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논문 기본 정보

자료유형
학술저널
저자정보
주혜지 (아주대학교) 김현철 (미국국립해양대기청) 김병욱 (미국조지아주환경청) 김영성 (한국외국어대학교) 신혜정 (국립환경과학원) 김순태 (아주대학교)
저널정보
한국대기환경학회 한국대기환경학회지(국문) 한국대기환경학회지 제34권 제1호
발행연도
2018.2
수록면
101 - 119 (19page)
DOI
10.5572/KOSAE.2018.34.1.101

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초록· 키워드

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In this study, we analyzed long-term measurements and air quality simulation results of four criteria air pollutants (PM<SUB>10</SUB>, O₃, NO₂, and SO₂) for 10 years, from 2006 to 2015, with emphasis on trends of annual variabilities. With the observation data, we conducted spatial interpolation using the Kriging method to estimate spatial distribution of pollutant concentrations. We also performed air quality simulations using the CMAQ model to consider the nonlinearity of the secondary air pollutants such as O₃ and the influence of long-range transport. In addition, these simulations are used to deduce the effect of long-term meteorological variations on trends of air quality changes because we fixed the emissions inventory while changing meteorological inputs. The nation-wide inter-annual variability of modeled PM<SUB>10</SUB> concentrations was - 0.11 μg/㎥/yr, while that of observed concentrations was - 0.84 μg/㎥/yr. For the Seoul Metropolitan Area, the inter-annual variability of observed PM<SUB>10</SUB> concentrations was - 1.64 μg/m3/yr that is two times rapid improvement compared to other regions. On the other hand, the interannual variability of observed O₃ concentrations is 0.62 ppb/yr which is larger than the simulated result of 0.13 ppb/yr. Magnitudes of differences between the modeled and observed inter-annual variabilities indicated that decreasing trend of PM<SUB>10</SUB> and increasing trend of O₃ are more influenced by emissions and oxidation states than meteorological conditions. We also found similar patterns in NO₂. However, NO₂ trends showed greater regional and seasonal differences than other pollutants. The analytic approach used in this study can be applicable to estimate changes in factors determining air quality such as emissions, weather, and surrounding conditions over a long term. Then analysis results can be used as important data for air quality management planning and evaluation of the chronic impact of air quality.

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Abstract
1. 서론
2. 연구 방법
3. 결과 및 고찰
4. 결론
References

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UCI(KEPA) : I410-ECN-0101-2018-539-001825359