| 摘要: |
| 城市水域、绿地空间及其系统可以有效消减局地可吸入颗粒物浓度，进而降低污染暴露风险水平，提升人居环境质量。以北京奥林匹克森林公园为例，
棋盘式取样法布局并实测17处样点区域PM2.5浓度数据并进行空间插值，结合试验同期获取的公园绿地区域手机信令数据进行PM2.5暴露风险水平评估。结果表
明：1)公园绿地范围内访客行为密度在主要游步道沿线、入口区及滨水景点区域呈现空间聚集性；2)公园绿地范围内基于PM2.5浓度的空气质量评价结果空间差
异性显著；集中连片林地区域空气质量评价结果优于草地，景观水域空气质量优于对比城市区域；面状林地内部，滨水线型区域与景观水域中心之间存在异质性
特征；3)公园绿地范围远离城市道路的面状林地、林地边缘及滨水线型区域PM2.5暴露风险水平最低，草地区域其次，景观水域较高；绿地主要入口区、邻近城市
道路的线型区域以及景观水域的暴露风险水平较高。研究结果为既有城市绿地内的景观游憩空间、游线合理布局，以及新建城市绿地内的功能型绿地景观体系构
建提供科学依据。 |
| 关键词: 风景园林 城市绿地 PM2.5 暴露风险 时空分异 |
| DOI：10.19775/j.cla.2025.02.0063 |
| 投稿时间：2023-10-15修订日期：2024-07-02 |
| 基金项目:国家自然科学基金项目(51641801) |
|
| Spatial Characteristics of Absorptive Fine Particulates and it's Exposure Risk in Beijing Olympic ForestPark |
| PAN Jianbin,,HUANG Tiantian,,SHI Chuan,,TAO Tao,,CHEN Xiaoyu |
| Abstract: |
| Long-term exposure to the environment with high concentrations of
inhalable fine particulate matter can have serious negative effects on human health.
Urban water-green space and its system can effectively reduce the inhalable fine
particle concentration, thereby reducing the level of exposure risk to pollution ,
improving air quality and urban microclimate and providing urban residents with
a healthier and more comfortable living environment. PM2.5 is a typical inhalable
fine particulate matter, which has the characteristics of spatial aggregation and
heterogeneity at large and medium scales (national territory, urban areas). This
study aimed to assess the PM2.5 Exposure Risk (PM2.5ER) in urban green spaces.
Beijing Olympic Forest Park (BOFP) is an artificially constructed urban green space,
that belongs to a small-scale space relatively. In this paper, BOFP is taken as an
example and areas along this park trail system are of particular concern. 17 sample
points away from large-scale crowd activity areas are arranged with the chessboard
sampling method in BOFP to measure PM2.5 concentration data and conduct Kriging
spatial interpolation to calculate the PM2.5 concentration of a 50m×50m spatial unit
to evaluate the air quality. At the same time, two comparison sample points are set
up. Combined with the spatiotemporal behavior density of park green space visitors
obtained from the 7-day continuous Mobile Signal Data (MSD) of 5G base stations
in BOFP during the same period of the test, PM2.5ER level is evaluated. Correlation
between the environmental characteristics of urban park green spaces and the spatial
heterogeneity of PM2.5 pollution, as well as the spatial characteristics of PM2.5ER
levels in urban park green spaces are analyzed and explained. The results show that:
1) The density of visitor behavior in three typical periods gradually increases with
time in BOFP. The difference in visitor behavior density shows spatial aggregation
along the main trails, entrance areas and waterfront attractions in BOFP. 2) The air
quality assessment results based on PM2.5 concentration in BOFP have significant
spatial differences. The air quality assessment result of concentrated contiguous forest
land area is better than that of grassland, and the air quality of landscape water area
is higher than compared urban areas. Moreover, the air quality inside the forest is
higher than that in the edge of the forest, and the air quality in the waterfront area
surrounding the landscape water is higher than that in the center of the landscape
water. In other words, there is heterogeneity between the waterfront area and the water
center within the areal forest land. 3) PM2.5ER in the area of forest land, the edge of
forest land and the waterfront area far from the urban road of BOFP is low, followed
by the grassland area, and which landscape water area is high. Due to the large flow
of people, PM2.5ER level of the main entrance area of BOFP, linear area near urban
roads and landscape water surface area is high. The spatial distribution characteristics
of high-exposure risk areas in BOFP basically coincide with the areas with relatively
high visitor spatiotemporal behavior density in the green space, and the spatial
distribution characteristics of low-exposure risk areas are consistent with the better
air quality evaluation areas presented in the spatiotemporal differentiation results
of green space air quality. The forest area in BOFP exhibits the highest proportion
and is concentrated in distribution. The research results indicate that the relatively
high living vegetation volume in this area is conducive to further reducing the PM2.5
concentration and effectively improving the air quality. Among the relevant factors
that influence the formation of the spatial pattern characteristics of PM2.5ER, the
correlation between green space plant community characteristics (living vegetation
volume, plant community structure, type, etc.) and the spatial pattern of PM2.5ER
is significant and green space plant community characteristics are its basic driving
factors. The PM2.5ER level in the green space of BOFP is jointly determined by the
spatial distribution characteristics of PM2.5 pollution and the density of visitor spatial
behavior. In park green areas featuring green plant communities with high abatement
efficiency and located far away from pollution "source" release areas, and when the
density of crowd behavior is within a certain range, the PM2.5 pollution risk level
of the area is low. The high PM2.5ER level in some landscape areas within the park
green space studied in this article can be improved by replanning the hiking trails
and increasing the regional forest coverage (living vegetation volume). The research
results provide a scientific basis for the rational arrangement of landscape recreational
spaces and tourist routes in existing urban green spaces. They also provide guidance
for the construction and optimization of functional green space landscape systems
in newly constructed urban green spaces, allowing planners to make more scientific
decisions so that newly built green spaces can better meet residents' leisure needs and
ecological benefits, and promote the sustainable development of urban green space
systems. |
| Key words: landscape architecture urban green space PM2.5 exposure risk spatial
differentiation |
