Harmful algal blooms and toxic air: The economic value of improved forecasts
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Abstract
The adverse economic impacts of harmful algal blooms can be mitigated via tailored forecasting methods. Adequate provision of these services requires knowledge of the losses avoided, or, in other words, the economic benefits they generate. The latter can be difficult to measure for broader population segments, especially if forecasting services or features do not yet exist. We illustrate how Stated Preference tools and Choice Experiments are well-suited for this case. Using as example forecasts of respiratory irritation levels associated with airborne toxins caused by Florida red tide, we show that 24-hour predictions of spatially and temporally refined air quality conditions are valued highly by the underlying population. This reflects the numerous channels and magnitude of red tide impacts on locals' life and activities, which are also highlighted by our study. Our approach is broadly applicable to any type of air quality impediment with risk of human exposure.