Sampling method for long-term monitoring of indoor environmental quality in residential buildings

Abstract

The data collected during long-term monitoring (LTM) of indoor environmental quality (IEQ) can reflect occupants’ exposure to contaminants and can be used to improve thermal comfort. As there are large differences among existing guidelines for IEQ monitoring of dwellings, it is important to identify a sampling method that balances data accuracy, sample size and cost. This paper reports the major findings that developed a systematic approach to determining the sample method for IEQ monitoring. In the study, LTM was carried out in 13 naturally ventilated urban residences in Kunming, China. We proposed the continuous sampling strategy (CSS) and discrete sampling strategy (DSS). Descriptive statistics was used to evaluate the performances of both strategies, and it was found that DSS could obtain more accurate data than CSS. Next, an algorithm was developed for calculating the optimal sampling frequencies for different parameters based on the Pearson correlation coefficient. We evaluated the required number of dwellings(RND) for various parameters that satisfied the statistical confidence in Kunming and other four cities of China. We found that with the increase in the household number in one city, the RND will reach to a critical threshold and no longer increase anymore. Using this threshold and the simple random sampling principle, we also provide guidance for determining the RND for IEQ monitoring in residence. It is expected that the results of this study will facilitate the selection of sampling method for similar studies in the future, with reduced manpower and consumption but a representative sample.