RESUMO
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.
RESUMO
Technological innovation has the promise to catalyze reduced environmental impacts through higher energy efficiency, product design that promotes reuse, and use of benign materials. However, as new technologies emerge, it is easy to lose sight of the environmental burden associated with technology transition and premature replacement of technology. Though product turnover can lead to gains in energy efficiency, it also can contribute to the creation of expanded and diversified waste streams. The market for residential lighting products continues to rapidly evolve, with new LED products emerging each year. Technology change in the lighting industry has unintended consequences, including new waste streams associated with the obsolete products. This paper examines the waste burden that occurs as a consequence of technology change when lighting products are replaced or upgraded. To understand the impact of residential lighting replacement, the authors used life cycle assessment to evaluate LED products. We defined three personas representing various typical technology adopters within the product adoption curve to quantify the volume and change rate of lighting products. The personas have also been used to estimate the waste impact for larger populations, and the results show that while an innovator's waste burden is lowest amongst the three personas, a non-trivial waste burden accompanies the transition to LED lighting products for all three personas. The results quantify the waste burden of high performance lighting and further motivate the development and implementation of recycling programs and policies to prevent waste diverted to landfills by consumers. The results also confirm that attention must be paid to how to reduce the waste burden of LED lighting products through improved design and lighting as a service models.