The housing boom and forest fires

This paper provides evidence that the combination of land-use restrictions and an increasing demand for housing can create incentives to induce forest fires as a means to circumvent regulation and increase the supply of land available for residential construction. I estimate the effect of the price of housing on the incidence of forest fires using Spanish data by region for 1991-2005. The results suggest that higher house prices led to a significant increase in the incidence of forest fires in a region. I also find that the increased incidence of forest fires led to a subsequent reduction in forest area and an increase in urban land area. This evidence supports the claims often found in the media that property speculators trying to build in forest land may be behind the recent increases in the incidence of forest fires in Mediterranean countries.Forest fires, housing prices, land-use change

Are Forest Fires Predictable?

Dynamic mean field theory is applied to the problem of forest fires. The starting point is the Monte Carlo simulation in a lattice of million cells. The statistics of the clusters is obtained by means of the Hoshen--Kopelman algorithm. We get the map $p_n\to p_{n+1}$, where $p_n$ is the probability of finding a tree in a cell, and $n$ is the discrete time. We demonstrate that the time evolution of $p$ is chaotic. The arguments are provided by the calculation of the bifurcation diagram and the Lyapunov exponent. The bifurcation diagram reveals several windows of stability, including periodic orbits of length three, five and seven. For smaller lattices, the results of the iteration are in qualitative agreement with the statistics of the forest fires in Canada in years 1970--2000.Comment: 13 pages, 13 figure

Seven-dimensional forest fires

We show that in high dimensional Bernoulli percolation, removing from a thin infinite cluster a much thinner infinite cluster leaves an infinite component. This observation has implications for the van den Berg-Brouwer forest fire process, also known as self-destructive percolation, for dimension high enough.Comment: 8 page

High resolution fire hazard index based on satellite images

In December 2015, after 3 year of activity, the FP7 project PREFER (Space-based Information Support for Prevention and REcovery of Forest Fires Emergency in the MediteRranean Area) came to an end. The project was designed to respond to the need to improve the use of satellite images in applications related to the emergency services, in particular, to forest fires. The project aimed at developing, validating and demonstrating information products based on optical and SAR (Synthetic Aperture Radar) imagery for supporting the prevention of forest fires and the recovery/damage assessment of burnt area. The present paper presents an improved version of one of the products developed under the PREFER project, which is the Daily Fire Hazard Index (DFHI)

Classroom on the Mountain

Outdoor class studies the history and impact of forest fires in the Cascade mountain range

Boreal forest fire emissions in fresh Canadian smoke plumes: C_1-C_(10) volatile organic compounds (VOCs), CO_2, CO, NO_2, NO, HCN and CH_3CN

Boreal regions comprise about 17% of the global land area, and they both affect and are influenced by climate change. To better understand boreal forest fire emissions and plume evolution, 947 whole air samples were collected aboard the NASA DC-8 research aircraft in summer 2008 as part of the ARCTAS-B field mission, and analyzed for 79 non-methane volatile organic compounds (NMVOCs) using gas chromatography. Together with simultaneous measurements of CO_2, CO, CH_4, CH_2O, NO_2, NO, HCN and CH_3CN, these measurements represent the most comprehensive assessment of trace gas emissions from boreal forest fires to date. Based on 105 air samples collected in fresh Canadian smoke plumes, 57 of the 80 measured NMVOCs (including CH_2O) were emitted from the fires, including 45 species that were quantified from boreal forest fires for the first time. After CO_2, CO and CH_4, the largest emission factors (EFs) for individual species were formaldehyde (2.1 ± 0.2 g kg^(−1)), followed by methanol, NO_2, HCN, ethene, α-pinene, β-pinene, ethane, benzene, propene, acetone and CH_3CN. Globally, we estimate that boreal forest fires release 2.4 ± 0.6 Tg C yr^(−1) in the form of NMVOCs, with approximately 41% of the carbon released as C_1-C_2 NMVOCs and 21% as pinenes. These are the first reported field measurements of monoterpene emissions from boreal forest fires, and we speculate that the pinenes, which are relatively heavy molecules, were detected in the fire plumes as the result of distillation of stored terpenes as the vegetation is heated. Their inclusion in smoke chemistry models is expected to improve model predictions of secondary organic aerosol (SOA) formation. The fire-averaged EF of dichloromethane or CH_2Cl_2, (6.9 ± 8.6) × 10^(−4)gkg^(−1), was not significantly different from zero and supports recent findings that its global biomass burning source appears to have been overestimated. Similarly, we found no evidence for emissions of chloroform (CHCl_3) or methyl chloroform (CH_3CCl_3) from boreal forest fires. The speciated hydrocarbon measurements presented here show the importance of carbon released by short-chain NMVOCs, the strong contribution of pinene emissions from boreal forest fires, and the wide range of compound classes in the most abundantly emitted NMVOCs, all of which can be used to improve biomass burning inventories in local/global models and reduce uncertainties in model estimates of trace gas emissions and their impact on the atmosphere