30 resultados para Environmental application

em CentAUR: Central Archive University of Reading - UK


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Life-Cycle Assessment (LCA) was used to assess the potential environmental and human health impacts of growing genetically-modified (GM), herbicide-tolerant sugar beet in the UK and Germany compared with conventional sugar beet varieties. The GM variety results in lower potential environmental impacts on global warming, airborne nutrification, ecotoxicity (of soil and water) and watercourse enrichment, and lower potential human health impacts in terms of production of toxic particulates, summer smog, carcinogens and ozone depletion. Although the overall contribution of GM sugar beet to reducing harmful emissions to the environment would be relatively small, the potential for GM crops to reduce pollution from agriculture, including diffuse water pollution, is highlighted.

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Shiga toxin producing Escherichia coli (STEC) strains are foodborne pathogens whose ability to produce Shiga toxin (Stx) is due to the integration of Stx-encoding lambdoid bacteriophage (Stx phage). Circulating, infective Stx phages are very difficult to isolate, purify and propagate such that there is no information on their genetic composition and properties. Here we describe a novel approach that exploits the phage's ability to infect their host and form a lysogen, thus enabling purification of Stx phages by a series of sequential lysogen isolation and induction steps. A total of 15 Stx phages were rigorously purified from water samples in this way, classified by TEM and genotyped using a PCR-based multi-loci characterisation system. Each phage possessed only one variant of each target gene type, thus confirming its purity, with 9 of the 15 phages possessing a short tail-spike gene and identified by TEM as Podoviridae. The remaining 6 phages possessed long tails, four of which appeared to be contractile in nature (Myoviridae) and two of which were morphologically very similar to bacteriophage lambda (Siphoviridae).

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This paper presents an integrative and spatially explicit modeling approach for analyzing human and environmental exposure from pesticide application of smallholders in the potato producing Andean region in Colombia. The modeling approach fulfills the following criteria: (i) it includes environmental and human compartments; (ii) it contains a behavioral decision-making model for estimating the effect of policies on pesticide flows to humans and the environment; (iii) it is spatially explicit; and (iv) it is modular and easily expandable to include additional modules, crops or technologies. The model was calibrated and validated for the Vereda La Hoya and was used to explore the effect of different policy measures in the region. The model has moderate data requirements and can be adapted relatively easy to other regions in developing countries with similar conditions.

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The accurate prediction of storms is vital to the oil and gas sector for the management of their operations. An overview of research exploring the prediction of storms by ensemble prediction systems is presented and its application to the oil and gas sector is discussed. The analysis method used requires larger amounts of data storage and computer processing time than other more conventional analysis methods. To overcome these difficulties eScience techniques have been utilised. These techniques potentially have applications to the oil and gas sector to help incorporate environmental data into their information systems

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Bioturbation at all scales, which tends to replace the primary fabric of a sediment by the ichnofabric (the overall fabric of a sediment that has been bioturbated), is now recognised as playing a major role in facies interpretation. The manner in which the substrate may be colonized, and the physical, chemical and ecological controls (grainsize, sedimentation rate, oxygenation, nutrition, salinity, ethology, community structure and succession), together with the several ways in which the substrate is tiered by bioturbators, are the factors and processes that determine the nature of the ichnofabric. Eleven main styles of substrate tiering are described, ranging from single, pioneer colonization to complex tiering under equilibria, their modification under environmental deterioration and amelioration, and diagenetic enhancement or obscuration. Ichnofabrics may be assessed by four attributes: primary sedimentary factors, Bioturbation Index (BI), burrow size and frequency, and ichnological diversity. Construction of tier and ichnofabric constituent diagrams aid visualization and comparison. The breaks or changes in colonization and style of tiering at key stratal surfaces accentuate the surfaces, and many reflect a major environmental shift of the trace-forming biota. due to change in hydrodynamic regime (leading to non-deposition and/or erosion and/or lithification), change in salinity regime, or subaerial exposure. The succession of gradational or abrupt changes in ichnofabric through genetically related successions, together with changes in colonization and tiering across event beds, may also be interpreted in terms of changes in environmental parameters. It is not the ichnotaxa per se that are important in discriminating between ichnofabrics, but rather the environmental conditions that determine the overall style of colonization. Fabrics composed of different ichnotaxa (and different taphonomies) but similar tier structure and ichnoguild may form in similar environments of different age or different latitude. Appreciation of colonization and tiering styles places ancient ichnofabrics on a sound processrelated basis for environmental interpretation. (C) 2002 Elsevier Science B.V. All rights reserved.

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The development of high throughput techniques ('chip' technology) for measurement of gene expression and gene polymorphisms (genomics), and techniques for measuring global protein expression (proteomics) and metabolite profile (metabolomics) are revolutionising life science research, including research in human nutrition. In particular, the ability to undertake large-scale genotyping and to identify gene polymorphisms that determine risk of chronic disease (candidate genes) could enable definition of an individual's risk at an early age. However, the search for candidate genes has proven to be more complex, and their identification more elusive, than previously thought. This is largely due to the fact that much of the variability in risk results from interactions between the genome and environmental exposures. Whilst the former is now very well defined via the Human Genome Project, the latter (e.g. diet, toxins, physical activity) are poorly characterised, resulting in inability to account for their confounding effects in most large-scale candidate gene studies. The polygenic nature of most chronic diseases offers further complexity, requiring very large studies to disentangle relatively weak impacts of large numbers of potential 'risk' genes. The efficacy of diet as a preventative strategy could also be considerably increased by better information concerning gene polymorphisms that determine variability in responsiveness to specific diet and nutrient changes. Much of the limited available data are based on retrospective genotyping using stored samples from previously conducted intervention trials. Prospective studies are now needed to provide data that can be used as the basis for provision of individualised dietary advice and development of food products that optimise disease prevention. Application of the new technologies in nutrition research offers considerable potential for development of new knowledge and could greatly advance the role of diet as a preventative disease strategy in the 21st century. Given the potential economic and social benefits offered, funding for research in this area needs greater recognition, and a stronger strategic focus, than is presently the case. Application of genomics in human health offers considerable ethical and societal as well as scientific challenges. Economic determinants of health care provision are more likely to resolve such issues than scientific developments or altruistic concerns for human health.

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The paper provides one of the first applications of the double bootstrap procedure (Simar and Wilson 2007) in a two-stage estimation of the effect of environmental variables on non-parametric estimates of technical efficiency. This procedure enables consistent inference within models explaining efficiency scores, while simultaneously producing standard errors and confidence intervals for these efficiency scores. The application is to 88 livestock and 256 crop farms in the Czech Republic, split into individual and corporate.

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The paper provides one of the first applications of the double bootstrap procedure (Simar and Wilson 2007) in a two-stage estimation of the effect of environmental variables on non-parametric estimates of technical efficiency. This procedure enables consistent inference within models explaining efficiency scores, while simultaneously producing standard errors and confidence intervals for these efficiency scores. The application is to 88 livestock and 256 crop farms in the Czech Republic, split into individual and corporate.

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Large scientific applications are usually developed, tested and used by a group of geographically dispersed scientists. The problems associated with the remote development and data sharing could be tackled by using collaborative working environments. There are various tools and software to create collaborative working environments. Some software frameworks, currently available, use these tools and software to enable remote job submission and file transfer on top of existing grid infrastructures. However, for many large scientific applications, further efforts need to be put to prepare a framework which offers application-centric facilities. Unified Air Pollution Model (UNI-DEM), developed by Danish Environmental Research Institute, is an example of a large scientific application which is in a continuous development and experimenting process by different institutes in Europe. This paper intends to design a collaborative distributed computing environment for UNI-DEM in particular but the framework proposed may also fit to many large scientific applications as well.

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The development of eutrophication in river systems is poorly understood given the complex relationship between fixed plants, algae, hydrodynamics, water chemistry and solar radiation. However there is a pressing need to understand the relationship between the ecological status of rivers and the controlling environmental factors to help the reasoned implementation of the Water Framework Directive and Catchment Sensitive Farming in the UK. This research aims to create a dynamic, process-based, mathematical in-stream model to simulate the growth and competition of different vegetation types (macrophytes, phytoplankton and benthic algae) in rivers. The model, applied to the River Frome (Dorset, UK), captured well the seasonality of simulated vegetation types (suspended algae, macrophytes, epiphytes, sediment biofilm). Macrophyte results showed that local knowledge is important for explaining unusual changes in biomass. Fixed algae simulations indicated the need for the more detailed representation of various herbivorous grazer groups, however this would increase the model complexity, the number of model parameters and the required observation data to better define the model. The model results also highlighted that simulating only phytoplankton is insufficient in river systems, because the majority of the suspended algae have benthic origin in short retention time rivers. Therefore, there is a need for modelling tools that link the benthic and free-floating habitats.

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A generic model of Exergy Assessment is proposed for the Environmental Impact of the Building Lifecycle, with a special focus on the natural environment. Three environmental impacts: energy consumption, resource consumption and pollutant discharge have been analyzed with reference to energy-embodied exergy, resource chemical exergy and abatement exergy, respectively. The generic model of Exergy Assessment of the Environmental Impact of the Building Lifecycle thus formulated contains two sub-models, one from the aspect of building energy utilization and the other from building materials use. Combined with theories by ecologists such as Odum, the paper evaluates a building's environmental sustainability through its exergy footprint and environmental impacts. A case study from Chongqing, China illustrates the application of this method. From the case study, it was found that energy consumption constitutes 70–80% of the total environmental impact during a 50-year building lifecycle, in which the operation phase accounts for 80% of the total environmental impact, the building material production phase 15% and 5% for the other phases.

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Agri-environment schemes (AESs) have been implemented across EU member states in an attempt to reconcile agricultural production methods with protection of the environment and maintenance of the countryside. To determine the extent to which such policy objectives are being fulfilled, participating countries are obliged to monitor and evaluate the environmental, agricultural and socio-economic impacts of their AESs. However, few evaluations measure precise environmental outcomes and critically, there are no agreed methodologies to evaluate the benefits of particular agri-environmental measures, or to track the environmental consequences of changing agricultural practices. In response to these issues, the Agri-Environmental Footprint project developed a common methodology for assessing the environmental impact of European AES. The Agri-Environmental Footprint Index (AFI) is a farm-level, adaptable methodology that aggregates measurements of agri-environmental indicators based on Multi-Criteria Analysis (MCA) techniques. The method was developed specifically to allow assessment of differences in the environmental performance of farms according to participation in agri-environment schemes. The AFI methodology is constructed so that high values represent good environmental performance. This paper explores the use of the AFI methodology in combination with Farm Business Survey data collected in England for the Farm Accountancy Data Network (FADN), to test whether its use could be extended for the routine surveillance of environmental performance of farming systems using established data sources. Overall, the aim was to measure the environmental impact of three different types of agriculture (arable, lowland livestock and upland livestock) in England and to identify differences in AFI due to participation in agri-environment schemes. However, because farm size, farmer age, level of education and region are also likely to influence the environmental performance of a holding, these factors were also considered. Application of the methodology revealed that only arable holdings participating in agri-environment schemes had a greater environmental performance, although responses differed between regions. Of the other explanatory variables explored, the key factors determining the environmental performance for lowland livestock holdings were farm size, farmer age and level of education. In contrast, the AFI value of upland livestock holdings differed only between regions. The paper demonstrates that the AFI methodology can be used readily with English FADN data and therefore has the potential to be applied more widely to similar data sources routinely collected across the EU-27 in a standardised manner.

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The present paper investigates pesticide application types adopted by smallholder potato producers in the Department of Boyacá , Colombia. In this region, environmental, health and adverse economic effects due to pesticide mis- or over-use respectively have been observed. Firstly, pesticide application types were identified based on input-effectiveness. Secondly, their determinants of adoption were investigated. Finally suggestions were given to develop intervention options for transition towards a more sustainable pesticide use. Three application types were identified for fungicide and insecticide. The types differed in terms of input (intensity of pesticide application), effect (damage control), frequency of application, average quantity applied per application, chemical class, and productivity. Then, the determinants of different pesticide application types were investigated with a multinomial logistic regression approach and applying the integrative agent centred (IAC) framework. The area of the plot, attendance at training sessions and educational and income levels were among the most relevant determinants. The analysis suggested that better pesticide use could be fostered to reduce pesticide-related risks in the region. Intervention options were outlined, which may help in targeting this issue. They aim not only at educating farmers, but to change their social and institutional context, by involving other agents of the agricultural system (i.e. pesticide producers), facilitating new institutional settings (i.e. cooperatives) and targeting social dynamics (i.e. conformity to social norms).

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Anticoagulant rodenticide (AR) resistance in Norway rat populations has been a problem for fifty years, however its impact on non-target species, particularly predatory and scavenging animals has received little attention. Field trials were conducted on farms in Germany and England where resistance to anticoagulant rodenticides had been confirmed. Resistance is conferred by different mutations of the VKORC1 gene in each of these regions: tyrosine139cysteine in Germany and leucine120glutamine in England. A modelling approach was used to study the transference of the anticoagulants into the environment during treatments for Norway rat control. Baiting with brodifacoum resulted in lower levels of AR entering the food chain via the rats and lower numbers of live rats carrying residues during and after the trials due to its lower application rate and efficacy against resistant rats. Bromadiolone and difenacoum resulted in markedly higher levels of AR uptake into the rat population and larger numbers of live rats carrying residues during the trials and for long periods after the baiting period. Neither bromadiolone nor difenacoum provided full control on any of the treated farms. In resistant areas where ineffective compounds are used there is the potential for higher levels of AR exposure to non-target animals, particularly predators of rats and scavengers of rat carcasses. Thus, resistance influences the total amount of AR available to non-targets and should be considered when dealing with rat infestations, as resistance-breakers may present a lower risk to wildlife.