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Influence of Precision of Emission Characteristic Parameters on Model Prediction Error of VOCs/Formaldehyde from Dry Building Material
- Source :
- PLoS ONE, PLoS ONE, Vol 8, Iss 12, p e80736 (2013)
- Publication Year :
- 2013
- Publisher :
- Public Library of Science (PLoS), 2013.
-
Abstract
- Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs) and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0), the diffusion coefficient (D), and the partition coefficient (K), can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C.
- Subjects :
- Model prediction
Formaldehyde
Air pollution
lcsh:Medicine
Building material
engineering.material
Atmospheric sciences
medicine.disease_cause
chemistry.chemical_compound
Predictive Value of Tests
Mass transfer
medicine
Humans
Diffusion (business)
lcsh:Science
Physics
Volatile Organic Compounds
Multidisciplinary
Observational error
Construction Materials
lcsh:R
Partition coefficient
Models, Chemical
chemistry
engineering
lcsh:Q
Research Article
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....e62ab404a34ea99822b273091918e5da