Development and Testing of a State-of-the-Art PMx Particulate Matter Module for Regional and Urban Air Pollution ModelsEPA Grant Number: R824793
Title: Development and Testing of a State-of-the-Art PMx Particulate Matter Module for Regional and Urban Air Pollution Models
Institution: Carnegie Mellon University
EPA Project Officer: Chung, Serena
Project Period: October 1, 1995 through September 30, 1998
Project Amount: $412,041
RFA: Air Pollutants (1995) Recipients Lists
Research Category: Air Quality and Air Toxics , Air
Description:Airborne particulate matter (PM) continues to pose serious health risks for susceptible members of the U.S. population and for sensitive ecosystems. Passage of the Clean Air Act of 1990 has created a strong interest in the mathematical modeling of the atmospheric aerosol processes and the relationship of ambient particulate concentrations to both natural and anthropogenic emission fluxes. EPA is currently reevaluating the standard for PM concentrations. This reevaluation process will probably result in a PMx mass concentration standard, where x is a diameter smaller than 10 microns. Modeling PMx concentrations requires reevaluation of the aerosol modeling techniques used in urban and regional air quality models, since fine aerosol mass is more sensitive to processes like growth, coagulation and nucleation. In addition, particles larger than x cannot be neglected in the simulations, since they compete with the remaining particles in processes like condensation and coagulation. Despite significant scientific advances in recent years, our ability to simulate atmospheric aerosol processes both accurately and efficiently has remained limited. The computational requirements of available methods for the simulation of the atmospheric aerosol size/composition distribution make them inappropriate for large scale atmospheric simulations. In some cases, the complexity of these methods is not required for satisfactory computational accuracy, but under other conditions simplifications may introduce significant errors.
The goal of this project is the development of a state-of-the-art "smart" PMx atmospheric aerosol module, that is able to internally use suitable assumptions and approximations reducing computational cost, but at the same time will provide the required accuracy for the atmospheric conditions where these approximations are inappropriate. The same model will be therefore able to simulate efficiently even the most complicated and challenging scenarios, as well as the simple cases. The key element of the modeling approach will be the accurate estimation of the errors associated with the various assumptions and approximations used in the competing modeling approaches. To achieve the modeling requirements for predicting PMx, concentrations will be systematically investigated. Our approach will be to develop a comprehensive model that is based on first principles and not on semi-empirical parametrizations. This model will be able to predict the full aerosol size/composition distribution including sulfates, ammonium, water, nitrate, organic and elemental carbon, metals and crustal elements. It will combine robustness and accuracy with computational efficiency. The project will result in new algorithms and modules for photochemical models that can be used by the scientific community in the analysis of transport and fate of atmospheric aerosols and in the regulation of atmospheric PMx concentrations.