The sustainable global energy economy: Hydrogen or silicon?

A sustainable global silicon energy economy is proposed as a potential alternative to the hydrogen economy. This first visualisation of a silicon energy economy is based on largescale and carbon-neutral metallic silicon production from major smelters in North Africa and elsewhere, supplied by desert silica sand and electricity from extensive solar generating systems. The resulting “fuel silicon” is shipped around the world to emission-free silicon power stations for either immediate electricity generation or stockpiling. The high energy density of silicon and its stable storage make it an ideal material for maintaining national economic functioning through security of base load power supply from a renewable source. This contrasts with the present situation of fossil fuel usage with its associated global warming and geopolitical supply uncertainties. Critical technological requirements for the silicon economy are carbon-neutral silicon production and the development of efficient silicon-fired power stations capable of high-temperature rapid oxidation of fuel silicon. A call is made for the development of research effort into these specific engineering issues, and also with respect to large-scale economical solar power generation

Note on the pumped storage potential of the Onslow-Manorburn depression, New Zealand

The Onslow-Manorburn depression in the South Island of New Zealand has possibility for development as the upper reservoir of the world's largest pumped storage scheme, as measured by an energy storage capacity of 10,200 GWh of realisable potential energy. This would more than triple the total national hydro-power energy storage capacity. It is envisaged that the scheme could either operate on a seasonal cycle or act as a passive energy reserve to buffer existing hydro-power capacity against the effect of dry years

A goodness of fit measure related to r² for model performance assessment

Checking the predictive worth of an environmental model inevitably includes a goodness of fit metric to quantify the degree of matching to recorded data, thereby giving a measure of model performance. Considerable analysis and discussion have taken place over fit indices in hydrology, but a neglected aspect is the degree of communicability to other disciplines. It is suggested that a fit index is best communicated to colleagues via reference to models giving unbiased predictions, because unbiased environmental models are a desirable goal across disciplines. That is, broad recognition of a fit index is aided if it simplifies in the unbiased case to a familiar and logical expression. This does not hold for the Nash–Sutcliffe Efficiency E which reduces to the somewhat awkward unbiased expression E = 2 – 1/r², where r² is the coefficient of determination. A new goodness of fit index V is proposed for model validation as V =  r²/(2-E), which simplifies to the easily communicated V = r4 in the unbiased case. The index is defined over the range 0 ≤ V ≤ 1, and it happens that V < E for larger values of E. Some synthetic and recorded data sets are used to illustrate characteristics of V in comparison to

Determination of Chemical Composition of Wood Pulp Hydrolyzates by Paper Chromatography

The available literature on paper chromatography was surveyed. Special attention was given to those techniques dealing with the analysis of wood pulp hydrolyzates. Five hardwood pulp hydrolyzates were analyzed by paper chromatographic means. All hardwood pulp hydrolyzates analyzed tended to fall in a relatively narrow range of chemical composition. Glucose and xylose were found to be the main constituents with traces of mannose and galactose present in some pulp hydrolyzates

Temporal moments of a tracer pulse in a perfectly parallel flow system

Perfectly parallel groundwater transport models partition water flow into isolated one-dimensional stream tubes which maintain total spatial correlation of all properties in the direction of flow. The case is considered of the temporal moments of a conservative tracer pulse released simultaneously into N stream tubes with arbitrarily different advective–dispersive transport and steady flow speeds in each of the stream tubes. No assumptions are made about the form of the individual stream tube arrival-time distributions or about the nature of the between-stream tube variation of hydraulic conductivity and flow speeds. The tracer arrival-time distribution g(t,x) is an N-component finite-mixture distribution, with the mean and variance of each component distribution increasing in proportion to tracer travel distance x. By utilising moment relations of finite mixture distributions, it is shown (to r=4) that the rth central moment of g(t,x) is an rth order polynomial function of x or φ, where φ is mean arrival time. In particular, the variance of g(t,x) is a positive quadratic function of x or φ. This generalises the well-known quadratic variance increase for purely advective flow in parallel flow systems and allows a simple means of regression estimation of the large-distance coefficient of variation of g(t,x). The polynomial central moment relation extends to the purely advective transport case which arises as a large-distance limit of advective–dispersive transport in parallel flow models. The associated limit g(t,x) distributions are of N-modal form and maintain constant shapes independent of travel distance. The finite-mixture framework for moment evaluation is also a potentially useful device for forecasting g(t,x) distributions, which may include multimodal forms. A synthetic example illustrates g(t,x) forecasting using a mixture of normal distributions

Note on y-truncation: a simple approach to generating bounded distributions for environmental applications

It may sometimes be desirable to introduce bounds into probability distributions to formalise the presence of upper or lower physical limits to data to which the distribution has been applied. For example, an upper bound in raindrop sizes might be represented by introducing an upper bound to an exponential drop-size distribution. However, the standard method of truncating unbounded probability distributions yields distributions with non-zero probability density at the resulting bounds. In reality it is likely that physical bounding processes in nature increase in intensity as the bound is approached, causing a progressive decline in observation relative frequency to zero at the bound. Truncation below a y-axis point is proposed as a simple alternative means of creating more natural truncated probability distributions for application to data of this type. The resulting “y-truncated” distributions have similarities with the traditional truncated distributions but probability densities have the desirable feature of always declining to zero at the bounds. In addition, the y-truncation approach can also serve in its own right as a mean