Recent dramatic and deadly increases in global wildfire activity have increased attention on the causes of wildfires, their consequences, and how risk from wildfire might be mitigated. Here we bring together data on the changing risk and societal burden of wildfire in the United States. We estimate that nearly 50 million homes are currently in the wildland–urban interface in the United States, a number increasing by 1 million houses every 3 y. To illustrate how changes in wildfire activity might affect air pollution and related health outcomes, and how these linkages might guide future science and policy, we develop a statistical model that relates satellite-based fire and smoke data to information from pollution monitoring stations. Using the model, we estimate that wildfires have accounted for up to 25% of PM 2.5 (particulate matter with diameter <2.5 μm) in recent years across the United States, and up to half in some Western regions, with spatial patterns in ambient smoke exposure that do not follow traditional socioeconomic pollution exposure gradients. We combine the model with stylized scenarios to show that fuel management interventions could have large health benefits and that future health impacts from climate-change–induced wildfire smoke could approach projected overall increases in temperature-related mortality from climate change—but that both estimates remain uncertain. We use model results to highlight important areas for future research and to draw lessons for policy.
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Wildfire!
Wildland fires have become a regular aspect of life for people living in the western United States. Wildfire smoke is now impacting air quality across the United States, and there are now more wildfire smoke-related illnesses and deaths in the eastern than the western United States. Unprecedented wildfires have swept through Australia, Russia, and Portugal in the last few years. Like other natural disasters, wildland fires can have a devastating impact on communities that are directly in their paths. However, they also cast a much bigger footprint due to the smoke they release on a global scale. These smoke events can lead to health warnings, noticeable irritation to the lungs, and cancelled outdoor events. They have quickly become part of the life experience of many students around the world. Their connections to global climate change and environmental policy, juxtaposition as positive forces in ecosystem succession, and relationship to a wide variety of both simple and complex natural phenomena leave science teachers with an opportunity to frame myriad lessons within the context of wildfire. We present a series of such lessons, adaptable to various levels of physical or integrated science.
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- Award ID(s):
- 1830047
- NSF-PAR ID:
- 10380663
- Date Published:
- Journal Name:
- The science teacher
- Volume:
- 90
- Issue:
- 2
- ISSN:
- 0036-8555
- Page Range / eLocation ID:
- 32-39
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The size and frequency of wildland fires in the western United States have dramatically increased in recent years. On high-fire-risk days, a small fire ignition can rapidly grow and become out of control. Early detection of fire ignitions from initial smoke can assist the response to such fires before they become difficult to manage. Past deep learning approaches for wildfire smoke detection have suffered from small or unreliable datasets that make it difficult to extrapolate performance to real-world scenarios. In this work, we present the Fire Ignition Library (FIgLib), a publicly available dataset of nearly 25,000 labeled wildfire smoke images as seen from fixed-view cameras deployed in Southern California. We also introduce SmokeyNet, a novel deep learning architecture using spatiotemporal information from camera imagery for real-time wildfire smoke detection. When trained on the FIgLib dataset, SmokeyNet outperforms comparable baselines and rivals human performance. We hope that the availability of the FIgLib dataset and the SmokeyNet architecture will inspire further research into deep learning methods for wildfire smoke detection, leading to automated notification systems that reduce the time to wildfire response.more » « less
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Abstract As anthropogenic emissions continue to decline and emissions from landscape (wild, prescribed, and agricultural) fires increase across the coming century, the relative importance of landscape‐fire smoke on air quality and health in the United States (US) will increase. Landscape fires are a large source of fine particulate matter (PM2.5), which has known negative impacts on human health. The seasonal and spatial distribution, particle composition, and co‐emitted species in landscape‐fire emissions are different from anthropogenic sources of PM2.5. The implications of landscape‐fire emissions on the sub‐national temporal and spatial distribution of health events and the relative health importance of specific pollutants within smoke are not well understood. We use a health impact assessment with observation‐based smoke PM2.5to determine the sub‐national distribution of mortality and the sub‐national and sub‐annual distribution of asthma morbidity attributable to US smoke PM2.5from 2006 to 2018. We estimate disability‐adjusted life years (DALYs) for PM2.5and 18 gas‐phase hazardous air pollutants (HAPs) in smoke. Although the majority of large landscape fires occur in the western US, we find the majority of mortality (74%) and asthma morbidity (on average 75% across 2006–2018) attributable to smoke PM2.5occurs outside the West, due to higher population density in the East. Across the US, smoke‐attributable asthma morbidity predominantly occurs in spring and summer. The number of DALYs associated with smoke PM2.5is approximately three orders of magnitude higher than DALYs associated with gas‐phase smoke HAPs. Our results indicate awareness and mitigation of landscape‐fire smoke exposure is important across the US.
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Accepted Manuscript1.0
- Journal Article:
- The DOI is not currently available.
