哈尔滨典型街谷空间PM2.5分布场与绿色界面指数相关性研究
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摘要
在城市化快速进程的背景下,城市街区PM2.5污染日益严重,本文选取哈尔滨在不同季节的典型街谷空间,对以叶面积密度(LAD)、叶面积指数(LAI)为实测要素的绿色界面指数以及PM2.5浓度进行实测对比研究。通过对实测数据的分析和挖掘,最终得出如下结论:首先,典型街谷空间PM2.5时段浓度呈现上午比下午平均高37.75%,冬季比夏季高4.7倍的特征;其次,街谷空间的灌木界面对PM2.5浓度场平均积极贡献率为18.62%;最后,对PM2.5的衰减率与实测街谷绿色界面的叶面积密度(LAD)与叶面积指数(LAI)进行相关性分析,结果显示街谷绿色界面对PM2.5浓度的衰减作用与叶面积密度(LAD)呈显著负相关关系,与叶面积指数(LAI)的相关性程度较弱。
Under the background of the acceleration of urbanization in China, the urban composite carrying capacity is increasing, and the urban environment such as air and water pollution is beginning to appear gradually. In some northern Chinese cities, due to its special severe cold climate, its main urban environmental pollutants are PM2.5. As an important part of the urban underlying surface, the special narrow and long form affects the air flow to form a special wind field, and thus forming a corresponding PM2.5 concentration field. As a "soft interface" of street space, plants are considered to be one of the most appropriate ways to reduce the concentration of air pollutants, and are widely used in the study of urban street and valley environment. This paper selects the typical street space of Harbin as the research object, and studies the influential mechanism of the green interface in the valley on the concentration field of PM2.5. In this paper, six typical Harbin typical street valleys with an aspect ratio of about 1.0 are selected. The concentration of PM2.5, leaf area index and leaf area density in six street valleys are measured in four seasons to analyze the density of different leaf areas. The influence of leaf area index and planting interval on the distribution field of concentration in PM2.5, determines the core influencing factors of PM2.5 distribution field, and establishes the concentration database of PM2.5 in different seasons. Through the analysis and excavation of the measured data, the following conclusions are drawn: the concentration of PM2.5 in the morning of typical street space indicates an average of 37.75% higher than the afternoon, and 4.7 times higher than the summer in winter.Considering twelve o'clock as the dividing line, the average concentration of the morning and afternoon of the six streets is compared. Except for the morning concentration of the company street(Fengqi Street-Railway Section), which is 0.54% lower than the afternoon concentration, the morning concentration of other streets is higher than the afternoon concentration. The values are: 62.77% of Company Street, 38.02% of Customs Street, 45.44% of Fuhua Sidao Street, 39.19% of Shangjiashu Street and 3.36% of Postal Street.According to the seasonal distribution of the average concentration of PM2.5, the concentration in PM2.5 of the six streets shows the highest in winter and the lowest in summer. The average concentration of PM2.5 in the northwest-southeast Sanjie Street in winter is 4.73 times of that in summer. The average concentration of PM2.5 in the three northeast-southwest streets in winter is 4.76 times of that in summer.Secondly, the shrub band in the street space has positive contribution with an average rate of 18.62% to the PM2.5 concentration field.There are two streets in the sample containing shrubs, which are the northwest-southeastoriented Customs Street(Post Street-Manzhouli Street) and the northeast-southwest-oriented Post Street(Customs Street-Beijing Section). Compared with the two measuring points of shrubs and street trees, the peaks of concentration in terms of the PM2.5 of the four seasons are smaller than the measuring points of the street trees. The specific values are: Customs Street(Post StreetManzhouli Street), 40.43% in winter, 4.92% in spring, 20.97% in summer, 19.54% in autumn. Post Street(Customs Street-Beijing Street) 5.74% in winter, 3.76% in spring, 36.01% in summer and 17.62% in autumn. It can be seen that the shrub plays a positive role in the reduction of concentration in PM2.5.Finally, the PM2.5 concentration distribution field shows a significant negative correlation with leaf area density(LAD) in the green interface, while it is significantly correlated with another parameter leaf area index(LAI). Correlation analysis between leaf area density(LAD) and leaf area index(LAI) and PM2.5 attenuation coefficient(PMDA) data is performed by SPSS. The results show that the correlation coefficient between PMDA and LAD is 0.04(less than the significant correlation standard threshold of 0.05), showing a significant negative correlation and the correlation coefficient is-0.598. Meanwhile, the correlation coefficient with LAI is 0.082, showing no significant correlation between the two. Therefore, in the study of the green interface and PM2.5 concentration field, it is more appropriate to use the leaf area density(LAD) with greater correlation weight as the green interface index.
Under the background of the acceleration of urbanization in China, the urban composite carrying capacity is increasing, and the urban environment such as air and water pollution is beginning to appear gradually. In some northern Chinese cities, due to its special severe cold climate, its main urban environmental pollutants are PM2.5. As an important part of the urban underlying surface, the special narrow and long form affects the air flow to form a special wind field, and thus forming a corresponding PM2.5 concentration field. As a "soft interface" of street space, plants are considered to be one of the most appropriate ways to reduce the concentration of air pollutants, and are widely used in the study of urban street and valley environment. This paper selects the typical street space of Harbin as the research object, and studies the influential mechanism of the green interface in the valley on the concentration field of PM2.5. In this paper, six typical Harbin typical street valleys with an aspect ratio of about 1.0 are selected. The concentration of PM2.5, leaf area index and leaf area density in six street valleys are measured in four seasons to analyze the density of different leaf areas. The influence of leaf area index and planting interval on the distribution field of concentration in PM2.5, determines the core influencing factors of PM2.5 distribution field, and establishes the concentration database of PM2.5 in different seasons. Through the analysis and excavation of the measured data, the following conclusions are drawn: the concentration of PM2.5 in the morning of typical street space indicates an average of 37.75% higher than the afternoon, and 4.7 times higher than the summer in winter.Considering twelve o'clock as the dividing line, the average concentration of the morning and afternoon of the six streets is compared. Except for the morning concentration of the company street(Fengqi Street-Railway Section), which is 0.54% lower than the afternoon concentration, the morning concentration of other streets is higher than the afternoon concentration. The values are: 62.77% of Company Street, 38.02% of Customs Street, 45.44% of Fuhua Sidao Street, 39.19% of Shangjiashu Street and 3.36% of Postal Street.According to the seasonal distribution of the average concentration of PM2.5, the concentration in PM2.5 of the six streets shows the highest in winter and the lowest in summer. The average concentration of PM2.5 in the northwest-southeast Sanjie Street in winter is 4.73 times of that in summer. The average concentration of PM2.5 in the three northeast-southwest streets in winter is 4.76 times of that in summer.Secondly, the shrub band in the street space has positive contribution with an average rate of 18.62% to the PM2.5 concentration field.There are two streets in the sample containing shrubs, which are the northwest-southeastoriented Customs Street(Post Street-Manzhouli Street) and the northeast-southwest-oriented Post Street(Customs Street-Beijing Section). Compared with the two measuring points of shrubs and street trees, the peaks of concentration in terms of the PM2.5 of the four seasons are smaller than the measuring points of the street trees. The specific values are: Customs Street(Post StreetManzhouli Street), 40.43% in winter, 4.92% in spring, 20.97% in summer, 19.54% in autumn. Post Street(Customs Street-Beijing Street) 5.74% in winter, 3.76% in spring, 36.01% in summer and 17.62% in autumn. It can be seen that the shrub plays a positive role in the reduction of concentration in PM2.5.Finally, the PM2.5 concentration distribution field shows a significant negative correlation with leaf area density(LAD) in the green interface, while it is significantly correlated with another parameter leaf area index(LAI). Correlation analysis between leaf area density(LAD) and leaf area index(LAI) and PM2.5 attenuation coefficient(PMDA) data is performed by SPSS. The results show that the correlation coefficient between PMDA and LAD is 0.04(less than the significant correlation standard threshold of 0.05), showing a significant negative correlation and the correlation coefficient is-0.598. Meanwhile, the correlation coefficient with LAI is 0.082, showing no significant correlation between the two. Therefore, in the study of the green interface and PM2.5 concentration field, it is more appropriate to use the leaf area density(LAD) with greater correlation weight as the green interface index.
引文
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[6]刘彦飞,邵龙义,王彦彪,等.哈尔滨春季大气PM2.5物理化学特征及来源解析[J].环境科学与技术,2010(2):131-134.LIU Y F,SHAO L Y,WANG Y B,et al.Physical and Chemical Characteristics and Source Analysis of Atmospheric PM2.5 in Harbin in Spring[J].Environmental Science and Technology,2010(2):131-134.
[7]迟晓德,周晶.哈尔滨城市空气PM2.5污染主要来源分析[J].环境科学与管理,2013,38(11):1-4.CHI X D,ZHOU J.Analysis of Main Sources of PM2.5 Pollution in Urban Air in Harbin[J].Environmental Science and Management,2013,38(11):1-4.
[8]COPPALLE.A street canyon model for low wind-speed conditions[J].International Journal of Environment&Pollution,2001,16(1):417-434.
[9]DEPAUL F T,SHEIH C M.Measurements of wind velocities in a street canyon[J].Atmospheric Environment,1986,20(3):455-459.
[10]YANG Y,SHAO Y.Numerical simulations of flow and pollution dispersion in urban atmospheric boundary layers[J].Environmental Modelling&Software,2008,23(7):906-921.
[11]SOULHAC L,PERKINS R J,SALIZZONI P.Flow in a Street Canyon for any External Wind Direction[J].Boundary-Layer Meteorology,2008,126(3):365-388.
[12]NAKAMURA Y,OKE T R.Wind,temperature and stability conditions in an east-west oriented urban canyon[J].Atmospheric Environment,1988,22(12):2691-2700.
[13]叶鹤宸,朱逊.哈尔滨市秋季城市公园空间特征健康恢复性影响研究——以兆麟公园为例[J].西部人居环境学刊,2018,33(4):79-85.YE H Z,ZHU X.Study on the Effect of Spatial Characteristics and Health Restoration of Urban Parks in Harbin Cityin Autumn—Taking Zhaolin Park as an Example[J].Journal of Human Settlements in West China,2018,33(4):79-85.
[14]卓健,曹根榕.街道空间管控视角下城市设计法律效力提升路径和挑战[J].规划师,2018(7):18-25.ZHUO J,CAO G R.The Pathway And Challenges Of Improving Statutory Power Of Urban Design In The Street Governance View[J].Planners,2018(7):18-25.
[15]GH ASEMIAN M,AM INI S,PRINCEVAC M.The influence of roadside solid and vegetation barriers on near-road air quality[J].Atmospheric Environment,2017,170(12):108-117.
[16]MORADPOUR M,AFSHIN H,FARHANIEH B.A numerical study of reactive pollutant dispersion in street canyons with green roofs[J].Building Simulation,2017,11(1):1-14.
[17]GROMKE C,RUCK B.Aerodynamic modelling of trees for small-scale wind tunnel studies[J].Forestry,2008,81(3):243-258.
[18]MORI J,FINI A,GALIMBERTI M,et al. Air pollution deposition on a roadside vegetation barrier in a Mediterranean environment:Combined effect of evergreen shrub species and planting density[J].Science of The Total Environment,2018,643:725-737.
[19]林钰琼,姚佳伟,郑静云,等.基于风洞可视化的环境性能建筑生形方法研究[J].南方建筑,2018(2):24-29.LIN Y Q,YAO J W,ZHENG J Y,et al.Research on the Building Morphology Generation Method Based on the Wind Tunnel Visualization of Environmental Performance[J].South Architecture,2018(2):24-29.
[20]ALI-TOUDERT F,MAYER H.Numerical study on the effects of aspect ratio and orientation of an urban street canyon on outdoor thermal comfort in hot and dry climate[J].Building&Environment,2006,41(2):94-108.
[21]鲍越.基于环境行为学的城市街道空间互动性研究[D].无锡:江南大学,2013.BAO Y.Research on spatial interactionof urban street based on environmental behavior[D].Wuxi:Jiangnan University,2013.
[22]JIN S,GUO J,WHEELER S,et al.Evaluation of impacts of trees on PM2.5,dispersion in urban streets[J].Atmospheric Environment,2014,99(99):277-287.
[2]WANIA A,BRUSE M,BLOND N,et al Analysing the influence of different street vegetation on traffic-induced particle dispersion using microscale simulations[J].Journal of Environmental Management,2012,94(1):91-101.
[3]程慧波.中国北方城市可吸入颗粒物时空分布特征及气象因素对其影响分析[C]//中国环境科学学会.2015年中国环境科学学会学术年会论文集.北京:中国环境科学出版社,2015:9.CHENG H B.Temporal and spatial distribution characteristics of inhalable particulate matter and the influence of meteorological factors in northern China[C]//Chinese Society for Environmental Sciences.Proceedings of the 2015 Annual Conference of Chinese Society of Environmental Sciences.Beijing:Chinese Society for Environmental Sciences,2015:9.
[4]王婷婷,任桂林,王华昕.2013-2015年哈尔滨市空气质量特征分析[J].黑龙江气象,2017,34(1):25-27.WANG T T,REN G L,WANG H X.Analysis of Air Quality Characteristics of Harbin City from 2013 to 2015[J].Heilongjiang Meteorology,2017,34(1):25-27.
[5]张莹,魏晓慧,王阿川.哈尔滨市PM2.5质量浓度变化特征及影响因素分析[J].环境科学与技术,2016,39(3):188-191.ZHANG Y,WEI X H,WANG A C.Analysis of Variation Characteristics and Influencing Factors of PM2.5Mass Concentration in Harbin[J].Environmental Science and Technology,2016,39(3):188-191.
[6]刘彦飞,邵龙义,王彦彪,等.哈尔滨春季大气PM2.5物理化学特征及来源解析[J].环境科学与技术,2010(2):131-134.LIU Y F,SHAO L Y,WANG Y B,et al.Physical and Chemical Characteristics and Source Analysis of Atmospheric PM2.5 in Harbin in Spring[J].Environmental Science and Technology,2010(2):131-134.
[7]迟晓德,周晶.哈尔滨城市空气PM2.5污染主要来源分析[J].环境科学与管理,2013,38(11):1-4.CHI X D,ZHOU J.Analysis of Main Sources of PM2.5 Pollution in Urban Air in Harbin[J].Environmental Science and Management,2013,38(11):1-4.
[8]COPPALLE.A street canyon model for low wind-speed conditions[J].International Journal of Environment&Pollution,2001,16(1):417-434.
[9]DEPAUL F T,SHEIH C M.Measurements of wind velocities in a street canyon[J].Atmospheric Environment,1986,20(3):455-459.
[10]YANG Y,SHAO Y.Numerical simulations of flow and pollution dispersion in urban atmospheric boundary layers[J].Environmental Modelling&Software,2008,23(7):906-921.
[11]SOULHAC L,PERKINS R J,SALIZZONI P.Flow in a Street Canyon for any External Wind Direction[J].Boundary-Layer Meteorology,2008,126(3):365-388.
[12]NAKAMURA Y,OKE T R.Wind,temperature and stability conditions in an east-west oriented urban canyon[J].Atmospheric Environment,1988,22(12):2691-2700.
[13]叶鹤宸,朱逊.哈尔滨市秋季城市公园空间特征健康恢复性影响研究——以兆麟公园为例[J].西部人居环境学刊,2018,33(4):79-85.YE H Z,ZHU X.Study on the Effect of Spatial Characteristics and Health Restoration of Urban Parks in Harbin Cityin Autumn—Taking Zhaolin Park as an Example[J].Journal of Human Settlements in West China,2018,33(4):79-85.
[14]卓健,曹根榕.街道空间管控视角下城市设计法律效力提升路径和挑战[J].规划师,2018(7):18-25.ZHUO J,CAO G R.The Pathway And Challenges Of Improving Statutory Power Of Urban Design In The Street Governance View[J].Planners,2018(7):18-25.
[15]GH ASEMIAN M,AM INI S,PRINCEVAC M.The influence of roadside solid and vegetation barriers on near-road air quality[J].Atmospheric Environment,2017,170(12):108-117.
[16]MORADPOUR M,AFSHIN H,FARHANIEH B.A numerical study of reactive pollutant dispersion in street canyons with green roofs[J].Building Simulation,2017,11(1):1-14.
[17]GROMKE C,RUCK B.Aerodynamic modelling of trees for small-scale wind tunnel studies[J].Forestry,2008,81(3):243-258.
[18]MORI J,FINI A,GALIMBERTI M,et al. Air pollution deposition on a roadside vegetation barrier in a Mediterranean environment:Combined effect of evergreen shrub species and planting density[J].Science of The Total Environment,2018,643:725-737.
[19]林钰琼,姚佳伟,郑静云,等.基于风洞可视化的环境性能建筑生形方法研究[J].南方建筑,2018(2):24-29.LIN Y Q,YAO J W,ZHENG J Y,et al.Research on the Building Morphology Generation Method Based on the Wind Tunnel Visualization of Environmental Performance[J].South Architecture,2018(2):24-29.
[20]ALI-TOUDERT F,MAYER H.Numerical study on the effects of aspect ratio and orientation of an urban street canyon on outdoor thermal comfort in hot and dry climate[J].Building&Environment,2006,41(2):94-108.
[21]鲍越.基于环境行为学的城市街道空间互动性研究[D].无锡:江南大学,2013.BAO Y.Research on spatial interactionof urban street based on environmental behavior[D].Wuxi:Jiangnan University,2013.
[22]JIN S,GUO J,WHEELER S,et al.Evaluation of impacts of trees on PM2.5,dispersion in urban streets[J].Atmospheric Environment,2014,99(99):277-287.
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