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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:

Estimation of high-resolution PM2.5 concentrations based on gap-filling aerosol optical depth using gradient boosting model
Min Han, Shuqin Jia, Chengkun Zhang
Air Quality Atmosphere & Health (2022) Vol. 15, Iss. 4, pp. 619-631
Closed Access | Times Cited: 10

Showing 10 citing articles:

A novel deep learning model integrating CNN and GRU to predict particulate matter concentrations
Zhuoyue Guo, Canyun Yang, Dongsheng Wang, et al.
Process Safety and Environmental Protection (2023) Vol. 173, pp. 604-613
Closed Access | Times Cited: 74
Addressing Biases in Ambient PM2.5 Exposure and Associated Health Burden Estimates by Filling Satellite AOD Retrieval Gaps over India
Varun Katoch, Alok Kumar, Fahad Imam, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 48, pp. 19190-19201
Closed Access | Times Cited: 17
Sectoral Contributions to Primary and Secondary PM2.5 in Regional Airsheds of India
Alok Kumar, Fahad Imam, Kuldeep Dixit, et al.
ACS Earth and Space Chemistry (2025)
Closed Access
State-of-art in modelling particulate matter (PM) concentration: a scoping review of aims and methods
Lorenzo Gianquintieri, Daniele Oxoli, Enrico G. Caiani, et al.
Environment Development and Sustainability (2024)
Open Access | Times Cited: 3
Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations
Jiaxin Yuan, Xuhong Wang, Zihao Feng, et al.
Remote Sensing (2023) Vol. 15, Iss. 18, pp. 4613-4613
Open Access | Times Cited: 8
A spatiotemporal XGBoost model for PM2.5 concentration prediction and its application in Shanghai
Zidong Wang, Xianhua Wu, You Wu
Heliyon (2023) Vol. 9, Iss. 12, pp. e22569-e22569
Open Access | Times Cited: 7
Enhanced PM2.5 estimation across China: An AOD-independent two-stage approach incorporating improved spatiotemporal heterogeneity representations
Q. Chen, Kaiwen Shao, Songlin Zhang
Journal of Environmental Management (2024) Vol. 368, pp. 122107-122107
Open Access | Times Cited: 2
Spatiotemporal retrieval of the aerosol optical thickness using Landsat 8 OLI imagery for Indian urban area
Akshay Chauhan, Namrata Jariwala, Robin A. Christian
Air Quality Atmosphere & Health (2024) Vol. 17, Iss. 7, pp. 1467-1478
Closed Access
Empirical Correlation Weighting (ECW) Spatial Interpolation Method for Satellite Aerosol Optical Depth Products by MODIS AOD over Northern China in 2016
Yang Wang, Xianmei Zhang, Pei Zhou, et al.
Remote Sensing (2023) Vol. 15, Iss. 18, pp. 4462-4462
Open Access | Times Cited: 1
PM2.5 estimation and analysis of BiCNN model considering spatiotemporal characteristics: a case study of the middle reaches of the Yangtze River urban agglomeration
Shuaiwen Wu, Hengkai Li, Yanbing Zhou, et al.
Theoretical and Applied Climatology (2023) Vol. 155, Iss. 4, pp. 2787-2799
Closed Access
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