940 resultados para Global environment
Modelling sediment supply and transport in the River Lugg: strategies for controlling sediment loads
Resumo:
The River Lugg has particular problems with high sediment loads that have resulted in detrimental impacts on ecology and fisheries. A new dynamic, process-based model of hydrology and sediments (INCA- SED) has been developed and applied to the River Lugg system using an extensive data set from 1995–2008. The model simulates sediment sources and sinks throughout the catchment and gives a good representation of the sediment response at 22 reaches along the River Lugg. A key question considered in using the model is the management of sediment sources so that concentrations and bed loads can be reduced in the river system. Altogether, five sediment management scenarios were selected for testing on the River Lugg, including land use change, contour tillage, hedging and buffer strips. Running the model with parameters altered to simulate these five scenarios produced some interesting results. All scenarios achieved some reduction in sediment levels, with the 40% land use change achieving the best result with a 19% reduction. The other scenarios also achieved significant reductions of between 7% and 9%. Buffer strips produce the best result at close to 9%. The results suggest that if hedge introduction, contour tillage and buffer strips were all applied, sediment reductions would total 24%, considerably improving the current sediment situation. We present a novel cost-effectiveness analysis of our results where we use percentage of land removed from production as our cost function. Given the minimal loss of land associated with contour tillage, hedges and buffer strips, we suggest that these management practices are the most cost-effective combination to reduce sediment loads.
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Remote sensing is the only practicable means to observe snow at large scales. Measurements from passive microwave instruments have been used to derive snow climatology since the late 1970’s, but the algorithms used were limited by the computational power of the era. Simplifications such as the assumption of constant snow properties enabled snow mass to be retrieved from the microwave measurements, but large errors arise from those assumptions, which are still used today. A better approach is to perform retrievals within a data assimilation framework, where a physically-based model of the snow properties can be used to produce the best estimate of the snow cover, in conjunction with multi-sensor observations such as the grain size, surface temperature, and microwave radiation. We have developed an existing snow model, SNOBAL, to incorporate mass and energy transfer of the soil, and to simulate the growth of the snow grains. An evaluation of this model is presented and techniques for the development of new retrieval systems are discussed.
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Satellite data are used to quantify and examine the bias in the outgoing long-wave (LW) radiation over North Africa during May–July simulated by a range of climate models and the Met Office global numerical weather prediction (NWP) model. Simulations from an ensemble-mean of multiple climate models overestimate outgoing clear-sky long-wave radiation (LWc) by more than 20 W m−2 relative to observations from Clouds and the Earth's Radiant Energy System (CERES) for May–July 2000 over parts of the west Sahara, and by 9 W m−2 for the North Africa region (20°W–30°E, 10–40°N). Experiments with the atmosphere-only version of the High-resolution Hadley Centre Global Environment Model (HiGEM), suggest that including mineral dust radiative effects removes this bias. Furthermore, only by reducing surface temperature and emissivity by unrealistic amounts is it possible to explain the magnitude of the bias. Comparing simulations from the Met Office NWP model with satellite observations from Geostationary Earth Radiation Budget (GERB) instruments suggests that the model overestimates the LW by 20–40 W m−2 during North African summer. The bias declines over the period 2003–2008, although this is likely to relate to improvements in the model and inhomogeneity in the satellite time series. The bias in LWc coincides with high aerosol dust loading estimated from the Ozone Monitoring Instrument (OMI), including during the GERBILS field campaign (18–28 June 2007) where model overestimates in LWc greater than 20 W m−2 and OMI-estimated aerosol optical depth (AOD) greater than 0.8 are concurrent around 20°N, 0–20°W. A model-minus-GERB LW bias of around 30 W m−2 coincides with high AOD during the period 18–21 June 2007, although differences in cloud cover also impact the model–GERB differences. Copyright © Royal Meteorological Society and Crown Copyright, 2010
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Tourism is the worlds largest employer, accounting for 10% of jobs worldwide (WTO, 1999). There are over 30,000 protected areas around the world, covering about 10% of the land surface(IUCN, 2002). Protected area management is moving towards a more integrated form of management, which recognises the social and economic needs of the worlds finest areas and seeks to provide long term income streams and support social cohesion through active but sustainable use of resources. Ecotourism - 'responsible travel to natural areas that conserves the environment and improves the well- being of local people' (The Ecotourism Society, 1991) - is often cited as a panacea for incorporating the principles of sustainable development in protected area management. However, few examples exist worldwide to substantiate this claim. In reality, ecotourism struggles to provide social and economic empowerment locally and fails to secure proper protection of the local and global environment. Current analysis of ecotourism provides a useful checklist of interconnected principles for more successful initiatives, but no overall framework of analysis or theory. This paper argues that applying common property theory to the application of ecotourism can help to establish more rigorous, multi-layered analysis that identifies the institutional demands of community based ecotourism (CBE). The paper draws on existing literature on ecotourism and several new case studies from developed and developing countries around the world. It focuses on the governance of CBE initiatives, particularly the interaction between local stakeholders and government and the role that third party non-governmental organisations can play in brokering appropriate institutional arrangements. The paper concludes by offering future research directions."
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Recent extreme precipitation events have caused widespread flooding to the UK. The prediction of the intensity of such events in a warmer climate is important for adaption strategies against future events. This study highlights the importance of using high-resolution models to predict these events. Using a high-resolution GCM it is shown that extreme precipitation events are predicted to become more frequent under the IPCC A1B warming scenario. It is also shown that current forecast models have difficulty in predicting the location, timing and intensity of small scale precipitation in areas with significant orography.
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The response of East Asian Summer Monsoon (EASM) precipitation to long term changes in regional anthropogenic aerosols (sulphate and black carbon) is explored in an atmospheric general circulation model, the atmospheric component of the UK High-Resolution Global Environment Model v1.2 (HiGAM). Separately, sulphur dioxide (SO2) and black carbon (BC) emissions in 1950 and 2000 over East Asia are used to drive model simulations, while emissions are kept constant at year 2000 level outside this region. The response of the EASM is examined by comparing simulations driven by aerosol emissions representative of 1950 and 2000. The aerosol radiative effects are also determined using an off-line radiative transfer model. During June, July and August, the EASM was not significantly changed as either SO2 or BC emissions increased from 1950 to 2000 levels. However, in September, precipitation is significantly decreased by 26.4% for sulphate aerosol and 14.6% for black carbon when emissions are at the 2000 level. Over 80% of the decrease is attributed to changes in convective precipitation. The cooler land surface temperature over China in September (0.8 °C for sulphate and 0.5 °C for black carbon) due to increased aerosols reduces the surface thermal contrast that supports the EASM circulation. However, mechanisms causing the surface temperature decrease in September are different between sulphate and BC experiments. In the sulphate experiment, the sulphate direct and the 1st indirect radiative effects contribute to the surface cooling. In the BC experiment, the BC direct effect is the main driver of the surface cooling, however, a decrease in low cloud cover due to the increased heating by BC absorption partially counteracts the direct effect. This results in a weaker land surface temperature response to BC changes than to sulphate changes. The resulting precipitation response is also weaker, and the responses of the monsoon circulation are different for sulphate and black carbon experiments. This study demonstrates a mechanism that links regional aerosol emission changes to the precipitation changes of the EASM, and it could be applied to help understand the future changes in EASM precipitation in CMIP5 simulations.
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Analysis of 20th century simulations of the High resolution Global Environment Model (HiGEM) and the Third Coupled Model Intercomparison Project (CMIP3) models shows that most have a cold sea-surface temperature (SST) bias in the northern Arabian Sea during boreal winter. The association between Arabian Sea SST and the South Asian monsoon has been widely studied in observations and models, with winter cold biases known to be detrimental to rainfall simulation during the subsequent monsoon in coupled general circulation models (GCMs). However, the causes of these SST biases are not well understood. Indeed this is one of the first papers to address causes of the cold biases. The models show anomalously strong north-easterly winter monsoon winds and cold air temperatures in north-west India, Pakistan and beyond. This leads to the anomalous advection of cold, dry air over the Arabian Sea. The cold land region is also associated with an anomalously strong meridional surface temperature gradient during winter, contributing to the enhanced low-level convergence and excessive precipitation over the western equatorial Indian Ocean seen in many models.
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Seasonal-to-interannual predictions of Arctic sea ice may be important for Arctic communities and industries alike. Previous studies have suggested that Arctic sea ice is potentially predictable but that the skill of predictions of the September extent minimum, initialized in early summer, may be low. The authors demonstrate that a melt season “predictability barrier” and two predictability reemergence mechanisms, suggested by a previous study, are robust features of five global climate models. Analysis of idealized predictions with one of these models [Hadley Centre Global Environment Model, version 1.2 (HadGEM1.2)], initialized in January, May and July, demonstrates that this predictability barrier exists in initialized forecasts as well. As a result, the skill of sea ice extent and volume forecasts are strongly start date dependent and those that are initialized in May lose skill much faster than those initialized in January or July. Thus, in an operational setting, initializing predictions of extent and volume in July has strong advantages for the prediction of the September minimum when compared to predictions initialized in May. Furthermore, a regional analysis of sea ice predictability indicates that extent is predictable for longer in the seasonal ice zones of the North Atlantic and North Pacific than in the regions dominated by perennial ice in the central Arctic and marginal seas. In a number of the Eurasian shelf seas, which are important for Arctic shipping, only the forecasts initialized in July have continuous skill during the first summer. In contrast, predictability of ice volume persists for over 2 yr in the central Arctic but less in other regions.
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The solar wind is an extended ionized gas of very high electrical conductivity, and therefore drags some magnetic flux out of the Sun to fill the heliosphere with a weak interplanetary magnetic field(1,2). Magnetic reconnection-the merging of oppositely directed magnetic fields-between the interplanetary field and the Earth's magnetic field allows energy from the solar wind to enter the near-Earth environment. The Sun's properties, such as its luminosity, are related to its magnetic field, although the connections are still not well understood(3,4). Moreover, changes in the heliospheric magnetic field have been linked with changes in total cloud cover over the Earth, which may influence global climate(5), Here we show that measurements of the near-Earth interplanetary magnetic field reveal that the total magnetic flux leaving the Sun has risen by a factor of 1.4 since 1964: surrogate measurements of the interplanetary magnetic field indicate that the increase since 1901 has been by a factor of 2,3, This increase may be related to chaotic changes in the dynamo that generates the solar magnetic field. We do not yet know quantitatively how such changes will influence the global environment.
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Future land cover will have a significant impact on climate and is strongly influenced by the extent of agricultural land use. Differing assumptions of crop yield increase and carbon pricing mitigation strategies affect projected expansion of agricultural land in future scenarios. In the representative concentration pathway 4.5 (RCP4.5) from phase 5 of the Coupled Model Intercomparison Project (CMIP5), the carbon effects of these land cover changes are included, although the biogeophysical effects are not. The afforestation in RCP4.5 has important biogeophysical impacts on climate, in addition to the land carbon changes, which are directly related to the assumption of crop yield increase and the universal carbon tax. To investigate the biogeophysical climatic impact of combinations of agricultural crop yield increases and carbon pricing mitigation, five scenarios of land-use change based on RCP4.5 are used as inputs to an earth system model [Hadley Centre Global Environment Model, version 2-Earth System (HadGEM2-ES)]. In the scenario with the greatest increase in agricultural land (as a result of no increase in crop yield and no climate mitigation) there is a significant -0.49 K worldwide cooling by 2100 compared to a control scenario with no land-use change. Regional cooling is up to -2.2 K annually in northeastern Asia. Including carbon feedbacks from the land-use change gives a small global cooling of -0.067 K. This work shows that there are significant impacts from biogeophysical land-use changes caused by assumptions of crop yield and carbon mitigation, which mean that land carbon is not the whole story. It also elucidates the potential conflict between cooling from biogeophysical climate effects of land-use change and wider environmental aims.
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Substantial changes in anthropogenic aerosols and precursor gas emissions have occurred over recent decades due to the implementation of air pollution control legislation and economic growth. The response of atmospheric aerosols to these changes and the impact on climate are poorly constrained, particularly in studies using detailed aerosol chemistry–climate models. Here we compare the HadGEM3-UKCA (Hadley Centre Global Environment Model-United Kingdom Chemistry and Aerosols) coupled chemistry–climate model for the period 1960–2009 against extensive ground-based observations of sulfate aerosol mass (1978–2009), total suspended particle matter (SPM, 1978–1998), PM10 (1997–2009), aerosol optical depth (AOD, 2000–2009), aerosol size distributions (2008–2009) and surface solar radiation (SSR, 1960–2009) over Europe. The model underestimates observed sulfate aerosol mass (normalised mean bias factor (NMBF) = −0.4), SPM (NMBF = −0.9), PM10 (NMBF = −0.2), aerosol number concentrations (N30 NMBF = −0.85; N50 NMBF = −0.65; and N100 NMBF = −0.96) and AOD (NMBF = −0.01) but slightly overpredicts SSR (NMBF = 0.02). Trends in aerosol over the observational period are well simulated by the model, with observed (simulated) changes in sulfate of −68 % (−78 %), SPM of −42 % (−20 %), PM10 of −9 % (−8 %) and AOD of −11 % (−14 %). Discrepancies in the magnitude of simulated aerosol mass do not affect the ability of the model to reproduce the observed SSR trends. The positive change in observed European SSR (5 %) during 1990–2009 ("brightening") is better reproduced by the model when aerosol radiative effects (ARE) are included (3 %), compared to simulations where ARE are excluded (0.2 %). The simulated top-of-the-atmosphere aerosol radiative forcing over Europe under all-sky conditions increased by > 3.0 W m−2 during the period 1970–2009 in response to changes in anthropogenic emissions and aerosol concentrations.
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P>1. The use of indicators to identify areas of conservation importance has been challenged on several grounds, but nonetheless retains appeal as no more parsimonious approach exists. Among the many variants, two indicator strategies stand out: the use of indicator species and the use of metrics of landscape structure. While the first has been thoroughly studied, the same cannot be said about the latter. We aimed to contrast the relative efficacy of species-based and landscape-based indicators by: (i) comparing their ability to reflect changes in community integrity at regional and landscape spatial scales, (ii) assessing their sensitivity to changes in data resolution, and (iii) quantifying the degree to which indicators that are generated in one landscape or at one spatial scale can be transferred to additional landscapes or scales. 2. We used data from more than 7000 bird captures in 65 sites from six 10 000-ha landscapes with different proportions of forest cover in the Atlantic Forest of Brazil. Indicator species and landscape-based indicators were tested in terms of how effective they were in reflecting changes in community integrity, defined as deviations in bird community composition from control areas. 3. At the regional scale, indicator species provided more robust depictions of community integrity than landscape-based indicators. At the landscape scale, however, landscape-based indicators performed more effectively, more consistently and were also more transferable among landscapes. The effectiveness of high resolution landscape-based indicators was reduced by just 12% when these were used to explain patterns of community integrity in independent data sets. By contrast, the effectiveness of species-based indicators was reduced by 33%. 4. Synthesis and applications. The use of indicator species proved to be effective; however their results were variable and sensitive to changes in scale and resolution, and their application requires extensive and time-consuming field work. Landscape-based indicators were not only effective but were also much less context-dependent. The use of landscape-based indicators may allow the rapid identification of priority areas for conservation and restoration, and indicate which restoration strategies should be pursued, using remotely sensed imagery. We suggest that landscape-based indicators might often be a better, simpler, and cheaper strategy for informing decisions in conservation.
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Muitos historiadores afirmam que estamos iniciando uma nova era, a era do conhecimento, da informação, a era digital. Surgem duas grandes armas estratégicas nesse novo ambiente global, para que as empresas sejam competitivas no século vinte e um: a criatividade e a integração. E muitas empresas estão adotando uma nova estrutura organizacional, a estrutura do tipo network, como solução para a gerência da criatividade e da integração. Essa estrutura não se preocupa com novas maneiras de manipular subordinados em vantagem própria. Ao contrário, ela nos desafia a repensar o básico: nossos valores, atitudes e considerações a respeito de liderança, trabalho e tempo. As estruturas hierárquicas convencionais não proporcionam a agilidade de resposta requerida pelo mercado atualmente, devido à burocracia por trás de todas as atividades. As pessoas especializam-se em pequenas atividades, perdendo o sentido do trabalho e a motivação intrínseca. E uma vez que as pessoas são crescentemente reconhecidas como o capital mais importante de qualquer empreendimento, a desmotivação se toma desastrosa para o futuro de qualquer negócio. A reciprocidade empresa-indivíduo é essencial. Esta dissertação pretende analisar o fator humano nos trabalhos realizados dentro da estrutura de network, traçando-se um paralelo entre as propostas dessa estrutura e as necessidades humanas, demonstrando a relação existente entre a estrutura organizacional da criatividade e da integração e a satisfação no trabalho. Iniciamente, apresenta-se uma revisão bibliográfica, sob três diferentes enfoques. Primeiro, explica-se como as transformações mundiais estão afetando a estratégia das empresas. Depois, mostra-se o impacto da estratégia do século vinte e um dentro da organização. Por fim, focaliza-se o lado psicológico do ser humano, suas necessidades, tais quais a autonomia, a competência e o relacionamento interpessoal, os fatores de satisfação intrínsecos e extrínsecos. Assim, pode-se avaliar o impacto de uma nova estrutura organizacional na motivação dos funcionários. A seguir, apresenta-se o projeto de uma pesquisa-piloto dos fatores de satisfação mais relevantes para as pessoas, confirmando-se a importância dos fatores de satisfação intrínsecos. Mostra-se também que os índices de satisfação são diretamente afetados pelo ambiente empresarial onde atuam, de acordo com seu grau de autonomia. Então, são mostradas as conclusões do trabalho e recomendações práticas para mudanças na estrutura organizacional dentro de uma empresa, seus custos e como elas devem ser administradas no longo prazo.