A Buoyancy-Decoupling Approach to Cookstove Modeling and Quantification Methods for Metal Oxide Type Pollutant Sensors

Nearly half the world\u27s population cooks with wood and charcoal, most of which is used in open `three stone fires\u27 or inefficient cookstoves. These methods are so \u22dirty\u22 that they produce one quarter of global carbon dioxide emissions and result in levels of respiratory illness rivaling the worldwide disease burden of HIV/AIDS. A clean cookstove, designed to make the combustion process less polluting and more thermally efficient, could significantly mitigate the detrimental health and environmental effects of biomass burning. This work has two foci. The first is to develop a method for better stove modeling and design. In particular, an empirical correlation is developed between combustion rate and bulk fluid flow in a forced convection stove case. This is coupled with computational models of stove operation in which fluid flow is a function of a constant heat flux. A parameter study between both cases gives sufficient data to determine where one would expect operating conditions to stabilize in a natural draft (buoyancy driven) cookstove. The second part of this work focuses on developing a quantification model for metal oxide type semiconductor sensors. These sensors are common in low-cost pollutant sensing applications, but their response has yet to be quantified with the accuracy necessary for the ambient monitoring of pollution. Together, these two sections provide tools for the design as well as the validation of cookstoves. Both steps are necessary if cookstoves are to be confidently disseminated as a significant and beneficial technology