Investigation by solid-phase micro-extraction and gas chromatography/mass spectrometry of organic films on stone monuments

✍ Scribed by F. De Angelis; A. Di Tullio; G. Mellerio; R. Quaresima; R. Volpe

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 72 KB
• Volume: 13
• Category: Article
• ISSN: 0951-4198
• DOI: 10.1002/(sici)1097-0231(19990530)13:10<895::aid-rcm580>3.0.co;2-x

✦ Synopsis

Deposition of organic chemicals on historical buildings is a well-known phenomenon. Such material originates from airborne pollution, from human activity, and from natural sources, and it tends to accumulate over long times on the surfaces in the form of a black film which covers considerable portions of the monument surface. Analysis is generally performed on grams of particulate, removed with obvious serious detriment to the monument itself; this material is then conventionally extracted with solvents and analyzed by gas chromatography/mass spectrometry (GC/MS). We propose here a new analytical strategy which takes advantage of the dry solid-phase micro-extraction headspace technique coupled with GC/MS. For this purpose, we used samples of no more than 100 mg of powdered material for each measurement. The black crusts coating the stone surfaces of ancient monuments, dating back to the 13-17th centuries and located in small towns, between high mountains and far away from urban (polluted) environments, have been analyzed. Despite their locations, organic chemicals connected with human activity from our contemporary age, hydrocarbons, PAHs, oxy-PAHs, and herbicides have been revealed. In addition fatty acid residues, probably due to microorganism growths, as well as a large number of mono-and sesquiterpenes reasonably arising from local natural sources, have been detected. The technique we describe, which has been used for the first time in a cultural heritage context, is rapid and not detrimental to the piece of art. The chromatograms thus obtained are characterized by a low background level and a high signal to noise ratio.