Future Health Effects due to Wildfire Smoke under Climate Change in the Western US

2016 ◽  
Vol 2016 (1) ◽  
Author(s):  
Jia Coco Liu* ◽  
Loretta Mickley ◽  
Melissa P. Sulprizio ◽  
Xu Yue ◽  
Francesca Dominici ◽  
...  
Keyword(s):  
Climate Change ◽  
Health Effects ◽  
Future Health ◽  
Wildfire Smoke ◽  
Western Us

scholarly journals Asthma exacerbation due to climate change-induced wildfire smoke in the Western US

2021 ◽  
Author(s):  
Jennifer D Stowell ◽  
Cheng-En Yang ◽  
Joshua S Fu ◽  
Noah Scovronick ◽  
Matthew J. Strickland ◽  
...  
Keyword(s):  
Climate Change ◽  
Asthma Exacerbation ◽  
Climate Model ◽  
Fine Particulate Matter ◽  
Fire Season ◽  
Future Climate Change ◽  
Future Health ◽  
Wildfire Smoke ◽  
Mitigation And Adaptation ◽  
Western Us

Abstract Climate change and human activities have drastically altered the natural wildfire balance in the Western US and increased population health risks due to exposure to pollutants from fire smoke. Using dynamically downscaled climate model projections, we estimated additional asthma emergency room visits and hospitalizations due to exposure to smoke fine particulate matter (PM2.5) in the Western US in the 2050s. Isolating the amount of PM2.5 from wildfire smoke is both difficult to estimate and, thus, utilized by relatively few studies. In this study, we use a sophisticated modeling approach to estimate future increase in wildfire smoke exposure over the reference period (2003-2010) and subsequent health care burden due to asthma exacerbation. Average increases in smoke PM2.5 during future fire season ranged from 0.05-9.5 µg/m3 with the highest increases seen in Idaho, Montana, and Oregon. Using the Integrated Climate and Land-Use Scenarios (ICLUS) A2 scenario, we estimated the smoke-related asthma events could increase at a rate of 15.1 visits per 10,000 persons in the Western US, with the highest rates of increased asthma (25.7-41.9 per 10,000) in Idaho, Montana, Oregon, and Washington. Finally, we estimated healthcare costs of smoke-induced asthma exacerbation to be over $1.5 billion during a single future fire season. Here we show the potential future health impact of climate-induced wildfire activity, which may serve as a key tool in future climate change mitigation and adaptation planning.

scholarly journals The changing risk and burden of wildfire in the United States

2021 ◽  
Vol 118 (2) ◽  
pp. e2011048118
Author(s):  
Marshall Burke ◽  
Anne Driscoll ◽  
Sam Heft-Neal ◽  
Jiani Xue ◽  
Jennifer Burney ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
The United States ◽  
Pollution Monitoring ◽  
Future Research ◽  
Future Health ◽  
Science And Policy ◽  
Wildfire Smoke ◽  
Management Interventions ◽  
Pollution Exposure

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 PM2.5 (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.

scholarly journals Future respiratory hospital admissions from wildfire smoke under climate change in the Western US

2016 ◽  
Vol 11 (12) ◽  
pp. 124018 ◽  
Author(s):  
Jia Coco Liu ◽  
Loretta J Mickley ◽  
Melissa P Sulprizio ◽  
Xu Yue ◽  
Roger D Peng ◽  
...  
Keyword(s):  
Climate Change ◽  
Hospital Admissions ◽  
Wildfire Smoke ◽  
Western Us

scholarly journals A Review of Dengue’s Historical and Future Health Risk from a Changing Climate

2021 ◽  
Author(s):  
Sutyajeet Soneja ◽  
Gina Tsarouchi ◽  
Darren Lumbroso ◽  
Dao Khanh Tung
Keyword(s):  
Climate Change ◽  
Health Risk ◽  
Dengue Infection ◽  
Future Health ◽  
Adaptation Measures ◽  
Lag Effects ◽  
Risk Estimates ◽  
The World ◽  
The Relationship ◽  
Research And Policy

Abstract Purpose of review The purpose of this review is to summarize research articles that provide risk estimates for the historical and future impact that climate change has had upon dengue published from 2007 through 2019. Recent findings Findings from 30 studies on historical health estimates, with the majority of the studies conducted in Asia, emphasized the importance of temperature, precipitation, and relative humidity, as well as lag effects, when trying to understand how climate change can impact the risk of contracting dengue. Furthermore, 35 studies presented findings on future health risk based upon climate projection scenarios, with a third of them showcasing global level estimates and findings across the articles emphasizing the need to understand risk at a localized level as the impacts from climate change will be experienced inequitably across different geographies in the future. Summary Dengue is one of the most rapidly spreading viral diseases in the world, with ~390 million people infected worldwide annually. Several factors have contributed towards its proliferation, including climate change. Multiple studies have previously been conducted examining the relationship between dengue and climate change, both from a historical and a future risk perspective. We searched the U.S. National Institute of Environmental Health (NIEHS) Climate Change and Health Portal for literature (spanning January 2007 to September 2019) providing historical and future health risk estimates of contracting dengue infection in relation to climate variables worldwide. With an overview of the evidence of the historical and future health risk posed by dengue from climate change across different regions of the world, this review article enables the research and policy community to understand where the knowledge gaps are and what areas need to be addressed in order to implement localized adaptation measures to mitigate the health risks posed by future dengue infection.

Managing the health effects of climate change

The Lancet ◽  
2009 ◽  
Vol 373 (9676) ◽  
pp. 1693-1733 ◽  
Author(s):  
Anthony Costello ◽  
Mustafa Abbas ◽  
Adriana Allen ◽  
Sarah Ball ◽  
Sarah Bell ◽  
...  
Keyword(s):  
Climate Change ◽  
Health Effects

scholarly journals Ensemble Predictions of Air Pollutants in China in 2013 for Health Effects Studies Using WRF/CMAQ Modeling System with Four Emission Inventories

2017 ◽  
Author(s):  
Jianlin Hu ◽  
Xun Li ◽  
Lin Huang ◽  
Qi Ying ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Health Effects ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Model Performance ◽  
Observation Data ◽  
Emission Inventories ◽  
Air Quality Model ◽  
Quality Model ◽  
Future Health

Abstract. Accurate exposure estimates are required for health effects analyses of severe air pollution in China. Chemical transport models (CTMs) are widely used tools to provide detailed information of spatial distribution, chemical composition, particle size fractions, and source origins of pollutants. The accuracy of CTMs' predictions in China is largely affected by the uncertainties of public available emission inventories. The Community Multi-scale Air Quality model (CMAQ) with meteorological inputs from the Weather Research and Forecasting model (WRF) were used in this study to simulate air quality in China in 2013. Four sets of simulations were conducted with four different anthropogenic emission inventories, including the Multi-resolution Emission Inventory for China (MEIC), the Emission Inventory for China by School of Environment at Tsinghua University (SOE), the Emissions Database for Global Atmospheric Research (EDGAR), and the Regional Emission inventory in Asia version 2 (REAS2). Model performance was evaluated against available observation data from 422 sites in 60 cities across China. Model predictions of O3 and PM2.5 with the four inventories generally meet the criteria of model performance, but difference exists in different pollutants and different regions among the inventories. Ensemble predictions were calculated by linearly combining the results from different inventories under the constraint that sum of the squared errors between the ensemble results and the observations from all the cities was minimized. The ensemble annual concentrations show improved agreement with observations in most cities. The mean fractional bias (MFB) and mean fractional errors (MFE) of the ensemble predicted annual PM2.5 at the 60 cities are −0.11 and 0.24, respectively, which are better than the MFB (−0.25–−0.16) and MFE (0.26–0.31) of individual simulations. The ensemble annual 1-hour peak O3 (O3-1 h) concentrations are also improved, with mean normalized bias (MNB) of 0.03 and mean normalized errors (MNE) of 0.14, compared to MNB of 0.06–0.19 and MNE of 0.16–0.22 of the individual predictions. The ensemble predictions agree better with observations with daily, monthly, and annual averaging times in all regions of China for both PM2.5 and O3-1 h. The study demonstrates that ensemble predictions by combining predictions from individual emission inventories can improve the accuracy of predicted temporal and spatial distributions of air pollutants. This study is the first ensemble model study in China using multiple emission inventories and the results are publicly available for future health effects studies.

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