Reduction potential of urban PM2.5 mortality risk using modern ventilation systems in buildings

We evaluated the impact on personal exposure to air pollutants of following advice which typically accompanies air quality advisories and indices. Scripts prescribed the time, location, duration and nature of activities intended to simulate daily activity patterns for adults and children. Scripts were paired such that one individual would proceed with usual activities (base scenario), whereas the other (intervention scenario) would alter activities as if following advice. Other than commuting, where the intervention group walked or used public transportation rather than riding in personal vehicles, this group generally spent less time outdoors. Ultra-fine particles (UFPs), particulate matter of median aerodynamic diameter less than 2.5 mm (PM 2.5 ) and total volatile organic compounds (VOCs) were measured using samplers carried by individuals during the course of daily activities. During daytime activities (e.g., work, daycare) constituting the largest share of sampling time (approximately 6 h per day), the intervention group experienced a 14% reduction in exposure to UFPs (P ¼ 0.01), a 21% reduction in exposure to PM 2.5 (P ¼ 0.08), and an 86% increase in exposure to VOCs (P ¼ 0.02). Other findings included an 89% increase in exposure to UFPs (P ¼ 0.02) and a threefold increase in exposure to VOCs (P ¼ 0.08) in the intervention group during evening cooking. Following smog advisory advice results in reduced exposures to some pollutants, while at the same time increasing exposure to others. Advice needs to be refined giving consideration to overall personal exposure.

Section: Discussionsupporting

confidence: 89%

A scripted activity study of the impact of protective advice on personal exposure to ultra-fine and fine particulate matter and volatile organic compounds

Stieb

Evans

Sabaliauskas

et al. 2007

“…Previous studies have demonstrated correlations between F inf and a number of building, meteorological and behavioral factors; however, such studies do not use data readily available for large populations. Factors found to be related to F inf include housing variables such as age, size, value, square footage, and ventilation conditions (Wallace, 1996;Sherman and Dickerhoff, 1998;Ozkaynak et al, 1999;Ebelt et al, 2000;Sherman and Matson, 2001;Thornburg et al, 2001;McKone et al, 2002;Hanninen et al, 2005;Chan et al, 2005); meteorological factors including temperature and exposure to wind and precipitation (Sherman and Dickerhoff, 1998;Chao and Tung, 2001;McKone et al, 2002); and occupant behaviors and characteristics, such as occupant income, window opening, and use of air conditioners and air filters (Sherman and Dickerhoff, 1998;Mosley et al, 2001;Janssen et al, 2002;Wallace et al, 2003;Koenig et al, 2005). A study by Chan et al (2005) analyzed approximately 70,000 air leakage measurements (a parameter related to F inf ) in the United State to determine predictive housing characteristics and found year of construction, size of dwelling and whether the dwelling was either energy-efficient or occupied by a low-income family to be important predictors of normalized leakage.…”

Section: Introductionmentioning

confidence: 99%

Modeling residential fine particulate matter infiltration for exposure assessment

Hystad

Setton

Allen

et al. 2008

Individuals spend the majority of their time indoors; therefore, estimating infiltration of outdoor-generated fine particulate matter (PM 2.5 ) can help reduce exposure misclassification in epidemiological studies. As indoor measurements in individual homes are not feasible in large epidemiological studies, we evaluated the potential of using readily available data to predict infiltration of ambient PM 2.5 into residences. Indoor and outdoor light scattering measurements were collected for 84 homes in Seattle, Washington, USA, and Victoria, British Columbia, Canada, to estimate residential infiltration efficiencies. Meteorological variables and spatial property assessment data (SPAD), containing detailed housing characteristics for individual residences, were compiled for both study areas using a geographic information system. Multiple linear regression was used to construct models of infiltration based on these data. Heating (October to February) and non-heating (March to September) season accounted for 36% of the yearly variation in detached residential infiltration. Two SPAD housing characteristic variables, low building value, and heating with forced air, predicted 37% of the variation found between detached residential infiltration during the heating season. The final model, incorporating temperature and the two SPAD housing characteristic variables, with a seasonal interaction term, explained 54% of detached residential infiltration. Residences with low building values had higher infiltration efficiencies than other residences, which could lead to greater exposure gradients between low and high socioeconomic status individuals than previously identified using only ambient PM 2.5 concentrations. This modeling approach holds promise for incorporating infiltration efficiencies into large epidemiology studies, thereby reducing exposure misclassification.

“…The efficiency, removal rates, and other performance characteristics of some of these devices have been characterized empirically (Chen et al, 2006;Shaughnessy and Sextro, 2006;MacIntosh et al, 2008). The potential for advanced filtration technology to mitigate indoor exposure to PM 2.5 of ambient origin in Europe was estimated from results of the EXPOLIS study (Hanninen et al, 2005). A similar modeling analysis was conducted for buildings in Singapore (Sultan, 2007).…”

Section: Introductionmentioning

confidence: 99%

The benefits of whole-house in-duct air cleaning in reducing exposures to fine particulate matter of outdoor origin: A modeling analysis

MacIntosh

Minegishi²,

Kaufman³

et al. 2009

Health risks of fine particle air pollution (PM 2.5 ) are an important public health concern that has the potential to be mitigated in part by interventions such as air cleaning devices that reduce personal exposure to ambient PM 2.5 . To characterize exposure to ambient PM 2.5 indoors as a function of residential air cleaners, a multi-zone indoor air quality model was used to integrate spatially resolved data on housing, meteorology, and ambient PM 2.5 , with performance testing of residential air cleaners to estimate short-term and annual average PM 2.5 of outdoor origin inside residences of three metropolitan areas. The associated public health impacts of reduced ambient PM 2.5 exposure were estimated using a standard health impact assessment methodology. Estimated indoor levels of ambient PM 2.5 varied substantially among ventilation and air cleaning configurations. The median 24-h average indooroutdoor ratio of ambient PM 2.5 was 0.57 for homes with natural ventilation, 0.35 for homes with central air conditioning (AC) with conventional filtration, and 0.1 for homes with central AC with high efficiency in-duct air cleaner. Median modeled 24-h average indoor concentrations of PM 2.5 of outdoor origin for those three configurations were 8.4, 5.3, and 1.5 mg/m 3 , respectively. The potential public health benefits of reduced exposure to ambient PM 2.5 afforded by air cleaning systems were substantial. If the entire population of single-family homes with central AC in the modeling domain converted from conventional filtration to high-efficiency in-duct air cleaning, the change in ambient PM 2.5 exposure is estimated to result in an annual reduction of 700 premature deaths, 940 hospital and emergency room visits, and 130,000 asthma attacks in these metropolitan areas. In addition to controlling emissions from sources, high-efficiency whole-house air cleaner are expected to reduce exposure to particles of outdoor origin and are projected to be an effective means of managing public health impacts of ambient particle pollution.