공기괴 역궤적 모델의 통계 분석을 통한 이산화탄소 배출 지역 추정
Statistical Back Trajectory Analysis for Estimation of CO2 Emission Source Regions
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참고문헌
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초록
Statistical trajectory analysis has been widely used to identify potential sourceregions for chemically and radiatively important chemical species in the atmosphere. The mostwidely used method is a statistical source–receptor model developed by Stohl (1996), of whichthe underlying principle is that elevated concentrations at an observation site are proportionallyrelated to both the average concentrations on a specific grid cell where the observed airmass has been passing over and the residence time staying over that grid cell. Thus, the methodcan compute a residence-time-weighted mean concentration for each grid cell by superimposingthe back trajectory domain on the grid matrix. The concentration on a grid cell could beused as a proxy for potential source strength of corresponding species. This technical notedescribes the statistical trajectory approach and introduces its application to estimate potentialsource regions of CO2 enhancements observed at Korean Global Atmosphere Watch Observatoryin Anmyeon-do. Back trajectories are calculated using HYSPLIT 4 model based on windfields provided by NCEP GDAS. The identified CO2 potential source regions responsible forthe pollution events observed at Anmyeon-do in 2010 were mainly Beijing area and the NorthernChina where Haerbin, Shenyang and Changchun mega cities are located. This is consistentwith bottom-up emission information. In spite of inherent uncertainties of this method in estimatingsharp spatial gradients within the vicinity of the emission hot spots, this study suggeststhat the statistical trajectory analysis can be a useful tool for identifying anthropogenic potentialsource regions for major GHGs.
Abstract
Statistical trajectory analysis has been widely used to identify potential sourceregions for chemically and radiatively important chemical species in the atmosphere. The mostwidely used method is a statistical source–receptor model developed by Stohl (1996), of whichthe underlying principle is that elevated concentrations at an observation site are proportionallyrelated to both the average concentrations on a specific grid cell where the observed airmass has been passing over and the residence time staying over that grid cell. Thus, the methodcan compute a residence-time-weighted mean concentration for each grid cell by superimposingthe back trajectory domain on the grid matrix. The concentration on a grid cell could beused as a proxy for potential source strength of corresponding species. This technical notedescribes the statistical trajectory approach and introduces its application to estimate potentialsource regions of CO2 enhancements observed at Korean Global Atmosphere Watch Observatoryin Anmyeon-do. Back trajectories are calculated using HYSPLIT 4 model based on windfields provided by NCEP GDAS. The identified CO2 potential source regions responsible forthe pollution events observed at Anmyeon-do in 2010 were mainly Beijing area and the NorthernChina where Haerbin, Shenyang and Changchun mega cities are located. This is consistentwith bottom-up emission information. In spite of inherent uncertainties of this method in estimatingsharp spatial gradients within the vicinity of the emission hot spots, this study suggeststhat the statistical trajectory analysis can be a useful tool for identifying anthropogenic potentialsource regions for major GHGs.
참고문헌 (18)
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