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
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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PM2.5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。
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. PM2.5 and O3 were selected as representative air pollutants for concentration simulation for their significant hazard. The concentration of PM2.5 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 PM2.5 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.
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. PM2.5 and O3 were selected as representative air pollutants for concentration simulation for their significant hazard. The concentration of PM2.5 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 PM2.5 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.
引文
陈莉,白志鹏,苏笛,等.2009.利用LUR模型模拟天津市大气污染物浓度的空间分布[J].中国环境科学,29(7):685-691.[Chen L,Bai Z P,Su D,et al.2009.Application of land use regression to simulate ambient air PM10and NO2concentration in Tianjin City.China Environmental Science,29(7):685-691.]
陈曦,冯建喜,Pnina Plaut.2018.基于暴露视角的城市健康空间公平性研究:以南京为例[J].城乡规划,(3):27-33.[Chen X,Feng J X,Pnina P.2018.Urban health equity from the exposure perspective:A case study of Nanjing.Urban and Rural Planning,(3):27-33.]
陈泳,毛婕,奚文沁,等.2016.机动化时代大城市居民步行行为特征与需求分析:以上海中心城区为例[J].现代城市研究,(7):103-112.[Chen Y,Mao J,Xi W Q,et al.2016.Pedestrian travel behavior and needs in large Chinese cities in the motorization age:A case study of the Shanghai central city.Modern Urban Research,(7):103-112.]
冯建喜,黄旭,汤爽爽.2017.客观与主观建成环境对老年人不同体力活动影响机制研究:以南京为例[J].上海城市规划,(3):17-23.[Feng J X,Huang X,Tang S S.2017.Comparing the influences of objective and subjective built environments on physical activities participation among the elderly:A case study of Nanjing,China.Shanghai Urban Planning Review,(3):17-23.]
何为,黄贤金.2012.半城市化:中国城市化进程中的两类异化现象研究[J].城市规划学刊,(2):24-32.[He W,Huang X J.2012.Incomplete urbanization:A research on China's urbanization.Urban Planning Forum,(2):24-32.]
黄建中,胡刚钰.2016.城市建成环境的步行性测度方法比较与思考[J].西部人居环境学刊,31(1):67-74.[Huang JZ,Hu G Y.2016.Comparison and thinking of the walkability measure methods on urban built environment.Journal of Human Settlements in West China,31(1):67-74.]
焦利民,许刚,赵素丽,等.2015.基于LUR的武汉市PM2.5浓度空间分布模拟[J].武汉大学学报(信息科学版),40(8):1088-1094.[Jiao L M,Xu G,Zhao S L,et al.2015.LUR-based simulation of the spatial distribution of PM2.5of Wuhan.Geomatics and Information Science of Wuhan University,40(8):1088-1094.]
刘永红,余志,黄艳玲,等.2011.城市空气污染分布不均匀特征分析[J].中国环境监测,27(3):93-96.[Liu Y H,Yu Z,Huang Y L,et al.2011.Characteristic analysis on uneven distribution of air pollution in cities.Environmental Monitoring in China,27(3):93-96.]
卢银桃,王德.2012.美国步行性测度研究进展及其启示[J].国际城市规划,27(1):10-15.[Lu Y T,Wang D.2012.Walkability measuring in America and its enlightenment.Urban Planning International,27(1):10-15.]
马静,柴彦威,符婷婷.2017.居民时空行为与环境污染暴露对健康影响的研究进展[J].地理科学进展,36(10):1260-1269.[Ma J,Chai Y W,Fu T T.2017.Progress of research on the health impact of people's space-time behavior and environmental pollution exposure.Progress in Geography,36(10):1260-1269.]
王叶晴,段小丽,李天昕,等.2012.空气污染健康风险评价中暴露参数的研究进展[J].环境与健康杂志,29(2):104-108.[Wang Y Q,Duan X L,Li T X,et al.2012.Inhalation exposure factors in health risk assessment.Journal of Environment and Health,29(2):104-108.]
吴健生,秦维,彭建,等.2014.基于步行指数的城市日常生活设施配置合理性评估:以深圳市福田区为例[J].城市发展研究,(10):49-56.[Wu J S,Qin W,Peng J,et al.2014.The evaluation of walkability and daily facility distribution reasonability of Futian District,Shenzhen based on walk score.Urban Development Studies,(10):49-56.]
游燕,白志鹏.2012.大气颗粒物暴露与健康效应研究进展[J].生态毒理学报,7(2):123-132.[You Y,Bai Z P.2012.Research advances in exposure to ambient particulate matter and health effects.Asian Journal of Ecotoxicolog,7(2):123-132.]
张延吉,秦波,唐杰.2018.基于倾向值匹配法的城市建成环境对居民生理健康的影响[J].地理学报,73(2):333-345.[Zhang Y Z,Qin B,Tang J.2018.The impact of urban built environment on residential physical health:Based on propensity score matching.Acta Geographica Sinica,73(2):333-345.]
Brauer M,Hoek G,Smit H A,et al.2007.Air pollution and development of asthma,allergy and infections in a birth cohort[J].European Respiratory Journal,29(5):879-888.
Brunekreef B,Holgate S T.2002.Air pollution and health[J].Lancet,360:1233-1242.
Charles E O,George J S,Percy H T.1957.The measurement of meaning[M].London,UK:Urbana,University of Illinois Press.
Fang T B,Lu Y.2011.Constructing a near real-time spacetime cube to depict urban ambient air pollution scenario[J].Transactions in GIS,15(5):635-649.
Feng J X.2016.The built environment and active travel:Evidence from Nanjing,China[J].International Journal of Environmental Research and Public Health,13(3):301-314.
Gehl J,Gemzoe L.1996.Public space public life[M].Copenhagen,Denmark:The Danish Architectural Press.
Hoek G,Beelen R,Hoogh K D,et al.2008.A review of land-use regression models to assess spatial variation of outdoor air pollution[J].Atmospheric Environment,42(33):7561-7578.
Leung Y,Leung K S,Wong M H,et al.2018.An integrated web-based air pollution decision support system-a prototype[J].International Journal of Geographical Information Science,32(9):1-28.
Marshall J,Nethery E,Brauer M.2008.Within-urban variability in ambient air pollution:Comparison of estimation methods[J].Atmospheric Environment,42(6):1359-1369.
Nazelle A D,Rodríguez D A,Crawfordbrown D.2009.The built environment and health:Impacts of pedestrian-friendly designs on air pollution exposure[J].Science of the Total Environment,407(8):2525-2535.
Owen N,Cerin E,Leslie E,et al.2007.Neighborhood walkability and the walking behavior of australian adults[J].American Journal of Preventive Medicine,33(5):387-395.
Sallis J F,Saelens B E,Frank L D,et al.2009.Neighborhood built environment and income:Examining multiple health outcomes[J].Social Science&Medicine,68(7):1285-1293.
Yang J,French S.2013.The travel-obesity connection:Discerning the impacts of commuting trips with the perspective of individual energy expenditure and time use[J].Environment&Planning B:Planning&Design,40(4):617-629.
(1)PM2.5的污染情况在每年冬季至次年春季相对严重,但O3在冬季污染情况不严重,之后随着气温升高污染情况逐渐加重,由于本文选取PM2.5与O3作为代表性空气污染物,需要同时考虑二者不同季节的污染情况,最终选用春季数据进行研究。
陈曦,冯建喜,Pnina Plaut.2018.基于暴露视角的城市健康空间公平性研究:以南京为例[J].城乡规划,(3):27-33.[Chen X,Feng J X,Pnina P.2018.Urban health equity from the exposure perspective:A case study of Nanjing.Urban and Rural Planning,(3):27-33.]
陈泳,毛婕,奚文沁,等.2016.机动化时代大城市居民步行行为特征与需求分析:以上海中心城区为例[J].现代城市研究,(7):103-112.[Chen Y,Mao J,Xi W Q,et al.2016.Pedestrian travel behavior and needs in large Chinese cities in the motorization age:A case study of the Shanghai central city.Modern Urban Research,(7):103-112.]
冯建喜,黄旭,汤爽爽.2017.客观与主观建成环境对老年人不同体力活动影响机制研究:以南京为例[J].上海城市规划,(3):17-23.[Feng J X,Huang X,Tang S S.2017.Comparing the influences of objective and subjective built environments on physical activities participation among the elderly:A case study of Nanjing,China.Shanghai Urban Planning Review,(3):17-23.]
何为,黄贤金.2012.半城市化:中国城市化进程中的两类异化现象研究[J].城市规划学刊,(2):24-32.[He W,Huang X J.2012.Incomplete urbanization:A research on China's urbanization.Urban Planning Forum,(2):24-32.]
黄建中,胡刚钰.2016.城市建成环境的步行性测度方法比较与思考[J].西部人居环境学刊,31(1):67-74.[Huang JZ,Hu G Y.2016.Comparison and thinking of the walkability measure methods on urban built environment.Journal of Human Settlements in West China,31(1):67-74.]
焦利民,许刚,赵素丽,等.2015.基于LUR的武汉市PM2.5浓度空间分布模拟[J].武汉大学学报(信息科学版),40(8):1088-1094.[Jiao L M,Xu G,Zhao S L,et al.2015.LUR-based simulation of the spatial distribution of PM2.5of Wuhan.Geomatics and Information Science of Wuhan University,40(8):1088-1094.]
刘永红,余志,黄艳玲,等.2011.城市空气污染分布不均匀特征分析[J].中国环境监测,27(3):93-96.[Liu Y H,Yu Z,Huang Y L,et al.2011.Characteristic analysis on uneven distribution of air pollution in cities.Environmental Monitoring in China,27(3):93-96.]
卢银桃,王德.2012.美国步行性测度研究进展及其启示[J].国际城市规划,27(1):10-15.[Lu Y T,Wang D.2012.Walkability measuring in America and its enlightenment.Urban Planning International,27(1):10-15.]
马静,柴彦威,符婷婷.2017.居民时空行为与环境污染暴露对健康影响的研究进展[J].地理科学进展,36(10):1260-1269.[Ma J,Chai Y W,Fu T T.2017.Progress of research on the health impact of people's space-time behavior and environmental pollution exposure.Progress in Geography,36(10):1260-1269.]
王叶晴,段小丽,李天昕,等.2012.空气污染健康风险评价中暴露参数的研究进展[J].环境与健康杂志,29(2):104-108.[Wang Y Q,Duan X L,Li T X,et al.2012.Inhalation exposure factors in health risk assessment.Journal of Environment and Health,29(2):104-108.]
吴健生,秦维,彭建,等.2014.基于步行指数的城市日常生活设施配置合理性评估:以深圳市福田区为例[J].城市发展研究,(10):49-56.[Wu J S,Qin W,Peng J,et al.2014.The evaluation of walkability and daily facility distribution reasonability of Futian District,Shenzhen based on walk score.Urban Development Studies,(10):49-56.]
游燕,白志鹏.2012.大气颗粒物暴露与健康效应研究进展[J].生态毒理学报,7(2):123-132.[You Y,Bai Z P.2012.Research advances in exposure to ambient particulate matter and health effects.Asian Journal of Ecotoxicolog,7(2):123-132.]
张延吉,秦波,唐杰.2018.基于倾向值匹配法的城市建成环境对居民生理健康的影响[J].地理学报,73(2):333-345.[Zhang Y Z,Qin B,Tang J.2018.The impact of urban built environment on residential physical health:Based on propensity score matching.Acta Geographica Sinica,73(2):333-345.]
Brauer M,Hoek G,Smit H A,et al.2007.Air pollution and development of asthma,allergy and infections in a birth cohort[J].European Respiratory Journal,29(5):879-888.
Brunekreef B,Holgate S T.2002.Air pollution and health[J].Lancet,360:1233-1242.
Charles E O,George J S,Percy H T.1957.The measurement of meaning[M].London,UK:Urbana,University of Illinois Press.
Fang T B,Lu Y.2011.Constructing a near real-time spacetime cube to depict urban ambient air pollution scenario[J].Transactions in GIS,15(5):635-649.
Feng J X.2016.The built environment and active travel:Evidence from Nanjing,China[J].International Journal of Environmental Research and Public Health,13(3):301-314.
Gehl J,Gemzoe L.1996.Public space public life[M].Copenhagen,Denmark:The Danish Architectural Press.
Hoek G,Beelen R,Hoogh K D,et al.2008.A review of land-use regression models to assess spatial variation of outdoor air pollution[J].Atmospheric Environment,42(33):7561-7578.
Leung Y,Leung K S,Wong M H,et al.2018.An integrated web-based air pollution decision support system-a prototype[J].International Journal of Geographical Information Science,32(9):1-28.
Marshall J,Nethery E,Brauer M.2008.Within-urban variability in ambient air pollution:Comparison of estimation methods[J].Atmospheric Environment,42(6):1359-1369.
Nazelle A D,Rodríguez D A,Crawfordbrown D.2009.The built environment and health:Impacts of pedestrian-friendly designs on air pollution exposure[J].Science of the Total Environment,407(8):2525-2535.
Owen N,Cerin E,Leslie E,et al.2007.Neighborhood walkability and the walking behavior of australian adults[J].American Journal of Preventive Medicine,33(5):387-395.
Sallis J F,Saelens B E,Frank L D,et al.2009.Neighborhood built environment and income:Examining multiple health outcomes[J].Social Science&Medicine,68(7):1285-1293.
Yang J,French S.2013.The travel-obesity connection:Discerning the impacts of commuting trips with the perspective of individual energy expenditure and time use[J].Environment&Planning B:Planning&Design,40(4):617-629.
(1)PM2.5的污染情况在每年冬季至次年春季相对严重,但O3在冬季污染情况不严重,之后随着气温升高污染情况逐渐加重,由于本文选取PM2.5与O3作为代表性空气污染物,需要同时考虑二者不同季节的污染情况,最终选用春季数据进行研究。