Association of subjective health symptoms with indoor air quality in European office buildings: The OFFICAIR project.

The aim of this study was to explore the association between the building-related occupants' reported health symptoms and the indoor pollutant concentrations in a sample of 148 office rooms, within the framework of the European OFFICAIR research project. A large field campaign was performed in 37 office buildings among eight countries, which included (a) 5-day air sampling of volatile organic compounds (VOCs), aldehydes, ozone, and NO2 (b) collection of information from 1299 participants regarding their personal characteristics and health perception at workplace using online questionnaires. Stepwise and multilevel logistic regressions were applied to investigate associations between health symptoms and pollutant concentrations considering personal characteristics as confounders. Occupants of offices with higher pollutant concentrations were more likely to report health symptoms. Among the studied VOCs, xylenes were associated with general (such as headache and tiredness) and skin symptoms, ethylbenzene with eye irritation and respiratory symptoms, a-pinene with respiratory and heart symptoms, d-limonene with general symptoms, and styrene with skin symptoms. Among aldehydes, formaldehyde was associated with respiratory and general symptoms, acrolein with respiratory symptoms, propionaldehyde with respiratory, general, and heart symptoms, and hexanal with general SBS. Ozone was associated with almost all symptom groups.

Environmental data treatment to support exposure studies: The statistical behavior for NO2, O3, PM10 and PM2.5 air concentrations in Europe.

In determining and assessing external exposure, there is a need for extensive environmental data sets of sufficient time and space resolution. It is unlikely that a complete set of those data exist for a specific study. Therefore, there will be a need to fill the necessary data gaps. As a first step towards this direction, the statistical behavior of the parameters involved can be estimated so that such parameters can be statistically reconstructed in finer scales. In this study the methodology has been applied to the air concentrations of the priority pollutants NO2, O3, PM10 (particulate matter with an aerodynamic diameter of<10 µm) and PM2.5 (particulate matter with an aerodynamic diameter of<2.5 µm). More specifically, the hourly and the daily concentrations at a given site of those pollutants can be statistically reconstructed assuming known (a) the concentration annual average (m), (b) the pdf of the ratio of the standard deviation over the annual average (σ/m) for the hourly/daily concentrations and (c) the pdf for hourly/daily concentrations themselves. In the case that PM2.5 annual value is missing, it is estimated statistically from the PM10 annual value and the PM2.5/PM10 ratio statistics. As a first test, the proposed methodology is applied for the year 2012 arriving to concrete proposals concerning the statistical behavior of the above-mentioned parameters.

Investigation of the PM2.5, NO2 and O3 I/O ratios for office and school microenvironments.

Differentiation of the exposure to PM2.5 (particulate matter less than 2.5 µm in aerodynamic diameter), NO2 and O3 i.e. pollutants of outdoor origin, due to the occupation of office and school microenvironments, was investigated through the quantification of the respective Indoor to Outdoor (I/O) ratios, in simple statistical terms. For that cause, indoor and outdoor observation data were retrieved from the HEALS EDMS database, and more specifically the data from the OFFICAIR and the SINPHONIE EU projects. The I/O ratios were produced and were statistically analyzed in order to be able to study the influence of the indoor environment against the pollutants coming from outdoors. The present statistical approach highlighted also the differences of I/O ratios between the two studied microenvironments for each pollutant. For exposure estimation to the above-mentioned pollutants, the probability and cumulative distribution function (pdf/cdf) empirical approximations led to the conclusion that for offices the I/O ratios of PM2.5 follow a normal distribution, while NO2 and O3 a gamma distribution. Respectively, for schools the I/O ratios of all pollutants follow a lognormal distribution.