An Evaluation of Particle Size Distributions and Particle Number-Based Reductions from Various PM Emission Control Technologies

2011 ◽  
Vol 4 (1) ◽  
pp. 498-507 ◽  
Author(s):  
Ajay Joshi ◽  
Sougato Chatterjee ◽  
Andrew Walker
Keyword(s):  
Particle Size ◽  
Particle Number ◽  
Emission Control ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Control Technologies

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 Particle formation at a continental background site: comparison of modelresults with observations

2002 ◽  
Vol 2 (6) ◽  
pp. 2413-2448
Author(s):  
U. Uhrner ◽  
W. Birmili ◽  
F. Stratmann ◽  
M. Wilck ◽  
I. J. Ackermann ◽  
...  
Keyword(s):  
Particle Size ◽  
Sulphuric Acid ◽  
Particle Number ◽  
Particle Formation ◽  
Rural Site ◽  
Size Distributions ◽  
Correction Factors ◽  
Convective Conditions ◽  
Particle Size Distributions ◽  
Measured Particle

Abstract. At Hohenpeissenberg (47°48'N, 11°07'E, 988 m asl), a rural site 200-300 m higher than the surrounding terrain, sulphuric acid concentrations, particle size distributions, and other trace gas concentrations were measured over a two and a half year period. Measured particle number concentrations and inferred particle surface area-concentrations were compared with box-model simulations based on a multimodal lognormal aerosol module that included a binary sulphuric acid water nucleation scheme. The calculated nucleation rates were corrected with a factor to match measured particle number concentrations. These corrections varied over a range of 10-3 - 1017. The correction factors were close to 1 for the measurements made in the winter, which represented stable thermal stratification and low wind conditions. In contrast, the correction factors were the largest for measurements made under strong convective conditions. Our comparison of measured and simulated particle size distributions suggest a distant particle-formation process under convective conditions near the interface of the mixed layer and the entrainment zone, followed by downward transport and particle growth. For stable stratification and low winds, our comparisons suggest that particles formed close to the measurement site.

scholarly journals Remarkable dynamics of nanoparticles in the urban atmosphere

2011 ◽  
Vol 11 (13) ◽  
pp. 6623-6637 ◽  
Author(s):  
M. Dall'Osto ◽  
A. Thorpe ◽  
D. C. S. Beddows ◽  
R. M. Harrison ◽  
J. F. Barlow ◽  
...  
Keyword(s):  
Particle Size ◽  
Size Distribution ◽  
Urban Areas ◽  
Particle Number ◽  
Road Traffic ◽  
Urban Atmosphere ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Number Count ◽  
Adverse Health Effects

Abstract. Nanoparticles emitted from road traffic are the largest source of respiratory exposure for the general public living in urban areas. It has been suggested that adverse health effects of airborne particles may scale with airborne particle number, which if correct, focuses attention on the nanoparticle (less than 100 nm) size range which dominates the number count in urban areas. Urban measurements of particle size distributions have tended to show a broadly similar pattern dominated by a mode centred on 20–30 nm diameter emitted by diesel engine exhaust. In this paper we report the results of measurements of particle number concentration and size distribution made in a major London park as well as on the BT Tower, 160 m aloft. These measurements taken during the REPARTEE project (Regents Park and BT Tower experiment) show a remarkable shift in particle size distributions with major losses of the smallest particle class as particles are advected away from the traffic source. In the Park, the traffic related mode at 20–30 nm diameter is much reduced with a new mode at <10 nm. Size distribution measurements also revealed higher number concentrations of sub-50 nm particles at the BT Tower during days affected by higher turbulence as determined by Doppler Lidar measurements and are indicative of loss of nanoparticles from air aged during less turbulent conditions. These results are suggestive of nanoparticle loss by evaporation, rather than coagulation processes. The results have major implications for understanding the impacts of traffic-generated particulate matter on human health.

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.

scholarly journals Size-segregated particle number and mass concentrations from different emission sources in urban Beijing

2020 ◽  
Vol 20 (21) ◽  
pp. 12721-12740
Author(s):  
Jing Cai ◽  
Biwu Chu ◽  
Lei Yao ◽  
Chao Yan ◽  
Liine M. Heikkinen ◽  
...  
Keyword(s):  
Particle Size ◽  
Particulate Matter ◽  
Source Apportionment ◽  
Particle Number ◽  
Fine Particles ◽  
Size Distributions ◽  
Vehicular Emissions ◽  
Particle Size Distributions ◽  
Chemical Fingerprints ◽  
Mass Concentrations

Abstract. Although secondary particulate matter is reported to be the main contributor of PM2.5 during haze in Chinese megacities, primary particle emissions also affect particle concentrations. In order to improve estimates of the contribution of primary sources to the particle number and mass concentrations, we performed source apportionment analyses using both chemical fingerprints and particle size distributions measured at the same site in urban Beijing from April to July 2018. Both methods resolved factors related to primary emissions, including vehicular emissions and cooking emissions, which together make up 76 % and 24 % of total particle number and organic aerosol (OA) mass, respectively. Similar source types, including particles related to vehicular emissions (1.6±1.1 µg m−3; 2.4±1.8×103 cm−3 and 5.5±2.8×103 cm−3 for two traffic-related components), cooking emissions (2.6±1.9 µg m−3 and 5.5±3.3×103 cm−3) and secondary aerosols (51±41 µg m−3 and 4.2±3.0×103 cm−3), were resolved by both methods. Converted mass concentrations from particle size distributions components were comparable with those from chemical fingerprints. Size distribution source apportionment separated vehicular emissions into a component with a mode diameter of 20 nm (“traffic-ultrafine”) and a component with a mode diameter of 100 nm (“traffic-fine”). Consistent with similar day- and nighttime diesel vehicle PM2.5 emissions estimated for the Beijing area, traffic-fine particles, hydrocarbon-like OA (HOA, traffic-related factor resulting from source apportionment using chemical fingerprints) and black carbon (BC) showed similar diurnal patterns, with higher concentrations during the night and morning than during the afternoon when the boundary layer is higher. Traffic-ultrafine particles showed the highest concentrations during the rush-hour period, suggesting a prominent role of local gasoline vehicle emissions. In the absence of new particle formation, our results show that vehicular-related emissions (14 % and 30 % for ultrafine and fine particles, respectively) and cooking-activity-related emissions (32 %) dominate the particle number concentration, while secondary particulate matter (over 80 %) governs PM2.5 mass during the non-heating season in Beijing.

Supervised regression learning for predictions of aerosol particle size distributions from PM2.5, total particle number and meteorological parameters at Helsinki SMEAR3 station

2020 ◽  
Author(s):  
Juha Kangasluoma ◽  
Yusheng Wu ◽  
Runlong Cai ◽  
Joel Kuula ◽  
Hilkka Timonen ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Surface Area ◽  
Aerosol Particle ◽  
Particle Number ◽  
Meteorological Parameters ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Aerosol Particle Size ◽  
Regression Learning

&lt;p&gt;Supervised regression learning for predictions of aerosol particle size distributions from PM2.5, total particle number and meteorological parameters at Helsinki SMEAR3 station&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;J. Kangasluoma&lt;sup&gt;1&lt;/sup&gt;, Y. Wu&lt;sup&gt;1&lt;/sup&gt;, R. Cai&lt;sup&gt;1&lt;/sup&gt;, J. Kuula&lt;sup&gt;2&lt;/sup&gt;, H. Timonen&lt;sup&gt;2&lt;/sup&gt;, P. P. Aalto&lt;sup&gt;1&lt;/sup&gt;, M. Kulmala&lt;sup&gt;1&lt;/sup&gt;, T. Pet&amp;#228;j&amp;#228;&lt;sup&gt;1&lt;/sup&gt;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; Institute for Atmospheric and Earth System Research / Physics, Faculty of Science, University of Helsinki, Finland&lt;/p&gt;&lt;p&gt;&lt;sup&gt;2 &lt;/sup&gt;Finnish Meteorological Institute, Erik Palm&amp;#233;nin aukio 1, 00560 Helsinki, Finland&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Atmospheric particulate material is a significant pollutant and causes millions premature deaths yearly especially in urban city environments. To conduct epidemiological studies and quantify of the role of sub-micron particles, especially role of the ultrafine particles (&lt;100 nm), in mortality caused by the particulate matter, long-term monitoring of the particle number, surface area, mass and chemical composition are needed. Such monitoring on large scale is currently done only for particulate mass, namely PM2.5 (mass of particulates smaller than 2.5 &amp;#956;m), while large body of evidence suggests that ultrafine particles, which dominate the number of the aerosol distribution, cause significant health effects that do not originate from particle mass.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;The chicken-egg-problem here is that monitoring of particle number or surface area is not required from the authorities due to lack of epidemiological evidence showing the harm and suitable instrumentation (although car industry already voluntarily limits the ultrafine particle number emissions), while these epidemiological studies are lacking because of the suitable lack of data. Here we present the first step in solving this &amp;#8220;lack of data issue&amp;#8221; by predicting aerosol particle size distributions based on PM2.5, particle total number and meteorological measurements, from which particle size distribution, and subsequently number, surface area and mass exposure can be calculated.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;We use baggedtree supervised regression learning (from Matlab toolbox) to train an algorithm with one full year data from SMEAR3 station at 10 min time resolution in Helsinki during 2018. The response variable is the particle size distribution (each bin separately) and the training variables are PM2.5, particle number and meteorological parameters. The trained algorithm is then used with the same training variables data, but from 2019 to predict size distributions, which are directly compared to the measured size distributions by a differential mobility particle sizer.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;To check the model performance, we divide the predicted distributions to three size bins, 3-25, 25-100 and 100-1000 nm, and calculate the coefficient of determination (r&lt;sup&gt;2&lt;/sup&gt;) between the measured and predicted number concentration at 10 min time resolution, which are 0.79, 0.60 and 0.50 respectively. We also calculate r&lt;sup&gt;2&lt;/sup&gt; between the measured and predicted number, surface area and mass exposure, which are 0.87, 0.79 and 0.74, respectively. Uncertainties in the prediction are mostly random, thus the r&lt;sup&gt;2&lt;/sup&gt; values will increase at longer averaging times.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Our results show that an algorithm that is trained with particle size distribution data, and particle number, PM2.5 and meteorological data can predict particle size distributions and number, surface area and mass exposures. In practice, these predictions can be realized e.g. in air pollution monitoring networks by implementing a condensation particle counter at each site, and circulating a differential mobility size spectrometer around the sites.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals A transition in atmospheric emissions of particles and gases from on-road heavy-duty trucks

2019 ◽  
Author(s):  
Liyuan Zhou ◽  
Åsa M. Hallquist ◽  
Mattias Hallquist ◽  
Christian M. Salvador ◽  
Samuel M. Gaita ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Number ◽  
Large Fraction ◽  
Urban Environments ◽  
Nox Emissions ◽  
Size Distributions ◽  
Atmospheric Emissions ◽  
Heavy Duty ◽  
Particle Size Distributions ◽  
Volatile Particle

Abstract. The transition in extent and characteristics of atmospheric emissions caused by the modernisation of the heavy-duty on-road fleet were studied utilising roadside measurements. Emissions of particle number (PN), particle mass (PM), black carbon (BC), nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbon (HC), particle size distributions and particle volatility were measured from 556 individual heavy-duty trucks (HDTs). Substantial reductions in PM, BC, NOx, CO and to a lesser extent PN were observed from Euro III to Euro VI HDTs by 99 %, 98 %, 93 % and 57 % for the average emissions factors of PM, BC, NOx, and CO respectively. Despite significant total reductions in NOx emissions, the fraction of NO2 in the NOx emissions increased continuously from Euro IV to Euro VI HDTs. Larger data scattering was evident for PN emissions in comparison to solid particle number (SPN) for Euro VI HDTs, indicating a highly variable fraction of volatile particle components. Particle size distributions of Euro III to EEV HDTs were bimodal, whereas those of Euro VI HDTs were nucleation mode dominated. High emitters disproportionately contributed to a large fraction of the total emissions with the highest-emitting 10 % of HDTs in each pollutant category being responsible for 65 % of total PM, 70 % of total PN and 44 % of total NOx emissions, respectively. Euro VI HDTs, which accounted for 53 % of total kilometres driven by Swedish HDTs, were estimated to only contribute to 2 %, 6 %, 12 % and 47 % of PM, BC, NOx, and PN emissions. A shift to a Euro VI HDTs dominant fleet would promote a transition of atmospheric emissions towards low PM, BC, NOx, and CO levels. Nonetheless, reducing PN, SPN, and NO2 emissions from Euro VI HDTs is still important to improve air quality in urban environments.

scholarly journals Variations in tropospheric submicron particle size distributions across the European continent 2008–2009

2014 ◽  
Vol 14 (8) ◽  
pp. 4327-4348 ◽  
Author(s):  
D. C. S. Beddows ◽  
M. Dall'Osto ◽  
R. M. Harrison ◽  
M. Kulmala ◽  
A. Asmi ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Number ◽  
The Arctic ◽  
Aerosol Size Distribution ◽  
Complex Data ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
European Continent ◽  
Complex Behaviour ◽  
Air Masses

Abstract. Cluster~analysis of particle number size distributions from~background sites across Europe~is presented. This generated a total of nine clusters of particle size distributions which could be further combined into two main groups, namely: a south-to-north category (four clusters) and a west-to-east category (five clusters). The first group was identified as most frequently being detected inside and around northern Germany and neighbouring countries, showing clear evidence of local afternoon nucleation and growth events that could be linked to movement of air masses from south to north arriving ultimately at the Arctic contributing to Arctic haze.~The second group of particle size spectra proved to have narrower size distributions and collectively showed a dependence of modal diameter upon the longitude of the site (west to east) at which they were most frequently detected.~These clusters indicated regional nucleation (at the coastal sites) growing to larger modes further inland. The apparent growth rate of the modal diameter was around 0.6–0.9 nm h−1. Four specific air mass back-trajectories were successively taken as case studies to examine in real time the evolution of aerosol size distributions across Europe. ~While aerosol growth processes can be observed as aerosol traverses Europe, the processes are often obscured by the addition of aerosol by emissions en route. This study revealed that some of the 24 stations exhibit more complex behaviour than others, especially when impacted by local sources or a variety of different air masses. Overall, the aerosol size distribution clustering analysis greatly simplifies the complex data set and allows a description of aerosol aging processes, which reflects the longer-term average development of particle number size distributions as air masses advect across Europe.

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