Characterization of submicron aerosols in the urban outflow of the central Pearl River Delta region of China

Submicron aerosol particles （with aerody- namic diameters less than 1 pm, PM1） were sampled and measured in Heshan, an urban outflow site of Guangzhou megacity in Pearl River Delta in South China, using an Aerodyne High-Resolution Time-of-Flight Aerosol Mass Spectrometer （HR-ToF-AMS） in November 2010 during 2010 Guangzhou Asian Games. The mean PM~ mass concentration measured was 47.9 ± 17.0 μg.m3 during the campaign, with organic aerosol （OA） and sulfate being the two dominant species, accounting for 36.3% and 20.9% of the total mass, respectively, followed by black carbon （17.1%, measured by an aethalometer）, nitrate （12.9%）, ammonium （9.6%） and chloride （3.1%）. The average size distributions of the species （except black carbon） were dominated by an accumulation mode peaking at -550 nm. Calculations based on high-resolution organic mass spectrum showed that, C, H, O and N on average contributed 58.1%, 7.3%, 30.7%, and 3.9% to the total organic mass, respectively. The average ratio of organic mass over organic carbon mass （OM/OC） was 1.73 ± 0.08. Four components of OA were identified by the Positive Matrix Factorization （PMF） analysis, including a hydro- carbon-like （HOA）, a biomass burning （BBOA） and two oxygenated （SV-OOA and LV-OOA） organic aerosol components, which on average accounted for 18.0%, 14.3%, 28.8% and 38.9% of the total organic mass, respectively.

Single particle analysis of ambient aerosols in Shanghai during the World Exposition,2010:two case studies

ATSI Model 3800 aerosol time-of-flight mass spectrometer(ATOFMS)was deployed for single-particle analysis in Shanghai during theWorld Exposition(EXPO),2010.Measurements on two extreme cases:polluted day(1st May)and clean day(25th September)were compared to show how meteorological conditions affected the concentration and composition of ambient aerosols.Mass spectra of 90496 and 50407 particles were analyzed respectively during the two sampling periods.The ART-2a neural network algorithm was applied to sort the collected particles.Seven major classes of particles were obtained:dust,sea salt,industrial,biomass burning,organic carbon(OC),elementary carbon(EC),and NH4-rich particles.Number concentration of ambient aerosols showed a strong anti-correlation with the boundary layer height variation.The external mixing states of aerosols were quite different during two sampling periods because of different air parcel trajectories.Number fraction of biomass burning particles(43.3%)during polluted episode was much higher than that(21.6%)of clean time.Air parcels from the East China Sea on clean day diluted local pollutant concentration and increased the portion of sea salt particle dramatically(13.3%).The large contribution of biomass burning particles in both cases might be an indication of a constant regional background of biomass burning emission.Mass spectrum analysis showed that chemical compositions and internal mixing states of almost all the particle types were more complicate during polluted episode compared with those observed in clean time.Strong nitrate signals in the mass spectra suggested that most of the particles collected on polluted day had gone through some aging processes before reaching the sampling site.