2004
DOI: 10.1016/j.atmosenv.2004.04.030
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Receptor modeling of ambient VOC at Santiago, Chile

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Cited by 93 publications
(42 citation statements)
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“…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%
“…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%
“…Over the last decade, this source receptor approach has been intensively used in urban areas (e.g., Baudic et al, 2016;Salameh et al, 2016;Yuan et al, 2012) and in remote/rural environments Leuchner et al, 2015;Michoud et al, 2017;Sauvage et al, 2009). Other receptor models such as principal component analysis/absolute principal component scores (PCA/APCSs) (Guo et al, 2007), UNMIX (Jorquera and Rappenglück, 2004) and chemical mass balance (CMB) (Badol et al, 2008) have been previously used in VOC source apportionment. Studies show that PMF models are more efficient in identifying source profiles (Jorquera and Rappenglück, 2004).…”
Section: Introductionmentioning
confidence: 99%
“…Other receptor models such as principal component analysis/absolute principal component scores (PCA/APCSs) (Guo et al, 2007), UNMIX (Jorquera and Rappenglück, 2004) and chemical mass balance (CMB) (Badol et al, 2008) have been previously used in VOC source apportionment. Studies show that PMF models are more efficient in identifying source profiles (Jorquera and Rappenglück, 2004). Yuan et al (2012) stressed the importance of the different reactivity of VOCs and the impact of photochemical aging on the interpretability of the resolved factors as source profiles that have not been considered in most of the studies applying PMF.…”
Section: Introductionmentioning
confidence: 99%
“…17,18 Both VOCs and NOx are precursors of ground-level ozone, which can interfere with lung function and aggravate diseases such as asthma, chronic bronchitis, and emphysema. High levels of SOx or PM can also irritate the respiratory system, contribute to respiratory illness, and aggravate asthma and existing heart and lung disease.…”
Section: Discussionmentioning
confidence: 99%