Jun Wang

20.0k total citations · 6 hit papers
384 papers, 12.7k citations indexed

About

Jun Wang is a scholar working on Global and Planetary Change, Atmospheric Science and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Jun Wang has authored 384 papers receiving a total of 12.7k indexed citations (citations by other indexed papers that have themselves been cited), including 259 papers in Global and Planetary Change, 258 papers in Atmospheric Science and 65 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Jun Wang's work include Atmospheric chemistry and aerosols (205 papers), Atmospheric aerosols and clouds (155 papers) and Atmospheric Ozone and Climate (100 papers). Jun Wang is often cited by papers focused on Atmospheric chemistry and aerosols (205 papers), Atmospheric aerosols and clouds (155 papers) and Atmospheric Ozone and Climate (100 papers). Jun Wang collaborates with scholars based in United States, China and Canada. Jun Wang's co-authors include Sundar A. Christopher, Xiaoguang Xu, Cui Ge, Jeffrey S. Reid, Zhanqing Li, Daniel J. Jacob, Jing Wei, E. J. Hyer, Pawan Gupta and Daven K. Henze and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Jun Wang

357 papers receiving 12.4k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Intercomparison between satellite‐derived aerosol optical thickness and PM_2.5 mass: Implications for air quality studies

2003 700 citations Jun Wang et al. Geophysical Research Letters profile →
Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China

2021 381 citations Jing Wei, Zhanqing Li et al. Remote Sensing of Environment profile →
Evaluation of the ERA5 reanalysis precipitation dataset over Chinese Mainland

2020 319 citations Jun Wang et al. profile →
Ground-level gaseous pollutants (NO ₂ , SO ₂ , and CO) in China: daily seamless mapping and spatiotemporal variations

2023 198 citations Jing Wei, Zhanqing Li et al. profile →
Ground-Level NO₂Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence

2022 188 citations Jing Wei, Zhanqing Li et al. Environmental Science & Technology profile →
Separating Daily 1 km PM_2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data

2023 97 citations Jing Wei, Zhanqing Li et al. Environmental Science & Technology profile →

Peers

Countries citing papers authored by Jun Wang

Since Specialization

Citations

This map shows the geographic impact of Jun Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wang more than expected).

Fields of papers citing papers by Jun Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jun Wang. The network helps show where Jun Wang may publish in the future.

Co-authorship network of co-authors of Jun Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Wang. A scholar is included among the top collaborators of Jun Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jun Wang. Jun Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Tracking NO2 and CO pollution hotspots at provincial scale in China with TROPOMI observations and image segmentation method 2025 ·Atmospheric Environment ·(unknown), Minghui Tao, Rong Li, (unknown), Lijuan Zhang, Jun Wang, Lunche Wang, Yì Wáng, (unknown), Liangfu Chen	0
2	Shipping emission inventory preparation with AIS data: A stratified random sampling method 2024 ·Transportation Research Part D Transport and Environment ·(unknown), Xianhua Wu, Jun Wang, Y. Lu	1
3	Elucidating the impacts of aerosol radiative effects for mitigating surface O3 and PM2.5 in Delhi, India during crop residue burning period 2024 ·Atmospheric Environment ·(unknown), Jun Wang, Huanxin Zhang, Xi Chen, Lorena Castro García, (unknown)	0
4	A calibration and prediction method of the camera imaging parameters in variable temperature environment 2024 ·Optics Communications ·(unknown), Mingli Dong, (unknown), (unknown), Jun Wang, (unknown)	0
5	First lunar-light mapping of nighttime dust season oceanic aerosol optical depth over North Atlantic from space 2024 ·Remote Sensing of Environment ·Meng Zhou, Jun Wang, Xi Chen, Yi Wang, Peter R. Colarco, R. C. Levy, Steven D. Miller	5
6	Effect of Dust Morphology on Aerosol Optics in the GEOS‐Chem Chemical Transport Model, on UV‐Vis Trace Gas Retrievals, and on Surface Area Available for Reactive Uptake 2024 ·Journal of Advances in Modeling Earth Systems ·(unknown), Randall V. Martin, Liam Bindle, (unknown), Chi Li, (unknown), Xiaoguang Xu, Jun Wang	1
7	Discriminant analysis of the freeze-up and break-up conditions in the Inner Mongolia Reach of the Yellow River 2023 ·Journal of Water and Climate Change ·(unknown), Jun Wang, Jueyi Sui, (unknown), Baosen Zhang, (unknown)	2
8	A calculation algorithm for ship pollutant gas emissions and diffusions based on real-time meteorological conditions and its application 2023 ·Ocean Engineering ·(unknown), Xianhua Wu, Jun Wang	8
9	A new hybrid model for monthly runoff prediction using ELMAN neural network based on decomposition-integration structure with local error correction method 2023 ·Expert Systems with Applications ·Dongmei Xu, Xiao-xue Hu, Wenchuan Wang, Kwok‐wing Chau, Hong-fei Zang, Jun Wang	44
10	A robust and flexible satellite aerosol retrieval algorithm for multi-angle polarimetric measurements with physics-informed deep learning method 2023 ·Remote Sensing of Environment ·Minghui Tao, Jinxi Chen, Xiaoguang Xu, (unknown), Lina Xu, Lunche Wang, Yi Wang, Jun Wang, Meng Fan, Muhammad Imran Shahzad, Liangfu Chen	19
11	Flood risk mapping for the area with mixed floods and human impact: a case study of Yarkant River Basin in Xinjiang, China 2023 ·Environmental Research Communications ·(unknown), Jun Wang, Yiming Hu, Binquan Li, (unknown), (unknown)	3
12	A Generalized Aerosol Algorithm for Multi‐Spectral Satellite Measurement With Physics‐Informed Deep Learning Method 2023 ·Geophysical Research Letters ·(unknown), Minghui Tao, (unknown), (unknown), (unknown), Jun Wang, Lunche Wang, Yi Wang, (unknown), Jinhua Tao, Liangfu Chen	10
13	Separating Daily 1 km PM_2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data breakdown → 2023 ·Environmental Science & Technology ·Jing Wei, Zhanqing Li, Xi Chen, Chi Li, Yele Sun, Jun Wang, Alexei Lyapustin, Guy Brasseur, Mengjiao Jiang, Lin Sun, Tao Wang, Chang Hoon Jung, (unknown), (unknown), Xuhui Liu, (unknown), Yan Wang, Ming Zhan, Xiaohong Song, Yuewei Liu	97
14	Aerosol Detection from the Cloud–Aerosol Transport System on the International Space Station: Algorithm Overview and Implications for Diurnal Sampling 2022 ·Atmosphere ·E. P. Nowottnick, (unknown), John E. Yorks, Matthew J. McGill, (unknown), Patrick Selmer, (unknown), Jun Wang, Santo V. Salinas	12
15	Beijing Climate Center Earth System Model version 1 (BCC-ESM1): model description and evaluation of aerosol simulations 2020 ·Geoscientific model development ·Tongwen Wu, Fang Zhang, Jie Zhang, Weihua Jie, Yanwu Zhang, Fanghua Wu, Laurent Li, Jinghui Yan, Xiaohong Liu, Xiao Lu, (unknown), Lin Zhang, Jun Wang, Aixue Hu	82
16	Detecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: hourly results from EPIC/DSCOVR in deep space 2019 ·Atmospheric measurement techniques ·Xiaoguang Xu, Jun Wang, (unknown), Jing Zeng, Omar Torres, Jeffrey S. Reid, Steven D. Miller, J. Vanderlei Martins, L. A. Remer	47
17	Development of the global atmospheric general circulation-chemistry model BCC-GEOS-Chem v1.0: model description and evaluation 2019 ·Xiao Lu, Lin Zhang, Tongwen Wu, M. S. Long, Jun Wang, Daniel J. Jacob, Fang Zhang, Jie Zhang, Sebastian D. Eastham, Lu Hu, Lei Zhu, Xiong Liu, Min Wei	3
18	Sense size‐dependent dust loading and emission from space using reflected solar and infrared spectral measurements: An observation system simulation experiment 2017 ·Journal of Geophysical Research Atmospheres ·Xiaoguang Xu, Jun Wang, Yi Wang, Daven K. Henze, Li Zhang, Georg Grell, S. A. McKeen, Bruce A. Wielicki	17
19	Passive remote sensing of altitude and optical depth of dust plumes using the oxygen A and B bands: First results from EPIC/DSCOVR at Lagrange‐1 point 2017 ·Geophysical Research Letters ·Xiaoguang Xu, Jun Wang, Yi Wang, Jing Zeng, Omar Torres, Yuekui Yang, Alexander Marshak, Jeffrey S. Reid, (unknown)	73
20	Retrieval of aerosol microphysical properties from AERONET\nphotopolarimetric measurements: 2. A new research\nalgorithm and case demonstration 2015 ·Insecta mundi ·Xiaoguang Xu, Jun Wang, Jing Zeng, Robert Spurr, Xiong Liu, Оleg Dubovik, Li Li, Zhengqiang Li, Michael I. Mishchenko, (unknown), B. N. Holben	63

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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