rate of PDMS hydrolysis varies with soil moisture content (5) and the type of clay (6). Using several soils, Lehmann et al. (5) showed that the rate of PDMS hydrolysis increased with a decrease in soil water content. However, rate of PDMS hydrolysis was not the same for all soil types. In general, the rate of hydrolysis was greater for highly weathered soils than less weathered soils (5). For example, the rate of PDMS hydrolysis in a moist (soil matric potential of -0.04 MPa) Alfisol from Michigan was the lowest (0.19% wk-1). Comparatively, the hydrolysis rate in Alfisol from Ohio, Ultisol from Georgia, and Oxisol from Puerto Rico were 0.41, 1.25, and 1.26% wk-1. The higher hydrolysis rates of PDMS in Ultisols and Oxisols are probably due to the presence of more reactive minerals. In an extensive monitoring of the wastewater treatment plants and associated sludge amended soils in North America, Fendinger et al. (1) showed that PDMS concentrations ranged from 50% by volume. The frequencies are summed in the ascending order of soil water content categories. The cumulative probabilities were then calculated as the ratio of the cumulative frequency (i) of a given soil water content category to the total number of years (n) in the database:
cumulative probability )
i n
(2)
The procedure for calculating PDMS concentration remaining in soil involved running the SHAW model for soil water content predictions using the soil and climatic inputs of a given site. The soil water content outputs were then imported in a Microsoft EXCEL spreadsheet where eq 1 was used to calculate PDMS degradation over time. Initial PDMS concentration was assumed at 10 mg kg-1 in the top 10 cm depth. After calculating the amount of PDMS degradation, these values were subtracted from the initial concentration to calculate the PDMS concentrations remaining at a given depth. These concentrations were then divided by the initial concentration to calculate the percent PDMS degradation at a given depth for a given site and a year. Probabilities of PDMS remaining in the soil were calculated using the predicted concentrations of PDMS in the soil at various depths. The procedure for calculating PDMS probabilities was similar to that for calculating the probabilities of soil water contents. For example on any given 268
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day, 30 year (24 years for San Juan, PR) predictions of PDMS remaining in the soil at a given depth were arranged in an ascending order, and then the cumulative probabilities were calculated using eq 2. Model simulations were also run to evaluate the impact of climate on PDMS degradation. For this objective, we ran simulations for five sites. The locations were St. Paul, MN; Columbus, OH; Athens, GA; Los Angeles, CA; and San Juan, PR. At all sites, we assumed that the soil was a Londo sandy clay loam (fine loamy, mixed, mesic, aeric Glossaqualfs) and there was no crop present during the simulation period. This soil had the slowest PDMS degradation under laboratory conditions and represents the worst case scenario for PDMS degradation. Particle size distribution as well as the parameters of the hydraulic properties for the Londo soil as estimated using the regression equations of Rawls et al. (18) are listed in Table 1. Daily soil water contents and PDMS remaining probabilites were calculated as discussed previously. Long-term climatic data for Columbus, OH; Athens, GA; San Juan, PR; and Los Angeles, CA were acquired from the National Climatic Data Center (NCDC) in Asheville, NC and from the Earth Info Inc. at Boulder, CO. Climatic data for St. Paul, MN were obtained from the Climate group in the Department of Soil, Water, and Climate, University of Minnesota, St. Paul, MN. Statistical Analysis. Two main statistics were used to characterize the differences between measured and predicted values. The first statistic is the mean difference (MD) between the measured and the predicted values defined as n
∑(M - P ) i
MD )
i
i)1
(3)
n
where M and P are the measured and the predicted values, respectively, and n is the number of observations. The other statistic is the root-mean-square error (RMSE) defined as
x
n
∑(M - P )
RMSE )
i
i)1
n
2
i
(4)
MD defines the overall trend between the measured and the predicted values, whereas RMSE defines the scatter between the predicted and the measured values (15). A positive value of MD means the measured values are higher than the predicted values, whereas a zero value of RMSE means that there is no scatter between the predicted and the measured values.
Results and Discussion Comparisons of Measured and Predicted Soil Water Contents. Comparison between measured and predicted water contents at Columbus, OH during 1995 and 1996 are shown in Figure 1. Measured water contents correspond to 0-5 cm depth, whereas the predicted water contents are for a node at 2.5 cm depth. Measured water contents plotted in Figure 1 are for the 0 and the 15 mt/ha sewage sludge application treatments. In general, the measured water contents were higher for the 15 mt/ha treatment compared to the control because of the additional water holding capacity of the organic matter as a result of sewage sludge addition (19). Although slightly higher than one would expect based on previous work (19), the increased water contents in 15 mt/ ha treatment are within the range of variability observed in field water contents measurements. The differences between
FIGURE 1. Comparison of predicted and measured (0, 15 mt/ha sludge addition) volumetric soil water contents at 2.5-cm depth for the Miamian loam at Columbus, OH during 1995 and 1996. Higher water contents early in the season were due to snowmelt ponding on frozen soils. this study and that of Gupta et al. (19) may be due to the differences in soil type (coarse sand vs silt loam). Predicted water contents tracked the variations in measured water contents very well for both years. The predicted values in 1995 were slightly lower than the measured values, whereas the predicted values in 1996 were slightly higher than the measured values. Over both years, predicted values were slightly higher than the measured values for the 0 mt/ ha treatment and slightly lower than the measured values for the 15 mt/ha treatment. MD and RMSE between the measured and predicted water contents were -0.2% and 7.3% for the 0 mt/ha sludge treatment and 1.5% and 7.3% for the 15 mt/ha sludge treatment over both years. These numbers show that model predictions averaged over 2 years were very close (
