Abstract: An air quality system comprising at least one air cleaner unit in communication with an interior air space. In one embodiment, an air quality system for an aircraft comprises a first set of air cleaner units in communication with a lower plenum of the aircraft recirculation system and a second set of air cleaner units in communication with an upper plenum of the aircraft recirculation system. Each air cleaner unit comprises at least one adsorbent unit in combination with at least one photocatalytic oxidation unit. In one embodiment, an air cleaner unit comprises a relatively weak adsorbent material upstream from a photocatalytic oxidation unit, and a relatively strong adsorbent material downstream from the photocatalytic oxidation unit. Methods for removing a pollutant from an air stream and for making an air cleaner unit are also disclosed.

Abstract: A sensor network provides the ability to detect, classify and identify a diverse range of agents over a large area, such as a geographical region or building. The network possesses speed of detection, sensitivity, and specificity for the diverse range of agents. Different functional level types of sensors are employed in the network to perform early warning, broadband detection and highly specific and sensitive detection. A high probability of detection with low probability of false alarm is provided by the processing of information provided from multiple sensors. A Bayesian net is utilized to combine probabilities from the multiple sensors in the network to reach a decision regarding the presence or absence of a threat. The network is field portable and capable of autonomous operation. It also is capable of providing automated output decisions.

Abstract: A sensor network provides the ability to detect, classify and identify a diverse range of agents over a large area, such as a geographical region or building. The network possesses speed of detection, sensitivity, and specificity for the diverse range of agents. Different functional level types of sensors are employed in the network to perform early warning, broadband detection and highly specific and sensitive detection. A high probability of detection with low probability of false alarm is provided by the processing of information provided from multiple sensors. A Bayesian net is utilized to combine probabilities from the multiple sensors in the network to reach a decision regarding the presence or absence of a threat. The network is field portable and capable of autonomous operation. It also is capable of providing automated output decisions.