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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:

Predicting ozone formation in petrochemical industrialized Lanzhou city by interpretable ensemble machine learning
Li Wang, Yuan Zhao, Jinsen Shi, et al.
Environmental Pollution (2022) Vol. 318, pp. 120798-120798
Closed Access | Times Cited: 21

Showing 21 citing articles:

Explainable ensemble machine learning revealing the effect of meteorology and sources on ozone formation in megacity Hangzhou, China
Lei Zhang, Lili Wang, Dan Ji, et al.
The Science of The Total Environment (2024) Vol. 922, pp. 171295-171295
Closed Access | Times Cited: 15
A Novel Approach Combining Indoor Mobile Measurements and Interpretable Machine Learning to Unveil Highly-Resolved Indoor Air Pollution
Zhiyuan Tang, Yuan Zhao, Li Wang, et al.
Building and Environment (2025) Vol. 270, pp. 112552-112552
Closed Access | Times Cited: 1
Spatiotemporal Air Pollution Forecasting in Houston-TX: A Case Study for Ozone Using Deep Graph Neural Networks
Victor Oliveira Santos, Paulo Alexandre Costa Rocha, John Scott, et al.
Atmosphere (2023) Vol. 14, Iss. 2, pp. 308-308
Open Access | Times Cited: 31
Supervised Machine Learning Approaches for Predicting Key Pollutants and for the Sustainable Enhancement of Urban Air Quality: A Systematic Review
Ismail Essamlali, Hasna Nhaila, Mohamed El Khaïli
Sustainability (2024) Vol. 16, Iss. 3, pp. 976-976
Open Access | Times Cited: 10
Enhancement of atmospheric oxidation capacity induced co-pollution of the O3 and PM2.5 in Lanzhou, northwest China
Li Wang, Yuan Zhao, Xiaoyue Liu, et al.
Environmental Pollution (2023) Vol. 341, pp. 122951-122951
Closed Access | Times Cited: 15
PM2.5 pollution modulates the response of ozone formation to VOC emitted from various sources: Insights from machine learning
Chenliang Tao, Qingzhu Zhang, Sisi Huo, et al.
The Science of The Total Environment (2024) Vol. 916, pp. 170009-170009
Closed Access | Times Cited: 5
Identification of driving factors for heavy metals and polycyclic aromatic hydrocarbons pollution in agricultural soils using interpretable machine learning
Jun Wang, Yirong Deng, Zaoquan Huang, et al.
The Science of The Total Environment (2025) Vol. 960, pp. 178384-178384
Closed Access
Ozone Formation in a Representative Urban Environment: Model Discrepancies and Critical Roles of Oxygenated Volatile Organic Compounds
Xiangpeng Huang, Wei Zheng, Yanchen Li, et al.
Environmental Science & Technology Letters (2025)
Closed Access
Optimizing the Architecture of a Quantum–Classical Hybrid Machine Learning Model for Forecasting Ozone Concentrations: Air Quality Management Tool for Houston, Texas
Victor Oliveira Santos, Paulo Alexandre Costa Rocha, Jesse Thé, et al.
Atmosphere (2025) Vol. 16, Iss. 3, pp. 255-255
Open Access
Machine learning for predicting urban greenhouse gas emissions: A systematic literature review
Yukai Jin, Ayyoob Sharifi
Renewable and Sustainable Energy Reviews (2025) Vol. 215, pp. 115625-115625
Open Access
Development of a multi-module data-driven integrated framework for identifying drivers of atmospheric particulate nitrate and reduction emissions: An application in an industrial city, China
Jiaqi Dong, Yulong Yan, Lin Peng, et al.
Environment International (2025), pp. 109394-109394
Open Access
Exploring the primary magnetic parameters affecting chemical fractions of heavy metal(loid)s in lake sediment through an interpretable workflow
Ligang Deng, Yifan Fan, Kai Liu, et al.
Journal of Hazardous Materials (2024) Vol. 468, pp. 133859-133859
Closed Access | Times Cited: 3
Exploring spatiotemporal patterns of algal cell density in lake Dianchi with explainable machine learning
Yiwen Tao, Jingli Ren, Huaiping Zhu, et al.
Environmental Pollution (2024) Vol. 356, pp. 124395-124395
Closed Access | Times Cited: 3
Observation-Based Ozone Formation Rules by Gradient Boosting Decision Trees Model in Typical Chemical Industrial Parks
Nana Cheng, Deji Jing, Zhenyu Gu, et al.
Atmosphere (2024) Vol. 15, Iss. 5, pp. 600-600
Open Access | Times Cited: 2
Fracture toughness prediction using well logs and Extreme gradient Boosting based on particle swarm optimization in shale gas reservoir
Mbula Ngoy Nadege, Biao Shu, Allou Koffi Franck Kouassi, et al.
Engineering Fracture Mechanics (2024) Vol. 315, pp. 110759-110759
Closed Access | Times Cited: 2
Revealing the Covariation of Atmospheric O2 and Pollutants in an Industrial Metropolis by Explainable Machine Learning
Xiaoyue Liu, Li Wang, Jianping Huang, et al.
Environmental Science & Technology Letters (2023) Vol. 10, Iss. 10, pp. 851-858
Closed Access | Times Cited: 5
Unraveling the Influence of Satellite-Observed Land Surface Temperature on High-Resolution Mapping of Ground-Level Ozone Using Interpretable Machine Learning
Qingqing He, Jingru Cao, Pablo E. Saide, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 36, pp. 15938-15948
Closed Access | Times Cited: 1
Predicting plateau atmospheric ozone concentrations by a machine learning approach: A case study of a typical city on the southwestern plateau of China
Qiyao Wang, Huaying Liu, Yingjie Li, et al.
Environmental Pollution (2024) Vol. 363, pp. 125071-125071
Closed Access | Times Cited: 1
Data imbalance causes underestimation of high ozone pollution in machine learning models: a weighted support vector regression solution
Ling Zhen, Baihua Chen, Lin Wang, et al.
Atmospheric Environment (2024), pp. 120952-120952
Closed Access | Times Cited: 1
Machine Learning Integrated PMF Model Reveals Influencing Factors of Ozone Pollution in a Coal Chemical Industry City at the Jiangsu-Shandong-Henan-Anhui Boundary
Chaolong Wang, Xiaofei Qin, Yisheng Zhang, et al.
Atmospheric Environment (2024) Vol. 342, pp. 120916-120916
Closed Access | Times Cited: 1
Accurate and efficient prediction of atmospheric PM1, PM2.5, PM10, and O3 concentrations using a customized software package based on a machine-learning algorithm
Le Xie, Jiawei He, R. T. Lei, et al.
Chemosphere (2024) Vol. 368, pp. 143752-143752
Closed Access
Refining the Understanding of Ozone Formation Response Regulations Through Ensemble Machine Learning Analysis in Highly Polluted Areas
Qiaoli Wang, Shengdong Yao, Chengzhi Wu, et al.
(2023)
Closed Access
Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal
Xiaoju Li, Luqman Chuah Abdullah, Shafreeza Sobri, et al.
Environmental Engineering Research (2023) Vol. 29, Iss. 4, pp. 230475
Open Access
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