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Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry
Published on: June 9, 2021
Monitoring volatile organic compound emissions from Tasmanian engineered wood products using static headspace
Hasini Perera1, Leo Lebanov2, Estrella Sanz Rodriguez2
1School of Engineering, University of Tasmania, Sandy Bay, 7006, Australia; Australian Forest and Wood Innovation (AFWI), Centre for Sustainable Resource and Product Solutions, University of Tasmania, Newnham, 7248, Australia.
Abstract:
This study presents, for the first time, a quantitative S-HS-SPME-GC-MS approach for long-term monitoring of VOC emissions from Tasmanian-manufactured glued-laminated timber, produced using Eucalyptus nitens and Picea abies, enabling temporal emission profiling of 18 target VOCs. Key SPME extraction, chromatographic separation, and MS detection parameters were optimised, resulting in a selective and sensitive analytical method. The method achieved LODs of 0.002 - 0.024 mg m-3 for all target analytes, with intra- and inter-day repeatability below 10% and 20%, respectively. VOC concentrations were monitored over an 84-day period and quantified using 11-point calibration curves, with coefficients of determination (R2) exceeding 0.994. Of the 18 target VOCs, phenyl isocyanate and butylated hydroxytoluene were not detected at any sampling point throughout the study. On Day 1, acetic acid and limonene were the dominant emissions from E. nitens and P. abies glued-laminated timber, respectively, reflecting the joint effect of the distinct chemical composition of the two wood species and the processing conditions applied during manufacturing. In contrast, emissions of adhesive-related VOCs, including chlorobenzene, ethylbenzene, and xylenes, were similar between the two products, reflecting their shared polyurethane adhesive composition. These compounds were emitted at low levels relative to the other target analytes. Principal component analysis identified three emission clusters. Clusters 1 and 2 emissions followed double exponential decay kinetics (R2 = 0.62 - 0.94 and ≥ 0.99, respectively), while Cluster 3 emissions showed irregular patterns that potentially reflect background variability rather than product-specific emissions. These distinct decay behaviours across clusters are likely driven by variations in diffusion-controlled mass transfer and emission decay kinetics.
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