David G. Streets and Fang Yan, Decision and Information Sciences, Argonne National Laboratory, Argonne, IL
Technology choice is a key determinant of the emissions of many important atmospheric species (SO2, PM, BC, OC, NH3, NMVOC, etc.) that influence climate. However, technology choice is a delicate matter and is influenced not only by regulation and policy, but also by economic conditions, personal preference (especially for vehicles), and commercial competition (for industry). Current economic models cannot simulate these choices well. At Argonne National Laboratory (ANL) we realized some years ago that for these important atmospheric species it was impossible to make realistic emission forecasts without addressing technology choice head-on. ANL is presently constructing a new technology driver model to: (a) quantify the linkage of technology choice in each economic sector to economic, energy, and policy drivers; (b) test the emissions outputs from the model within the GU-WRF/Chem air quality and climate simulation model; and (c) explore the policy implications of the resulting environmental impacts. We believe that it is necessary to examine technology development quantitatively within the framework of a macroeconomic model or as a stand-alone tool driven by macroeconomic model outputs, in order to make reliable forecasts of atmospheric species that will influence climate change in the future. We assert that such a model can be made sensitive to a wide range of policy measures and other factors that fundamentally influence technology choices, in order to provide a tool to test the effects of these policy measures on future emissions in an integrated way (including greenhouse gases, agricultural emissions, and species of concern to local and regional air quality). It is our belief that climate change and air pollution can be co-mitigated through emission reductions under carefully-selected future technology and policy choices. To test our hypotheses, we will apply the model to generate forecasts of 2050 emissions under a variety of alternative policy futures that will be more advanced and reliable than anything available today.