###A novel ‘OLFACTORY’ methodology for assessing the presence of mould in buildings
Project ID: 2228bd1128 (You will need this ID for your application)
Research Theme: Engineering
UCL Lead department: Bartlett School of Environment, Energy and Resources
Lead Supervisor: Hector Altamirano
Project Summary:
According to the English Housing Survey (EHS), the number of homes affected by moisture-related problems has decreased during the last decade. Percentages as low as 3% of the residential social sector were reported to have severe condensation and mould problems (2019-20 EHS). However, recent evidence from SHELTER shows that almost 50% of the rented properties are affected by mould, which is a significant issue for social housing landlords, given the legal requirement that rental properties should be fit for human habitation (Act 2018). The latter has been even more relevant for the UK’shousing sector given the recently reported death of a two-year-old boy living in a mould-contaminated flat. The variability in the data lies in inconsistent methods of information collection combined with tenants’ poor understanding of visible mould. This project aims to establish a new methodology to assess moisture-related problems based on olfactory perception. Since the microbial volatile organic compounds (mVOCs) produced by mould shave a strong smell and are quickly released into the air, smelling ‘damp’ is an effective indication of the existence of mould. The PhD will explore i) The common mould species found in UK homes and their water requirements for germination and growth, from highly hydrophilic (wet loving) to highly xerophilic (dry loving) species. ii) the influence of indoor environmental conditions on mould development, specifically on the production and release of microbial volatile organic compounds (mVOCs), and iii) the variation of smells associated with those microbial volatile organic compounds (mVOCs). Experimental work will be carried out analysing common moulds growing in buildings using chromatography/mass-spectrometry coupled with olfactometric detection (GC-O). This technique enables human analysts to record data on odour sensations. An interdisciplinary methodology to assess indoor mould in residential properties will be developed and tested in mould-contaminated properties.