Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation
A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cui, Hongyang [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015transfer abstract |
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| Schlagwörter: |
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| Umfang: |
10 |
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| Übergeordnetes Werk: |
Enthalten in: The internal pudendal artery turnover (IPAT) flap: A new, simple and reliable technique for perineal reconstruction - Nassar, M.K. ELSEVIER, 2021, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:116 ; year:2015 ; pages:262-271 ; extent:10 |
| Links: |
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| DOI / URN: |
10.1016/j.atmosenv.2015.06.054 |
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ELV018799213 |
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| 520 | |a A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. | ||
| 520 | |a A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. | ||
| 650 | 7 | |a WRF/Chem modeling |2 Elsevier | |
| 650 | 7 | |a Observation data analysis |2 Elsevier | |
| 650 | 7 | |a PM2.5 |2 Elsevier | |
| 650 | 7 | |a Source apportionment |2 Elsevier | |
| 700 | 1 | |a Chen, Weihua |4 oth | |
| 700 | 1 | |a Dai, Wei |4 oth | |
| 700 | 1 | |a Liu, Huan |4 oth | |
| 700 | 1 | |a Wang, Xuemei |4 oth | |
| 700 | 1 | |a He, Kebin |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Nassar, M.K. ELSEVIER |t The internal pudendal artery turnover (IPAT) flap: A new, simple and reliable technique for perineal reconstruction |d 2021 |g Amsterdam [u.a.] |w (DE-627)ELV00656139X |
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10.1016/j.atmosenv.2015.06.054 doi GBVA2015019000012.pica (DE-627)ELV018799213 (ELSEVIER)S1352-2310(15)30195-3 DE-627 ger DE-627 rakwb eng 550 690 550 DE-600 690 DE-600 610 VZ 44.65 bkl Cui, Hongyang verfasserin aut Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. WRF/Chem modeling Elsevier Observation data analysis Elsevier PM2.5 Elsevier Source apportionment Elsevier Chen, Weihua oth Dai, Wei oth Liu, Huan oth Wang, Xuemei oth He, Kebin oth Enthalten in Elsevier Science Nassar, M.K. ELSEVIER The internal pudendal artery turnover (IPAT) flap: A new, simple and reliable technique for perineal reconstruction 2021 Amsterdam [u.a.] (DE-627)ELV00656139X volume:116 year:2015 pages:262-271 extent:10 https://doi.org/10.1016/j.atmosenv.2015.06.054 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.65 Chirurgie VZ AR 116 2015 262-271 10 045F 550 |
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10.1016/j.atmosenv.2015.06.054 doi GBVA2015019000012.pica (DE-627)ELV018799213 (ELSEVIER)S1352-2310(15)30195-3 DE-627 ger DE-627 rakwb eng 550 690 550 DE-600 690 DE-600 610 VZ 44.65 bkl Cui, Hongyang verfasserin aut Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. WRF/Chem modeling Elsevier Observation data analysis Elsevier PM2.5 Elsevier Source apportionment Elsevier Chen, Weihua oth Dai, Wei oth Liu, Huan oth Wang, Xuemei oth He, Kebin oth Enthalten in Elsevier Science Nassar, M.K. ELSEVIER The internal pudendal artery turnover (IPAT) flap: A new, simple and reliable technique for perineal reconstruction 2021 Amsterdam [u.a.] (DE-627)ELV00656139X volume:116 year:2015 pages:262-271 extent:10 https://doi.org/10.1016/j.atmosenv.2015.06.054 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.65 Chirurgie VZ AR 116 2015 262-271 10 045F 550 |
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10.1016/j.atmosenv.2015.06.054 doi GBVA2015019000012.pica (DE-627)ELV018799213 (ELSEVIER)S1352-2310(15)30195-3 DE-627 ger DE-627 rakwb eng 550 690 550 DE-600 690 DE-600 610 VZ 44.65 bkl Cui, Hongyang verfasserin aut Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. WRF/Chem modeling Elsevier Observation data analysis Elsevier PM2.5 Elsevier Source apportionment Elsevier Chen, Weihua oth Dai, Wei oth Liu, Huan oth Wang, Xuemei oth He, Kebin oth Enthalten in Elsevier Science Nassar, M.K. ELSEVIER The internal pudendal artery turnover (IPAT) flap: A new, simple and reliable technique for perineal reconstruction 2021 Amsterdam [u.a.] (DE-627)ELV00656139X volume:116 year:2015 pages:262-271 extent:10 https://doi.org/10.1016/j.atmosenv.2015.06.054 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.65 Chirurgie VZ AR 116 2015 262-271 10 045F 550 |
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10.1016/j.atmosenv.2015.06.054 doi GBVA2015019000012.pica (DE-627)ELV018799213 (ELSEVIER)S1352-2310(15)30195-3 DE-627 ger DE-627 rakwb eng 550 690 550 DE-600 690 DE-600 610 VZ 44.65 bkl Cui, Hongyang verfasserin aut Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. WRF/Chem modeling Elsevier Observation data analysis Elsevier PM2.5 Elsevier Source apportionment Elsevier Chen, Weihua oth Dai, Wei oth Liu, Huan oth Wang, Xuemei oth He, Kebin oth Enthalten in Elsevier Science Nassar, M.K. ELSEVIER The internal pudendal artery turnover (IPAT) flap: A new, simple and reliable technique for perineal reconstruction 2021 Amsterdam [u.a.] (DE-627)ELV00656139X volume:116 year:2015 pages:262-271 extent:10 https://doi.org/10.1016/j.atmosenv.2015.06.054 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.65 Chirurgie VZ AR 116 2015 262-271 10 045F 550 |
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10.1016/j.atmosenv.2015.06.054 doi GBVA2015019000012.pica (DE-627)ELV018799213 (ELSEVIER)S1352-2310(15)30195-3 DE-627 ger DE-627 rakwb eng 550 690 550 DE-600 690 DE-600 610 VZ 44.65 bkl Cui, Hongyang verfasserin aut Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. WRF/Chem modeling Elsevier Observation data analysis Elsevier PM2.5 Elsevier Source apportionment Elsevier Chen, Weihua oth Dai, Wei oth Liu, Huan oth Wang, Xuemei oth He, Kebin oth Enthalten in Elsevier Science Nassar, M.K. ELSEVIER The internal pudendal artery turnover (IPAT) flap: A new, simple and reliable technique for perineal reconstruction 2021 Amsterdam [u.a.] (DE-627)ELV00656139X volume:116 year:2015 pages:262-271 extent:10 https://doi.org/10.1016/j.atmosenv.2015.06.054 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.65 Chirurgie VZ AR 116 2015 262-271 10 045F 550 |
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Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation |
| abstract |
A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. |
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A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. |
| abstract_unstemmed |
A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRD region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOX, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRD region and the pollutants transported from the areas north of PRD region both played important roles. |
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