Spatial variation of PM2.5 chemical species and source-apportioned mass concentrations in New York City

被引:170
作者
Ito, K [1 ]
Xue, N
Thurston, G
机构
[1] NYU, Sch Med, Nelson Inst Environm Med, Tuxedo Pk, NY 10987 USA
[2] Albert Einstein Coll Med, Dept Epidemiol & Populat Hlth, Div Biostat, Bronx, NY 10461 USA
关键词
D O I
10.1016/j.atmosenv.2004.02.063
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 mum 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. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:5269 / 5282
页数:14
相关论文
共 18 条
[1]  
[Anonymous], EPA600P95001
[2]   ON THE PROPAGATION OF ERROR IN AIR-POLLUTION MEASUREMENTS [J].
EVANS, JS ;
COOPER, DW ;
KINNEY, P .
ENVIRONMENTAL MONITORING AND ASSESSMENT, 1984, 4 (02) :139-153
[3]   OBLIQUE FACTOR ANALYTIC SOLUTIONS BY ORTHOGONAL TRANSFORMATIONS [J].
HARRIS, CW ;
KAISER, HF .
PSYCHOMETRIKA, 1964, 29 (04) :347-362
[4]   Application of SAFER model to the Los Angeles PM10 data [J].
Kim, BM ;
Henry, RC .
ATMOSPHERIC ENVIRONMENT, 2000, 34 (11) :1747-1759
[5]   Association of fine particulate matter from different sources with daily mortality in six US cities [J].
Laden, F ;
Neas, LM ;
Dockery, DW ;
Schwartz, J .
ENVIRONMENTAL HEALTH PERSPECTIVES, 2000, 108 (10) :941-947
[6]   Source apportionment of phoenix PM2.5 aerosol with the Unmix receptor model [J].
Lewis, CW ;
Norris, GA ;
Conner, TL ;
Henry, RC .
JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, 2003, 53 (03) :325-338
[7]   Associations between air pollution and mortality in Phoenix, 1995-1997 [J].
Mar, TF ;
Norris, GA ;
Koenig, JQ ;
Larson, TV .
ENVIRONMENTAL HEALTH PERSPECTIVES, 2000, 108 (04) :347-353
[8]   ASSOCIATIONS BETWEEN 1980 UNITED-STATES MORTALITY-RATES AND ALTERNATIVE MEASURES OF AIRBORNE PARTICLE CONCENTRATION [J].
OZKAYNAK, H ;
THURSTON, GD .
RISK ANALYSIS, 1987, 7 (04) :449-461
[9]  
OZKAYNAK H, 1996, ASS DAILY MORTALITY
[10]   ANALYSIS OF DIFFERENT MODES OF FACTOR-ANALYSIS AS LEAST-SQUARES FIT PROBLEMS [J].
PAATERO, P ;
TAPPER, U .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1993, 18 (02) :183-194