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Enhancing Decision-Making for Air Quality: Insights from Emission Models

This presentation by Amir Hakami at Carleton University discusses the pivotal role of emission models in informing policymakers about health and environmental impacts. By quantifying the costs of action versus inaction, we can derive tangible decision metrics that improve air quality and public health. Key examples illustrate the monetized benefits of emission reductions, showing significant potential savings from policies like the Toronto subway. The talk emphasizes the necessity for integrated assessments and effective communication across disciplines to tackle uncertainties in air quality management.

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Enhancing Decision-Making for Air Quality: Insights from Emission Models

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Presentation Transcript

  1. From Models to Decisions Amir Hakami Carleton University

  2. Where do models fit? • Emissions are the only variable we can control. • Use models to provide Policymakers with tangible “decision metrics”. Meteorology Transport and Transformation Pollution Emissions Health Influences Health Outcome Exposure

  3. Improving air quality • Reducing emissions is costly. • Assessing the benefits of emission reductions in terms that are comparable with costs (i.e., monetized) enhances the decision-making process. • What is the cost of action vs. inaction?

  4. Benefit from one average vehicle • Value for Toronto and coastal California: $400-$800/yr • Estimated benefit from the Toronto subway: $130,000,000/yr • NB: A fraction of benefits (non-fatal, long-term, or PM effects not included) Pappin and Hakami, 2013

  5. Health benefits: marginal benefit/damage Mobile sources Point sources • What the numbers mean? • Marginal benefits are key decision parameters.

  6. Health benefits are substantial Abatement costs Health damage Marginal benefits and costs of NOx emission reductions from power plants in the US. Mesbah et al., 2013

  7. Bonus: increasing benefits with controls! Mobile Sources Point Sources

  8. Next steps for air quality scientists • Facilitate integrated assessment. • Enhance our communication skills with other disciplines. • Quantify/reduce various uncertainties in our understanding of processes that affect air quality. • Uncertainty is not a justified reason for inaction.

  9. Next steps for air quality scientists - II Decision model Air quality model McRae and Cass (1981)

  10. Next steps for air quality scientists - III Decision model Air quality model

  11. Comments/questions Thank you! Funding provided by NSERC, CIHR, Environment Canada, Health Canada

  12. Rate of change in marginal damage $ Marginal cost Marginal damage Emission level New optimal level

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