Modelling the Ecological Vulnerability to Forest Fires in Mediterranean Ecosystems Using Geographic Information Technologies

Forest fires represent a major driver of change at the ecosystem and landscape levels in the Mediterranean region. Environmental features and vegetation are key factors to estimate the ecological vulnerability to fire; defined as the degree to which an ecosystem is susceptible to, and unable to cope with, adverse effects of fire (provided a fire occurs). Given the predicted climatic changes for the region, it is urgent to validate spatially explicit tools for assessing this vulnerability in order to support the design of new fire prevention and restoration strategies. This work presents an innovative GIS-based modelling approach to evaluate the ecological vulnerability to fire of an ecosystem, considering its main components (soil and vegetation) and different time scales. The evaluation was structured in three stages: short-term (focussed on soil degradation risk), medium-term (focussed on changes in vegetation), and coupling of the short- and medium-term vulnerabilities. The model was implemented in two regions: Aragón (inland North-eastern Spain) and Valencia (eastern Spain). Maps of the ecological vulnerability to fire were produced at a regional scale. We partially validated the model in a study site combining two complementary approaches that focused on testing the adequacy of model’s predictions in three ecosystems, all very common in fire-prone landscapes of eastern Spain: two shrublands and a pine forest. Both approaches were based on the comparison of model’s predictions with values of NDVI (Normalized Difference Vegetation Index), which is considered a good proxy for green biomass. Both methods showed that the model’s performance is satisfactory when applied to the three selected vegetation types.     

Wind power projects in Brazil: challenges and opportunities increasing co-benefits and implications for climate and energy policies

The purpose of this article is to analyze the challenges to, and opportunities for, increasing sustainable development (SD) co-benefits delivered by clean development mechanism (CDM) wind power projects in northeastern Brazil and the resulting implications for climate and energy policies. Five methodological phases were met: First, a documentary research was conducted in the main CDM database; second was a literature review, creating the analytical framework and a survey questionnaire needed to assess the SD co-benefits from the projects; third, documentary research was used to enable ex-ante analysis of the SD co-benefits proposed in the CDM Project Design Documents (PDDs); fourth, survey allowed for the analysis of SD co-benefits perceived by project entrepreneurs (ex-post analysis); and finally, a comparison between the ex-ante and ex-post analyses was completed. The results show the importance of carrying out SD co-benefit studies after the implementation of CDM projects in order to learn lessons for new mechanisms of climate governance. The lowest SD co-benefits were water management improvement in the project influence area, soil pollution prevention, health and safety improvements and technology transfer. The greatest opportunities for increasing SD co-benefits come from the environmental licensing process and the strengthening of Corporate Social Responsibility. The greatest challenges are new technology development, stakeholders’ engagement and SD co-benefit audits. We conclude that the improvement of multi-level climate and energy governance plays a key role in increasing SD co-benefits.

     

Determination of road dust loadings and chemical characteristics using resuspension

The contribution of fugitive dust from traffic to air pollution can no longer be ignored in China. In order to obtain the road dust loadings and to understand the chemical characteristics of PM₁₀ and PM_2.5 from typical road dust, different paved roads in eight districts of Beijing were selected for dust collection during the four seasons of 2005. Ninety-eight samples from 28 roads were obtained. The samples were resuspended using equipment assembled to simulate the rising process of road dust caused by the wind or wheels in order to obtain the PM₁₀ and PM_2.5 filter samples. The average road dust loading was 3.82 g m^− 2, with the highest of 24.22 g m^− 2 being in Hutongs in the rural–urban continuum during winter. The road dust loadings on higher-grade roads were lower than those on lower-grade roads. Attention should be paid to the pollution in the rural–urban continuum areas. The sums of element abundances measured were 16.17% and 18.50% for PM₁₀ and PM_2.5 in road dust. The average abundances of OC and EC in PM₁₀ and PM_2.5 in road dust were 11.52%, 2.01% and 12.50%, 2.06%, respectively. The abundance of elements, water-soluble ions, and OC, EC in PM₁₀ and PM_2.5 resuspended from road dust did not change greatly with seasons and road types. The soil dust, construction dust, dust emitted from burning coal, vehicle exhaust, and deposition of particles in the air were the main sources of road dust in Beijing. Affected by the application of snow-melting agents in Beijing during winter, the amount of Cl⁻ and Na⁺ was much higher during that time than in the other seasons. This will have a certain influence on roads, bridges, vegetations, and groundwater.