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

James D. Johnston
Brianna M. Magnusson
Dennis Eggett
Scott C. Collingwood
Scott A. Bernhardt, Utah State University

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.