Improving Forest Fire Smoke Forecasts for Public Health
Among the consequences of our changing climate is an increase in the intensity and frequency of forest fires. Wildfire is a natural process that is vital for the healthy renewal of temperate mountain forests; however, fires also impact human populations. In addition to the direct risks they pose to human safety and infrastructure, forest fires affect public health by creating smoke. The fine particulate matter found in smoke can worsen some pre-existing health conditions and has been linked to respiratory diseases, such as asthma. Further, the smoke generated by forest fires can remain in the atmosphere for days and often travel long distances by wind.
Forest fires are difficult to predict, adding to the challenge of forecasting public smoke exposure. Health authorities currently rely on a variety of information sources to measure and predict smoke exposure, including ground surface air quality measurements, satellite measurements, weather data, and fire details (e.g., fuel type). While different methods each have their own strengths and weaknesses, researchers from the British Columbia Centre for Disease Control, University of British Columbia, and Environment and Climate Change Canada sought to strengthen their ability to predict smoke exposure with a hybrid approach that blended forecasting tools with measured air quality and satellite observations. Researchers used health indicators, collected throughout the southern portion of British Columbia during the summer fire seasons of 2014 and 2015, to compare the performance of different predictive smoke exposure models both individually and in combination. They found that blended model forecasts outperformed the conventional single model forecasts. This study shows how multiple sources of information can be used together to produce better smoke exposure projections and improve public health preparedness.
This is a summary article authored by Charlie Loewen. For further information, please see the original published research:
Weiran Yuchi, Jiayun Yao, Kathleen E. McLean, Roland Stull, Radenko Pavlovic, Didier Davignon, Michael D. Moran & Sarah B. Henderson (2016) Blending forest fire smoke forecasts with observed data can improve their utility for public health applications. Atmospheric Environment, 145:308–317 (doi:10.1016/j.atmosenv.2016.09.049).