Articles | Volume 13, issue 5
https://doi.org/10.5194/essd-13-2147-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-2147-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
19 May 2021
Data description paper |
| 19 May 2021
| 19 May 2021
Long-term trends of ambient nitrate (NO3−) concentrations across China based on ensemble machine-learning models
Rui Li
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, China
Lulu Cui
CORRESPONDING AUTHOR
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, China
Yilong Zhao
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, China
Wenhui Zhou
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, China
Hongbo Fu
CORRESPONDING AUTHOR
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, China
Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology, Nanjing 210044, China
Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
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This work systematically explained the nonlinear effect of NOx level on isoprene-SOA mass yield through a series of chamber experiments. We found that the turning point under various oxidants was smaller than previous reported in the presence of OH precursors, which could be attributed to the RO2 pathway competition in nucleation and condensation of low volatile products. The highest SOA yield was at a branching ratio β of 0.5, which can be used as a reference for field campaign and modeling.
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Brown carbon (BrC) is prevalent in the troposphere and can efficiently absorb solar and terrestrial radiation. Our observations show that the enhanced light absorption of BrC relative to black carbon at the tropopause can be attributed to the formation of nitrogen-containing organic compounds through the aqueous-phase reactions of carbonyls with ammonium.
Fan Zhang, Binyu Xiao, Zeyu Liu, Yan Zhang, Chongguo Tian, Rui Li, Can Wu, Yali Lei, Si Zhang, Xinyi Wan, Yubao Chen, Yong Han, Min Cui, Cheng Huang, Hongli Wang, Yingjun Chen, and Gehui Wang
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Preprint archived
Short summary
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This work systematically explained the nonlinear effect of NOx level on isoprene-SOA mass yield through a series of chamber experiments. We found that the turning point under various oxidants was smaller than previous reported in the presence of OH precursors, which could be attributed to the RO2 pathway competition in nucleation and condensation of low volatile products. The highest SOA yield was at a branching ratio β of 0.5, which can be used as a reference for field campaign and modeling.
Can Wu, Xiaodi Liu, Ke Zhang, Si Zhang, Cong Cao, Jianjun Li, Rui Li, Fan Zhang, and Gehui Wang
Atmos. Chem. Phys., 24, 9263–9275, https://doi.org/10.5194/acp-24-9263-2024, https://doi.org/10.5194/acp-24-9263-2024, 2024
Short summary
Short summary
Brown carbon (BrC) is prevalent in the troposphere and can efficiently absorb solar and terrestrial radiation. Our observations show that the enhanced light absorption of BrC relative to black carbon at the tropopause can be attributed to the formation of nitrogen-containing organic compounds through the aqueous-phase reactions of carbonyls with ammonium.
Fan Zhang, Binyu Xiao, Zeyu Liu, Yan Zhang, Chongguo Tian, Rui Li, Can Wu, Yali Lei, Si Zhang, Xinyi Wan, Yubao Chen, Yong Han, Min Cui, Cheng Huang, Hongli Wang, Yingjun Chen, and Gehui Wang
Atmos. Chem. Phys., 24, 8999–9017, https://doi.org/10.5194/acp-24-8999-2024, https://doi.org/10.5194/acp-24-8999-2024, 2024
Short summary
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Mandatory use of low-sulfur fuel due to global sulfur limit regulations means large uncertainties in volatile organic compound (VOC) emissions. On-board tests of VOCs from nine cargo ships in China were carried out. Results showed that switching from heavy-fuel oil to diesel increased emission factor VOCs by 48 % on average, enhancing O3 and the secondary organic aerosol formation potential. Thus, implementing a global ultra-low-sulfur oil policy needs to be optimized in the near future.
Shijie Liu, Xinbei Xu, Si Zhang, Rongjie Li, Zheng Li, Can Wu, Rui Li, Guiqin Zhang, and Gehui Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1599, https://doi.org/10.5194/egusphere-2024-1599, 2024
Preprint archived
Short summary
Short summary
We conducted α-pinene photooxidation experiments in an atmospheric chamber at different NOx concentrations. The increased distribution coefficient of the oxidation products between the aerosol and gas phases with NOx was responsible for the increased SOA yields with NOx under low-NOx conditions. We also found the fraction of SOA made up of nitrogen-containing organic compounds (NOCs) increased with NOx.
Rui Li, Yining Gao, Lijia Zhang, Yubing Shen, Tianzhao Xu, Wenwen Sun, and Gehui Wang
Atmos. Chem. Phys., 24, 7623–7636, https://doi.org/10.5194/acp-24-7623-2024, https://doi.org/10.5194/acp-24-7623-2024, 2024
Short summary
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A three-stage model was developed to obtain the global maps of reactive nitrogen components during 2000–2100. The results implied that cross-validation R2 values of four species showed satisfactory performance (R2 > 0.55). Most reactive nitrogen components, except NH3, in China showed increases during 2000–2013. In the future scenarios, SSP3-7.0 (traditional-energy scenario) and SSP1-2.6 (carbon neutrality scenario) showed the highest and lowest reactive nitrogen component concentrations.
Hannah J. Rubin, Joshua S. Fu, Frank Dentener, Rui Li, Kan Huang, and Hongbo Fu
Atmos. Chem. Phys., 23, 7091–7102, https://doi.org/10.5194/acp-23-7091-2023, https://doi.org/10.5194/acp-23-7091-2023, 2023
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We update the 2010 global deposition budget for nitrogen (N) and sulfur (S) with new regional wet deposition measurements, improving the ensemble results of 11 global chemistry transport models from HTAP II. Our study demonstrates that a global measurement–model fusion approach can substantially improve N and S deposition model estimates at a regional scale and represents a step forward toward the WMO goal of global fusion products for accurately mapping harmful air pollution.
Rui Li, Yining Gao, Yubao Chen, Meng Peng, Weidong Zhao, Gehui Wang, and Jiming Hao
Atmos. Chem. Phys., 23, 4709–4726, https://doi.org/10.5194/acp-23-4709-2023, https://doi.org/10.5194/acp-23-4709-2023, 2023
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A random forest model was used to isolate the effects of emission and meteorology to trace elements in PM2.5 in Tangshan. The results suggested that control measures facilitated decreases of Ga, Co, Pb, Zn, and As, due to the strict implementation of coal-to-gas strategies and optimisation of industrial structure and layout. However, the deweathered levels of Ca, Cr, and Fe only displayed minor decreases, indicating that ferrous metal smelting and vehicle emission controls should be enhanced.
Chaohao Ling, Lulu Cui, and Rui Li
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An ensemble machine-learning model coupled with chemical transport models (CTMs) was applied to assess the impact of COVID-19 on ambient benzene. The change ratio of the deweathered benzene concentration from the pre-lockdown to lockdown period was in the order of India (−23.6 %) > Europe (−21.9 %) > the United States (−16.2 %) > China (−15.6 %), which might be associated with local serious benzene pollution and substantial emission reduction in the industrial and transportation sectors.
Yu Han, Tao Wang, Rui Li, Hongbo Fu, Yusen Duan, Song Gao, Liwu Zhang, and Jianmin Chen
Atmos. Chem. Phys., 23, 2877–2900, https://doi.org/10.5194/acp-23-2877-2023, https://doi.org/10.5194/acp-23-2877-2023, 2023
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Limited knowledge is available on volatile organic compound (VOC) multi-site research of different land-use types at city level. This study performed a concurrent multi-site observation campaign on the three typical land-use types of Shanghai, East China. The results showed that concentrations, sources and ozone and secondary organic aerosol formation potentials of VOCs varied with the land-use types.
Tao Wang, Yangyang Liu, Hanyun Cheng, Zhenzhen Wang, Hongbo Fu, Jianmin Chen, and Liwu Zhang
Atmos. Chem. Phys., 22, 13467–13493, https://doi.org/10.5194/acp-22-13467-2022, https://doi.org/10.5194/acp-22-13467-2022, 2022
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Rui Li, Yilong Zhao, Hongbo Fu, Jianmin Chen, Meng Peng, and Chunying Wang
Atmos. Chem. Phys., 21, 8677–8692, https://doi.org/10.5194/acp-21-8677-2021, https://doi.org/10.5194/acp-21-8677-2021, 2021
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Based on a random forest model, the strict lockdown measures significantly decreased primary components such as Cr (−67 %) and Fe (−61 %) in PM2.5 (p < 0.01), whereas the higher relative humidity (RH) and NH3 level and the lower air temperature (T) remarkably enhanced the production of secondary aerosol including SO42− (29 %), NO3− (29 %), and NH4+ (21 %) (p < 0.05). The natural experiment suggested that the NH3 emission should be strictly controlled.
Rui Li, Yilong Zhao, Wenhui Zhou, Ya Meng, Ziyu Zhang, and Hongbo Fu
Atmos. Chem. Phys., 20, 6159–6175, https://doi.org/10.5194/acp-20-6159-2020, https://doi.org/10.5194/acp-20-6159-2020, 2020
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The Tibetan Plateau lacks ground-level O3 observation due to its unique geographical environment. It is imperative to employ modelling methods to simulate the O3 level. The present study proposed a novel technique for estimating the surface O3 level in remote regions. The result captured long-term O3 concentration on the Tibetan Plateau, which was beneficial for assessing the effects of O3 on climate change and ecosystem safety, especially in a vulnerable area of the ecological environment.
Zhenzhen Wang, Tao Wang, Hongbo Fu, Liwu Zhang, Mingjin Tang, Christian George, Vicki H. Grassian, and Jianmin Chen
Atmos. Chem. Phys., 19, 12569–12585, https://doi.org/10.5194/acp-19-12569-2019, https://doi.org/10.5194/acp-19-12569-2019, 2019
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This study confirmed that SO2 uptake on mineral particles could be greatly enhanced during cloud processing. The large pH fluctuations between the cloud-aerosol modes could significantly modify the microphysical properties of particles, and triggered the formation of reactive Fe particles to accelerate sulfate formation via a self-amplifying process. Results of this study could partly explain the missing source of sulfate and improve agreement between models and field observations.
Rui Li, Lulu Cui, Yilong Zhao, Ziyu Zhang, Tianming Sun, Junlin Li, Wenhui Zhou, Ya Meng, Kan Huang, and Hongbo Fu
Atmos. Chem. Phys., 19, 11043–11070, https://doi.org/10.5194/acp-19-11043-2019, https://doi.org/10.5194/acp-19-11043-2019, 2019
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Acid deposition is still an important environmental issue in China. Rainwater samples in 320 cities in China were collected to determine the acidic ion concentrations and identify their spatiotemporal variations and sources. The higher acidic ions showed higher concentrations in winter. Furthermore, the highest acidic ion concentrations were mainly distributed in YRD and SB. These acidic ions were mainly sourced from industrial emissions and agricultural activities.
Tao Wang, Yangyang Liu, Yue Deng, Hanyun Cheng, Yang Yang, Yiqing Feng, Muhammad Ali Tahir, Xiaozhong Fang, Xu Dong, Kejian Li, Saira Ajmal, Aziz-Ur-Rahim Bacha, Iqra Nabi, Hongbo Fu, Liwu Zhang, and Jianmin Chen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-315, https://doi.org/10.5194/acp-2019-315, 2019
Revised manuscript not accepted
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We studied the heterogeneous formation of nitrate and nitrite aerosols by in-situ laboratory tests and field observations. Sunlight becomes the protagonist under weak illumination, while a costar under strong irradiation, attributing to the balance between NO2 adsorption and the formation of photoinduced active species. Meanwhile, sunlight determines the association between atmospheric nitrate and nitrite. We hope this work offer more suggestions for modelling studies.
Zhong Li, Chunlin Li, Xingnan Ye, Hongbo Fu, Lin Wang, Xin Yang, Xinke Wang, Zhuohui Zhao, Haidong Kan, Abdelwahid Mellouki, and Jianmin Chen
Atmos. Chem. Phys., 18, 14445–14464, https://doi.org/10.5194/acp-18-14445-2018, https://doi.org/10.5194/acp-18-14445-2018, 2018
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Air quality over the Yangtze River is important as it may significantly influence aquatic ecosystems, public health, and coastal areas. A comprehensive 15-day cruise campaign, TEMP, was performed in the mid–lower reaches of the Yangtze River in winter of 2015. Based on the filter samples, the chemical composition of PM2.5 greatly varied or fluctuated.
Rui Li, Yunjie Hu, Ling Li, Hongbo Fu, and Jianmin Chen
Atmos. Chem. Phys., 17, 5079–5093, https://doi.org/10.5194/acp-17-5079-2017, https://doi.org/10.5194/acp-17-5079-2017, 2017
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Five episodes were divided based on meteorological conditions and chemical composition. The clear episodes (EP-2 and EP-4) featured low light extinction with fewer pollutants, which are mostly externally mixed. In contrast, EP-1 and EP-5 were impacted by the industrial activities and biomass burning through the southern air mass, respectively. Soot at the fog period detected in EP-3 was mostly internally mixed with sulfates and nitrates.
L. D. Kong, X. Zhao, Z. Y. Sun, Y. W. Yang, H. B. Fu, S. C. Zhang, T. T. Cheng, X. Yang, L. Wang, and J. M. Chen
Atmos. Chem. Phys., 14, 9451–9467, https://doi.org/10.5194/acp-14-9451-2014, https://doi.org/10.5194/acp-14-9451-2014, 2014
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A global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology based on deep-learning methods
A dataset of ground-based vertical profile observations of aerosol, NO2, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023)
Nineteenth- and twentieth-century semi-quantitative surface ozone along subtropical European to tropical Africa Atlantic coasts
Global Stable Isotope Dataset for Surface Water
Global Methane Budget 2000–2020
A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS)
Aerial Estimates of Methane and Carbon Dioxide Emission Rates Using a Mass Balance Approach in New York State
EEAR-Clim: a high-density observational dataset of daily precipitation and air temperature for the Extended European Alpine Region
A comprehensive in situ and remote sensing data set collected during the HALO–(𝒜 𝒞)3 aircraft campaign
Radon-222 monitoring at German ICOS atmosphere stations
Biologically effective daily radiant exposure for erythema appearance, previtamin D3 synthesis and clearing of psoriatic lesions from erythema biometers at Belsk, Poland, for the period 1976–2023
Remote sensing measurements during PaCE 2022 campaign
Observational ozone data over the global oceans and polar regions: The TOAR-II Oceans data set version 2024
TROPOMI Level 3 tropospheric NO2 Dataset with Advanced Uncertainty Analysis from the ESA CCI+ ECV Precursor Project
Calm ocean, stormy sea: atmospheric and oceanographic observations of the Atlantic during the Atlantic References and Convection (ARC) ship campaign
Quantifying Dust Deposition over the Atlantic Ocean
Fluorescent aerosol particles in the Finnish sub-Arctic during the Pallas Cloud Experiment 2022 campaign
Climate change risks illustrated by the Intergovernmental Panel on Climate Change (IPCC) “burning embers”
Aerosol single scattering albedo derived by merging OMI/POLDER satellite products and AERONET ground observations
Data supporting the North Atlantic Climate System Integrated Study (ACSIS) programme, including atmospheric composition; oceanographic and sea-ice observations (2016–2022); and output from ocean, atmosphere, land, and sea-ice models (1950–2050)
ARMTRAJ: a set of multipurpose trajectory datasets augmenting the Atmospheric Radiation Measurement (ARM) user facility measurements
Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018
CREST: a Climate Data Record of Stratospheric Aerosols
Multiyear high-temporal-resolution measurements of submicron aerosols at 13 French urban sites: data processing and chemical composition
Large synthesis of in situ field measurements of the size distribution of mineral dust aerosols across their life cycles
Global high-resolution fire-sourced PM2.5 concentrations for 2000–2023
A 10 km daily-level ultraviolet-radiation-predicting dataset based on machine learning models in China from 2005 to 2020
GHOST: a globally harmonised dataset of surface atmospheric composition measurements
Changes in air pollutant emissions in China during two clean-air action periods derived from the newly developed Inversed Emission Inventory for Chinese Air Quality (CAQIEI)
Version 1 NOAA-20/OMPS Nadir Mapper total column SO2 product: continuation of NASA long-term global data record
GERB Obs4MIPs: a dataset for evaluating diurnal and monthly variations in top-of-atmosphere radiative fluxes in climate models
Multiwavelength aerosol lidars at the Maïdo supersite, Réunion Island, France: instrument description, data processing chain, and quality assessment
PM2.5 concentrations based on near-surface visibility in the Northern Hemisphere from 1959 to 2022
MAP-IO: an atmospheric and marine observatory program on board Marion Dufresne over the Southern Ocean
Retrieving ground-level PM2.5 concentrations in China (2013–2021) with a numerical-model-informed testbed to mitigate sample-imbalance-induced biases
Reconstructing long-term (1980–2022) daily ground particulate matter concentrations in India (LongPMInd)
Visibility-derived aerosol optical depth over global land from 1959 to 2021
Characterizing clouds with the CCClim dataset, a machine learning cloud class climatology
A Level 3 monthly gridded ice cloud dataset derived from 12 years of CALIOP measurements
IPB-MSA&SO4: a daily 0.25° resolution dataset of in situ-produced biogenic methanesulfonic acid and sulfate over the North Atlantic during 1998–2022 based on machine learning
Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence
The Total Carbon Column Observing Network's GGG2020 data version
Global anthropogenic emissions (CAMS-GLOB-ANT) for the Copernicus Atmosphere Monitoring Service simulations of air quality forecasts and reanalyses
Deep Convective Microphysics Experiment (DCMEX) coordinated aircraft and ground observations: microphysics, aerosol, and dynamics during cumulonimbus development
High-resolution physicochemical dataset of atmospheric aerosols over the Tibetan Plateau and its surroundings
Introduction to the NJIAS Himawari-8/9 Cloud Feature Dataset for climate and typhoon research
The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020
PalVol v1: a proxy-based semi-stochastic ensemble reconstruction of volcanic stratospheric sulfur injection for the last glacial cycle (140 000–50 BP)
Xiaoran Guo, Jianping Guo, Deli Meng, Yuping Sun, Zhen Zhang, Hui Xu, Liping Zeng, Juan Chen, Ning Li, and Tianmeng Chen
Earth Syst. Sci. Data, 17, 3541–3552, https://doi.org/10.5194/essd-17-3541-2025, https://doi.org/10.5194/essd-17-3541-2025, 2025
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Optimal atmospheric dynamic conditions are essential for convective storms. This study generates a dataset of high-resolution divergence and vorticity profiles using the measurements of a radar wind profiler mesonet in Beijing. The negative divergence and positive vorticity are present ahead of rainfall events. This suggests that this dataset can help improve our understanding of the pre-storm environment and has the potential to be applied in weather forecasting.
Cheng Chen, Xuefeng Lei, Zhenhai Liu, Haorang Gu, Oleg Dubovik, Pavel Litvinov, David Fuertes, Yujia Cao, Haixiao Yu, Guangfeng Xiang, Binghuan Meng, Zhenwei Qiu, Xiaobing Sun, Jin Hong, and Zhengqiang Li
Earth Syst. Sci. Data, 17, 3497–3519, https://doi.org/10.5194/essd-17-3497-2025, https://doi.org/10.5194/essd-17-3497-2025, 2025
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Particulate Observing Scanning Polarization (POSP) on board the second GaoFen-5 (GF-5(02)) satellite is the first space-borne ultraviolet–visible–near-infrared–shortwave-infrared (UV–VIS–NIR–SWIR) multi-spectral cross-track scanning polarimeter. Due to its wide spectral range and polarimetric capabilities, POSP measurements provide rich information for aerosol and surface characterization. We present the detailed aerosol/surface products generated from POSP's first 18 months of operation, including spectral aerosol optical depth, aerosol-size-/absorption-related properties, surface black-sky and white-sky albedos, etc.
Yuanyuan Wu, Jihu Liu, Yannian Zhu, Yu Zhang, Yang Cao, Kang-En Huang, Boyang Zheng, Yichuan Wang, Yanyun Li, Quan Wang, Chen Zhou, Yuan Liang, Jianning Sun, Minghuai Wang, and Daniel Rosenfeld
Earth Syst. Sci. Data, 17, 3243–3258, https://doi.org/10.5194/essd-17-3243-2025, https://doi.org/10.5194/essd-17-3243-2025, 2025
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Based on a deep-learning method, we established a global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology. This aims to promote a comprehensive understanding of cloud dynamics and cloud–climate feedback. Closed mesoscale cellular convection (MCC) clouds occur more frequently at night, while suppressed cumulus clouds exhibit remarkable decreases. Solid stratus and MCC cloud types show clear seasonal variations.
Peiyuan Jiao, Chengzhi Xing, Yikai Li, Xiangguang Ji, Wei Tan, Qihua Li, Haoran Liu, and Cheng Liu
Earth Syst. Sci. Data, 17, 3167–3187, https://doi.org/10.5194/essd-17-3167-2025, https://doi.org/10.5194/essd-17-3167-2025, 2025
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Vertical profile observations are key to understanding regional air pollution but remain scarce due to existing limits. This study presents a high-time-resolution (ca. 15 min) dataset of aerosol, nitrogen dioxide, and formaldehyde vertical profiles from 32 sites in China (2019–2023) using passive remote sensing. It documents vertical distribution, seasonal variations, and diurnal patterns, revealing long-term trends. Data are available at Zenodo under https://doi.org/10.5281/zenodo.15211604.
Juan A. Añel, Juan-Carlos Antuña-Marrero, Antonio Cid Samamed, Celia Pérez-Souto, Laura de la Torre, Maria Antonia Valente, Yuri Brugnara, Alfonso Saiz-Lopez, and Luis Gimeno
Earth Syst. Sci. Data, 17, 2437–2446, https://doi.org/10.5194/essd-17-2437-2025, https://doi.org/10.5194/essd-17-2437-2025, 2025
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Ozone (discovered in 1837) was first measured in 1847 using paper strips that reacted with ozone, providing an indication of its concentration based on colour changes. Here, we present the data, covering over 60 years of daily observations conducted along the eastern Atlantic coast, spanning from the tropics to the northern extratropics.
Rui Li, Guofeng Zhu, Longhu Chen, Xiaoyu Qi, Siyu Lu, Gaojia Meng, Yuhao Wang, Wenmin Li, Zhijie Zheng, Jiangwei Yang, and Yani Gun
Earth Syst. Sci. Data, 17, 2135–2145, https://doi.org/10.5194/essd-17-2135-2025, https://doi.org/10.5194/essd-17-2135-2025, 2025
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The study of hydrogen and oxygen stable isotopes in surface water is vital for understanding the global water cycle and its response to climate change. Analysing data from 22 389 global sampling stations over 67 years, we uncover spatial and temporal variations in isotopes, showing depletion from the Equator to the poles and from coastal to inland areas. These variations, influenced by geographic, topographic and meteorological factors, reveal the water cycle's heterogeneity.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Rajesh Kumar, Piyush Bhardwaj, Cenlin He, Jennifer Boehnert, Forrest Lacey, Stefano Alessandrini, Kevin Sampson, Matthew Casali, Scott Swerdlin, Olga Wilhelmi, Gabriele G. Pfister, Benjamin Gaubert, and Helen Worden
Earth Syst. Sci. Data, 17, 1807–1834, https://doi.org/10.5194/essd-17-1807-2025, https://doi.org/10.5194/essd-17-1807-2025, 2025
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We have created a 14-year hourly air quality dataset at 12 km resolution by combining satellite observations of atmospheric composition with air quality models over the contiguous United States (CONUS). The dataset has been found to reproduce key observed features of air quality over the CONUS. To enable easy visualization and interpretation of county-level air quality measures and trends by stakeholders, an ArcGIS air quality dashboard has also been developed.
Alexandra M. Catena, Mackenzie L. Smith, Lee T. Murray, Eric M. Leibensperger, Jie Zhang, Margaret J. Schwab, and James J. Schwab
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-135, https://doi.org/10.5194/essd-2025-135, 2025
Revised manuscript accepted for ESSD
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Methane and carbon dioxide emission rates were calculated for facilities across several sectors in New York State using aerial observations. Of the sampled facilities, landfills dominated the methane emission rates while combustion facilities had the highest carbon dioxide emission rates, followed by landfills. The self-reported EPA inventory is mostly underestimating landfill methane emissions apart from a few facilities with comparable numbers.
Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi
Earth Syst. Sci. Data, 17, 1367–1391, https://doi.org/10.5194/essd-17-1367-2025, https://doi.org/10.5194/essd-17-1367-2025, 2025
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EEAR-Clim is a new and unprecedented observational dataset gathering in situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and time series significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.
André Ehrlich, Susanne Crewell, Andreas Herber, Marcus Klingebiel, Christof Lüpkes, Mario Mech, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Matthias Buschmann, Hans-Christian Clemen, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Andreas Giez, Sarah Grawe, Christophe Gourbeyre, Jörg Hartmann, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsófia Jurányi, Benjamin Kirbus, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Christian Mallaun, Johanna Mayer, Stephan Mertes, Guillaume Mioche, Manuel Moser, Hanno Müller, Veronika Pörtge, Nils Risse, Greg Roberts, Sophie Rosenburg, Johannes Röttenbacher, Michael Schäfer, Jonas Schaefer, Andreas Schäfler, Imke Schirmacher, Johannes Schneider, Sabrina Schnitt, Frank Stratmann, Christian Tatzelt, Christiane Voigt, Andreas Walbröl, Anna Weber, Bruno Wetzel, Martin Wirth, and Manfred Wendisch
Earth Syst. Sci. Data, 17, 1295–1328, https://doi.org/10.5194/essd-17-1295-2025, https://doi.org/10.5194/essd-17-1295-2025, 2025
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This paper provides an overview of the HALO–(AC)3 aircraft campaign data sets, the campaign-specific instrument operation, data processing, and data quality. The data set comprises in situ and remote sensing observations from three research aircraft: HALO, Polar 5, and Polar 6. All data are published in the PANGAEA database by instrument-separated data subsets. It is highlighted how the scientific analysis of the HALO–(AC)3 data benefits from the coordinated operation of three aircraft.
Maksym Gachkivskyi, Ute Karstens, Bernd Fischer, Dagmar Kubistin, Jennifer Müller-Williams, Matthias Lindauer, and Ingeborg Levin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-551, https://doi.org/10.5194/essd-2024-551, 2025
Revised manuscript accepted for ESSD
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222Radon (Rn) can be used to distinguish marine and continental air masses or to validate transport models. The Heidelberg Radon Monitor (HRM) measures 214Polonium (Po), a progeny of Rn. This study presents Po-based Rn activity concentrations measured with the HRM at 8 stations in Germany with guidelines for estimating Rn from Po measurements. Comparison between modeled and measured activity concentrations show that at high relative humidity Po measurements cannot be interpreted as Rn.
Janusz W. Krzyścin, Agnieszka Czerwińska, Bonawentura Rajewska-Więch, Janusz Jarosławski, Piotr S. Sobolewski, and Izabela Pawlak
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-622, https://doi.org/10.5194/essd-2024-622, 2025
Revised manuscript accepted for ESSD
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Time series (1976−2023) of biologically effective (for skin redness, vitamin D3 production and psoriasis healing) daily radiant exposure (RE) at Belsk from standard erythemal biometers are examined. Comparisons of the measured data for cloudless days with values from a radiation transfer model provide a basis for data homogenization. Averaged results from different versions of the recalculated data give the 1976−2004 trend of about 6 % per 10 years in annual RE for all biological effects.
Simo Tukiainen, Tuomas Siipola, Niko Leskinen, and Ewan O'Connor
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-605, https://doi.org/10.5194/essd-2024-605, 2025
Revised manuscript accepted for ESSD
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Measurement campaigns are crucial for advancing the understanding of complex cloud–aerosol interactions in the atmosphere. Ground-based remote sensing measurements were conducted in Kenttärova, Finland, during the PaCE 2022 campaign. These measurements were processed using the Cloudnet methodology, and the data are available through the ACTRIS Cloudnet data portal.
Yugo Kanaya, Roberto Sommariva, Alfonso Saiz-Lopez, Andrea Mazzeo, Theodore K. Koenig, Kaori Kawana, James E. Johnson, Aurélie Colomb, Pierre Tulet, Suzie Molloy, Ian E. Galbally, Rainer Volkamer, Anoop Mahajan, John W. Halfacre, Paul B. Shepson, Julia Schmale, Hélène Angot, Byron Blomquist, Matthew D. Shupe, Detlev Helmig, Junsu Gil, Meehye Lee, Sean C. Coburn, Ivan Ortega, Gao Chen, James Lee, Kenneth C. Aikin, David D. Parrish, John S. Holloway, Thomas B. Ryerson, Ilana B. Pollack, Eric J. Williams, Brian M. Lerner, Andrew J. Weinheimer, Teresa Campos, Frank M. Flocke, J. Ryan Spackman, Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Ralf M. Staebler, Amir A. Aliabadi, Wanmin Gong, Roeland Van Malderen, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Juan Carlos Gómez Martin, Masatomo Fujiwara, Katie Read, Matthew Rowlinson, Keiichi Sato, Junichi Kurokawa, Yoko Iwamoto, Fumikazu Taketani, Hisahiro Takashima, Monica Navarro Comas, Marios Panagi, and Martin G. Schultz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-566, https://doi.org/10.5194/essd-2024-566, 2025
Revised manuscript accepted for ESSD
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The first comprehensive dataset of tropospheric ozone over oceans/polar regions is presented, including 77 ship/buoy and 48 aircraft campaign observations (1977–2022, 0–5000 m altitude), supplemented by ozonesonde and surface data. Air masses isolated from land for 72+ hours are systematically selected as essentially oceanic. Among the 11 global regions, they show daytime decreases of 10–16% in the tropics, while near-zero depletions are rare, unlike in the Arctic, implying different mechanisms.
Isolde Glissenaar, Klaas Folkert Boersma, Isidora Anglou, Pieter Rijsdijk, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Michel Van Roozendael, and Henk Eskes
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-616, https://doi.org/10.5194/essd-2024-616, 2025
Revised manuscript accepted for ESSD
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We developed a new global dataset of nitrogen dioxide (NO2) levels in the lower atmosphere, using data from TROPOMI for 2018–2021. This dataset offers improved accuracy and detail compared to earlier versions, meeting high international standards for climate data. By refining how measurement errors are calculated and reduced over time and space, we provide clearer insights into pollution patterns. This work supports better air quality monitoring and informs actions to address pollution globally.
Laura Köhler, Julia Windmiller, Dariusz Baranowski, Michał Brennek, Michał Ciuryło, Lennéa Hayo, Daniel Kȩpski, Stefan Kinne, Beata Latos, Bertrand Lobo, Tobias Marke, Timo Nischik, Daria Paul, Piet Stammes, Artur Szkop, and Olaf Tuinder
Earth Syst. Sci. Data, 17, 633–659, https://doi.org/10.5194/essd-17-633-2025, https://doi.org/10.5194/essd-17-633-2025, 2025
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We present atmospheric and oceanic data from the Atlantic References and Convection ship campaign with the Maria S. Merian from Mindelo to Punta Arenas observed with the integrated ship sensors; humidity and temperature profiler; ceilometer; aerosol instruments (Calitoo, Microtops, and DustTrak); radiosondes; uncrewed aircraft vehicles; and conductivity, temperature, and depth scans. The data include three complete profiles of the Intertropical Convergence Zone and a storm in the South Atlantic.
Emmanouil Proestakis, Vassilis Amiridis, Carlos Pérez García-Pando, Svetlana Tsyro, Jan Griesfeller, Antonis Gkikas, Thanasis Georgiou, María Gonçalves Ageitos, Jeronimo Escribano, Stelios Myriokefalitakis, Elisa Bergas Masso, Enza Di Tomaso, Sara Basart, Jan-Berend W. Stuut, and Angela Benedetti
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-43, https://doi.org/10.5194/essd-2025-43, 2025
Revised manuscript accepted for ESSD
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Quantification of dust deposition into the broader Atlantic Ocean is provided, with the estimates established on the basis of Earth Observations. The dataset is considered unique with respect to a range of applications, including compensating for spatiotemporal gaps of sediment-trap measurements, assessments of model simulations, shedding light into physical processes related to the dust cycle, and to better understand dust biogeochemical impacts on oceanic ecosystems, on weather, and climate.
Jürgen Gratzl, David Brus, Konstantinos Doulgeris, Alexander Böhmländer, Ottmar Möhler, and Hinrich Grothe
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-543, https://doi.org/10.5194/essd-2024-543, 2025
Revised manuscript accepted for ESSD
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Near-real time monitoring of airborne biological particles like fungal spores or pollen grains is of great interest for two main reasons: To improve atmospheric allergen forecasts and deepen the understanding of how bioaerosols influence cloud formation. Here, we measured fluorescent bioaerosols in the Finnish sub-Arctic with high time resolution. A data set that might improve our understanding of biosphere-cloud interactions and the dynamics of bioaerosols in the atmosphere.
Philippe Marbaix, Alexandre K. Magnan, Veruska Muccione, Peter W. Thorne, and Zinta Zommers
Earth Syst. Sci. Data, 17, 317–349, https://doi.org/10.5194/essd-17-317-2025, https://doi.org/10.5194/essd-17-317-2025, 2025
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Since 2001, the Intergovernmental Panel on Climate Change (IPCC) has used burning-ember diagrams to show how risks increase with global warming. We bring these data into a harmonized framework available through an online Climate Risks Embers Explorer. Without high levels of adaptation, most risks reach a high level around 2 to 2.3 °C of global warming. Improvements in future reports could include systematic collection of explanatory information and broader coverage of regions and adaptation.
Yueming Dong, Jing Li, Zhenyu Zhang, Chongzhao Zhang, and Qiurui Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-583, https://doi.org/10.5194/essd-2024-583, 2025
Revised manuscript accepted for ESSD
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This study develops two merged global land aerosol single scattering albedo (SSA) datasets by combining AERONET ground observations and two satellite datasets using an Ensemble Kalman Filter data synergy method. The merged datasets exhibit significantly improved accuracy compared to the original satellite data. These results can provide more reliable estimates of aerosol scattering and absorption properties, essential for improving climate modeling and assessing aerosol climate effects.
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.
Israel Silber, Jennifer M. Comstock, Michael R. Kieburtz, and Lynn M. Russell
Earth Syst. Sci. Data, 17, 29–42, https://doi.org/10.5194/essd-17-29-2025, https://doi.org/10.5194/essd-17-29-2025, 2025
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We present ARMTRAJ, a set of multipurpose trajectory datasets, which augments cloud, aerosol, and boundary layer studies utilizing the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility data. ARMTRAJ data include ensemble run statistics that enhance consistency and serve as uncertainty metrics for air mass coordinates and state variables. ARMTRAJ will soon become a near real-time product that will accompany past, ongoing, and future ARM deployments.
Fan Mei, Jennifer M. Comstock, Mikhail S. Pekour, Jerome D. Fast, Krista L. Gaustad, Beat Schmid, Shuaiqi Tang, Damao Zhang, John E. Shilling, Jason M. Tomlinson, Adam C. Varble, Jian Wang, L. Ruby Leung, Lawrence Kleinman, Scot Martin, Sebastien C. Biraud, Brian D. Ermold, and Kenneth W. Burk
Earth Syst. Sci. Data, 16, 5429–5448, https://doi.org/10.5194/essd-16-5429-2024, https://doi.org/10.5194/essd-16-5429-2024, 2024
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Our study explores a comprehensive dataset from airborne field studies (2013–2018) conducted using the US Department of Energy's Gulfstream 1 (G-1). The 236 flights span diverse regions, including the Arctic, US Southern Great Plains, US West Coast, eastern North Atlantic, Amazon Basin in Brazil, and Sierras de Córdoba range in Argentina. This dataset provides unique insights into atmospheric dynamics, aerosols, and clouds and makes data available in a more accessible format.
Viktoria F. Sofieva, Alexei Rozanov, Monika Szelag, John P. Burrows, Christian Retscher, Robert Damadeo, Doug Degenstein, Landon A. Rieger, and Adam Bourassa
Earth Syst. Sci. Data, 16, 5227–5241, https://doi.org/10.5194/essd-16-5227-2024, https://doi.org/10.5194/essd-16-5227-2024, 2024
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Climate-related studies need information about the distribution of stratospheric aerosols, which influence the energy balance of the Earth’s atmosphere. In this work, we present a merged dataset of vertically resolved stratospheric aerosol extinction coefficients, which is derived from data of six limb and occultation satellite instruments. The created aerosol climate record covers the period from October 1984 to December 2023. It can be used in various climate-related studies.
Hasna Chebaicheb, Joel F. de Brito, Tanguy Amodeo, Florian Couvidat, Jean-Eudes Petit, Emmanuel Tison, Gregory Abbou, Alexia Baudic, Mélodie Chatain, Benjamin Chazeau, Nicolas Marchand, Raphaële Falhun, Florie Francony, Cyril Ratier, Didier Grenier, Romain Vidaud, Shouwen Zhang, Gregory Gille, Laurent Meunier, Caroline Marchand, Véronique Riffault, and Olivier Favez
Earth Syst. Sci. Data, 16, 5089–5109, https://doi.org/10.5194/essd-16-5089-2024, https://doi.org/10.5194/essd-16-5089-2024, 2024
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Long-term (2015–2021) quasi-continuous measurements have been obtained at 13 French urban sites using online mass spectrometry, to acquire the comprehensive chemical composition of submicron particulate matter. The results show their spatial and temporal differences and confirm the predominance of organics in France (40–60 %). These measurements can be used for many future studies, such as trend and epidemiological analyses, or comparisons with chemical transport models.
Paola Formenti and Claudia Di Biagio
Earth Syst. Sci. Data, 16, 4995–5007, https://doi.org/10.5194/essd-16-4995-2024, https://doi.org/10.5194/essd-16-4995-2024, 2024
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Particles from deserts and semi-vegetated areas (mineral dust) are important for Earth's climate and human health, notably depending on their size. In this paper we collect and make a synthesis of a body of these observations since 1972 in order to provide researchers modeling Earth's climate and developing satellite observations from space with a simple way of confronting their results and understanding their validity.
Yonghang Hu, Chenguang Tian, Xu Yue, Yadong Lei, Yang Cao, Rongbin Xu, and Yuming Guo
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-414, https://doi.org/10.5194/essd-2024-414, 2024
Revised manuscript accepted for ESSD
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We develop a global dataset of daily fire-sourced PM2.5 concentration at a spatial resolution of 0.25° for 2000–2023, using a chemical transport model driven with two fire emission inventories and a machine learning approach trained with ground measurements from over 9000 sites. The dataset shows significant spatiotemporal variations of fire PM2.5 in the past decades, serving a useful tool for exploring the impacts of fire-related air pollutants on climate, ecosystems, and public health.
Yichen Jiang, Su Shi, Xinyue Li, Chang Xu, Haidong Kan, Bo Hu, and Xia Meng
Earth Syst. Sci. Data, 16, 4655–4672, https://doi.org/10.5194/essd-16-4655-2024, https://doi.org/10.5194/essd-16-4655-2024, 2024
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Limited ultraviolet (UV) measurements hindered further investigation of its health effects. This study used a machine learning algorithm to predict UV radiation with a daily and 10 km resolution of high accuracy in mainland China in 2005–2020. Then, uneven spatial distribution and population exposure risks as well as increased temporal trend of UV radiation were found in China. The long-term and high-quality UV dataset could further facilitate health-related research in the future.
Dene Bowdalo, Sara Basart, Marc Guevara, Oriol Jorba, Carlos Pérez García-Pando, Monica Jaimes Palomera, Olivia Rivera Hernandez, Melissa Puchalski, David Gay, Jörg Klausen, Sergio Moreno, Stoyka Netcheva, and Oksana Tarasova
Earth Syst. Sci. Data, 16, 4417–4495, https://doi.org/10.5194/essd-16-4417-2024, https://doi.org/10.5194/essd-16-4417-2024, 2024
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GHOST (Globally Harmonised Observations in Space and Time) represents one of the biggest collections of harmonised measurements of atmospheric composition at the surface. In total, 7 275 148 646 measurements from 1970 to 2023, from 227 different components, and from 38 reporting networks are compiled, parsed, and standardised. Components processed include gaseous species, total and speciated particulate matter, and aerosol optical properties.
Lei Kong, Xiao Tang, Zifa Wang, Jiang Zhu, Jianjun Li, Huangjian Wu, Qizhong Wu, Huansheng Chen, Lili Zhu, Wei Wang, Bing Liu, Qian Wang, Duohong Chen, Yuepeng Pan, Jie Li, Lin Wu, and Gregory R. Carmichael
Earth Syst. Sci. Data, 16, 4351–4387, https://doi.org/10.5194/essd-16-4351-2024, https://doi.org/10.5194/essd-16-4351-2024, 2024
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A new long-term inversed emission inventory for Chinese air quality (CAQIEI) is developed in this study, which contains constrained monthly emissions of NOx, SO2, CO, PM2.5, PM10, and NMVOCs in China from 2013 to 2020 with a horizontal resolution of 15 km. Emissions of different air pollutants and their changes during 2013–2020 were investigated and compared with previous emission inventories, which sheds new light on the complex variations of air pollutant emissions in China.
Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
Earth Syst. Sci. Data, 16, 4291–4309, https://doi.org/10.5194/essd-16-4291-2024, https://doi.org/10.5194/essd-16-4291-2024, 2024
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Sulfur dioxide (SO2), a poisonous gas from human activities and volcanoes, causes air pollution, acid rain, and changes to climate and the ozone layer. Satellites have been used to monitor SO2 globally, including remote areas. Here we describe a new satellite SO2 dataset from the OMPS instrument that flies on the N20 satellite. Results show that the new dataset agrees well with the existing ones from other satellites and can help to continue the global monitoring of SO2 from space.
Jacqueline E. Russell, Richard J. Bantges, Helen E. Brindley, and Alejandro Bodas-Salcedo
Earth Syst. Sci. Data, 16, 4243–4266, https://doi.org/10.5194/essd-16-4243-2024, https://doi.org/10.5194/essd-16-4243-2024, 2024
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We present a dataset of top-of-atmosphere diurnally resolved reflected solar and emitted thermal energy for Earth system model evaluation. The multi-year, monthly hourly dataset, derived from observations made by the Geostationary Earth Radiation Budget instrument, covers the range 60° N–60° S, 60° E–60° W at 1° resolution. Comparison with two versions of the Hadley Centre Global Environmental Model highlight how the data can be used to assess updates to key model parameterizations.
Dominique Gantois, Guillaume Payen, Michaël Sicard, Valentin Duflot, Nelson Bègue, Nicolas Marquestaut, Thierry Portafaix, Sophie Godin-Beekmann, Patrick Hernandez, and Eric Golubic
Earth Syst. Sci. Data, 16, 4137–4159, https://doi.org/10.5194/essd-16-4137-2024, https://doi.org/10.5194/essd-16-4137-2024, 2024
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We describe three instruments that have been measuring interactions between aerosols (particles of various origin) and light over Réunion Island since 2012. Aerosols directly or indirectly influence the temperature in the atmosphere and can interact with clouds. Details are given on how we derived aerosol properties from our measurements and how we assessed the quality of our data before sharing them with the scientific community. A good correlation was found between the three instruments.
Hongfei Hao, Kaicun Wang, Guocan Wu, Jianbao Liu, and Jing Li
Earth Syst. Sci. Data, 16, 4051–4076, https://doi.org/10.5194/essd-16-4051-2024, https://doi.org/10.5194/essd-16-4051-2024, 2024
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In this study, daily PM2.5 concentrations are estimated from 1959 to 2022 using a machine learning method at more than 5000 terrestrial sites in the Northern Hemisphere based on hourly atmospheric visibility data, which are extracted from the Meteorological Terminal Aviation Routine Weather Report (METAR).
Pierre Tulet, Joel Van Baelen, Pierre Bosser, Jérome Brioude, Aurélie Colomb, Philippe Goloub, Andrea Pazmino, Thierry Portafaix, Michel Ramonet, Karine Sellegri, Melilotus Thyssen, Léa Gest, Nicolas Marquestaut, Dominique Mékiès, Jean-Marc Metzger, Gilles Athier, Luc Blarel, Marc Delmotte, Guillaume Desprairies, Mérédith Dournaux, Gaël Dubois, Valentin Duflot, Kevin Lamy, Lionel Gardes, Jean-François Guillemot, Valérie Gros, Joanna Kolasinski, Morgan Lopez, Olivier Magand, Erwan Noury, Manuel Nunes-Pinharanda, Guillaume Payen, Joris Pianezze, David Picard, Olivier Picard, Sandrine Prunier, François Rigaud-Louise, Michael Sicard, and Benjamin Torres
Earth Syst. Sci. Data, 16, 3821–3849, https://doi.org/10.5194/essd-16-3821-2024, https://doi.org/10.5194/essd-16-3821-2024, 2024
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The MAP-IO program aims to compensate for the lack of atmospheric and oceanographic observations in the Southern Ocean by equipping the ship Marion Dufresne with a set of 17 scientific instruments. This program collected 700 d of measurements under different latitudes, seasons, sea states, and weather conditions. These new data will support the calibration and validation of numerical models and the understanding of the atmospheric composition of this region of Earth.
Siwei Li, Yu Ding, Jia Xing, and Joshua S. Fu
Earth Syst. Sci. Data, 16, 3781–3793, https://doi.org/10.5194/essd-16-3781-2024, https://doi.org/10.5194/essd-16-3781-2024, 2024
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Surface PM2.5 data have gained widespread application in health assessments and related fields, while the inherent uncertainties in PM2.5 data persist due to the lack of ground-truth data across the space. This study provides a novel testbed, enabling comprehensive evaluation across the entire spatial domain. The optimized deep-learning model with spatiotemporal features successfully retrieved surface PM2.5 concentrations in China (2013–2021), with reduced biases induced by sample imbalance.
Shuai Wang, Mengyuan Zhang, Hui Zhao, Peng Wang, Sri Harsha Kota, Qingyan Fu, Cong Liu, and Hongliang Zhang
Earth Syst. Sci. Data, 16, 3565–3577, https://doi.org/10.5194/essd-16-3565-2024, https://doi.org/10.5194/essd-16-3565-2024, 2024
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Long-term, open-source, gap-free daily ground-level PM2.5 and PM10 datasets for India (LongPMInd) were reconstructed using a robust machine learning model to support health assessment and air quality management.
Hongfei Hao, Kaicun Wang, Chuanfeng Zhao, Guocan Wu, and Jing Li
Earth Syst. Sci. Data, 16, 3233–3260, https://doi.org/10.5194/essd-16-3233-2024, https://doi.org/10.5194/essd-16-3233-2024, 2024
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In this study, we employed a machine learning technique to derive daily aerosol optical depth from hourly visibility observations collected at more than 5000 airports worldwide from 1959 to 2021 combined with reanalysis meteorological parameters.
Arndt Kaps, Axel Lauer, Rémi Kazeroni, Martin Stengel, and Veronika Eyring
Earth Syst. Sci. Data, 16, 3001–3016, https://doi.org/10.5194/essd-16-3001-2024, https://doi.org/10.5194/essd-16-3001-2024, 2024
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CCClim displays observations of clouds in terms of cloud classes that have been in use for a long time. CCClim is a machine-learning-powered product based on multiple existing observational products from different satellites. We show that the cloud classes in CCClim are physically meaningful and can be used to study cloud characteristics in more detail. The goal of this is to make real-world clouds more easily understandable to eventually improve the simulation of clouds in climate models.
David Winker, Xia Cai, Mark Vaughan, Anne Garnier, Brian Magill, Melody Avery, and Brian Getzewich
Earth Syst. Sci. Data, 16, 2831–2855, https://doi.org/10.5194/essd-16-2831-2024, https://doi.org/10.5194/essd-16-2831-2024, 2024
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Clouds play important roles in both weather and climate. In this paper we describe version 1.0 of a unique global ice cloud data product derived from over 12 years of global spaceborne lidar measurements. This monthly gridded product provides a unique vertically resolved characterization of the occurrence and properties, optical and physical, of thin ice clouds and the tops of deep convective clouds. It should provide significant value for cloud research and model evaluation.
Karam Mansour, Stefano Decesari, Darius Ceburnis, Jurgita Ovadnevaite, Lynn M. Russell, Marco Paglione, Laurent Poulain, Shan Huang, Colin O'Dowd, and Matteo Rinaldi
Earth Syst. Sci. Data, 16, 2717–2740, https://doi.org/10.5194/essd-16-2717-2024, https://doi.org/10.5194/essd-16-2717-2024, 2024
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We propose and evaluate machine learning predictive algorithms to model freshly formed biogenic methanesulfonic acid and sulfate concentrations. The long-term constructed dataset covers the North Atlantic at an unprecedented resolution. The improved parameterization of biogenic sulfur aerosols at regional scales is essential for determining their radiative forcing, which could help further understand marine-aerosol–cloud interactions and reduce uncertainties in climate models
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
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This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, and Steven J. Smith
Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
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Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Declan L. Finney, Alan M. Blyth, Martin Gallagher, Huihui Wu, Graeme J. Nott, Michael I. Biggerstaff, Richard G. Sonnenfeld, Martin Daily, Dan Walker, David Dufton, Keith Bower, Steven Böing, Thomas Choularton, Jonathan Crosier, James Groves, Paul R. Field, Hugh Coe, Benjamin J. Murray, Gary Lloyd, Nicholas A. Marsden, Michael Flynn, Kezhen Hu, Navaneeth M. Thamban, Paul I. Williams, Paul J. Connolly, James B. McQuaid, Joseph Robinson, Zhiqiang Cui, Ralph R. Burton, Gordon Carrie, Robert Moore, Steven J. Abel, Dave Tiddeman, and Graydon Aulich
Earth Syst. Sci. Data, 16, 2141–2163, https://doi.org/10.5194/essd-16-2141-2024, https://doi.org/10.5194/essd-16-2141-2024, 2024
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The DCMEX (Deep Convective Microphysics Experiment) project undertook an aircraft- and ground-based measurement campaign of New Mexico deep convective clouds during July–August 2022. The campaign coordinated a broad range of instrumentation measuring aerosol, cloud physics, radar signals, thermodynamics, dynamics, electric fields, and weather. The project's objectives included the utilisation of these data with satellite observations to study the anvil cloud radiative effect.
Jianzhong Xu, Xinghua Zhang, Wenhui Zhao, Lixiang Zhai, Miao Zhong, Jinsen Shi, Junying Sun, Yanmei Liu, Conghui Xie, Yulong Tan, Kemei Li, Xinlei Ge, Qi Zhang, and Shichang Kang
Earth Syst. Sci. Data, 16, 1875–1900, https://doi.org/10.5194/essd-16-1875-2024, https://doi.org/10.5194/essd-16-1875-2024, 2024
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A comprehensive aerosol observation project was carried out in the Tibetan Plateau (TP) and its surroundings in recent years to investigate the properties and sources of atmospheric aerosols as well as their regional differences by performing multiple intensive field observations. The release of this dataset can provide basic and systematic data for related research in the atmospheric, cryospheric, and environmental sciences in this unique region.
Xiaoyong Zhuge, Xiaolei Zou, Lu Yu, Xin Li, Mingjian Zeng, Yilun Chen, Bing Zhang, Bin Yao, Fei Tang, Fengjiao Chen, and Wanlin Kan
Earth Syst. Sci. Data, 16, 1747–1769, https://doi.org/10.5194/essd-16-1747-2024, https://doi.org/10.5194/essd-16-1747-2024, 2024
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The Himawari-8/9 level-2 operational cloud product has a low spatial resolution and is available only during the daytime. To supplement this official dataset, a new dataset named the NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD) was constructed. The NJIAS HCFD provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the years 2016–2022 by 30 retrieved cloud variables. The NJIAS HCFD has been demonstrated to outperform the official dataset.
Honglin Pan, Jianping Huang, Jiming Li, Zhongwei Huang, Minzhong Wang, Ali Mamtimin, Wen Huo, Fan Yang, Tian Zhou, and Kanike Raghavendra Kumar
Earth Syst. Sci. Data, 16, 1185–1207, https://doi.org/10.5194/essd-16-1185-2024, https://doi.org/10.5194/essd-16-1185-2024, 2024
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We applied several correction procedures and rigorously checked for data quality constraints during the long observation period spanning almost 14 years (2007–2020). Nevertheless, some uncertainties remain, mainly due to technical constraints and limited documentation of the measurements. Even though not completely accurate, this strategy is expected to at least reduce the inaccuracy of the computed characteristic value of aerosol optical parameters.
Julie Christin Schindlbeck-Belo, Matthew Toohey, Marion Jegen, Steffen Kutterolf, and Kira Rehfeld
Earth Syst. Sci. Data, 16, 1063–1081, https://doi.org/10.5194/essd-16-1063-2024, https://doi.org/10.5194/essd-16-1063-2024, 2024
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Volcanic forcing of climate resulting from major explosive eruptions is a dominant natural driver of past climate variability. To support model studies of the potential impacts of explosive volcanism on climate variability across timescales, we present an ensemble reconstruction of volcanic stratospheric sulfur injection over the last 140 000 years that is based primarily on tephra records.
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Short summary
A unique monthly NO3− dataset at 0.25° resolution over China during 2005–2015 was developed by assimilating multi-source variables. The newly developed product featured an excellent cross-validation R2 value (0.78) and relatively lower RMSE (1.19 μg N m−3) and mean absolute error (MAE: 0.81 μg N m−3). The dataset also exhibited relatively robust performance at the spatial and temporal scales. The dataset over China could deepen knowledge of the status of N pollution in China.
A unique monthly NO3− dataset at 0.25° resolution over China during 2005–2015 was developed by...
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