Research of Mechanism of Fire Protection with Wood Lacquer

The effect of the composition on the weight loss of wood protected by a coating based on inorganic and organic substances in the process of thermal exposure, which is a feature of the study of the flame retardant effectiveness of the composition, is investigated. The solution of this problem is carried out by specially developed methods. The influence of fire protection under the influence of high-temperature heat flux on the change in the process of loss of mass of fire-protected wood is determined and the mechanism of kinetics of action of the composition is characterized, which is characterized by a decrease in the speed of flame propagation and mass loss. The results of thermogravimetric studies determined the weight loss of the coatings as a function of temperature, the results of which investigated the activation energy at the temperature decomposition of the coatings and found that for wood it was 36.56 kJ / mol, and in the case of fire protection it increased 2.3 times. which makes it possible to conclude that it is advisable to use lacquer varnish to improve the fire retardant efficiency of wood. Thus, for the specimen of fire-retardant lacquer wood, there is a gradual decrease in temperature, ie, the work of the coating is fixed, and, accordingly, the activation energy is increased during the decomposition of the wood. In order to establish the flame retardant efficiency in the application of high-temperature blowing lacquer, studies were conducted to determine the combustibility index of wood by mass loss, flame spread and temperature increase of flue gases and found that when processing wood goes to the group of combustible materials with a burning index.

An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting

Internet of Things (IoT) appliances, especially those realized through wireless sensor networks (WSNs), have been a dominant subject for heavy research in the environmental and agricultural sectors. To address the ever-increasing demands for real-time monitoring and sufficiently handle the growing volumes of raw data, the cloud/fog computing paradigm is deemed a highly promising solution. This paper presents a WSN-based IoT system that seamlessly integrates all aforementioned technologies, having at its core the cloud/fog hybrid network architecture. The system was intensively validated using a demo prototype in the Ionian University facilities, focusing on response time, an important metric of future smart applications. Further, the developed prototype is able to autonomously adjust its sensing behavior based on the criticality of the prevailing environmental conditions, regarding one of the most notable climate hazards, wildfires. Extensive experimentation verified its efficiency and reported on its alertness and highly conforming characteristics considering the use-case scenario of Corfu Island’s 2019 fire risk severity. In all presented cases, it is shown that through fog leveraging it is feasible to contrive significant delay reduction, with high precision and throughput, whilst controlling the energy consumption levels. Finally, a user-driven web interface is highlighted to accompany the system; it is capable of augmenting the data curation and visualization, and offering real-time wildfire risk forecasting based on Chandler’s burning index scoring.

Response of Siberian River Discharge to Disturbances of Forests Caused by Wildfires

The objective of this work was to perform a quantitative analysis of the correlation between the forest burning index and abnormal decrease in river discharge under conditions of the cryolithozone of Siberia. We analyzed the long-term and seasonal variation of river discharge in Central Siberia (Nizhnyaya Tunguska and Podkamennaya Tunguska rivers) and in Eastern Siberia (Aldan, Viluy rivers) together with the forest burning dynamics within the river basins. The data on river discharge were obtained from the archive of The Global Runoff Data Centre for 1939–2015. The relative burned area (RBA) index was calculated from wildfire databases collected using satellite technique for 1996–2017. RBA was evaluated as the ratio of the annual burned area within the river basin to the total area of the river basin. RBA values of 2.5–6.1% per year were considered as extremely high. The analysis of available chronologies of extreme fire events in Central and Eastern Siberia showed high correlation (r > −0.55) with long-term data on the runoff minima. Abnormally low levels of discharge were 68–78% of the averaged annual rate. The most significant response of river discharge to the wildfire effect was shown for the summer–autumn period of the season after extreme burning in mid-summer.

TG Analysis on Burning Characteristic of Food Waste Ethanol Fermentation Residue Mixed with Coal

In order to reduce and re-utilize the ethanol fermentation residue from food waste, this study utilized residues to produce solid biomass fuel and carried out burning test by thermal gravity (TG) analysis. The results demonstrated that the residue from food waste shared the characteristic of high volatile content, high heat potential, low fixed carbon and low ash content. The burnable content was about 86.99% based on dry mass, while the heat potential was 23.06 MJ•kg-1. Lignitous coal or blind coal was adopted as the additive to improve the burning characteristic of the fermentation residue. The result for a mixture of lignitous coal and residue was better than those of blind coal with the increase of complex burning index S from 2.38E-07°C-3•min-2 to 7.99E-08°C-3•min-2, decrease of ignition point, enhancement of average burning ratio and amelioration of burning characteristic. All these provided theoretical guidance for fermentation residue utilization as the solid fuel.

NCEP - ECPC monthly to seasonal US fire danger forecasts

Five National Fire Danger Rating System indices (including the Ignition Component, Energy Release Component, Burning Index, Spread Component, and the Keetch–Byram Drought Index) and the Fosberg Fire Weather Index are used to characterise US fire danger. These fire danger indices and input meteorological variables, including temperature, relative humidity, precipitation, cloud cover and wind speed, can be skilfully predicted at weekly to seasonal time scales by a global to regional dynamical prediction system modified from the National Centers for Environmental Prediction’s Coupled Forecast System. The System generates global and regional spectral model ensemble forecasts, which in turn provide required input meteorological variables for fire danger. Seven-month US regional forecasts were generated every month from 1982 to 2007. This study shows that coarse-scale global predictions were more skilful than persistence, and fine-scale regional model predictions were more skilful than global predictions. The fire indices were better related to fire counts and area burned than meteorological variables, although relative humidity and temperature were useful predictors of fire characteristics.

A critical assessment of the Burning Index in Los Angeles County, California

The Burning Index (BI) is commonly used as a predictor of wildfire activity. An examination of data on the BI and wildfires in Los Angeles County, California, from January 1976 to December 2000 reveals that although the BI is positively associated with wildfire occurrence, its predictive value is quite limited. Wind speed alone has a higher correlation with burn area than BI, for instance, and a simple alternative point process model using wind speed, relative humidity, precipitation and temperature well outperforms the BI in terms of predictive power. The BI is generally far too high in winter and too low in fall, and may exaggerate the impact of individual variables such as wind speed or temperature during times when other variables, such as precipitation or relative humidity, render the environment ill suited for wildfires.

Seasonal fire danger forecasts for the USA

The Scripps Experimental Climate Prediction Center has been making experimental, near-real-time, weekly to seasonal fire danger forecasts for the past 5 years. US fire danger forecasts and validations are based on standard indices from the National Fire Danger Rating System (NFDRS), which include the ignition component (IC), energy release component (ER), burning index (BI), spread component (SC), and the Keetch–Byram drought index (KB). The Fosberg fire weather index, which is a simplified form of the BI, has been previously used not only for the USA but also for other global regions and is thus included for comparison. As will be shown, all of these indices can be predicted well at weekly times scales and there is even skill out to seasonal time scales over many US West locations. The most persistent indices (BI and ER) tend to have the greatest seasonal forecast skill. The NFDRS indices also have a weak relation to observed fire characteristics such as fire counts and acres burned, especially when the validation fire danger indices are used.

Evaluation of the Experimental Climate Prediction Center's fire danger forecasts with remote automated weather station observations

The Scripps Experimental Climate Prediction Center has been routinely making regional forecasts of atmospheric elements and fire danger indices since 27 September 1997. This study evaluates these forecasts using selected remote automated weather station observations over the western USA. Bias and anomaly correlations are computed for daily 2-m maximum, minimum, average temperature, 2-m maximum, minimum and average relative humidity, precipitation and afternoon 10-m wind speed, and four National Fire Danger Rating System indices—ignition component, spread component, burning index and energy release component. Of the atmospheric elements, temperature generally correlates well, but relative humidity, precipitation and wind speed are less correlated. Fire danger indices have much lower correlations, but do show useful spatial structure in some areas such as Southern California, Arizona and Nevada.

Relating Burning Index to Wildfire Workload Over Broad Geographic Areas

The burning index of the National Fire Danger Rating System is designed to measure potential fire workload over broad geographic areas that can be repre sented as being homogeneous with respect to fuel, topo graphic, and weather conditions. The utility of this index is confirmed by its relation to three measures of fire workload-number of fires, area burned, and number of personnel used in fire suppression for National Forests in southern California. The distributions of these mea sures over 15 years were skewed heavily to the right ("heavy-tailed distributions"). We selected the75 th, 90th, and 95th percentile values of each distribution at ten percentile values of the burning index to investigate and display the association between fire workload and the burning index. The results provide a distinct view of the direct relationship between wildfire workload and critical burning index values for the southern California area as a whole, and point to the potential value of this approach for anticipating fire control problems in other areas.