The State of Multimedia Mass-Balance Modeling in Environmental

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Environ. Sci. Technol. 2010, 44, 8360–8364

The State of Multimedia Mass-Balance Modeling in Environmental Science and Decision-Making MATTHEW MACLEOD* MARTIN SCHERINGER* ETH Zurich, Switzerland THOMAS E. MCKONE Lawrence Berkeley National Laboratory, University of California Berkeley, Berkeley, California KONRAD HUNGERBUHLER ETH Zurich, Switzerland

Are multimedia models dinosaurs in the modern world?

The Origin and Evolution of Mass-Balance Models One of the fundamental challenges of environmental chemistry is to understand and characterize levels of chemical pollutants in air, water, soil, and vegetation, and to estimate chemical mass flows between these different media, and between geographical regions. This is particularly important for assessing the environmental hazard and risks posed by chemical products. Tens of thousands of chemicals need to be assessed with more added every year, and their properties span many orders of magnitude of vapor pressure, water solubility, and degradability. Confronting this challenge requires a quantitative modeling approach that describes the environmental fate of chemicals, including sources, phase partitioning, transformation and degradation, and transport. In 1978, Baughman and Lassiter (1) pioneered the development of such models for the aquatic environment. Their ideas were shortly thereafter adapted and extended by Mackay and Paterson into a family of four “levels” of multimedia mass-balance models with different sets of simplifying assumptions that describe the entire system of a chemical and the environment (2-4). 8360

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The multimedia mass-balance models advocated by these pioneers provided a powerful framework for understanding the behavior of chemicals in the environment. The massbalance approach adopted from the field of chemical engineering focused attention on how chemical properties determine environmental behavior by requiring that air, water, soils, and even the tissues of animals be viewed only in terms of their capacity to hold a chemical pollutant. The description of the environment as a “unit world” made it clear that the environment is finite, and focused attention on how the properties of chemicals determine their behavior as environmental pollutants. Multimedia mass-balance models at different levels of detail provided a “tool box” that could be applied to different types of problems, and a logical and integrated framework for introducing environmental chemistry concepts to students. Therefore, it is not surprising that in subsequent decades these techniques proliferated and spawned an entire discipline dedicated to modeling environmental contaminants in multimedia environments (5). In the ensuing three decades, multimedia mass-balance models played an important role in the scientific study of the behavior of chemicals in the environment. For example, the models supported the development of the concepts of persistence (P) and long-range transport (LRTP) that are now key hazard indicators used in chemical assessment (6). Models of the uptake of chemicals by fish from water and food were instrumental in elucidating the mechanisms of bioconcentration and biomagnification (7, 8). Global-scale multimedia models illustrated the potential that certain persistent pollutants could migrate to, and accumulate in, polar regions (9-11). Multimedia models provided a basis for quantifying cumulative, multipathway exposure to pollutants that originate from contaminated air, water, and soil (12). Mass-balance models were employed to characterize the relative importance of local and distant sources of contaminants (13), to identify environmental and chemical processes that control levels of pollutants (14), and, they motivated empirical and theoretical studies to improve knowledge of the physicochemical properties and degradability of commercially important chemicals and byproducts of industry and energy production (15, 16). At the same time, multimedia mass-balance models were adopted as decision-support tools by industry and governments. The EU System for the Evaluation of Substances (EUSES) was built upon a multimedia chemical fate model (17). In the U.S., the California Environmental Protection Agency sponsored the development of CalTOX, a multimedia contaminant fate and exposure model for assessing hazardous waste sites (18). The U.S. Environmental Protection Agency (EPA) Center for Exposure Assessment Modeling (19) developed a number of models designed for use in decisionmaking. Later, multimedia models were incorporated into the EPA’s PBT Profiler (20) and the EPI Suite collection of exposure assessment tools (21). In the Great Lakes region of North America, multimedia models are used as decisionsupport tools to develop strategies to reduce levels of highpriority contaminants (22, 23). 10.1021/es100968w

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Published on Web 10/08/2010

A remarkable feature of the development of the field over the last three decades is that many of the assumptions underlying multimedia mass-balance models have not significantly changed. Unit world models similar to the ones described by Mackay and Paterson are used every day around the world by scientists and regulators. More detailed models introduce spatial differentiation by linking unit world models with flows of air and water estimated from long-term averages (24). Wania and Mackay (25) argued that the unit world structure and generally low spatial and temporal resolution of multimedia models are appropriate for describing the behavior of persistent contaminants in the environment. However, there are limitations to this approach, and these have been identified in particular by developers of contaminant fate and transport models that describe the temporal and spatial variability of the circulation of the atmosphere and oceans with high resolution (26). Increasingly, such chemistry transport models (CTMs) are being developed or adapted to describe levels and transport pathways for trace environmental contaminants, a field that was previously dominated by the multimedia approach (for example, refs 26-29). In some cases, CTMs have been employed to address aspects of chemical pollution that cannot be readily addressed by models based on the unitworld approach, such as how persistence and long-range transport of substances depends on the specific time and location of release (30), and how episodic transport events can deliver pollutants to remote ecosystems (31). Against this backdrop, our goal is to take stock of the present state of the field of multimedia mass-balance modeling and to look toward its future. We do this by first briefly reviewing the conceptualization and design of multimedia mass-balance models in contrast to the more highly resolved and more detailed chemical fate and transport models that have been developed in recent years. We propose that all contaminant fate models can be viewed as repositories of knowledge and understanding about chemicals in the environment. We then move on to address both the scientific and decision-support roles of modeling and examine several questions: What contributions can be made by models in the modern science of environmental chemistry? What is the role of models in decision-making, and how can they be more effectively used? What are the future directions for model development, and what role will be played by multimedia mass-balance models in the future?

Model Conceptualization and Design Before addressing these questions, it is useful to review the characteristics of multimedia mass-balance models, and compare them to CTMs. On a technical level, multimedia mass-balance models are a system of simultaneous massbalance equations, with one equation for the mass of each chemical species of interest in each environmental compartment included in the model. A key feature of multimedia mass-balance models is that equations are formulated only for the mass balance of the chemical (or chemicals) of interest. The focus of the model is thus placed squarely on the pollutants, and the environment is treated in many respects as having fixed characteristics. For example, flows of air and water that carry chemicals are represented in multimedia mass-balance models by mass transfer coefficients that appear as constant coefficients in the mass-balance equations. These transfer coefficients are estimated from spatial and temporal averages of air and water flows that are prescribed input values to the model. In contrast, CTMs describe air and water flows with a much higher degree of detail. In some cases dynamic equations are used to calculate atmosphere and ocean circulation patterns online, at temporal scales less than a day, and spatial scales of tens or hundreds of kilometers.

The differences between multimedia mass-balance models and CTMs reflect different decisions made during the model conceptualization and design phase about how much emphasis to place on describing different aspects of the system. No model can be a true representation of the real system, and optimal model performance can only be achieved by balancing increasing the model’s level of detail against increasing the demand for input parameters that are always uncertain (32). Multimedia models strike this balance by focusing on a quantitative accounting of the mass fluxes, inventories, and equilibrium status of chemical pollutants in a defined environmental system. Both types of models are usually applied to describe field data without calibration. Especially for persistent chemicals, multimedia mass-balance models have been shown to provide very good agreement between model results and field data (for a review, see 33). In at least one study, this agreement was found to be better than that obtained with a CTM (34). Thus, although CTMs devote high computational effort to solving dynamic equations of air and water flow, this does not guarantee that they provide a more accurate description of contaminant fate than a multimedia massbalance model.

Contaminant Fate Models As Repositories of Knowledge and Understanding Multimedia mass-balance models are composed of equations and algorithms that are quantitative expressions of knowledge and understanding derived from theoretical and empirical studies of chemical mass transport and degradation conducted in the field and laboratory. The models are thus a framework for organizing a wide array of information and concepts into a consistent and cohesive overall picture, as illustrated in Figure 1. They can thus be viewed as repositories of knowledge and understanding about processes that determine levels of pollutants in the environment. When a model is used to describe the behavior of a chemical, this repository of knowledge is accessed. The power of multimedia mass-balance models thus lies in demonstrating the connections among different factors that determine the chemical concentrations and the rates of transport and transformation of chemicals in the environment. A recent example of multimedia mass-balance models being applied to synthesize and evaluate information about physical chemical properties, degradation rate constants, and emissions on one hand, and observations of the levels of pollution in the environment on the other is the global scale modeling of perfluorooctanoic acid (PFOA) and its precursors (35-37). This work has helped to clarify the relative contribution of direct sources of PFOA and of degradation of precursor substances to contamination of the Arctic environment. Multimedia mass-balance models also facilitate direct comparison of the relative importance of competing processes that cannot be directly measured, such as the competition between degradation by hydroxyl radicals and dilution by mixing in the atmosphere (38). Calculation of the equilibrium status of concentrations of chemical pollutants in air, water, and soil by using the fugacity concept, which was one of the core themes of Mackay’s original papers, provides insight into the likely nature of sources and sinks that cannot be gained by examining the relative concentrations alone (for example, 39). In all of these examples, massbalance models are used to organize scientific concepts and understanding into a common form in which disparate aspects can be compared.

The Role of Mass-Balance Models In Science Much of modern environmental science is concerned with the detailed study of selected aspects of the whole environVOL. 44, NO. 22, 2010 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Multimedia mass-balance models play a central role in environmental chemistry by acting as repositories of knowledge and conceptual understanding about the system of a chemical and the environment. Curved arrows illustrate the flow of information in the environmental assessment of a chemical using a mass-balance model. The quantitative framework provided by models allows the disparate aspects of the system to be assembled together into a unified description of mass fluxes and inventories of the pollutant, and compared for internal consistency. mental system, with subdisciplines segregated by environmental media. Thus, there are atmospheric scientists, oceanographers, and soil scientists, for example. Similarly, many environmental chemists study a particular class of chemical; for example, volatile organics, petroleum hydrocarbons, or pesticides; or particular phenomena, such as partitioning between the gas phase and aerosols, or pathways for chemical degradation. Such specialization in scientific work is appropriate and necessary. In contrast, however, developers of multimedia mass-balance models seek to integrate scientific knowledge about all environmental media, and to generalize and extrapolate principles of environmental chemistry across substances. It is the science of “the big picture”. This situation presents a profound opportunity for both model developers and scientists in specialized fields of study to collaborate and learn from each other. As repositories of knowledge and conceptual understanding, all types of contaminant fate models must be continuously evaluated. This is accomplished by applying models to relatively well-understood and well-characterized chemical contaminants and evaluating the model results against empirical estimates of emissions, property data, and environmental levels. In cases where model results do not agree with empirical data within acceptable limits there is evidence of a deficiency in our understanding of the system, and/or in the accuracy of the empirical data. Sensitivity and uncertainty analysis of the model can then be used to identify critical parameters or process descriptions, which may be taken up as priorities for study by more specialized scientists. In other cases, where agreement between model results and empirical data is good, confidence increases that the model is an adequate description of the real system within the domain of chemical and environmental variability represented by the case studied. With this foundation, the model and the modeler are positioned to address novel challenges posed by new chemicals or new environmental conditions. Thus, models are scientific tools for evaluating where our knowledge is adequate, and where it is incomplete, and they provide the basis for identifying where improvements in data or in mechanistic understanding derived from fundamental research would contribute to better understanding of the entire system. Although mass-balance models are repositories of knowledge about the science of environmental chemistry, this does 8362

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not mean that model development must lag behind other scientific fields. On the contrary, multimedia mass-balance models can lead scientific inquiry in new directions by acting as a platform for testing new hypotheses, for example about emissions, substance properties, and fate processes. Often, new hypotheses can be evaluated by using a model more rapidly and less expensively than by experiments, since it requires only modifying the input parameters or the model code and rerunning the model. Experiments with a model system do not create empirical knowledge, but they can guide the development of real-world experiments, and point the way toward fruitful areas of research. Thus, models can and should be used to help set the agenda for scientific work.

The Role of Models In Decision-Making Models are essential tools for informing environmental decision-making because they provide the basis to assess the impacts of alternative actions, and perform prospective hazard and risk assessment (40). To confront environmental management challenges, models are often developed without the benefit of extensive data about a particular system. For models to be effective decision-support tools, it must be possible to interrogate them for information that can be used to inform decisions. However, decisions often must be made based on model results that are difficult or impossible to evaluate against empirical data. In such cases, it is essential that the model and its results be fully understood by decisionmakers. This means understanding the model’s conceptual basis, assumptions, input data requirements, and past applications (40). In addition, results must be considered in the context of their range of uncertainty, which may be determined from evaluation of alternative scenarios or by sensitivity and uncertainty analysis. Recognizing these requirements, an expert panel convened by the U.S. National Academy of Science recently introduced parsimony as a criterion for models used in decision-making (40). They identify a parsimonious model as one that is no more complicated than is necessary to inform a decision. Parsimonious models are preferred because they are more likely to be understood by decision-makers, and therefore the model results can be more confidently used as the basis for decisions, or, where appropriate, ignored as irrelevant to the question under consideration. As an added

benefit, parsimonious models are generally not computationally intensive, which makes sensitivity and uncertainty analysis feasible and provides additional information for decision-makers. We believe multimedia mass-balance models are suitable as decision-support tools in this context because they focus first and foremost on the mass balance of the chemical itself, rather than on variable characteristics of the environment, and because they are built on the foundation of well-established and intuitive concepts such as the law of conservation of mass and thermodynamic equilibrium as a limiting state for a system. Recent examples of multimedia mass-balance models designed for use in decision-making that also embody the philosophy of parsimony are the Organization for Economic Cooperation and Development (OECD) tool for evaluating persistence and long-range transport potential of organic chemicals (41), the Risk Assessment, Identification and Ranking (RAIDAR) model (42), and the USEtox model for calculating human and ecotoxicity characterization factors in life-cycle impact assessment (43, 44).

Multimedia Models: Current State and Prospects For The Future Multimedia mass-balance models address the problem of chemical pollution in a comprehensive way by composing a complete quantitative accounting of sources, fate, and transport processes and sinks for a chemical. This is a daunting task because it is inherently multidisciplinary, and there are inevitably large uncertainties and data gaps that must be overcome. However, the success of the mass-balance modeling approach illustrates that powerful insights can be gained by quantitatively modeling the problem of environmental pollution in its entirety, including emissions, transport, and partitioning, and ultimate removal from the environment, even in the face of large uncertainties. We can identify two opposing trends in model development. One is a trend toward more detailed models with higher fidelity to the real system, driven by the availability of highly resolved environmental data, increases in computer power, and progress in atmospheric and earth sciences. The other trend is toward models that are tailor-made to specific scientific questions or decision-making problems, driven by the philosophy of parsimony and the increase in the need for scientific results as a basis for decision-making in modern society. Environmental systems can, in principle, be modeled in a highly realistic fashion by incorporating scientific understanding developed in individual disciplines such as atmospheric physics, oceanography, and soil sciences. However, at the same time it is desirable to build modelssfor both scientific and decision-support applicationssthat are only as detailed as needed to adequately address the problem under consideration. This, in turn, means there is a constant need to develop new models and modeling approaches that focus on different aspects of the system or different scientific or policy questions, and to add details to the model only up to the point that is needed. The limits of applicability of models should be clear, and they should be easily refutable by demonstrating cases where they do not adequately describe the real system. Thus, models that do not reflect all aspects of scientific understanding of every component of the system being modeled are not diminished in their worth as scientific and policy support tools. The value of a model should not be measured according to its level of detail or degree of fidelity to the real system, and highly detailed models should not be viewed as inherently superior to less detailed models. The utility of models is derived to a large extent from comprehending the behavior of the model, and then using this as

a guide to understand essential elements of the real system. Indeed, a model that is so detailed and complicated that it cannot be readily comprehended cannot be easily translated into insights or testable hypotheses about the real system. In the future, as in the past, models will be required to address a range of interdisciplinary scientific questions about chemicals in the environment. We are sure that mass-balance models at different spatial and temporal scales and with different levels of detail, including multimedia models based on the unit world approach, will continue to be essential tools in research, education, and decision support in the future. In the last 30 years, models based on these principles have accrued significant credibility by providing insights into many key problems in environmental chemistry. These tools are now well established and mature, and at our disposal to study a new generation of environmental pollutants. The principles that have been developed for mass-balance models of chemical substances also stand ready to be adapted to address emerging challenges including supporting the development of green chemistry, addressing engineered nanomaterials, which are of increasing economic importance and behave differently from the chemicals we are familiar with, and biological materials like proteins, prions, and bacteria. Therefore, 30 years after the establishment of the field, we believe multimedia environmental contaminant fate modeling remains a vibrant scientific discipline that has a central role in science and decision-making in environmental chemistry. Matthew MacLeod was formerly a lecturer at the Swiss Federal Institute of Technology (ETH) in Zurich, and is now an associate professor of environmental chemistry at Stockholm University. Martin Scheringer is a senior scientist at ETH Zurich. Thomas E. McKone is a senior staff scientist at Lawrence Berkeley National Laboratory and an adjunct professor of environmental health sciences at the University of California, Berkeley. Konrad Hungerbuhler is a professor for safety & environmental technology at ETH Zurich. Please address correspondence regarding this article to MacLeod at [email protected] and Scheringer at [email protected].

Acknowledgments Authors at ETH Zurich were supported by a grant (200020116622) from the Swiss National Science Foundation. T.E.M. was supported by a Laboratory Directed Research and Development (LDRD) grant at the Lawrence Berkeley National Laboratory, which is operated for the U.S. Department of Energy (DOE) under contract grant DE-AC02-05CH11231.

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