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.

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 Trends and spatial shifts in lightning fires and smoke concentrations in response to 21st century climate over the forests of the Western United States

2020 ◽  
Author(s):  
Yang Li ◽  
Loretta J. Mickley ◽  
Pengfei Liu ◽  
Jed O. Kaplan
Keyword(s):  
Climate Change ◽  
United States ◽  
21St Century ◽  
Transport Model ◽  
Fine Particulate Matter ◽  
The United States ◽  
Western United States ◽  
Fire Season ◽  
Future Climate Change ◽  
Chemical Transport Model

Abstract. Almost US$ 3bn per year is appropriated for wildfire management on public land in the United States. Recent studies have suggested that ongoing climate change will lead to warmer and drier conditions in the Western United States with a consequent increase in the number and size of wildfires, yet large uncertainty exists in these projections. To assess the influence of future changes in climate and land cover on lightning-caused wildfires in National Forests and Parks of the Western United States and the consequences of these fires on air quality, we link a dynamic vegetation model that includes a process-based representation of fire (LPJ-LMfire) to a global chemical transport model (GEOS-Chem). Under a scenario of moderate future climate change (RCP4.5), increasing lightning-caused wildfire enhances the burden of smoke fine particulate matter (PM), with mass concentration increases of ~ 53 % by the late-21st century during the fire season. In a high-emissions scenario (RCP8.5), smoke PM concentrations double by 2100. RCP8.5 also shows large, northward shifts in dry matter burned, leading to enhanced lightning-caused fire activity especially over forests in the northern states.

scholarly journals Historical greenhouse gas concentrations

2016 ◽  
Author(s):  
Malte Meinshausen ◽  
Elisabeth Vogel ◽  
Alexander Nauels ◽  
Katja Lorbacher ◽  
Nicolai Meinshausen ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Radiative Forcing ◽  
Sulfur Hexafluoride ◽  
Climate Model ◽  
Future Climate Change ◽  
Large Set ◽  
Mixing Ratios ◽  
Surface Mixing ◽  
Cooling Effects

Abstract. Atmospheric greenhouse gas concentrations are at unprecedented, record-high levels compared to pre-industrial reconstructions over the last 800,000 years. Those elevated greenhouse gas concentrations warm the planet and together with net cooling effects by aerosols, they are the reason of observed climate change over the past 150 years. An accurate representation of those concentrations is hence important to understand and model recent and future climate change. So far, community efforts to create composite datasets with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since 1980s. Here, we provide consolidated data sets of historical atmospheric (volume) mixing ratios of 43 greenhouse gases specifically for the purpose of climate model runs. The presented datasets are based on AGAGE and NOAA networks and a large set of literature studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved, and include seasonality over the period between year 0 to 2014. We assimilate data for CO2, methane (CH4) and nitrous oxide (N2O), 5 chlorofluorocarbons (CFCs), 3 hydrochlorofluorocarbons (HCFCs), 16 hydrofluorocarbons (HFCs), 3 halons, methyl bromide (CH3Br), 3 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen triflouride (NF3) and sulfuryl fluoride (SO2F2). We estimate 1850 annual and global mean surface mixing ratios of CO2 at 284.3 ppmv, CH4 at 808.2 ppbv and N2O at 273.0 ppbv and quantify the seasonal and hemispheric gradients of surface mixing ratios. Compared to earlier intercomparisons, the stronger implied radiative forcing in the northern hemisphere winter (due to the latitudinal gradient and seasonality) may help to improve the skill of climate models to reproduce past climate and thereby reduce uncertainty in future projections.

scholarly journals Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Joseph Leedale ◽  
Adrian M. Tompkins ◽  
Cyril Caminade ◽  
Anne E. Jones ◽  
Grigory Nikulin ◽  
...  
Keyword(s):  
Climate Change ◽  
Malaria Transmission ◽  
Climate Models ◽  
Climate Model ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Climate Projections ◽  
Model Ensemble ◽  
East African Community ◽  
Recent Climate

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

scholarly journals Projected changes in temperature and precipitation over mainland Southeast Asia by CMIP6 models

2021 ◽  
Author(s):  
S. Supharatid ◽  
J. Nafung ◽  
T. Aribarg
Keyword(s):  
Climate Change ◽  
Coupled Model ◽  
Southwest Monsoon ◽  
Future Climate Change ◽  
Boreal Summer ◽  
Northeast Monsoon ◽  
Adaptation Measures ◽  
Mitigation And Adaptation ◽  
Temperature And Precipitation ◽  
Projected Changes

Abstract Five mainland SEA countries (Cambodia, Laos, Myanmar, Vietnam, and Thailand) are threatened by climate change. Here, the latest 18 Coupled Model Intercomparison Project Phase 6 (CMIP6) is employed to examine future climate change in this region under two SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP2-4.5 and SSP5-8.5). The bias-corrected multi-model ensemble (MME) projects a warming (wetting) over Cambodia, Laos, Myanmar, Vietnam, and Thailand by 1.88–3.89, 2.04–4.22, 1.88–4.09, 2.03–4.25, and 1.90–3.96 °C (8.76–20.47, 12.69–21.10, 9.54–21.10, 13.47–22.12, and 7.03–15.17%) in the 21st century with larger values found under SSP5-8.5 than SSP2-4.5. The MME model displays approximately triple the current rainfall during the boreal summer. Overall, there are robust increases in rainfall during the Southwest Monsoon (3.41–3.44, 8.44–9.53, and 10.89–17.59%) and the Northeast Monsoon (−2.58 to 0.78, −0.43 to 2.81, and 2.32 to 5.45%). The effectiveness of anticipated climate change mitigation and adaptation strategies under SSP2-4.5 results in slowing down the warming trends and decreasing precipitation trends after 2050. All these findings imply that member countries of mainland SEA need to prepare for appropriate adaptation measures in response to the changing climate.

scholarly journals An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets

2020 ◽  
Vol 12 (4) ◽  
pp. 2959-2970
Author(s):  
Maialen Iturbide ◽  
José M. Gutiérrez ◽  
Lincoln M. Alves ◽  
Joaquín Bedia ◽  
Ruth Cerezo-Mota ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Atmospheric Model ◽  
Future Climate Change ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Scatter Plots ◽  
Projected Changes

Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

Evaluation of critical atmospheric patterns for the occurrence of forest fires in a climate change context in the northwest of Argentine Patagonia.

2021 ◽  
Author(s):  
Verónica Dankiewicz ◽  
Matilde M. Rusticucci ◽  
Soledad M. Collazo
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Fire Hazard ◽  
Fire Danger ◽  
Fire Season ◽  
Historical Period ◽  
Fire Weather Index ◽  
Mitigation And Adaptation ◽  
Argentine Patagonia ◽  
In Fire

<p>Forest fires are a global phenomenon and result from complex interactions between weather and climate conditions, ignition sources, and humans. Understanding these relationships will contribute to the development of management strategies for their mitigation and adaptation. In the context of climate change, fire hazard conditions are expected to increase in many regions of the world due to projected changes in climate, which include an increase in temperatures and the occurrence of more intense droughts. In Argentina, northwestern Patagonia is an area very sensitive to these changes because of its climate, vegetation, the urbanizations highly exposed to fires, and the proximity of two of the largest and oldest National Parks in the country. The main objective of this work is to analyze the possible influence of climate change on some atmospheric patterns related to fire danger in northwestern Argentine Patagonia. The data were obtained from two CMIP5 global climate models CSIRO-Mk3-6-0 and GFDL-ESM2G and the CMIP5 multimodel ensemble, in the historical experiment and two representative concentration pathways: RCP2.6 and RCP8.5. The data used in this study cover the region's fire season (FS), from September to April, and were divided into five periods of 20 years each, a historical period (1986-2005), which was compared with four future periods: near (2021-2040), medium (2041-2060), far (2061-2080) and very far (2081-2100). The statistical distribution of the monthly composite fields of the FS was studied for some of the main fire drivers: sea surface temperature in the region of the index EN3.4 (SST EN3.4), sea level pressure anomalies ​​(SLP), surface air temperature anomalies (TAS), the Antarctic Oscillation Index (AOI) and monthly accumulated precipitation (PR). In addition, the partial correlation coefficient was calculated to determine the independent contribution of each atmospheric variable to the Fire Weather Index (FWI), used as a proxy for the mean FS danger. As a result, we observed that SST EN3.4 is the only one that could indicate a reduction in fire danger in the future, although no variable presented a significant contribution to the FWI with respect to the others. In the RCP8.5 scenario, greater fire danger is projected by the TAS, the PR, the SLP, and relative by the AOI, while in the RCP2.6 scenario, only the TAS shows influence leading to an increase, which would be offset by the opposite influence of SST EN3.4 for the same periods in this scenario. In conclusion, in RCP8.5 it could be assumed that there is a trend towards an increase in fire danger given the influence in this sense of most of the variables analyzed, but not in RCP2.6 where there would be no significant changes.</p>

Potential changes in monthly fire risk in the eastern Canadian boreal forest under future climate change

2009 ◽  
Vol 39 (12) ◽  
pp. 2369-2380 ◽  
Author(s):  
Héloïse Le Goff ◽  
Mike D. Flannigan ◽  
Yves Bergeron
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Fire Risk ◽  
Weather Conditions ◽  
Future Climate ◽  
Fire Season ◽  
Future Climate Change ◽  
Change Scenario ◽  
Fire Weather Index ◽  
Fire Activity

The main objective of this paper is to evaluate whether future climate change would trigger an increase in the fire activity of the Waswanipi area, central Quebec. First, we used regression analyses to model the historical (1973–2002) link between weather conditions and fire activity. Then, we calculated Fire Weather Index system components using 1961–2100 daily weather variables from the Canadian Regional Climate Model for the A2 climate change scenario. We tested linear trends in 1961–2100 fire activity and calculated rates of change in fire activity between 1975–2005, 2030–2060, and 2070–2100. Our results suggest that the August fire risk would double (+110%) for 2100, while the May fire risk would slightly decrease (–20%), moving the fire season peak later in the season. Future climate change would trigger weather conditions more favourable to forest fires and a slight increase in regional fire activity (+7%). While considering this long-term increase, interannual variations of fire activity remain a major challenge for the development of sustainable forest management.

scholarly journals Changes to the tropical circulation in the mid-Pliocene and their implications for future climate

2017 ◽  
Vol 13 (2) ◽  
pp. 135-147 ◽  
Author(s):  
Shawn Corvec ◽  
Christopher G. Fletcher
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Hadley Circulation ◽  
Walker Circulation ◽  
Tropical Indian Ocean ◽  
Future Climate ◽  
Sea Surface ◽  
Future Climate Change ◽  
Overturning Circulation ◽  
Future Projections

Abstract. The two components of the tropical overturning circulation, the meridional Hadley circulation (HC) and the zonal Walker circulation (WC), are key to the re-distribution of moisture, heat and mass in the atmosphere. The mid-Pliocene Warm Period (mPWP; ∼ 3.3–3 Ma) is considered a very rough analogue of near-term future climate change, yet changes to the tropical overturning circulations in the mPWP are poorly understood. Here, climate model simulations from the Pliocene Model Intercomparison Project (PlioMIP) are analyzed to show that the tropical overturning circulations in the mPWP were weaker than preindustrial circulations, just as they are projected to be in future climate change. The weakening HC response is consistent with future projections, and its strength is strongly related to the meridional gradient of sea surface warming between the tropical and subtropical oceans. The weakening of the WC is less robust in PlioMIP than in future projections, largely due to inter-model variations in simulated warming of the tropical Indian Ocean (TIO). When the TIO warms faster (slower) than the tropical mean, local upper tropospheric divergence increases (decreases) and the WC weakens less (more). These results provide strong evidence that changes to the tropical overturning circulation in the mPWP and future climate are primarily controlled by zonal (WC) and meridional (HC) gradients in tropical–subtropical sea surface temperatures.

THE SCIENCE UNDERLYING THE ISSUE OF CLIMATE CHANGE AND PROSPECTS FOR ADAPTATION

2001 ◽  
Vol 41 (1) ◽  
pp. 689
Author(s):  
C.D. Mitchell ◽  
G.I. Pearman
Keyword(s):  
Climate Change ◽  
Risk Management ◽  
Greenhouse Gas ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Initial Response ◽  
Lower Atmosphere ◽  
Future Climate Change ◽  
Atmospheric Concentration

The prospect of global-scale changes in climate resulting from changes in atmospheric greenhouse gas concentrations has produced a complex set of public and private- sector responses. This paper reviews several elements of this issue that are likely to be most important to industry.Scientific research continues to provide evidence to suggest that global climate will change significantly over the coming decades due to increases in the atmospheric concentration of greenhouse gases. Nonetheless, there exists a debate over the difference between observations of temperature retrieved from satellite and temperature measurements taken from the surface. Recent research undertaken to inform the debate is discussed, with the conclusion that there are real differences in trend between the surface and the lower atmosphere that can be explained in physical terms. Attention is turning to developing an understanding as to why climate model results show apparently consistent trends between the surface and the lower atmosphere, in contrast to these observations.While such uncertainties in the underlying science have been used to question whether action on the greenhouse issues is necessary, the initial response, as evidenced by international negotiations, has been to start mitigating greenhouse gas emissions. Adaptation to future climate change has received less attention than mitigation. A number of reasons for this are discussed, including the fact that regional scenarios of climate change are uncertain.The principles of risk management may be one way to manage the uncertainties associated with projections of regional climate change. Although the application of risk management to the potential impacts of climate change requires further investigation, elements of such a framework are identified, and include:Identifying the critical climate-related thresholds that are important to industry and its operations (for example, a 1-in-100 year return tropical cyclone).Using this understanding to analyse, and where possible quantify, industry’s pre-existing or baseline adaptive state through the use of sensitivity surfaces and quantified thresholds (for example, were facilities designed for a 1-in-100 event or a 1-in-500 year event?)Establishing probabilistic statements or scenarios of climate that are relevant to industry practice (for example, risk of a storm surge may be more important to operations than elevated wind strength; if so, what is the probability that an event will exceed the design threshold during the lifetime of the facility?).Bringing information on existing adaptive mechanisms together with climate scenarios to produce a quantitative risk assessment.Deciding on risk treatment (additional adaptive measures).

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