Repace Associates

MD, United States

Repace Associates

MD, United States

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Dacunto P.J.,Stanford University | Cheng K.-C.,Stanford University | Cheng K.-C.,Environmental Health Laboratory | Acevedo-Bolton V.,Stanford University | And 6 more authors.
Environmental Sciences: Processes and Impacts | Year: 2013

Indoor sources can greatly contribute to personal exposure to particulate matter less than 2.5 μm in diameter (PM2.5). To accurately assess PM2.5 mass emission factors and concentrations, real-time particle monitors must be calibrated for individual sources. Sixty-six experiments were conducted with a common, real-time laser photometer (TSI SidePak™ Model AM510 Personal Aerosol Monitor) and a filter-based PM2.5 gravimetric sampler to quantify the monitor calibration factors (CFs), and to estimate emission factors for common indoor sources including cigarettes, incense, cooking, candles, and fireplaces. Calibration factors for these indoor sources were all significantly less than the factory-set CF of 1.0, ranging from 0.32 (cigarette smoke) to 0.70 (hamburger). Stick incense had a CF of 0.35, while fireplace emissions ranged from 0.44-0.47. Cooking source CFs ranged from 0.41 (fried bacon) to 0.65-0.70 (fried pork chops, salmon, and hamburger). The CFs of combined sources (e.g., cooking and cigarette emissions mixed) were linear combinations of the CFs of the component sources. The highest PM2.5 emission factors per time period were from burned foods and fireplaces (15-16 mg min-1), and the lowest from cooking foods such as pizza and ground beef (0.1-0.2 mg min-1). © 2013 The Royal Society of Chemistry.


Dacunto P.J.,Stanford University | Cheng K.-C.,Stanford University | Cheng K.-C.,Environmental Health Laboratory | Acevedo-Bolton V.,Stanford University | And 6 more authors.
Indoor Air | Year: 2014

Identifying and quantifying secondhand tobacco smoke (SHS) that drifts between multiunit homes is critical to assessing exposure. Twenty-three different gaseous and particulate measurements were taken during controlled emissions from smoked cigarettes and six other common indoor source types in 60 single-room and 13 two-room experiments. We used measurements from the 60 single-room experiments for (i) the fitting of logistic regression models to predict the likelihood of SHS and (ii) the creation of source profiles for chemical mass balance (CMB) analysis to estimate source apportionment. We then applied these regression models and source profiles to the independent data set of 13 two-room experiments. Several logistic regression models correctly predicted the presence of cigarette smoke more than 80% of the time in both source and receptor rooms, with one model correct in 100% of applicable cases. CMB analysis of the source room provided significant PM2.5 concentration estimates of all true sources in 9 of 13 experiments and was half-correct (i.e., included an erroneous source or missed a true source) in the remaining four. In the receptor room, CMB provided significant estimates of all true sources in 9 of 13 experiments and was half-correct in another two. © 2013 John Wiley & Sons A/S.


Dacunto P.J.,Stanford University | Dacunto P.J.,United States Military Academy | Klepeis N.E.,Stanford University | Klepeis N.E.,San Diego State University | And 6 more authors.
Environmental Sciences: Processes and Impacts | Year: 2015

Real-time particle monitors are essential for accurately estimating exposure to fine particles indoors. However, many such monitors tend to be prohibitively expensive for some applications, such as a tenant or homeowner curious about the quality of the air in their home. A lower cost version (the Dylos Air Quality Monitor) has recently been introduced, but it requires appropriate calibration to reflect the mass concentration units required for exposure assessment. We conducted a total of 64 experiments with a suite of instruments including a Dylos DC1100, another real-time laser photometer (TSI SidePak™ Model AM-510 Personal Aerosol Monitor), and a gravimetric sampling apparatus to estimate Dylos calibration factors for emissions from 17 different common indoor sources including cigarettes, incense, fried bacon, chicken, and hamburger. Comparison of minute-by-minute data from the Dylos with the gravimetrically calibrated SidePak yielded relationships that enable the conversion of the raw Dylos particle counts less than 2.5 μm (in #/0.01 ft3) to estimated PM2.5 mass concentration (e.g. μg m-3). The relationship between the exponentially-decaying Dylos particle counts and PM2.5 mass concentration can be described by a theoretically-derived power law with source-specific empirical parameters. A linear relationship (calibration factor) is applicable to fresh or quickly decaying emissions (i.e.; before the aerosol has aged and differential decay rates introduce curvature into the relationship). The empirical parameters for the power-law relationships vary greatly both between and within source types, although linear factors appear to have lower uncertainty. The Dylos Air Quality Monitor is likely most useful for providing instantaneous feedback and context on mass particle levels in home and work situations for field-survey or personal awareness applications. © The Royal Society of Chemistry.


Dacunto P.J.,Stanford University | Cheng K.-C.,Stanford University | Acevedo-Bolton V.,Stanford University | Klepeis N.E.,Stanford University | And 4 more authors.
Atmospheric Environment | Year: 2013

Accurate identification and quantification of the secondhand tobacco smoke (SHS) that drifts between multiunit homes (MUHs) is essential for assessing resident exposure and health risk. We collected 24 gaseous and particle measurements over 6-9 day monitoring periods in five nonsmoking MUHs with reported SHS intrusion problems. Nicotine tracer sampling showed evidence of SHS intrusion in all five homes during the monitoring period; logistic regression and chemical mass balance (CMB) analysis enabled identification and quantification of some of the precise periods of SHS entry. Logistic regression models identified SHS in eight periods when residents complained of SHS odor, and CMB provided estimates of SHS magnitude in six of these eight periods. Both approaches properly identified or apportioned all six cooking periods used as no-SHS controls. Finally, both approaches enabled identification and/or apportionment of suspected SHS in five additional periods when residents did not report smelling smoke. The time resolution of this methodology goes beyond sampling methods involving single tracers (such as nicotine), enabling the precise identification of the magnitude and duration of SHS intrusion, which is essential for accurate assessment of human exposure. © 2013.


PubMed | San Diego State University, United States Military Academy, Stanford University and Repace Associates
Type: Journal Article | Journal: Environmental science. Processes & impacts | Year: 2015

Real-time particle monitors are essential for accurately estimating exposure to fine particles indoors. However, many such monitors tend to be prohibitively expensive for some applications, such as a tenant or homeowner curious about the quality of the air in their home. A lower cost version (the Dylos Air Quality Monitor) has recently been introduced, but it requires appropriate calibration to reflect the mass concentration units required for exposure assessment. We conducted a total of 64 experiments with a suite of instruments including a Dylos DC1100, another real-time laser photometer (TSI SidePak Model AM-510 Personal Aerosol Monitor), and a gravimetric sampling apparatus to estimate Dylos calibration factors for emissions from 17 different common indoor sources including cigarettes, incense, fried bacon, chicken, and hamburger. Comparison of minute-by-minute data from the Dylos with the gravimetrically calibrated SidePak yielded relationships that enable the conversion of the raw Dylos particle counts less than 2.5 m (in #/0.01 ft(3)) to estimated PM2.5 mass concentration (e.g. g m(-3)). The relationship between the exponentially-decaying Dylos particle counts and PM2.5 mass concentration can be described by a theoretically-derived power law with source-specific empirical parameters. A linear relationship (calibration factor) is applicable to fresh or quickly decaying emissions (i.e., before the aerosol has aged and differential decay rates introduce curvature into the relationship). The empirical parameters for the power-law relationships vary greatly both between and within source types, although linear factors appear to have lower uncertainty. The Dylos Air Quality Monitor is likely most useful for providing instantaneous feedback and context on mass particle levels in home and work situations for field-survey or personal awareness applications.

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