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Intermittent rainfall in dynamic multimedia fate modeling.

E G Hertwich1

  • 1Institute for Product Design and Industrial Ecology Program, Norwegian University of Science and Technology, Kolbjørn Hejes vei 2b, 7491 Trondheim, Norway. hertwich@altavista.com

Environmental Science & Technology
|May 16, 2001
PubMed
Summary

Steady-state models underestimate air pollutant levels with low Henry's law constants. A new dynamic model accurately predicts concentrations under intermittent rain, improving exposure assessments.

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Area of Science:

  • Environmental Chemistry
  • Environmental Modeling
  • Atmospheric Science

Background:

  • Steady-state multimedia models (Level III fugacity models) underestimate air concentrations for chemicals with low Henry's law constants.
  • This underestimation is due to the assumption of steady rainfall, leading to errors in spatial range and inhalation exposure estimations.

Purpose of the Study:

  • Develop a dynamic multimedia model for pollutant fate under intermittent rainfall conditions.
  • Calculate the time-varying pollutant concentrations in various environmental compartments.
  • Address the limitations of steady-state models in accurately predicting environmental concentrations.

Main Methods:

  • Developed a dynamic model of pollutant fate incorporating intermittent rainfall.
  • Utilized a novel, mathematically efficient approach based on the convolution of solutions to the initial conditions problem.

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  • Applied this dynamic modeling approach to intermittent rainfall scenarios for the first time.

    • Main Results:

    • The dynamic model accurately calculates the time profile of pollutant concentrations.
    • Time-averaged pollutant concentrations under intermittent rainfall can be approximated by a weighted average of steady-state concentrations (with and without rain).
    • Demonstrated the effectiveness of the dynamic approach for chemicals with low Henry's law constants.

    Conclusions:

    • Dynamic multimedia models are essential for accurate pollutant fate assessment under variable environmental conditions like intermittent rainfall.
    • The developed model provides a more realistic estimation of air concentrations and potential exposures.
    • The findings improve the reliability of environmental models for risk assessment and regulatory purposes.