Jun Man

774 citations
36 papers · 545 · 1 hit paper · h-index 12

Impact in

Papers in

Jun Man

34 papers receiving 534 citations

Jun Man's Hit Papers

Escalating arsenic contamination throughout Chinese soils 2024 · 126 citations
1260+1Years since publication4080120

Peers

Jun Man
Comparison fields: 5 of 78
  • Environmental Engineering 171
  • Pollution 78
  • Environmental Chemistry 65
  • Water Science and Technology 67
  • Civil and Structural Engineering 95
Replace Travis M. McGuire with:
Travis M. McGuire United States
George E. DeVaull United States
Reza Taherdangkoo Germany
Peng Pei China
Adam Brun Denmark
Arun Kumar Deb United States
Matthew A. Lahvis United States
Karlheinz Spitz Australia
Jun Man relative to Travis M. McGuire United States Travis M. McGuire's profile →
Citations per field
00.5×5×10×15×20.3×
Travis M. McGuire · 1×
Citations per year

Countries citing papers authored by Jun Man

Since Specialization
Citations

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

Fields of papers citing papers by Jun Man

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Man, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Man Line = papers co-authored together Jun Man links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Escalating arsenic contamination throughout Chinese soils
Hit paper breakdown →
2024126
2 201881
3 201844
4 201928
5 201022
6 201622
7 202118
8 201718
9 202116
10 202216
11 201614
12 201913
13 202410
14 20089
15 20229
16 20209
17 20208
18 20258
19 20188
20 20258

About Jun Man

Jun Man is a scholar working on Environmental Engineering, Statistics, Probability and Uncertainty, Civil and Structural Engineering, Pollution and Health, Toxicology and Mutagenesis, having authored 36 papers that have together received 545 indexed citations. Recurring topics across this work include Groundwater flow and contamination studies (14 papers), Soil and Unsaturated Flow (8 papers), Probabilistic and Robust Engineering Design (7 papers), Heavy Metal Exposure and Toxicity (4 papers), Heavy metals in environment (4 papers), Geochemistry and Geologic Mapping (3 papers), Soil Geostatistics and Mapping (3 papers) and Hydrology and Watershed Management Studies (3 papers). The work is most often cited by research in Environmental Engineering (171 citations), Pollution (78 citations), Environmental Chemistry (65 citations), Water Science and Technology (67 citations) and Civil and Structural Engineering (95 citations). Jun Man has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Lingzao Zeng, Laosheng Wu, Jiangjiang Zhang, Yijun Yao, Changlong Wei, Qiang Chen, Shuyou Zhang, Yongming Luo, Lili Niu and Jianqing Ma. Their work appears in journals such as Advances in Water Resources, Journal of Hazardous Materials, Water Resources Research, Journal of Hydrology and Vadose Zone Journal.

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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