Jae-Bum Lee

745 total citations
41 papers, 503 citations indexed

About

Jae-Bum Lee is a scholar working on Atmospheric Science, Health, Toxicology and Mutagenesis and Environmental Engineering. According to data from OpenAlex, Jae-Bum Lee has authored 41 papers receiving a total of 503 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Atmospheric Science, 26 papers in Health, Toxicology and Mutagenesis and 19 papers in Environmental Engineering. Recurrent topics in Jae-Bum Lee's work include Atmospheric chemistry and aerosols (33 papers), Air Quality and Health Impacts (25 papers) and Air Quality Monitoring and Forecasting (19 papers). Jae-Bum Lee is often cited by papers focused on Atmospheric chemistry and aerosols (33 papers), Air Quality and Health Impacts (25 papers) and Air Quality Monitoring and Forecasting (19 papers). Jae-Bum Lee collaborates with scholars based in South Korea, United States and Austria. Jae-Bum Lee's co-authors include Chang‐Keun Song, Jung‐Hun Woo, Chang‐Hoi Ho, Youn-Seo Koo, Lim‐Seok Chang, Jinwon Kim, Rokjin J. Park, Younha Kim, Sung-Chul Hong and Jin‐Seok Han and has published in prestigious journals such as The Science of The Total Environment, Scientific Reports and Environmental Pollution.

In The Last Decade

Jae-Bum Lee

39 papers receiving 450 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jae-Bum Lee South Korea	12	379	282	205	186	66	41	503
G. Calori Italy	12	319 0.8×	367 1.3×	149 0.7×	231 1.2×	94 1.4×	29	533
Laurent Létinois France	8	252 0.7×	201 0.7×	160 0.8×	92 0.5×	50 0.8×	13	344
C. Cuvelier Italy	6	416 1.1×	378 1.3×	174 0.8×	168 0.9×	136 2.1×	6	509
Junxi Zhang China	9	218 0.6×	235 0.8×	107 0.5×	166 0.9×	45 0.7×	13	388
Alex Gbaguidi China	11	489 1.3×	345 1.2×	315 1.5×	177 1.0×	51 0.8×	16	579
Jin Shen China	12	285 0.8×	286 1.0×	104 0.5×	194 1.0×	43 0.7×	21	418
Beiyao Xu China	8	321 0.8×	295 1.0×	139 0.7×	194 1.0×	45 0.7×	9	431
Ting Qiao China	8	329 0.9×	382 1.4×	84 0.4×	199 1.1×	110 1.7×	10	482
Yvonne Scorgie Australia	12	193 0.5×	199 0.7×	169 0.8×	143 0.8×	44 0.7×	20	374
Haseeb Hakkim India	11	229 0.6×	225 0.8×	113 0.6×	107 0.6×	65 1.0×	26	369

Countries citing papers authored by Jae-Bum Lee

Since Specialization

Citations

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

Fields of papers citing papers by Jae-Bum Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae-Bum Lee. 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 Jae-Bum Lee. The network helps show where Jae-Bum Lee may publish in the future.

Co-authorship network of co-authors of Jae-Bum Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Jae-Bum Lee. A scholar is included among the top collaborators of Jae-Bum Lee 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 Jae-Bum Lee. Jae-Bum Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Woo, Jung‐Hun, Younha Kim, Yongmi Lee, et al.. (2024). Development of a greenhouse gas - air pollution interactions and synergies model for Korea (GAINS-Korea). Scientific Reports. 14(1). 3372–3372. 2 indexed citations

Kim, Jinseok, et al.. (2023). Update of the year 2019 modeling emission inventory in China. Asian Journal of Atmospheric Environment. 17(1). 3 indexed citations

Hong, Sung-Chul, et al.. (2023). Modeling of Organic Aerosol in Seoul Using CMAQ with AERO7. Atmosphere. 14(5). 874–874. 7 indexed citations

Lee, Hyo‐Jung, Lim‐Seok Chang, Daniel A. Jaffe, et al.. (2022). Satellite-Based Diagnosis and Numerical Verification of Ozone Formation Regimes over Nine Megacities in East Asia. Remote Sensing. 14(5). 1285–1285. 16 indexed citations

Lee, Jae-Bum, et al.. (2022). Development of a deep neural network for predicting 6 h average PM _2.5 concentrations up to 2 subsequent days using various training data. Geoscientific model development. 15(9). 3797–3813. 11 indexed citations

Ho, Chang‐Hoi, et al.. (2022). PM2.5 Forecast in Korea using the Long Short-Term Memory (LSTM) Model. Asia-Pacific Journal of Atmospheric Sciences. 59(5). 563–576. 23 indexed citations

Jeong, Jee‐Hoon, Sung‐Ho Woo, Sang‐Woo Kim, et al.. (2022). A novel statistical-dynamical method for a seasonal forecast of particular matter in South Korea. The Science of The Total Environment. 848. 157699–157699. 9 indexed citations

Yoo, Changhyun, Sang‐Wook Yeh, Jin‐Ho Yoon, et al.. (2022). Statistical Seasonal Forecasting of Winter and Spring PM2.5 Concentrations Over the Korean Peninsula. Asia-Pacific Journal of Atmospheric Sciences. 58(4). 549–561. 9 indexed citations

Lee, Hyo‐Jung, Lim‐Seok Chang, Daniel A. Jaffe, et al.. (2021). Ozone Continues to Increase in East Asia Despite Decreasing NO2: Causes and Abatements. Remote Sensing. 13(11). 2177–2177. 36 indexed citations

10.

Lee, Jae-Bum, et al.. (2021). Crop Residue Burning in Northeast China and Its Impact on PM2.5 Concentrations in South Korea. Atmosphere. 12(9). 1212–1212. 7 indexed citations

11.

Lee, Jae-Bum, et al.. (2021). Development of a deep neural network for predicting 6-hour average PM _2.5 concentrations up to two subsequent days using various training data. 1 indexed citations

12.

Lee, Jae-Bum, et al.. (2021). Development of a deep neural network for predicting 6-hour average PM2.5 concentrations up to two subsequent days using various training data. Zenodo (CERN European Organization for Nuclear Research).

13.

Kim, Hyun Cheol, Changhan Bae, Minah Bae, et al.. (2020). Space-Borne Monitoring of NOx Emissions from Cement Kilns in South Korea. Atmosphere. 11(8). 881–881. 18 indexed citations

14.

Choi, Won Jun, et al.. (2019). Power Generation Performance of Building-Integrated Photovoltaic Systems in a Zero Energy Building. Energies. 12(13). 2471–2471. 9 indexed citations

15.

Lee, Jae-Bum, Jung‐Hun Woo, Sung-Chul Hong, et al.. (2017). Development of an Emissions Processing System for Climate Scenario Inventories to Support Global and Asian Air Quality Modeling Studies. Asian Journal of Atmospheric Environment. 11(4). 330–343. 1 indexed citations

16.

Ho, Chang‐Hoi, et al.. (2016). Evaluating the predictability of PM10 grades in Seoul, Korea using a neural network model based on synoptic patterns. Environmental Pollution. 218. 1324–1333. 28 indexed citations

17.

Koo, Youn-Seo, et al.. (2016). The Effect of Dust Emissions on PM<sub>10</sub> Concentration in East Asia. Journal of Korean Society for Atmospheric Environment. 32(1). 32–45. 8 indexed citations

18.

Kim, Minjoong J., Rokjin J. Park, Chang-Hoi Ho, et al.. (2014). Future ozone and oxidants change under the RCP scenarios. Atmospheric Environment. 101. 103–115. 40 indexed citations

19.

Choi, Jin, Seungyeon Kim, Sung-Chul Hong, et al.. (2012). Evaluation of Temperature and Precipitation on Integrated Climate and Air Quality Modeling System (ICAMS) for Air Quality Prediction. Journal of Korean Society for Atmospheric Environment. 28(6). 615–631. 4 indexed citations

20.

Kim, Seungyeon, et al.. (2011). Analysis of the Characteristics and High Concentrations of Carbon Dioxide Measured at the Gosan Site in Jeju, Korea in 2007. Journal of Climate Change Research. 2(1). 1–14. 3 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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