Comparison of Single-Point and Continuous Sampling Methods for Estimating Residential Indoor Temperature and Humidity

Abstract

Residential temperature and humidity are associated with multiple health effects. Studies commonly use single-point measures to estimate indoor temperature and humidity exposures, but there is little evidence to support this sampling strategy. This study evaluated the relationship between single-point and continuous monitoring of air temperature, apparent temperature, relative humidity, and absolute humidity over four exposure intervals (5-min, 30-min, 24-hr, and 12-days) in 9 northern Utah homes, from March-June 2012. Three homes were sampled twice, for a total of 12 observation periods. Continuous data-logged sampling was conducted in homes for 2–3 wks, and simultaneous single-point measures (n = 114) were collected using handheld thermo-hygrometers. Time-centered single-point measures were moderately correlated with short-term (30-min) data logger mean air temperature (r = 0.76, β = 0.74), apparent temperature (r = 0.79, β = 0.79), relative humidity (r = 0.70, β = 0.63), and absolute humidity (r = 0.80, β = 0.80). Data logger 12-day means were also moderately correlated with single-point air temperature (r = 0.64, β = 0.43) and apparent temperature (r = 0.64, β = 0.44), but were weakly correlated with single-point relative humidity (r = 0.53, β = 0.35) and absolute humidity (r = 0.52, β = 0.39). Of the single-point RH measures, 59 (51.8%) deviated more than ±5%, 21 (18.4%) deviated more than ±10%, and 6 (5.3%) deviated more than ±15% from data logger 12-day means. Where continuous indoor monitoring is not feasible, single-point sampling strategies should include multiple measures collected at prescribed time points based on local conditions.