Articles | Volume 13, issue 22
https://doi.org/10.5194/acp-13-11403-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-13-11403-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
25 Nov 2013
Research article |
| 25 Nov 2013
An inverse modeling method to assess the source term of the Fukushima Nuclear Power Plant accident using gamma dose rate observations
O. Saunier
Institut de Radioprotection et de Sûreté Nucléaire (IRSN), PRP-CRI, SESUC, BMTA, Fontenay-aux-Roses, 92262, France
now at: BERTIN Technologies, Montigny-le-Bretonneux, France
A. Mathieu
Institut de Radioprotection et de Sûreté Nucléaire (IRSN), PRP-CRI, SESUC, BMTA, Fontenay-aux-Roses, 92262, France
D. Didier
Institut de Radioprotection et de Sûreté Nucléaire (IRSN), PRP-CRI, SESUC, BMTA, Fontenay-aux-Roses, 92262, France
M. Tombette
Institut de Radioprotection et de Sûreté Nucléaire (IRSN), PRP-CRI, SESUC, BMTA, Fontenay-aux-Roses, 92262, France
Institut de Radioprotection et de Sûreté Nucléaire (IRSN), PRP-CRI, SESUC, BMTA, Fontenay-aux-Roses, 92262, France
V. Winiarek
CEREA, Joint Laboratory École des Ponts ParisTech and EDF R&D, Champs-sur-Marne, France
INRIA, Paris-Rocquencourt research center, France
M. Bocquet
CEREA, Joint Laboratory École des Ponts ParisTech and EDF R&D, Champs-sur-Marne, France
INRIA, Paris-Rocquencourt research center, France
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Wenbo Yu, Anirbit Ghosh, Tobias Sebastian Finn, Rossella Arcucci, Marc Bocquet, and Sibo Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2025-2836, https://doi.org/10.5194/egusphere-2025-2836, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We introduce the first denoising diffusion model for wildfire spread prediction, a new kind of generative AI model that learns to simulate fires not just as one fixed outcome, but as a range of possible scenarios. This allows us to capture the inherent uncertainty of wildfire dynamics. Our model produces ensembles of forecasts that reflect physically meaningful distributions of where fire might go next.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Charlotte Durand, Tobias Sebastian Finn, Alban Farchi, Marc Bocquet, Julien Brajard, and Laurent Bertino
EGUsphere, https://doi.org/10.5194/egusphere-2024-4028, https://doi.org/10.5194/egusphere-2024-4028, 2025
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This paper presents a four-dimensional variational data assimilation system based on a neural network emulator for sea-ice thickness, learned from neXtSIM simulation outputs. Testing with simulated and real observation retrievals, the system improves forecasts and bias error, performing comparably to operational methods, demonstrating the promise of sea-ice data-driven data assimilation systems.
Simon Driscoll, Alberto Carrassi, Julien Brajard, Laurent Bertino, Einar Ólason, Marc Bocquet, and Amos Lawless
EGUsphere, https://doi.org/10.5194/egusphere-2024-2476, https://doi.org/10.5194/egusphere-2024-2476, 2024
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The formation and evolution of sea ice melt ponds (ponds of melted water) are complex, insufficiently understood and represented in models with considerable uncertainty. These uncertain representations are not traditionally included in climate models potentially causing the known underestimation of sea ice loss in climate models. Our work creates the first observationally based machine learning model of melt ponds that is also a ready and viable candidate to be included in climate models.
Tobias Sebastian Finn, Lucas Disson, Alban Farchi, Marc Bocquet, and Charlotte Durand
Nonlin. Processes Geophys., 31, 409–431, https://doi.org/10.5194/npg-31-409-2024, https://doi.org/10.5194/npg-31-409-2024, 2024
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We train neural networks as denoising diffusion models for state generation in the Lorenz 1963 system and demonstrate that they learn an internal representation of the system. We make use of this learned representation and the pre-trained model in two downstream tasks: surrogate modelling and ensemble generation. For both tasks, the diffusion model can outperform other more common approaches. Thus, we see a potential of representation learning with diffusion models for dynamical systems.
Marc Bocquet, Pierre J. Vanderbecken, Alban Farchi, Joffrey Dumont Le Brazidec, and Yelva Roustan
Nonlin. Processes Geophys., 31, 335–357, https://doi.org/10.5194/npg-31-335-2024, https://doi.org/10.5194/npg-31-335-2024, 2024
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A novel approach, optimal transport data assimilation (OTDA), is introduced to merge DA and OT concepts. By leveraging OT's displacement interpolation in space, it minimises mislocation errors within DA applied to physical fields, such as water vapour, hydrometeors, and chemical species. Its richness and flexibility are showcased through one- and two-dimensional illustrations.
Yumeng Chen, Polly Smith, Alberto Carrassi, Ivo Pasmans, Laurent Bertino, Marc Bocquet, Tobias Sebastian Finn, Pierre Rampal, and Véronique Dansereau
The Cryosphere, 18, 2381–2406, https://doi.org/10.5194/tc-18-2381-2024, https://doi.org/10.5194/tc-18-2381-2024, 2024
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We explore multivariate state and parameter estimation using a data assimilation approach through idealised simulations in a dynamics-only sea-ice model based on novel rheology. We identify various potential issues that can arise in complex operational sea-ice models when model parameters are estimated. Even though further investigation will be needed for such complex sea-ice models, we show possibilities of improving the observed and the unobserved model state forecast and parameter accuracy.
Charlotte Durand, Tobias Sebastian Finn, Alban Farchi, Marc Bocquet, Guillaume Boutin, and Einar Ólason
The Cryosphere, 18, 1791–1815, https://doi.org/10.5194/tc-18-1791-2024, https://doi.org/10.5194/tc-18-1791-2024, 2024
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This paper focuses on predicting Arctic-wide sea-ice thickness using surrogate modeling with deep learning. The model has a predictive power of 12 h up to 6 months. For this forecast horizon, persistence and daily climatology are systematically outperformed, a result of learned thermodynamics and advection. Consequently, surrogate modeling with deep learning proves to be effective at capturing the complex behavior of sea ice.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Tobias Sebastian Finn, Charlotte Durand, Alban Farchi, Marc Bocquet, Yumeng Chen, Alberto Carrassi, and Véronique Dansereau
The Cryosphere, 17, 2965–2991, https://doi.org/10.5194/tc-17-2965-2023, https://doi.org/10.5194/tc-17-2965-2023, 2023
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We combine deep learning with a regional sea-ice model to correct model errors in the sea-ice dynamics of low-resolution forecasts towards high-resolution simulations. The combined model improves the forecast by up to 75 % and thereby surpasses the performance of persistence. As the error connection can additionally be used to analyse the shortcomings of the forecasts, this study highlights the potential of combined modelling for short-term sea-ice forecasting.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, https://doi.org/10.5194/gmd-16-3997-2023, 2023
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Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, https://doi.org/10.5194/amt-16-1745-2023, 2023
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Instruments dedicated to monitoring atmospheric gaseous compounds from space will provide images of urban-scale plumes. We discuss here the use of new metrics to compare observed plumes with model predictions that will be less sensitive to meteorology uncertainties. We have evaluated our metrics on diverse plumes and shown that by eliminating some aspects of the discrepancies, they are indeed less sensitive to meteorological variations.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, https://doi.org/10.5194/gmd-16-1039-2023, 2023
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When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima Daiichi.
Here, we propose Bayesian inverse modelling methods and the reversible-jump Markov chain Monte Carlo technique, which allows one to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
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Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Arnaud Quérel, Khadija Meddouni, Denis Quélo, Thierry Doursout, and Sonia Chuzel
Adv. Geosci., 57, 109–124, https://doi.org/10.5194/adgeo-57-109-2022, https://doi.org/10.5194/adgeo-57-109-2022, 2022
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A radon long-range atmospheric transport modelling is set up from soil (exhalation) to soil (deposition of its progeny) and the consequent ambient gamma dose rate is evaluated. The whole is statistically assessed in regards to more than 15 000 gamma dose rate peaks. The model has proven to be of the correct magnitude, with room for substantial improvements. It may be used to validate an atmospheric transport modelling and to test any exhalation maps of radon at continental scale.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Atmos. Chem. Phys., 21, 13247–13267, https://doi.org/10.5194/acp-21-13247-2021, https://doi.org/10.5194/acp-21-13247-2021, 2021
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The assessment of the environmental consequences of a radionuclide release depends on the estimation of its source. This paper aims to develop inverse Bayesian methods which combine transport models with measurements, in order to reconstruct the ensemble of possible sources.
Three methods to quantify uncertainties based on the definition of probability distributions and the physical models are proposed and evaluated for the case of 106Ru releases over Europe in 2017.
Colin Grudzien, Marc Bocquet, and Alberto Carrassi
Geosci. Model Dev., 13, 1903–1924, https://doi.org/10.5194/gmd-13-1903-2020, https://doi.org/10.5194/gmd-13-1903-2020, 2020
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All scales of a dynamical physical process cannot be resolved accurately in a multiscale, geophysical model. The behavior of unresolved scales of motion are often parametrized by a random process to emulate their effects on the dynamically resolved variables, and this results in a random–dynamical model. We study how the choice of a numerical discretization of such a system affects the model forecast and estimation statistics, when the random–dynamical model is unbiased in its parametrization.
Thomas Lauvaux, Liza I. Díaz-Isaac, Marc Bocquet, and Nicolas Bousserez
Atmos. Chem. Phys., 19, 12007–12024, https://doi.org/10.5194/acp-19-12007-2019, https://doi.org/10.5194/acp-19-12007-2019, 2019
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A small-size ensemble of mesoscale simulations has been filtered to characterize the spatial structures of transport errors in atmospheric CO2 mixing ratios. The extracted error structures in in situ and column CO2 show similar length scales compared to other meteorological variables, including seasonality, which could be used as proxies in regional inversion systems.
Marc Bocquet, Julien Brajard, Alberto Carrassi, and Laurent Bertino
Nonlin. Processes Geophys., 26, 143–162, https://doi.org/10.5194/npg-26-143-2019, https://doi.org/10.5194/npg-26-143-2019, 2019
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This paper describes an innovative way to use data assimilation to infer the dynamics of a physical system from its observation only. The method can operate with noisy and partial observation of the physical system. It acts as a deep learning technique specialised to dynamical models without the need for machine learning tools. The method is successfully tested on chaotic dynamical systems: the Lorenz-63, Lorenz-96, and Kuramoto–Sivashinski models and a two-scale Lorenz model.
Julien Brajard, Alberto Carrassi, Marc Bocquet, and Laurent Bertino
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-136, https://doi.org/10.5194/gmd-2019-136, 2019
Revised manuscript not accepted
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We explore the possibility of combining data assimilation with machine learning. We introduce a new hybrid method for a two-fold scope: (i) emulating hidden, possibly chaotic, dynamics and (ii) predicting its future states. Numerical experiments have been carried out using the chaotic Lorenz 96 model, proving both the convergence of the hybrid method and its statistical skills including short-term forecasting and emulation of the long-term dynamics.
Liza I. Díaz-Isaac, Thomas Lauvaux, Marc Bocquet, and Kenneth J. Davis
Atmos. Chem. Phys., 19, 5695–5718, https://doi.org/10.5194/acp-19-5695-2019, https://doi.org/10.5194/acp-19-5695-2019, 2019
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We demonstrate that transport model errors, one of the main contributors to the uncertainty in regional CO2 inversions, can be represented by a small-size ensemble carefully calibrated with meteorological data. Our results also confirm transport model errors represent a significant fraction of the model–data mismatch in CO2 mole fractions and hence in regional inverse CO2 fluxes.
Alban Farchi and Marc Bocquet
Nonlin. Processes Geophys., 25, 765–807, https://doi.org/10.5194/npg-25-765-2018, https://doi.org/10.5194/npg-25-765-2018, 2018
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Data assimilation looks for an optimal way to learn from observations of a dynamical system to improve the quality of its predictions. The goal is to filter out the noise (both observation and model noise) to retrieve the true signal. Among all possible methods, particle filters are promising; the method is fast and elegant, and it allows for a Bayesian analysis. In this review paper, we discuss implementation techniques for (local) particle filters in high-dimensional systems.
Colin Grudzien, Alberto Carrassi, and Marc Bocquet
Nonlin. Processes Geophys., 25, 633–648, https://doi.org/10.5194/npg-25-633-2018, https://doi.org/10.5194/npg-25-633-2018, 2018
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Using the framework Lyapunov vectors, we analyze the asymptotic properties of ensemble based Kalman filters and how these are influenced by dynamical chaos, especially in the context of random model errors and small ensemble sizes. Particularly, we show a novel derivation of the evolution of forecast uncertainty for ensemble-based Kalman filters with weakly-nonlinear error growth, and discuss its impact for filter design in geophysical models.
Olivier Pannekoucke, Marc Bocquet, and Richard Ménard
Nonlin. Processes Geophys., 25, 481–495, https://doi.org/10.5194/npg-25-481-2018, https://doi.org/10.5194/npg-25-481-2018, 2018
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The forecast of weather prediction uncertainty is a real challenge and is crucial for risk management. However, uncertainty prediction is beyond the capacity of supercomputers, and improvements of the technology may not solve this issue. A new uncertainty prediction method is introduced which takes advantage of fluid equations to predict simple quantities which approximate real uncertainty but at a low numerical cost. A proof of concept is shown by an academic model derived from fluid dynamics.
Anthony Fillion, Marc Bocquet, and Serge Gratton
Nonlin. Processes Geophys., 25, 315–334, https://doi.org/10.5194/npg-25-315-2018, https://doi.org/10.5194/npg-25-315-2018, 2018
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This study generalizes a paper by Pires et al. (1996) to state-of-the-art data assimilation techniques, such as the iterative ensemble Kalman smoother (IEnKS). We show that the longer the time window over which observations are assimilated, the better the accuracy of the IEnKS. Beyond a critical time length that we estimate, we show that this accuracy finally degrades. We show that the use of the quasi-static minimizations but generalized to the IEnKS yields a significantly improved accuracy.
J.-M. Haussaire and M. Bocquet
Geosci. Model Dev., 9, 393–412, https://doi.org/10.5194/gmd-9-393-2016, https://doi.org/10.5194/gmd-9-393-2016, 2016
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The focus is on the development of low-order models of atmospheric transport and chemistry and their use for data assimilation purposes. A new low-order coupled chemistry meteorology model is developed. It consists of the Lorenz40-variable model used as a wind field coupled with a simple ozone photochemistry module. Advanced ensemble variational methods are applied to this model to obtain insights on the use of data assimilation with coupled models, in an offline mode or in an online mode.
M. Bocquet, P. N. Raanes, and A. Hannart
Nonlin. Processes Geophys., 22, 645–662, https://doi.org/10.5194/npg-22-645-2015, https://doi.org/10.5194/npg-22-645-2015, 2015
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The popular data assimilation technique known as the ensemble Kalman filter (EnKF) suffers from sampling errors due to the limited size of the ensemble. This deficiency is usually cured by inflating the sampled error covariances and by using localization. This paper further develops and discusses the finite-size EnKF, or EnKF-N, a variant of the EnKF that does not require inflation. It expands the use of the EnKF-N to a wider range of dynamical regimes.
M. Bocquet, H. Elbern, H. Eskes, M. Hirtl, R. Žabkar, G. R. Carmichael, J. Flemming, A. Inness, M. Pagowski, J. L. Pérez Camaño, P. E. Saide, R. San Jose, M. Sofiev, J. Vira, A. Baklanov, C. Carnevale, G. Grell, and C. Seigneur
Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, https://doi.org/10.5194/acp-15-5325-2015, 2015
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Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of concentrations, and perform inverse modeling. Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. We review here the current status of data assimilation in atmospheric chemistry models, with a particular focus on future prospects for data assimilation in CCMM.
Y. Wang, K. N. Sartelet, M. Bocquet, P. Chazette, M. Sicard, G. D'Amico, J. F. Léon, L. Alados-Arboledas, A. Amodeo, P. Augustin, J. Bach, L. Belegante, I. Binietoglou, X. Bush, A. Comerón, H. Delbarre, D. García-Vízcaino, J. L. Guerrero-Rascado, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, F. Molero, N. Montoux, A. Muñoz, C. Muñoz, D. Nicolae, A. Papayannis, G. Pappalardo, J. Preissler, V. Rizi, F. Rocadenbosch, K. Sellegri, F. Wagner, and F. Dulac
Atmos. Chem. Phys., 14, 12031–12053, https://doi.org/10.5194/acp-14-12031-2014, https://doi.org/10.5194/acp-14-12031-2014, 2014
Y. Wang, K. N. Sartelet, M. Bocquet, and P. Chazette
Atmos. Chem. Phys., 14, 3511–3532, https://doi.org/10.5194/acp-14-3511-2014, https://doi.org/10.5194/acp-14-3511-2014, 2014
M. Bocquet and P. Sakov
Nonlin. Processes Geophys., 20, 803–818, https://doi.org/10.5194/npg-20-803-2013, https://doi.org/10.5194/npg-20-803-2013, 2013
M. R. Koohkan, M. Bocquet, Y. Roustan, Y. Kim, and C. Seigneur
Atmos. Chem. Phys., 13, 5887–5905, https://doi.org/10.5194/acp-13-5887-2013, https://doi.org/10.5194/acp-13-5887-2013, 2013
Y. Wang, K. N. Sartelet, M. Bocquet, and P. Chazette
Atmos. Chem. Phys., 13, 269–283, https://doi.org/10.5194/acp-13-269-2013, https://doi.org/10.5194/acp-13-269-2013, 2013
Related subject area
Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Regional variability of aerosol impacts on clouds and radiation in global kilometer-scale simulations
A novel method to quantify the uncertainty contribution of aerosol–radiation interaction factors
Exploring the aerosol activation properties in coastal shallow convection using cloud- and particle-resolving models
Machine-learning-assisted inference of the particle charge fraction and the ion-induced nucleation rates during new particle formation events
Modeling CMAQ dry deposition treatment over the western Pacific: a distinct characteristic of mineral dust and anthropogenic aerosols
Impact of post-monsoon crop residue burning on PM2.5 over northern India: optimizing emissions using a high-density in situ surface observation network
Modeling simulation of aerosol light absorption over the Beijing–Tianjin–Hebei region: the impact of mixing state and aging processes
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How to trace the origins of short-lived atmospheric species: an Arctic example
Dust-producing weather patterns of the North American Great Plains
High-resolution air quality maps for Bucharest using a mixed-effects modeling framework
Interdecadal shift in the impact of winter land-sea thermal contrasts on following spring transcontinental dust transport pathways in North Africa
Anthropogenic and Natural Causes for the Interannual Variation of PM2.5 in East Asia During Summer Monsoon Periods From 2008 to 2018
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An uncertain future for the climate and health impacts of anthropogenic aerosols in Africa
The impact of uncertainty in black carbon's refractive index on simulated optical depth and radiative forcing
Gas-phase collision rate enhancement factors for acid-base clusters up to 2 nm in diameter from atomistic simulation and the interacting hard sphere model
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
Direct radiative forcing of light-absorbing carbonaceous aerosol and the influencing factors over China
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
Modeling urban pollutant transport at multi-resolutions: Impacts of turbulent mixing
Homogeneous ice nucleation in adsorbed water films: A theoretical approach
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
Impact of Topographic Wind Conditions on Dust Particle Size Distribution: Insights from a Regional Dust Reanalysis Dataset
Uncovering the Impact of Urban Functional Zones on Air Quality in China
Seasonal differences in observed versus modeled new particle formation over boreal regions
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
Radiative and climate effects of aerosol scattering in long-wave radiation based on global climate modeling
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
Strong inter-model differences and biases in CMIP6 simulations of PM2.5, aerosol optical depth, and precipitation over Africa
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)
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
Ross J. Herbert, Andrew I. L. Williams, Philipp Weiss, Duncan Watson-Parris, Elisabeth Dingley, Daniel Klocke, and Philip Stier
Atmos. Chem. Phys., 25, 7789–7814, https://doi.org/10.5194/acp-25-7789-2025, https://doi.org/10.5194/acp-25-7789-2025, 2025
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Clouds exist at scales that climate models struggle to represent, limiting our knowledge of how climate change may impact clouds. Here we use a new kilometer-scale global model representing an important step towards the necessary scale. We focus on how aerosol particles modify clouds, radiation, and precipitation. We find the magnitude and manner of responses tend to vary from region to region, highlighting the potential of global kilometer-scale simulations and a need to represent aerosols in climate models.
Bishuo He and Chunsheng Zhao
Atmos. Chem. Phys., 25, 7765–7776, https://doi.org/10.5194/acp-25-7765-2025, https://doi.org/10.5194/acp-25-7765-2025, 2025
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Factor uncertainty analysis helps us understand the impacts of factors on complex systems. Traditional methods have many limitations. This study introduces a new method to measure how each factor contributes to uncertainty. It gains insights into the role of each variable and works for all multi-factor systems. As an application, we analyzed how aerosols affect solar radiation and identified the key factors. These analyses can improve our understanding of the role of aerosols in climate change.
Ge Yu, Yueya Wang, Zhe Wang, and Xiaoming Shi
Atmos. Chem. Phys., 25, 7527–7542, https://doi.org/10.5194/acp-25-7527-2025, https://doi.org/10.5194/acp-25-7527-2025, 2025
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Studying the cloud-forming capacity of aerosols is crucial in climate research. The PartMC model can provide detailed particle information and help these studies. This model is integrated with the ideal meteorological Cloud Model 1 (CM1) to simulate the aerosols at cloud-forming locations. Significant changes are revealed in the hygroscopicity distribution of aerosols within ascending air parcels. Additionally, different ascent times also affect aerosol aging processes.
Pan Wang, Yue Zhao, Jiandong Wang, Veli-Matti Kerminen, Jingkun Jiang, and Chenxi Li
Atmos. Chem. Phys., 25, 7431–7446, https://doi.org/10.5194/acp-25-7431-2025, https://doi.org/10.5194/acp-25-7431-2025, 2025
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We developed a numerical model to investigate the evolution of the charge state of newly formed atmospheric particles. Based on the simulation results, we successfully employed neural networks to predict particle charge states and estimate ion-induced nucleation rates. This study provides new insights into the dynamics of particle charging and introduces advanced methods for evaluating ion-induced nucleation in atmospheric research.
Steven Soon-Kai Kong, Joshua S. Fu, Neng-Huei Lin, Guey-Rong Sheu, and Wei-Syun Huang
Atmos. Chem. Phys., 25, 7245–7268, https://doi.org/10.5194/acp-25-7245-2025, https://doi.org/10.5194/acp-25-7245-2025, 2025
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The accuracy of the chemical transport model, a key focus of our research, is strongly dependent on the dry deposition parameterization. Our findings show that the refined CMAQ dust model correlated well with ground-based and high-altitude in situ measurements by implementing the suggested dry deposition schemes. Furthermore, we reveal the mixing state of two types of aerosols at the upper level, a finding supported by both the optimized model and measurements.
Mizuo Kajino, Kentaro Ishijima, Joseph Ching, Kazuyo Yamaji, Rio Ishikawa, Tomoki Kajikawa, Tanbir Singh, Tomoki Nakayama, Yutaka Matsumi, Koyo Kojima, Taisei Machida, Takashi Maki, Prabir K. Patra, and Sachiko Hayashida
Atmos. Chem. Phys., 25, 7137–7160, https://doi.org/10.5194/acp-25-7137-2025, https://doi.org/10.5194/acp-25-7137-2025, 2025
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Air pollution in Delhi during the post-monsoon period is severe, and association with intensive crop residue burning (CRB) over Punjab state has attracted attention. However, the relationship has been unclear as the CRB emissions conventionally derived from satellites were underestimated due to clouds or thick smoke/haze over the region. We evaluated the impact of CRB on PM2.5 to be about 50 %, based on a combination of numerical modeling and an observation network using low-cost sensors we installed.
Huiyun Du, Jie Li, Xueshun Chen, Gabriele Curci, Fangqun Yu, Yele Sun, Xu Dao, Song Guo, Zhe Wang, Wenyi Yang, Lianfang Wei, and Zifa Wang
Atmos. Chem. Phys., 25, 5665–5681, https://doi.org/10.5194/acp-25-5665-2025, https://doi.org/10.5194/acp-25-5665-2025, 2025
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Inadequate consideration of mixing states and coatings on black carbon (BC) hinders aerosol radiation forcing quantification. Core–shell mixing aligns well with observations, but partial internal mixing is a more realistic representation. We used a microphysics module to determine the fraction of embedded BC and coating aerosols, constraining the mixing state. This reduced absorption enhancement by 30 %–43 % in northern China, offering insights into BC's radiative effects.
Zhixin Xue, Nair Udaysankar, and Sundar A. Christopher
Atmos. Chem. Phys., 25, 5497–5517, https://doi.org/10.5194/acp-25-5497-2025, https://doi.org/10.5194/acp-25-5497-2025, 2025
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Canadian wildfires in August 2018 significantly increased surface air pollution across the United States (US) – by up to 69 % in some areas. Using model, satellite, and ground measurements, the study highlights how weather patterns and long-range smoke transport drive pollution. The northwestern US was most affected by Canadian wildfire smoke, while the northeastern US experienced the least impact. These findings indicate the growing concern that wildfire smoke poses to air quality across the US.
Anderson Da Silva, Louis Marelle, Jean-Christophe Raut, Yvette Gramlich, Karolina Siegel, Sophie L. Haslett, Claudia Mohr, and Jennie L. Thomas
Atmos. Chem. Phys., 25, 5331–5354, https://doi.org/10.5194/acp-25-5331-2025, https://doi.org/10.5194/acp-25-5331-2025, 2025
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Particle sources in polar climates are unclear, affecting climate representation in models. This study introduces an evaluated method for tracking particles with backward modeling. Tests on simulated particles allowed us to show that traditional detection methods often misidentify sources. An improved method that accurately traces the origins of aerosol particles in the Arctic is presented. The study recommends using this enhanced method for better source identification of atmospheric species.
Stuart Evans
Atmos. Chem. Phys., 25, 4833–4845, https://doi.org/10.5194/acp-25-4833-2025, https://doi.org/10.5194/acp-25-4833-2025, 2025
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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 southwestern 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.
Camelia Talianu, Jeni Vasilescu, Doina Nicolae, Alexandru Ilie, Andrei Dandocsi, Anca Nemuc, and Livio Belegante
Atmos. Chem. Phys., 25, 4639–4654, https://doi.org/10.5194/acp-25-4639-2025, https://doi.org/10.5194/acp-25-4639-2025, 2025
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For Bucharest, Romania's capital, mobile measurements during two intensive campaigns and mixed-effect LUR (land-use regression) models to derive seasonal maps of near-surface PM10, NO2 and UFPs (ultrafine particles) have successfully been used. The model's performance was evaluated, demonstrating its potential for high-resolution mapping in other cities with well-characterized urban structures and diverse in situ monitoring stations.
Qi Wen, Yan Li, Mengying Du, Wenjun Song, Linbo Wei, Zhilan Wang, and Xu Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-826, https://doi.org/10.5194/egusphere-2025-826, 2025
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We find that, through an interdecadal phase-locking effect of sea-land thermal forcing-North Atlantic Oscillation-Westerly Jet coupling, springtime dust from North Africa is more likely to be transported eastwards (extending into North America) after the late 1990s, whereas before that time westward transport paths for dust were more frequent. Subject to thermal forcing, wind speed and drought contribute to dust emissions in the two periods, respectively.
Danyang Ma, Min Xie, Huan He, Tijian Wang, Mengzhu Xi, Lingyun Feng, Shuxian Zhang, and Shitong Chen
EGUsphere, https://doi.org/10.5194/egusphere-2025-10, https://doi.org/10.5194/egusphere-2025-10, 2025
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The PM2.5 concentration in China underwent significant changes in 2013. We examined the underlying causes from three perspectives: anthropogenic pollutant emissions, meteorological conditions, and CO2 concentration variations. Our study highlighted the importance of considering the role of CO2 on vegetation when predicting PM2.5 concentrations and developing corresponding control strategies.
Jiangtao Li, Xingqin An, Zhaobin Sun, Caihua Ye, Qing Hou, Yuxin Zhao, and Zhe Liu
Atmos. Chem. Phys., 25, 3583–3602, https://doi.org/10.5194/acp-25-3583-2025, https://doi.org/10.5194/acp-25-3583-2025, 2025
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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 10 August, peaks around 30 August and ends by 25 September, lasting about 45 d. Over time, annual pollen emissions exhibit significant fluctuations and a downward trend.
Joe Adabouk Amooli, Marianne T. Lund, Sourangsu Chowdhury, Gunnar Myhre, Ane N. Johansen, Bjørn H. Samset, and Daniel M. Westervelt
EGUsphere, https://doi.org/10.5194/egusphere-2025-948, https://doi.org/10.5194/egusphere-2025-948, 2025
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We analyze various projections of African aerosol emissions and their potential impacts on climate and public health. We find that future emissions vary widely across emission projections, with differences in sectoral emission distributions. Using the Oslo chemical transport model, we show that air pollution exposure in some regions of Africa could increase significantly by 2050, increasing pollution-related deaths, with most scenarios projecting aerosol-induced warming over sub-Saharan Africa.
Ruth A. R. Digby, Knut von Salzen, Adam H. Monahan, Nathan P. Gillett, and Jiangnan Li
Atmos. Chem. Phys., 25, 3109–3130, https://doi.org/10.5194/acp-25-3109-2025, https://doi.org/10.5194/acp-25-3109-2025, 2025
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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.
Valtteri Tikkanen, Huan Yang, Hanna Vehkamäki, and Bernhard Reischl
EGUsphere, https://doi.org/10.5194/egusphere-2025-507, https://doi.org/10.5194/egusphere-2025-507, 2025
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Collisions of neutral molecules and clusters is the prevalent pathway in atmospheric new particle formation. In heavily polluted urban areas, where clusters are formed rapidly and in large number, cluster-cluster collisions also become relevant. We calculate cluster-cluster collision rates from atomistic molecular dynamics simulations and an interacting hard sphere model. Not accounting for long-range attractive interactions underestimates collision and particle formation rates significantly.
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
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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
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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
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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
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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
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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
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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
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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.
Shuangqin Yang, Yusi Liu, Li Chen, Nan Cao, Jing Wang, and Shuang Gao
EGUsphere, https://doi.org/10.5194/egusphere-2024-3705, https://doi.org/10.5194/egusphere-2024-3705, 2025
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Black carbon, primary brown carbon, and secondary brown carbon are the leading light-absorbing carbonaceous aerosols (LACs) that contribute significantly to climate change. We modified the GEOS-Chem model to simulate the climate change by LACs based on local emission inventory, and explored the impacts of LACs properties and atmospheric variables on the corresponding DRFs in seven regions of China. The study confirms the warming effect of LACs and deepens our knowledge of their climatic effects.
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
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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
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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
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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
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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.
Zining Yang, Qiuyan Du, Qike Yang, Chun Zhao, Gudongze Li, Zihan Xia, Mingyue Xu, Renmin Yuan, Yubin Li, Kaihui Xia, Jun Gu, and Jiawang Feng
EGUsphere, https://doi.org/10.5194/egusphere-2024-3890, https://doi.org/10.5194/egusphere-2024-3890, 2025
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This study investigates the impact of turbulent mixing on black carbon (BC) concentrations in urban areas using WRF-Chem at 25, 5, and 1 km resolutions. Significant variations in BC and turbulent mixing occur mainly at night. Higher resolutions reduce BC overestimation due to enhanced PBL mixing coefficients and vertical wind fluxes. Small-scale eddies at higher resolutions increase BC lifetime and column concentrations. Land use and terrain variations across multi-resolutions affect PBL mixing.
Ari Laaksonen, Golnaz Roudsari, Ana A. Piedehierro, and André Welti
EGUsphere, https://doi.org/10.5194/egusphere-2024-4095, https://doi.org/10.5194/egusphere-2024-4095, 2025
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The mechanisms of ice nucleation at temperatures below 235 K have remained unclear for the past century. We suggest that ice nucleation is caused by the freezing of water adsorbed on aerosol surfaces. To test this hypothesis, we derived theoretical equations to predict the exact atmospheric conditions under which ice nucleation occurs. Our predictions agree well with experiments. The new theory thus provides a basis for an improved description of ice nucleation in the atmosphere.
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
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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
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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.
Xinyue Huang, Wenyu Gao, and Hosein Foroutan
EGUsphere, https://doi.org/10.5194/egusphere-2024-3076, https://doi.org/10.5194/egusphere-2024-3076, 2024
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This study investigates the relationship between wind-blown dust aerosols size distribution and wind conditions over topography at a regional scale, utilizing 10 years of dust reanalysis data. Linear regression models suggest that higher wind speeds and steeper land slopes, particularly under uphill winds, are associated with increased fractions of coarser dust particles. Moreover, these positive correlations weaken during summer and afternoon events, likely related to the haboob storms.
Lulu Yuan, Wenchao Han, Jiachen Meng, Yang Wang, Haojie Yu, and Wenze Li
EGUsphere, https://doi.org/10.5194/egusphere-2024-3350, https://doi.org/10.5194/egusphere-2024-3350, 2024
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This study utilizes multi-source data to reveal the impact of various urban functional zones in China on the spatial distribution of pollutants. The findings indicate that the residential and commercial zones see notable air quality gains, but the improvement of air quality in the transportation zone is the least considerable. Moreover, the industrial zone has the most seasonal air quality variation. Therefore, air pollution prevention policies should consider differences in functional zones.
Carl Svenhag, Pontus Roldin, Tinja Olenius, Robin Wollesen de Jonge, Sara Blichner, Daniel Yazgi, and Moa Sporre
EGUsphere, https://doi.org/10.5194/egusphere-2024-3626, https://doi.org/10.5194/egusphere-2024-3626, 2024
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This study investigates the model representation of how particles are formed and grow in the atmosphere. Using modeled and observed data from two boreal forest stations in 2018, we identify key factors for NPF to improve particle-climate predictions in the global EC-Earth3 model. Comparisons with the detailed ADCHEM model show that adding ammonia improves particle growth predictions, though EC-Earth3 still highly underestimates the number of particles during warmer months.
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
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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
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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
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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
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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.
Thomas Drugé, Pierre Nabat, Martine Michou, and Marc Mallet
EGUsphere, https://doi.org/10.5194/egusphere-2024-3659, https://doi.org/10.5194/egusphere-2024-3659, 2024
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Aerosol scattering in long-wave radiation is often neglected in climate models. In this study, we analyze its impact through a physical modeling of this process in the CNRM ARPEGE-Climat model. It mainly leads to surface LW radiation increases across Sahara, Sahel and Arabian Peninsula, resulting in daily minimum near-surface temperature rises. Other changes in atmospheric fields are also simulated.
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
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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
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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
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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
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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.
Catherine Anne Toolan, Joe Adabouk Amooli, Laura J. Wilcox, Bjørn H. Samset, Andrew G. Turner, and Daniel M. Westervelt
EGUsphere, https://doi.org/10.5194/egusphere-2024-3057, https://doi.org/10.5194/egusphere-2024-3057, 2024
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Our research explores how well air pollution and rainfall patterns in Africa are represented in current climate models, by comparing model data to observations from 1981 to 2023. While most models capture seasonal air quality changes well, they struggle to replicate the distribution of non-dust pollutants and certain rainfall patterns, especially over east Africa. Improving these models is crucial for better climate predictions and preparing for future risks.
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
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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
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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
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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.
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
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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.
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