About the Journal | Editor Board | Guide for Authors | Journal Issue | Submission |
Sorry.
You are not permitted to access the full text of articles.
If you have any questions about permissions,
please contact the Society.
์ฃ์กํฉ๋๋ค.
ํ์๋์ ๋ ผ๋ฌธ ์ด์ฉ ๊ถํ์ด ์์ต๋๋ค.
๊ถํ ๊ด๋ จ ๋ฌธ์๋ ํํ๋ก ๋ถํ ๋๋ฆฝ๋๋ค.
Editor-In-Chief | Rokjin Park (Seoul National University) |
---|---|
Manuscript | Sang-Woo Kim |
Editor | (Seoul National University) |
Editorial office | ![]() |
![]() |
|
![]() |
|
ISSN | 1598-7132(Print) |
2383-5346(Online) | |
Indexed in SCOPUS/KCI Excellence Accredited Journal/Emerging Sources Citation Index (ESCI) |
The Journal of Korean Society for Atmospheric Environment is the official Journal of Koran Society for Atmospheric Environment. The abbreviated title is โJ. Korean Soc. Atmos. Environ.โ It was launched in 1985 under the title of โJournal of Korea Air Pollution Research Associationโ. The title was changed to โJournal of Korean Society for Atmospheric Environmentโ in 1999. It is a multidisciplinary forum for the publication of original researches relevant to the nature, distribution, control technology, and ecological effects of all types and forms of chemical and biological constituents as well as physical phenomena in the atmosphere and between the atmosphere and other environmental spheres. It publishes research articles, review articles, technical information, special features, and discussion and reply. Journals are scheduled to be published on the last days of February, April, June, August, October, and December each year. All articles published in this journal are indexed in Emerging Sources Citation Index(ESCI) of the web of Science Core Collection and DOI/Crossref.
J. Korean Soc. Atmos. Environ is devoted to the advancement of knowledge in the fields listed below.
- Atmospheric measurements and analysis
- Current status and management
- Dispersion and reaction
- Control technology
- Climate Change and Energy
- Human and ecosystem impact
- Indoor air quality
- Other related fields
Five types of manuscripts are published in this journal:
(1) Research papers, (2) Review papers, (3) Technical information, (4) Special features, and (5) Discussion and Reply.
(1) Research Papers:
Original findings pertaining to the scope of the journal will be published after editorial review. In full-length research articles, authors should present new experimental or theoretical results of significant importance.
(2) Review Papers:
Authoritative review can be published either by the invitation or by direct submission. In both cases, the work will be subject to a peer-review. The review article should include a critical review of important areas in atmospheric science and engineering in order to inform the general reader of the background, state-of-the art, and outstanding research works.
(3) Technical Information:
A report, which includes relevant analytical or treatment information, new experimental elaboration on previous journal articles, etc, with a brief piece of work, although not sufficiently comprehensive for a full article, can be published as technical information.
(4) Special Features:
Special features will be published by invitation only and will be on atmospheric environmental topics judged to be important by editorial board.
(5) Discussions and Reply:
Opinion and comments on the contents of articles published in Journal of Korean Society for Atmospheric Environment within one year period can be published as discussions and reply.
Volume 41(3); June 2025
Research Trends on Enhancing the Collection Efficiency of Electrostatic Precipitators
Myong-Hwa Lee, Jong-Ho Kim
Electrostatic precipitators (ESPs) are extensively utilized for removing particulate matter exhausted from industrial facilities due to their high collection ef...
Modeling of Secondary Air Pollutants in East Asia: Recent Trends and Future Challenges
Seung-Mi Kim, Yeri Kang, Kwon-ho Jeon, Jong-Jae Lee, Chang-Keun Song
The rapid economic and industrial development in East Asia has led to a significant increase in precursor gas emissions, exacerbating secondary air pollution an...
Jimin Kim, Minseo Choi, Yeji Jeon, Taehee Kim, Kyung-Hwan Kwak, Greem Lee, Byeong-Cheol Kang, Sun-A Jung
PM compositions are important indicators for identifying emission sources and formation pathways of particulate matters in the atmosphere. In Korea, the Ministr...
Chang-Jin Ma, Gong-Unn Kang
In March 2025, South Korea experienced massive wildfires in the Gyeongbuk region, resulting in the destruction of approximately 48,239 hectares of forested land...
Jongbyeok Jun, Jihae Shim, Seok-Jun Seo, Junhyun Park, Myounghwa Byun
This study analyzes the long-term trends and source contributions of black carbon (BC) in South Korea using Aethalometer measurements collected from Baengnyeong...
Time-resolved Analysis of Ozone Precursor Influx Using Box Model-based Data Assimilation Techniques
Jeonghwan Kim, Giwan Kim, Joon-Young Ahn, Limseok Chang, Gangwoong Lee
Accurate representation of precursor emissions and photochemical processes is essential for improving ozone (Oโ) simulations in air quality models. In this stud...
Eunho Park, Jongheon Han, Hee-Jung Yoo, Se-Hwan Yang, Sumin Kim, Young-Ah Kim, Dukjin Won, Man-Hae Kim, Sang-Woo Kim
This study examines the seasonal characteristics of particle number size distribution and new particle formation using 20-year dataset (2005-2024) from Scanning...
Okhwa Hwang, Jun Yeob Lee, Junsu Park
This study evaluated the effect of applying fermented liquid fertilizer to the pit of a pig barn on ammonia reduction and analyzed slurry characteristics to ide...
PM2.5 Vulnerability Areas Analysis Using Deep Neural Network: Application to Seoul City
Moonjo Park, Yekyeong Lee, Yeonjoon Kim, Donghee Jung, Changjung An, Hyung-Sup Jung
Fine particulate matter (PM), defined as particles with a diameter of 2.5 micrometers or less, poses significant health risks as it can penetrate alveoli upon i...
Seong-il Lee, Dong Hun Lee, Hyo-Jong Song, Joon-Young Ahn, Seung-Myung Park, Jaeyun Lee
This study aims to improve the prediction accuracy of PM concentrations by applying ensemble machine learning techniques and the Kalman Filter (KF), using detai...