DISCRETE PARTICLE-DETECTION AND METAL EMISSIONS MONITORING USING LASER-INDUCED BREAKDOWN SPECTROSCOPY

The unique conditions for the application of laser-induced breakdown s pectroscopy (LIBS) as a metal emissions monitoring technology have bee n discussed. Because of the discrete, particulate nature of effluent m etals, the utilization of LIBS is considered in part as a statistical sampling problem involving the finite laser-induced plasma volume, as well as the concentration and size distribution of the target metal sp ecies. Particle sampling rates are evaluated and Monte Carlo simulatio ns are presented for relevant LIES parameters and wastestream conditio ns. For low metal effluent levels and submicrometer-sized particles, a LIBS-based technique mag become sample limited. An approach based on random LIBS sampling and the conditional analysis of the resulting dat a is proposed as a means to enhance the LIBS sensitivity in actual was testreams. Monte Carlo simulations and experimental results from a pyr olytic waste processing facility are presented, which demonstrate that a significant enhancement of LIBS performance, greater than an order of magnitude, may be realized by taking advantage of the discrete part iculate nature of metals.