Su Shi

1.0k total citations
37 papers, 622 citations indexed

About

Su Shi is a scholar working on Health, Toxicology and Mutagenesis, Environmental Engineering and Pollution. According to data from OpenAlex, Su Shi has authored 37 papers receiving a total of 622 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Health, Toxicology and Mutagenesis, 9 papers in Environmental Engineering and 5 papers in Pollution. Recurrent topics in Su Shi's work include Air Quality and Health Impacts (23 papers), Climate Change and Health Impacts (17 papers) and Air Quality Monitoring and Forecasting (8 papers). Su Shi is often cited by papers focused on Air Quality and Health Impacts (23 papers), Climate Change and Health Impacts (17 papers) and Air Quality Monitoring and Forecasting (8 papers). Su Shi collaborates with scholars based in China, United States and South Korea. Su Shi's co-authors include Haidong Kan, Xia Meng, Renjie Chen, Qingli Zhang, Weidong Wang, Lena Kan, Bo Yang, Jian Lei, Hongliang Zhang and Tao Xue and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and Renewable and Sustainable Energy Reviews.

In The Last Decade

Su Shi

30 papers receiving 611 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Su Shi China 13 400 117 114 105 59 37 622
Mingyao Yao China 15 238 0.6× 184 1.6× 152 1.3× 120 1.1× 33 0.6× 38 630
Diogo Lopes Portugal 13 453 1.1× 261 2.2× 215 1.9× 35 0.3× 215 3.6× 50 749
David Agis Spain 12 575 1.4× 236 2.0× 147 1.3× 20 0.2× 63 1.1× 23 901
Kai-Chung Cheng United States 15 513 1.3× 247 2.1× 71 0.6× 22 0.2× 58 1.0× 30 697
Majid Shafiepour Motlagh Iran 14 221 0.6× 173 1.5× 30 0.3× 57 0.5× 101 1.7× 38 532
Lina Vitali Italy 14 281 0.7× 230 2.0× 65 0.6× 174 1.7× 201 3.4× 38 654
Omid Ghaffarpasand United Kingdom 15 281 0.7× 195 1.7× 241 2.1× 42 0.4× 60 1.0× 36 560
Artur Badyda Poland 16 545 1.4× 253 2.2× 154 1.4× 36 0.3× 109 1.8× 84 790
Kwonchul Ha South Korea 10 269 0.7× 106 0.9× 147 1.3× 24 0.2× 64 1.1× 35 466
Jia Xu China 17 589 1.5× 273 2.3× 111 1.0× 29 0.3× 124 2.1× 45 707

Countries citing papers authored by Su Shi

Since Specialization
Citations

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

Fields of papers citing papers by Su Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Su Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Su Shi. A scholar is included among the top collaborators of Su Shi 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 Su Shi. Su Shi 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.
Chen, Jiaxin, Su Shi, Xinyue Li, et al.. (2025). Predicting hourly indoor ozone concentrations with sensor-based measurements and easily accessible predictors. PubMed. 4(3). 100170–100170.
2.
Wang, Menghao, Yali Wang, Liang He, et al.. (2025). Associations between long-term particulate matter exposure and various metabolic syndrome components: Evidence from a prospective cohort study in Eastern China. Journal of Hazardous Materials Advances. 18. 100656–100656.
3.
4.
Shi, Su, et al.. (2025). A Distributed Multi-Microgrid Cooperative Energy Sharing Strategy Based on Nash Bargaining. Electronics. 14(15). 3155–3155.
5.
6.
Chen, Jiaxin, Shengqiang Zhu, Peng Wang, et al.. (2024). Predicting particulate matter, nitrogen dioxide, and ozone across Great Britain with high spatiotemporal resolution based on random forest models. The Science of The Total Environment. 926. 171831–171831. 15 indexed citations
7.
Yin, Peng, Xiaolei Lin, Su Shi, et al.. (2024). Joint Effect of Short-Term Exposure to Fine Particulate Matter and Ozone on Mortality: A Time Series Study in 272 Chinese Cities. Environmental Science & Technology. 58(29). 12865–12874. 4 indexed citations
8.
Li, Xiaocheng, Xinhuan Chen, Yayun Zhu, et al.. (2024). Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD). Journal of Proteome Research. 23(6). 2253–2264. 1 indexed citations
9.
Shi, Su, Renjie Chen, Peng Wang, et al.. (2024). An Ensemble Machine Learning Model to Enhance Extrapolation Ability of Predicting Coarse Particulate Matter with High Resolutions in China. Environmental Science & Technology. 58(43). 19325–19337. 4 indexed citations
10.
11.
Yang, Bo, Qiang Li, Qian Chen, et al.. (2023). Critical summary and perspectives on state-of-health of lithium-ion battery. Renewable and Sustainable Energy Reviews. 190. 114077–114077. 100 indexed citations
12.
Meng, Xia, Su Shi, Yue Niu, et al.. (2023). Epigenome-wide association study on short-, intermediate- and long-term ozone exposure in Han Chinese, the NSPT study. Journal of Hazardous Materials. 463. 132780–132780. 5 indexed citations
13.
Chen, Renjie, Cong Liu, Yue Niu, et al.. (2023). Short-term exposure to ozone may trigger the onset of Kawasaki disease: An individual-level, case-crossover study in East China. Chemosphere. 349. 140828–140828. 3 indexed citations
14.
Li, Xinyue, Peng Wang, Weidong Wang, et al.. (2023). Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models. Environment International. 176. 107967–107967. 28 indexed citations
15.
Lei, Jian, Renjie Chen, Cong Liu, et al.. (2023). Fine and coarse particulate air pollution and hospital admissions for a wide range of respiratory diseases: a nationwide case-crossover study. International Journal of Epidemiology. 52(3). 715–726. 34 indexed citations
16.
Zhang, Qingli, Xia Meng, Su Shi, et al.. (2022). Overview of particulate air pollution and human health in China: Evidence, challenges, and opportunities. The Innovation. 3(6). 100312–100312. 104 indexed citations
17.
Meng, Xia, Weidong Wang, Su Shi, et al.. (2022). Evaluating the spatiotemporal ozone characteristics with high-resolution predictions in mainland China, 2013–2019. Environmental Pollution. 299. 118865–118865. 89 indexed citations
18.
Zhang, Lina, Shuyan Shi, Ying Yang, et al.. (2022). Effects of greenness on preterm birth: A national longitudinal study of 3.7 million singleton births. The Innovation. 3(3). 100241–100241. 26 indexed citations
19.
Lei, Jian, Ting Yang, Yixiang Zhu, et al.. (2022). Non-optimum ambient temperature may decrease pulmonary function: A longitudinal study with intensively repeated measurements among asthmatic adult patients in 25 Chinese cities. Environment International. 164. 107283–107283. 15 indexed citations
20.
Shi, Su, Weidong Wang, Xinyue Li, et al.. (2022). Optimizing modeling windows to better capture the long-term variation of PM2.5 concentrations in China during 2005–2019. The Science of The Total Environment. 854. 158624–158624. 39 indexed citations

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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