Xiaohui Bi

4.2k citations
85 papers · 3.2k indexed · 1 hit paper · h-index 32

Xiaohui Bi

82 papers receiving 3.2k citations

Hit Papers

Revealing Drivers of Haze Pollution by Explainable Machin...156202220262023202450100150

Peers

Xiaohui Bi
Comparison fields: 5 of 116
  • Health, Toxicology and Mutagenesis 2.4k
  • Atmospheric Science 2.1k
  • Environmental Engineering 1.2k
  • Automotive Engineering 643
  • Pollution 349
Replace Mauro Masiol with:
Mauro Masiol Italy
Qili Dai China
María de Fátima Andrade Brazil
Begoña Artı́ñano Spain
Md Firoz Khan Malaysia
Tomoaki Okuda Japan
Angeliki Karanasiou Spain
María Cruz Minguillón Spain
Huang Zheng China
Fumo Yang China
Xiaohui Bi relative to Mauro Masiol Italy Mauro Masiol's profile →
Citations per field
00.5×1.5×
Mauro Masiol · 1×
Citations per year

Countries citing papers authored by Xiaohui Bi

Since Specialization
Citations

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

Fields of papers citing papers by Xiaohui Bi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Xiaohui Bi, 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 Xiaohui Bi Line = papers co-authored together Xiaohui Bi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20245
2 20240
3 20242
4 20242
5 202337
6 20234
7 202312
8 202321
9 20232
10
Revealing Drivers of Haze Pollution by Explainable Machine Learningbreakdown →
2022156
11 20222
12 202137
13 202117
14 20217
15 202056
16 201912
17 201937
18
Refined source apportionment of coal-combustion source based on CALPUFF-CMB models.
20181
19 20182
20 201134

About Xiaohui Bi

Xiaohui Bi is a scholar working on Health, Toxicology and Mutagenesis, Atmospheric Science, Environmental Engineering, Automotive Engineering and Earth-Surface Processes, having authored 85 papers that have together received 3.2k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (63 papers), Atmospheric chemistry and aerosols (58 papers), Air Quality Monitoring and Forecasting (26 papers), Vehicle emissions and performance (20 papers), Aeolian processes and effects (5 papers), Atmospheric aerosols and clouds (5 papers), COVID-19 impact on air quality (4 papers) and Heavy metals in environment (4 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (2.4k citations), Atmospheric Science (2.1k citations), Environmental Engineering (1.2k citations), Automotive Engineering (643 citations) and Pollution (349 citations). Xiaohui Bi has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yinchang Feng, Jianhui Wu, Yufen Zhang, Qili Dai, Baoshuang Liu, Danni Liang, Philip K. Hopke, Zhimei Xiao, Jiamei Yang and Congbo Song. Their work appears in journals such as Environmental Pollution, The Science of The Total Environment, Atmospheric Environment, Atmospheric Research and Aerosol and Air Quality Research.

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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