535 resultados para Farm life.

em Queensland University of Technology - ePrints Archive


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Farm It Right is an innovative creative work that simulates sustainable farming techniques using ecological models prepared by academics at Bradford University (School of Life Sciences). This interactive work simulates the farming conditions and options of our ancestors and demonstrates the direct impact their actions had on their environment and on the ’future of their cultures’ (Schmidt 2008). Specifically, the simulation allows users to explore and experiment with the complex relationships between environmental factors and human decision making within the harsh conditions of an early (9th century) Nordic farm. The simulation interface displays both statistical and graphical feedback in response to the users selections regarding animal reproduction rates, shelter provisions, food supplies etc. as well as demonstrating resulting impacts to soil erosion, water supply, animal population sizes etc.---------- 'Farm It Right' is now used at Bradford University (School of Life Sciences) as a dynamic e-Learning resource for incorporating environmental archaeology with sustainable development education, improving the engagement with complex data and the appreciation of human impacts on the environment and the future of their cultures. 'Farm It Right' is also demonstrated as an exemplar case study for interaction design students at Queensland University of Technology.

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In life cycle assessment studies, greenhouse gas (GHG) emissions from direct land-use change have been estimated to make a significant contribution to the global warming potential of agricultural products. However, these estimates have a high uncertainty due to the complexity of data requirements and difficulty in attribution of land-use change. This paper presents estimates of GHG emissions from direct land-use change from native woodland to grazing land for two beef production regions in eastern Australia, which were the subject of a multi-impact life cycle assessment study for premium beef production. Spatially- and temporally consistent datasets were derived for areas of forest cover and biomass carbon stocks using published remotely sensed tree-cover data and regionally applicable allometric equations consistent with Australia's national GHG inventory report. Standard life cycle assessment methodology was used to estimate GHG emissions and removals from direct land-use change attributed to beef production. For the northern-central New South Wales region of Australia estimates ranged from a net emission of 0.03 t CO2-e ha-1 year-1 to net removal of 0.12 t CO2-e ha-1 year-1 using low and high scenarios, respectively, for sequestration in regrowing forests. For the same period (1990-2010), the study region in southern-central Queensland was estimated to have net emissions from land-use change in the range of 0.45-0.25 t CO2-e ha-1 year-1. The difference between regions reflects continuation of higher rates of deforestation in Queensland until strict regulation in 2006 whereas native vegetation protection laws were introduced earlier in New South Wales. On the basis of liveweight produced at the farm-gate, emissions from direct land-use change for 1990-2010 were comparable in magnitude to those from other on-farm sources, which were dominated by enteric methane. However, calculation of land-use change impacts for the Queensland region for a period starting 2006, gave a range from net emissions of 0.11 t CO2-e ha-1 year-1 to net removals of 0.07 t CO2-e ha-1 year-1. This study demonstrated a method for deriving spatially- and temporally consistent datasets to improve estimates for direct land-use change impacts in life cycle assessment. It identified areas of uncertainty, including rates of sequestration in woody regrowth and impacts of land-use change on soil carbon stocks in grazed woodlands, but also showed the potential for direct land-use change to represent a net sink for GHG.

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OBJECTIVE: To evaluate the scored Patient-generated Subjective Global Assessment (PG-SGA) tool as an outcome measure in clinical nutrition practice and determine its association with quality of life (QoL). DESIGN: A prospective 4 week study assessing the nutritional status and QoL of ambulatory patients receiving radiation therapy to the head, neck, rectal or abdominal area. SETTING: Australian radiation oncology facilities. SUBJECTS: Sixty cancer patients aged 24-85 y. INTERVENTION: Scored PG-SGA questionnaire, subjective global assessment (SGA), QoL (EORTC QLQ-C30 version 3). RESULTS: According to SGA, 65.0% (39) of subjects were well-nourished, 28.3% (17) moderately or suspected of being malnourished and 6.7% (4) severely malnourished. PG-SGA score and global QoL were correlated (r=-0.66, P<0.001) at baseline. There was a decrease in nutritional status according to PG-SGA score (P<0.001) and SGA (P<0.001); and a decrease in global QoL (P<0.001) after 4 weeks of radiotherapy. There was a linear trend for change in PG-SGA score (P<0.001) and change in global QoL (P=0.003) between those patients who improved (5%) maintained (56.7%) or deteriorated (33.3%) in nutritional status according to SGA. There was a correlation between change in PG-SGA score and change in QoL after 4 weeks of radiotherapy (r=-0.55, P<0.001). Regression analysis determined that 26% of the variation of change in QoL was explained by change in PG-SGA (P=0.001). CONCLUSION: The scored PG-SGA is a nutrition assessment tool that identifies malnutrition in ambulatory oncology patients receiving radiotherapy and can be used to predict the magnitude of change in QoL.

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Until now health impact assessment and environmental impact assessment are two different issues, often not addressed together. Both issues have to be dealt with for sustainable building. The aim of this paper is to link healthy and sustainable housing in life cycle assessment. Two strategies are studied: clean air as a functional unity and health as a quality indicator. The strategies are illustrated with an example on the basis of Eco-Quantum, which is a Dutch whole-building assessment tool. It turns out that both strategies do not conflict with the LCA methodology. The LCA methodology has to be refined for this purpose.