30 resultados para Adverse impacts

em CentAUR: Central Archive University of Reading - UK


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This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.

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The breeding success of Cory's shearwaters Calonectris diomedea borealis at its important Atlantic colony on Selvagern Grande has been monitored periodically at two study plots since 1982. A successful eradication programme was implemented to remove two alien invasive mammals, rabbits Oryctolagus cuniculus and house mice Mus musculus, from the island during 2002. The availability of long-term breeding data for Cory's shearwaters on Selvagern Grande provided a unique opportunity to study the effects of the removal of rabbits and mice on seabird breeding. Annual observation of approximately 400 Cory's nests showed that significantly more birds fledged from both study sites in the five breeding seasons after the eradication than in the 13 seasons prior to it for which reliable breeding data were available. The numbers of young birds present at the time of fledging were an average of 47 and 23% greater than pre-eradication numbers at the two study sites. The eradication of rabbits and mice was simultaneous and, therefore, it was impossible to attribute the increased breeding success of Cory's shearwaters to the removal of one or other species. However, both are known to have adverse impacts on the breeding of nesting seabirds. These observations provide important justification for the implementation of further programmes for the removal of alien invasive mammals from oceanic islands.

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Although the construction pollution index has been put forward and proved to be an efficient approach to reducing or mitigating pollution level during the construction planning stage, the problem of how to select the best construction plan based on distinguishing the degree of its potential adverse environmental impacts is still a research task. This paper first reviews environmental issues and their characteristics in construction, which are critical factors in evaluating potential adverse impacts of a construction plan. These environmental characteristics are then used to structure two decision models for environmental-conscious construction planning by using an analytic network process (ANP), including a complicated model and a simplified model. The two ANP models are combined and called the EnvironalPlanning system, which is applied to evaluate potential adverse environmental impacts of alternative construction plans.

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Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

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Executive summary Nature of the problem • Environmental problems related to nitrogen concern all economic sectors and impact all media: atmosphere, pedosphere, hydrosphere and anthroposphere. • Therefore, the integration of fluxes allows an overall coverage of problems related to reactive nitrogen (Nr) in the environment, which is not accessible from sectoral approaches or by focusing on specific media. Approaches • This chapter presents a set of high resolution maps showing key elements of the N flux budget across Europe, including N2 and Nr fluxes. • Comparative nitrogen budgets are also presented for a range of European countries, highlighting the most efficient strategies for mitigating Nr problems at a national scale. A new European Nitrogen Budget (EU-27) is presented on the basis of state-of-the-art Europe-wide models and databases focusing on different segments of Europe’s society. Key findings • From c. 18 Tg Nr yr −1 input to agriculture in the EU-27, only about 7 Tg Nr yr− 1 find their way to the consumer or are further processed by industry. • Some 3.7 Tg Nr yr−1 is released by the burning of fossil fuels in the EU-27, whereby the contribution of the industry and energy sectors is equal to that of the transport sector. More than 8 Tg Nr yr−1 are disposed of to the hydrosphere, while the EU-27 is a net exporter of reactive nitrogen through atmospheric transport of c. 2.3 Tg Nr yr−1. • The largest single sink for Nr appears to be denitrifi cation to N2 in European coastal shelf regions (potentially as large as the input of mineral fertilizer, about 11 Tg N yr–1 for the EU-27); however, this sink is also the most uncertain, because of the uncertainty of Nr import from the open ocean. Major uncertainties • National nitrogen budgets are diffi cult to compile using a large range of data sources and are currently available only for a limited number of countries. • Modelling approaches have been used to fill in the data gaps in some of these budgets, but it became obvious during this study that further research is needed in order to collect necessary data and make national nitrogen budgets inter-comparable across Europe. • In some countries, due to inconsistent or contradictory information coming from different data sources, closure of the nitrogen budget was not possible. Recommendations • The large variety of problems associated with the excess of Nr in the European environment,including adverse impacts, requires an integrated nitrogen management approach that would allow for creation and closure of N budgets within European environments. • Development of nitrogen budgets nationwide, their assessment and management could become an effective tool to prioritize measures and prevent unwanted side effects.

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Experiments assimilating the RAPID dataset of deep temperature and salinity profiles at 26.5°N on the western and eastern Atlantic boundaries into a 1° global NEMO ocean model have been performed. The meridional overturning circulation (MOC) is then assessed against the transports calculated directly from observations. The best initialization found for this short period was obtained by assimilating the EN3 upper-ocean hydrography database prior to 2004, after which different methods of assimilating 5-day average RAPID profiles at the western boundary were tested. The model MOC is strengthened by ∼ 2 Sv giving closer agreement with the RAPID array transports, when the western boundary profiles are assimilated only below 900 m (the approximate depth of the Florida Straits, which are not well resolved) and when the T,S observations are spread meridionally from 10 to 35°N along the deep western boundary. The use of boundary-focused covariances has the largest impact on the assimilation results, otherwise using more conventional Gaussian covariances has a very local impact on the MOC at 26°N with strong adverse impacts on the MOC stream function at higher and lower latitudes. Even using boundary-focused covariances only enables the MOC to be strengthened for ∼ 2 years, after which the increased transport of warm waters leads to a negative feedback on water formation in the subpolar gyre which then reduces the MOC. This negative feedback can be mitigated if EN3 hydrography data continue to be assimilated along with the RAPID array boundary data. Copyright © 2012 Royal Meteorological Society and Crown in the right of Canada.

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Requirements for research, practices and policies affecting soil management in relation to global food security are reviewed. Managing soil organic carbon (C) is central because soil organic matter influences numerous soil properties relevant to ecosystem functioning and crop growth. Even small changes in total C content can have disproportionately large impacts on key soil physical properties. Practices to encourage maintenance of soil C are important for ensuring sustainability of all soil functions. Soil is a major store of C within the biosphere – increases or decreases in this large stock can either mitigate or worsen climate change. Deforestation, conversion of grasslands to arable cropping and drainage of wetlands all cause emission of C; policies and international action to minimise these changes are urgently required. Sequestration of C in soil can contribute to climate change mitigation but the real impact of different options is often misunderstood. Some changes in management that are beneficial for soil C, increase emissions of nitrous oxide (a powerful greenhouse gas) thus cancelling the benefit. Research on soil physical processes and their interactions with roots can lead to improved and novel practices to improve crop access to water and nutrients. Increased understanding of root function has implications for selection and breeding of crops to maximise capture of water and nutrients. Roots are also a means of delivering natural plant-produced chemicals into soil with potentially beneficial impacts. These include biocontrol of soil-borne pests and diseases and inhibition of the nitrification process in soil (conversion of ammonium to nitrate) with possible benefits for improved nitrogen use efficiency and decreased nitrous oxide emission. The application of molecular methods to studies of soil organisms, and their interactions with roots, is providing new understanding of soil ecology and the basis for novel practical applications. Policy makers and those concerned with development of management approaches need to keep a watching brief on emerging possibilities from this fast-moving area of science. Nutrient management is a key challenge for global food production: there is an urgent need to increase nutrient availability to crops grown by smallholder farmers in developing countries. Many changes in practices including inter-cropping, inclusion of nitrogen-fixing crops, agroforestry and improved recycling have been clearly demonstrated to be beneficial: facilitating policies and practical strategies are needed to make these widely available, taking account of local economic and social conditions. In the longer term fertilizers will be essential for food security: policies and actions are needed to make these available and affordable to small farmers. In developed regions, and those developing rapidly such as China, strategies and policies to manage more precisely the necessarily large flows of nutrients in ways that minimise environmental damage are essential. A specific issue is to minimise emissions of nitrous oxide whilst ensuring sufficient nitrogen is available for adequate food production. Application of known strategies (through either regulation or education), technological developments, and continued research to improve understanding of basic processes will all play a part. Decreasing soil erosion is essential, both to maintain the soil resource and to minimise downstream damage such as sedimentation of rivers with adverse impacts on fisheries. Practical strategies are well known but often have financial implications for farmers. Examples of systems for paying one group of land users for ecosystem services affecting others exist in several parts of the world and serve as a model.

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Previous assessments of the impacts of climate change on heat-related mortality use the "delta method" to create temperature projection time series that are applied to temperature-mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heatrelated mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature-mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heatrelated mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2°C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.

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The aim of this paper is to demonstrate the importance of changing temperature variability with climate change in assessments of future heat-related mortality. Previous studies have only considered changes in the mean temperature. Here we present estimates of heat-related mortality resulting from climate change for six cities: Boston, Budapest, Dallas, Lisbon, London and Sydney. They are based on climate change scenarios for the 2080s (2070-2099) and the temperature-mortality (t-m) models constructed and validated in Gosling et al. (2007). We propose a novel methodology for assessing the impacts of climate change on heat-related mortality that considers both changes in the mean and variability of the temperature distribution.

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The INtegrated CAtchment (INCA) model has been developed to simulate the impact of mine discharges on river systems. The model accounts for the key kinetic chemical processes operating as well as the dilution, mixing and redistribution of pollutants in rivers downstream of mine discharges or acid rock drainage sites. The model is dynamic and simulates the day-to-day behaviour of hydrology and eight metals (cadmium, mercury, copper, zinc, lead, arsenic, manganese and chromium) as well as cyanide and ammonia. The model is semi-distributed and can simulate catchments, sub-catchment and in-stream river behaviour. The model has been applied to the Roia Montan Mine in Transylvania, Romania, and used to assess the impacts of old mine adits on the local catchments as well as on the downstream Aries and Mures river system. The question of mine restoration is investigated and a set of clean-up scenarios investigated. It is shown that the planned restoration will generate a much improved water quality from the mine and also alleviate the metal pollution of the river system.

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A modelling study has been undertaken to assess the likely impacts of climate change on water quality across the UK. A range of climate change scenarios have been used to generate future precipitation, evaporation and temperature time series at a range of catchments across the UK. These time series have then been used to drive the Integrated Catchment (INCA) suite of flow, water quality and ecological models to simulate flow, nitrate, ammonia, total and soluble reactive phosphorus, sediments, macrophytes and epiphytes in the Rivers Tamar, Lugg, Tame, Kennet, Tweed and Lambourn. A wide range of responses have been obtained with impacts varying depending on river character, catchment location, flow regime, type of scenario and the time into the future. Essentially upland reaches of river will respond differently to lowland reaches of river, and the responses will vary depending on the water quality parameter of interest.

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It is now accepted that some human-induced climate change is unavoidable. Potential impacts on water supply have received much attention, but relatively little is known about the concomitant changes in water quality. Projected changes in air temperature and rainfall could affect river flows and, hence, the mobility and dilution of contaminants. Increased water temperatures will affect chemical reaction kinetics and, combined with deteriorations in quality, freshwater ecological status. With increased flows there will be changes in stream power and, hence, sediment loads with the potential to alter the morphology of rivers and the transfer of sediments to lakes, thereby impacting freshwater habitats in both lake and stream systems. This paper reviews such impacts through the lens of UK surface water quality. Widely accepted climate change scenarios suggest more frequent droughts in summer, as well as flash-flooding, leading to uncontrolled discharges from urban areas to receiving water courses and estuaries. Invasion by alien species is highly likely, as is migration of species within the UK adapting to changing temperatures and flow regimes. Lower flows, reduced velocities and, hence, higher water residence times in rivers and lakes will enhance the potential for toxic algal blooms and reduce dissolved oxygen levels. Upland streams could experience increased dissolved organic carbon and colour levels, requiring action at water treatment plants to prevent toxic by-products entering public water supplies. Storms that terminate drought periods will flush nutrients from urban and rural areas or generate acid pulses in acidified upland catchments. Policy responses to climate change, such as the growth of bio-fuels or emission controls, will further impact freshwater quality.

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The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.