OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Global spatiotemporal estimation of daily high-resolution surface carbon monoxide concentrations using Deep Forest
Yuan Wang, Qiangqiang Yuan, Tongwen Li, et al.
Journal of Cleaner Production (2022) Vol. 350, pp. 131500-131500
Closed Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution
Yi Xiao, Qiangqiang Yuan, Kui Jiang, et al.
Information Fusion (2023) Vol. 96, pp. 297-311
Closed Access | Times Cited: 150

Spectral super-resolution meets deep learning: Achievements and challenges
Jiang He, Qiangqiang Yuan, Jie Li, et al.
Information Fusion (2023) Vol. 97, pp. 101812-101812
Open Access | Times Cited: 43

Substantially underestimated global health risks of current ozone pollution
Yuan Wang, Yuanjian Yang, Qiangqiang Yuan, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 3

Study on the spatiotemporal dynamic of ground-level ozone concentrations on multiple scales across China during the blue sky protection campaign
Bin Guo, Haojie Wu, Lin Pei, et al.
Environment International (2022) Vol. 170, pp. 107606-107606
Open Access | Times Cited: 49

Air quality indicators and AQI prediction coupling long-short term memory (LSTM) and sparrow search algorithm (SSA): A case study of Shanghai
Xingpo Liu, Hongyuan Guo
Atmospheric Pollution Research (2022) Vol. 13, Iss. 10, pp. 101551-101551
Closed Access | Times Cited: 41

Modeling air quality PM2.5 forecasting using deep sparse attention-based transformer networks
Zhen-Yu Zhang, Shiqing Zhang
International Journal of Environmental Science and Technology (2023) Vol. 20, Iss. 12, pp. 13535-13550
Open Access | Times Cited: 27

Generating a long-term (2003−2020) hourly 0.25° global PM2.5 dataset via spatiotemporal downscaling of CAMS with deep learning (DeepCAMS)
Yi Xiao, Yuan Wang, Qiangqiang Yuan, et al.
The Science of The Total Environment (2022) Vol. 848, pp. 157747-157747
Closed Access | Times Cited: 25

Global spatiotemporal completion of daily high-resolution TCCO from TROPOMI over land using a swath-based local ensemble learning method
Yuan Wang, Qiangqiang Yuan, Siqin Zhou, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 194, pp. 167-180
Open Access | Times Cited: 25

A new perspective to satellite-based retrieval of ground-level air pollution: Simultaneous estimation of multiple pollutants based on physics-informed multi-task learning
Qianqian Yang, Qiangqiang Yuan, Meng Gao, et al.
The Science of The Total Environment (2022) Vol. 857, pp. 159542-159542
Closed Access | Times Cited: 21

A synchronized estimation of hourly surface concentrations of six criteria air pollutants with GEMS data
Qianqian Yang, Jhoon Kim, Yeseul Cho, et al.
npj Climate and Atmospheric Science (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 13

Systematic Review of Machine Learning and Deep Learning Techniques for Spatiotemporal Air Quality Prediction
Israel Edem Agbehadji, Ibidun Christiana Obagbuwa
Atmosphere (2024) Vol. 15, Iss. 11, pp. 1352-1352
Open Access | Times Cited: 4

Transport into the polar stratosphere from the Asian monsoon region
Xiaolu Yan, Paul Konopka, Felix Ploeger, et al.
Atmospheric chemistry and physics (2025) Vol. 25, Iss. 2, pp. 1289-1305
Open Access

Spatial-and-local-aware deep learning approach for Ground-Level NO2 estimation in England with multisource data from satellite-based observations and chemical transport models
Siying Wang, Shuangyin Zhang, Dawei Wang, et al.
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 139, pp. 104506-104506
Closed Access

Estimating monthly surface ozone using multi-source satellite products in China based on Deep Forest model
Xueyao Chen, Zhige Wang, Yulin Shangguan, et al.
Atmospheric Environment (2023) Vol. 307, pp. 119819-119819
Closed Access | Times Cited: 10

From Ensemble Learning to Deep Ensemble Learning: A case study on multi-indicator prediction of pavement performance
Yi‐Ying Wu
Applied Soft Computing (2024) Vol. 166, pp. 112188-112188
Closed Access | Times Cited: 3

Exploring high-resolution near-surface CO concentrations based on Himawari-8 top-of-atmosphere radiation data: Assessing the distribution of city-level CO hotspots in China
Бин Чэн, Jiashun Hu, Zhihao Song, et al.
Atmospheric Environment (2023) Vol. 312, pp. 120021-120021
Closed Access | Times Cited: 7

Machine learning for sustainable development: leveraging technology for a greener future
Muneza Kagzi, Sayantan Khanra, Sanjoy Kumar Paul
Journal of Systems and Information Technology (2023) Vol. 25, Iss. 4, pp. 440-479
Closed Access | Times Cited: 7

Transport into the polar stratosphere from the Asian monsoon region
Xiaolu Yan, Paul Konopka, Felix Ploeger, et al.
(2024)
Open Access | Times Cited: 1

High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model
Mingyun Hu, Xingcheng Lu, Yiang Chen, et al.
Journal of Environmental Management (2024) Vol. 371, pp. 123096-123096
Closed Access | Times Cited: 1

Comment on egusphere-2024-782
Xiaolu Yan, Paul Konopka, Felix Ploeger, et al.
(2024)
Open Access

Comment on egusphere-2024-782
Xiaolu Yan, Paul Konopka, Felix Ploeger, et al.
(2024)
Open Access

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