03 / Bay Area
HEAT-SAFE HOMES: DATA-DRIVEN HOUSING RESILIENCE
R.03

Abstract
Outdated, inefficient housing in the Bay Area disproportionately impacts disadvantaged communities through greater exposure to extreme heat and high energy burdens. I evaluated the Bay Area Jobs First Regional Plan's data systems and designed a targeted program to increase reliable HVAC access and weatherization in DAC homes. The project produced a theory of change (TOC), quantitative targets (e.g., 25% increase in reliable HVAC systems by November 2025), and a multi-method, community-based implementation and analysis plan to inform future funding and policy.
Case StudyBay Area Jobs First Regional Plan — DAC Housing Resilience
LocationBay Area, CA
StudioUC BERKELEY CED | CYPLAN 190
RoleResearcher & Program Designer
Year2025
Actionable Methodology
- 01Ground a theory of change in disaggregated data: pair climate hazard layers (extreme-heat days, urban heat island, wildfire smoke exposure) with demographic and public-health indicators so disadvantaged communities are identified by overlapping burden, not a single proxy
- 02Translate ambition into measurable targets early—e.g., a 25% increase in reliable HVAC systems by a fixed date—so program design, budget, and evaluation all key off the same number instead of drifting toward outputs
- 03Design mixed-method evaluation up front: combine utility and CalEnviroScreen data with resident surveys and partner interviews so quantitative targets are validated by lived experience and the program can adjust mid-cycle
- 04Anchor implementation in existing community-based organizations and weatherization pipelines rather than standing up new delivery infrastructure, which preserves trust, shortens ramp-up, and channels funding to groups already serving DAC residents
- 05Write recommendations to be funder-ready: a clear problem frame, a TOC diagram, named indicators, and an implementation timeline so the document can move directly into Regional Plan funding and policy conversations