Articles | Volume 21, issue 5
https://doi.org/10.5194/acp-21-3919-2021
© 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/acp-21-3919-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Mar 2021
Research article |
| 17 Mar 2021
| 17 Mar 2021
Meteorology-driven variability of air pollution (PM1) revealed with explainable machine learning
Roland Stirnberg
CORRESPONDING AUTHOR
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Jan Cermak
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Simone Kotthaus
Institut Pierre Simon Laplace, École Polytechnique, CNRS, Institut Polytechnique de Paris, Palaiseau, France
Martial Haeffelin
Institut Pierre Simon Laplace, École Polytechnique, CNRS, Institut Polytechnique de Paris, Palaiseau, France
Hendrik Andersen
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Julia Fuchs
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Jean-Eudes Petit
Laboratoire des Sciences du Climat et de l'Environnement, CEA/Orme des Merisiers, Gif sur Yvette, France
Olivier Favez
Institut National de l'Environnement Industriel et des Risques, Parc Technologique ALATA, Verneuil en Halatte, France
Related authors
No articles found.
Hanrui Lang, Yunjiang Zhang, Sheng Zhong, Yongcai Rao, Minfeng Zhou, Jian Qiu, Jingyi Li, Diwen Liu, Florian Couvidat, Olivier Favez, Didier Hauglustaine, and Xinlei Ge
Atmos. Chem. Phys., 25, 10587–10601, https://doi.org/10.5194/acp-25-10587-2025, https://doi.org/10.5194/acp-25-10587-2025, 2025
Short summary
Short summary
This study investigates how dust pollution influences particulate nitrate formation. We found that dust pollution could reduce the effectiveness of ammonia emission controls by altering aerosol chemistry. Using field observations and modeling, we showed that dust particles affect nitrate distribution between gas and particle phases. Our findings highlight the need for pollution control strategies that consider both human emissions and dust sources for better urban air quality management.
Sijia Lou, Manish Shrivastava, Alexandre Albinet, Sophie Tomaz, Deepchandra Srivastava, Olivier Favez, Huizhong Shen, and Aijun Ding
Atmos. Chem. Phys., 25, 8163–8183, https://doi.org/10.5194/acp-25-8163-2025, https://doi.org/10.5194/acp-25-8163-2025, 2025
Short summary
Short summary
Polycyclic aromatic hydrocarbons (PAHs), emitted from incomplete combustion, pose serious health risks due to their carcinogenic properties. This research demonstrates that viscous organic aerosol coatings significantly hinder PAH oxidation, with spatial distributions sensitive to the degradation modeling approach. Our findings emphasize the need for accurate modeling of PAH oxidation processes in risk assessments, considering both fresh and oxidized PAHs in evaluating human health risks.
Deepanshu Malik, Hendrik Andersen, Jan Cermak, Roland Vogt, and Bianca Adler
EGUsphere, https://doi.org/10.5194/egusphere-2025-2645, https://doi.org/10.5194/egusphere-2025-2645, 2025
Short summary
Short summary
We investigated cloud base height changes in the Namib Desert and developed a method to estimate it using ground-based humidity data. This improves fog monitoring by distinguishing fog from low clouds, which satellites alone cannot reliably do. Our results reveal diurnal patterns and linkages to coastal proximity in the vertical dynamics of fog and low clouds, highlighting key atmospheric processes with potential importance for future research.
Qingxiao Meng, Yunjiang Zhang, Sheng Zhong, Jie Fang, Lili Tang, Yongcai Rao, Minfeng Zhou, Jian Qiu, Xiaofeng Xu, Jean-Eudes Petit, Olivier Favez, and Xinlei Ge
Atmos. Chem. Phys., 25, 7485–7498, https://doi.org/10.5194/acp-25-7485-2025, https://doi.org/10.5194/acp-25-7485-2025, 2025
Short summary
Short summary
We developed a machine-learning-based method to reconstruct missing elemental carbon (EC) data in four Chinese cities from 2013 to 2023. Using machine learning, we filled data gaps and introduced a new approach to analyze EC trends. Our findings reveal a significant decline in EC due to stricter pollution controls, though this slowed after 2020. This study provides a versatile framework for addressing data gaps and supports strategies to reduce urban air pollution and its climate impacts.
Vy Ngoc Thuy Dinh, Gaëlle Uzu, Pamela Dominutti, Stéphane Sauvage, Rhabira Elazzouzi, Sophie Darfeuil, Céline Voiron, Abdoulaye Samaké, Shouwen Zhang, Stéphane Socquet, Olivier Favez, and Jean-Luc Jaffrezo
EGUsphere, https://doi.org/10.5194/egusphere-2025-1968, https://doi.org/10.5194/egusphere-2025-1968, 2025
Short summary
Short summary
PMF is widely used for apportion the source of particulate matter. However, the inherent model has some subjective aspects which should be reduce to ensure the robustness of the result. To do so, this study developed a systematic method, by performing tests on the input and the result validation. Finally, we proposed recommendations for input selection and result validation. A Python package is developed, providing advanced tools for input preparation, validation and visualization results.
Vy Ngoc Thuy Dinh, Jean-Luc Jaffrezo, Pamela Dominutti, Rhabira Elazzouzi, Sophie Darfeuil, Céline Voiron, Anouk Marsal, Stéphane Socquet, Gladys Mary, Julie Cozic, Catherine Coulaud, Marc Durif, Olivier Favez, and Gaëlle Uzu
EGUsphere, https://doi.org/10.5194/egusphere-2025-2933, https://doi.org/10.5194/egusphere-2025-2933, 2025
Short summary
Short summary
Long-term particulate matter (PM) filter sampling at a French urban background and temperature measurements at different altitudes were used to investigate decadal trends of the main PM sources and related oxidative potential metrics. Positive Matrix Factorization analyses were conducted on the corresponding 11-year dataset, which determined ten PM sources. Temporal evolution of these sources is investigated, highlighting a strong downward trend of anthropogenic sources over 11 years.
Hasna Chebaicheb, Mélodie Chatain, Olivier Favez, Joel F. de Brito, Vincent Crenn, Tanguy Amodeo, Mohamed Gherras, Emmanuel Jantzem, Caroline Marchand, and Véronique Riffault
EGUsphere, https://doi.org/10.5194/egusphere-2025-648, https://doi.org/10.5194/egusphere-2025-648, 2025
Short summary
Short summary
This study compares carbonaceous aerosols source apportionment at paired traffic and background locations in urban environment (Strasbourg, France). Positive matrix factorization was applied (individually and in a combined input dataset) to aerosol mass spectrometry measurements at both sites, providing notably insights into the challenges of attributing real sources to organic aerosol (OA) factors and the impact of instrumental result specificities leading to differences in OA mass spectra.
Ludovico Di Antonio, Matthias Beekmann, Guillaume Siour, Vincent Michoud, Christopher Cantrell, Astrid Bauville, Antonin Bergé, Mathieu Cazaunau, Servanne Chevaillier, Manuela Cirtog, Joel F. de Brito, Paola Formenti, Cecile Gaimoz, Olivier Garret, Aline Gratien, Valérie Gros, Martial Haeffelin, Lelia N. Hawkins, Simone Kotthaus, Gael Noyalet, Diana L. Pereira, Jean-Eudes Petit, Eva Drew Pronovost, Véronique Riffault, Chenjie Yu, Gilles Foret, Jean-François Doussin, and Claudia Di Biagio
Atmos. Chem. Phys., 25, 4803–4831, https://doi.org/10.5194/acp-25-4803-2025, https://doi.org/10.5194/acp-25-4803-2025, 2025
Short summary
Short summary
The summer of 2022 has been considered a proxy for future climate scenarios due to its hot and dry conditions. In this paper, we use the measurements from the Atmospheric Chemistry of the Suburban Forest (ACROSS) campaign, conducted in the Paris area in June–July 2022, along with observations from existing networks, to evaluate a 3D chemistry transport model (WRF–CHIMERE) simulation. Results are shown to be satisfactory, allowing us to explain the gas and aerosol variability at the campaign sites.
Diana L. Pereira, Chiara Giorio, Aline Gratien, Alexander Zherebker, Gael Noyalet, Servanne Chevaillier, Stéphanie Alage, Elie Almarj, Antonin Bergé, Thomas Bertin, Mathieu Cazaunau, Patrice Coll, Ludovico Di Antonio, Sergio Harb, Johannes Heuser, Cécile Gaimoz, Oscar Guillemant, Brigitte Language, Olivier Lauret, Camilo Macias, Franck Maisonneuve, Bénédicte Picquet-Varrault, Raquel Torres, Sylvain Triquet, Pascal Zapf, Lelia Hawkins, Drew Pronovost, Sydney Riley, Pierre-Marie Flaud, Emilie Perraudin, Pauline Pouyes, Eric Villenave, Alexandre Albinet, Olivier Favez, Robin Aujay-Plouzeau, Vincent Michoud, Christopher Cantrell, Manuela Cirtog, Claudia Di Biagio, Jean-François Doussin, and Paola Formenti
Atmos. Chem. Phys., 25, 4885–4905, https://doi.org/10.5194/acp-25-4885-2025, https://doi.org/10.5194/acp-25-4885-2025, 2025
Short summary
Short summary
In order to study aerosols in environments influenced by anthropogenic and biogenic emissions, we performed analyses of samples collected during the ACROSS (Atmospheric Chemistry Of the Suburban Forest) campaign in summer 2022 in the greater Paris area. After analysis of the chemical composition by means of total carbon determination and high-resolution mass spectrometry, this work highlights the influence of anthropogenic inputs on the chemical composition of both urban and forested areas.
Babak Jahani, Steffen Karalus, Julia Fuchs, Tobias Zech, Marina Zara, and Jan Cermak
Atmos. Meas. Tech., 18, 1927–1941, https://doi.org/10.5194/amt-18-1927-2025, https://doi.org/10.5194/amt-18-1927-2025, 2025
Short summary
Short summary
Fog and low stratus (FLS) are both persistent clouds close to the Earth's surface. This study introduces a new machine-learning-based algorithm developed for the Meteosat Second Generation geostationary satellites that can provide a coherent and detailed view of FLS development over large areas over the 24 h day cycle.
William Morrison, Dana Looschelders, Jonnathan Céspedes, Bernie Claxton, Marc-Antoine Drouin, Jean-Charles Dupont, Aurélien Faucheux, Martial Haeffelin, Christopher C. Holst, Simone Kotthaus, Valéry Masson, James McGregor, Jeremy Price, Matthias Zeeman, Sue Grimmond, and Andreas Christen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-167, https://doi.org/10.5194/essd-2025-167, 2025
Preprint under review for ESSD
Short summary
Short summary
We conducted research using sophisticated wind sensors to better understand wind patterns in Paris. By installing these sensors across the city, we gathered detailed data on wind speeds and directions from 2022 to 2024. This information helps improve weather and climate models, making them more accurate for city environments. Our findings offer valuable insights for scientists studying urban air and weather, improving predictions and understanding of city-scale atmospheric processes.
Soo-Jin Park, Lya Lugon, Oscar Jacquot, Youngseob Kim, Alexia Baudic, Barbara D'Anna, Ludovico Di Antonio, Claudia Di Biagio, Fabrice Dugay, Olivier Favez, Véronique Ghersi, Aline Gratien, Julien Kammer, Jean-Eudes Petit, Olivier Sanchez, Myrto Valari, Jérémy Vigneron, and Karine Sartelet
Atmos. Chem. Phys., 25, 3363–3387, https://doi.org/10.5194/acp-25-3363-2025, https://doi.org/10.5194/acp-25-3363-2025, 2025
Short summary
Short summary
To accurately represent the population exposure to outdoor concentrations of pollutants of interest to health (NO2, PM2.5, black carbon, and ultrafine particles), multi-scale modelling down to the street scale is set up and evaluated using measurements from field campaigns. An exposure scaling factor is defined, allowing regional-scale simulations to be corrected to evaluate population exposure. Urban heterogeneities strongly influence NO2, black carbon, and ultrafine particles but less strongly PM2.5.
Ludovico Di Antonio, Claudia Di Biagio, Paola Formenti, Aline Gratien, Vincent Michoud, Christopher Cantrell, Astrid Bauville, Antonin Bergé, Mathieu Cazaunau, Servanne Chevaillier, Manuela Cirtog, Patrice Coll, Barbara D'Anna, Joel F. de Brito, David O. De Haan, Juliette R. Dignum, Shravan Deshmukh, Olivier Favez, Pierre-Marie Flaud, Cecile Gaimoz, Lelia N. Hawkins, Julien Kammer, Brigitte Language, Franck Maisonneuve, Griša Močnik, Emilie Perraudin, Jean-Eudes Petit, Prodip Acharja, Laurent Poulain, Pauline Pouyes, Eva Drew Pronovost, Véronique Riffault, Kanuri I. Roundtree, Marwa Shahin, Guillaume Siour, Eric Villenave, Pascal Zapf, Gilles Foret, Jean-François Doussin, and Matthias Beekmann
Atmos. Chem. Phys., 25, 3161–3189, https://doi.org/10.5194/acp-25-3161-2025, https://doi.org/10.5194/acp-25-3161-2025, 2025
Short summary
Short summary
The spectral complex refractive index (CRI) and single scattering albedo were retrieved from submicron aerosol measurements at three sites within the greater Paris area during the ACROSS field campaign (June–July 2022). Measurements revealed urban emission impact on surrounding areas. CRI full period averages at 520 nm were 1.41 – 0.037i (urban), 1.52 – 0.038i (peri-urban), and 1.50 – 0.025i (rural). Organic aerosols dominated the aerosol mass and contributed up to 22 % of absorption at 370 nm.
Hector Navarro-Barboza, Jordi Rovira, Vincenzo Obiso, Andrea Pozzer, Marta Via, Andres Alastuey, Xavier Querol, Noemi Perez, Marjan Savadkoohi, Gang Chen, Jesus Yus-Díez, Matic Ivancic, Martin Rigler, Konstantinos Eleftheriadis, Stergios Vratolis, Olga Zografou, Maria Gini, Benjamin Chazeau, Nicolas Marchand, Andre S. H. Prevot, Kaspar Dallenbach, Mikael Ehn, Krista Luoma, Tuukka Petäjä, Anna Tobler, Jaroslaw Necki, Minna Aurela, Hilkka Timonen, Jarkko Niemi, Olivier Favez, Jean-Eudes Petit, Jean-Philippe Putaud, Christoph Hueglin, Nicolas Pascal, Aurélien Chauvigné, Sébastien Conil, Marco Pandolfi, and Oriol Jorba
Atmos. Chem. Phys., 25, 2667–2694, https://doi.org/10.5194/acp-25-2667-2025, https://doi.org/10.5194/acp-25-2667-2025, 2025
Short summary
Short summary
Brown carbon (BrC) absorbs ultraviolet (UV) and visible light, influencing climate. This study explores BrC's imaginary refractive index (k) using data from 12 European sites. Residential emissions are a major organic aerosol (OA) source in winter, while secondary organic aerosol (SOA) dominates in summer. Source-specific k values were derived, improving model accuracy. The findings highlight BrC's climate impact and emphasize source-specific constraints in atmospheric models.
Shravan Deshmukh, Laurent Poulain, Birgit Wehner, Silvia Henning, Jean-Eudes Petit, Pauline Fombelle, Olivier Favez, Hartmut Herrmann, and Mira Pöhlker
Atmos. Chem. Phys., 25, 741–758, https://doi.org/10.5194/acp-25-741-2025, https://doi.org/10.5194/acp-25-741-2025, 2025
Short summary
Short summary
Aerosol hygroscopicity has been investigated at a sub-urban site in Paris; analysis shows the sub-saturated regime's measured hygroscopicity and the chemically derived hygroscopic growth, shedding light on the large effect of external particle mixing and its influence on predicting hygroscopicity.
Alexandre Mass, Hendrik Andersen, Jan Cermak, Paola Formenti, Eva Pauli, and Julian Quinting
Atmos. Chem. Phys., 25, 491–510, https://doi.org/10.5194/acp-25-491-2025, https://doi.org/10.5194/acp-25-491-2025, 2025
Short summary
Short summary
This study investigates the interaction between smoke aerosols and fog and low clouds (FLCs) in the Namib Desert between June and October. Here, a satellite-based dataset of FLCs, reanalysis data and machine learning are used to systematically analyze FLC persistence under different aerosol loadings. Aerosol plumes are shown to modify local thermodynamics, which increase FLC persistence. But fully disentangling aerosol effects from meteorological ones remains a challenge.
Martial Haeffelin, Jean-François Ribaud, Jonnathan Céspedes, Jean-Charles Dupont, Aude Lemonsu, Valéry Masson, Tim Nagel, and Simone Kotthaus
Atmos. Chem. Phys., 24, 14101–14122, https://doi.org/10.5194/acp-24-14101-2024, https://doi.org/10.5194/acp-24-14101-2024, 2024
Short summary
Short summary
This study highlights how the state of the urban atmospheric boundary layer impacts urban park cooling effect intensity at night. Under summertime heat wave conditions, the urban atmosphere becomes stable at night, which inhibits turbulent motions. Under those specific conditions, urban parks and woods cool much more efficiently than the surrounding built-up neighbourhoods in the evening and through the night, providing cooler air temperatures by 4 to 6° C depending on park size.
Yichen Jia, Hendrik Andersen, and Jan Cermak
Atmos. Chem. Phys., 24, 13025–13045, https://doi.org/10.5194/acp-24-13025-2024, https://doi.org/10.5194/acp-24-13025-2024, 2024
Short summary
Short summary
We present a near-global observation-based explainable machine learning framework to quantify the response of cloud fraction (CLF) of marine low clouds to cloud droplet number concentration (Nd), accounting for the covariations with meteorological factors. This approach provides a novel data-driven method to analyse the CLF adjustment by assessing the CLF sensitivity to Nd and numerous meteorological factors as well as the dependence of the Nd–CLF sensitivity on the meteorological conditions.
Hasna Chebaicheb, Joel F. de Brito, Tanguy Amodeo, Florian Couvidat, Jean-Eudes Petit, Emmanuel Tison, Gregory Abbou, Alexia Baudic, Mélodie Chatain, Benjamin Chazeau, Nicolas Marchand, Raphaële Falhun, Florie Francony, Cyril Ratier, Didier Grenier, Romain Vidaud, Shouwen Zhang, Gregory Gille, Laurent Meunier, Caroline Marchand, Véronique Riffault, and Olivier Favez
Earth Syst. Sci. Data, 16, 5089–5109, https://doi.org/10.5194/essd-16-5089-2024, https://doi.org/10.5194/essd-16-5089-2024, 2024
Short summary
Short summary
Long-term (2015–2021) quasi-continuous measurements have been obtained at 13 French urban sites using online mass spectrometry, to acquire the comprehensive chemical composition of submicron particulate matter. The results show their spatial and temporal differences and confirm the predominance of organics in France (40–60 %). These measurements can be used for many future studies, such as trend and epidemiological analyses, or comparisons with chemical transport models.
Jonnathan Céspedes, Simone Kotthaus, Jana Preissler, Clément Toupoint, Ludovic Thobois, Marc-Antoine Drouin, Jean-Charles Dupont, Aurélien Faucheux, and Martial Haeffelin
Atmos. Chem. Phys., 24, 11477–11496, https://doi.org/10.5194/acp-24-11477-2024, https://doi.org/10.5194/acp-24-11477-2024, 2024
Short summary
Short summary
The low-level jet (LLJ) is common in Paris during summer. The LLJ core height and speed significantly influence vertical mixing in the urban boundary layer, which affects air temperature variations between the urban canopy layer and surrounding rural areas, determining the urban heat island (UHI) intensity. This study highlights the importance of wind profile observations for understanding urban boundary layer dynamics and near-surface atmospheric conditions relevant to health.
Matthieu Vida, Gilles Foret, Guillaume Siour, Florian Couvidat, Olivier Favez, Gaelle Uzu, Arineh Cholakian, Sébastien Conil, Matthias Beekmann, and Jean-Luc Jaffrezo
Atmos. Chem. Phys., 24, 10601–10615, https://doi.org/10.5194/acp-24-10601-2024, https://doi.org/10.5194/acp-24-10601-2024, 2024
Short summary
Short summary
We simulate 2 years of atmospheric fungal spores over France and use observations of polyols and primary biogenic factors from positive matrix factorisation. The representation of emissions taking into account a proxy for vegetation surface and specific humidity enables us to reproduce very accurately the seasonal cycle of fungal spores. Furthermore, we estimate that fungal spores can account for 20 % of PM10 and 40 % of the organic fraction of PM10 over vegetated areas in summer.
Sarah Wilson Kemsley, Paulo Ceppi, Hendrik Andersen, Jan Cermak, Philip Stier, and Peer Nowack
Atmos. Chem. Phys., 24, 8295–8316, https://doi.org/10.5194/acp-24-8295-2024, https://doi.org/10.5194/acp-24-8295-2024, 2024
Short summary
Short summary
Aiming to inform parameter selection for future observational constraint analyses, we incorporate five candidate meteorological drivers specifically targeting high clouds into a cloud controlling factor framework within a range of spatial domain sizes. We find a discrepancy between optimal domain size for predicting locally and globally aggregated cloud radiative anomalies and identify upper-tropospheric static stability as an important high-cloud controlling factor.
Vy Dinh Ngoc Thuy, Jean-Luc Jaffrezo, Ian Hough, Pamela A. Dominutti, Guillaume Salque Moreton, Grégory Gille, Florie Francony, Arabelle Patron-Anquez, Olivier Favez, and Gaëlle Uzu
Atmos. Chem. Phys., 24, 7261–7282, https://doi.org/10.5194/acp-24-7261-2024, https://doi.org/10.5194/acp-24-7261-2024, 2024
Short summary
Short summary
The capacity of particulate matter (PM) to generate reactive oxygen species in vivo is represented by oxidative potential (OP). This study focuses on finding the appropriate model to evaluate the oxidative character of PM sources in six sites using the PM sources and OP. Eight regression techniques are introduced to assess the OP of PM. The study highlights the importance of selecting a model according to the input data characteristics and establishes some recommendations for the procedure.
Alice Maison, Lya Lugon, Soo-Jin Park, Alexia Baudic, Christopher Cantrell, Florian Couvidat, Barbara D'Anna, Claudia Di Biagio, Aline Gratien, Valérie Gros, Carmen Kalalian, Julien Kammer, Vincent Michoud, Jean-Eudes Petit, Marwa Shahin, Leila Simon, Myrto Valari, Jérémy Vigneron, Andrée Tuzet, and Karine Sartelet
Atmos. Chem. Phys., 24, 6011–6046, https://doi.org/10.5194/acp-24-6011-2024, https://doi.org/10.5194/acp-24-6011-2024, 2024
Short summary
Short summary
This study presents the development of a bottom-up inventory of urban tree biogenic emissions. Emissions are computed for each tree based on their location and characteristics and are integrated in the regional air quality model WRF-CHIMERE. The impact of these biogenic emissions on air quality is quantified for June–July 2022. Over Paris city, urban trees increase the concentrations of particulate organic matter by 4.6 %, of PM2.5 by 0.6 %, and of ozone by 1.0 % on average over 2 months.
Karine Desboeufs, Paola Formenti, Raquel Torres-Sánchez, Kerstin Schepanski, Jean-Pierre Chaboureau, Hendrik Andersen, Jan Cermak, Stefanie Feuerstein, Benoit Laurent, Danitza Klopper, Andreas Namwoonde, Mathieu Cazaunau, Servanne Chevaillier, Anaïs Feron, Cécile Mirande-Bret, Sylvain Triquet, and Stuart J. Piketh
Atmos. Chem. Phys., 24, 1525–1541, https://doi.org/10.5194/acp-24-1525-2024, https://doi.org/10.5194/acp-24-1525-2024, 2024
Short summary
Short summary
This study investigates the fractional solubility of iron (Fe) in dust particles along the coast of Namibia, a critical region for the atmospheric Fe supply of the South Atlantic Ocean. Our results suggest a possible two-way interplay whereby marine biogenic emissions from the coastal marine ecosystems into the atmosphere would increase the solubility of Fe-bearing dust by photo-reduction processes. The subsequent deposition of soluble Fe could act to further enhance marine biogenic emissions.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
Short summary
Short summary
For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Cheikh Dione, Martial Haeffelin, Frédéric Burnet, Christine Lac, Guylaine Canut, Julien Delanoë, Jean-Charles Dupont, Susana Jorquera, Pauline Martinet, Jean-François Ribaud, and Felipe Toledo
Atmos. Chem. Phys., 23, 15711–15731, https://doi.org/10.5194/acp-23-15711-2023, https://doi.org/10.5194/acp-23-15711-2023, 2023
Short summary
Short summary
This paper documents the role of thermodynamics and turbulence in the fog life cycle over southwestern France. It is based on a unique dataset collected during the SOFOG3D field campaign in autumn and winter 2019–2020. The paper gives a threshold for turbulence driving the different phases of the fog life cycle and the role of advection in the night-time dissipation of fog. The results can be operationalised to nowcast fog and improve short-range forecasts in numerical weather prediction models.
Abd El Rahman El Mais, Barbara D'Anna, Luka Drinovec, Andrew T. Lambe, Zhe Peng, Jean-Eudes Petit, Olivier Favez, Selim Aït-Aïssa, and Alexandre Albinet
Atmos. Chem. Phys., 23, 15077–15096, https://doi.org/10.5194/acp-23-15077-2023, https://doi.org/10.5194/acp-23-15077-2023, 2023
Short summary
Short summary
Polycyclic aromatic hydrocarbons (PAHS) and furans are key precursors of secondary organic aerosols (SOAs) related to biomass burning emissions. We evaluated and compared the formation yields, and the physical and light absorption properties, of laboratory-generated SOAs from the oxidation of such compounds for both, day- and nighttime reactivities. The results illustrate that PAHs are large SOA precursors and may contribute significantly to the biomass burning brown carbon in the atmosphere.
Hendrik Andersen, Jan Cermak, Alyson Douglas, Timothy A. Myers, Peer Nowack, Philip Stier, Casey J. Wall, and Sarah Wilson Kemsley
Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, https://doi.org/10.5194/acp-23-10775-2023, 2023
Short summary
Short summary
This study uses an observation-based cloud-controlling factor framework to study near-global sensitivities of cloud radiative effects to a large number of meteorological and aerosol controls. We present near-global sensitivity patterns to selected thermodynamic, dynamic, and aerosol factors and discuss the physical mechanisms underlying the derived sensitivities. Our study hopes to guide future analyses aimed at constraining cloud feedbacks and aerosol–cloud interactions.
Jean-Philippe Putaud, Enrico Pisoni, Alexander Mangold, Christoph Hueglin, Jean Sciare, Michael Pikridas, Chrysanthos Savvides, Jakub Ondracek, Saliou Mbengue, Alfred Wiedensohler, Kay Weinhold, Maik Merkel, Laurent Poulain, Dominik van Pinxteren, Hartmut Herrmann, Andreas Massling, Claus Nordstroem, Andrés Alastuey, Cristina Reche, Noemí Pérez, Sonia Castillo, Mar Sorribas, Jose Antonio Adame, Tuukka Petaja, Katrianne Lehtipalo, Jarkko Niemi, Véronique Riffault, Joel F. de Brito, Augustin Colette, Olivier Favez, Jean-Eudes Petit, Valérie Gros, Maria I. Gini, Stergios Vratolis, Konstantinos Eleftheriadis, Evangelia Diapouli, Hugo Denier van der Gon, Karl Espen Yttri, and Wenche Aas
Atmos. Chem. Phys., 23, 10145–10161, https://doi.org/10.5194/acp-23-10145-2023, https://doi.org/10.5194/acp-23-10145-2023, 2023
Short summary
Short summary
Many European people are still exposed to levels of air pollution that can affect their health. COVID-19 lockdowns in 2020 were used to assess the impact of the reduction in human mobility on air pollution across Europe by comparing measurement data with values that would be expected if no lockdown had occurred. We show that lockdown measures did not lead to consistent decreases in the concentrations of fine particulate matter suspended in the air, and we investigate why.
Jinghui Lian, Thomas Lauvaux, Hervé Utard, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, Olivier Laurent, Ivonne Albarus, Mali Chariot, Simone Kotthaus, Martial Haeffelin, Olivier Sanchez, Olivier Perrussel, Hugo Anne Denier van der Gon, Stijn Nicolaas Camiel Dellaert, and Philippe Ciais
Atmos. Chem. Phys., 23, 8823–8835, https://doi.org/10.5194/acp-23-8823-2023, https://doi.org/10.5194/acp-23-8823-2023, 2023
Short summary
Short summary
This study quantifies urban CO2 emissions via an atmospheric inversion for the Paris metropolitan area over a 6-year period from 2016 to 2021. Results show a long-term decreasing trend of about 2 % ± 0.6 % per year in the annual CO2 emissions over Paris. We conclude that our current capacity can deliver near-real-time CO2 emission estimates at the city scale in under a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.
Frédéric Ledoux, Cloé Roche, Gilles Delmaire, Gilles Roussel, Olivier Favez, Marc Fadel, and Dominique Courcot
Atmos. Chem. Phys., 23, 8607–8622, https://doi.org/10.5194/acp-23-8607-2023, https://doi.org/10.5194/acp-23-8607-2023, 2023
Short summary
Short summary
We quantify the emissions from the marine sector in northern France, whether from natural or human-made sources. Therefore, a 1-year PM10 sampling campaign was conducted at a French coastal site. Results showed that sea salts contributed 37 %, while secondary nitrate and sulfate contributed 42 %, biomass burning 8 %, and heavy-fuel-oil combustion from shipping emissions 5 %. Sources contributing more than 80 % of PM10 are of regional and/or long-range origin.
Joanna E. Dyson, Lisa K. Whalley, Eloise J. Slater, Robert Woodward-Massey, Chunxiang Ye, James D. Lee, Freya Squires, James R. Hopkins, Rachel E. Dunmore, Marvin Shaw, Jacqueline F. Hamilton, Alastair C. Lewis, Stephen D. Worrall, Asan Bacak, Archit Mehra, Thomas J. Bannan, Hugh Coe, Carl J. Percival, Bin Ouyang, C. Nicholas Hewitt, Roderic L. Jones, Leigh R. Crilley, Louisa J. Kramer, W. Joe F. Acton, William J. Bloss, Supattarachai Saksakulkrai, Jingsha Xu, Zongbo Shi, Roy M. Harrison, Simone Kotthaus, Sue Grimmond, Yele Sun, Weiqi Xu, Siyao Yue, Lianfang Wei, Pingqing Fu, Xinming Wang, Stephen R. Arnold, and Dwayne E. Heard
Atmos. Chem. Phys., 23, 5679–5697, https://doi.org/10.5194/acp-23-5679-2023, https://doi.org/10.5194/acp-23-5679-2023, 2023
Short summary
Short summary
The hydroxyl (OH) and closely coupled hydroperoxyl (HO2) radicals are vital for their role in the removal of atmospheric pollutants. In less polluted regions, atmospheric models over-predict HO2 concentrations. In this modelling study, the impact of heterogeneous uptake of HO2 onto aerosol surfaces on radical concentrations and the ozone production regime in Beijing in the summertime is investigated, and the implications for emissions policies across China are considered.
Leïla Simon, Valérie Gros, Jean-Eudes Petit, François Truong, Roland Sarda-Estève, Carmen Kalalian, Alexia Baudic, Caroline Marchand, and Olivier Favez
Earth Syst. Sci. Data, 15, 1947–1968, https://doi.org/10.5194/essd-15-1947-2023, https://doi.org/10.5194/essd-15-1947-2023, 2023
Short summary
Short summary
Long-term measurements of volatile organic compounds (VOCs) have been set up to better characterize the atmospheric chemistry at the SIRTA national facility (Paris area, France). Results obtained from the first 2 years (2020–2021) confirm the importance of local sources for short-lived compounds and the role played by meteorology and air mass origins in the long-term analysis of VOCs. They also point to a substantial influence of anthropogenic on the monoterpene loadings.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
Short summary
Short summary
Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Andreas Plach, Rolf Rüfenacht, Simone Kotthaus, and Markus Leuenberger
EGUsphere, https://doi.org/10.5194/egusphere-2022-1019, https://doi.org/10.5194/egusphere-2022-1019, 2022
Preprint archived
Short summary
Short summary
Greenhouse gases emissions are contributing to global warming and it is essential to better understand where they originate from and how they are transported. In this study we analyze greenhouse gas observations at a Swiss tall tower where measurements are taken more than 200 m above ground and investigate their origin by looking at the condition of the atmosphere at the time of the observations. We find that most pollution at this site is caused from emissions transported from further away.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
Short summary
Short summary
We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Marsailidh M. Twigg, Augustinus J. C. Berkhout, Nicholas Cowan, Sabine Crunaire, Enrico Dammers, Volker Ebert, Vincent Gaudion, Marty Haaima, Christoph Häni, Lewis John, Matthew R. Jones, Bjorn Kamps, John Kentisbeer, Thomas Kupper, Sarah R. Leeson, Daiana Leuenberger, Nils O. B. Lüttschwager, Ulla Makkonen, Nicholas A. Martin, David Missler, Duncan Mounsor, Albrecht Neftel, Chad Nelson, Eiko Nemitz, Rutger Oudwater, Celine Pascale, Jean-Eudes Petit, Andrea Pogany, Nathalie Redon, Jörg Sintermann, Amy Stephens, Mark A. Sutton, Yuk S. Tang, Rens Zijlmans, Christine F. Braban, and Bernhard Niederhauser
Atmos. Meas. Tech., 15, 6755–6787, https://doi.org/10.5194/amt-15-6755-2022, https://doi.org/10.5194/amt-15-6755-2022, 2022
Short summary
Short summary
Ammonia (NH3) gas in the atmosphere impacts the environment, human health, and, indirectly, climate. Historic NH3 monitoring was labour intensive, and the instruments were complicated. Over the last decade, there has been a rapid technology development, including “plug-and-play” instruments. This study is an extensive field comparison of the currently available technologies and provides evidence that for routine monitoring, standard operating protocols are required for datasets to be comparable.
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
Short summary
Short summary
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.
Julia Fuchs, Hendrik Andersen, Jan Cermak, Eva Pauli, and Rob Roebeling
Atmos. Meas. Tech., 15, 4257–4270, https://doi.org/10.5194/amt-15-4257-2022, https://doi.org/10.5194/amt-15-4257-2022, 2022
Short summary
Short summary
Two cloud-masking approaches, a local and a regional approach, using high-resolution satellite data are developed and validated for the region of Paris to improve applicability for analyses of urban effects on low clouds. We found that cloud masks obtained from the regional approach are more appropriate for the high-resolution analysis of locally induced cloud processes. Its applicability is tested for the analysis of typical fog conditions over different surface types.
Adam Brighty, Véronique Jacob, Gaëlle Uzu, Lucille Borlaza, Sébastien Conil, Christoph Hueglin, Stuart K. Grange, Olivier Favez, Cécile Trébuchon, and Jean-Luc Jaffrezo
Atmos. Chem. Phys., 22, 6021–6043, https://doi.org/10.5194/acp-22-6021-2022, https://doi.org/10.5194/acp-22-6021-2022, 2022
Short summary
Short summary
With an revised analytical method and long-term sampling strategy, we have been able to elucidate much more information about atmospheric plant debris, a poorly understood class of particulate matter. We found weaker seasonal patterns at urban locations compared to rural locations and significant interannual variability in concentrations between previous years and 2020, during the COVID-19 pandemic. This suggests a possible man-made influence on plant debris concentration and source strength.
Babak Jahani, Hendrik Andersen, Josep Calbó, Josep-Abel González, and Jan Cermak
Atmos. Chem. Phys., 22, 1483–1494, https://doi.org/10.5194/acp-22-1483-2022, https://doi.org/10.5194/acp-22-1483-2022, 2022
Short summary
Short summary
The change in the state of sky from cloudy to cloudless (or vice versa) comprises an additional phase called
transition zonewith characteristics laying between those of aerosols and clouds. This study presents an approach for the quantification of the broadband longwave radiative effects of the cloud–aerosol transition zone at the top of the atmosphere during daytime over the ocean based on satellite observations and radiative transfer simulations.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
Short summary
Short summary
Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Jean-François Ribaud, Martial Haeffelin, Jean-Charles Dupont, Marc-Antoine Drouin, Felipe Toledo, and Simone Kotthaus
Atmos. Meas. Tech., 14, 7893–7907, https://doi.org/10.5194/amt-14-7893-2021, https://doi.org/10.5194/amt-14-7893-2021, 2021
Short summary
Short summary
PARAFOG is a near-real-time decision tool that aims to retrieve pre-fog alert levels minutes to hours prior to fog onset. The second version of PARAFOG allows us to discriminate between radiation and stratus lowering fog situations. It is based upon the combination of visibility observations and automatic lidar and ceilometer measurements. The overall performance of the second version of PARAFOG over more than 300 fog cases at five different locations presents a good perfomance.
Clémence Rose, Martine Collaud Coen, Elisabeth Andrews, Yong Lin, Isaline Bossert, Cathrine Lund Myhre, Thomas Tuch, Alfred Wiedensohler, Markus Fiebig, Pasi Aalto, Andrés Alastuey, Elisabeth Alonso-Blanco, Marcos Andrade, Begoña Artíñano, Todor Arsov, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Juan Andrés Casquero-Vera, Sébastien Conil, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Maria I. Gini, Francisco Javier Gómez-Moreno, Martin Gysel-Beer, Anna Gannet Hallar, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Neng-Huei Lin, Hassan Lyamani, Angela Marinoni, Sebastiao Martins Dos Santos, Olga L. Mayol-Bracero, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Jakub Ondracek, Marco Pandolfi, Noemi Pérez, Tuukka Petäjä, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Jean-Philippe Putaud, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Junying Sun, Pierre Tulet, Ville Vakkari, Pieter Gideon van Zyl, Fernando Velarde, Paolo Villani, Stergios Vratolis, Zdenek Wagner, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Vladimir Zdimal, and Paolo Laj
Atmos. Chem. Phys., 21, 17185–17223, https://doi.org/10.5194/acp-21-17185-2021, https://doi.org/10.5194/acp-21-17185-2021, 2021
Short summary
Short summary
Aerosol particles are a complex component of the atmospheric system the effects of which are among the most uncertain in climate change projections. Using data collected at 62 stations, this study provides the most up-to-date picture of the spatial distribution of particle number concentration and size distribution worldwide, with the aim of contributing to better representation of aerosols and their interactions with clouds in models and, therefore, better evaluation of their impact on climate.
Jean-Eudes Petit, Jean-Charles Dupont, Olivier Favez, Valérie Gros, Yunjiang Zhang, Jean Sciare, Leila Simon, François Truong, Nicolas Bonnaire, Tanguy Amodeo, Robert Vautard, and Martial Haeffelin
Atmos. Chem. Phys., 21, 17167–17183, https://doi.org/10.5194/acp-21-17167-2021, https://doi.org/10.5194/acp-21-17167-2021, 2021
Short summary
Short summary
The COVID-19 outbreak led to lockdowns at national scales in spring 2020. Large cuts in emissions occurred, but the quantitative assessment of their role from observations is hindered by weather and interannual variability. That is why we developed an innovative methodology in order to best characterize the impact of lockdown on atmospheric chemistry. We find that a local decrease in traffic-related pollutants triggered a decrease of secondary aerosols and an increase in ozone.
Michael Biggart, Jenny Stocker, Ruth M. Doherty, Oliver Wild, David Carruthers, Sue Grimmond, Yiqun Han, Pingqing Fu, and Simone Kotthaus
Atmos. Chem. Phys., 21, 13687–13711, https://doi.org/10.5194/acp-21-13687-2021, https://doi.org/10.5194/acp-21-13687-2021, 2021
Short summary
Short summary
Heat-related illnesses are of increasing concern in China given its rapid urbanisation and our ever-warming climate. We examine the relative impacts that land surface properties and anthropogenic heat have on the urban heat island (UHI) in Beijing using ADMS-Urban. Air temperature measurements and satellite-derived land surface temperatures provide valuable means of evaluating modelled spatiotemporal variations. This work provides critical information for urban planners and UHI mitigation.
Felipe Toledo, Martial Haeffelin, Eivind Wærsted, and Jean-Charles Dupont
Atmos. Chem. Phys., 21, 13099–13117, https://doi.org/10.5194/acp-21-13099-2021, https://doi.org/10.5194/acp-21-13099-2021, 2021
Short summary
Short summary
The article presents a new conceptual model to describe the temporal evolution of continental fog layers, developed based on 7 years of fog measurements performed at the SIRTA observatory, France. This new paradigm relates the visibility reduction caused by fog to its vertical thickness and liquid water path and provides diagnostic variables that could substantially improve the reliability of fog dissipation nowcasting at a local scale, based on real-time profiling observation.
Rebecca D. Kutzner, Juan Cuesta, Pascale Chelin, Jean-Eudes Petit, Mokhtar Ray, Xavier Landsheere, Benoît Tournadre, Jean-Charles Dupont, Amandine Rosso, Frank Hase, Johannes Orphal, and Matthias Beekmann
Atmos. Chem. Phys., 21, 12091–12111, https://doi.org/10.5194/acp-21-12091-2021, https://doi.org/10.5194/acp-21-12091-2021, 2021
Short summary
Short summary
Our work investigates the diurnal evolution of atmospheric ammonia concentrations during a major pollution event. It analyses it in regard of both chemical (gas–particle conversion) and physical (vertical mixing, meteorology) processes in the atmosphere. These mechanisms are key for understanding the evolution of the physicochemical state of the atmosphere; therefore, it clearly fits into the scope of Atmospheric Chemistry and Physics.
Samuël Weber, Gaëlle Uzu, Olivier Favez, Lucille Joanna S. Borlaza, Aude Calas, Dalia Salameh, Florie Chevrier, Julie Allard, Jean-Luc Besombes, Alexandre Albinet, Sabrina Pontet, Boualem Mesbah, Grégory Gille, Shouwen Zhang, Cyril Pallares, Eva Leoz-Garziandia, and Jean-Luc Jaffrezo
Atmos. Chem. Phys., 21, 11353–11378, https://doi.org/10.5194/acp-21-11353-2021, https://doi.org/10.5194/acp-21-11353-2021, 2021
Short summary
Short summary
Oxidative potential (OP) of aerosols is apportioned to the main PM sources found in 15 sites over France. The sources present clear distinct intrinsic OPs at a large geographic scale, and a drastic redistribution between the mass concentration and OP measured by both ascorbic acid and dithiothreitol is highlighted. Moreover, the high discrepancy between the mean and median contributions of the sources to the given metrics raises some important questions when dealing with health endpoints.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais
Atmos. Chem. Phys., 21, 10707–10726, https://doi.org/10.5194/acp-21-10707-2021, https://doi.org/10.5194/acp-21-10707-2021, 2021
Short summary
Short summary
Currently there is growing interest in monitoring city-scale CO2 emissions based on atmospheric CO2 measurements, atmospheric transport modeling, and inversion technique. We analyze the various sources of uncertainty that impact the atmospheric CO2 modeling and that may compromise the potential of this method for the monitoring of CO2 emission over Paris. Results suggest selection criteria for the assimilation of CO2 measurements into the inversion system that aims at retrieving city emissions.
Claire E. Reeves, Graham P. Mills, Lisa K. Whalley, W. Joe F. Acton, William J. Bloss, Leigh R. Crilley, Sue Grimmond, Dwayne E. Heard, C. Nicholas Hewitt, James R. Hopkins, Simone Kotthaus, Louisa J. Kramer, Roderic L. Jones, James D. Lee, Yanhui Liu, Bin Ouyang, Eloise Slater, Freya Squires, Xinming Wang, Robert Woodward-Massey, and Chunxiang Ye
Atmos. Chem. Phys., 21, 6315–6330, https://doi.org/10.5194/acp-21-6315-2021, https://doi.org/10.5194/acp-21-6315-2021, 2021
Short summary
Short summary
The impact of isoprene on atmospheric chemistry is dependent on how its oxidation products interact with other pollutants, specifically nitrogen oxides. Such interactions can lead to isoprene nitrates. We made measurements of the concentrations of individual isoprene nitrate isomers in Beijing and used a model to test current understanding of their chemistry. We highlight areas of uncertainty in understanding, in particular the chemistry following oxidation of isoprene by the nitrate radical.
Lucille Joanna S. Borlaza, Samuël Weber, Gaëlle Uzu, Véronique Jacob, Trishalee Cañete, Steve Micallef, Cécile Trébuchon, Rémy Slama, Olivier Favez, and Jean-Luc Jaffrezo
Atmos. Chem. Phys., 21, 5415–5437, https://doi.org/10.5194/acp-21-5415-2021, https://doi.org/10.5194/acp-21-5415-2021, 2021
Short summary
Short summary
This study focuses on fully discriminating the origins of particulates by tackling specific secondary organic aerosol (SOA) sources that are difficult to resolve using traditional datasets, especially at a city scale. This is done through the use of additional fit-for-purpose tracers in the Positive Matrix Factorization (PMF) model, which can be obtained using simpler and more targeted techniques, and the comparison of the PMF models from sites in close range but with different urban typologies.
Wenhua Wang, Longyi Shao, Claudio Mazzoleni, Yaowei Li, Simone Kotthaus, Sue Grimmond, Janarjan Bhandari, Jiaoping Xing, Xiaolei Feng, Mengyuan Zhang, and Zongbo Shi
Atmos. Chem. Phys., 21, 5301–5314, https://doi.org/10.5194/acp-21-5301-2021, https://doi.org/10.5194/acp-21-5301-2021, 2021
Short summary
Short summary
We compared the characteristics of individual particles at ground level and above the mixed-layer height. We found that the particles above the mixed-layer height during haze periods are more aged compared to ground level. More coal-combustion-related primary organic particles were found above the mixed-layer height. We suggest that the particles above the mixed-layer height are affected by the surrounding areas, and once mixed down to the ground, they might contribute to ground air pollution.
Jianhui Jiang, Imad El Haddad, Sebnem Aksoyoglu, Giulia Stefenelli, Amelie Bertrand, Nicolas Marchand, Francesco Canonaco, Jean-Eudes Petit, Olivier Favez, Stefania Gilardoni, Urs Baltensperger, and André S. H. Prévôt
Geosci. Model Dev., 14, 1681–1697, https://doi.org/10.5194/gmd-14-1681-2021, https://doi.org/10.5194/gmd-14-1681-2021, 2021
Short summary
Short summary
We developed a box model with a volatility basis set to simulate organic aerosol (OA) from biomass burning and optimized the vapor-wall-loss-corrected OA yields with a genetic algorithm. The optimized parameterizations were then implemented in the air quality model CAMx v6.5. Comparisons with ambient measurements indicate that the vapor-wall-loss-corrected parameterization effectively improves the model performance in predicting OA, which reduced the mean fractional bias from −72.9 % to −1.6 %.
Lisa K. Whalley, Eloise J. Slater, Robert Woodward-Massey, Chunxiang Ye, James D. Lee, Freya Squires, James R. Hopkins, Rachel E. Dunmore, Marvin Shaw, Jacqueline F. Hamilton, Alastair C. Lewis, Archit Mehra, Stephen D. Worrall, Asan Bacak, Thomas J. Bannan, Hugh Coe, Carl J. Percival, Bin Ouyang, Roderic L. Jones, Leigh R. Crilley, Louisa J. Kramer, William J. Bloss, Tuan Vu, Simone Kotthaus, Sue Grimmond, Yele Sun, Weiqi Xu, Siyao Yue, Lujie Ren, W. Joe F. Acton, C. Nicholas Hewitt, Xinming Wang, Pingqing Fu, and Dwayne E. Heard
Atmos. Chem. Phys., 21, 2125–2147, https://doi.org/10.5194/acp-21-2125-2021, https://doi.org/10.5194/acp-21-2125-2021, 2021
Short summary
Short summary
To understand how emission controls will impact ozone, an understanding of the sources and sinks of OH and the chemical cycling between peroxy radicals is needed. This paper presents measurements of OH, HO2 and total RO2 taken in central Beijing. The radical observations are compared to a detailed chemistry model, which shows that under low NO conditions, there is a missing OH source. Under high NOx conditions, the model under-predicts RO2 and impacts our ability to model ozone.
Rutambhara Joshi, Dantong Liu, Eiko Nemitz, Ben Langford, Neil Mullinger, Freya Squires, James Lee, Yunfei Wu, Xiaole Pan, Pingqing Fu, Simone Kotthaus, Sue Grimmond, Qiang Zhang, Ruili Wu, Oliver Wild, Michael Flynn, Hugh Coe, and James Allan
Atmos. Chem. Phys., 21, 147–162, https://doi.org/10.5194/acp-21-147-2021, https://doi.org/10.5194/acp-21-147-2021, 2021
Short summary
Short summary
Black carbon (BC) is a component of particulate matter which has significant effects on climate and human health. Sources of BC include biomass burning, transport, industry and domestic cooking and heating. In this study, we measured BC emissions in Beijing, finding a dominance of traffic emissions over all other sources. The quantitative method presented here has benefits for revising widely used emissions inventories and for understanding BC sources with impacts on air quality and climate.
Felipe Toledo, Julien Delanoë, Martial Haeffelin, Jean-Charles Dupont, Susana Jorquera, and Christophe Le Gac
Atmos. Meas. Tech., 13, 6853–6875, https://doi.org/10.5194/amt-13-6853-2020, https://doi.org/10.5194/amt-13-6853-2020, 2020
Short summary
Short summary
Cloud observations are essential to rainfall, fog and climate change forecasts. One key instrument for these observations is cloud radar. Yet, discrepancies are found when comparing radars from different ground stations or satellites. Our work presents a calibration methodology for cloud radars based on reference targets, including an analysis of the uncertainty sources. The method enables the calibration of reference instruments to improve the quality and value of the cloud radar network data.
Laurent Poulain, Gerald Spindler, Achim Grüner, Thomas Tuch, Bastian Stieger, Dominik van Pinxteren, Jean-Eudes Petit, Olivier Favez, Hartmut Herrmann, and Alfred Wiedensohler
Atmos. Meas. Tech., 13, 4973–4994, https://doi.org/10.5194/amt-13-4973-2020, https://doi.org/10.5194/amt-13-4973-2020, 2020
Short summary
Short summary
The stability and the comparability between ACSM and collocated filter sampling and MPSS measurements was investigated in order to examine the instruments robustness for year-long measurements. Specific attention was paid to the influence of the upper size cutoff diameter to better understand how it might affect the data validation. Recommendations are provided for better on-site quality assurance and quality control of the ACSM, which would be useful for either long-term or intensive campaigns.
Cited articles
Baklanov, A., Molina, L. T., and Gauss, M.: Megacities, air quality and
climate, Atmos. Environ., 126, 235–249,
https://doi.org/10.1016/j.atmosenv.2015.11.059, 2016. a
Beekmann, M., Prévôt, A. S. H., Drewnick, F., Sciare, J., Pandis, S. N., Denier van der Gon, H. A. C., Crippa, M., Freutel, F., Poulain, L., Ghersi, V., Rodriguez, E., Beirle, S., Zotter, P., von der Weiden-Reinmüller, S.-L., Bressi, M., Fountoukis, C., Petetin, H., Szidat, S., Schneider, J., Rosso, A., El Haddad, I., Megaritis, A., Zhang, Q. J., Michoud, V., Slowik, J. G., Moukhtar, S., Kolmonen, P., Stohl, A., Eckhardt, S., Borbon, A., Gros, V., Marchand, N., Jaffrezo, J. L., Schwarzenboeck, A., Colomb, A., Wiedensohler, A., Borrmann, S., Lawrence, M., Baklanov, A., and Baltensperger, U.: In situ, satellite measurement and model evidence on the dominant regional contribution to fine particulate matter levels in the Paris megacity, Atmos. Chem. Phys., 15, 9577–9591, https://doi.org/10.5194/acp-15-9577-2015, 2015. a
Bressi, M., Sciare, J., Ghersi, V., Bonnaire, N., Nicolas, J. B., Petit, J.-E., Moukhtar, S., Rosso, A., Mihalopoulos, N., and Féron, A.: A one-year comprehensive chemical characterisation of fine aerosol (PM2.5) at urban, suburban and rural background sites in the region of Paris (France), Atmos. Chem. Phys., 13, 7825–7844, https://doi.org/10.5194/acp-13-7825-2013, 2013. a, b, c, d, e, f, g, h, i, j, k, l
Bressi, M., Sciare, J., Ghersi, V., Mihalopoulos, N., Petit, J.-E., Nicolas, J. B., Moukhtar, S., Rosso, A., Féron, A., Bonnaire, N., Poulakis, E., and Theodosi, C.: Sources and geographical origins of fine aerosols in Paris (France), Atmos. Chem. Phys., 14, 8813–8839, https://doi.org/10.5194/acp-14-8813-2014, 2014. a, b
Cermak, J. and Knutti, R.: Beijing Olympics as an aerosol field experiment,
Geophys. Res. Lett., 36, L10806, https://doi.org/10.1029/2009GL038572, 2009. a, b
Chafe, Z. A., Brauer, M., Klimont, Z., Van Dingenen, R., Mehta, S., Rao, S.,
Riahi, K., Dentener, F., and Smith, K. R.: Household Cooking with Solid
Fuels Contributes to Ambient PM2.5 Air Pollution and the Burden of Disease,
Environ. Health Perspect., 122, 1314–1320, https://doi.org/10.1289/ehp.1206340, 2014. a
Chen, G., Li, S., Zhang, Y., Zhang, W., Li, D., Wei, X., He, Y., Bell, M. L.,
Williams, G., Marks, G. B., Jalaludin, B., Abramson, M. J., and Guo, Y.:
Effects of ambient PM1 air pollution on daily emergency hospital visits in
China: an epidemiological study, Lancet Planet. Heal., 1, 221–229,
https://doi.org/10.1016/S2542-5196(17)30100-6, 2017. a, b
Chen, Y., Schleicher, N., Chen, Y., Chai, F., and Norra, S.: The influence of
governmental mitigation measures on contamination characteristics of PM2.5 in
Beijing, Sci. Total Environ., 490, 647–658,
https://doi.org/10.1016/j.scitotenv.2014.05.049, 2014. a
Cheng, Y., Zheng, G., Wei, C., Mu, Q., Zheng, B., Wang, Z., Gao, M., Zhang, Q.,
He, K., Carmichael, G., Pöschl, U., and Su, H.: Reactive nitrogen
chemistry in aerosol water as a source of sulfate during haze events in
China, Sci. Adv., 2, e1601530, https://doi.org/10.1126/sciadv.1601530, 2016. a
Chiriaco, M., Dupont, J.-C., Bastin, S., Badosa, J., Lopez, J., Haeffelin, M., Chepfer, H., and Guzman, R.: ReOBS: a new approach to synthesize long-term multi-variable dataset and application to the SIRTA supersite, Earth Syst. Sci. Data, 10, 919–940, https://doi.org/10.5194/essd-10-919-2018, 2018. a
Churkina, G., Kuik, F., Bonn, B., Lauer, A., Grote, R., Tomiak, K., and Butler,
T. M.: Effect of VOC Emissions from Vegetation on Air Quality in Berlin
during a Heatwave, Environ. Sci. Technol., 51, 6120–6130,
https://doi.org/10.1021/acs.est.6b06514, 2017. a, b
Clegg, S. L., Brimblecombe, P., and Wexler, A. S.: Thermodynamic Model of the
System H+–NH
Dawson, J. P., Adams, P. J., and Pandis, S. N.: Sensitivity of PM2.5 to climate in the Eastern US: a modeling case study, Atmos. Chem. Phys., 7, 4295–4309, https://doi.org/10.5194/acp-7-4295-2007, 2007. a, b, c, d
Dey, S., Caulfield, B., and Ghosh, B.: Potential health and economic benefits
of banning diesel traffic in Dublin, Ireland, J. Transp. Heal., 10,
156–166, https://doi.org/10.1016/j.jth.2018.04.006, 2018. a
Doherty, R. M., Heal, M. R., and O'Connor, F. M.: Climate change impacts on
human health over Europe through its effect on air quality, Environ. Heal.,
16, 118, https://doi.org/10.1186/s12940-017-0325-2, 2017. a
Drinovec, L., Močnik, G., Zotter, P., Prévôt, A. S. H., Ruckstuhl, C., Coz, E., Rupakheti, M., Sciare, J., Müller, T., Wiedensohler, A., and Hansen, A. D. A.: The “dual-spot” Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation, Atmos. Meas. Tech., 8, 1965–1979, https://doi.org/10.5194/amt-8-1965-2015, 2015. a
Dupont, J.-C., Haeffelin, M., Badosa, J., Elias, T., Favez, O., Petit, J.,
Meleux, F., Sciare, J., Crenn, V., and Bonne, J.: Role of the boundary layer
dynamics effects on an extreme air pollution event in Paris, Atmos.
Environ., 141, 571–579, https://doi.org/10.1016/j.atmosenv.2016.06.061, 2016. a, b, c, d, e, f, g, h, i
Elith, J., Leathwick, J. R., and Hastie, T.: A working guide to boosted
regression trees, J. Anim. Ecol., 77, 802–813,
https://doi.org/10.1111/j.1365-2656.2008.01390.x, 2008. a, b, c
Ervens, B., Turpin, B. J., and Weber, R. J.: Secondary organic aerosol formation in cloud droplets and aqueous particles (aqSOA): a review of laboratory, field and model studies, Atmos. Chem. Phys., 11, 11069–11102, https://doi.org/10.5194/acp-11-11069-2011, 2011. a
Favez, O., Cachier, H., Sciare, J., Sarda-Estève, R., and Martinon, L.:
Evidence for a significant contribution of wood burning aerosols to PM2.5
during the winter season in Paris, France, Atmos. Environ., 43, 3640–3644,
https://doi.org/10.1016/j.atmosenv.2009.04.035, 2009. a
Fowler, D., Pilegaard, K., Sutton, M., Ambus, P., Raivonen, M., Duyzer, J.,
Simpson, D., Fagerli, H., Fuzzi, S., Schjoerring, J., Granier, C., Neftel,
A., Isaksen, I., Laj, P., Maione, M., Monks, P., Burkhardt, J., Daemmgen, U.,
Neirynck, J., Personne, E., Wichink-Kruit, R., Butterbach-Bahl, K., Flechard,
C., Tuovinen, J., Coyle, M., Gerosa, G., Loubet, B., Altimir, N., Gruenhage,
L., Ammann, C., Cieslik, S., Paoletti, E., Mikkelsen, T., Ro-Poulsen, H.,
Cellier, P., Cape, J., Horváth, L., Loreto, F., Niinemets, Ü.,
Palmer, P., Rinne, J., Misztal, P., Nemitz, E., Nilsson, D., Pryor, S.,
Gallagher, M., Vesala, T., Skiba, U., Brüggemann, N.,
Zechmeister-Boltenstern, S., Williams, J., O'Dowd, C., Facchini, M.,
de Leeuw, G., Flossman, A., Chaumerliac, N., and Erisman, J.: Atmospheric
composition change: Ecosystems-Atmosphere interactions, Atmos. Environ.,
43, 5193–5267, https://doi.org/10.1016/j.atmosenv.2009.07.068, 2009. a
Friedman, J. H.: Greedy Function Approximation: A Gradient Boosting Machine,
Ann. Stat., 29, 1189–1232, https://doi.org/10.1214/aos/1013203451, 2001. a
Friedman, J. H.: Stochastic gradient boosting, Comput. Stat. Data Anal., 38,
367–378, https://doi.org/10.1016/S0167-9473(01)00065-2, 2002. a, b
Fuchs, J., Cermak, J., and Andersen, H.: Building a cloud in the southeast Atlantic: understanding low-cloud controls based on satellite observations with machine learning, Atmos. Chem. Phys., 18, 16537–16552, https://doi.org/10.5194/acp-18-16537-2018, 2018. a
Geiß, A., Wiegner, M., Bonn, B., Schäfer, K., Forkel, R., von Schneidemesser, E., Münkel, C., Chan, K. L., and Nothard, R.: Mixing layer height as an indicator for urban air quality?, Atmos. Meas. Tech., 10, 2969–2988, https://doi.org/10.5194/amt-10-2969-2017, 2017. a
Gen, M., Zhang, R., Huang, D. D., Li, Y., and Chan, C. K.: Heterogeneous
SO2 Oxidation in Sulfate Formation by Photolysis of Particulate
Nitrate, Environ. Sci. Technol. Lett., 6, 86–91,
https://doi.org/10.1021/acs.estlett.8b00681, 2019. a
Goldstein, A., Kapelner, A., Bleich, J., and Pitkin, E.: Peeking Inside the
Black Box: Visualizing Statistical Learning With Plots of Individual
Conditional Expectation, J. Comput. Graph. Stat., 24, 44–65,
https://doi.org/10.1080/10618600.2014.907095, 2015. a
Grange, S. K., Carslaw, D. C., Lewis, A. C., Boleti, E., and Hueglin, C.: Random forest meteorological normalisation models for Swiss PM10 trend analysis, Atmos. Chem. Phys., 18, 6223–6239, https://doi.org/10.5194/acp-18-6223-2018, 2018. a, b, c
Guenther, A. B., Zimmerman, P. R., Harley, P. C., Monson, R. K., and Fall, R.:
Isoprene and monoterpene emission rate variability: Model evaluations and
sensitivity analyses, J. Geophys. Res., 98, 12609–12617,
https://doi.org/10.1029/93JD00527, 1993. a, b
Gupta, P. and Christopher, S. A.: Particulate matter air quality assessment
using integrated surface, satellite, and meteorological products: Multiple
regression approach, J. Geophys. Res., 114, D14205,
https://doi.org/10.1029/2008JD011496, 2009. a
Haeffelin, M., Bock, O., Boitel, C., Bony, S., Bouniol, D., Chepfer, H.,
Chiriaco, M., Cuesta, J., Drobinski, P., Flamant, C., Grall, M., Hodzic, A.,
Hourdin, F., Lapouge, F., Mathieu, A., Morille, Y., Naud, C., Pelon, J.,
Pietras, C., Protat, A., Romand, B., Scialom, G., and Vautard, R.: SIRTA, a
ground-based atmospheric observatory for cloud and aerosol research, Ann.
Geophys., 23, 253–275, 2005. a
Healy, R. M., Sciare, J., Poulain, L., Kamili, K., Merkel, M., Müller, T., Wiedensohler, A., Eckhardt, S., Stohl, A., Sarda-Estève, R., McGillicuddy, E., O'Connor, I. P., Sodeau, J. R., and Wenger, J. C.: Sources and mixing state of size-resolved elemental carbon particles in a European megacity: Paris, Atmos. Chem. Phys., 12, 1681–1700, https://doi.org/10.5194/acp-12-1681-2012, 2012. a, b
Hennig, F., Quass, U., Hellack, B., Küpper, M., Kuhlbusch, T. A. J.,
Stafoggia, M., and Hoffmann, B.: Ultrafine and Fine Particle Number and
Surface Area Concentrations and Daily Cause-Specific Mortality in the Ruhr
Area, Germany, 2009–2014, Environ. Health Perspect., 126, 027008,
https://doi.org/10.1289/EHP2054, 2018. a
Hoffmann, C. and Funk, R.: Diurnal changes of PM10-emission from arable soils
in NE-Germany, Aeolian Res., 17, 117–127,
https://doi.org/10.1016/j.aeolia.2015.03.002, 2015. a
Hu, X., Belle, J. H., Meng, X., Wildani, A., Waller, L. A., Strickland, M. J.,
and Liu, Y.: Estimating PM2.5 Concentrations in the Conterminous United
States Using the Random Forest Approach, Environ. Sci. Technol., 51,
6936–6944, https://doi.org/10.1021/acs.est.7b01210, 2017. a
Hueglin, C., Gehrig, R., Baltensperger, U., Gysel, M., Monn, C., and Vonmont,
H.: Chemical characterisation of PM2.5, PM10 and coarse particles at urban,
near-city and rural sites in Switzerland, Atmos. Environ., 39, 637–651,
https://doi.org/10.1016/j.atmosenv.2004.10.027, 2005. a
Hughes, H. E., Morbey, R., Fouillet, A., Caserio-Schönemann, C., Dobney,
A., Hughes, T. C., Smith, G. E., and Elliot, A. J.: Retrospective
observational study of emergency department syndromic surveillance data
during air pollution episodes across London and Paris in 2014, BMJ Open, 8,
1–12, https://doi.org/10.1136/bmjopen-2017-018732, 2018. a
Jiang, J., Aksoyoglu, S., El-Haddad, I., Ciarelli, G., Denier van der Gon, H. A. C., Canonaco, F., Gilardoni, S., Paglione, M., Minguillón, M. C., Favez, O., Zhang, Y., Marchand, N., Hao, L., Virtanen, A., Florou, K., O'Dowd, C., Ovadnevaite, J., Baltensperger, U., and Prévôt, A. S. H.: Sources of organic aerosols in Europe: a modeling study using CAMx with modified volatility basis set scheme, Atmos. Chem. Phys., 19, 15247–15270, https://doi.org/10.5194/acp-19-15247-2019, 2019. a, b, c
Just, A., De Carli, M., Shtein, A., Dorman, M., Lyapustin, A., and Kloog, I.:
Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine
Learning for Modeling PM2.5 in the Northeastern USA, Remote Sens., 10, 803,
https://doi.org/10.3390/rs10050803, 2018. a
Kiesewetter, G., Borken-Kleefeld, J., Schöpp, W., Heyes, C., Thunis, P., Bessagnet, B., Terrenoire, E., Fagerli, H., Nyiri, A., and Amann, M.: Modelling street level PM10 concentrations across Europe: source apportionment and possible futures, Atmos. Chem. Phys., 15, 1539–1553, https://doi.org/10.5194/acp-15-1539-2015, 2015. a
Klingner, M. and Sähn, E.: Prediction of PM10 concentration on the basis
of high resolution weather forecasting, Meteorol. Z., 17, 263–272,
https://doi.org/10.1127/0941-2948/2008/0288, 2008. a
Kotthaus, S. and Grimmond, C. S. B.: Atmospheric boundary-layer
characteristics from ceilometer measurements. Part 1: A new method to track
mixed layer height and classify clouds, Q. J. Roy. Meteorol. Soc., 144,
1525–1538, https://doi.org/10.1002/qj.3299, 2018a. a, b
Kotthaus, S. and Grimmond, C. S. B.: Atmospheric boundary-layer
characteristics from ceilometer measurements. Part 2: Application to London's
urban boundary layer, Q. J. Roy. Meteorol. Soc., 144, 1511–1524,
https://doi.org/10.1002/qj.3298, 2018b. a
Laborde, M., Crippa, M., Tritscher, T., Jurányi, Z., Decarlo, P. F., Temime-Roussel, B., Marchand, N., Eckhardt, S., Stohl, A., Baltensperger, U., Prévôt, A. S. H., Weingartner, E., and Gysel, M.: Black carbon physical properties and mixing state in the European megacity Paris, Atmos. Chem. Phys., 13, 5831–5856, https://doi.org/10.5194/acp-13-5831-2013, 2013. a
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The
contribution of outdoor air pollution sources to premature mortality on a
global scale, Nature, 525, 367–371, https://doi.org/10.1038/nature15371, 2015. a
Lelieveld, J., Klingmüller, K., Pozzer, A., Pöschl, U., Fnais, M.,
Daiber, A., and Münzel, T.: Cardiovascular disease burden from ambient
air pollution in Europe reassessed using novel hazard ratio functions, Eur.
Heart J., 40, 1–7, https://doi.org/10.1093/eurheartj/ehz135, 2019. a
Leung, D. M., Tai, A. P. K., Mickley, L. J., Moch, J. M., van Donkelaar, A., Shen, L., and Martin, R. V.: Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China, Atmos. Chem. Phys., 18, 6733–6748, https://doi.org/10.5194/acp-18-6733-2018, 2018. a
Li, Y., Zhang, J., Sailor, D. J., and Ban-Weiss, G. A.: Effects of urbanization on regional meteorology and air quality in Southern California, Atmos. Chem. Phys., 19, 4439–4457, https://doi.org/10.5194/acp-19-4439-2019, 2019. a
Li, Z., Guo, J., Ding, A., Liao, H., Liu, J., Sun, Y., Wang, T., Xue, H.,
Zhang, H., and Zhu, B.: Aerosol and boundary-layer interactions and impact
on air quality, Natl. Sci. Rev., 4, 810–833, https://doi.org/10.1093/nsr/nwx117,
2017. a, b
Liu, Q., Jia, X., Quan, J., Li, J., Li, X., Wu, Y., Chen, D., Wang, Z., and
Liu, Y.: New positive feedback mechanism between boundary layer meteorology
and secondary aerosol formation during severe haze events, Sci. Rep., 8,
1–8, https://doi.org/10.1038/s41598-018-24366-3, 2018. a
Lundberg, S. M. and Lee, S.-I.: A Unified Approach to Interpreting Model
Predictions, arXiv [preprint], arXiv:1705.07874, 25 November 2017. a, b, c, d
Lundberg, S. M., Nair, B., Vavilala, M. S., Horibe, M., Eisses, M. J., Adams,
T., Liston, D. E., Low, D. K.-W., Newman, S.-F., Kim, J., and Lee, S.-I.:
Explainable machine-learning predictions for the prevention of hypoxaemia
during surgery, Nat. Biomed. Eng., 2, 749–760,
https://doi.org/10.1038/s41551-018-0304-0, 2018. a, b
Lundberg, S. M., Erion, G., Chen, H., DeGrave, A., Prutkin, J. M., Nair, B.,
Katz, R., Himmelfarb, J., Bansal, N., and Lee, S.-I.: From local
explanations to global understanding with explainable AI for trees, Nat.
Mach. Intell., 2, 56–67, https://doi.org/10.1038/s42256-019-0138-9, 2020. a, b, c, d
McGovern, A., Lagerquist, R., John Gagne, D., Jergensen, G. E., Elmore,
K. L., Homeyer, C. R., and Smith, T.: Making the Black Box More Transparent:
Understanding the Physical Implications of Machine Learning, B. Am.
Meteorol. Soc., 100, 2175–2199, https://doi.org/10.1175/BAMS-D-18-0195.1, 2019. a
Megaritis, A. G., Fountoukis, C., Charalampidis, P. E., Pilinis, C., and Pandis, S. N.: Response of fine particulate matter concentrations to changes of emissions and temperature in Europe, Atmos. Chem. Phys., 13, 3423–3443, https://doi.org/10.5194/acp-13-3423-2013, 2013. a, b
Megaritis, A. G., Fountoukis, C., Charalampidis, P. E., Denier van der Gon, H. A. C., Pilinis, C., and Pandis, S. N.: Linking climate and air quality over Europe: effects of meteorology on PM2.5 concentrations, Atmos. Chem. Phys., 14, 10283–10298, https://doi.org/10.5194/acp-14-10283-2014, 2014. a, b, c, d, e
Ng, N. L., Herndon, S. C., Trimborn, A., Canagaratna, M. R., Croteau, P. L.,
Onasch, T. B., Sueper, D., Worsnop, D. R., Zhang, Q., Sun, Y. L., and Jayne,
J. T.: An Aerosol Chemical Speciation Monitor (ACSM) for routine monitoring
of the composition and mass concentrations of ambient aerosol, Aerosol Sci.
Technol., 45, 770–784, https://doi.org/10.1080/02786826.2011.560211, 2011. a, b
Paatero, P. and Tapper, U.: Positive matrix factorization: A non-negative
factor model with optimal utilization of error estimates of data values,
Environmetrics, 5, 111–126, https://doi.org/10.1002/env.3170050203, 1994. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Müller, A., Nothman, J., Louppe, G., Prettenhofer, P.,
Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher,
M., Perrot, M., and Duchesnay, É.: Scikit-learn: Machine Learning in
Python, J. Mach. Learn. Res., arXiv [preprint], arXiv:1201.0490, https://arxiv.org/abs/1201.0490, 2012. a
Petäjä, T., Järvi, L., Kerminen, V.-M., Ding, A., Sun, J.,
Nie, W., Kujansuu, J., Virkkula, A., Yang, X., Fu, C., Zilitinkevich, S., and
Kulmala, M.: Enhanced air pollution via aerosol-boundary layer feedback in
China, Sci. Rep., 6, 18998, https://doi.org/10.1038/srep18998, 2016. a
Petetin, H., Beekmann, M., Sciare, J., Bressi, M., Rosso, A., Sanchez, O., and Ghersi, V.: A novel model evaluation approach focusing on local and advected contributions to urban PM2.5 levels – application to Paris, France, Geosci. Model Dev., 7, 1483–1505, https://doi.org/10.5194/gmd-7-1483-2014, 2014. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r
Petit, J.-E., Favez, O., Sciare, J., Canonaco, F., Croteau, P., Močnik, G., Jayne, J., Worsnop, D., and Leoz-Garziandia, E.: Submicron aerosol source apportionment of wintertime pollution in Paris, France by double positive matrix factorization (PMF2) using an aerosol chemical speciation monitor (ACSM) and a multi-wavelength Aethalometer, Atmos. Chem. Phys., 14, 13773–13787, https://doi.org/10.5194/acp-14-13773-2014, 2014. a, b, c, d, e, f, g, h, i
Petit, J.-E., Favez, O., Sciare, J., Crenn, V., Sarda-Estève, R., Bonnaire, N., Močnik, G., Dupont, J.-C., Haeffelin, M., and Leoz-Garziandia, E.: Two years of near real-time chemical composition of submicron aerosols in the region of Paris using an Aerosol Chemical Speciation Monitor (ACSM) and a multi-wavelength Aethalometer, Atmos. Chem. Phys., 15, 2985–3005, https://doi.org/10.5194/acp-15-2985-2015, 2015. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Petit, J. E., Amodeo, T., Meleux, F., Bessagnet, B., Menut, L., Grenier, D.,
Pellan, Y., Ockler, A., Rocq, B., Gros, V., Sciare, J., and Favez, O.:
Characterising an intense PM pollution episode in March 2015 in France from
multi-site approach and near real time data: Climatology, variabilities,
geographical origins and model evaluation, Atmos. Environ., 155, 68–84,
https://doi.org/10.1016/j.atmosenv.2017.02.012, 2017. a, b, c, d, e, f, g, h, i, j, k, l, m
Putaud, J.-P., Raes, F., Van Dingenen, R., Brüggemann, E., Facchini,
M.-C., Decesari, S., Fuzzi, S., Gehrig, R., Hüglin, C., Laj, P.,
Lorbeer, G., Maenhaut, W., Mihalopoulos, N., Müller, K., Querol, X.,
Rodriguez, S., Schneider, J., Spindler, G., ten Brink, H., Tørseth, K.,
and Wiedensohler, A.: A European aerosol phenomenology – 2: chemical
characteristics of particulate matter at kerbside, urban, rural and
background sites in Europe, Atmos. Environ., 38, 2579–2595,
https://doi.org/10.1016/j.atmosenv.2004.01.041, 2004. a
Radke, L. F., Hobbs, P. V., and Eltgroth, M. W.: Scavenging of aerosol
particles by precipitation, J. Appl. Meteorol., 19, 715–722,
https://doi.org/10.1175/1520-0450(1980)019<0715:SOAPBP>2.0.CO;2, 1980. a
Rengarajan, R., Sudheer, A., and Sarin, M.: Wintertime PM2.5 and PM10
carbonaceous and inorganic constituents from urban site in western India,
Atmos. Res., 102, 420–431, https://doi.org/10.1016/j.atmosres.2011.09.005, 2011. a
Rosenfeld, D., Dai, J., Yu, X., Yao, Z., Xu, X., Yang, X., and Du, C.: Inverse
relations between amounts of air pollution and orographic precipitation,
Science, 315, 1396–1398, 2007. a
Rost, J., Holst, T., Sahn, E., Klingner, M., Anke, K., Ahrens, D., and Mayer,
H.: Variability of PM10 concentrations dependent on meteorological
conditions, Int. J. Environ. Pollut., 36, 3–18,
https://doi.org/10.1504/IJEP.2009.021813, 2009. a
Rybarczyk, Y. and Zalakeviciute, R.: Machine learning approaches for outdoor
air quality modelling: A systematic review, Appl. Sci., 8, 2570, https://doi.org/10.3390/app8122570, 2018. a
Sá, E., Martins, H., Ferreira, J., Marta-Almeida, M., Rocha, A.,
Carvalho, A., Freitas, S., and Borrego, C.: Climate change and pollutant
emissions impacts on air quality in 2050 over Portugal, Atmos. Environ.,
131, 209–224, https://doi.org/10.1016/j.atmosenv.2016.01.040, 2016. a
Samoli, E., Peng, R., Ramsay, T., Pipikou, M., Touloumi, G., Dominici, F.,
Burnett, R., Cohen, A., Krewski, D., Samet, J., and Katsouyanni, K.: Acute
effects of ambient particulate matter on mortality in Europe and North
America: Results from the APHENA study, Environ. Health Perspect., 116,
1480–1486, https://doi.org/10.1289/ehp.11345, 2008. a
Samoli, E., Stafoggia, M., Rodopoulou, S., Ostro, B., Declercq, C.,
Alessandrini, E., Díaz, J., Karanasiou, A., Kelessis, A. G., Le
Tertre, A., Pandolfi, P., Randi, G., Scarinzi, C., Zauli-Sajani, S.,
Katsouyanni, K., and Forastiere, F.: Associations between Fine and Coarse
Particles and Mortality in Mediterranean Cities: Results from the
MED-PARTICLES Project, Environ. Health Perspect., 121, 932–938,
https://doi.org/10.1289/ehp.1206124, 2013. a
Schäfer, K., Wagner, P., Emeis, S., Jahn, C., Münkel, C., Suppan: Mixing layer height and air pollution levels
in urban area, Proc. SPIE, 8534, 1–10, https://doi.org/10.1117/12.974328, 2012. a
Sciare, J., d'Argouges, O., Zhang, Q. J., Sarda-Estève, R., Gaimoz, C., Gros, V., Beekmann, M., and Sanchez, O.: Comparison between simulated and observed chemical composition of fine aerosols in Paris (France) during springtime: contribution of regional versus continental emissions, Atmos. Chem. Phys., 10, 11987–12004, https://doi.org/10.5194/acp-10-11987-2010, 2010. a, b, c
Shapley, L.: A Value for n-Person Games, in: Contributions to Theory Games,
edited by: Kuhn, H. W. and Tucker, A. W.,
Princeton University Press, Princeton, USA, 307–318,
https://doi.org/10.1515/9781400881970-018, 1953. a
SIRTA/IPSL: SIRTA-ReOBS, available at: https://sirta.ipsl.fr/reobs.html, last access: 15 March 2021. a
Srivastava, D., Favez, O., Bonnaire, N., Lucarelli, F., Haeffelin, M.,
Perraudin, E., Gros, V., Villenave, E., and Albinet, A.: Speciation of
organic fractions does matter for aerosol source apportionment. Part 2:
Intensive short-term campaign in the Paris area (France), Sci. Total
Environ., 634, 267–278, https://doi.org/10.1016/j.scitotenv.2018.03.296, 2018. a, b, c, d, e, f, g, h, i, j
Srivastava, D., Favez, O., Petit, J., Zhang, Y., Sofowote, U. M., Hopke, P. K.,
and Bonnaire, N.: Science of the Total Environment Speciation of organic
fractions does matter for aerosol source apportionment. Part 3: Combining
off-line and on-line measurements, Sci. Total Environ., 690, 944–955,
https://doi.org/10.1016/j.scitotenv.2019.06.378, 2019. a
Su, J. G., Apte, J. S., Lipsitt, J., Garcia-Gonzales, D. A., Beckerman, B. S.,
de Nazelle, A., Texcalac-Sangrador, J. L., and Jerrett, M.: Populations
potentially exposed to traffic-related air pollution in seven world cities,
Environ. Int., 78, 82–89, https://doi.org/10.1016/j.envint.2014.12.007, 2015. a
Sujatha, P., Mahalakshmi, D., Ramiz, A., Rao, P., and Naidu, C.: Ventilation
coefficient and boundary layer height impact on urban air quality, Cogent.
Environ. Sci., 2, 1–9, https://doi.org/10.1080/23311843.2015.1125284, 2016. a, b, c
Wagner, P. and Schäfer, K.: Influence of mixing layer height on air
pollutant concentrations in an urban street canyon, Urban Clim., 22, 64–79,
https://doi.org/10.1016/j.uclim.2015.11.001, 2017. a, b
Wang, G., Zhang, R., Gomez, M. E., Yang, L., Zamora, M. L., Hu, M., Lin, Y.,
Peng, J., Guo, S., Meng, J., Li, J., Cheng, C., Hu, T., Ren, Y., Wang, Y.,
Gao, J., Cao, J., An, Z., Zhou, W., Li, G., Wang, J., Tian, P.,
Marrero-Ortiz, W., Secrest, J., Du, Z., Zheng, J., Shang, D., Zeng, L., Shao,
M., Wang, W., Huang, Y., Wang, Y., Zhu, Y., Li, Y., Hu, J., Pan, B., Cai, L.,
Cheng, Y., Ji, Y., Zhang, F., Rosenfeld, D., Liss, P. S., Duce, R. A., Kolb,
C. E., and Molina, M. J.: Persistent sulfate formation from London Fog to
Chinese haze, P. Natl. Acad. Sci. USA, 113, 13630–13635,
https://doi.org/10.1073/pnas.1616540113, 2016. a, b
Wang, X., Dickinson, R. E., Su, L., Zhou, C., and Wang, K.: PM2.5 Pollution in
China and How It Has Been Exacerbated by Terrain and Meteorological
Conditions, B. Am. Meteorol. Soc., 99, 105–119,
https://doi.org/10.1175/BAMS-D-16-0301.1, 2018. a, b
Yang, M., Chu, C., Bloom, M. S., Li, S., Chen, G., Heinrich, J., Markevych, I.,
Knibbs, L. D., Bowatte, G., Dharmage, S. C., Komppula, M., Leskinen, A.,
Hirvonen, M.-R., Roponen, M., Jalava, P., Wang, S.-Q., Lin, S., Zeng, X.-W.,
Hu, L.-W., Liu, K.-K., Yang, B.-Y., Chen, W., Guo, Y., and Dong, G.-H.: Is
smaller worse? New insights about associations of PM1 and respiratory health
in children and adolescents, Environ. Int., 120, 516–524,
https://doi.org/10.1016/j.envint.2018.08.027, 2018.
a, b
Yang, Y. Q., Wang, J. Z., Gong, S. L., Zhang, X. Y., Wang, H., Wang, Y. Q., Wang, J., Li, D., and Guo, J. P.: PLAM – a meteorological pollution index for air quality and its applications in fog-haze forecasts in North China, Atmos. Chem. Phys., 16, 1353–1364, https://doi.org/10.5194/acp-16-1353-2016, 2016. a
Zhang, Y., Favez, O., Canonaco, F., Liu, D., Močnik, G., Amodeo, T.,
Sciare, J., Prévôt, A. S., Gros, V., and Albinet, A.: Evidence of
major secondary organic aerosol contribution to lensing effect black carbon
absorption enhancement, npj Clim. Atmos. Sci., 1, 1–8, 2018. a
Zhang, Y., Favez, O., Petit, J.-E., Canonaco, F., Truong, F., Bonnaire, N., Crenn, V., Amodeo, T., Prévôt, A. S. H., Sciare, J., Gros, V., and Albinet, A.: Six-year source apportionment of submicron organic aerosols from near-continuous highly time-resolved measurements at SIRTA (Paris area, France), Atmos. Chem. Phys., 19, 14755–14776, https://doi.org/10.5194/acp-19-14755-2019, 2019. a, b
Short summary
Air pollution endangers human health and poses a problem particularly in densely populated areas. Here, an explainable machine learning approach is used to analyse periods of high particle concentrations for a suburban site southwest of Paris to better understand its atmospheric drivers. Air pollution is particularly excaberated by low temperatures and low mixed layer heights, but processes vary substantially between and within seasons.
Air pollution endangers human health and poses a problem particularly in densely populated...
Altmetrics
Final-revised paper
Preprint