Articles | Volume 22, issue 9
https://doi.org/10.5194/acp-22-6291-2022
© 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-22-6291-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Trends in secondary inorganic aerosol pollution in China and its responses to emission controls of precursors in wintertime
Fanlei Meng
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
Yibo Zhang
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou,
Zhejiang 310058, P.R. China
Jiahui Kang
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
Mathew R. Heal
School of Chemistry, The University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
Stefan Reis
UK Centre for Ecology & Hydrology, Penicuik, EH26 0QB, United
Kingdom
School of Chemistry, The University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
University of Exeter Medical School, European Centre for Environment and Human Health, Knowledge Spa, Truro, TR1 3HD United Kingdom
Mengru Wang
Water Systems and Global Change Group, Wageningen University &
Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Lei Liu
College of Earth and Environmental Sciences, Lanzhou University,
Lanzhou 730000, China
Kai Wang
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
Research Center for Air Pollution and Health, Key Laboratory of
Environmental Remediation and Ecological Health, Ministry of Education,
College of Environment and Resource Sciences, Zhejiang University, Hangzhou,
Zhejiang 310058, P.R. China
Pengfei Li
College of Science and Technology, Hebei Agricultural University,
Baoding, Hebei 071000, China
Department of Atmospheric and Oceanic Science, Earth System Science
Interdisciplinary Center, University of Maryland, College Park 20740, USA
Yong Hou
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
Ying Zhang
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
Xuejun Liu
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
Zhenling Cui
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
Fusuo Zhang
College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant–Soil Interactions,
Ministry of Education, National Observation and Research Station of
Agriculture Green Development (Quzhou, Hebei), China Agricultural
University, Beijing 100193, China
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Biao Luo, Lei Liu, David H. Y. Yung, Tiangang Yuan, Jingwei Zhang, Leo T. H. Ng, and Amos P. K. Tai
Atmos. Chem. Phys., 25, 10089–10108, https://doi.org/10.5194/acp-25-10089-2025, https://doi.org/10.5194/acp-25-10089-2025, 2025
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Through a combination of emission models and air quality models, this study aims to address the pressing issue of poor nitrogen management while promoting sustainable food systems and public health in China. We discovered that improving nitrogen management of crops and livestock can substantially reduce air pollutant emissions, particularly in the North China Plain. Our findings further provide the benefits of such interventions for PM2.5 reductions, offering valuable insights for policymakers.
Zhe Song, Shaocai Yu, Pengfei Li, Ningning Yao, Lang Chen, Yuhai Sun, Boqiong Jiang, and Daniel Rosenfeld
Atmos. Chem. Phys., 25, 2473–2494, https://doi.org/10.5194/acp-25-2473-2025, https://doi.org/10.5194/acp-25-2473-2025, 2025
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Our results with injected sea salt aerosols for five open oceans show that sea salt aerosols with low injection amounts dominate shortwave radiation, mainly through indirect effects. As indirect aerosol effects saturate with increasing injection rates, direct effects exceed indirect effects. This implies that marine cloud brightening is best implemented in areas with extensive cloud cover, while aerosol direct scattering effects remain dominant when clouds are scarce.
Xu Yang, Fobang Liu, Shuqi Yang, Yuling Yang, Yanan Wang, Jingjing Li, Mingyu Zhao, Zhao Wang, Kai Wang, Chi He, and Haijie Tong
Atmos. Chem. Phys., 24, 11029–11043, https://doi.org/10.5194/acp-24-11029-2024, https://doi.org/10.5194/acp-24-11029-2024, 2024
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A study in the rural North China Plain showed environmentally persistent free radicals (EPFRs) in atmospheric particulate matter (PM), with a notable water-soluble fraction likely from atmospheric oxidation during transport. Significant positive correlations between EPFRs and the water-soluble oxidative potential of PM2.5 were found, primarily attributable to the water-soluble fractions of EPFRs. These findings emphasize understanding EPFRs' atmospheric evolution for climate and health impacts.
Yao Ge, Sverre Solberg, Mathew R. Heal, Stefan Reimann, Willem van Caspel, Bryan Hellack, Thérèse Salameh, and David Simpson
Atmos. Chem. Phys., 24, 7699–7729, https://doi.org/10.5194/acp-24-7699-2024, https://doi.org/10.5194/acp-24-7699-2024, 2024
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Atmospheric volatile organic compounds (VOCs) constitute many species, acting as precursors to ozone and aerosol. Given the uncertainties in VOC emissions, lack of evaluation studies, and recent changes in emissions, this work adapts the EMEP MSC-W to evaluate emission inventories in Europe. We focus on the varying agreement between modelled and measured VOCs across different species and underscore potential inaccuracies in total and sector-specific emission estimates.
Prerita Agarwal, David S. Stevenson, and Mathew R. Heal
Atmos. Chem. Phys., 24, 2239–2266, https://doi.org/10.5194/acp-24-2239-2024, https://doi.org/10.5194/acp-24-2239-2024, 2024
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Air pollution levels across northern India are amongst some of the worst in the world, with episodic and hazardous haze events. Here, the ability of the WRF-Chem model to predict air quality over northern India is assessed against several datasets. Whilst surface wind speed and particle pollution peaks are over- and underestimated, respectively, meteorology and aerosol trends are adequately captured, and we conclude it is suitable for investigating severe particle pollution events.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Gemma Purser, Mathew R. Heal, Edward J. Carnell, Stephen Bathgate, Julia Drewer, James I. L. Morison, and Massimo Vieno
Atmos. Chem. Phys., 23, 13713–13733, https://doi.org/10.5194/acp-23-13713-2023, https://doi.org/10.5194/acp-23-13713-2023, 2023
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Forest expansion is a ″net-zero“ pathway, but change in land cover alters air quality in many ways. This study combines tree planting suitability data with UK measured emissions of biogenic volatile organic compounds to simulate spatial and temporal changes in atmospheric composition for planting scenarios of four species. Decreases in fine particulate matter are relatively larger than increases in ozone, which may indicate a net benefit of tree planting on human health aspects of air quality.
Kaiyue Zhou, Wen Xu, Lin Zhang, Mingrui Ma, Xuejun Liu, and Yu Zhao
Atmos. Chem. Phys., 23, 8531–8551, https://doi.org/10.5194/acp-23-8531-2023, https://doi.org/10.5194/acp-23-8531-2023, 2023
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We developed a dataset of the long-term (2005–2020) variabilities of China’s nitrogen and sulfur deposition, with multiple statistical models that combine available observations and chemistry transport modeling. We demonstrated the strong impact of human activities and national pollution control actions on the spatiotemporal changes in deposition and indicated a relatively small benefit of emission abatement on deposition (and thereby ecological risk) for China compared to Europe and the USA.
Yao Ge, Massimo Vieno, David S. Stevenson, Peter Wind, and Mathew R. Heal
Atmos. Chem. Phys., 23, 6083–6112, https://doi.org/10.5194/acp-23-6083-2023, https://doi.org/10.5194/acp-23-6083-2023, 2023
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The sensitivity of fine particles and reactive N and S species to reductions in precursor emissions is investigated using the EMEP MSC-W (European Monitoring and Evaluation Programme Meteorological Synthesizing Centre – West) atmospheric chemistry transport model. This study reveals that the individual emissions reduction has multiple and geographically varying co-benefits and small disbenefits on different species, demonstrating the importance of prioritizing regional emissions controls.
Yuchen Wang, Xvli Guo, Yajie Huo, Mengying Li, Yuqing Pan, Shaocai Yu, Alexander Baklanov, Daniel Rosenfeld, John H. Seinfeld, and Pengfei Li
Atmos. Chem. Phys., 23, 5233–5249, https://doi.org/10.5194/acp-23-5233-2023, https://doi.org/10.5194/acp-23-5233-2023, 2023
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Substantial advances have been made in recent years toward detecting and quantifying methane super-emitters from space. However, such advances have rarely been expanded to measure the global methane pledge because large-scale swaths and high-resolution sampling have not been coordinated. Here we present a versatile spaceborne architecture that can juggle planet-scale and plant-level methane retrievals, challenge official emission reports, and remain relevant for stereoscopic measurements.
Chuanhua Ren, Xin Huang, Tengyu Liu, Yu Song, Zhang Wen, Xuejun Liu, Aijun Ding, and Tong Zhu
Geosci. Model Dev., 16, 1641–1659, https://doi.org/10.5194/gmd-16-1641-2023, https://doi.org/10.5194/gmd-16-1641-2023, 2023
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Ammonia in the atmosphere has wide impacts on the ecological environment and air quality, and its emission from soil volatilization is highly sensitive to meteorology, making it challenging to be well captured in models. We developed a dynamic emission model capable of calculating ammonia emission interactively with meteorological and soil conditions. Such a coupling of soil emission with meteorology provides a better understanding of ammonia emission and its contribution to atmospheric aerosol.
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023, https://doi.org/10.5194/acp-23-1511-2023, 2023
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This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
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This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Pu Liu, Jia Ding, Lei Liu, Wen Xu, and Xuejun Liu
Atmos. Chem. Phys., 22, 9099–9110, https://doi.org/10.5194/acp-22-9099-2022, https://doi.org/10.5194/acp-22-9099-2022, 2022
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Ammonia (NH3) is the important alkaline gas and the key component of fine particulate matter. We used satellite-based observations to analyze the changes in hourly NH3 concentrations and estimated surface NH3 concentrations and NH3 emissions in China. This study shows enormous potential for using satellite data to estimate surface NH3 concentrations and NH3 emissions and provides an important reference for understanding NH3 variation in China.
Yao Ge, Massimo Vieno, David S. Stevenson, Peter Wind, and Mathew R. Heal
Atmos. Chem. Phys., 22, 8343–8368, https://doi.org/10.5194/acp-22-8343-2022, https://doi.org/10.5194/acp-22-8343-2022, 2022
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Reactive N and S gases and aerosols are critical determinants of air quality. We report a comprehensive analysis of the concentrations, wet and dry deposition, fluxes, and lifetimes of these species globally as well as for 10 world regions. We used the EMEP MSC-W model coupled with WRF meteorology and 2015 global emissions. Our work demonstrates the substantial regional variation in these quantities and the need for modelling to simulate atmospheric responses to precursor emissions.
Yun Lin, Jiwen Fan, Pengfei Li, Lai-yung Ruby Leung, Paul J. DeMott, Lexie Goldberger, Jennifer Comstock, Ying Liu, Jong-Hoon Jeong, and Jason Tomlinson
Atmos. Chem. Phys., 22, 6749–6771, https://doi.org/10.5194/acp-22-6749-2022, https://doi.org/10.5194/acp-22-6749-2022, 2022
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How sea spray aerosols may affect cloud and precipitation over the region by acting as ice-nucleating particles (INPs) is unknown. We explored the effects of INPs from marine aerosols on orographic cloud and precipitation for an atmospheric river event observed during the 2015 ACAPEX field campaign. The marine INPs enhance the formation of ice and snow, leading to less shallow warm clouds but more mixed-phase and deep clouds. This work suggests models need to consider the impacts of marine INPs.
Kai Wang, Yang Zhang, Shaocai Yu, David C. Wong, Jonathan Pleim, Rohit Mathur, James T. Kelly, and Michelle Bell
Geosci. Model Dev., 14, 7189–7221, https://doi.org/10.5194/gmd-14-7189-2021, https://doi.org/10.5194/gmd-14-7189-2021, 2021
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The two-way coupled WRF-CMAQ model accounting for complex chemistry–meteorology feedbacks has been applied to the long-term predictions of regional meteorology and air quality over the US. The model results show superior performance and importance of chemistry–meteorology feedbacks when compared to the offline coupled WRF and CMAQ simulations, which suggests that feedbacks should be considered along with other factors in developing future model applications to inform policy making.
Linhui Jiang, Yan Xia, Lu Wang, Xue Chen, Jianjie Ye, Tangyan Hou, Liqiang Wang, Yibo Zhang, Mengying Li, Zhen Li, Zhe Song, Yaping Jiang, Weiping Liu, Pengfei Li, Daniel Rosenfeld, John H. Seinfeld, and Shaocai Yu
Atmos. Chem. Phys., 21, 16985–17002, https://doi.org/10.5194/acp-21-16985-2021, https://doi.org/10.5194/acp-21-16985-2021, 2021
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This paper establishes a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at a spatial resolution 1–3 orders of magnitude higher than current inventories. The results show that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74 kg, 40 kg, 8 kg, and 2 kg, respectively. Integrating our traffic-monitoring-based approach with urban measurements, we could address major data gaps between urban air pollutant emissions and concentrations.
Yao Ge, Mathew R. Heal, David S. Stevenson, Peter Wind, and Massimo Vieno
Geosci. Model Dev., 14, 7021–7046, https://doi.org/10.5194/gmd-14-7021-2021, https://doi.org/10.5194/gmd-14-7021-2021, 2021
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This study reports the first evaluation of the global EMEP MSC-W ACTM driven by WRF meteorology, with a focus on surface concentrations and wet deposition of reactive N and S species. The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. The statistics from the comprehensive evaluations presented in this study support the application of this model framework for global analysis of the budgets and fluxes of reactive N and SIA.
Ernesto Reyes-Villegas, Upasana Panda, Eoghan Darbyshire, James M. Cash, Rutambhara Joshi, Ben Langford, Chiara F. Di Marco, Neil J. Mullinger, Mohammed S. Alam, Leigh R. Crilley, Daniel J. Rooney, W. Joe F. Acton, Will Drysdale, Eiko Nemitz, Michael Flynn, Aristeidis Voliotis, Gordon McFiggans, Hugh Coe, James Lee, C. Nicholas Hewitt, Mathew R. Heal, Sachin S. Gunthe, Tuhin K. Mandal, Bhola R. Gurjar, Shivani, Ranu Gadi, Siddhartha Singh, Vijay Soni, and James D. Allan
Atmos. Chem. Phys., 21, 11655–11667, https://doi.org/10.5194/acp-21-11655-2021, https://doi.org/10.5194/acp-21-11655-2021, 2021
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This paper shows the first multisite online measurements of PM1 in Delhi, India, with measurements over different seasons in Old Delhi and New Delhi in 2018. Organic aerosol (OA) source apportionment was performed using positive matrix factorisation (PMF). Traffic was the main primary aerosol source for both OAs and black carbon, seen with PMF and Aethalometer model analysis, indicating that control of primary traffic exhaust emissions would make a significant reduction to Delhi air pollution.
James M. Cash, Ben Langford, Chiara Di Marco, Neil J. Mullinger, James Allan, Ernesto Reyes-Villegas, Ruthambara Joshi, Mathew R. Heal, W. Joe F. Acton, C. Nicholas Hewitt, Pawel K. Misztal, Will Drysdale, Tuhin K. Mandal, Shivani, Ranu Gadi, Bhola Ram Gurjar, and Eiko Nemitz
Atmos. Chem. Phys., 21, 10133–10158, https://doi.org/10.5194/acp-21-10133-2021, https://doi.org/10.5194/acp-21-10133-2021, 2021
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We present the first real-time composition of submicron particulate matter (PM1) in Old Delhi using high-resolution aerosol mass spectrometry. Seasonal analysis shows peak concentrations occur during the post-monsoon, and novel-tracers reveal the largest sources are a combination of local open and regional crop residue burning. Strong links between increased chloride aerosol concentrations and burning sources of PM1 suggest burning sources are responsible for the post-monsoon chloride peak.
Jing Wei, Zhanqing Li, Rachel T. Pinker, Jun Wang, Lin Sun, Wenhao Xue, Runze Li, and Maureen Cribb
Atmos. Chem. Phys., 21, 7863–7880, https://doi.org/10.5194/acp-21-7863-2021, https://doi.org/10.5194/acp-21-7863-2021, 2021
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This study developed a space-time Light Gradient Boosting Machine (STLG) model to derive the high-temporal-resolution (1 h) and high-quality PM2.5 dataset in China (i.e., ChinaHighPM2.5) at a 5 km spatial resolution from the Himawari-8 Advanced Himawari Imager aerosol products. Our model outperforms most previous related studies with a much lower computation burden in terms of speed and memory, making it most suitable for real-time air pollution monitoring in China.
Zixun Chen, Xuejun Liu, Xiaoqing Cui, Yaowen Han, Guoan Wang, and Jiazhu Li
Biogeosciences, 18, 2859–2870, https://doi.org/10.5194/bg-18-2859-2021, https://doi.org/10.5194/bg-18-2859-2021, 2021
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δ13C in plants is a sensitive long-term indicator of physiological acclimatization. The present study suggests that precipitation change and increasing atmospheric N deposition have little impact on δ13C of H. ammodendron, a dominant plant in central Asian deserts, but affect its gas exchange. In addition, this study shows that δ13C of H. ammodendron could not indicate its water use efficiency (WUE), suggesting that whether δ13C of C4 plants indicates WUE is species-specific.
Robbie Ramsay, Chiara F. Di Marco, Mathew R. Heal, Matthias Sörgel, Paulo Artaxo, Meinrat O. Andreae, and Eiko Nemitz
Biogeosciences, 18, 2809–2825, https://doi.org/10.5194/bg-18-2809-2021, https://doi.org/10.5194/bg-18-2809-2021, 2021
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The exchange of the gas ammonia between the atmosphere and the surface is an important biogeochemical process, but little is known of this exchange for certain ecosystems, such as the Amazon rainforest. This study took measurements of ammonia exchange over an Amazon rainforest site and subsequently modelled the observed deposition and emission patterns. We observed emissions of ammonia from the rainforest, which can be simulated accurately by using a canopy resistance modelling approach.
Pooja V. Pawar, Sachin D. Ghude, Chinmay Jena, Andrea Móring, Mark A. Sutton, Santosh Kulkarni, Deen Mani Lal, Divya Surendran, Martin Van Damme, Lieven Clarisse, Pierre-François Coheur, Xuejun Liu, Gaurav Govardhan, Wen Xu, Jize Jiang, and Tapan Kumar Adhya
Atmos. Chem. Phys., 21, 6389–6409, https://doi.org/10.5194/acp-21-6389-2021, https://doi.org/10.5194/acp-21-6389-2021, 2021
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In this study, simulations of atmospheric ammonia (NH3) with MOZART-4 and HTAP-v2 are compared with satellite (IASI) and ground-based measurements to understand the spatial and temporal variability of NH3 over two emission hotspot regions of Asia, the IGP and the NCP. Our simulations indicate that the formation of ammonium aerosols is quicker over the NCP than the IGP, leading to smaller NH3 columns over the higher NH3-emitting NCP compared to the IGP region for comparable emissions.
Gemma Purser, Julia Drewer, Mathew R. Heal, Robert A. S. Sircus, Lara K. Dunn, and James I. L. Morison
Biogeosciences, 18, 2487–2510, https://doi.org/10.5194/bg-18-2487-2021, https://doi.org/10.5194/bg-18-2487-2021, 2021
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Short-rotation forest plantations could help reduce greenhouse gases but can emit biogenic volatile organic compounds. Emissions were measured at a plantation trial in Scotland. Standardised emissions of isoprene from foliage were higher from hybrid aspen than from Sitka spruce and low from Italian alder. Emissions of total monoterpene were lower. The forest floor was only a small source. Model estimates suggest an SRF expansion of 0.7 Mha could increase total UK emissions between < 1 %–35 %.
Y. Sim Tang, Chris R. Flechard, Ulrich Dämmgen, Sonja Vidic, Vesna Djuricic, Marta Mitosinkova, Hilde T. Uggerud, Maria J. Sanz, Ivan Simmons, Ulrike Dragosits, Eiko Nemitz, Marsailidh Twigg, Netty van Dijk, Yannick Fauvel, Francisco Sanz, Martin Ferm, Cinzia Perrino, Maria Catrambone, David Leaver, Christine F. Braban, J. Neil Cape, Mathew R. Heal, and Mark A. Sutton
Atmos. Chem. Phys., 21, 875–914, https://doi.org/10.5194/acp-21-875-2021, https://doi.org/10.5194/acp-21-875-2021, 2021
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The DELTA® approach provided speciated, monthly data on reactive gases (NH3, HNO3, SO2, HCl) and aerosols (NH4+, NO3−, SO42−, Cl−, Na+) across Europe (2006–2010). Differences in spatial and temporal concentrations and patterns between geographic regions and four ecosystem types were captured. NH3 and NH4NO3 were dominant components, highlighting their growing relative importance in ecosystem impacts (acidification, eutrophication) and human health effects (NH3 as a precursor to PM2.5) in Europe.
Robbie Ramsay, Chiara F. Di Marco, Matthias Sörgel, Mathew R. Heal, Samara Carbone, Paulo Artaxo, Alessandro C. de Araùjo, Marta Sá, Christopher Pöhlker, Jost Lavric, Meinrat O. Andreae, and Eiko Nemitz
Atmos. Chem. Phys., 20, 15551–15584, https://doi.org/10.5194/acp-20-15551-2020, https://doi.org/10.5194/acp-20-15551-2020, 2020
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The Amazon rainforest is a unique
laboratoryto study the processes which govern the exchange of gases and aerosols to and from the atmosphere. This study investigated these processes by measuring the atmospheric concentrations of trace gases and particles at the Amazon Tall Tower Observatory. We found that the long-range transport of pollutants can affect the atmospheric composition above the Amazon rainforest and that the gases ammonia and nitrous acid can be emitted from the rainforest.
Liqiang Wang, Shaocai Yu, Pengfei Li, Xue Chen, Zhen Li, Yibo Zhang, Mengying Li, Khalid Mehmood, Weiping Liu, Tianfeng Chai, Yannian Zhu, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 20, 14787–14800, https://doi.org/10.5194/acp-20-14787-2020, https://doi.org/10.5194/acp-20-14787-2020, 2020
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The Chinese government has made major strides in curbing anthropogenic emissions. In this study, we constrain a state-of-the-art CTM by a reliable data assimilation method with extensive chemical and meteorological observations. This comprehensive technical design provides a crucial advance in isolating the influences of emission changes and meteorological perturbations over the Yangtze River Delta (YRD) from 2016 to 2019, thus establishing the first map of the PM2.5 mitigation across the YRD.
Baozhu Ge, Syuichi Itahashi, Keiichi Sato, Danhui Xu, Junhua Wang, Fan Fan, Qixin Tan, Joshua S. Fu, Xuemei Wang, Kazuyo Yamaji, Tatsuya Nagashima, Jie Li, Mizuo Kajino, Hong Liao, Meigen Zhang, Zhe Wang, Meng Li, Jung-Hun Woo, Junichi Kurokawa, Yuepeng Pan, Qizhong Wu, Xuejun Liu, and Zifa Wang
Atmos. Chem. Phys., 20, 10587–10610, https://doi.org/10.5194/acp-20-10587-2020, https://doi.org/10.5194/acp-20-10587-2020, 2020
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Performances of the simulated deposition for different reduced N (Nr) species in China were conducted with the Model Inter-Comparison Study for Asia. Results showed that simulated wet deposition of oxidized N was overestimated in northeastern China and underestimated in south China, but Nr was underpredicted in all regions by all models. Oxidized N has larger uncertainties than Nr, indicating that the chemical reaction process is one of the most importance factors affecting model performance.
Cited articles
An, Z. S., Huang, R. J., Zhang, R. Y., Tie, X. X., Li, G. H., Cao, J. J.,
Zhou, W. J., Shi, Z. G., Han, Y. M., Gu, Z. L., and Ji, Y. M.: Severe haze
in northern China: A synergy of anthropogenic emissions and atmospheric
processes, P. Natl. Acad. Sci. USA, 116, 8657–8666,
https://doi.org/10.1073/pnas.1900125116, 2019.
Backes, A., Aulinger, A., Bieser, J., Matthias, V., and Quante, M.: Ammonia
emissions in Europe, part II: How ammonia emission abatement strategies
affect secondary aerosols, Atmos. Environ., 126, 153–161,
https://doi.org/10.1016/j.atmosenv.2015.11.039, 2016.
Bai, Z., Winiwarter, W., Klimont, Z., Velthof, G., Misselbrook, T., Zhao,
Z., Jin, X., Oenema, O., Hu, C., and Ma, L.: Further improvement of air
quality in China needs clear ammonia mitigation target, Environ. Sci.
Technol., 53, 10542–10544, https://doi.org/10.1021/acs.est.9b04725, 2019.
Benitez-Lopez, A., Alkemade, R., Schipper, A. M., Ingram, D. J., Verweij, P.
A., Eikelboom, J. A. J., and Huijbregts, M. A. J.: The impact of hunting on
tropical mammal and bird populations, Science, 356, 180–183,
https://doi.org/10.1126/science.aaj1891, 2017.
Bracken, M. B.: Statistical methods for analysis of effects of treatment in
overviews of randomized trials, in: Effective care of the newborn infant, edited by: Sinclair, J. C. and Bracken, M. B., Oxford University Press, 1992.
Chen, Z., Chen, D., Wen, W., Zhuang, Y., Kwan, M.-P., Chen, B., Zhao, B., Yang, L., Gao, B., Li, R., and Xu, B.: Evaluating the “2+26” regional strategy for air quality improvement during two air pollution alerts in Beijing: variations in PM2.5 concentrations, source apportionment, and the relative contribution of local emission and regional transport, Atmos. Chem. Phys., 19, 6879–6891, https://doi.org/10.5194/acp-19-6879-2019, 2019.
Cheng, Y. F., Zheng, G. A., Wei, C., Mu, Q., Zheng, B., Wang, Z. B., Gao, M.,
Zhang, Q., He, K. B., Carmichael, G., Pöschl, U., and Su, H.: Reactive
nitrogen chemistry in aerosol water as a source of sulfate during haze
events in China, Sci. Adv., 2, e1601530, https://doi.org/10.1126/sciadv.1601530,
2016.
CEC (China Electricity Council): China Power Industry Annual Development Report
2019, https://www.cec.org.cn/yaowenkuaidi/2019-06-14/191782.html, last access: 14 June 2019.
CSC (China State Council): The 11th Five-Year plan on energy saving and
emissions reduction, http://www.gov.cn/zhengce/content/2008-03/28/content_4877.htm (last access: 28 March 2008), 2007.
CSC (China State Council): The 12th Five-Year plan on energy saving and
emissions reduction, http://www.gov.cn/zwgk/2011-12/20/content_2024895.htm, last access: 20 December 2011.
CSC (China State Council): Action Plan on Prevention and Control of Air
Pollution, China State Council, Beijing, China, http://www.gov.cn/zwgk/2013-09/12/content_2486773.htm, last access: 12 September 2013a.
CSC (China State Council): The 13th Five-Year plan on energy saving and
emissions reduction, http://www.gov.cn/zhengce/content/2016-12/05/content_5143290.htm, last access: 12 September 2013b.
CSC (China State Council): Air quality targets set by the Action Plan have
been fully realized, http://www.gov.cn/xinwen/2018-02/01/content_5262720.htm, last access: 1 February
2018a.
CSC (China State Council): Notice of the state council on issuing the
three-year action plan for winning the Blue Sky defense battle, http://www.gov.cn/zhengce/content/2018-07/03/content_5303158.htm, last access: 3 July 2018b.
Dunn, O. J.: Multiple comparisons using rank sums, Technometrics, 6, 241–252,
1964.
Fountoukis, C., Racherla, P. N., Denier van der Gon, H. A. C., Polymeneas, P., Charalampidis, P. E., Pilinis, C., Wiedensohler, A., Dall'Osto, M., O'Dowd, C., and Pandis, S. N.: Evaluation of a three-dimensional chemical transport model (PMCAMx) in the European domain during the EUCAARI May 2008 campaign, Atmos. Chem. Phys., 11, 10331–10347, https://doi.org/10.5194/acp-11-10331-2011, 2011.
Fan, C., Li, Z., Li, Y., Dong, J., van der A, R., and de Leeuw, G.: Variability of NO2 concentrations over China and effect on air quality derived from satellite and ground-based observations, Atmos. Chem. Phys., 21, 7723–7748, https://doi.org/10.5194/acp-21-7723-2021, 2021.
Feng, S. J., Xu, W., Cheng, M. M., Ma, Y. X., Wu, L. B., Kang, J. H., Wang,
K., Tang, A. H., Collett Jr., J. L., Fang, Y. T., Goulding, K., Liu, X. J.,
and Zhang, F. S.: Overlooked nonagricultural and wintertime agricultural
NH3 emissions in Quzhou County, North China Plain: Evidence from
15N-stable isotopes, Environ. Sci. Tech. Let., 9, 127–133,
https://doi.org/10.1021/acs.estlett.1c00935, 2022.
Gao, M., Carmichael, G. R., Wang, Y., Saide, P. E., Yu, M., Xin, J., Liu, Z., and Wang, Z.: Modeling study of the 2010 regional haze event in the North China Plain, Atmos. Chem. Phys., 16, 1673–1691, https://doi.org/10.5194/acp-16-1673-2016, 2016.
Geng, G., Zhang, Q., Tong, D., Li, M., Zheng, Y., Wang, S., and He, K.: Chemical composition of ambient PM2.5 over China and relationship to precursor emissions during 2005–2012, Atmos. Chem. Phys., 17, 9187–9203, https://doi.org/10.5194/acp-17-9187-2017, 2017.
Geng, G., Xiao, Q., Zheng, Y., Tong, D., Zhang, Y., Zhang, X., Zhang, Q.,
He, K., and Liu, Y.: Impact of China's air pollution prevention and control
action plan on PM2.5 chemical composition over eastern China, Sci. China
Earth Sci., 62, 1872–1884, https://doi.org/10.1007/s11430-018-9353-x, 2019.
Geng, G., Xiao, Q., Liu, S., Liu, X., Cheng, J., Zheng, Y., Xue, T., Tong,
D., Zheng, B., Peng, Y., and Huang, X.: Tracking air pollution in China:
Near real-time PM2.5 retrievals from multisource data fusion, Environ. Sci.
Technol., 55, 12106–12115, https://doi.org/10.1021/acs.est.1c01863, 2021.
Gu, B. J., Zhu, Y. M., Chang, J., Peng, C. H., Liu, D., Min, Y., Luo, W. D.,
Howarth, R. W., and Ge, Y.: The role of technology and policy in mitigating
regional nitrogen pollution, Environ. Res. Lett., 6, 014011,
https://doi.org/10.1088/1748-9326/6/1/014011, 2011.
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012.
Han, Y., Wu, Y. F., Don, H. Y., and Chen, F.: Characteristics of PM2.5 and its chemical composition during the Asia-Pacific Economic Cooperation
Summit in Beijing-Tianjin-Hebei Region and surrounding cities, Environ. Sci.
Technol., 40, 134–138, 2017 (in Chinese with English abstract).
Huang, R. J., Zhang, Y. L., Bozzetti, C., Ho, K. F., Cao, J. J., Han, Y. M.,
Daellenbach, K. R., Slowik, J. G., Platt, S. M., Canonaco, F., Zotter, P.,
Wolf, R., Pieber, S. M., Bruns, E. A., Crippa, M., Ciarelli, G.,
Piazzalunga, A., Schwikowski, M., Abbaszade, G., Schnelle-Kreis, J.,
Zimmermann, R., An, Z. S., Szidat, S., Baltensperger, U., El Haddad, I., and
Prevot, A. S.: High secondary aerosol contribution to particulate pollution
during haze events in China, Nature, 514, 218–222,
https://doi.org/10.1038/nature13774, 2014.
Huang, X., Ding, A. J., Gao, J., Zheng, B., Zhou, D. R., Qi, X. M., Tang, R.,
Wang, J. P., Ren, C. H., Nie, W., Chi, X. G., Xu, Z., Chen, L. D., Li, Y.
Y., Che, F., Pang, N. N., Wang, H. K., Tong, D., Qin, W., Cheng, W., Liu, W.
J., Fu, Q. Y., Liu, B. X., Chai, F. H., Davis, S. J., Zhang, Q., and He, K.
B.: Enhanced secondary pollution offset reduction of primary emissions
during COVID-19 lockdown in China, Natl. Sci. Rev., 8, nwaa137,
https://doi.org/10.1093/nsr/nwaa137, 2021.
Ianniello, A., Spataro, F., Esposito, G., Allegrini, I., Rantica, E., Ancora, M. P., Hu, M., and Zhu, T.: Occurrence of gas phase ammonia in the area of Beijing (China), Atmos. Chem. Phys., 10, 9487–9503, https://doi.org/10.5194/acp-10-9487-2010, 2010.
Kang, Y., Liu, M., Song, Y., Huang, X., Yao, H., Cai, X., Zhang, H., Kang, L., Liu, X., Yan, X., He, H., Zhang, Q., Shao, M., and Zhu, T.: High-resolution ammonia emissions inventories in China from 1980 to 2012, Atmos. Chem. Phys., 16, 2043–2058, https://doi.org/10.5194/acp-16-2043-2016, 2016.
Kruskal, W. H. and Wallis, W. A.: Use of ranks in one-criterion variance
analysis, J. Am. Stat. Assoc., 47, 583–621,
https://doi.org/10.1080/01621459.1952.10483441, 1952.
Kuerban, M., Waili, Y., Fan, F., Liu, Y., Qin, W., Dore, A. J., Dore, A. J.,
Xu, W., and Zhang, F. S.: Spatio-temporal patterns of air pollution in China
from 2015 to 2018 and implications for health risks, Environ. Pollut., 258,
113659, https://doi.org/10.1016/j.envpol.2019.113659, 2020.
Li, H., Zhang, Q., Zheng, B., Chen, C., Wu, N., Guo, H., Zhang, Y., Zheng, Y., Li, X., and He, K.: Nitrate-driven urban haze pollution during summertime over the North China Plain, Atmos. Chem. Phys., 18, 5293–5306, https://doi.org/10.5194/acp-18-5293-2018, 2018.
Li, H., Cheng, J., Zhang, Q., Zheng, B., Zhang, Y., Zheng, G., and He, K.: Rapid transition in winter aerosol composition in Beijing from 2014 to 2017: response to clean air actions, Atmos. Chem. Phys., 19, 11485–11499, https://doi.org/10.5194/acp-19-11485-2019, 2019.
Li, K., Jacob, D. J., Shen, L., Lu, X., De Smedt, I., and Liao, H.: Increases in surface ozone pollution in China from 2013 to 2019: anthropogenic and meteorological influences, Atmos. Chem. Phys., 20, 11423–11433, https://doi.org/10.5194/acp-20-11423-2020, 2020.
Li, M., Liu, H., Geng, G., Geng, G. N., Hong, C. P., Liu, F., Song, Y.,
Tong, D., Zheng, B., Cui, H. Y., Man, H. Y., Zhang, Q., and He, K. B.: Anthropogenic
emission inventories in China: a review, Natl. Sci. Rev., 4, 834–866,
https://doi.org/10.1093/nsr/nwx150, 2017.
Li, X., Bei, N., Hu, B., Wu, J., Pan, Y., Wen, T., Liu, Z., Liu, L., Wang,
R., and Li, G.: Mitigating NOx emissions does not help alleviate
wintertime particulate pollution in Beijing-Tianjin-Hebei, China, Environ.
Pollut., 279, 116931, https://doi.org/10.1016/j.envpol.2021.116931, 2021.
Liang, F. C., Xiao, Q. Y., Huang, K. Y., Yang, X. L., Liu, F. C ., Li, J. X.,
Lu, X. F., Liu, Y., and Gu, D. F.: The 17-y spatiotemporal trend of
PM2.5 and its mortality burden in China, P. Natl. Acad. Sci. USA, 117, 25601–25608, https://doi.org/10.1073/pnas.1919641117, 2020.
Liu, J., Han, Y. Q., Tang, X., Zhu, J., and Zhu, T.: Estimating adult
mortality attributable to PM2.5 exposure in China with assimilated
PM2.5 concentrations based on a ground monitoring network, Sci.
Total. Environ., 568, 1253–1262, https://doi.org/10.1016/j.scitotenv.2016.05.165, 2016.
Liu, L., Zhang, X., Wong, A. Y. H., Xu, W., Liu, X., Li, Y., Mi, H., Lu, X., Zhao, L., Wang, Z., Wu, X., and Wei, J.: Estimating global surface ammonia concentrations inferred from satellite retrievals, Atmos. Chem. Phys., 19, 12051–12066, https://doi.org/10.5194/acp-19-12051-2019, 2019.
Liu, M. X., Huang, X., Song, Y., Tang, J., Cao, J. J., Zhang, X. Y., Zhang,
Q., Wang, S. X., Xu, T. T., Kang, L., Cai, X. H., Zhang, H. S., Yang, F. M.,
Wang, H. B., Yu, J. Z., Lau, A. K. H., He, L. Y., Huang, X. F., Duan, L.,
Ding, A. J., Xue, L. K., Gao, J., Liu, B., and Zhu, T.: Ammonia emission
control in China would mitigate haze pollution and nitrogen deposition, but
worsen acid rain, P. Natl. Acad. Sci. USA, 116, 7760–7765,
https://doi.org/10.1073/pnas.1814880116, 2019.
Liu, X. J., Sha, Z. P., Song, Y., Dong, H. M., Pan, Y. P., Gao, Z. L., Li, Y. E.,
Ma, L., Dong, W. X., Hu, C. S., Wang, W. L., Wang, Y., Geng, H., Zheng, Y. H.,
and Gu, M. N.: China's atmospheric ammonia emission characteristics,
mitigation options and policy recommendations, Res. Environ. Sci., 34,
149–157, https://doi.org/10.13198/j.issn.1001-6929.2020.11.12, 2021.
Mao, S. S., Chen, T, Fu, J. M., Liang, J. L., An, X. X., Luo, X. X., Zhang,
D. W., and Liu, B. X.: Characteristic analysis for the thick winter air
pollution accidents in Beijing based on the online observations, Journal of
Safety and Environment, 1, 1009–6094,
2018 (in Chinese with English abstract).
MEEP: The Ministry of Ecology and Environment of the People's Republic of
China, 57 pp., China Ecological Environment Bulletin,
http://www.mee.gov.cn/hjzl/sthjzk/zghjzkgb/ (last access: 2 June 2020), 2019.
Megaritis, A. G., Fountoukis, C., Charalampidis, P. E., Pilinis, C., and Pandis, S. N.: Response of fine particulate matter concentrations to changes of emissions and temperature in Europe, Atmos. Chem. Phys., 13, 3423–3443, https://doi.org/10.5194/acp-13-3423-2013, 2013.
Meng, F. L., Wang, M. R., Strokal, M., Kroeze, C., Ma, L., Li, Y. N., Zhang,
Q., Wei, Z. B., Hou, Y., Liu, X. J., Xu, W., and Zhang, F. S.: Nitrogen
losses from food production in the North China Plain: A case study for
Quzhou, Sci. Total. Environ., 816, 151557,
https://doi.org/10.1016/j.scitotenv.2021.151557, 2022.
MEPC: Ministry of Environment Protection of China, Ambient air quality
standards (GB3095–2012), http://www.mep. gov.cn/, last access: 26 June 2012.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics
on the development of trailing stratiform precipitation in a simulated
squall line: comparison of one- and two-moment schemes, Mon. Weather. Rev.,
137, 991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009.
Nakagawa, S. and Santos, E. S. A.: Methodological issues and advances in
biological meta-analysis, Evol. Ecol., 26, 1253–1274,
https://doi.org/10.1007/s10682-012-9555-5, 2012.
Ortiz-Montalvo, D., Häkkinen, S. A. K., Schwier, A. N., Lim, Y. B., Faye
McNeill, V., and Turpin, B. J.: Ammonium addition (and aerosol pH) has a
dramatic impact on the volatility and yield of glyoxal secondary organic
aerosol, Environ. Sci. Technol., 48, 255–262,
https://doi.org/10.1021/es4035667, 2014.
Pan, Y. P., Wang, Y. S., Tang, G. Q., and Wu, D.: Wet and dry deposition of atmospheric nitrogen at ten sites in Northern China, Atmos. Chem. Phys., 12, 6515–6535, https://doi.org/10.5194/acp-12-6515-2012, 2012.
Pinder, R. W., Adams, P. J., and Pandis, S. N.: Ammonia emission controls as
a cost-effective strategy for reducing atmospheric particulate matter in the
eastern United States, Environ. Sci. Technol., 41, 380–386,
https://doi.org/10.1021/es060379a, 2007.
Sun, Y. L., Zhuang, G. S., Tang, A. H., Wang, Y., and An, Z. S.: Chemical
characteristics of PM2.5 and PM10 in haze-fog episodes in
Beijing, Environ. Sci. Technol., 40, 3148–3155,
https://doi.org/10.1021/es051533g, 2006.
Tao, J., Gao, J., Zhang, L. M., Wang, H., Qiu, X. H., Zhang, Z. S., Wu, Y.
F., Chai, F. H., and Wang, S. L: Chemical and optical characteristics of
atmospheric aerosols in Beijing during the Asia-Pacific Economic Cooperation
China 2014, Atmos. Environ., 144, 8–16,
https://doi.org/10.1016/j.atmosenv.2016.08.067, 2016.
van der A, R. J., Mijling, B., Ding, J., Koukouli, M. E., Liu, F., Li, Q., Mao, H., and Theys, N.: Cleaning up the air: effectiveness of air quality policy for SO2 and NOx emissions in China, Atmos. Chem. Phys., 17, 1775–1789, https://doi.org/10.5194/acp-17-1775-2017, 2017.
Wang, G. H., Zhang, R. Y., Gomez, M. E., Yang, L. X., Zamora, M. L., Hu, M.,
Lin, Y., Peng, J. F., Guo, S., Meng, J. J., Li, J. J., Cheng, C. L., Hu, T.
F., Ren, Y. Q., Wang, Y. S., Gao, J., Cao, J. J., An, Z. S., Zhou, W. J.,
Li, G. H., Wang, J. Y., Tian, P. F., Marrero-Ortiz, W., Secrest, J., Du, Z.
F., Zheng, J., Shang, D. J., Zeng, L. M., Shao, M., Wang, W. G., Huang, Y.,
Wang, Y., Zhu, Y. J., Li, Y. X., Hu, J. X., Pan, B., Cai, L., Cheng, Y.
T., Ji, Y. M., Zhang, F., Rosenfeld, D., Liss, P. S., Duce, R. A., Kolb, C.
E., and Molina, M. J.: Persistent sulfate formation from London Fog to
Chinese haze, P. Natl. Acad. Sci. USA, 113, 13630–13635,
https://doi.org/10.1073/pnas.1616540113, 2016.
Wang, L., Chen, X., Zhang, Y., Li, M., Li, P., Jiang, L., Xia, Y., Li, Z.,
Li, J., Wang, L., Hou, T., Liu, W., Rosenfeld, D., Zhu, T., Zhang, Y., Chen,
J., Wang, S., Huang, Y., Seinfeld, J. H., and Yu, S.: Switching to electric
vehicles can lead to significant reductions of PM2.5 and NO2
across China, One Earth, 4, 1037–1048, https://doi.org/10.1016/j.oneear.2021.06.008, 2021.
Wang, L., Yu, S., Li, P., Chen, X., Li, Z., Zhang, Y., Li, M., Mehmood, K., Liu, W., Chai, T., Zhu, Y., Rosenfeld, D., and Seinfeld, J. H.: Significant wintertime PM2.5 mitigation in the Yangtze River Delta, China, from 2016 to 2019: observational constraints on anthropogenic emission controls , Atmos. Chem. Phys., 20, 14787–14800, https://doi.org/10.5194/acp-20-14787-2020, 2020.
Wang, Q. H., Zhou, F., Shang, Z. Y., Ciais, P., Winiwarter, W., Jackson, R.
B., Tubiello, F. N., Janssens-Maenhout, G., Tian, H. Q., Cui, X. Q.,
Canadell, J. G., Piao, S. L., and Tao, S.: Data-driven estimates of global
nitrous oxide emissions from cropland, Natl. Sci. Rev., 7, 441–452,
https://doi.org/10.1093/nsr/nwz087, 2020.
Wang, S.: How to promote ultra-low emissions during the 14th Five-Year Plan?,
China. Environment. News., http://epaper.cenews.com.cn/html/2021-04/30/node_7.htm, last access: 30 April 2021.
Wang, S. X., Xing, J., Jang, C., Jang, C. R., Zhu, Y., Fu, J. S., and Hao, J.
M.: Impact assessment of ammonia emissions on inorganic aerosols in East
China using response surface modeling technique, Environ. Sci. Technol., 45,
9293–9300, https://doi.org/10.1021/es2022347, 2011.
Wang, Y., Wang, Y., Wang, L., Petäjä, T., Zha, Q., Gong, C., Li, S., Pan, Y., Hu, B., Xin, J., and Kulmala, M.: Increased inorganic aerosol fraction contributes to air pollution and haze in China, Atmos. Chem. Phys., 19, 5881–5888, https://doi.org/10.5194/acp-19-5881-2019, 2019.
Wang, Y., Zhang, Q. Q., He, K., Zhang, Q., and Chai, L.: Sulfate-nitrate-ammonium aerosols over China: response to 2000–2015 emission changes of sulfur dioxide, nitrogen oxides, and ammonia, Atmos. Chem. Phys., 13, 2635–2652, https://doi.org/10.5194/acp-13-2635-2013, 2013.
Wang, Y. C., Chen, J., Wang, Q. Y., Qin, Q. D., Ye, J. H., Han, Y. M., Li, L.,
Zhen, W., Zhi, Q., Zhang, Y. X., and Cao, J. J.: Increased secondary aerosol
contribution and possible processing on polluted winter days in
China, Environ. Int., 127, 78–84, https://doi.org/10.1016/j.envint.2019.03.021,
2019.
Wei, J., Li, Z., Cribb, M., Huang, W., Xue, W., Sun, L., Guo, J., Peng, Y., Li, J., Lyapustin, A., Liu, L., Wu, H., and Song, Y.: Improved 1 km resolution PM2.5 estimates across China using enhanced space–time extremely randomized trees, Atmos. Chem. Phys., 20, 3273–3289, https://doi.org/10.5194/acp-20-3273-2020, 2020.
Wei, J., Li, Z. Q., Lyapustin, A., Sun, L., Peng, Y. R., Xue, W. H., Su, T.
N., and Cribb, M.: Reconstructing 1-km-resolution high-quality
PM2.5 data records from 2000 to 2018 in China: spatiotemporal
variations and policy implications, Remote. Sens. Environ., 252, 112136,
https://doi.org/10.1016/j.rse.2020.112136, 2021.
Wu, Y. J., Wang, P., Yu, S. C., Wang, L. Q., Li, P. F., Li, Z., Mehmood, K.,
Liu, W. P., Wu, J., Lichtfouse, E., Rosenfeld, D., and Seinfeld, J. H.:
Residential emissions predicted as a major source of fine particulate matter
in winter over the Yangtze River Delta, China, Environ. Chem. Lett., 16,
1117–1127, https://doi.org/10.1007/s10311-018-0735-6, 2018.
Wu, Y. Y., Xi, X. C., Tang, X., Luo, D. M., Gu, B. J., Lam, S. K.,
Vitousek, P. M., and Chen, D. L.: Policy distortions, farm size, and the
overuse of agricultural chemicals in China, P. Natl. Acad. Sci. USA,
115, 7010–7015, https://doi.org/10.1073/pnas.1806645115, 2018.
Xiao, Q., Zheng, Y., Geng, G., Chen, C., Huang, X., Che, H., Zhang, X., He, K., and Zhang, Q.: Separating emission and meteorological contributions to long-term PM2.5 trends over eastern China during 2000–2018, Atmos. Chem. Phys., 21, 9475–9496, https://doi.org/10.5194/acp-21-9475-2021, 2021.
Xiao, Q. Y., Geng, G. N., Liang, F. C., Wang, X., Lv, Z., Lei, Y., Huang, X. M.,
Zhang, Q., Liu, Y., and He, K. B.: Changes in spatial patterns of PM2.5
pollution in China 2000–2018: Impact of clean air policies, Environ. Int.,
141, 105776, https://doi.org/10.1016/j.envint.2020.105776, 2020.
Xing, J., Liu, X., Wang, S. X., Wang, T., Ding, D., Yu, S., Shindell, D.,
Ou, Y., Morawska, L., Li, S. W., Ren, L., Zhang, Y. Q., Loughlin, D.,
Zheng, H. T., Zhao, B., Liu, S. C., Smith, K. R., and Hao, J. M.: The quest
for improved air quality may push China to continue its CO2 reduction
beyond the Paris Commitment, P. Natl. Acad. Sci. USA, 117,
29535–29542, https://doi.org/10.1073/pnas.2013297117, 2021.
Xu, Q. C., Wang, S. X., Jiang, J. K., Bhattarai, N., Li, X. X., Chang, X.,
Qiu, X. H., Zheng, M., Hua, Y., and Hao, J. M.: Nitrate dominates the
chemical composition of PM2.5 during haze event in Beijing, China,
Sci. Total. Environ., 689, 1293–1303,
https://doi.org/10.1016/j.scitotenv.2019.06.294, 2019.
Xu, W.:
Supplementary information_Dataset_PM2.5 and associated chemical components.xlsx, figshare [data set], https://doi.org/10.6084/m9.figshare.16429092, 2022.
Xu, W., Luo, X. S., Pan, Y. P., Zhang, L., Tang, A. H., Shen, J. L., Zhang, Y., Li, K. H., Wu, Q. H., Yang, D. W., Zhang, Y. Y., Xue, J., Li, W. Q., Li, Q. Q., Tang, L., Lu, S. H., Liang, T., Tong, Y. A., Liu, P., Zhang, Q., Xiong, Z. Q., Shi, X. J., Wu, L. H., Shi, W. Q., Tian, K., Zhong, X. H., Shi, K., Tang, Q. Y., Zhang, L. J., Huang, J. L., He, C. E., Kuang, F. H., Zhu, B., Liu, H., Jin, X., Xin, Y. J., Shi, X. K., Du, E. Z., Dore, A. J., Tang, S., Collett Jr., J. L., Goulding, K., Sun, Y. X., Ren, J., Zhang, F. S., and Liu, X. J.: Quantifying atmospheric nitrogen deposition through a nationwide monitoring network across China, Atmos. Chem. Phys., 15, 12345–12360, https://doi.org/10.5194/acp-15-12345-2015, 2015.
Xu, W., Wu, Q. H., Liu, X. J., Tang, A. H., Dore, A. J., and Heal, M. R.:
Characteristics of ammonia, acid gases, and PM2.5 for three
typical land-use types in the North China Plain, Environ Sci Pollut R., 23,
1158–1172, https://doi.org/10.1007/s11356-015-5648-3, 2016.
Xu, W., Song, W., Zhang, Y., Liu, X., Zhang, L., Zhao, Y., Liu, D., Tang, A., Yang, D., Wang, D., Wen, Z., Pan, Y., Fowler, D., Collett Jr., J. L., Erisman, J. W., Goulding, K., Li, Y., and Zhang, F.: Air quality improvement in a megacity: implications from 2015 Beijing Parade Blue pollution control actions, Atmos. Chem. Phys., 17, 31–46, https://doi.org/10.5194/acp-17-31-2017, 2017.
Xu, W., Liu, L., Cheng, M., Zhao, Y., Zhang, L., Pan, Y., Zhang, X., Gu, B., Li, Y., Zhang, X., Shen, J., Lu, L., Luo, X., Zhao, Y., Feng, Z., Collett Jr., J. L., Zhang, F., and Liu, X.: Spatial–temporal patterns of inorganic nitrogen air concentrations and deposition in eastern China, Atmos. Chem. Phys., 18, 10931–10954, https://doi.org/10.5194/acp-18-10931-2018, 2018.
Xue, T., Liu, J., Zhang, Q., Geng, G. N., Zheng, Y. X., Tong, D., Liu, Z.,
Guan, D. B., Bo, Y., Zhu, T., He, K. B., and Hao, J. M.: Rapid improvement of
PM2.5 pollution and associated health benefits in China during
2013–2017, Sci. China Earth Sci., 62, 1847–1856,
https://doi.org/10.1007/s11430-018-9348-2, 2019.
Yang, F., Tan, J., Zhao, Q., Du, Z., He, K., Ma, Y., Duan, F., Chen, G., and Zhao, Q.: Characteristics of PM2.5 speciation in representative megacities and across China, Atmos. Chem. Phys., 11, 5207–5219, https://doi.org/10.5194/acp-11-5207-2011, 2011.
Ying, H., Yin, Y. L., Zheng, H. F., Wang, Y. C., Zhang, Q. S., Xue, Y. F.,
Stefanovski, D., Cui, Z. L., and Dou, Z. X.: Newer and select maize, wheat,
and rice varieties can help mitigate N footprint while producing more grain,
Glob. Change Biol., 12, 4273–4281, https://doi.org/10.1111/gcb.14798, 2019.
Yu, S. C., Dennis, R., Roselle, S., Nenes, A., Walker, J., Eder, B., Schere,
K., Swall, J., and Robarge, W.: An assessment of the ability of
three-dimensional air quality models with current thermodynamic equilibrium
models to predict aerosol NO , J. Geophys. Res.-Atmos., 110, D07S13,
https://doi.org/10.1029/2004JD004718, 2005.
Yue, H. B., He, C. Y., Huang, Q. X., Yin, D., and Bryan, B. A.: Stronger
policy required to substantially reduce deaths from PM2.5 pollution
in China, Nat. Commun., 11, 1462,
https://doi.org/10.1038/s41467-020-15319-4, 2020.
Zhai, S., Jacob, D. J., Wang, X., Liu, Z., Wen, T., Shah, V., Li, K., Moch,
J. M., Bates, K. H., Song, S., and Shen, L.: Control of particulate nitrate air
pollution in China, Nat. Geosci., 14, 389–395,
https://doi.org/10.1038/s41561-021-00726-z, 2021.
Zhan, X. Y., Adalibieke, W., Cui, X. Q., Winiwarter, W., Reis, S., Zhang, L.,
Bai, Z. H., Wang, Q. H., Huang, W. C., and Zhou, F.: Improved estimates of
ammonia emissions from global croplands, Environ. Sci. Technol., 55,
1329–1338, https://doi.org/10.1021/acs.est.0c05149, 2021.
Zhang, L., Jacob, D. J., Knipping, E. M., Kumar, N., Munger, J. W., Carouge, C. C., van Donkelaar, A., Wang, Y. X., and Chen, D.: Nitrogen deposition to the United States: distribution, sources, and processes, Atmos. Chem. Phys., 12, 4539–4554, https://doi.org/10.5194/acp-12-4539-2012, 2012.
Zhang, Q., Zheng, Y. X., Tong, D., Shao, M., Wang, S. X., Zhang, Y. H., Xu,
X. D., Wang, J. N., He, H., Liu, W. Q., Ding, Y. H., Lei, Y., Li, J. H.,
Wang, Z. F., Zhang, X. Y., Wang, Y. S., Cheng, J., Liu, Y., Shi, Q. R.,
Yan, L., Geng, G. N., Hong, C. P., Li, M., Liu, F., Zheng, B., Cao, J. J.,
Ding, A. J., Gao, J., Fu, Q. Y., Huo, J. T., Liu, B. X., Liu, Z. R., Yang,
F. M., He, K. B., and Hao, J. M.: Drivers of improved PM2.5 air quality
in China from 2013 to 2017, P. Natl. Acad. Sci. USA, 49,
24463–24469, https://doi.org/10.1073/pnas.1907956116, 2019.
Zhang, X. M., Gu, B. J., van Grinsven, H., Lam, S. K., Liang, X., Bai, M.,
and Chen, D. L.: Societal benefits of halving agricultural ammonia emissions
in China far exceed the abatement costs, Nat. Commun., 11, 4357,
https://doi.org/10.1038/s41467-020-18196-z, 2020.
Zhang, Y., Vu, T. V., Sun, J., He, J., Shen, X., Lin, W., Zhang, X., Zhang,
J., Gao, W., Wang, Y., Fu, T., Ma, Y., Li, W., and Shi, Z.: Significant
changes in chemistry of fine particles in wintertime Beijing from 2007 to
2017: Impact of clean air actions, Environ. Sci. Technol., 54, 1344–1352,
https://doi.org/10.1021/acs.est.9b04678, 2020.
Zhang, Y., Chen, X., Yu, S., Wang, L., Li, Z., Li, M., Liu, W., Li, P.,
Rosenfeld, D., and Seinfeld, J. H.: City-level air quality improvement in the
Beijing-Tianjin-Hebei region from 2016/17 to 2017/18 heating seasons:
Attributions and process analysis, Environ. Pollut., 274, 116523,
https://doi.org/10.1016/j.envpol.2021.116523, 2021a.
Zhang, Y., Liu, X., Zhang, L., Tang, A., Goulding, K., and Collett Jr., J. L.:
Evolution of secondary inorganic aerosols amidst improving PM2.5 air quality in the North China Plain, Environ. Pollut., 281, 117027,
https://doi.org/10.1016/j.envpol.2021.117027, 2021b.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095–14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zheng, G. J., Duan, F. K., Su, H., Ma, Y. L., Cheng, Y., Zheng, B., Zhang, Q., Huang, T., Kimoto, T., Chang, D., Pöschl, U., Cheng, Y. F., and He, K. B.: Exploring the severe winter haze in Beijing: the impact of synoptic weather, regional transport and heterogeneous reactions, Atmos. Chem. Phys., 15, 2969–2983, https://doi.org/10.5194/acp-15-2969-2015, 2015.
Short summary
PM2.5 pollution is a pressing environmental issue threatening human health and food security globally. We combined a meta-analysis of nationwide measurements and air quality modeling to identify efficiency gains by striking a balance between controlling NH3 and acid gas emissions. Persistent secondary inorganic aerosol pollution in China is limited by acid gas emissions, while an additional control on NH3 emissions would become more important as reductions in SO2 and NOx emissions progress.
PM2.5 pollution is a pressing environmental issue threatening human health and food security...
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