scholarly journals Understanding primary and secondary sources of ambient carbonyl compounds in Beijing using the PMF model

2013 ◽  
Vol 13 (6) ◽  
pp. 15749-15781
Author(s):  
W. T. Chen ◽  
M. Shao ◽  
S. H. Lu ◽  
M. Wang ◽  
L. M. Zeng
Keyword(s):  
Source Apportionment ◽  
Carbonyl Compounds ◽  
Anthropogenic Sources ◽  
Positive Matrix ◽  
Secondary Sources ◽  
Pmf Model ◽  
Five Factors ◽  
Secondary Formation ◽  
Volatile Organic ◽  
Peking University

Abstract. Carbonyls are important intermediates in atmospheric photochemistry. To determine the relative contributions of primary and secondary carbonyl sources in Beijing, carbonyls and other trace gases were measured at Peking University in winter and summer. The Positive Matrix Factorization (PMF) model was used for source apportionment. As volatile organic compounds (VOCs) will undergo photochemical processes in the atmosphere, and such processes may interfere with factors identification, the relationships between the contributions of the resolved PMF factors to each non-methane hydrocarbon (NMHC) species and its kOH value were used to distinguish between photochemically aged factors and fresh factors. As the result of PMF, five factors were resolved in winter, and two of them were identified as sources of photochemically aged emissions. In summer, four factors were resolved, including an aged factor. Carbonyls in the aged factors were simulated by NMHCs consumption and the corresponding carbonyl production yields, and the simulated abundances agreed well with the results obtained by PMF. The source apportionment results indicated that secondary formation was the major source of carbonyls in both seasons, with the contribution of 51.2% and 46.0%. For the three major carbonyl species, primary anthropogenic sources contributed 28.9% and 32.3% to ambient formaldehyde, 53.7% and 41.6% to acetaldehyde, 68.1% and 56.2% to acetone in winter and summer, respectively.

scholarly journals Understanding primary and secondary sources of ambient carbonyl compounds in Beijing using the PMF model

2014 ◽  
Vol 14 (6) ◽  
pp. 3047-3062 ◽  
Author(s):  
W. T. Chen ◽  
M. Shao ◽  
S. H. Lu ◽  
M. Wang ◽  
L. M. Zeng ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Carbonyl Compounds ◽  
Anthropogenic Sources ◽  
Urban Site ◽  
Positive Matrix ◽  
Secondary Sources ◽  
Pmf Model ◽  
Five Factors ◽  
Secondary Formation ◽  
Volatile Organic

Abstract. Carbonyl compounds are important intermediates in atmospheric photochemistry. To explore the relative contributions of primary and secondary carbonyl sources, carbonyls and other volatile organic compounds (VOCs) were measured at an urban site in both winter and summer in Beijing. The positive matrix factorization (PMF) model was used for source apportionment of VOCs. As VOCs undergo photochemical processes in the atmosphere, and such processes may interfere with factor identification, the relationships between the contributions of the resolved PMF factors to each non-methane hydrocarbon (NMHC) species and its kOH value were used to distinguish fresh factors and photochemically aged factors. As the result of PMF, five factors were resolved in winter, and two of them were identified as photochemically aged emissions. In summer, four factors were resolved, including one aged factor. Carbonyls abundances from aged factors were simulated by VOCs consumption and the corresponding carbonyl production yields, and the simulated abundances agreed well with the results obtained by the PMF model. The source apportionment results indicated that secondary formation was the major source of carbonyls in both winter and summer, with the respective contributions of 51.2% and 46.0%. For the three major carbonyl species, primary anthropogenic sources contributed 28.9% and 32.3% to ambient formaldehyde, 53.7% and 41.6% to acetaldehyde, 68.1% and 56.2% to acetone in winter and summer, respectively.

scholarly journals An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 390 ◽  
Author(s):  
Fenjuan Wang ◽  
Zhenyi Zhang ◽  
Costanza Acciai ◽  
Zhangxiong Zhong ◽  
Zhaokai Huang ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Source Apportionment ◽  
Correlation Coefficient ◽  
Organic Compounds ◽  
Industrial Emissions ◽  
Integrated Method ◽  
Pmf Model ◽  
Volatile Organic ◽  
Measurement Period

The positive matrix factorization (PMF) model is widely used for source apportionment of volatile organic compounds (VOCs). The question about how to select the proper number of factors, however, is rarely studied. In this study, an integrated method to determine the most appropriate number of sources was developed and its application was demonstrated by case study in Wuhan. The concentrations of 103 ambient volatile organic compounds (VOCs) were measured intensively using online gas chromatography/mass spectrometry (GC/MS) during spring 2014 in an urban residential area of Wuhan, China. During the measurement period, the average temperature was approximately 25 °C with very little domestic heating and cooling. The concentrations of the most abundant VOCs (ethane, ethylene, propane, acetylene, n-butane, benzene, and toluene) in Wuhan were comparable to other studies in urban areas in China and other countries. The newly developed integrated method to determine the most appropriate number of sources is in combination of a fixed minimum threshold value for the correlation coefficient, the average weighted correlation coefficient of each species, and the normalized minimum error. Seven sources were identified by using the integrated method, and they were vehicular emissions (45.4%), industrial emissions (22.5%), combustion of coal (14.7%), liquefied petroleum gas (LPG) (9.7%), industrial solvents (4.4%), and pesticides (3.3%) and refrigerants. The orientations of emission sources have been characterized taking into account the frequency of wind directions and contributions of sources in each wind direction for the measurement period. It has been concluded that the vehicle exhaust contribution is greater than 40% distributed in all directions, whereas industrial emissions are mainly attributed to the west southwest and south southwest.

scholarly journals Source Apportionment of PM2.5 in Guangzhou Based on an Approach of Combining Positive Matrix Factorization with the Bayesian Mixing Model and Radiocarbon

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 512
Author(s):  
Tingting Li ◽  
Jun Li ◽  
Hongxing Jiang ◽  
Duohong Chen ◽  
Zheng Zong ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Matrix Factorization ◽  
Coal Combustion ◽  
Mixing Model ◽  
Positive Matrix ◽  
Traffic Emission ◽  
Bayesian Mixing Model ◽  
Pmf Model ◽  
Aerosol Source ◽  
Biogenic Source

To accurately apportion the sources of aerosols, a combined method of positive matrix factorization (PMF) and the Bayesian mixing model was applied in this study. The PMF model was conducted to identify the sources of PM2.5 in Guangzhou. The secondary inorganic aerosol source was one of the seven main sources in Guangzhou. Based on stable isotopes of oxygen and nitrogen (δ15N-NO3− and δ18O-NO3−), the Bayesian mixing model was performed to apportion the source of NO3− to coal combustion, traffic emission and biogenic source. Then the secondary aerosol source was subdivided into three sources according to the discrepancy in source apportionment of NO3− between PMF and Bayesian mixing model results. After secondary aerosol assignment, the six main sources of PM2.5 were traffic emission (30.6%), biomass burning (23.1%), coal combustion (17.7%), ship emission (14.0%), biomass boiler (9.9%) and industrial emission (4.7%). To assess the source apportionment results, fossil/non-fossil source contributions to organic carbon (OC) and element carbon (EC) inferred from 14C measurements were compared with the corresponding results in the PMF model. The results showed that source distributions of EC matched well between those two methods, indicating that the PMF model captured the primary sources well. Probably because of the lack of organic molecular markers to identify the biogenic source of OC, the non-fossil source contribution to OC in PMF results was obviously lower than 14C results. Thus, an indicative organic molecular tracer should be used to identify the biogenic source when accurately apportioning the sources of aerosols, especially in the region with high plant coverage or intense biomass burning.

scholarly journals SoFi, an Igor based interface for the efficient use of the generalized multilinear engine (ME-2) for source apportionment: application to aerosol mass spectrometer data

2013 ◽  
Vol 6 (4) ◽  
pp. 6409-6443 ◽  
Author(s):  
F. Canonaco ◽  
M. Crippa ◽  
J. G. Slowik ◽  
U. Baltensperger ◽  
A. S. H. Prévôt
Keyword(s):  
Source Apportionment ◽  
Mass Spectra ◽  
A Priori ◽  
Aerosol Mass Spectrometer ◽  
Pmf Model ◽  
Aerosol Mass ◽  
Five Factors ◽  
Multilinear Engine ◽  
Constrained Models ◽  
Spectrometer Data

Abstract. Source apportionment using the bilinear model through the multilinear engine (ME-2) was successfully applied to non-refractory organic aerosol (OA) mass spectra collected during winter 2011 and 2012 in Zurich, Switzerland using the aerosol chemical speciation monitor ACSM. Five factors were identified: low-volatility oxygenated OA (LV-OOA), semivolatile oxygenated OA (SV-OOA), hydrocarbon-like OA (HOA), cooking OA (COA) and biomass burning OA (BBOA). A graphical user interface SoFi (Source Finder) was developed at PSI in order to facilitate the testing of different rotational techniques available within the ME-2 engine by providing a priori factor profiles for some or all of the expected factors. ME-2 was used to test the positive matrix factorization (PMF) model, the fully constrained chemical mass balance (CMB) model, and partially constrained models utilizing a values and pulling equations. Within the set of model solutions determined to be environmentally reasonable, BBOA and SV-OOA factor mass spectra and time series showed the greatest variability. This variability represents uncertainty in the model solution and indicates that analysis of model rotations provides a useful approach for assessing the uncertainty of bilinear source apportionment models.

scholarly journals Size-resolved aerosol water-soluble ionic compositions in the summer of Beijing: implication of regional secondary formation

2009 ◽  
Vol 9 (6) ◽  
pp. 23955-23986 ◽  
Author(s):  
S. Guo ◽  
M. Hu ◽  
Z. B. Wang ◽  
J. Slanina ◽  
Y. L. Zhao
Keyword(s):  
Fine Particles ◽  
Secondary Compounds ◽  
Water Soluble ◽  
Rural Site ◽  
Urban Site ◽  
Condensation Process ◽  
Pmf Model ◽  
Secondary Formation ◽  
Aerosol Pollution ◽  
Peking University

Abstract. To characterize aerosol pollution in Beijing, size-resolved aerosols were collected by MOUDIs during CAREBEIJING-2006 field campaign at Peking University (urban site) and Yufa (upwind rural site). Fine particle concentrations (PM1.8 by MOUDI) were 99.8±77.4 μg/m3 and 78.2±58.4 μg/m3, with PM1.8/PM10 ratios of 0.64±0.08 and 0.76±0.08 at PKU and Yufa, respectively, and secondary compounds accounted for more than 50% in fine particles. PMF model was used to resolve the particle modes. Three modes were resolved at Yufa, representing condensation, droplet and coarse mode. However, one more droplet mode with bigger size was resolved, which was considered probably from regional transport. Condensation mode accounted for 10%–60% of the total mass at both sites, indicating it must be taken into account in summer. The formation of sulfate was mainly attributed to in-cloud or aerosol droplet process (PKU 80%, Yufa 70%) and gas condensation process (PKU 14%, Yufa 22%). According to the thermodynamic instability of NH4NO3, size distributions of nitrate were classified as three categories by RH. The existence of Ca(NO3)2 in droplet mode indicated the reaction of HNO3 with crustal particles was also important in fine particles. Linear regression gave a rough estimation that 69% of the PM10 and 87% of the PM1.8 at PKU were regional contributions. Sulfate, ammonium and oxalate were formed regionally, with the regional contributions of 90%, 87% and 95% to PM1.8. Nitrate formation was local dominant. In summary regional secondary formation led to aerosol pollution in the summer of Beijing.

Source apportionment of ambient PM2.5 in two locations in central Tehran using the Positive Matrix Factorization (PMF) model

2018 ◽  
Vol 628-629 ◽  
pp. 672-686 ◽  
Author(s):  
Sina Taghvaee ◽  
Mohammad H. Sowlat ◽  
Amirhosein Mousavi ◽  
Mohammad Sadegh Hassanvand ◽  
Masud Yunesian ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Matrix Factorization ◽  
Positive Matrix Factorization ◽  
Positive Matrix ◽  
Pmf Model

scholarly journals Size-resolved aerosol water-soluble ionic compositions in the summer of Beijing: implication of regional secondary formation

2010 ◽  
Vol 10 (3) ◽  
pp. 947-959 ◽  
Author(s):  
S. Guo ◽  
M. Hu ◽  
Z. B. Wang ◽  
J. Slanina ◽  
Y. L. Zhao
Keyword(s):  
Fine Particles ◽  
Secondary Compounds ◽  
Water Soluble ◽  
Rural Site ◽  
Urban Site ◽  
Condensation Process ◽  
Pmf Model ◽  
Secondary Formation ◽  
Aerosol Pollution ◽  
Peking University

Abstract. To characterize aerosol pollution in Beijing, size-resolved aerosols were collected by MOUDIs during CAREBEIJING-2006 field campaign at Peking University (urban site) and Yufa (upwind rural site). Fine particle concentrations (PM1.8 by MOUDI) were 99.8±77.4 μg/m3 and 78.2±58.4 μg/m3, with PM1.8/PM10 ratios of 0.64±0.08 and 0.76±0.08 at PKU and Yufa, respectively, and secondary compounds accounted for more than 50% in fine particles. PMF model analysis was used to resolve the particle modes. Three modes were resolved at Yufa, representing condensation, droplet and coarse mode. However, one more droplet mode with bigger size was resolved, which was considered probably from regional transport. Condensation mode accounted for 10%–60% of the total mass at both sites, indicating that the gas-to-particle condensation process was important in summer. The formation of sulfate was mainly attributed to in-cloud or aerosol droplet process (PKU 80%, Yufa 70%) and gas condensation process (PKU 14%, Yufa 22%). According to the thermodynamic instability of NH4NO3, size distributions of nitrate were classified as three categories by RH. The existence of Ca(NO3)2 in droplet mode indicated the reaction of HNO3 with crustal particles was also important in fine particles. A rough estimation was given that 69% of the PM10 and 87% of the PM1.8 in Beijing urban were regional contributions. Sulfate, ammonium and oxalate were formed regionally, with the regional contributions of 90%, 87% and 95% to PM1.8. Nitrate formation was local dominant. In summary regional secondary formation led to aerosol pollution in the summer of Beijing.

scholarly journals VOC source apportionment and emission inventory evaluation over the great Athens, comparison with other cities of the Mediterranean basin

2019 ◽  
Author(s):  
Αναστασία Πανοπούλου
Keyword(s):  
Volatile Organic Compounds ◽  
Source Apportionment ◽  
Organic Compounds ◽  
Matrix Factorization ◽  
Mediterranean Basin ◽  
Emission Inventory ◽  
Positive Matrix Factorization ◽  
Positive Matrix ◽  
Volatile Organic ◽  
The Mediterranean Basin

Παρά τις πρωτοβουλίες για τον περιορισμό και μείωση των ατμοσφαιρικών ρύπων, στη Μεσόγειο και τις πόλεις που την περιβάλλουν εξακολουθούν να καταγράφονται υπερβάσεις των προβλεπόμενων οριακών τιμών για την προστασία της υγείας. Παρόλα αυτά, οι μελέτες στα αστικά κέντρα της περιοχής για Πτητικούς Οργανικούς Υδρογονάνθρακες (Volatile Organic Compounds ή VOC), οι οποίοι είναι πρόδρομοι του τροποσφαιρικού όζοντος (Ο3) και των αερολυμάτων, είναι περιορισμένες, ενώ ορισμένες υποδεικνύουν αβεβαιότητες στις παρατηρήσεις που προκύπτουν από συγκρίσεις με βάσεις δεδομένων εκπομπών, σχετιζόμενες με τη συνεισφορά των πηγών εκπομπής και το χημικό τους αποτύπωμα. Συνεπώς, η Αθήνα αποτελεί ιδανική τοποθεσία για μετρήσεις των ενώσεων αυτών, λόγω της μη-καταγραφής των επιπέδων τους τα τελευταία 15 χρόνια (πλην ελάχιστων εξαιρέσεων), της συνεχούς υπέρβασης των ορίων του Ο3 και των αερολυμάτων, καθώς και της αύξησης των εκπομπών από μέχρι πρότινος ασθενείς πηγές ρύπων (π.χ. καύση ξύλου για οικιακή θέρμανση). Στην παρούσα εργασία παρουσιάζονται τα αποτελέσματα μιας 17μηνης καμπάνιας ατμοσφαιρικών μετρήσεων πεδίου για μη-Μεθανικούς Υδρογονάνθρακες (non-Methane Hydrocarbons ή NMHCs) στην Αθήνα (Οκτώβριος 2015 - Φεβρουάριος 2017), στο πλαίσιο του διεθνούς προγράμματος ChArMEX (The Chemistry - Aerosol Mediterranean Experiment). Παράλληλα, εκπονήθηκαν δύο εντατικές περίοδοι εποχικών μετρήσεων (χειμώνα και καλοκαίρι) στον ίδιο σταθμό και επιπλέον, δύο εκστρατείες συλλογής δειγμάτων αέρα σε γνωστές πηγές ρύπανσης (σήραγγα και αστικός σταθμός μετρήσεων).Τα δεδομένα περισσότερων από 40 VOC με 2 έως 16 άτομα άνθρακα, που συλλέχθηκαν κατά τη διάρκεια της καμπάνιας, χρησιμοποιήθηκαν για τη μελέτη της ημερήσιας και εποχιακής διακύμανσης τους σε ετήσια βάση και των παραγόντων που την επηρεάζουν, ενώ τα επίπεδα C2 - C3 NMHCs στην Αθήνα παρουσιάζονται για πρώτη φορά. Η εποχικότητα παρουσιάζει σαφή διακύμανση, με μέγιστο το χειμώνα και ελάχιστο το καλοκαίρι για την πλειονότητα των ενώσεων, ενώ η ημερήσια διακύμανση επηρεάζεται από την ένταση των εκπομπών των πηγών, την ταχύτητα του ανέμου και το ύψος του στρώματος ανάμειξης. Η σύγκριση των αποτελεσμάτων αυτών με παρόμοιες έρευνες σε άλλες πόλεις ανέδειξαν το ρόλο των πηγών στα παρατηρούμενα επίπεδα, όπου για την Αθήνα αυτή η επίδραση είναι πιο έντονη τον χειμώνα. Επιπρόσθετα, τα μονοτερπένια και το ισοπρένιο, γνωστές ενώσεις βιογενούς προέλευσης, παρουσίασαν μία μοναδική μεταβλητότητα επηρεασμένη από ανθρωπογενείς εκπομπές, η οποία δεν λαμβάνεται υπόψη κατά την εκτίμηση της ποιότητας του αέρα. Τέλος, η χρήση του στατιστικού μοντέλου Positive Matrix Factorization (PMF) επέτρεψε τον προσδιορισμό των κύριων πηγών NMHCs στην Αθήνα και την εκτίμηση της συνεισφοράς τους στα επίπεδα των συγκεντρώσεων. Από αυτές, οι εκπομπές από την κίνηση οχημάτων και την οικιακή θέρμανση επικρατούν, ενώ μια δεύτερη PMF προσομοίωση στα δεδομένα της εποχικής εντατικής περιόδου παρατήρησης επιβεβαίωσε τα αποτελέσματα, δίνοντας επίσης πληροφορίες για πρόσθετες πηγές.

Sign in / Sign up

Export Citation Format

Share Document