Hong-di He

3.0k total citations
122 papers, 2.4k citations indexed

About

Hong-di He is a scholar working on Health, Toxicology and Mutagenesis, Automotive Engineering and Environmental Engineering. According to data from OpenAlex, Hong-di He has authored 122 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Health, Toxicology and Mutagenesis, 60 papers in Automotive Engineering and 43 papers in Environmental Engineering. Recurrent topics in Hong-di He's work include Air Quality and Health Impacts (62 papers), Vehicle emissions and performance (56 papers) and Air Quality Monitoring and Forecasting (34 papers). Hong-di He is often cited by papers focused on Air Quality and Health Impacts (62 papers), Vehicle emissions and performance (56 papers) and Air Quality Monitoring and Forecasting (34 papers). Hong-di He collaborates with scholars based in China, United States and Hong Kong. Hong-di He's co-authors include Jane W. Z. Lu, Zhong‐Ren Peng, Yu Xue, Xiaobing Li, Guanghan Peng, Zhanyong Wang, Kai-Fa Lu, Hongwei Wang, H. Oliver Gao and Wei Pan and has published in prestigious journals such as Environmental Science & Technology, The Science of The Total Environment and Journal of Cleaner Production.

In The Last Decade

Hong-di He

115 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hong-di He China 28 1.1k 1.1k 812 525 518 122 2.4k
Qing-Chang Lu China 24 378 0.3× 344 0.3× 232 0.3× 111 0.2× 439 0.8× 71 1.7k
Liqun Peng China 13 1.6k 1.4× 780 0.7× 492 0.6× 132 0.3× 172 0.3× 43 2.8k
Enrico Pisoni Italy 28 1.3k 1.1× 774 0.7× 669 0.8× 53 0.1× 234 0.5× 122 2.2k
Tianhe Chi China 17 739 0.6× 1.1k 1.0× 344 0.4× 38 0.1× 116 0.2× 91 1.9k
Ling Peng China 17 710 0.6× 1.1k 1.0× 344 0.4× 35 0.1× 79 0.2× 48 1.8k
Xiaojing Yao China 14 589 0.5× 818 0.8× 270 0.3× 35 0.1× 86 0.2× 38 1.4k
Amit Agarwal India 17 377 0.3× 190 0.2× 257 0.3× 81 0.2× 384 0.7× 63 1.1k
Feifeng Jiang Hong Kong 20 303 0.3× 558 0.5× 211 0.3× 54 0.1× 173 0.3× 37 1.4k

Countries citing papers authored by Hong-di He

Since Specialization
Citations

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

Fields of papers citing papers by Hong-di He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hong-di He. 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 Hong-di He. The network helps show where Hong-di He may publish in the future.

Co-authorship network of co-authors of Hong-di He

This figure shows the co-authorship network connecting the top 25 collaborators of Hong-di He. A scholar is included among the top collaborators of Hong-di He 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 Hong-di He. Hong-di He 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.
Peng, Zhong‐Ren, et al.. (2025). Examining fine-grained commuting CO2 emission using cellular signaling data: insights from Shanghai, China. International Journal of Transportation Science and Technology. 20. 270–284.
2.
Liu, Kaixuan, Zhanyong Wang, Fuwang Zhang, et al.. (2025). Mitigating traffic pollution alongside elevated roads: Insights into vertical emission transmissions. Transportation Research Part D Transport and Environment. 148. 105004–105004.
4.
Zhang, Zhe, et al.. (2024). Analysis of factors influencing energy consumption of electric vehicles: Statistical, predictive, and causal perspectives. Applied Energy. 375. 124110–124110. 13 indexed citations
5.
He, Hong-di, et al.. (2024). A deep learning model incorporating frequency domain information for ultra multi-step air pollutant forecasting: A case study of Shanghai. Atmospheric Pollution Research. 15(10). 102247–102247. 2 indexed citations
6.
Xue, Yu, et al.. (2024). Study on traffic flows with connected vehicles and human-driven vehicles. Applied Mathematics and Computation. 490. 129182–129182. 1 indexed citations
7.
Zhang, Zhe, et al.. (2024). Carbon emission reduction benefits of ride-hailing vehicle electrification considering energy structure. Applied Energy. 377. 124548–124548. 7 indexed citations
8.
9.
He, Hong-di, Danni Lu, Hongmei Zhao, & Zhong‐Ren Peng. (2023). Characterizing CO2 and NOx emission of vehicles crossing toll stations in highway. Transportation Research Part D Transport and Environment. 126. 104024–104024. 26 indexed citations
10.
He, Hong-di, et al.. (2023). Quantifying traffic-related carbon emissions on elevated roads through on-road measurements. Environmental Research. 231(Pt 2). 116200–116200. 10 indexed citations
11.
He, Hong-di, et al.. (2023). Impact of urban viaducts on the vertical distribution of fine particles in street canyons. Atmospheric Pollution Research. 14(4). 101726–101726. 6 indexed citations
12.
Liu, Xin, et al.. (2023). Quantifying the effects of urban fabric and vegetation combination pattern to mitigate particle pollution in near-road areas using machine learning. Sustainable Cities and Society. 93. 104524–104524. 18 indexed citations
13.
He, Hong-di, Ziye Wang, Hongmei Zhao, Wei Pan, & Jane W. Z. Lu. (2023). Spatial-temporal distribution and pedestrian exposure assessment of size-fractionated particles on crosswalk of urban intersection. Environmental Science and Pollution Research. 30(35). 83917–83928. 2 indexed citations
14.
Li, Bai, et al.. (2022). Three-dimensional diffusion patterns of traffic-related air pollutants on the roadside based on unmanned aerial vehicles monitoring. Building and Environment. 219. 109159–109159. 14 indexed citations
15.
Wang, Zhanyong, et al.. (2021). Characterizing spatiotemporal distributions of black carbon and PM2.5 at a toll station: Observations on manual and electronic toll collection lanes. Building and Environment. 199. 107933–107933. 22 indexed citations
16.
Cao, Rong, Bai Li, Hongwei Wang, et al.. (2020). Vertical and Horizontal Profiles of Particulate Matter and Black Carbon Near Elevated Highways Based on Unmanned Aerial Vehicle Monitoring. Sustainability. 12(3). 1204–1204. 27 indexed citations
17.
Chen, Qian, Dongsheng Wang, Xiaobing Li, et al.. (2019). Vertical Characteristics of Winter Ozone Distribution within the Boundary Layer in Shanghai Based on Hexacopter Unmanned Aerial Vehicle Platform. Sustainability. 11(24). 7026–7026. 20 indexed citations
18.
He, Hong-di, et al.. (2018). Prediction of PM2.5 concentration based on the similarity in air quality monitoring network. Building and Environment. 137. 11–17. 58 indexed citations
19.
Wang, Zhanyong, et al.. (2018). Fine-scale variations in PM2.5 and black carbon concentrations and corresponding influential factors at an urban road intersection. Building and Environment. 141. 215–225. 77 indexed citations
20.
Ma, Zi‐Feng, Pan Zhang, & Hong-di He. (1999). GREENHOUSE GAS EMISSION FACTOR FOR COAL POWER CHAIN IN CHINA AND THE COMPARISON WITH NUCLEAR POWER CHAIN. 5 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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