미세먼지관리, 특성화대학원

Lab

Air Quality Big Data
Convergence Forecast
Modeling Lab.
(ABCFM)

새창으로 숨김 컨텐츠 열기 Air Quality Big Data Convergence Forecast Modeling Lab. (ABCFM)

Adviser Yoon-Seo Koo

  • "Korea Air Quality Forecasting System (KAQFS)" operating and upgrading of the real-time forecast system
  • Forecasting and diagnostic modeling on air quality, weather, emission and odor etc in regional and local region.
  • Analysis of big data for air quality forecasting
  • Developing the artificial intelligence air quality forecast model using machine learning(ML)
  • Assessment of contribution on air pollutants for air quality policy making by local governments.
Introduction
Air Quality Big Data Convergence Forecast Modeling Lab.(Suri Hall, room 212) is conducting research to predict air pollutant concentrations using big data, air chemical transport models, and artificial intelligence.

On-going research projects are as follows:

1) Development and operation of Korea Air Quality Forecasting System (http://kaq.or.kr/)
Developed by Eco-Technopia 21 Projects (Project title: A Development of air quality forecasting system package, research period: 2004.12-2007.11)
Started operating in 2007 and continuously operating and upgrading
Linux-based PC-cluster system built by WRF (v3.6.1), CMAQ (v4.7.1), and SMOKE (v2.7)
Forecast results are newly released twice daily (5:00 am and 3:00 pm KST).
Monitoring substances: PM10, PM2.5, O3, NO2, SO2

2) Development of short-term prediction tools for PMs using artificial intelligence
Development of artificial intelligence model for 3-days forecast of PM2.5 using measurement and forecasting model data such as weather, air quality etc.
Optimizing preprocess on big data for artificial intelligence forecasting model
Establishing and upgrading an artificial intelligence forecasting network in real-time prediction, and optimizing a convergence artificial intelligence model

3) Air pollution exposure data for Korea Disease Control and Prevention Agency
Establishing DB on exposure to air pollution for research on the cause of diseases and early deaths due to environmental factors such as climate change and air pollution and establishment of the preventive measures
Producing the data on exposure to air pollution in various spatiotemporal units (administrative unit/grid unit, day/month/year, etc.)
Data by chemical transport modeling using CMAQ (considering meteorological factors such as wind fields by time and space, temperature and humidity fields, and emissions by chemical speciation, time and space calculated in the emission model)
Complementing and verifying data on PM10, PM2.5, and O3 using satellite observation Aerosol Optical Depth (AOD) and multiple linear regression (MLR)

4) Establishment of measures for air pollution management by local governments
Analyzing environmental big data such as air pollution monitoring data and emission data of local governments
Estimating the concentration on air pollution in various spatiotemporal units (administrative unit/grid unit, day/month/year, etc.)
Assessment on the influence area of air pollution around local governments and industrial complexes
Setting a goal for improving air pollution level and estimation of reduction on air pollutant emissions

5) Contribution analysis of PM using chemical transport model in Northeast Asia
Analyzing the contribution of PM by regions & pollution sources using probing tool of a chemical transport model
Air quality assessment of emission reduction effect by air quality policy using chemical transport model
Professor
Head Professor : Yoon-Seo Koo
Professors : Hui-Young Yun, Dae-Ryun Choi
Researchers
Keun-Hye Shim, Kyung-Hui Wang, Chae-Yeon Lee, Joo-Yong Lee, Min-Woo Jung
Contact
Hui-Young Yun : huiyoung@anyang.ac.kr

Smart
Air Environmental
Monitoring
Lab.

숨김 컨텐츠 열기 Smart Air Environmental Monitoring Lab

Adviser Jin-Seok Han

  • Measurement and analysis of pollutants in the atmosphere
  • Sensor performance evaluation and SMART measurement
  • Reaction, formation and transformation mechanisms of fine particle and air pollutants in the atmosphere
  • Receptor Modeling of air pollutants
  • Air pollution monitoring network, air quality standard, and evaluation on air pollution management and policy
  • The characteristics of HAPs (hazardous air pollutants)
  • Odor measurement method and management policy
Introduction
Lab Location : Suri Hall, room 201-1 ( Suri Hall room 516, B05, B04)

Recent researches are as follows:

  • Measurement and analysis of pollutants in the atmosphere: sampling and analysis of fine particles, general air pollutants and hazardous air pollutants with complex mechanisms of formation
  • Sensor performance evaluation and SMART measurement: performance test of PM and gas sensors used in the field, evaluation of the sensor-type field monitoring system, maintenance for field application of IoT smart measurement system
  • Reaction, formation and transformation mechanisms of fine particle and air pollutants in the atmosphere; analyzing formation and reaction of precursors and air pollutants in the atmosphere using IC(Ion chromatography)
  • Receptor Modeling of air pollutants: identifying the source and estimating the contribution of emissions at the sampling site using receptor model, identifying the inflow pathways using the back trajectory model
  • Air pollution monitoring network, air quality standard, and evaluation on air pollution management and policy: proposal, review and evaluation of amendments (drafts) to air environment related standards and laws such as Official Air Pollution Test Method
  • The characteristics of HAPs (hazardous air pollutants): analysis of generation characteristics and sources of hazardous particulate and gaseous air pollutants
  • Odor measurement method and management policy: sampling and analyzing odor substances directly in the field using sensors and odor substance analyzers, etc., real-time analysis using high-resolution equipment such as PTR-ToF-Ms, proposal, review and evaluation of amendments (drafts) to odor-related standards laws such as Official Odor Compounds Test Method
Faculty and Professor
Head Professor : Jin-Seok Han
Doctoral program : Sang-Woo Han, Yong-Gu Lee, Chun-Sang Lee, Kyung-Chan Kim
Master's program : Byeong-Hoon Oh, Hyeon-Seop Kim, Da-Young Choi, Hee-Jun Song
Undergraduate : Seung-Hyeon Bang, Yu-Jin Joo, Shin-Woo Kim
Contact
gguniangs@naver.com
nierhan@hanmail.net

Smart
Air Emission
Monitoring
Lab.
(SAEM)

숨김 컨텐츠 열기 Smart Air Emission Monitoring Lab. (SAEM)

Adviser Hung-Soo Joo

  • Monitoring of air pollutants
  • Measurement of odor substances such as ammonia and hydrogen sulfide
  • Performance test of IoT sensor and application of smart measurement
  • Development of methodology for air emission load
  • Toxicity test of particulate matter and gaseous compounds (Oxidative potential)
Introduction
Office and Laboratory : Suri Hall, room Room 213 & B05

On-going research projects are as follows:

  • Monitoring of air pollutants such as PMs: sampling and PM2.5 physicochemical analysis and measurement of gaseous pollutants generated by various sources
  • Measurement of odor substances such as ammonia and hydrogen sulfide: field sampling and analysis of odor samples real-time measurement of odorants and VOCs using a high-resolution measurement equipment
  • Performance test of IoT sensor and application of smart measurement: performance test of odorants and air pollutant measurement sensors, test of the sensor monitoring system, maintenance for field application of IoT smart measurement system
  • Development of methodology for air emission: development of PM2.5 emission factor produced from various sources, calculation of ammonia emissions from agricultural area sector and improvement of calculation method, improvement and development of methodology for estimating air emissions
  • Toxicity test of particulate matter and gaseous compounds (Oxidative potential): chemical toxicity test of fine particles using OP-DTT and OP-ESR
Professor
Head Professor : Hung-Soo Joo
Contact
dlalgkrdlrms1@gmail.com
hjoo@anyang.ac.kr
특성화대학원, 미세먼지관리