Brownfield programs are intended to achieve three goals: reduce environmental hazards, spur economic growth, and address social justice concerns. Ideally, projects should generate profit for private parties who undertake such activities. Thus, brownfields can potentially serve as prototypes for innovative governance arrangements that meet multiple sets potentially conflicting goals. Despite the substantial investment of public and private resources and an innovative policy approach relying on voluntary action, very few states collect any sort of outcome data related to brownfield projects. The current literature also largely relies on anecdotal evidence of success or on a subject's impressions of success. Thus, neither researchers, nor the public, know if programs are succeeding, on the whole, in achieving any of the identified goals. This project investigates the outcomes of brownfield remediation, focusing in particular on California, which is one of the few states that collect data on a portion of its estimated 90,000 brownfields. This project analyzes site specific characteristics, zoning and land use changes, and economic and census tract data for a stratified, random sample of brownfield sites within California. Using a series of quantitative methods, including cluster analysis and geographically weighted regression, this research investigates how different factors impact the likelihood of successful projects across environmental, fiscal, and social goals
