50 resultados para Strategic environment planning
Resumo:
Mineralogical, hydrochemical and S isotope data were used to constrain hydrogeochemical processes that produce acid mine drainage from sulfidic waste at the historic Mount Morgan Au–Cu mine, and the factors controlling the concentration of SO4 and environmentally hazardous metals in the nearby Dee River in Queensland, Australia. Some highly contaminated acid waters, with metal contents up to hundreds of orders of magnitude greater than the Australia–New Zealand environmental standards, by-pass the water management system at the site and drain into the adjacent Dee River. Mine drainage precipitates at Mt. Morgan were classified into 4 major groups and were identified as hydrous sulfates and hydroxides of Fe and Al with various contents of other metals. These minerals contain adsorbed or mineralogically bound metals that are released into the water system after rainfall events. Sulfate in open pit water and collection sumps generally has a narrow range of S isotope compositions (δ34S = 1.8–3.7‰) that is comparable to the orebody sulfides and makes S isotopes useful for tracing SO4 back to its source. The higher δ34S values for No. 2 Mill Diesel sump may be attributed to a difference in the source. Dissolved SO4 in the river above the mine influence and 20 km downstream show distinctive heavier isotope compositions (δ34S = 5.4–6.8‰). The Dee River downstream of the mine is enriched in 34S (δ34S = 2.8–5.4‰) compared with mine drainage possibly as a result of bacterial SO4 reduction in the weir pools, and in the water bodies within the river channel. The SO4 and metals attenuate downstream by a combination of dilution with the receiving waters, SO4 reduction, and the precipitation of Fe and Al sulfates and hydroxides. It is suggested here that in subtropical Queensland, with distinct wet and dry seasons, temporary reducing environments in the river play an important role in S isotope systematics
Resumo:
Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.
Resumo:
The quantitative description of the quantum entanglement between a qubit and its environment is considered. Specifically, for the ground state of the spin-boson model, the entropy of entanglement of the spin is calculated as a function of α, the strength of the ohmic coupling to the environment, and ɛ, the level asymmetry. This is done by a numerical renormalization group treatment of the related anisotropic Kondo model. For ɛ=0, the entanglement increases monotonically with α, until it becomes maximal for α→1-. For fixed ɛ>0, the entanglement is a maximum as a function of α for a value, α=αM
Resumo:
Argumentation is modelled as a game where the payoffs are measured in terms of the probability that the claimed conclusion is, or is not, defeasibly provable, given a history of arguments that have actually been exchanged, and given the probability of the factual premises. The probability of a conclusion is calculated using a standard variant of Defeasible Logic, in combination with standard probability calculus. It is a new element of the present approach that the exchange of arguments is analysed with game theoretical tools, yielding a prescriptive and to some extent even predictive account of the actual course of play. A brief comparison with existing argument-based dialogue approaches confirms that such a prescriptive account of the actual argumentation has been almost lacking in the approaches proposed so far.