Antonopoulos Chrissi, Dillon H E, Gall Elliott
Maseeh College of Engineering and Computer Science, Portland State University, Portland, OR 97201, USA.
Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA.
Pollutants. 2024 Mar;4(1):26-41. doi: 10.3390/pollutants4010003. Epub 2024 Jan 28.
Increasingly large and frequent wildfires affect air quality even indoors by emitting and dispersing fine/ultrafine particulate matter known to pose health risks to residents. With this health threat, we are working to help the building science community develop simplified tools that may be used to estimate impacts to large numbers of homes based on high-level housing characteristics. In addition to reviewing literature sources, we performed an experiment to evaluate interventions to mitigate degraded indoor air quality. We instrumented one residence for one week during an extreme wildfire event in the Pacific Northwest. Outdoor ambient concentrations of reached historic levels, sustained at over 200 μg/m for multiple days. Outdoor and indoor were monitored, and data regarding building characteristics, infiltration, and mechanical system operation were gathered to be consistent with the type of information commonly known for residential energy models. Two conditions were studied: a high-capture minimum efficiency rated value (MERV 13) filter integrated into a central forced air (CFA) system, and a CFA with MERV 13 filtration operating with a portable air cleaner (PAC). With intermittent CFA operation and no PAC, indoor corrected concentrations of reached 280 μg/m, and indoor/outdoor (I/O) ratios reached a mean of 0.55. The measured I/O ratio was reduced to a mean of 0.22 when both intermittent CFA and the PAC were in operation. Data gathered from the test home were used in a modeling exercise to assess expected I/O ratios from both interventions. The mean modeled I/O ratio for the CFA with an MERV 13 filter was 0.48, and 0.28 when the PAC was added. The model overpredicted the MERV 13 performance and underpredicted the CFA with an MERV 13 filter plus a PAC, though both conditions were predicted within 0.15 standard deviation. The results illustrate the ways that models can be used to estimate indoor concentrations in residences during extreme wildfire smoke events.
规模越来越大且愈发频繁的野火会排放并扩散已知对居民健康构成风险的细颗粒物/超细颗粒物，甚至对室内空气质量也会产生影响。面对这种健康威胁，我们正致力于帮助建筑科学界开发简化工具，这些工具可根据高层次房屋特征来估算对大量房屋的影响。除了查阅文献资料，我们还开展了一项实验，以评估减轻室内空气质量恶化的干预措施。在太平洋西北地区发生极端野火事件期间，我们对一所住宅进行了为期一周的监测。室外环境浓度达到历史最高水平，连续多日维持在200微克/立方米以上。对室外和室内的[具体污染物名称未给出]进行了监测，并收集了有关建筑特征、渗透和机械系统运行的数据，以与住宅能源模型通常已知的信息类型保持一致。研究了两种情况：一种是将高效滤网（最低效率报告值为MERV 13）集成到中央强制空气（CFA）系统中，另一种是配备MERV 13滤网的CFA与便携式空气净化器（PAC）一起运行。在CFA间歇性运行且没有PAC的情况下，室内校正后的[具体污染物名称未给出]浓度达到280微克/立方米，室内/室外（I/O）比率平均达到0.55。当CFA间歇性运行且PAC也运行时，测得的I/O比率降至平均0.22。从测试房屋收集的数据被用于建模练习，以评估这两种干预措施的预期I/O比率。配备MERV 13滤网的CFA的平均建模I/O比率为0.48，添加PAC后为0.28。该模型高估了MERV 13滤网的性能，低估了配备MERV 13滤网加PAC的CFA的性能，不过两种情况的预测值都在0.15标准差范围内。结果说明了在极端野火烟雾事件期间，模型可用于估算住宅内室内[具体污染物名称未给出]浓度的方法。
