Characterisation of Treated Timber Sources of Pesticide Contaminants using Source Modelling Techniques

Exposure to indoor air contaminants is recognised as a major contributor to human health risk. Level of contaminants are generally higher indoors than outdoors. As people spend 80 to 90% of their time indoors, these elevated contaminant levels cause high exposures which may increase the risk of acute and chronic health effects. Pesticides derived from insecticidal and fungicidal treatments may constitute contaminants of indoor air. This work addresses pesticide emission from remedially treated timber. Little is known about the nature of pesticide dispersal or the level of contamination, exposure and health risk. It is currently not possible to predict exposure levels. To quantify these effects, the source must be characterised, A structured methodology for source characterisation is utilised. In this research, pesticide emission is characterised by mathematical (source) modelling techniques utilising source test data. For a hypothetical exposure scenario, source models are used both to characterise occupant exposure (lAQ modelling) and occupant health risk. Source models are based on compartment model system theory. Techniques new to the field are utilised both to format the governing equations prior to solving and to solve the equations. Available source models are assessed using these techniques and numerically identical solutions are obtained. As a consequence of the treatment process and the anisotropic structure of timber, pesticides are not uniformly distributed in the source. A new family of two compartment source models are developed to reflect this distribution. These models gave more favourable predictions than currently available one compartment source models when compared to pesticide concentration profiles. Analysis of the results indicated that the level of uncertainty associated with the model parameter estimates was related to inadequacies in the source test data and in particular with insufficient measured data at early times post-treatment. For predictive lAQ models, test chamber conditions should be correlated with those prevalent in buildings. Correlation was achieved using fundamental mass transfer theory (boundary layer theory, dimensional analysis and molecular diffusion theory). Comparison of estimated mass transfer based model parameters with values available in the literature were favourable. Discrepancies were largely attributable to experimental methodology. The intrinsic properties of the source model were preliminarily validated using literature data. Predictive lAQ modelling for a hypothetical scenario showed that lindane poses a chronic health risk to building occupants. Mitigation measures based on short-term increased ventilation, absence from the building and the presence of adsorbent (sink) materials, were found to be ineffective in reducing this hazard. The adsorbent (sink) materials were assessed using fundamental adsorption theory. Appropriate adsorption models were expressed in a form consistent with this research. The performance of the sorption model was excellent. The partitioning of lindane between the vapour- and sorbed-phases was shown to be a function of the desorption rate, indicating chemical interaction with the adsorbent. The work has produced two families of (mathematical) source models for use in contaminant source characterisation. The first family is generic whilst the second family is designed for use with pesticide contaminants from treated timber. The relationships between models in the same family and analogous models in the different families have been identified. The work provides context for the use of these models within a broad source characterisation methodology, identifies and evaluates the key features and model parameters and illustrates how these models could be used for predicting occupant exposure and risk in real buildings.

Name dc:type.qualificationname

PhD

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

De Montfort University

Year dc:date.issued

1999

Author dc:creator

• Spalding, Duncan Robert

Licence

• https://dora.dmu.ac.uk/bitstreams/349ee1f9-423c-42f0-8418-4ce970c29716/download