When planning and running an air quality program, cities need a clear way to gauge success and flag potential issues. A strong evaluation plan builds accountability, helps strengthen the case for future funding and creates opportunities to learn and improve while mitigating any negative impacts.
This section will help your city find tools to assess whether your programs are meeting clean air goals, such as reducing emissions, and to measure effects on air quality, public health and equity.
Designing a program evaluation: logic models
Logic models show how an air quality program is designed to work by linking inputs like funding, research and stakeholder input to activities (e.g. specific emissions reduction strategies), outputs (e.g. reduction in NOx emissions), outcomes (e.g. reduction in ambient ozone) and long‑term impacts (e.g. improvements in public health).
Logic models help identify the right metrics and indicators to measure program effectiveness, such as emissions reductions or improvements in air quality and health. A strong logic model is a critical first step in program evaluation and serves as a shared guide for all stakeholders.
Example logic model for anti-idling diesel emission reduction program
Inputs
- Funding and grants
- Research
- Staff time and resources
Activities
- Implementation of anti-idling ordinances
- Installation of electrification at distribution centers
Outputs
- Chang in number of hours idling of diesel trucks
Short-term outcomes
- Reduction in NOx and PM2.5 emissions
- Reduced diesel fuel consumption
Long-term impacts
- Reduction in ambient ozone and PM2.5
- Improvements in public health
