Evaluating the design of emissions trading programs using air quality models

In order to meet the US EPA's National Ambient Air Quality Standards as set under the provisions of the Clean Air Act, states and regions throughout the United States are designing cap and trade programs aimed at reducing the emissions of the two dominant precursors for ozone, nitrogen oxides (NOx) and Volatile Organic Compounds (VOCs). While emission cap and trade programs are becoming more common, relatively few analyses have examined the air quality implications of moving emissions from one location to another (due to trading of emissions between facilities), from one sector to another (due to the use of technologies such as Plug-in Electric Hybrid Vehicles - PHEVs), and changing the temporal distribution of emissions (through emissions trading among facilities with different temporal profiles). This thesis will examine, in detail, the air quality implications of two emission cap and trade programs. The first program is a NOx trading program that covers Electricity Generating Units (EGUs) in the Northeastern United States. Results show that refining the temporal limits on this cap and trade program, by charging facilities more to emit NOx on days when ozone is most likely to form, has the potential to significantly reduce NOx emissions and ozone concentrations. Additionally, this research also shows that, for this region, the spatial redistribution of NOx emissions due to trading leads to greater ozone reductions than similar amounts of NOx emission reductions applied evenly across all facilities. Analyses also indicate that displacing emissions from the on-road mobile sector (vehicles) to the EGU sector through the use of PHEVs decreases ozone in most areas, but some highly localized areas show increases in ozone concentration. The second trading program examined in this thesis is limited to Houston, Texas, where a VOC trading program is focused on a sub-set of four Highly Reactive Volatile Organic Compounds (HRVOCs), which have been identified as having substantial ozone formation potential. Work presented in this thesis examined whether this trading program, in its current form or in an expanded form, could lead to air pollution hot spots, due to spatial reallocation of emissions. Results show that the program as currently designed is unlikely to lead to ozone hot spots, so no further spatial limitations are required for this program. Expanding the trading to include Other VOCs, fugitive emissions and chlorine emissions, based on reactivity weighted trading, is also unlikely to lead to the formation of ozone hot spots, and could create more flexibility in a trading market that is currently not very active. Based on these air quality modeling results, policy suggestions are provided that may increase participation in the trading market. These case studies demonstrate that use of detailed air analyses can provide improved designs for increasingly popular emission cap and trade programs, with improved understanding of the impacts of modifying spatial and temporal distributions of emissions.