수도권 초미세먼지 농도모사: (III) 관측농도 대비 모사농도 비율 적용에 따른 기여도 변화 검토

PM2.5 Simulations for the Seoul Metropolitan Area: (III) Application of the Modeled and Observed PM2.5 Ratio on the Contribution Estimation

  • 배창한 (아주대학교 환경안전공학과) ;
  • 유철 (환경부 대기환경정책과) ;
  • 김병욱 (미국조지아주환경청) ;
  • 김현철 (미국국립해양대기청) ;
  • 김순태 (아주대학교 환경안전공학과)
  • Bae, Changhan (Department of Environmental & Safety Engineering, Ajou University) ;
  • Yoo, Chul (Air Quality Policy Division, Ministry of Environment) ;
  • Kim, Byeong-Uk (Georgia Environmental Protection Division) ;
  • Kim, Hyun Cheol (Air Resources Laboratory, National Oceanic and Atmospheric Administration) ;
  • Kim, Soontae (Department of Environmental & Safety Engineering, Ajou University)
  • 투고 : 2017.05.11
  • 심사 : 2017.08.09
  • 발행 : 2017.10.31


In this study, we developed an approach to better account for uncertainties in estimated contributions from fine particulate matter ($PM_{2.5}$) modeling. Our approach computes a Concentration Correction Factor (CCF) which is a ratio of observed concentrations to baseline model concentrations. We multiply modeled direct contribution estimates with CCF to obtain revised contributions. Overall, the modeling system showed reasonably good performance, correlation coefficient R of 0.82 and normalized mean bias of 2%, although the model underestimated some PM species concentrations. We also noticed that model biases vary seasonally. We compared contribution estimates of major source sectors before and after applying CCFs. We observed that different source sectors showed variable magnitudes of sensitivities to the CCF application. For example, the total primary $PM_{2.5}$ contribution was increased $2.4{\mu}g/m^3$ or 63% after the CCF application. Out of a $2.4{\mu}g/m^3$ increment, line sources and area source made up $1.3{\mu}g/m^3$ and $0.9{\mu}g/m^3$ which is 92% of the total contribution changes. We postulated two major reasons for variations in estimated contributions after the CCF application: (1) monthly variability of unadjusted contributions due to emission source characteristics and (2) physico-chemical differences in environmental conditions that emitted precursors undergo. Since emissions-to-$PM_{2.5}$ concentration conversion rate is an important piece of information to prioritize control strategy, we examined the effects of CCF application on the estimated conversion rates. We found that the application of CCFs can alter the rank of conversion efficiencies of source sectors. Finally, we discussed caveats of our current approach such as no consideration of ion neutralization which warrants further studies.


연구 과제 주관 기관 : 국립환경과학원


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피인용 문헌

  1. Impact of Emission Inventory Choices on PM10 Forecast Accuracy and Contributions in the Seoul Metropolitan Area vol.33, pp.5, 2017,