Abstract “Auto-mode” portable air cleaners (PACs) designed to turn on automatically in response to elevated indoor PM2.5 concentrations are widely used in residences. This study assesses the impacts of using such PACs equipped with high-efficiency particulate air filters on residential PM2.5 levels in six households recruited in Seattle, Washington, for a randomized crossover study, in which participants used a PAC in their homes under three intervention scenarios: (1) sham-mode filtration in which all filters in the PAC were removed, (2) auto-mode filtration in which the PAC was set to auto mode, and (3) adjustable-mode filtration in which the participants were allowed to manually adjusted the PACs. Each filtration session was one-week long. PM2.5 levels were measured at 1-min intervals in the kitchen and living room of each household. Also, an hourly time-activity log was collected from each participant. The empirical concentrations and I/O ratios of PM2.5 were compared among the three filtration modes. Additionally, linear mixed-effects regression models (LMER) were developed to reveal the impacts of different filtration modes on indoor PM2.5, while controlling for outdoor PM2.5, indoor cooking events, and indoor relative humidity, and temperature. Based on the LMER models, when indoor cooking events were present and absent, auto-mode filtration significantly reduced the indoor PM2.5 levels by 31% [95% CI: 19%, 42%] and 28% [95% CI: 22%, 34%], respectively, compared with sham-mode filtration, and reduced the indoor PM2.5 levels by 19% [95% CI: 6%, 31%] and 4% [95% CI: 4%, 11%], respectively, compared with adjustable-mode filtration. These findings suggest that using such PACs running in auto mode is a practical and effective way to reduce indoor PM2.5 levels.

中文翻译：

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使用自动模式便携式空气净化器对室内 PM2.5 水平的影响：一项干预研究

摘要 “自动模式”便携式空气净化器 (PAC) 旨在响应室内 PM2.5 浓度升高而自动开启，广泛用于住宅。本研究评估了在华盛顿西雅图招募的六个家庭中使用配备高效微粒空气过滤器的此类 PAC 对住宅 PM2.5 水平的影响，进行随机交叉研究，参与者在三个干预下在家中使用 PAC场景：（1）假模式过滤，其中移除了 PAC 中的所有过滤器，（2）自动模式过滤，其中 PAC 设置为自动模式，以及（3）可调模式过滤，其中允许参与者手动调整 PAC。每次过滤时间为一周。PM2.5 水平在每个家庭的厨房和客厅中以 1 分钟的间隔进行测量。还，从每个参与者那里收集了每小时的时间活动日志。PM2.5 的经验浓度和 I/O 比在三种过滤模式之间进行了比较。此外，还开发了线性混合效应回归模型 (LMER)，以揭示不同过滤模式对室内 PM2.5 的影响，同时控制室外 PM2.5、室内烹饪事件以及室内相对湿度和温度。基于 LMER 模型，当存在和不存在室内烹饪事件时，自动模式过滤将室内 PM2.5 水平显着降低 31% [95% CI：19%、42%] 和 28% [95% CI：22 %, 34%]，分别与假模式过滤相比，将室内 PM2.5 水平降低 19% [95% CI: 6%, 31%] 和 4% [95% CI: 4%, 11%] ]，分别与可调模式过滤相比。