Pond model

Mathematical models have also predicted a low volatility for methyl parathion (Jury et al. 1983 McLean et al. 1988). One study using a laboratory model designed to mimic conditions at soil pit and evaporation pond disposal sites (Sanders and Seiber 1983) did find a high volatility from the soil pit model (75% of the deposited material), but a low volatility for the evaporation pond model (3. 7% of the deposited material). A study of methyl parathion and the structurally similar compound ethyl parathion, which have similar vapor pressures, foimd that methyl parathion underwent less volatilization than ethyl parathion in a review of the data, the reduced level of volatilization for methyl parathion was determined to be due to its adsorption to the soil phase (Alvarez-Benedi et al. 1999). 

Collect temperature data as the solar pond model heats and cools. 

Water is transparent to visible light but opaque to infrared radiation. How do you think these properties will affect your solar pond model ... 

If you used only tap water in your model, convection currents would bring warmer, less dense water from the bottom to the surface. Do you think this will happen with your solar pond model Explain your answer. 

The next day, prepare the solar pond model. Place the black plastic dish on the lab bench where you want to run the experiment. Use a small piece of waterproof tape to attach one of the temperature probes to the bottom of the black plastic dish. Plug this probe into Channel 1 of the CBL System. Slowly pour the 100 mL of saturated salt solution into the dish. 

Position the 150-watt lightbulb about 15 to 20 cm over the top of the solar pond model. Turn on the light. Press ENTER on the calculator to begin collecting data. After about 6 to 8 minutes, turn off the lightbulb and move it away from the solar pond model. Do not disturb the experiment until the calculator is finished with its 30-minute run. 

Comparing and Contrasting Which layer of your solar pond model did the best job of trapping and storing heat ... 

A well-documented example of this approach is a study of the fate of the pesticide, chlorpyrifos, in a pond in Missouri (87 reviewed by Branson, 75). The conceptual model includes rate constants for each of the transport and transformation processes affecting the final concentrations of chlorpyrifos in the water, the sediment, and the fish. The rate constant for evaporation from water is estimated from data on vapor pressure, solubility, and molecular weight (for techniques, see 33, 68, 71). The remaining rate constants for the pond model are derived from laboratory studies. When validated by sampling in a pond, the predicted and environmentally measured concentrations of chlorpyrifos showed close agreement (75). 

The Interview protocol was semi-structured and developed in collaboration with researchers at the University of Michigan, U. S. A. The interviewer used questions that followed the questionnaire, but which also varied, based in part on each participant s responses to the questionnaire. The purpose of the Interview was for clarification and to provide an opportunity for in-depth probing into participants understandings. The Pre-instruction Interviews were audio taped, and the Postinstruction Interviews were both audio taped and video taped. An important aspect of the Post-instruction Interviews was that these were context-rich. The interviewer (the second author) encouraged participants to reference their own pond models, which they had built. During the interviews he probed preservice science teachers ideas, as the participants discussed the models diey had built and tested (Creswell, 1998). 

In the quest for better methods of establishing the environmental safety (or otherwise) of chemicals, interest has grown in the use of microcosms and meso-cosms—artificial systems in which the effects of chemicals on populations and communities can be tested in a controlled way, with replication of treatments. Mesocosms have been defined as bounded and partially enclosed outdoor units that closely resemble the natural environment, especially the aquatic environment (Crossland 1994). Microcosms are smaller and less complex multispecies systems. They are less comparable with the real world than are mesocosms. Experimental ponds and model streams are examples of mesocosms (for examples, see Caquet et al. 2000, Giddings et al. 2001, and Solomon et al. 2001). The effects of chemicals at the levels of population and community can be tested in mesocosms, although the extent to which such effects can be related to events in the natural environment is questionable. Although mesocosms have been developed by both industrial... 

An ecosystem can be thought of as a representative segment or model of the environment in which one is interested. Three such model ecosystems will be discussed (Figures 1 and 2). A terrestrial model, a model pond, and a model ecosystem, which combines the first two models, are described in terms of equilibrium schemes and compartmental parameters. The selection of a particular model will depend on the questions asked regarding the chemical. For example, if one is interested in the partitioning behavior of a soil-applied pesticide the terrestrial model would be employed. The model pond would be selected for aquatic partitioning questions and the model ecosystem would be employed if overall environmental distribution is considered. 

Therefore, the percent of chemical in the water can be solved for, and having this value the percent of chemical in each compartment can be subsequently calculated. Equations for the terrestrial model and the model pond are solved similarly. Also, the sizes of the compartments can be changed to represent different types of environmental conditions. 

Table III. Chemical distribution using model pond. 

Progress can best be made by applying these models to new and existing chemicals at all scales, i.e. to real environments such as Lake Michigan, to rivers, or small ponds, to microcosms and ultimately to laboratory flasks in which one process is isolated for study. The fugacity models described here will, it is hoped, contribute to the integration of such disparate data into more accurate profiles of chemical behavior in the environment. 

The comparisons in Table 1 using anthracene as the model pollutant showed that the dialysis and sorption techniques compare well. For both Boonton Humic Acid and Pakim Pond Humic Acid the results were not significantly different. 

This gives an example of fate modeling in which the risks of an insect growth inhibitor, CGA-72662, in aquatic environments were assessed using a combination of the SWRRB and EXAMS mathematical models.. Runoff of CGA-72662 from agricultural watersheds was estimated using the SWRRB model. The runoff data were then used to estimate the loading of CGA-72662 into the EXAMS model for aquatic environments. EXAMS was used to estimate the maximum concentrations of CGA-72662 that would occur in various compartments of the defined ponds and lakes. The maximum expected environmental concentrations of CGA-72662 in water were then compared with acute and chronic toxicity data for CGA-72662 in fish and aquatic invertebrates in order to establish a safety factor for CGA-72662 in aquatic environments. 

The following data were input into the EXAMS model to determine the fate of CGA-72662 resulting from runoff (0.001 lbs. ai/A) into ponds or lakes. 

Aquatic safety factors ranged from 5.5 X 107 for rainbow trout in ponds to 9.3 X 108 for daphnia in lakes. These data emphasize that exposure levels of CGA-72662 are low and must be taken into account for a risk assessment. Although the persistence of CGA-72662 in eutrophic lakes is relatively long, the exposure is extremely low and of no environmental consequence. Overall, use of SWRRB runoff and EXAMS models show CGA-72662 to be very safe in aquatic habitats when used on vegetables in Florida muck soil. 

A pipeline is installed to transport a red mud slurry from an open tank in an alumina plant to a disposal pond. The line is 5 in. sch 80 commercial steel, 12,000 ft long, and is designed to transport the slurry at a rate of 300 gpm. The slurry properties can be described by the Bingham plastic model, with a yield stress of 15 dyn/cm2, a limiting viscosity of 20 cP, and an SG of 1.3. You may neglect any fittings in this pipeline. 

Oxidation half-lives predicted by one compartment model t,/2 = 38 h in stream, eutrophic pond or lake and oligotrophic lake based on peroxy radical concentration of 10-9 M (Smith et al. 1978) aquatic fate rate k = 5 x 103 M-1 s-1 with t,/2 = 38 h (Callahan et al. 1979) ... 

Tsushimoto, G., F. Matsumura, and R. Sago. 1982. Fate of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in an outdoor pond and in model aquatic ecosystems. Environ. Toxicol. Chem. 1 61-68. 

The environmental impact of a new product needs to be assessed before it can be released for general use. Chemicals released into the environment can enter the food chain and be concentrated in plants and animals. Aquatic ecosystems are particularly sensitive, in this respect, since chemicals, when applied to agricultural land, can be transported in the ground water to rivers and then to the lakes, where they can accumulate in fish and plant life. The ecokinetic model presented here is based on a simple compartmental analysis and is based on laboratory ecosystem studies (Blau et ah, 1975). The model is useful in simulating the results of events, such as the accidental spillage of an agrochemical into a pond, where it is not ethical to perform actual experimental studies. 

The dominant transport process from water is volatilization. Based on mathematical models developed by the EPA, the half-life for M-hexane in bodies of water with any degree of turbulent mixing (e.g., rivers) would be less than 3 hours. For standing bodies of water (e.g., small ponds), a half-life no longer than one week (6.8 days) is estimated (ASTER 1995 EPA 1987a). Based on the log octanol/water partition coefficient (i.e., log[Kow]) and the estimated log sorption coefficient (i.e., log[Koc]) (see Table 3-2), ii-hexane is not expected to become concentrated in biota (Swann et al. 1983). A calculated bioconcentration factor (BCF) of 453 for a fathead minnow (ASTER 1995) further suggests a low potential for -hcxanc to bioconcentrate or bioaccumulate in trophic food chains. 

Based on its very small calculated Henry s law constant of 4.0xl07-5.4xl0"7 atm-m3/mol (see Table 3-2) and its strong adsorption to sediment particles, endrin would be expected to partition very little from water into air (Thomas 1990). The half-life for volatilization of endrin from a model river 1 meter deep, flowing 1 meter per second, with a wind speed of 3 meters per second, was estimated to be 9.6 days whereas, a half-life of greater than 4 years has been estimated for volatilization of endrin from a model pond (Howard 1991). Adsorption of endrin to sediment may reduce the rate of volatilization from water. 

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