Historical seasonal changes in prescribed burn windows in California

Baijnath-Rodino, Janine A.; Li, Shu; Martinez, Alexandre; Kumar, Mukesh; Quinn‐Davidson, Lenya; York, R.A.; Banerjee, Tirtha

doi:10.1016/j.scitotenv.2022.155723

Cited by 13 publications

(12 citation statements)

References 40 publications

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“…Clearly, there are more discrepancies between the three data sets as the level of PM 2.5 increases and as we move from warm to cold season. The generally worse accuracy of the model estimates in the cold season may have implications for studies investigating differential health impacts of wild and prescribed fires because the latter mostly occur/have been increasingly occurring during what we are defining as the cold season. , Worse estimation accuracy for smoke during the cold season may also have implications for studies investigating health interaction effects between temperature and smoke (or PM 2.5 in general), for which there is already some evidence. , …”

Section: Resultsmentioning

confidence: 99%

“…The generally worse accuracy of the model estimates in the cold season may have implications for studies investigating differential health impacts of wild and prescribed fires because the latter mostly occur/ have been increasingly occurring during what we are defining as the cold season. 39,40 Worse estimation accuracy for smoke during the cold season may also have implications for studies investigating health interaction effects between temperature and smoke (or PM 2.5 in general), for which there is already some evidence. 7,41 The yellow bars, comparing the Di and Reid estimates, show by far the highest agreement (across levels of PM 2.5 and warm/ cold season), confirming that the two sets of model estimates tend to be more similar to each other than either is to the smoke monitor data.…”

Section: Summary Statisticsmentioning

confidence: 99%

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Evaluation of Model-Based PM_2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.

Considine

Hao

deSouza

et al. 2023

Environ. Sci. Technol.

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Investigating the health impacts of wildfire smoke requires data on people’s exposure to fine particulate matter (PM2.5) across space and time. In recent years, it has become common to use machine learning models to fill gaps in monitoring data. However, it remains unclear how well these models are able to capture spikes in PM2.5 during and across wildfire events. Here, we evaluate the accuracy of two sets of high-coverage and high-resolution machine learning-derived PM2.5 data sets created by Di et al. and Reid et al. In general, the Reid estimates are more accurate than the Di estimates when compared to independent validation data from mobile smoke monitors deployed by the US Forest Service. However, both models tend to severely under-predict PM2.5 on high-pollution days. Our findings complement other recent studies calling for increased air pollution monitoring in the western US and support the inclusion of wildfire-specific monitoring observations and predictor variables in model-based estimates of PM2.5. Lastly, we call for more rigorous error quantification of machine-learning derived exposure data sets, with special attention to extreme events.

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Section: Resultsmentioning

confidence: 99%

Section: Summary Statisticsmentioning

confidence: 99%

Evaluation of Model-Based PM_2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.

Considine

Hao

deSouza

et al. 2023

Environ. Sci. Technol.

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“…Thus, more research is needed in order to inform how to best integrate exposure reduction strategies into existing regulatory processes. While state natural resource agencies aim to limit burning for management purposes to days when meteorological conditions for ideal dispersion patterns, conditions can change and burns are not always carried out according to plan, particularly as burns windows shrink in the face of climate change (Baijnath‐Rodino et al., 2022 ; Kupfer et al., 2020 ). In these instances, establishing communication channels between burners and local health agencies in advance could prove crucial in reducing community exposures in ways that are not possible during unplanned wildfire events.…”

Section: Discussionmentioning

confidence: 99%

Exposure to Smoke From Wildfire, Prescribed, and Agricultural Burns Among At‐Risk Populations Across Washington, Oregon, and California

Schollaert,

Marlier,

Marshall

et al. 2024

GeoHealth

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Wildfires, prescribed burns, and agricultural burns all impact ambient air quality across the Western U.S.; however, little is known about how communities across the region are differentially exposed to smoke from each of these fire types. To address this gap, we quantify smoke exposure stemming from wildfire, prescribed, and agricultural burns across Washington, Oregon, and California from 2014 to 2020 using a fire type‐specific biomass burning emissions inventory and the GEOS‐Chem chemical transport model. We examine fire type‐specific PM2.5 concentration by race/ethnicity, socioeconomic status, and in relation to the Center for Disease Control's Social Vulnerability Index. Overall, population‐weighted PM2.5 concentrations are greater from wildfires than from prescribed and from agricultural burns. While we found limited evidence of exposure disparities among sub‐groups across the full study area, we did observe disproportionately higher exposures to wildfire‐specific PM2.5 exposures among Native communities in all three states and, in California, higher agricultural burn‐specific PM2.5 exposures among lower socioeconomic groups. We also identified, for all three states, areas of significant spatial clustering of smoke exposures from all fire types and increased social vulnerability. These results provide a first look at the differential contributions of smoke from wildfires, prescribed burns, and agricultural burns to PM2.5 exposures among demographic subgroups, which can be used to inform more tailored exposure reduction strategies across sources.

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“…Since seasonal employees currently make up the bulk of the workforce needed to implement burns, capitalizing on burn days outside of historical burn window timing—especially during winter, as our findings suggest will be increasingly important in a warming climate—would require a pronounced shift in agency fire crew staffing. Recent research focused on prescribed fire implementation in California ecosystems found that favorable meteorological conditions have indeed decreased in recent decades—but that winter and spring (DJF and MAM) have been historically underutilized due to staffing constraints that could potentially be alleviated via new administrative and policy choices 35 .…”

Section: Discussionmentioning

confidence: 99%

Climate change is narrowing and shifting prescribed fire windows in western United States

Swain,

Abatzoglou,

Kolden

et al. 2023

Commun Earth Environ

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Escalating wildfire activity in the western United States has accelerated adverse societal impacts. Observed increases in wildfire severity and impacts to communities have diverse anthropogenic causes—including the legacy of fire suppression policies, increased development in high-risk zones, and aridification by a warming climate. However, the intentional use of fire as a vegetation management tool, known as “prescribed fire,” can reduce the risk of destructive fires and restore ecosystem resilience. Prescribed fire implementation is subject to multiple constraints, including the number of days characterized by weather and vegetation conditions conducive to achieving desired outcomes. Here, we quantify observed and projected trends in the frequency and seasonality of western United States prescribed fire days. We find that while ~2 C of global warming by 2060 will reduce such days overall (−17%), particularly during spring (−25%) and summer (−31%), winter (+4%) may increasingly emerge as a comparatively favorable window for prescribed fire especially in northern states.

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Historical seasonal changes in prescribed burn windows in California

Cited by 13 publications

References 40 publications

Evaluation of Model-Based PM_2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.

Evaluation of Model-Based PM_2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.

Exposure to Smoke From Wildfire, Prescribed, and Agricultural Burns Among At‐Risk Populations Across Washington, Oregon, and California

Climate change is narrowing and shifting prescribed fire windows in western United States

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Historical seasonal changes in prescribed burn windows in California

Cited by 13 publications

References 40 publications

Evaluation of Model-Based PM2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.

Evaluation of Model-Based PM2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.

Exposure to Smoke From Wildfire, Prescribed, and Agricultural Burns Among At‐Risk Populations Across Washington, Oregon, and California

Climate change is narrowing and shifting prescribed fire windows in western United States

Contact Info

Product

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Evaluation of Model-Based PM_2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.

Evaluation of Model-Based PM_2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.