The urban building stock needs to be transformed to deliver on climate change goals as buildings account for two thirds of New York City’s greenhouse gas emissions. There are varied financial mechanisms being used by state and national governments to facilitate this transition, such as New York State’s Clean Energy Fund and the National Infrastructure Reduction Act. Whilst climate change mitigation is the main motivation for these funds, climate change policies also seek to address other societal challenges such as spurring economic growth, reducing energy insecurity and providing quality housing for low-income citizens. This interdisciplinary project seeks to systematically evaluate these co-benefits of building stock decarbonization using quality-diversity (or illumination) optimization algorithms and evaluate how the generated solutions can act as a “coordination device” to help street-level bureaucrats and community stakeholders identify mutually acceptable approaches to building stock decarbonization. The aim of this proposal is to demonstrate (1) that quality-diversity algorithms can provide more acceptable candidate solutions to stakeholders than the prevailing multi-objective optimization approaches due to the rugged fitness landscape of building energy modeling problems and (2) that this framework can be a useful coordination tool to aid in generating consensus from a broad array of stakeholders. As an interdisciplinary engineering project rooted in community engagement and decarbonization, the project will focus on a case study region of the Bronx and engage with community organizations and public institutions to define the co-benefits, evaluate candidate solutions, and generate consensus. By structuring the project in this way, innovatively, the project itself serves as a “coordination tool” that will evolve in real time enabling the use of ethnographic observatory approach to evaluate its effectiveness.
