Soon-Bark Kwon

1.7k total citations
79 papers, 1.4k citations indexed

About

Soon-Bark Kwon is a scholar working on Automotive Engineering, Health, Toxicology and Mutagenesis and Electrical and Electronic Engineering. According to data from OpenAlex, Soon-Bark Kwon has authored 79 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Automotive Engineering, 26 papers in Health, Toxicology and Mutagenesis and 17 papers in Electrical and Electronic Engineering. Recurrent topics in Soon-Bark Kwon's work include Vehicle emissions and performance (27 papers), Air Quality and Health Impacts (24 papers) and Aerosol Filtration and Electrostatic Precipitation (14 papers). Soon-Bark Kwon is often cited by papers focused on Vehicle emissions and performance (27 papers), Air Quality and Health Impacts (24 papers) and Aerosol Filtration and Electrostatic Precipitation (14 papers). Soon-Bark Kwon collaborates with scholars based in South Korea, Japan and Spain. Soon-Bark Kwon's co-authors include Duckshin Park, Youngmin Cho, Ki‐Tae Kim, Kyung Hwa Cho, Takafumi Seto, Sechan Park, K.W. Lee, Wootae Jeong, Chungyoon Chun and K.S. Lim and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and The Science of The Total Environment.

In The Last Decade

Soon-Bark Kwon

72 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Soon-Bark Kwon South Korea 19 577 441 423 234 197 79 1.4k
Yu–Hsiang Cheng Taiwan 22 1.0k 1.8× 524 1.2× 529 1.3× 179 0.8× 446 2.3× 64 1.5k
Mats Bohgard Sweden 23 1.3k 2.3× 398 0.9× 559 1.3× 181 0.8× 534 2.7× 95 2.2k
Tracy L. Thatcher United States 13 1.1k 1.8× 555 1.3× 190 0.4× 73 0.3× 356 1.8× 21 1.5k
Farhad Salimi Australia 21 882 1.5× 379 0.9× 338 0.8× 51 0.2× 356 1.8× 45 1.5k
Mauro Scungio Italy 17 427 0.7× 326 0.7× 178 0.4× 47 0.2× 64 0.3× 36 894
Neyval Costa Reis Brazil 21 610 1.1× 562 1.3× 140 0.3× 67 0.3× 272 1.4× 82 1.3k
Milan Jamriska Australia 18 741 1.3× 369 0.8× 339 0.8× 133 0.6× 331 1.7× 42 1.0k
Wen-Yinn Lin Taiwan 21 710 1.2× 194 0.4× 327 0.8× 218 0.9× 334 1.7× 49 1.4k
Zhuangbo Feng China 29 542 0.9× 967 2.2× 99 0.2× 524 2.2× 116 0.6× 83 2.3k
Marco Dell’Isola Italy 28 420 0.7× 696 1.6× 77 0.2× 266 1.1× 63 0.3× 104 2.2k

Countries citing papers authored by Soon-Bark Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Soon-Bark Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soon-Bark Kwon. 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 Soon-Bark Kwon. The network helps show where Soon-Bark Kwon may publish in the future.

Co-authorship network of co-authors of Soon-Bark Kwon

This figure shows the co-authorship network connecting the top 25 collaborators of Soon-Bark Kwon. A scholar is included among the top collaborators of Soon-Bark Kwon 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 Soon-Bark Kwon. Soon-Bark Kwon 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.
Ko, Sangwon, Wootae Jeong, Duckshin Park, & Soon-Bark Kwon. (2019). Numerical analysis of droplets exhaled by train cabin passengers. Journal of Odor and Indoor Environment. 18(2). 131–139. 4 indexed citations
2.
Kwon, Soon-Bark, et al.. (2018). Effect of train velocity on the amount of airborne wear particles generated from wheel–rail contacts. Wear. 414-415. 296–302. 13 indexed citations
3.
Woo, Sang-Hee, et al.. (2018). Size-dependent characteristics of diurnal particle concentration variation in an underground subway tunnel. Environmental Monitoring and Assessment. 190(12). 740–740. 5 indexed citations
4.
Park, Sechan, et al.. (2017). Estimation of inhaled airborne particle number concentration by subway users in Seoul, Korea. Environmental Pollution. 231(Pt 1). 663–670. 13 indexed citations
5.
Park, Sechan, et al.. (2017). Study on the optimal design of floor exhaust system using computational fluid dynamics for subway platform. Journal of the Korea Academia-Industrial cooperation Society. 18(2). 443–449. 1 indexed citations
6.
Park, Sechan, et al.. (2017). Predicting PM10 concentration in Seoul metropolitan subway stations using artificial neural network (ANN). Journal of Hazardous Materials. 341. 75–82. 139 indexed citations
7.
Kim, Minsoo, Sechan Park, Sang-Hee Woo, et al.. (2016). Size distribution analysis of airborne wear particles released by subway brake system. Wear. 372-373. 169–176. 30 indexed citations
8.
Park, Duckshin, et al.. (2016). Effect of a fuel activation device (FAD) on particulate matter and black carbon emissions from a diesel locomotive engine. The Science of The Total Environment. 575. 97–102. 10 indexed citations
9.
Kwon, Soon-Bark, et al.. (2016). Transient variation of aerosol size distribution in an underground subway station. Environmental Monitoring and Assessment. 188(6). 362–362. 17 indexed citations
10.
Park, Duckshin, Yongil Lee, Wootae Jeong, et al.. (2016). Economic analysis of particulate matter control technologies used in a subway. Journal of Odor and Indoor Environment. 15(1). 46–52. 1 indexed citations
11.
Lee, Jaeyoung, et al.. (2013). Investigation on CO Adsorption and Catalytic Oxidation of Commercial Impregnated Activated Carbons. Applied Chemistry for Engineering. 24(5). 513–517. 2 indexed citations
12.
Kwon, Soon-Bark, et al.. (2013). Effect of Ventilation Type on the Trajectory of Coughed Particles in a Hospital Ward. 9(2). 59–67. 1 indexed citations
13.
Park, Duckshin, Soon-Bark Kwon, Youngmin Cho, et al.. (2012). Reduction of Particulate Matters Levels in Railway Cabins in Korea. Korean Journal of Environmental Health Sciences. 38(1). 51–56. 1 indexed citations
14.
Jeong, Wootae, et al.. (2012). Design of an intelligent duct cleaning robot with force compliant brush. International Conference on Control, Automation and Systems. 2033–2037. 4 indexed citations
15.
Park, Duckshin, et al.. (2012). The effects of operating conditions on particulate matter exhaust from diesel locomotive engines. The Science of The Total Environment. 419. 76–80. 20 indexed citations
16.
Kwon, Soon-Bark & Changsoo Kim. (2010). Review of Recent Studies on the Airborne Infection. 6(2). 81–90.
17.
Kwon, Soon-Bark, et al.. (2004). An Experimental Study of Underexpanded Moist Air Jet Impinging on a Flat Plate. 한국추진공학회 학술대회논문집. 768–773. 3 indexed citations
18.
Song, Chen, et al.. (2004). Study on Size Distribution of Total Aerosol and Water-Soluble Ions During an Asian Dust Storm Event at Jeju Island, Korea. Environmental Monitoring and Assessment. 93(1-3). 157–183. 56 indexed citations
19.
Kwon, Soon-Bark, et al.. (1992). A STUDY ON SUPERSONIC FLOW WITH CONDENSATION ALONG A WAVY WALL IN CHANNEL. 1298–1301. 1 indexed citations
20.
Kwon, Soon-Bark, et al.. (1990). The Post-Shock Expansion in a Supersonic Nozzle. 52–57. 1 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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