Integrated Energy and Air Quality Assessment of Clean Energy Initiatives in the New York State

RICHARD MAHUZE, Bo Yuan, K. Max Zhang, Cornell University

     Abstract Number: 609
     Working Group: Urban Aerosols

Abstract
The increasing frequency and intensity of extreme weather events, combined with the urgent need to transition to low-carbon energy systems, pose significant challenges for energy infrastructure planning. In New York State—where ambitious renewable energy targets and emission reduction commitments are in place—building resilience to both gradual climate shifts and sudden, severe weather events is essential. To aid in this transition, power system planners need high-resolution data to accurately project future energy demand and renewable resource variability. This research presents an integrated modeling framework that combines renewable energy resources, power systems, and air quality dynamics. The framework leverages a suite of analytical tools, including geographical information systems (GIS), optimal power flow (OPF), numerical weather simulation (WRF), and air quality chemical transport modeling (CMAQ). All components are synchronized within a unified weather regime, offering a holistic view of the system and capturing the interdependencies among these components. The entire framework is developed in Python, with all tools publicly accessible on GitHub. The framework is evaluated against various meteorological and air quality observational datasets. Future scenarios indicate significant reductions in winter PM2.5 and summer ozone levels from 2018 to 2030. However, substantial demand growth in the building and transportation sectors, driven by aggressive electrification policies, could partially offset emissions reductions achieved by phasing out thermal power generation.