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PurposeThe current fire protection measures in buildings do not account for all contemporary fire hazard issues, which has made fire safety a growing concern. Therefore, this paper aims to present a critical review of current fire protection measures and their applicability to address current challenges relating to fire hazards in buildings.Design/methodology/approachTo overcome fire hazards in buildings, impact of fire hazards is also reviewed to set the context for fire protection measures. Based on the review, an integrated framework for mitigation of fire hazards is proposed. The proposed framework involves enhancement of fire safety in four key areas: fire protection features in buildings, regulation and enforcement, consumer awareness and technology and resources advancement. Detailed strategies on improving fire safety in buildings in these four key areas are presented, and future research and training needs are identified.FindingsCurrent fire protection measures lead to an unquantified level of fire safety in buildings, provide minimal strategies to mitigate fire hazard and do not account for contemporary fire hazard issues. Implementing key measures that include reliable fire protection systems, proper regulation and enforcement of building code provisions, enhancement of public awareness and proper use of technology and resources is key to mitigating fire hazard in buildings. Major research and training required to improve fire safety in buildings include developing cost-effective fire suppression systems and rational fire design approaches, characterizing new materials and developing performance-based codes.Practical implicationsThe proposed framework encompasses both prevention and management of fire hazard. To demonstrate the applicability of this framework in improving fire safety in buildings, major limitations of current fire protection measures are identified, and detailed strategies are provided to address these limitations using proposed fire safety framework.Social implicationsFire represents a severe hazard in both developing and developed countries and poses significant threat to life, structure, property and environment. The proposed framework has social implications as it addresses some of the current challenges relating to fire hazard in buildings and will enhance overall fire safety.Originality/valueThe novelty of proposed framework lies in encompassing both prevention and management of fire hazard. This is unlike current fire safety improvement strategies, which focus only on improving fire protection features in buildings (i.e. managing impact of fire hazard) using performance-based codes. To demonstrate the applicability of this framework in improving fire safety in buildings, major limitations of current fire protection measures are identified and detailed strategies are provided to address these limitations using proposed fire safety framework. Special emphasis is given to cost-effectiveness of proposed strategies, and research and training needs for further enhancing building fire safety are identified.

Cheatgrass (Bromus tectorum) is an invasive grass pervasive across the Intermountain Western US and linked to major increases in fire frequency. Despite widespread ecological impacts associated with cheatgrass, we lack a spatially extensive model of cheatgrass invasion in the Intermountain West. Here, we leverage satellite phenology predictors and thousands of field surveys of cheatgrass abundance to create regional models of cheatgrass distribution and percent cover. We compare cheatgrass presence to fire probability, fire seasonality and ignition source. Regional models of percent cover had low predictive power (34% of variance explained), but distribution models based on a threshold of 15% cover to differentiate high abundance from low abundance had an overall accuracy of 74%. Cheatgrass achieves ≥ 15% cover over 210,000 km2 (31%) of the Intermountain West. These lands were twice as likely to burn as those with low abundance, and four times more likely to burn multiple times between 2000 and 2015. Fire probability increased rapidly at low cheatgrass cover (1–5%) but remained similar at higher cover, suggesting that even small amounts of cheatgrass in an ecosystem can increase fire risk. Abundant cheatgrass was also associated with a 10 days earlier fire seasonality and interacted strongly with anthropogenic ignitions. Fire in cheatgrass was particularly associated with human activity, suggesting that increased awareness of fire danger in invaded areas could reduce risk. This study suggests that cheatgrass is much more spatially extensive and abundant than previously documented and that invasion greatly increases fire frequency, even at low percent cover.

Canada is expected to see an increase in fire risk under future climate projections. Large fires, such as that near Fort McMurray, Alberta in 2016, can be devastating to the communities affected. Understanding the role of human emissions in the occurrence of such extreme fire events can lend insight into how these events might change in the future. An event attribution framework is used to quantify the influence of anthropogenic forcings on extreme fire risk in the current climate of a western Canada region. Fourteen metrics from the Canadian Forest Fire Danger Rating System are used to define the extreme fire seasons. For the majority of these metrics and during the current decade, the combined effect of anthropogenic and natural forcing is estimated to have made extreme fire risk events in the region 1.5 to 6 times as likely compared to a climate that would have been with natural forcings alone.

The current conditions of many seasonally dry forests in the western and southern United States, especially those that once experienced low- to moderate-intensity fire regimes, leave them uncharacteristically susceptible to high-severity wildfire. Both prescribed fire and its mechanical surrogates are generally successful in meeting short-term fuel-reduction objectives such that treated stands are more resilient to high-intensity wildfire. Most available evidence suggests that these objectives are typically accomplished with few unintended consequences, since most ecosystem components (vegetation, soils, wildlife, bark beetles, carbon sequestration) exhibit very subtle effects or no measurable effects at all. Although mechanical treatments do not serve as complete surrogates for fire, their application can help mitigate costs and liability in some areas. Desired treatment effects on fire hazards are transient, which indicates that after fuel-reduction management starts, managers need to be persistent with repeated treatment, especially in the faster-growing forests in the southern United States.

Modeling wildfire activity is crucial for informing science-based risk management and understanding the spatiotemporal dynamics of fire-prone ecosystems worldwide. Models help disentangle the relative influences of different factors, understand wildfire predictability, and provide insights into specific events. Here, we develop Firelihood, a two-component, Bayesian, hierarchically structured, probabilistic model of daily fire activity, which is modeled as the outcome of a marked point process: individual fires are the points (occurrence component), and fire sizes are the marks (size component). The space-time Poisson model for occurrence is adjusted to gridded fire counts using the integrated nested Laplace approximation (INLA) combined with the stochastic partial differential equation (SPDE) approach. The size model is based on piecewise-estimated Pareto and generalized Pareto distributions, adjusted with INLA. The Fire Weather Index (FWI) and forest area are the main explanatory variables. Temporal and spatial residuals are included to improve the consistency of the relationship between weather and fire occurrence. The posterior distribution of the Bayesian model provided 1,000 replications of fire activity that were compared with observations at various temporal and spatial scales in Mediterranean France. The number of fires larger than 1 ha across the region was coarsely reproduced at the daily scale, and was more accurately predicted on a weekly basis or longer. The regional weekly total number of larger fires (10–100 ha) was predicted as well, but the accuracy degraded with size, as the model uncertainty increased with event rareness. Local predictions of fire numbers or burned areas also required a longer aggregation period to maintain model accuracy. The estimation of fires larger than 1 ha was also consistent with observations during the extreme fire season of the 2003 unprecedented heat wave, but the model systematically underrepresented large fires and burned areas, which suggests that the FWI does not consistently rate the actual danger of large fire occurrence during heat waves. Firelihood enabled a novel analysis of the stochasticity underlying fire hazard, and offers a variety of applications, including fire hazard predictions for management and projections in the context of climate change.

Underground mining, including underground coal mining, is accompanied by accidents and fire hazards that pose a threat to the life safety of miners. The fire hazard increases with an increase in the mining depth. Currently, most accidents in coal mines are mine fires. The cost of eliminating mine fires is 80–95% of the cost of eliminating all accidents occurring at mining enterprises. Therefore, the problem of developing a new methodology for modeling the ventilation network parameters of the mine to increase the reliability of controlling the aerogas mode at the excavation site is very relevant. The comprehensive analysis and assessment of gas-dynamic processes in coalmines under study were carried out using the methods of probability theory and mathematical statistics. Spatial data were processed using spline interpolation in “gnuplot”. As a result, a generalized expression for the transfer functions of coalmine objects, taking into account delays, was developed, including the description of dynamic properties of mining sites under various operating modes. The principal possibility of using a graphical method for estimating additional parameters of the sections of the ventilation system branches has been proved due to the alignment of their profiles at an equivalent distance relative to an arbitrary analogue. The improved method of spatial modeling was used to determine the gas-dynamic characteristics through additive gas-dynamic processes. The studies have been carried out and the method for managing the process of changing connections between devices (controllers–switches) of the technical system was developed in order to obtain greater reliability for safe mining. In subsequent studies, there is an issue of more detailed clarification of the peculiarities concerning the interrelations between the studied parameters in several projections of the response space.

Forest fire activity has increased in recent years in central and south-central Chile. Drought conditions have been associated with the increase of large wildfires, area burned and longer fire seasons. This study examines the influence of drought on fire regimes and discusses landscape management opportunities to decrease fire hazard. Specifically, we investigate the effect of the 2010–2015 Megadrought (MD) compared to 1990–2009 period on fire activity (fire-season length, number of fires and burned area across months, fire sizes, regions and vegetation cover types, simultaneity, and duration of fires) in central and south-central Chile (32°–39° S), using contemporary fire statistics derived from the Chilean Forest Service. For large fire events (>200 ha) the average season length increased by 67 d (44%), comparing 2010–2015 to 1990–2009. Earlier and later ignition dates resulted in extended fire seasons in MD years. During the MD, the number, area burned, simultaneity, and duration of large fires increased significantly compared to the control period, including the unprecedented occurrence of large fires during winter. The burned area in large fires increased in all vegetation types, during the MD compared to the control period, especially in the exotic plantation cover type. The regions that were most affected by fire (i.e., total area burned) during the MD were Maule, B ıo-B ıo, and Araucan ıa (35–39° S) that concentrate >75% of forest plantations in Chile. Although both maximum temperatures and precipitation are drivers of fire activity, a simple attribution analysis indicates that the sustained rainfall deficit during 2010–2015 was the most critical factor in the enhanced fire activity. Future climate change predictions indicate more recurrent, intense, and temporally extended droughts for central and south-central Chile. Under this scenario, land-use planning and fire and forest management strategies must promote a more diverse and less flammable landscape mosaic limiting high load, homogenous, and continuous exotic plantations.

Wildland fire scientists and land managers working in fire-prone areas require spatial estimates of wildfire potential. To fulfill this need, a simulation-modelling approach was developed whereby multiple individual wildfires are modelled in an iterative fashion across a landscape to obtain location-based measures of fire likelihood and fire behaviour (e.g. fire intensity, biomass consumption). This method, termed burn probability (BP) modelling, takes advantage of fire spread algorithms created for operational uses and the proliferation of available data representing wildfire patterns, fuels and weather. This review describes this approach and provides an overview of its applications in wildland fire research, risk analysis and land management. We broadly classify the application of BP models as (1) direct examination, (2) neighbourhood processes, (3) fire hazard and risk and (4) integration with secondary models. Direct examination analyses are those that require no further processing of model outputs; they range from a simple visual examination of outputs to an assessment of alternate states (i.e. scenarios). Neighbourhood process analyses examine patterns of fire ignitions and subsequent spread across land designations. Fire hazard combines fire probability and a quantitative assessment of fire behaviour, whereas risk is the product of fire likelihood and potential impacts of wildfire. The integration with secondary models represents situations where BP model outputs are integrated into, or used in conjunction with, other models or modelling platforms.

BackgroundWildfires are increasing in size and severity due to climate change combined with overstocked forests. Fire increases the likelihood of debris flows, posing significant threats to life, property, and water supplies.AimsWe conducted a debris-flow hazard assessment of the Santa Fe Municipal Watershed (SFMW) to answer two questions: (1) where are debris flows most likely to occur; and (2) how much debris might they produce? We also document the influence of fuel treatments on fire severity and debris flows.MethodsWe modelled post-fire debris-flow likelihood and volume in 103 sub-basins for 2-year, 5-year, and Probable Maximum Precipitation rainfalls following modelled low-, moderate-, and high-severity wildfires.Key resultsPost-fire debris-flow likelihoods were >90% in all but the lowest fire and rain scenarios. Sub-basins with fuel treatments had the lowest burn severities, debris-flow likelihoods, and sediment volumes, but treatment effects decreased with increased fire severity and rain intensity.ConclusionsPost-fire debris flows with varying debris volumes are likely to occur following wildfire in the SFMW, but fuel treatments can reduce likelihood and volume.ImplicationsFuture post-fire debris flows will continue to threaten water supplies, but fuel reduction treatments and debris-flow mitigation provide opportunities to minimise effects.

Soil moisture conditions are represented in fire danger rating systems mainly through simple drought indices based on meteorological variables, even though better sources of soil moisture information are increasingly available. This review summarises a growing body of evidence indicating that greater use of in situ, remotely sensed, and modelled soil moisture information in fire danger rating systems could lead to better estimates of dynamic live and dead herbaceous fuel loads, more accurate live and dead fuel moisture predictions, earlier warning of wildfire danger, and better forecasts of wildfire occurrence and size. Potential uses of soil moisture information in existing wildfire danger rating systems include (1) as a supplement or replacement for drought indices, (2) for live and (3) dead fuel moisture modelling, (4) for estimating herbaceous fuel curing, and (5) for estimating fuel loads. We identify key remaining research questions and note the logistical challenge of convincing wildfire professionals of the importance of soil moisture compared with more familiar wildfire danger metrics. While obstacles remain, the path forward is clear. Soil moisture information can and should be used to improve fire danger rating systems and contribute to more effective fire management for the protection of communities and ecosystems worldwide.