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Wildfires are a threat to human life and property, yet they are an unavoidable part of nature and in some instances they are necessary for the natural maintenance and evolution of forests. Investigators have attempted to describe the behavior (speed, direction, modes of spread) of wildfires for over fifty years. Current models for numerical description are mainly algebraic and based on statistical or empirical ideas. The authors describe, in contrast, a transport model called FIRETEC, which is a self-determining fire behavior model. The use of transport formulations connects the propagation rates to the full conservation equations for energy, momentum, species concentrations, mass, and turbulence. In this text, highlights of the model formulation and results are described. The goal of the FIRETEC model is to describe average behavior of the gases and fuels. It represents the essence of the combination of many small-scale processes without resolving each process in complete detail. The FIRETEC model is implemented into a computer code that examines line-fire propagation in a vertical spatial cut parallel to the direction of advancement. With this code the authors are able to examine wind effects, slope effects, and the effects of nonhomogeneous fuel distribution.

Climate change is already impacting coastal communities, and ongoing and future shifts in fisheries species productivity from climate change have implications for the livelihoods and cultures of coastal communities. Harvested marine species in the California Current Large Marine Ecosystem support U.S. West Coast communities economically, socially, and culturally. Ecological vulnerability assessments exist for individual species in the California Current but ecological and human vulnerability are linked and vulnerability is expected to vary by community. Here, we present automatable, reproducible methods for assessing the vulnerability of U.S. West Coast fishing dependent communities to climate change within a social-ecological vulnerability framework. We first assessed the ecological risk of marine resources, on which fishing communities rely, to 50 years of climate change projections. We then combined this with the adaptive capacity of fishing communities, based on social indicators, to assess the potential ability of communities to cope with future changes. Specific communities (particularly in Washington state) were determined to be at risk to climate change mainly due to economic reliance on at risk marine fisheries species, like salmon, hake, or sea urchins. But, due to higher social adaptive capacity, these communities were often not found to be the most vulnerable overall. Conversely, certain communities that were not the most at risk, ecologically and economically, ranked in the category of highly vulnerable communities due to low adaptive capacity based on social indicators (particularly in Southern California). Certain communities were both ecologically at risk due to catch composition and socially vulnerable (low adaptive capacity) leading to the highest tier of vulnerability. The integration of climatic, ecological, economic, and societal data reveals that factors underlying vulnerability are variable across fishing communities on the U.S West Coast, and suggests the need to develop a variety of well-aligned strategies to adapt to the ecological impacts of climate change.

The primary photovoltaic (PV) system investment decision‐making criteria are economics. These criteria are focused on system efficiency and cost, which is reasonable in the context of generous financial support schemes. However, when financial support is phased out, the PV market becomes technologically diversified. Environmental concerns and other qualitative issues become significant, whereas efficiency and costs may fail to describe PV systems properly. This study presents the first application of outranking techniques for PV technologies within an overall framework that includes qualitative, economic, technical and environmental criteria. The multi‐criteria analysis method, ELECTRE III, identifies optimal investment decisions from a pre‐determined set of investment alternatives. A case study based on a grid‐connected household PV system in the United Kingdom illustrates the methodology. The results suggest emerging excitronic PV technologies such as organic PV to lead the ranking when compared with inorganic technologies. These results have to be taken in the context of a number of assumptions and estimates as well as free market, no financial support schemes and promising future technology developments. The overall decision‐making framework provides comprehensive mathematical evaluations that assist PV owners, policy makers and the business community decide on technology, financial support schemes or business strategies.

Land types play an important guiding role in human survival and production. Clarifying the division of land types is the basis for ensuring the sustainable and coordinated development of social-economic-natural complex ecosystems. To date, the land type classification system has not formed a unified standard, and the existing classification fails to highlight the natural background elements of land. Therefore, it is important to construct a classification system that can reflect natural background elements. Additionally, land type classification is often based on land resource surveys. Updating the land type is generally difficult and slow, mainly due to a lack of appropriate information. Hence, it is necessary to develop an automatic land type renewal method using multisource information. This study proposes the ecology-geomorphology cognition (Eco-geoC) approach for land type classification. The approach is realized by the segmentation of land units using remote sensing images, geographic information, vegetation, soil, DEM, and geoscience knowledge. This approach is an extension of the object-based image analysis method. The spatial objects segmented from different attribute data are integrated, and finally, a comprehensive land mapping unit representing a certain degree of geographical homogeneity and land use potential is generated. The results show that the Eco-geoC approach is an integrated approach with objectification cognition on remote sensing images and multisource information using geo-knowledge. The Eco-geoC approach is tested in the Altay region. From coarse to fine scales, the study area is divided into two kinds of natural belts, 27 land systems and 78 land units, and a 1:500,000 land-type map, which shows a good coupling relationship between the physiognomy, vegetation, and soil in the Altay region, is compiled. The results of this study show that the use of the Eco-geoC approach for land type classification is significant and has potential for land assessment and planning. This approach can provide a scientific basis for the restoration of the regional ecology and the comprehensive management and adjustment of land resources and the environment.

Abstract Motivated by the practical application of information and communication technologies (ICT)-based innovations in environmental and social responsibility (ESR) investment, this study investigates a sustainable power supply chain that consists of a traditional energy power generation firm (TEF), a renewable energy power generation firm (REF) and a downstream power distributor (PD). Each supply chain member can invest in ESR to achieve energy conservation and emission reduction, and thereby gain economic benefits. To achieve higher power level for better ESR investment, the TEF may actively form an alliance with the REF or the PD, or not, which leads to three different alliance strategies, i.e., Strategy HA, Strategy VA, and Strategy NA, respectively. The results show that NA is the equilibrium strategy when the TEF’s investment cost is low while the PD’s investment cost is medium. However, when the TEF’s investment cost is medium while the PD’s investment cost is low, VA is the equilibrium strategy. Moreover, when the investment cost of the TEF and the REF are both low, HA is the equilibrium strategy. In the other cost intervals, the three power firms will not invest in ESR simultaneously, and consequently the alliance strategy has no effect on the revenue allocation. Therefore, the TEF forms no alliance with either the REF or the PD. By comparison with the unaligned case, we find that alliance not only benefits the TEF, but also the other firms in the power supply chain as well as the whole society resulting from the improved ESR investment, which achieves a “win-win-win” situation.

Abstract. The repetition of droughts in France has led to a growing demand for irrigation water and consequently to an increase in requests for the construction of small farm dams. Although such dams are small, their accumulation in a basin affects river flows, because the water collected in these small farm dams is used for irrigation and thus does not contribute to river flow. In order to gain more insight into their impact on the annual and monthly discharges, especially during dry years, a small farm dam model was built and connected to a hydrometeorological model. Several scenarios with different volume capacities, filling catchment sizes and filling periods were tested for such dams. The results were analysed in a small basin in western France, where the pressure for building such dams is high, and then extended to the entire country. It was found that, due to the hydrometeorological conditions (mainly low precipitation compared to other regions in France), the development of small farm dams in north-western France would result in greater decreases in river flows and less efficient filling of small farm dams than in other regions. Therefore, such dams might not be as efficient as expected in supplying water to farmers when needed. Moreover, the ability to fill small farm dams is projected to decrease in a context of climate change, despite the uncertainty on the evolution of precipitation, thus worsening the situation.

The average antimony concentration in municipal solid waste is estimated to be about 10-60 ppm. Thermodynamical models predict a volatile behavior for antimony compounds, yet literature mass balances show that about 50% of the antimony input remains in the grate ashes. This fact can be explained by the formation of thermally stable antimonates in the fuel bed due to interactions with alkali or earth-alkali metals. Thermogravimetric experiments revealed an increased thermal stability for antimony oxide in presence of oxygen and calcium oxide. Spiking experiments on the test incinerator TAMARA showed that chlorination processes have a strong effect on antimony volatilization whereas high fuel-bed temperatures and addition of antimony oxide only have a moderate effect. In the grate ashes, antimony shows a pH-depending leaching property, which is typical for anionic species. This fact supports the thesis that antimony is present in the grate ashes in an anionic speciation.

Abstract Besides the apparent need to reduce greenhouse gas emissions, other important factors contributing to the renewed interest in biofuels are energy security concerns and the need of sustainable transportation fuel. Nearly 30% of the annual CO2 emissions in the U.S. come from the transportation sector and more than half of the fuel is imported. Biofuels appear to be a promising option to reduce carbon dioxide emissions, and the reliance on imported oil concomitantly. The interest on (ligno) cellulosic ethanol is gaining momentum as corn-based ethanol is criticized for using agricultural outputs for fuel production. Among many lignocellulosic feedstocks, woodchips is viewed as one of the most promising feedstocks for producing liquid transportation fuels. The renewable and carbon neutral nature of the feedstocks, similar chemical and physical properties to gasoline, and the low infrastructure cost due to the availability of fuel flex vehicles and transportation networks make (ligno) cellulosic bioethanol an attractive option. An in-depth LCA of woodchips shows that harvesting and woodchips processing stage and transportation to the facility stage emit large amount of environmental pollutants compared to other life cycle stages of ethanol production. Our analysis also found that fossil fuel consumption and respiratory inorganic effects are the two most critical environmental impact categories in woodchips production. We have used Eco-indicator 99 based cradle-to-gate LCA method with a functional unit of 4 m3 of dry hardwood chips production.