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.
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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Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-156, https://doi.org/10.5194/gmd-2024-156, 2024
Preprint under review for GMD
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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 image, 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.
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)
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
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
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
Decomposing the effective radiative forcing of anthropogenic aerosols based on CMIP6 Earth system models
Modeling impacts of dust mineralogy on fast climate response
Representation of iron aerosol size distributions is critical in evaluating atmospheric soluble iron input to the ocean
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
Multi-model effective radiative forcing of the 2020 sulphur cap for shipping
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
Warming effects of reduced sulfur emissions from shipping
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
Predicting Hygroscopic Growth of Organosulfur Aerosol Particles Using COSMOtherm
Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data
Simulated phase state and viscosity of secondary organic aerosols over China
Comparing the simulated influence of biomass burning plumes on low-level clouds over the southeastern Atlantic under varying smoke conditions
Improved simulations of biomass burning aerosol optical properties and lifetimes in the NASA GEOS Model during the ORACLES-I campaign
Retrieval of refractive index and water content for the coating materials of aged black carbon aerosol based on optical properties: a theoretical analysis
Revealing dominant patterns of aerosols regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations
Sharp increase in Saharan dust intrusions over the western Euro-Mediterranean in February–March 2020–2022 and associated atmospheric circulation
Temporal and spatial variations in dust activity in Australia based on remote sensing and reanalysis datasets
Sensitivity of global direct aerosol shortwave radiative forcing to uncertainties in aerosol optical properties
Molecular-level study on the role of methanesulfonic acid in iodine oxoacid nucleation
Improving estimation of a record breaking East Asian dust storm emission with lagged aerosol Ångström Exponent observations
Regional to global distributions, trends, and drivers of biogenic volatile organic compound emission from 2001 to 2020
Impacts of ice-nucleating particles on cirrus clouds and radiation derived from global model simulations with MADE3 in EMAC
Seasonal characteristics of emission, distribution, and radiative effect of marine organic aerosols over the western Pacific Ocean: an investigation with a coupled regional climate aerosol model
Fire–precipitation interactions amplify the quasi-biennial variability in fires over southern Mexico and Central America
Improved estimates of smoke exposure during Australia fire seasons: importance of quantifying plume injection heights
New particle formation induced by anthropogenic–biogenic interactions on the southeastern Tibetan Plateau
Investigation of observed dust trends over the Middle East region in NASA Goddard Earth Observing System (GEOS) model simulations
Impact of Biomass Burning Aerosols (BBA) on the tropical African climate in an ocean-atmosphere-aerosols coupled climate model
A new process-based and scale-aware desert dust emission scheme for global climate models – Part II: Evaluation in the Community Earth System Model version 2 (CESM2)
How well do Earth system models reproduce the observed aerosol response to rapid emission reductions? A COVID-19 case study
Global modeling of aerosol nucleation with an explicit chemical mechanism for highly oxygenated organic molecules (HOMs)
Observationally constrained analysis of sulfur cycle in the marine atmosphere with NASA ATom measurements and AeroCom model simulations
Impact of acidity and surface-modulated acid dissociation on cloud response to organic aerosol
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.
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
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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.
Giorgio Veratti, Alessandro Bigi, Michele Stortini, Sergio Teggi, and Grazia Ghermandi
Atmos. Chem. Phys., 24, 10475–10512, https://doi.org/10.5194/acp-24-10475-2024, https://doi.org/10.5194/acp-24-10475-2024, 2024
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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.
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
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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
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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
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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
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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
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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
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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.
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
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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
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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.
Mingxu Liu, Hitoshi Matsui, Douglas Hamilton, Sagar Rathod, Kara Lamb, and Natalie Mahowald
EGUsphere, https://doi.org/10.5194/egusphere-2024-1454, https://doi.org/10.5194/egusphere-2024-1454, 2024
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Atmospheric aerosol deposition provides iron to promote marine primary production, yet its amount remains highly uncertain. This study demonstrates that iron-containing particle size at emission is a critical factor in regulating their input to open oceans by performing global aerosol simulations. Further observational constraints on this are needed to reduce modelling uncertainties.
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
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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
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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
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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
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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
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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
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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.
Ragnhild Bieltvedt Skeie, Rachael Byrom, Øivind Hodnebrog, Caroline Jouan, and Gunnar Myhre
EGUsphere, https://doi.org/10.5194/egusphere-2024-1394, https://doi.org/10.5194/egusphere-2024-1394, 2024
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In 2020 new regulations by the International Maritime Organization of sulphur emissions came into force that reduced emissions of SO2 from the shipping sector by approximately 80 %. In this study, we use multiple models to calculate by how much the Earth energy balance changed due to the emission reduction, 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 two to three years.
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
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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
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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.
Masaru Yoshioka, Daniel P. Grosvenor, Ben B. B. Booth, Colin P. Morice, and Kenneth S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2024-1428, https://doi.org/10.5194/egusphere-2024-1428, 2024
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Sulfur emissions from shipping has been reduced by about 80 % as a result of the new regulation introduced in 2020. This has reduced aerosol in the atmosphere and its cooling effect through interactions with clouds. As a result, our coupled climate model simulations predict a global warming of 0.04 K averaged over three decades, potentially surpassing the Paris target of 1.5 K or contributing to recent temperature spikes, particularly notable in the Arctic with a mean warming of 0.15 K.
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
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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
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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
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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.
Zijun Li, Angela Buchholz, and Noora Hyttinen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1182, https://doi.org/10.5194/egusphere-2024-1182, 2024
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Evaluating organosulfur (OS) hygroscopicity is important for assessing the 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 AS. A good agreement was observed between their model-estimated and experimental HGFs.
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
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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.
Zhiqiang Zhang, Ying Li, Haiyan Ran, Junling An, Yu Qu, Wei Zhou, Weiqi Xu, Weiwei Hu, Hongbin Xie, Zifa Wang, Yele Sun, and Manabu Shiraiwa
Atmos. Chem. Phys., 24, 4809–4826, https://doi.org/10.5194/acp-24-4809-2024, https://doi.org/10.5194/acp-24-4809-2024, 2024
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Secondary organic aerosols (SOAs) can exist in liquid, semi-solid, or amorphous solid states, which are rarely accounted for in current chemical transport models. We predict the phase state of SOA particles over China and find that in northwestern China SOA particles are mostly highly viscous or glassy solid. Our results indicate that the particle phase state should be considered in SOA formation in chemical transport models for more accurate prediction of SOA mass concentrations.
Alejandro Baró Pérez, Michael S. Diamond, Frida A.-M. Bender, Abhay Devasthale, Matthias Schwarz, Julien Savre, Juha Tonttila, Harri Kokkola, Hyunho Lee, David Painemal, and Annica M. L. Ekman
Atmos. Chem. Phys., 24, 4591–4610, https://doi.org/10.5194/acp-24-4591-2024, https://doi.org/10.5194/acp-24-4591-2024, 2024
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We use a numerical model to study interactions between humid light-absorbing aerosol plumes, clouds, and radiation over the southeast Atlantic. We find that the warming produced by the aerosols reduces cloud cover, especially in highly polluted situations. Aerosol impacts on drizzle play a minor role. However, aerosol effects on cloud reflectivity and moisture-induced changes in cloud cover dominate the climatic response and lead to an overall cooling by the biomass burning plumes.
Sampa Das, Peter R. Colarco, Huisheng Bian, and Santiago Gassó
Atmos. Chem. Phys., 24, 4421–4449, https://doi.org/10.5194/acp-24-4421-2024, https://doi.org/10.5194/acp-24-4421-2024, 2024
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The smoke aerosols emitted from vegetation burning can alter the regional energy budget via multiple pathways. We utilized detailed observations from the NASA ORACLES airborne campaign based in Namibia during September 2016 to improve the representation of smoke aerosol properties and lifetimes in our GEOS Earth system model. The improved model simulations are for the first time able to capture the observed changes in the smoke absorption during long-range plume transport.
Jia Liu, Cancan Zhu, Donghui Zhou, and Jinbao Han
EGUsphere, https://doi.org/10.5194/egusphere-2024-1000, https://doi.org/10.5194/egusphere-2024-1000, 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, and this method is verified from theoretical inspect. This method performs well for thickly coated BC at high RHs.
Jingmin Li, Mattia Righi, Johannes Hendricks, Christof G. Beer, Ulrike Burkhardt, and Anja Schmidt
EGUsphere, https://doi.org/10.5194/egusphere-2024-1024, https://doi.org/10.5194/egusphere-2024-1024, 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 SSP scenarios. The results provide a clear and condensed picture of the spatial extent and distribution of aerosols for different time periods and emission scenarios.
Emilio Cuevas-Agulló, David Barriopedro, Rosa Delia García, Silvia Alonso-Pérez, Juan Jesús González-Alemán, Ernest Werner, David Suárez, Juan José Bustos, Gerardo García-Castrillo, Omaira García, África Barreto, and Sara Basart
Atmos. Chem. Phys., 24, 4083–4104, https://doi.org/10.5194/acp-24-4083-2024, https://doi.org/10.5194/acp-24-4083-2024, 2024
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During February–March (FM) 2020–2022, unusually intense dust storms from northern Africa hit the western Euro-Mediterranean (WEM). Using dust products from satellites and atmospheric reanalysis for 2003–2022, results show that cut-off lows and European blocking are key drivers of FM dust intrusions over the WEM. A higher frequency of cut-off lows associated with subtropical ridges is observed in the late 2020–2022 period.
Yahui Che, Bofu Yu, and Katherine Bracco
Atmos. Chem. Phys., 24, 4105–4128, https://doi.org/10.5194/acp-24-4105-2024, https://doi.org/10.5194/acp-24-4105-2024, 2024
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Dust events occur more frequently during the Austral spring and summer in dust regions, including central Australia, the southwest of Western Australia, and the northern and southern regions of eastern Australia using remote sensing and reanalysis datasets. High-concentration dust is distributed around central Australia and in the downwind northern and southern Australia. Typically, around 50 % of the dust lifted settles on Australian land, with the remaining half being deposited in the ocean.
Jonathan Elsey, Nicolas Bellouin, and Claire Ryder
Atmos. Chem. Phys., 24, 4065–4081, https://doi.org/10.5194/acp-24-4065-2024, https://doi.org/10.5194/acp-24-4065-2024, 2024
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Aerosols influence the Earth's energy balance. The uncertainty in this radiative forcing is large depending partly on uncertainty in measurements of aerosol optical properties. We have developed a freely available new framework of millions of radiative transfer simulations spanning aerosol uncertainty and assess the impact on radiative forcing uncertainty. We find that reducing these uncertainties would reduce radiative forcing uncertainty, but non-aerosol uncertainties must also be considered.
Jing Li, Nan Wu, Biwu Chu, An Ning, and Xiuhui Zhang
Atmos. Chem. Phys., 24, 3989–4000, https://doi.org/10.5194/acp-24-3989-2024, https://doi.org/10.5194/acp-24-3989-2024, 2024
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Iodic acid (HIO3) nucleates with iodous acid (HIO2) efficiently in marine areas; however, whether methanesulfonic acid (MSA) can synergistically participate in the HIO3–HIO2-based nucleation is unclear. We provide molecular-level evidence that MSA can efficiently promote the formation of HIO3–HIO2-based clusters using a theoretical approach. The proposed MSA-enhanced iodine nucleation mechanism may help us to deeply understand marine new particle formation events with bursts of iodine particles.
Yueming Cheng, Tie Dai, Junji Cao, Daisuke Goto, Jianbing Jin, Teruyuki Nakajima, and Guangyu Shi
EGUsphere, https://doi.org/10.5194/egusphere-2024-840, https://doi.org/10.5194/egusphere-2024-840, 2024
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In March 2021, East Asia experienced an outbreak of severe dust storms after an absence of one and a half decades. Here, we innovative used the time-lagged ground-based aerosol size information with the fixed-lag ensemble Kalman smoother to optimize the dust emission and reproduce the dust storm. This work is valuable for the quantification of health damage, aviation risks, and profound impacts on the Earth system, but also to reveal the climatic driving force and the process of desertification.
Hao Wang, Xiaohong Liu, Chenglai Wu, and Guangxing Lin
Atmos. Chem. Phys., 24, 3309–3328, https://doi.org/10.5194/acp-24-3309-2024, https://doi.org/10.5194/acp-24-3309-2024, 2024
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We quantified different global- and regional-scale drivers of biogenic volatile organic compound (BVOC) emission trends over the past 20 years. The results show that global greening trends significantly boost BVOC emissions and deforestation reduces BVOC emissions in South America and Southeast Asia. Elevated temperature in Europe and increased soil moisture in East and South Asia enhance BVOC emissions. The results deepen our understanding of long-term BVOC emission trends in hotspots.
Christof G. Beer, Johannes Hendricks, and Mattia Righi
Atmos. Chem. Phys., 24, 3217–3240, https://doi.org/10.5194/acp-24-3217-2024, https://doi.org/10.5194/acp-24-3217-2024, 2024
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Ice-nucleating particles (INPs) have important influences on cirrus clouds and the climate system; however, the understanding of their global impacts is still uncertain. We perform numerical simulations with a global aerosol–climate model to analyse INP-induced cirrus changes and the resulting climate impacts. We evaluate various sources of uncertainties, e.g. the ice-nucleating ability of INPs and the role of model dynamics, and provide a new estimate for the global INP–cirrus effect.
Jiawei Li, Zhiwei Han, Pingqing Fu, Xiaohong Yao, and Mingjie Liang
Atmos. Chem. Phys., 24, 3129–3161, https://doi.org/10.5194/acp-24-3129-2024, https://doi.org/10.5194/acp-24-3129-2024, 2024
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Organic aerosols of marine origin are important for aerosol climatic effects but are poorly understood. For the first time, an online coupled regional chemistry–climate model is applied to explore the characteristics of emission, distribution, and direct and indirect radiative effects of marine organic aerosols over the western Pacific, which reveals an important role of marine organic aerosols in perturbing cloud and radiation and promotes understanding of global aerosol climatic impact.
Yawen Liu, Yun Qian, Philip J. Rasch, Kai Zhang, Lai-yung Ruby Leung, Yuhang Wang, Minghuai Wang, Hailong Wang, Xin Huang, and Xiu-Qun Yang
Atmos. Chem. Phys., 24, 3115–3128, https://doi.org/10.5194/acp-24-3115-2024, https://doi.org/10.5194/acp-24-3115-2024, 2024
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Fire management has long been a challenge. Here we report that spring-peak fire activity over southern Mexico and Central America (SMCA) has a distinct quasi-biennial signal by measuring multiple fire metrics. This signal is initially driven by quasi-biennial variability in precipitation and is further amplified by positive feedback of fire–precipitation interaction at short timescales. This work highlights the importance of fire–climate interactions in shaping fires on an interannual scale.
Xu Feng, Loretta J. Mickley, Michelle L. Bell, Tianjia Liu, Jenny A. Fisher, and Maria Val Martin
Atmos. Chem. Phys., 24, 2985–3007, https://doi.org/10.5194/acp-24-2985-2024, https://doi.org/10.5194/acp-24-2985-2024, 2024
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During severe wildfire seasons, smoke can have a significant impact on air quality in Australia. Our study demonstrates that characterization of the smoke plume injection fractions greatly affects estimates of surface smoke PM2.5. Using the plume behavior predicted by the machine learning method leads to the best model agreement with observed surface PM2.5 in key cities across Australia, with smoke PM2.5 accounting for 5 %–52 % of total PM2.5 on average during fire seasons from 2009 to 2020.
Shiyi Lai, Ximeng Qi, Xin Huang, Sijia Lou, Xuguang Chi, Liangduo Chen, Chong Liu, Yuliang Liu, Chao Yan, Mengmeng Li, Tengyu Liu, Wei Nie, Veli-Matti Kerminen, Tuukka Petäjä, Markku Kulmala, and Aijun Ding
Atmos. Chem. Phys., 24, 2535–2553, https://doi.org/10.5194/acp-24-2535-2024, https://doi.org/10.5194/acp-24-2535-2024, 2024
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By combining in situ measurements and chemical transport modeling, this study investigates new particle formation (NPF) on the southeastern Tibetan Plateau. We found that the NPF was driven by the presence of biogenic gases and the transport of anthropogenic precursors. The NPF was vertically heterogeneous and shaped by the vertical mixing. This study highlights the importance of anthropogenic–biogenic interactions and meteorological dynamics in NPF in this climate-sensitive region.
Adriana Rocha-Lima, Peter R. Colarco, Anton S. Darmenov, Edward P. Nowottnick, Arlindo M. da Silva, and Luke D. Oman
Atmos. Chem. Phys., 24, 2443–2464, https://doi.org/10.5194/acp-24-2443-2024, https://doi.org/10.5194/acp-24-2443-2024, 2024
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Observations show an increasing aerosol optical depth trend in the Middle East between 2003–2012. We evaluate the NASA Goddard Earth Observing System (GEOS) model's ability to capture these trends and examine the meteorological and surface parameters driving dust emissions. Our results highlight the importance of data assimilation for long-term trends of atmospheric aerosols and support the hypothesis that vegetation cover loss may have contributed to increasing dust emissions in the period.
Marc Mallet, Aurore Voldoire, Fabien Solmon, Pierre Nabat, Thomas Drugé, and Romain Roehrig
EGUsphere, https://doi.org/10.5194/egusphere-2024-496, https://doi.org/10.5194/egusphere-2024-496, 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 by reducing the precipitation of the coastal Western Africa. It also highlights the key role of the ocean temperature response and its feedbacks for the September to November season.
Danny M. Leung, Jasper F. Kok, Longlei Li, Natalie M. Mahowald, David M. Lawrence, Simone Tilmes, Erik Kluzek, Martina Klose, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 2287–2318, https://doi.org/10.5194/acp-24-2287-2024, https://doi.org/10.5194/acp-24-2287-2024, 2024
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This study uses a premier Earth system model to evaluate a new desert dust emission scheme proposed in our companion paper. We show that our scheme accounts for more dust emission physics, hence matching better against observations than other existing dust emission schemes do. Our scheme's dust emissions also couple tightly with meteorology, hence likely improving the modeled dust sensitivity to climate change. We believe this work is vital for improving dust representation in climate models.
Ruth A. R. Digby, Nathan P. Gillett, Adam H. Monahan, Knut von Salzen, Antonis Gkikas, Qianqian Song, and Zhibo Zhang
Atmos. Chem. Phys., 24, 2077–2097, https://doi.org/10.5194/acp-24-2077-2024, https://doi.org/10.5194/acp-24-2077-2024, 2024
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The COVID-19 lockdowns reduced aerosol emissions. We ask whether these reductions affected regional aerosol optical depth (AOD) and compare the observed changes to predictions from Earth system models. Only India has an observed AOD reduction outside of typical variability. Models overestimate the response in some regions, but when key biases have been addressed, the agreement is improved. Our results suggest that current models can realistically predict the effects of future emission changes.
Xinyue Shao, Minghuai Wang, Xinyi Dong, Yaman Liu, Wenxiang Shen, Stephen Arnold, Leighton Regayre, Meinrat Andreae, Mira Pöhlker, Duseong Jo, Man Yue, and Ken Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2024-401, https://doi.org/10.5194/egusphere-2024-401, 2024
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Highly oxygenated organic molecules (HOMs) play an important role in atmospheric new particle formation (NPF). By 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, NPF event frequency. Our results reveal that HOMs-driven NPF leads to a considerable increase in particle and cloud condensation nuclei burden globally.
Huisheng Bian, Mian Chin, Peter R. Colarco, Eric C. Apel, Donald R. Blake, Karl Froyd, Rebecca S. Hornbrook, Jose Jimenez, Pedro Campuzano Jost, Michael Lawler, Mingxu Liu, Marianne Tronstad Lund, Hitoshi Matsui, Benjamin A. Nault, Joyce E. Penner, Andrew W. Rollins, Gregory Schill, Ragnhild B. Skeie, Hailong Wang, Lu Xu, Kai Zhang, and Jialei Zhu
Atmos. Chem. Phys., 24, 1717–1741, https://doi.org/10.5194/acp-24-1717-2024, https://doi.org/10.5194/acp-24-1717-2024, 2024
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This work studies sulfur in the remote troposphere at global and seasonal scales using aircraft measurements and multi-model simulations. The goal is to understand the sulfur cycle over remote oceans, spread of model simulations, and observation–model discrepancies. Such an understanding and comparison with real observations are crucial to narrow down the uncertainties in model sulfur simulations and improve understanding of the sulfur cycle in atmospheric air quality, climate, and ecosystems.
Gargi Sengupta, Minjie Zheng, and Nønne L. Prisle
Atmos. Chem. Phys., 24, 1467–1487, https://doi.org/10.5194/acp-24-1467-2024, https://doi.org/10.5194/acp-24-1467-2024, 2024
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The effect of organic acid aerosol on sulfur chemistry and cloud properties was investigated in an atmospheric model. Organic acid dissociation was considered using both bulk and surface-related properties. We found that organic acid dissociation leads to increased hydrogen ion concentrations and sulfate aerosol mass in aqueous aerosols, increasing cloud formation. This could be important in large-scale climate models as many organic aerosol components are both acidic and surface-active.
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