Demonstrating particle matter (PM) emissions compliance with environmental regulations is required for operation of
any industrial, commercial or military facility. Emission sources are initially screened based on their visible opacity via
US EPA Method 9 standard. Nowadays, it is rather surprising that opacity is still visually determined by human eyes
with smoke school training and semi-annual certification. Nonetheless, opacity alone doesn’t reveal particle
concentration and size distribution which is crucial to determine PM values. It would be desirable to have an automated,
calibratable device to make such a measurement with higher accuracy and reliability and is not available to date. We
present our preliminary work on developing a compact, hand portable system capable of quantitatively determining
plume optical opacity in combination with possible particle concentration and size distribution (and hence PM)
measurement for standoff distances up to 150 meters. Our benchtop lidar-based system was built with a frequencydoubled
Q-switched Nd:YAG laser and an optical receiver. We have demonstrated the feasibility of a remote-capable
optical sensor system for real-time continuous monitoring of visible emission plumes and its effectiveness for
quantitative opacity measurement. The hand-portable Remote Plume Particulate Matter (RPPM) meter being developed
will be capable of determining opacity and PM load from remote PM sources will provide a regulatory compliance
solution for visible emissions from sources for environmental studies, industrial and military applications.
The Dual Optical Embedded Dust Sensor (DOEDS) is designed for the sensitive, accurate detection of particles for
preventive health monitoring of the AGT1500 engine and M1 Abrams/Ground Combat Vehicles (GCVs). DOEDS is a
real-time sensor that uses an innovative combination of optical particle sensing technologies and mechanical packaging
in a rugged, compact and non-intrusive optical design. The optical sensor, implementing both a single particle sensor and
a mass sensor, can operate in harsh environments (up to 400°F) to meet the particle size, size distribution, mass
concentration, and response time criteria. The sensor may be flush- or inline-mounted in multiple engine locations and
environments.
Smiths Detection and Intelligent Optical Systems have developed prototypes for the Lightweight Autonomous Chemical
Identification System (LACIS) for the US Department of Homeland Security. LACIS is to be a handheld detection
system for Chemical Warfare Agents (CWAs) and Toxic Industrial Chemicals (TICs). LACIS is designed to have a low
limit of detection and rapid response time for use by emergency responders and could allow determination of areas
having dangerous concentration levels and if protective garments will be required. Procedures for protection of
responders from hazardous materials incidents require the use of protective equipment until such time as the hazard can
be assessed. Such accurate analysis can accelerate operations and increase effectiveness.
LACIS is to be an improved point detector employing novel CBRNE detection modalities that includes a militaryproven
ruggedized ion mobility spectrometer (IMS) with an array of electro-resistive sensors to extend the range of
chemical threats detected in a single device. It uses a novel sensor data fusion and threat classification architecture to
interpret the independent sensor responses and provide robust detection at low levels in complex backgrounds with
minimal false alarms.
The performance of LACIS prototypes have been characterized in independent third party laboratory tests at the Battelle
Memorial Institute (BMI, Columbus, OH) and indoor and outdoor field tests at the Nevada National Security Site
(NNSS). LACIS prototypes will be entering operational assessment by key government emergency response groups to
determine its capabilities versus requirements.
Conference Committee Involvement (1)
Photonic Applications for Aerospace, Transportation, and Harsh Environment III
23 April 2012 | Baltimore, Maryland, United States
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