Source apportionment of particulate matter in China

2013 ◽  
Author(s):  
Baoqing Wang ◽  
Deqing Wang ◽  
Qitao Ma ◽  
Shuai Yin ◽  
Shu Yao
Keyword(s):  
Particulate Matter ◽  
Source Apportionment

scholarly journals Organic aerosol source apportionment by offline-AMS over a full year in Marseille

2017 ◽  
Author(s):  
Carlo Bozzetti ◽  
Imad El Haddad ◽  
Dalia Salameh ◽  
Kaspar Rudolf Daellenbach ◽  
Paola Fermo ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Mediterranean Sea ◽  
Source Apportionment ◽  
Organic Aerosol ◽  
Aerodynamic Diameter ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Aerosol Source

Abstract. We investigated the seasonal trends of OA sources affecting the air quality of Marseille (France) which is the largest harbor of the Mediterranean Sea. This was achieved by measurements of nebulized filter extracts using an aerosol mass spectrometer (offline-AMS). PM2.5 (particulate matter with an aerodynamic diameter

scholarly journals Source Apportionment of Fine and Coarse Particulate Matter in Industrial Areas of Kaduna, Northern Nigeria

2016 ◽  
Vol 16 (5) ◽  
pp. 1179-1190 ◽  
Author(s):  
Sunday A. Orogade ◽  
Kayode O. Owoade ◽  
Philip K. Hopke ◽  
Donatus B. Adie ◽  
Abubakar Ismail ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Northern Nigeria ◽  
Industrial Areas ◽  
Coarse Particulate Matter

Source apportionment of airborne particulate matter using inorganic and organic species as tracers

2012 ◽  
Vol 55 ◽  
pp. 525-532 ◽  
Author(s):  
Yungang Wang ◽  
Philip K. Hopke ◽  
Xiaoyan Xia ◽  
Oliver V. Rattigan ◽  
David C. Chalupa ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Airborne Particulate Matter ◽  
Airborne Particulate ◽  
Organic Species ◽  
Inorganic And Organic

scholarly journals Fine particulate matter source apportionment using a hybrid chemical transport and receptor model approach

2013 ◽  
Vol 13 (10) ◽  
pp. 26657-26698
Author(s):  
Y. Hu ◽  
S. Balachandran ◽  
J. E. Pachon ◽  
J. Baek ◽  
C. Ivey ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Hybrid Method ◽  
Fine Particulate Matter ◽  
Hybrid Approach ◽  
Chemical Transport ◽  
Measurement Information ◽  
Analysis Tool ◽  
Receptor Model ◽  
Fine Particulate

Abstract. A hybrid fine particulate matter (PM2.5) source apportionment approach based on a receptor-model (RM) species balance and species specific source impacts from a chemical transport model (CTM) equipped with a sensitivity analysis tool is developed to provide physically- and chemically-consistent relationships between source emissions and receptor impacts. This hybrid approach enhances RM results by providing initial estimates of source impacts from a much larger number of sources than are typically used in RMs, and provides source-receptor relationships for secondary species. Further, the method addresses issues of source collinearities, and accounts for emissions uncertainties. Hybrid method results also provide information on the resulting source impact uncertainties. We apply this hybrid approach to conduct PM2.5 source apportionment at Chemical Speciation Network (CSN) sites across the US. Ambient PM2.5 concentrations at these receptor sites were apportioned to 33 separate sources. Hybrid method results led to large changes of impacts from CTM estimates for sources such as dust, woodstove, and other biomass burning sources, but limited changes to others. The refinements reduced the differences between CTM-simulated and observed concentrations of individual PM2.5 species by over 98% when using a weighted least squared error minimization. The rankings of source impacts changed from the initial estimates, revealing that CTM-only results should be evaluated with observations. Assessment with RM results at six US locations showed that the hybrid results differ somewhat from commonly resolved sources. The hybrid method also resolved sources that typical RM methods do not capture without extra measurement information on unique tracers. The method can be readily applied to large domains and long (such as multi-annual) time periods to provide source impact estimates for management- and health-related studies.

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