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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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.
Marc Bocquet, Pierre J. Vanderbecken, Alban Farchi, Joffrey Dumont Le Brazidec, and Yelva Roustan
EGUsphere, https://doi.org/10.5194/egusphere-2023-2755, https://doi.org/10.5194/egusphere-2023-2755, 2023
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A novel approach, the Optimal Transport Data Assimilation, is introduced to merge data assimilation and optimal transport concepts. By leveraging optimal transport's displacement interpolation in space, it minimises mislocation errors within data assimilation applied to physical fields, such as water vapour, hydrometeors, chemical species, etc. Its richness and flexibility are showcased through one- and two-dimensional illustrations.
Tobias Sebastian Finn, Lucas Disson, Alban Farchi, Marc Bocquet, and Charlotte Durand
EGUsphere, https://doi.org/10.5194/egusphere-2023-2261, https://doi.org/10.5194/egusphere-2023-2261, 2023
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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.
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)
Uncertainties in laboratory-measured shortwave refractive indices of mineral dust aerosols and derived optical properties: a theoretical assessment
Diagnosing uncertainties in global biomass burning emission inventories and their impact on modeled air pollutants
Role of atmospheric aerosols in severe winter fog over the Indo-Gangetic Plain of India: a case study
Long-term variability in black carbon emissions constrained by gap-filled absorption aerosol optical depth and associated premature mortality in China
Intercomparison of aerosol optical depths from four reanalyses and their multi-reanalysis consensus
Global aviation contrail climate effects from 2019 to 2021
Rapid iodine oxoacid nucleation enhanced by dimethylamine in broad marine regions
Simulations of the impact of cloud condensation nuclei and ice-nucleating particles perturbations on the microphysics and radar reflectivity factor of stratiform mixed-phase clouds
Aerosols in the central Arctic cryosphere: satellite and model integrated insights during Arctic spring and summer
Observationally constrained regional variations of shortwave absorption by iron oxides emphasize the cooling effect of dust
Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions
Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data
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
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
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
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
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
The contribution of residential wood combustion to the PM2.5 concentrations in the Helsinki metropolitan area
Analysis of atmospheric particle growth based on vapor concentrations measured at the high-altitude GAW station Chacaltaya in the Bolivian Andes
Investigating the sign of stratocumulus adjustments to aerosols in the global storm-resolving model ICON
Expanding the simulation of East Asian super dust storms: physical transport mechanisms impacting the western Pacific
Insights into the sources of ultrafine particle numbers at six European urban sites obtained by investigating COVID–19 lockdowns
Improving 3-day deterministic air pollution forecasts using machine learning algorithms
Opinion: The importance of historical and paleoclimate aerosol radiative effects
Assessing the assimilation of Himawari-8 observations on aerosol forecasts and radiative effects during pollution transport from South Asia to the Tibetan Plateau
Aerosol–meteorology feedback diminishes the transboundary transport of black carbon into the Tibetan Plateau
Associations of interannual variation in summer tropospheric ozone with the Western Pacific Subtropical High in China from 1999 to 2017
Modeling impacts of dust mineralogy on Earth’s Radiation and Climate
Climate intervention using marine cloud brightening (MCB) compared with stratospheric aerosol injection (SAI) in the UKESM1 climate model
Comparison of six approaches to predicting droplet activation of surface active aerosol – Part 2: Strong surfactants
A model study on investigating the sensitivity of aerosol forcing on the volatilities of semi-volatile organic compounds
Decomposing the Effective Radiative Forcing of anthropogenic aerosols based on CMIP6 Earth System Models
Increased importance of aerosol–cloud interactions for surface PM2.5 pollution relative to aerosol–radiation interactions in China with the anthropogenic emission reductions
The role of temporal scales in extracting dominant meteorological drivers of major airborne pollutants
Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns
Air pollution trapping in the Dresden Basin from gray-zone scale urban modeling
The effect of atmospherically relevant aminium salts on water uptake
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.
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.
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.
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.
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.
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.
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.
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.
Leena Kangas, Jaakko Kukkonen, Mari Kauhaniemi, Kari Riikonen, Mikhail Sofiev, Anu Kousa, Jarkko V. Niemi, and Ari Karppinen
Atmos. Chem. Phys., 24, 1489–1507, https://doi.org/10.5194/acp-24-1489-2024, https://doi.org/10.5194/acp-24-1489-2024, 2024
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Residential wood combustion is a major source of fine particulate matter. This study has evaluated the contribution of residential wood combustion to fine particle concentrations and its year-to-year and seasonal variation in te Helsinki metropolitan area. The average concentrations attributed to wood combustion in winter were up to 10- or 15-fold compared to summer. Wood combustion caused 12 % to 14 % of annual fine particle concentrations. In winter, the contribution ranged from 16 % to 21 %.
Arto Heitto, Cheng Wu, Diego Aliaga, Luis Blacutt, Xuemeng Chen, Yvette Gramlich, Liine Heikkinen, Wei Huang, Radovan Krejci, Paolo Laj, Isabel Moreno, Karine Sellegri, Fernando Velarde, Kay Weinhold, Alfred Wiedensohler, Qiaozhi Zha, Federico Bianchi, Marcos Andrade, Kari E. J. Lehtinen, Claudia Mohr, and Taina Yli-Juuti
Atmos. Chem. Phys., 24, 1315–1328, https://doi.org/10.5194/acp-24-1315-2024, https://doi.org/10.5194/acp-24-1315-2024, 2024
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Particle growth at the Chacaltaya station in Bolivia was simulated based on measured vapor concentrations and ambient conditions. Major contributors to the simulated growth were low-volatility organic compounds (LVOCs). Also, sulfuric acid had major role when volcanic activity was occurring in the area. This study provides insight on nanoparticle growth at this high-altitude Southern Hemispheric site and hence contributes to building knowledge of early growth of atmospheric particles.
Emilie Fons, Ann Kristin Naumann, David Neubauer, Theresa Lang, and Ulrike Lohmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-195, https://doi.org/10.5194/egusphere-2024-195, 2024
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Aerosols can modify the liquid water path (LWP) of stratocumulus (Sc), and thus their radiative effect. This study compares model outputs and satellite data that disagree on the sign of Sc LWP adjustments: positive and negative, respectively. We use causality to diagnose this discrepancy and find that strong precipitation and cloud deepening under a weak inversion contribute to positive LWP adjustments to aerosols in the model, while entrainment enhancement prevails in observations.
Steven Soon-Kai Kong, Saginela Ravindra Babu, Sheng-Hsiang Wang, Stephen M. Griffith, Jackson Hian-Wui Chang, Ming-Tung Chuang, Guey-Rong Sheu, and Neng-Huei Lin
Atmos. Chem. Phys., 24, 1041–1058, https://doi.org/10.5194/acp-24-1041-2024, https://doi.org/10.5194/acp-24-1041-2024, 2024
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In this study, we combined ground observations from 7-SEAS Dongsha Experiment, MERRA-2 reanalysis, and MODIS satellite images for evaluation and improvement of the CMAQ dust model for cases of East Asian Dust reaching the Taiwan region, including Dongsha in the western Pacific. We proposed a better CMAQ dust treatment over East Asia and for the first time revealed the impact of typhoons on dust transport.
Alex Rowell, James Brean, David C. S. Beddows, Zongbo Shi, Tuukka Petäjä, Máté Vörösmarty, Imre Salma, Jarkko V. Niemi, Hanna E. Manninen, Dominik van Pinxteren, Roy M. Harrison, Thomas Tuch, and Kay Weinhold
EGUsphere, https://doi.org/10.5194/egusphere-2023-3053, https://doi.org/10.5194/egusphere-2023-3053, 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 Factorization. The various sources responded differently to the changes in emissions associated with Covid 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.
Zhiguo Zhang, Christer Johansson, Magnuz Engardt, Massimo Stafoggia, and Xiaoliang Ma
Atmos. Chem. Phys., 24, 807–851, https://doi.org/10.5194/acp-24-807-2024, https://doi.org/10.5194/acp-24-807-2024, 2024
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Up-to-date information on present and near-future air quality help people avoid exposure to high levels of air pollution. We apply different machine learning models to significantly improve traditional forecasts of PM10, NOx, and O3 in Stockholm, Sweden. It is shown that forecasts of all air pollutants are improved by the input of lagged measurements and taking calendar information into account. The final modelled errors are substantially smaller than uncertainties in the measurements.
Natalie M. Mahowald, Longlei Li, Samuel Albani, Douglas S. Hamilton, and Jasper F. Kok
Atmos. Chem. Phys., 24, 533–551, https://doi.org/10.5194/acp-24-533-2024, https://doi.org/10.5194/acp-24-533-2024, 2024
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Estimating past aerosol radiative effects and their uncertainties is an important topic in climate science. Aerosol radiative effects propagate into large uncertainties in estimates of how present and future climate evolves with changing greenhouse gas emissions. A deeper understanding of how aerosols interacted with the atmospheric energy budget under past climates is hindered in part by a lack of relevant paleo-observations and in part because less attention has been paid to the problem.
Min Zhao, Tie Dai, Daisuke Goto, Hao Wang, and Guangyu Shi
Atmos. Chem. Phys., 24, 235–258, https://doi.org/10.5194/acp-24-235-2024, https://doi.org/10.5194/acp-24-235-2024, 2024
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During a springtime pollution input from South Asia to the Tibetan Plateau, we combined atmospheric chemistry modeling and data assimilation methods to assimilate and forecast aerosols from South Asia and the Tibetan Plateau. Assimilation of observations over a whole time window leads to a more reasonable distribution of daily variations in the aerosol forecast field. We also find that aerosol assimilation can improve the surface solar energy forecast in the Tibetan Plateau region.
Yuling Hu, Haipeng Yu, Shichang Kang, Junhua Yang, Mukesh Rai, Xiufeng Yin, Xintong Chen, and Pengfei Chen
Atmos. Chem. Phys., 24, 85–107, https://doi.org/10.5194/acp-24-85-2024, https://doi.org/10.5194/acp-24-85-2024, 2024
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The Tibetan Plateau (TP) saw a record-breaking aerosol pollution event from April 20 to May 10, 2016. We studied the impact of aerosol–meteorology feedback on the transboundary transport flux of black carbon (BC) during this severe pollution event. It was found that the aerosol–meteorology feedback decreases the transboundary transport flux of BC from the central and western Himalayas towards the TP. This study is of great significance for the protection of the ecological environment of the TP.
Xiaodong Zhang, Ruiyu Zhugu, Xiaohu Jian, Xinrui Liu, Kaijie Chen, Shu Tao, Junfeng Liu, Hong Gao, Tao Huang, and Jianmin Ma
Atmos. Chem. Phys., 23, 15629–15642, https://doi.org/10.5194/acp-23-15629-2023, https://doi.org/10.5194/acp-23-15629-2023, 2023
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WRF-Chem modeling was conducted to assess impacts of Western Pacific Subtropical High Pressure (WPSH) on interannual fluctuations of O3 pollution in China. We find that, while precursor emissions dominated the long-term trend and magnitude of O3 from 1999 to 2017, WPSH determined interannual variation of summer O3. The response of O3 pollution to WPSH in major urban clusters depended on the proximity of these urban areas to WPSH. The results could help long-term O3 pollution mitigation planning.
Qianqian Song, Paul Ginoux, María Gonçalves Ageitos, Ron L. Miller, Vincenzo Obiso, and Carlos Pérez García-Pando
EGUsphere, https://doi.org/10.5194/egusphere-2023-2938, https://doi.org/10.5194/egusphere-2023-2938, 2023
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We implement and simulate the distribution of eight dust minerals in the GFDL AM4.0 model. Resolving dust mineralogy reduces dust absorption and results in better agreement with observation-based results. Resolving dust mineralogy results in significant impacts on radiation, land surface temperature, surface winds and precipitation over North Africa in JJA.
Jim M. Haywood, Andy Jones, Anthony C. Jones, Paul Halloran, and Philip J. Rasch
Atmos. Chem. Phys., 23, 15305–15324, https://doi.org/10.5194/acp-23-15305-2023, https://doi.org/10.5194/acp-23-15305-2023, 2023
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The difficulties in ameliorating global warming and the associated climate change via conventional mitigation are well documented, with all climate model scenarios exceeding 1.5 °C above the preindustrial level in the near future. There is therefore a growing interest in geoengineering to reflect a greater proportion of sunlight back to space and offset some of the global warming. We use a state-of-the-art Earth-system model to investigate two of the most prominent geoengineering strategies.
Sampo Vepsäläinen, Silvia M. Calderón, and Nønne L. Prisle
Atmos. Chem. Phys., 23, 15149–15164, https://doi.org/10.5194/acp-23-15149-2023, https://doi.org/10.5194/acp-23-15149-2023, 2023
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Atmospheric aerosols act as seeds for cloud formation. Many aerosols contain surface active material that accumulates at the surface of growing droplets. This can affect cloud droplet activation, but the broad significance of the effect and the best way to model it are still debated. We compare predictions of six models to surface activity of strongly surface active aerosol and find significant differences between the models, especially with large fractions of surfactant in the dry particles.
Muhammed Irfan, Thomas Kühn, Taina Yli-Juuti, Anton Laakso, Eemeli Holopainen, Douglas R. Worsnop, Annele Virtanen, and Harri Kokkola
EGUsphere, https://doi.org/10.5194/egusphere-2023-2768, https://doi.org/10.5194/egusphere-2023-2768, 2023
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The study underscores the influence of semi-volatile organic compounds on the formation of secondary organic aerosol (SOA). Our findings demonstrate their considerable impact on climate, emphasizing the necessity to improve their representation in large-scale climate models. This research provides a nuanced perspective on the challenges in modelling, emphasizing the significance of semi-volatile compounds and their volatility distribution in 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
EGUsphere, https://doi.org/10.5194/egusphere-2023-2571, https://doi.org/10.5194/egusphere-2023-2571, 2023
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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.
Da Gao, Bin Zhao, Shuxiao Wang, Yuan Wang, Brian Gaudet, Yun Zhu, Xiaochun Wang, Jiewen Shen, Shengyue Li, Yicong He, Dejia Yin, and Zhaoxin Dong
Atmos. Chem. Phys., 23, 14359–14373, https://doi.org/10.5194/acp-23-14359-2023, https://doi.org/10.5194/acp-23-14359-2023, 2023
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Surface PM2.5 concentrations can be enhanced by aerosol–radiation interactions (ARIs) and aerosol–cloud interactions (ACIs). In this study, we found PM2.5 enhancement induced by ACIs shows a significantly smaller decrease ratio than that induced by ARIs in China with anthropogenic emission reduction from 2013 to 2021, making ACIs more important for enhancing PM2.5 concentrations. ACI-induced PM2.5 enhancement needs to be emphatically considered to meet the national PM2.5 air quality standard.
Miaoqing Xu, Jing Yang, Manchun Li, Xiao Chen, Qiancheng Lv, Qi Yao, Bingbo Gao, and Ziyue Chen
Atmos. Chem. Phys., 23, 14065–14076, https://doi.org/10.5194/acp-23-14065-2023, https://doi.org/10.5194/acp-23-14065-2023, 2023
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Although the temporal-scale effects on PM2.5–meteorology associations have been discussed, no quantitative evidence has proved this before. Based on rare 3 h meteorology data, we revealed that the dominant meteorological factor for PM2.5 concentrations across China extracted at the 3 h and 24 h scales presented large variations. This research suggests that data sources of different temporal scales should be comprehensively considered for better attribution and prevention of airborne pollution.
Calvin Howes, Pablo E. Saide, Hugh Coe, Amie Dobracki, Steffen Freitag, Jim M. Haywood, Steven G. Howell, Siddhant Gupta, Janek Uin, Mary Kacarab, Chongai Kuang, L. Ruby Leung, Athanasios Nenes, Greg M. McFarquhar, James Podolske, Jens Redemann, Arthur J. Sedlacek, Kenneth L. Thornhill, Jenny P. S. Wong, Robert Wood, Huihui Wu, Yang Zhang, Jianhao Zhang, and Paquita Zuidema
Atmos. Chem. Phys., 23, 13911–13940, https://doi.org/10.5194/acp-23-13911-2023, https://doi.org/10.5194/acp-23-13911-2023, 2023
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To better understand smoke properties and its interactions with clouds, we compare the WRF-CAM5 model with observations from ORACLES, CLARIFY, and LASIC field campaigns in the southeastern Atlantic in August 2017. The model transports and mixes smoke well but does not fully capture some important processes. These include smoke chemical and physical aging over 4–12 days, smoke removal by rain, sulfate particle formation, aerosol activation into cloud droplets, and boundary layer turbulence.
Michael Weger and Bernd Heinold
Atmos. Chem. Phys., 23, 13769–13790, https://doi.org/10.5194/acp-23-13769-2023, https://doi.org/10.5194/acp-23-13769-2023, 2023
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This study investigates the effects of complex terrain on air pollution trapping using a numerical model which simulates the dispersion of emissions under real meteorological conditions. The additionally simulated aerosol age allows us to distinguish areas that accumulate aerosol over time from areas that are more influenced by fresh emissions. The Dresden Basin, a widened section of the Elbe Valley in eastern Germany, is selected as the target area in a case study to demonstrate the concept.
Noora Hyttinen
Atmos. Chem. Phys., 23, 13809–13817, https://doi.org/10.5194/acp-23-13809-2023, https://doi.org/10.5194/acp-23-13809-2023, 2023
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Water activity in aerosol particles describes how particles respond to variations in relative humidity. Here, water activities were calculated for a set of 80 salts that may be present in aerosol particles using a state-of-the-art quantum-chemistry-based method. The effect of the dissociated salt on water activity varies with both the cation and anion. Most of the studied salts increase water uptake compared to pure water-soluble organic particles.
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