This research was conducted within the framework of project SI2.825082, funded by the European Commission—DG GROW. The project's objective was to finalise a European approach for assessing the fire performance of façades under medium and large fire exposure conditions. The national standards BS 8414-1:2020/BS 8414-2:2020 and DIN 4102-20:2017 served as the foundation for developing the new assessment method. As part of the project, a theoretical round robin, initial testing activities and a large-scale experimental round robin were carried out. The theoretical round robin aimed to examine how different laboratories interpreted the preliminary assessment method. Subsequently, the initial testing phase explored the design of the fire source, combustion chamber and secondary opening. The experimental round robin involved testing four façade systems across three laboratories using the assessment method documents, resulting in 12 tests for medium-scale and 12 for large-scale exposure—24 tests in total. These tests provided data to develop a calibration scheme and define appropriate performance criteria for classification. In this paper, the representatives of the project consortium summarise the research process and outline the proposed testing and evaluation methodology, which is intended to form the foundation of a future European testing standard for façades. The article also highlights the need for further research to establish rules for extended application of test results

European spring grassfire danger in a changing climate

Wildfires constitute a frequent example of climate change impact. Fire‑prone weather has increased across much of the world and contributes to a global rise of wildfire disasters. Changing drought patterns affect Mediterranean regions (California, Chile, South Africa) while boreal forests are drying more rapidly during warm summer days.In southern Europe, large and intense fires occur during high summer causing fatalities and affect buildings and ecosystems. In other (north and east) more mesic parts of Europe, smaller early‑spring fires are most numerous. For Scandinavia, these are the fires that cause the greatest damage to people and buildings.In eastern and northern Europe, cold winter weather leads to senescence of grasses and herbs. As sunlight and temperatures rise in dry spring air, this highly flammable litter dries quickly and can spread flames much faster than typically observed for forest fires. However, the grass‑fire season lasts only a few weeks until fresh green grass, with highmoisture content, emerges through the litter. Thus, grasses become flammable indifferent weather conditions than forests, and their seasons are often separated in time.While the impact of climate change to increasing forest fire danger is well established, changes of grassfire risks are not yet studied. An expected increase of dry and warm early‑summer weather would typically increase spread rates, and reduced snow cover expose more litter, thus enabling fire for dry conditions. By contrast, shorter snow seasons and warmer winters accelerates green-up which impedes fire spread potential. Reduced solar radiation and changes in dry winds, cloudiness, and precipitation patterns are also important factors whose influence on grassfire risk remains uncertain.Here we calculate rate of spread in spring grasslands using the Swedish grass fire danger model. Using two scenarios with five independent climate models each,grassfire risks in ten European regions are assessed towards the end of this century in terms of (i) the number of risk days and (ii) each season’s maximum spread rate.The results show that in all non-mountainous regions both the number of risk days and the season’s maximum risk peak are projected to decrease. Under RCP8.5, maximum spread rates decrease by roughly 10% across most lowland regions between the reference period (2006-2035) to the 30-years period (2071-2100). The number of risk days also decrease with 11% to 35%, depending on region, with the greatest reductions occur in places where the largest proportion of snow days is expected to disappear. Faster onset of grass growth shifts the combustible season into less dry weather. In these cases, increased temperatures actually lead to lower flammability through a phenological shift.The Scandes exhibit only small changes while both the Alps and the Carpathians display increasing numbers of risk days. Spatial variability across the mountain regions is large and, in contrast to the lowlands, the areas with the greatest snow loss also show the largest increase in risk days. This trend is driven by more fire‑prone (dry and windy) weather during the early winter months, when grassfire risk rises by increasingly exposed litter layer before the onset of green-up. 

Retrospective analyses of fire danger typically use reanalysed data, but its relation to observed fire danger is not well researched. Here we use daily weather observations to calculate fire danger for nine weather stations in Sweden, spanning 1100 km N–S, for the period 1951–2020, making it among the longest series of observed fire danger to date. All sites except the northernmost one exhibited increasing seasonal FWI-metrics over the period and linear trends were statistically significant for three sites. On average, annual peak 7-day moving-average FWI increased by 18% over 70 years. Increasing trends were mostly driven by higher noon-temperature and not by altered precipitation patterns. Further, observed fire danger differed substantially from that based on ERA5 reanalysis data. For FWI > 5, reanalysis FWI-values were on average 25% lower than corresponding observational values. The strength of reanalysis data is to form gridded data using single assimilation schemes against homogeneous model fits and it is not designed to fully represent actual point scale weather. While reanalysis data enables comprehensive geographical analyses, this study shows how it also underestimates peak fire weather in northern Europe. We recommend checking extreme-value bias against point observations in future studies.

Large test methods of the fire performance of façades in which a full façade is exposed to flaming impingement from what resembles the external plume from a post-flashover fire are common for assessing regulatory compliance of façade systems. Unlike many other fire performance tests, this type of testing is only marginally harmonised internationally, and test methods vary greatly in size, fuel sources and assessment criteria. Many European regulatory systems, including the proposed future pan-European method, define fuel sources of several 100 kg of wood cribs. While wood cribs are historically reliable, they also induce problems for harmonisation between countries and regulations. This paper provides raw data of the exposure to an incombustible façade using the proposed European façade test method with wood cribs. We also show that one can obtain similar thermal exposure using propane gas burners by tailoring the test setup dimensions. The use of gas burners improved repeatability and can allow for lower total heights of the test elements.

This study features a cohesive modelling approach of human-caused wildfire ignitions applied to a set of representative regions in terms of fire activity across Europe (pilot sites, PS). Our main goal was to develop a common approach to model human-caused ignition probability at a fine-grained spatial resolution (100 m) and identify the main drivers of ignitions. Specifically, we (i) ascertain which factors influence ignitions in each PS; (ii) deliver a spatial-explicit representation of ignition probability, and (iii) provide a framework for comparison with regional-scale models among PS. To do so, we calibrated Random Forest models from historical fire records compiled by local fire agencies, and geospatial layers of land cover, accessibility, population density and dead fine-fuel moisture content (DFMC). Models were built individually for each PS, comparing them with a full model constructed from all PS. Furthermore, special attention was given to the effect of spatial autocorrelation in model performance. All models achieved sufficient predictive performance (Areas Under the Receiver Operating Characteristic Curve (AUCs) from 0.70 to 0.89). For all PS models, the yearly anomaly in DFMC was the most influential variable. Among human-related factors, distance to the Wildland Urban Interface emerged as the most relevant variable, followed by proximity to roads, population density, and the fraction of wildland coverage. The performance of the full model achieved an AUC value of 0.81, with mean DFMC and anomaly being the main ignition factors, modulated by distance to roads and population density. The local performance of the full model dropped by 0.10 for AUC in both Southern Sweden and Attica (Greece) regions. The wildfire occurrence models developed in this study are essential for understanding wildfire ignition hazard and may help implement integrated wildfire risk management strategies and mitigation policies in fire-prone EU landscapes

Wildfire damage to the built environment and people is typically understood through case studies of high-impact events, or from incident databases where the smallest wildfires are not always accounted for. We analyzed an exhaustive database of 131 040 reported fire service wildfire dispatches (1996–2022) in Sweden. There were on average per year 126 wildfires that threatened buildings, 22 that ignited buildings, 17.6 that injured people and 1.1 that led to a fatality. The analysis showed that building ignitions, human injuries as well as fatalities in this region were caused primarily by relatively small fires (90th percentile <10 ha) and that they occurred predominantly in the spring season. Untended grass litter near buildings constituted a much higher fire threat to the built environment than did forest vegetation, even when fire danger was relatively low. The source of the ignitions was 99 % anthropogenic and mostly connected with intentional fire use such as burning grass litter or garden debris. Our study highlights the need for improved fire statistics to cover the full extent of threats to life and property from wildfires. Further, it suggests that the potential for harm reduction through improved wildfire knowledge among the rural population should be large.

Climate change is increasing the frequency and intensity of extreme wildfires globally, yet our understanding of these high-impact events remains uneven and shaped by media attention and regional research biases. The State of Wildfires project systematically tracks global and regional fire activity of each annual fire season, analyses the causes of prominent extreme wildfire events, and projects the likelihood of similar events occurring in future climate scenarios. This, its second annual report, covers the March 2024 to February 2025 fire season. During the 2024–2025 fire season, fire-related carbon (C) emissions totalled 2.2 Pg C, 9 % above average and the sixth highest on record since 2003, despite below-average global burned area (BA). Extreme fire seasons in South America’s rainforests, dry forests, and wetlands and in Canada’s boreal forests pushed up the global C emissions total. Fire C emissions were over 4 times above average in Bolivia, 3 times above average in Canada, and ∼ 50 % above average in Brazil and Venezuela. Wildfires in 2024–2025 caused 100 fatalities in Nepal, 34 in South Africa, and 31 in Los Angeles, with additional fatalities reported in Canada, Côte d’Ivoire, Portugal, and Türkiye. The Eaton and Palisades fires in Southern California caused 150 000 evacuations and USD 140 billion in damages. Communities in Brazil, Bolivia, Southern California, and northern India were exposed to fine particulate matter at concentrations 13–60 times WHO’s daily air quality standards. We evaluated the causes and predictability of four extreme wildfire episodes from the 2024–2025 fire season, including in Northeast Amazonia (January–March 2024), the Pantanal–Chiquitano border regions of Brazil and Bolivia (August–September 2024), Southern California (January 2025), and the Congo Basin (July–August 2024). Anomalous weather created conditions for these regional extremes, while fuel availability and human ignitions shaped spatial patterns and temporal fire dynamics. In the three tropical regions, prolonged drought was the dominant fire enabler, whereas in California, extreme heat, wind, and antecedent fuel build-up were compounding enablers. Our attribution analyses show that climate change made extreme fire weather in Northeast Amazonia 30–70 times more likely, increasing BA roughly 4-fold compared to a scenario without climate change. In the Pantanal–Chiquitano, fire weather was 4–5 times more likely, with 35-fold increases in BA. Meanwhile, our analyses suggest that BA was 25 times higher in Southern California due to climate change. The Congo Basin’s fire weather was 3–8 times more likely with climate change, with a 2.7-fold increase in BA. Socioeconomic changes since the pre-industrial period, including land-use change, also likely increased BA in Northeast Amazonia. Our models project that events on the scale of 2024–2025 will become up to 57 %, 34 %, and 50 % more frequent than in the modern era in Northeast Amazonia, the Pantanal–Chiquitano, and the Congo Basin, respectively, under a medium–high scenario (SSP370) by 2100. Climate action can limit the added risk, with frequency increases held to below 15 % in all three regions under a strong mitigation scenario (SSP126). In Southern California, the future trajectory of extreme fire likelihood remains highly uncertain due to poorly constrained climate–vegetation–fire interactions influencing fuel moisture, though our models suggest that risk may decline in future. This annual report from the State of Wildfires project integrates and advances cutting-edge fire observations and modelling with regional expertise to track changing global wildfire hazard, guiding policy and practice towards improved preparedness, mitigation, adaptation, and societal benefit. Thirteen new datasets and model codebases presented in this work are available from the State of Wildfires Project’s Zenodo community, including updated annual statistics on wildfire extent (Jones et al., 2025; https://doi.org/10.5281/zenodo.15525674), outputs from modelling of fire causality using PoF model (Di Giuseppe, 2025; https://doi.org/10.24433/CO.8570224.v1) and codebase for the extreme event attribution/projections model, ConFLAME (Barbosa et al., 2025a, https://doi.org/10.5281/zenodo.16790787).

Wildfires in Scandinavia are predicted to become more frequent and severe [1,2], necessitating a deeper understanding of the fire behaviour in scenarios unique to local conditions. Therefore, the Norwegian Pilot in the EU-funded wildfire project TREEADS focuses on understanding fire dynamics and fire spread mechanisms inherent for Norwegian wildfires and develop a relevant and scalable lab test method to document the fire resilience of materials against wildfires.