Articles | Volume 7, issue 3
https://doi.org/10.5194/gmd-7-799-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-799-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
12 May 2014
Development and technical paper |
| 12 May 2014
Development of a new semi-empirical parameterization for below-cloud scavenging of size-resolved aerosol particles by both rain and snow
X. Wang
Kellys Environmental Services, Toronto, Ontario, Canada
Air Quality Research Division, Science and Technology Branch, Environment Canada, 4905 Dufferin St, Toronto, Ontario, M3H 5T4, Canada
M. D. Moran
Air Quality Research Division, Science and Technology Branch, Environment Canada, 4905 Dufferin St, Toronto, Ontario, M3H 5T4, Canada
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Atmos. Chem. Phys., 13, 10005–10025, https://doi.org/10.5194/acp-13-10005-2013, https://doi.org/10.5194/acp-13-10005-2013, 2013
Tamara Emmerichs, Abdulla Al Mamun, Lisa Emberson, Huiting Mao, Leiming Zhang, Limei Ran, Clara Betancourt, Anthony Wong, Gerbrand Koren, Giacomo Gerosa, Min Huang, and Pierluigi Guaita
EGUsphere, https://doi.org/10.5194/egusphere-2025-429, https://doi.org/10.5194/egusphere-2025-429, 2025
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The risk of ozone pollution to plants is estimated based on the flux through the plant pores which still has uncertainties. In this study, we estimate this quantity with 9 models at different land types worldwide. The input data stems from a database. The models estimated mostly reasonable summertime ozone deposition. The different results of the models varied by land cover which were mostly related to the moisture deficit. This is an important step for assessing the ozone impact on vegetation.
Diego Guizzardi, Monica Crippa, Tim Butler, Terry Keating, Rosa Wu, Jacek W. Kamiński, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Rachel Hoesly, Marilena Muntean, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Annie Duhamel, Tabish Ansari, Kristen Foley, Guannan Geng, Yifei Chen, and Qiang Zhang
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The global air pollution emission mosaic HTAP_v3.1 is the state-of-the-art database for addressing the evolution of a set of policy-relevant air pollutants over the past 2 decades. The inventory is made by the harmonization and blending of seven regional inventories, gapfilled using the most recent release of EDGAR (EDGARv8). By incorporating the best available local information, the HTAP_v3.1 mosaic inventory can be used for policy-relevant studies at both regional and global levels.
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Deposition from sulfur and nitrogen pollution can harm ecosystems, and recovery from this type of pollution can take decades or longer. To identify risk to Canadian soils, we created maps showing sensitivity to sulfur and nitrogen pollution. Results show that some ecosystems are at risk from acid and nutrient nitrogen deposition: 10 % of protected areas are receiving acid deposition beyond their damage threshold, and 70 % may be receiving nitrogen deposition that could cause biodiversity loss.
Zihan Song, Leiming Zhang, Chongguo Tian, Qiang Fu, Zhenxing Shen, Renjian Zhang, Dong Liu, and Song Cui
Atmos. Chem. Phys., 24, 13101–13113, https://doi.org/10.5194/acp-24-13101-2024, https://doi.org/10.5194/acp-24-13101-2024, 2024
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EGUsphere, https://doi.org/10.5194/egusphere-2024-3038, https://doi.org/10.5194/egusphere-2024-3038, 2024
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Vegetation removes tropospheric ozone through stomatal uptake, and accurately modeling the stomatal uptake of ozone is important for modeling dry deposition and air quality. We evaluated the stomatal component of ozone dry deposition modeled by atmospheric chemistry models at six sites. We find that models and observation-based estimates agree at times during the growing season at all sites, but some models overestimated the stomatal component during the dry summers at a seasonally dry site.
Irene Cheng, Amanda Cole, Leiming Zhang, and Alexandra Steffen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2895, https://doi.org/10.5194/egusphere-2024-2895, 2024
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Using the Positive Matrix Factorization (PMF) model and observations, we showed natural surface emission (wildfires and re-emitted Hg) dominated anthropogenic contributions to total gaseous mercury (TGM). Decreasing TGM was due to reduced shipping and regional emissions. This has led to increasing relative contributions from natural surface emissions of 1.0–1.6 % yr-1. Results showed Hg control measures have been effective, but greater attention is needed on monitoring surface re-emissions.
Pierluigi Renan Guaita, Riccardo Marzuoli, Leiming Zhang, Steven Turnock, Gerbrand Koren, Oliver Wild, Paola Crippa, and Giacomo Alessandro Gerosa
EGUsphere, https://doi.org/10.5194/egusphere-2024-2573, https://doi.org/10.5194/egusphere-2024-2573, 2024
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Xiaohong Yao and Leiming Zhang
Atmos. Chem. Phys., 24, 7773–7791, https://doi.org/10.5194/acp-24-7773-2024, https://doi.org/10.5194/acp-24-7773-2024, 2024
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Juanjuan Qin, Leiming Zhang, Yuanyuan Qin, Shaoxuan Shi, Jingnan Li, Zhao Shu, Yuwei Gao, Ting Qi, Jihua Tan, and Xinming Wang
Atmos. Chem. Phys., 24, 7575–7589, https://doi.org/10.5194/acp-24-7575-2024, https://doi.org/10.5194/acp-24-7575-2024, 2024
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The present research unveiled that acidity dominates while transition metal ions harmonize with the light absorption properties of humic-like substances (HULIS). Cu2+ has quenching effects on HULIS by complexation, hydrogen substitution, or electrostatic adsorption, with aromatic structures of HULIS. Such effects are less pronounced if from Mn2+, Ni2+, Zn2+, and Cu2+. Oxidized HULIS might contain electron-donating groups, whereas N-containing compounds might contain electron-withdrawing groups.
Olivia E. Clifton, Donna Schwede, Christian Hogrefe, Jesse O. Bash, Sam Bland, Philip Cheung, Mhairi Coyle, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, and Leiming Zhang
Atmos. Chem. Phys., 23, 9911–9961, https://doi.org/10.5194/acp-23-9911-2023, https://doi.org/10.5194/acp-23-9911-2023, 2023
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Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
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Yu Lin, Leiming Zhang, Qinchu Fan, He Meng, Yang Gao, Huiwang Gao, and Xiaohong Yao
Atmos. Chem. Phys., 22, 16073–16090, https://doi.org/10.5194/acp-22-16073-2022, https://doi.org/10.5194/acp-22-16073-2022, 2022
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Irene Cheng, Leiming Zhang, Zhuanshi He, Hazel Cathcart, Daniel Houle, Amanda Cole, Jian Feng, Jason O'Brien, Anne Marie Macdonald, Julian Aherne, and Jeffrey Brook
Atmos. Chem. Phys., 22, 14631–14656, https://doi.org/10.5194/acp-22-14631-2022, https://doi.org/10.5194/acp-22-14631-2022, 2022
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Nitrogen (N) and sulfur (S) deposition decreased significantly at 14 Canadian sites during 2000–2018. The greatest decline was observed in southeastern Canada owing to regional SO2 and NOx reductions. Wet deposition was more important than dry deposition, comprising 71–95 % of total N and 45–89 % of total S deposition. While critical loads (CLs) were exceeded at a few sites in the early 2000s, acidic deposition declined below CLs after 2012, which signifies recovery from legacy acidification.
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
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A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
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We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Hui Zhang, Xuewu Fu, Ben Yu, Baoxin Li, Peng Liu, Guoqing Zhang, Leiming Zhang, and Xinbin Feng
Atmos. Chem. Phys., 21, 15847–15859, https://doi.org/10.5194/acp-21-15847-2021, https://doi.org/10.5194/acp-21-15847-2021, 2021
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Our observations of speciated atmospheric mercury at the Waliguan GAW Baseline Observatory show that concentrations of gaseous elemental mercury (GEM) and particulate bound mercury (PBM) were elevated compared to the Northern Hemisphere background. We propose that the major sources of GEM and PBM were mainly related to anthropogenic emissions and desert dust sources. This study highlights that dust-related sources played an important role in the variations of PBM in the Tibetan Plateau.
Zhiyong Wu, Leiming Zhang, John T. Walker, Paul A. Makar, Judith A. Perlinger, and Xuemei Wang
Geosci. Model Dev., 14, 5093–5105, https://doi.org/10.5194/gmd-14-5093-2021, https://doi.org/10.5194/gmd-14-5093-2021, 2021
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A community dry deposition algorithm for modeling the gaseous dry deposition process in chemistry transport models was extended to include an additional 12 oxidized volatile organic compounds and hydrogen cyanide based on their physicochemical properties and was then evaluated using field flux measurements over a mixed forest. This study provides a useful tool that is needed in chemistry transport models with increasing complexity for simulating an important atmospheric process.
Katherine Hayden, Shao-Meng Li, Paul Makar, John Liggio, Samar G. Moussa, Ayodeji Akingunola, Robert McLaren, Ralf M. Staebler, Andrea Darlington, Jason O'Brien, Junhua Zhang, Mengistu Wolde, and Leiming Zhang
Atmos. Chem. Phys., 21, 8377–8392, https://doi.org/10.5194/acp-21-8377-2021, https://doi.org/10.5194/acp-21-8377-2021, 2021
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We developed a method using aircraft measurements to determine lifetimes with respect to dry deposition for oxidized sulfur and nitrogen compounds over the boreal forest in Alberta, Canada. Atmospheric lifetimes were significantly shorter than derived from chemical transport models with differences related to modelled dry deposition velocities. The shorter lifetimes suggest models need to reassess dry deposition treatment and predictions of sulfur and nitrogen in the atmosphere and ecosystems.
Xuewu Fu, Chen Liu, Hui Zhang, Yue Xu, Hui Zhang, Jun Li, Xiaopu Lyu, Gan Zhang, Hai Guo, Xun Wang, Leiming Zhang, and Xinbin Feng
Atmos. Chem. Phys., 21, 6721–6734, https://doi.org/10.5194/acp-21-6721-2021, https://doi.org/10.5194/acp-21-6721-2021, 2021
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TGM concentrations and isotopic compositions in 10 Chinese cities showed strong seasonality with higher TGM concentrations and Δ199Hg and lower δ202Hg in summer. We found the seasonal variations in TGM concentrations and isotopic compositions were highly related to regional surface Hg(0) emissions, suggesting land surface Hg(0) emissions are an important source of atmospheric TGM that contribute dominantly to the seasonal variations in TGM concentrations and isotopic compositions.
Xiaofei Qin, Leiming Zhang, Guochen Wang, Xiaohao Wang, Qingyan Fu, Jian Xu, Hao Li, Jia Chen, Qianbiao Zhao, Yanfen Lin, Juntao Huo, Fengwen Wang, Kan Huang, and Congrui Deng
Atmos. Chem. Phys., 20, 10985–10996, https://doi.org/10.5194/acp-20-10985-2020, https://doi.org/10.5194/acp-20-10985-2020, 2020
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The uncertainties in mercury emissions are much larger from natural sources than anthropogenic sources. A method was developed to quantify the contributions of natural surface emissions to ambient GEM based on PMF modeling. The annual GEM concentration in eastern China showed a decreasing trend from 2015 to 2018, while the relative contribution of natural surface emissions increased significantly from 41 % in 2015 to 57 % in 2018, gradually surpassing those from anthropogenic sources.
Cynthia H. Whaley, Elisabeth Galarneau, Paul A. Makar, Michael D. Moran, and Junhua Zhang
Atmos. Chem. Phys., 20, 2911–2925, https://doi.org/10.5194/acp-20-2911-2020, https://doi.org/10.5194/acp-20-2911-2020, 2020
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Benzene and polycyclic aromatic compounds are toxic air pollutants and ubiquitous in the environment. Using a chemical transport model, we have determined the net impact of vehicle emissions on ambient concentrations of these species. Traffic emissions were found to be a significant fraction of ambient pollution in the densely populated modelled region of North America. Our simulations demonstrate the air quality benefits that would result from transitioning to a zero-emission vehicle fleet.
Mark W. Shephard, Enrico Dammers, Karen E. Cady-Pereira, Shailesh K. Kharol, Jesse Thompson, Yonatan Gainariu-Matz, Junhua Zhang, Chris A. McLinden, Andrew Kovachik, Michael Moran, Shabtai Bittman, Christopher E. Sioris, Debora Griffin, Matthew J. Alvarado, Chantelle Lonsdale, Verica Savic-Jovcic, and Qiong Zheng
Atmos. Chem. Phys., 20, 2277–2302, https://doi.org/10.5194/acp-20-2277-2020, https://doi.org/10.5194/acp-20-2277-2020, 2020
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Presented is a description and survey demonstrating the capabilities of the CrIS ammonia product for monitoring, air quality forecast model evaluation, dry deposition estimates, and emission estimates of an agricultural hotspot.
Xiaohong Yao and Leiming Zhang
Atmos. Chem. Phys., 20, 721–733, https://doi.org/10.5194/acp-20-721-2020, https://doi.org/10.5194/acp-20-721-2020, 2020
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An innovative approach is developed to preprocess monitored wet deposition data of inorganic ions for generating their decadal trends. Differing from traditional approaches which directly apply annual or seasonal average data to trend analysis tools, the proposed new approach makes use of slopes of regression equations between a series of study years and a climatology (base) year in terms of monthly averaged data. The new approach yields more robust results than the traditional tools.
Xiaoyi Zhao, Debora Griffin, Vitali Fioletov, Chris McLinden, Jonathan Davies, Akira Ogyu, Sum Chi Lee, Alexandru Lupu, Michael D. Moran, Alexander Cede, Martin Tiefengraber, and Moritz Müller
Atmos. Chem. Phys., 19, 10619–10642, https://doi.org/10.5194/acp-19-10619-2019, https://doi.org/10.5194/acp-19-10619-2019, 2019
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New nitrogen dioxide (NO2) retrieval algorithms are developed for Pandora zenith-sky measurements. A column-to-surface conversion look-up table was produced for the Pandora instruments; therefore, quick and practical Pandora-based surface NO2 concentration data can be obtained for air quality monitoring purposes. It is demonstrated that the surface NO2 concentration is controlled not only by the planetary boundary layer height but also by both boundary layer dynamics and photochemistry.
Jack Chen, Kerry Anderson, Radenko Pavlovic, Michael D. Moran, Peter Englefield, Dan K. Thompson, Rodrigo Munoz-Alpizar, and Hugo Landry
Geosci. Model Dev., 12, 3283–3310, https://doi.org/10.5194/gmd-12-3283-2019, https://doi.org/10.5194/gmd-12-3283-2019, 2019
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Emissions from wildland fires can cause significant impacts on regional air quality. We introduce the Canadian Forest Fire Emissions Prediction System and demonstrate its integration with Canada's FireWork operational air quality forecast system with biomass burning emissions. The coupled system shows improved skill in providing short-term, 48 h forecasts of surface air pollutant concentrations (PM2.5, O3, and NO2) from the impacts of regional wildland fires across the North American domain.
Jun Tao, Zhisheng Zhang, Yunfei Wu, Leiming Zhang, Zhijun Wu, Peng Cheng, Mei Li, Laiguo Chen, Renjian Zhang, and Junji Cao
Atmos. Chem. Phys., 19, 8471–8490, https://doi.org/10.5194/acp-19-8471-2019, https://doi.org/10.5194/acp-19-8471-2019, 2019
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Mass-scattering efficiencies (MSE) of dominant chemical species in atmospheric aerosols are important parameters for building the relationships between chemical species and the particle-scattering coefficient. Particle MSE mainly depends on the mass fractions of (NH4)2SO4, NH4NO3, and organic matter and their MSEs in the droplet mode. MSEs of (NH4)2SO4, NH4NO3 and organic matter were determined by their size distributions in the droplet mode.
Matthew Russell, Amir Hakami, Paul A. Makar, Ayodeji Akingunola, Junhua Zhang, Michael D. Moran, and Qiong Zheng
Atmos. Chem. Phys., 19, 4393–4417, https://doi.org/10.5194/acp-19-4393-2019, https://doi.org/10.5194/acp-19-4393-2019, 2019
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High-resolution air-quality forecast modeling results are compared for two different grid spacings for the Environment and Climate Change Canada GEM-MACH model. While the higher-resolution simulations have worse formal error scores, we show that the higher-resolution model nevertheless has the ability to better resolve plume maxima and has better performance when the evaluation occurs using new scoring metrics which operate on an equal-representative-area basis.
Yang Chen, Mi Tian, Ru-Jin Huang, Guangming Shi, Huanbo Wang, Chao Peng, Junji Cao, Qiyuan Wang, Shumin Zhang, Dongmei Guo, Leiming Zhang, and Fumo Yang
Atmos. Chem. Phys., 19, 3245–3255, https://doi.org/10.5194/acp-19-3245-2019, https://doi.org/10.5194/acp-19-3245-2019, 2019
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Amine-containing particles were characterized in an urban area of Chongqing during both summer and winter using a single-particle aerosol mass spectrometer (SPAMS). Amines were observed to internally mix with elemental carbon (EC), organic carbon (OC), sulfate, and nitrate. Diethylamine (DEA) was the most abundant in both number and peak area among amine-containing particles. Vegetation and traffic were the primary sources of particulate amines.
Junhua Zhang, Michael D. Moran, Qiong Zheng, Paul A. Makar, Pegah Baratzadeh, George Marson, Peter Liu, and Shao-Meng Li
Atmos. Chem. Phys., 18, 10459–10481, https://doi.org/10.5194/acp-18-10459-2018, https://doi.org/10.5194/acp-18-10459-2018, 2018
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This paper discusses the development of new synthesized emissions inventories and the generation of air quality model-ready emissions files for the Athabasca Oil Sands Region of Alberta, Canada, using multiple emissions inventories, continuous emissions monitoring data, and inferred emission rates based on aircraft measurements. Novel facility-specific gridded spatial surrogate fields were generated to allocate emissions spatially within each huge mining facility.
Paul A. Makar, Ayodeji Akingunola, Julian Aherne, Amanda S. Cole, Yayne-abeba Aklilu, Junhua Zhang, Isaac Wong, Katherine Hayden, Shao-Meng Li, Jane Kirk, Ken Scott, Michael D. Moran, Alain Robichaud, Hazel Cathcart, Pegah Baratzedah, Balbir Pabla, Philip Cheung, Qiong Zheng, and Dean S. Jeffries
Atmos. Chem. Phys., 18, 9897–9927, https://doi.org/10.5194/acp-18-9897-2018, https://doi.org/10.5194/acp-18-9897-2018, 2018
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Complex computer model output was compared to and fused with observation data, to estimate potential damage due to acidifying precipitation for ecosystems in the Canadian provinces of Alberta and Saskatchewan. Estimated deposition was compared to the maximum no-damage ecosystem capacity for sulfur and/or nitrogen uptake; these critical loads were exceeded, for areas between 10 000 and 330 000 square kilometres, depending on ecosystem type: ecosystem damage will occur at 2013 emission levels.
Ayodeji Akingunola, Paul A. Makar, Junhua Zhang, Andrea Darlington, Shao-Meng Li, Mark Gordon, Michael D. Moran, and Qiong Zheng
Atmos. Chem. Phys., 18, 8667–8688, https://doi.org/10.5194/acp-18-8667-2018, https://doi.org/10.5194/acp-18-8667-2018, 2018
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We examine the manner in which air-quality models simulate lofting of buoyant plumes of emissions from stacks (plume rise) and the impact of the level of detail in algorithms simulating particles' variation in size (particle size distribution). The most commonly used plume rise algorithm underestimates the height of plumes compared to observations, while a revised algorithm has much better performance. A 12-bin size distribution reduced the forecast 2-bin size distribution bias error by 32 %.
Stephanie C. Pugliese, Jennifer G. Murphy, Felix R. Vogel, Michael D. Moran, Junhua Zhang, Qiong Zheng, Craig A. Stroud, Shuzhan Ren, Douglas Worthy, and Gregoire Broquet
Atmos. Chem. Phys., 18, 3387–3401, https://doi.org/10.5194/acp-18-3387-2018, https://doi.org/10.5194/acp-18-3387-2018, 2018
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We developed the Southern Ontario CO2 Emissions (SOCE) inventory, which identifies the spatial and temporal distribution (2.5 km and hourly, respectively) of CO2 emissions from seven source sectors. When the SOCE inventory was used with a chemistry transport model, we found strong agreement between modelled and measured mixing ratios. We were able to quantify that natural gas combustion contributes > 80 % of CO2 emissions at nighttime while on-road emissions contribute > 70 % during the day.
Xin Qiu, Irene Cheng, Fuquan Yang, Erin Horb, Leiming Zhang, and Tom Harner
Atmos. Chem. Phys., 18, 3457–3467, https://doi.org/10.5194/acp-18-3457-2018, https://doi.org/10.5194/acp-18-3457-2018, 2018
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We developed emissions databases for polycyclic aromatic compounds (PACs) in the Athabasca oil sands region and evaluated the emissions databases by comparing CALPUFF-modelled concentrations with monitored data. Model–measurement agreement improved near oil sands mines due to updated PAC emissions from tailings ponds. Modelled concentrations were underestimated at remote sites and for alkylated PACs suggesting that the emissions of PACs particularly alkylated compounds are underestimated.
Cynthia H. Whaley, Paul A. Makar, Mark W. Shephard, Leiming Zhang, Junhua Zhang, Qiong Zheng, Ayodeji Akingunola, Gregory R. Wentworth, Jennifer G. Murphy, Shailesh K. Kharol, and Karen E. Cady-Pereira
Atmos. Chem. Phys., 18, 2011–2034, https://doi.org/10.5194/acp-18-2011-2018, https://doi.org/10.5194/acp-18-2011-2018, 2018
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Using a modified air quality forecasting model, we have found that a significant fraction (> 50 %) of ambient ammonia comes from re-emission from plants and soils in the broader Athabasca Oil Sands region and much of Alberta and Saskatchewan. We also found that about 20 % of ambient ammonia in Alberta and Saskatchewan came from forest fires in the summer of 2013. The addition of these two processes improved modelled ammonia, which was a motivating factor in undertaking this research.
Huanbo Wang, Mi Tian, Yang Chen, Guangming Shi, Yuan Liu, Fumo Yang, Leiming Zhang, Liqun Deng, Jiayan Yu, Chao Peng, and Xuyao Cao
Atmos. Chem. Phys., 18, 865–881, https://doi.org/10.5194/acp-18-865-2018, https://doi.org/10.5194/acp-18-865-2018, 2018
Yuan You, Ralf M. Staebler, Samar G. Moussa, Yushan Su, Tony Munoz, Craig Stroud, Junhua Zhang, and Michael D. Moran
Atmos. Chem. Phys., 17, 14119–14143, https://doi.org/10.5194/acp-17-14119-2017, https://doi.org/10.5194/acp-17-14119-2017, 2017
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A novel approach for traffic emission measurements is shown to have the capacity to provide high-time-resolution accurate concentrations of key air pollutants. A top-down method for quantifying real-world emission rates produced vehicular emission factor estimates for carbon monoxide that agreed well with bottom-up values. Significant ammonia and hydrogen cyanide emissions were observed. The main factors modulating the concentrations were turbulent mixing and traffic density.
Vitali Fioletov, Chris A. McLinden, Shailesh K. Kharol, Nickolay A. Krotkov, Can Li, Joanna Joiner, Michael D. Moran, Robert Vet, Antoon J. H. Visschedijk, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys., 17, 12597–12616, https://doi.org/10.5194/acp-17-12597-2017, https://doi.org/10.5194/acp-17-12597-2017, 2017
Huiting Mao, Dolly Hall, Zhuyun Ye, Ying Zhou, Dirk Felton, and Leiming Zhang
Atmos. Chem. Phys., 17, 11655–11671, https://doi.org/10.5194/acp-17-11655-2017, https://doi.org/10.5194/acp-17-11655-2017, 2017
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Mercury (Hg) is a global pollutant hazardous to human and ecosystem health, and its emission control is imperative. Anthropogenic mercury emissions have been reduced by 78 % in the United States from 1990 to 2014. However, no clearly defined trend was observed in Hg concentrations at urban locations such as the one in this study. This indicates that other factors may have dominated over anthropogenic emission control. The implications of this study could hence be highly policy relevant.
Jun Tao, Leiming Zhang, Junji Cao, and Renjian Zhang
Atmos. Chem. Phys., 17, 9485–9518, https://doi.org/10.5194/acp-17-9485-2017, https://doi.org/10.5194/acp-17-9485-2017, 2017
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In this study, studies on PM2.5 chemical composition, source apportionment and its impact on aerosol optical properties across China are thoroughly reviewed, and historical emission control policies in China and their effectiveness in reducing PM2.5 are discussed.
Leiming Zhang, Seth Lyman, Huiting Mao, Che-Jen Lin, David A. Gay, Shuxiao Wang, Mae Sexauer Gustin, Xinbin Feng, and Frank Wania
Atmos. Chem. Phys., 17, 9133–9144, https://doi.org/10.5194/acp-17-9133-2017, https://doi.org/10.5194/acp-17-9133-2017, 2017
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Future research needs are proposed for improving the understanding of atmospheric mercury cycling. These include refinement of mercury emission estimations, quantification of dry deposition and air–surface exchange, improvement of the treatment of chemical mechanisms in chemical transport models, increase in the accuracy of oxidized mercury measurements, better interpretation of atmospheric mercury chemistry data, and harmonization of network operation.
Yunfei Wu, Xiaojia Wang, Jun Tao, Rujin Huang, Ping Tian, Junji Cao, Leiming Zhang, Kin-Fai Ho, Zhiwei Han, and Renjian Zhang
Atmos. Chem. Phys., 17, 7965–7975, https://doi.org/10.5194/acp-17-7965-2017, https://doi.org/10.5194/acp-17-7965-2017, 2017
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As black carbon (BC) aerosols play an important role in the climate and environment, the size distribution of refractory BC (rBC) was investigated. On this basis, the source of rBC was further analyzed. The local traffic exhausts contributed greatly to the rBC in urban areas. However, its contribution decreased significantly in the polluted period compared to the clean period, implying the increasing contribution of other sources, e.g., coal combustion or biomass burning, in the polluted period.
Irene Cheng and Leiming Zhang
Atmos. Chem. Phys., 17, 4711–4730, https://doi.org/10.5194/acp-17-4711-2017, https://doi.org/10.5194/acp-17-4711-2017, 2017
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Geographical and long-term (1983–2011) trends in air concentrations and wet deposition of inorganic ions and aerosol and precipitation acidity were analyzed at 31 sites in Canada. Declines in atmospheric ammonium, nitrate, and sulfate were consistent with decreasing emissions of NH3, NOx, and SO2. A decline in nitrate and sulfate wet deposition was also observed. Wet scavenging was further studied by estimating scavenging ratios and relative contributions of gases and aerosols to wet deposition.
Xiaohong Xu, Yanyin Liao, Irene Cheng, and Leiming Zhang
Atmos. Chem. Phys., 17, 1381–1400, https://doi.org/10.5194/acp-17-1381-2017, https://doi.org/10.5194/acp-17-1381-2017, 2017
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This study addresses two issues related to source–receptor analysis of speciated atmospheric mercury: (1) comparing PMF and PCA and (2) testing different approaches in data selection for PMF modeling.
L. Paige Wright, Leiming Zhang, and Frank J. Marsik
Atmos. Chem. Phys., 16, 13399–13416, https://doi.org/10.5194/acp-16-13399-2016, https://doi.org/10.5194/acp-16-13399-2016, 2016
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The current knowledge concerning mercury dry deposition is reviewed, including dry deposition algorithms used in chemical transport models and at monitoring sites, measurement methods and studies for quantifying dry deposition of oxidized mercury, and measurement studies of litterfall and throughfall mercury. Over all the regions, dry deposition, estimated as the sum of litterfall and throughfall minus open-field wet deposition, is more dominant than wet deposition for Hg deposition.
Huiting Mao, Irene Cheng, and Leiming Zhang
Atmos. Chem. Phys., 16, 12897–12924, https://doi.org/10.5194/acp-16-12897-2016, https://doi.org/10.5194/acp-16-12897-2016, 2016
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Understanding of spatial and temporal variations of atmospheric speciated mercury can advance our knowledge of mercury cycling in various environments. This review summarized spatiotemporal variations of TGM/GEM, GOM, and PBM in environments including oceans, continents, high elevation, the free troposphere, and low to high latitudes. Remaining questions/issues and recommendations were provided for future research.
Vitali E. Fioletov, Chris A. McLinden, Nickolay Krotkov, Can Li, Joanna Joiner, Nicolas Theys, Simon Carn, and Mike D. Moran
Atmos. Chem. Phys., 16, 11497–11519, https://doi.org/10.5194/acp-16-11497-2016, https://doi.org/10.5194/acp-16-11497-2016, 2016
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We introduce the first space-based catalogue of SO2 emission sources seen by OMI. The inventory contains about 500 sources. They account for about a half of all SO2 emissions; the remaining half is likely related to sources emitting less than 30 kt yr−1 and not detected by OMI. The sources are grouped by type (volcanoes, power plants, oil- and gas-related sources, and smelters) and country. The catalogue presented herein can be used for verification of available SO2 emission inventories.
Xiaohong Yao and Leiming Zhang
Atmos. Chem. Phys., 16, 11465–11475, https://doi.org/10.5194/acp-16-11465-2016, https://doi.org/10.5194/acp-16-11465-2016, 2016
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Atmospheric NH3 plays an important role in forming secondary aerosols and has a direct impact on sensitive ecosystems. This study aims to study its long-term variation and find that the long-term trend can be affected by climate change as well as other anthropogenic factors, depending on sites. A large percentage increase of atmospheric NH3 at remote American sites is surprising and may cause a potential threat to sensitive ecosystems in the future.
Xiaodong Zhang, Tao Huang, Leiming Zhang, Yanjie Shen, Yuan Zhao, Hong Gao, Xiaoxuan Mao, Chenhui Jia, and Jianmin Ma
Atmos. Chem. Phys., 16, 6949–6960, https://doi.org/10.5194/acp-16-6949-2016, https://doi.org/10.5194/acp-16-6949-2016, 2016
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This paper assesses long-term trend of biogenic isoprene emissions in the Three-North Shelter Forest Program, also known as "the Green Great Wall", the largest artificial afforestation in the human history. Results show that the TNRSF has altered the long-term emission trend in north China from a decreasing to an increasing trend from 1982 to 2010. Isoprene emission fluxes have increased in many places of the TNRSF over the last 3 decades due to the growing trees and vegetation coverage.
Lei Zhang, Shuxiao Wang, Qingru Wu, Fengyang Wang, Che-Jen Lin, Leiming Zhang, Mulin Hui, Mei Yang, Haitao Su, and Jiming Hao
Atmos. Chem. Phys., 16, 2417–2433, https://doi.org/10.5194/acp-16-2417-2016, https://doi.org/10.5194/acp-16-2417-2016, 2016
C. G. Nolte, K. W. Appel, J. T. Kelly, P. V. Bhave, K. M. Fahey, J. L. Collett Jr., L. Zhang, and J. O. Young
Geosci. Model Dev., 8, 2877–2892, https://doi.org/10.5194/gmd-8-2877-2015, https://doi.org/10.5194/gmd-8-2877-2015, 2015
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This study is the most comprehensive evaluation of CMAQ inorganic
aerosol size-composition distributions conducted to date. We compare two
methods of inferring PM2.5 concentrations from the model: (1) based on
the sum of the masses in the fine aerosol modes, as is most commonly
done in CMAQ model evaluation; and (2) computed using the simulated size
distributions. Differences are generally less than 1 microgram/m3, and
are largest over the eastern USA during the summer.
I. Cheng, X. Xu, and L. Zhang
Atmos. Chem. Phys., 15, 7877–7895, https://doi.org/10.5194/acp-15-7877-2015, https://doi.org/10.5194/acp-15-7877-2015, 2015
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Current knowledge of receptor-based studies using speciated atmospheric mercury is reviewed and recommendations for future research needs are provided.
Z. Y. Wu, L. Zhang, X. M. Wang, and J. W. Munger
Atmos. Chem. Phys., 15, 7487–7496, https://doi.org/10.5194/acp-15-7487-2015, https://doi.org/10.5194/acp-15-7487-2015, 2015
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In this study, we have developed a modified micrometeorological gradient method (MGM), although based on existing micrometeorological theory, to estimate O3 dry deposition fluxes over a forest canopy using concentration gradients between a level above and a level below the canopy top. The new method provides an alternative approach in monitoring/estimating long-term deposition fluxes of similar pollutants over tall canopies and is expected to be useful for the scientific community.
L. Zhang, I. Cheng, D. Muir, and J.-P. Charland
Atmos. Chem. Phys., 15, 1421–1434, https://doi.org/10.5194/acp-15-1421-2015, https://doi.org/10.5194/acp-15-1421-2015, 2015
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This study analyzed air and precipitation concentrations of 43 polycyclic aromatic compounds (PACs) collected in the Athabasca oil sands region. A database has been built for the parameter scavenging ratio, which is defined as the ratio of the concentration of PACs in precipitation to that in air. A better understanding of the potential differences between gas and particulate scavenging and between snow and rain scavenging has been achieved.
J. Tao, J. Gao, L. Zhang, R. Zhang, H. Che, Z. Zhang, Z. Lin, J. Jing, J. Cao, and S.-C. Hsu
Atmos. Chem. Phys., 14, 8679–8699, https://doi.org/10.5194/acp-14-8679-2014, https://doi.org/10.5194/acp-14-8679-2014, 2014
Z. J. Lin, Z. S. Zhang, L. Zhang, J. Tao, R. J. Zhang, J. J. Cao, S. J. Fan, and Y. H. Zhang
Atmos. Chem. Phys., 14, 7631–7644, https://doi.org/10.5194/acp-14-7631-2014, https://doi.org/10.5194/acp-14-7631-2014, 2014
D. Wen, L. Zhang, J. C. Lin, R. Vet, and M. D. Moran
Geosci. Model Dev., 7, 1037–1050, https://doi.org/10.5194/gmd-7-1037-2014, https://doi.org/10.5194/gmd-7-1037-2014, 2014
P. A. Makar, R. Nissen, A. Teakles, J. Zhang, Q. Zheng, M. D. Moran, H. Yau, and C. diCenzo
Geosci. Model Dev., 7, 1001–1024, https://doi.org/10.5194/gmd-7-1001-2014, https://doi.org/10.5194/gmd-7-1001-2014, 2014
E. Galarneau, P. A. Makar, Q. Zheng, J. Narayan, J. Zhang, M. D. Moran, M. A. Bari, S. Pathela, A. Chen, and R. Chlumsky
Atmos. Chem. Phys., 14, 4065–4077, https://doi.org/10.5194/acp-14-4065-2014, https://doi.org/10.5194/acp-14-4065-2014, 2014
L. Zhang and Z. He
Atmos. Chem. Phys., 14, 3729–3737, https://doi.org/10.5194/acp-14-3729-2014, https://doi.org/10.5194/acp-14-3729-2014, 2014
X. H. Yao and L. Zhang
Biogeosciences, 10, 7913–7925, https://doi.org/10.5194/bg-10-7913-2013, https://doi.org/10.5194/bg-10-7913-2013, 2013
S. Chen, X. Qiu, L. Zhang, F. Yang, and P. Blanchard
Atmos. Chem. Phys., 13, 11287–11293, https://doi.org/10.5194/acp-13-11287-2013, https://doi.org/10.5194/acp-13-11287-2013, 2013
L. Zhang, X. Wang, M. D. Moran, and J. Feng
Atmos. Chem. Phys., 13, 10005–10025, https://doi.org/10.5194/acp-13-10005-2013, https://doi.org/10.5194/acp-13-10005-2013, 2013
I. Cheng, L. Zhang, P. Blanchard, J. Dalziel, and R. Tordon
Atmos. Chem. Phys., 13, 6031–6048, https://doi.org/10.5194/acp-13-6031-2013, https://doi.org/10.5194/acp-13-6031-2013, 2013
E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, K. W. Appel, V. Matthias, P. Grossi, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. B. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, and S. Galmarini
Geosci. Model Dev., 6, 791–818, https://doi.org/10.5194/gmd-6-791-2013, https://doi.org/10.5194/gmd-6-791-2013, 2013
G. Kos, A. Ryzhkov, A. Dastoor, J. Narayan, A. Steffen, P. A. Ariya, and L. Zhang
Atmos. Chem. Phys., 13, 4839–4863, https://doi.org/10.5194/acp-13-4839-2013, https://doi.org/10.5194/acp-13-4839-2013, 2013
D. Wen, J. C. Lin, L. Zhang, R. Vet, and M. D. Moran
Geosci. Model Dev., 6, 327–344, https://doi.org/10.5194/gmd-6-327-2013, https://doi.org/10.5194/gmd-6-327-2013, 2013
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Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
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Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
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High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Cited articles
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