Articles | Volume 7, issue 9
https://doi.org/10.5194/amt-7-2953-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-2953-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
16 Sep 2014
Research article |
| 16 Sep 2014
Measuring the atmospheric organic aerosol volatility distribution: a theoretical analysis
E. Karnezi
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, USA
I. Riipinen
Department of Applied Environmental Studies, Stockholm University, Stockholm, Sweden
S. N. Pandis
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, USA
Department of Chemical Engineering, University of Patras, Patra, Greece
Inst. of Chemical Engineering Sciences, FORTH/ICEHT, Patra, Greece
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Atmos. Chem. Phys., 24, 891–909, https://doi.org/10.5194/acp-24-891-2024, https://doi.org/10.5194/acp-24-891-2024, 2024
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Atmos. Chem. Phys., 23, 13555–13564, https://doi.org/10.5194/acp-23-13555-2023, https://doi.org/10.5194/acp-23-13555-2023, 2023
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Christina N. Vasilakopoulou, Kalliopi Florou, Christos Kaltsonoudis, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 16, 2837–2850, https://doi.org/10.5194/amt-16-2837-2023, https://doi.org/10.5194/amt-16-2837-2023, 2023
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Aristeidis Voliotis, Mao Du, Yu Wang, Yunqi Shao, Thomas J. Bannan, Michael Flynn, Spyros N. Pandis, Carl J. Percival, M. Rami Alfarra, and Gordon McFiggans
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Brian T. Dinkelacker, Pablo Garcia Rivera, Ksakousti Skyllakou, Peter J. Adams, and Spyros N. Pandis
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-648, https://doi.org/10.5194/acp-2022-648, 2022
Revised manuscript not accepted
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Pablo Garcia Rivera, Brian T. Dinkelacker, Ioannis Kioutsioukis, Peter J. Adams, and Spyros N. Pandis
Atmos. Chem. Phys., 22, 2011–2027, https://doi.org/10.5194/acp-22-2011-2022, https://doi.org/10.5194/acp-22-2011-2022, 2022
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The contribution of various pollution sources to the variability of fine PM in an urban area was examined using as an example the city of Pittsburgh. Biomass burning aerosol shows the largest variability during the winter with local maxima within the city and in the suburbs. During both periods the largest contributing source to the average PM2.5 is particles from outside the modeling domain. The average population-weighted PM2.5 concentration does not change significantly with resolution.
David Patoulias and Spyros N. Pandis
Atmos. Chem. Phys., 22, 1689–1706, https://doi.org/10.5194/acp-22-1689-2022, https://doi.org/10.5194/acp-22-1689-2022, 2022
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Our simulations indicate that the recently identified production and subsequent condensation effect of extremely low-volatility organic compounds have a smaller-than-expected effect on the total concentration of atmospheric particles. On the other hand, the oxidation of intermediate-volatility organic compounds leads to decreases in the ultrafine-particle concentrations. These results improve our understanding of the links between secondary organic aerosol formation and ultrafine particles.
Miska Olin, David Patoulias, Heino Kuuluvainen, Jarkko V. Niemi, Topi Rönkkö, Spyros N. Pandis, Ilona Riipinen, and Miikka Dal Maso
Atmos. Chem. Phys., 22, 1131–1148, https://doi.org/10.5194/acp-22-1131-2022, https://doi.org/10.5194/acp-22-1131-2022, 2022
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An emission factor particle size distribution was determined from the measurements at an urban traffic site. It was used in updating a pre-existing emission inventory, and regional modeling was performed after the update. Emission inventories typically underestimate nanoparticle emissions due to challenges in determining them with high certainty. This update reveals that the simulated aerosol levels have previously been underestimated especially for urban areas and for sub-50 nm particles.
Ksakousti Skyllakou, Pablo Garcia Rivera, Brian Dinkelacker, Eleni Karnezi, Ioannis Kioutsioukis, Carlos Hernandez, Peter J. Adams, and Spyros N. Pandis
Atmos. Chem. Phys., 21, 17115–17132, https://doi.org/10.5194/acp-21-17115-2021, https://doi.org/10.5194/acp-21-17115-2021, 2021
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Significant reductions in pollutant emissions took place in the US from 1990 to 2010. The reductions in sulfur dioxide emissions from electric-generating units have dominated the reductions in fine particle mass. The reductions in transportation emissions have led to a 30 % reduction of elemental concentrations and of organic particulate matter by a factor of 3. On the other hand, changes in biomass burning and biogenic secondary organic aerosol have been modest.
Spiro D. Jorga, Kalliopi Florou, Christos Kaltsonoudis, John K. Kodros, Christina Vasilakopoulou, Manuela Cirtog, Axel Fouqueau, Bénédicte Picquet-Varrault, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 21, 15337–15349, https://doi.org/10.5194/acp-21-15337-2021, https://doi.org/10.5194/acp-21-15337-2021, 2021
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We test the hypothesis that significant secondary organic aerosol production can take place even during winter nights through the oxidation of the emitted organic vapors by the nitrate radicals produced during the reaction of ozone and nitrogen oxides. Our experiments, using as a starting point the ambient air of an urban area with high biomass burning activity, demonstrate that, even with sunlight, there is 20 %–70 % additional organic aerosol formed in a few hours.
Aristeidis Voliotis, Yu Wang, Yunqi Shao, Mao Du, Thomas J. Bannan, Carl J. Percival, Spyros N. Pandis, M. Rami Alfarra, and Gordon McFiggans
Atmos. Chem. Phys., 21, 14251–14273, https://doi.org/10.5194/acp-21-14251-2021, https://doi.org/10.5194/acp-21-14251-2021, 2021
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Secondary organic aerosol (SOA) formation from mixtures of volatile precursors can be affected by the molecular interactions of the products. Composition and volatility measurements of SOA formed from mixtures of anthropogenic and biogenic precursors reveal processes that can increase or decrease the SOA volatility. The unique products of the mixture were more oxygenated and less volatile than those from either precursor. Analytical context is provided to explore the SOA volatility in mixtures.
Athanasios Nenes, Spyros N. Pandis, Maria Kanakidou, Armistead G. Russell, Shaojie Song, Petros Vasilakos, and Rodney J. Weber
Atmos. Chem. Phys., 21, 6023–6033, https://doi.org/10.5194/acp-21-6023-2021, https://doi.org/10.5194/acp-21-6023-2021, 2021
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Ecosystems and air quality are affected by the dry deposition of inorganic reactive nitrogen (Nr, the sum of ammonium and nitrate). Its large variability is driven by the large difference in deposition velocity of N when in the gas or particle phase. Here we show that aerosol liquid water and acidity, by affecting gas–particle partitioning, modulate the dry deposition velocity of NH3, HNO3, and Nr worldwide. These effects explain the rapid accumulation of nitrate aerosol during haze events.
Georgia N. Theodoritsi, Giancarlo Ciarelli, and Spyros N. Pandis
Geosci. Model Dev., 14, 2041–2055, https://doi.org/10.5194/gmd-14-2041-2021, https://doi.org/10.5194/gmd-14-2041-2021, 2021
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Two schemes based on the volatility basis set were used for the simulation of biomass burning organic aerosol (bbOA) in the continental US. The first is the default scheme of the PMCAMx-SR model, and the second is a recently developed scheme based on laboratory experiments. The alternative bbOA scheme predicts much higher concentrations. The default scheme performed better during summer and fall, while the alternative scheme was a little better during spring.
Weiqi Xu, Chun Chen, Yanmei Qiu, Ying Li, Zhiqiang Zhang, Eleni Karnezi, Spyros N. Pandis, Conghui Xie, Zhijie Li, Jiaxing Sun, Nan Ma, Wanyun Xu, Pingqing Fu, Zifa Wang, Jiang Zhu, Douglas R. Worsnop, Nga Lee Ng, and Yele Sun
Atmos. Chem. Phys., 21, 5463–5476, https://doi.org/10.5194/acp-21-5463-2021, https://doi.org/10.5194/acp-21-5463-2021, 2021
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Here aerosol volatility and viscosity at a rural site (Gucheng) and an urban site (Beijing) in the North China Plain (NCP) were investigated in summer and winter. Our results showed that organic aerosol (OA) in winter in the NCP is more volatile than that in summer due to enhanced primary emissions from coal combustion and biomass burning. We also found that OA existed mainly as a solid in winter in Beijing but as semisolids in Beijing in summer and Gucheng in winter.
Stylianos Kakavas, David Patoulias, Maria Zakoura, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 21, 799–811, https://doi.org/10.5194/acp-21-799-2021, https://doi.org/10.5194/acp-21-799-2021, 2021
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The dependence of aerosol acidity on particle size, location, and altitude over Europe during a summertime period is investigated. Differences of up to 1–4 pH units are predicted between sub- and supermicron particles in northern and southern Europe. Particles of all sizes become increasingly acidic with altitude (0.5–2.5 pH units decrease over 2.5 km). The size-dependent pH differences carry important implications for pH-sensitive processes in the aerosol.
Antonios Tasoglou, Evangelos Louvaris, Kalliopi Florou, Aikaterini Liangou, Eleni Karnezi, Christos Kaltsonoudis, Ningxin Wang, and Spyros N. Pandis
Atmos. Chem. Phys., 20, 11625–11637, https://doi.org/10.5194/acp-20-11625-2020, https://doi.org/10.5194/acp-20-11625-2020, 2020
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A month-long set of summertime measurements in a remote area in the Mediterranean is used to quantify aerosol absorption. The measured light absorption was two or more times higher than that of fresh black carbon. The absorption enhancement due to the coating of black carbon cores by other aerosol components could explain only part of this absorption enhancement. The rest was due to brown carbon, mostly in the form of extremely low volatility organic compounds.
Athanasios Nenes, Spyros N. Pandis, Rodney J. Weber, and Armistead Russell
Atmos. Chem. Phys., 20, 3249–3258, https://doi.org/10.5194/acp-20-3249-2020, https://doi.org/10.5194/acp-20-3249-2020, 2020
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We show that aerosol acidity (pH) and liquid water content naturally emerge as previously ignored parameters that drive particulate matter formation in the atmosphere, and its sensitivity to emissions of ammonia and nitric acid. The simple framework presented is easily applied to ambient measurements or model output, and it provides the
chemical regimeof PM sensitivity to ammonia and nitric acid availability.
Weiqi Xu, Conghui Xie, Eleni Karnezi, Qi Zhang, Junfeng Wang, Spyros N. Pandis, Xinlei Ge, Jingwei Zhang, Junling An, Qingqing Wang, Jian Zhao, Wei Du, Yanmei Qiu, Wei Zhou, Yao He, Ying Li, Jie Li, Pingqing Fu, Zifa Wang, Douglas R. Worsnop, and Yele Sun
Atmos. Chem. Phys., 19, 10205–10216, https://doi.org/10.5194/acp-19-10205-2019, https://doi.org/10.5194/acp-19-10205-2019, 2019
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We present the first aerosol volatility measurements in Beijing in summer using a thermodenuder coupled with aerosol mass spectrometers. Our results showed that organic aerosol (OA) comprised mainly semi-volatile organic compounds in summer, and the freshly oxidized secondary OA was the most volatile component. We also found quite different volatility distributions in black-carbon-containing primary and secondary OA, ambient OA, ambient secondary OA and the WRF-Chem model.
Christos Kaltsonoudis, Spiro D. Jorga, Evangelos Louvaris, Kalliopi Florou, and Spyros N. Pandis
Atmos. Meas. Tech., 12, 2733–2743, https://doi.org/10.5194/amt-12-2733-2019, https://doi.org/10.5194/amt-12-2733-2019, 2019
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A portable dual-smog-chamber system was developed using two identical pillow-shaped smog chambers surrounded by UV lamps. The system has been designed to use ambient air as the starting point of the experiments. It can be easily disassembled and transported, enabling the study of various atmospheric environments and it can be used with natural sunlight. The results of test experiments using ambient air are discussed as examples of applications of this system.
Katerina S. Karadima, Vlasis G. Mavrantzas, and Spyros N. Pandis
Atmos. Chem. Phys., 19, 5571–5587, https://doi.org/10.5194/acp-19-5571-2019, https://doi.org/10.5194/acp-19-5571-2019, 2019
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We explore the morphologies of multicomponent nanoparticles through atomistic molecular dynamics simulations under atmospherically relevant conditions. Phase separation is predicted for almost all simulated nanoparticles either between organics and inorganics or between hydrophobic and hydrophilic constituents. Three main particle types were identified: organic islands at the surface, inorganic core-organic shell morphologies and complex structures with hydrophobic and hydrophilic domains.
Georgia N. Theodoritsi and Spyros N. Pandis
Atmos. Chem. Phys., 19, 5403–5415, https://doi.org/10.5194/acp-19-5403-2019, https://doi.org/10.5194/acp-19-5403-2019, 2019
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The chemical transport model PMCAMx was extended to investigate the effects of partitioning and photochemical aging of biomass burning emissions on organic aerosol (OA) concentrations and was applied in Europe. During the summer, the contribution of biomass burning to total OA levels over continental Europe was 16 % and during winter 47 %. Intermediate volatility organic compounds are predicted to be important precursors of secondary OA from biomass burning.
Anthoula D. Drosatou, Ksakousti Skyllakou, Georgia N. Theodoritsi, and Spyros N. Pandis
Atmos. Chem. Phys., 19, 973–986, https://doi.org/10.5194/acp-19-973-2019, https://doi.org/10.5194/acp-19-973-2019, 2019
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The ability of positive matrix factorization (PMF) factor analysis to identify and quantify the organic aerosol (OA) sources accurately is tested in this modeling study. The estimated uncertainty of the contribution of fresh biomass burning is less than 30 % and of the other primary sources is less than 40 %, when these sources contribute more than 20 % to the OA. Τhe first oxygenated OA factor includes mainly highly aged OA, while the second oxygenated OA factor contains fresher secondary OA.
Ningxin Wang, Spiro D. Jorga, Jeffery R. Pierce, Neil M. Donahue, and Spyros N. Pandis
Atmos. Meas. Tech., 11, 6577–6588, https://doi.org/10.5194/amt-11-6577-2018, https://doi.org/10.5194/amt-11-6577-2018, 2018
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The interaction of particles with the chamber walls has been a significant source of uncertainty when analyzing results of secondary organic aerosol formation experiments performed in Teflon chambers. We evaluated the performance of several particle wall-loss correction methods for aging experiments of α-pinene ozonolysis products. Experimental procedures are proposed for the characterization of particle losses during different stages of these experiments.
David Patoulias, Christos Fountoukis, Ilona Riipinen, Ari Asmi, Markku Kulmala, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 13639–13654, https://doi.org/10.5194/acp-18-13639-2018, https://doi.org/10.5194/acp-18-13639-2018, 2018
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PMCAMx-UF, a 3-D chemical transport model focusing on the simulation of ultrafine particles, has been extended with the addition of the volatility basis set (VBS) approach for the simulation of organic aerosol. The model was applied in Europe and its predictions were evaluated against field observations collected during the PEGASOS 2012 campaign. The condensation of organics led to an increase (50–120 %) in the larger particles but the total number concentration decreased by 10–30 %.
Alexandra P. Tsimpidi, Vlassis A. Karydis, Andrea Pozzer, Spyros N. Pandis, and Jos Lelieveld
Geosci. Model Dev., 11, 3369–3389, https://doi.org/10.5194/gmd-11-3369-2018, https://doi.org/10.5194/gmd-11-3369-2018, 2018
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A new module, ORACLE 2-D, that calculates the concentrations of surrogate organic species in two-dimensional space defined by volatility and oxygen-to-carbon ratio has been developed and evaluated. ORACLE 2-D uses a simple photochemical aging scheme that efficiently simulates the net effects of fragmentation and functionalization. ORACLE 2-D can be used to compute the ability of organic particles to act as cloud condensation nuclei and serves as a tool to quantify their climatic impact.
Eleni Karnezi, Benjamin N. Murphy, Laurent Poulain, Hartmut Herrmann, Alfred Wiedensohler, Florian Rubach, Astrid Kiendler-Scharr, Thomas F. Mentel, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 10759–10772, https://doi.org/10.5194/acp-18-10759-2018, https://doi.org/10.5194/acp-18-10759-2018, 2018
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Different parameterizations of the organic aerosol (OA) formation and evolution are evaluated using ground and airborne measurements collected in the 2012 PEGASOS field campaign in the Po Valley (Italy). Total OA concentration and O : C ratios were reproduced within experimental error by a number of schemes. Anthropogenic secondary OA (SOA) contributed 15–25 % of the total OA, 20–35 % of SOA from intermediate volatility compounds oxidation, and 15–45 % of biogenic SOA depending on the scheme.
Evangelia Kostenidou, Eleni Karnezi, James R. Hite Jr., Aikaterini Bougiatioti, Kate Cerully, Lu Xu, Nga L. Ng, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 5799–5819, https://doi.org/10.5194/acp-18-5799-2018, https://doi.org/10.5194/acp-18-5799-2018, 2018
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The volatility distribution of organic aerosol (OA) and its sources during the Southern Oxidant and Aerosol Study (SOAS) was estimated. The volatility distribution of all components covered a wide range including both semi-volatile and low-volatility components. The oxygen content of the factors can be combined with their estimated volatility and hygroscopicity to provide a better view of their physical properties.
Ningxin Wang, Evangelia Kostenidou, Neil M. Donahue, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 3589–3601, https://doi.org/10.5194/acp-18-3589-2018, https://doi.org/10.5194/acp-18-3589-2018, 2018
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This study investigates aging in the α-pinene ozonolysis system with hydroxyl radicals (OH) through smog chamber experiments. After an equivalent of 2–4 days of typical atmospheric oxidation conditions, homogeneous OH oxidation of the α-pinene ozonolysis products resulted in a 20–40 % net increase in the organic aerosol concentration and an increase in aerosol O : C by up to 0.04. The relative humidity in the 5–50 % range had a minimum effect on aging.
Kerrigan P. Cain and Spyros N. Pandis
Atmos. Meas. Tech., 10, 4865–4876, https://doi.org/10.5194/amt-10-4865-2017, https://doi.org/10.5194/amt-10-4865-2017, 2017
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Hygroscopicity, oxidation level, and volatility of organic pollutants are three crucial properties that determine their fate in the atmosphere. This study assesses the feasibility of a novel measurement and analysis technique to determine these properties of organic aerosol
components at the same time and to establish their relationship.
Evangelos E. Louvaris, Eleni Karnezi, Evangelia Kostenidou, Christos Kaltsonoudis, and Spyros N. Pandis
Atmos. Meas. Tech., 10, 3909–3918, https://doi.org/10.5194/amt-10-3909-2017, https://doi.org/10.5194/amt-10-3909-2017, 2017
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A method for the determination of the organic aerosol volatility distribution combining thermodenuder and isothermal dilution measurements is developed. The approach was tested in experiments that were conducted in a smog chamber using organic aerosol produced during meat charbroiling. Addition of the dilution measurements to the thermodenuder data results in a lower uncertainty of the estimated vaporization enthalpy as well as the semivolatile content of the aerosol.
Alexandra P. Tsimpidi, Vlassis A. Karydis, Spyros N. Pandis, and Jos Lelieveld
Atmos. Chem. Phys., 17, 7345–7364, https://doi.org/10.5194/acp-17-7345-2017, https://doi.org/10.5194/acp-17-7345-2017, 2017
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We analyzed the sensitivity of model-predicted global-scale OA to parameters and assumptions that control primary emissions, photochemical aging, and the scavenging efficiency of LVOCs, SVOCs, and IVOCs. The simulated OA concentrations were evaluated against a global dataset of AMS measurements. According to our analysis, a combination of increased IVOCs and decreased hygroscopicity of the freshly emitted IVOCs can help reduce discrepancies between simulated SOA and observed OOA concentrations.
Christos Kaltsonoudis, Evangelia Kostenidou, Evangelos Louvaris, Magda Psichoudaki, Epameinondas Tsiligiannis, Kalliopi Florou, Aikaterini Liangou, and Spyros N. Pandis
Atmos. Chem. Phys., 17, 7143–7155, https://doi.org/10.5194/acp-17-7143-2017, https://doi.org/10.5194/acp-17-7143-2017, 2017
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Cooking emissions can be a significant source of particulate matter in urban areas. In this study the aerosol- and gas-phase emissions from meat charbroiling were characterized. More than 99% of the aerosol emitted was composed of organic compounds. The fresh particles were similar to the cooking organic aerosol over Greek cities during the winter, while the reacted particles were similar to those found in the atmosphere during the summer.
Kalliopi Florou, Dimitrios K. Papanastasiou, Michael Pikridas, Christos Kaltsonoudis, Evangelos Louvaris, Georgios I. Gkatzelis, David Patoulias, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Chem. Phys., 17, 3145–3163, https://doi.org/10.5194/acp-17-3145-2017, https://doi.org/10.5194/acp-17-3145-2017, 2017
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The composition of fine particulate matter (PM) in two major Greek cities (Athens and Patras) was measured during two wintertime campaigns in 2012 and 2013. Residential wood burning has dramatically increased due to the Greek financial crisis, contributing around 50 % of the fine PM on average and more than 80 % during nighttime. Cooking is also an important source during both midday and evening, while transportation dominates only during the morning rush hour.
Christos Kaltsonoudis, Evangelia Kostenidou, Kalliopi Florou, Magda Psichoudaki, and Spyros N. Pandis
Atmos. Chem. Phys., 16, 14825–14842, https://doi.org/10.5194/acp-16-14825-2016, https://doi.org/10.5194/acp-16-14825-2016, 2016
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Volatile organic compounds (VOCs) were monitored in urban backgrounds sites, in Athens and Patras in Greece. In summer most of the measured VOCs were due to biogenic and traffic emissions. Winter measurements in Athens revealed that biomass burning used for residential heating was the dominant VOC source. The biomass burning VOC emission ratios and emission factors were estimated.
Antigoni Panagiotopoulou, Panagiotis Charalampidis, Christos Fountoukis, Christodoulos Pilinis, and Spyros N. Pandis
Geosci. Model Dev., 9, 4257–4272, https://doi.org/10.5194/gmd-9-4257-2016, https://doi.org/10.5194/gmd-9-4257-2016, 2016
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The ability of chemical transport model PMCAMx to reproduce ground and satellite aerosol optical depth (AOD) measurements over Europe is evaluated. PMCAMx reproduces AOD values over Spain, the UK, central Europe, and Russia with a fractional bias of less than 15 % and a fractional error of less than 30 %. The model overestimates the AOD over northern Europe probably due to an overestimation of organic aerosol and sulfates, and underestimates over the Balkans due to an underestimation of sulfates.
Elham Baranizadeh, Benjamin N. Murphy, Jan Julin, Saeed Falahat, Carly L. Reddington, Antti Arola, Lars Ahlm, Santtu Mikkonen, Christos Fountoukis, David Patoulias, Andreas Minikin, Thomas Hamburger, Ari Laaksonen, Spyros N. Pandis, Hanna Vehkamäki, Kari E. J. Lehtinen, and Ilona Riipinen
Geosci. Model Dev., 9, 2741–2754, https://doi.org/10.5194/gmd-9-2741-2016, https://doi.org/10.5194/gmd-9-2741-2016, 2016
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The molecular mechanisms through which new ultrafine (< 100 nm) aerosol particles are formed in the atmosphere have puzzled the scientific community for decades. In the past few years, however, significant progress has been made in unraveling these processes through laboratory studies and computational efforts. In this work we have implemented these new developments to an air quality model and study the implications of anthropogenically driven particle formation for European air quality.
Alexandra P. Tsimpidi, Vlassis A. Karydis, Spyros N. Pandis, and Jos Lelieveld
Atmos. Chem. Phys., 16, 8939–8962, https://doi.org/10.5194/acp-16-8939-2016, https://doi.org/10.5194/acp-16-8939-2016, 2016
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In this work we use a global chemistry climate model together with a comprehensive global AMS data set in order to provide valuable insights into the temporal and geographical variability of the contribution of the emitted particles and the chemically processed organic material from combustion sources to total OA. This study reveals the high importance of SOA from anthropogenic sources on global OA concentrations and identifies plausible sources of discrepancy between models and measurements.
Christos Fountoukis, Athanasios G. Megaritis, Ksakousti Skyllakou, Panagiotis E. Charalampidis, Hugo A. C. Denier van der Gon, Monica Crippa, André S. H. Prévôt, Friederike Fachinger, Alfred Wiedensohler, Christodoulos Pilinis, and Spyros N. Pandis
Atmos. Chem. Phys., 16, 3727–3741, https://doi.org/10.5194/acp-16-3727-2016, https://doi.org/10.5194/acp-16-3727-2016, 2016
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We use PMCAMx with high grid resolution over Paris to simulate carbonaceous aerosol during the summer and winter MEGAPOLI campaigns. PMCAMx reproduces BC observations well. Addition of cooking organic aerosol emissions of 80 mg per day per capita is needed to reproduce the corresponding observations. While the oxygenated organic aerosol predictions during the summer are encouraging a major wintertime source appears to be missing.
Andrea Paciga, Eleni Karnezi, Evangelia Kostenidou, Lea Hildebrandt, Magda Psichoudaki, Gabriella J. Engelhart, Byong-Hyoek Lee, Monica Crippa, André S. H. Prévôt, Urs Baltensperger, and Spyros N. Pandis
Atmos. Chem. Phys., 16, 2013–2023, https://doi.org/10.5194/acp-16-2013-2016, https://doi.org/10.5194/acp-16-2013-2016, 2016
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We estimate the volatility distribution for the organic aerosol (OA) components during summer and winter field campaigns in Paris, France as part of the collaborative project MEGAPOLI. The OA factors (hydrocarbon like OA, cooking OA, marine OA, oxygenated OA) had a broad spectrum of volatilities with no direct link between the average volatility and average oxygen to carbon of the OA components.
G. I. Gkatzelis, D. K. Papanastasiou, K. Florou, C. Kaltsonoudis, E. Louvaris, and S. N. Pandis
Atmos. Meas. Tech., 9, 103–114, https://doi.org/10.5194/amt-9-103-2016, https://doi.org/10.5194/amt-9-103-2016, 2016
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A method for the measurement of the nonvolatile atmospheric particle size distribution is developed and tested. The tests include laboratory experiments with biogenic and anthropogenic secondary organic aerosol as well as nucleation experiments with ambient air. The method is then further tested during an ambient campaign.
J. Zábori, N. Rastak, Y. J. Yoon, I. Riipinen, and J. Ström
Atmos. Chem. Phys., 15, 13803–13817, https://doi.org/10.5194/acp-15-13803-2015, https://doi.org/10.5194/acp-15-13803-2015, 2015
C. E. Scott, D. V. Spracklen, J. R. Pierce, I. Riipinen, S. D. D'Andrea, A. Rap, K. S. Carslaw, P. M. Forster, P. Artaxo, M. Kulmala, L. V. Rizzo, E. Swietlicki, G. W. Mann, and K. J. Pringle
Atmos. Chem. Phys., 15, 12989–13001, https://doi.org/10.5194/acp-15-12989-2015, https://doi.org/10.5194/acp-15-12989-2015, 2015
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To understand the radiative effects of biogenic secondary organic aerosol (SOA) it is necessary to consider the manner in which it is distributed across the existing aerosol size distribution. We explore the importance of the approach taken by global-scale models to do this, when calculating the direct radiative effect (DRE) & first aerosol indirect effect (AIE) due to biogenic SOA. This choice has little effect on the DRE, but a substantial impact on the magnitude and even sign of the first AIE
E. Kostenidou, K. Florou, C. Kaltsonoudis, M. Tsiflikiotou, S. Vratolis, K. Eleftheriadis, and S. N. Pandis
Atmos. Chem. Phys., 15, 11355–11371, https://doi.org/10.5194/acp-15-11355-2015, https://doi.org/10.5194/acp-15-11355-2015, 2015
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The concentration and chemical composition of fine particulate matter were measured during the summer of 2012 in two Greek cities, Patras and Athens. The composition of PM1 was surprisingly similar in both areas, demonstrating the importance of regional sources. Analysis of the Aerosol Mass Spectrometer data suggested that the contribution of the primary sources to organic aerosol was important (22% in Patras and 35% in Athens) but not dominant.
M. Pikridas, J. Sciare, F. Freutel, S. Crumeyrolle, S.-L. von der Weiden-Reinmüller, A. Borbon, A. Schwarzenboeck, M. Merkel, M. Crippa, E. Kostenidou, M. Psichoudaki, L. Hildebrandt, G. J. Engelhart, T. Petäjä, A. S. H. Prévôt, F. Drewnick, U. Baltensperger, A. Wiedensohler, M. Kulmala, M. Beekmann, and S. N. Pandis
Atmos. Chem. Phys., 15, 10219–10237, https://doi.org/10.5194/acp-15-10219-2015, https://doi.org/10.5194/acp-15-10219-2015, 2015
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Aerosol size distribution measurements from three ground sites, two mobile laboratories, and one airplane are combined to investigate the spatial and temporal variability of ultrafine particles in and around Paris during the summer and winter MEGAPOLI campaigns. The role of nucleation as a particle source and the influence of Paris emissions on their surroundings are examined.
M. Beekmann, A. S. H. Prévôt, F. Drewnick, J. Sciare, S. N. Pandis, H. A. C. Denier van der Gon, M. Crippa, F. Freutel, L. Poulain, V. Ghersi, E. Rodriguez, S. Beirle, P. Zotter, S.-L. von der Weiden-Reinmüller, M. Bressi, C. Fountoukis, H. Petetin, S. Szidat, J. Schneider, A. Rosso, I. El Haddad, A. Megaritis, Q. J. Zhang, V. Michoud, J. G. Slowik, S. Moukhtar, P. Kolmonen, A. Stohl, S. Eckhardt, A. Borbon, V. Gros, N. Marchand, J. L. Jaffrezo, A. Schwarzenboeck, A. Colomb, A. Wiedensohler, S. Borrmann, M. Lawrence, A. Baklanov, and U. Baltensperger
Atmos. Chem. Phys., 15, 9577–9591, https://doi.org/10.5194/acp-15-9577-2015, https://doi.org/10.5194/acp-15-9577-2015, 2015
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A detailed characterization of air quality in the Paris (France) agglomeration, a megacity, during two summer and winter intensive campaigns and from additional 1-year observations, revealed that about 70% of the fine particulate matter (PM) at urban background is transported into the megacity from upwind regions. Unexpectedly, a major part of organic PM is of modern origin (woodburning and cooking activities, secondary formation from biogenic VOC).
S. Fuzzi, U. Baltensperger, K. Carslaw, S. Decesari, H. Denier van der Gon, M. C. Facchini, D. Fowler, I. Koren, B. Langford, U. Lohmann, E. Nemitz, S. Pandis, I. Riipinen, Y. Rudich, M. Schaap, J. G. Slowik, D. V. Spracklen, E. Vignati, M. Wild, M. Williams, and S. Gilardoni
Atmos. Chem. Phys., 15, 8217–8299, https://doi.org/10.5194/acp-15-8217-2015, https://doi.org/10.5194/acp-15-8217-2015, 2015
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Particulate matter (PM) constitutes one of the most challenging problems both for air quality and climate change policies. This paper reviews the most recent scientific results on the issue and the policy needs that have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate-PM interactions and the effects of PM on human health and the environment.
L. Hildebrandt Ruiz, A. L. Paciga, K. M. Cerully, A. Nenes, N. M. Donahue, and S. N. Pandis
Atmos. Chem. Phys., 15, 8301–8313, https://doi.org/10.5194/acp-15-8301-2015, https://doi.org/10.5194/acp-15-8301-2015, 2015
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Secondary organic aerosol (SOA) is transformed after its initial formation. We explored the effects of this chemical aging on the composition, mass yield, volatility, and hygroscopicity of SOA formed from the photo-oxidation of small aromatic volatile organic compounds. Higher exposure to the hydroxyl radical resulted in different SOA composition, average carbon oxidation state, and mass yield. The vapor pressure of SOA formed under different conditions varied by as much as a factor of 30.
D. Patoulias, C. Fountoukis, I. Riipinen, and S. N. Pandis
Atmos. Chem. Phys., 15, 6337–6350, https://doi.org/10.5194/acp-15-6337-2015, https://doi.org/10.5194/acp-15-6337-2015, 2015
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A new aerosol dynamics model (DMANx) describing the organic vapor condensation on nanoparticles based on the volatility basis set framework is used to simulate typical nucleation events in two contrasting environments in Hyytiälä (Finland) and Finokalia (Greece). The role of semivolatile, low, and extremely low volatility organics and the corresponding surface energies is investigated.
I. Riipinen, N. Rastak, and S. N. Pandis
Atmos. Chem. Phys., 15, 6305–6322, https://doi.org/10.5194/acp-15-6305-2015, https://doi.org/10.5194/acp-15-6305-2015, 2015
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Atmospheric organic aerosol is complex and thus a challenge to model. We introduce a theoretical framework (solubility distributions) to represent the solubility of multicomponent mixtures. Using the framework, we evaluate the commonly made assumptions about the cloud condensation nucleus (CCN) activity of organic mixtures. We find that material with water solubilities larger than 0.1-100 g/L can usually be treated as completely soluble, which simplifies the treatment of organic CCN.
A. Tasoglou and S. N. Pandis
Atmos. Chem. Phys., 15, 6035–6046, https://doi.org/10.5194/acp-15-6035-2015, https://doi.org/10.5194/acp-15-6035-2015, 2015
M. Dalirian, H. Keskinen, L. Ahlm, A. Ylisirniö, S. Romakkaniemi, A. Laaksonen, A. Virtanen, and I. Riipinen
Atmos. Chem. Phys., 15, 3815–3829, https://doi.org/10.5194/acp-15-3815-2015, https://doi.org/10.5194/acp-15-3815-2015, 2015
S. D. D'Andrea, J. C. Acosta Navarro, S. C. Farina, C. E. Scott, A. Rap, D. K. Farmer, D. V. Spracklen, I. Riipinen, and J. R. Pierce
Atmos. Chem. Phys., 15, 2247–2268, https://doi.org/10.5194/acp-15-2247-2015, https://doi.org/10.5194/acp-15-2247-2015, 2015
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We use modeled estimates of BVOCs from the years 1000 to 2000 to test the effect of anthropogenic BVOC emission changes on SOA formation, aerosol size distributions, and radiative effects using the GEOS-Chem-TOMAS model. Changes of >25% in the number of particles with diameters >80nm are predicted regionally due to extensive land-use changes, leading to increases in combined radiative effect of >0.5 Wm-2. This change in radiative forcing could be an overlooked anthropogenic effect on climate.
A. P. Tsimpidi, V. A. Karydis, A. Pozzer, S. N. Pandis, and J. Lelieveld
Geosci. Model Dev., 7, 3153–3172, https://doi.org/10.5194/gmd-7-3153-2014, https://doi.org/10.5194/gmd-7-3153-2014, 2014
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A computationally efficient module for the description of OA composition and evolution in the atmosphere has been developed. This module subdivides OA into several compounds based on their source of origin and volatility, allowing the quantification of POA vs. SOA as well as biogenic vs. anthropogenic contributions to OA concentrations. Such fundamental information can shed light on long-term changes in OA abundance, and hence project the effects of OA on future air quality and climate.
A. G. Megaritis, C. Fountoukis, P. E. Charalampidis, H. A. C. Denier van der Gon, C. Pilinis, and S. N. Pandis
Atmos. Chem. Phys., 14, 10283–10298, https://doi.org/10.5194/acp-14-10283-2014, https://doi.org/10.5194/acp-14-10283-2014, 2014
C. Fountoukis, A. G. Megaritis, K. Skyllakou, P. E. Charalampidis, C. Pilinis, H. A. C. Denier van der Gon, M. Crippa, F. Canonaco, C. Mohr, A. S. H. Prévôt, J. D. Allan, L. Poulain, T. Petäjä, P. Tiitta, S. Carbone, A. Kiendler-Scharr, E. Nemitz, C. O'Dowd, E. Swietlicki, and S. N. Pandis
Atmos. Chem. Phys., 14, 9061–9076, https://doi.org/10.5194/acp-14-9061-2014, https://doi.org/10.5194/acp-14-9061-2014, 2014
N. Rastak, S. Silvergren, P. Zieger, U. Wideqvist, J. Ström, B. Svenningsson, M. Maturilli, M. Tesche, A. M. L. Ekman, P. Tunved, and I. Riipinen
Atmos. Chem. Phys., 14, 7445–7460, https://doi.org/10.5194/acp-14-7445-2014, https://doi.org/10.5194/acp-14-7445-2014, 2014
M. Crippa, F. Canonaco, V. A. Lanz, M. Äijälä, J. D. Allan, S. Carbone, G. Capes, D. Ceburnis, M. Dall'Osto, D. A. Day, P. F. DeCarlo, M. Ehn, A. Eriksson, E. Freney, L. Hildebrandt Ruiz, R. Hillamo, J. L. Jimenez, H. Junninen, A. Kiendler-Scharr, A.-M. Kortelainen, M. Kulmala, A. Laaksonen, A. A. Mensah, C. Mohr, E. Nemitz, C. O'Dowd, J. Ovadnevaite, S. N. Pandis, T. Petäjä, L. Poulain, S. Saarikoski, K. Sellegri, E. Swietlicki, P. Tiitta, D. R. Worsnop, U. Baltensperger, and A. S. H. Prévôt
Atmos. Chem. Phys., 14, 6159–6176, https://doi.org/10.5194/acp-14-6159-2014, https://doi.org/10.5194/acp-14-6159-2014, 2014
B. N. Murphy, N. M. Donahue, A. L. Robinson, and S. N. Pandis
Atmos. Chem. Phys., 14, 5825–5839, https://doi.org/10.5194/acp-14-5825-2014, https://doi.org/10.5194/acp-14-5825-2014, 2014
A. Bougiatioti, I. Stavroulas, E. Kostenidou, P. Zarmpas, C. Theodosi, G. Kouvarakis, F. Canonaco, A. S. H. Prévôt, A. Nenes, S. N. Pandis, and N. Mihalopoulos
Atmos. Chem. Phys., 14, 4793–4807, https://doi.org/10.5194/acp-14-4793-2014, https://doi.org/10.5194/acp-14-4793-2014, 2014
J. Hong, S. A. K. Häkkinen, M. Paramonov, M. Äijälä, J. Hakala, T. Nieminen, J. Mikkilä, N. L. Prisle, M. Kulmala, I. Riipinen, M. Bilde, V.-M. Kerminen, and T. Petäjä
Atmos. Chem. Phys., 14, 4733–4748, https://doi.org/10.5194/acp-14-4733-2014, https://doi.org/10.5194/acp-14-4733-2014, 2014
E.-M. Kyrö, R. Väänänen, V.-M. Kerminen, A. Virkkula, T. Petäjä, A. Asmi, M. Dal Maso, T. Nieminen, S. Juhola, A. Shcherbinin, I. Riipinen, K. Lehtipalo, P. Keronen, P. P. Aalto, P. Hari, and M. Kulmala
Atmos. Chem. Phys., 14, 4383–4396, https://doi.org/10.5194/acp-14-4383-2014, https://doi.org/10.5194/acp-14-4383-2014, 2014
K. Skyllakou, B. N. Murphy, A. G. Megaritis, C. Fountoukis, and S. N. Pandis
Atmos. Chem. Phys., 14, 2343–2352, https://doi.org/10.5194/acp-14-2343-2014, https://doi.org/10.5194/acp-14-2343-2014, 2014
T. Yli-Juuti, K. Barsanti, L. Hildebrandt Ruiz, A.-J. Kieloaho, U. Makkonen, T. Petäjä, T. Ruuskanen, M. Kulmala, and I. Riipinen
Atmos. Chem. Phys., 13, 12507–12524, https://doi.org/10.5194/acp-13-12507-2013, https://doi.org/10.5194/acp-13-12507-2013, 2013
L. Ahlm, J. Julin, C. Fountoukis, S. N. Pandis, and I. Riipinen
Atmos. Chem. Phys., 13, 10271–10283, https://doi.org/10.5194/acp-13-10271-2013, https://doi.org/10.5194/acp-13-10271-2013, 2013
E. Kostenidou, C. Kaltsonoudis, M. Tsiflikiotou, E. Louvaris, L. M. Russell, and S. N. Pandis
Atmos. Chem. Phys., 13, 8797–8811, https://doi.org/10.5194/acp-13-8797-2013, https://doi.org/10.5194/acp-13-8797-2013, 2013
S. A. K. Häkkinen, H. E. Manninen, T. Yli-Juuti, J. Merikanto, M. K. Kajos, T. Nieminen, S. D. D'Andrea, A. Asmi, J. R. Pierce, M. Kulmala, and I. Riipinen
Atmos. Chem. Phys., 13, 7665–7682, https://doi.org/10.5194/acp-13-7665-2013, https://doi.org/10.5194/acp-13-7665-2013, 2013
D. M. Westervelt, J. R. Pierce, I. Riipinen, W. Trivitayanurak, A. Hamed, M. Kulmala, A. Laaksonen, S. Decesari, and P. J. Adams
Atmos. Chem. Phys., 13, 7645–7663, https://doi.org/10.5194/acp-13-7645-2013, https://doi.org/10.5194/acp-13-7645-2013, 2013
Q. J. Zhang, M. Beekmann, F. Drewnick, F. Freutel, J. Schneider, M. Crippa, A. S. H. Prevot, U. Baltensperger, L. Poulain, A. Wiedensohler, J. Sciare, V. Gros, A. Borbon, A. Colomb, V. Michoud, J.-F. Doussin, H. A. C. Denier van der Gon, M. Haeffelin, J.-C. Dupont, G. Siour, H. Petetin, B. Bessagnet, S. N. Pandis, A. Hodzic, O. Sanchez, C. Honoré, and O. Perrussel
Atmos. Chem. Phys., 13, 5767–5790, https://doi.org/10.5194/acp-13-5767-2013, https://doi.org/10.5194/acp-13-5767-2013, 2013
H. Keskinen, A. Virtanen, J. Joutsensaari, G. Tsagkogeorgas, J. Duplissy, S. Schobesberger, M. Gysel, F. Riccobono, J. G. Slowik, F. Bianchi, T. Yli-Juuti, K. Lehtipalo, L. Rondo, M. Breitenlechner, A. Kupc, J. Almeida, A. Amorim, E. M. Dunne, A. J. Downard, S. Ehrhart, A. Franchin, M.K. Kajos, J. Kirkby, A. Kürten, T. Nieminen, V. Makhmutov, S. Mathot, P. Miettinen, A. Onnela, T. Petäjä, A. Praplan, F. D. Santos, S. Schallhart, M. Sipilä, Y. Stozhkov, A. Tomé, P. Vaattovaara, D. Wimmer, A. Prevot, J. Dommen, N. M. Donahue, R.C. Flagan, E. Weingartner, Y. Viisanen, I. Riipinen, A. Hansel, J. Curtius, M. Kulmala, D. R. Worsnop, U. Baltensperger, H. Wex, F. Stratmann, and A. Laaksonen
Atmos. Chem. Phys., 13, 5587–5600, https://doi.org/10.5194/acp-13-5587-2013, https://doi.org/10.5194/acp-13-5587-2013, 2013
L. Riuttanen, M. Dal Maso, G. de Leeuw, I. Riipinen, L. Sogacheva, V. Vakkari, L. Laakso, and M. Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-4289-2013, https://doi.org/10.5194/acpd-13-4289-2013, 2013
Revised manuscript has not been submitted
E. Athanasopoulou, H. Vogel, B. Vogel, A. P. Tsimpidi, S. N. Pandis, C. Knote, and C. Fountoukis
Atmos. Chem. Phys., 13, 625–645, https://doi.org/10.5194/acp-13-625-2013, https://doi.org/10.5194/acp-13-625-2013, 2013
V.-M. Kerminen, M. Paramonov, T. Anttila, I. Riipinen, C. Fountoukis, H. Korhonen, E. Asmi, L. Laakso, H. Lihavainen, E. Swietlicki, B. Svenningsson, A. Asmi, S. N. Pandis, M. Kulmala, and T. Petäjä
Atmos. Chem. Phys., 12, 12037–12059, https://doi.org/10.5194/acp-12-12037-2012, https://doi.org/10.5194/acp-12-12037-2012, 2012
Related subject area
Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
A novel probabilistic source apportionment approach: Bayesian auto-correlated matrix factorization
Towards a hygroscopic growth calibration for low-cost PM2.5 sensors
Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry
Machine learning approaches for automatic classification of single-particle mass spectrometry data
A searchable database and mass spectral comparison tool for the Aerosol Mass Spectrometer (AMS) and the Aerosol Chemical Speciation Monitor (ACSM)
Numerical investigation on retrieval errors of mixing states of fractal black carbon aerosols using single-particle soot photometer based on Mie scattering and the effects on radiative forcing estimation
Performance evaluation of MOMA (MOment MAtching) – a remote network calibration technique for PM2.5 and PM10 sensors
Mapping the performance of a versatile water-based condensation particle counter (vWCPC) with numerical simulation and experimental study
Development and evaluation of an improved offline aerosol mass spectrometry technique
SMEARcore – modular data infrastructure for atmospheric measurement stations
A multiple-charging correction algorithm for a broad-supersaturation scanning cloud condensation nuclei (BS2-CCN) system
An evaluation of the U.S. EPA's correction equation for PurpleAir sensor data in smoke, dust, and wintertime urban pollution events
Typhoon-associated air quality over the Guangdong–Hong Kong–Macao Greater Bay Area, China: machine-learning-based prediction and assessment
Quantification of primary and secondary organic aerosol sources by combined factor analysis of extractive electrospray ionisation and aerosol mass spectrometer measurements (EESI-TOF and AMS)
A new method for calculating average visibility from the relationship between extinction coefficient and visibility
In situ particle sampling relationships to surface and turbulent fluxes using large eddy simulations with Lagrangian particles
The effect of the averaging period for PMF analysis of aerosol mass spectrometer measurements during offline applications
Calibrating networks of low-cost air quality sensors
Source apportionment resolved by time of day for improved deconvolution of primary source contributions to air pollution
Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data
Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison
Comprehensive detection of analytes in large chromatographic datasets by coupling factor analysis with a decision tree
Combined organic and inorganic source apportionment on yearlong ToF-ACSM dataset at a suburban station in Athens
Retrieval of the sea spray aerosol mode from submicron particle size distributions and supermicron scattering during LASIC
Automated identification of local contamination in remote atmospheric composition time series
Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques
Regularized inversion of aerosol hygroscopic growth factor probability density function: application to humidity-controlled fast integrated mobility spectrometer measurements
A systematic re-evaluation of methods for quantification of bulk particle-phase organic nitrates using real-time aerosol mass spectrometry
Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data
Data imputation in in situ-measured particle size distributions by means of neural networks
Analysis of mobile monitoring data from the microAeth® MA200 for measuring changes in black carbon on the roadside in Augsburg
New correction method for the scattering coefficient measurements of a three-wavelength nephelometer
Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network
Modeled source apportionment of black carbon particles coated with a light-scattering shell
Estimation of particulate organic nitrates from thermodenuder–aerosol mass spectrometer measurements in the North China Plain
Aerosol pH indicator and organosulfate detectability from aerosol mass spectrometry measurements
Determination of equivalent black carbon mass concentration from aerosol light absorption using variable mass absorption cross section
Effects of multi-charge on aerosol hygroscopicity measurement by a HTDMA
A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to 1 year of organic aerosol data
Estimation of pollen counts from light scattering intensity when sampling multiple pollen taxa – establishment of an automated multi-taxa pollen counting estimation system (AME system)
A novel lidar gradient cluster analysis method of nocturnal boundary layer detection during air pollution episodes
Assessment of particle size magnifier inversion methods to obtain the particle size distribution from atmospheric measurements
A global analysis of climate-relevant aerosol properties retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories
Development of an automatic linear calibration method for high-resolution single-particle mass spectrometry: improved chemical species identification for atmospheric aerosols
A hybrid method for reconstructing the historical evolution of aerosol optical depth from sunshine duration measurements
The influence of the baseline drift on the resulting extinction values of a cavity attenuated phase shift-based extinction monitor (CAPS PMex)
Evaluation of equivalent black carbon source apportionment using observations from Switzerland between 2008 and 2018
Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations
Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles
Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in Delhi
Anton Rusanen, Anton Björklund, Manousos I. Manousakas, Jianhui Jiang, Markku T. Kulmala, Kai Puolamäki, and Kaspar R. Daellenbach
Atmos. Meas. Tech., 17, 1251–1277, https://doi.org/10.5194/amt-17-1251-2024, https://doi.org/10.5194/amt-17-1251-2024, 2024
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We present a Bayesian non-negative matrix factorization model that performs better on our test datasets than currently widely used models. Its advantages are better use of time information and providing a direct error estimation. We believe this could lead to better estimates of emission sources from measurements.
Milan Y. Patel, Pietro F. Vannucci, Jinsol Kim, William M. Berelson, and Ronald C. Cohen
Atmos. Meas. Tech., 17, 1051–1060, https://doi.org/10.5194/amt-17-1051-2024, https://doi.org/10.5194/amt-17-1051-2024, 2024
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Low-cost particulate matter (PM) sensors are becoming increasingly common in community monitoring and atmospheric research, but these sensors require proper calibration to provide accurate reporting. Here, we propose a hygroscopic growth calibration scheme that evolves in time to account for seasonal changes in hygroscopic growth. In San Francisco and Los Angeles, CA, applying a seasonal hygroscopic growth calibration can account for sensor biases driven by the seasonal cycles in PM composition.
Xinlei Ge, Yele Sun, Justin Trousdell, Mindong Chen, and Qi Zhang
Atmos. Meas. Tech., 17, 423–439, https://doi.org/10.5194/amt-17-423-2024, https://doi.org/10.5194/amt-17-423-2024, 2024
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This study aims to enhance the application of the Aerodyne high-resolution aerosol mass spectrometer (HR-AMS) in characterizing organic nitrogen (ON) species within aerosol particles and droplets. A thorough analysis was conducted on 75 ON standards that represent a diverse spectrum of ambient ON types. The results underscore the capacity of the HR-AMS in examining the concentration and chemistry of atmospheric ON compounds, thereby offering insights into their sources and environmental impacts.
Guanzhong Wang, Heinrich Ruser, Julian Schade, Johannes Passig, Thomas Adam, Günther Dollinger, and Ralf Zimmermann
Atmos. Meas. Tech., 17, 299–313, https://doi.org/10.5194/amt-17-299-2024, https://doi.org/10.5194/amt-17-299-2024, 2024
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This research aims to develop a novel warning system for the real-time monitoring of pollutants in the atmosphere. The system is capable of sampling and investigating airborne aerosol particles on-site, utilizing artificial intelligence to learn their chemical signatures and to classify them in real time. We applied single-particle mass spectrometry for analyzing the chemical composition of aerosol particles and suggest several supervised algorithms for highly reliable automatic classification.
Sohyeon Jeon, Michael J. Walker, Donna T. Sueper, Douglas A. Day, Anne V. Handschy, Jose L. Jimenez, and Brent J. Williams
Atmos. Meas. Tech., 16, 6075–6095, https://doi.org/10.5194/amt-16-6075-2023, https://doi.org/10.5194/amt-16-6075-2023, 2023
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A searchable database tool for the Aerosol Mass Spectrometer (AMS) and Aerosol Chemical Speciation Monitor (ACSM) mass spectral datasets was built to improve the efficiency of data analysis using Igor Pro. The tool incorporates the published mass spectra (MS) and sample information uploaded on the website. The tool allows users to compare their own mass spectrum with the reference MS in the database.
Jia Liu, Guangya Wang, Cancan Zhu, Donghui Zhou, and Lin Wang
Atmos. Meas. Tech., 16, 4961–4974, https://doi.org/10.5194/amt-16-4961-2023, https://doi.org/10.5194/amt-16-4961-2023, 2023
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Single-particle soot photometer (SP2) employs the core-shell model to represent coated BC particles, which introduces retrieval errors in the mixing state (Dp/Dc) of BC. We construct fractal models to represent thinly and thickly coated BC particles, and the retrieval errors of the mixing state are investigated from the numerical aspect. We find that errors in Dp/Dc are noteworthy, and the errors in Dp/Dc can further affect the evaluation accuracy of the radiative forcing of BC.
Lena Francesca Weissert, Geoff Steven Henshaw, David Edward Williams, Brandon Feenstra, Randy Lam, Ashley Collier-Oxandale, Vasileios Papapostolou, and Andrea Polidori
Atmos. Meas. Tech., 16, 4709–4722, https://doi.org/10.5194/amt-16-4709-2023, https://doi.org/10.5194/amt-16-4709-2023, 2023
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We apply a previously developed remote calibration framework to a network of particulate matter (PM) sensors deployed in Southern California. Our results show that a remote calibration can improve the accuracy of PM data, which was particularly visible for PM10. We highlight that sensor drift was mostly due to differences in particle composition than monitor operational factors. Thus, PM sensors may require frequent calibration if PM sources vary with different wind conditions or seasons.
Weixing Hao, Fan Mei, Susanne Hering, Steven Spielman, Beat Schmid, Jason Tomlinson, and Yang Wang
Atmos. Meas. Tech., 16, 3973–3986, https://doi.org/10.5194/amt-16-3973-2023, https://doi.org/10.5194/amt-16-3973-2023, 2023
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Airborne aerosol instrumentation plays a crucial role in understanding the spatial distribution of ambient aerosol particles. This study investigates a versatile water-based condensation particle counter through simulations and experiments. It provides valuable insights to improve versatile water-based condensation particle counter (vWCPC) aerosol measurement and operation for the community.
Christina N. Vasilakopoulou, Kalliopi Florou, Christos Kaltsonoudis, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 16, 2837–2850, https://doi.org/10.5194/amt-16-2837-2023, https://doi.org/10.5194/amt-16-2837-2023, 2023
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The offline aerosol mass spectrometry technique is a useful tool for the source apportionment of organic aerosol in areas and periods during which an aerosol mass spectrometer is not available. In this work, an improved offline technique was developed and evaluated in an effort to capture most of the partially soluble and insoluble organic aerosol material, reducing the uncertainty of the corresponding source apportionment significantly.
Anton Rusanen, Kristo Hõrrak, Lauri R. Ahonen, Tuomo Nieminen, Pasi P. Aalto, Pasi Kolari, Markku Kulmala, Tuukka Petäjä, and Heikki Junninen
Atmos. Meas. Tech., 16, 2781–2793, https://doi.org/10.5194/amt-16-2781-2023, https://doi.org/10.5194/amt-16-2781-2023, 2023
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We present a framework for setting up SMEAR (Station for Measuring Ecosystem–Atmosphere Relations) type measurement station data flows. This framework, called SMEARcore, consists of modular open-source software components that can be chosen to suit various station configurations. The benefits of using this framework are automation of routine operations and real-time monitoring of measurement results.
Najin Kim, Hang Su, Nan Ma, Ulrich Pöschl, and Yafang Cheng
Atmos. Meas. Tech., 16, 2771–2780, https://doi.org/10.5194/amt-16-2771-2023, https://doi.org/10.5194/amt-16-2771-2023, 2023
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We propose a multiple-charging correction algorithm for a broad-supersaturation scanning cloud condensation nuclei (BS2-CCN) system which can obtain high time-resolution aerosol hygroscopicity and CCN activity. The correction algorithm aims at deriving the activation fraction's true value for each particle size. The meaningful differences between corrected and original κ values (single hygroscopicity parameter) emphasize the correction algorithm's importance for ambient aerosol measurement.
Daniel A. Jaffe, Colleen Miller, Katie Thompson, Brandon Finley, Manna Nelson, James Ouimette, and Elisabeth Andrews
Atmos. Meas. Tech., 16, 1311–1322, https://doi.org/10.5194/amt-16-1311-2023, https://doi.org/10.5194/amt-16-1311-2023, 2023
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PurpleAir sensors (PASs) are low-cost tools to measure fine particulate matter (PM) concentrations. However, the raw PAS data have significant biases, so the sensors must be corrected. We analyzed data from numerous sites and found that the standard correction to the PAS Purple Air data is accurate in urban pollution events and smoke events but leads to a 6-fold underestimate in the PM2.5 concentrations in dust events. We propose a new correction algorithm to address this problem.
Yilin Chen, Yuanjian Yang, and Meng Gao
Atmos. Meas. Tech., 16, 1279–1294, https://doi.org/10.5194/amt-16-1279-2023, https://doi.org/10.5194/amt-16-1279-2023, 2023
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The Guangdong–Hong Kong–Macao Greater Bay Area suffers from summertime air pollution events related to typhoons. The present study leverages machine learning to predict typhoon-associated air quality over the area. The model evaluation shows that the model performs excellently. Moreover, the change in meteorological drivers of air quality on typhoon days and non-typhoon days suggests that air pollution control strategies should have different focuses on typhoon days and non-typhoon days.
Yandong Tong, Lu Qi, Giulia Stefenelli, Dongyu Simon Wang, Francesco Canonaco, Urs Baltensperger, André Stephan Henry Prévôt, and Jay Gates Slowik
Atmos. Meas. Tech., 15, 7265–7291, https://doi.org/10.5194/amt-15-7265-2022, https://doi.org/10.5194/amt-15-7265-2022, 2022
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We present a method for positive matrix factorisation (PMF) analysis on a single dataset that includes measurements from both EESI-TOF and AMS in Zurich, Switzerland. For the first time, we resolved and quantified secondary organic aerosol (SOA) sources. Meanwhile, we also determined the retrieved EESI-TOF factor-dependent sensitivities. This method provides a framework for exploiting semi-quantitative, high-resolution instrumentation for quantitative source apportionment.
Zefeng Zhang, Hengnan Guo, Hanqing Kang, Jing Wang, Junlin An, Xingna Yu, Jingjing Lv, and Bin Zhu
Atmos. Meas. Tech., 15, 7259–7264, https://doi.org/10.5194/amt-15-7259-2022, https://doi.org/10.5194/amt-15-7259-2022, 2022
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In this study, we first analyze the relationship between the visibility, the extinction coefficient, and atmospheric compositions. Then we propose to use the harmonic average of visibility data as the average visibility, which can better reflect changes in atmospheric extinction coefficients and aerosol concentrations. It is recommended to use the harmonic average visibility in the studies of climate change, atmospheric radiation, air pollution, environmental health, etc.
Hyungwon John Park, Jeffrey S. Reid, Livia S. Freire, Christopher Jackson, and David H. Richter
Atmos. Meas. Tech., 15, 7171–7194, https://doi.org/10.5194/amt-15-7171-2022, https://doi.org/10.5194/amt-15-7171-2022, 2022
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We use numerical models to study field measurements of sea spray aerosol particles and conclude that both the atmospheric state and the methods of instrument sampling are causes for the variation in the production rate of aerosol particles: a critical metric to learn the aerosol's effect on processes like cloud physics and radiation. This work helps field observers improve their experimental design and interpretation of measurements because of turbulence in the atmosphere.
Christina Vasilakopoulou, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 15, 6419–6431, https://doi.org/10.5194/amt-15-6419-2022, https://doi.org/10.5194/amt-15-6419-2022, 2022
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Offline aerosol mass spectrometer (AMS) measurements can provide valuable information about ambient organic aerosols when online AMS measurements are not available. In this study, we examine whether and how the low time resolution (usually 24 h) of the offline technique affects source apportionment results. We concluded that use of the daily averages resulted in estimated average contributions that were within 8 % of the total OA compared with the high-resolution analysis.
Priyanka deSouza, Ralph Kahn, Tehya Stockman, William Obermann, Ben Crawford, An Wang, James Crooks, Jing Li, and Patrick Kinney
Atmos. Meas. Tech., 15, 6309–6328, https://doi.org/10.5194/amt-15-6309-2022, https://doi.org/10.5194/amt-15-6309-2022, 2022
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How sensitive are the spatial and temporal trends of PM2.5 derived from a network of low-cost sensors to the calibration adjustment used? How transferable are calibration equations developed at a few co-location sites to an entire network of low-cost sensors? This paper attempts to answer this question and offers a series of suggestions on how to develop the most robust calibration function for different end uses. It uses measurements from the Love My Air network in Denver as a test case.
Sahil Bhandari, Zainab Arub, Gazala Habib, Joshua S. Apte, and Lea Hildebrandt Ruiz
Atmos. Meas. Tech., 15, 6051–6074, https://doi.org/10.5194/amt-15-6051-2022, https://doi.org/10.5194/amt-15-6051-2022, 2022
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We present a new method to conduct source apportionment resolved by time of day using the underlying approach of positive matrix factorization. We report results for four example time periods in two seasons (winter and monsoon 2017) in Delhi, India. Compared to the traditional approach, we extract a larger number of factors that represent the expected sources of primary organic aerosol. This method can capture diurnal time series patterns of sources at low computational cost.
Alireza Moallemi, Rob L. Modini, Tatyana Lapyonok, Anton Lopatin, David Fuertes, Oleg Dubovik, Philippe Giaccari, and Martin Gysel-Beer
Atmos. Meas. Tech., 15, 5619–5642, https://doi.org/10.5194/amt-15-5619-2022, https://doi.org/10.5194/amt-15-5619-2022, 2022
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Aerosol properties (size distributions, refractive indices) can be retrieved from in situ, angularly resolved light scattering measurements performed with polar nephelometers. We apply an established framework to assess the aerosol property retrieval potential for different instrument configurations, target applications, and assumed prior knowledge. We also demonstrate how a reductive greedy algorithm can be used to determine the optimal placements of the angular sensors in a polar nephelometer.
Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, Jianhui Jiang, Hannes Keernik, Chunshui Lin, Nicolas Marchand, Cristina Marin, Colin O'Dowd, Jurgita Ovadnevaite, Jean-Eudes Petit, Michael Pikridas, Véronique Riffault, Jean Sciare, Jay G. Slowik, Leïla Simon, Jeni Vasilescu, Yunjiang Zhang, Olivier Favez, André S. H. Prévôt, Andrés Alastuey, and María Cruz Minguillón
Atmos. Meas. Tech., 15, 5479–5495, https://doi.org/10.5194/amt-15-5479-2022, https://doi.org/10.5194/amt-15-5479-2022, 2022
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This work presents the differences resulting from two techniques (rolling and seasonal) of the positive matrix factorisation model that can be run for organic aerosol source apportionment. The current state of the art suggests that the rolling technique is more accurate, but no proof of its effectiveness has been provided yet. This paper tackles this issue in the context of a synthetic dataset and a multi-site real-world comparison.
Sungwoo Kim, Brian M. Lerner, Donna T. Sueper, and Gabriel Isaacman-VanWertz
Atmos. Meas. Tech., 15, 5061–5075, https://doi.org/10.5194/amt-15-5061-2022, https://doi.org/10.5194/amt-15-5061-2022, 2022
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Atmospheric samples can be complex, and current analysis methods often require substantial human interaction and discard potentially important information. To improve analysis accuracy and computational cost of these large datasets, we developed an automated analysis algorithm that utilizes a factor analysis approach coupled with a decision tree. We demonstrate that this algorithm cataloged approximately 10 times more analytes compared to a manual analysis and in a quarter of the analysis time.
Olga Zografou, Maria Gini, Manousos I. Manousakas, Gang Chen, Athina C. Kalogridis, Evangelia Diapouli, Athina Pappa, and Konstantinos Eleftheriadis
Atmos. Meas. Tech., 15, 4675–4692, https://doi.org/10.5194/amt-15-4675-2022, https://doi.org/10.5194/amt-15-4675-2022, 2022
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A yearlong ToF-ACSM dataset was used to characterize ambient aerosols over a suburban Athenian site, and innovative software for source apportionment was implemented in order to distinguish the sources of the total non-refractory species of PM1. A comparison between the methodology of combined organic and inorganic PMF analysis and the conventional organic PMF took place.
Jeramy L. Dedrick, Georges Saliba, Abigail S. Williams, Lynn M. Russell, and Dan Lubin
Atmos. Meas. Tech., 15, 4171–4194, https://doi.org/10.5194/amt-15-4171-2022, https://doi.org/10.5194/amt-15-4171-2022, 2022
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A new method is presented to retrieve the sea spray aerosol size distribution by combining submicron size and nephelometer scattering based on Mie theory. Using available sea spray tracers, we find that this approach serves as a comparable substitute to supermicron size distribution measurements, which are limited in availability at marine sites. Application of this technique can expand sea spray observations and improve the characterization of marine aerosol impacts on clouds and climate.
Ivo Beck, Hélène Angot, Andrea Baccarini, Lubna Dada, Lauriane Quéléver, Tuija Jokinen, Tiia Laurila, Markus Lampimäki, Nicolas Bukowiecki, Matthew Boyer, Xianda Gong, Martin Gysel-Beer, Tuukka Petäjä, Jian Wang, and Julia Schmale
Atmos. Meas. Tech., 15, 4195–4224, https://doi.org/10.5194/amt-15-4195-2022, https://doi.org/10.5194/amt-15-4195-2022, 2022
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We present the pollution detection algorithm (PDA), a new method to identify local primary pollution in remote atmospheric aerosol and trace gas time series. The PDA identifies periods of contaminated data and relies only on the target dataset itself; i.e., it is independent of ancillary data such as meteorological variables. The parameters of all pollution identification steps are adjustable so that the PDA can be tuned to different locations and situations. It is available as open-access code.
Emily B. Franklin, Lindsay D. Yee, Bernard Aumont, Robert J. Weber, Paul Grigas, and Allen H. Goldstein
Atmos. Meas. Tech., 15, 3779–3803, https://doi.org/10.5194/amt-15-3779-2022, https://doi.org/10.5194/amt-15-3779-2022, 2022
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The composition of atmospheric aerosols are extremely complex, containing hundreds of thousands of estimated individual compounds. The majority of these compounds have never been catalogued in widely used databases, making them extremely difficult for atmospheric chemists to identify and analyze. In this work, we present Ch3MS-RF, a machine-learning-based model to enable characterization of complex mixtures and prediction of structure-specific properties of unidentifiable organic compounds.
Jiaoshi Zhang, Yang Wang, Steven Spielman, Susanne Hering, and Jian Wang
Atmos. Meas. Tech., 15, 2579–2590, https://doi.org/10.5194/amt-15-2579-2022, https://doi.org/10.5194/amt-15-2579-2022, 2022
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New nonparametric, regularized methods are developed to invert the growth factor probability density function (GF-PDF) from humidity-controlled fast integrated mobility spectrometer measurements. These algorithms are computationally efficient, require no prior assumptions of the GF-PDF distribution, and reduce the error in inverted GF-PDF. They can be applied to humidified tandem differential mobility analyzer data. Among all algorithms, Twomey’s method retrieves GF-PDF with the smallest error.
Douglas A. Day, Pedro Campuzano-Jost, Benjamin A. Nault, Brett B. Palm, Weiwei Hu, Hongyu Guo, Paul J. Wooldridge, Ronald C. Cohen, Kenneth S. Docherty, J. Alex Huffman, Suzane S. de Sá, Scot T. Martin, and Jose L. Jimenez
Atmos. Meas. Tech., 15, 459–483, https://doi.org/10.5194/amt-15-459-2022, https://doi.org/10.5194/amt-15-459-2022, 2022
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Particle-phase nitrates are an important component of atmospheric aerosols and chemistry. In this paper, we systematically explore the application of aerosol mass spectrometry (AMS) to quantify the organic and inorganic nitrate fractions of aerosols in the atmosphere. While AMS has been used for a decade to quantify nitrates, methods are not standardized. We make recommendations for a more universal approach based on this analysis of a large range of field and laboratory observations.
Markus D. Petters
Atmos. Meas. Tech., 14, 7909–7928, https://doi.org/10.5194/amt-14-7909-2021, https://doi.org/10.5194/amt-14-7909-2021, 2021
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Inverse methods infer physical properties from a measured instrument response. Measurement noise often interferes with the inversion. This work presents a general, domain-independent, accessible, and computationally efficient software implementation of a common class of statistical inversion methods. In addition, a new method to invert data from humidified tandem differential mobility analyzers is introduced. Results show that the approach is suitable for inversion of large-scale datasets.
Pak Lun Fung, Martha Arbayani Zaidan, Ola Surakhi, Sasu Tarkoma, Tuukka Petäjä, and Tareq Hussein
Atmos. Meas. Tech., 14, 5535–5554, https://doi.org/10.5194/amt-14-5535-2021, https://doi.org/10.5194/amt-14-5535-2021, 2021
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Aerosol size distribution measurements rely on a variety of techniques to classify the aerosol size and measure the size distribution. However, due to the instrumental insufficiency and inversion limitations, the raw dataset contains missing gaps or negative values, which hinder further analysis. With a merged particle size distribution in Jordan, this paper suggests a neural network method to estimate number concentrations at a particular size bin by the number concentration at other size bins.
Xiansheng Liu, Hadiatullah Hadiatullah, Xun Zhang, L. Drew Hill, Andrew H. A. White, Jürgen Schnelle-Kreis, Jan Bendl, Gert Jakobi, Brigitte Schloter-Hai, and Ralf Zimmermann
Atmos. Meas. Tech., 14, 5139–5151, https://doi.org/10.5194/amt-14-5139-2021, https://doi.org/10.5194/amt-14-5139-2021, 2021
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A monitoring campaign was conducted in Augsburg to determine a suitable noise reduction algorithm for the MA200 Aethalometer. Results showed that centred moving average (CMA) post-processing effectively removed spurious negative concentrations without major bias and reliably highlighted effects from local sources, effectively increasing spatio-temporal resolution in mobile measurements. Evaluation of each method on peak sample reduction and background correction further supports the reliability.
Jie Qiu, Wangshu Tan, Gang Zhao, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 4879–4891, https://doi.org/10.5194/amt-14-4879-2021, https://doi.org/10.5194/amt-14-4879-2021, 2021
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Considering nephelometers' major problems of a nonideal Lambertian light source and angle truncation, a new correction method based on a machine learning model is proposed. Our method has the advantage of obtaining data with high accuracy while achieving self-correction, which means that researchers can get more accurate scattering coefficients without the need for additional observation data. This method provides a more precise estimation of the aerosol’s direct radiative forcing.
Amir Yazdani, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 14, 4805–4827, https://doi.org/10.5194/amt-14-4805-2021, https://doi.org/10.5194/amt-14-4805-2021, 2021
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We propose a spectroscopic method for estimating several mixture-averaged molecular properties (carbon number and molecular weight) in particulate matter relevant for understanding its chemical origins. This estimation is enabled by calibration models built and tested using laboratory standards containing molecules with known structure, and can be applied to filter samples of PM2.5 currently collected in existing air pollution monitoring networks and field campaigns.
Aki Virkkula
Atmos. Meas. Tech., 14, 3707–3719, https://doi.org/10.5194/amt-14-3707-2021, https://doi.org/10.5194/amt-14-3707-2021, 2021
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The Aethalometer model is used widely for estimating the contributions of fossil fuel emissions and biomass burning to black carbon. The calculation is based on measured absorption Ångström exponents, which is ambiguous since it not only depends on the dominant absorber but also on the size and internal structure of the particles, core size, and shell thickness. The uncertainties of the fractions of absorption by eBC from fossil fuel and biomass burning are evaluated with a core–shell Mie model.
Weiqi Xu, Masayuki Takeuchi, Chun Chen, Yanmei Qiu, Conghui Xie, Wanyun Xu, Nan Ma, Douglas R. Worsnop, Nga Lee Ng, and Yele Sun
Atmos. Meas. Tech., 14, 3693–3705, https://doi.org/10.5194/amt-14-3693-2021, https://doi.org/10.5194/amt-14-3693-2021, 2021
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Here we developed a method for estimation of particulate organic nitrates (pON) from the measurements of a high-resolution aerosol mass spectrometer coupled with a thermodenuder based on the volatility differences between inorganic nitrate and pON. The results generally had improvements in reducing negative values due to the influences of a high concentration of inorganic nitrate and a constant ratio of NO+ to NO2+ of organic nitrates (RON).
Melinda K. Schueneman, Benjamin A. Nault, Pedro Campuzano-Jost, Duseong S. Jo, Douglas A. Day, Jason C. Schroder, Brett B. Palm, Alma Hodzic, Jack E. Dibb, and Jose L. Jimenez
Atmos. Meas. Tech., 14, 2237–2260, https://doi.org/10.5194/amt-14-2237-2021, https://doi.org/10.5194/amt-14-2237-2021, 2021
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This work focuses on two important properties of the aerosol, acidity, and sulfate composition, which is important for our understanding of aerosol health and environmental impacts. We explore different methods to understand the composition of the aerosol with measurements from a specific instrument and apply those methods to a large dataset. These measurements are confounded by other factors, making it challenging to predict aerosol sulfate composition; pH estimations, however, show promise.
Weilun Zhao, Wangshu Tan, Gang Zhao, Chuanyang Shen, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 1319–1331, https://doi.org/10.5194/amt-14-1319-2021, https://doi.org/10.5194/amt-14-1319-2021, 2021
Chuanyang Shen, Gang Zhao, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 1293–1301, https://doi.org/10.5194/amt-14-1293-2021, https://doi.org/10.5194/amt-14-1293-2021, 2021
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Aerosol hygroscopicity measured by the humidified tandem differential mobility analyzer (HTDMA) is affected by multiply charged particles from two aspects: (1) number contribution and (2) the weakening effect. An algorithm is proposed to do the multi-charge correction and applied to a field measurement. Results show that the difference between corrected and measured size-resolved κ can reach 0.05, highlighting that special attention needs to be paid to the multi-charge effect when using HTDMA.
Francesco Canonaco, Anna Tobler, Gang Chen, Yulia Sosedova, Jay Gates Slowik, Carlo Bozzetti, Kaspar Rudolf Daellenbach, Imad El Haddad, Monica Crippa, Ru-Jin Huang, Markus Furger, Urs Baltensperger, and André Stephan Henry Prévôt
Atmos. Meas. Tech., 14, 923–943, https://doi.org/10.5194/amt-14-923-2021, https://doi.org/10.5194/amt-14-923-2021, 2021
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Long-term ambient aerosol mass spectrometric data were analyzed with a statistical model (PMF) to obtain source contributions and fingerprints. The new aspects of this paper involve time-dependent source fingerprints by a rolling technique and the replacement of the full visual inspection of each run by a user-defined set of criteria to monitor the quality of each of these runs more efficiently. More reliable sources will finally provide better instruments for political mitigation strategies.
Kenji Miki and Shigeto Kawashima
Atmos. Meas. Tech., 14, 685–693, https://doi.org/10.5194/amt-14-685-2021, https://doi.org/10.5194/amt-14-685-2021, 2021
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Laser optics have long been used in pollen counting systems. To clarify the limitations and potential new applications of laser optics for automatic pollen counting and discrimination, we determined the light scattering patterns of various pollen types, tracked temporal changes in these distributions, and introduced a new theory for automatic pollen discrimination.
Yinchao Zhang, Su Chen, Siying Chen, He Chen, and Pan Guo
Atmos. Meas. Tech., 13, 6675–6689, https://doi.org/10.5194/amt-13-6675-2020, https://doi.org/10.5194/amt-13-6675-2020, 2020
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Air pollution has an important impact on human health, climatic patterns, and the ecological environment. The complexity of the nocturnal boundary layer (NBL), combined with its strong physio-chemical effect, induces worse polluted episodes. Therefore, we present a new approach named cluster analysis of gradient method (CA-GM) to overcome the multilayer structure and remove the fluctuation of NBL height using raw data resolution.
Tommy Chan, Runlong Cai, Lauri R. Ahonen, Yiliang Liu, Ying Zhou, Joonas Vanhanen, Lubna Dada, Yan Chao, Yongchun Liu, Lin Wang, Markku Kulmala, and Juha Kangasluoma
Atmos. Meas. Tech., 13, 4885–4898, https://doi.org/10.5194/amt-13-4885-2020, https://doi.org/10.5194/amt-13-4885-2020, 2020
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Using a particle size magnifier (PSM; Airmodus, Finland), we determined the particle size distribution using four inversion methods and compared each method to the others to establish their strengths and weaknesses. Furthermore, we provided a step-by-step procedure on how to invert measured data using the PSM. Finally, we provided recommendations, code and data related to the data inversion. This is an important paper, as no operating procedure exists regarding how to process measured PSM data.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
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The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Shengqiang Zhu, Lei Li, Shurong Wang, Mei Li, Yaxi Liu, Xiaohui Lu, Hong Chen, Lin Wang, Jianmin Chen, Zhen Zhou, Xin Yang, and Xiaofei Wang
Atmos. Meas. Tech., 13, 4111–4121, https://doi.org/10.5194/amt-13-4111-2020, https://doi.org/10.5194/amt-13-4111-2020, 2020
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Single-particle aerosol mass spectrometry (SPAMS) is widely used to detect chemical compositions and sizes of individual aerosol particles. However, it has a major issue: the mass accuracy of high-resolution SPAMS is relatively low. Here we developed an automatic linear calibration method to greatly improve the mass accuracy of SPAMS spectra so that the elemental compositions of organic peaks, such as Cx, CxHy, CxHyOz and CxHyNO peaks, can be directly identified just based on their m / z values.
William Wandji Nyamsi, Antti Lipponen, Arturo Sanchez-Lorenzo, Martin Wild, and Antti Arola
Atmos. Meas. Tech., 13, 3061–3079, https://doi.org/10.5194/amt-13-3061-2020, https://doi.org/10.5194/amt-13-3061-2020, 2020
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This paper proposes a novel and accurate method for estimating and reconstructing aerosol optical depth from sunshine duration measurements under cloud-free conditions at any place and time since the late 19th century. The method performs very well when compared to AErosol RObotic NETwork measurements and operates an efficient detection of signals from massive volcanic eruptions. Reconstructed long-term aerosol optical depths are in agreement with the dimming/brightening phenomenon.
Sascha Pfeifer, Thomas Müller, Andrew Freedman, and Alfred Wiedensohler
Atmos. Meas. Tech., 13, 2161–2167, https://doi.org/10.5194/amt-13-2161-2020, https://doi.org/10.5194/amt-13-2161-2020, 2020
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The effect of the baseline drift on the resulting extinction values of three CAPS PMex monitors with different wavelengths was analysed for an urban background station. A significant baseline drift was observed, which leads to characteristic measurement artefacts for particle extinction. Two alternative methods for recalculating the baseline are shown. With these methods the extinction artefacts are diminished and the effective scattering of the resulting extinction values is reduced.
Stuart K. Grange, Hanspeter Lötscher, Andrea Fischer, Lukas Emmenegger, and Christoph Hueglin
Atmos. Meas. Tech., 13, 1867–1885, https://doi.org/10.5194/amt-13-1867-2020, https://doi.org/10.5194/amt-13-1867-2020, 2020
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Black carbon (BC) is an important atmospheric pollutant and can be monitored by instruments called aethalometers. A pragmatic data processing technique called the
aethalometer modelcan be used to apportion aethalometer observations into traffic and woodburning components. We present an exploratory data analysis evaluating the aethalometer model and use the outputs for BC trend analysis across Switzerland. The aethalometer model's robustness and utility for such analyses is discussed.
Charlotte Bürki, Matteo Reggente, Ann M. Dillner, Jenny L. Hand, Stephanie L. Shaw, and Satoshi Takahama
Atmos. Meas. Tech., 13, 1517–1538, https://doi.org/10.5194/amt-13-1517-2020, https://doi.org/10.5194/amt-13-1517-2020, 2020
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Infrared spectroscopy is a chemically informative method for particulate matter characterization. However, recent work has demonstrated that predictions depend heavily on the choice of calibration model parameters. We propose a means for managing parameter uncertainties by combining available data from laboratory standards, molecular databases, and collocated ambient measurements to provide useful characterization of atmospheric organic matter on a large scale.
Kaixu Bai, Ke Li, Jianping Guo, Yuanjian Yang, and Ni-Bin Chang
Atmos. Meas. Tech., 13, 1213–1226, https://doi.org/10.5194/amt-13-1213-2020, https://doi.org/10.5194/amt-13-1213-2020, 2020
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A novel gap-filling method called the diurnal-cycle-constrained empirical orthogonal function (DCCEOF) is proposed. Cross validation indicates that this method gives high accuracy in predicting missing values in daily PM2.5 time series by accounting for the local diurnal phases, especially by reconstructing daily extrema that cannot be accurately restored by other approaches. The DCCEOF method can be easily applied to other data sets because of its self-consistent capability.
Tongshu Zheng, Michael H. Bergin, Ronak Sutaria, Sachchida N. Tripathi, Robert Caldow, and David E. Carlson
Atmos. Meas. Tech., 12, 5161–5181, https://doi.org/10.5194/amt-12-5161-2019, https://doi.org/10.5194/amt-12-5161-2019, 2019
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Here we present a simultaneous Gaussian process regression (GPR) and linear regression pipeline to calibrate and monitor dense wireless low-cost particulate matter sensor networks (WLPMSNs) on the fly by using all available reference monitors across an area. Our approach can achieve an overall 30 % prediction error at a 24 h scale, can differentiate malfunctioning nodes, and track drift. Our solution can substantially reduce manual labor for managing WLPMSNs and prolong their lifetimes.
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