This project falls under challenge area 15: Translational Science, addressing challenge topic 15-TW- 101 Models to predict health effects of climate change. One potential result of climate change in the United States is increased frequency and intensity of wildland fires. These wildfire fires have the potential to destroy large amounts of public and private property, as was seen during the summer of 2003 and 2007 in San Diego County, California. In addition to this, there is evidence that particulate emissions from these extreme fire events lead to public health problems, particularly respiratory and cardiac related distress. It is important to understand the effects that climate change will have on the health of populations that are vulnerable to increased exposure to particulate emissions from wildfires. In this project we propose to create a comprehensive descriptive and predictive wildland fire particulate emissions model that will allow us to quantify the exposure of populations to particulate emissions during fire events. Levels of exposure will be compared to public health records to quantify the effect of wildland fire emissions on public health.
In specific aim #1, we will construct an emissions profile for the 2003 and 2007 forest fires in our study area of Southern California. This will be accomplished using remotely sensed burn intensity, fire progression, posterior severity profile, and fuels modeling.
In specific aim #2, we propose the use and modification of an existing plume advection and dispersion model to relate the wildfire emissions to particulate matter concentrations in downwind populated areas. The spatial estimate of particulate matter concentrations will be conditioned to in situ particulate matter concentrations measurements from ground stations.
For specific aim #3, we will use the results of the plume dispersion model along with spatially explicit health surveillance data to quantify particulate emission exposure levels on a ZIP code or finer scale, relating these exposure levels to respiratory and cardiovascular health responses. Finally, for specific aim #4, we will use our modeling framework to examine realistic changes in the fire regime under different climate change scenarios and estimate the impact that changes in particulate emissions will have on public health. This will allow for public health officials to plan for scenarios where air quality may be affected by more frequent and intense wildland fires during a potentially longer fire season. In addition, systems can be implemented to preemptively alert the public to potential decreases in air quality from smoke events. Climate change has the potential to increase the frequency and intensity of wildland fires in the United States. Particulate emissions from wildland fires near urban areas have been shown to have an adverse effect on the respiratory and cardiac health of those populations. The goals of this proposal are to: 1) quantify the amount and type of emissions from wildland fires in specific regions of the United States, 2) use smoke plume models to quantify the exposure of urban populations to particulate emissions from wildland fires, 3) assess the impact that these emissions have by measuring increases in respiratory distress and illness as a function of spatially indexed particulate matter concentrations, and 4) quantify the effect that different climate change scenarios will have on increased frequency and intensity of wildland fires and from that, the effect it will have on the public health of vulnerable areas.
Climate change has the potential to increase the frequency and intensity of wildland fires in the United States. Particulate emissions from wildland fires near urban areas have been shown to have an adverse effect on the respiratory and cardiac health of those populations. The goals of this proposal are to: 1) quantify the amount and type of emissions from wildland fires in specific regions of the United States, 2) use smoke plume models to quantify the exposure of urban populations to particulate emissions from wildland fires, 3) assess the impact that these emissions have by measuring increases in respiratory distress and illness as a function of spatially indexed particulate matter concentrations, and 4) quantify the effect that different climate change scenarios will have on increased frequency and intensity of wildland fires and from that, the effect it will have on the public health of vulnerable areas.
| Thelen, Brian; French, Nancy H F; Koziol, Benjamin W et al. (2013) Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling. Environ Health 12:94 |
| Huang, Y; Wu, S; Dubey, M K et al. (2012) Impact of aging mechanism on model simulated carbonaceous aerosols. Atmos Chem Phys 12: |
