| Popis: |
During normal operations, buildings can protect their occupants from outdoor hazards, including airborne pollutants. A long-term international research effort has advanced our knowledge of building protection physics. However, only recently has an operationally efficient, regional-scale methodology - called Regional Shelter Analysis (RSA) - become available to account for both building protection and the distribution of people within and among buildings.In this study, we apply the previously developed RSA method and develop an implementation that assesses the protection against inhalation of airborne particles for each US Census tract. The present paper focuses on passive protection, i.e., no active measures are taken to improve building protection, and aims to provide representative values for the US building stock. This “proof of principle” implementation is suitable for population-level assessments of many classes of airborne inhalation hazards (gaseous hazards are covered in a separate report). In developing this implementation, we have assembled and summarized the published literature relevant to indoor particulate losses including (a) deposition to indoor surfaces, (b) losses that occur when particles penetrate through the building envelope, and (c) heating, ventilation and air conditioning (HVAC) system filtration efficiencies as well as general building operating conditions. The summarized results and primary simulation data are both provided.Our analysis indicates that the building protection against inhaling particulate hazards varies strongly, i.e., by orders of magnitude, according to building use (occupancy) and particle size. Single family homes, manufactured homes, and multi-unit apartment buildings have similar (within a factor of 2) protection values. The protection for people within US Census tracts is broadly similar during the night compared to the workday. On average, there is slightly better protection during the night when people are at home. The variability of protection within a given US Census tract often spans one or more orders of magnitude. |
