WASHINGTON UNIVERSITY
SEVER INSTITUTE OF TECHNOLOGY
DEPARTMENT OF MECHANICAL ENGINEERING
THE RETRIEVAL OF POLLUTANT EMISSION FIELDS
FROM AMBIENT CONCENTRATION AND PRECIPITATION
CHEMISTRY DATA
By
Bret Schichtel
Prepared under the direction of Professor Rudolf B. Husar
A thesis presented to the Sever Institute of
Washington University in partial fulfillment
of the requirements of the degree of
DOCTOR OF SCIENCE
January, 1996
St. Louis, Missouri
1.1.1 Source Type Identification Using Receptor Models
1.1.2 Source Region Identification Using Airmass Histories
1.1.3 Source Field Reconstruction using Dispersion Models
Chapter 2 Physical Principles of the General Source Receptor Relationship
2.1 Lagrangian Formulation of the Source Receptor Relationship
2.1.2 Kinetic Species
2.1.3 Discretisation of the SRR
2.1.4 Transfer Matrix
2.2 Matrix Representation of the SRR
2.3 Reducing the SRR Resolution
2.3.1 Reducing the Receptor Volume Resolution
2.3.2 Reducing the Source Volume Resolution
2.3.3 Reducing the Particle Age Resolution
2.3.4 Reducing the Receptor Time Resolution
2.3.5 Reducing the Number of Emission Values in the Matrix SRR
2.4 Source and Receptor Oriented Expressions of the SRR
2.5 Input Parameters to the SRR
2.6 Effects of Nonlinear Kinetics on the SRR
Chapter 3 Regional Scale Pollutant Simulation: The CAPITA Monte Carlo Model
3.1.1 Monte Carlo Approach
3.1.2 Data Flow
3.2.1 Transport Simulation
3.3 Chemical Transformation and Removal Kinetics
3.3.1 Approach
3.4 Retrieval of Kinetic Rate Coefficient Equations for the SO2 - SO42- system over the Eastern US
3.4.1 Data sets
3.4.2 The Physical Formulation of the SO2 - SO42- Rate Equations
3.4.3 Tuning of Rate Coefficients
3.4.4 Comparison of Simulated SO42- Concentrations and Wet Deposition Rates to Observed Data
3.5 SO42- Surface Concentration and Wet Deposition Transfer Matrices
Chapter 4 Inversion of the Source Receptor Relationship
4.1.1 The General Inverse Problem
4.1.2 Solution Techniques
4.2.1 Robust Inversion by M-Estimates
4.3 Ill-conditioning of the Source Receptor Relationship
4.3.1 Smoothing
4.3.2 Resolution of Source Space
4.3.3 Resolution of Receptor Space
4.3.4 Examples of Ill-Conditioning
4.4 Implementation of the Inversion Algorithm
4.4.1 Influence of Eigenvalues on the solution
4.4.2 Robust Inversion of the Source Receptor Relationship
4.5 Retrieval of Seasonal Emission Fields
4.5.1 Retrieval of Seasonal SO2 Emission Fields
4.5.2 Retrieval of Seasonal NH3 Emission Fields
4.5.3 Retrieval of Seasonal NO2 Emission Fields
Chapter 5 Summary and Conclusions
Appendix B Metrics of the Inversion Performance for the Retrieval of Seasonal NH3 Emission Fields
Appendix C Metrics of the Inversion Performance for the Retrieval of Seasonal NO2 Emission Fields