This work proposes a new thermal image processing method for computing the rate of spread (ROS) of forest fires. It is based on an application for linear flame fronts that are generated on flat surfaces with known dimensions. In the first step of the method, the correspondence between the points of the thermal image obtained and the real plane is calculated by means of a direct linear transformation (DLT). Subsequently, the position of the flame front is determined by applying a threshold-valuesearching criterion within the temperature matrix of the target surface. The design principles for the implementation of this method in the laboratory are described in depth, as well as the considerations that must be taken into account if the method is to be correctly extrapolated to more complex experimental scenarios, such as prescribed burnings or real forest fire emergencies.

Southern Europe is recurrently being hit by forest fires affecting wildland-urban interface (WUI) areas which, particularly in the last decade, have resulted in tremendous consequences. In the years to come, self-protection of communities will be a first priority over fire suppression, demanding better fire-resistant and resilient WUI scenarios through actions grounded on solid and sound regulations and legislation. As of today, the European Union as a whole, and the Member States in particular, are belatedly articulating new and appropriate regulations and implementing policies for the protection of WUI areas against forest fires. Spain is one of the EU Member States, holding 1.1 million ha of WUI areas (above 4% of the total forested land) and experiencing an average of 12,500 forest fires per year over the past decade. In this paper a review of the state of the art on regulations, codes, plans and recommendations on WUI fire prevention and management in Spain is presented. Shortcomings due to the current lack of building and urban planning standards and technical codes for WUI communities are highlighted. We underline some paramount needs to be covered by scientific research and fire engineering in particular topics. Some of them have received little attention in the literature related to European WUI fires while some others have been almost unexplored, such as planning of low-fuel fringes, design of road networks and accessibility, dimension of water supply networks, study of ignitability and combustibility of residential vegetation, role of construction methods and materials, and the wildland-industrial interface. Outcomes from research activities on such topics should lead to appropriately drive and inform the policy making processes on WUI fire prevention and management in Spain and, by extension, in other Southern European countries under a similar situation.

No abstract

Harmonized atmospheric 222Rn observations are required by the scientific community: these data have been lacking in southern Europe. We report on three recently established ground‐based atmospheric 222Rn monitoring stations in Spain. We characterize the variability of atmospheric 222Rn concentrations at each of these stations in relation to source strengths, local, and regional atmospheric processes. For the study, measured atmospheric 222Rn concentrations, estimated 222Rn fluxes, and regional footprint analysis have been used. In addition, the atmospheric radon monitor operating at each station has been compared to a 222Rn progeny monitor. Annual means of 222Rn concentrations at Gredos (GIC3), Delta de l'Ebre (DEC3), and Huelva (UHU) stations were 17.3 ± 2.0 Bq m−3, 5.8 ± 0.8 Bq m−3, and 5.1 ± 0.7 Bq m−3, respectively. The GIC3 station showed high 222Rn concentration differences during the day and by seasons. The coastal station DEC3 presented background concentrations typical of the region, except when inland 222Rn‐rich air masses are transported into the deltaic area. The highest 222Rn concentrations at UHU station were observed when local recirculation facilitates accumulation of 222Rn from nearby source represented by phosphogypsum piles. Results of the comparison performed between monitors revealed that the performance of the direct radon monitor is not affected by meteorological conditions, whereas the 222Rn progeny monitor seems to underestimate 222Rn concentrations under saturated atmospheric conditions. Initial findings indicate that the monitor responses seem to be in agreement for unsaturated atmospheric conditions but a further long‐term comparison study will be needed to confirm this result.

Abstract. The ClimaDat station at Gredos (GIC3) has been continuously measuring atmospheric (dry air) mixing ratios of carbon dioxide (CO2) and methane (CH4), as well as meteorological parameters, since November 2012. In this study we investigate the atmospheric variability of CH4 mixing ratios between 2013 and 2015 at GIC3 with the help of co-located observations of 222Rn concentrations, modelled 222Rn fluxes and modelled planetary boundary layer heights (PBLHs). Both daily and seasonal changes in atmospheric CH4 can be better understood with the help of atmospheric concentrations of 222Rn (and the corresponding fluxes). On a daily timescale, the variation in the PBLH is the main driver for 222Rn and CH4 variability while, on monthly timescales, their atmospheric variability seems to depend on emission changes. To understand (changing) CH4 emissions, nocturnal fluxes of CH4 were estimated using two methods: the radon tracer method (RTM) and a method based on the EDGARv4.2 bottom-up emission inventory, both using FLEXPARTv9.0.2 footprints. The mean value of RTM-based methane fluxes (FR_CH4) is 0.11 mg CH4 m−2 h−1 with a standard deviation of 0.09 or 0.29 mg CH4 m−2 h−1 with a standard deviation of 0.23 mg CH4 m−2 h−1 when using a rescaled 222Rn map (FR_CH4_rescale). For our observational period, the mean value of methane fluxes based on the bottom-up inventory (FE_CH4) is 0.33 mg CH4 m−2 h−1 with a standard deviation of 0.08 mg CH4 m−2 h−1. Monthly CH4 fluxes based on RTM (both FR_CH4 and FR_CH4_rescale) show a seasonality which is not observed for monthly FE_CH4 fluxes. During January–May, RTM-based CH4 fluxes present mean values 25 % lower than during June–December. This seasonal increase in methane fluxes calculated by RTM for the GIC3 area appears to coincide with the arrival of transhumant livestock at GIC3 in the second half of the year.