Renewable gases exploration by TD-GC×GC-TOFMS (Agathe Legendre, MDCW 2023)

• 🎤 Presenter: Agathe Legendre¹,², Sandy Bsaibes², Didier Thiebaut¹, José Dugay¹, Dairo Ballestas Castro², Lorena Cuccia², Jérôme Vial¹ (¹LSABM, UMR CBI 8231CNRS, ESPCI Paris, PSL Université, Paris, France. ²GRTgaz, RICE (Research and Innovation Center for Energy), Villeneuve-la-Garenne, France)

💡 Book in your calendar: 15th Multidimensional Chromatography Workshop (MDCW) January 2024

15th Multidimensional Chromatography (MDC) Workshop 2024

Abstract

In the context of the energy transition, the French gas network is diversifying to include renewable gases from innovative processes such as pyrogasification implemented at the moment in R&D pilots. Pyrogasification consists in heating solids such as biomass or Solid Recovered Fuel at high temperatures from 600 to 900°C. Yet, the detailed composition of the produced gas is far from being well known because focus is generally put on the analysis of major components. A better knowledge in the detailed composition of the produced gas is mandatory to adapt the purification steps. The aim of the present study was to characterize trace organic compounds, including alkanes, aromatics, oxygen-organic compounds, halogenorganic compounds and sulfur-organic compounds, at different steps of the process, by thermal desorption GCxGC-TOFMS.

First, a sampling system was investigated to ensure the representativity of the collected sample. Then, the TD-GCxGC-ToFMS method was developed to take into account the presence of a high content of light alkanes (C2 – C14) in the samples. To do this, the cryogenic modulation system has been optimized concerning the duration of cold and hot jets. A compound family approach, based on the use of one reference compound by chemical family, was proposed to perform a quantification by equivalent on real samples and map volatile organic impurities in biosourced gases. Finally, this method allowed the comparison of the composition of several real renewable gases from different inputs. The highlighting of specific differences in their composition was performed using a tile-based Fisher Ratio analysis.