
Enabling Better Access to Federal Transportation Funds for Small and Rural Communities
Summary
Most federal transportation funds are distributed to state and regional transportation entities by a legislatively set formula for different types of transportation. An exception to this rule is the U.S. Department of Transportation’s (USDOT) Better Utilizing Investments to Leverage Development (BUILD) Transportation Discretionary Grants program (formerly known as the TIGER program). The BUILD program is extremely flexible, with funding available for any kind of surface-transportation project and any government agency, and it the only transportation program that provides direct capital support to local transportation projects. This flexibility has made the BUILD program incredibly popular, receiving 10 times more applications than can be funded. However, the application process is extensive and can require outside assistance to produce, making the application itself too expensive for some areas to take on, especially considering the high level of competition. USDOT should create a simpler application that most public agencies can manage with internal staff to make the program more universally available to communities of all sizes and levels of capacity.
Confronting this crisis requires decision-makers to understand the lived realities of wildfire risk and resilience, and to work together across party lines. Safewoods helps make both possible.
Yesterday, the U.S. Environmental Protection Agency proposed revoking its 2009 “endangerment finding” that greenhouse gases pose a substantial threat to the public. The Federation of American Scientists stands in strong opposition.
The Federation of American Scientists supports H.R. 4420, the Cool Corridors Act of 2025, which would reauthorize the Healthy Streets program through 2030 and seeks to increase green and other shade infrastructure in high-heat areas.
The federal government can support more proactive, efficient, and cost-effective resiliency planning by certifying predictive models to validate and publicly indicate their quality.