Locating landmines and UXO by detection of the chemical signature emanating from these devices is extremely challenging due to several of the physical properties of explosives. Because the explosives used in landmines and UXO have extremely low vapor pressures, the concentration of explosive vapors escaping from the ordnance is very low. Fate and transport studies of explosives in soil over buried ordnance have indicated that once released into the soil, virtually all of the explosive vapor is quickly adsorbed onto the surface of soil particles. This behavior is not surprising, since explosives are known to readily adsorb onto most types of surfaces. The adsorption of explosive onto soil particles is to an extent a reversible process, enabling diffusion of explosive through the soil. Unfortunately, because of irreversible adsorption and other processes occurring in the soil that destroy or degrade the explosive, the concentration of explosive reaching the surface of the ground is extremely low. However, dogs are able to locate buried ordnance, indicating that explosive signature compounds are present at or near the surface of the ground at concentrations in excess of the minimum detection limit of canines. Since the fate and transport studies indicate a much higher concentration of explosive adsorbed onto soil particles than in the vapor phase, sampling the explosive adsorbed onto soil particles may be a more efficient approach to sampling explosives than sampling explosive vapor in the air over buried ordnance. An electrostatic particle sampler has been designed which is capable of rapidly and efficiently sampling soil particles. Once the soil particles have been sampled, the explosive is desorbed from the particles, concentrated, and then presented to a sensitive chemical detector for analysis. In its present configuration, the particle sampler delivers a vapor phase sample to the detector, but the device could be adapted to deliver samples in the solvent phase as well. This makes the sampler compatible with a number of sensor technologies.