Chemical Engineering

Sunday, July 22, 2007

Biofuels - Small scale use of biofuels

Biofuel is any fuel that derives from biomass - recently living organisms or their metabolic byproducts, such as manure from cows. It is a renewable energy, unlike natural resources such as petroleum, coal and nuclear fuels.

Typically biofuel is burned to release its stored chemical energy. Research into more efficient methods of converting biofuels and other fuels into electricity utilizing fuel cells is an area of very active work.

The carbon in biofuels was recently extracted from atmospheric carbon dioxide by growing plants, so burning it does not contribute carbon dioxide to the Earth's atmosphere.

Bioenergy covers about 15% of the world's energy consumption. Sweden and Finland supply 17% and 19% respectively, of their energy needs with bioenergy. Biomass can be used both for centralized production of electricity and district heat, and for local heating.

Oxidisation of biomass does not release more CO2 than that which was absorbed by production of that same biomass. Both agricultural products specifically grown for this use and waste from industry, agriculture, forestry, and households -including straw, lumber, manure, and food leftovers-can be used for the production of bioenergy.

A widespread use of biofuels is in Home cooking and heating. Typical fuels for this are wood, charcoal or dried dung. The biofuel may be burned on an open fireplace or in a special stove. The efficiency of this process may vary widely from 10% for a well made fire up (even less if the fire is not made carefully) to 40% for a custom designed charcoal stove1. Inefficient use of fuel may be a minor cause of deforestation (though this is negligible compared to deliberate destruction to clear land for agricultural use) but more importantly it means that more work has to be put into gathering fuel, thus the quality of cooking stoves has a direct influence on the viability of biofuels.

Unfortunately, much cooking with biofuels is done indoors, without efficient ventilation and using those fuels such as dung which cause most airborne polution. This can be a serious health hazard; 1.5 million deaths were attributed to this cause by the World Health Organisation in 20002. There are various responses to this, such as improved stoves, including those with inbuilt flues and switching to alternative fuel sources. Most of these responses have difficulties, for example flues are expensive and easily damage; alternative fuels tend to be more expensive which is difficult to implement since the people who rely on biofuels often do so precisely because they cannot afford alternatives.3 Organisations such as Intermediate Technology Development Group work to make improved facilities for biofuel use and better alternatives accessible to those who cannot currently get them. This work be done through designing improved ventilation, a switch to different usage of biomass such as through the creation of biogas from solid biomatter or a switch to other alternatives such as micro-hydro power.

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Chemical Caliborations

Bayesian Archaeology

Since archaeological problems are typified by being relatively data poor and prior information rich, there are strong philosophical arguments for routine use of the Bayesian paradigm in archaeological research. Indeed, a number of researchers argued for adoption of such methods long before Bayesian statistics were being routinely used in other disciplines. As a result, archaeology was one of the very first applied areas to benefit from the recent developments in Markov chain Monte Carlo (MCMC) simulation techniques. Now that we can implement tailor-made models for a wide range of problem types, Bayesian methods are really coming into their own.

Bayesian methods are an important aid to archaeological data interpretation because we very often have relatively little data but considerable, informative prior information which is complex and hard to interpret heuristically. The Bayesian framework provides us with a formal set of tools for incorporating subjective a priori information into the interpretive process and, as a result, it has proved useful to specialists in a number of sub-disciplines of archaeology including the following.

  • Estimating the radiocarbon calibration curve. Due to sun-spot activity and to a range of other less well understood events, the amount of radioactive carbon in our atmosphere has not remained constant over time. Thus, in order to convert radiocarbon determinations obtained from a radiocarbon laboratory into true calender dates, we need a calibration curve derived from radiocarbon determinations for known age samples. Such calibration data exist and have been collated and updated for more than 25 years. All members of Sheffield's Bayesian archaeology research group have recently worked on this problem and Caitlin Buck was the statistician on the IntCal04 team that put together the internationally-agreed radiocarbon calibration curve (for more on this see below).
  • Interpreting radiocarbon data from archaeological and environmental research projects. Once the radiocarbon calibration curve has been estimated, there is still a great deal of statistical work to do in utilising the curve to help date groups of related archaeological and/or environmental samples. Members of our research group have undertaken collaborative work in this area for many years (see below for publications). We continue to develop and improve the statistical tools available by devising tailored models in response to particular problems encountered by the user communities. Currently, we have two PhD students working on such problems. Angela Howard has English Heritage and EPSRC funding for a project with the title Robust and Flexible Tools for Archaeological Chronology Construction (supervised by Caitlin Buck and Paul Blackwell). Lynsey McColl is funded by NERC/EPSRC under their Environmental Mathematics and Statistics initiative and is jointly supervised by Caitlin Buck, Paul Pettitt (University of Sheffield Archaeology Department) and Andrew Millard (University of Durham Archaeology Department). Her project has the title Statistical Tools for Investigating Issues of Contemporaneity in Palaeo-environmental and Archaeological Records.
  • Field survey. Field survey is now a vital part of archaeological research. It includes use of techniques like geophysical surveying (ground resistivity, magnetometry, ground penetrating radar and the like), collection and analysis of soil samples or cores (for soil phosphate, pollen, chemical composition analysis and the like) and field walking (in which teams of archaeologists walk across landscapes recording surface finds such as pottery, architectural stone and flint tools). Bayesian methods have been shown to be of particular interest in the interpretation of particularly noisy field survey results, in particular soil phosphate data. Since a great deal of organic material (both animal and vegetable) contains phosphate, human activity (particularly sedentary agricultural activity) often gives rise to higher levels of phosphate in the soil than those which arise naturally. Unfortunately, however, most of the rapid techniques available for soil phosphate surveying give rise to data which are noisy, contain missing values and are often on quite a coarse scale. Typically, all archaeologists are wishing to do with such data is to assign cells in the survey grid as either associated with previous human activity or not. Even this level of interpretation, however, proves difficult using heuristic methods. Bayesian change-point methods, which allow for the inclusion of prior information about the likely levels of phosphate (both `on-site' and `off-site') in any given landscape, have been shown to have considerable interpretive power.
  • Structural analysis. Much of prehistoric architecture in Europe is simple and has well understood structural properties (such as dry stone walling or mud bricks). In Greece and several other parts of Europe, however, there exists a class of structures with structural properties that are far less will understood. These are known collectively as corbelled domes, but the specific examples in Sardinia are called nuraghi and in Greece they tend to be called tholoi. These structures are, in fact, not strictly `domes' since the more modern technique of vaulting is not used to enclose the space. Corbelling must be undertaken with great care if it is to be stable as it involves the enclosing of a roof space by over-sailing courses of masonry until the space is spanned. For some time, architectural historians and archaeologists have been fascinated by these structures and have sought to understand how prehistoric peoples would have constructed them and made them so stable. There are a number of ways in which Bayesian statisticians could help in the investigation of such issues and one that has proved quite successful is to use change point analysis to identify possible locations for changes in the form or profile of a particular structure. It is now clear that not all prehistoric corbelled domes were constructed in the same way. More work is still needed before we will understand whether corbelled domes in different places have similar or different structures and the nature of any spatial structure involved.
  • Chemical compositional analysis. Chemical composition analysis is now used quite widely by archaeologists to help them understand about things like pottery manufacture, soil composition and alteration, and to aid in the identification of forgeries. Sometimes such data can be interpreted quite easily without the need for statistical methods - especially in the case of very poor forgeries for example. In situations where we wish to group objects or soil types together on the basis of chemical composition, however, we can be dealing with large arrays of data and complex questions relating to the similarities between samples or groups of samples. Since the data are often noisy, are prone to missing values, and we sometimes have quite informative prior information about the nature of the groupings we would expect, Bayesian cluster analysis has been applied to data of this type with some success.
  • Building relative chronologies. One of the best established uses of formal mathematical methods in archaeology is as a tool to aid in construction of relative chronologies on the basis of artefact types found during excavation (in particular of human burials). The techniques used to do this have become known as seriation and rely on the assumption that artefact types come into use, stay in fashion for a while and finally go out of fashion without ever appearing again in the archaeological record. Early formal tools for helping with identifying likely chronological orderings on the basis of this assumption were either deterministic or used non-tailored statistical tools. More recently, however, a relatively simple Bayesian modelling of the problem has been implemented using MCMC, allowing any prior information about orderings and structure to be included in the seriation process.

These are just a few of the archaeology projects that members of the Bayesian cluster have been involved with over the years. For more about on-going research in this area see below and for more on other archaeological and environmental work in the Department see the pages for our Statistical Modelling and Applied Statistics cluster.

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Sunday, May 27, 2007

Journals on Chemical Engineering

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