In the Classroom
Intermolecular Forces as a Key to Understanding the Environmental Fate of Organic Xenobiotics Ryan E. Casey* Department of Chemistry, Towson University, Towson, MD 21252-0001; *
[email protected] Faith A. Pittman Science Department, Northeast High School, 1121 Duvall Highway, Pasadena, MD 21122
To someone without a technical background, the complexities of environmental issues can be intimidating or even incomprehensible. Yet community members with nontechnical backgrounds are often stakeholders in the environmental decision-making process on issues ranging from cleanup of hazardous waste sites to approving land uses (1, 2). Often, if participants in such processes better understood the molecular nature of these issues they would be more able to make informed decisions for themselves and their communities. For this reason, it is important to develop environmental education courses targeting undergraduate nonscience majors and high school students to increase the molecular-level understanding of environmental issues among the general public (3). This article describes a module that can be incorporated into chemistry or environmental science classes at the high school or undergraduate level. The module assumes little more than a basic knowledge of the molecular nature of mat-
charge separation/ molecular polarity
chemical background
intermolecular forces
functional groups/ structural shorthand "like dissolves like"
polarity of environmental media
qualitative environmental partitioning
defintion of Kow
quantitative env. partitioning (modeling)
relation of vapor pressure to IMFs
ter (atoms and bonds) on a level that would be discussed in the introductory weeks of a high school or college chemistry course. Developing the relationship between macroscopic phenomena and interactions at the molecular level is one of the fundamental challenges of chemical education (4). After completing this module, students can delve into a host of environmental applications and case studies that tie together processes in the macroscopic world with their particulate causes. Especially for nonscience majors, case studies are an important tool (5) that can bring them into the world of science instead of leaving them as spectators on the outside, merely memorizing facts and formulas. With a small investment in chemistry concepts students can make scientifically valid predictions about the fate of environmental contaminants. These predictions can then be verified through existing data sets, computer models, or laboratory experimentation. By placing students in an active role where they can make and verify predictions, we hope to alleviate some of the anxiety that students often feel toward chemistry and improve their ability to address complex issues. Course Context This module is currently being taught at Towson University in Introduction to Environmental Chemistry. This course has no prerequisites and is used to fulfill the Chemistry requirement for the policy-oriented environmental studies major and additionally serves as a general education laboratory course. Currently the majority of students are enrolled for general education credit. The chemistry concepts presented are limited to those facilitating investigations of the molecular-level aspects of environmental issues. At the high school level, the module was incorporated into traditional general chemistry and honors chemistry courses. Module Design
additional applications
toxicology
bioaccumulation/ biomagnification
groundwater contamination
Figure 1. Model sequence.
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Because the prerequisite knowledge for this module is limited to a basic understanding of atoms and chemical bonds, the module can be incorporated at almost any stage of a chemistry or environmental science course. At Towson University, the module begins in the third week of the course following basic discussions of the scientific method, atomic theory, the periodic table, and chemical bonding. The module is divided into a series of segments (Figure 1), each of which incorporates several concepts and results in students making significant predictions about the behavior of organic xenobiotics (man-made substances, “foreign to life”). We
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In the Classroom
cover the main body of the module in approximately four one-hour lectures and one three-hour laboratory period (for the computer model). We then spend an additional 3–4 lectures on applications. In the high school version, the module was originally intended to follow bonding, however, the module was actually incorporated at the end of the semester. This served to expose students to introductory organic structural formulas and functional groups. It also served as a capstone experience by providing an excellent opportunity to revisit topics such as solubility, polar and nonpolar molecules, and bonding. Chemical Background The module begins by introducing chemical concepts that are essential to understanding the relationship between molecular structure and molecular polarity (List 1). We also include a discussion of organic shorthand notation and introduce several relevant functional groups that will be important when students evaluate complicated molecules like pesticides and industrial chemicals later in the module. After completion of the first three concepts in List 1, students are expected to be capable of the following: identification of IMFs in a molecule; identification of structural elements that contribute to the polarity of a molecule; and determination of relative polarity between pairs of chemical structures or among homologous series of structures. The last chemical concept introduced is the idea that substances with similar polarities are attracted to one another at the molecular level (“like dissolves like”). This is a critical concept that provides an entryway into a host of environmental applications. At this point, given molecular structures, students can predict relative polarities between pairs of molecules (such as a pesticide and its degradation product, or two different pesticides). They can also predict the relative solubility (high or low) of an organic solute in solvents such as water, fat, gasoline, et cetera.
1. Charge separation in molecules Electronegativity (if not covered previously) Polar covalent bonds Molecular polarity 2. Attractions between opposite charges Dipole–dipole forces Hydrogen bonding Ion–dipole forces Water as a solvent for ionic materials Instantaneous, temporary charge separation London dispersion forces 3. Structural elements associated with charge separation Organic shorthand notation -OH, COOH
One of the most important aspects of environmental chemistry is the determination of a substance’s location once it is released into the environment. Environmental partitioning is based on the principle of “like dissolves like” and therefore, the partitioning behavior of a substance can be evaluated if the polarity of the substance and the polarity of the different environmental compartments are known. After completion of the previous segment, students know how to evaluate the polarity of molecules, thus the only information that they require to predict environmental partitioning is the nature of polarity in environmental media. The environment can be broken down into a number of compartments, such as water, soil, sediment, biota, and air. Water is obviously a polar compartment; however, when determining the partitioning of organic chemicals, the behavior of soil and sediment is dominated by the organic fraction of the compartment. The organic matter in these compartments is predominantly nonpolar in nature. Biota are also heterogeneous mixtures of chemicals, however, in terms of partitioning their behavior is dominated by the lipid content of the organism. Because lipid is nonpolar, biota also serve as a nonpolar compartment. It may seem that the atmospheric compartment does not fit into this model. Unlike condensed-phase compartments, the interactions between atmospheric gases and organic molecules are negligible and do not control the ability of a molecule to enter the atmosphere. However, atmospheric partitioning is related to the magnitude of intermolecular attractions, one measure of which is vapor pressure. Thus far, students can predict where a substance is likely to accumulate in the environment based on the predicted polarity of the substance. For example, if students are given the structure of the pesticide p,p´-DDT they should be able to predict that it is a nonpolar substance that will partition into soil, sediments, and biota and that it will be largely absent from the aqueous compartment. This prediction can be verified by obtaining literature data on actual residue analyses that confirm that DDT has a low solubility in water and is instead found in association with organic matter in soils, sediments and biota (6). It is important to note that the conceptual framework built throughout this module is appropriate for describing the partitioning behavior of neutral organic molecules. Processes such as ion exchange also involve the properties of solutes and particulate phases; however, the chemistry of ion exchange cannot be adequately explained using intermolecular forces and the concept of “like dissolves like” (7). It is also important to note that solubility and partitioning are equilibrium processes that involve both enthalpy and entropy terms. While “like dissolves like” forms the basis of a conceptual model that successfully describes many partitioning phenomena, that concept alone is inadequate for more advanced considerations of the driving factors behind solubility. Quantitative Environmental Partitioning
-phenyl groups, alkyl groups 4. “Like dissolves like” List 1. Chemical concepts relating molecular structure to molecular polarity in Introduction to Environmental Chemistry.
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Qualitative Environmental Partitioning
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Up to this point the module has been entirely qualitative. While students can make valid predictions at the qualitative level, there are several relevant ways in which quantitative
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Chemical Properties Molecular mass Water solubility Vapor pressure log Kow Melting point Temperature for above data Mass of chemical emitted into environment Environmental Properties Size of environmental compartments: air, water, soil, sediment, suspended sediment, fish, and aerosol Organic C content of soil and sediments Lipid content of fish Densities of each environmental compartment
List 2. Input parameters for the Level 1 computer models.
aspects of polarity can be easily incorporated. One important measure of a substance’s polarity is a partition coefficient, particularly Kow, the octanol–water partition coefficient. The Kow is obtained by equilibrating a substance between 1octanol and water then determining the equilibrium concentration in each phase (Kow = Co兾Cw). 1-Octanol has similar solvent properties to lipids in biota and humic matter in soils (8), which makes the Kow particularly useful for predicting partitioning in these media. The Kow is a quantitative measure of partitioning behavior that is related to the polarity of a substance. Incorporating Kow into the module allows students to go beyond relative comparisons of polarity based on their evaluation of chemical structures and instead gives them a quantitative distribution of polarity with which they can refine their partitioning predictions. In addition, by evaluating Kow values for a series of chemicals, students can improve their ability to predict relative molecular polarities based on chemical structures alone. Other partition coefficients that could be incorporated into the module include the Kom and Koc, both of which are used to determine partitioning into solid phases based, respectively, on the organic matter (om) or organic carbon (oc) contents of the solid (Kom = Com兾Cw; Koc = Coc兾Cw) (9).
Quantitative estimates of partitioning can also be obtained using a computer model that simulates distribution in the environment based on the physical parameters of a specified chemical. The Level 1 model (10), developed by Trent University, determines equilibrium partitioning based on calculated fugacities (11). The model allows the user to specify the chemical to be modeled as well as the size and composition of the environmental compartments into which the chemical is released (List 2). The Canadian Environmental Modelling Centre makes the model freely available on the Internet (12). The model output can be displayed in a diagram that shows each of the compartments pictorially along with the interconnections between compartments and the quantity of chemical in each compartment at equilibrium. The quantity is given in three different ways: mass; percent of total mass released; concentration in the compartmental medium (ng L᎑1, mg kg᎑1, etc.). The diagrammatic output makes this model particularly accessible for nonscience students and helps to bridge the gap between the quantitative output and a conceptual understanding of the overall partitioning process. Examples Continuing with the example of DDT mentioned earlier, using the default conditions of the model, the distribution of DDT in the modeled environment can be used to validate the qualitative predictions made by students (Table 1). In this case, the concentration of DDT in the solid phases is highest and is proportional to the quantity of organic carbon in each compartment. The concentration in water is low (as expected for a nonpolar molecule with a high Kow) and the concentration in the air is low (as expected for a molecule with a low vapor pressure). The model can also be used for comparative experiments, such as evaluating the effects of substitution on a series of chlorinated benzenes (Table 2) or determining differences in distribution between the herbicide atrazine and its degradation product, hydroxyatrazine (Figure 2). In the case of the chlorinated benzenes, students can see the interplay between decreasing vapor pressure (less in the air) and increasing Kow (more in the soil, sediment, and biota) in the series. In the case of atrazine and hydroxyatrazine, students should be able
Table 1. Modeled Distribution of DDT Using Default Parameter in Level 1 Compartment/ (Conc. Unit) Air/(ng m᎑3)
Quantity of DDT in Compartment Mass/kg
Concentration
32.2
0.33
0.0332
29.4
0.29
0.0294
97625.0
4.25
97.6252
69.6
0.35
0.0696
Sediment/(ng g᎑1)
2169.0
9.04
2.1694
Suspended Sediment/(ng g᎑1)
67.8
45.2
0.0678
5.5
27.6
0.0055
᎑3
Aerosol/(ng m ) ᎑1
Soil/(ng g ) Water/(ng g᎑1)
Fish/(ng g᎑1)
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H
Mass Percent (%)
Cl N
O
N
N
N
N
H
atrazine
N
N
H
H
N N
N H
hydroxyatrazine
Figure 2. Structures of the herbicide atrazine and its degradation product hydroxyatrazine.
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to evaluate the structures of these two chemicals and determine that the degradation product is more water-soluble owing to the substitution of a hydroxyl group into the structure. Given the appropriate physical properties students can model the behavior of each chemical separately and then compare and explain the output for the two substances. Results can also be compared against data from regulatory agencies or the primary literature (13, 14). Several Web sites have proven useful for obtaining physical properties for a variety of substances (15, 16), however it is important to note that physical properties for less commonly investigated substances like pesticide metabolites may be difficult to obtain from readily available databases and may require searching the primary literature Discussion After completion of this segment of the module, students can interpret the output of a model like Level 1 and explain how the distribution patterns are related to the chemical structure of the substance. They can also understand the input parameters and explain how properties such as Kow and vapor pressure relate to chemical structure as well as partitioning in the environment. In the case of compounds with very high Kow values, students may correctly predict that such compounds will be found in nonpolar compartments such as lipids, sediments, or soils. However, it is important to note that the definition of Kow implies that the quantity of the substance that will be found in water is not in fact zero. While the quantity in the water may be negligible for the purposes of describing environmental partitioning, the toxicological implications of these low concentrations may be of great importance, as in the case of a substance that has significant toxicological impacts even at low doses. Additional Applications The three segments described above can serve as an introduction into a variety of other applications involving environmental chemistry. In the course at Towson University, partitioning is followed by a discussion of toxicology. Xenobiotics must cross membranes to reach sites of action in organisms. Therefore the ability of an organic toxicant to cross the nonpolar lipid bilayer of a membrane is directly related to the polarity of the substance. Due to the concept of
“like dissolves like”, nonpolar chemicals cross the lipid bilayer most readily (17). Also, the final distribution of a toxicant within an organism (blood versus fat) is a function of the substance’s polarity as well. Distribution is also related to the phenomena of bioaccumulation (increase in concentration in comparison to an environmental medium) and biomagnification (increase in concentration along a food chain). Nonpolar substances primarily pose a risk for bioaccumulation and biomagnification because accumulation of organics occurs in the fat, which has low metabolic activity and can be conserved over long periods. Groundwater contamination and the transport of xenobiotics by groundwater are also related to polarity. Only relatively polar substances can percolate through soils to reach groundwater without adsorbing to soils, so given the concepts in the first two segments of this module, students should be able to determine what kinds of substances pose a risk for groundwater contamination. Student Response and Performance On examination questions and laboratory reports related to this module, students had an average performance of 83% and 87% in fall 2002 and spring 2003, respectively, in the course at Towson University. Students were able to accomplish the goals of the module and successfully make predictions about polarity, solubility, and partitioning of substances based on chemical structures. Students were also able to easily manipulate the Level 1 computer model and make the appropriate interpretations of the input and output. While performance was good, student engagement was moderate. To some extent, students did not appear to appreciate the depth to which this module allowed them to participate in environmental chemistry. As mentioned earlier, the majority of students enrolled in the Towson University course are fulfilling general education credit. This is an audience that is frequently difficult to engage. In the future, we will include more case studies to increase the ties between the conceptual framework of the module and real world applications. Literature Cited 1. Beierle, T. C. Risk Analysis 2002, 22, 739–749. 2. Mullen, M. W.; Allison, B. E. J. Am. Water Res. Assoc. 1999, 35, 655–662.
Table 2. Modeled Distribution of a Series of Chlorinated Benzenes in Selected Environmental Compartments Quantity of Substance in Compartment
Compartment/ (Conc. Unit)
Benzene
Air/(ng m᎑3)
990
᎑1
Soil/(ng g )
0.295
Water/(ng g )
4.4
Sediment/(ng g᎑1)
0.00974
0.589
Fish/(ng g᎑1)
0.0297
1.8
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Hexachlorobenzene
908
4870 ᎑1
o-Dichloro benzene
13.3
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84.2 4.13
Pentachlorophenol 0.15 4.48
1.59
4.87
8.26
8.96
25.2
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In the Classroom 3. Dunnivant, F. M.; Moore, A.; Alfano, M. J.; Brzenk, R.; Buckley, P. T.; Newman, M. E. J. Chem. Educ. 2000, 77, 1602–1603. 4. Smith, Kimberly Jo; Metz, Patricia A. J. Chem. Educ. 1996, 73, 233–238. 5. Cheng, V. K. W. J. Chem. Educ. 1995, 72, 525–527. 6. Gitahi, S. M.; Harper, D. M.; Muchiri, S. M.; Tole, M. P.; Ng’ang’a, R. N. Hydrobiologia 2002, 488, 123–128. 7. Davies, G.; Ghabbour, E. A.; Steelink, C. J. J. Chem. Educ. 2001, 78, 1609–1614. 8. vanLoon, G. W.; Duffy, S. J. Environmental Chemistry: A Global Perspective; Oxford University Press: New York, 2000. 9. Dolan, E.; Zhang, Y.; Klarup, D. J. Chem. Educ. 1998, 75, 1609–1610. 10. Level I, version 2.11; Trent University: Peterborough, Ontario,
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Canada, 1999. 11. Mackay, D. Multimedia Environmental Models: The Fugacity Approach; Lewis Publ., CRC Press: Boca Raton, FL, 1991. 12. Canadiian Environmental Modelling Centre Home Page. http:// www.trentu.ca/cemc/models/models.html (accessed Nov 2004). 13. Lerch R. N.; Blanchard P. E.; Thurman E. M. Environ. Sci. Technol. 1998, 32, 40–48. 14. Kruger E. L.; Zhu B. L.; Coats J. R. Environ. Toxicol. Chem. 1996, 15, 691–695. 15. ChemFinder.com. http://chemfinder.cambridgesoft.com/ (accessed Nov 2004). 16. Online Log P Calculation. http://www.syrres.com/esc/ free_demos.htm (accessed Nov 2004). 17. Hodgson, E.; Levi, P. E. Introduction to Biochemical Toxicology, 2nd ed.; Appleton & Lang: Norwalk, 1994.
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