Department of Public Health, China Medical University, Taichung 40402, Taiwan.
Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 70403, Taiwan.
Int J Environ Res Public Health. 2020 Aug 14;17(16):5906. doi: 10.3390/ijerph17165906.
Exposure to indoor particulate matter less than 2.5 µm in diameter (PM) is a critical health risk factor. Therefore, measuring indoor PM concentrations is important for assessing their health risks and further investigating the sources and influential factors. However, installing monitoring instruments to collect indoor PM data is difficult and expensive. Therefore, several indoor PM concentration prediction models have been developed. However, these prediction models only assess the daily average PM concentrations in cold or temperate regions. The factors that influence PM concentration differ according to climatic conditions. In this study, we developed a prediction model for hourly indoor PM concentrations in Taiwan (tropical and subtropical region) by using a multiple linear regression model and investigated the impact factor. The sample comprised 93 study cases (1979 measurements) and 25 potential predictor variables. Cross-validation was performed to assess performance. The prediction model explained 74% of the variation, and outdoor PM concentrations, the difference between indoor and outdoor CO levels, building type, building floor level, bed sheet cleaning, bed sheet replacement, and mosquito coil burning were included in the prediction model. Cross-validation explained 75% of variation on average. The results also confirm that the prediction model can be used to estimate indoor PM concentrations across seasons and areas. In summary, we developed a prediction model of hourly indoor PM concentrations and suggested that outdoor PM concentrations, ventilation, building characteristics, and human activities should be considered. Moreover, it is important to consider outdoor air quality while occupants open or close windows or doors for regulating ventilation rate and human activities changing also can reduce indoor PM concentrations.
暴露于直径小于 2.5μm 的室内颗粒物（PM）是一个关键的健康风险因素。因此，测量室内 PM 浓度对于评估其健康风险以及进一步研究来源和影响因素非常重要。然而，安装监测仪器来收集室内 PM 数据既困难又昂贵。因此，已经开发了几种室内 PM 浓度预测模型。然而，这些预测模型仅评估了寒冷或温带地区的日平均 PM 浓度。影响 PM 浓度的因素因气候条件而异。在这项研究中，我们通过使用多元线性回归模型开发了台湾（热带和亚热带地区）每小时室内 PM 浓度的预测模型，并研究了影响因素。样本包括 93 个研究案例（1979 次测量）和 25 个潜在预测变量。交叉验证用于评估性能。预测模型解释了 74%的变化，并且包括了室外 PM 浓度、室内和室外 CO 水平之间的差异、建筑物类型、建筑物楼层水平、床单清洁、床单更换和蚊香燃烧等因素。交叉验证平均解释了 75%的变化。结果还证实，该预测模型可用于估计跨季节和跨地区的室内 PM 浓度。总之，我们开发了一种每小时室内 PM 浓度的预测模型，并建议考虑室外 PM 浓度、通风、建筑物特征和人类活动。此外，在调节通风率和人类活动改变时，还应考虑室外空气质量，因为人们打开或关闭窗户或门也可以降低室内 PM 浓度。
