Articles | Volume 25, issue 9
https://doi.org/10.5194/acp-25-4639-2025
© Author(s) 2025. 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-25-4639-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
High-resolution air quality maps for Bucharest using a mixed-effects modeling framework
Camelia Talianu
CORRESPONDING AUTHOR
National Institute of Research and Development for Optoelectronics (INOE 2000), Str. Atomistilor 409, Măgurele, 077125, Ilfov, Romania
Institute of Meteorology and Climatology, Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Gregor-Mendel Street 33, Vienna, 1180, Vienna, Austria
National Institute of Research and Development for Optoelectronics (INOE 2000), Str. Atomistilor 409, Măgurele, 077125, Ilfov, Romania
Doina Nicolae
CORRESPONDING AUTHOR
National Institute of Research and Development for Optoelectronics (INOE 2000), Str. Atomistilor 409, Măgurele, 077125, Ilfov, Romania
Alexandru Ilie
National Institute of Research and Development for Optoelectronics (INOE 2000), Str. Atomistilor 409, Măgurele, 077125, Ilfov, Romania
Faculty of Geography, University of Bucharest, Bulevardul Nicolae Bălcescu 1, Bucharest, 010041, Bucharest, Romania
Andrei Dandocsi
National Institute of Research and Development for Optoelectronics (INOE 2000), Str. Atomistilor 409, Măgurele, 077125, Ilfov, Romania
National University of Science and Technology POLITEHNICA Bucharest, Splaiul Independentei 313, Bucharest, 060042, Romania
Anca Nemuc
National Institute of Research and Development for Optoelectronics (INOE 2000), Str. Atomistilor 409, Măgurele, 077125, Ilfov, Romania
Livio Belegante
National Institute of Research and Development for Optoelectronics (INOE 2000), Str. Atomistilor 409, Măgurele, 077125, Ilfov, Romania
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Over the past decade, researchers at RADO-Bucharest have measured and analyzed aerosol properties to understand their optical and microphysical characteristics, seasonal variability, and transport pathways. Using advanced lidar and photometer techniques the study reveals that fine-mode aerosols dominate, with pollution-driven regimes and seasonal influences by dust, biomass burning, and marine sources highlighting the impact of regional pollution and long-range transport on local air quality.
Doina Nicolae, Gabriela-Ancuta Ciocan, Anca Nemuc, Victor Nicolae, Camelia Talianu, Jeni Vasilescu, Alexandru Dandocsi, Cristian Radu, Marius-Mihai Cazacu, Viorel Vulturescu, and Livio Belegante
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Over the past decade, researchers at RADO-Bucharest have measured and analyzed aerosol properties to understand their optical and microphysical characteristics, seasonal variability, and transport pathways. Using advanced lidar and photometer techniques the study reveals that fine-mode aerosols dominate, with pollution-driven regimes and seasonal influences by dust, biomass burning, and marine sources highlighting the impact of regional pollution and long-range transport on local air quality.
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023, https://doi.org/10.5194/amt-16-6025-2023, 2023
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EARLINET/ACTRIS organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, Jianhui Jiang, Hannes Keernik, Chunshui Lin, Nicolas Marchand, Cristina Marin, Colin O'Dowd, Jurgita Ovadnevaite, Jean-Eudes Petit, Michael Pikridas, Véronique Riffault, Jean Sciare, Jay G. Slowik, Leïla Simon, Jeni Vasilescu, Yunjiang Zhang, Olivier Favez, André S. H. Prévôt, Andrés Alastuey, and María Cruz Minguillón
Atmos. Meas. Tech., 15, 5479–5495, https://doi.org/10.5194/amt-15-5479-2022, https://doi.org/10.5194/amt-15-5479-2022, 2022
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This work presents the differences resulting from two techniques (rolling and seasonal) of the positive matrix factorisation model that can be run for organic aerosol source apportionment. The current state of the art suggests that the rolling technique is more accurate, but no proof of its effectiveness has been provided yet. This paper tackles this issue in the context of a synthetic dataset and a multi-site real-world comparison.
Alexandru Mereuţă, Nicolae Ajtai, Andrei T. Radovici, Nikolaos Papagiannopoulos, Lucia T. Deaconu, Camelia S. Botezan, Horaţiu I. Ştefănie, Doina Nicolae, and Alexandru Ozunu
Atmos. Chem. Phys., 22, 5071–5098, https://doi.org/10.5194/acp-22-5071-2022, https://doi.org/10.5194/acp-22-5071-2022, 2022
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In this study we analysed oil smoke plumes from 30 major industrial events within a 12-year timeframe. To our knowledge, this is the first study of its kind that uses a synergetic approach based on satellite remote sensing techniques. Satellite data offer access to these events, which are mainly located in war-prone or hazardous areas. Our study highlights the need for improved aerosol models and algorithms for these types of aerosols with implications on air quality and climate change.
Mariana Adam, Iwona S. Stachlewska, Lucia Mona, Nikolaos Papagiannopoulos, Juan Antonio Bravo-Aranda, Michaël Sicard, Doina N. Nicolae, Livio Belegante, Lucja Janicka, Dominika Szczepanik, Maria Mylonaki, Christina-Anna Papanikolaou, Nikolaos Siomos, Kalliopi Artemis Voudouri, Luca Alados-Arboledas, Arnoud Apituley, Ina Mattis, Anatoli Chaikovsky, Constantino Muñoz-Porcar, Aleksander Pietruczuk, Daniele Bortoli, Holger Baars, Ivan Grigorov, and Zahary Peshev
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-759, https://doi.org/10.5194/acp-2021-759, 2021
Revised manuscript not accepted
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Results over 10 years of biomass burning events measured by EARLINET are analysed by means of the intensive parameters, based on the methodology described in Part I. Smoke type is characterized for each of the four geographical regions based on continental smoke origin. Relationships between intensive parameters or colour ratios are shown. The smoke is labelled in average as aged smoke.
Maria Mylonaki, Elina Giannakaki, Alexandros Papayannis, Christina-Anna Papanikolaou, Mika Komppula, Doina Nicolae, Nikolaos Papagiannopoulos, Aldo Amodeo, Holger Baars, and Ourania Soupiona
Atmos. Chem. Phys., 21, 2211–2227, https://doi.org/10.5194/acp-21-2211-2021, https://doi.org/10.5194/acp-21-2211-2021, 2021
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We introduce an automated aerosol type classification method, SCAN. The output of SCAN is compared with two aerosol classification methods: (1) the Mahalanobis distance automatic aerosol type classification and (2) a neural network aerosol typing algorithm. A total of 97 free tropospheric aerosol layers from four EARLINET stations in the period 2014–2018 were classified.
Mariana Adam, Doina Nicolae, Iwona S. Stachlewska, Alexandros Papayannis, and Dimitris Balis
Atmos. Chem. Phys., 20, 13905–13927, https://doi.org/10.5194/acp-20-13905-2020, https://doi.org/10.5194/acp-20-13905-2020, 2020
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Biomass burning events measured by EARLINET are analysed using intensive parameters. The pollution layers are labelled smoke layers if fires were found along the air-mass back trajectory. The number of contributing fires to the smoke measurements is quantified. It is shown that most of the time we measure mixed smoke. The methodology provides three research directions: fires measured by several stations, long-range transport from N. America, and an analysis function of continental sources.
Alexis Merlaud, Livio Belegante, Daniel-Eduard Constantin, Mirjam Den Hoed, Andreas Carlos Meier, Marc Allaart, Magdalena Ardelean, Maxim Arseni, Tim Bösch, Hugues Brenot, Andreea Calcan, Emmanuel Dekemper, Sebastian Donner, Steffen Dörner, Mariana Carmelia Balanica Dragomir, Lucian Georgescu, Anca Nemuc, Doina Nicolae, Gaia Pinardi, Andreas Richter, Adrian Rosu, Thomas Ruhtz, Anja Schönhardt, Dirk Schuettemeyer, Reza Shaiganfar, Kerstin Stebel, Frederik Tack, Sorin Nicolae Vâjâiac, Jeni Vasilescu, Jurgen Vanhamel, Thomas Wagner, and Michel Van Roozendael
Atmos. Meas. Tech., 13, 5513–5535, https://doi.org/10.5194/amt-13-5513-2020, https://doi.org/10.5194/amt-13-5513-2020, 2020
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The AROMAT campaigns took place in Romania in 2014 and 2015. They aimed to test airborne observation systems dedicated to air quality studies and to verify the concept of such campaigns in support of the validation of space-borne atmospheric missions. We show that airborne measurements of NO2 can be valuable for the validation of air quality satellites. For H2CO and SO2, the validation should involve ground-based measurement systems at key locations that the AROMAT measurements help identify.
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Short summary
For Bucharest, Romania's capital, mobile measurements during two intensive campaigns and mixed-effect LUR (land-use regression) models to derive seasonal maps of near-surface PM10, NO2 and UFPs (ultrafine particles) have successfully been used. The model's performance was evaluated, demonstrating its potential for high-resolution mapping in other cities with well-characterized urban structures and diverse in situ monitoring stations.
For Bucharest, Romania's capital, mobile measurements during two intensive campaigns and...
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