Fumo Yang

8.9k total citations · 2 hit papers
132 papers, 4.8k citations indexed

About

Fumo Yang is a scholar working on Health, Toxicology and Mutagenesis, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, Fumo Yang has authored 132 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 99 papers in Health, Toxicology and Mutagenesis, 89 papers in Atmospheric Science and 48 papers in Environmental Engineering. Recurrent topics in Fumo Yang's work include Air Quality and Health Impacts (95 papers), Atmospheric chemistry and aerosols (87 papers) and Air Quality Monitoring and Forecasting (45 papers). Fumo Yang is often cited by papers focused on Air Quality and Health Impacts (95 papers), Atmospheric chemistry and aerosols (87 papers) and Air Quality Monitoring and Forecasting (45 papers). Fumo Yang collaborates with scholars based in China, United States and Canada. Fumo Yang's co-authors include Kebin He, Yongliang Ma, Xiaojiang Yao, Steven H. Cadle, Patricia A. Mulawa, Qiang Zhang, Mi Tian, Tai L. Chan, Xiaohong Yao and Chak K. Chan and has published in prestigious journals such as Environmental Science & Technology, The Science of The Total Environment and Journal of Hazardous Materials.

In The Last Decade

Fumo Yang

127 papers receiving 4.7k citations

Hit Papers

The characteristics of PM2.5 in Beijing, China 2001 2026 2009 2017 2001 2011 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fumo Yang China 31 3.2k 2.8k 1.2k 972 812 132 4.8k
Fumo Yang China 30 1.7k 0.5× 1.8k 0.7× 706 0.6× 562 0.6× 459 0.6× 55 2.6k
Hairong Cheng China 36 2.6k 0.8× 2.3k 0.8× 1.2k 1.0× 412 0.4× 502 0.6× 88 4.0k
Tarun Gupta India 42 3.2k 1.0× 2.5k 0.9× 1.1k 0.9× 1.2k 1.3× 522 0.6× 222 5.5k
Zhijun Wu China 54 4.8k 1.5× 6.0k 2.2× 1.7k 1.4× 2.9k 2.9× 881 1.1× 198 9.1k
Biwu Chu China 31 1.8k 0.6× 2.2k 0.8× 863 0.7× 864 0.9× 442 0.5× 129 3.0k
Mi Tian China 30 1.9k 0.6× 1.5k 0.5× 531 0.4× 508 0.5× 288 0.4× 65 2.8k
Yujing Mu China 42 2.5k 0.8× 3.3k 1.2× 1.5k 1.2× 1.1k 1.2× 360 0.4× 189 5.5k
Jianfei Peng China 33 3.5k 1.1× 3.9k 1.4× 1.1k 0.9× 1.7k 1.7× 372 0.5× 119 5.3k
Richard M. Kamens United States 44 5.2k 1.6× 5.4k 2.0× 1.4k 1.1× 982 1.0× 399 0.5× 122 7.2k
Steven Sai Hang Ho China 54 6.1k 1.9× 4.5k 1.6× 1.9k 1.6× 780 0.8× 367 0.5× 210 7.9k

Countries citing papers authored by Fumo Yang

Since Specialization
Citations

This map shows the geographic impact of Fumo Yang'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 Fumo Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fumo Yang more than expected).

Fields of papers citing papers by Fumo Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fumo Yang. 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 Fumo Yang. The network helps show where Fumo Yang may publish in the future.

Co-authorship network of co-authors of Fumo Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Fumo Yang. A scholar is included among the top collaborators of Fumo Yang 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 Fumo Yang. Fumo Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zheng, Xi, Zixiang Zhao, Xinyi Liu, et al.. (2025). Deep transfer learning for spatiotemporal mapping of PM2.5 nitrate across China: Addressing small data challenges in environmental machine learning. Journal of Hazardous Materials. 492. 138206–138206. 2 indexed citations
2.
Liu, Yiliang, Yan Han, Mi Tian, et al.. (2025). Evaluating the Effects of Biomass Burning on Severe Haze Formation in a Megacity of Sichuan Basin, Southwestern China. Journal of Geophysical Research Atmospheres. 130(2). 3 indexed citations
4.
Wang, Ning, Li Zhou, Liping Liu, et al.. (2024). Chemical characteristics and formation mechanisms of PM2.5 during wintertime in two cities with different industrial structures in the Sichuan Basin, China. Journal of Cleaner Production. 462. 142618–142618. 2 indexed citations
5.
Qiu, Yang, Zhiyu Chen, Fumo Yang, et al.. (2023). Third trimester as the susceptibility window for maternal PM2.5 exposure and preterm birth: A nationwide surveillance-based association study in China. The Science of The Total Environment. 880. 163274–163274. 7 indexed citations
6.
Li, Qing, et al.. (2023). Springtime reactive volatile organic compounds (VOCs) and impacts on ozone in urban areas of Yunnan-Guizhou plateau, China: A PTR-TOF-MS study. Atmospheric Environment. 307. 119800–119800. 5 indexed citations
7.
Li, Qing, Shi-Yong Xia, Keding Lu, et al.. (2023). Biogenic volatile organic compounds dominated the near-surface ozone generation in Sichuan Basin, China, during fall and wintertime. Journal of Environmental Sciences. 141. 215–224. 5 indexed citations
9.
Wang, Yan, et al.. (2023). Climatology of the planetary boundary layer height over China and its characteristics during periods of extremely temperature. Atmospheric Research. 294. 106960–106960. 5 indexed citations
10.
Wang, Huanbo, Hongli Tao, Fumo Yang, et al.. (2023). Atmospheric humic-like substances (HULIS) in Chongqing, Southwest China: Abundance, light absorption properties, and potential sources. Atmospheric Research. 295. 107016–107016. 3 indexed citations
11.
Lü, Chengwei, Ting Chen, Xinyue Yang, et al.. (2023). Development and Application of a Novel Snow Peak Sighting Forecast System over Chengdu. Atmosphere. 14(7). 1181–1181. 1 indexed citations
12.
Shi, Guangming, et al.. (2023). Transport Channels of Air Pollutants Affecting the Southern Sichuan Basin Based on Gridded Dispersion Simulation. International Journal of Environmental Research and Public Health. 20(7). 5396–5396.
13.
Liu, Yuelin, Guangming Shi, Yu Zhan, Li Zhou, & Fumo Yang. (2021). Characteristics of PM2.5 spatial distribution and influencing meteorological conditions in Sichuan Basin, southwestern China. Atmospheric Environment. 253. 118364–118364. 27 indexed citations
14.
15.
Chen, Yang, Guangming Shi, Jing Cai, et al.. (2020). Simultaneous measurements of urban and rural particles in Beijing – Part 2: Case studies of haze events and regional transport. Atmospheric chemistry and physics. 20(15). 9249–9263. 7 indexed citations
17.
Liu, Dongren, Baofeng Di, Yuzhou Luo, et al.. (2019). Estimating ground-level CO concentrations across China based on the national monitoring network and MOPITT: potentially overlooked CO hotspots in the Tibetan Plateau. Atmospheric chemistry and physics. 19(19). 12413–12430. 32 indexed citations
18.
Wang, Huanbo, Mi Tian, Yang Chen, et al.. (2018). Seasonal characteristics, formation mechanisms and source origins of PM 2.5 in two megacities in Sichuan Basin, China. Atmospheric chemistry and physics. 18(2). 865–881. 159 indexed citations
19.
Guo, Songjun, Fumo Yang, Jihua Tan, & Jingchun Duan. (2011). Nonmethane Hydrocarbons in Ambient Air of Hazy and Normal Days in Foshan, South China. Environmental Engineering Science. 29(4). 262–269. 14 indexed citations
20.
Yang, Fumo, Jihua Tan, Qingguo Zhao, et al.. (2011). Characteristics of PM 2.5 speciation in representative megacities and across China. Atmospheric chemistry and physics. 11(11). 5207–5219. 528 indexed citations breakdown →

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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