University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2004 Predicting Air Quality Near Roadway Intersections Through The Applicat Brian Kim University of Central Florida Part of the Environmental Engineering Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Doctoral Dissertation (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Kim, Brian, "Predicting Air Quality Near Roadway Intersections Through The Applicat" (2004). Electronic Theses and Dissertations, 2004-2019. 200. https://stars.library.ucf.edu/etd/200 PREDICTING AIR QUALITY NEAR ROADWAY INTERSECTIONS THROUGH THE APPLICATION OF A GAUSSIAN PUFF MODEL TO MOVING SOURCES by BRIAN Y. KIM B.S. University of California at Irvine, 1990 M.S. California Polytechnic State University at San Luis Obispo, 1996 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Civil and Environmental Engineering in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida Fall Term 2004 ABSTRACT With substantial health and economic impacts attached to many highway-related projects, it has become imperative that the models used to assess air quality be as accurate as possible. The United States (US) Environmental Protection Agency (EPA) currently promulgates the use of CAL3QHC to model concentrations of carbon monoxide (CO) near roadway intersections. This model uses steady-state and macroscopic methods to model the physical phenomena (e.g., emission rates, atmospheric dispersion, etc.) occurring at intersections. These methods are not straightforward and unintuitive for the users. Therefore, this project investigated the possibility of developing a model that is theoretically more realistic and flexible than CAL3QHC. The new model entitled, Traffic Air Quality Simulation Model (TRAQSIM), uses a microscopic approach by modeling vehicle movements and dispersion in a simulation environment. Instead of steady-state plume equations used in the CAL3QHC model, TRAQSIM uses a discrete puff methodology that can be used to model time-based dispersion of pollutants. Most of the components incorporated into TRAQSIM have been drawn from existing methodologies and therefore, are not new. However, the combination of these different methods into a single integrated model is new and presents a novel approach to such a model. Initial verification and sensitivity/trend studies of the model indicate that TRAQSIM uses reasonable/realistic traffic parameters and behaves intuitively correct. A validation study showed that TRAQSIM produces good results when compared to actual measured data with an overall R2 value of 0.605 for 11 scenarios comprising 264 data points. Although most statistical parameters showed CAL3QHC agrees better overall with measured data (R2 value of 0.721), the comparisons were mixed on a scenario-by-scenario basis; that is, CAL3QHC showed better ii results for 6 scenarios and TRAQSIM showed better results for 5 scenarios. Additional tests with larger datasets, which were beyond the scope of this work, could be conducted to obtain more definitive conclusions and allow further development of TRAQSIM. While CAL3QHC is a mature model that has been developed over many years, TRAQSIM is new and has much more potential for improvement. The physical parameters used in TRAQSIM allow it to be more directly (more logically) improved than the approximations used in CAL3QHC. In addition, although the fundamental-level modeling in TRAQSIM make it a more complex model internally, it is much more intuitive for the user to understand and use. iii To my parents and brother, Who have supported me in all the things I have done in my life To my wife’s parents, Who have given me my soul mate To my daughter, Rachel Who has given me such joy To my wife, Linda Whom I fall in love with each day iv ACKNOWLEDGMENTS I would like to express my gratitude to my advisor, Dr. Roger L. Wayson, without who’s guidance I could not have completed this degree. I am forever grateful for all of the financial and moral support that he has provide over the years. And I can truly say that I would not be where I am today without him. I would also like to thank the other members of my committee: Dr. C. David Cooper for the best air quality book ever published and for setting an example of quality work; Dr. Linda C. Malone for the best statistics course I ever took; Dr. Essam Radwan for his great departmental advice and encouragement; and Mr. Gregg G. Fleming for his generosity in the workplace and who’s work ethic I try to emulate. I also need to officially acknowledge my parents and brother. Without their support and nurturing through the years, this degree would not have been achievable. They have earned the right to call the degree theirs. And finally, my wife Linda has to be acknowledged. Her support and endurance have given me the strength and inspiration to complete this dissertation. She has definitely been my better half. v TABLE OF CONTENTS ABSTRACT.................................................................................................................................... ii ACKNOWLEDGMENTS .............................................................................................................. v TABLE OF CONTENTS...............................................................................................................vi LIST OF FIGURES ....................................................................................................................... xi LIST OF TABLES....................................................................................................................... xiv LIST OF TABLES....................................................................................................................... xiv LIST OF ACRONYMS/ABBREVIATIONS.............................................................................. xvi LIST OF ACRONYMS/ABBREVIATIONS.............................................................................. xvi CHAPTER ONE: INTRODUCTION............................................................................................. 1 1.1 Problem Statement................................................................................................................ 1 1.2 Objective............................................................................................................................... 3 1.3 Overview of New Model ...................................................................................................... 4 1.4 Organization.......................................................................................................................... 5 CHAPTER TWO: LITERATURE REVIEW................................................................................. 6 2.1 Comparable Intersection Air Quality Models....................................................................... 6 2.1.1 CAL3QHC ..................................................................................................................... 6 2.1.2 CALINE4....................................................................................................................... 8 2.1.3 TEXIN2-4 ...................................................................................................................... 9 2.1.4 FLINT ............................................................................................................................ 9 2.1.5 HYROAD 1.1 .............................................................................................................. 10 2.2 Emission Factor Models ..................................................................................................... 11 vi 2.2.1 MOBILE ...................................................................................................................... 11 2.2.2 EMFAC........................................................................................................................ 14 2.2.3 Colorado Department of Highways (CDOH) Method................................................. 14 2.2.4 CALINE4’s Modal Emissions Model.......................................................................... 16 2.2.5 Virginia Tech’s Microscopic Emissions Model .......................................................... 17 2.2.6 Georgia Tech’s MEASURE model.............................................................................. 18 2.2.7 University of California at Riverside’s (UCR’s) Comprehensive Modal Emissions Model (CMEM) .................................................................................................................... 19 2.3 Traffic Simulation Models.................................................................................................. 20 2.3.1 Urban Street Network Simulation: NETSIM.............................................................. 20 2.3.2 Freeway Network Simulation: FRESIM..................................................................... 21 2.4 Atmospheric Dispersion Models......................................................................................... 22 2.4.1 AERMOD ...................................................................................................................