Seasonality of the particle number concentration and size
distribution: a global analysis retrieved from the network of Global
Atmosphere Watch (GAW) near-surface observatories

Coen, Martine Collaud; Andrews, Elisabeth; Lin, Yong; Bossert, Isaline; Myhre, Cathrine Lund; Tuch, Thomas; Wiedensohler, Alfred; Fiebig, Markus; Aalto, Pasi; Alastuey, Andrés; Alonso‐Blanco, Elisabeth; Andrade, Marcos; Artı́ñano, Begoña; Arsov, Todor; Baltensperger, Urs; Bastian, Susanne; Bath, Olaf; Beukes, Johan P.; Brem, Benjamin T.; Bukowiecki, Nicolas; Casquero-Vera, Juan Andrés; Conil, Sébastien; Eleftheriadis, Konstantinos; Favez, Olivier; Flentje, H.; Gini, Maria I.; Gómez-Moreno, Francisco J.; Gysel, M.; Hallar, A. Gannet; Kalapov, Ivo; Kalivitis, N.; Kasper‐Giebl, Anne; Keywood, Melita; Kim, Jeong Eun; Kim, Sang‐Woo; Kristensson, Adam; Kulmala, Markku; Lihavainen, Heikki; Lin, Neng-Huei; Lyamani, H.; Marinoni, Angela; Santos, Sebastiao Martins Dos; Mayol-Bracero, O. L.; Meinhardt, F.; Merkel, Maik; Metzger, Jean‐Marc; Mihalopoulos, Nikolaos; Ondráček, Jakub; Pandolfi, M.; Pérez, Noemí; Petäj̈ä, Tuukka; Petit, Jean-Eudes; Picard, David; Pichon, Maxime; Pont, Véronique; Putaud, Jean‐Philippe; Reisen, Fabienne; Sellegri, Karine; Sharma, Sangeeta; Schauer, Gerhard; Sheridan, Patrick J.; Sherman, James P.; Schwerin, Andreas; Sohmer, Ralf; Sorribas, M.; Sun, Junying; Tulet, Pierre; Vakkari, Ville; Zyl, P. G. van; Velarde, Fernando; Villani, Paolo; Vratolis, Stergios; Wagner, Z.; Wang, Sheng Hsiang; Weinhold, Kay; Weller, Rolf; Yela, Margarita; Ždı́mal, Vladimı́r; Laj, Paolo

doi:10.5194/acp-2020-1311

Cited by 3 publications

(4 citation statements)

References 34 publications

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“…To extract some more valuable information, the k-means clustering method used in various studies has been considered to be a preferred technique for data analysis in environmental fields (Sabaliauskas et al, 2013;Tunved et al, 2004).…”

Section: Cluster Analysis Methodsmentioning

confidence: 99%

“…Aitken mode particles are primarily emitted from combustion processes, such as coal combustion for domestic heating in wintertime and also from hygroscopic growth and coagulation of nucleation mode particles. For a relatively clean environment, the growth of nucleation mode particles is predominant due to a smaller coagulation sink (Rose et al, 2021), while the primary emissions are more important at the highly polluted urban areas (Hussein et al, 2004). Accumulation mode particles originate from the coagulation and hygroscopic growth of Aitken mode particles and long-range transport from the highly polluted areas.…”

Section: Overview Of the Particle Number Concentrationmentioning

confidence: 99%

“…The more recent study of Zhao et al (2021) found that interdecadal AOD had a negative trend from 2009 to 2018, which may be related to the variation in particle size distribution. Some aerosol monitoring networks were established around the world for long-term measurements of climate-relevant aerosol properties, such as Geophysical Monitoring for Climate Change (GMCC, Bodhaine, 1983) and Global Atmosphere Watch (GAW, Rose et al, 2021). The particle number concentrations (PNCs) and size distributions (PNSDs), considered to be primary indicators of human impacts on atmospheric composition, were the main aerosol properties measured at the networks.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Response of particle number concentrations to the clean air action plan: lessons from the first long-term aerosol measurements in a typical urban valley in western China

Zhao

et al. 2021

Atmos. Chem. Phys.

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Abstract. The strictest ever clean air action (CAA) plan has been implemented by the Chinese government since 2013 to alleviate the severe haze pollution. The PM2.5 mass concentration was found to largely be reduced in response to emission mitigation policies, but the response of particle number concentrations (PNCs) to CAA was less evaluated in the previous studies, which may be significantly different from PM2.5 mass due to newly formed particle impacts. In this work, the first in situ observation of particle number size distributions (PNSDs) during 2012–2019 in urban Lanzhou was used to analyze long-term PNC variations and CAA impacts. The average number of particles in nucleation (N13−25, particle number in the size range of 13–25 nm), Aitken (N25−100, particle number in the size range of 25–100 nm) and accumulation (N100−800, particle number in the size range of 100–800 nm) modes were respectively 2514.0, 10 768.7 and 3258.4 cm−3, and N25−100 accounted for about 65.1 % of total PNCs during the campaign. The k-means clustering technique was used to classify the hourly mean PNSDs into six clusters, and each cluster corresponded to a specific source and influencing factor. The polluted clusters governed the winter PNCs before 2016, and their occurrence was less and less frequent after 2016, which was largely dominated by reduction in primary emissions. However, the contribution of new particle formation (NPF) events to summer N13−25 decreased from 50 % to about 10 % during 2013 to 2015 and then increased to reach around 60 % in 2019. The trends of size-resolved PNCs for each cluster were quantified by Theil–Sen regression. The size-segregated PNCs exhibited downward trends for all clusters during 2012–2015, especially in spring. The annual relative slopes of spring PNCs varied from −54.7 % to −17.2 %, −42.6 % to −14.1 %, and −40.7 % to −17.5 % per year for 13–25, 25–100, and 100–800 nm size ranges, and the reduction in the polluted clusters was much larger than NPF clusters. The ultrafine particle number was increased, and the amplitude was much greater during 2016–2019. The annual relative slopes of N13−25 varied between 8.0 % in fall and 135.5 % in spring for the NPF cluster. In response to CAA, the increased daytime net radiation, higher ambient temperature and lower relative humidity at noon for NPF events also could partly explain the higher N13−25 induced by the more frequent nucleation events after 2016, especially in spring. The air masses were mainly from the adjacent regions of urban Lanzhou and less affected by long-range transport for NPF events, and thus the particles were not easily grown by coagulation during transport processes, which was helpful for the occurrence of NPF events. Therefore, some effective measures to cooperatively control particle number concentration and mass should be taken for the Chinese megacities.

show abstract

Section: Cluster Analysis Methodsmentioning

confidence: 99%

Section: Overview Of the Particle Number Concentrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Response of particle number concentrations to the clean air action plan: lessons from the first long-term aerosol measurements in a typical urban valley in western China

Zhao

et al. 2021

Atmos. Chem. Phys.

View full text Add to dashboard Cite

show abstract

“…Aitken mode particles are primarily emitted from combustion processes, such as coal combustion for domestic heating in wintertime, and also from hygroscopic growth and coagulation of nucleation mode particles. For relatively clean environment, the growth of nucleation mode particles is predominant due to less coagulation sink (Rose et al, 2021), while the primary emissions are more important at the highly polluted urban areas (Hussein et al, 20 2004). Accumulation mode particles originate from coagulation and hygroscopic growth of Aitken mode particles and long-range transport from the highly polluted areas.…”

Section: Overview Of the Particle Number Concentrationmentioning

confidence: 99%

Response of particle number concentrations to Clean Air Action: Lessons from the first long-term aerosol measurements in a typical urban valley, West China

Zhao

et al. 2021

Preprint

View full text Add to dashboard Cite

Abstract. The strictest ever Clean Air Action (CAA) has been implemented by Chinese government since 2013 to alleviate the severe haze pollution. The PM2.5 mass concentration was found to be largely reduced in response to emission mitigation policies, but response of particle number concentrations (PNCs) to CAA was less evaluated in the previous studies, which may be largely different from PM2.5 mass due to newly formed particle impacts. In this work, the first in-situ observation of particle number size distributions (PNSDs) during 2012–2019 in urban Lanzhou was used to analyze long-term PNCs variations and CAA impacts. The average number of particles in nucleation (N13–25, particle number in the size range of 13–25 nm), Aitken (N25–100, particle number in the size range of 25–100 nm) and accumulation (N100–800, particle number in the size range of 100–800 nm) modes were respectively 2514.0 cm−3, 10768.7 cm−3, and 3258.4 cm−3, and N25–100 accounted for about 65.1 % of total PNCs during the campaign. K-means clustering technique was used to classify the hourly mean PNSDs into six clusters, and each cluster corresponded to a specific source and influencing factor. The polluted clusters governed the winter PNCs before 2016, and their occurrence was less and less frequent after 2016, which was largely dominated by reduction in primary emissions. However, the contribution of new particle formation (NPF) events to summer N13–25 decreased from 50 % to about 10 % during 2013 to 2015, and then increased to reach around 60 % in 2019. The trends of size-resolved PNCs for each cluster were quantified by Theil-Sen regression. The size-segregated PNCs exhibited downward trends for all clusters during 2012–2015, especially in spring. The annual relative slopes of spring PNCs varied from −54.7 % to −17.2 %, −42.6 % to −14.1 %, and −40.7 % to −17.5 % per year for 13–25, 25–100, and 100–800 nm size ranges, and the reduction in the polluted clusters was much larger than NPF clusters. The ultrafine particle number was increased and the amplitude was much greater during 2016–2019. The annual relative slopes of N13–25 varied between 8.0 % in fall and 135.5 % in spring for NPF cluster. In response to CAA, the increased daytime net radiation, higher ambient temperature and lower relative humidity at noon for NPF events also could partly explain the higher N13–25 induced by the more frequent nucleation events after 2016, especially in spring. The air mass were mainly from the adjacent regions of urban Lanzhou and less affected by long-range transport for NPF events, and the thus particles were not easily grown by coagulation during transport processes, which was helpful for occurrence of NPF events. Therefore, some effective control measures cooperatively controlled particle number and mass should be took for the Chinese megacities.

show abstract

Seasonality of the particle number concentration and size distribution: a global analysis retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories

et al. 2021

Self Cite

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Abstract. Aerosol particles are a complex component of the atmospheric system which influence climate directly by interacting with solar radiation, and indirectly by contributing to cloud formation. The variety of their sources, as well as the multiple transformations they may undergo during their transport (including wet and dry deposition), result in significant spatial and temporal variability of their properties. Documenting this variability is essential to provide a proper representation of aerosols and cloud condensation nuclei (CCN) in climate models. Using measurements conducted in 2016 or 2017 at 62 ground-based stations around the world, this study provides the most up-to-date picture of the spatial distribution of particle number concentration (Ntot) and number size distribution (PNSD, from 39 sites). A sensitivity study was first performed to assess the impact of data availability on Ntot's annual and seasonal statistics, as well as on the analysis of its diel cycle. Thresholds of 50 % and 60 % were set at the seasonal and annual scale, respectively, for the study of the corresponding statistics, and a slightly higher coverage (75 %) was required to document the diel cycle. Although some observations are common to a majority of sites, the variety of environments characterizing these stations made it possible to highlight contrasting findings, which, among other factors, seem to be significantly related to the level of anthropogenic influence. The concentrations measured at polar sites are the lowest (∼ 102 cm−3) and show a clear seasonality, which is also visible in the shape of the PNSD, while diel cycles are in general less evident, due notably to the absence of a regular day–night cycle in some seasons. In contrast, the concentrations characteristic of urban environments are the highest (∼ 103–104 cm−3) and do not show pronounced seasonal variations, whereas diel cycles tend to be very regular over the year at these stations. The remaining sites, including mountain and non-urban continental and coastal stations, do not exhibit as obvious common behaviour as polar and urban sites and display, on average, intermediate Ntot (∼ 102–103 cm−3). Particle concentrations measured at mountain sites, however, are generally lower compared to nearby lowland sites, and tend to exhibit somewhat more pronounced seasonal variations as a likely result of the strong impact of the atmospheric boundary layer (ABL) influence in connection with the topography of the sites. ABL dynamics also likely contribute to the diel cycle of Ntot observed at these stations. Based on available PNSD measurements, CCN-sized particles (considered here as either >50 nm or >100 nm) can represent from a few percent to almost all of Ntot, corresponding to seasonal medians on the order of ∼ 10 to 1000 cm−3, with seasonal patterns and a hierarchy of the site types broadly similar to those observed for Ntot. Overall, this work illustrates the importance of in situ measurements, in particular for the study of aerosol physical properties, and thus strongly supports the development of a broad global network of near surface observatories to increase and homogenize the spatial coverage of the measurements, and guarantee as well data availability and quality. The results of this study also provide a valuable, freely available and easy to use support for model comparison and validation, with the ultimate goal of contributing to improvement of the representation of aerosol–cloud interactions in models, and, therefore, of the evaluation of the impact of aerosol particles on climate.

show abstract

Seasonality of the particle number concentration and size distribution: a global analysis retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories

Cited by 3 publications

References 34 publications

Response of particle number concentrations to the clean air action plan: lessons from the first long-term aerosol measurements in a typical urban valley in western China

Response of particle number concentrations to the clean air action plan: lessons from the first long-term aerosol measurements in a typical urban valley in western China

Response of particle number concentrations to Clean Air Action: Lessons from the first long-term aerosol measurements in a typical urban valley, West China

Seasonality of the particle number concentration and size distribution: a global analysis retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories

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