欧洲城市布局类型对城市热岛、空气污染、二氧化碳排放和死亡率的影响:一种数据科学方法。

IF 24.1 1区 医学 Q1 ENVIRONMENTAL SCIENCES
Tamara Iungman MPH , Sasha Khomenko PhD , Evelise Pereira Barboza MPH , Marta Cirach MSc , Karen Gonçalves PhD , Paula Petrone PhD , Thilo Erbertseder PhD , Prof Hannes Taubenböck PhD , Tirthankar Chakraborty PhD , Prof Mark Nieuwenhuijsen PhD
{"title":"欧洲城市布局类型对城市热岛、空气污染、二氧化碳排放和死亡率的影响:一种数据科学方法。","authors":"Tamara Iungman MPH ,&nbsp;Sasha Khomenko PhD ,&nbsp;Evelise Pereira Barboza MPH ,&nbsp;Marta Cirach MSc ,&nbsp;Karen Gonçalves PhD ,&nbsp;Paula Petrone PhD ,&nbsp;Thilo Erbertseder PhD ,&nbsp;Prof Hannes Taubenböck PhD ,&nbsp;Tirthankar Chakraborty PhD ,&nbsp;Prof Mark Nieuwenhuijsen PhD","doi":"10.1016/S2542-5196(24)00120-7","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO<sub>2</sub>, CO<sub>2</sub> per person emissions, and age-standardised mortality.</p></div><div><h3>Methods</h3><p>We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal–Wallis test followed by a post-hoc Dunn's test.</p></div><div><h3>Findings</h3><p>We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO<sub>2</sub> exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO<sub>2</sub> emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types.</p></div><div><h3>Interpretation</h3><p>Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health.</p></div><div><h3>Funding</h3><p>Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.</p></div>","PeriodicalId":48548,"journal":{"name":"Lancet Planetary Health","volume":"8 7","pages":"Pages e489-e505"},"PeriodicalIF":24.1000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2542519624001207/pdfft?md5=751d84e8c8ca3e0c9ced350c68345759&pid=1-s2.0-S2542519624001207-main.pdf","citationCount":"0","resultStr":"{\"title\":\"The impact of urban configuration types on urban heat islands, air pollution, CO2 emissions, and mortality in Europe: a data science approach\",\"authors\":\"Tamara Iungman MPH ,&nbsp;Sasha Khomenko PhD ,&nbsp;Evelise Pereira Barboza MPH ,&nbsp;Marta Cirach MSc ,&nbsp;Karen Gonçalves PhD ,&nbsp;Paula Petrone PhD ,&nbsp;Thilo Erbertseder PhD ,&nbsp;Prof Hannes Taubenböck PhD ,&nbsp;Tirthankar Chakraborty PhD ,&nbsp;Prof Mark Nieuwenhuijsen PhD\",\"doi\":\"10.1016/S2542-5196(24)00120-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO<sub>2</sub>, CO<sub>2</sub> per person emissions, and age-standardised mortality.</p></div><div><h3>Methods</h3><p>We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal–Wallis test followed by a post-hoc Dunn's test.</p></div><div><h3>Findings</h3><p>We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO<sub>2</sub> exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO<sub>2</sub> emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types.</p></div><div><h3>Interpretation</h3><p>Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health.</p></div><div><h3>Funding</h3><p>Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.</p></div>\",\"PeriodicalId\":48548,\"journal\":{\"name\":\"Lancet Planetary Health\",\"volume\":\"8 7\",\"pages\":\"Pages e489-e505\"},\"PeriodicalIF\":24.1000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2542519624001207/pdfft?md5=751d84e8c8ca3e0c9ced350c68345759&pid=1-s2.0-S2542519624001207-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Lancet Planetary Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2542519624001207\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lancet Planetary Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2542519624001207","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

背景:世界正日益城市化。随着世界各地城市的不断发展,城市规划者和决策者必须了解不同的城市布局模式如何影响环境和人类健康。然而,以往的研究结果喜忧参半。我们的目的是根据当地气候带类别和开放街道地图中的街道设计变量来确定欧洲城市的布局类型,并评估它们与机动车流量、地表城市热岛强度、对流层二氧化氮、人均二氧化碳排放量和年龄标准化死亡率之间的关系:我们考虑了来自 31 个国家的 946 个欧洲城市,对其中 919 个欧洲城市进行了分析。数据以 250 米 × 250 米的网格单元分辨率收集。我们根据伯吉斯同心城市规划模型将所有城市划分为五个同心环,并计算每个环的所有变量的平均值。首先,为了识别不同的城市配置类型,我们采用了统一曲面逼近和投影降维方法,然后使用了 k-means 聚类算法。接下来,我们使用 Kruskal-Wallis 检验和 Dunn's 事后检验,评估了得出的城市配置类型之间在暴露量(包括 SUHI)和死亡率方面的统计差异:我们确定了欧洲城市的四种不同城市结构类型:紧凑型高密度城市(246 人)、开放式低层中密度城市(245 人)、开放式低层低密度城市(261 人)和绿色低密度城市(167 人)。紧凑型高密度城市面积小,人口密度高,自然区域较少。相比之下,绿色低密度城市面积大,人口密度低,自然区域和自行车道较多。开放式低层中低密度城市的面积为中小型,人口密度为中低水平,绿化面积为中低水平。与绿色低密度城市和开放式低层低密度城市相比,紧凑型高密度城市和开放式低层中密度城市的机动车流量和二氧化氮暴露量明显较高。此外,与所有其他城市结构类型相比,绿色低密度城市的 SUHI 效应明显较低。与绿色低密度城市相比,紧凑型高密度城市的人均二氧化碳排放量明显较低。最后,与所有其他城市布局类型相比,绿色低密度城市的死亡率明显较低:我们的研究结果表明,尽管紧凑型城市模式更具可持续性,但欧洲的紧凑型城市仍然面临着与环境质量和健康状况不佳有关的挑战。我们的研究结果对欧洲的城市和交通规划政策具有显著的影响,并有助于当前关于哪种城市模式能为环境、气候和健康带来最大益处的讨论:西班牙科学与创新部、国家研究机构、加泰罗尼亚自治区、红色流行病学和公共卫生生物研究中心,以及欧洲地平线项目 "用于决策的城市疾病负担估算"。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of urban configuration types on urban heat islands, air pollution, CO2 emissions, and mortality in Europe: a data science approach

Background

The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO2, CO2 per person emissions, and age-standardised mortality.

Methods

We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal–Wallis test followed by a post-hoc Dunn's test.

Findings

We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO2 exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types.

Interpretation

Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health.

Funding

Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
28.40
自引率
2.30%
发文量
272
审稿时长
8 weeks
期刊介绍: The Lancet Planetary Health is a gold Open Access journal dedicated to investigating and addressing the multifaceted determinants of healthy human civilizations and their impact on natural systems. Positioned as a key player in sustainable development, the journal covers a broad, interdisciplinary scope, encompassing areas such as poverty, nutrition, gender equity, water and sanitation, energy, economic growth, industrialization, inequality, urbanization, human consumption and production, climate change, ocean health, land use, peace, and justice. With a commitment to publishing high-quality research, comment, and correspondence, it aims to be the leading journal for sustainable development in the face of unprecedented dangers and threats.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信