Clothing impacts indoor air quality: a collaborative modeling study

Published in Chemistry
Clothing impacts indoor air quality: a collaborative modeling study

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The World Health Organization estimates that 3.8 million people die prematurely from exposure to indoor air pollution per year. However, in comparison to outdoor air pollution, indoor air has not been studied in much detail. Indoor air chemistry is different to outdoor air chemistry as follows; (1) sources of indoor pollutants include outdoor-to-indoor transport but daily activities such as cooking and cleaning are also important (2) chemical species are trapped in a relatively small space and transported outdoors at the air-exchange rate, (3) photochemistry is reduced and (4) a high surface area indoors which includes walls, carpets, furniture and people makes heterogeneous chemistry especially important.

Modelers are an integral part of the outdoor atmospheric chemistry community; they test hypotheses regarding experimental measurements, contribute towards explaining field measurements and extrapolate measurements to different conditions. In addition, they can feed back to experimentalists and those making field measurements what information is required to improve the model such that the accuracy of it’s predictions is improved. We were fortunate to be part of the MOdelling Consortium for Chemistry of Indoor Environments (MOCCIE), which is funded by the Chemistry in Indoor Environments Program of the Alfred P. Sloan foundation. MOCCIE aims to develop models which can help to assess the gaps in our knowledge of indoor air processes, help to guide measurements and that could be used in the design and operation of buildings. The people involved in MOCCIE cover a range of modelling aspects including molecular dynamics (MD) simulations, gas-phase chemistry, SOA formation, surface chemistry and computational fluid dynamic (CFD) simulations. One of the principal goals is to collaborate with each other to bridge different models with a wide range of temporal and spatial scales. However, we wondered, would it really be possible to link MD simulations, which investigate molecular processes occurring on length and time scales of nano-meter and nano-seconds to CFD modelling which can predict the concentration of species throughout a room on length and time scales of meters and hours? We hope that in our clothing study we have demonstrated that it is possible.

MOCCIE Modelling team to develop an integrated indoor chemistry model.

In the publication “The impact of clothing on ozone and squalene ozonolysis products in indoor environments” we sought to investigate the formation of carbonyls and the loss of ozone indoors due to the ozonolysis of skin oils on clothing. Carbonyls are known to be skin and respiratory irritants while the impacts of exposure to ozone to health have been widely reported. MD simulations provided several different input parameters to our kinetic-multi layer model. The kinetic multi-layer model investigates the interplay between partitioning, diffusion and chemical reactions of chemical species. We were able to reproduce experimental measurements of carbonyl concentrations formed when soiled clothing was exposed to ozone using this model. The kinetic multi-layer model was then used to provide inputs to the CFD model which provided estimates of the distribution of ozone and carbonyls throughout a room. Our main conclusions were that clothing protects underlying skin from ozone and that soiled clothing can lead to carbonyl concentrations increasing to ppb levels depending on air exchange rates. Primary carbonyl products were also predicted to be up to a factor of two higher in the breathing zone compared to bulk room air. We also realize that there are still uncertainties in parameters associated with modeling a complex system like clothing and we hope that the discussion in our paper will encourage further experiments and MD simulations to better constrain our parameters.

Figure 1. Schematic of the kinetic model for interactions of O3 with skin and clothing to bridge molecular dynamics simulations and computational fluid dynamics simulations. (Figure 1 in Lakey et al., 2019).

To learn more about our paper which was published in Communications Chemistry please click here.

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