A Novel Approach to Near-Real Time Monitoring of Ventilation Rate and Indoor Air Quality in Residential Houses

Syracuse, NY

Physics-based infiltration models, like Lawrence Berkeley Laboratory (LBL) and Alberta Infiltration Model (AIM-2), have been used to predict infiltration rate in near-real time. These models are derived from the driving forces of wind and temperature difference across the building enclosure system, both of which cause pressure differences across the enclosure system for infiltration. The model incorporates other major factors like building leakage characteristics, distributions of openings, microenvironment conditions around the building enclosure as affected by building shields, topography and building shape. The accuracy of the models dependents on getting these factors right. However, these factors are specific for individual buildings and measuring these factors in occupied buildings is difficult. In theory, these can be determined by using generalized table and blower door test but it requires heavy equipment and skilled work force, which is difficult to implement in occupied houses. In this paper, a methodology is developed to determine the air change rate (ACH) and Indoor air quality (IAQ) in near-real time by combining a physics-based infiltration model with a tracer gas decay test method. The methodology is applicable to naturally ventilated houses. Existing infiltration models are modified explicitly to include the impact of the wind direction. The input data for the models also include indoor air temperature and weather data. Tracer gas method is used to determine the infiltration model parameters using multi variable nonlinear regression. Once these parameters are obtained, it is able to predict the ACH with 10% and 16% error for AIM-2 and LBL models, respectively

https://surface.syr.edu/ibpc/2018/IE4/1