Estimating annual GHG and particulate matter emissions from rural and forest fires based on an integrated modelling approach.

Rural and forest fires represent one of the most significant sources of emissions in the atmosphere of trace gases and aerosol particles, which significantly impact carbon budget, air quality, and human health. This paper aims to illustrate an integrated modelling approach combining spatial and non-spatial inputs to provide and enhance the estimation of GHG and particulate matter emissions from surface fires using Italy as a case study over the period 2007-2017. Three main improvements characterize the approach proposed in this work: (i) the collection and development of comprehensive and accurate data inputs related to burned area; (ii) the use of the most recent data on fuel type and load; and (iii) the modelling application to estimate fuel moisture, burning efficiency, and fuel consumption considering meteorological factors and combustion phases.

Corrigendum to "The wildland-anthropic interface raster data of the Italy-France maritime cooperation area (Sardinia, Corsica, Tuscany, Liguria, and Provence-Alpes-Côte d'Azur)" [Data in Brief Volume 38 (2021) Article 107355].

[This corrects the article DOI: 10.1016/j.dib.

Assessing the Effectiveness of Silvicultural Treatments on Fire Behavior in the Hyrcanian Temperate Forests of Northern Iran.

We implemented a fire modeling approach to evaluate the effectiveness of silvicultural treatments in reducing potential losses to the Hyrcanian temperate forests of northern Iran, in the Siahkal National Forest (57,110 ha). We compared the effectiveness of selection cutting, low thinning, crown thinning, and clear-cutting treatments implemented during the last ten years (n = 241, 9500-ha) on simulated stand-scale and landscape-scale fire behavior. First, we built a set of fuel models for the different treatment prescriptions.

The wildland-anthropic interface raster data of the Italy-France maritime cooperation area (Sardinia, Corsica, Tuscany, Liguria, and Provence-Alpes-Côte d'Azur).

We applied a geographical information system analysis to reclassify and characterize anthropic buildings based on structure density and area covered, land type, and proximity to wildlands able to originate intense wildfires and spot fires. The methodology was carried out in the 93,000 km Italy-France Maritime cooperation area (which includes the Regions of Sardinia, Tuscany, and Liguria, in Italy, and Corsica, and Provence-Alpes-Côte d'Azur, in France). We produced a 100-m raster dataset that characterizes and maps medium-high anthropic presence, wildland-anthropic areas, dispersed anthropic areas, and non-anthropic zones, in the whole study area.

The impact of wildland fires on calcareous Mediterranean pedosystems (Sardinia, Italy) - An integrated multiple approach.

Sardinia (Italy), the second largest island of the Mediterranean Sea, is a fire-prone land. Most Sardinian environments over time were shaped by fire, but some of them are too intrinsically fragile to withstand the currently increasing fire frequency. Calcareous pedoenvironments represent a significant part of Mediterranean areas, and require important efforts to prevent long-lasting degradation from fire.

Modeling the effects of different fuel treatment mosaics on wildfire spread and behavior in a Mediterranean agro-pastoral area.

Wildfire spread and behavior can be limited by fuel treatments, even if their effects can vary according to a number of factors including type, intensity, extension, and spatial arrangement. In this work, we simulated the response of key wildfire exposure metrics to variations in the percentage of treated area, treatment unit size, and spatial arrangement of fuel treatments under different wind intensities. The study was carried out in a fire-prone 625 km agro-pastoral area mostly covered by herbaceous fuels, and located in Northern Sardinia, Italy.

Wildfire spread, hazard and exposure metric raster grids for central Catalonia.

We provide 40 m resolution wildfire spread, hazard and exposure metric raster grids for the 0.13 million ha fire-prone Bages County in central Catalonia (northeastern Spain) corresponding to node influence grid (NIG), crown fraction burned (CFB) and fire transmission to residential houses (TR). Fire spread and behavior data (NIG, CFB and fire perimeters) were generated with fire simulation modeling considering wildfire season extreme fire weather conditions (97 percentile).

Optimizing prescribed fire allocation for managing fire risk in central Catalonia.

We used spatial optimization to allocate and prioritize prescribed fire treatments in the fire-prone Bages County, central Catalonia (northeastern Spain). The goal of this study was to identify suitable strategic locations on forest lands for fuel treatments in order to: 1) disrupt major fire movements, 2) reduce ember emissions, and 3) reduce the likelihood of large fires burning into residential communities. We first modeled fire spread, hazard and exposure metrics under historical extreme fire weather conditions, including node influence grid for surface fire pathways, crown fraction burned and fire transmission to residential structures.

Assessing Climate Change Impacts on Wildfire Exposure in Mediterranean Areas.

We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981-2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981-2010, 2011-2040, and 2041-2070).

Assessing landscape scale wildfire exposure for highly valued resources in a Mediterranean area.

We used a fire simulation modeling approach to assess landscape scale wildfire exposure for highly valued resources and assets (HVR) on a fire-prone area of 680 km(2) located in central Sardinia, Italy. The study area was affected by several wildfires in the last half century: some large and intense fire events threatened wildland urban interfaces as well as other socioeconomic and cultural values. Historical wildfire and weather data were used to inform wildfire simulations, which were based on the minimum travel time algorithm as implemented in FlamMap.

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy.

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September.