947 resultados para spodic horizon
Resumo:
Methane is the second most important anthropogenic greenhouse gas in the atmosphere next to carbon dioxide. Its global warming potential (GWP) for a time horizon of 100 years is 25, which makes it an attractive target for climate mitigation policies. Although the methane GWP traditionally includes the methane indirect effects on the concentrations of ozone and stratospheric water vapour, it does not take into account the production of carbon dioxide from methane oxidation. We argue here that this CO2-induced effect should be included for fossil sources of methane, which results in slightly larger GWP values for all time horizons. If the global temperature change potential is used as an alternative climate metric, then the impact of the CO2-induced effect is proportionally much larger. We also discuss what the correction term should be for methane from anthropogenic biogenic sources.
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Dissolved organic carbon (DOC) concentrations have been rising in streams and lakes draining catchments with organic soils across Northern Europe. These increases have shown a correlation with decreased sulphate and chloride concentrations. One hypothesis to explain this phenomenon is that these relationships are due an increased in DOC release from soils to freshwaters, caused by a decline in pollutant sulphur and sea-salt deposition. We carried out controlled deposition experiments in the laboratory on intact peat and organomineral O-horizon cores to test this hypothesis. Preliminary data showed a clear correlation between the change in soil water pH and change in DOC concentrations, however uncertainty still remains about whether this is due to changes in biological activity or chemical solubility.
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This article discusses approaches to the interpretation and analysis an event that is poised between reality and performance. It focuses upon a real event witnessed by the author while driving out of Los Angeles, USA. A body hanging on a rope from a bridge some 25/30 feet above the freeway held up the traffic. The status of the body was unclear. Was it the corpse of a dead human being or a stuffed dummy, a simulation of a death? Was it is tragic accident or suicide or was it a stunt, a protest or a performance? Whether a real body or not, it was an event: it drew an audience, it took place in a defined public space bound by time and it disrupted everyday normality and the familiar. The article debates how approaches to performance can engage with a shocking event, such as the Hanging Man, and the frameworks of interpretation that can be brought to bear on it. The analysis takes account of the function of memory in reconstructing the event, and the paradigms of cultural knowledge that offered themselves as parallels, comparators or distinctions against which the experience could be measured, such as the incidents of self-immolation related to demonstrations against the Vietnam War, the protest by the Irish Hunger Strikers and the visual impact of Anthony Gormley’s 2007 work, 'Event Horizon'. Theoretical frameworks deriving from analytical approaches to performance, media representation and ethical dilemmas are evaluated as means to assimilate an indeterminate and challenging event, and the notion of what an ‘event’ may be is itself addressed.
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Long-term monitoring data from eastern North America and Europe indicate a link between increased dissolved organic carbon (DOC) concentrations in surface waters over the last two decades and decreased atmospheric pollutant and marine sulphur (S) deposition. The hypothesis is that decreased acidity and ionic strength associated with declining S deposition has increased the solubility of DOC. However, the sign and magnitude of DOC trends have varied between sites, and in some cases at sites where S deposition has declined, no significant increase in DOC has been observed, creating uncertainty about the causal mechanisms driving the observed trends. In this paper, we demonstrate chemical regulation of DOC release from organic soils in batch experiments caused by changes in acidity and conductivity (measured as a proxy for ionic strength) associated with controlled SO42− additions. DOC release from the top 10 cm of the O-horizon of organo-mineral soils and peats decreased by 21–60% in response to additions of 0–437 µeq SO42− l−1 sulphuric acid (H2SO4) and neutral sea-salt solutions (containing Na+, Mg2+, Cl−, SO42−) over a 20-hour extraction period. A significant decrease in the proportion of the acid-sensitive coloured aromatic humic acids (measured by specific ultra-violet absorbance (SUVA) at 254 nm) was also found with increasing acidity (P < 0.05) in most, but not all, soils, confirming that DOC quality, as well as quantity, changed with SO42− additions. DOC release appeared to be more sensitive to increased acidity than to increased conductivity. By comparing the change in DOC release with bulk soil properties, we found that DOC release from the O-horizon of organo-mineral soils and semi-confined peats, which contained greater exchangeable aluminium (Al) and had lower base saturation (BS), were more sensitive to SO42− additions than DOC release from blanket peats with low concentrations of exchangeable Al and greater BS. Therefore, variation in soil type and acid/base status between sites may partly explain the difference in the magnitude of DOC changes seen at different sites where declines in S deposition have been similar.
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In industrial practice, constrained steady state optimisation and predictive control are separate, albeit closely related functions within the control hierarchy. This paper presents a method which integrates predictive control with on-line optimisation with economic objectives. A receding horizon optimal control problem is formulated using linear state space models. This optimal control problem is very similar to the one presented in many predictive control formulations, but the main difference is that it includes in its formulation a general steady state objective depending on the magnitudes of manipulated and measured output variables. This steady state objective may include the standard quadratic regulatory objective, together with economic objectives which are often linear. Assuming that the system settles to a steady state operating point under receding horizon control, conditions are given for the satisfaction of the necessary optimality conditions of the steady-state optimisation problem. The method is based on adaptive linear state space models, which are obtained by using on-line identification techniques. The use of model adaptation is justified from a theoretical standpoint and its beneficial effects are shown in simulations. The method is tested with simulations of an industrial distillation column and a system of chemical reactors.
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DISOPE is a technique for solving optimal control problems where there are differences in structure and parameter values between reality and the model employed in the computations. The model reality differences can also allow for deliberate simplification of model characteristics and performance indices in order to facilitate the solution of the optimal control problem. The technique was developed originally in continuous time and later extended to discrete time. The main property of the procedure is that by iterating on appropriately modified model based problems the correct optimal solution is achieved in spite of the model-reality differences. Algorithms have been developed in both continuous and discrete time for a general nonlinear optimal control problem with terminal weighting, bounded controls and terminal constraints. The aim of this paper is to show how the DISOPE technique can aid receding horizon optimal control computation in nonlinear model predictive control.
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A novel optimising controller is designed that leads a slow process from a sub-optimal operational condition to the steady-state optimum in a continuous way based on dynamic information. Using standard results from optimisation theory and discrete optimal control, the solution of a steady-state optimisation problem is achieved by solving a receding-horizon optimal control problem which uses derivative and state information from the plant via a shadow model and a state-space identifier. The paper analyzes the steady-state optimality of the procedure, develops algorithms with and without control rate constraints and applies the procedure to a high fidelity simulation study of a distillation column optimisation.
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The performance of various statistical models and commonly used financial indicators for forecasting securitised real estate returns are examined for five European countries: the UK, Belgium, the Netherlands, France and Italy. Within a VAR framework, it is demonstrated that the gilt-equity yield ratio is in most cases a better predictor of securitized returns than the term structure or the dividend yield. In particular, investors should consider in their real estate return models the predictability of the gilt-equity yield ratio in Belgium, the Netherlands and France, and the term structure of interest rates in France. Predictions obtained from the VAR and univariate time-series models are compared with the predictions of an artificial neural network model. It is found that, whilst no single model is universally superior across all series, accuracy measures and horizons considered, the neural network model is generally able to offer the most accurate predictions for 1-month horizons. For quarterly and half-yearly forecasts, the random walk with a drift is the most successful for the UK, Belgian and Dutch returns and the neural network for French and Italian returns. Although this study underscores market context and forecast horizon as parameters relevant to the choice of the forecast model, it strongly indicates that analysts should exploit the potential of neural networks and assess more fully their forecast performance against more traditional models.
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By employing Moody’s corporate default and rating transition data spanning the last 90 years we explore how much capital banks should hold against their corporate loan portfolios to withstand historical stress scenarios. Specifically, we will focus on the worst case scenario over the observation period, the Great Depression. We find that migration risk and the length of the investment horizon are critical factors when determining bank capital needs in a crisis. We show that capital may need to rise more than three times when the horizon is increased from 1 year, as required by current and future regulation, to 3 years. Increases are still important but of a lower magnitude when migration risk is introduced in the analysis. Further, we find that the new bank capital requirements under the so-called Basel 3 agreement would enable banks to absorb Great Depression-style losses. But, such losses would dent regulatory capital considerably and far beyond the capital buffers that have been proposed to ensure that banks survive crisis periods without government support.
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Given a nonlinear model, a probabilistic forecast may be obtained by Monte Carlo simulations. At a given forecast horizon, Monte Carlo simulations yield sets of discrete forecasts, which can be converted to density forecasts. The resulting density forecasts will inevitably be downgraded by model mis-specification. In order to enhance the quality of the density forecasts, one can mix them with the unconditional density. This paper examines the value of combining conditional density forecasts with the unconditional density. The findings have positive implications for issuing early warnings in different disciplines including economics and meteorology, but UK inflation forecasts are considered as an example.
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Food security is one of this century’s key global challenges. By 2050 the world will require increased crop production in order to feed its predicted 9 billion people. This must be done in the face of changing consumption patterns, the impacts of climate change and the growing scarcity of water and land. Crop production methods will also have to sustain the environment, preserve natural resources and support livelihoods of farmers and rural populations around the world. There is a pressing need for the ‘sustainable intensifi cation’ of global agriculture in which yields are increased without adverse environmental impact and without the cultivation of more land. Addressing the need to secure a food supply for the whole world requires an urgent international effort with a clear sense of long-term challenges and possibilities. Biological science, especially publicly funded science, must play a vital role in the sustainable intensifi cation of food crop production. The UK has a responsibility and the capacity to take a leading role in providing a range of scientifi c solutions to mitigate potential food shortages. This will require signifi cant funding of cross-disciplinary science for food security. The constraints on food crop production are well understood, but differ widely across regions. The availability of water and good soils are major limiting factors. Signifi cant losses in crop yields occur due to pests, diseases and weed competition. The effects of climate change will further exacerbate the stresses on crop plants, potentially leading to dramatic yield reductions. Maintaining and enhancing the diversity of crop genetic resources is vital to facilitate crop breeding and thereby enhance the resilience of food crop production. Addressing these constraints requires technologies and approaches that are underpinned by good science. Some of these technologies build on existing knowledge, while others are completely radical approaches, drawing on genomics and high-throughput analysis. Novel research methods have the potential to contribute to food crop production through both genetic improvement of crops and new crop and soil management practices. Genetic improvements to crops can occur through breeding or genetic modifi cation to introduce a range of desirable traits. The application of genetic methods has the potential to refi ne existing crops and provide incremental improvements. These methods also have the potential to introduce radical and highly signifi cant improvements to crops by increasing photosynthetic effi ciency, reducing the need for nitrogen or other fertilisers and unlocking some of the unrealised potential of crop genomes. The science of crop management and agricultural practice also needs to be given particular emphasis as part of a food security grand challenge. These approaches can address key constraints in existing crop varieties and can be applied widely. Current approaches to maximising production within agricultural systems are unsustainable; new methodologies that utilise all elements of the agricultural system are needed, including better soil management and enhancement and exploitation of populations of benefi cial soil microbes. Agronomy, soil science and agroecology—the relevant sciences—have been neglected in recent years. Past debates about the use of new technologies for agriculture have tended to adopt an either/or approach, emphasising the merits of particular agricultural systems or technological approaches and the downsides of others. This has been seen most obviously with respect to genetically modifi ed (GM) crops, the use of pesticides and the arguments for and against organic modes of production. These debates have failed to acknowledge that there is no technological panacea for the global challenge of sustainable and secure global food production. There will always be trade-offs and local complexities. This report considers both new crop varieties and appropriate agroecological crop and soil management practices and adopts an inclusive approach. No techniques or technologies should be ruled out. Global agriculture demands a diversity of approaches, specific to crops, localities, cultures and other circumstances. Such diversity demands that the breadth of relevant scientific enquiry is equally diverse, and that science needs to be combined with social, economic and political perspectives. In addition to supporting high-quality science, the UK needs to maintain and build its capacity to innovate, in collaboration with international and national research centres. UK scientists and agronomists have in the past played a leading role in disciplines relevant to agriculture, but training in agricultural sciences and related topics has recently suffered from a lack of policy attention and support. Agricultural extension services, connecting farmers with new innovations, have been similarly neglected in the UK and elsewhere. There is a major need to review the support for and provision of extension services, particularly in developing countries. The governance of innovation for agriculture needs to maximise opportunities for increasing production, while at the same time protecting societies, economies and the environment from negative side effects. Regulatory systems need to improve their assessment of benefits. Horizon scanning will ensure proactive consideration of technological options by governments. Assessment of benefi ts, risks and uncertainties should be seen broadly, and should include the wider impacts of new technologies and practices on economies and societies. Public and stakeholder dialogue—with NGOs, scientists and farmers in particular—needs to be a part of all governance frameworks.
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This paper describes the integration of constrained predictive control and computed-torque control, and its application on a six degree-of-freedom PUMA 560 manipulator arm. The real-time implementation was based on SIMULINK, with the predictive controller and the computed-torque control law implemented in the C programming language. The constrained predictive controller solved a quadratic programming problem at every sampling interval, which was as short as 10 ms, using a prediction horizon of 150 steps and an 18th order state space model.
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We reconsider the theory of the linear response of non-equilibrium steady states to perturbations. We �rst show that by using a general functional decomposition for space-time dependent forcings, we can de�ne elementary susceptibilities that allow to construct the response of the system to general perturbations. Starting from the de�nition of SRB measure, we then study the consequence of taking di�erent sampling schemes for analysing the response of the system. We show that only a speci�c choice of the time horizon for evaluating the response of the system to a general time-dependent perturbation allows to obtain the formula �rst presented by Ruelle. We also discuss the special case of periodic perturbations, showing that when they are taken into consideration the sampling can be �ne-tuned to make the de�nition of the correct time horizon immaterial. Finally, we discuss the implications of our results in terms of strategies for analyzing the outputs of numerical experiments by providing a critical review of a formula proposed by Reick.
Resumo:
The use of discounted cash flow (DCF) methods in investment valuation and appraisal is argued by many academics as being rational and more rigorous than the traditional capitalisation model. However those advocates of DCF should be cautious in their claims for rationality. The various DCF models all rely upon an all-encompassing equated yield (IRR) within the calculation. This paper will argue that this is a simplification of the risk perception which the investor places on the income profile from property. In determining the long term capital value of a property an 'average' DCF method will produce the 'correct' price, however, the individual short term values of each cash-flow may differ significantly. In the UK property market today, where we are facing a period in which prices are not expected to rise generally at the same rate or with such persistence as hitherto, investors and tenants are increasingly concerned with the down side implications of rental growth and investors may indeed be interested in trading property over a shorter investment horizon than they had originally planned. The purpose of this paper is therefore to bring to the analysis a rigorous framework which can be used to analyse the constituent cash flows within the freehold valuation. We show that the arbitrage analysis lends itself to segregating the capital value of the cash flows in a way which is more appropriate for financial investors