scholarly journals Long-term measurements of particle number size distributions and the relationships with air mass history and source apportionment in the summer of Beijing

2013 ◽  
Vol 13 (20) ◽  
pp. 10159-10170 ◽  
Author(s):  
Z. B. Wang ◽  
M. Hu ◽  
Z. J. Wu ◽  
D. L. Yue ◽  
L. Y. He ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Particle Number ◽  
Olympic Games ◽  
Size Distributions ◽  
The South ◽  
Particle Volume ◽  
Air Mass ◽  
Combustion Sources

Abstract. A series of long-term and temporary measurements were conducted to study the improvement of air quality in Beijing during the Olympic Games period (8–24 August 2008). To evaluate actions taken to improve the air quality, comparisons of particle number and volume size distributions of August 2008 and 2004–2007 were performed. The total particle number and volume concentrations were 14 000 cm−3 and 37 μm−3 cm−3 in August of 2008, respectively. These were reductions of 41% and 35% compared with mean values of August 2004–2007. A cluster analysis on air mass history and source apportionment were performed, exploring reasons for the reduction of particle concentrations. Back trajectories were classified into five major clusters. Air masses from the south direction are always associated with pollution events during the summertime in Beijing. In August 2008, the frequency of air mass arriving from the south was 1.3 times higher compared to the average of the previous years, which however did not result in elevated particle volume concentrations in Beijing. Therefore, the reduced particle number and volume concentrations during the 2008 Beijing Olympic Games cannot be only explained by meteorological conditions. Four factors were found influencing particle concentrations using a positive matrix factorization (PMF) model. They were identified as local and remote traffic emissions, combustion sources as well as secondary transformation. The reductions of the four sources were calculated to 47%, 44%, 43% and 30%, respectively. The significant reductions of particle number and volume concentrations may attribute to actions taken, focusing on primary emissions, especially related to the traffic and combustion sources.

scholarly journals Long-term measurements of particle number size distributions and the relationships with air mass history and source apportionment in the summer of Beijing

2013 ◽  
Vol 13 (2) ◽  
pp. 5165-5197 ◽  
Author(s):  
Z. B. Wang ◽  
M. Hu ◽  
Z. J. Wu ◽  
D. L. Yue ◽  
L. Y. He ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Particle Number ◽  
Olympic Games ◽  
Size Distributions ◽  
Particle Volume ◽  
Air Mass ◽  
Mean Values ◽  
Combustion Sources

Abstract. A series of long-term and temporary measurements were conducted to study the improvement of air quality in Beijing during Olympic Games period (8–24 August 2008). To evaluate actions taken to improve the air quality, comparisons of particle number and volume size distributions of August 2008 and 2004–2007 were performed. The total particle number and volume concentrations were 14 000 cm−3 and 37 μm3 cm−3 in August of 2008, respectively. These were reductions of 41% and 35% compared with the mean values of August 2004–2007. A cluster analysis on air mass history and source apportionment were performed, exploring reasons of the reduction of particle concentrations. Back trajectories were classified into five major clusters. Air mass from south direction are always associated with pollution events during the summertime of Beijing. In August 2008, the frequency of air mass arriving from south has been twice higher compared to the average of the previous years, these southerly air masses did however not result in elevated particle volume concentrations in Beijing. This result implied that the air mass history was not the key factor, explaining reduced particle number and volume concentrations during the Beijing 2008 Olympic Games. Four factors were found influencing particle concentrations using a Positive matrix factorization (PMF) model. They were identified to local and remote traffic emissions, combustion sources as well as secondary transformation. The reductions of the four sources were calculated to 47%, 44%, 43% and 30%, respectively. The significant reductions of particle number and volume concentrations may attribute to actions taken, focusing on primary emissions, especially related to the traffic and combustion sources.

scholarly journals Size-resolved particle number emissions in Beijing determined from measured particle size distributions

2020 ◽  
Vol 20 (19) ◽  
pp. 11329-11348 ◽  
Author(s):  
Jenni Kontkanen ◽  
Chenjuan Deng ◽  
Yueyun Fu ◽  
Lubna Dada ◽  
Ying Zhou ◽  
...  
Keyword(s):  
Particle Size ◽  
Air Quality ◽  
Particle Number ◽  
Aerosol Particles ◽  
Urban Environments ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Measured Particle

Abstract. The climate and air quality effects of aerosol particles depend on the number and size of the particles. In urban environments, a large fraction of aerosol particles originates from anthropogenic emissions. To evaluate the effects of different pollution sources on air quality, knowledge of size distributions of particle number emissions is needed. Here we introduce a novel method for determining size-resolved particle number emissions, based on measured particle size distributions. We apply our method to data measured in Beijing, China, to determine the number size distribution of emitted particles in a diameter range from 2 to 1000 nm. The observed particle number emissions are dominated by emissions of particles smaller than 30 nm. Our results suggest that traffic is the major source of particle number emissions with the highest emissions observed for particles around 10 nm during rush hours. At sizes below 6 nm, clustering of atmospheric vapors contributes to calculated emissions. The comparison between our calculated emissions and those estimated with an integrated assessment model GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) shows that our method yields clearly higher particle emissions at sizes below 60 nm, but at sizes above that the two methods agree well. Overall, our method is proven to be a useful tool for gaining new knowledge of the size distributions of particle number emissions in urban environments and for validating emission inventories and models. In the future, the method will be developed by modeling the transport of particles from different sources to obtain more accurate estimates of particle number emissions.

scholarly journals Sources of organic aerosols in Europe: a modeling study using CAMx with modified volatility basis set scheme

2019 ◽  
Vol 19 (24) ◽  
pp. 15247-15270 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Agricultural Waste ◽  
Organic Aerosols ◽  
Basis Set ◽  
Anthropogenic Sources ◽  
Wood Burning ◽  
Gasoline Vehicles

Abstract. Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 to −0.4 µg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.

Long-term air quality monitoring at the South Pole by the NOAA Program Geophysical Monitoring for Climatic Change

1988 ◽  
Vol 26 (1) ◽  
pp. 63 ◽  
Author(s):  
E. Robinson ◽  
B. A. Bodhaine ◽  
W. D. Komhyr ◽  
S. J. Oltmans ◽  
L. P. Steele ◽  
...  
Keyword(s):  
Air Quality ◽  
Climatic Change ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
South Pole ◽  
The South ◽  
Geophysical Monitoring

scholarly journals Dispersion of traffic-related exhaust particles near the Berlin urban motorway: estimation of fleet emission factors

2008 ◽  
Vol 8 (4) ◽  
pp. 15537-15594 ◽  
Author(s):  
W. Birmili ◽  
B. Alaviippola ◽  
D. Hinneburg ◽  
O. Knoth ◽  
T. Tuch ◽  
...  
Keyword(s):  
Particle Number ◽  
Dispersion Model ◽  
Flow Simulation ◽  
Emission Factors ◽  
Size Distributions ◽  
Tracer Transport ◽  
Particle Volume ◽  
Traffic Emission ◽  
Atmospheric Particle ◽  
Particulate Number

Abstract. Atmospheric particle number size distributions of airborne particles (diameter range 10–500 nm) were measured over ten weeks at three sites in the vicinity of the A100 urban motorway in Berlin, Germany. The A100 carries about 180 000 vehicles on a weekday, and roadside particle size distributions showed a number maximum between 20 and 60 nm clearly related to the motorway emissions. The average total number concentration at roadside was 28 000 cm−3 with a total range between 1200 and 168 000 cm−3. At distances of 80 and 400 m from the motorway the concentrations decreased to mean levels of 11 000 and 9 000 cm−3, respectively. An obstacle-resolving dispersion model was applied to simulate the 3-D flow field and traffic tracer transport in the urban environment around the motorway. By inverse modelling, vehicle emission factors were derived, representative of a relative share of 6% lorry-like vehicles, and a driving speed of about 80 km h−1. Three different calculation approaches were compared, which differ in the choice of the experimental winds driving the flow simulation. The average emission factor per vehicle was 2.1(±0.2) · 1014 km−1 for particle number and 0.077(±0.01) · 1014 cm3 km−1 for particle volume. Regression analysis suggested that lorry-like vehicles emit 116 (± 21) times more particulate number than passenger car-like vehicles, and that lorry-like vehicles account for about 91% of particulate number emissions on weekdays. Our work highlights the increasing applicability of 3-D flow models in urban microscale environments and their usefulness in determining traffic emission factors.

Spatiotemporal variability of submicrometer particle number size distributions in an air quality management district

2012 ◽  
Vol 425 ◽  
pp. 135-145 ◽  
Author(s):  
Li-Hao Young ◽  
Yi-Ting Wang ◽  
Hung-Chieh Hsu ◽  
Ching-Hui Lin ◽  
Yi-Jyun Liou ◽  
...  
Keyword(s):  
Air Quality ◽  
Quality Management ◽  
Particle Number ◽  
Spatiotemporal Variability ◽  
Size Distributions ◽  
Air Quality Management

scholarly journals Characterisation and Source Apportionment of Submicron Particle Number Size Distributions in a Busy Street Canyon

2015 ◽  
Vol 15 (1) ◽  
pp. 220-233 ◽  
Author(s):  
Patricia Krecl ◽  
Admir Créso Targino ◽  
Christer Johansson ◽  
Johan Ström
Keyword(s):  
Source Apportionment ◽  
Street Canyon ◽  
Particle Number ◽  
Size Distributions ◽  
Submicron Particle ◽  
Busy Street

scholarly journals Size-resolved particle number emissions in Beijing determined from measured particle size distributions

2020 ◽  
Author(s):  
Jenni Kontkanen ◽  
Chenjuan Deng ◽  
Yueyun Fu ◽  
Lubna Dada ◽  
Ying Zhou ◽  
...  
Keyword(s):  
Particle Size ◽  
Air Quality ◽  
Particle Number ◽  
Aerosol Particles ◽  
Urban Environments ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Measured Particle

Abstract. The climate and air quality effects of aerosol particles depend on the number and size of the particles. In urban environments, a large fraction of aerosol particles originates from anthropogenic emissions. To evaluate the effects of different pollution sources on air quality, knowledge of size distributions of particle number emissions is needed. Here we introduce a novel method for determining size-resolved particle number emissions based on measured particle size distributions. We apply our method to data measured in Beijing, China, to determine the number size distribution of emitted particles in diameter range from 2 to 1000 nm. The observed particle number emissions are dominated by emissions of particles smaller than 30 nm. Our results suggest that traffic is the major source of particle number emissions with the highest emissions observed for particles around 10 nm during rush hours. At sizes below 6 nm, clustering of atmospheric vapors contributes to calculated emissions. The comparison between our calculated emissions and those estimated with an integrated assessment model GAINS shows that our method yields clearly higher particle emissions at sizes below 60 nm, but at sizes above that the two methods agree well. Overall, our method is proven to be a useful tool for gaining new knowledge of size distributions of particle number emissions in urban environments.

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