2006
DOI: 10.1080/02786820600796616
|View full text |Cite
|
Sign up to set email alerts
|

Apportionment of Ambient Primary and Secondary PM2.5During a 2001 Summer Intensive Study at the NETL Pittsburgh Site Using PMF2 and EPA UNMIX

Abstract: Apportionment of primary and secondary pollutants during a July 2001 intensive study at the National Energy Technology Laboratory is reported. PM 2.5 was apportioned into primary and secondary contributions using PMF2, and results were compared with apportionment based on UNMIX 2.3. Input to PMF2 included PM 2.5 mass data from four per 24 hour PC-BOSS filters and TEOM, NO x , NO 2 , O 3 , non-volatile, semi-volatile, and volatile organic material, elemental carbon, sulfate, and PIXE determined trace metals. Ni… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
23
0

Year Published

2006
2006
2024
2024

Publication Types

Select...
8

Relationship

2
6

Authors

Journals

citations
Cited by 14 publications
(25 citation statements)
references
References 22 publications
(41 reference statements)
2
23
0
Order By: Relevance
“…More attention should be paid to semivolatile organic carbon in the future (Fig. 1), considering its secondary nature (Modey et al, 2004;Eatough et al, 2006), and its influence on regional haze (Long et al, 2005). Calculation of the attenuation coefficient of EC and PC is essential for the accurate split of OC and EC, based on the current thermal-optical method.…”
Section: Discussionmentioning
confidence: 99%
“…More attention should be paid to semivolatile organic carbon in the future (Fig. 1), considering its secondary nature (Modey et al, 2004;Eatough et al, 2006), and its influence on regional haze (Long et al, 2005). Calculation of the attenuation coefficient of EC and PC is essential for the accurate split of OC and EC, based on the current thermal-optical method.…”
Section: Discussionmentioning
confidence: 99%
“…139,209,210 It has shown good performance at discriminating between source profiles with similar compositions and the ability to find better, cleaner source profiles than can be obtained with UNMIX. 210,211 Likewise, PMF proved better than other models such as CMB, PCA/ absolute principal component scores (APCS), and UNMIX in extracting the major source profiles using a dataset for PM 2.5 mass concentrations at the U.S. Environmental Protection Agency (EPA) Jefferson Street Supersite in Atlanta, GA. 212 Another important aspect of PMF is that it does not rely on information from the correlation matrix but utilizes a point-by-point least-squares minimization scheme. Recently, CMB and PMF approaches were used to estimate the source contributions to PM 2.5 levels with an organic marker compound and it was found that the impact of direct emissions from biomass combustion can be isolated from the effects of primary emissions on secondary sulfate formation.…”
Section: Pmf Modelmentioning
confidence: 99%
“…that are indicators of atmospheric conversion processes. 139,210,215 The factors identified by PMF must be interpreted as to their probable origin in the atmosphere. Usually this is done by relating the profile of the factor and, if the data are obtained in a short enough time frame, 139,221 on the diurnal patterns of the material associated with the factor.…”
Section: Comparison Of Cmb and Pmf Sourcementioning
confidence: 99%
“…17 These sites were characterized by 1-to 3-day episodes during which PM 2.5 concentrations exceeded 40 g/m 3 . These episodes typically involved high sulfate concentrations, with no diurnal variability, associated with long-range transport of pollutants.…”
Section: Northeastern United Statesmentioning
confidence: 99%