24 resultados para Impact assessments

em CentAUR: Central Archive University of Reading - UK


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Interest in the impacts of climate change is ever increasing. This is particularly true of the water sector where understanding potential changes in the occurrence of both floods and droughts is important for strategic planning. Climate variability has been shown to have a significant impact on UK climate and accounting for this in future climate cahgne projections is essential to fully anticipate potential future impacts. In this paper a new resampling methodology is developed which includes the variability of both baseline and future precipitation. The resampling methodology is applied to 13 CMIP3 climate models for the 2080s, resulting in an ensemble of monthly precipitation change factors. The change factors are applied to the Eden catchment in eastern Scotland with analysis undertaken for the sensitivity of future river flows to the changes in precipitation. Climate variability is shown to influence the magnitude and direction of change of both precipitation and in turn river flow, which are not apparent without the use of the resampling methodology. The transformation of precipitation changes to river flow changes display a degree of non-linearity due to the catchment's role in buffering the response. The resampling methodology developed in this paper provides a new technique for creating climate change scenarios which incorporate the important issue of climate variability.

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Impact Assessments (IAs) were introduced at the EU level under the rhetorical facade of ‘better regulation’. The actual aim was to improve not only the quality but also the reputation of EU regulation before stakeholders. However, evidence brought forward by a number of evaluations pointed out that IAs are yet to achieve acceptable quality standards. The paper offers an overview of different disciplinary approaches for looking at IAs. It suggests that risk regulation encompasses the theoretical foundations to help understand the role of IAs in the EU decisionmaking process. The analysis of 60 early days preliminary IAs provides empirical evidence regarding policy alternatives, methodology of consultation and use of quantitative techniques. Findings suggest that dawn period IAs were used mainly to provide some empirical evidence for regulatory intervention in front of stakeholders. The paper concludes with assumptions about the future role of IAs at EU level.

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Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator.

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We develop a new governance perspective on port–hinterland linkages and related port impacts. Many stakeholders in a port’s hinterland now demand tangible economic benefits from port activities, as a precondition for supporting port expansion and infrastructural investments. We use a governance lens to assess this farsighted contracting challenge. We find that most contemporary economic impact assessments of port investment projects pay scant attention to the contractual relationship challenges in port-hinterland relationships. In contrast, we focus explicitly on the spatial distribution of such impacts and the related contractual relationship issues facing port authorities or port users and their stakeholders in the port hinterland. We introduce a new concept, the Port Hinterland Impact (PHI) matrix, which focuses explicitly on the spatial distribution of port impacts and related contractual relationship challenges. The PHI matrix offers insight into port impacts using two dimensions: logistics dedicatedness, as an expression of Williamsonian asset specificity in the sphere of logistics contractual relationships, and geographic reach, with a longer reach typically reflecting the need for more complex contacting to overcome ‘distance’ challenges with external stakeholders. We use the PHI matrix in our empirical, governance-based analysis of contractual relationships between the port authorities in Antwerp and Zeebrugge, and their respective stakeholders.

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This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.

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Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.

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As part of the rebuilding efforts following the long civil war, the Liberian government has renegotiated long-term contracts with international investors to exploit natural resources. Substantial areas of land have been handed out in large-scale concessions across Liberia during the last five years. While this may promote economic growth at the national level, such concessions are likely to have major environmental, social and economic impacts on local communities, who may not have been consulted on the proposed developments. This report examines the potential socio-economic and environmental impacts of a proposed large-scale oil palm concession in Bopolu District, Gbarpolu County in Liberia. The research provided an in-depth mapping of current resource use, livelihoods and ecosystems services, in addition to analysis of community consultation and perceptions of the potential impacts of the proposed development. This case study of a palm oil concession in Liberia highlights wider policy considerations regarding large-scale land acquisitions in the global South: • Formal mechanisms may be needed to ensure the process of Free, Prior, Informed Consent takes place effectively with affected communities and community land rights are safeguarded. • Rigorous Environmental and Social Impact Assessments need to be conducted before operations start. Accurate mapping of customary land rights, community resources and cultural sites, livelihoods, land use, biodiversity and ecosystems services is a critical tool in this process. • Greater clarity and awareness-raising of land tenure laws and policies is needed at all levels. Good governance and capacity-building of key institutions would help to ensure effective implementation of relevant laws and policies. • Efforts are needed to improve basic services and infrastructure in rural communities and invest in food crop cultivation in order to enhance food security and poverty alleviation. Increasing access to inputs, equipment, training and advice is especially important if male and female farmers are no longer able to practice shifting cultivation due to the reduction/ loss of customary land and the need to farm more intensively on smaller areas of land.

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Spatio-temporal landscape heterogeneity has rarely been considered in population-level impact assessments. Here we test whether landscape heterogeneity is important by examining the case of a pesticide applied seasonally to orchards which may affect non-target vole populations, using a validated ecologically realistic and spatially explicit agent-based model. Voles thrive in unmanaged grasslands and untreated orchards but are particularly exposed to applied pesticide treatments during dispersal between optimal habitats. We therefore hypothesised that vole populations do better (1) in landscapes containing more grassland and (2) where areas of grassland are closer to orchards, but (3) do worse if larger areas of orchards are treated with pesticide. To test these hyposeses we made appropriate manipulations to a model landscape occupied by field voles. Pesticide application reduced model population sizes in all three experiments, but populations subsequently wholly or partly recovered. Population depressions were, as predicted, lower in landscapes containing more unmanaged grassland, in landscapes with reduced distance between grassland and orchards, and in landscapes with fewer treated orchards. Population recovery followed a similar pattern except for an unexpected improvement in recovery when the area of treated orchards was increased. Outside the period of pesticide application, orchards increase landscape connectivity and facilitate vole dispersal and so speed population recovery. Overall our results show that accurate prediction of population impact cannot be achieved without taking account of landscape structure. The specifics of landscape structure and habitat connectivity are likely always important in mediating the effects of stressors.

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Incomplete understanding of three aspects of the climate system—equilibrium climate sensitivity, rate of ocean heat uptake and historical aerosol forcing—and the physical processes underlying them lead to uncertainties in our assessment of the global-mean temperature evolution in the twenty-first century1,2. Explorations of these uncertainties have so far relied on scaling approaches3,4, large ensembles of simplified climate models1,2, or small ensembles of complex coupled atmosphere–ocean general circulation models5,6 which under-represent uncertainties in key climate system properties derived from independent sources7–9. Here we present results from a multi-thousand-member perturbed-physics ensemble of transient coupled atmosphere–ocean general circulation model simulations. We find that model versions that reproduce observed surface temperature changes over the past 50 years show global-mean temperature increases of 1.4–3 K by 2050, relative to 1961–1990, under a mid-range forcing scenario. This range of warming is broadly consistent with the expert assessment provided by the Intergovernmental Panel on Climate Change Fourth Assessment Report10, but extends towards larger warming than observed in ensemblesof-opportunity5 typically used for climate impact assessments. From our simulations, we conclude that warming by the middle of the twenty-first century that is stronger than earlier estimates is consistent with recent observed temperature changes and a mid-range ‘no mitigation’ scenario for greenhouse-gas emissions.

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In 2006 the UK government announced a move to zero carbon homes by 2016. The demand posed a major challenge to policy makers and construction professionals entailing a protracted process of policy design. The task of giving content to this target is used to explore the role of evidence in the policy process. Whereas much literature on policy and evidence treats evidence as an external input, independent of politics, this paper explores the ongoing mutual constitution of both. Drawing on theories of policy framing and the sociology of classification, the account follows the story of a policy for Zero Carbon Homes from the parameters and values used to specify the target. Particular attention is given to the role of Regulatory Impact Assessments (RIAs) and to the creation of a new policy venue, the Zero Carbon Hub. The analysis underlines the way in which the choices about how to model and measure the aims potentially transforms them, the importance of policy venues for transparency and the role of RIAs in the authorization of particular definitions. A more transparent, open approach to policy formulation is needed in which the framing of evidence is recognized as an integral part of the policy process.

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Land surface albedo, a key parameter to derive Earth's surface energy balance, is used in the parameterization of numerical weather prediction, climate monitoring and climate change impact assessments. Changes in albedo due to fire have not been fully investigated on a continental and global scale. The main goal of this study, therefore, is to quantify the changes in instantaneous shortwave albedo produced by biomass burning activities and their associated radiative forcing. The study relies on the MODerate-resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned-area product to create an annual composite of areas affected by fire and the MCD43C2 bidirectional reflectance distribution function (BRDF) albedo snow-free product to compute a bihemispherical reflectance time series. The approximate day of burning is used to calculate the instantaneous change in shortwave albedo. Using the corresponding National Centers for Environmental Prediction (NCEP) monthly mean downward solar radiation flux at the surface, the global radiative forcing associated with fire was computed. The analysis reveals a mean decrease in shortwave albedo of −0.014 (1σ = 0.017), causing a mean positive radiative forcing of 3.99 Wm−2 (1σ = 4.89) over the 2002–20012 time period in areas affected by fire. The greatest drop in mean shortwave albedo change occurs in 2002, which corresponds to the highest total area burned (378 Mha) observed in the same year and produces the highest mean radiative forcing (4.5 Wm−2). Africa is the main contributor in terms of burned area, but forests globally give the highest radiative forcing per unit area and thus give detectable changes in shortwave albedo. The global mean radiative forcing for the whole period studied (~0.0275 Wm−2) shows that the contribution of fires to the Earth system is not insignificant.

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Pronounced intermodel differences in the projected response of land surface precipitation (LSP) to future anthropogenic forcing remain in the Coupled Model Intercomparison Project Phase 5 model integrations. A large fraction of the intermodel spread in projected LSP trends is demonstrated here to be associated with systematic differences in simulated sea surface temperature (SST) trends, especially the representation of changes in (i) the interhemispheric SST gradient and (ii) the tropical Pacific SSTs. By contrast, intermodel differences in global mean SST, representative of differing global climate sensitivities, exert limited systematic influence on LSP patterns. These results highlight the importance to regional terrestrial precipitation changes of properly simulating the spatial distribution of large-scale, remote changes as reflected in the SST response to increasing greenhouse gases. Moreover, they provide guidance regarding which region-specific precipitation projections may be potentially better constrained for use in climate change impact assessments.

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This paper introduces the special issue of Climatic Change on the QUEST-GSI project, a global-scale multi-sectoral assessment of the impacts of climate change. The project used multiple climate models to characterise plausible climate futures with consistent baseline climate and socio-economic data and consistent assumptions, together with a suite of global-scale sectoral impacts models. It estimated impacts across sectors under specific SRES emissions scenarios, and also constructed functions relating impact to change in global mean surface temperature. This paper summarises the objectives of the project and its overall methodology, outlines how the project approach has been used in subsequent policy-relevant assessments of future climate change under different emissions futures, and summarises the general lessons learnt in the project about model validation and the presentation of multi-sector, multi-region impact assessments and their associated uncertainties to different audiences.

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Question: What is the impact of the presence of Rhinanthus minor on forb abundance in newly established swards? Location: Wetherby, West Yorkshire, UK (53 degrees 55' N, 1 degrees 22(1) W). Method: A standard meadow mix containing six forbs and six grasses was sown on an ex-arable field and immediately over-sown using a randomised plot design with three densities of Rhinanthus minor (0, 600, and 1000 seeds per m(2)). Above-ground biomass was analysed over a period of three years, while detailed assessments of sward composition were performed during the first two years. Results: Values of grass biomass were reduced in the presence of Rhinanthus, especially at the higher sowing density. The ratio of grass: forb biomass was also lower in association with Rhinanthus, but only at the higher sowing density. The presence of Rhinanthus, had no effect on species number or diversity, which decreased between years regardless of treatment. Conclusions: Although not tested in a multi-site experiment, the benefit of introducing Rhinanthus into newly established swards to promote for abundance was determined. The efficacy of Rhinanthus presence is likely to depend on whether species not susceptible to the effects of parasitism are present.