Author Date

2020-08-07

Degree Name

BS

Department

Plant and Wildlife Sciences

College

Life Sciences

Defense Date

2020-07-16

Publication Date

2020-08-07

First Faculty Advisor

Benjamin W. Abbott

First Faculty Reader

Natalie Romeri-Lewis

Honors Coordinator

Craig Coleman

Keywords

Air pollution, expert assessment, environmental policy, science communication, ecological economics

Abstract

Recent scholarship has found that air pollution damages our health and economy more than previously understood, with approximately one in four deaths associated with exposure to air pollution globally. However, translating these research findings into policy and behavior change at local levels remains a major challenge, partially because of mismatch between the scale of air pollution research (often national or global) and governance frameworks (typically local to regional). Here, we used an expert assessment to bridge this research-policy divide in Utah, USA. We combined quantitative and qualitative input from 23 Utah-specific researchers and specialists, asking for estimates of human health and economic costs of air pollution, as well as recommendations for what policy actions would be most effective at reducing those costs. Experts estimated that air pollution in Utah is causing 2,480 to 8,000 premature deaths annually (90% confidence interval) and decreasing the median life expectancy by 1.1 to 3.6 years. The direct and indirect costs of air pollution in Utah totaled $0.75 to $3.3 billion annually, up to 1.7% of the state’s gross domestic product. Expert estimates of the health consequences were generally higher than previous studies downscaled to Utah, but the economic costs were generally lower than previous studies. We presented these Utah-specific findings, including recommended actions to improve air quality, to the state legislature in the 2020 legislative session. We discuss the response of Utah policymakers to these results and present a framework of involving local researchers to increase the assimilation of data into decision making.

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