Articles | Volume 24, issue 18
https://doi.org/10.5194/acp-24-10475-2024
© Author(s) 2024. 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-24-10475-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measurement report
| 
19 Sep 2024
Measurement report |
| 19 Sep 2024
| 19 Sep 2024
Measurement report: Source attribution and estimation of black carbon levels in an urban hotspot of the central Po Valley – an integrated approach combining high-resolution dispersion modelling and micro-aethalometers
Giorgio Veratti
CORRESPONDING AUTHOR
Department of Life Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy
“Enzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, 41125 Modena, Italy
Alessandro Bigi
“Enzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, 41125 Modena, Italy
Michele Stortini
ARPAE, Regional Environmental Agency of Emilia–Romagna, 40122 Bologna, Italy
Sergio Teggi
“Enzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, 41125 Modena, Italy
Grazia Ghermandi
“Enzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, 41125 Modena, Italy
Related authors
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
Short summary
In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Alessandro Bigi, Giorgio Veratti, Elisabeth Andrews, Martine Collaud Coen, Lorenzo Guerrieri, Vera Bernardoni, Dario Massabò, Luca Ferrero, Sergio Teggi, and Grazia Ghermandi
Atmos. Chem. Phys., 23, 14841–14869, https://doi.org/10.5194/acp-23-14841-2023, https://doi.org/10.5194/acp-23-14841-2023, 2023
Short summary
Short summary
Atmospheric particles include compounds that play a key role in the greenhouse effect and air toxicity. Concurrent observations of these compounds by multiple instruments are presented, following deployment within an urban environment in the Po Valley, one of Europe's pollution hotspots. The study compares these data, highlighting the impact of ground emissions, mainly vehicular traffic and biomass burning, on the absorption of sun radiation and, ultimately, on climate change and air quality.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
Short summary
In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Ayah Abu-Hani, Jia Chen, Vigneshkumar Balamurugan, Adrian Wenzel, and Alessandro Bigi
Atmos. Meas. Tech., 17, 3917–3931, https://doi.org/10.5194/amt-17-3917-2024, https://doi.org/10.5194/amt-17-3917-2024, 2024
Short summary
Short summary
This study examined the transferability of machine learning calibration models among low-cost sensor units targeting NO2 and NO. The global models were evaluated under similar and different emission conditions. To counter cross-sensitivity, the study proposed integrating O3 measurements from nearby reference stations, in Switzerland. The models show substantial improvement when O3 measurements are incorporated, which is more pronounced when in regions with elevated O3 concentrations.
Tommaso Isolabella, Vera Bernardoni, Alessandro Bigi, Marco Brunoldi, Federico Mazzei, Franco Parodi, Paolo Prati, Virginia Vernocchi, and Dario Massabò
Atmos. Meas. Tech., 17, 1363–1373, https://doi.org/10.5194/amt-17-1363-2024, https://doi.org/10.5194/amt-17-1363-2024, 2024
Short summary
Short summary
We present an innovative software toolkit to differentiate sources of carbonaceous aerosol in the atmosphere. Our toolkit implements an upgraded mathematical model which allows for determination of fundamental optical properties of the aerosol, its sources, and the mass concentration of different carbonaceous species of particulate matter. We have tested the functionality of the software by re-analysing published data, and we obtained a compatible results with additional information.
Alessandro Bigi, Giorgio Veratti, Elisabeth Andrews, Martine Collaud Coen, Lorenzo Guerrieri, Vera Bernardoni, Dario Massabò, Luca Ferrero, Sergio Teggi, and Grazia Ghermandi
Atmos. Chem. Phys., 23, 14841–14869, https://doi.org/10.5194/acp-23-14841-2023, https://doi.org/10.5194/acp-23-14841-2023, 2023
Short summary
Short summary
Atmospheric particles include compounds that play a key role in the greenhouse effect and air toxicity. Concurrent observations of these compounds by multiple instruments are presented, following deployment within an urban environment in the Po Valley, one of Europe's pollution hotspots. The study compares these data, highlighting the impact of ground emissions, mainly vehicular traffic and biomass burning, on the absorption of sun radiation and, ultimately, on climate change and air quality.
Lina Vitali, Kees Cuvelier, Antonio Piersanti, Alexandra Monteiro, Mario Adani, Roberta Amorati, Agnieszka Bartocha, Alessandro D'Ausilio, Paweł Durka, Carla Gama, Giulia Giovannini, Stijn Janssen, Tomasz Przybyła, Michele Stortini, Stijn Vranckx, and Philippe Thunis
Geosci. Model Dev., 16, 6029–6047, https://doi.org/10.5194/gmd-16-6029-2023, https://doi.org/10.5194/gmd-16-6029-2023, 2023
Short summary
Short summary
Air quality forecasting models play a key role in fostering short-term measures aimed at reducing human exposure to air pollution. Together with this role comes the need for a thorough assessment of the model performances to build confidence in models’ capabilities, in particular when model applications support policymaking. In this paper, we propose an evaluation methodology and test it on several domains across Europe, highlighting its strengths and room for improvement.
Martine Collaud Coen, Elisabeth Andrews, Alessandro Bigi, Giovanni Martucci, Gonzague Romanens, Frédéric P. A. Vogt, and Laurent Vuilleumier
Atmos. Meas. Tech., 13, 6945–6964, https://doi.org/10.5194/amt-13-6945-2020, https://doi.org/10.5194/amt-13-6945-2020, 2020
Short summary
Short summary
The Mann–Kendall trend test requires prewhitening in the presence of serially correlated data. The effects of five prewhitening methods and time granularity, autocorrelation, temporal segmentation and length of the time series on the statistical significance and the slope are studies for seven atmospheric datasets. Finally, a new algorithm using three prewhitening methods is proposed in order to optimize the power of the test, the amount of erroneous false positive trends and the slope estimate.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
Short summary
Short summary
The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Alessandro Bigi, Michael Mueller, Stuart K. Grange, Grazia Ghermandi, and Christoph Hueglin
Atmos. Meas. Tech., 11, 3717–3735, https://doi.org/10.5194/amt-11-3717-2018, https://doi.org/10.5194/amt-11-3717-2018, 2018
Short summary
Short summary
Low cost sensors for monitoring atmospheric pollution are growing in popularity worldwide. Nonetheless, the expectations from these devices were seldom met, thus urging for more research. This study focuses on sensor performance within the realistic framework of an initial calibration next to a reference instrument and the subsequent distant deployment. Within this framework, we assessed the uncertainty of these sensors and their suitability to map intra-urban gradients of NO/NO2.
Alessandro Bigi and Grazia Ghermandi
Atmos. Chem. Phys., 16, 15777–15788, https://doi.org/10.5194/acp-16-15777-2016, https://doi.org/10.5194/acp-16-15777-2016, 2016
Short summary
Short summary
Po Valley (northern Italy, 42 000 km2, 15 million inhabitants) is a real-scale model to test whether environmental policies may improve one of the worst air qualities in Europe. In this study we show how pollution from fine and coarse atmospheric particles (PM2.5 and PM10–2.5), largely originating from anthropogenic emissions, dropped thanks to the broader use of cleaner and more efficient technologies.
P. Kupiszewski, E. Weingartner, P. Vochezer, M. Schnaiter, A. Bigi, M. Gysel, B. Rosati, E. Toprak, S. Mertes, and U. Baltensperger
Atmos. Meas. Tech., 8, 3087–3106, https://doi.org/10.5194/amt-8-3087-2015, https://doi.org/10.5194/amt-8-3087-2015, 2015
A. Bigi and G. Ghermandi
Atmos. Chem. Phys., 14, 4895–4907, https://doi.org/10.5194/acp-14-4895-2014, https://doi.org/10.5194/acp-14-4895-2014, 2014
Related subject area
Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Characterization of brown carbon absorption in different European environments through source contribution analysis
Accounting for the black carbon aging process in a two-way coupled meteorology–air quality model
The effectiveness of solar radiation management using fine sea spray across multiple climatic regions
A global dust emission dataset for estimating dust radiative forcings in climate models
Tropospheric aerosols over the western North Atlantic Ocean during the winter and summer deployments of ACTIVATE 2020: life cycle, transport, and distribution
Spatial and temporal evolution of future atmospheric reactive nitrogen deposition in China under different climate change mitigation strategies
Steady-state mixing state of black carbon aerosols from a particle-resolved model
Distinctive dust weather intensities in North China resulted from two types of atmospheric circulation anomalies
Biomass burning emission analysis based on MODIS aerosol optical depth and AeroCom multi-model simulations: implications for model constraints and emission inventories
Quasi-weekly oscillation of regional PM2.5 transport over China driven by the synoptic-scale disturbance of the East Asian winter monsoon circulation
Solar radiation estimation in West Africa: impact of dust conditions during the 2021 dry season
Gaps in our understanding of ice-nucleating particle sources exposed by global simulation of the UK Earth System Model
The role of interfacial tension in the size-dependent phase separation of atmospheric aerosol particles
Warming effects of reduced sulfur emissions from shipping
The key role of atmospheric absorption in the Asian summer monsoon response to dust emissions in CMIP6 models
Multi-model effective radiative forcing of the 2020 sulfur cap for shipping
Representation of iron aerosol size distributions of anthropogenic emissions is critical in evaluating atmospheric soluble iron input to the ocean
High-resolution air quality maps for Bucharest using Mixed-Effects Modeling Framework
Revealing dominant patterns of aerosol regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations
Improving estimation of a record-breaking east Asian dust storm emission with lagged aerosol Ångström exponent observations
Impact of biomass burning aerosols (BBA) on the tropical African climate in an ocean–atmosphere–aerosol coupled climate model
Retrieval of refractive index and water content for the coating materials of aged black carbon aerosol based on optical properties: a theoretical analysis
Predicting hygroscopic growth of organosulfur aerosol particles using COSMOtherm
Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia
Global modeling of aerosol nucleation with a semi-explicit chemical mechanism for highly oxygenated organic molecules (HOMs)
Dust-producing weather patterns of the North American Great Plains
Synergistic effects of the winter North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) on dust activities in North China during the following spring
Aerosol composition, air quality, and boundary layer dynamics in the urban background of Stuttgart in winter
Construction and Application of a Pollen Emissions Model based on Phenology and Random Forests
Microphysical modelling of aerosol scavenging by different types of clouds: description and validation of the approach
Insights into the sources of ultrafine particle numbers at six European urban sites obtained by investigating COVID-19 lockdowns
In-plume and out-of-plume analysis of aerosol–cloud interactions derived from the 2014–2015 Holuhraun volcanic eruption
Impacts of atmospheric circulation patterns and cloud inhibition on aerosol radiative effect and boundary layer structure during winter air pollution in Sichuan Basin, China
Investigating the sign of stratocumulus adjustments to aerosols in the ICON global storm-resolving model
A model study investigating the sensitivity of aerosol forcing to the volatilities of semi-volatile organic compounds
The impact of uncertainty in black carbon's refractive index on simulated optical depth and radiative forcing
Decomposing the effective radiative forcing of anthropogenic aerosols based on CMIP6 Earth system models
Modeling impacts of dust mineralogy on fast climate response
Uncertainties in laboratory-measured shortwave refractive indices of mineral dust aerosols and derived optical properties: a theoretical assessment
Diagnosing uncertainties in global biomass burning emission inventories and their impact on modeled air pollutants
Role of atmospheric aerosols in severe winter fog over the Indo-Gangetic Plain of India: a case study
Long-term variability in black carbon emissions constrained by gap-filled absorption aerosol optical depth and associated premature mortality in China
Intercomparison of aerosol optical depths from four reanalyses and their multi-reanalysis consensus
Global aviation contrail climate effects from 2019 to 2021
Rapid iodine oxoacid nucleation enhanced by dimethylamine in broad marine regions
Simulations of the impact of cloud condensation nuclei and ice-nucleating particles perturbations on the microphysics and radar reflectivity factor of stratiform mixed-phase clouds
Aerosols in the central Arctic cryosphere: satellite and model integrated insights during Arctic spring and summer
Observationally constrained regional variations of shortwave absorption by iron oxides emphasize the cooling effect of dust
Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions
Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data
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.
Yuzhi Jin, Jiandong Wang, Chao Liu, David C. Wong, Golam Sarwar, Kathleen M. Fahey, Shang Wu, Jiaping Wang, Jing Cai, Zeyuan Tian, Zhouyang Zhang, Jia Xing, Aijun Ding, and Shuxiao Wang
Atmos. Chem. Phys., 25, 2613–2630, https://doi.org/10.5194/acp-25-2613-2025, https://doi.org/10.5194/acp-25-2613-2025, 2025
Short summary
Short summary
Black carbon (BC) affects climate and the environment, and its aging process alters its properties. Current models, like WRF-CMAQ, lack full accounting for it. We developed the WRF-CMAQ-BCG model to better represent BC aging by introducing bare and coated BC species and their conversion. The WRF-CMAQ-BCG model introduces the capability to simulate BC mixing states and bare and coated BC wet deposition, and it improves the accuracy of BC mass concentration and aerosol optics.
Zhe Song, Shaocai Yu, Pengfei Li, Ningning Yao, Lang Chen, Yuhai Sun, Boqiong Jiang, and Daniel Rosenfeld
Atmos. Chem. Phys., 25, 2473–2494, https://doi.org/10.5194/acp-25-2473-2025, https://doi.org/10.5194/acp-25-2473-2025, 2025
Short summary
Short summary
Our results with injected sea salt aerosols for five open oceans show that sea salt aerosols with low injection amounts dominate shortwave radiation, mainly through indirect effects. As indirect aerosol effects saturate with increasing injection rates, direct effects exceed indirect effects. This implies that marine cloud brightening is best implemented in areas with extensive cloud cover, while aerosol direct scattering effects remain dominant when clouds are scarce.
Danny M. Leung, Jasper F. Kok, Longlei Li, David M. Lawrence, Natalie M. Mahowald, Simone Tilmes, and Erik Kluzek
Atmos. Chem. Phys., 25, 2311–2331, https://doi.org/10.5194/acp-25-2311-2025, https://doi.org/10.5194/acp-25-2311-2025, 2025
Short summary
Short summary
This study derives a gridded dust emission dataset for 1841–2000 by employing a combination of observed dust from core records and reanalyzed global dust cycle constraints. We evaluate the ability of global models to replicate the observed historical dust variability by using the emission dataset to force a historical simulation in an Earth system model. We show that prescribing our emissions forces the model to better match observations than other mechanistic models.
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
Atmos. Chem. Phys., 25, 2087–2121, https://doi.org/10.5194/acp-25-2087-2025, https://doi.org/10.5194/acp-25-2087-2025, 2025
Short summary
Short summary
We use the GEOS-Chem model to simulate aerosol distributions and properties over the western North Atlantic Ocean (WNAO) during the winter and summer deployments in 2020 of the NASA ACTIVATE mission. Model results are evaluated against aircraft, ground-based, and satellite observations. The improved understanding of life cycle, composition, transport pathways, and distribution of aerosols has important implications for characterizing aerosol–cloud–meteorology interactions over WNAO.
Mingrui Ma, Jiachen Cao, Dan Tong, Bo Zheng, and Yu Zhao
Atmos. Chem. Phys., 25, 2147–2166, https://doi.org/10.5194/acp-25-2147-2025, https://doi.org/10.5194/acp-25-2147-2025, 2025
Short summary
Short summary
We combined two global climate change pathways and three national emission control scenarios to analyze the future evolution of reactive nitrogen (Nr) deposition till the 2060s in China with air quality modeling. We show China’s clean air and carbon neutrality policies would overcome the adverse effects of climate change and efficiently reduce Nr deposition. The outflow of Nr fluxes from mainland China to the west Pacific would also be clearly reduced from continuous stringent emission controls.
Zhouyang Zhang, Jiandong Wang, Jiaping Wang, Nicole Riemer, Chao Liu, Yuzhi Jin, Zeyuan Tian, Jing Cai, Yueyue Cheng, Ganzhen Chen, Bin Wang, Shuxiao Wang, and Aijun Ding
Atmos. Chem. Phys., 25, 1869–1881, https://doi.org/10.5194/acp-25-1869-2025, https://doi.org/10.5194/acp-25-1869-2025, 2025
Short summary
Short summary
Black carbon (BC) exerts notable warming effects. We use a particle-resolved model to investigate the long-term behavior of the BC mixing state, revealing its compositions, coating thickness distribution, and optical properties all stabilize with a characteristic time of less than 1 d. This study can effectively simplify the description of the BC mixing state, which facilitates the precise assessment of the optical properties of BC aerosols in global and chemical transport models.
Qianyi Huo, Zhicong Yin, Xiaoqing Ma, and Huijun Wang
Atmos. Chem. Phys., 25, 1711–1724, https://doi.org/10.5194/acp-25-1711-2025, https://doi.org/10.5194/acp-25-1711-2025, 2025
Short summary
Short summary
Dust days during the spring seasons of 2015–2023 in North China were classified into Mongolian cyclone and cold high types depending on the presence of the Mongolian cyclone. The Mongolian cyclone type led to more frequent and severe dust weather, indicated by PM10 concentrations. To comprehensively forecast the two types of dust weather, a common predictor was established based on 500 hPa anomalous circulation systems, offering insights for dust weather forecasting and climate prediction.
Mariya Petrenko, Ralph Kahn, Mian Chin, Susanne E. Bauer, Tommi Bergman, Huisheng Bian, Gabriele Curci, Ben Johnson, Johannes W. Kaiser, Zak Kipling, Harri Kokkola, Xiaohong Liu, Keren Mezuman, Tero Mielonen, Gunnar Myhre, Xiaohua Pan, Anna Protonotariou, Samuel Remy, Ragnhild Bieltvedt Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Hailong Wang, Duncan Watson-Parris, and Kai Zhang
Atmos. Chem. Phys., 25, 1545–1567, https://doi.org/10.5194/acp-25-1545-2025, https://doi.org/10.5194/acp-25-1545-2025, 2025
Short summary
Short summary
We compared smoke plume simulations from 11 global models to each other and to satellite smoke amount observations aimed at constraining smoke source strength. In regions where plumes are thick and background aerosol is low, models and satellites compare well. However, the input emission inventory tends to underestimate in many places, and particle property and loss rate assumptions vary enormously among models, causing uncertainties that require systematic in situ measurements to resolve.
Yongqing Bai, Tianliang Zhao, Kai Meng, Yue Zhou, Jie Xiong, Xiaoyun Sun, Lijuan Shen, Yanyu Yue, Yan Zhu, Weiyang Hu, and Jingyan Yao
Atmos. Chem. Phys., 25, 1273–1287, https://doi.org/10.5194/acp-25-1273-2025, https://doi.org/10.5194/acp-25-1273-2025, 2025
Short summary
Short summary
We proposed a composite statistical method to identify the quasi-weekly oscillation (QWO) of regional PM2.5 transport over China in winter from 2015 to 2019. The QWO of regional PM2.5 transport is constrained by synoptic-scale disturbances of the East Asian winter monsoon circulation with the periodic activities of the Siberian high, providing a new insight into the understanding of regional pollutant transport with meteorological drivers in atmospheric environment changes.
Léo Clauzel, Sandrine Anquetin, Christophe Lavaysse, Gilles Bergametti, Christel Bouet, Guillaume Siour, Rémy Lapere, Béatrice Marticorena, and Jennie Thomas
Atmos. Chem. Phys., 25, 997–1021, https://doi.org/10.5194/acp-25-997-2025, https://doi.org/10.5194/acp-25-997-2025, 2025
Short summary
Short summary
Solar energy production in West Africa is set to rise and needs accurate solar radiation estimates which are affected by desert dust. This work analyses a March 2021 dust event using a modelling strategy incorporating desert dust. Results show that considering desert dust cuts errors in solar radiation estimates by 75 % and reduces surface solar radiation by 18 %. This highlights the importance of incorporating dust aerosols into solar forecasting for better accuracy.
Ross J. Herbert, Alberto Sanchez-Marroquin, Daniel P. Grosvenor, Kirsty J. Pringle, Stephen R. Arnold, Benjamin J. Murray, and Kenneth S. Carslaw
Atmos. Chem. Phys., 25, 291–325, https://doi.org/10.5194/acp-25-291-2025, https://doi.org/10.5194/acp-25-291-2025, 2025
Short summary
Short summary
Aerosol particles that help form ice in clouds vary in number and type around the world and with time. However, in many weather and climate models cloud ice is not linked to aerosols that are known to nucleate ice. Here we report the first steps towards representing ice-nucleating particles within the UK Earth System Model. We conclude that in addition to ice nucleation by sea spray and mineral components of soil dust, we also need to represent ice nucleation by the organic components of soils.
Ryan Schmedding and Andreas Zuend
Atmos. Chem. Phys., 25, 327–346, https://doi.org/10.5194/acp-25-327-2025, https://doi.org/10.5194/acp-25-327-2025, 2025
Short summary
Short summary
Four different approaches for computing the interfacial tension between liquid phases in aerosol particles were tested for particles with diameters from 10 nm to more than 5 μm. Antonov's rule led to the strongest reductions in the onset relative humidity of liquid–liquid phase separation and reproduced measured interfacial tensions for highly immiscible systems. A modified form of the Butler equation was able to best reproduce measured interfacial tensions in more miscible systems.
Masaru Yoshioka, Daniel P. Grosvenor, Ben B. B. Booth, Colin P. Morice, and Ken S. Carslaw
Atmos. Chem. Phys., 24, 13681–13692, https://doi.org/10.5194/acp-24-13681-2024, https://doi.org/10.5194/acp-24-13681-2024, 2024
Short summary
Short summary
A 2020 regulation has reduced sulfur emissions from shipping by about 80 %, leading to a decrease in atmospheric aerosols that have a cooling effect primarily by affecting cloud properties and amounts. Our climate model simulations predict a global temperature increase of 0.04 K over the next 3 decades as a result, which could contribute to surpassing the Paris Agreement's 1.5 °C target. Reduced aerosols may have also contributed to the recent temperature spikes.
Alcide Zhao, Laura J. Wilcox, and Claire L. Ryder
Atmos. Chem. Phys., 24, 13385–13402, https://doi.org/10.5194/acp-24-13385-2024, https://doi.org/10.5194/acp-24-13385-2024, 2024
Short summary
Short summary
Climate models include desert dust aerosols, which cause atmospheric heating and can change circulation patterns. We assess the effect of dust on the Indian and east Asian summer monsoons through multi-model experiments isolating the effect of dust in current climate models for the first time. Dust atmospheric heating results in a southward shift of western Pacific equatorial rainfall and an enhanced Indian summer monsoon. This shows the importance of accurate dust representation in models.
Ragnhild Bieltvedt Skeie, Rachael Byrom, Øivind Hodnebrog, Caroline Jouan, and Gunnar Myhre
Atmos. Chem. Phys., 24, 13361–13370, https://doi.org/10.5194/acp-24-13361-2024, https://doi.org/10.5194/acp-24-13361-2024, 2024
Short summary
Short summary
In 2020, new regulations by the International Maritime Organization regarding sulfur emissions came into force, reducing emissions of SO2 from the shipping sector by approximately 80 %. In this study, we use multiple models to calculate how much the Earth energy balance changed due to the emission reduction or the so-called effective radiative forcing. The calculated effective radiative forcing is weak, comparable to the effect of the increase in CO2 over the last 2 to 3 years.
Mingxu Liu, Hitoshi Matsui, Douglas S. Hamilton, Sagar D. Rathod, Kara D. Lamb, and Natalie M. Mahowald
Atmos. Chem. Phys., 24, 13115–13127, https://doi.org/10.5194/acp-24-13115-2024, https://doi.org/10.5194/acp-24-13115-2024, 2024
Short summary
Short summary
Atmospheric aerosol deposition provides bioavailable iron to promote marine primary production, yet the estimates of its fluxes remain highly uncertain. This study, by performing global aerosol simulations, demonstrates that iron-containing particle size upon emission is a critical factor in regulating soluble iron input to open oceans. Further observational constraints on this are needed to reduce modeling uncertainties.
Camelia Talianu, Jeni Vasilescu, Doina Nicolae, Alexandru Ilie, Andrei Dandocsi, Anca Nemuc, and Livio Belegante
EGUsphere, https://doi.org/10.5194/egusphere-2024-2930, https://doi.org/10.5194/egusphere-2024-2930, 2024
Short summary
Short summary
Bucharest, Romania's capital, has successfully used mobile measurements and mixed-effects LUR models to derive seasonal maps of near-surface PM10, NO2, and UFP. The data was collected during two intensive campaigns, covering high-traffic streets, residential, industrial, and commercial districts. 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.
Jingmin Li, Mattia Righi, Johannes Hendricks, Christof G. Beer, Ulrike Burkhardt, and Anja Schmidt
Atmos. Chem. Phys., 24, 12727–12747, https://doi.org/10.5194/acp-24-12727-2024, https://doi.org/10.5194/acp-24-12727-2024, 2024
Short summary
Short summary
Aiming to understand underlying patterns and trends in aerosols, we characterize the spatial patterns and long-term evolution of lower tropospheric aerosols by clustering multiple aerosol properties from preindustrial times to the year 2050 under three Shared
Socioeconomic Pathway scenarios. The results provide a clear and condensed picture of the spatial extent and distribution of aerosols for different time periods and emission scenarios.
Socioeconomic Pathway scenarios. The results provide a clear and condensed picture of the spatial extent and distribution of aerosols for different time periods and emission scenarios.
Yueming Cheng, Tie Dai, Junji Cao, Daisuke Goto, Jianbing Jin, Teruyuki Nakajima, and Guangyu Shi
Atmos. Chem. Phys., 24, 12643–12659, https://doi.org/10.5194/acp-24-12643-2024, https://doi.org/10.5194/acp-24-12643-2024, 2024
Short summary
Short summary
In March 2021, east Asia experienced an outbreak of severe dust storms after an absence of 1.5 decades. Here, we innovatively used the time-lagged ground-based aerosol size information with the fixed-lag ensemble Kalman smoother to optimize dust emission and reproduce the dust storm. This work is valuable for not only the quantification of health damage, aviation risks, and profound impacts on the Earth's system but also revealing the climatic driving force and the process of desertification.
Marc Mallet, Aurore Voldoire, Fabien Solmon, Pierre Nabat, Thomas Drugé, and Romain Roehrig
Atmos. Chem. Phys., 24, 12509–12535, https://doi.org/10.5194/acp-24-12509-2024, https://doi.org/10.5194/acp-24-12509-2024, 2024
Short summary
Short summary
This study investigates the interactions between smoke aerosols and climate in tropical Africa using a coupled ocean–atmosphere–aerosol climate model. The work shows that smoke plumes have a significant impact by increasing the low-cloud fraction, decreasing the ocean and continental surface temperature and reducing the precipitation of coastal western Africa. It also highlights the role of the ocean temperature response and its feedbacks for the September–November season.
Jia Liu, Cancan Zhu, Donghui Zhou, and Jinbao Han
Atmos. Chem. Phys., 24, 12341–12354, https://doi.org/10.5194/acp-24-12341-2024, https://doi.org/10.5194/acp-24-12341-2024, 2024
Short summary
Short summary
The hydrophilic coatings of aged black carbon (BC) particles absorb moisture during the hygroscopic growth process, but it is difficult to characterize how much water is absorbed under different relative humidities (RHs). In this study, we propose a method to obtain the water content in the coatings based on the equivalent complex refractive index retrieved from optical properties. This method is verified from a theoretical perspective, and it performs well for thickly coated BC at high RHs.
Zijun Li, Angela Buchholz, and Noora Hyttinen
Atmos. Chem. Phys., 24, 11717–11725, https://doi.org/10.5194/acp-24-11717-2024, https://doi.org/10.5194/acp-24-11717-2024, 2024
Short summary
Short summary
Evaluating organosulfur (OS) hygroscopicity is important for assessing aerosol–cloud climate interactions in the post-fossil-fuel future, when SO2 emissions decrease and OS compounds become increasingly important. Here a state-of-the-art quantum-chemistry-based method was used to predict the hygroscopic growth factors (HGFs) of a group of atmospherically relevant OS compounds and their mixtures with (NH4)2SO4. A good agreement was observed between their model-estimated and experimental HGFs.
Jamie R. Banks, Bernd Heinold, and Kerstin Schepanski
Atmos. Chem. Phys., 24, 11451–11475, https://doi.org/10.5194/acp-24-11451-2024, https://doi.org/10.5194/acp-24-11451-2024, 2024
Short summary
Short summary
The Aralkum is a new desert in Central Asia formed by the desiccation of the Aral Sea. This has created a source of atmospheric dust, with implications for the balance of solar and thermal radiation. Simulating these effects using a dust transport model, we find that Aralkum dust adds radiative cooling effects to the surface and atmosphere on average but also adds heating events. Increases in surface pressure due to Aralkum dust strengthen the Siberian High and weaken the summer Asian heat low.
Xinyue Shao, Minghuai Wang, Xinyi Dong, Yaman Liu, Wenxiang Shen, Stephen R. Arnold, Leighton A. Regayre, Meinrat O. Andreae, Mira L. Pöhlker, Duseong S. Jo, Man Yue, and Ken S. Carslaw
Atmos. Chem. Phys., 24, 11365–11389, https://doi.org/10.5194/acp-24-11365-2024, https://doi.org/10.5194/acp-24-11365-2024, 2024
Short summary
Short summary
Highly oxygenated organic molecules (HOMs) play an important role in atmospheric new particle formation (NPF). By semi-explicitly coupling the chemical mechanism of HOMs and a comprehensive nucleation scheme in a global climate model, the updated model shows better agreement with measurements of nucleation rate, growth rate, and NPF event frequency. Our results reveal that HOM-driven NPF leads to a considerable increase in particle and cloud condensation nuclei burden globally.
Stuart Evans
EGUsphere, https://doi.org/10.5194/egusphere-2024-2820, https://doi.org/10.5194/egusphere-2024-2820, 2024
Short summary
Short summary
This study of the North American Great Plains identifies the various weather patterns responsible for blowing dust in all parts of the region using a weather pattern classification. In the southwest plains passing cold fronts are the primary cause of dust; in the understudied northern plains, summertime patterns and southerly pre-frontal winds are most important in the west and east, respectively. These results are valuable to understanding and forecasting dust in this complex source region.
Falei Xu, Shuang Wang, Yan Li, and Juan Feng
Atmos. Chem. Phys., 24, 10689–10705, https://doi.org/10.5194/acp-24-10689-2024, https://doi.org/10.5194/acp-24-10689-2024, 2024
Short summary
Short summary
This study examines how the winter North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) affect dust activities in North China during the following spring. The results show that the NAO and ENSO, particularly in their negative phases, greatly influence dust activities. When both are negative, their combined effect on dust activities is even greater. This research highlights the importance of these climate patterns in predicting spring dust activities in North China.
Hengheng Zhang, Wei Huang, Xiaoli Shen, Ramakrishna Ramisetty, Junwei Song, Olga Kiseleva, Christopher Claus Holst, Basit Khan, Thomas Leisner, and Harald Saathoff
Atmos. Chem. Phys., 24, 10617–10637, https://doi.org/10.5194/acp-24-10617-2024, https://doi.org/10.5194/acp-24-10617-2024, 2024
Short summary
Short summary
Our study unravels how stagnant winter conditions elevate aerosol levels in Stuttgart. Cloud cover at night plays a pivotal role, impacting morning air quality. Validating a key model, our findings aid accurate air quality predictions, crucial for effective pollution mitigation in urban areas.
Jiangtao Li, Xingqin An, Zhaobin Sun, Caihua Ye, Qing Hou, Yuxin Zhao, and Zhe Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2000, https://doi.org/10.5194/egusphere-2024-2000, 2024
Short summary
Short summary
Climate change and pollution have intensified pollen allergies. We developed a pollen emissions model using phenology and random forests. Key factors affecting annual pollen emissions include temperature, relative humidity, and sunshine hours. Pollen dispersal starts around August 10, peaks around August 30, and ends by September 25, lasting about 45 days. Over time, annual pollen emissions exhibit significant fluctuations and a downward trend.
Pascal Lemaitre, Arnaud Quérel, Alexis Dépée, Alice Guerra Devigne, Marie Monier, Thibault Hiron, Chloé Soto Minguez, Daniel Hardy, and Andrea Flossmann
Atmos. Chem. Phys., 24, 9713–9732, https://doi.org/10.5194/acp-24-9713-2024, https://doi.org/10.5194/acp-24-9713-2024, 2024
Short summary
Short summary
A new in-cloud scavenging scheme is proposed. It is based on a microphysical model of cloud formation and may be applied to long-distance atmospheric transport models (> 100 km) and climatic models. This model is applied to the two most extreme precipitating cloud types in terms of both relative humidity and vertical extension: cumulonimbus and stratus.
Alex Rowell, James Brean, David C. S. Beddows, Tuukka Petäjä, Máté Vörösmarty, Imre Salma, Jarkko V. Niemi, Hanna E. Manninen, Dominik van Pinxteren, Thomas Tuch, Kay Weinhold, Zongbo Shi, and Roy M. Harrison
Atmos. Chem. Phys., 24, 9515–9531, https://doi.org/10.5194/acp-24-9515-2024, https://doi.org/10.5194/acp-24-9515-2024, 2024
Short summary
Short summary
Different sources of airborne particles in the atmospheres of four European cities were distinguished by recognising their particle size distributions using a statistical procedure, positive matrix factorisation. The various sources responded differently to the changes in emissions associated with COVID-19 lockdowns, and the reasons are investigated. While traffic emissions generally decreased, particles formed from reactions of atmospheric gases decreased in some cities but increased in others.
Amy H. Peace, Ying Chen, George Jordan, Daniel G. Partridge, Florent Malavelle, Eliza Duncan, and Jim M. Haywood
Atmos. Chem. Phys., 24, 9533–9553, https://doi.org/10.5194/acp-24-9533-2024, https://doi.org/10.5194/acp-24-9533-2024, 2024
Short summary
Short summary
Natural aerosols from volcanic eruptions can help us understand how anthropogenic aerosols modify climate. We use observations and model simulations of the 2014–2015 Holuhraun eruption plume to examine aerosol–cloud interactions in September 2014. We find a shift to clouds with smaller, more numerous cloud droplets in the first 2 weeks of the eruption. In the third week, the background meteorology and previous conditions experienced by air masses modulate the aerosol perturbation to clouds.
Hua Lu, Min Xie, Bingliang Zhuang, Danyang Ma, Bojun Liu, Yangzhihao Zhan, Tijian Wang, Shu Li, Mengmeng Li, and Kuanguang Zhu
Atmos. Chem. Phys., 24, 8963–8982, https://doi.org/10.5194/acp-24-8963-2024, https://doi.org/10.5194/acp-24-8963-2024, 2024
Short summary
Short summary
To identify cloud, aerosol, and planetary boundary layer (PBL) interactions from an air quality perspective, we summarized two pollution patterns characterized by denser liquid cloud and by obvious cloud radiation interaction (CRI). Numerical simulation experiments showed CRI could cause a 50 % reduction in aerosol radiation interaction (ARI) under a low-trough system. The results emphasized the nonnegligible role of CRI and its inhibition of ARI under wet and cloudy pollution synoptic patterns.
Emilie Fons, Ann Kristin Naumann, David Neubauer, Theresa Lang, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 8653–8675, https://doi.org/10.5194/acp-24-8653-2024, https://doi.org/10.5194/acp-24-8653-2024, 2024
Short summary
Short summary
Aerosols can modify the liquid water path (LWP) of stratocumulus and, thus, their radiative effect. We compare storm-resolving model and satellite data that disagree on the sign of LWP adjustments and diagnose this discrepancy with causal inference. We find that strong precipitation, the absence of wet scavenging, and cloud deepening under a weak inversion contribute to positive LWP adjustments to aerosols in the model, despite weak negative effects from cloud-top entrainment enhancement.
Muhammed Irfan, Thomas Kühn, Taina Yli-Juuti, Anton Laakso, Eemeli Holopainen, Douglas R. Worsnop, Annele Virtanen, and Harri Kokkola
Atmos. Chem. Phys., 24, 8489–8506, https://doi.org/10.5194/acp-24-8489-2024, https://doi.org/10.5194/acp-24-8489-2024, 2024
Short summary
Short summary
The study examines how the volatility of semi-volatile organic compounds affects secondary organic aerosol (SOA) formation and climate. Our simulations show that uncertainties in these volatilities influence aerosol mass and climate impacts. Accurate representation of these compounds in climate models is crucial for predicting global climate patterns.
Ruth A. R. Digby, Knut von Salzen, Adam H. Monahan, Nathan P. Gillett, and Jiangnan Li
EGUsphere, https://doi.org/10.5194/egusphere-2024-1796, https://doi.org/10.5194/egusphere-2024-1796, 2024
Short summary
Short summary
The refractive index of black carbon (BCRI), which determines how much energy black carbon absorbs and scatters, is difficult to measure and different climate models use different values. We show that varying the BCRI across commonly used values can increase absorbing aerosol optical depth by 42 % and the warming effect from interactions between black carbon and radiation by 47 %, an appreciable fraction of the overall spread between models reported in recent literature assessments.
Alkiviadis Kalisoras, Aristeidis K. Georgoulias, Dimitris Akritidis, Robert J. Allen, Vaishali Naik, Chaincy Kuo, Sophie Szopa, Pierre Nabat, Dirk Olivié, Twan van Noije, Philippe Le Sager, David Neubauer, Naga Oshima, Jane Mulcahy, Larry W. Horowitz, and Prodromos Zanis
Atmos. Chem. Phys., 24, 7837–7872, https://doi.org/10.5194/acp-24-7837-2024, https://doi.org/10.5194/acp-24-7837-2024, 2024
Short summary
Short summary
Effective radiative forcing (ERF) is a metric for estimating how human activities and natural agents change the energy flow into and out of the Earth’s climate system. We investigate the anthropogenic aerosol ERF, and we estimate the contribution of individual processes to the total ERF using simulations from Earth system models within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our findings highlight that aerosol–cloud interactions drive ERF variability during the last 150 years.
Qianqian Song, Paul Ginoux, María Gonçalves Ageitos, Ron L. Miller, Vincenzo Obiso, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 7421–7446, https://doi.org/10.5194/acp-24-7421-2024, https://doi.org/10.5194/acp-24-7421-2024, 2024
Short summary
Short summary
We implement and simulate the distribution of eight dust minerals in the GFDL AM4.0 model. We found that resolving the eight minerals reduces dust absorption compared to the homogeneous dust used in the standard GFDL AM4.0 model that assumes a globally uniform hematite content of 2.7 % by volume. Resolving dust mineralogy results in significant impacts on radiation, land surface temperature, surface winds, and precipitation over North Africa in summer.
Senyi Kong, Zheng Wang, and Lei Bi
Atmos. Chem. Phys., 24, 6911–6935, https://doi.org/10.5194/acp-24-6911-2024, https://doi.org/10.5194/acp-24-6911-2024, 2024
Short summary
Short summary
The retrieval of refractive indices of dust aerosols from laboratory optical measurements is commonly done assuming spherical particles. This paper aims to investigate the uncertainties in the shortwave refractive indices and corresponding optical properties by considering non-spherical and inhomogeneous models for dust samples. The study emphasizes the significance of using non-spherical models for simulating dust aerosols.
Wenxuan Hua, Sijia Lou, Xin Huang, Lian Xue, Ke Ding, Zilin Wang, and Aijun Ding
Atmos. Chem. Phys., 24, 6787–6807, https://doi.org/10.5194/acp-24-6787-2024, https://doi.org/10.5194/acp-24-6787-2024, 2024
Short summary
Short summary
In this study, we diagnose uncertainties in carbon monoxide and organic carbon emissions from four inventories for seven major wildfire-prone regions. Uncertainties in vegetation classification methods, fire detection products, and cloud obscuration effects lead to bias in these biomass burning (BB) emission inventories. By comparing simulations with measurements, we provide certain inventory recommendations. Our study has implications for reducing uncertainties in emissions in further studies.
Chandrakala Bharali, Mary Barth, Rajesh Kumar, Sachin D. Ghude, Vinayak Sinha, and Baerbel Sinha
Atmos. Chem. Phys., 24, 6635–6662, https://doi.org/10.5194/acp-24-6635-2024, https://doi.org/10.5194/acp-24-6635-2024, 2024
Short summary
Short summary
This study examines the role of atmospheric aerosols in winter fog over the Indo-Gangetic Plains of India using WRF-Chem. The increase in RH with aerosol–radiation feedback (ARF) is found to be important for fog formation as it promotes the growth of aerosols in the polluted environment. Aqueous-phase chemistry in the fog increases PM2.5 concentration, further affecting ARF. ARF and aqueous-phase chemistry affect the fog intensity and the timing of fog formation by ~1–2 h.
Wenxin Zhao, Yu Zhao, Yu Zheng, Dong Chen, Jinyuan Xin, Kaitao Li, Huizheng Che, Zhengqiang Li, Mingrui Ma, and Yun Hang
Atmos. Chem. Phys., 24, 6593–6612, https://doi.org/10.5194/acp-24-6593-2024, https://doi.org/10.5194/acp-24-6593-2024, 2024
Short summary
Short summary
We evaluate the long-term (2000–2020) variabilities of aerosol absorption optical depth, black carbon emissions, and associated health risks in China with an integrated framework that combines multiple observations and modeling techniques. We demonstrate the remarkable emission abatement resulting from the implementation of national pollution controls and show how human activities affected the emissions with a spatiotemporal heterogeneity, thus supporting differentiated policy-making by region.
Peng Xian, Jeffrey S. Reid, Melanie Ades, Angela Benedetti, Peter R. Colarco, Arlindo da Silva, Tom F. Eck, Johannes Flemming, Edward J. Hyer, Zak Kipling, Samuel Rémy, Tsuyoshi Thomas Sekiyama, Taichu Tanaka, Keiya Yumimoto, and Jianglong Zhang
Atmos. Chem. Phys., 24, 6385–6411, https://doi.org/10.5194/acp-24-6385-2024, https://doi.org/10.5194/acp-24-6385-2024, 2024
Short summary
Short summary
The study compares and evaluates monthly AOD of four reanalyses (RA) and their consensus (i.e., ensemble mean). The basic verification characteristics of these RA versus both AERONET and MODIS retrievals are presented. The study discusses the strength of each RA and identifies regions where divergence and challenges are prominent. The RA consensus usually performs very well on a global scale in terms of how well it matches the observational data, making it a good choice for various applications.
Roger Teoh, Zebediah Engberg, Ulrich Schumann, Christiane Voigt, Marc Shapiro, Susanne Rohs, and Marc E. J. Stettler
Atmos. Chem. Phys., 24, 6071–6093, https://doi.org/10.5194/acp-24-6071-2024, https://doi.org/10.5194/acp-24-6071-2024, 2024
Short summary
Short summary
The radiative forcing (RF) due to aviation contrails is comparable to that caused by CO2. We estimate that global contrail net RF in 2019 was 62.1 mW m−2. This is ~1/2 the previous best estimate for 2018. Contrail RF varies regionally due to differences in conditions required for persistent contrails. COVID-19 reduced contrail RF by 54% in 2020 relative to 2019. Globally, 2 % of all flights account for 80 % of the annual contrail energy forcing, suggesting a opportunity to mitigate contrail RF.
Haotian Zu, Biwu Chu, Yiqun Lu, Ling Liu, and Xiuhui Zhang
Atmos. Chem. Phys., 24, 5823–5835, https://doi.org/10.5194/acp-24-5823-2024, https://doi.org/10.5194/acp-24-5823-2024, 2024
Short summary
Short summary
The nucleation of iodic acid (HIO3) and iodous acid (HIO2) was proven to be critical in marine areas. However, HIO3–HIO2 nucleation cannot effectively derive the rapid nucleation in some polluted coasts. We find a significant enhancement of dimethylamine (DMA) on the HIO3–HIO2 nucleation in marine and polar regions with abundant DMA sources, which may establish reasonable connections between the HIO3–HIO2 nucleation and the rapid formation of new particles in polluted marine and polar regions.
Junghwa Lee, Patric Seifert, Tempei Hashino, Maximilian Maahn, Fabian Senf, and Oswald Knoth
Atmos. Chem. Phys., 24, 5737–5756, https://doi.org/10.5194/acp-24-5737-2024, https://doi.org/10.5194/acp-24-5737-2024, 2024
Short summary
Short summary
Spectral bin model simulations of an idealized supercooled stratiform cloud were performed with the AMPS model for variable CCN and INP concentrations. We performed radar forward simulations with PAMTRA to transfer the simulations into radar observational space. The derived radar reflectivity factors were compared to observational studies of stratiform mixed-phase clouds. These studies report a similar response of the radar reflectivity factor to aerosol perturbations as we found in our study.
Basudev Swain, Marco Vountas, Aishwarya Singh, Nidhi L. Anchan, Adrien Deroubaix, Luca Lelli, Yanick Ziegler, Sachin S. Gunthe, Hartmut Bösch, and John P. Burrows
Atmos. Chem. Phys., 24, 5671–5693, https://doi.org/10.5194/acp-24-5671-2024, https://doi.org/10.5194/acp-24-5671-2024, 2024
Short summary
Short summary
Arctic amplification (AA) accelerates the warming of the central Arctic cryosphere and affects aerosol dynamics. Limited observations hinder a comprehensive analysis. This study uses AEROSNOW aerosol optical density (AOD) data and GEOS-Chem simulations to assess AOD variability. Discrepancies highlight the need for improved observational integration into models to refine our understanding of aerosol effects on cloud microphysics, ice nucleation, and radiative forcing under evolving AA.
Vincenzo Obiso, María Gonçalves Ageitos, Carlos Pérez García-Pando, Jan P. Perlwitz, Gregory L. Schuster, Susanne E. Bauer, Claudia Di Biagio, Paola Formenti, Kostas Tsigaridis, and Ron L. Miller
Atmos. Chem. Phys., 24, 5337–5367, https://doi.org/10.5194/acp-24-5337-2024, https://doi.org/10.5194/acp-24-5337-2024, 2024
Short summary
Short summary
We calculate the dust direct radiative effect (DRE) in an Earth system model accounting for regionally varying soil mineralogy through a new observationally constrained method. Linking dust absorption at solar wavelengths to the varying amount of specific minerals (i.e., iron oxides) improves the modeled range of dust single scattering albedo compared to observations and increases the global cooling by dust. Our results may contribute to improved estimates of the dust DRE and its climate impact.
Charlotte M. Beall, Po-Lun Ma, Matthew W. Christensen, Johannes Mülmenstädt, Adam Varble, Kentaroh Suzuki, and Takuro Michibata
Atmos. Chem. Phys., 24, 5287–5302, https://doi.org/10.5194/acp-24-5287-2024, https://doi.org/10.5194/acp-24-5287-2024, 2024
Short summary
Short summary
Single-layer warm liquid clouds cover nearly one-third of the Earth's surface, and uncertainties regarding the impact of aerosols on their radiative properties pose a significant challenge to climate prediction. Here, we demonstrate how satellite observations can be used to constrain Earth system model estimates of the radiative forcing from the interactions of aerosols with clouds due to warm rain processes.
Xiaoli Wei, Qian Cui, Leiming Ma, Feng Zhang, Wenwen Li, and Peng Liu
Atmos. Chem. Phys., 24, 5025–5045, https://doi.org/10.5194/acp-24-5025-2024, https://doi.org/10.5194/acp-24-5025-2024, 2024
Short summary
Short summary
A new aerosol-type classification algorithm has been proposed. It includes an optical database built by Mie scattering and a complex refractive index working as a baseline to identify different aerosol types. The new algorithm shows high accuracy and efficiency. Hence, a global map of aerosol types was generated to characterize aerosol types across the five continents. It will help improve the accuracy of aerosol inversion and determine the sources of aerosol pollution.
Cited articles
ACI (Automobile Club d'Italia): Autoritratto, http://www.aci.it/laci/studi-e-ricerche/dati-e-statistiche/autoritratto.html (last access: 16 September 2024), 2023. a
Aethlabs: https://help.aethlabs.com/s/article/Define-Specific-Atte nuation-Cross-section-σATN-or-Sigma-Value-for-the-microAe
th-MA-Series-instruments (last access: 16 September 2024), 2024. a
Alas, H. D. C., Müller, T., Weinhold, K., Pfeifer, S., Glojek, K., Gregorič, A., Močnik, G., Drinovec, L., Costabile, F., Ristorini, M., and Wiedensohler, A.: Performance of microAethalometers: Real-world Field Intercomparisons from Multiple Mobile Measurement Campaigns in Different Atmospheric Environments, Aerosol Air Qual. Res., 20, 2640–2653, https://doi.org/10.4209/aaqr.2020.03.0113, 2020. a
Ali, M. U., Siyi, L., Yousaf, B., Abbas, Q., Hameed, R., Zheng, C., Kuang, X., and Wong, M. H.: Emission sources and full spectrum of health impacts of black carbon associated polycyclic aromatic hydrocarbons (PAHs) in urban environment: A review, Crit. Rev. Env. Sci. Tec., 51, 857–896, https://doi.org/10.1080/10643389.2020.1738854, 2021. a
Almbauer, R., Pucher, K., and Sturm, P. J.: Air quality modeling for the city of Graz, Meteorol. Atmos. Phys., 57, 31–42, https://doi.org/10.1007/BF01044152, 1995. a, b
Amato, F.: Non-Exhaust Emissions: An Urban Air Quality Problem for Public Health; Impact and Mitigation Measures, Academic Press, ISBN 978-0-12-811751-4, 2018. a
Amato, F., Karanasiou, A., Moreno, T., Alastuey, A., Orza, J. A. G., Lumbreras, J., Borge, R., Boldo, E., Linares, C., and Querol, X.: Emission factors from road dust resuspension in a Mediterranean freeway, Atmos. Environ., 61, 580–587, https://doi.org/10.1016/j.atmosenv.2012.07.065, 2012. a, b, c
Avolio, E., Federico, S., Miglietta, M. M., Lo Feudo, T., Calidonna, C. R., and Sempreviva, A. M.: Sensitivity analysis of WRF model PBL schemes in simulating boundary-layer variables in southern Italy: An experimental campaign, Atmos. Res., 192, 58–71, https://doi.org/10.1016/j.atmosres.2017.04.003, 2017. a
Bauer, J. J., Yu, X.-Y., Cary, R., Laulainen, N., and Berkowitz, C.: Characterization of the Sunset Semi-Continuous Carbon Aerosol Analyzer, J. Air Waste Manage., 59, 826–833, https://doi.org/10.3155/1047-3289.59.7.826, 2009. a
Becerril-Valle, M., Coz, E., Prévôt, A. S. H., Močnik, G., Pandis, S. N., Sánchez de la Campa, A. M., Alastuey, A., Díaz, E., Pérez, R. M., and Artíñano, B.: Characterization of atmospheric black carbon and co-pollutants in urban and rural areas of Spain, Atmos. Environ., 169, 36–53, https://doi.org/10.1016/j.atmosenv.2017.09.014, 2017. a
Belis, C. A., Pikridas, M., Lucarelli, F., Petralia, E., Cavalli, F., Calzolai, G., Berico, M., and Sciare, J.: Source apportionment of fine PM by combining high time resolution organic and inorganic chemical composition datasets, Atmospheric Environment: X, 3, 100046, https://doi.org/10.1016/j.aeaoa.2019.100046, 2019. a
Berchet, A., Zink, K., Muller, C., Oettl, D., Brunner, J., Emmenegger, L., and Brunner, D.: A cost-effective method for simulating city-wide air flow and pollutant dispersion at building resolving scale, Atmos. Environ., 158, 181–196, https://doi.org/10.1016/j.atmosenv.2017.03.030, 2017. a
Bernardoni, V., Vecchi, R., Valli, G., Piazzalunga, A., and Fermo, P.: PM10 source apportionment in Milan (Italy) using time-resolved data, Science Total Environ., 409, 4788–4795, https://doi.org/10.1016/j.scitotenv.2011.07.048, 2011. a, b
Bernardoni, V., Elser, M., Valli, G., Valentini, S., Bigi, A., Fermo, P., Piazzalunga, A., and Vecchi, R.: Size-segregated aerosol in a hot-spot pollution urban area: Chemical composition and three-way source apportionment, Environ. Pollut., 231, 601–611, https://doi.org/10.1016/j.envpol.2017.08.040, 2017a. a
Bernardoni, V., Pileci, R. E., Caponi, L., and Massabò, D.: The Multi-Wavelength Absorption Analyzer (MWAA) Model as a Tool for Source and Component Apportionment Based on Aerosol Absorption Properties: Application to Samples Collected in Different Environments, Atmosphere, 8, 218, https://doi.org/10.3390/atmos8110218, 2017b. a, b, c, d
Bernardoni, V., Ferrero, L., Bolzacchini, E., Forello, A. C., Gregorič, A., Massabò, D., Močnik, G., Prati, P., Rigler, M., Santagostini, L., Soldan, F., Valentini, S., Valli, G., and Vecchi, R.: Determination of Aethalometer multiple-scattering enhancement parameters and impact on source apportionment during the winter 2017/18 EMEP/ACTRIS/COLOSSAL campaign in Milan, Atmos. Meas. Tech., 14, 2919–2940, https://doi.org/10.5194/amt-14-2919-2021, 2021. a, b, c, d
Bessagnet, B., Pirovano, G., Mircea, M., Cuvelier, C., Aulinger, A., Calori, G., Ciarelli, G., Manders, A., Stern, R., Tsyro, S., García Vivanco, M., Thunis, P., Pay, M.-T., Colette, A., Couvidat, F., Meleux, F., Rouïl, L., Ung, A., Aksoyoglu, S., Baldasano, J. M., Bieser, J., Briganti, G., Cappelletti, A., D'Isidoro, M., Finardi, S., Kranenburg, R., Silibello, C., Carnevale, C., Aas, W., Dupont, J.-C., Fagerli, H., Gonzalez, L., Menut, L., Prévôt, A. S. H., Roberts, P., and White, L.: Presentation of the EURODELTA III intercomparison exercise – evaluation of the chemistry transport models' performance on criteria pollutants and joint analysis with meteorology, Atmos. Chem. Phys., 16, 12667–12701, https://doi.org/10.5194/acp-16-12667-2016, 2016. a
Bigi, A.: Aerosol absorption data in Modena, Italy published in the journal article by Bigi et. al. (2023), Version 1.0.0, Zenodo [data set], https://doi.org/10.5281/zenodo.8140250, 2023. a
Bigi, A. and Ghermandi, G.: Trends and variability of atmospheric PM2.5 and PM10−2.5 concentration in the Po Valley, Italy, Atmos. Chem. Phys., 16, 15777–15788, https://doi.org/10.5194/acp-16-15777-2016, 2016. a
Bigi, A., Ghermandi, G., and Harrison, R. M.: Analysis of the air pollution climate at a background site in the Po valley, J. Environ. Monitor., 14, 552–563, https://doi.org/10.1039/C1EM10728C, 2012. a, b
Bigi, A., Bianchi, F., De Gennaro, G., Di Gilio, A., Fermo, P., Ghermandi, G., Prévôt, A. S. H., Urbani, M., Valli, G., Vecchi, R., and Piazzalunga, A.: Hourly composition of gas and particle phase pollutants at a central urban background site in Milan, Italy, Atmos. Res., 186, 83–94, https://doi.org/10.1016/j.atmosres.2016.10.025, 2017. a
Bigi, A., Veratti, G., Andrews, E., Collaud Coen, M., Guerrieri, L., Bernardoni, V., Massabò, D., Ferrero, L., Teggi, S., and Ghermandi, G.: Aerosol absorption using in situ filter-based photometers and ground-based sun photometry in the Po Valley urban atmosphere, Atmos. Chem. Phys., 23, 14841–14869, https://doi.org/10.5194/acp-23-14841-2023, 2023. a, b, c
Blanco-Donado, E. P., Schneider, I. L., Artaxo, P., Lozano-Osorio, J., Portz, L., and Oliveira, M. L. S.: Source identification and global implications of black carbon, Geosci. Front., 13, 101149, https://doi.org/10.1016/j.gsf.2021.101149, 2022. a
Bond, T. C., Habib, G., and Bergstrom, R. W.: Limitations in the enhancement of visible light absorption due to mixing state, J. Geophys. Res.-Atmos., 111, D20211, https://doi.org/10.1029/2006JD007315, 2006. a
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne, S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M., Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K., Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U., Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C. S.: Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res.-Atmos., 118, 5380–5552, https://doi.org/10.1002/jgrd.50171, 2013. a
Brasseur, O., Declerck, P., Heene, B., and Vanderstraeten, P.: Modelling Black Carbon concentrations in two busy street canyons in Brussels using CANSBC, Atmos. Environ., 101, 72–81, https://doi.org/10.1016/j.atmosenv.2014.10.049, 2015. a
Brown, S., Minor, H., O'Brien, T., Hameed, Y., Feenstra, B., Kuebler, D., Wetherell, W., Day, R., Tun, R., Landis, E., and Rice, J.: Review of Sunset OC/EC Instrument Measurements During the EPA’s Sunset Carbon Evaluation Project, Atmosphere, 10, 287, https://doi.org/10.3390/atmos10050287, 2019. a
Cappa, C. D., Onasch, T. B., Massoli, P., Worsnop, D. R., Bates, T. S., Cross, E. S., Davidovits, P., Hakala, J., Hayden, K. L., Jobson, B. T., Kolesar, K. R., Lack, D. A., Lerner, B. M., Li, S.-M., Mellon, D., Nuaaman, I., Olfert, J. S., Petäjä, T., Quinn, P. K., Song, C., Subramanian, R., Williams, E. J., and Zaveri, R. A.: Radiative Absorption Enhancements Due to the Mixing State of Atmospheric Black Carbon, Science, 337, 1078–1081, https://doi.org/10.1126/science.1223447, 2012. a
Chan, T. W., Brook, J. R., Smallwood, G. J., and Lu, G.: Time-resolved measurements of black carbon light absorption enhancement in urban and near-urban locations of southern Ontario, Canada, Atmos. Chem. Phys., 11, 10407–10432, https://doi.org/10.5194/acp-11-10407-2011, 2011. a
Chang, C.-Y., You, R., Armstrong, D., Bandi, A., Cheng, Y.-T., Burkhardt, P. M., Becerra-Dominguez, L., Madison, M. C., Tung, H.-Y., Zeng, Z., Wu, Y., Song, L., Phillips, P. E., Porter, P., Knight, J. M., Putluri, N., Yuan, X., Marcano, D. C., McHugh, E. A., Tour, J. M., Catic, A., Maneix, L., Burt, B. M., Lee, H.-S., Corry, D. B., and Kheradmand, F.: Chronic exposure to carbon black ultrafine particles reprograms macrophage metabolism and accelerates lung cancer, Science Advances, 8, eabq0615, https://doi.org/10.1126/sciadv.abq0615, 2022. a
Charbouillot, T., Janet, D. C., Schaal, P., Beynier, I., Boulat, J.-M., Grandchamp, A., and Biesse, F.: Methodology for the direct measurement of tire emission factors, Sci. Total Environ., 863, 160853, https://doi.org/10.1016/j.scitotenv.2022.160853, 2023. a, b
Cherian, R., Quaas, J., Salzmann, M., and Tomassini, L.: Black carbon indirect radiative effects in a climate model, Tellus B, 69, 1369342, https://doi.org/10.1080/16000889.2017.1369342, 2017. a
Chow, J. C., Watson, J. G., Chen, L.-W. A., Chang, M. O., Robinson, N. F., Trimble, D., and Kohl, S.: The IMPROVE_A Temperature Protocol for Thermal/Optical Carbon Analysis: Maintaining Consistency with a Long-Term Database, J. Air Waste Manage., 57, 1014–1023, https://doi.org/10.3155/1047-3289.57.9.1014, 2007. a
Chung, S. H. and Seinfeld, J. H.: Climate response of direct radiative forcing of anthropogenic black carbon, J. Geophys. Res.-Atmos., 110, D11102, https://doi.org/10.1029/2004JD005441, 2005. a
ARPAE-SIMC: LIBSIM, https://github.com/ARPA-SIMC/libsim (last access: 16 September 2024), 2023. a
Costabile, F., Alas, H., Aufderheide, M., Avino, P., Amato, F., Argentini, S., Barnaba, F., Berico, M., Bernardoni, V., Biondi, R., Casasanta, G., Ciampichetti, S., Calzolai, G., Canepari, S., Conidi, A., Cordelli, E., Di Ianni, A., Di Liberto, L., Facchini, M. C., Facci, A., Frasca, D., Gilardoni, S., Grollino, M. G., Gualtieri, M., Lucarelli, F., Malaguti, A., Manigrasso, M., Montagnoli, M., Nava, S., Perrino, C., Padoan, E., Petenko, I., Querol, X., Simonetti, G., Tranfo, G., Ubertini, S., Valli, G., Valentini, S., Vecchi, R., Volpi, F., Weinhold, K., Wiedensohler, A., Zanini, G., Gobbi, G. P., and Petralia, E.: First Results of the “Carbonaceous Aerosol in Rome and Environs (CARE)” Experiment: Beyond Current Standards for PM10, Atmosphere, 8, 249, https://doi.org/10.3390/atmos8120249, 2017a. a
Costabile, F., Gilardoni, S., Barnaba, F., Di Ianni, A., Di Liberto, L., Dionisi, D., Manigrasso, M., Paglione, M., Poluzzi, V., Rinaldi, M., Facchini, M. C., and Gobbi, G. P.: Characteristics of brown carbon in the urban Po Valley atmosphere, Atmos. Chem. Phys., 17, 313–326, https://doi.org/10.5194/acp-17-313-2017, 2017b. a
Crippa, M., Solazzo, E., Huang, G., Guizzardi, D., Koffi, E., Muntean, M., Schieberle, C., Friedrich, R., and Janssens-Maenhout, G.: High resolution temporal profiles in the Emissions Database for Global Atmospheric Research, Scientific Data, 7, 121, https://doi.org/10.1038/s41597-020-0462-2, 2020. a
Curci, G., Alyuz, U., Barò, R., Bianconi, R., Bieser, J., Christensen, J. H., Colette, A., Farrow, A., Francis, X., Jiménez-Guerrero, P., Im, U., Liu, P., Manders, A., Palacios-Peña, L., Prank, M., Pozzoli, L., Sokhi, R., Solazzo, E., Tuccella, P., Unal, A., Vivanco, M. G., Hogrefe, C., and Galmarini, S.: Modelling black carbon absorption of solar radiation: combining external and internal mixing assumptions, Atmos. Chem. Phys., 19, 181–204, https://doi.org/10.5194/acp-19-181-2019, 2019. a, b
Demir, T., Karakaş, D., and Yenisoy-Karakaş, S.: Source identification of exhaust and non-exhaust traffic emissions through the elemental carbon fractions and Positive Matrix Factorization method, Environ. Res., 204, 112399, https://doi.org/10.1016/j.envres.2021.112399, 2022. a
Denby, B. R., Sundvor, I., Johansson, C., Pirjola, L., Ketzel, M., Norman, M., Kupiainen, K., Gustafsson, M., Blomqvist, G., Kauhaniemi, M., and Omstedt, G.: A coupled road dust and surface moisture model to predict non-exhaust road traffic induced particle emissions (NORTRIP). Part 2: Surface moisture and salt impact modelling, Atmos. Environ., 81, 485–503, https://doi.org/10.1016/j.atmosenv.2013.09.003, 2013. a, b
Doran, J. C., Fast, J. D., Barnard, J. C., Laskin, A., Desyaterik, Y., and Gilles, M. K.: Applications of lagrangian dispersion modeling to the analysis of changes in the specific absorption of elemental carbon, Atmos. Chem. Phys., 8, 1377–1389, https://doi.org/10.5194/acp-8-1377-2008, 2008. 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, b, c
Drinovec, L., Jagodič, U., Pirker, L., Škarabot, M., Kurtjak, M., Vidović, K., Ferrero, L., Visser, B., Röhrbein, J., Weingartner, E., Kalbermatter, D. M., Vasilatou, K., Bühlmann, T., Pascale, C., Müller, T., Wiedensohler, A., and Močnik, G.: A dual-wavelength photothermal aerosol absorption monitor: design, calibration and performance, Atmos. Meas. Tech., 15, 3805–3825, https://doi.org/10.5194/amt-15-3805-2022, 2022. a, b
EEA: The application of models under the European Union's Air Quality Directive: A technical reference guide, European Environment Agency, https://www.eea.europa.eu/publications/fairmode (last access: 16 September 2024), 2011. a
EEA: 1. A Combustion, European Environment Agency, https://www.eea.europa.eu/publications/emep-eea-guidebook-2019/part-b-sectoral-guidance-chapters/1-energy/1-a-combustion (last access: 16 September 2024), 2019. a
EPA: Meteorological Monitoring Guidance for Regulatory Modeling Applications, NEPIS | US EPA, https://nepis.epa.gov/Exe/ZyNET.exe/2000D6B8.TXT?ZyActionD=ZyDocument&Client=EPA&Index=1995+Thru+1999&Docs=&Query=&Time=&EndTime=&SearchMethod=1&TocRestrict=n&Toc=&TocEntry=&QField=&QFieldYear=&QFieldMonth=&QFieldDay=&IntQFieldOp=0&ExtQFieldOp=0&XmlQuery=&File=D%3A%5Czyfiles%5CIndex%20Data%5C95thru99%5CTxt%5C00000016%5C2000D6B8.txt&User=ANONYMOUS&Password=anonymous&SortMethod=h%7C-&MaximumDocuments=1&FuzzyDegree=0&ImageQuality=r75g8/r75g8/x150y150g16/i425&Display=hpfr&DefSeekPage=x&SearchBack=ZyActionL&Back=ZyActionS&BackDesc=Results%20page&MaximumPages=1&ZyEntry=1&SeekPage=x&ZyPURL (last access: 16 September 2024), 2000. a
European Council: On Ambient Air Quality and Cleaner Air for Europe 2008/50/EC, Off. J. Eur. Union, 1, 1–44, https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32008L0050&from=en (last access: 16 September 2024), 2008. a
European Council: Proposal for a directive of the European Parliament and of the Council on ambient air quality and cleaner air for Europe (recast), Document 52022PC0542, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM%3A2022%3A542%3AFIN (last access: January 2023), 2022. a
Fay, B. and Neunhäuserer, L.: Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia, Atmos. Chem. Phys., 6, 2107–2128, https://doi.org/10.5194/acp-6-2107-2006, 2006. a
Ferrero, L., Riccio, A., Perrone, M. G., Sangiorgi, G., Ferrini, B. S., and Bolzacchini, E.: Mixing height determination by tethered balloon-based particle soundings and modeling simulations, Atmos. Res., 102, 145–156, https://doi.org/10.1016/j.atmosres.2011.06.016, 2011. a
Ferrero, L., Močnik, G., Cogliati, S., Gregorič, A., Colombo, R., and Bolzacchini, E.: Heating Rate of Light Absorbing Aerosols: Time-Resolved Measurements, the Role of Clouds, and Source Identification, Environ. Sci. Technol., 52, 3546–3555, https://doi.org/10.1021/acs.est.7b04320, 2018. a
Ferrero, L., Bernardoni, V., Santagostini, L., Cogliati, S., Soldan, F., Valentini, S., Massabò, D., Močnik, G., Gregorič, A., Rigler, M., Prati, P., Bigogno, A., Losi, N., Valli, G., Vecchi, R., and Bolzacchini, E.: Consistent determination of the heating rate of light-absorbing aerosol using wavelength- and time-dependent Aethalometer multiple-scattering correction, Sci. Total Environ., 791, 148277, https://doi.org/10.1016/j.scitotenv.2021.148277, 2021. a
Fischer, D. A. and Smith, G. D.: A portable, four-wavelength, single-cell photoacoustic spectrometer for ambient aerosol absorption, Aerosol Sci. Tech., 52, 393–406, https://doi.org/10.1080/02786826.2017.1413231, 2018. a
Forello, A. C., Bernardoni, V., Calzolai, G., Lucarelli, F., Massabò, D., Nava, S., Pileci, R. E., Prati, P., Valentini, S., Valli, G., and Vecchi, R.: Exploiting multi-wavelength aerosol absorption coefficients in a multi-time resolution source apportionment study to retrieve source-dependent absorption parameters, Atmos. Chem. Phys., 19, 11235–11252, https://doi.org/10.5194/acp-19-11235-2019, 2019. a, b
Galperin, B., Sukoriansky, S., and Anderson, P. S.: On the critical Richardson number in stably stratified turbulence, Atmos. Sci. Lett., 8, 65–69, https://doi.org/10.1002/asl.153, 2007. a
Gehrig, R., Zeyer, K., Bukowiecki, N., Lienemann, P., Poulikakos, L. D., Furger, M., and Buchmann, B.: Mobile load simulators – A tool to distinguish between the emissions due to abrasion and resuspension of PM10 from road surfaces, Atmos. Environ., 44, 4937–4943, https://doi.org/10.1016/j.atmosenv.2010.08.020, 2010. a
Geoportale-Emilia-Romagna: Homepage, https://geoportale.regione.emilia-romagna.it (last access: 16 September 2024), 2023. a
Ghermandi, G., Fabbi, S., Arvani, B., Veratti, G., Bigi, A., and Teggi, S.: Impact Assessment of Pollutant Emissions in the Atmosphere from a Power Plant over a Complex Terrain and under Unsteady Winds, Sustainability, 9, 2076, https://doi.org/10.3390/su9112076, 2017. a
Ghermandi, G., Fabbi, S., Bigi, A., Veratti, G., Despini, F., Teggi, S., Barbieri, C., and Torreggiani, L.: Impact assessment of vehicular exhaust emissions by microscale simulation using automatic traffic flow measurements, Atmos. Pollut. Res., 10, 1473–1481, https://doi.org/10.1016/j.apr.2019.04.004, 2019. a
Ghermandi, G., Fabbi, S., Veratti, G., Bigi, A., and Teggi, S.: Estimate of Secondary NO2 Levels at Two Urban Traffic Sites Using Observations and Modelling, Sustainability, 12, 7897, https://doi.org/10.3390/su12197897, 2020. a
Gilardoni, S., Massoli, P., Marinoni, A., Mazzoleni, C., Freedman, A., Lonati, G., Iuliis, S. D., and Gianelle, V.: Spatial and Temporal Variability of Carbonaceous Aerosol Absorption in the Po Valley, Aerosol Air Qual. Res., 20, 2624–2639, https://doi.org/10.4209/aaqr.2020.03.0085, 2020. a, b
Grachev, A. A., Andreas, E. L., Fairall, C. W., Guest, P. S., and Persson, P. O. G.: The Critical Richardson Number and Limits of Applicability of Local Similarity Theory in the Stable Boundary Layer, Bound.-Lay. Meteorol., 147, 51–82, https://doi.org/10.1007/s10546-012-9771-0, 2013. a
Grahame, T. J., Klemm, R., and Schlesinger, R. B.: Public health and components of particulate matter: the changing assessment of black carbon, J. Air Waste Manage., 64, 620–660, https://doi.org/10.1080/10962247.2014.912692, 2014. a
Grange, S. K., Lötscher, H., Fischer, A., Emmenegger, L., and Hueglin, C.: Evaluation of equivalent black carbon source apportionment using observations from Switzerland between 2008 and 2018, Atmos. Meas. Tech., 13, 1867–1885, https://doi.org/10.5194/amt-13-1867-2020, 2020. a, b, c
Guevara, M., Tena, C., Porquet, M., Jorba, O., and Pérez García-Pando, C.: HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 2: The bottom–up module, Geosci. Model Dev., 13, 873–903, https://doi.org/10.5194/gmd-13-873-2020, 2020. a
Guo, X., Nakayama, T., Yamada, H., Inomata, S., Tonokura, K., and Matsumi, Y.: Measurement of the light absorbing properties of diesel exhaust particles using a three-wavelength photoacoustic spectrometer, Atmos. Environ., 94, 428–437, https://doi.org/10.1016/j.atmosenv.2014.05.042, 2014. a
Hanna, S. and Chang, J.: Acceptance criteria for urban dispersion model evaluation, Meteorol. Atmos. Phys., 116, 133–146, https://doi.org/10.1007/s00703-011-0177-1, 2012. a
Harrison, R. M., Allan, J., Carruthers, D., Heal, M. R., Lewis, A. C., Marner, B., Murrells, T., and Williams, A.: Non-exhaust vehicle emissions of particulate matter and VOC from road traffic: A review, Atmos. Environ., 262, 118592, https://doi.org/10.1016/j.atmosenv.2021.118592, 2021. a
Helin, A., Niemi, J. V., Virkkula, A., Pirjola, L., Teinilä, K., Backman, J., Aurela, M., Saarikoski, S., Rönkkö, T., Asmi, E., and Timonen, H.: Characteristics and source apportionment of black carbon in the Helsinki metropolitan area, Finland, Atmos. Environ., 190, 87–98, https://doi.org/10.1016/j.atmosenv.2018.07.022, 2018. a, b
Hendricks, J., Kärcher, B., and Lohmann, U.: Effects of ice nuclei on cirrus clouds in a global climate model, J. Geophys. Res.-Atmos., 116, D18206, https://doi.org/10.1029/2010JD015302, 2011. a
Henzing, J. S., Olivié, D. J. L., and van Velthoven, P. F. J.: A parameterization of size resolved below cloud scavenging of aerosols by rain, Atmos. Chem. Phys., 6, 3363–3375, https://doi.org/10.5194/acp-6-3363-2006, 2006. a
Holmes, N. S. and Morawska, L.: A review of dispersion modelling and its application to the dispersion of particles: An overview of different dispersion models available, Atmos. Environ., 40, 5902–5928, https://doi.org/10.1016/j.atmosenv.2006.06.003, 2006. a
ISPRA: Inventario Nazionale – EMISSIONI, https://emissioni.sina.isprambiente.it/inventario-nazionale/, last access: 16 September 2024, 2023. a
Janssen, N. A., Gerlofs-Nijland, M. E., Lanki, T., Salonen, R. O., Cassee, F., Hoek, G., Fischer, P., Brunekreef, B., and Krzyzanowski, M.: Health effects of black carbon, World Health Organization. Regional Office for Europe, ISBN 978-92-890-0265-3, https://apps.who.int/iris/handle/10665/352615 (last access: 16 September 2024), 2012. a
Janssen, N. A. H., Hoek, G., Simic-Lawson, M., Fischer, P., van Bree, L., ten Brink, H., Keuken, M., Atkinson, R. W., Anderson, H. R., Brunekreef, B., and Cassee, F. R.: Black carbon as an additional indicator of the adverse health effects of airborne particles compared with PM10 and PM2.5, Environ. Health Persp., 119, 1691–1699, https://doi.org/10.1289/ehp.1003369, 2011. a
Ježek, I., Blond, N., Skupinski, G., and Močnik, G.: The traffic emission-dispersion model for a Central-European city agrees with measured black carbon apportioned to traffic, Atmos. Environ., 184, 177–190, https://doi.org/10.1016/j.atmosenv.2018.04.028, 2018. a
Karakaş, D., Berberler, E., Bayramoğlu Karşı, M. B., Demir, T., Aslan, Ö., Karadeniz, H., Ağa, Ö., and Yenisoy-Karakaş, S.: Simultaneous Quantification of Real-World Elemental Contributions from the Exhaust and Non-Exhaust Vehicular Emissions Using Road Dust Enrichment Factor-Elemental Carbon Tracer Method (EFECT), Atmosphere, 14, 631, https://doi.org/10.3390/atmos14040631, 2023. a
Kaskaoutis, D. G., Grivas, G., Stavroulas, I., Bougiatioti, A., Liakakou, E., Dumka, U. C., Gerasopoulos, E., and Mihalopoulos, N.: Apportionment of black and brown carbon spectral absorption sources in the urban environment of Athens, Greece, during winter, Sci. Total Environ., 801, 149739, https://doi.org/10.1016/j.scitotenv.2021.149739, 2021a. a
Kaskaoutis, D. G., Grivas, G., Stavroulas, I., Liakakou, E., Dumka, U. C., Gerasopoulos, E., and Mihalopoulos, N.: Effect of aerosol types from various sources at an urban location on spectral curvature of scattering and absorption coefficients, Atmos. Res., 264, 105865, https://doi.org/10.1016/j.atmosres.2021.105865, 2021b. a
Davulienė, L., Šemčuk, S., Kandrotaitė, K., Minderytė, A., Davtalab, M., Uogintė, I., Skapas, M., Dudoitis, V., and Byčenkienė, S.: Integrated personal exposure and deposition of black carbon on human lungs, Air Qual. Atmos. Hlth., 17, 35–50, https://doi.org/10.1007/s11869-023-01428-8, 2024. a
Kim, J., Park, E., Moon, H., Son, H., Hong, J., Wi, E., Kwon, J.-T., Seo, D. Y., Lee, H., and Kim, Y.: Estimation of the concentration of nano-carbon black in tire-wear particles using emission factors of PM10, PM2.5, and black carbon, Chemosphere, 303, 134976, https://doi.org/10.1016/j.chemosphere.2022.134976, 2022. a
Koch, D., Balkanski, Y., Bauer, S. E., Easter, R. C., Ferrachat, S., Ghan, S. J., Hoose, C., Iversen, T., Kirkevåg, A., Kristjansson, J. E., Liu, X., Lohmann, U., Menon, S., Quaas, J., Schulz, M., Seland, Ø., Takemura, T., and Yan, N.: Soot microphysical effects on liquid clouds, a multi-model investigation, Atmos. Chem. Phys., 11, 1051–1064, https://doi.org/10.5194/acp-11-1051-2011, 2011. a, b
Kouridis, C., Gkatzoflias, D., Kioutsoukis, I., Ntziachristos, L., Pastorello, C., and Dilara, P.: Uncertainty Estimates and Guidance for Road Transport Emission Calculations, Publications Office of the European Union, Luxemburg, https://doi.org/10.2788/78236, iSBN: 9789279153075, ISSN: 1018-5593, 2010. a
Kuenen, J., Dellaert, S., Visschedijk, A., Jalkanen, J.-P., Super, I., and Denier van der Gon, H.: CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling, Earth Syst. Sci. Data, 14, 491–515, https://doi.org/10.5194/essd-14-491-2022, 2022. a
Lee, J. and Moosmüller, H.: Measurement of Light Absorbing Aerosols with Folded-Jamin Photothermal Interferometry, Sensors, 20, 2615, https://doi.org/10.3390/s20092615, 2020. a
Li, B., Wang, Y., and Li, Z.: A method for monitoring mass concentration of black carbon particulate matter using photothermal interferometry, Environ. Sci. Pollut. R., 23, 4692–4699, https://doi.org/10.1007/s11356-015-5702-1, 2016. a
Li, C., Windwer, E., Fang, Z., Nissenbaum, D., and Rudich, Y.: Correcting micro-aethalometer absorption measurements for brown carbon aerosol, Sci. Total Environ., 777, 146143, https://doi.org/10.1016/j.scitotenv.2021.146143, 2021. a
Li, F., Luo, B., Zhai, M., Liu, L., Zhao, G., Xu, H., Deng, T., Deng, X., Tan, H., Kuang, Y., and Zhao, J.: Black carbon content of traffic emissions significantly impacts black carbon mass size distributions and mixing states, Atmos. Chem. Phys., 23, 6545–6558, https://doi.org/10.5194/acp-23-6545-2023, 2023. a
Liakakou, E., Stavroulas, I., Kaskaoutis, D. G., Grivas, G., Paraskevopoulou, D., Dumka, U. C., Tsagkaraki, M., Bougiatioti, A., Oikonomou, K., Sciare, J., Gerasopoulos, E., and Mihalopoulos, N.: Long-term variability, source apportionment and spectral properties of black carbon at an urban background site in Athens, Greece, Atmos. Environ., 222, 117137, https://doi.org/10.1016/j.atmosenv.2019.117137, 2020. a, b, c
Liu, C., Chung, C. E., Yin, Y., and Schnaiter, M.: The absorption Ångström exponent of black carbon: from numerical aspects, Atmos. Chem. Phys., 18, 6259–6273, https://doi.org/10.5194/acp-18-6259-2018, 2018. a
Liu, D., Whitehead, J., Alfarra, M. R., Reyes-Villegas, E., Spracklen, D. V., Reddington, C. L., Kong, S., Williams, P. I., Ting, Y.-C., Haslett, S., Taylor, J. W., Flynn, M. J., Morgan, W. T., McFiggans, G., Coe, H., and Allan, J. D.: Black-carbon absorption enhancement in the atmosphere determined by particle mixing state, Nat. Geosci., 10, 184–188, https://doi.org/10.1038/ngeo2901, 2017. a
Lonati, G., Ozgen, S., Ripamonti, G., and Signorini, S.: Variability of Black Carbon and Ultrafine Particle Concentration on Urban Bike Routes in a Mid-Sized City in the Po Valley (Northern Italy), Atmosphere, 8, 40, https://doi.org/10.3390/atmos8020040, 2017. a
Lugon, L., Vigneron, J., Debert, C., Chrétien, O., and Sartelet, K.: Black carbon modeling in urban areas: investigating the influence of resuspension and non-exhaust emissions in streets using the Street-in-Grid model for inert particles (SinG-inert), Geosci. Model Dev., 14, 7001–7019, https://doi.org/10.5194/gmd-14-7001-2021, 2021. a, b, c, d, e
Lyons, R., Panofsky, H. A., and Wollaston, S.: The Critical Richardson Number and Its Implications for Forecast Problems, J. Appl. Meteor. Climatol., 3, 136–142, https://doi.org/10.1175/1520-0450(1964)003<0136:TCRNAI>2.0.CO;2, 1964. a
Lyu, Y. and Olofsson, U.: On black carbon emission from automotive disc brakes, J. Aerosol Sci., 148, 105610, https://doi.org/10.1016/j.jaerosci.2020.105610, 2020. a
Mailler, S., Menut, L., Khvorostyanov, D., Valari, M., Couvidat, F., Siour, G., Turquety, S., Briant, R., Tuccella, P., Bessagnet, B., Colette, A., Létinois, L., Markakis, K., and Meleux, F.: CHIMERE-2017: from urban to hemispheric chemistry-transport modeling, Geosci. Model Dev., 10, 2397–2423, https://doi.org/10.5194/gmd-10-2397-2017, 2017. a, b
Marongiu, A., Angelino, E., and Distefano, G.: Methodology for estimating atmospheric emissions from residential biomass heating considering technology turnover and real utilization - Black Carbon Ensemble Emission Map Estimates from national to local level, TFEIP 2024 Meeting, Dessau, Germany, 14–16 May 2024, https://www.tfeip-secretariat.org/_files/ugd/e5a9c7_2ea5dcce45ed45549185a0dfe68ee10f.pdf (last access: 16 September 2024), 2024. a
Massabò, D., Caponi, L., Bernardoni, V., Bove, M. C., Brotto, P., Calzolai, G., Cassola, F., Chiari, M., Fedi, M. E., Fermo, P., Giannoni, M., Lucarelli, F., Nava, S., Piazzalunga, A., Valli, G., Vecchi, R., and Prati, P.: Multi-wavelength optical determination of black and brown carbon in atmospheric aerosols, Atmos. Environ., 108, 1–12, https://doi.org/10.1016/j.atmosenv.2015.02.058, 2015. a, b, c, d
Mbengue, S., Zikova, N., Schwarz, J., Vodička, P., Holubová Šmejkalová, A., and Holoubek, I.: Mass absorption cross-section and absorption enhancement from long term black and elemental carbon measurements: A rural background station in Central Europe, Sci. Total Environ., 794, 148365, https://doi.org/10.1016/j.scitotenv.2021.148365, 2021. a
Menon, S., Hansen, J., Nazarenko, L., and Luo, Y.: Climate Effects of Black Carbon Aerosols in China and India, Science, 297, 2250–2253, https://doi.org/10.1126/science.1075159, 2002. a
Menut, L., Bessagnet, B., Briant, R., Cholakian, A., Couvidat, F., Mailler, S., Pennel, R., Siour, G., Tuccella, P., Turquety, S., and Valari, M.: The CHIMERE v2020r1 online chemistry-transport model, Geosci. Model Dev., 14, 6781–6811, https://doi.org/10.5194/gmd-14-6781-2021, 2021. a
Merico, E., Cesari, D., Dinoi, A., Gambaro, A., Barbaro, E., Guascito, M. R., Giannossa, L. C., Mangone, A., and Contini, D.: Inter-comparison of carbon content in PM10 and PM2.5 measured with two thermo-optical protocols on samples collected in a Mediterranean site, Environ. Sci. Pollut. R., 26, 29334–29350, https://doi.org/10.1007/s11356-019-06117-7, 2019. a
Milinković, A., Gregorič, A., Grgičin, V. D., Vidič, S., Penezić, A., Kušan, A. C., Alempijević, S. B., Kasper-Giebl, A., and Frka, S.: Variability of black carbon aerosol concentrations and sources at a Mediterranean coastal region, Atmos. Pollut. Res., 12, 101221, https://doi.org/10.1016/j.apr.2021.101221, 2021. a
Minderytė, A., Pauraite, J., Dudoitis, V., Plauškaitė, K., Kilikevičius, A., Matijošius, J., Rimkus, A., Kilikevičienė, K., Vainorius, D., and Byčenkienė, S.: Carbonaceous aerosol source apportionment and assessment of transport-related pollution, Atmos. Environ., 279, 119043, https://doi.org/10.1016/j.atmosenv.2022.119043, 2022. a
Mircea, M., Bessagnet, B., D'Isidoro, M., Pirovano, G., Aksoyoglu, S., Ciarelli, G., Tsyro, S., Manders, A., Bieser, J., Stern, R., Vivanco, M. G., Cuvelier, C., Aas, W., Prévôt, A. S. H., Aulinger, A., Briganti, G., Calori, G., Cappelletti, A., Colette, A., Couvidat, F., Fagerli, H., Finardi, S., Kranenburg, R., Rouïl, L., Silibello, C., Spindler, G., Poulain, L., Herrmann, H., Jimenez, J. L., Day, D. A., Tiitta, P., and Carbone, S.: EURODELTA III exercise: An evaluation of air quality models' capacity to reproduce the carbonaceous aerosol, Atmospheric Environment: X, 2, 100018, https://doi.org/10.1016/j.aeaoa.2019.100018, 2019. a, b, c
Moffet, R. C. and Prather, K. A.: In-situ measurements of the mixing state and optical properties of soot with implications for radiative forcing estimates, P. Natl. Acad. Sci. USA, 106, 11872–11877, https://doi.org/10.1073/pnas.0900040106, 2009. a
Moosmüller, H., Chakrabarty, R. K., and Arnott, W. P.: Aerosol light absorption and its measurement: A review, J. Quant. Spectrosc. Ra., 110, 844–878, https://doi.org/10.1016/j.jqsrt.2009.02.035, 2009. a
Mousavi, A., Sowlat, M. H., Lovett, C., Rauber, M., Szidat, S., Boffi, R., Borgini, A., De Marco, C., Ruprecht, A. A., and Sioutas, C.: Source apportionment of black carbon (BC) from fossil fuel and biomass burning in metropolitan Milan, Italy, Atmos. Environ., 203, 252–261, https://doi.org/10.1016/j.atmosenv.2019.02.009, 2019. a, b, c
Mues, A., Kuenen, J., Hendriks, C., Manders, A., Segers, A., Scholz, Y., Hueglin, C., Builtjes, P., and Schaap, M.: Sensitivity of air pollution simulations with LOTOS-EUROS to the temporal distribution of anthropogenic emissions, Atmos. Chem. Phys., 14, 939–955, https://doi.org/10.5194/acp-14-939-2014, 2014. a
Ning, Z., Chan, K. L., Wong, K. C., Westerdahl, D., Močnik, G., Zhou, J. H., and Cheung, C. S.: Black carbon mass size distributions of diesel exhaust and urban aerosols measured using differential mobility analyzer in tandem with Aethalometer, Atmos. Environ., 80, 31–40, https://doi.org/10.1016/j.atmosenv.2013.07.037, 2013. a
Oettl, D.: Evaluation of the Revised Lagrangian Particle Model GRAL Against Wind-Tunnel and Field Observations in the Presence of Obstacles, Bound.-Lay. Meteorol., 155, 271–287, https://doi.org/10.1007/s10546-014-9993-4, 2015a. a
Oettl, D.: A multiscale modelling methodology applicable for regulatory purposes taking into account effects of complex terrain and buildings on pollutant dispersion: a case study for an inner Alpine basin, Environ. Sci. Pollut. R., 22, 17860–17875, https://doi.org/10.1007/s11356-015-4966-9, 2015b. a, b, c
Oettl, D.: Quality assurance of the prognostic, microscale wind-field model GRAL 14.8 using wind-tunnel data provided by the German VDI guideline 3783-9, J. Wind Eng. Ind. Aerod., 142, 104–110, https://doi.org/10.1016/j.jweia.2015.03.014, 2015c. a, b, c
Oettl, D.: Development of the Mesoscale Model GRAMM-SCI: Evaluation of Simulated Highly-Resolved Flow Fields in an Alpine and Pre-Alpine Region, Atmosphere, 12, 298, https://doi.org/10.3390/atmos12030298, 2021. a
Oettl, D. and Reifeltshammer, R.: Recent developments in high-resolution wind field modeling in complex terrain for dispersion simulations using GRAMM-SCI, Air Qual. Atmos. Hlth., 16, 2209–2223, https://doi.org/10.1007/s11869-023-01403-3, 2023. a
Oettl, D. and Veratti, G.: A comparative study of mesoscale flow-field modelling in an Eastern Alpine region using WRF and GRAMM-SCI, Atmos. Res., 249, 105288, https://doi.org/10.1016/j.atmosres.2020.105288, 2021. a
Paglione, M., Gilardoni, S., Rinaldi, M., Decesari, S., Zanca, N., Sandrini, S., Giulianelli, L., Bacco, D., Ferrari, S., Poluzzi, V., Scotto, F., Trentini, A., Poulain, L., Herrmann, H., Wiedensohler, A., Canonaco, F., Prévôt, A. S. H., Massoli, P., Carbone, C., Facchini, M. C., and Fuzzi, S.: The impact of biomass burning and aqueous-phase processing on air quality: a multi-year source apportionment study in the Po Valley, Italy, Atmos. Chem. Phys., 20, 1233–1254, https://doi.org/10.5194/acp-20-1233-2020, 2020. a
Pandolfo, J. P.: Motions with Inertial and Diurnal Period, J. Mar. Res., 27, 301–317, 1969. a
Pani, S. K., Wang, S.-H., Lin, N.-H., Chantara, S., Lee, C.-T., and Thepnuan, D.: Black carbon over an urban atmosphere in northern peninsular Southeast Asia: Characteristics, source apportionment, and associated health risks, Environ. Pollut., 259, 113871, https://doi.org/10.1016/j.envpol.2019.113871, 2020. a
Park, S. S., Hansen, A. D. A., and Cho, S. Y.: Measurement of real time black carbon for investigating spot loading effects of Aethalometer data, Atmos. Environ., 44, 1449–1455, https://doi.org/10.1016/j.atmosenv.2010.01.025, 2010. a
Pashneva, D., Minderytė, A., Davulienė, L., Dudoitis, V., and Byčenkienė, S.: Understanding the Dynamics of Source-Apportioned Black Carbon in an Urban Background Environment, Atmosphere, 15, 832, https://doi.org/10.3390/atmos15070832, 2024. a, b
Peng, J., Hu, M., Guo, S., Du, Z., Zheng, J., Shang, D., Levy Zamora, M., Zeng, L., Shao, M., Wu, Y.-S., Zheng, J., Wang, Y., Glen, C. R., Collins, D. R., Molina, M. J., and Zhang, R.: Markedly enhanced absorption and direct radiative forcing of black carbon under polluted urban environments, P. Natl. Acad. Sci. USA, 113, 4266–4271, https://doi.org/10.1073/pnas.1602310113, 2016. a
Pepe, N., Pirovano, G., Balzarini, A., Toppetti, A., Riva, G. M., Amato, F., and Lonati, G.: Enhanced CAMx source apportionment analysis at an urban receptor in Milan based on source categories and emission regions, Atmospheric Environment: X, 2, 100020, https://doi.org/10.1016/j.aeaoa.2019.100020, 2019. a
Pernigotti, D., Georgieva, E., Thunis, P., and Bessagnet, B.: Impact of meteorology on air quality modeling over the Po valley in northern Italy, Atmos. Environ., 51, 303–310, https://doi.org/10.1016/j.atmosenv.2011.12.059, 2012a. a
Pernigotti, D., Georgieva, E., Thunis, P., Cuvelier, C., and de Meij, A.: The Impact of Meteorology on Air Quality Simulations over the Po Valley in Northern Italy, in: Air Pollution Modeling and its Application XXI, edited by: Steyn, D. G. and Trini Castelli, S., NATO Science for Peace and Security Series C: Environmental Security, Springer Netherlands, Dordrecht, 485–490, https://doi.org/10.1007/978-94-007-1359-8_81, ISBN 978-94-007-1359-8, 2012b. a
Pernigotti, D., Thunis, P., Cuvelier, C., Georgieva, E., Gsella, A., De Meij, A., Pirovano, G., Balzarini, A., Riva, G. M., Carnevale, C., Pisoni, E., Volta, M., Bessagnet, B., Kerschbaumer, A., Viaene, P., De Ridder, K., Nyiri, A., and Wind, P.: POMI: a model inter-comparison exercise over the Po Valley, Air Qual. Atmos. Hlth., 6, 701–715, https://doi.org/10.1007/s11869-013-0211-1, 2013. a
Perrino, C., Catrambone, M., Dalla Torre, S., Rantica, E., Sargolini, T., and Canepari, S.: Seasonal variations in the chemical composition of particulate matter: a case study in the Po Valley. Part I: macro-components and mass closure, Environ. Sci. Pollut. R., 21, 3999–4009, https://doi.org/10.1007/s11356-013-2067-1, 2014. a
Petzold, A. and Niessner, R.: Photoacoustic soot sensor for in-situ black carbon monitoring, Appl. Phys. B, 63, 191–197, https://doi.org/10.1007/BF01095272, 1996. a
Petzold, A., Ogren, J. A., Fiebig, M., Laj, P., Li, S.-M., Baltensperger, U., Holzer-Popp, T., Kinne, S., Pappalardo, G., Sugimoto, N., Wehrli, C., Wiedensohler, A., and Zhang, X.-Y.: Recommendations for reporting “black carbon” measurements, Atmos. Chem. Phys., 13, 8365–8379, https://doi.org/10.5194/acp-13-8365-2013, 2013. a, b, c, d
Pirovano, G., Balzarini, A., Bessagnet, B., Emery, C., Kallos, G., Meleux, F., Mitsakou, C., Nopmongcol, U., Riva, G. M., and Yarwood, G.: Investigating impacts of chemistry and transport model formulation on model performance at European scale, Atmos. Environ., 53, 93–109, https://doi.org/10.1016/j.atmosenv.2011.12.052, 2012. a
Ramanathan, V. and Carmichael, G.: Global and regional climate changes due to black carbon, Nat. Geosci., 1, 221–227, https://doi.org/10.1038/ngeo156, 2008. a
Ramanathan, V., Crutzen, P. J., Kiehl, J. T., and Rosenfeld, D.: Aerosols, Climate, and the Hydrological Cycle, Science, 294, 2119–2124, https://doi.org/10.1126/science.1064034, 2001. a
Reche, C., Querol, X., Alastuey, A., Viana, M., Pey, J., Moreno, T., Rodríguez, S., González, Y., Fernández-Camacho, R., de la Rosa, J., Dall'Osto, M., Prévôt, A. S. H., Hueglin, C., Harrison, R. M., and Quincey, P.: New considerations for PM, Black Carbon and particle number concentration for air quality monitoring across different European cities, Atmos. Chem. Phys., 11, 6207–6227, https://doi.org/10.5194/acp-11-6207-2011, 2011. a
Roberts, D. L. and Jones, A.: Climate sensitivity to black carbon aerosol from fossil fuel combustion, J. Geophys. Res.-Atmos., 109, D16202, https://doi.org/10.1029/2004JD004676, 2004. a
Rohr, A. and McDonald, J.: Health effects of carbon-containing particulate matter: focus on sources and recent research program results, Crit. Rev. Toxicol., 46, 97–137, https://doi.org/10.3109/10408444.2015.1107024, 2016. a
Saide, P. E., Carmichael, G. R., Spak, S. N., Gallardo, L., Osses, A. E., Mena-Carrasco, M. A., and Pagowski, M.: Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF–Chem CO tracer model, Atmos. Environ., 45, 2769–2780, https://doi.org/10.1016/j.atmosenv.2011.02.001, 2011. a
Sandradewi, J., Prévôt, A. S. H., Szidat, S., Perron, N., Alfarra, M. R., Lanz, V. A., Weingartner, E., and Baltensperger, U.: Using Aerosol Light Absorption Measurements for the Quantitative Determination of Wood Burning and Traffic Emission Contributions to Particulate Matter, Environ. Sci. Technol., 42, 3316–3323, https://doi.org/10.1021/es702253m, 2008. a
Saputra, D., Yoon, J.-H., Park, H., Heo, Y., Yang, H., Lee, E. J., Lee, S., Song, C.-W., and Lee, K.: Inhalation of Carbon Black Nanoparticles Aggravates Pulmonary Inflammation in Mice, Toxicological Research, 30, 83–90, https://doi.org/10.5487/TR.2014.30.2.083, 2014. a
Savadkoohi, M., Pandolfi, M., Reche, C., Niemi, J. V., Mooibroek, D., Titos, G., Green, D. C., Tremper, A. H., Hueglin, C., Liakakou, E., Mihalopoulos, N., Stavroulas, I., Artiñano, B., Coz, E., Alados-Arboledas, L., Beddows, D., Riffault, V., De Brito, J. F., Bastian, S., Baudic, A., Colombi, C., Costabile, F., Chazeau, B., Marchand, N., Gómez-Amo, J. L., Estellés, V., Matos, V., van der Gaag, E., Gille, G., Luoma, K., Manninen, H. E., Norman, M., Silvergren, S., Petit, J.-E., Putaud, J.-P., Rattigan, O. V., Timonen, H., Tuch, T., Merkel, M., Weinhold, K., Vratolis, S., Vasilescu, J., Favez, O., Harrison, R. M., Laj, P., Wiedensohler, A., Hopke, P. K., Petäjä, T., Alastuey, A., and Querol, X.: The variability of mass concentrations and source apportionment analysis of equivalent black carbon across urban Europe, Environ. Int., 178, 108081, https://doi.org/10.1016/j.envint.2023.108081, 2023. a, b, c, d
Savadkoohi, M., Pandolfi, M., Favez, O., Putaud, J.-P., Eleftheriadis, K., Fiebig, M., Hopke, P. K., Laj, P., Wiedensohler, A., Alados-Arboledas, L., Bastian, S., Chazeau, B., María, Á. C., Colombi, C., Costabile, F., Green, D. C., Hueglin, C., Liakakou, E., Luoma, K., Listrani, S., Mihalopoulos, N., Marchand, N., Močnik, G., Niemi, J. V., Ondráček, J., Petit, J.-E., Rattigan, O. V., Reche, C., Timonen, H., Titos, G., Tremper, A. H., Vratolis, S., Vodička, P., Funes, E. Y., Zíková, N., Harrison, R. M., Petäjä, T., Alastuey, A., and Querol, X.: Recommendations for reporting equivalent black carbon (eBC) mass concentrations based on long-term pan-European in-situ observations, Environ. Int., 185, 108553, https://doi.org/10.1016/j.envint.2024.108553, 2024. a, b
Schwarz, J. P., Gao, R. S., Spackman, J. R., Watts, L. A., Thomson, D. S., Fahey, D. W., Ryerson, T. B., Peischl, J., Holloway, J. S., Trainer, M., Frost, G. J., Baynard, T., Lack, D. A., de Gouw, J. A., Warneke, C., and Del Negro, L. A.: Measurement of the mixing state, mass, and optical size of individual black carbon particles in urban and biomass burning emissions, Geophys. Res. Lett., 35, L13810, https://doi.org/10.1029/2008GL033968, 2008. a, b
Scotto, F., Bacco, D., Lasagni, S., Trentini, A., Poluzzi, V., and Vecchi, R.: A multi-year source apportionment of PM2.5 at multiple sites in the southern Po Valley (Italy), Atmos. Pollut. Res., 12, 101192, https://doi.org/10.1016/j.apr.2021.101192, 2021. a
Segersson, D., Eneroth, K., Gidhagen, L., Johansson, C., Omstedt, G., Nylén, A. E., and Forsberg, B.: Health Impact of PM10, PM2.5 and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden, Int. J. Env. Res. Pub. He., 14, 742, https://doi.org/10.3390/ijerph14070742, 2017. a
Singh, V., Ravindra, K., Sahu, L., and Sokhi, R.: Trends of atmospheric black carbon concentration over the United Kingdom, Atmos. Environ., 178, 148–157, https://doi.org/10.1016/j.atmosenv.2018.01.030, 2018. a
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: NCAR Tech. Note NCAR/TN-475+STR: A Description of the Advanced Research WRF Version 3, https://doi.org/10.5065/D68S4MVH, 2008. a
Sokhi, R. S., Moussiopoulos, N., Baklanov, A., Bartzis, J., Coll, I., Finardi, S., Friedrich, R., Geels, C., Grönholm, T., Halenka, T., Ketzel, M., Maragkidou, A., Matthias, V., Moldanova, J., Ntziachristos, L., Schäfer, K., Suppan, P., Tsegas, G., Carmichael, G., Franco, V., Hanna, S., Jalkanen, J.-P., Velders, G. J. M., and Kukkonen, J.: Advances in air quality research – current and emerging challenges, Atmos. Chem. Phys., 22, 4615–4703, https://doi.org/10.5194/acp-22-4615-2022, 2022. a
Song, X., Hu, Y., Ma, Y., Jiang, L., Wang, X., Shi, A., Zhao, J., Liu, Y., Liu, Y., Tang, J., Li, X., Zhang, X., Guo, Y., and Wang, S.: Is short-term and long-term exposure to black carbon associated with cardiovascular and respiratory diseases? A systematic review and meta-analysis based on evidence reliability, BMJ Open, 12, e049516, https://doi.org/10.1136/bmjopen-2021-049516, 2022. a
Stavroulas, I., Pikridas, M., Grivas, G., Bezantakos, S., Liakakou, E., Kalkavouras, P., Veratti, G., Bigi, A., Gerasopoulos, E., Sciare, J., and Mihalopoulos, N.: Field evaluation of miniature absorption photometers in an Eastern Mediterranean urban environment, in: 11th International Aerosol Conference (IAC 2022), Athens, Greece, 4–9 September 2022. a
Stortini, M., Arvani, B., and Deserti, M.: Operational Forecast and Daily Assessment of the Air Quality in Italy: A Copernicus-CAMS Downstream Service, Atmosphere, 11, 447, https://doi.org/10.3390/atmos11050447, 2020. a
Tang, J., Cheng, W., Gao, J., Li, Y., Yao, R., Rothman, N., Lan, Q., Campen, M. J., Zheng, Y., and Leng, S.: Occupational exposure to carbon black nanoparticles increases inflammatory vascular disease risk: an implication of an ex vivo biosensor assay, Part. Fibre Toxicol., 17, 47, https://doi.org/10.1186/s12989-020-00378-8, 2020. a
Team, C. W., Lee, H., and Romero, J. (Eds.): Climate Change 2023: Synthesis Report, Intergovernmental Panel on Climate Change, Geneva, Switzerland, https://doi.org/10.59327/IPCC/AR6-9789291691647, 2023. a
Thorpe, A. and Harrison, R. M.: Sources and properties of non-exhaust particulate matter from road traffic: A review, Sci. Total Environ., 400, 270–282, https://doi.org/10.1016/j.scitotenv.2008.06.007, 2008. a
Thouron, L., Seigneur, C., Kim, Y., Mahé, F., André, M., Lejri, D., Villegas, D., Bruge, B., Chanut, H., and Pellan, Y.: Intercomparison of three modeling approaches for traffic-related road dust resuspension using two experimental data sets, Transport. Res. D-Tr. E., 58, 108–121, https://doi.org/10.1016/j.trd.2017.11.003, 2018. a
Thunis, P., Galmarini, S., Martilli, A., Clappier, A., Andronopoulos, S., Bartzis, J., Vlachogiannis, D., De Ridder, K., Moussiopoulos, N., Sahm, P., Almbauer, R., Sturm, P., Oettl, D., Dierer, S., and Schlünzen, K. H.: An inter-comparison exercise of mesoscale flow models applied to an ideal case simulation, Atmos. Environ., 37, 363–382, https://doi.org/10.1016/S1352-2310(02)00888-9, 2003. a
Thunis, P., Clappier, A., Beekmann, M., Putaud, J. P., Cuvelier, C., Madrazo, J., and de Meij, A.: Non-linear response of PM2.5 to changes in NOx and NH3 emissions in the Po basin (Italy): consequences for air quality plans, Atmos. Chem. Phys., 21, 9309–9327, https://doi.org/10.5194/acp-21-9309-2021, 2021. a
Titos, G., del Águila, A., Cazorla, A., Lyamani, H., Casquero-Vera, J. A., Colombi, C., Cuccia, E., Gianelle, V., Močnik, G., Alastuey, A., Olmo, F. J., and Alados-Arboledas, L.: Spatial and temporal variability of carbonaceous aerosols: Assessing the impact of biomass burning in the urban environment, Sci. Total Environ., 578, 613–625, https://doi.org/10.1016/j.scitotenv.2016.11.007, 2017. a
Tobler, A. K., Skiba, A., Canonaco, F., Močnik, G., Rai, P., Chen, G., Bartyzel, J., Zimnoch, M., Styszko, K., Nęcki, J., Furger, M., Różański, K., Baltensperger, U., Slowik, J. G., and Prevot, A. S. H.: Characterization of non-refractory (NR) PM1 and source apportionment of organic aerosol in Kraków, Poland, Atmos. Chem. Phys., 21, 14893–14906, https://doi.org/10.5194/acp-21-14893-2021, 2021. a
Tominaga, Y. and Stathopoulos, T.: Ten questions concerning modeling of near-field pollutant dispersion in the built environment, Build. Environ., 105, 390–402, https://doi.org/10.1016/j.buildenv.2016.06.027, 2016. a
Travis, K. R., Crawford, J. H., Chen, G., Jordan, C. E., Nault, B. A., Kim, H., Jimenez, J. L., Campuzano-Jost, P., Dibb, J. E., Woo, J.-H., Kim, Y., Zhai, S., Wang, X., McDuffie, E. E., Luo, G., Yu, F., Kim, S., Simpson, I. J., Blake, D. R., Chang, L., and Kim, M. J.: Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ, Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, 2022. a
Troen, I. B. and Mahrt, L.: A simple model of the atmospheric boundary layer; sensitivity to surface evaporation, Bound.-Lay. Meteorol., 37, 129–148, https://doi.org/10.1007/BF00122760, 1986. a, b
Ullrich, B., Wankmüller, R., and Schindlbacher, S.: Inventory Review 2023, Review of emission data reported under the LRTAP Convention, https://www.ceip.at/fileadmin/inhalte/ceip/00_pdf_other/2023/dp188.pdf (last access: 16 September 2024), 2023. a
Van Leer, B.: Towards the ultimate conservative difference scheme. IV. A new approach to numerical convection, J. Comput. Phys., 23, 276–299, https://doi.org/10.1016/0021-9991(77)90095-X, 1977. a
Vecchi, R., Bernardoni, V., Valentini, S., Piazzalunga, A., Fermo, P., and Valli, G.: Assessment of light extinction at a European polluted urban area during wintertime: Impact of PM1 composition and sources, Environ. Pollut., 233, 679–689, https://doi.org/10.1016/j.envpol.2017.10.059, 2018. a
Veratti, G.: Diurnal variability of Black Carbon in Modena: Modeled concentration maps for winter 2020 and 2021, Version v1, Zenodo [video], https://doi.org/10.5281/zenodo.12960786, 2024a. a
Veratti, G.: Advanced Tools for Black Carbon Dispersion Modelling, Version v1, Zenodo [code], https://doi.org/10.5281/zenodo.13255628, 2024b. a
Veratti, G., Fabbi, S., Bigi, A., Lupascu, A., Tinarelli, G., Teggi, S., Brusasca, G., Butler, T. M., and Ghermandi, G.: Towards the coupling of a chemical transport model with a micro-scale Lagrangian modelling system for evaluation of urban NOx levels in a European hotspot, Atmos. Environ., 223, 117285, https://doi.org/10.1016/j.atmosenv.2020.117285, 2020. a, b, c
Veratti, G., Bigi, A., Lupascu, A., Butler, T. M., and Ghermandi, G.: Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach, Atmos. Environ., 261, 118566, https://doi.org/10.1016/j.atmosenv.2021.118566, 2021. a, b, c, d
Veratti, G., Stortini, M., Amorati, R., Bressan, L., Giovannini, G., Bande, S., Bissardella, F., Ghigo, S., Angelino, E., Colombo, L., Fossati, G., Malvestiti, G., Marongiu, A., Dalla Fontana, A., Intini, B., and Pillon, S.: Impact of NOx and NH3 Emission Reduction on Particulate Matter across Po Valley: A LIFE-IP-PREPAIR Study, Atmosphere, 14, 762, https://doi.org/10.3390/atmos14050762, 2023. a, b, c
Veratti, G., Bigi, A., Teggi, S., and Ghermandi, G.: Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows, Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, 2024. a
Virkkula, A., Mäkelä, T., Hillamo, R., Yli-Tuomi, T., Hirsikko, A., Hämeri, K., and Koponen, I. K.: A Simple Procedure for Correcting Loading Effects of Aethalometer Data, J. Air Waste Manage., 57, 1214–1222, https://doi.org/10.3155/1047-3289.57.10.1214, 2007. a
Visser, B., Röhrbein, J., Steigmeier, P., Drinovec, L., Močnik, G., and Weingartner, E.: A single-beam photothermal interferometer for in situ measurements of aerosol light absorption, Atmos. Meas. Tech., 13, 7097–7111, https://doi.org/10.5194/amt-13-7097-2020, 2020. a
Visser, B., Bilal, J., Flöry, N., Wipf, M., Steigmeier, P., Rüggeberg, T., Betschon, F., and Weingartner, E.: Waveguide based passively demodulated photothermal interferometer for light absorption measurements of trace substances, Appl. Optics, 62, 374–384, https://doi.org/10.1364/AO.476868, 2023. a, b
Vitali, L., Cuvelier, K., Piersanti, A., Monteiro, A., Adani, M., Amorati, R., Bartocha, A., D'Ausilio, A., Durka, P., Gama, C., Giovannini, G., Janssen, S., Przybyła, T., Stortini, M., Vranckx, S., and Thunis, P.: A standardized methodology for the validation of air quality forecast applications (F-MQO): lessons learnt from its application across Europe, Geosci. Model Dev., 16, 6029–6047, https://doi.org/10.5194/gmd-16-6029-2023, 2023. a
Wang, C.: A modeling study on the climate impacts of black carbon aerosols, J. Geophys. Res.-Atmos., 109, D03106, https://doi.org/10.1029/2003JD004084, 2004. a
Wang, R., Balkanski, Y., Boucher, O., Ciais, P., Schuster, G. L., Chevallier, F., Samset, B. H., Liu, J., Piao, S., Valari, M., and Tao, S.: Estimation of global black carbon direct radiative forcing and its uncertainty constrained by observations, J. Geophys. Res.-Atmos., 121, 5948–5971, https://doi.org/10.1002/2015JD024326, 2016. a
Weingartner, E., Saathoff, H., Schnaiter, M., Streit, N., Bitnar, B., and Baltensperger, U.: Absorption of light by soot particles: determination of the absorption coefficient by means of aethalometers, J. Aerosol Sci., 34, 1445–1463, https://doi.org/10.1016/S0021-8502(03)00359-8, 2003. a
WHO: Global air quality guidelines: particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide, World Health Organization, ISBN 978-92-4-003422-8, https://iris.who.int/handle/10665/345329 (last access: 16 September 2024), 2021. a
Woo, S.-H., Jang, H., Lee, S.-B., and Lee, S.: Comparison of total PM emissions emitted from electric and internal combustion engine vehicles: An experimental analysis, Sci. Total Environ., 842, 156961, https://doi.org/10.1016/j.scitotenv.2022.156961, 2022. a
Yus-Díez, J., Bernardoni, V., Močnik, G., Alastuey, A., Ciniglia, D., Ivančič, M., Querol, X., Perez, N., Reche, C., Rigler, M., Vecchi, R., Valentini, S., and Pandolfi, M.: Determination of the multiple-scattering correction factor and its cross-sensitivity to scattering and wavelength dependence for different AE33 Aethalometer filter tapes: a multi-instrumental approach, Atmos. Meas. Tech., 14, 6335–6355, https://doi.org/10.5194/amt-14-6335-2021, 2021. a, b
Zhang, L., Gong, S., Padro, J., and Barrie, L.: A size-segregated particle dry deposition scheme for an atmospheric aerosol module, Atmos. Environ., 35, 549–560, https://doi.org/10.1016/S1352-2310(00)00326-5, 2001. a
Zotter, P., Herich, H., Gysel, M., El-Haddad, I., Zhang, Y., Močnik, G., Hüglin, C., Baltensperger, U., Szidat, S., and Prévôt, A. S. H.: Evaluation of the absorption Ångström exponents for traffic and wood burning in the Aethalometer-based source apportionment using radiocarbon measurements of ambient aerosol, Atmos. Chem. Phys., 17, 4229–4249, https://doi.org/10.5194/acp-17-4229-2017, 2017. a
Short summary
In a study of two consecutive winter seasons, we used measurements and modelling tools to identify the levels and sources of black carbon pollution in a medium-sized urban area of the Po Valley, Italy. Our findings show that biomass burning and traffic-related emissions (especially from Euro 4 diesel cars) significantly contribute to BC concentrations. This research offers crucial insights for policymakers and urban planners aiming to improve air quality in cities.
In a study of two consecutive winter seasons, we used measurements and modelling tools to...
Altmetrics
Final-revised paper
Preprint
Similar articles
The impact of uncertainty in black...
Digby et al.
Accounting for the black carbon aging...
Jin et al.
Characterization of brown carbon...
Navarro-Barboza et al.