Enhanced real-time bioaerosol detection : atmospheric dispersion modeling and characterization of a family of wetted-wall bioaerosol sampling cyclones

This work is a multi-scale effort to confront the rapidly evolving threat of biological weapons attacks through improved bioaerosol surveillance, detection, and response capabilities. The effects of bioaerosol release characteristics, transport in the atmospheric surface layer, and implications for bioaerosol sampler design and real-time detection were studied to develop risk assessment and modeling tools to enhance our ability to respond to biological weapons attacks. A simple convection-diffusion-sedimentation model was formulated and used to simulate atmospheric bioaerosol dispersion. Model predictions suggest particles smaller than 60 micrometers in aerodynamic diameter (AD) are likely to be transported several kilometers from the source. A five fold increase in effective mass collection rate, a significant bioaerosol detection advantage, is projected for samplers designed to collect particles larger than the traditional limit of 10 micrometers AD when such particles are present in the source distribution.
A family of dynamically scaled wetted-wall bioaerosol sampling cyclones (WWC) was studied to provide bioaerosol sampling capability under various threat scenarios. The effects of sampling environment, i.e. air conditions, and air flow rate on liquid recovery rate and response time were systematically studied. The discovery of a critical liquid input rate parameter enabled the description of all data with self-similar relationships. Empirical correlations were then integrated into system control algorithms to maintain microfluidic liquid output rates ideally suited for advanced biological detection technologies. Autonomous ambient air sampling with an output rate of 25 microliters per minute was achieved with open-loop control. This liquid output rate corresponds to a concentration rate on the order of 2,000,000, a substantial increase with respect to other commercially available bioaerosol samplers. Modeling of the WWC was performed to investigate the underlying physics of liquid recovery. The set of conservative equations governing multiphase heat and mass transfer within the WWC were formulated and solved numerically. Approximate solutions were derived for the special cases of adiabatic and isothermal conditions. The heat and mass transfer models were then used to supplement empirical correlations. The resulting semi-empirical models offer enhanced control over liquid concentration factor and further enable the WWC to be deployed as an autonomous bioaerosol sampler.