Quantile regression of indoor air concentrations of volatile organic compounds (VOC).
There are many factors determining the concentration of volatile organic compounds (VOCs) in indoor air. On the basis of 601 population-based measurements we develop an explicit exposure model that includes factors, such as renovation, furniture, flat size, smoking, and education level of the occupants. As a novel method for the evaluation of concentrations of indoor air pollutants we use quantile regression, which has the advantages of robustness against non-Gaussian distributions (and outliers) and can adjust for unbalanced frequencies of observations. The applied bi- and multivariate quantile regressions provide (1) the VOC burden that is representative for the population of Leipzig, Germany, and (2) an inter-comparison of the effects of the studied factors and their levels. As a result, we find strong evidence for factors of general impact on most VOC components, such as the season, flooring, the type of the room, and the size of the apartment. Other impact factors are very specific to the VOC components. For example, wooden flooring (parquet) and new furniture increase the concentration of terpenes as well as the modifying factors high education and sampling in the child's room. Smokers ventilate their flats in an extent that in general reduces the VOC concentrations, except for benzene (contained in tobacco smoke), which is still higher in smoking than in non-smoking flats. Very often dampness is associated with an increased VOC burden in indoor air. An investigation of mixtures emphasises a high burden of co-occurring terpenes in very small and very large apartments.
Schlink
Uwe
U
Helmholtz Centre for Environmental Research UFZ, Leipzig, Germany. uwe.schlink@ufz.de
Thiem
Alexander
A
Kohajda
Tibor
T
Richter
Matthias
M
Strebel
Kathrin
K
D016902:Air Pollution, Indoor / Q000032:analysis* / Q000706:statistics & numerical data; D003710:Demography; D004781:Environmental Exposure / Q000032:analysis / Q000706:statistics & numerical data; D006801:Humans; D008956:Models, Chemical; D015999:Multivariate Analysis; D012044:Regression Analysis; D014028:Tobacco Smoke Pollution / Q000032:analysis / Q000706:statistics & numerical data; D055549:Volatile Organic Compounds / Q000032:analysis*
D014028:Tobacco Smoke Pollution; D055549:Volatile Organic Compounds