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
Related authors
Si Zhang, Yining Gao, Xinbei Xu, Luyao Chen, Can Wu, Zheng Li, Rongjie Li, Binyu Xiao, Xiaodi Liu, Rui Li, Fan Zhang, and Gehui Wang
Atmos. Chem. Phys., 24, 14177–14190, https://doi.org/10.5194/acp-24-14177-2024, https://doi.org/10.5194/acp-24-14177-2024, 2024
Short summary
Short summary
Secondary organic aerosols (SOAs) from acetone photooxidation in the presence of various seeds were studied to illustrate SOA formation kinetics under ammonia-rich conditions. The oxidation mechanism of acetone was investigated using an observation-based model incorporating a Master Chemical Mechanism model. A higher SOA yield of acetone was observed compared to methylglyoxal due to an enhanced uptake of the small photooxidation products of acetone.
Binyu Xiao, Fan Zhang, Zeyu Liu, Yan Zhang, Rui Li, Can Wu, Xinyi Wan, Yi Wang, Yubao Chen, Yong Han, Min Cui, Libo Zhang, Yingjun Chen, and Gehui Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3433, https://doi.org/10.5194/egusphere-2024-3433, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Intermediate/semi-volatile organic compounds in both gas and particle phases from ship exhausts are enhanced due to the switch of fuels from low-sulfur to ultra-low-sulfur. The findings indicate that optimization is necessary for the forthcoming global implementation of an ultra-low-sulfur oil policy. Besides, we find that organic diagnostic markers of hopanes, in conjunction with the ratio of octadecanoic to tetradecanoic could be considered as potential tracers for HFO exhausts.
Xinbei Xu, Yining Gao, Si Zhang, Luyao Chen, Rongjie Li, Zheng Li, Rui Li, and Gehui Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3046, https://doi.org/10.5194/egusphere-2024-3046, 2024
Short summary
Short summary
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.
Baoye Hu, Naihua Chen, Rui Li, Mingqiang Huang, Jinsheng Chen, Youwei Hong, Lingling Xu, Xiaolong Fan, Mengren Li, Lei Tong, Qiuping Zheng, and Yuxiang Yang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2631, https://doi.org/10.5194/egusphere-2024-2631, 2024
Short summary
Short summary
Box modeling with the master chemical mechanism (MCM) was used to address the puzzle of summertime PAN formation and its association with aerosol pollution under high ozone conditions. The MCM model proves to be an ideal tool for investigating PAN photochemical formation (IOA=0.75). The model performed better during the clean period than during the haze period. Through the machine learning method of XGBoost, we found that the top three factors leading to simulation bias were NH3, NO3, and PM2.5.
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
Short summary
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
Short summary
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.
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
Short summary
Short summary
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
Atmos. Chem. Phys., 23, 3311–3324, https://doi.org/10.5194/acp-23-3311-2023, https://doi.org/10.5194/acp-23-3311-2023, 2023
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Si Zhang, Yining Gao, Xinbei Xu, Luyao Chen, Can Wu, Zheng Li, Rongjie Li, Binyu Xiao, Xiaodi Liu, Rui Li, Fan Zhang, and Gehui Wang
Atmos. Chem. Phys., 24, 14177–14190, https://doi.org/10.5194/acp-24-14177-2024, https://doi.org/10.5194/acp-24-14177-2024, 2024
Short summary
Short summary
Secondary organic aerosols (SOAs) from acetone photooxidation in the presence of various seeds were studied to illustrate SOA formation kinetics under ammonia-rich conditions. The oxidation mechanism of acetone was investigated using an observation-based model incorporating a Master Chemical Mechanism model. A higher SOA yield of acetone was observed compared to methylglyoxal due to an enhanced uptake of the small photooxidation products of acetone.
Binyu Xiao, Fan Zhang, Zeyu Liu, Yan Zhang, Rui Li, Can Wu, Xinyi Wan, Yi Wang, Yubao Chen, Yong Han, Min Cui, Libo Zhang, Yingjun Chen, and Gehui Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3433, https://doi.org/10.5194/egusphere-2024-3433, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Intermediate/semi-volatile organic compounds in both gas and particle phases from ship exhausts are enhanced due to the switch of fuels from low-sulfur to ultra-low-sulfur. The findings indicate that optimization is necessary for the forthcoming global implementation of an ultra-low-sulfur oil policy. Besides, we find that organic diagnostic markers of hopanes, in conjunction with the ratio of octadecanoic to tetradecanoic could be considered as potential tracers for HFO exhausts.
Xinbei Xu, Yining Gao, Si Zhang, Luyao Chen, Rongjie Li, Zheng Li, Rui Li, and Gehui Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3046, https://doi.org/10.5194/egusphere-2024-3046, 2024
Short summary
Short summary
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.
Baoye Hu, Naihua Chen, Rui Li, Mingqiang Huang, Jinsheng Chen, Youwei Hong, Lingling Xu, Xiaolong Fan, Mengren Li, Lei Tong, Qiuping Zheng, and Yuxiang Yang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2631, https://doi.org/10.5194/egusphere-2024-2631, 2024
Short summary
Short summary
Box modeling with the master chemical mechanism (MCM) was used to address the puzzle of summertime PAN formation and its association with aerosol pollution under high ozone conditions. The MCM model proves to be an ideal tool for investigating PAN photochemical formation (IOA=0.75). The model performed better during the clean period than during the haze period. Through the machine learning method of XGBoost, we found that the top three factors leading to simulation bias were NH3, NO3, and PM2.5.
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
Short summary
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
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Atmos. Chem. Phys., 23, 3311–3324, https://doi.org/10.5194/acp-23-3311-2023, https://doi.org/10.5194/acp-23-3311-2023, 2023
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
This study compared the gas-phase, aqueous-phase, and heterogeneous SO2 oxidation pathways by combining laboratory work with a modelling study. The heterogeneous oxidation, particularly that induced by the dust surface drivers, presents positive implications for the removal of airborne SO2 and formation of sulfate aerosols. This work highlighted the atmospheric significance of heterogeneous oxidation and suggested a comparison model to evaluate the following heterogeneous laboratory research.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Related subject area
Atmospheric chemistry and physics
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
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)
Climate change risks illustrated by the IPCC “burning embers”
Calm ocean, stormy sea: Atmospheric and oceanographic observations of the Atlantic during the ARC ship campaign
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
ARMTRAJ: A Set of Multi-Purpose Trajectory Datasets Augmenting the Atmospheric Radiation Measurement (ARM) User Facility Measurements
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)
Four decades of global surface albedo estimates in the third edition of the CM SAF cLoud, Albedo and surface Radiation (CLARA) climate data record
Data supporting the North Atlantic Climate System: Integrated Studies (ACSIS) programme, including atmospheric composition, oceanographic and sea ice observations (2016–2022) and output from ocean, atmosphere, land and sea-ice models (1950–2050)
Ground- and ship-based microwave radiometer measurements during EUREC4A
Shortwave and longwave components of the surface radiation budget measured at the Thule High Arctic Atmospheric Observatory, Northern Greenland
Cloud condensation nuclei concentrations derived from the CAMS reanalysis
A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS
12 years of continuous atmospheric O2, CO2 and APO data from Weybourne Atmospheric Observatory in the United Kingdom
CLAAS-3: the third edition of the CM SAF cloud data record based on SEVIRI observations
Using machine learning to construct TOMCAT model and occultation measurement-based stratospheric methane (TCOM-CH4) and nitrous oxide (TCOM-N2O) profile data sets
High-resolution aerosol data from the top 3.8 kyr of the East Greenland Ice coring Project (EGRIP) ice core
A database of aircraft measurements of carbon monoxide (CO) with high temporal and spatial resolution during 2011–2021
A first global height-resolved cloud condensation nuclei data set derived from spaceborne lidar measurements
A monthly 1° resolution dataset of daytime cloud fraction over the Arctic during 2000–2020 based on multiple satellite products
Seamless mapping of long-term (2010–2020) daily global XCO2 and XCH4 from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatiotemporally self-supervised fusion method
Spatially coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: the NASA ACTIVATE dataset
Network for the Detection of Atmospheric Composition Change (NDACC) Fourier transform infrared (FTIR) trace gas measurements at the University of Toronto Atmospheric Observatory from 2002 to 2020
Deconstruction of tropospheric chemical reactivity using aircraft measurements: the Atmospheric Tomography Mission (ATom) data
Spatial variability of Saharan dust deposition revealed through a citizen science campaign
Radiative sensitivity quantified by a new set of radiation flux kernels based on the ECMWF Reanalysis v5 (ERA5)
Updated observations of clouds by MODIS for global model assessment
An investigation of the global uptake of CO2 by lime from 1930 to 2020
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Philippe Marbaix, Alexandre K. Magnan, Veruska Muccione, Peter W. Thorne, and Zinta Zommers
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-312, https://doi.org/10.5194/essd-2024-312, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Since 2001, the IPCC has used 'burning ember' diagrams to show how risks increase with global warming. We bring this data into a harmonised framework and facilitate access through an online 'climate risks ember explorer'. Without high levels of adaptation, most risks reach a high level around 2 to 2.3 °C of global warming. Improvements in future IPCC reports could include systematic collection of explanatory information, broader coverage of regions and greater consideration of adaptation.
Laura Köhler, Julia Windmiller, Dariusz Baranowski, Michał Brennek, Michał Ciuryło, Lennéa Hayo, Daniel Kepski, Stefan Kinne, Beata Latos, Bertrand Lobo, Tobias Marke, Timo Nischik, Daria Paul, Piet Stammes, Artur Szkop, and Olaf Tuinder
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-275, https://doi.org/10.5194/essd-2024-275, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
We present atmospheric and oceanic data from the ARC ship campaign in the Atlantic with the RV Maria S. Merian from Mindelo, Cape Verde, to Punta Arenas, Chile. Included instruments are the integrated ship sensors (DShip), a Humidity and Temperature Profiler, a Ceilometer, aerosol instruments, radiosondes, UAVs, and Conductivity, Temperature, and Depth scans. The data include three complete profiles of the Atlantic Intertropical Convergence Zone and a storm in the South Atlantic.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Israel Silber, Jennifer M. Comstock, Michael R. Kieburtz, and Lynn M. Russell
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-127, https://doi.org/10.5194/essd-2024-127, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
We present ARMTRAJ, a set of multi-purpose trajectory datasets generated using HYSPLIT informed by ERA5 reanalysis at 0.25° resolution, which augments cloud, aerosol, and boundary layer studies utilizing the U.S. DOE ARM data. ARMTRAJ data include ensemble run statistics that enhance consistency and serve as uncertainty metrics for airmass coordinates and state variables. ARMTRAJ is expected to become a near real-time product that will accompany past, ongoing, and future ARM deployments.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Aku Riihelä, Emmihenna Jääskeläinen, and Viivi Kallio-Myers
Earth Syst. Sci. Data, 16, 1007–1028, https://doi.org/10.5194/essd-16-1007-2024, https://doi.org/10.5194/essd-16-1007-2024, 2024
Short summary
Short summary
We describe a new climate data record describing the surface albedo, or reflectivitity, of Earth's surface (called CLARA-A3 SAL). The climate data record spans over 4 decades of satellite observations, beginning in 1979. We conduct a quality assessment of the generated data, comparing them against other satellite data and albedo observations made on the ground. We find that the new data record in general matches surface observations well and is stable through time.
Alexander T. Archibald, Bablu Sinha, Maria Russo, Emily Matthews, Freya Squires, N. Luke Abraham, Stephane Bauguitte, Thomas Bannan, Thomas Bell, David Berry, Lucy Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Ben I. Moat, Katie Read, Chris Reed, Malcolm Roberts, Reinhard Schiemann, David Schroeder, Tim Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Ming-Xi Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-405, https://doi.org/10.5194/essd-2023-405, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Here we present an overview of the data generated as part of the North Atlantic Climate System Integrated Studies (ACSIS) programme which 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). ACSIS data cover the full North Atlantic System comprising: the North Atlantic Ocean, the atmosphere above it including its composition, Arctic Sea Ice and the Greenland Ice Sheet.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
Short summary
Short summary
This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Daniela Meloni, Filippo Calì Quaglia, Virginia Ciardini, Annalisa Di Bernardino, Tatiana Di Iorio, Antonio Iaccarino, Giovanni Muscari, Giandomenico Pace, Claudio Scarchilli, and Alcide di Sarra
Earth Syst. Sci. Data, 16, 543–566, https://doi.org/10.5194/essd-16-543-2024, https://doi.org/10.5194/essd-16-543-2024, 2024
Short summary
Short summary
Solar and infrared radiation are key factors in determining Arctic climate. Only a few sites in the Arctic perform long-term measurements of the surface radiation budget (SRB). At the Thule High Arctic Atmospheric Observatory (THAAO, 76.5° N, 68.8° W) in Northern Greenland, solar and infrared irradiance measurements were started in 2009. These data are of paramount importance in studying the impact of the atmospheric (mainly clouds and aerosols) and surface (albedo) parameters on the SRB.
Karoline Block, Mahnoosh Haghighatnasab, Daniel G. Partridge, Philip Stier, and Johannes Quaas
Earth Syst. Sci. Data, 16, 443–470, https://doi.org/10.5194/essd-16-443-2024, https://doi.org/10.5194/essd-16-443-2024, 2024
Short summary
Short summary
Aerosols being able to act as condensation nuclei for cloud droplets (CCNs) are a key element in cloud formation but very difficult to determine. In this study we present a new global vertically resolved CCN dataset for various humidity conditions and aerosols. It is obtained using an atmospheric model (CAMS reanalysis) that is fed by satellite observations of light extinction (AOD). We investigate and evaluate the abundance of CCNs in the atmosphere and their temporal and spatial occurrence.
Jianping Guo, Jian Zhang, Jia Shao, Tianmeng Chen, Kaixu Bai, Yuping Sun, Ning Li, Jingyan Wu, Rui Li, Jian Li, Qiyun Guo, Jason B. Cohen, Panmao Zhai, Xiaofeng Xu, and Fei Hu
Earth Syst. Sci. Data, 16, 1–14, https://doi.org/10.5194/essd-16-1-2024, https://doi.org/10.5194/essd-16-1-2024, 2024
Short summary
Short summary
A global continental merged high-resolution (PBLH) dataset with good accuracy compared to radiosonde is generated via machine learning algorithms, covering the period from 2011 to 2021 with 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input, with PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.
Karina E. Adcock, Penelope A. Pickers, Andrew C. Manning, Grant L. Forster, Leigh S. Fleming, Thomas Barningham, Philip A. Wilson, Elena A. Kozlova, Marica Hewitt, Alex J. Etchells, and Andy J. Macdonald
Earth Syst. Sci. Data, 15, 5183–5206, https://doi.org/10.5194/essd-15-5183-2023, https://doi.org/10.5194/essd-15-5183-2023, 2023
Short summary
Short summary
We present a 12-year time series of continuous atmospheric measurements of O2 and CO2 at the Weybourne Atmospheric Observatory in the United Kingdom. These measurements are combined into the term atmospheric potential oxygen (APO), a tracer that is not influenced by land biosphere processes. The datasets show a long-term increasing trend in CO2 and decreasing trends in O2 and APO between 2010 and 2021.
Nikos Benas, Irina Solodovnik, Martin Stengel, Imke Hüser, Karl-Göran Karlsson, Nina Håkansson, Erik Johansson, Salomon Eliasson, Marc Schröder, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, https://doi.org/10.5194/essd-15-5153-2023, 2023
Short summary
Short summary
This paper describes CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI, which was created based on observations from geostationary Meteosat satellites. CLAAS-3 cloud properties are evaluated using a variety of reference datasets, with very good overall results. The demonstrated quality of CLAAS-3 ensures its usefulness in a wide range of applications, including studies of local- to continental-scale cloud processes and evaluation of climate models.
Sandip S. Dhomse and Martyn P. Chipperfield
Earth Syst. Sci. Data, 15, 5105–5120, https://doi.org/10.5194/essd-15-5105-2023, https://doi.org/10.5194/essd-15-5105-2023, 2023
Short summary
Short summary
There are no long-term stratospheric profile data sets for two very important greenhouse gases: methane (CH4) and nitrous oxide (N2O). Along with radiative feedback, these species play an important role in controlling ozone loss in the stratosphere. Here, we use machine learning to fuse satellite measurements with a chemical model to construct long-term gap-free profile data sets for CH4 and N2O. We aim to construct similar data sets for other important trace gases (e.g. O3, Cly, NOy species).
Tobias Erhardt, Camilla Marie Jensen, Florian Adolphi, Helle Astrid Kjær, Remi Dallmayr, Birthe Twarloh, Melanie Behrens, Motohiro Hirabayashi, Kaori Fukuda, Jun Ogata, François Burgay, Federico Scoto, Ilaria Crotti, Azzurra Spagnesi, Niccoló Maffezzoli, Delia Segato, Chiara Paleari, Florian Mekhaldi, Raimund Muscheler, Sophie Darfeuil, and Hubertus Fischer
Earth Syst. Sci. Data, 15, 5079–5091, https://doi.org/10.5194/essd-15-5079-2023, https://doi.org/10.5194/essd-15-5079-2023, 2023
Short summary
Short summary
The presented paper provides a 3.8 kyr long dataset of aerosol concentrations from the East Greenland Ice coring Project (EGRIP) ice core. The data consists of 1 mm depth-resolution profiles of calcium, sodium, ammonium, nitrate, and electrolytic conductivity as well as decadal averages of these profiles. Alongside the data a detailed description of the measurement setup as well as a discussion of the uncertainties are given.
Chaoyang Xue, Gisèle Krysztofiak, Vanessa Brocchi, Stéphane Chevrier, Michel Chartier, Patrick Jacquet, Claude Robert, and Valéry Catoire
Earth Syst. Sci. Data, 15, 4553–4569, https://doi.org/10.5194/essd-15-4553-2023, https://doi.org/10.5194/essd-15-4553-2023, 2023
Short summary
Short summary
To understand tropospheric air pollution at regional and global scales, an infrared laser spectrometer called SPIRIT was used on aircraft to rapidly and accurately measure carbon monoxide (CO), an important indicator of air pollution, during the last decade. Measurements were taken for more than 200 flight hours over three continents. Levels of CO are mapped with 3D trajectories for each flight. Additionally, this can be used to validate model performance and satellite measurements.
Goutam Choudhury and Matthias Tesche
Earth Syst. Sci. Data, 15, 3747–3760, https://doi.org/10.5194/essd-15-3747-2023, https://doi.org/10.5194/essd-15-3747-2023, 2023
Short summary
Short summary
Aerosols in the atmosphere that can form liquid cloud droplets are called cloud condensation nuclei (CCN). Accurate measurements of CCN, especially CCN of anthropogenic origin, are necessary to quantify the effect of anthropogenic aerosols on the present-day as well as future climate. In this paper, we describe a novel global 3D CCN data set calculated from satellite measurements. We also discuss the potential applications of the data in the context of aerosol–cloud interactions.
Xinyan Liu, Tao He, Shunlin Liang, Ruibo Li, Xiongxin Xiao, Rui Ma, and Yichuan Ma
Earth Syst. Sci. Data, 15, 3641–3671, https://doi.org/10.5194/essd-15-3641-2023, https://doi.org/10.5194/essd-15-3641-2023, 2023
Short summary
Short summary
We proposed a data fusion strategy that combines the complementary features of multiple-satellite cloud fraction (CF) datasets and generated a continuous monthly 1° daytime cloud fraction product covering the entire Arctic during the sunlit months in 2000–2020. This study has positive significance for reducing the uncertainties for the assessment of surface radiation fluxes and improving the accuracy of research related to climate change and energy budgets, both regionally and globally.
Yuan Wang, Qiangqiang Yuan, Tongwen Li, Yuanjian Yang, Siqin Zhou, and Liangpei Zhang
Earth Syst. Sci. Data, 15, 3597–3622, https://doi.org/10.5194/essd-15-3597-2023, https://doi.org/10.5194/essd-15-3597-2023, 2023
Short summary
Short summary
We propose a novel spatiotemporally self-supervised fusion method to establish long-term daily seamless global XCO2 and XCH4 products. Results show that the proposed method achieves a satisfactory accuracy that distinctly exceeds that of CAMS-EGG4 and is superior or close to those of GOSAT and OCO-2. In particular, our fusion method can effectively correct the large biases in CAMS-EGG4 due to the issues from assimilation data, such as the unadjusted anthropogenic emission for COVID-19.
Armin Sorooshian, Mikhail D. Alexandrov, Adam D. Bell, Ryan Bennett, Grace Betito, Sharon P. Burton, Megan E. Buzanowicz, Brian Cairns, Eduard V. Chemyakin, Gao Chen, Yonghoon Choi, Brian L. Collister, Anthony L. Cook, Andrea F. Corral, Ewan C. Crosbie, Bastiaan van Diedenhoven, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Eva-Lou Edwards, Marta A. Fenn, Richard A. Ferrare, David van Gilst, Johnathan W. Hair, David B. Harper, Miguel Ricardo A. Hilario, Chris A. Hostetler, Nathan Jester, Michael Jones, Simon Kirschler, Mary M. Kleb, John M. Kusterer, Sean Leavor, Joseph W. Lee, Hongyu Liu, Kayla McCauley, Richard H. Moore, Joseph Nied, Anthony Notari, John B. Nowak, David Painemal, Kasey E. Phillips, Claire E. Robinson, Amy Jo Scarino, Joseph S. Schlosser, Shane T. Seaman, Chellappan Seethala, Taylor J. Shingler, Michael A. Shook, Kenneth A. Sinclair, William L. Smith Jr., Douglas A. Spangenberg, Snorre A. Stamnes, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Andrzej P. Wasilewski, Hailong Wang, Edward L. Winstead, Kira Zeider, Xubin Zeng, Bo Zhang, Luke D. Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data, 15, 3419–3472, https://doi.org/10.5194/essd-15-3419-2023, https://doi.org/10.5194/essd-15-3419-2023, 2023
Short summary
Short summary
The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions. HU-25 Falcon and King Air aircraft conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.
Shoma Yamanouchi, Stephanie Conway, Kimberly Strong, Orfeo Colebatch, Erik Lutsch, Sébastien Roche, Jeffrey Taylor, Cynthia H. Whaley, and Aldona Wiacek
Earth Syst. Sci. Data, 15, 3387–3418, https://doi.org/10.5194/essd-15-3387-2023, https://doi.org/10.5194/essd-15-3387-2023, 2023
Short summary
Short summary
Nineteen years of atmospheric composition measurements made at the University of Toronto Atmospheric Observatory (TAO; 43.66° N, 79.40° W; 174 m.a.s.l.) are presented. These are retrieved from Fourier transform infrared (FTIR) solar absorption spectra recorded with a spectrometer from May 2002 to December 2020. The retrievals have been optimized for fourteen species: O3, HCl, HF, HNO3, CH4, C2H6, CO, HCN, N2O, C2H2, H2CO, CH3OH, HCOOH, and NH3.
Michael J. Prather, Hao Guo, and Xin Zhu
Earth Syst. Sci. Data, 15, 3299–3349, https://doi.org/10.5194/essd-15-3299-2023, https://doi.org/10.5194/essd-15-3299-2023, 2023
Short summary
Short summary
The Atmospheric Tomography Mission (ATom) measured the chemical composition in air parcels from 0–12 km altitude on 2 km horizontal by 80 m vertical scales for four seasons, resolving most scales of chemical heterogeneity. ATom is one of the first missions designed to calculate the chemical evolution of each parcel, providing semi-global diurnal budgets for ozone and methane. Observations covered the remote troposphere: Pacific and Atlantic Ocean basins, Southern Ocean, Arctic basin, Antarctica.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
Short summary
Short summary
Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
Han Huang and Yi Huang
Earth Syst. Sci. Data, 15, 3001–3021, https://doi.org/10.5194/essd-15-3001-2023, https://doi.org/10.5194/essd-15-3001-2023, 2023
Short summary
Short summary
We present a newly generated set of ERA5-based radiative kernels and compare them with other published kernels for the top of the atmosphere and surface radiation budgets. For both, the discrepancies in sensitivity values are generally of small magnitude, except for temperature kernels for the surface, likely due to improper treatment in the perturbation experiments used for kernel computation. The kernel bias is not a major cause of the inter-GCM (general circulation model) feedback spread.
Robert Pincus, Paul A. Hubanks, Steven Platnick, Kerry Meyer, Robert E. Holz, Denis Botambekov, and Casey J. Wall
Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, https://doi.org/10.5194/essd-15-2483-2023, 2023
Short summary
Short summary
This paper describes a new global dataset of cloud properties observed by a specific satellite program created to facilitate comparison with a matching observational proxy used in climate models. Statistics are accumulated over daily and monthly timescales on an equal-angle grid. Statistics include cloud detection, cloud-top pressure, and cloud optical properties. Joint histograms of several variable pairs are also available.
Longfei Bing, Mingjing Ma, Lili Liu, Jiaoyue Wang, Le Niu, and Fengming Xi
Earth Syst. Sci. Data, 15, 2431–2444, https://doi.org/10.5194/essd-15-2431-2023, https://doi.org/10.5194/essd-15-2431-2023, 2023
Short summary
Short summary
We provided CO2 uptake inventory for global lime materials from 1930–2020, The majority of CO2 uptake was from the lime in China.
Our dataset and the accounting mathematical model may serve as a set of tools to improve the CO2 emission inventories and provide data support for policymakers to formulate scientific and reasonable policies under
carbon neutraltarget.
Cited articles
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, 2001.
Chen, H., Li, D., Gurmesa, G. A., Yu, G., Li, L., Zhang, W., Fang, H., and Mo, J.: Effects of nitrogen deposition on carbon cycle in terrestrial ecosystems of China: A meta-analysis, Environ. Pollut., 206, 352–360, https://doi.org/10.1016/j.envpol.2015.07.033, 2015.
Chen, J., Yin, J., Zang, L., Zhang, T., and Zhao, M.: Stacking machine learning model for estimating hourly PM2.5 in China based on Himawari-8 aerosol optical depth data, Sci. Total Environ., 697, 134021, https://doi.org/10.1016/j.scitotenv.2019.134021, 2019.
Chen, Z., Chen, D., Kwan, M.-P., Chen, B., Gao, B., Zhuang, Y., Li, R., and Xu, B.: The control of anthropogenic emissions contributed to 80 % of the decrease in PM2.5 concentrations in Beijing from 2013 to 2017, Atmos. Chem. Phys., 19, 13519–13533, https://doi.org/10.5194/acp-19-13519-2019, 2019.
Chen, Z. Y., Zhang, R., Zhang, T. H., Ou, C. Q., and Guo, Y.: A kriging-calibrated machine learning method for estimating daily ground-level NO2 in mainland China, Sci. Total Environ., 690, 556–564, https://doi.org/10.1016/j.scitotenv.2019.06.349, 2019.
Compton, J. E., Harrison, J. A., Dennis, R. L., Greaver, T. L., Hill, B. H., Jordan, S. J., Walker, H., and Campbell, H. V.: Ecosystem services altered by human changes in the nitrogen cycle: a new perspective for US decision making, Ecol. Lett., 14, 804–815, https://doi.org/10.1111/j.1461-0248.2011.01631.x, 2011.
Cui, S., Shi, Y., Malik, A., Lenzen, M., Gao, B., and Huang, W.: A hybrid method for quantifying China's nitrogen footprint during urbanisation from 1990 to 2009, Environ. Int., 97, 137–145, https://doi.org/10.1016/j.envint.2016.08.012, 2016.
Du, E., de Vries, W., Galloway, J. N., Hu, X., and Fang, J.: Changes in wet nitrogen deposition in the United States between 1985 and 2012, Environ. Res. Lett., 9, 095004, https://doi.org/10.1088/1748-9326/9/9/095004, 2014.
Duncan, B. N., Lamsal, L. N., Thompson, A. M., Yoshida, Y., Lu, Z., Streets, D. G., Hurwitz, M. M., and Pickering, K. E.: A space-based, high-resolution view of notable changes in urban NOx pollution around the world (2005–2014), J. Geophy. Res., 121, 976–996, https://doi.org/10.1002/2015JD024121, 2016.
Erisman, J. W., Galloway, J. N., Seitzinger, S., Bleeker, A., Dise, N. B., Petrescu, A. R., Leach, A. M., and de Vries, W.: Consequences of human modification of the global nitrogen cycle, Philos. T. R. Soc. B, 368, 20130116, https://doi.org/10.1098/rstb.2013.0116, 2013.
Fu, H. and Chen, J.: Formation, features and controlling strategies of severe haze-fog pollutions in China, Sci. Total Environ., 578, 121–138, https://doi.org/10.1016/j.scitotenv.2016.10.201, 2017.
Fu, X., Wang, S., Xing, J., Zhang, X., Wang, T., and Hao, J.: Increasing ammonia concentrations reduce the effectiveness of particle pollution control achieved via SO2 and NOX emissions reduction in east China, Environ. Sci. Tech. Lett., 4, 221–227, https://doi.org/10.1021/acs.estlett.7b00143, 2017.
Geng, G. N., Murray, N. L., Chang, H. H., and Liu, Y.: The sensitivity of satellite-based PM2.5 estimates to its inputs: Implications to model development in data-poor regions, Environ. Interna., 121, 550–560, 2018.
Geng, G. N., Xiao, Q. Y., Zheng, Y. X., Tong, D., Zhang, Y. X., Zhang, X. Y., Zhang, Q., He, K. B., and Liu, Y.: Impact of China's Air Pollution Prevention and Control Action Plan on PM2.5 chemical composition over eastern China, Atmos. Chem. Phys. Sci. China Earth Sci., 62, 1–13, 2019.
Granier, C., Granier, L., Sindelarova, K., Liousse, C., Darras, S., Bouarar, I., van der Gon, H. D., Frost, G. J., Janssens-Maenhout, G., and Crippa, M.: Trends in anthropogenic emissions from 1960 to 2015, HAL Archives, International Emission Inventory Conference “Applying Science and Streamlining Processes to Improve Inventories”, August 2017, Baltimore, United States, hal-02144893, 2017.
Guo, J., Su, T., Chen, D., Wang, J., Li, Z., Lv, Y., Guo, X., Liu, H., Cribb, M., and Zhai, P.: Declining Summertime Local-Scale Precipitation Frequency Over China and the United States, 1981–2012. The Disparate Roles of Aerosols, Geophys. Res. Lett., 46, 13281–13289, https://doi.org/10.1029/2019GL085442, 2019.
Han, X., Zhang, M., Skorokhod, A., and Kou, X.: Modeling dry deposition of reactive nitrogen in China with RAMS-CMAQ, Atmos. Environ., 166, 47–61, https://doi.org/10.1016/j.atmosenv.2017.07.015, 2017.
Hu, M., Zhang, J., and Wu, Z.: Chemical compositions of precipitation and scavenging of particles in Beijing, Sci. China Ser. B, 48, 265–272, 2005.
Huang, Z., Wang, S., Zheng, J., Yuan, Z., Ye, S., and Kang, D.: Modeling inorganic nitrogen deposition in Guangdong province, China, Atmos. Environ., 109, 147–160, https://doi.org/10.1016/j.atmosenv.2015.03.014, 2015.
Itahashi, S., Uno, I., Osada, K., Kamiguchi, Y., Yamamoto, S., Tamura, K., Wang, Z., Kurosaki, Y., and Kanaya, Y.: Nitrate transboundary heavy pollution over East Asia in winter, Atmos. Chem. Phys., 17, 3823–3843, https://doi.org/10.5194/acp-17-3823-2017, 2017.
Jia, Y., Yu, G., Gao, Y., He, N., Wang, Q., Jiao, C., and Zuo, Y.: Global inorganic nitrogen dry deposition inferred from ground-and space-based measurements, Sci. Rep., 6, 19810, https://doi.org/10.1038/srep19810, 2016.
Kanada, M., Dong, L., Fujita, T., Fujii, M., Inoue, T., Hirano, Y., Togawa, T., and Geng, Y.: Regional disparity and cost-effective SO2 pollution control in China: A case study in 5 mega-cities, Energ. Policy, 61, 1322–1331, https://doi.org/10.1016/j.enpol.2013.05.105, 2013.
Kendall, M. G.: Rank Correlation methods[M], Charles Griffin, London, 1975.
Kong, L., Hu, M., Tan, Q., Feng, M., Qu, Y., An, J., Zhang, Y., Liu, X., and Cheng, N.: Aerosol optical properties under different pollution levels in the Pearl River Delta (PRD) region of China, J. Environ. Sci., 87, 49–59, https://doi.org/10.1016/j.jes.2019.02.019, 2020.
Kong, L., Tang, X., Zhu, J., Wang, Z., Li, J., Wu, H., Wu, Q., Chen, H., Zhu, L., Wang, W., Liu, B., Wang, Q., Chen, D., Pan, Y., Song, T., Li, F., Zheng, H., Jia, G., Lu, M., Wu, L., and Carmichael, G. R.: A 6-year-long (2013–2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC, Earth Syst. Sci. Data, 13, 529–570, https://doi.org/10.5194/essd-13-529-2021, 2021.
Li, R., Cui, L., Li, J., Zhao, A., Fu, H., Wu, Y., Zhang, L., Kong, L., and Chen, J.: Spatial and temporal variation of particulate matter and gaseous pollutants in China during 2014–2016, Atmos. Environ., 161, 235–246, https://doi.org/10.1016/j.atmosenv.2017.05.008, 2017.
Li, R., Wang, Z., Cui, L., Fu, H., Zhang, L., Kong, L., Chen, W., and Chen, J.: Air pollution characteristics in China during 2015–2016: Spatiotemporal variations and key meteorological factors, Sci. Total Environ., 648, 902–915, https://doi.org/10.1016/j.scitotenv.2018.08.181, 2019.
Li, R., Cui, L., Hongbo, F., Li, J., Zhao, Y., and Chen, J.: Satellite-based estimation of full-coverage ozone (O3) concentration and health effect assessment across Hainan Island, J. Clean. Prod., 244, 118773, https://doi.org/10.1016/j.jclepro.2019.118773, 2020a.
Li, R., Cui, L., Liang, J., Zhao, Y., Zhang, Z., and Fu, H.: Estimating historical SO2 level across the whole China during 1973–2014 using random forest model, Chemosphere, 125839, https://doi.org/10.1016/j.chemosphere.2020.125839, 2020b.
Li, R., Cui, L. L., Zhao, Y. L., Zhou, W. H., and Fu, H. B.: Long-term trends of ambient nitrate (
Liu, L., Zhang, X., Xu, W., Liu, X., Li, Y., Lu, X., Zhang, Y., and Zhang, W.: Temporal characteristics of atmospheric ammonia and nitrogen dioxide over China based on emission data, satellite observations and atmospheric transport modeling since 1980, Atmos. Chem. Phys., 17, 9365–9378, https://doi.org/10.5194/acp-17-9365-2017, 2017.
Liu, X., Duan, L., Mo, J., Du, E., Shen, J., Lu, X., Zhang, Y., Zhou, X., He, C., and Zhang, F.: Nitrogen deposition and its ecological impact in China: an overview, Environ. Pollut., 159, 2251–2264, https://doi.org/10.1016/j.envpol.2010.08.002, 2011.
Liu, X., Xu, W., Duan, L., Du, E., Pan, Y., Lu, X., Zhang, L., Wu, Z., Wang, X., and Zhang, Y.: Atmospheric nitrogen emission, deposition, and air quality impacts in China: An overview, Current Pollution Reports, 3, 65–77, 2017.
Liu, Z., Gao, W., Yu, Y., Hu, B., Xin, J., Sun, Y., Wang, L., Wang, G., Bi, X., Zhang, G., Xu, H., Cong, Z., He, J., Xu, J., and Wang, Y.: Characteristics of PM2.5 mass concentrations and chemical species in urban and background areas of China: emerging results from the CARE-China network, Atmos. Chem. Phys., 18, 8849–8871, https://doi.org/10.5194/acp-18-8849-2018, 2018.
Lu, Z., Streets, D. G., de Foy, B., and Krotkov, N. A.: Ozone Monitoring Instrument observations of interannual increases in SO2 emissions from Indian coal-fired power plants during 2005–2012, Environ. Sci. Tech., 47, 13993–14000, https://doi.org/10.1021/es4039648, 2013.
Ma, Z., Liu, R., Liu, Y., and Bi, J.: Effects of air pollution control policies on PM2.5 pollution improvement in China from 2005 to 2017: a satellite-based perspective, Atmos. Chem. Phys., 19, 6861–6877, https://doi.org/10.5194/acp-19-6861-2019, 2019.
Mann, H. B.: Nonparametric tests against trend Econometrica, J. Econom. Soc., 13, 245–259, 1945.
Ming, L., Jin, L., Li, J., Fu, P., Yang, W., Liu, D., Zhang, G., Wang, Z., and Li, X.: PM2.5 in the Yangtze River Delta, China: Chemical compositions, seasonal variations, and regional pollution events, Environ. Pollut., 223, 200–212, https://doi.org/10.1016/j.envpol.2017.01.013, 2017.
Qi, J., Liu, X., Yao, X., Zhang, R., Chen, X., Lin, X., Gao, H., and Liu, R.: The concentration, source and deposition flux of ammonium and nitrate in atmospheric particles during dust events at a coastal site in northern China, Atmos. Chem. Phys., 18, 571–586, https://doi.org/10.5194/acp-18-571-2018, 2018.
Qiao, X., Xiao, W., Jaffe, D., Kota, S. H., Ying, Q., and Tang, Y.: Atmospheric wet deposition of sulfur and nitrogen in Jiuzhaigou national nature reserve, Sichuan province, China, Sci. Total Environ., 511, 28–36, https://doi.org/10.1016/j.scitotenv.2014.12.028, 2015.
Qin, K., Zou, J., Guo, J., Lu, M., Bilal, M., Zhang, K., Ma, F., and Zhang, Y.: Estimating PM1 concentrations from MODIS over Yangtze River Delta of China during 2014–2017, Atmos. Environ., 195, 149–158, https://doi.org/10.1016/j.atmosenv.2018.09.054, 2018.
Quan, J., Tie, X., Zhang, Q., Liu, Q., Li, X., Gao, Y., and Zhao, D.: Characteristics of heavy aerosol pollution during the 2012–2013 winter in Beijing, China, Atmos. Environ., 88, 83–89, https://doi.org/10.1016/j.atmosenv.2014.01.058, 2014.
Schreifels, J. J., Fu, Y., and Wilson, E. J.: Sulfur dioxide control in China: policy evolution during the 10th and 11th Five-year Plans and lessons for the future, Energ. Policy, 48, 779–789, https://doi.org/10.1016/j.enpol.2012.06.015, 2012.
Shen, J., Tang, A., Liu, X., Fangmeier, A., Goulding, K., and Zhang, F.: High concentrations and dry deposition of reactive nitrogen species at two sites in the North China Plain, Environ. Pollut., 157, 3106–3113, https://doi.org/10.1016/j.envpol.2009.05.016, 2009.
Shen, J., Li, Y., Liu, X., Luo, X., Tang, H., Zhang, Y., and Wu, J.: Atmospheric dry and wet nitrogen deposition on three contrasting land use types of an agricultural catchment in subtropical central China, Atmos. Environ., 67, 415–424, https://doi.org/10.1016/j.atmosenv.2012.10.068, 2013.
Singh, S., Sharma, A., Kumar, B., and Kulshrestha, U.: Wet deposition fluxes of atmospheric inorganic reactive nitrogen at an urban and rural site in the Indo-Gangetic Plain, Atmos. Pollut. Res., 8, 669–677, https://doi.org/10.1016/j.apr.2016.12.021, 2017.
Tang, Q. H., Lan, C., Su, F. G., Liu, X. C., Sun, H., Ding, J., Wang, L., Leng, G. Y., Zhang, Y. Q., Sang, Y. F., Fang, H. Y., Zhang, S. F., Han, D. M., Liu, X. M., He, L., Xu, X. M., Tang, Y., and Chen, D. L.: Streamflow change on the Qinghai-Tibet Plateau and its impacts, Sci. Bull., 64, 2807–2821, 2019.
Tian, M., Wang, H., Chen, Y., Zhang, L., Shi, G., Liu, Y., Yu, J., Zhai, C., Wang, J., and Yang, F.: Highly time-resolved characterization of water-soluble inorganic ions in PM2.5 in a humid and acidic mega city in Sichuan Basin, China, Sci. Total Environ., 580, 224–234, https://doi.org/10.1016/j.scitotenv.2016.12.048, 2017.
Vasilakos, P., Russell, A., Weber, R., and Nenes, A.: Understanding nitrate formation in a world with less sulfate, Atmos. Chem. Phys., 18, 12765–12775, https://doi.org/10.5194/acp-18-12765-2018, 2018.
Vrekoussis, M., Richter, A., Hilboll, A., Burrows, J., Gerasopoulos, E., Lelieveld, J., Barrie, L., Zerefos, C., and Mihalopoulos, N.: Economic crisis detected from space: Air quality observations over Athens/Greece, Geophy. Res. Lett., 40, 458–463, https://doi.org/10.1002/grl.50118, 2013.
Wang, H., Shi, G., Tian, M., Zhang, L., Chen, Y., Yang, F., and Cao, X.: Aerosol optical properties and chemical composition apportionment in Sichuan Basin, China, Sci. Total Environ., 577, 245–257, https://doi.org/10.1016/j.scitotenv.2016.10.173, 2017.
Wang, Q., Zhuang, G., Huang, K., Liu, T., Lin, Y., Deng, C., Fu, Q., Fu, J. S., Chen, J., and Zhang, W.: Evolution of particulate sulfate and nitrate along the Asian dust pathway: Secondary transformation and primary pollutants via long-range transport, Atmos. Res., 169, 86–95, https://doi.org/10.1016/j.atmosres.2015.09.013, 2016.
Wang, W., Xu, W., Wen, Z., Wang, D., Wang, S., Zhang, Z., Zhao, Y., and Liu, X.: Characteristics of Atmospheric Reactive Nitrogen Deposition in Nyingchi City, Sci. Rep., 9, 1–11, https://doi.org/10.1038/s41598-019-39855-2, 2019.
Wang, Y., Li, W., Gao, W., Liu, Z., Tian, S., Shen, R., Ji, D., Wang, S., Wang, L., and Tang, G.: Trends in particulate matter and its chemical compositions in China from 2013–2017, Sci. China Earth Sci., 62, 1857–1871, https://doi.org/10.1007/s11430-018-9373-1, 2019a.
Wang, Y., Li, W., Gao, W., Liu, Z., Tian, S., Shen, R., Ji, D., Wang, S., Wang, L., and Tang, G.: Trends in particulate matter and its chemical compositions in China from 2013–2017, Sci. China Earth Sci., 62, 1–15, https://doi.org/10.1007/s11430-018-9373-1, 2019b.
Wang, Y. L., Song, W., Yang, W., Sun, X. C., Tong, Y. D., Wang, X. M., Liu, C. Q., Bai, Z. P., and Liu, X. Y.: Influences of atmospheric pollution on the contributions of major oxidation pathways to PM2.5 nitrate formation in Beijing, J. Geophy. Res., 124, 4174–4185, https://doi.org/10.1029/2019JD030284, 2019.
Wei, J., Huang, W., Li, Z., Xue, W., Peng, Y., Sun, L., and Cribb, M.: Estimating 1-km-resolution PM2.5 concentrations across China using the space-time random forest approach, Remote Sens. Environ., 231, 111221, https://doi.org/10.1016/j.rse.2019.111221, 2019.
Wolpert, D. H.: Stacked generalization, Neural Networks, 5, 241–259, https://doi.org/10.1016/S0893-6080(05)80023-1, 1992.
Xiao, Q., Chang, H., Geng, G., and Liu, Y.: An ensemble machine-learning model to predict historical PM2.5 concentrations in China from satellite data, Environ. Sci. Tech., 52, 13260–13269, https://doi.org/10.1021/acs.est.8b02917, 2018.
Xie, Y., Wang, G., Wang, X., Chen, J., Chen, Y., Tang, G., Wang, L., Ge, S., Xue, G., Wang, Y., and Gao, J.: Nitrate-dominated PM2.5 and elevation of particle pH observed in urban Beijing during the winter of 2017, Atmos. Chem. Phys., 20, 5019–5033, https://doi.org/10.5194/acp-20-5019-2020, 2020.
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, 2018a.
Xu, W., Zhao, Y., Liu, X., Dore, A. J., Zhang, L., Liu, L., and Cheng, M.: Atmospheric nitrogen deposition in the Yangtze River basin: Spatial pattern and source attribution, Environ. Pollut., 232, 546–555, https://doi.org/10.1016/j.envpol.2017.09.086, 2018b.
Xu, W., Zhang, L., and Liu, X. J.: a database of atmospheric nitrogen concentration and deposition from the nationwide monitoring network in China, Sci. Data, 6, 51, https://doi.org/10.1038/s41597-019-0061-2, 2019.
Xue, T., Zheng, Y. X., Tong, D., Zheng, B., Li, X., Zhu, T., and Zhang, Q.: Spatiotemporal continuous estimates of PM2.5 concentrations in China, 2000–2016: A machine learning method with inputs from satellites, chemical transport model, and ground observations, Environ. Int., 123, 345–357, https://doi.org/10.1016/j.envint.2018.11.075, 2019.
Yang, J., Kang, S., and Ji, Z.: Sensitivity analysis of chemical mechanisms in the WRF-chem model in reconstructing aerosol concentrations and optical properties in the Tibetan plateau, Aerosol Air Qual. Res., 18, 505–521, https://doi.org/10.4209/aaqr.2017.05.0156, 2018.
Zang, L., Mao, F., Guo, J., Wang, W., Pan, Z., Shen, H., Zhu, B., and Wang, Z.: Estimation of spatiotemporal PM1.0 distributions in China by combining PM2.5 observations with satellite aerosol optical depth, Sci. Total Environ., 658, 1256–1264, https://doi.org/10.1016/j.scitotenv.2018.12.297, 2019.
Zhai, B. X. and Chen, J. G.: Development of a stacked ensemble model for forecasting and analyzing daily average PM2.5 concentrations in Beijing, China, Sci. Total Environ., 635, 644–658, https://doi.org/10.1016/j.scitotenv.2018.04.040, 2018.
Zhan, Y., Luo, Y., Deng, X., Chen, H., Grieneisen, M. L., Shen, X., Zhu, L., and Zhang, M.: Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm, Atmos. Environ., 155, 129–139, https://doi.org/10.1016/j.atmosenv.2017.02.023, 2017.
Zhan, Y., Luo, Y., Deng, X., Grieneisen, M. L., Zhang, M., and Di, B.: Spatiotemporal prediction of daily ambient ozone levels across China using random forest for human exposure assessment, Environ. Pollut., 233, 464–473, https://doi.org/10.1016/j.envpol.2017.10.029, 2018a.
Zhan, Y., Luo, Y., Deng, X., Zhang, K., Zhang, M., Grieneisen, M. L., and Di, B.: Satellite-Based estimates of daily NO2 exposure in China using hybrid random forest and spatiotemporal Kriging model, Environ. Sci. Tech., 52, 4180–4189, https://doi.org/10.1021/acs.est.7b05669, 2018b.
Zhang, X. Y., Zhang, W. T., Lu, X. H., Liu, X. J., Chen, D. M., Liu, L., and Huang, X. J.: Long-term trends in NO2 columns related to economic developments and air quality policies from 1997 to 2016 in China, Sci. Total Environ., 639, 146–155, https://doi.org/10.1016/j.scitotenv.2018.04.435, 2018.
Zhao, Y., Zhang, L., Chen, Y., Liu, X., Xu, W., Pan, Y., and Duan, L.: Atmospheric nitrogen deposition to China: A model analysis on nitrogen budget and critical load exceedance, Atmos. Environ., 153, 32–40, https://doi.org/10.1016/j.atmosenv.2017.01.018, 2017.
Zhou, K., Yang, S., Shen, C., Ding, S., and Sun, C.: Energy conservation and emission reduction of China's electric power industry, Renew. Sust. Energ. Rev., 45, 10–19, https://doi.org/10.1016/j.rser.2015.01.056, 2015.
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...
Altmetrics
Final-revised paper
Preprint