Deminers and dismounted countermine engineers commonly use metal detectors, ground penetrating radar and probes to locate mines. Many modern landmines have a very low metal content, which severely limits the effectiveness of metal detectors. Canines have also been used for landmine detection for decades. Experiments have shown that canines smell the explosives which are known to leak from most types of landmines. The fact that dogs can detect landmines indicates that vapor sensing is a viable approach to landmine detection. Several groups are currently developing systems to detect landmines by “sniffing” for the ultra-trace explosive vapors above the soil. The amount of material that is available to passive vapor sensing systems is limited to no more than the vapor in equilibrium with the explosive related chemicals (ERCs) distributed in the surface soils over and near the landmine. The low equilibrium vapor pressure of TNT in the soil/atmosphere boundary layer and the limited volume of the boundary layer air imply that passive chemical vapor sensing systems require sensitivities in the picogram range, or lower. ADA is working to overcome many of the limitations of passive sampling methods, by the use of an active sampling method that employs a high-powered (1,200+ joules) strobe lamp to create a highly amplified plume of vapor and/or ERC-bearing fine particulates. Initial investigations have demonstrated that this approach can amplify the detectability of TNT by two or three orders of magnitude. This new active sampling technique could be used with any suitable explosive sensor.
In the event of a Weapons of Mass Destruction (WMD) chemical or radiological release, quick identification of the nature and source of the release can support efforts to warn, protect and evacuate threatened populations downwind; mitigate the release; provide
more accurate plume forecasting; and collect critical transient evidence to help identify the perpetrator(s). Although there are systems available to assist in tracking a WMD release and then predicting where a plume may be traveling, there are no reliable systems available to determine the source location of that release. This would typically require the timely deployment of a remote sensing capability, a grid of expendable air samplers, or a surface sampling plan if the plume has dissipated. Each of these typical solutions has major drawbacks (i.e.: excessive cost, technical feasibility, duration to accomplish, etc...). This paper presents data to support the use of existing rapid-response meteorological modeling coupled with existing transport and diffusion modeling along with a prototype cost-effective situational awareness monitor which would reduce the sensor network requirements while still accomplishing the overall mission of having a 95% probability in converging on a source location within 100 meters.