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The development of numerical tools for characterizing and quantifying biomass cookstove impact




L'Orange, Christian, author
Willson, Bryan, advisor
DeFoort, Morgan, advisor
Marchese, Anthony, committee member
Volckens, John, committee member

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Biomass cookstove use can be damaging to both human health and the global climate. In an effort to minimize these impacts, numerous programs are working to disseminate improved biomass cookstoves. However, few programs have achieved extensive success towards improving either climate or health. One reason programs have only resulted in limited improvements has been the sector's inability to quantify cookstove performance. A numeric tool has been developed for characterizing biomass cookstove performance. This dissertation documents the development of that tool. The document is comprised of three components: (i) the critical analysis of the uncertainty associated with current methods for cookstove field-testing, (ii) the development and validation of a probabilistic impact model for biomass cookstoves, and (iii) the application of these numerical tools to quantify cookstove impact. Biomass cookstoves have traditionally been evaluated empirically. Cookstoves are tested in both the field and the laboratory, with each approach having advantages and limitations. Neither laboratory nor field testing are sufficient, however, for quantifying cookstove impact. Field-testing provides invaluable data on cookstove use but is limited by the large variability typically seen in the results. Drawing conclusions from field tests is challenging due to this variability. Many groups attempt to address testing variability by increasing the number of test replicates conducted. A numeric model was developed to determine the number of test replicates required to quantify cookstove performance in field settings. Because of the large number of test replicates required to have statistical confidence in field-based data, an improved method of quantifying biomass cookstove performance is needed. Therefore, to address this need a probabilistic Monte Carlo prediction model was developed to quantify cookstove performance. The intention of the model is to serve as a tool for predicting the impact of various cookstove designs. The model integrates various facets of existing cookstove performance knowledge in more a cohesive fashion. Model simulations were compared to experimental studies to validate this approach. Numeric tools are only valuable if they result in useful information; for example, information that allows informed decisions to be made. The potential of numeric models to provide valuable information for cookstove programs has been demonstrated by simulating the performance of multiple cookstove designs. Three improved cookstoves designs have been compared to a traditional three-stone fire. Each design was evaluated for multiple scenarios, use patterns, and locations. The impact of each design (in regard to climate and health) was then quantified and monetized. This exercise yielded two important findings. First, consideration of location and context is critical when comparing the performance of cookstoves. Second, numeric models can be used as highly informative tools to support decision-making in the cookstove sector. Empirical testing is necessary for most technical programs; this is especially true for cookstoves projects. There are aspects of cookstove designs that can only be evaluated experimentally. Examples include whether an individual likes the cookstove, or if the design is appropriate for the specific cooking requirements of a particular community. Physical testing is needed to answer some basic questions such as: Do users find the cookstove intuitive to use? Do they like the color? However, empirical testing is not well-suited to answer every question related to cookstove performance. For example, comparing the climate impact of different cookstove designs is difficult in the field. The work presented demonstrates the potential of numerical models to provide invaluable information to the cookstove sector. The development and validation of these models has been documented. These models can help quantify the impact of current designs and help guide the development of future cookstove programs.


2013 Summer.
Includes bibliographical references.

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Monte Carlo


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