Sylvie Buteau

Internal structure and conditions of permafrost mounds at Umiujaq in Nunavik, Canada, inferred from field investigation and electrical resistivity tomography

A systematic approach was used for the interpretation of the electrical resistivity tomography carried out on two permafrost mounds at Umiujaq in Nunavik, Canada, to assess their internal structure and conditions. Prior information under the form of a geocryologic model of the permafrost mounds was integrated in the inversion of the pseudo-section of apparent electrical resistivity. The geocryologic model was developed from the synthesis of previous field investigations, including shallow and deep sampling, temperature and electrical resistivity logging, and cone penetration tests performed in the permafrost mounds. Values of electrical resistivity were ascribed to the different layers making of the geocryologic model to define a synthetic resistivity model of the permafrost mounds used as a reference model to constrain the inversion. The constrained resistivity model clearly show the presence of ice-rich cores in the permafrost mounds underscored by high resistivity values in excess of 30 000 Ωm, while t...

Effect of growth media and washing on the spectral signatures of aerosolized biological simulants

We have evaluated the influence of growth media and washing on the laser-induced fluorescence spectra of bacteria. Three different bacterial simulants were cultured in three types of growth media. Three kinds of samples were generated from each culture: the culture itself, the growth medium alone, and a triple-washed sample. The materials were injected as aerosols in a lab-sized lidar aerosol chamber to obtain their spectra. Using two different analysis approaches, signature variations were observed between the three kinds of samples for most combinations of growth media/bacteria. This study concludes that the culture media used influences the spectral signatures.

Bioaerosols laser-induced fluorescence provides specific robust signatures for standoff detection

One of todays primary security challenges is the emerging biological threat due to the increased accessibility to biological warfare technology and the limited efficiency of detection against such menace. At the end of the 90s, Defence R&D Canada developed a standoff bioaerosol sensor, SINBAHD, based on intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF) with an excitation at 351 nm. This LIDAR system generates specific spectrally wide fluorescence signals originating from inelastic interactions with complex molecules forming the building blocks of most bioaerosols. This LIF signal is spectrally collected by a combination of a dispersive element and a range-gated ICCD that limits the spectral information within a selected atmospheric cell. The system can detect and classify bioaerosols in real-time, with the help of a data exploitation process based on a least-square fit of the acquired fluorescence signal by a linear combination of normalized spectral signatures. The detection and classification processes are hence directly dependant on the accuracy of these signatures to represent the intrinsic fluorescence of bioaerosols and their discrepancy. Comparisons of spectral signatures acquired at Suffield in 2001 and at Dugway in 2005 of bioaerosol simulants, Bacillius subtilis var globiggi (BG) and Erwinia herbicola (EH), having different origin, preparation protocol and/or dissemination modes, has been made and demonstrates the robustness of the obtained spectral signatures in these particular cases. Specific spectral signatures and their minimum detectable concentrations for different simulants/interferents obtained at the Joint Biological Standoff Detection System (JBSDS) increment II field demonstration trial, Dugway Proving Ground (DPG) in June 2005, are also presented.

Bioaerosol Standoff Monitoring Using Intensified Range-Gated Laser-Induced Fluorescence Spectroscopy

The biological aerosol threat has become a major military and civilian security challenge, primarily due to the increased accessibility to biological technologies, and perhaps partially due to technical difficulties in developing effective detection systems. Defence Research and Development Canada (DRDC) has investigated various technologies, including point and standoff systems for environmental aerosol monitoring, to enhance readiness for such threats. Standoff bio-aerosol systems were based on infrared techniques and laser-induced fluorescence (LIF) approaches. These LIDAR systems were designed to monitor the atmosphere from a standoff position, measuring light scatter or fluorescence signals originating from particle-based biological molecules. In the case of LIF, the signal is spectrally resolved by a combination of grating elements and a range-gated intensified charge couple device (ICCD) that records the spectral information within a range-selected atmospheric volume. Multivariate data analysis techniques may be used to achieve real time detection. Advanced data processing techniques combined with the sensitive sensor have demonstrated the potential to detect and discriminate a mixture of several biological species. Instrument detection limits were determined to be within the target range specified for military and civilian scenarios. The potential of this innovative sensor to measure spectral data of various biological agent simulants, interferants and ambient bio-aerosols of natural and anthropogenic origins will be discussed. The detection limits obtained with this new sensor during open air releases for several given materials, cloud depths and ranges were assessed.

Spectrally resolved laser-induced fluorescence for bioaerosols standoff detection

An efficient standoff biological warfare detection capability could become an important asset for both defence and security communities based on the increasing biological threat and the limits of the presently existing protection systems. Defence R&D Canada (DRDC) has developed, by the end of the 90s, a standoff bioaerosol sensor prototype based on intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF). This LIDAR system named SINBAHD monitors the spectrally resolved LIF originating from inelastic interactions with bioaerosols present in atmospheric cells customizable in size and in range. SINBAHD has demonstrated the capability of near real-time detection and classification of bioaerosolized threats at multi-kilometre ranges. In spring 2005, DRDC has initiated the BioSense demonstration project, which combines the SINBAHD technology with a geo-referenced Near InfraRed (NIR) LIDAR cloud mapper. SINBAHD is now being used to acquire more signatures to add in the spectral library and also to optimize and test the new BioSense algorithm strategy. In September 2006, SINBAHD has participated in a two-week trial held at DRDC-Suffield where different open-air wet releases of live and killed bioagent simulants, growth media and obscurants were performed. An autoclave killing procedure was performed on two biological materials (Bacillus subtilis var globigii or BG, and Bacillus thuringiensis or Bt) before being aerosolized, disseminated and spectrally characterized with SINBAHD. The obtained results showed no significant impact of this killing process on their normalised spectral signature in comparison with their live counterparts. Correlation between the detection signals from SINBAHD, an array of slit samplers and a FLuorescent Aerosol Particle Sensor (C-FLAPS) was obtained and SINBAHDs sensitivity could then be estimated. At the 2006 trial, a detection limit of a few tens of Agent Containing Particles per Liter of Air (ACPLA) was obtained for a 15-m thick cloud of live BG located at a range of 400 m.

Evaluation of adaptive algorithms for detection and classification of fluorescent aerosols in the atmosphere

Photon counting technologies are developed and could be used in the future to measure the return from laser induced fluorescence. Currently, the spectral detection of light emitted by fluorescing aerosols is performed with ICCD, Intensified Charge Coupled Device. The signal to noise ratio of ICCD devices is smaller by a factor of √2compared to photon counting devices having the same sensitivity. We studied the impact of this difference of signal to noise ratio on the capability of multivariate detection and classification algorithms to operate on various conditions. Signal simulations have been performed to obtain ROC (Receiver Operation Characteristics) Curves and Confusion Matrix to obtain the detection performance and the ability of algorithms to discriminate a potential source from another. Two detection algorithms are used, the Integrated Laser Induced Fluorescence(ILIF) and the Matched Filter. For the classification, three algorithms are used, the Adaptive Matched Filter (AMF), the Adaptive Coherent Estimator (ACE) and the Adaptive Least Squares (ALS). The best algorithm for detection is the AMF using the signature of the material present in a cloud, the ILIF detector performs very well. For the classification, the three algorithms are surprisingly giving the same results for the same data. The classification performs better if the distance between the signatures recorded in a database is important. The performance of the detector and of the classificator improves with an increase of the signal to noise ratio and is consistently and significantly better for the photon counting compared to ICCD.

Bioaerosol standoff detection and correlation assessment with concentration and viability point sensors

A standoff bioaerosol sensor based on intensified range-gated spectrometric detection of Laser Induced Fluorescence was used to spectrally characterize bioaerosol simulants during in-chamber and open-air releases at Suffield, Canada, in August 2008 from a standoff position. In total, 42 in-chamber Bacillus atrophaeus (formerly Bacillus subtilis var globigii; BG) cloud and 27 open-air releases of either BG, Pantoea agglomerans (formerly Erwinia herbicola; EH), MS2 and ovalbumin (OV) were generated. The clouds were refereed by different point sensors including Aerodynamic Particle Sizer (APS) and slit or impingers samplers. The APS monitored the particle size distribution and concentration and the samplers characterized the viable portion of the cloud. The extracted spectral signatures show robustness to different degree. The correlation assessment showed good results in most cases where the LIF signal to noise ratio was significant. The sensor 4σ sensitivity was evaluated to 1 300, 600, 100 and 30 ppl for BG, OV, MS2 and EH respectively. Correlation results are presented by plotting the SINBAHD metric versus the corresponding particle concentration, in which case, the obtained slope is proportional to the material fluorescence cross-section. The different acquired signal is hence compared in terms of their fluorescence cross-section additionally to their spectral characteristics.

Spectroscopic Calibration Correlation of Field and Lab-Sized Fluorescence LIDAR Systems

A method has been developed to correlate spectral signatures obtained with various fluorescence LIght Detection And Ranging (LIDAR) systems. A calibrated fluorescence reference target was used to calibrate the spectral response of the LIDAR transmitter channels and obtain their transfer functions. Two LIDAR systems have been spectrally characterized, and corrected signatures for two bioaerosols are presented. The first LIDAR system is the Standoff Integrated Bioserosol Active Hyperspectral Detection field LIDAR developed by Defence R&D Canada. This standoff system uses a 351-nm pulsed laser in a monoaxial design. The second system is a lab-sized aerosol chamber designed to characterize fluorescent aerosols under controlled environmental conditions. The chamber was designed according to classical short-range biaxial LIDAR principles, with the purpose of duplicating the results obtained with field LIDAR systems. Aerosols generated within the chamber are probed by a 355-nm pulsed laser, and autofluorescence spectra are measured with a spectrometer and an intensified charge-coupled device camera. This chamber is used to collect the reference spectra of various fluorescing aerosols and simulants of biological agents. One of the main objectives in using this chamber is to produce and compile a library of instrument-free fluorescing spectra that can be transferred to other LIDAR-based bioaerosol sensors with known optical transfer functions.

Bioaerosols standoff detection simultaneously refereed with particle concentration (ppl) and viability units (ACPLA)

Defence R&D Canada (DRDC) has developed, by the end of the 90s, a standoff bioaerosol sensor prototype based on intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF) called SINBAHD. This LIDAR system was used to characterize spectrally the LIF of bioaerosol agent simulants and obscurants during 57 cross-wind open-air releases at Suffield, CAN in July 2007. An autoclave and gamma-irradiation killing procedures were performed on Bacillus subtilis var globigii (BG) samples before they were aerosolized, disseminated and spectrally characterized. Slight discrepancies were observed in the spectral characteristics of killed versus live samples but none between the two killing methodologies. Significant signature variabilities were observed from the different batches of Erwinia Herbicolas (EH). The generated cloud was simultaneously characterized in Agent Containing Particle per Liter of Air (ACPLA) by slit sampler units and in particle per litter of air (ppl) by an Aerodynamic Particle Sizer (APS). Correlation assessment between the stand-off sensor SINBAHD and the two referee point sensors was done, allowing an estimation of SINBAHDs sensitivity in ACPLA and in ppl. For a 20-m thick cloud at a range of 990 m, a detection limit of a few tens of ACPLA and a few ACPLA were obtained for BG and EH respectively. The extracted correlation between ACPLA and ppl data for releases performed with an agricultural sprayer showed a high degree of variability: 2 to 29% and 1 to 6% of ACPLA/ppl ratio for BG and EH, respectively.

Standoff detection of bioaerosols over wide area using a newly developed sensor combining a cloud mapper and a spectrometric LIF lidar

A standoff sensor called BioSense was developed to demonstrate the capacity to map, track and classify bioaerosol clouds from a distant range and over wide area. The concept of the system is based on a two steps dynamic surveillance: 1) cloud detection using an infrared (IR) scanning cloud mapper and 2) cloud classification based on a staring ultraviolet (UV) Laser Induced Fluorescence (LIF) interrogation. The system can be operated either in an automatic surveillance mode or using manual intervention. The automatic surveillance operation includes several steps: mission planning, sensor deployment, background monitoring, surveillance, cloud detection, classification and finally alarm generation based on the classification result. One of the main challenges is the classification step which relies on a spectrally resolved UV LIF signature library. The construction of this library relies currently on in-chamber releases of various materials that are simultaneously characterized with the standoff sensor and referenced with point sensors such as Aerodynamic Particle Sizer® (APS). The system was tested at three different locations in order to evaluate its capacity to operate in diverse types of surroundings and various environmental conditions. The system showed generally good performances even though the troubleshooting of the system was not completed before initiating the Test and Evaluation (T&E) process. The standoff system performances appeared to be highly dependent on the type of challenges, on the climatic conditions and on the period of day. The real-time results combined with the experience acquired during the 2012 T & E allowed to identify future ameliorations and investigation avenues.