Background
Chemical exposure models play an important part in environmental chemistry and chemical risk assessment by helping us assess the fate, i.e. transformation and transport, and distribution of chemicals across different environmental media after their emission. Models serve as integrative platforms to synthesize our understanding of chemical and environmental processes, with data on physico-chemical properties of different substances and information on their emission patterns, into forecasts of exposure levels in air, water, soil, sediment and sometimes also in biota and humans. Comparing such predicted environmental concentrations (PECs) with toxicity thresholds (e.g. predicted no-effect concentrations, PNECs) enables chemical risk assessment.
Model building blocks
Most models used to estimate environmental exposure to chemicals are based on the multimedia mass-balance modelling approach. In multimedia mass-balance models environmental media such as air, water, soil and sediments (in some cases also vegetation, biota, etc.) are treated as discrete, but interconnected compartments (well-mixed boxes). A set of coupled mass-balance equations track the change in chemical concentration over time as a function of all input and output processes adding or removing the chemical from a given compartment. Inputs are governed by emissions from (one or multiple sources) and transport into a given compartment (diffusive or advective transport, e.g. via water flowing from upstream in a river). Outputs are a combination of degradation (or transformation) processes and transport out of a compartment.
With such mass-balance equations models of a wide range of complexity can be built, by connecting as many compartments asdesired, each with its own mass-balance equations. From the simplest 1-box models (e.g. representing the water compartment of a lake), or evaluative “Unit World” models to spatially-explicit global-scale models with hundreds or even thousands of connected boxes (and mass-balance equations). The resulting system of differential equations can be solved either in a time-resolved manner or at steady-state (provided all rate constants describing the fate processes follow (pseudo)first-order kinetics). Outputs are time-resolved or steady-state concentrations of the chemical of interest in all model compartments.
Model inputs
On the chemical side, most environmental exposure models require degradation half-lives (in air, water, soil and ideally other compartments of interest) and partition coefficients, as inputs. Partition coefficients are very important, as they indicate the preference of a chemical for different environmental phases and e.g. the proportion of sorbed vs. free chemicals in soils, sediments or on aerosol particles in the air (which in turn impacts degradation and transport processes). The Kow (octanol-water partition coefficient) and Henry’s Law constant (air-water partitioning) are the most used partition coefficients in exposure modelling and are often used in the models to estimate partitioning between specific environmental phases empirical partition coefficients are not available (e.g. by estimating Kd or Koc values, as well as organic matter-air partitioning).
Recorded Lecture
Antonia Praetorius who is based at the University of Amsterdam where she specialises in the environmental transport and fate of chemicals, provides a general introduction to environmental exposure modelling.
Key Reading
Wania, F., and D. Mackay. “The Evolution of Mass Balance Models of Persistent Organic Pollutant Fate in the Environment.” Environmental Pollution 100, no. 1 (1999): 223–40. https://doi.org/10.1016/S0269-7491(99)00093-7.
MacLeod, Matthew, Martin Scheringer, Thomas E. McKone, and Konrad Hungerbuhler. “The State of Multimedia Mass-Balance Modeling in Environmental Science and Decision-Making.” Environmental Science & Technology 44, no. 22 (2010): 8360–64. https://doi.org/10.1021/es100968w.
Zhu, Ying, Oliver R. Price, Shu Tao, Kevin C. Jones, and Andy J. Sweetman. “A New Multimedia Contaminant Fate Model for China: How Important Are Environmental Parameters in Influencing Chemical Persistence and Long-Range Transport Potential?” Environment International 69: 18–27. https://doi.org/10.1016/j.envint.2014.03.020.
Quik, J. T. K., J. A. J. Meesters, and A. A. Koelmans. “A Multimedia Model to Estimate Environmental Fate of Microplastic Particles.” Science of The Total Environment 882: 163437. https://doi.org/10.1016/j.scitotenv.2023.163437.