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

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.

Does climate change affect the chronobiological trends in occurrence of acute coronary syndromes?

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
L Kuzma ◽  
A Kurasz ◽  
M Niwinska ◽  
EJ Dabrowski ◽  
M Swieczkowski ◽  
...  
Keyword(s):  
Climate Change ◽  
Acute Coronary Syndromes ◽  
Hospital Admissions ◽  
Global Climate ◽  
Weather Conditions ◽  
Temperature Changes ◽  
Funding Sources ◽  
Relative Risks ◽  
Coronary Syndromes ◽  
Atmospheric Changes

Abstract Funding Acknowledgements Type of funding sources: None. Background Acute coronary syndromes (ACS) are the leading cause of death all over the world, in the last years chronobiology of their occurrence has been changing. Purpose The aim of this study was to assess the influence of climate change on hospital admissions due to ACS. Methods Medical records of 10,529 patients hospitalized for ACS in 2008–2017 were examined. Weather conditions data were obtained from the Institute of Meteorology. Results Among the patients, 3537 (33.6%) were hospitalized for STEMI, 3947 (37.5%) for NSTEMI, and 3045 (28.9%) for UA. The highest seasonal mean for ACS was recorded in spring (N = 2782, mean = 2.52, SD = 1.7; OR 1.07; 95% CI 1.0-1.2; P = 0.049) and it was a season with the highest temperature changes day to day (Δ temp.=11.7). On the other hand, every 10ºC change in temperature was associated with an increased admission due to ACS by 13% (RR 1.13; 95% CI 1.04-1.3; P = 0.008). Analysis of weekly changes showed that the highest frequency of ACS occurred on Thursday (N = 1703, mean = 2.7, SD = 1.9; OR 1.16; 95% CI 1.0-1.23; P = 0.004), in STEMI subgroup it was Monday (N = 592, mean = 0.9, SD = 1.6, OR 1.2; 95% CI 1.1-1.4; P = 0.002). Sunday was associated with decreased admissions due to all types of ACS (N = 1098, mean = 1.7, SD = 1.4; OR 0.69; 95% CI 0.6-0.8, P < 0.001). In the second half of the study period (2013-2018) the relative risks of hospital admissions due to ACS were 1.043 (95%CI: 1.009-1.079, P = 0.014, lag 0) and 0.957 (95%CI: 0.925-0.990, P = 0.010, lag 1) for each 10ºC decrease in temperature; 1.049 (95% CI: 1.015-1.084, P = 0.004, lag 0) and 1.045 (95%CI: 1.011-1.080, P = 0.008, lag 1) for each 10 hPa decrease in atmospheric pressure and 1.180 (95% CI: 1.078-1.324, P = 0.007, lag 0) for every 10ºC change in temperature. For the first half of the study the risk was significantly lower. Conclusion We observed a shift in the seasonal peak of ACS occurrence from winter to spring which may be related to temperature fluctuation associated with climate change in this season. The lowest frequency of ACS took place on weekends. Atmospheric changes had a much more pronounced effect on admissions due to ACS in the second half of the analyzed period, which is in line with the dynamics of global climate change.

scholarly journals Forest fires and climate-induced tree range shifts in the western US

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Avery P. Hill ◽  
Christopher B. Field
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Fire Management ◽  
Range Shifts ◽  
Inventory Analysis ◽  
Plant Populations ◽  
Wildfire Occurrence ◽  
Western Us ◽  
The Difference ◽  
Climate Space

AbstractDue to climate change, plant populations experience environmental conditions to which they are not adapted. Our understanding of the next century’s vegetation geography depends on the distance, direction, and rate at which plant distributions shift in response to a changing climate. In this study we test the sensitivity of tree range shifts (measured as the difference between seedling and mature tree ranges in climate space) to wildfire occurrence, using 74,069 Forest Inventory Analysis plots across nine states in the western United States. Wildfire significantly increased the seedling-only range displacement for 2 of the 8 tree species in which seedling-only plots were displaced from tree-plus-seedling plots in the same direction with and without recent fire. The direction of climatic displacement was consistent with that expected for warmer and drier conditions. The greater seedling-only range displacement observed across burned plots suggests that fire can accelerate climate-related range shifts and that fire and fire management will play a role in the rate of vegetation redistribution in response to climate change.

scholarly journals Comparison of wildfire smoke estimation methods and associations with cardiopulmonary-related hospital admissions

GeoHealth ◽  
2017 ◽  
Vol 1 (3) ◽  
pp. 122-136 ◽  
Author(s):  
Ryan W. Gan ◽  
Bonne Ford ◽  
William Lassman ◽  
Gabriele Pfister ◽  
Ambarish Vaidyanathan ◽  
...  
Keyword(s):  
Hospital Admissions ◽  
Estimation Methods ◽  
Wildfire Smoke

scholarly journals How will climate change affect wildland fire severity in the western US?

2016 ◽  
Vol 11 (3) ◽  
pp. 035002 ◽  
Author(s):  
Sean A Parks ◽  
Carol Miller ◽  
John T Abatzoglou ◽  
Lisa M Holsinger ◽  
Marc-André Parisien ◽  
...  
Keyword(s):  
Climate Change ◽  
Wildland Fire ◽  
Fire Severity ◽  
Western Us

scholarly journals SnowClim v1.0: High-resolution snow model and data for the western United States

2021 ◽  
Author(s):  
Abby C. Lute ◽  
John Abatzoglou ◽  
Timothy Link
Keyword(s):  
Climate Change ◽  
United States ◽  
Spatial Resolution ◽  
Snow Water Equivalent ◽  
High Spatial Resolution ◽  
Western United States ◽  
Climate Data ◽  
Western Us ◽  
Snow Water ◽  
Snow Model

Abstract. Seasonal snowpack dynamics shape the biophysical and societal characteristics of many global regions. However, snowpack accumulation and duration have generally declined in recent decades largely due to anthropogenic climate change. Mechanistic understanding of snowpack spatiotemporal heterogeneity and climate change impacts will benefit from snow data products that are based on physical principles, that are simulated at high spatial resolution, and that cover large geographic domains. Existing datasets do not meet these requirements, hindering our ability to understand both contemporary and changing snow regimes and to develop adaptation strategies in regions where snowpack patterns and processes are important components of Earth systems. We developed a computationally efficient physics-based snow model, SnowClim, that can be run in the cloud. The model was evaluated and calibrated at Snowpack Telemetry sites across the western United States (US), achieving a site-median root mean square error for daily snow water equivalent of 62 mm, bias in peak snow water equivalent of −9.6 mm, and bias in snow duration of 1.2 days when run hourly. Positive biases were found at sites with mean winter temperature above freezing where the estimation of precipitation phase is prone to errors. The model was applied to the western US using newly developed forcing data created by statistically downscaling pre-industrial, historical, and pseudo-global warming climate data from the Weather Research and Forecasting (WRF) model. The resulting product is the SnowClim dataset, a suite of summary climate and snow metrics for the western US at 210 m spatial resolution (Lute et al., 2021). The physical basis, large extent, and high spatial resolution of this dataset will enable novel analyses of changing hydroclimate and its implications for natural and human systems.

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