Dry deposition and wet deposition are Removal mechanisms of air pollutants in the atmospheric environment. Especially, wet deposition is effective removal process that high-level air pollutants can be removed by rain or snow in a short time. It is necessary to estimate removal efficiency of air po...
Dry deposition and wet deposition are Removal mechanisms of air pollutants in the atmospheric environment. Especially, wet deposition is effective removal process that high-level air pollutants can be removed by rain or snow in a short time. It is necessary to estimate removal efficiency of air pollutants by precipitation for control strategies of air pollutants. This study begins to estimate on removal efficiency of major air pollutants by precipitation according to this necessity.
This study utilized the telemetry system (TMS) data collected by the Korean Ministry of Environment and precipitation data collected by the Korean Meteorological Administration (KMA) from 1990 to 1999. The target site was Kwanghwamun air monitoring site that is a traffic area in central part of Seoul. The raw data sets were composed of 7 variables such as SO2, TSP, PM10, CO, NO2, O3, and precipitation at an interval of 1 hour. This study analyze the only case when it is raining.
To survey behavior of each variable whenever it is raining, various univariate statistical analyses were examined in the beginning of the study. In order to estimate relationship between precipitation and each pollutant, the data sets were classified by three criteria. First, since precipitation amounts of every season was quite different, the data sets were divided into 4 groups season-by-season. Second, for the 4 groups, the infrequent occurrences of precipitation amounts were highlighted by higher rank 10 percentile. Thus, cases in each group is classified on the basis of 90 percentile value of precipitation amounts every season. The cases belonging to greater than higher rank 10 percentile value were classified as an outlier group and another cases belonging to less than 90 percentile value were intensively analyzed. Third, diurnal variation of pollutants can be identified by people's activity time, for example, the diurnal patterns of SO2 show maximum values in the morning, minimum values in th e afternoon, and slightly increasing values in the evening. Thus, the removal efficiency of air pollutants were estimated according to time zone such as Night, Morning, Afternoon, and Evening. Moreover, removal efficiency was calculated on the basis of a difference between values at 1 hour before starting time and values at stopping time of precipitation divided by the former.
As a result, the removal efficiency per 1 ㎜ of precipitation for 6 air pollutants were analyzed as follows: 1) 13.7 % of SO2, 6.2 % of TSP, -0.3 % of PM10, 5.9 % of CO, 2.6 % of NO2, and 13.7% of O3 during the afternoon of spring, 2) 11.2 % of SO2, 5.3 % of TSP, 1.3 % of PM10, 1.3 % of CO, -1.0 % of NO2, and 6.8 % of O3 during the afternoon of summer, 3) 29.6 % of SO2, 9.3 % of TSP, -5.5 % of PM10, 1.9 % of CO, 7.1 % of NO2, and 20.8 % of O3 during the afternoon of fall, and 4) 12.9 % of SO2, 14.6 % of TSP, 2.8 % of PM10, 5.2 % of CO, 2.7 % of NO2, and 1.3 % of O3 during the afternoon of winter.
Dry deposition and wet deposition are Removal mechanisms of air pollutants in the atmospheric environment. Especially, wet deposition is effective removal process that high-level air pollutants can be removed by rain or snow in a short time. It is necessary to estimate removal efficiency of air pollutants by precipitation for control strategies of air pollutants. This study begins to estimate on removal efficiency of major air pollutants by precipitation according to this necessity.
This study utilized the telemetry system (TMS) data collected by the Korean Ministry of Environment and precipitation data collected by the Korean Meteorological Administration (KMA) from 1990 to 1999. The target site was Kwanghwamun air monitoring site that is a traffic area in central part of Seoul. The raw data sets were composed of 7 variables such as SO2, TSP, PM10, CO, NO2, O3, and precipitation at an interval of 1 hour. This study analyze the only case when it is raining.
To survey behavior of each variable whenever it is raining, various univariate statistical analyses were examined in the beginning of the study. In order to estimate relationship between precipitation and each pollutant, the data sets were classified by three criteria. First, since precipitation amounts of every season was quite different, the data sets were divided into 4 groups season-by-season. Second, for the 4 groups, the infrequent occurrences of precipitation amounts were highlighted by higher rank 10 percentile. Thus, cases in each group is classified on the basis of 90 percentile value of precipitation amounts every season. The cases belonging to greater than higher rank 10 percentile value were classified as an outlier group and another cases belonging to less than 90 percentile value were intensively analyzed. Third, diurnal variation of pollutants can be identified by people's activity time, for example, the diurnal patterns of SO2 show maximum values in the morning, minimum values in th e afternoon, and slightly increasing values in the evening. Thus, the removal efficiency of air pollutants were estimated according to time zone such as Night, Morning, Afternoon, and Evening. Moreover, removal efficiency was calculated on the basis of a difference between values at 1 hour before starting time and values at stopping time of precipitation divided by the former.
As a result, the removal efficiency per 1 ㎜ of precipitation for 6 air pollutants were analyzed as follows: 1) 13.7 % of SO2, 6.2 % of TSP, -0.3 % of PM10, 5.9 % of CO, 2.6 % of NO2, and 13.7% of O3 during the afternoon of spring, 2) 11.2 % of SO2, 5.3 % of TSP, 1.3 % of PM10, 1.3 % of CO, -1.0 % of NO2, and 6.8 % of O3 during the afternoon of summer, 3) 29.6 % of SO2, 9.3 % of TSP, -5.5 % of PM10, 1.9 % of CO, 7.1 % of NO2, and 20.8 % of O3 during the afternoon of fall, and 4) 12.9 % of SO2, 14.6 % of TSP, 2.8 % of PM10, 5.2 % of CO, 2.7 % of NO2, and 1.3 % of O3 during the afternoon of winter.
주제어
#강수
#대기오염물질
#환경
#대기오염
#세정제거
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