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SPATIAL VARIATION OF PM 2.5 CHEMICAL SPECIES AND SOURCE-APPORTIONED MASS CONCENTRATIONS IN NEW YORK CITY. (R827351C001)
Citation:
Ito, K., N. Xue, AND G. D. Thurston. SPATIAL VARIATION OF PM 2.5 CHEMICAL SPECIES AND SOURCE-APPORTIONED MASS CONCENTRATIONS IN NEW YORK CITY. (R827351C001). ATMOSPHERIC ENVIRONMENT (2004).
Description:
Particulate matter (PM) is a chemically non-specific pollutant, and may originate or be derived from different emission source types. Thus, its toxicity may well vary depending on its chemical composition. If the PM toxicity could be determined based on source types, the regulation of PM may be implemented more effectively. A large number of monitors began collecting PM less than 2.5 μm in diameter (PM2.5) mass samples for subsequent chemical speciation starting 2000–2001 in the US. The data from this chemical speciation network can be useful for source-oriented evaluations of PM health effects. However, there are several issues that need to be considered in the analysis and interpretation of these data. One major issue is a monitor's representation of regional, sub-regional, and local air pollution exposures to the population in a city or metropolitan area. Because health outcomes in time-series air pollution epidemiological studies are aggregated over a wide geographical area, regional PM pollution may have smaller errors in exposure estimates than more spatially varying local pollution. However, the relative strength of association between source-apportioned PM and health outcomes may not be interpretable as the relative causal role of the source types. To our knowledge, there has not yet been a systematic and quantitative evaluation of this issue. In this study, we attempt to evaluate this issue by analyzing newly available PM2.5 speciation data from three monitors (a few miles apart) in New York City during 2001–2002. The strongest temporal correlations across the three monitors were found for the individual PM components that are related to secondary aerosols (e.g., S, NH4). We also conducted source-apportionment of the data using absolute principal component analysis and positive matrix factorization. We identified four major source/pollution types: (1) secondary (largely regional) aerosols; (2) soil; (3) traffic-related; and (4) residual oil burning/incineration, in each of the three monitors. The estimated source-apportioned PM2.5 mass showed generally the highest monitor-to-monitor correlation for the secondary aerosol factor (r range: 0.72–0.93). The correlation for the more localized traffic-related factor was more variable (r range: 0.26–0.95). The estimated mean PM2.5 mass contributions by source/pollution type across the monitors varied least for the secondary aerosol factor. The extent of variability in the source-apportioned PM2.5 mass by the monitor was comparable to that from the difference due to the two source-apportionment techniques used. The implication of the results of our study is that a source-oriented evaluation of PM health effects needs to take into consideration the uncertainty associated with spatial representative of the species measured at a single monitor.