Articles | Volume 14, issue 2
https://doi.org/10.5194/gmd-14-675-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-675-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
PyCHAM (v2.1.1): a Python box model for simulating aerosol chambers
Simon Patrick O'Meara
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
National Centre for Atmospheric Science, University of Manchester, Manchester, M13 9PL, UK
Shuxuan Xu
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
David Topping
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
M. Rami Alfarra
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
National Centre for Atmospheric Science, University of Manchester, Manchester, M13 9PL, UK
Gerard Capes
Research Computing Services, University of Manchester, Manchester, M13 9PL, UK
Douglas Lowe
Research Computing Services, University of Manchester, Manchester, M13 9PL, UK
Yunqi Shao
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
Gordon McFiggans
CORRESPONDING AUTHOR
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
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Ernesto Reyes-Villegas, Douglas Lowe, Jill S. Johnson, Kenneth S. Carslaw, Eoghan Darbyshire, Michael Flynn, James D. Allan, Hugh Coe, Ying Chen, Oliver Wild, Scott Archer-Nicholls, Alex Archibald, Siddhartha Singh, Manish Shrivastava, Rahul A. Zaveri, Vikas Singh, Gufran Beig, Ranjeet Sokhi, and Gordon McFiggans
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Aristeidis Voliotis, Mao Du, Yu Wang, Yunqi Shao, M. Rami Alfarra, Thomas J. Bannan, Dawei Hu, Kelly L. Pereira, Jaqueline F. Hamilton, Mattias Hallquist, Thomas F. Mentel, and Gordon McFiggans
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higher-yield precursor's oxidation products and products from
cross-product formation. This study also identifies potential tracer compounds in a mixed vapour system that might be used in SOA source attribution in future ambient studies.
Mao Du, Aristeidis Voliotis, Yunqi Shao, Yu Wang, Thomas J. Bannan, Kelly L. Pereira, Jacqueline F. Hamilton, Carl J. Percival, M. Rami Alfarra, and Gordon McFiggans
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Atmospheric chemistry plays a key role in the understanding of aerosol formation and air pollution. We designed chamber experiments for the characterization of secondary organic aerosol (SOA) from a biogenic precursor with inorganic seed. Our results highlight the advantages of a combination of online FIGAERO-CIMS and offline LC-Orbitrap MS analytical techniques to characterize the chemical composition of SOA in chamber studies.
Matthias Karl, Liisa Pirjola, Tiia Grönholm, Mona Kurppa, Srinivasan Anand, Xiaole Zhang, Andreas Held, Rolf Sander, Miikka Dal Maso, David Topping, Shuai Jiang, Leena Kangas, and Jaakko Kukkonen
Geosci. Model Dev., 15, 3969–4026, https://doi.org/10.5194/gmd-15-3969-2022, https://doi.org/10.5194/gmd-15-3969-2022, 2022
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The community aerosol dynamics model MAFOR includes several advanced features: coupling with an up-to-date chemistry mechanism for volatile organic compounds, a revised Brownian coagulation kernel that takes into account the fractal geometry of soot particles, a multitude of nucleation parameterizations, size-resolved partitioning of semi-volatile inorganics, and a hybrid method for the formation of secondary organic aerosols within the framework of condensation and evaporation.
Yu Wang, Aristeidis Voliotis, Dawei Hu, Yunqi Shao, Mao Du, Ying Chen, Judith Kleinheins, Claudia Marcolli, M. Rami Alfarra, and Gordon McFiggans
Atmos. Chem. Phys., 22, 4149–4166, https://doi.org/10.5194/acp-22-4149-2022, https://doi.org/10.5194/acp-22-4149-2022, 2022
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Aerosol water uptake plays a key role in atmospheric physicochemical processes. We designed chamber experiments on aerosol water uptake of secondary organic aerosol (SOA) from mixed biogenic and anthropogenic precursors with inorganic seed. Our results highlight this chemical composition influences the reconciliation of the sub- and super-saturated water uptake, providing laboratory evidence for understanding the chemical controls of water uptake of the multi-component aerosol.
Jessica Slater, Hugh Coe, Gordon McFiggans, Juha Tonttila, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 2937–2953, https://doi.org/10.5194/acp-22-2937-2022, https://doi.org/10.5194/acp-22-2937-2022, 2022
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This paper shows the specific impact of black carbon (BC) on the aerosol–planetary boundary layer (PBL) feedback and its influence on a Beijing haze episode. Overall, this paper shows that strong temperature inversions prevent BC heating within the PBL from significantly increasing PBL height, while BC above the PBL suppresses PBL development significantly through the day. From this we suggest a method by which both locally and regionally emitted BC may impact urban pollution episodes.
Yunqi Shao, Yu Wang, Mao Du, Aristeidis Voliotis, M. Rami Alfarra, Simon P. O'Meara, S. Fiona Turner, and Gordon McFiggans
Atmos. Meas. Tech., 15, 539–559, https://doi.org/10.5194/amt-15-539-2022, https://doi.org/10.5194/amt-15-539-2022, 2022
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A comprehensive description and characterisation of the Manchester Aerosol Chamber (MAC) was conducted. The MAC has good temperature and relative humidity homogeneity, fast mixing times, and comparable losses of gases and particles with other chambers. The MAC's bespoke control system allows improved duty cycles and repeatable experiments. Moreover, the effect of contamination on performance was also investigated. It is highly recommended to regularly track the chamber's performance.
Dawei Hu, M. Rami Alfarra, Kate Szpek, Justin M. Langridge, Michael I. Cotterell, Claire Belcher, Ian Rule, Zixia Liu, Chenjie Yu, Yunqi Shao, Aristeidis Voliotis, Mao Du, Brett Smith, Greg Smallwood, Prem Lobo, Dantong Liu, Jim M. Haywood, Hugh Coe, and James D. Allan
Atmos. Chem. Phys., 21, 16161–16182, https://doi.org/10.5194/acp-21-16161-2021, https://doi.org/10.5194/acp-21-16161-2021, 2021
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Here, we developed new techniques for investigating these properties in the laboratory and applied these to BC and BrC from different sources, including diesel exhaust, inverted propane flame and wood combustion. These have allowed us to quantify the changes in shape and chemical composition of different soots according to source and variables such as the moisture content of wood.
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.
Ernesto Reyes-Villegas, Upasana Panda, Eoghan Darbyshire, James M. Cash, Rutambhara Joshi, Ben Langford, Chiara F. Di Marco, Neil J. Mullinger, Mohammed S. Alam, Leigh R. Crilley, Daniel J. Rooney, W. Joe F. Acton, Will Drysdale, Eiko Nemitz, Michael Flynn, Aristeidis Voliotis, Gordon McFiggans, Hugh Coe, James Lee, C. Nicholas Hewitt, Mathew R. Heal, Sachin S. Gunthe, Tuhin K. Mandal, Bhola R. Gurjar, Shivani, Ranu Gadi, Siddhartha Singh, Vijay Soni, and James D. Allan
Atmos. Chem. Phys., 21, 11655–11667, https://doi.org/10.5194/acp-21-11655-2021, https://doi.org/10.5194/acp-21-11655-2021, 2021
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This paper shows the first multisite online measurements of PM1 in Delhi, India, with measurements over different seasons in Old Delhi and New Delhi in 2018. Organic aerosol (OA) source apportionment was performed using positive matrix factorisation (PMF). Traffic was the main primary aerosol source for both OAs and black carbon, seen with PMF and Aethalometer model analysis, indicating that control of primary traffic exhaust emissions would make a significant reduction to Delhi air pollution.
Yu Wang, Aristeidis Voliotis, Yunqi Shao, Taomou Zong, Xiangxinyue Meng, Mao Du, Dawei Hu, Ying Chen, Zhijun Wu, M. Rami Alfarra, and Gordon McFiggans
Atmos. Chem. Phys., 21, 11303–11316, https://doi.org/10.5194/acp-21-11303-2021, https://doi.org/10.5194/acp-21-11303-2021, 2021
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Aerosol phase behaviour plays a profound role in atmospheric physicochemical processes. We designed dedicated chamber experiments to study the phase state of secondary organic aerosol from biogenic and anthropogenic mixed precursors. Our results highlight the key role of the organic–inorganic ratio and relative humidity in phase state, but the sources and organic composition are less important. The result provides solid laboratory evidence for understanding aerosol phase in a complex atmosphere.
Langwen Huang and David Topping
Geosci. Model Dev., 14, 2187–2203, https://doi.org/10.5194/gmd-14-2187-2021, https://doi.org/10.5194/gmd-14-2187-2021, 2021
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As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing community mechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. With this in mind we present JlBox v1.1, written in Julia.
Michael Priestley, Thomas J. Bannan, Michael Le Breton, Stephen D. Worrall, Sungah Kang, Iida Pullinen, Sebastian Schmitt, Ralf Tillmann, Einhard Kleist, Defeng Zhao, Jürgen Wildt, Olga Garmash, Archit Mehra, Asan Bacak, Dudley E. Shallcross, Astrid Kiendler-Scharr, Åsa M. Hallquist, Mikael Ehn, Hugh Coe, Carl J. Percival, Mattias Hallquist, Thomas F. Mentel, and Gordon McFiggans
Atmos. Chem. Phys., 21, 3473–3490, https://doi.org/10.5194/acp-21-3473-2021, https://doi.org/10.5194/acp-21-3473-2021, 2021
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A significant fraction of emissions from human activity consists of aromatic hydrocarbons, e.g. benzene, which oxidise to form new compounds important for particle growth. Characterisation of benzene oxidation products highlights the range of species produced as well as their chemical properties and contextualises them within relevant frameworks, e.g. MCM. Cluster analysis of the oxidation product time series distinguishes behaviours of CHON compounds that could aid in identifying functionality.
Douglas Morrison, Ian Crawford, Nicholas Marsden, Michael Flynn, Katie Read, Luis Neves, Virginia Foot, Paul Kaye, Warren Stanley, Hugh Coe, David Topping, and Martin Gallagher
Atmos. Chem. Phys., 20, 14473–14490, https://doi.org/10.5194/acp-20-14473-2020, https://doi.org/10.5194/acp-20-14473-2020, 2020
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We provide conservative estimates of the concentrations of bacteria within transatlantic dust clouds, originating from the African continent. We observe significant seasonal differences in the overall concentrations of particles but no seasonal variation in the ratio between bacteria and dust. With bacteria contributing to ice formation at warmer temperatures than dust, our observations should improve the accuracy of climate models.
Jessica Slater, Juha Tonttila, Gordon McFiggans, Paul Connolly, Sami Romakkaniemi, Thomas Kühn, and Hugh Coe
Atmos. Chem. Phys., 20, 11893–11906, https://doi.org/10.5194/acp-20-11893-2020, https://doi.org/10.5194/acp-20-11893-2020, 2020
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The feedback effect between aerosol particles, radiation and meteorology reduces turbulent motion and results in increased surface aerosol concentrations during Beijing haze. Observational analysis and regional modelling studies have examined the feedback effect but these studies are limited. In this work, we set up a high-resolution model for the Beijing environment to examine the sensitivity of the aerosol feedback effect to initial meteorological conditions and aerosol loading.
David Topping, David Watts, Hugh Coe, James Evans, Thomas J. Bannan, Douglas Lowe, Caroline Jay, and Jonathan W. Taylor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-270, https://doi.org/10.5194/gmd-2020-270, 2020
Publication in GMD not foreseen
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Time-series forecasting methods have often been used to mitigate some of the challenges associated with deploying chemical transport models. In this study we deploy and evaluate Facebook’s Prophetmodel v0.6 in predicting hourly concentrations of Nitrogen Dioxide [NO2]. et. Overall we find the Prophet model offers a relatively effective and simple way to make predictions about NO2 at local levels.
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Short summary
User-friendly and open-source software for simulating aerosol chambers is a valuable tool for research scientists in designing and analysing their experiments. This paper describes a new version of such software and will therefore provide a useful reference for those applying it. Central to the paper is an assessment of the software's accuracy through comparison against previously published simulations.
User-friendly and open-source software for simulating aerosol chambers is a valuable tool for...