![Sample our Food Science & Technology journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5936/TOC-Subject-Sample-2021-Food-Science-Technology.jpg"})
ABSTRACT
Inhalation rates are used for quantifying inhalation health risks. The time-activity-ventilation (TAV) approach has had longstanding acceptance for estimating inhalation rate (IR) as a time-weighted average across a number of activity levels comprising a typical day. Probability density functions (PDFs) describing 24-hour inhalation rates were updated in this study by incorporating supplemental minute volume (V i ) and time-activity (t i ) data published since the time of the previous study and by correlating V i with metabolic equivalents (METs) for the physical activities at the time of measurement. The metabolic correlations are an improvement over the previous study because they enable interpolation to fill data gaps where V i data are sparse or absent for certain age groups at specific levels of physical activity. The updated PDFs were developed using Monte Carlo simulation and can be described with log normal distributions. The updated PDFs were compared with IR distributions developed through two other approaches: the metabolic energy conversion (MEC) approach; and the doubly labeled water (DLW) approach. Compared to the previous TAV estimates, this study's PDFs suggest lower IR for toddlers and teenagers, higher IR for adults and seniors, and similar IR for infants and children.
ACKNOWLEDGMENT
The authors gratefully acknowledge Health Canada, Contaminated Sites Division, which funded updating of the inhalation PDFs and provided helpful comments and critique.
Notes
aThe amount of time awake but not crying was determined by subtracting the amount of time spent sleeping and crying from 1440 min/day.
aPDFs given in ,
bpoint estimates, age adjusted,
cage adjusted; estimated from percentiles,
daverage of mean values for males and females.