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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.

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Showing 1-25 of 61 citing articles:

A review of machine learning for modeling air quality: Overlooked but important issues
Dié Tang, Yu Zhan, Fumo Yang
Atmospheric Research (2024) Vol. 300, pp. 107261-107261
Closed Access | Times Cited: 37
Estimating ground-level PM2.5 using subset regression model and machine learning algorithms in Asian megacity, Dhaka, Bangladesh
Abu Reza Md. Towfiqul Islam, Mohammed Al Awadh, Javed Mallick, et al.
Air Quality Atmosphere & Health (2023) Vol. 16, Iss. 6, pp. 1117-1139
Open Access | Times Cited: 26
An interpretable self-adaptive deep neural network for estimating daily spatially-continuous PM2.5 concentrations across China
Binjie Chen, Shixue You, Ye Yang, et al.
The Science of The Total Environment (2021) Vol. 768, pp. 144724-144724
Open Access | Times Cited: 53
Obtaining vertical distribution of PM2.5 from CALIOP data and machine learning algorithms
Бин Чэн, Zhihao Song, Feng Pan, et al.
The Science of The Total Environment (2021) Vol. 805, pp. 150338-150338
Open Access | Times Cited: 50
A CatBoost approach with wavelet decomposition to improve satellite-derived high-resolution PM2.5 estimates in Beijing-Tianjin-Hebei
Yu Ding, Zuoqi Chen, Wenfang Lu, et al.
Atmospheric Environment (2021) Vol. 249, pp. 118212-118212
Closed Access | Times Cited: 47
A machine learning-based framework for high resolution mapping of PM2.5 in Tehran, Iran, using MAIAC AOD data
Hossein Bagheri
Advances in Space Research (2022) Vol. 69, Iss. 9, pp. 3333-3349
Open Access | Times Cited: 34
A novel multi-factor & multi-scale method for PM2.5 concentration forecasting
Wenyan Yuan, Kaiqi Wang, Xin Bo, et al.
Environmental Pollution (2019) Vol. 255, pp. 113187-113187
Closed Access | Times Cited: 46
Estimation of monthly 1 km resolution PM2.5 concentrations using a random forest model over “2 + 26” cities, China
Jing Lu, Yuhu Zhang, Mingxing Chen, et al.
Urban Climate (2020) Vol. 35, pp. 100734-100734
Open Access | Times Cited: 43
A full-coverage estimation of PM2.5 concentrations using a hybrid XGBoost-WD model and WRF-simulated meteorological fields in the Yangtze River Delta Urban Agglomeration, China
Jiajia Wang, Li He, Xiaoman Lu, et al.
Environmental Research (2021) Vol. 203, pp. 111799-111799
Closed Access | Times Cited: 37
Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia
Nurul Amalin Fatihah Kamarul Zaman, Kasturi Devi Kanniah, Dimitris G. Kaskaoutis, et al.
Applied Sciences (2021) Vol. 11, Iss. 16, pp. 7326-7326
Open Access | Times Cited: 36
Incorporating land-use regression into machine learning algorithms in estimating the spatial-temporal variation of carbon monoxide in Taiwan
Pei-Yi Wong, Chin-Yu Hsu, Jhao-Yi Wu, et al.
Environmental Modelling & Software (2021) Vol. 139, pp. 104996-104996
Open Access | Times Cited: 34
Combining Himawari-8 AOD and deep forest model to obtain city-level distribution of PM2.5 in China
Zhihao Song, Bin Chen, Jianping Huang
Environmental Pollution (2022) Vol. 297, pp. 118826-118826
Closed Access | Times Cited: 28
An investigation of PM2.5 concentration changes in Mid-Eastern China before and after COVID-19 outbreak
Yongjun Zhang, Wenpin Wu, Yiliang Li, et al.
Environment International (2023) Vol. 175, pp. 107941-107941
Open Access | Times Cited: 14
Spatial prediction of PM2.5 concentration using hyper-parameter optimization XGBoost model in China
Yingqiang Song, Changjian Zhang, Xin Jin, et al.
Environmental Technology & Innovation (2023) Vol. 32, pp. 103272-103272
Open Access | Times Cited: 14
Modeling the Effects of Drivers on PM2.5 in the Yangtze River Delta with Geographically Weighted Random Forest
Zhangwen Su, Lin Lin, Zhenhui Xu, et al.
Remote Sensing (2023) Vol. 15, Iss. 15, pp. 3826-3826
Open Access | Times Cited: 14
Combined use of principal component analysis and artificial neural network approach to improve estimates of PM2.5 personal exposure: A case study on older adults
Shuang Gao, Hong Zhao, Zhipeng Bai, et al.
The Science of The Total Environment (2020) Vol. 726, pp. 138533-138533
Closed Access | Times Cited: 36
Retrieving PM2.5 with high spatio-temporal coverage by TOA reflectance of Himawari-8
Jianhua Yin, Feiyue Mao, Lin Zang, et al.
Atmospheric Pollution Research (2021) Vol. 12, Iss. 4, pp. 14-20
Open Access | Times Cited: 31
Including the feature of appropriate adjacent sites improves the PM2.5 concentration prediction with long short-term memory neural network model
Mengfan Teng, Siwei Li, Ge Song, et al.
Sustainable Cities and Society (2021) Vol. 76, pp. 103427-103427
Open Access | Times Cited: 29
Application of machine learning algorithms to improve numerical simulation prediction of PM2.5 and chemical components
Lingling Lv, Wei Peng, Juan Li, et al.
Atmospheric Pollution Research (2021) Vol. 12, Iss. 11, pp. 101211-101211
Closed Access | Times Cited: 27
Remote sensing estimation of surface PM2.5 concentrations using a deep learning model improved by data augmentation and a particle size constraint
Shun‐Chao Yin, Tongwen Li, Xiao Cheng, et al.
Atmospheric Environment (2022) Vol. 287, pp. 119282-119282
Closed Access | Times Cited: 20
Estimation of Near-Surface High Spatiotemporal Resolution Ozone Concentration in China Using Himawari-8 AOD
Yixuan Wang, Chongshui Gong, Li Dong, et al.
Remote Sensing (2025) Vol. 17, Iss. 3, pp. 528-528
Open Access
High-resolution monthly assessment of population exposure to PM2.5 and its relationship with socioeconomic activities using multisource geospatial data
Ma Yu, Chen Zhou, Manchun Li, et al.
Environmental Monitoring and Assessment (2025) Vol. 197, Iss. 3
Closed Access
Temporally boosting neural network for improving dynamic prediction of PM2.5 concentration with changing and unbalanced distribution
Haoze Shi, Xin Yang, Hong Tang, et al.
Journal of Environmental Management (2025) Vol. 383, pp. 125371-125371
Closed Access
Estimating hourly PM2.5 concentrations using MODIS 3 km AOD and an improved spatiotemporal model over Beijing-Tianjin-Hebei, China
Xinpeng Wang, Wenbin Sun, Kangning Zheng, et al.
Atmospheric Environment (2019) Vol. 222, pp. 117089-117089
Closed Access | Times Cited: 31
Air quality warning system based on a localized PM2.5 soft sensor using a novel approach of Bayesian regularized neural network via forward feature selection
Deepak Balram, Kuang‐Yow Lian, Neethu Sebastian
Ecotoxicology and Environmental Safety (2019) Vol. 182, pp. 109386-109386
Closed Access | Times Cited: 30
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