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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:

The varying driving forces of PM2.5 concentrations in Chinese cities: Insights from a geographically and temporally weighted regression model
Qianqian Liu, Rong Wu, Wenzhong Zhang, et al.
Environment International (2020) Vol. 145, pp. 106168-106168
Open Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

The effects of technological factors on carbon emissions from various sectors in China—A spatial perspective
Xiaohui Yang, Zhen Jia, Zhongmin Yang, et al.
Journal of Cleaner Production (2021) Vol. 301, pp. 126949-126949
Closed Access | Times Cited: 76
Impacts of natural and socioeconomic factors on PM2.5 from 2014 to 2017
Yichen Wang, ChenGuang Liu, Qiyuan Wang, et al.
Journal of Environmental Management (2021) Vol. 284, pp. 112071-112071
Closed Access | Times Cited: 70
Spatiotemporal variations of PM2.5 pollution and its dynamic relationships with meteorological conditions in Beijing-Tianjin-Hebei region
Chuxiong Deng, Chunyan Qin, Zhongwu Li, et al.
Chemosphere (2022) Vol. 301, pp. 134640-134640
Closed Access | Times Cited: 42
Spatiotemporal evolution and determinants of urban land use efficiency under green development orientation: Insights from 284 cities and eight economic zones in China, 2005–2019
Yuxuan Zhou, Yi Lü
Applied Geography (2023) Vol. 161, pp. 103117-103117
Closed Access | Times Cited: 30
Investigating the multiscale associations between urban landscape patterns and PM1 pollution in China using a new combined framework
Huimin Zhu, Ping Zhang, Ning Wang, et al.
Journal of Cleaner Production (2024) Vol. 456, pp. 142306-142306
Closed Access | Times Cited: 9
Effect of urban form on PM2.5 concentrations in urban agglomerations of China: Insights from different urbanization levels and seasons
Genhong Gao, Steven G. Pueppke, Qin Tao, et al.
Journal of Environmental Management (2022) Vol. 327, pp. 116953-116953
Closed Access | Times Cited: 28
Spatio-temporal variations and socio-economic drivers of air pollution: Evidence from 332 Chinese prefecture-level cities
Xue Zhou, Xiaolu Zhang, Yanan Wang, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 6, pp. 101782-101782
Closed Access | Times Cited: 18
Spatiotemporal heterogeneity of the relationships between PM2.5 concentrations and their drivers in China's coastal ports
Yang Zhang, Yuanyuan Yang, Jihong Chen, et al.
Journal of Environmental Management (2023) Vol. 345, pp. 118698-118698
Closed Access | Times Cited: 16
Spatiotemporal evolution and the driving factors of PM2.5 in Chinese urban agglomerations between 2000 and 2017
Qilong Wu, Runxiu Guo, Jinhui Luo, et al.
Ecological Indicators (2021) Vol. 125, pp. 107491-107491
Open Access | Times Cited: 40
Exploring the real contribution of socioeconomic variation to urban PM2.5 pollution: New evidence from spatial heteroscedasticity
Dan Yan, Xiaohang Ren, Wanli Zhang, et al.
The Science of The Total Environment (2021) Vol. 806, pp. 150929-150929
Closed Access | Times Cited: 34
Estimating 1 km gridded daily air temperature using a spatially varying coefficient model with sign preservation
Tao Zhang, Yuyu Zhou, Li Wang, et al.
Remote Sensing of Environment (2022) Vol. 277, pp. 113072-113072
Open Access | Times Cited: 24
Spatiotemporal analysis of the impact of urban landscape forms on PM 2.5 in China from 2001 to 2020
S. Y. Zhu, Jiayi Tang, Xiaolu Zhou, et al.
International Journal of Digital Earth (2023) Vol. 16, Iss. 1, pp. 3417-3434
Open Access | Times Cited: 13
An interpretable physics-informed deep learning model for estimating multiple air pollutants
Binjie Chen, Jiacong Hu, Yumiao Wang, et al.
GIScience & Remote Sensing (2025) Vol. 62, Iss. 1
Open Access
Spatiotemporal pattern analysis of PM2.5 and the driving factors in the middle Yellow River urban agglomerations
Yifeng Mi, Ken Sun, Li Li, et al.
Journal of Cleaner Production (2021) Vol. 299, pp. 126904-126904
Closed Access | Times Cited: 32
Gaussian Markov random fields improve ensemble predictions of daily 1 km PM2.5 and PM10 across France
Ian Hough, Ron Sarafian, Alexandra Shtein, et al.
Atmospheric Environment (2021) Vol. 264, pp. 118693-118693
Open Access | Times Cited: 30
Strengthening grassland carbon source and sink management to enhance its contribution to regional carbon neutrality
Xin Lyu, Xiaobing Li, Kai Wang, et al.
Ecological Indicators (2023) Vol. 152, pp. 110341-110341
Open Access | Times Cited: 11
The pressure of political promotion and renewable energy technological innovation: A spatial econometric analysis from China
Dongqin Cao, Peng Can, Guanglei Yang
Technological Forecasting and Social Change (2022) Vol. 183, pp. 121888-121888
Closed Access | Times Cited: 18
Multiple driving factors and hierarchical management of PM2.5: Evidence from Chinese central urban agglomerations using machine learning model and GTWR
Changhong Ou, Fei Li, Jingdong Zhang, et al.
Urban Climate (2022) Vol. 46, pp. 101327-101327
Closed Access | Times Cited: 18
The socioeconomic factors influencing the PM2.5 levels of 160 cities in China
Wenli Li, Guangfei Yang, Xiangyu Qian
Sustainable Cities and Society (2022) Vol. 84, pp. 104023-104023
Closed Access | Times Cited: 16
An Estimating Method for Carbon Emissions of China Based on Nighttime Lights Remote Sensing Satellite Images
Tianjiao Yang, Jing Liu, MI Hai-bo, et al.
Sustainability (2022) Vol. 14, Iss. 4, pp. 2269-2269
Open Access | Times Cited: 14
What Factors Dominate the Change of PM2.5 in the World from 2000 to 2019? A Study from Multi-Source Data
Xiankang Xu, Kaifang Shi, Zhongyu Huang, et al.
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 3, pp. 2282-2282
Open Access | Times Cited: 8
Spatiotemporal Heterogeneity of the Characteristics and Influencing Factors of Energy-Consumption-Related Carbon Emissions in Jiangsu Province Based on DMSP-OLS and NPP-VIIRS
Hongzhi Meng, Xiaoke Zhang, Xindong Du, et al.
Land (2023) Vol. 12, Iss. 7, pp. 1369-1369
Open Access | Times Cited: 7
Determination of the best geographic weighted function and estimation of spatio temporal model – Geographically weighted panel regression using weighted least square
Sifriyani Sifriyani, I Nyoman Budiantara, M. Fariz Fadillah Mardianto, et al.
MethodsX (2024) Vol. 12, pp. 102605-102605
Open Access | Times Cited: 2
Differences in urban–rural gradient and driving factors of PM2.5 concentration in the Zhengzhou Metropolitan Area
Liang Chen, Lingfei Shi
Air Quality Atmosphere & Health (2024) Vol. 17, Iss. 10, pp. 2187-2201
Closed Access | Times Cited: 2
Analyzing the effects of socioeconomic, natural and landscape factors on PM2.5 concentrations from a spatial perspective
Jun Song, Chunlin Li, Yuanman Hu, et al.
Environment Development and Sustainability (2024)
Closed Access | Times Cited: 2
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