Experimental and Modeled Assessment of Interventions to Reduce PM2.5 in a Residence during a Wildfire Event

Author:

Antonopoulos Chrissi12ORCID,Dillon H. E.23ORCID,Gall Elliott1ORCID

Affiliation:

1. Maseeh College of Engineering and Computer Science, Portland State University, Portland, OR 97201, USA

2. Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA

3. Mechanical Engineering, University of Washington, Tacoma, WA 98402, USA

Abstract

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 PM2.5 reached historic levels, sustained at over 200 μg/m3 for multiple days. Outdoor and indoor PM2.5 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 PM2.5 reached 280 μg/m3, 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 PM2.5 concentrations in residences during extreme wildfire smoke events.

Funder

U.S. Department of Energy Building America Study

Environmental Protection Agency

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference58 articles.

1. Climate change presents increased potential for very large fires in the contiguous United States;Barbero;Int. J. Wildland Fire,2015

2. Trends in global wildfire potential in a changing climate;Liu;For. Ecol. Manag.,2010

3. Wildfire and prescribed burning impacts on air quality in the United States;Jaffe;J. Air Waste Manag. Assoc.,2020

4. Indoor Air: Potential Health Risks Related to Residential Wood Smoke, as Determined under the Assumptions of the US EPA Risk Assessment Model;Sidhu;Indoor Environ.,1993

5. Wildfire smoke impacts respiratory health more than fine particles from other sources: Observational evidence from Southern California;Aguilera;Nat. Commun.,2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3