Journal of the Korean Association of Geographic Information Studies (한국지리정보학회지)

The Korean Association of Geographic Information Studies (한국지리정보학회)
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Improved Estimation of Hourly Surface Ozone Concentrations using Stacking Ensemble-based Spatial Interpolation

스태킹 앙상블 모델을 이용한 시간별 지상 오존 공간내삽 정확도 향상

  • KIM, Ye-Jin (Dept. of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • KANG, Eun-Jin (Dept. of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • CHO, Dong-Jin (Dept. of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • LEE, Si-Woo (Dept. of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • IM, Jung-Ho (Dept. of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology)
  • 김예진 (울산과학기술원 도시환경공학부) ;
  • 강은진 (울산과학기술원 도시환경공학부) ;
  • 조동진 (울산과학기술원 도시환경공학부) ;
  • 이시우 (울산과학기술원 도시환경공학부) ;
  • 임정호 (울산과학기술원 도시환경공학부)
  • Received : 2022.09.07
  • Accepted : 2022.09.18
  • Published : 2022.09.30
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Abstract

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

지상 오존은 차량 및 산업 현장에서 배출된 질소화합물(Nitrogen oxides; NOx)과 휘발성 유기화합물(Volatile Organic Compounds; VOCs)의 광화학 반응을 통해 생성되어 식생 및 인체에 악영향을 끼친다. 국내에서는 실시간 오존 모니터링을 수행하고 있지만 관측소 기반으로, 미관측 지역의 공간 분포 분석에 어려움이 있다. 본 연구에서는 스태킹 앙상블 기법을 활용하여 매시간 남한 지역의 지상 오존 농도를 1.5km의 공간해상도로 공간내삽하였고, 5-fold 교차검증을 수행하였다. 스태킹 앙상블의 베이스 모델로는 코크리깅(Cokriging), 다중 선형 회귀(Multi-Linear Regression; MLR), 랜덤 포레스트(Random Forest; RF), 서포트 벡터 회귀(Support Vector Regression; SVR)를 사용하였다. 각 모델의 정확도 비교 평가 결과, 스태킹 앙상블 모델이 연구 기간 내 시간별 평균 R 및 RMSE이 0.76, 0.0065ppm으로 가장 높은 성능을 보여주었다. 스태킹 앙상블 모델의 지상 오존 농도 지도는 복잡한 지형 및 도시화 변수의 특징이 잘 드러나며 더 넓은 농도 범위를 보여주었다. 개발된 모델은 매시간 공간적으로 연속적인 공간 지도를 산출할 수 있을 뿐만 아니라 8시간 평균치 산출 및 시계열 분석에 있어서도 활용 가능성이 클 것으로 기대된다.

Keywords

Acknowledgement

이 논문은 2022년도 정부(해양수산부)의 재원으로 해양수산과학기술진흥원-과학기술기반 해양환경영향평가 기술개발사업 지원을 받았으며 (KIMST-20210427), 환경부의 재원으로 한국환경산업기술원의 환경보건디지털 조사기반 구축 기술개발사업의 지원을 받아 연구되었습니다(2021003330001(NTIS: 1485017948))

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