2006 Progress Report: Air Quality, Emissions, Growth, and Change: A Method to Prescribe a Desirable FutureEPA Grant Number: R831838
Title: Air Quality, Emissions, Growth, and Change: A Method to Prescribe a Desirable Future
Investigators: Chang, Michael E. , Akhtar, Farhan , Carpenter, Ann , Chapman, James , Chirico, Jennifer M , Noonan, Douglas , Russell, Armistead G.
Institution: Georgia Institute of Technology , Lawrence Frank and Company, Inc.
EPA Project Officer: Chung, Serena
Project Period: December 1, 2004 through November 30, 2007 (Extended to November 30, 2009)
Project Period Covered by this Report: December 1, 2005 through November 30, 2006
Project Amount: $649,999
RFA: Regional Development, Population Trend, and Technology Change Impacts on Future Air Pollution Emissions (2004) RFA Text | Recipients Lists
Research Category: Global Climate Change , Climate Change , Air
At the scale of 50 years, we postulate that emissions and the activities, processes, and infrastructure associated with them, are pliant – that is, they are adaptable. Rather than trying to predict how emissions will change in the future and what impact they will have on future air quality (and hoping that the impact is beneficial), we propose a method in which we define a desirable air quality state and then derive the emissions and activity profiles required to achieve it. Our objectives then are threefold: 1) to develop and apply at the regional community scale a reasonable method for defining one or more desirable future air quality states; 2) to develop and demonstrate an “inverse” approach that utilizes the future desired air quality to derive the emissions, activities, processes, and infrastructure that are needed to achieve the desired future; and 3) to identify the types and amounts of land use modifications, technology advancements, and other changes that will be required to transform or morph the present emissions scenario into the future desired emissions scenario.
During this second project year, we defined one specific future air quality state based on economic criteria (and continue to work on others), developed the computer code that will execute the air quality model in an inverse mode, began running evaluations to insure that the code is functioning properly, and prepared for the third phase of the project to identify tangible urban characteristics that meet the inverse-model-derived emissions constraints. In anticipation of the final phase of the project, we conducted analyses that compared urban form metrics at the scale inherent to the air quality model to scales inherent to the SMARTRAQ database – the latter being the database we have available in the Atlanta area that relates urban form to emissions. This furthers our project goal of inverse-modeling the ideal air quality for Atlanta in 2050 by providing the computational means to derive emissions necessary to achieve the objective air quality state, and to relate those emissions to real, and tangible urban forms and household characteristics. Beyond this project, this work further contributes to the understanding of land use, emissions, and air quality in the Atlanta area simply by making the connections between urban form, household travel characteristics, and emissions (i.e. what SMARTRAQ is), with emissions, air quality, and the physical environment (i.e. what Models-3 does).
Project year 3 first will be dedicated to completing the second objective: to develop and demonstrate an “inverse” approach that utilizes the future desired air quality to derive the emissions, activities, processes, and infrastructure that are needed to achieve the desired future.” As reported here, we have developed the computer codes and programs that will be used to run an existing and validated air quality model application (CMAQ) for the Atlanta, Georgia metropolitan area in an inverse mode, and are now in the process of testing those codes. The culmination of this phase will be the inverse model run that uses the future “desired” air quality state that was determined in phase I (as well as any subsequent and interesting scenarios we can develop). This will lead to the final phase of the project and the balance of project year 3 in which emissions are related to specific types of neighborhoods and communities, and the amenities and characteristics inherent to them that fit within the constraints of those emissions. The chief challenge at this point is finding common ground between the emissions and air quality model and the SMARTRAQ database. Finally, we will continue the process of communicating results and methods to others in the community.