Integration of measurements and model simulations to characterize Eyjafjallajökull volcanic aerosols over south-eastern Italy

Abstract. Volcanic aerosols resulting from the Eyjafjallajökull eruption were detected in south-eastern Italy from 20 to 22 April 2010, at a distance of approximately 4000 km from the volcano, and have been characterized by lidar, sun/sky photometer, and surface in-situ measurements. Volcanic particles added to the pre-existing aerosol load and measurement data allow quantifying the impact of volcanic particles on the aerosol vertical distribution, lidar ratios, the aerosol size distribution, and the ground-level particulate-matter concentrations. Lidar measurements reveal that backscatter coefficients by volcanic particles were about one order of magnitude smaller over south-eastern Italy than over Central Europe. Mean lidar ratios at 355 nm were equal to 64 ± 5 sr inside the volcanic aerosol layer and were characterized by smaller values (47 ± 2 sr) in the underlying layer on 20 April, 19:30 UTC. Lidar ratios and their dependence with the height reduced in the following days, mainly because of the variability of the volcanic particle contributions. Size distributions from sun/sky photometer measurements reveal the presence of volcanic particles with radii r > 0.5 μm on 21 April and that the contribution of coarse volcanic particles increased from 20 to 22 April. The aerosol fine mode fraction from sun/sky photometer measurements varied between values of 0.85 and 0.94 on 20 April and decreased to values between 0.25 and 0.82 on 22 April. Surface measurements of particle size distributions were in good accordance with column averaged particle size distributions from sun/sky photometer measurements. PM1/PM2.5 mass concentration ratios of 0.69, 0.66, and 0.60 on 20, 21, and 22 April, respectively, support the increase of super-micron particles at ground. Measurements from the Regional Air Quality Agency show that PM10 mass concentrations on 20, 21, and 22 April 2010 were enhanced in the entire Apulia Region. More specifically, PM10 mass concentrations have on average increased over Apulia Region 22%, 50%, and 28% on 20, 21, and 22 April, respectively, compared to values on 19 April. Finally, the comparison of measurement data with numerical simulations by the FLEXPART dispersion model demonstrates the ability of FLEXPART to model the advection of the volcanic ash over the 4000 km from the Eyjafjallajökull volcano to Southern Italy.

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Spatial and Seasonal Variations of PM Concentration and Size Distribution in Manure-Belt Poultry Layer Houses

Transactions of the ASABE ◽

10.13031/trans.12950 ◽

2019 ◽

Vol 62 (2) ◽

pp. 415-427 ◽

Cited By ~ 1

Author(s):

Reyna M. Knight ◽

Xinjie Tong ◽

Zhenyu Liu ◽

Sewoon Hong ◽

Lingying Zhao

Keyword(s):

Particle Size ◽

Particulate Matter ◽

Size Distribution ◽

Seasonal Variations ◽

Size Distributions ◽

Particle Size Distributions ◽

Potential Health ◽

Significant Difference ◽

Autumn And Winter ◽

Mass Concentrations

Abstract. Poultry layer houses are a significant source of particulate matter (PM) emissions, which potentially affect worker and animal health. Particulate matter characteristics, such as concentration and size distribution inside layer houses, are critical information for assessment of the potential health risks and development of effective PM mitigation technologies. However, this information and its spatial and seasonal variations are lacking for typical layer facilities. In this study, two TSI DustTrak monitors (DRX 8533) and an Aerodynamic Particle Sizer (APS 3321) were used to measure PM mass concentrations and number-weighted particle size distributions in two typical manure-belt poultry layer houses in Ohio in three seasons: summer, autumn, and winter. Bimodal particle size distributions were consistently observed. The average count median diameters (mean ±SD) were 1.68 ±0.25, 2.16 ±0.31, and 1.87 ±0.07 µm in summer, autumn, and winter, respectively. The average geometric standard deviations of particle size were 2.16 ±0.23, 2.16 ±0.18, and 1.74 ±0.17 in the three seasons, respectively. The average mass concentrations were 67.4 ±54.9, 289.9 ±216.2, and 428.1 ±269.9 µg m-3 for PM2.5; 73.6 ±59.5, 314.6 ±228.9, and 480.8 ±306.5 µg m-3 for PM4; and 118.8 ±99.6, 532.5 ±353.0, and 686.2 ±417.7 µg m-3 for PM10 in the three seasons, respectively. Both statistically significant (p < 0.05) and practically significant (difference of means >20% of smaller value) seasonal variations were observed. Spatial variations were only practically significant for autumn mass concentrations, likely due to external dust infiltration from nearby agricultural activities. The OSHA-mandated permissible exposure limit for respirable PM was not exceeded in any season. Keywords: Air quality, Particulate matter, Poultry housing, Seasonal variation, Spatial variation.

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The MESSy aerosol submodel MADE3 (v2.0b): description and a box model test

Geoscientific Model Development ◽

10.5194/gmd-7-1137-2014 ◽

2014 ◽

Vol 7 (3) ◽

pp. 1137-1157 ◽

Cited By ~ 16

Author(s):

J. C. Kaiser ◽

J. Hendricks ◽

M. Righi ◽

N. Riemer ◽

R. A. Zaveri ◽

...

Keyword(s):

Particle Size ◽

Box Model ◽

Aerosol Size Distribution ◽

Sea Spray ◽

Test Case ◽

Size Distributions ◽

Particle Size Distributions ◽

Aerosol Dynamics ◽

Coarse Mode ◽

Made In

Abstract. We introduce MADE3 (Modal Aerosol Dynamics model for Europe, adapted for global applications, 3rd generation; version: MADE3v2.0b), an aerosol dynamics submodel for application within the MESSy framework (Modular Earth Submodel System). MADE3 builds on the predecessor aerosol submodels MADE and MADE-in. Its main new features are the explicit representation of coarse mode particle interactions both with other particles and with condensable gases, and the inclusion of hydrochloric acid (HCl) / chloride (Cl) partitioning between the gas and condensed phases. The aerosol size distribution is represented in the new submodel as a superposition of nine lognormal modes: one for fully soluble particles, one for insoluble particles, and one for mixed particles in each of three size ranges (Aitken, accumulation, and coarse mode size ranges). In order to assess the performance of MADE3 we compare it to its predecessor MADE and to the much more detailed particle-resolved aerosol model PartMC-MOSAIC in a box model simulation of an idealised marine boundary layer test case. MADE3 and MADE results are very similar, except in the coarse mode, where the aerosol is dominated by sea spray particles. Cl is reduced in MADE3 with respect to MADE due to the HCl / Cl partitioning that leads to Cl removal from the sea spray aerosol in our test case. Additionally, the aerosol nitrate concentration is higher in MADE3 due to the condensation of nitric acid on coarse mode particles. MADE3 and PartMC-MOSAIC show substantial differences in the fine particle size distributions (sizes &lesssim; 2 μm) that could be relevant when simulating climate effects on a global scale. Nevertheless, the agreement between MADE3 and PartMC-MOSAIC is very good when it comes to coarse particle size distributions (sizes &gtrsim; 2 μm), and also in terms of aerosol composition. Considering these results and the well-established ability of MADE in reproducing observed aerosol loadings and composition, MADE3 seems suitable for application within a global model.

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

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-12721-2020 ◽

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.

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

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-4327-2014 ◽

2014 ◽

Vol 14 (8) ◽

pp. 4327-4348 ◽

Cited By ~ 26

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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Size segregated particle number and mass emissions in urban Beijing

10.5194/acp-2020-248 ◽

2020 ◽

Cited By ~ 1

Author(s):

Jing Cai ◽

Biwu Chu ◽

Lei Yao ◽

Chao Yan ◽

Liine M. Heikkinen ◽

...

Keyword(s):

Particle Size ◽

Particulate Matter ◽

Source Apportionment ◽

Particle Number ◽

Related Factor ◽

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 night-time diesel vehicle PM2.5 emissions estimated for the Beijing area, Traffic-fine, 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 (14 % and 30 % for ultrafine and fine particles, respectively) and cooking (32 %) emissions dominate the particle number concentration while secondary particulate matter (over 80 %) governs PM2.5 mass during the non-heating season in Beijing.

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Development of a new nanoparticle sizer equipped with a 12-channel multi-port differential mobility analyzer and multi-condensation particle counters

Atmospheric Measurement Techniques ◽

10.5194/amt-13-1551-2020 ◽

2020 ◽

Vol 13 (3) ◽

pp. 1551-1562

Author(s):

Hong Ku Lee ◽

Handol Lee ◽

Kang-Ho Ahn

Keyword(s):

Particle Size ◽

Steady State ◽

Size Distribution ◽

Particle Concentration ◽

Measurement Data ◽

Size Distributions ◽

Differential Mobility Analyzer ◽

Particle Size Distributions ◽

Scanning Mobility Particle Sizer ◽

Differential Mobility

Abstract. Measuring particle size distributions precisely is an important concern in addressing environmental and human health-related issues. To measure particle size distributions, a scanning mobility particle sizer (SMPS) is often used. However, it is difficult to analyze particle size distributions under fast-changing concentration conditions because the SMPS cannot respond fast enough to reflect current conditions due to the time necessary for voltage scanning. In this research, we developed a new nanoparticle sizer (NPS), which consists of a multi-port differential mobility analyzer (MP-DMA) with 12 sampling ports and multi-condensation particle counters (M-CPCs) that simultaneously measure concentrations of particles classified by the sampling ports. The M-CPC can completely condense particles larger than 10 nm, and the total particle concentrations measured by each CPC in the M-CPCs and an electrometer were in agreement up to 20 000 no.cm-3. We conducted size distribution measurements under steady-state conditions using an aerosol generator and under unsteady conditions by switching the aerosol supply on or off. The data obtained by the NPS corresponded closely to the SMPS measurement data for the steady-state particle concentration case. In addition, the NPS could successfully capture the changes in particle size distribution under fast-changing particle concentration conditions. Finally, we present NPS measurement results of size distributions in a common situation (cooking) as an exemplary real-world application.

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