Articles | Volume 22, issue 13
https://doi.org/10.5194/acp-22-8617-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-8617-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Jul 2022
Research article |
| 05 Jul 2022
| 05 Jul 2022
Improving NOx emission estimates in Beijing using network observations and a perturbed emissions ensemble
Yusuf Hamied Department of Chemistry, University of Cambridge,
Cambridge, CB2 1EW, UK
Olalekan A. M. Popoola
Yusuf Hamied Department of Chemistry, University of Cambridge,
Cambridge, CB2 1EW, UK
Christina Hood
Cambridge Environmental Research Consultants, Cambridge, CB2 1SJ, UK
David Carruthers
Cambridge Environmental Research Consultants, Cambridge, CB2 1SJ, UK
Roderic L. Jones
Yusuf Hamied Department of Chemistry, University of Cambridge,
Cambridge, CB2 1EW, UK
Haitong Zhe Sun
Yusuf Hamied Department of Chemistry, University of Cambridge,
Cambridge, CB2 1EW, UK
Huan Liu
State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, International
Joint Laboratory on Low Carbon Clean Energy Innovation, School of the Environment, Tsinghua University, Beijing, 100084, China
Qiang Zhang
Ministry of Education Key Laboratory for Earth System Modeling,
Department of Earth System Science, Tsinghua University, Beijing, 100084,
China
Yusuf Hamied Department of Chemistry, University of Cambridge,
Cambridge, CB2 1EW, UK
National Centre for Atmospheric Science, Cambridge, CB2 1EW, UK
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EGUsphere, https://doi.org/10.5194/egusphere-2026-1935, https://doi.org/10.5194/egusphere-2026-1935, 2026
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We developed a model to track near-real-time global ship emissions. Previous methods failed to include newly-built ship activities or account for different compliance strategies ships used to meet environmental laws. Our model uncovered significant underestimated carbon dioxide and particular matter emissions, especially in the Indian Ocean and South China Sea. The findings provide a more accurate foundation for understanding how shipping affects our air quality and climate.
Shuling Xu, Yang Liu, Sha Yu, Weidong Jia, Yongye Jiang, Yuqin Li, Zeyuan Liu, Andy Miller, Jianxiang Shen, Jingyang Song, Can Wang, Huaxuan Wang, Rui Wang, Fan Wu, Hongzhi Zhang, Mengting Zhu, Rongqi Zhu, Jenna Behrendt, Matthew Binsted, Jing Cheng, Robert Dahowski, Casie Davidson, Shiyu Deng, Jay Fuhrman, Matthew Gidden, Chaoyi Guo, Jill Horing, Hanwoong Kim, Chaojun Li, Bo Liu, Xunzhang Pan, Pralit Patel, Meiyin Qian, Yang Qiu, Tianming Shao, Yisheng Sun, Lining Wang, Yuyao Yang, Brinda Yarlagadda, Zihua Yin, Jian Zang, Qianzhi Zhang, Wenjia Cai, Wenying Chen, Leon Clarke, Ryna Cui, Nathan Hultman, Bengang Li, Jiashuo Li, Xi Lu, Haewon McJeon, Bo Wang, Can Wang, Peng Wang, Shuxiao Wang, Zhaohua Wang, Lixiao Zhang, Qiang Zhang, and Yang Ou
EGUsphere, https://doi.org/10.5194/egusphere-2026-1919, https://doi.org/10.5194/egusphere-2026-1919, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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This study introduces a new open-source model GCAM-China-v8, developed by the community to better understand China’s energy and emissions at both national and provincial levels. The model links detailed regional systems with global trends, allowing users to explore how economic growth, technology, and policy choices shape future pathways. It provides a transparent and flexible tool to support research and decision making on energy and climate issues.
Xingpei Ye, Lin Zhang, Xiaolin Wang, Ni Lu, Sebastian Hickman, Guo Luo, and Alex T. Archibald
Atmos. Chem. Phys., 26, 6377–6390, https://doi.org/10.5194/acp-26-6377-2026, https://doi.org/10.5194/acp-26-6377-2026, 2026
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This study investigates how meteorology influences long-term surface ozone trends and pollution events across three major regions in eastern China using an explainable machine learning framework. The results show physically interpretable yet model-dependent ozone-meteorology relationships, highlighting both the potential and the limitations of explainable machine learning for process understanding in atmospheric chemistry.
Detlef P. Van Vuuren, Brian C. O'Neill, Claudia Tebaldi, Benjamin M. Sanderson, Louise P. Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh M. N. Fall, Katja Frieler, Matthew J. Gidden, Laila K. Gohar, Annika Högner, Andrew D. Jones, Jarmo Kikstra, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camilla Mathison, Shahbaz Mehmood, Zebedee Nicholls, Luciana F. Prado, Qiang Zhang, Steven K. Rose, Alex C. Ruane, Marit Sandstad, Carl-Friedrich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna A. Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha S. Vishwanathan, Tokuta Yokohata, Marco Zecchetto, and Tilo Ziehn
Geosci. Model Dev., 19, 2627–2656, https://doi.org/10.5194/gmd-19-2627-2026, https://doi.org/10.5194/gmd-19-2627-2026, 2026
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We propose a set of seven plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
Gunnar Myhre, Øivind Hodnebrog, Srinath Krishnan, Maria Sand, Marit Sandstad, Ragnhild B. Skeie, Lieven Clarisse, Bruno Franco, Dylan B. Millet, Kelley C. Wells, Alexander Archibald, Hannah N. Bryant, Alex T. Chaudhri, David S. Stevenson, Didier Hauglustaine, Michael Prather, J. Christopher Kaiser, Dirk J. L. Olivie, Michael Schulz, Oliver Wild, Ye Wang, Thérèse Salameh, Jason E. Williams, Philippe Le Sager, Fabien Paulot, Kostas Tsigaridis, and Haley E. Plaas
Geosci. Model Dev., 19, 2577–2591, https://doi.org/10.5194/gmd-19-2577-2026, https://doi.org/10.5194/gmd-19-2577-2026, 2026
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Volatile organic compounds (VOCs) affect air quality and climate, but their behavior in the atmosphere is still uncertain. We launched a global research effort to compare how different models represent these compounds and to improve their accuracy. By analyzing model results alongside observations and satellite data, we aim to better understand the atmospheric composition of these compounds.
Xu-Cheng He, Nathan Luke Abraham, Han Ding, Maria R. Russo, Daniel P. Grosvenor, Yao Ge, Xuemei Wang, Anthony C. Jones, Pedro Campuzano-Jost, Benjamin Nault, Agnieszka Kupc, Donald Blake, Jose L. Jimenez, Christina J. Williamson, James Weber, Alexander T. Archibald, and Hamish Gordon
Atmos. Chem. Phys., 26, 3805–3851, https://doi.org/10.5194/acp-26-3805-2026, https://doi.org/10.5194/acp-26-3805-2026, 2026
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Aerosols affect clouds and climate. However, current climate models still struggle to simulate them accurately. We used aircraft data from a global mission to evaluate how well the UK Earth System Model represents aerosols and their precursors. Our results show that the model misses key formation processes in clean ocean regions, suggesting that future improvements should focus on better representing how aerosols form naturally in the atmosphere.
Lorrie S. D. Jacob, Benedict E. H. Harvey, Chiara Giorio, and Alexander T. Archibald
Atmos. Chem. Phys., 26, 3567–3587, https://doi.org/10.5194/acp-26-3567-2026, https://doi.org/10.5194/acp-26-3567-2026, 2026
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We develop an approach to determine the uncertainty in reactions involved in the breakdown of dimethyl sulfide and methanethiol in the atmosphere, and run simulations spanning temperate, tropical, and polar conditions to quantify the impacts of this uncertainty on the concentration of these sulfur species and their products. We extend this analysis to identify key reactions that drive the uncertainty and highlight areas for further experimental and theoretical work.
Megan A. J. Brown, Nicola J. Warwick, Nathan Luke Abraham, Paul T. Griffiths, Steve T. Rumbold, Gerd A. Folberth, Fiona M. O'Connor, Hannah Bryant, and Alex T. Archibald
Geosci. Model Dev., 19, 1537–1557, https://doi.org/10.5194/gmd-19-1537-2026, https://doi.org/10.5194/gmd-19-1537-2026, 2026
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Hydrogen (H2) is an indirect greenhouse gas by increasing methane (CH4) lifetime. Interaction between H2 and CH4 is important for hydrogen’s global warming potential (GWP). Global models do not represent this interaction well; H2 or CH4 are prescribed at the surface. We implement an interactive H2 scheme into a global model coupled with interactive CH4. We simulate scenarios demonstrating its capability, improving model performance and more accurately representing H2-CH4 interaction.
Ruth M. Doherty, Zhenze Liu, Massimo Vieno, Oliver Wild, Fiona M. O'Connor, Steven T. Turnock, Christina M. Hood, Jenny R. Stocker, Mathew R. Heal, Dwayne E. Heard, Emma G. Sands, David J. Carruthers, and Lisa K. Whalley
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This study developed a coupled model approach to investigate key processes determining how climate change impacts 21st-century air quality. Elevated isoprene emissions drive summer ozone and fine particulate matter increases over continental Europe; but their response to climate change is uncertain. Unabated climate change, without emission reductions, poses a challenge for achieving ozone, fine particulate matter and nitrogen dioxide long-term air quality guidelines over much of Europe by 2100.
Diego Guizzardi, Monica Crippa, 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, 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
Earth Syst. Sci. Data, 17, 5915–5950, https://doi.org/10.5194/essd-17-5915-2025, https://doi.org/10.5194/essd-17-5915-2025, 2025
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Zhige Wang, Ce Zhang, Kejian Shi, Yulin Shangguan, Bifeng Hu, Xueyao Chen, Danqing Wei, Songchao Chen, Peter M. Atkinson, and Qiang Zhang
Earth Syst. Sci. Data, 17, 5355–5375, https://doi.org/10.5194/essd-17-5355-2025, https://doi.org/10.5194/essd-17-5355-2025, 2025
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The irreversible trend in global warming underscores the necessity for accurate monitoring of atmospheric carbon dynamics on a global scale. This study generated a global dataset of column-averaged dry-air mole fraction of CO2 (XCO2) at 0.05° resolution with full coverage using carbon satellite data and a deep learning model. The dataset accurately depicts global and regional XCO2 patterns, advancing the monitoring of carbon emissions and understanding of global carbon dynamics.
Ruochong Xu, Hanchen Ma, Jingxian Li, Dan Tong, Liu Yan, Lanyuan Wang, Xinying Qin, Qingyang Xiao, Xizhe Yan, Hanwen Hu, Yujia Fu, Nana Wu, Huaxuan Wang, Yuexuanzi Wang, Xiaodong Liu, Guannan Geng, Kebin He, and Qiang Zhang
Atmos. Chem. Phys., 25, 12675–12700, https://doi.org/10.5194/acp-25-12675-2025, https://doi.org/10.5194/acp-25-12675-2025, 2025
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In this study, we developed a new global emission inventory for non-methane volatile organic compounds (NMVOC) for the period of 1970–2020, with a focus on improving the representation of NMVOC-emission-related technologies. Our analysis revealed that activity growth, technology advancements, and policy-driven emission controls were key driving forces of NMVOC emission changes, but their roles were different across sectors and regions.
Paul T. Griffiths, Laura J. Wilcox, Robert J. Allen, Vaishali Naik, Fiona M. O'Connor, Michael Prather, Alex Archibald, Florence Brown, Makoto Deushi, William Collins, Stephanie Fiedler, Naga Oshima, Lee T. Murray, Bjørn H. Samset, Chris Smith, Steven Turnock, Duncan Watson-Parris, and Paul J. Young
Atmos. Chem. Phys., 25, 8289–8328, https://doi.org/10.5194/acp-25-8289-2025, https://doi.org/10.5194/acp-25-8289-2025, 2025
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The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) aimed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. We review its contribution to AR6 (Sixth Assessment Report of the Intergovernmental Panel on Climate Change) and the wider understanding of the role of these species in climate and climate change. We identify challenges and provide recommendations to improve the utility and uptake of climate model data, detailed summary tables of CMIP6 models, experiments, and emergent diagnostics.
Xiaolin Duan, Guangjie Zheng, Chuchu Chen, Qiang Zhang, and Kebin He
Atmos. Chem. Phys., 25, 3919–3928, https://doi.org/10.5194/acp-25-3919-2025, https://doi.org/10.5194/acp-25-3919-2025, 2025
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Aerosol acidity is an important parameter in atmospheric chemistry, while its driving factors, especially chemical profiles versus meteorological conditions, are not yet fully understood. Here, we established a hierarchical quantitative analysis framework to understand the driving factors of aerosol acidity on different timescales. Its application in Changzhou, China, revealed distinct driving factors and corresponding mechanisms of aerosol acidity from annual trends to random residuals.
Alex T. Archibald, Bablu Sinha, Maria R. Russo, Emily Matthews, Freya A. Squires, N. Luke Abraham, Stephane J.-B. Bauguitte, Thomas J. Bannan, Thomas G. Bell, David Berry, Lucy J. Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian A. King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Bengamin I. Moat, Katie Read, Chris Reed, Malcolm J. Roberts, Reinhard Schiemann, David Schroeder, Timothy J. Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Mingxi Yang
Earth Syst. Sci. Data, 17, 135–164, https://doi.org/10.5194/essd-17-135-2025, https://doi.org/10.5194/essd-17-135-2025, 2025
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Here, we present an overview of the data generated as part of the North Atlantic Climate System Integrated Study (ACSIS) programme that are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA; www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC; bodc.ac.uk). The datasets described here cover the North Atlantic Ocean, the atmosphere above (it including its composition), and Arctic sea ice.
Liu Yan, Qiang Zhang, Bo Zheng, and Kebin He
Earth Syst. Sci. Data, 16, 4497–4509, https://doi.org/10.5194/essd-16-4497-2024, https://doi.org/10.5194/essd-16-4497-2024, 2024
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A new database of fuel-, vehicle-type-, and age-specific CO2 emissions from global on-road vehicles from 1970 to 2020 is developed with the fleet turnover model built in this study. Based on this database, the evolution of the global vehicle stock over 50 years is analyzed, the dominant emission contributors by vehicle and fuel type are identified, and the age distribution of on-road CO2 emissions is characterized further.
Yuan Cheng, Xu-bing Cao, Sheng-qiang Zhu, Zhi-qing Zhang, Jiu-meng Liu, Hong-liang Zhang, Qiang Zhang, and Ke-bin He
Atmos. Chem. Phys., 24, 9869–9883, https://doi.org/10.5194/acp-24-9869-2024, https://doi.org/10.5194/acp-24-9869-2024, 2024
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The agreement between observational and modeling results is essential for the development of efficient air pollution control strategies. Here we constrained the modeling results of carbonaceous aerosols by field observation in Northeast China, a historically overlooked but recently targeted region of national clean-air actions. Our study suggested that the simulation of agricultural fire emissions and secondary organic aerosols remains challenging.
Nana Wu, Guannan Geng, Ruochong Xu, Shigan Liu, Xiaodong Liu, Qinren Shi, Ying Zhou, Yu Zhao, Huan Liu, Yu Song, Junyu Zheng, Qiang Zhang, and Kebin He
Earth Syst. Sci. Data, 16, 2893–2915, https://doi.org/10.5194/essd-16-2893-2024, https://doi.org/10.5194/essd-16-2893-2024, 2024
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The commonly used method for developing large-scale air pollutant emission datasets for China faces challenges due to limited availability of detailed parameter information. In this study, we develop an efficient integrated framework to gather such information by harmonizing seven heterogeneous inventories from five research institutions. Emission characterizations are analyzed and validated, demonstrating that the dataset provides more accurate emission magnitudes and spatiotemporal patterns.
Meng Li, Junichi Kurokawa, Qiang Zhang, Jung-Hun Woo, Tazuko Morikawa, Satoru Chatani, Zifeng Lu, Yu Song, Guannan Geng, Hanwen Hu, Jinseok Kim, Owen R. Cooper, and Brian C. McDonald
Atmos. Chem. Phys., 24, 3925–3952, https://doi.org/10.5194/acp-24-3925-2024, https://doi.org/10.5194/acp-24-3925-2024, 2024
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In this work, we developed MIXv2, a mosaic Asian emission inventory for 2010–2017. With high spatial (0.1°) and monthly temporal resolution, MIXv2 integrates anthropogenic and open biomass burning emissions across seven sectors following a mosaic methodology. It provides CO2 emissions data alongside nine key pollutants and three chemical mechanisms. Our publicly accessible gridded monthly emissions data can facilitate long-term atmospheric and climate model analyses.
Lorrie Simone Denise Jacob, Chiara Giorio, and Alexander Thomas Archibald
Atmos. Chem. Phys., 24, 3329–3347, https://doi.org/10.5194/acp-24-3329-2024, https://doi.org/10.5194/acp-24-3329-2024, 2024
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Recent studies on DMS have provided new challenges to our mechanistic understanding. Here we synthesise a number of recent studies to further develop and extend a state-of-the-art mechanism. Our new mechanism is shown to outperform all existing mechanisms when compared over a wide set of conditions. The development of an improved DMS mechanism will help lead the way to better the understanding the climate impacts of DMS emissions in past, present, and future atmospheric conditions.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Yusuf A. Bhatti, Laura E. Revell, Alex J. Schuddeboom, Adrian J. McDonald, Alex T. Archibald, Jonny Williams, Abhijith U. Venugopal, Catherine Hardacre, and Erik Behrens
Atmos. Chem. Phys., 23, 15181–15196, https://doi.org/10.5194/acp-23-15181-2023, https://doi.org/10.5194/acp-23-15181-2023, 2023
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Aerosols are a large source of uncertainty over the Southern Ocean. A dominant source of sulfate aerosol in this region is dimethyl sulfide (DMS), which is poorly simulated by climate models. We show the sensitivity of simulated atmospheric DMS to the choice of oceanic DMS data set and emission scheme. We show that oceanic DMS has twice the influence on atmospheric DMS than the emission scheme. Simulating DMS more accurately in climate models will help to constrain aerosol uncertainty.
Ben A. Cala, Scott Archer-Nicholls, James Weber, N. Luke Abraham, Paul T. Griffiths, Lorrie Jacob, Y. Matthew Shin, Laura E. Revell, Matthew Woodhouse, and Alexander T. Archibald
Atmos. Chem. Phys., 23, 14735–14760, https://doi.org/10.5194/acp-23-14735-2023, https://doi.org/10.5194/acp-23-14735-2023, 2023
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Dimethyl sulfide (DMS) is an important trace gas emitted from the ocean recognised as setting the sulfate aerosol background, but its oxidation is complex. As a result representation in chemistry-climate models is greatly simplified. We develop and compare a new mechanism to existing mechanisms via a series of global and box model experiments. Our studies show our updated DMS scheme is a significant improvement but significant variance exists between mechanisms.
Nicola J. Warwick, Alex T. Archibald, Paul T. Griffiths, James Keeble, Fiona M. O'Connor, John A. Pyle, and Keith P. Shine
Atmos. Chem. Phys., 23, 13451–13467, https://doi.org/10.5194/acp-23-13451-2023, https://doi.org/10.5194/acp-23-13451-2023, 2023
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A chemistry–climate model has been used to explore the atmospheric response to changes in emissions of hydrogen and other species associated with a shift from fossil fuel to hydrogen use. Leakage of hydrogen results in indirect global warming, offsetting greenhouse gas emission reductions from reduced fossil fuel use. To maximise the benefit of hydrogen as an energy source, hydrogen leakage and emissions of methane, carbon monoxide and nitrogen oxides should be minimised.
Maria Rosa Russo, Brian John Kerridge, Nathan Luke Abraham, James Keeble, Barry Graham Latter, Richard Siddans, James Weber, Paul Thomas Griffiths, John Adrian Pyle, and Alexander Thomas Archibald
Atmos. Chem. Phys., 23, 6169–6196, https://doi.org/10.5194/acp-23-6169-2023, https://doi.org/10.5194/acp-23-6169-2023, 2023
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Tropospheric ozone is an important component of the Earth system as it can affect both climate and air quality. In this work we use observed tropospheric ozone derived from satellite observations and compare it to tropospheric ozone from model simulations. Our aim is to investigate recent changes (2005–2018) in tropospheric ozone in the North Atlantic region and to understand what factors are driving such changes.
Scott Archer-Nicholls, Rachel Allen, Nathan L. Abraham, Paul T. Griffiths, and Alex T. Archibald
Atmos. Chem. Phys., 23, 5801–5813, https://doi.org/10.5194/acp-23-5801-2023, https://doi.org/10.5194/acp-23-5801-2023, 2023
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The nitrate radical is a major oxidant at nighttime, but much less is known about it than about the other oxidants ozone and OH. We use Earth system model calculations to show how the nitrate radical has changed in abundance from 1850–2014 and to 2100 under a range of different climate and emission scenarios. Depending on the emissions and climate scenario, significant increases are projected with implications for the oxidation of volatile organic compounds and the formation of fine aerosol.
Ernesto Reyes-Villegas, Douglas Lowe, Jill S. Johnson, Kenneth S. Carslaw, Eoghan Darbyshire, Michael Flynn, James D. Allan, Hugh Coe, Ying Chen, Oliver Wild, Scott Archer-Nicholls, Alex Archibald, Siddhartha Singh, Manish Shrivastava, Rahul A. Zaveri, Vikas Singh, Gufran Beig, Ranjeet Sokhi, and Gordon McFiggans
Atmos. Chem. Phys., 23, 5763–5782, https://doi.org/10.5194/acp-23-5763-2023, https://doi.org/10.5194/acp-23-5763-2023, 2023
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Organic aerosols (OAs), their sources and their processes remain poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem, can be a useful tool to describe primary OA (POA) production and aging. However, the main disadvantage is its complexity. We used a Gaussian process simulator to reproduce model results and to estimate the sources of model uncertainty. We do this by comparing the outputs with OA observations made at Delhi, India, in 2018.
Joanna E. Dyson, Lisa K. Whalley, Eloise J. Slater, Robert Woodward-Massey, Chunxiang Ye, James D. Lee, Freya Squires, James R. Hopkins, Rachel E. Dunmore, Marvin Shaw, Jacqueline F. Hamilton, Alastair C. Lewis, Stephen D. Worrall, Asan Bacak, Archit Mehra, Thomas J. Bannan, Hugh Coe, Carl J. Percival, Bin Ouyang, C. Nicholas Hewitt, Roderic L. Jones, Leigh R. Crilley, Louisa J. Kramer, W. Joe F. Acton, William J. Bloss, Supattarachai Saksakulkrai, Jingsha Xu, Zongbo Shi, Roy M. Harrison, Simone Kotthaus, Sue Grimmond, Yele Sun, Weiqi Xu, Siyao Yue, Lianfang Wei, Pingqing Fu, Xinming Wang, Stephen R. Arnold, and Dwayne E. Heard
Atmos. Chem. Phys., 23, 5679–5697, https://doi.org/10.5194/acp-23-5679-2023, https://doi.org/10.5194/acp-23-5679-2023, 2023
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The hydroxyl (OH) and closely coupled hydroperoxyl (HO2) radicals are vital for their role in the removal of atmospheric pollutants. In less polluted regions, atmospheric models over-predict HO2 concentrations. In this modelling study, the impact of heterogeneous uptake of HO2 onto aerosol surfaces on radical concentrations and the ozone production regime in Beijing in the summertime is investigated, and the implications for emissions policies across China are considered.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
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Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Fouzia Fahrin, Daniel C. Jones, Yan Wu, James Keeble, and Alexander T. Archibald
Atmos. Chem. Phys., 23, 3609–3627, https://doi.org/10.5194/acp-23-3609-2023, https://doi.org/10.5194/acp-23-3609-2023, 2023
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We use a machine learning technique called Gaussian mixture modeling (GMM) to classify vertical ozone profiles into groups based on how the ozone concentration changes with pressure. Even though the GMM algorithm was not provided with spatial information, the classes are geographically coherent. We also detect signatures of tropical broadening in UKESM1 future climate scenarios. GMM may be useful for understanding ozone structures in modeled and observed datasets.
Qingyang Xiao, Guannan Geng, Shigan Liu, Jiajun Liu, Xia Meng, and Qiang Zhang
Atmos. Chem. Phys., 22, 13229–13242, https://doi.org/10.5194/acp-22-13229-2022, https://doi.org/10.5194/acp-22-13229-2022, 2022
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We provided complete coverage PM2.5 concentrations at a 1-km resolution from 2000 to the present, carefully considering the significant changes in land use characteristics in China. This high-resolution PM2.5 data successfully revealed the local-scale PM2.5 variations. We noticed changes in PM2.5 spatial patterns in association with the clean air policies, with the pollution hotspots having transferred from urban centers to rural regions with limited air quality monitoring.
Marios Panagi, Roberto Sommariva, Zoë L. Fleming, Paul S. Monks, Gongda Lu, Eloise A. Marais, James R. Hopkins, Alastair C. Lewis, Qiang Zhang, James D. Lee, Freya A. Squires, Lisa K. Whalley, Eloise J. Slater, Dwayne E. Heard, Robert Woodward-Massey, Chunxiang Ye, and Joshua D. Vande Hey
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-379, https://doi.org/10.5194/acp-2022-379, 2022
Revised manuscript not accepted
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A dispersion model and a box model were combined to investigate the evolution of VOCs in Beijing once they are emitted from anthropogenic sources. It was determined that during the winter time the VOC concentrations in Beijing are driven predominantly by sources within Beijing and by a combination of transport and chemistry during the summer. Furthermore, the results in the paper highlight the need for a season specific policy.
Daniel R. Peters, Olalekan A. M. Popoola, Roderic L. Jones, Nicholas A. Martin, Jim Mills, Elizabeth R. Fonseca, Amy Stidworthy, Ella Forsyth, David Carruthers, Megan Dupuy-Todd, Felicia Douglas, Katie Moore, Rishabh U. Shah, Lauren E. Padilla, and Ramón A. Alvarez
Atmos. Meas. Tech., 15, 321–334, https://doi.org/10.5194/amt-15-321-2022, https://doi.org/10.5194/amt-15-321-2022, 2022
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We present more than 2 years of NO2 pollution measurements from a sensor network in Greater London and compare results to an extensive network of expensive reference-grade monitors. We show the ability of our lower-cost network to generate robust insights about local air pollution. We also show how irregularities in sensor performance lead to some uncertainty in results and demonstrate ways that future users can characterize and mitigate uncertainties to get the most value from sensor data.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Yuqiang Zhang, Drew Shindell, Karl Seltzer, Lu Shen, Jean-Francois Lamarque, Qiang Zhang, Bo Zheng, Jia Xing, Zhe Jiang, and Lei Zhang
Atmos. Chem. Phys., 21, 16051–16065, https://doi.org/10.5194/acp-21-16051-2021, https://doi.org/10.5194/acp-21-16051-2021, 2021
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In this study, we use a global chemical transport model to simulate the effects on global air quality and human health due to emission changes in China from 2010 to 2017. By performing sensitivity analysis, we found that the air pollution control policies not only decrease the air pollutant concentration but also bring significant co-benefits in air quality to downwind regions. The benefits for the improved air pollution are dominated by PM2.5.
Yuan Cheng, Qin-qin Yu, Jiu-meng Liu, Xu-bing Cao, Ying-jie Zhong, Zhen-yu Du, Lin-lin Liang, Guan-nan Geng, Wan-li Ma, Hong Qi, Qiang Zhang, and Ke-bin He
Atmos. Chem. Phys., 21, 15199–15211, https://doi.org/10.5194/acp-21-15199-2021, https://doi.org/10.5194/acp-21-15199-2021, 2021
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Open burning policies in Heilongjiang Province experienced a rapid transition during 2018 to 2020. This study evaluated the responses of PM2.5 pollution to this transition and suggested that neither of the policies could be considered successful. In addition, heterogeneous reactions were found to be at play in secondary aerosol formation, even in the frigid atmosphere in Heilongjiang. The unique haze in northeast China deserves more attention.
Michael Biggart, Jenny Stocker, Ruth M. Doherty, Oliver Wild, David Carruthers, Sue Grimmond, Yiqun Han, Pingqing Fu, and Simone Kotthaus
Atmos. Chem. Phys., 21, 13687–13711, https://doi.org/10.5194/acp-21-13687-2021, https://doi.org/10.5194/acp-21-13687-2021, 2021
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Heat-related illnesses are of increasing concern in China given its rapid urbanisation and our ever-warming climate. We examine the relative impacts that land surface properties and anthropogenic heat have on the urban heat island (UHI) in Beijing using ADMS-Urban. Air temperature measurements and satellite-derived land surface temperatures provide valuable means of evaluating modelled spatiotemporal variations. This work provides critical information for urban planners and UHI mitigation.
James Weber, Scott Archer-Nicholls, Nathan Luke Abraham, Youngsub M. Shin, Thomas J. Bannan, Carl J. Percival, Asan Bacak, Paulo Artaxo, Michael Jenkin, M. Anwar H. Khan, Dudley E. Shallcross, Rebecca H. Schwantes, Jonathan Williams, and Alex T. Archibald
Geosci. Model Dev., 14, 5239–5268, https://doi.org/10.5194/gmd-14-5239-2021, https://doi.org/10.5194/gmd-14-5239-2021, 2021
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The new mechanism CRI-Strat 2 features state-of-the-art isoprene chemistry not previously available in UKCA and improves UKCA's ability to reproduce observed concentrations of isoprene, monoterpenes, and OH in tropical regions. The enhanced ability to model isoprene, the most widely emitted non-methane volatile organic compound (VOC), will allow understanding of how isoprene and other biogenic VOCs affect atmospheric composition and, through biosphere–atmosphere feedbacks, climate change.
Gongda Lu, Eloise A. Marais, Tuan V. Vu, Jingsha Xu, Zongbo Shi, James D. Lee, Qiang Zhang, Lu Shen, Gan Luo, and Fangqun Yu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-428, https://doi.org/10.5194/acp-2021-428, 2021
Revised manuscript not accepted
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Emission controls were imposed in Beijing-Tianjin-Hebei in northern China in autumn-winter 2017. We find that regional PM2.5 targets (15 % decrease relative to previous year) were exceeded. Our analysis shows that decline in precursor emissions only leads to less than half (43 %) the improved air quality. Most of the change (57 %) is due to interannual variability in meteorology. Stricter emission controls may be necessary in years with unfavourable meteorology.
Meng Gao, Yang Yang, Hong Liao, Bin Zhu, Yuxuan Zhang, Zirui Liu, Xiao Lu, Chen Wang, Qiming Zhou, Yuesi Wang, Qiang Zhang, Gregory R. Carmichael, and Jianlin Hu
Atmos. Chem. Phys., 21, 11405–11421, https://doi.org/10.5194/acp-21-11405-2021, https://doi.org/10.5194/acp-21-11405-2021, 2021
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Light absorption and radiative forcing of black carbon (BC) is influenced by both BC itself and its interactions with other aerosol chemical compositions. In this study, we used the online coupled WRF-Chem model to examine how emission control measures during the Asian-Pacific Economic Cooperation (APEC) conference affect the mixing state and light absorption of BC and the associated implications for BC-PBL interactions.
Benjamin A. Nault, Duseong S. Jo, Brian C. McDonald, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Jason C. Schroder, James Allan, Donald R. Blake, Manjula R. Canagaratna, Hugh Coe, Matthew M. Coggon, Peter F. DeCarlo, Glenn S. Diskin, Rachel Dunmore, Frank Flocke, Alan Fried, Jessica B. Gilman, Georgios Gkatzelis, Jacqui F. Hamilton, Thomas F. Hanisco, Patrick L. Hayes, Daven K. Henze, Alma Hodzic, James Hopkins, Min Hu, L. Greggory Huey, B. Thomas Jobson, William C. Kuster, Alastair Lewis, Meng Li, Jin Liao, M. Omar Nawaz, Ilana B. Pollack, Jeffrey Peischl, Bernhard Rappenglück, Claire E. Reeves, Dirk Richter, James M. Roberts, Thomas B. Ryerson, Min Shao, Jacob M. Sommers, James Walega, Carsten Warneke, Petter Weibring, Glenn M. Wolfe, Dominique E. Young, Bin Yuan, Qiang Zhang, Joost A. de Gouw, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 11201–11224, https://doi.org/10.5194/acp-21-11201-2021, https://doi.org/10.5194/acp-21-11201-2021, 2021
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Secondary organic aerosol (SOA) is an important aspect of poor air quality for urban regions around the world, where a large fraction of the population lives. However, there is still large uncertainty in predicting SOA in urban regions. Here, we used data from 11 urban campaigns and show that the variability in SOA production in these regions is predictable and is explained by key emissions. These results are used to estimate the premature mortality associated with SOA in urban regions.
Qingyang Xiao, Yixuan Zheng, Guannan Geng, Cuihong Chen, Xiaomeng Huang, Huizheng Che, Xiaoye Zhang, Kebin He, and Qiang Zhang
Atmos. Chem. Phys., 21, 9475–9496, https://doi.org/10.5194/acp-21-9475-2021, https://doi.org/10.5194/acp-21-9475-2021, 2021
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We used both statistical methods and a chemical transport model to assess the contribution of meteorology and emissions to PM2.5 during 2000–2018. Both methods revealed that emissions dominated the long-term PM2.5 trend with notable meteorological effects ranged up to 37.9 % of regional annual average PM2.5. The meteorological contribution became more beneficial to PM2.5 control in southern China but more unfavorable in northern China during the studied period.
Bo Zheng, Qiang Zhang, Guannan Geng, Cuihong Chen, Qinren Shi, Mengshi Cui, Yu Lei, and Kebin He
Earth Syst. Sci. Data, 13, 2895–2907, https://doi.org/10.5194/essd-13-2895-2021, https://doi.org/10.5194/essd-13-2895-2021, 2021
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Here we report the monthly anthropogenic pollutant emissions in China during the COVID-19 pandemic by using a bottom-up approach based on near-real-time data. The COVID lockdowns were estimated to have reduced China's emissions substantially between January and March in 2020, with the largest reduction in February. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to levels comparable to those of 2019 through December 2020.
John Staunton-Sykes, Thomas J. Aubry, Youngsub M. Shin, James Weber, Lauren R. Marshall, Nathan Luke Abraham, Alex Archibald, and Anja Schmidt
Atmos. Chem. Phys., 21, 9009–9029, https://doi.org/10.5194/acp-21-9009-2021, https://doi.org/10.5194/acp-21-9009-2021, 2021
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Short summary
Emission estimates represent a major source of uncertainty in air quality modelling. We developed a novel approach to improve emission estimates from existing inventories using air quality models and routine in situ observations. Using this approach, we derived improved estimates of NOx emissions from the transport sector in Beijing in 2016. This approach has great potential in deriving timely updates of emissions for other pollutants, particularly in regions undergoing rapid emission changes.
Emission estimates represent a major source of uncertainty in air quality modelling. We...
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