From leadership research to district action: Lessons from the first U.S. school districts with real-time indoor environmental quality (IEQ) sensors in classrooms: benefits, barriers and opportunities

AI-assisted editorial implementation guide. Proposed district actions are separate from the original authors’ findings and recommendations. Independent peer review of this guide is not asserted.

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Evidence and transfer

Education-related source: verify which participants, institutions and outcomes were actually studied before district adoption. Source publication type: research-article. License and identity checks do not establish study quality or causality.

Original authors’ abstract, reproduced under the source license:

Abstract With aging buildings, rising temperatures, and limited budgets, school districts in the United States need effective strategies to address classroom environmental issues, secure funding for upgrades, and develop climate resilience plans. Collecting real-time indoor environmental quality (IEQ) data in classrooms can support these goals, yet few districts have adopted comprehensive school environmental monitoring, and little is known about the barriers and facilitators to its use. Understanding the value of this approach to ensure good environmental conditions inside schools, the challenges faced by early adopters, and strategies to overcome them will be essential for broader implementation. During the spring of 2025, we interviewed 13 school staff members from 5 public school districts across the United States that were early adopters of IEQ monitoring. Discussions covered perceptions of IEQ in their districts, benefits of collecting this data, and barriers and facilitators to implementing sensors and leveraging the data collected. Participants identified many uses for classroom IEQ data, including supporting operations (e.g. simplifying environmental audits, remotely validating complaints, holding mechanical ventilation vendors accountable) and sustainability efforts (e.g. advocating for capital upgrades, monitoring wildfire smoke infiltration, predicting mold growth, ensuring medication safety, and student education). Opinions were mixed on publicly sharing the data. Barriers included database complexity, the need for environmental health (EH) and data expertise, high costs, technical challenges, workload, and ethical concerns. Schools addressed these challenges through vendor support, artificial intelligence, and partnerships with academic researchers. Key opportunities to advance environmental equity in schools include improving EH literacy among staff and leadership and establishing indoor air quality standards. This study highlights lessons learned from pioneering districts and demonstrates how IEQ monitoring can improve classroom conditions, support operations and funding, and guide climate resilience and sustainability initiatives. The findings offer valuable insights for school districts, governments, and researchers considering installing environmental monitoring in classrooms. Keywords: indoor environmental quality, indoor environmental monitoring, environmental health literacy, data literacy, schools, climate resilience, sustainability

Study methods

We conducted one-on-one semi-structured interviews with school staff members working in districts across the U.S. where classroom indoor environmental data is currently collected, and used thematic analysis to identify benefits, barriers, and opportunities to using IEQ data.

Limitations

Everyone highlighted the value of continuous environmental monitoring in classrooms, and staff members who consult the IEQ data frequently (Operations roles) felt they had enough skills to explore the information. However, the size and complexity of the data was brought up by eight school staff members as a barrier to fully capitalize on this information, which requires EH and data science expertise. A staff member with a Sustainability/Energy role explained the limitations of making sense of the large volumes of data collected by the sensors. ‘The data by itself is interesting, but does not tell a story.’ Lack of data literacy was pointed out as a barrier for the general public to use this information, ‘The challenge to these monitors and to the platform is that it takes a certain level of education and information to be able to interpret what you are reading,’ said one participant in a Student Health position. Participants who typically use the IEQ data reported that there was not a designated data science individual within their school district for managing and analyzing the classroom IEQ data (mentioned by 7). Specifically, a participant clarified that while there may be individuals in their organization with the necessary skills, analyzing IEQ data is not part of their current responsibilities, “There are a couple of people who could do that. It is not their job. And that’s a distinction that I need to make.” Three operations staff expressed the need for having such expertise in-house. However, currently, the responsibility for managing and analyzing the data is spread across different roles and layered over their current job responsibilities, limiting how much they can engage with the data.

A 90-day district inquiry

Days 1–15 · Appraise. Read the source methods, recruitment, comparator, outcomes and limitations. Record how the study setting differs from your district and which claim the design can support.
Days 16–30 · Design. Choose one school improvement question with teachers. Protect a short shared planning cycle, agree an instructional change and use a common rubric for examining student work. Agree participation, privacy protections, baseline and stopping rules before starting.
Days 31–60 · Observe. Collect the pre-agreed measures, keep a log of implementation changes and invite confidential voluntary feedback. Preserve existing support for staff and learners.
Days 61–90 · Decide. Review implementation fidelity, teacher time and independently scored student work against a recorded baseline. Examine access differences and competing explanations before attributing changes to leadership. Make a dated decision to stop, revise or extend the inquiry.

Board decision brief

Present the local problem, source setting, evidence limits, intervention, responsible owner, total cost, measured changes and uncertainty. Separate staff perceptions, implementation measures and student learning outcomes.

Attribution and reuse

M Pilar Botana Martinez; M Patricia Fabian; Kyleigh Gunn; Katherine H Walsh; Madeleine K Scammell. Lessons from the first U.S. school districts with real-time indoor environmental quality (IEQ) sensors in classrooms: benefits, barriers and opportunities. Environmental Research, Health (2026-05-26). https://doi.org/10.1088/2752-5309/ae5fc3

Prepared 2026-11-07. Source authorship and DOI are preserved. The abstract and source passages are attributed extracts; this editorial guide is offered under the same CC BY 4.0 license.