Evaluation of Regional-Scale Receptor Modeling

被引:18
作者
Lowenthal, Douglas H. [1 ]
Watson, John G. [1 ]
Koracin, Darko [1 ]
Chen, L. -W. Antony [1 ]
Dubois, David [1 ]
Vellore, Ramesh [1 ]
Kumar, Naresh [2 ]
Knipping, Eladio M. [2 ]
Wheeler, Neil [3 ]
Craig, Kenneth [4 ]
Reid, Stephen [4 ]
机构
[1] Desert Res Inst, Reno, NV 89512 USA
[2] Elect Power Res Inst, Palo Alto, CA USA
[3] Sonoma Technol Inc, Atmospher Modeling & Informat Syst, Petaluma, CA USA
[4] Sonoma Technol Inc, Emiss Assessment, Petaluma, CA USA
关键词
POSITIVE MATRIX FACTORIZATION; SOURCE APPORTIONMENT; QUALITY MODEL; GRAND-CANYON; AIR; AEROSOL; POLLUTION; EXTINCTION; SULFUR;
D O I
10.3155/1047-3289.60.1.26
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The ability of receptor models to estimate regional contributions to fine particulate matter (PM2.5) was assessed with synthetic, speciated datasets at Brigantine National Wildlife Refuge (BRIG) in New Jersey and Great Smoky Mountains National Park (GRSM) in Tennessee. Synthetic PM2.5 chemical concentrations were generated for the summer of 2002 using the Community Multiscale Air Quality (CMAQ) model and chemically speciated PM2.5 source profiles from the U.S. Environmental Protection Agency (EPA)'s SPECIATE and Desert Research Institute's source profile databases. CMAQ estimated the "true" contributions of seven regions in the eastern United States to chemical species concentrations and individual source contributions to primary PM2.5 at both sites. A seven-factor solution by the positive matrix factorization (PMF) receptor model explained approximately 99% of the variability in the data at both sites. At BRIG, PMF captured the first four major contributing sources (including a secondary sulfate factor), although diesel and gasoline vehicle contributions were not separated. However, at GRSM, the resolved factors did not correspond well to major PM2.5 sources. There were no correlations between PMF factors and regional contributions to sulfate at either site. Unmix produced five- and seven-factor solutions, including a secondary sulfate factor, at both sites. Some PMF factors were combined or missing in the Unmix factors. The trajectory mass balance regression (TMBR) model apportioned sulfate concentrations to the seven source regions using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) trajectories based on Meteorological Model Version 5 (MM5) and Eta Data Simulation System (EDAS) meteorological input. The largest estimated sulfate contributions at both sites were from the local regions; this agreed qualitatively with the true regional apportionments. Estimated regional contributions depended on the starting elevation of the trajectories and on the meteorological input data.
引用
收藏
页码:26 / 42
页数:17
相关论文
共 71 条
[22]   Multivariate receptor modeling by N-dimensional edge detection [J].
Henry, RC .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2003, 65 (02) :179-189
[23]   CURRENT FACTOR-ANALYSIS RECEPTOR MODELS ARE ILL-POSED [J].
HENRY, RC .
ATMOSPHERIC ENVIRONMENT, 1987, 21 (08) :1815-1820
[24]   Multivariate receptor models - current practice and future trends [J].
Henry, RC .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2002, 60 (1-2) :43-48
[25]   REVIEW OF RECEPTOR MODEL FUNDAMENTALS [J].
HENRY, RC ;
LEWIS, CW ;
HOPKE, PK ;
WILLIAMSON, HJ .
ATMOSPHERIC ENVIRONMENT, 1984, 18 (08) :1507-1515
[26]  
HENRY RC, 1986, T RECEPTOR METHODS S, P68
[27]  
HENRY RC, 1997, CHEMOM INTELL LAB SY, V48, P91
[28]  
HENRY RC, 1977, P 5 C PROB STAT ATM
[29]  
HOPKE P, 2001, J AEROSOL SCI, V32, P363
[30]  
Hopke P.K., 1985, RECEPTOR MODELING EN