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Estimating ZIP Code-Level Air Quality and Health Risks of New York City’s Transportation Decarbonization Pathways using COMET and ZAPPA
Citation:
Kaplanakman, Pervin, C. Seppanen, AND S. Arunachalam. Estimating ZIP Code-Level Air Quality and Health Risks of New York City’s Transportation Decarbonization Pathways using COMET and ZAPPA. Annual CMAS Conference, Chapel Hill, NC, October 16 - 18, 2023.
Impact/Purpose:
In this study, we utilize a technology-rich, bottom-up, energy system optimization model (EPA's City-based Optimization Model for Energy Technologies: COMET) to delve into the cost and air emissions implications of New York City’s proposed CO2 reduction policies, with a specific focus on the transportation sector. Central to our investigation is a scenario framework that methodically captures two uncertainties in achieving these CO2 reduction goals, (1) pace of grid decarbonization and (2) pace of transportation fleets decarbonization. Along with a business as usual scenario (Reference), two additional scenarios were generated. The scenarios revealed that the early turnover of light-duty vehicles (LDV) led to increased fuel efficiency of fleets, and electrification of LDVs at earlier periods is essential for deeper reductions in air emissions. Along with technology and fuel choices for the transport fleets, COMET generated air emission projections and changes at borough level for NOx, PM2.5, SO2, NH3 and SOA. We then translated changes in air emissions at borough levels from various source categories into tangible health outcomes and benefits at a more detailed geographical scale using the ZIP Code-Level Air Pollution Policy Assessment (ZAPPA) tool. ZAPPA connects shifts in air quality to their subsequent health repercussions at a localized level. This type of analysis will inform policy makers in how the decarbonization policies at federal, state and city levels would be realized at local neighborhood scale and could inform just transition efforts.
Description:
In this study, we utilize a technology-rich, bottom-up, energy system optimization model (EPA's City-based Optimization Model for Energy Technologies: COMET) to delve into the cost and air emissions implications of New York City’s proposed CO2 reduction policies, with a specific focus on the transportation sector. Central to our investigation is a scenario framework that methodically captures two uncertainties in achieving these CO2 reduction goals, (1) pace of grid decarbonization and (2) pace of transportation fleets decarbonization. Along with a business as usual scenario (Reference), two additional scenarios were generated. First one, DEPENDENCE, considered grid emissions were tracking business as usual trends, and identified a least cost pathway to reduce CO2 emissions by 80% in 2050. The second scenario (REVOLUTION) explored evolution of electric grid toward renewables at a pace that was set by state level energy policy (New York’s Clean Energy Standard) and still aimed to reduce city-level CO2 emissions by 80% in 2050. The analysis revealed that the early turnover of light-duty vehicles (LDV) led to increased fuel efficiency of fleets, and electrification of LDVs at earlier periods is essential for deeper reductions in air emissions. These actions yielded the anticipated in-city CO2 reductions for the DEPENDENCE scenario where the grid had more CO2-intense electricity. The REVOLUTION scenario resulted in electrification of LDV fleets later in the modeling years. Along with technology and fuel choices for the transport fleets, COMET generated air emission projections and changes at borough level for NOx, PM2.5, SO2, NH3 and SOA. Next is to translate changes in air emissions at borough levels from various source categories into tangible health outcomes and benefits at a more detailed geographical scale. COMET generated air emission changes at borough level, these findings were then integrated into the ZIP Code-Level Air Pollution Policy Assessment (ZAPPA) tool. ZAPPA connects shifts in air quality to their subsequent health repercussions at a localized level. A preliminary step involved comparing the 2016 baseline emission figures with the reference scenario, ensuring the robustness of the ZAPPA model. Following this, we extended the percent changes in emissions derived from our trio of scenarios to the year 2030. ZAPPA was first run, considering emission alterations between its 2016 baseline and a chosen future year, 2030. This step discerned health impacts purely due to the progression of years in the REFERENCE case. Another run of ZAPPA then assessed the variations in emissions between the 2016 benchmark and the selected future-year scenario, REVOLUTION 2030 results. The outcomes of the first step were deducted from the second to discern the net health impacts resulting solely from the scenario adoption in the target year. Preliminary results indicate that at borough level on average total health benefits range from $186 to $418 Million, and total PM2.5 concentration reduced by 0.05 ug/m3.