본 연구의 목적은 도시계획시설로 조성되는 완충녹지가 PM2.5(초미세먼지) 저감에 효과가 있는지를 규명하고, 도로변 완충녹지의 구조, 녹량(녹지용적), 식재유형에 따른 초미세먼지 변화량을 분석하여 그 결과를 토대로 초미세먼지 저감을 위한 완충녹지 조성시 활용할 수 있는 요소들을 도출하는 것이었다. 연구대상지는 서울시 통계자료를 활용해 PM2.5의 연간 배출량 및 단위면적당 배출량이 가장 많은 지역인 송파구를 선정하였고, 송파구의 대표가로인 양재대로, 송파대로에 인접한 5개의 완충녹지에서 16개의 조사구를 선정해 현장조사를 실시하였다. 완충녹지 현황은 녹지폭, 보도폭, 조성높이, 단면유형을 조사하였고, 완충녹지의 식재구조 현황은 교목, 관목을 구분하여 수종, ...
본 연구의 목적은 도시계획시설로 조성되는 완충녹지가 PM2.5(초미세먼지) 저감에 효과가 있는지를 규명하고, 도로변 완충녹지의 구조, 녹량(녹지용적), 식재유형에 따른 초미세먼지 변화량을 분석하여 그 결과를 토대로 초미세먼지 저감을 위한 완충녹지 조성시 활용할 수 있는 요소들을 도출하는 것이었다. 연구대상지는 서울시 통계자료를 활용해 PM2.5의 연간 배출량 및 단위면적당 배출량이 가장 많은 지역인 송파구를 선정하였고, 송파구의 대표가로인 양재대로, 송파대로에 인접한 5개의 완충녹지에서 16개의 조사구를 선정해 현장조사를 실시하였다. 완충녹지 현황은 녹지폭, 보도폭, 조성높이, 단면유형을 조사하였고, 완충녹지의 식재구조 현황은 교목, 관목을 구분하여 수종, 흉고직경, 수고, 지하고, 수관폭 등의 규격과 위치를 조사해 평면도와 단면도를 작성하였다. PM2.5 농도 측정 시기는 겨울과 봄의 발생량이 더 높다는 기존 연구결과를 바탕으로 서울시 AWS를 분석해 1월과 5월 총 2회에 걸쳐 차량이동이 많은 평일 출근시간대에 농도를 측정하였다. 조사방법은 조사구마다 도로, 보도, 녹지, 주거지 네 곳으로 구분해 8회 반복 측정하였다. 완충녹지 현황을 살펴보면 녹지유형을 지형구조에 따라 사면형 10개소, 평지형 3개소, 마운딩형 3개소로 구분하여 녹량의 평균을 분석한 결과 마운딩형 녹지가 교목 녹지용적계수 5.35㎥/㎡, 관목 녹지용적계수 0.48㎥/㎡로 가장 녹량이 많았으나 사면형 녹지는 교목 녹지용적계수 2.95㎥/㎡, 평지형 녹지는 관목 녹지용적계수가 0.11㎥/㎡로 두 녹지유형간 교목녹량은 사면형이 많았고, 관목녹량은 평지형이 상대적으로 많았다. 식재구조는 교목구조를 식재열수에 따라 1열, 2열, 3열로 구분한 결과 1열 4개소, 2열 9개소, 3열 3개소 였으며, 관목구조를 식재층수에 따라 단층, 복층, 다층구조로 구분한 결과 단층 3개소, 복층 11개소, 다층 2개소로 조사구 녹지현황을 정리하였다. PM2.5 농도 측정결과 조사구별 평균농도는 계절 상관없이 보도 46.6㎍/㎥, 녹지 45.5㎍/㎥, 주거지 42.9㎍/㎥ 모두 도로(53.2㎍/㎥)보다 낮았으며, 특히 주거지 농도값이 가장 낮았다. 계절별 특징으로 겨울에는 녹지가 55.5㎍/㎥로 보도 54.2㎍/㎥보다 높았으나 봄에는 녹지가 35.9㎍/㎥로 보도의 39.0㎍/㎥보다 낮았다. 조사구별 농도상대비율은 겨울에는 사면형이 93.9%로 평지형 88.5%보다 초미세먼지 상대비율이 높았고, 봄에는 사면형이 69.5%로 평지형 75.1%보다 상대비율이 낮아지는 경향을 보였다. 따라서 교목녹량이 많은 사면형은 봄에, 관목녹량이 많은 평지형은 겨울에 저감효과가 더 큰 것으로 분석되어 완충녹지의 녹량이 초미세먼지 저감에 영향을 주고 있음을 확인하였다. 완충녹지의 농도저감 효과 확인을 위해 완충녹지의 녹량과 초미세먼지 상대비율간의 상관관계 분석결과 교목, 관목의 녹피율과 조사구내 수관용적과 관계가 있는 것으로 나타나 녹지 구성요인들이 상호 복합적으로 초미세먼지 농도에 영향을 주고 있었다. 녹량별 특성에 따라 완충녹지의 유형을 구분한 결과 녹량 균형형, 녹량 부족형, 관목 풍부형, 교목 부족형, 관목 부족형 5개 그룹이었고, PM2.5 농도와의 분석결과 교목과 관목 전체 녹량이 높은 그룹의 상대비율이 낮은 것으로 확인되어 완충녹지 녹량의 영향력을 증명했으며, 관목 부족형이 교목 부족형 보다 농도상대비율이 더 높은 것으로 확인되어 녹량에서는 관목의 영향이 더 큰 것으로 판단되었다. 식재구조와의 상관관계 분석결과 교목 1열은 89.1%, 교목 2열은 79.8%, 교목 3열은 72.9%로 여러 열의 교목구조에서 PM2.5 상대비율이 더 낮아지는 음의 상관관계가 있음을 확인하였으며, 관목구조에 따른 상대비율은 단층 90.2%, 복층 79.3%, 다층 69.8%로 다층구조의 관목을 식재하는 것이 PM2.5 농도저감에 효과적인 것으로 확인되었다. 겨울철 완충녹지의 PM2.5 농도저감 특성을 분석한 결과 사면형, 평지형, 마운딩형녹지 모두 관목 녹피율이 높을수록 농도값이 낮아지는 경향을 보였다. 또한, 교목과 관목의 식재구조에 따른 녹피율과 녹지용적계수가 복합적으로 PM2.5 농도 저감에 영향을 미치고 있었으며, 교목의 열수와 관목의 층위구조가 PM2.5 농도 저감에 중요한 영향요인으로 판단되었다. 특히, 초미세먼지 농도가 높은 겨울철 완충녹지의 PM2.5 농도저감 특성 분석결과 관목의 녹피율이 중요한 요인이었다.
본 연구의 목적은 도시계획시설로 조성되는 완충녹지가 PM2.5(초미세먼지) 저감에 효과가 있는지를 규명하고, 도로변 완충녹지의 구조, 녹량(녹지용적), 식재유형에 따른 초미세먼지 변화량을 분석하여 그 결과를 토대로 초미세먼지 저감을 위한 완충녹지 조성시 활용할 수 있는 요소들을 도출하는 것이었다. 연구대상지는 서울시 통계자료를 활용해 PM2.5의 연간 배출량 및 단위면적당 배출량이 가장 많은 지역인 송파구를 선정하였고, 송파구의 대표가로인 양재대로, 송파대로에 인접한 5개의 완충녹지에서 16개의 조사구를 선정해 현장조사를 실시하였다. 완충녹지 현황은 녹지폭, 보도폭, 조성높이, 단면유형을 조사하였고, 완충녹지의 식재구조 현황은 교목, 관목을 구분하여 수종, 흉고직경, 수고, 지하고, 수관폭 등의 규격과 위치를 조사해 평면도와 단면도를 작성하였다. PM2.5 농도 측정 시기는 겨울과 봄의 발생량이 더 높다는 기존 연구결과를 바탕으로 서울시 AWS를 분석해 1월과 5월 총 2회에 걸쳐 차량이동이 많은 평일 출근시간대에 농도를 측정하였다. 조사방법은 조사구마다 도로, 보도, 녹지, 주거지 네 곳으로 구분해 8회 반복 측정하였다. 완충녹지 현황을 살펴보면 녹지유형을 지형구조에 따라 사면형 10개소, 평지형 3개소, 마운딩형 3개소로 구분하여 녹량의 평균을 분석한 결과 마운딩형 녹지가 교목 녹지용적계수 5.35㎥/㎡, 관목 녹지용적계수 0.48㎥/㎡로 가장 녹량이 많았으나 사면형 녹지는 교목 녹지용적계수 2.95㎥/㎡, 평지형 녹지는 관목 녹지용적계수가 0.11㎥/㎡로 두 녹지유형간 교목녹량은 사면형이 많았고, 관목녹량은 평지형이 상대적으로 많았다. 식재구조는 교목구조를 식재열수에 따라 1열, 2열, 3열로 구분한 결과 1열 4개소, 2열 9개소, 3열 3개소 였으며, 관목구조를 식재층수에 따라 단층, 복층, 다층구조로 구분한 결과 단층 3개소, 복층 11개소, 다층 2개소로 조사구 녹지현황을 정리하였다. PM2.5 농도 측정결과 조사구별 평균농도는 계절 상관없이 보도 46.6㎍/㎥, 녹지 45.5㎍/㎥, 주거지 42.9㎍/㎥ 모두 도로(53.2㎍/㎥)보다 낮았으며, 특히 주거지 농도값이 가장 낮았다. 계절별 특징으로 겨울에는 녹지가 55.5㎍/㎥로 보도 54.2㎍/㎥보다 높았으나 봄에는 녹지가 35.9㎍/㎥로 보도의 39.0㎍/㎥보다 낮았다. 조사구별 농도상대비율은 겨울에는 사면형이 93.9%로 평지형 88.5%보다 초미세먼지 상대비율이 높았고, 봄에는 사면형이 69.5%로 평지형 75.1%보다 상대비율이 낮아지는 경향을 보였다. 따라서 교목녹량이 많은 사면형은 봄에, 관목녹량이 많은 평지형은 겨울에 저감효과가 더 큰 것으로 분석되어 완충녹지의 녹량이 초미세먼지 저감에 영향을 주고 있음을 확인하였다. 완충녹지의 농도저감 효과 확인을 위해 완충녹지의 녹량과 초미세먼지 상대비율간의 상관관계 분석결과 교목, 관목의 녹피율과 조사구내 수관용적과 관계가 있는 것으로 나타나 녹지 구성요인들이 상호 복합적으로 초미세먼지 농도에 영향을 주고 있었다. 녹량별 특성에 따라 완충녹지의 유형을 구분한 결과 녹량 균형형, 녹량 부족형, 관목 풍부형, 교목 부족형, 관목 부족형 5개 그룹이었고, PM2.5 농도와의 분석결과 교목과 관목 전체 녹량이 높은 그룹의 상대비율이 낮은 것으로 확인되어 완충녹지 녹량의 영향력을 증명했으며, 관목 부족형이 교목 부족형 보다 농도상대비율이 더 높은 것으로 확인되어 녹량에서는 관목의 영향이 더 큰 것으로 판단되었다. 식재구조와의 상관관계 분석결과 교목 1열은 89.1%, 교목 2열은 79.8%, 교목 3열은 72.9%로 여러 열의 교목구조에서 PM2.5 상대비율이 더 낮아지는 음의 상관관계가 있음을 확인하였으며, 관목구조에 따른 상대비율은 단층 90.2%, 복층 79.3%, 다층 69.8%로 다층구조의 관목을 식재하는 것이 PM2.5 농도저감에 효과적인 것으로 확인되었다. 겨울철 완충녹지의 PM2.5 농도저감 특성을 분석한 결과 사면형, 평지형, 마운딩형녹지 모두 관목 녹피율이 높을수록 농도값이 낮아지는 경향을 보였다. 또한, 교목과 관목의 식재구조에 따른 녹피율과 녹지용적계수가 복합적으로 PM2.5 농도 저감에 영향을 미치고 있었으며, 교목의 열수와 관목의 층위구조가 PM2.5 농도 저감에 중요한 영향요인으로 판단되었다. 특히, 초미세먼지 농도가 높은 겨울철 완충녹지의 PM2.5 농도저감 특성 분석결과 관목의 녹피율이 중요한 요인이었다.
This study aims to verify the effect of green buffers, built as urban planning facilities, on the reduction of ultra-fine particles(PM2.5) and analyze changes in ultra-fine particles by the structure, green volume and planting types of wayside green buffers, thus drawing factors that can be used whe...
This study aims to verify the effect of green buffers, built as urban planning facilities, on the reduction of ultra-fine particles(PM2.5) and analyze changes in ultra-fine particles by the structure, green volume and planting types of wayside green buffers, thus drawing factors that can be used when green buffers are built to reduce ultra-fine particles based on the results. As a research subject, this study selected Songpa-gu, which showed the most emission of PM2.5 per year and per unit area according to the statistical data about Seoul, and investigated 16 sites on 5 green buffers, adjacent to two of Songpa-gu's main roads, 'Yangjaedaero' and 'Songpadaero.' As an investigation into the current situation of green buffers, this study examined the width of sidewalk and the width, the height and the cross-section type of each green buffer, and as an investigation into the planting type and structure of green buffers, this study examined the species, DBH-growth, height, clear-length and crown width of trees and shrubs, and their populations and locations, and made a plane view and a sectional view based on the results. After analyzing the AWS of Seoul City based on the results of previous studies that more ultra-fine particles(PM2.5) are generated most in spring and winter, this study measured the concentration of PM2.5 for office-going hours with heavy traffic during the weekdays, twice in January and May. Particularly, each investigation site was divided into 4 types such as roads, sidewalks, green spaces and residential areas. and this measurement was conducted 8 times repeatedly for each spot. As for current situation of each investigation site, this study divided all the green spaces into 3 different types-slope type, plain type and mounding type, and analyzed the mean green volume. As a result, the mounding-type green space was highest with 5.35㎥/㎡ in the tree green volume coefficient and 0.48㎥/㎡ in the shrub green volume coefficient, but as the tree green volume coefficient of the slope-type green space was 2.95㎥/㎡, and the shrub green volume coefficient of the plain-type green space was 0.11㎥/㎡, the slope type had a more tree green volume than the plain type, while the plain type had a more shrub green volume than the slope type. As for the planting structure, this study divided the structure of trees into three types of tree row-single row, two rows, and three rows and the structure of shrubs into three types of layer-single layer, double layer and multi-layer to arrange the actual states of green spaces in each investigation site. As a result of measuring the concentration of PM2.5, this study found out that it was 55.5㎍/㎥ on average in winter, which was a harmful level according to the integrated environmental index provided by Seoul City, saying that levels above 50㎍/㎥ may have harmful effect on a sensitive group of people. Particularly, the concentration of PM2.5 was 38.6㎍/㎥ on average in spring, which exceeded the mean concentration of PM2.5 in Seoul City in 2015. The mean concentrations of PM2.5 in every investigation spot were 46.6㎍/㎥ for sidewalks, 45.5㎍/㎥ for green spaces and 42.9㎍/㎥ for residential areas, all of which were lower than 53.2㎍/㎥ for roads, regardless of the season, and especially the concentration of PM2.5 for residential areas was lowest. As seasonal characteristics, the concentration of PM2.5 for green spaces 55.5㎍/㎥ was higher than that for sidewalks 54.2㎍/㎥ in winter, but in spring, that for green spaces 35.9㎍/㎥ became lower than that for sidewalks 39.0㎍/㎥. As for the fluctuated concentration rate of ultra-fine particles in every investigation spot, the slope type showed an increase by 93.9% in winter, which was higher than the increased rate of the plain type 88.5%, and in spring, the slope type showed a decrease by 69.5%, which was lower than the decreased rate of the plain type 75.1%. Accordingly, this study confirmed that the slope type having the most tree green volume was more effective on reducing ultra-fine particles in spring, while the plain type having the most shrub green volume was more effective in winter, which indicates that the green volume of green buffers has great effect on the reduction of ultra-fine particles. In the stage of confirming the effect of green buffers, this study analyzed the correlation between the green volume of vegetation and the fluctuated rate of ultra-fine particles. As a result, it was found that the green coverage rate of trees and shrubs was related with the crown volume in every investigation spot, but they were mutually and complexly affected by each other. This study also divided all the green spaces into 5 groups by green-volume characteristics, green volume-balanced group, green volume-insufficient group, shrub-abundant group, tree-insufficient group and shrub-insufficient group and analyzed them. As a result, it was found that a group with higher green volumes of both trees and shrubs showed a lower fluctuation rate, further proving greater influence on the reduction of ultra-fine particles, and as the shrub-insufficient group showed a higher fluctuation rate than the tree-insufficient group, this study judged that the effect of shrubs is greater in terms of green volume. As a result of analyzing correlations between fluctuated concentration rate and the tree structure, this study found out that single row of trees showed the highest fluctuated concentration rate of PM2.5 89.1%, followed by two rows of trees 79.8% and tree rows of trees 72.9% which indicates a negative correlation showing that the fluctuated concentration rate of PM2.5 becomes lower in more rows of trees. Besides, as a result of analyzing the effect of shrub structure, it was found that the single layer showed 90.2% in the fluctuated concentration rate, while the double layer and the multi-layer showed 79.3% and 69.8% respectively. Therefore, this study judged that the more layers of shrubs are made, the more effective it is on reducing the concentration of PM2.5. As for seasonal characteristics, this study analyzed the correlation between the concentration of PM2.5 for residential areas in winter and the green coverage rate of each green space type. As a result, this study found out that there was a negative correlation showing that the higher the shrub green coverage rate is, the lower the concentration value becomes in all the slope-type, plain-type and mounding-type green spaces. All the factors affecting the reduction of ultra-fine particles were related to the green space coefficient(㎥/㎡) through the green coverage rate(%) as a meaning of area and the green volume(㎥) as a meaning of bulk, and they were also affected by the complex structure of trees and shrubs. Thus, this study confirmed that the number of tree rows and the number of shrub layers have negative correlations with the fluctuated concentration rate of PM2.5. Especially, it was judged that the shrub green volume has greater effect than any other factor, and each green space type shows a negative correlation with the shrub coverage rate in winter.
This study aims to verify the effect of green buffers, built as urban planning facilities, on the reduction of ultra-fine particles(PM2.5) and analyze changes in ultra-fine particles by the structure, green volume and planting types of wayside green buffers, thus drawing factors that can be used when green buffers are built to reduce ultra-fine particles based on the results. As a research subject, this study selected Songpa-gu, which showed the most emission of PM2.5 per year and per unit area according to the statistical data about Seoul, and investigated 16 sites on 5 green buffers, adjacent to two of Songpa-gu's main roads, 'Yangjaedaero' and 'Songpadaero.' As an investigation into the current situation of green buffers, this study examined the width of sidewalk and the width, the height and the cross-section type of each green buffer, and as an investigation into the planting type and structure of green buffers, this study examined the species, DBH-growth, height, clear-length and crown width of trees and shrubs, and their populations and locations, and made a plane view and a sectional view based on the results. After analyzing the AWS of Seoul City based on the results of previous studies that more ultra-fine particles(PM2.5) are generated most in spring and winter, this study measured the concentration of PM2.5 for office-going hours with heavy traffic during the weekdays, twice in January and May. Particularly, each investigation site was divided into 4 types such as roads, sidewalks, green spaces and residential areas. and this measurement was conducted 8 times repeatedly for each spot. As for current situation of each investigation site, this study divided all the green spaces into 3 different types-slope type, plain type and mounding type, and analyzed the mean green volume. As a result, the mounding-type green space was highest with 5.35㎥/㎡ in the tree green volume coefficient and 0.48㎥/㎡ in the shrub green volume coefficient, but as the tree green volume coefficient of the slope-type green space was 2.95㎥/㎡, and the shrub green volume coefficient of the plain-type green space was 0.11㎥/㎡, the slope type had a more tree green volume than the plain type, while the plain type had a more shrub green volume than the slope type. As for the planting structure, this study divided the structure of trees into three types of tree row-single row, two rows, and three rows and the structure of shrubs into three types of layer-single layer, double layer and multi-layer to arrange the actual states of green spaces in each investigation site. As a result of measuring the concentration of PM2.5, this study found out that it was 55.5㎍/㎥ on average in winter, which was a harmful level according to the integrated environmental index provided by Seoul City, saying that levels above 50㎍/㎥ may have harmful effect on a sensitive group of people. Particularly, the concentration of PM2.5 was 38.6㎍/㎥ on average in spring, which exceeded the mean concentration of PM2.5 in Seoul City in 2015. The mean concentrations of PM2.5 in every investigation spot were 46.6㎍/㎥ for sidewalks, 45.5㎍/㎥ for green spaces and 42.9㎍/㎥ for residential areas, all of which were lower than 53.2㎍/㎥ for roads, regardless of the season, and especially the concentration of PM2.5 for residential areas was lowest. As seasonal characteristics, the concentration of PM2.5 for green spaces 55.5㎍/㎥ was higher than that for sidewalks 54.2㎍/㎥ in winter, but in spring, that for green spaces 35.9㎍/㎥ became lower than that for sidewalks 39.0㎍/㎥. As for the fluctuated concentration rate of ultra-fine particles in every investigation spot, the slope type showed an increase by 93.9% in winter, which was higher than the increased rate of the plain type 88.5%, and in spring, the slope type showed a decrease by 69.5%, which was lower than the decreased rate of the plain type 75.1%. Accordingly, this study confirmed that the slope type having the most tree green volume was more effective on reducing ultra-fine particles in spring, while the plain type having the most shrub green volume was more effective in winter, which indicates that the green volume of green buffers has great effect on the reduction of ultra-fine particles. In the stage of confirming the effect of green buffers, this study analyzed the correlation between the green volume of vegetation and the fluctuated rate of ultra-fine particles. As a result, it was found that the green coverage rate of trees and shrubs was related with the crown volume in every investigation spot, but they were mutually and complexly affected by each other. This study also divided all the green spaces into 5 groups by green-volume characteristics, green volume-balanced group, green volume-insufficient group, shrub-abundant group, tree-insufficient group and shrub-insufficient group and analyzed them. As a result, it was found that a group with higher green volumes of both trees and shrubs showed a lower fluctuation rate, further proving greater influence on the reduction of ultra-fine particles, and as the shrub-insufficient group showed a higher fluctuation rate than the tree-insufficient group, this study judged that the effect of shrubs is greater in terms of green volume. As a result of analyzing correlations between fluctuated concentration rate and the tree structure, this study found out that single row of trees showed the highest fluctuated concentration rate of PM2.5 89.1%, followed by two rows of trees 79.8% and tree rows of trees 72.9% which indicates a negative correlation showing that the fluctuated concentration rate of PM2.5 becomes lower in more rows of trees. Besides, as a result of analyzing the effect of shrub structure, it was found that the single layer showed 90.2% in the fluctuated concentration rate, while the double layer and the multi-layer showed 79.3% and 69.8% respectively. Therefore, this study judged that the more layers of shrubs are made, the more effective it is on reducing the concentration of PM2.5. As for seasonal characteristics, this study analyzed the correlation between the concentration of PM2.5 for residential areas in winter and the green coverage rate of each green space type. As a result, this study found out that there was a negative correlation showing that the higher the shrub green coverage rate is, the lower the concentration value becomes in all the slope-type, plain-type and mounding-type green spaces. All the factors affecting the reduction of ultra-fine particles were related to the green space coefficient(㎥/㎡) through the green coverage rate(%) as a meaning of area and the green volume(㎥) as a meaning of bulk, and they were also affected by the complex structure of trees and shrubs. Thus, this study confirmed that the number of tree rows and the number of shrub layers have negative correlations with the fluctuated concentration rate of PM2.5. Especially, it was judged that the shrub green volume has greater effect than any other factor, and each green space type shows a negative correlation with the shrub coverage rate in winter.
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