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Jonathan E Kenny

Publications and source records attributed to Jonathan E Kenny.

3 recordsLinked to original sources

Estuarial fingerprinting through multidimensional fluorescence and multivariate analysis.

As part of a strategy for preventing the introduction of aquatic nuisance species (ANS) to U.S. estuaries, ballast water exchange (BWE) regulations have been imposed. Enforcing these regulations requires a reliable method for determining the port of origin of water in the ballast tanks of ships entering U.S. waters. This study shows that a three-dimensional fluorescence fingerprinting technique, excitation emission matrix (EEM) spectroscopy, holds great promise as a ballast water analysis tool. In our technique, EEMs are analyzed by multivariate classification and curve resolution methods, such as N-way partial least squares Regression-discriminant analysis (NPLS-DA) and parallel factor analysis (PARAFAC). We demonstrate that classification techniques can be used to discriminate among sampling sites less than 10 miles apart, encompassing Boston Harbor and two tributaries in the Mystic River Watershed. To our knowledge, this work is the first to use multivariate analysis to classify water as to location of origin. Furthermore, it is shown that curve resolution can show seasonal features within the multidimensional fluorescence data sets, which correlate with difficulty in classification.

Classification↗

In situ measurements of subsurface contaminants with a multi-channel laser-induced fluorescence system.

A new multi-channel laser-induced fluorescence (LIF) probe with novel optical fiber probe geometry has been designed and integrated into a cone penetrometer testing (CPT) system for in situ contamination detection. The system is capable of collecting excitation and emission matrices (EEMs) of subsurface contaminants as a function of depth in seconds. Compared to our previous multi-channel LIF-CPT system, the new system is faster and more compact, with reduced probe size and sampling area. This article describes the first field demonstration of the system at Hanscom Air Force Base, Massachusetts. One contaminated site within the base was characterized through in situ measurements of 26 LIF-CPT pushes. To validate the LIF results, core samples taken at five locations were analyzed by both on-site LIF measurements and by off-site laboratory analyses with EPA methods. The comparison of the LIF and laboratory results is presented, along with the results of the in situ measurements.

Soil↗

A laser-induced fluorescence dual-fiber optic array detector applied to the rapid HPLC separation of polycyclic aromatic hydrocarbons.

A multi-channel detection system utilizing fiber optics has been developed for the laser-induced fluorescence (LIF) analysis of chromatographic eluents. It has been applied to the detection of polycyclic aromatic hydrocarbons (PAH) in a chromatographically overlapped standard mixture and to a complex soil sample extract obtained during fieldwork. The instrument utilizes dual-fiber optic arrays, one to deliver multiple excitation wavelengths (258-342 nm) generated by a Raman shifter, and the other to collect fluorescence generated by the sample at each excitation wavelength; the collected fluorescence is dispersed and detected with a spectrograph/CCD combination. The resulting data were arranged into excitation emission matrices (EEM) for visualization and data analysis. Rapid characterization of PAH mixtures was achieved under isocratic chromatographic conditions (1.5 mL min(-1) and 80% acetonitrile in water), with mid microg L(-1) detection limits, in less than 4 minutes. The ability of the instrument to identify co-eluting compounds was demonstrated by identifying and quantifying analytes in the rapid analysis of a 17 component laboratory-prepared PAH mixture and a soil extracted sample. Identification and quantification were accomplished using rank annihilation factor analysis (RAFA) using pure component standards and the EEMs of mixtures measured during the rapid high-performance liquid chromatography (HPLC) method as the unknowns. The percentage errors of the retention times (RTs) determined using RAFA compared to the known RTs measured with a standard absorbance detector were between 0 and 11%. For the standard PAH mixture, all 17 components were identified correctly and for the soil extracted sample, all 8 analytes present were correctly identified with only one false positive. Overall, the system achieved excellent qualitative performance with semi-quantitative results in the concentration predictions of both the standard mixture and the real-world sample. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s00216-001-1125-6.

Journal Article↗