scholarly journals PM2.5 Source Apportionment Applying Material Balance and Receptor Models in the MAMC

10.5772/19028 ◽  
2011 ◽  
Author(s):  
V. Mugica ◽  
R. Vallesa ◽  
J. Aguilar ◽  
J. Figueroa ◽  
F. Mugic
Keyword(s):  
Source Apportionment ◽  
Material Balance ◽  
Receptor Models

A comparison between two receptor models to determine the source apportionment of atmospheric pollutants

2006 ◽  
Vol 17 (5) ◽  
pp. 507-516 ◽  
Author(s):  
Maurizio Caselli ◽  
Gianluigi de Gennaro ◽  
Pierina Ielpo
Keyword(s):  
Source Apportionment ◽  
Atmospheric Pollutants ◽  
Receptor Models

scholarly journals Source Apportionment of PM2.5 in the Metropolitan Area of Costa Rica Using Receptor Models

2013 ◽  
Vol 03 (04) ◽  
pp. 562-575 ◽  
Author(s):  
Jorge Herrera Murillo ◽  
Susana Rodríguez Roman ◽  
José Félix Rojas Marín ◽  
Beatriz Cardenas
Keyword(s):  
Costa Rica ◽  
Source Apportionment ◽  
Metropolitan Area ◽  
Receptor Models

scholarly journals Introduction and Application of the PMF Model to Estimate the Source Apportionment of PM2.5 at Various Sites

1970 ◽  
Vol 8 (3) ◽  
pp. 25-31 ◽  
Author(s):  
Injo Hwang
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Receptor Site ◽  
Ambient Air ◽  
Receptor Modeling ◽  
Ambient Air Quality ◽  
Receptor Models ◽  
Pmf Model ◽  
Source Contributions ◽  
Reduction Strategies

To manage ambient air quality and establish effective emissions reduction strategies, it is necessary to identify sources and to apportion the ambient PM mass. To do so, receptor models have been developed that analyze various measured properties of the pollutants at the receptor site, identify the sources, and estimate their contributions. Receptor modeling is based on a mathematical model that analyzes the physicochemical properties of gaseous and/or particulate pollutants at various atmospheric receptors. Among the multivariate receptor models used for PM source identification and apportionment, positive matrix factorization (PMF) has been developed by Paatero in 1997. PMF have been developed for providing a new approach to multivariate receptor modeling based on explicit least-squares technique. Also, PMF shown to be a powerful technique relative to traditional multivariate receptor models. PMF has been implemented in two different algorithms: PMF2 (or PMF3) and the multilinear engine (ME). Since the release of PMF2 and ME, these programs have been successfully applied to assess ambient PM source contributions at many locations in the world. In this study, I would like to introduce about outline of the PMF model and application of the PMF model to estimate the source apportionment of ambient PM2.5 at various sampling sites in USA and Korea. This study suggests the possible role for maintain and manage ambient air quality and achieve reasonable air pollution strategies. DOI: http://dx.doi.org/10.3126/jie.v8i3.5928 JIE 2011; 8(3): 25-31

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