Ecology & Natural Resources Projects

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Prescribed fires are one of the most effective tools to reduce the buildup of hazardous fuels (vegetation) that are contributing to severe wildfires in the western U.S. In the coming years, California is expected to significantly increase the use of prescribed fires. Any vegetation burning emits smoke and harmful air pollutants; however, prescribed fires can minimize smoke impacts on downwind air quality, especially in comparison to uncontrolled wildfires. To conduct prescribed fires effectively, land and air quality managers need information and tools to support smoke management.

In this project, funded by CAL FIRE, Sonoma Technology has partnered with the Desert Research Institute to develop a turnkey decision support tool for prescribed fire planning and wildfire response. The tool will allow users to specify a time window and location for a planned prescribed fire or current wildfire, and instantaneously view the probability of downwind smoke impacts and smoke weather statistics based on 20 years of climatological data.

Tool development involves hourly air parcel trajectory modeling at a fine spatial scale for California and Nevada using high-resolution (2 km) meteorological data from 2001 through 2020. Modeling results will determine the probability of air parcel transport from any location within California for multiple time scales (e.g., week, month). A geospatial risk score will be generated by integrating air parcel transport probabilities with population data and other relevant information (e.g., school and hospital locations). Historical statistics of weather parameters relevant to fire and smoke conditions (e.g., relative humidity, temperature, mixing height) will be developed from the climatology for any given location in the domain. The trajectory modeling and climatological analysis outcomes will be implemented into a simple and interactive online dashboard. Air and land managers can use the dashboard to plan prescribed fires, which will allow for more timely public messaging regarding potential smoke impacts and proactive mitigation efforts to assist at-risk populations.

Fire research and management applications, such as fire behavior analysis and emissions modeling, require consistent, highly resolved spatiotemporal information on the progression of wildfire growth. Sonoma Technology developed a new fire mapping method that uses quality-assured sub-daily active fire/thermal anomaly satellite retrievals (2003-2020 MODIS and 2012-2020 VIIRS data) to develop a high-resolution wildfire growth dataset. This dataset includes growth areas, perimeters, and cross-referenced fire information from agency reports. Satellite fire detections were buffered using a historical pixel-to-fire size relationship, then grouped spatiotemporally into individual fire events. Sub-daily and daily growth areas and perimeters were calculated for each fire event. After assembly, fire event characteristics, including location, size, and date, were merged with agency records to create a cross-referenced dataset. Our satellite-based total fire size shows excellent agreement with agency records for MODIS (R2 = 0.95) and VIIRS (R2 = 0.97). VIIRS-based estimates show an improvement over MODIS for fires with areas less than 4,047 hectares (10,000 acres). 

The novel spatiotemporal resolution and methodological consistency of our dataset enables advances in applications related to historical fire-weather analysis, fire-weather modeling, characterizing wildfire growth potential, historical/future smoke modeling, and near-real-time fire monitoring. We are currently incorporating fire detection data from geostationary satellites in the method to derive hourly fire growth information. This work is published in the International Journal of Wildland Fire.

Wildfires in California are threatening public security, health, and safety. Prescribed fires can help mitigate the risks of wildfires, and CAL FIRE and the U.S. Forest Service plan to significantly increase the use of prescribed fires. This project aimed to address an important question: in a future of growing wildfires, how does the increased use of prescribed fires impact air quality and public health?
This research investigated smoke (fine particulate matter, PM2.5) from prescribed fires and wildfires to understand their public health impacts and estimated potential impacts under a future target scenario of increased prescribed fires. The study also characterized emissions of greenhouse gases from prescribed fires and wildfires, including carbon dioxide and methane. The Sonoma Technology team was responsible for exposure modeling, and used emissions estimates for these burn scenarios in a dispersion model to predict PM2.5 concentrations. Our results are published in the journal Atmospheric Environment.
The health analysis team at the California Department of Public Health and U.S. EPA investigated the public impacts and health burdens of ambient air pollution, as well as smoke from wildfires and prescribed fires, using information on hospital and emergency department visits. 

To build a more wholistic picture of the health impacts, the project conducted community engagement activities in wildland-urban interface (WUI) areas, including listening sessions in El Dorado and Nevada counties and a survey of medically vulnerable persons in Mariposa County. These activities gathered input directly from local residents about their knowledge, health concerns, and communication needs regarding prescribed fires, and their recommendations for improving community resilience to wildfire and prescribed fire smoke. Community engagement results can be found in the International Journal of Environmental Research and Public Health, and in the report published by the California Department of Public Health. 

The project was conducted in an interdisciplinary collaboration of researchers with expertise in air pollution, wildland fire smoke modeling, epidemiology, and forestry, and included experts from the California Department of Public Health, Sonoma Technology, U.S. EPA, the U.S. Forest Service, the Michigan Technological University, and the Sequoia Foundation.