To store, manage, and analyze the complex datasets collected by this monitoring system, the Sustainable School's Project relies on research computing resources, including high-performance clusters at BU and MGHPCC. These tools enable the team to process large volumes of data and apply advanced statistical methods required to identify disparities in environmental conditions across districts, assess health risks from exposure to poor indoor environmental conditions, and inform building design and policy decisions.

Recent papers from the group include a blueprint for leveraging classroom environmental data, through a case-study of school carbon dioxide, a district-wide characterization of heat exposure using novel exposure metrics , and the development of a cost-effective, scalable method to estimate classroom air ventilation rates, key to reducing viral infections indoors.

By combining environmental monitoring with computational modeling, the project provides a framework for data-driven, community-engaged, and actionable research that highlights the transformative potential of classroom indoor environmental monitoring systems to promote student well-being and academic achievement. The Sustainable Schools Project exemplifies how computational power and community-based research can work together to promote healthy indoor are for all students.