During the past three decades, receptor models have been used to identify and apportion ambient concentrations to sources. A number of groups are employing these methods to provide input into air quality management planning. A workshop has explored the use of resolved source contributions in health effects models. Multiple groups have analyzed particulate composition data sets from Washington, DC and Phoenix, AZ. Similar source profiles were extracted from these data sets by the investigators using different factor analysis methods. There was good agreement among the major resolved source types. Crustal (soil), sulfate, oil, and salt were the sources that were most unambiguously identified (generally highest correlation across the sites). Traffic and vegetative burning showed considerable variability among the results with variability in the ability of the methods to partition the motor vehicle contributions between gasoline and diesel vehicles. However, if the total motor vehicle contributions are estimated, good correspondence was obtained among the results. The source impacts were especially similar across various analyses for the larger mass contributors (e.g., in Washington, secondary sulfate SE ¼ 7% and 11% for traffic; in Phoenix, secondary sulfate SE ¼ 17% and 7% for traffic). Especially important for time-series health effects assessment, the source-specific impacts were found to be highly correlated across analysis methods/researchers for the major components (e.g., mean analysis to analysis correlation, r40.9 for traffic and secondary sulfates in Phoenix and for traffic and secondary nitrates in Washington. The sulfate mean r value is 40.75 in Washington.). Overall, although these intercomparisons suggest areas where further research is needed (e.g., better division of traffic emissions between diesel and gasoline vehicles), they provide support the contention that PM 2.5 mass source apportionment results are consistent across users and methods, and that today's source apportionment methods are robust enough for application to PM 2.5 health effects assessments.
The link between elevated concentrations of ambient particulate matter (PM) and increased mortality has been investigated in numerous studies. Here we analyzed the role of different particle size fractions with respect to total and cardio-respiratory mortality in Erfurt, Germany, between 1995 and 2001. Number concentrations (NC) of PM were measured using an aerosol spectrometer consisting of a Differential Mobility Particle Sizer and a Laser Aerosol Spectrometer to characterize particles between 0.01 and 0.5 and between 0.1 and 2.5 mm, respectively. We derived daily means of particle NC for ultrafine (0.01-0.1 mm) and for fine particles (0.01-2.5 mm). Assuming spherical particles of a constant density, we estimated the mass concentrations (MC) of particles in these size ranges. Concurrently, data on daily total and cardio-respiratory death counts were obtained from local health authorities. The data were analyzed using Poisson Generalized Additive Models adjusting for trend, seasonality, influenza epidemics, day of the week, and meteorology using smooth functions or indicator variables. We found statistically significant associations between elevated ultrafine particle (UFP; diameter: 0.01-0.1 mm) NC and total as well as cardio-respiratory mortality, each with a 4 days lag. The relative mortality risk (RR) for a 9748 cm À3 increase in UFP NC was RR ¼ 1.029 and its 95% confidence interval (CI) ¼ 1.003-1.055 for total mortality. For cardio-respiratory mortality we found: RR ¼ 1.031, 95% CI: 1.003-1.060. No association between fine particle MC and mortality was found. This study shows that UFP, representing fresh combustion particles, may be an important component of urban air pollution associated with health effects.
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.