MEMS-Based Micropacked Thermal Desorption GC/PID for In-Field Volatile Organic Compound Profiling from Hot Mix Asphalt

MEMS-Based Micropacked Thermal Desorption GC/PID for In-Field Volatile Organic Compound Profiling from Hot Mix Asphalt

Background: In response to the growing demand for the real-time, in-field characterization of odorous anthropogenic emissions, this study develops and uses a MEMS-based micropacked thermal desorption Gas Chromatography system coupled with a PhotoIonization Detector (GC/PID) for Hot Mix Asphalt (HMA)...

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Main Authors: Stefano Dugheri, Giovanni Cappelli, Riccardo Gori, Stefano Zampolli, Niccolò Fanfani, Ettore Guerriero, Donato Squillaci, Ilaria Rapi, Lorenzo Venturini, Alexander Pittella, Chiara Vita, Fabio Cioni, Domenico Cipriano, Mieczyslaw Sajewicz, Ivan Elmi, Luca Masini, Simone De Sio, Antonio Baldassarre, Veronica Traversini, Nicola Mucci
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Separations
Subjects:
gas chromatography
odour
emission
MEMS
VOCs
hot mix asphalt
Online Access:https://www.mdpi.com/2297-8739/12/5/133
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Summary:Background: In response to the growing demand for the real-time, in-field characterization of odorous anthropogenic emissions, this study develops and uses a MEMS-based micropacked thermal desorption Gas Chromatography system coupled with a PhotoIonization Detector (GC/PID) for Hot Mix Asphalt (HMA) plant emissions. Methods: The innovative portable device, Pyxis GC, enables the high-sensitivity profiling of Volatile Organic Compounds (VOCs), particularly aldehydes and ketones, with sub-ppb detection limits using ambient air as the carrier gas. A comprehensive experimental design optimized the preconcentration parameters, resulting in an efficient, green analytical method evaluated via the Green Analytical Procedure Index (GAPI). Sorbent comparison showed quinoxaline-bridged cavitands outperform the conventional materials. Results and conclusions: The method was successfully deployed on site for source-specific sampling at an HMA plant, generating robust emission fingerprints. To assess environmental impact, a Generalized Additive Model (GAM) was developed, incorporating the process temperature and Sum of Odour Activity Values (SOAV) to predict odour concentrations. The model revealed a significant non-linear influence of temperature on emissions and validated its predictive capability despite the limited sample size. This integrated analytical–statistical approach demonstrates the utility of MEMS technology for real-time air quality assessment and odour dispersion modelling, offering a powerful tool for environmental monitoring and regulatory compliance.
ISSN:2297-8739

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