Simulation and thermal imaging of the 2006 Esperanza Wildfire in southern California: application of a coupled weather–wildland fire model

2014 ◽  
Vol 23 (6) ◽  
pp. 755 ◽  
Author(s):  
Janice L. Coen ◽  
Philip J. Riggan
Keyword(s):  
Thermal Imaging ◽  
Large Scale ◽  
Transient Flow ◽  
Wildland Fire ◽  
Fire Spread ◽  
Early Morning ◽  
Fuel Load ◽  
Dynamic Interactions ◽  
Riverside County ◽  
Layer Flow

The 2006 Esperanza Fire in Riverside County, California, was simulated with the Coupled Atmosphere–Wildland Fire Environment (CAWFE) model to examine how dynamic interactions of the atmosphere with large-scale fire spread and energy release may affect observed patterns of fire behaviour as mapped using the FireMapper thermal-imaging radiometer. CAWFE simulated the meteorological flow in and near the fire, the fire’s growth as influenced by gusty Santa Ana winds and interactions between the fire and weather through fire-induced winds during the first day of burning. The airflow was characterised by thermally stratified, two-layer flow channelled between the San Bernardino and San Jacinto mountain ranges with transient flow accelerations driving the fire in Cabazon Peak’s lee. The simulation reproduced distinguishing features of the fire including its overall direction and width, rapid spread west-south-westward across canyons, spread up canyons crossing its southern flank, splitting into two heading regions and feathering of the fire line. The simulation correctly depicted the fire’s location at the time of an early-morning incident involving firefighter fatalities. It also depicted periods of deep plume growth, but anomalously described downhill spread of the head of the fire under weak winds that was less rapid than observed. Although capturing the meteorological flow was essential to reproducing the fire’s evolution, fuel factors including fuel load appeared to play a secondary role.

Fuel load, structure, and potential fire behaviour in black spruce bogs

2015 ◽  
Vol 45 (7) ◽  
pp. 888-899 ◽  
Author(s):  
D.C. Johnston ◽  
M.R. Turetsky ◽  
B.W. Benscoter ◽  
B.M. Wotton
Keyword(s):  
High Intensity ◽  
Large Scale ◽  
Black Spruce ◽  
Fire Spread ◽  
Extreme Weather Events ◽  
Fuel Load ◽  
Fire Season ◽  
Future Climate Change ◽  
Organic Soils ◽  
Crown Fire

Boreal peatlands in Canada comprise a substantial store of soil organic carbon (peat), and this peat is vulnerable to extensive burning during periods of extended drying. Increased frequency of extreme weather events in boreal regions is expected with future climate change, and the conditions that would support sustained smouldering peat combustion within peatlands may be more common. Organic soils tend to burn by smouldering combustion, a very slow-moving process in fuels such as those found in peatlands. Thus the most extreme conditions for carbon loss to the atmosphere due to the burning of peat likely occur when widespread propagation of flaming combustion leads to widespread initiation of smouldering. To investigate the potential for large-scale, high-intensity fire spread across forested bogs, we examined the fuel conditions in forested bogs necessary to support active crown fire. We measured surface and canopy fine fuels (those available to contribute to the propagating energy flux of the main flaming front) across a postfire chronosequence of forested boreal bog from central Alberta, Canada. We found that fuel load of fine surface material remained relatively constant across the chronosequence and at levels large enough to support crown fire initiation. Black spruce (Picea mariana (Mill.) B.S.P.) regeneration begins to fill in the crown space with increasing time since disturbance and achieves crown bulk densities similar to black spruce upland forests. We estimated that after about 80 years, the black spruce canopy has developed enough available fuel to support active crown fire on between 10% to 40% of days in a typical fire season in central Alberta, Canada. Broad-scale propagation of high-intensity fire across a peatland when coincident with drought-induced lower moisture in deep peatland layers has the potential to lead to a substantial release of stored terrestrial carbon.

scholarly journals EGCG binds intrinsically disordered N-terminal domain of p53 and disrupts p53-MDM2 interaction

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jing Zhao ◽  
Alan Blayney ◽  
Xiaorong Liu ◽  
Lauren Gandy ◽  
Weihua Jin ◽  
...  
Keyword(s):  
Large Scale ◽  
Molecular Mechanisms ◽  
Epigallocatechin Gallate ◽  
Cancer Drug ◽  
Dynamic Interactions ◽  
Cancer Drug Discovery ◽  
Intrinsically Disordered ◽  
Terminal Domain ◽  
Cancerous Cells

AbstractEpigallocatechin gallate (EGCG) from green tea can induce apoptosis in cancerous cells, but the underlying molecular mechanisms remain poorly understood. Using SPR and NMR, here we report a direct, μM interaction between EGCG and the tumor suppressor p53 (KD = 1.6 ± 1.4 μM), with the disordered N-terminal domain (NTD) identified as the major binding site (KD = 4 ± 2 μM). Large scale atomistic simulations (>100 μs), SAXS and AUC demonstrate that EGCG-NTD interaction is dynamic and EGCG causes the emergence of a subpopulation of compact bound conformations. The EGCG-p53 interaction disrupts p53 interaction with its regulatory E3 ligase MDM2 and inhibits ubiquitination of p53 by MDM2 in an in vitro ubiquitination assay, likely stabilizing p53 for anti-tumor activity. Our work provides insights into the mechanisms for EGCG’s anticancer activity and identifies p53 NTD as a target for cancer drug discovery through dynamic interactions with small molecules.

scholarly journals Current Wildland Fire Patterns and Challenges in Europe: A Synthesis of National Perspectives

2021 ◽  
Vol 14 ◽  
pp. 117862212110281
Author(s):  
Nieves Fernandez-Anez ◽  
Andrey Krasovskiy ◽  
Mortimer Müller ◽  
Harald Vacik ◽  
Jan Baetens ◽  
...  
Keyword(s):  
Land Use ◽  
Large Scale ◽  
Wildland Fire ◽  
Human Life ◽  
Local Analysis ◽  
Wildland Fires ◽  
Fire Statistics ◽  
Quantitative Evidence ◽  
Wide Range ◽  
Fire Patterns

Changes in climate, land use, and land management impact the occurrence and severity of wildland fires in many parts of the world. This is particularly evident in Europe, where ongoing changes in land use have strongly modified fire patterns over the last decades. Although satellite data by the European Forest Fire Information System provide large-scale wildland fire statistics across European countries, there is still a crucial need to collect and summarize in-depth local analysis and understanding of the wildland fire condition and associated challenges across Europe. This article aims to provide a general overview of the current wildland fire patterns and challenges as perceived by national representatives, supplemented by national fire statistics (2009–2018) across Europe. For each of the 31 countries included, we present a perspective authored by scientists or practitioners from each respective country, representing a wide range of disciplines and cultural backgrounds. The authors were selected from members of the COST Action “Fire and the Earth System: Science & Society” funded by the European Commission with the aim to share knowledge and improve communication about wildland fire. Where relevant, a brief overview of key studies, particular wildland fire challenges a country is facing, and an overview of notable recent fire events are also presented. Key perceived challenges included (1) the lack of consistent and detailed records for wildland fire events, within and across countries, (2) an increase in wildland fires that pose a risk to properties and human life due to high population densities and sprawl into forested regions, and (3) the view that, irrespective of changes in management, climate change is likely to increase the frequency and impact of wildland fires in the coming decades. Addressing challenge (1) will not only be valuable in advancing national and pan-European wildland fire management strategies, but also in evaluating perceptions (2) and (3) against more robust quantitative evidence.

scholarly journals A Deep Learning Approach to Downscale Geostationary Satellite Imagery for Decision Support in High Impact Wildfires

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 294
Author(s):  
Nicholas F. McCarthy ◽  
Ali Tohidi ◽  
Yawar Aziz ◽  
Matt Dennie ◽  
Mario Miguel Valero ◽  
...  
Keyword(s):  
Deep Learning ◽  
Decision Support ◽  
Real Time ◽  
Forest Fires ◽  
Wildland Fire ◽  
Fire Spread ◽  
Low Earth Orbit ◽  
Practical Implementation ◽  
Spatiotemporal Resolution ◽  
Active Fire

Scarcity in wildland fire progression data as well as considerable uncertainties in forecasts demand improved methods to monitor fire spread in real time. However, there exists at present no scalable solution to acquire consistent information about active forest fires that is both spatially and temporally explicit. To overcome this limitation, we propose a statistical downscaling scheme based on deep learning that leverages multi-source Remote Sensing (RS) data. Our system relies on a U-Net Convolutional Neural Network (CNN) to downscale Geostationary (GEO) satellite multispectral imagery and continuously monitor active fire progression with a spatial resolution similar to Low Earth Orbit (LEO) sensors. In order to achieve this, the model trains on LEO RS products, land use information, vegetation properties, and terrain data. The practical implementation has been optimized to use cloud compute clusters, software containers and multi-step parallel pipelines in order to facilitate real time operational deployment. The performance of the model was validated in five wildfires selected from among the most destructive that occurred in California in 2017 and 2018. These results demonstrate the effectiveness of the proposed methodology in monitoring fire progression with high spatiotemporal resolution, which can be instrumental for decision support during the first hours of wildfires that may quickly become large and dangerous. Additionally, the proposed methodology can be leveraged to collect detailed quantitative data about real-scale wildfire behaviour, thus supporting the development and validation of fire spread models.

scholarly journals Pyrolysis Characteristics of Undervalued Wood Varieties in the Portuguese Charcoal Sector

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2537
Author(s):  
Felix Charvet ◽  
Felipe Silva ◽  
Luís Ruivo ◽  
Luís Tarelho ◽  
Arlindo Matos ◽  
...  
Keyword(s):  
Large Scale ◽  
Fixed Bed ◽  
Management Control ◽  
Fixed Bed Reactor ◽  
Fuel Load ◽  
Charcoal Production ◽  
Pyrolysis Characteristics ◽  
Major Market ◽  
Burnt Wood ◽  
Fuel Particles

Charcoal production in Portugal is mostly based on the valorization of woody residues from cork oak and holm oak, the latter being considered a reference feedstock in the market. Nevertheless, since wildfire prevention became a priority in Portugal, after the recent dramatic wildfires, urgent actions are being conducted to reduce the fuel load in the forests, which is increasing the amount of biomass that is available for valorization. Additionally, biomass residues from agriculture, forest management, control of invasive species, partially burnt wood from post-fire recovery actions, and waste wood from storm devastated forests need also to be considered within the national biomass valorization policies. This has motivated the present work on whether the carbonization process can be used to valorize alternative woody biomasses not currently used on a large scale. For this purpose, slow pyrolysis experiments were carried out with ten types of wood, using a fixed bed reactor allowing the controlled heating of large fuel particles at 0.1 to 5 °C/min and final temperatures within 300–450 °C. Apart from an evaluation of the mass balance of the process, emphasis was given to the properties of the resulting charcoals considering its major market in Portugal—barbecue charcoal for both recreational and professional purposes.

Characterisation of the fuel and fire environment in southern Ontario’s tallgrass prairie

2015 ◽  
Vol 24 (8) ◽  
pp. 1118 ◽  
Author(s):  
Susan Kidnie ◽  
B. Mike Wotton
Keyword(s):  
Moisture Content ◽  
Tallgrass Prairie ◽  
Prescribed Burning ◽  
Fire Spread ◽  
Fuel Load ◽  
Prairie Restoration ◽  
Prescribed Burn ◽  
Spread Rate ◽  
Prescribed Burns ◽  
Tallgrass Prairie Restoration

Prescribed burning can be an integral part of tallgrass prairie restoration and management. Understanding fire behaviour in this fuel is critical to conducting safe and effective prescribed burns. Our goal was to quantify important physical characteristics of southern Ontario’s tallgrass fuel complex prior to and during prescribed burns and synthesise our findings into useful applications for the prescribed fire community. We found that the average fuel load in tallgrass communities was 0.70 kg m–2. Fuel loads varied from 0.38 to 0.96 kg m–2. Average heat of combustion did not vary by species and was 17 334 kJ kg–1. A moisture content model was developed for fully cured, matted field grass, which was found to successfully predict moisture content of the surface layers of cured tallgrass in spring. We observed 25 head fires in spring-season prescribed burns with spread rates ranging from 4 to 55 m min–1. Flame front residence time averaged 27 s, varying significantly with fuel load but not fire spread rate. A grassland spread rate model from Australia showed the closest agreement with observed spread rates. These results provide prescribed-burn practitioners in Ontario better information to plan and deliver successful burns.

scholarly journals Modelling and mitigating dose to firefighters from inhalation of radionuclides in wildland fire smoke

2015 ◽  
Vol 24 (5) ◽  
pp. 723 ◽  
Author(s):  
Brian J. Viner ◽  
Tim Jannik ◽  
Daniel Stone ◽  
Allan Hepworth ◽  
Luke Naeher ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Wildland Fire ◽  
Radioactive Material ◽  
Fuel Load ◽  
Base Case ◽  
Published Data ◽  
Case Scenario ◽  
Base Case Scenario ◽  
Fuel Loads ◽  
Radiological Dose

Firefighters responding to wildland fires where surface litter and vegetation contain radiological contamination will receive a radiological dose by inhaling resuspended radioactive material in the smoke. This may increase their lifetime risk of contracting certain types of cancer. Using published data, we modelled hypothetical radionuclide emissions, dispersion and dose for 70th and 97th percentile environmental conditions and for average and high fuel loads at the Savannah River Site. We predicted downwind concentration and potential dose to firefighters for radionuclides of interest (137Cs, 238Pu, 90Sr and 210Po). Predicted concentrations exceeded dose guidelines in the base case scenario emissions of 1.0 × 107 Bq ha–1 for 238Pu at 70th percentile environmental conditions and average fuel load levels for both 4- and 14-h shifts. Under 97th percentile environmental conditions and high fuel loads, dose guidelines were exceeded for several reported cases for 90Sr, 238Pu and 210Po. The potential for exceeding dose guidelines was mitigated by including plume rise (>2 m s–1) or moving a small distance from the fire owing to large concentration gradients near the edge of the fire. This approach can quickly estimate potential dose from airborne radionuclides in wildland fire and assist decision-making to reduce firefighter exposure.

scholarly journals Fractal properties of forest fires in Amazonia as a basis for modelling pan-tropical burnt area

2014 ◽  
Vol 11 (6) ◽  
pp. 1449-1459 ◽  
Author(s):  
I. N. Fletcher ◽  
L. E. O. C. Aragão ◽  
A. Lima ◽  
Y. Shimabukuro ◽  
P. Friedlingstein
Keyword(s):  
Forest Fires ◽  
Large Scale ◽  
Fire Spread ◽  
Small Scale ◽  
Burnt Area ◽  
Active Fire ◽  
Fractal Properties ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Current methods for modelling burnt area in dynamic global vegetation models (DGVMs) involve complex fire spread calculations, which rely on many inputs, including fuel characteristics, wind speed and countless parameters. They are therefore susceptible to large uncertainties through error propagation, but undeniably useful for modelling specific, small-scale burns. Using observed fractal distributions of fire scars in Brazilian Amazonia in 2005, we propose an alternative burnt area model for tropical forests, with fire counts as sole input and few parameters. This model is intended for predicting large-scale burnt area rather than looking at individual fire events. A simple parameterization of a tapered fractal distribution is calibrated at multiple spatial resolutions using a satellite-derived burnt area map. The model is capable of accurately reproducing the total area burnt (16 387 km2) and its spatial distribution. When tested pan-tropically using the MODIS MCD14ML active fire product, the model accurately predicts temporal and spatial fire trends, but the magnitude of the differences between these estimates and the GFED3.1 burnt area products varies per continent.

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