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Estimation of Representative Area-Level Concentrations of Particulate Matter(PM10) in Seoul, Korea

미세먼지(PM10)의 지역적 대푯값 산정 방법에 관한 연구 - 서울특별시를 대상으로

  • SONG, In-Sang (Department of Geography, Seoul National University) ;
  • KIM, Sun-Young (Institute of Health and Environment, Seoul National University)
  • Received : 2016.09.27
  • Accepted : 2016.11.22
  • Published : 2016.12.31

Abstract

Many epidemiological studies, relying on administrative air pollution monitoring data, have reported the association between particulate matter ($PM_{10}$) air pollution and human health. These monitoring data were collected at a limited number of fixed sites, whereas government-generated health data are aggregated at the area level. To link these two data types for assessing health effects, it is necessary to estimate area-level concentrations of $PM_{10}$. In this study, we estimated district (Gu)-level $PM_{10}$ concentrations using a previously developed pointwise exposure prediction model for $PM_{10}$ and three types of point locations in Seoul, Korea. These points included 16,230 centroids of the largest census output residential areas, 422 community service centers, and 610 centroids on the 1km grid. After creating three types of points, we predicted $PM_{10}$ annual average concentrations at all locations and calculated Gu averages of predicted $PM_{10}$ concentrations as representative Gu-estimates. Then, we compared estimates to each other and to measurements. Prediction-based Gu-level estimates showed higher correlations with measurement-based estimates as prediction locations became more population representative ($R^2=0.06-0.59$). Among the three estimates, grid-based estimates gave lowest correlations compared to the other two(0.35-0.47). This study provides an approach for estimating area-level air pollution concentrations and assesses air pollution health effects using national-scale administrative health data.

미세먼지($PM_{10}$)의 건강영향에 대한 많은 연구들은 정부의 대기오염 측정자료를 이용해서 악영향을 보고했다. 정부 대기오염 측정자료가 제한된 수의 측정소에서 생산되는 반면, 사망률이나 유병률과 같은 정부생산 건강결과 자료는 지역별로 집계되어 공개된다. 따라서 정부에서 생산하는 건강통계자료를 이용해서 건강영향을 분석하기 위해서는, $PM_{10}$ 농도의 지역적인 대푯값을 산출할 필요가 있다. 본 연구에서는 서울특별시를 대상으로 이전 연구에서 개발된 점 사상에 대한 $PM_{10}$ 농도 예측 모형을 이용하여 구별 대푯값을 산정하였다. 이를 위해, 세 가지 종류의 위치들을 대상으로 지점들을 생성한 후, 그 지점들에 예측한 $PM_{10}$ 농도의 구별 평균으로 구별 대푯값을 구했다. 세 가지 위치는 16,230개 집계구 내 가장 넓은 주거지역의 중심점, 424개 동 주민센터, 610개 1km 격자의 중심점이었다. 위치별 구별 대푯값들을 비교하기 위하여 측정치와의 관련성 및 추정치 간 관련성을 탐색하였다. 측정치와의 비교 결과, 측정치와 세 가지 구별 대푯값 추정치들 간의 관련성은 위치의 인구 대표성이 높아짐에 따라 향상되었고($R^2=0.06-0.59$), 상호비교에서는 격자 중심점을 이용한 추정치가 다른 추정치들과의 관련성이 상대적으로 낮았다(0.35-0.47). 본 연구는 $PM_{10}$의 지역별 평균 농도를 추정함으로써 향후 정부 통계에 기반한 전국 규모의 지역 단위 건강영향분석 연구에 기여할 수 있을 것으로 기대된다.

Keywords

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