• 한국환경과학회지
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• 제26권2호
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• pp.221-230
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• 2017

To determine the effect of air pollution reduction policies, the long-term trend of air pollutants should be analyzed. Kolmogorov-Zurbenko (KZ) filter is a low-pass filter, produced through repeated iterations of a moving average to separate each variable into its temporal components. The moving average for a KZ(m, p) filter is calculated by a filter with window length m and p iterations. The output of the first pass subsequently becomes the input for the next pass. Adjusting the window length and the number of iterations makes it possible to control the filtering of different scales of motion. To break down the daily mean $PM_{10}$ into individual time components, we assume that the original time series comprises of a long-term trend, seasonal variation, and a short-term component. The short-term component is attributable to weather and short-term fluctuations in precursor emissions, while the seasonal component is a result of changes in the solar angle. The long-term trend results from changes in overall emissions, pollutant transport, climate, policy and/or economics. The long-term trend of the daily mean $PM_{10}$ decreased sharply from $59.6ug/m^3$ in 2002 to $44.6ug/m^3$ in 2015. This suggests that there was a long-term downward trend since 2005. The difference between the unadjusted and meteorologically adjusted long-term $PM_{10}$ is small. Therefore, we can conclude that $PM_{10}$ is unaffected by the meteorological variables (total insolation, daily mean temperature, daily mean relative humidity, daily mean wind speed, and daily mean local atmospheric pressure) in Busan.

• 한국대기환경학회지
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• 제24권1호
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• pp.63-71
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• 2008

Local meteorological conditions exert a strong influence over day-to-day variations in air pollutant concentrations. Therefore, the meteorological fluctuations have to be removed in order for air quality planners and managers to examine underlying emissions-related trends and make better air quality management decisions for future. In this study, the meteorologically adjusted $PM_{10}$ trends in Seoul are investigated over the period $1999{\sim}2006$ using Kolmogorov-Zurbenco (KZ) filter. The result indicated that meteorologicaJ variability accounts for about 25% of $PM_{10}$ variability. Both the meteorologically adjusted and unadjusted Jong-term daily $PM_{10}$ concentrations had a significant downward trends and the difference between the meteorologically adjusted and unadjusted was small. So it was assumed that in long-term daily $PM_{10}$ changes, localized changes in emissions is more important than the changes caused by meteorological conditions.

• 한국대기환경학회지
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• 제19권5호
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• pp.561-568
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• 2003

Surface ozone concentrations are highly sensitive to meteorological variability. Therefore, in order to reveal the long-term changes in ozone due to the changes in precursor emissions, we need to remove the effects of meteorological fluctuations on the annual distribution of surface ozone. In this paper, the meteorologically adjusted trends of daily maximum surface ozone concentrations in two major Korean cities (Seoul and Busan) are investigated based on ozone data from 11 (Seoul) and 6 (Busan) sites over the period 1992 ∼ 2000. The original time series consisting of the logarithm of daily maximum ozone concentrations are splitted into long-term, seasonal and short-term component using Kolmogorov-Zurbenko (KZ) filter. Meteorological effects are removed from filtered ozone series using multiple linear regression based on meteorologcial variables. The long-term evolution of ozone forming capability due to changes in precursor emission can be obtained applying the KZ filter to the residuals of the regression. The results indicated that meteorologically adjusted long-term daily maximum ozone concentrations had a significant upward trend (Seoul: ＋ 3.02% yr$^{-1}$ , Busan: ＋ 3.45% yr$^{-1}$ ). These changes of meteorologically adjusted ozone concentrations represent the effects of changing background ozone concentrations as well as the more localized changes in emissions.

• 환경영향평가
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• 제24권2호
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• pp.111-118
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• 2015

본 연구는 서울의 오존 장기변동 특성을 대표하는 대표측정소를 선정하기 위한 통계적인 기법을 구축하기 위하여 수행되었다. 2002년부터 2011년까지 10년간의 오존 시간 농도자료를 분석에 적용하였다. KZ 필터, 상관관계 매트릭스, 군집분석, 공간 분석 방법을 적용하여 대표측정소를 선정하였다. 상관관계 분석 결과 서울 신정동, 사당동, 번동 측정소의 오존 장기간 변동 추세가 높은 상관관계를 나타내었다. 군집분석에서도 세 측정소가 같은 군집으로 분석되었다. 공간분석 결과, 세 측정소가 다른 측정소와 공간적인 상관관계가 높게 나타났다. 이러한 분석결과와 상관계수값을 고려하였을 때, 신정동 측정소가 서울의 오존 장기변동 추세를 대표하는 측정소로 적합하였다. 본 연구 결과는 오존 이외의 대기오염물질의 분석을 위한 대표측정소 선정에도 적용될 수 있으며, 국가대기측정망의 공간적인 분포의 적절성을 평가하기 위해서도 사용될 수 있을 것으로 판단된다.

• 한국음향학회지
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• 제10권3호
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• pp.5-12
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• 1991

本 硏究에서는 韓國語 10개 도市名을 認識 對象으로 하였다. 各 單語는 男性 話者 10人에 의하여 5번씩 反復 發音한 500單語를 對象으로 하여 필터뱅크 出力을 抽出하여 認識 파라미터로 使用하였다. 필터뱅크는 RC 能動素子를 利用하여 200[Kz]부터 1/3 octave 間隔으로 15채널로 構成하였다. 基準音은 集團化 알고리즘에 의해 設定하였으며 類似度 比較를 위해 DTW 알고리즘을 利用하였다. 距離 計算式에 따른 認識結果를 把握하기 위하여 유크리드 式과 체비셔브 式을 使用하여 距離를 計算하였으며 認識 結果 각각 16.4[%], 15.0[%]의 誤認識率을 얻었다.