More than 20 million children ride the bus to school, and most of those buses run on diesel. Diesel exhaust is a carcinogen with links to asthma, cognitive development impacts and other health issues. Children from low-income communities and communities of color are disproportionately subjected to this harmful air pollution. For these reasons, the World Resources Institute’s Electric School Bus Initiative set out to help electrify all U.S. school buses.
We soon discovered a major data gap: there was no publicly available, nationwide dataset of school districts’ bus fleets. This data is needed to determine which school districts have the oldest, most polluting buses, enabling clean school bus funding programs to target districts with the greatest need. It can also help communities and advocates target their campaigns to create the most impact, and help utilities plan the grid upgrades needed to electrify transportation.
To fill this data gap, we spent nine months submitting public records requests (FOIAs) to government agencies in every state and compiled a first-of-its-kind dataset containing almost 480,000 buses owned by over 12,000 school districts and other entities in 46 states and the District of Columbia. The dataset includes approximately 30 variables that describe the buses and their owners, such as the model year and fuel type. (https://datasets.wri.org/dataset/school_bus_fleets)
This presentation will offer lessons learned from our experience navigating the states’ public records request process: How can government agencies make this data more useful and accessible? How can people more effectively seek out similar datasets from government agencies? It will also include a case study of findings on NYC’s school bus fleet. How does it stack up against other New York state school districts and other major cities? What are the environmental and health benefits and harms of the current NYC school bus fleet, and what could be improved? Participants will be invited to brainstorm uses and research questions that this dataset could address.