Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 Daily PM2.5 and PM10 over Italy Using an Ensemble Model
Alexandra Shtein, Itai Kloog, Joel Schwartz, et al.
Environmental Science & Technology (2019) Vol. 54, Iss. 1, pp. 120-128
Closed Access | Times Cited: 99

Showing 1-25 of 99 citing articles:

Using a land use regression model with machine learning to estimate ground level PM2.5
Pei-Yi Wong, Hsiao‐Yun Lee, Yu‐Cheng Chen, et al.
Environmental Pollution (2021) Vol. 277, pp. 116846-116846
Open Access | Times Cited: 112
Global estimates of daily ambient fine particulate matter concentrations and unequal spatiotemporal distribution of population exposure: a machine learning modelling study
Wenhua Yu, Tingting Ye, Yiwen Zhang, et al.
The Lancet Planetary Health (2023) Vol. 7, Iss. 3, pp. e209-e218
Closed Access | Times Cited: 112
Estimation of High-Resolution PM2.5 over the Indo-Gangetic Plain by Fusion of Satellite Data, Meteorology, and Land Use Variables
Alaa Mhawish, Tirthankar Banerjee, Meytar Sorek‐Hamer, et al.
Environmental Science & Technology (2020) Vol. 54, Iss. 13, pp. 7891-7900
Closed Access | Times Cited: 96
Satellite remote sensing of atmospheric particulate matter mass concentration: Advances, challenges, and perspectives
Ying Zhang, Zhengqiang Li, Kaixu Bai, et al.
Fundamental Research (2021) Vol. 1, Iss. 3, pp. 240-258
Open Access | Times Cited: 87
A Random Forest Approach to Estimate Daily Particulate Matter, Nitrogen Dioxide, and Ozone at Fine Spatial Resolution in Sweden
Massimo Stafoggia, Christer Johansson, Paul Glantz, et al.
Atmosphere (2020) Vol. 11, Iss. 3, pp. 239-239
Open Access | Times Cited: 73
Deep Ensemble Machine Learning Framework for the Estimation of PM2.5 Concentrations
Wenhua Yu, Shanshan Li, Tingting Ye, et al.
Environmental Health Perspectives (2022) Vol. 130, Iss. 3
Open Access | Times Cited: 49
Flexible Bayesian Ensemble Machine Learning Framework for Predicting Local Ozone Concentrations
Xiang Ren, Zhongyuan Mi, Ting Cai, et al.
Environmental Science & Technology (2022) Vol. 56, Iss. 7, pp. 3871-3883
Open Access | Times Cited: 46
Relationship of long-term air pollution exposure with asthma and rhinitis in Italy: an innovative multipollutant approach
Sara Maio, Salvatore Fasola, Alessandro Marcon, et al.
Environmental Research (2023) Vol. 224, pp. 115455-115455
Open Access | Times Cited: 26
An ensemble mixed spatial model in estimating long-term and diurnal variations of PM2.5 in Taiwan
Pei-Yi Wong, Huey‐Jen Su, Shih‐Chun Candice Lung, et al.
The Science of The Total Environment (2023) Vol. 866, pp. 161336-161336
Open Access | Times Cited: 22
Land use regression model established using Light Gradient Boosting Machine incorporating the WRF/CMAQ model for highly accurate spatiotemporal PM2.5 estimation in the central region of Thailand
Tin Thongthammachart, Hikari Shimadera, Shin Araki, et al.
Atmospheric Environment (2023) Vol. 297, pp. 119595-119595
Closed Access | Times Cited: 22
Dynamic Traffic Data in Machine-Learning Air Quality Mapping Improves Environmental Justice Assessment
Yifan Wen, Shaojun Zhang, Yuan Wang, et al.
Environmental Science & Technology (2024)
Closed Access | Times Cited: 14
Improving 3-day deterministic air pollution forecasts using machine learning algorithms
Zhiguo Zhang, Christer Johansson, Magnuz Engardt, et al.
Atmospheric chemistry and physics (2024) Vol. 24, Iss. 2, pp. 807-851
Open Access | Times Cited: 9
A multi-city air pollution population exposure study: Combined use of chemical-transport and random-Forest models with dynamic population data
Claudio Gariazzo, Giuseppe Carlino, Camillo Silibello, et al.
The Science of The Total Environment (2020) Vol. 724, pp. 138102-138102
Open Access | Times Cited: 63
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
GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms
Abdulwaheed Tella, Abdul‐Lateef Balogun
Environmental Science and Pollution Research (2021) Vol. 29, Iss. 57, pp. 86109-86125
Closed Access | Times Cited: 44
Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification
Qiang Pu, Eun‐Hye Yoo
Environmental Pollution (2021) Vol. 274, pp. 116574-116574
Closed Access | Times Cited: 43
Full-coverage spatiotemporal mapping of ambient PM2.5 and PM10 over China from Sentinel-5P and assimilated datasets: Considering the precursors and chemical compositions
Yuan Wang, Qiangqiang Yuan, Tongwen Li, et al.
The Science of The Total Environment (2021) Vol. 793, pp. 148535-148535
Open Access | Times Cited: 41
Optimizing modeling windows to better capture the long-term variation of PM2.5 concentrations in China during 2005–2019
Su Shi, Weidong Wang, Xinyue Li, et al.
The Science of The Total Environment (2022) Vol. 854, pp. 158624-158624
Closed Access | Times Cited: 37
Application of satellite remote sensing data and random forest approach to estimate ground-level PM2.5 concentration in Northern region of Thailand
Pimchanok Wongnakae, Pakkapong Chitchum, Rungduen Sripramong, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 38, pp. 88905-88917
Closed Access | Times Cited: 19
Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach
Siddhartha Mandal, Ajit Rajiva, Itai Kloog, et al.
PNAS Nexus (2024) Vol. 3, Iss. 3
Open Access | Times Cited: 7
Comparison of Air Pollution–Mortality Associations Using Observed Particulate Matter Concentrations and Reanalysis Data in 33 Spanish Cities
Dominic Royé, Carmen Íñiguez, Aurelio Tobı́as
Environment & Health (2024) Vol. 2, Iss. 3, pp. 161-169
Open Access | Times Cited: 6
Improving the quantification of fine particulates (PM2.5) concentrations in Malaysia using simplified and computationally efficient models
Nurul Amalin Fatihah Kamarul Zaman, Kasturi Devi Kanniah, Dimitris G. Kaskaoutis, et al.
Journal of Cleaner Production (2024) Vol. 448, pp. 141559-141559
Closed Access | Times Cited: 6
Spatially and temporally coherent reconstruction of tropospheric NO2 over China combining OMI and GOME-2B measurements
Qin He, Kai Qin, Jason Blake Cohen, et al.
Environmental Research Letters (2020) Vol. 15, Iss. 12, pp. 125011-125011
Open Access | Times Cited: 42
Ensemble averaging using remote sensing data to model spatiotemporal PM10 concentrations in sparsely monitored South Africa
Oluwaseyi Olalekan Arowosegbe, Martin Röösli, Nino Künzli, et al.
Environmental Pollution (2022) Vol. 310, pp. 119883-119883
Open Access | Times Cited: 22
Unveiling the migration of Cr and Cd to biochar from pyrolysis of manure and sludge using machine learning
Jie Li, Lanjia Pan, Zhiwei Li, et al.
The Science of The Total Environment (2023) Vol. 885, pp. 163895-163895
Closed Access | Times Cited: 15
Page 1 - Next Page

Scroll to top