2024年纽约州总量控制交易和投资设计对空气质量的影响报告

Air Quality Impacts of New York StateCap-Trade-and-Invest Design Issue Brief 24-10 byMolly Robertson,Eunice Ko, Alan Krupnick, Eddie Bautista, andWesley LookOctober 2024 improve air quality for New Yorkers, especially thosein DACs. Earlier reports offer more detail on overallemissions changes across the state and generator-level emissions changes in the power sector. Separateair quality modeling from the emissions modelingwas needed because the relationship between directemissions and local air quality is highly affectedby complex chemical processes and atmosphericconditions. 1.Introduction The New York Department of EnvironmentalConservation (DEC), the New York State EnergyResearch and Development Authority (NYSERDA), andthe New York Governor are currently finalizing draftregulations that will determine how an economy-wideemissions cap-and-trade system (also referred to as“NYCI” by the State) will work in New York State. Theregulations will influence how much and how equitablygreenhouse gas (GHG) and copollutant emissionsare reduced. Advocates, such as New York CityEnvironmental Justice Alliance and New York Renews,referring to the program as “cap-trade-and-invest,”have been calling for guardrails in the program to makesure the State complies with the Climate Leadershipand Community Protection Act (or the “Climate Act”),and that disadvantaged communities (DACs) do notexperience more air pollution or slower, lower rates of airquality improvement compared to non-DACs. Advocacygroups have also been calling for regulations that willbolster the amount of program revenue for climateinvestment and action. In this report, we leverage the emissions findingsreported in Krupnick et al. (2024) and Robertson et al.(2024) to conduct a robust air quality analysis usinga state-of-the-art atmospheric model initially usedin Krupnick et al. (2023). Emissions changes in sulfurdioxide, nitrous oxides, and direct PM2.5are used toestimate local PM2.5concentrations at a 4km2gridresolution. We focus on PM2.5concentrations becausethis pollutant is tied directly to health and wellnessoutcomes, and small changes in concentrations can leadto meaningful impacts on mortality and chronic disease(e.g., asthma) rates (Di et al. 2017; Krewski et al. 2009;Lepuele et al. 2012). This analysis compares tract-level air quality estimatesfor four policy cases: Our research to date has analyzed different cap-trade-and-invest policy designs and their correspondingGHG emissions, copollutant emissions, and householdcost impacts. Previous work conducted by Resourcesfor the Future (RFF) and New York City EnvironmentalJustice Alliance (NYC-EJA), Krupnick et al. (2024)and Robertson et al. (2024), found that the cap-trade-and-invest program can reduce GHG and copollutantemissions. The research presented in this issue briefshows that guardrails, such as restricted trading, facility-specific caps, and obligating the electricity sector 1.The Business as Usual (BAU) case, which includesthe NY Clean Energy Standard, the RegionalGreenhouse Gas Initiative (RGGI), InflationReduction Act (IRA) policies, renewable generationmandates, zero emissions vehicle mandates, andother existing policies. In this case, there is no cap-trade-and-invest program. 2.The Electricity not Obligated Case (ENOC), wherecap-trade-and-invest is implemented in New York guardrails under consideration to improve outcomesfor disadvantaged communities. NYC-EJA offeredtheir expertise on the New York policy landscapeand the specific policy questions most relevant todisadvantaged communities as the program designcontinues to take shape. State, but the electricity sector is not covered.Power sector facilities in the state are still requiredto purchase allowances from the RGGI market. 3.The Full Trading Case (FTC), where cap-trade-and-invest is implemented, electricity is covered undercap-trade-and-invest, and there is full tradingacross sectors. The PM2.5concentrations in this analysis were producedusing an air quality model that leverages emissionsestimates from the power, transportation, and residentialbuildings models presented in Krupnick et al. (2024) andRobertson et al. (2024).1Two air quality models are usedto estimate PM2.5concentrations at a grid resolution of4km2across New York State for 2030 under the fourpolicy scenarios. The first is the Weather Research andForecasting model coupled to chemistry (WRF-Chemv4.3). WRF-Chem is a state-of-science online-coupled3-D air quality model containing comprehensiverepresentations of atmospheric transport, physics,and chemistry to simulate PM2.5concentrations. It wasapplied at a grid resolution of 36km2. The second modelused is a computationally efficient statistical modelutilizing the 36km2simulation results from the 3-Dair quality model to predict PM2.5concentrations at agrid resolution of 4km2. Appendix C in Krupnick et al.(2023) offers greater detail on the air quality modelingmethodology used in this work. 4.The Restricted Trading