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In addition to the biodegradation problems encountered in buildings, exposure of their occupants to mold is responsible for numerous diseases such as respiratory infections, immediate or delayed allergies and different types of irritations. However, current techniques are unable to detect mold at an early stage of development or hidden contaminants. Moularat et al., in 2008 has established chemical fingerprints of moldy growth from Volatile Organic Compounds (VOCs) arising specifically from fungal metabolism and developed the Fungal Contamination Index (FCI) (Moularat et al., 2008a,b). This index has the advantage of detecting fungal development both reliably and rapidly before any visible signs of contamination could be detected. However, even though the FCI has been widely tested, VOCs' analysis by GC/MS, which is required for index calculation, is incompatible with real-time monitoring strategy for indoor environments. In this context, researches around FCI exploitation have been followed up in order to provide a monitoring device widely deployable which is the result of the miniaturization of an analytical chain for portable, reliable and low-cost applications. This device is based on one hand the selection and concentration of chemical compounds from the sample of interest and on the other hand the development of an array of different conducting polymer based sensors in order to obtain a specific footprint. This fungal contamination detection device was the subject of patent applications by the CSTB. The modularity of the system (ability to vary both the elements of detection polymers and retention time of interest) allows for expansion of its use to other pollutants.

A dual computational/experimental approach enabled to rank the performance of series of MOFs for α-pinene capture in terms of affinity and uptake. UiO-66(Zr) is demonstrated to be a good candidate...

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