In many regions, wood combustion is a significant source of wintertime aerosols. However, since wood combustion sources are interspersed within neighborhoods, near-field concentration variability has the potential to cause large variations in the exposure levels between residents over a relatively small area. This field study compared filter samples and aethalometer measurements of black carbon concentration within a 1 km 2 study region with no significant aerosol sources except wood combustion. Sampling occurred on 15 nights over two winter seasons in a small California coastal town. Even over the small distances in the study area, large spatial and temporal variations were observed. Measured black carbon concentrations varied by as much as a factor of 10 over a 12-hour night-time period. The spatial variability was non-random, with the highest location in the study area experiencing 4 times the average concentration within the neighborhood, when averaged over all sample periods. The results of this study indicate that within neighborhoods with residential wood combustion sources using an average concentration for a region to predict exposure may significantly undervalue the exposure of some residents and overvalue the exposure for others.
Black carbon, a proxy for woodsmoke was measured indoors and outdoors for an occupied residence in Cambria, CA during the winter months of 2009. The purpose was to investigate the infiltration parameters: air exchange rate, deposition rate, and penetration factor. The second part of this study investigated the light absorption properties of organic carbon from residential wood combustion, the dominant fraction of woodsmoke.To assess woodsmoke variation, a study conducted parallel to the one presented in this thesis (Ward, 2009), a grid array of personal emission monitors (PEMS) and aethalometers were placed in a small area, approximately one square kilometer, within a community in Cambria, California between the months of November 2008 and March 2009. In this study, PEMS were used to collect particles on filters, which were analyzed for tracers for woodsmoke, including levoglucosan, elemental carbon, and organic carbon. Aethalometers measured black carbon, an indicator of carbon combustion.Additional PEMS and aethalometers were placed inside one residential home to better understand infiltration of woodsmoke.To model the infiltration of woodsmoke, the Lawrence Berkeley National Laboratory Air Infiltration Model was used. The home of interest was chosen such that indoor sources of particulate matter (PM) were minimal. This ensures that all PM v measured indoors was from outdoor sources, namely household chimneys. While indoor sources such as indoor fires and resuspension of particles were of concern, homes were chosen to minimize these sources.To investigate the infiltration parameters, four different solution techniques were used. Two of the solution techniques used SOLVER, a Microsoft Excel program, to minimize the sum of squared differences between calculated indoor concentrations and measured indoor concentrations, with all three parameters (air exchange rate, penetration, and deposition) as independent variables. The other two solution techniques used the Air Exchange Rate (AER) model from Lawrence Berkeley National Laboratory (LBNL) (Sherman & Grimsrud, 1980) and then used SOLVER to calculate deposition rate and penetration factor.Solution techniques 1 and 3, which used SOLVER to find all three parameters, had average penetration factors of 0.94 and 0.97 respectively, while solution techniques 2 and 4, which used the LBNL AER model had average penetration factors of 0.85 and 0.78 respectively. The deposition rates for solution techniques 1,2,3, and 4 were 0.10, 0.07, 0.08, and 0.04 hr -1 respectively. The air exchange rates varied throughout the study and ranged from 0.1 to 0.7 hr -1 . The average indoor/outdoor ratio was also found to be 0.75.The aerosols derived from the study samples were found to have light absorption properties that were heavily spectrally dependent, which is consistent with expectations for wood combustion aerosols. Conversely, traffic derived aerosols are not found to be heavily spectrally dependent and follow the power law relationship of " -1 whereas our samples followed " -1.7 acr...
In many communities, residential wood burning is the source of a significant fraction of wintertime PM2.5 and produces exposures to nearby residents inside their homes. To evaluate the magnitude of this effect, black carbon particles were measured as a proxy for woodsmoke indoors and outdoors in a community where residential woodsmoke is the only significant particle source. Thirteen indoor/outdoor measurement pairs were obtained at 4 different residences and showed an average indoor/outdoor concentration ratio of 0.78 ± 0.21 for residences without indoor generation. In addition, a time dependent mass balance model was used in conjunction with aethalometer measurements taken over 16 nights at a single residence to estimate an average air exchange rate of 0.26 ± 0.08 h −1 , an average deposition loss rate of 0.08 ± 0.03 h −1 , and an average penetration factor of 0.97 ± 0.02. Using a mechanistic approach which utilizes these average values in a steady state model, the predicted average infiltration factor was 0.74 for the residence studied. The high values for both measured I/O ratio and modeled infiltration factor show that residential environments provide inhabitants with relatively little protection from recently generated wood smoke particles.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.