954 resultados para Environmental impact analysis -- Catalonia -- Garrotxa
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The study examines the property value impacts of an announcement of a project which has potential environmental impacts as distinct from other studies that address costs associated with under-construction and the operating impacts of developments. The hypothesis is that the announcement of a proposed project with potential environmental impact creates uncertainty in the property market of the affected area, and this impact is greater on properties closer to the project than those farther from it. The results of the study confirm the hypothesis and indicate that the marginal willingness to pay for properties within a 5 km distance declined by AU$17,020 per km proximity to the proposed heavy vehicle route, after the proposed route was announced. The results support the need for more holistic measurement of cost–benefit analysis of projects and provide a basis for improved consideration by policy makers of the rights of affected parties.
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Increases in fish demand in the coming decades are projected to be largely met by growth of aquaculture. However, increased aquaculture production is linked to higher demand for natural resources and energy as well as emissions to the environment. This paper explores the use of Life Cycle Assessment to improve knowledge of potential environmental impacts of future aquaculture growth. Different scenarios of future aquaculture development are taken into account in calculating the life cycle environmental impacts. The environmental impact assessments were built on Food and Agriculture Organization statistics in terms of production volume of different species, whereas the inputs and outputs associated with aquaculture production systems were sourced from the literature. The matrix of input-output databases was established through the Blue Frontiers study.
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The potential impact of the abrupt 8.2 ka cold event on human demography, settlement patterns and culture in Europe and the Near East has emerged as a key theme in current discussion and debate. We test whether this event had an impact on the Mesolithic population of western Scotland, a case study located within the North Atlantic region where the environmental impact of the 8.2 ka event is likely to have been the most severe. By undertaking a Bayesian analysis of the radiocarbon record and using the number of activity events as a proxy for the size of the human population, we find evidence for a dramatic reduction in the Mesolithic population synchronous with the 8.2 ka event. We interpret this as reflecting the demographic collapse of a low density population that lacked the capability to adapt to the rapid onset of new environmental conditions. This impact of the 8.2 ka event in the North Atlantic region lends credence to the possibility of a similar impact on populations in Continental Europe and the Near East.
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The environmental performance of a 50 MW parabolic trough Concentrated Solar Power (CSP) plant hybridised with different fuels was determined using a Life Cycle Assessment methodology. Six different scenarios were investigated, half of which involved hybridisation with fossil fuels (natural gas, coal and fuel oil), and the other three involved hybridisation with renewable fuels (wheat straw, wood pellets and biogas). Each scenario was compared to a solar-only operation. Nine different environmental categories as well as the Cumulative Energy Demand and the Energy Payback Time (EPT) were evaluated using Simapro software for 1 MWh of electricity produced. The results indicate a worse environmental performance for a CSP plant producing 12% of the electricity from fuel than in a solar-only operation for every indicator, except for the eutrophication and toxicity categories, whose results for the natural gas scenario are slightly better. In the climate change category, the results ranged between 26.9 and 187 kg CO2 eq/MWh, where a solar-only operation had the best results and coal hybridisation had the worst. Considering a weighted single score indicator, the environmental impact of the renewable fuels scenarios is approximately half of those considered in fossil fuels, with the straw scenario showing the best results, and the coal scenario the worstones. EPT for solar-only mode is 1.44 years, while hybridisation scenarios EPT vary in a range of 1.72 -1.83 years for straw and pellets respectively. The fuels with more embodied energy are biomethane and wood pellets.
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Mode of access: Internet.
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Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.
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Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This paper presents the development of a parallel Hybrid Electric Propulsion System (HEPS) on a small fixed-wing UAV incorporating an Ideal Operating Line (IOL) control strategy. A simulation model of an UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine were determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).
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This study examined the association between socio-environmental factors and suicide in Australia. The high risk areas were identified using advanced spatial analysis methods. Higher proportion of Indigenous population, unemployment rate and bigger temperature difference appeared to be among the main socio-environmental drivers of suicide across different places. Both temperature difference and unemployment were positively associated with suicide over time in general. Temperature difference seemed to affect suicide more in months when unemployment rates were high compared with the periods when unemployment rates were low. The findings may provide useful information for determining the socio-environmental impact on suicide and designing effective suicide control and prevention programs.
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Airport efficiency is important because it has a direct impact on customer safety and satisfaction and therefore the financial performance and sustainability of airports, airlines, and affiliated service providers. This is especially so in a world characterized by an increasing volume of both domestic and international air travel, price and other forms of competition between rival airports, airport hubs and airlines, and rapid and sometimes unexpected changes in airline routes and carriers. It also reflects expansion in the number of airports handling regional, national, and international traffic and the growth of complementary airport facilities including industrial, commercial, and retail premises. This has fostered a steadily increasing volume of research aimed at modeling and providing best-practice measures and estimates of airport efficiency using mathematical and econometric frontiers. The purpose of this chapter is to review these various methods as they apply to airports throughout the world. Apart from discussing the strengths and weaknesses of the different approaches and their key findings, the paper also examines the steps faced by researchers as they move through the modeling process in defining airport inputs and outputs and the purported efficiency drivers. Accordingly, the chapter provides guidance to those conducting empirical research on airport efficiency and serves as an aid for aviation regulators and airport operators among others interpreting airport efficiency research outcomes.
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Most persistent organic pollutants (POPs) like polychlorinated biphenyls (PCBs), a range of polybrominated diphenyl ethers (PBDEs) and organochlorine pesticides (OCPs) are readily absorbed (via the ingestion and inhalation) and accumulate in fatty tissue, including adipose tissue and human milk [1]. Health effects related to exposure to these chemicals may include neurological effects, altered functioning of the nervous system and/or endocrine disruption [2-4]. The burden of environmental disease is recognized as much higher for children than adults, especially in young children under 5 years of age worldwide [5]. There is increased concern regarding the environmental impact on the health of children who have been disproportionately affected by environmental problems. For example they may be subjected to relatively higher exposure, have greater physiological susceptibility and/or suffer more extreme consequences due to growth [6-9]. It is therefore worthwhile to assess the correlation between burden of disease and exposure to xenobiotic chemical pollutants like POPs. Such assessment may provide guidance for legislative changes regarding chemical bans and give reliable advice to parents including lactating mothers.
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In earlier cultures and societies, hazards and risks to human health were dealt with by methods derived from myth, metaphor and ritual. In modem society however, notions of hazard and risk have been transformed from the level of a folk discourse to that of an expert centred concept (Plough & Krimsky, 1987). With the professionalization of risk and hazard analysis came a preferred framework for decision making based on a range of 'technical' methodologies (Giere, 1991 ). This is especially true for decision processes relating to risk assessment and management, and impact assessment. Such approaches however, often entail narrow technical-based theoretical assumptions about human behaviour and the natural world, and the· methods used. They therefore carry 'in-built' error factors that contribute considerable uncertainty to the results.
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Public concern about the safety of many forms of industrial technology are known to be linked to a range of factors including a perceived lack of confidence in regulatory decision making.1 The use of transgenic plants in agriculture may be seen as an issue that could generate similar concern. Criticism has been made about the completeness of knowledge on the potential for aberrant behaviour of genetically manipulated organisms (GMO's) in release environments, and the adequacy of existing pre‐release screening and assessment methodologies (Goldberg & Tjaden, 1990). Such comments are important because any perceived shortcomings in the pre-release assessment of GMO safety may lead to decreased public support of the technology -‐and the industry itself...
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Nitrogen (N) and phosphorus (P) are essential elements for all living organisms. However, in excess, they contribute to several environmental problems such as aquatic and terrestrial eutrophication. Globally, human action has multiplied the volume of N and P cycling since the onset of industrialization. The multiplication is a result of intensified agriculture, increased energy consumption and population growth. Industrial ecology (IE) is a discipline, in which human interaction with the ecosystems is investigated using a systems analytical approach. The main idea behind IE is that industrial systems resemble ecosystems, and, like them, industrial systems can then be described using material, energy and information flows and stocks. Industrial systems are dependent on the resources provided by the biosphere, and these two cannot be separated from each other. When studying substance flows, the aims of the research from the viewpoint of IE can be, for instance, to elucidate the ways how the cycles of a certain substance could be more closed and how the flows of a certain substance could be decreased per unit of production (= dematerialization). In Finland, N and P are studied widely in different ecosystems and environmental emissions. A holistic picture comparing different societal systems is, however, lacking. In this thesis, flows of N and P were examined in Finland using substance flow analysis (SFA) in the following four subsystems: I) forest industry and use of wood fuels, II) food production and consumption, III) energy, and IV) municipal waste. A detailed analysis at the end of the 1990s was performed. Furthermore, historical development of the N and P flows was investigated in the energy system (III) and the municipal waste system (IV). The main research sources were official statistics, literature, monitoring data, and expert knowledge. The aim was to identify and quantify the main flows of N and P in Finland in the four subsystems studied. Furthermore, the aim was to elucidate whether the nutrient systems are cyclic or linear, and to identify how these systems could be more efficient in the use and cycling of N and P. A final aim was to discuss how this type of an analysis can be used to support decision-making on environmental problems and solutions. Of the four subsystems, the food production and consumption system and the energy system created the largest N flows in Finland. For the creation of P flows, the food production and consumption system (Paper II) was clearly the largest, followed by the forest industry and use of wood fuels and the energy system. The contribution of Finland to N and P flows on a global scale is low, but when compared on a per capita basis, we are one of the largest producers of these flows, with relatively high energy and meat consumption being the main reasons. Analysis revealed the openness of all four systems. The openness is due to the high degree of internationality of the Finnish markets, the large-scale use of synthetic fertilizers and energy resources and the low recycling rate of many waste fractions. Reduction in the use of fuels and synthetic fertilizers, reorganization of the structure of energy production, reduced human intake of nutrients and technological development are crucial in diminishing the N and P flows. To enhance nutrient recycling and replace inorganic fertilizers, recycling of such wastes as wood ash and sludge could be promoted. SFA is not usually sufficiently detailed to allow specific recommendations for decision-making to be made, but it does yield useful information about the relative magnitude of the flows and may reveal unexpected losses. Sustainable development is a widely accepted target for all human action. SFA is one method that can help to analyse how effective different efforts are in leading to a more sustainable society. SFA's strength is that it allows a holistic picture of different natural and societal systems to be drawn. Furthermore, when the environmental impact of a certain flow is known, the method can be used to prioritize environmental policy efforts.
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There are increasing requirements for impact assessment by development partners in order to increase the accountability and effectiveness of research and development projects. Impact assessment research has been dominated by conventional economic methods. This context challenges agricultural research organizations to develop and apply alternative impact assessment methods incorporating economic, social, and environmental impact components. In this study, we use the Tradeoff Analysis for Multi-Dimensional Impact Assessment (TOA-MD) model to evaluate the impact of integrated aquaculture-agriculture (IAA) adoption in Malawi. The study demonstrated that with a minimal data set, the TOA-MD model can be applied to predict and assess the adoption rates of new technologies and practices as well as their economic and non-economic impacts.
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A sensitivity study has been conducted to assess the robustness of the conclusions presented in the MIT Fuel Cycle Study. The Once Through Cycle (OTC) is considered as the base-line case, while advanced technologies with fuel recycling characterize the alternative fuel cycles. The options include limited recycling in LWRs and full recycling in fast reactors and in high conversion LWRs. Fast reactor technologies studied include both oxide and metal fueled reactors. The analysis allowed optimization of the fast reactor conversion ratio with respect to desired fuel cycle performance characteristics. The following parameters were found to significantly affect the performance of recycling technologies and their penetration over time: Capacity Factors of the fuel cycle facilities, Spent Fuel Cooling Time, Thermal Reprocessing Introduction Date, and incore and Out-of-core TRU Inventory Requirements for recycling technology. An optimization scheme of the nuclear fuel cycle is proposed. Optimization criteria and metrics of interest for different stakeholders in the fuel cycle (economics, waste management, environmental impact, etc.) are utilized for two different optimization techniques (linear and stochastic). Preliminary results covering single and multi-variable and single and multi-objective optimization demonstrate the viability of the optimization scheme.