基于步行性与污染物暴露空间格局比较的建成环境健康效应——以南京为例

doi:10.18306/dlkxjz.2019.02.012

摘要/Abstract

摘要：

在雾霾问题日益严重的中国,通过提高建成环境的步行性以增加居民户外体力活动的同时,也会增加居民的污染物暴露度,最终的健康效应不一定为正。针对这一悖论,论文以南京为例,通过步行指数测度步行性,基于土地利用回归模型和插值模拟PM_2.5和O₃浓度的空间分布,在此基础上比较步行性与污染物暴露的空间关系,从而对建成环境健康效应进行评价。研究表明：确实存在高步行性但同时也是高污染物暴露的城市空间,这部分空间主要分布在城市中心区,在这些地区片面强调提高步行活动其实是存在很大健康风险的;城市郊区则呈现低步行性且低污染物暴露的特征,其健康效应亦难以直接判断;靠近城市中心但又距其有一定距离的大面积绿地周边地区呈现高步行性且低污染物暴露的特征,其健康效应为正;而城乡交界的半城市化地区容易成为低步行性且高污染物暴露的健康效应为负的空间。研究结果可以为精准制定健康城市的土地利用政策提供参考依据。

关键词: 步行指数, 健康城市, PM_2.5, O₃, 南京

Abstract:

Haze problem is becoming increasingly more serious in China. Improving walkability of cities to increase outdoor physical activities of urban residents may also increase their exposure to air pollution, and the health effect is not necessarily positive. In view of this paradox, by taking Nanjing City as an example, this study measured walkability and simulated air pollutant concentration based on a land use regression model and spatial interpolation. It then compared these to evaluate the health effects of the built environment. The calculation of the walkability score includes three steps: 1) Assign weights and distance attenuation of the concerned service facilities, based on which the basic walkability score of the point of interest (POI) is obtained. 2) Obtain the single-point walkability score of the POI, considering the impact of the walking environment. 3) Obtain walkability score by spatial interpolation. It was found that the walking index of the main urban area of Nanjing City showed a multi-center axial attenuation pattern. PM_2.5 and O₃ were selected as representative air pollutants for concentration simulation for their significant hazard. The concentration of PM_2.5 was mainly simulated by establishing a regression model with relevant geographic variables, and the O₃ concentration was simulated by spatial interpolation because it showed different characteristics in space. The result indicates that there is a large area of high walkability and high pollutant exposure. These areas are mainly distributed in the urban center. In such areas, it is risky to emphasize the improvement of walking activities through modifying the built environment to promote health. The area of low walkability and low pollutant exposure is mainly distributed in the suburbs, and it is difficult to directly assess the health effects of such areas. Health-promoting area of high walkability and low PM_2.5 concentration is mainly distributed around the city's large green areas. Areas of high walkability and low O₃ concentration are distributed in the second circle of the city center but not inside the center. Therefore, the surrounding area of green space that is close to the city center but not at the center is more likely to become space of high walkability and low pollutant exposure, which has positive health effects. On the other hand, the semi-urbanized areas at the junction of urban and rural areas tend to become space of low walkability and high pollutant exposure because industrial expansion does not match the lagging service provision. Such areas have negative health effects. The results can provide a reference for the accurate formulation of land use policies for healthy cities.

Key words: walkability, healthy city, PM_2.5, O₃, Nanjing City

陈曦, 冯建喜. 基于步行性与污染物暴露空间格局比较的建成环境健康效应——以南京为例[J]. 地理科学进展, 2019, 38(2): 296-304.

Xi CHEN, Jianxi FENG. Health effects of built environment based on a comparison of walkability and air pollution:A case study of Nanjing City[J]. PROGRESS IN GEOGRAPHY, 2019, 38(2): 296-304.

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	设施分类	分类权重	权重
餐饮	餐馆	0.75, 0.45, 0.25, 0.25, 0.225, 0.225, 0.225, 0.225, 0.2, 0.2	3
餐饮	咖啡店	2	2
购物	商场	0.5, 0.45, 0.4, 0.35, 0.3	2
购物	便利店	3	3
休闲	公园	1	1
	书店	1	1
	娱乐场所	1	1
公共服务	学校	1	1
	银行	1	1
	医院	1	1
总计		16	16

交叉口密度/(个/km²)	衰减率/%	适宜步行道路占比/%	衰减率/%	街区尺度/m	衰减率/%
>77	0	>88	0	<120	0
58~77	1	69~88	1	120~150	1
47~58	2	51~69	2	150~165	2
35~47	3	33~51	3	165~180	3
23~35	4	12~33	4	180~195	4
<23	5	<12	5	>195	5

污染物	迈皋桥	瑞金路	浦口	奥体中心	中华门	草场门	玄武湖	山西路	仙林大学城
PM_2.5	42.77	47.77	38.54	48.39	41.66	33.31	32.83	42.26	40.73
O₃	85.99	90.71	92.25	75.63	92.39	105.87	90.04	111.21	92.96

影响因子	与PM_2.5浓度相关系数R
道路长度_500 m (x₁)	0.585^*
道路长度_1000 m (x₂)	0.167
道路长度_1500 m (x₃)	0.159
道路长度_2000 m (x₄)	0.072
水域面积_500 m (x₅)	-0.557
水域面积_1000 m (x₆)	-0.627^*
水域面积_1500 m (x₇)	-0.623^*
水域面积_2000 m (x₈)	-0.629^*
建设用地面积_500 m (x₉)	0.713^**
建设用地面积_1000 m (x₁₀)	0.793^**
建设用地面积_1500 m (x₁₁)	0.710^**
建设用地面积_2000 m (x₁₂)	0.402
植被面积_500 m (x₁₃)	-0.510
植被面积_1000 m (x₁₄)	-0.784^**
植被面积_1500 m (x₁₅)	-0.679^**
植被面积_2000 m (x₁₆)	-0.550
人口密度(x₁₇)	0.168
工业污染影响(x₁₈)	0.232

监测点	草场门	中华门	瑞金路	玄武湖	迈皋桥	山西路	仙林大学城	奥体中心	浦口
预测值	34.95	41.44	47.45	32.61	40.12	44.01	40.18	48.73	38.74
差值	1.64	-0.22	-0.32	-0.22	-2.65	1.75	-0.55	0.34	0.20
误差率/%	4.92	-0.52	-0.68	-0.66	-6.20	4.13	-1.35	0.70	0.51