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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:

Accurate Prediction of Soil Heavy Metal Pollution Using an Improved Machine Learning Method: A Case Study in the Pearl River Delta, China
Wenhao Zhao, Jin Ma, Qiyuan Liu, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 46, pp. 17751-17761
Closed Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Exploring the environmental risks and seasonal variations of potentially toxic elements (PTEs) in fine road dust in resource-based cities based on Monte Carlo simulation, geo-detector and random forest model
Y. Richard Yang, Xinwei Lu, Bo Yu, et al.
Journal of Hazardous Materials (2024) Vol. 473, pp. 134708-134708
Closed Access | Times Cited: 18
Improving prediction of soil heavy metal(loid) concentration by developing a combined Co-kriging and geographically and temporally weighted regression (GTWR) model
Huijuan Wang, Menglu Zhao, Xinmiao Huang, et al.
Journal of Hazardous Materials (2024) Vol. 468, pp. 133745-133745
Closed Access | Times Cited: 14
Major influencing factors identification and probabilistic health risk assessment of soil potentially toxic elements pollution in coal and metal mines across China: A systematic review
Jingjing Yu, Xiaoyang Liu, Bin Yang, et al.
Ecotoxicology and Environmental Safety (2024) Vol. 274, pp. 116231-116231
Open Access | Times Cited: 14
Artificial intelligence in microplastic detection and pollution control
Jin Hui, Fanhao Kong, Xiangyu Li, et al.
Environmental Research (2024) Vol. 262, pp. 119812-119812
Closed Access | Times Cited: 13
Machine learning approaches for monitoring environmental metal pollutants: Recent advances in source apportionment, detection, quantification, and risk assessment.
François Nkinahamira, Anqi Feng, Lijie Zhang, et al.
TrAC Trends in Analytical Chemistry (2024), pp. 117980-117980
Closed Access | Times Cited: 8
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 | Times Cited: 1
Prediction of Zinc, Cadmium, and Arsenic in European Soils Using Multi-End Machine Learning Models
Mohammad Sadegh Barkhordari, Chongchong Qi
Journal of Hazardous Materials (2025) Vol. 490, pp. 137800-137800
Closed Access | Times Cited: 1
Assessing and mitigating health risks of workers exposed to volatile organic compounds in contaminated soils during active pit excavation: Accounting for exposure variability and uncertainty
Jihong Li, Maosheng Zhong, Lin Jiang, et al.
Journal of Cleaner Production (2024) Vol. 469, pp. 143227-143227
Open Access | Times Cited: 6
Perspectives on Advancing Multimodal Learning in Environmental Science and Engineering Studies
Wenjia Liu, Jingwen Chen, Haobo Wang, et al.
Environmental Science & Technology (2024)
Closed Access | Times Cited: 6
Source apportionment and migration characteristics of heavy metal(loid)s in soil and groundwater of contaminated site
Yaobin Zhang, Qiulan Zhang, Wenfang Chen, et al.
Environmental Pollution (2023) Vol. 338, pp. 122584-122584
Closed Access | Times Cited: 16
Bioavailability (BA)-based risk assessment of soil heavy metals in provinces of China through the predictive BA-models
Jiawen Zhang, Xiaonan Wang, Jihong Li, et al.
Journal of Hazardous Materials (2023) Vol. 465, pp. 133327-133327
Closed Access | Times Cited: 14
Machine learning-based prediction of cadmium bioaccumulation capacity and associated analysis of driving factors in tobacco grown in Zunyi City, China
Zilun Gou, Chengshuai Liu, Qi Meng, et al.
Journal of Hazardous Materials (2023) Vol. 463, pp. 132910-132910
Closed Access | Times Cited: 13
Machine Learning in Geosciences: A Review of Complex Environmental Monitoring Applications
Maria Silvia Binetti, Carmine Massarelli, Vito Felice Uricchio
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 2, pp. 1263-1280
Open Access | Times Cited: 5
Improved mapping of heavy metals in agricultural soils using machine learning augmented with spatial regionalization indices
Xudong Ma, Dong‐Xing Guan, ChaoSheng Zhang, et al.
Journal of Hazardous Materials (2024) Vol. 478, pp. 135407-135407
Closed Access | Times Cited: 5
Accurate prediction of spatial distribution of soil potentially toxic elements using machine learning and associated key influencing factors identification: A case study in mining and smelting area in southwestern China
Kai Li, Guanghui Guo, Degang Zhang, et al.
Journal of Hazardous Materials (2024) Vol. 478, pp. 135454-135454
Closed Access | Times Cited: 5
Utilizing machine learning to evaluate heavy metal pollution in the world's largest mangrove forest
Ram Proshad, Md. Abdur Rahim, Mahfuzur Rahman, et al.
The Science of The Total Environment (2024) Vol. 951, pp. 175746-175746
Closed Access | Times Cited: 5
Using machine learning to trace the pollution sources of disinfection by-products precursors compared to receptor models
Yuan Xiao, Shunjun Ma, Shumin Yang, et al.
The Science of The Total Environment (2024) Vol. 914, pp. 169671-169671
Closed Access | Times Cited: 4
Boosted simultaneous removal of chlortetracycline and Cu (II) by Litchi Leaves Biochar: Influence of pH, ionic strength, and background electrolyte ions
Xian Guo Hu, Yifan Qu, Lixian Yao, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 7, pp. 10430-10442
Closed Access | Times Cited: 4
Effects of remediation agents on rice and soil in toxic metal(loid)s contaminated paddy fields: A global meta-analysis
Meng Liu, Ruiqing Xu, Xuedan Cui, et al.
The Science of The Total Environment (2024) Vol. 925, pp. 171656-171656
Closed Access | Times Cited: 4
Predictive Analysis and Risk Assessment of Potentially Toxic Elements in Beijing Gas Station Soils Using Machine Learning and Two-Dimensional Monte Carlo Simulations
Meiying Wang, Zilun Gou, Wenhao Zhao, et al.
Journal of Hazardous Materials (2024) Vol. 477, pp. 135393-135393
Closed Access | Times Cited: 4
Evaluation of fluoride emissions and pollution from an electrolytic aluminum plant located in Yunnan province
Ли Бин, Liping Zhang, Mingqian Cheng, et al.
Journal of Hazardous Materials (2024) Vol. 478, pp. 135500-135500
Closed Access | Times Cited: 4
Predicting and regulating potential zone for heavy metal re-contaminated farmland: Case study in Taiwan
Jieh‐Haur Chen, Mu-Chun Su, Meng-Fen Yeh, et al.
Environmental Development (2025), pp. 101147-101147
Closed Access
A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution
Sheng Miao, Ni Guo, Guangze Kong, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0316940-e0316940
Open Access
Predicting the Zinc Content in Rice from Farmland Using Machine Learning Models: Insights from Universal Geochemical Parameters
Wenda Geng, Tingting Li, Xin Zhu, et al.
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1273-1273
Open Access
Heavy Metal Contamination in Plants: Sources, Monitoring, and Data‐Driven Insights
Achana Yadav, M. Mehedi Hasan, Simranjeet Kour, et al.
Macromolecular Symposia (2025) Vol. 414, Iss. 1
Closed Access
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