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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:

Estimating the geographical patterns and health risks associated with PM2.5-bound heavy metals to guide PM2.5 control targets in China based on machine-learning algorithms
Tong Lyu, Yilin Tang, Hongbin Cao, et al.
Environmental Pollution (2023) Vol. 337, pp. 122558-122558
Closed Access | Times Cited: 11

Showing 11 citing articles:

A significant reduction in the coal contribution to PM2.5 and exposed health risks due to the energy structure transition
Dongmei Hu, Mingyang Yuan, Yulong Yan, et al.
Atmospheric Pollution Research (2025), pp. 102457-102457
Closed Access | Times Cited: 1
Control priority based on source-specific DALYs of PM2.5-bound heavy metals by PMF-PSCF-IsoSource model in urban and suburban Beijing
Yue Gao, Tong Lyu, Weidong Zhang, et al.
Journal of Environmental Management (2024) Vol. 352, pp. 120016-120016
Closed Access | Times Cited: 8
Nasal filter reveal exposure risks of inhalable particulates and heavy metals in urban women
Wei Guo, Xinyou Zhang, Junhui Yue, et al.
Environment International (2024) Vol. 188, pp. 108743-108743
Open Access | Times Cited: 4
Assessment of the gridded burden of disease caused by PM2.5-bound heavy metals in Beijing based on machine learning algorithm and DALYs
Tong Lyu, Xin Meng, Yilin Tang, et al.
The Science of The Total Environment (2025) Vol. 968, pp. 178788-178788
Closed Access
Atmospheric Heavy Metal Pollution Characteristics and Health Risk Assessment Across Various Type of Cities in China
Zhichun Cha, Xi Zhang, Kai Zhang, et al.
Toxics (2025) Vol. 13, Iss. 3, pp. 220-220
Open Access
A city-level dataset of heavy metal emissions into the atmosphere across China from 2015–2020
Qi Dong, Yue Li, Xinhua Wei, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 3
Recommendations for the reference concentration of cadmium exposure based on a physiologically based toxicokinetic model integrated with a human respiratory tract model
Yilin Tang, Tong Lyu, Hongbin Cao, et al.
Journal of Hazardous Materials (2024) Vol. 477, pp. 135323-135323
Closed Access | Times Cited: 3
Quantifying the pollution changes and meteorological dependence of airborne trace elements coupling source apportionment and machine learning
Haolin Wang, Xu Guan, Jiao Li, et al.
The Science of The Total Environment (2024) Vol. 948, pp. 174452-174452
Closed Access | Times Cited: 2
Advancing water quality prediction through integrating machine learning with data augmentation: A case study for First Nations communities in British Columbia
Anqi Chen
(2024)
Open Access
A comprehensive evaluation of the atmospheric impacts and health risks of cooking fumes from different cuisines
Junfeng Zhang, Wenjiao Duan, Shuiyuan Cheng, et al.
Atmospheric Environment (2024), pp. 120837-120837
Closed Access
Significant spatiotemporal changes in atmospheric particulate mercury pollution in China: Insights from meta-analysis and machine-learning
Haolin Wang, Tianshuai Li, Guoqiang Wang, et al.
The Science of The Total Environment (2024) Vol. 955, pp. 177184-177184
Closed Access
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