Urban Climate最新文献

{"title":"Urbanization effects on temperature: 1826–1850","authors":"Donald F. Vitaliano","doi":"10.1016/j.uclim.2024.102196","DOIUrl":"10.1016/j.uclim.2024.102196","url":null,"abstract":"<div><div>Mean, minimum and maximum monthly temperatures for 58 stations in New York State covering the period 1826–1850 are used to estimate a random effects panel regression. Controlling for latitude, elevation and seasonality, a statistically significant positive effect of population on minimum temperature is detected. At the mean population of 8500, the estimated effect is 0.19 °F (0.105 °C), which is consistent with published estimates for later periods. Mean and maximum temperature effects are +0.06 °F (+0.033 °C) and − 0.05 °F (−0.027 °C), respectively, but are not statistically significant. Microclimate and other unmeasured weather station heterogeneity is captured as a random ‘effects’ distribution variable, a novel treatment. Heat island effects appear to exist at very low levels of population when energy was based on animals and water power, perhaps due to loss of greenspace. Based on these results urbanization could contribute as much as 27.5 % to 41 % of the centennial temperature rise in New York.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102196"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating impacts of micro-scale land use/land cover change on urban thermal comfort zone in Rajshahi, Bangladesh: A GIS and remote sensing based approach","authors":"Md. Shakil Ar Salan ,&nbsp;Mohammad Amir Hossain Bhuiyan","doi":"10.1016/j.uclim.2024.102187","DOIUrl":"10.1016/j.uclim.2024.102187","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Rapid urban growth causes significant decrease in green cover which ultimately results higher temperature and strongest Urban Thermal Field Variance Index (UTFVI) effect. Rajshahi has the highest heat index score after the southwest region. Hence, Rajshahi city is particularly vulnerable to heat waves. There is a major gap in exploring the micro-scale thermal conditions in Rajshahi. The primary purpose of this study is to evaluate urban ecological health in the four major urbanized zones of Rajshahi City Corporation (RCC) area namely, City Centre, Eastern Fringe, Western Fringe and Northern Fringe over the past three decades (1992–2022). Land Use/Land Cover (LULC) variations, ecological balance, and their effects on the thermal environment at various scales have all been extensively analyzed using an integrated approach of geographic information systems (GIS) and remote sensing (RS). Landsat satellite images with a 30 m spatial resolution were used to carry out this micro-scale study. In ENVI 5.3 software, the Support Vector Machines (SVM) algorithm was used for its accuracy and popularity in image classification. Images from the past three decades were classified at five-year intervals using SVM, relying on specific training procedures. Four land cover indices are utilized to assess the geographical and temporal differences in Land Surface Temperature (LST) caused by land cover. Statistical relationship between various land cover indices and LST was performed using Statistical Package/Program for Social Sciences (SPSS). The overall increase of urban area during the study period was 53.61 %, resulting in a concentration of 28.09 km&lt;sup&gt;2&lt;/sup&gt; of urban area (58.45 %) in 2022 from 2.32 km&lt;sup&gt;2&lt;/sup&gt; (4.83 %) of 1992. The directional analysis of Thermal Comfort Zone (TCZ) reveals a significant decrease of thermal comfort environment due to loss of green space in NE to NW region during the study period. The regression analysis among LULC and LST revealed significant negative relation (&lt;em&gt;p&lt;/em&gt; &lt; 0.05) for water body and vegetation cover while the relationship is positive for urban area which concluded that urban centres experienced the most substantial LST increases, as evidenced by the study's observation of a substantial increase in higher temperature zones. This urban encroachment, which is influenced by factors such as population growth and economic development, has resulted in a reduction in comfortable thermal zones, which has exacerbated the urban heat island effect and impacted the ecological sustainability of urban areas. By avoiding concentrated impermeable surfaces, such as built-up areas, and boosting green cover, urban development can effectively mitigate the effects of LST and UTFVI. Again, effective distribution of LULC can play a crucial role in mitigating the effects to a significant extent. The findings of this study reflect the necessity of proper sustainable solution through the successful implementation of urban ","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102187"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards better understanding the urban environment and its interactions with regional climate change - The WCRP CORDEX Flagship Pilot Study URB-RCC","authors":"Gaby S. Langendijk ,&nbsp;Tomas Halenka ,&nbsp;Peter Hoffmann ,&nbsp;Marianna Adinolfi ,&nbsp;Aitor Aldama Campino ,&nbsp;Olivier Asselin ,&nbsp;Sophie Bastin ,&nbsp;Benjamin Bechtel ,&nbsp;Michal Belda ,&nbsp;Angelina Bushenkova ,&nbsp;Angelo Campanale ,&nbsp;Kwok Pan Chun ,&nbsp;Katiana Constantinidou ,&nbsp;Erika Coppola ,&nbsp;Matthias Demuzere ,&nbsp;Quang-Van Doan ,&nbsp;Jason Evans ,&nbsp;Hendrik Feldmann ,&nbsp;Jesus Fernandez ,&nbsp;Lluís Fita ,&nbsp;Jiacan Yuan","doi":"10.1016/j.uclim.2024.102165","DOIUrl":"10.1016/j.uclim.2024.102165","url":null,"abstract":"<div><div>High-quality climate information tailored to cities' needs assists decision makers to prepare for and adapt to climate change impacts, as well as to support the targeted transition towards climate resilient cities. During the last decades, two main modelling approaches emerged to understand and analyse the urban climate and to generate information. Firstly, meso- and microscale urban climate models commonly resolve the street to city scale climate (1 m to 1 km) through simulating short “weather” type episodes, possibly under climate change conditions. Secondly, regional climate models (RCMs) are currently approaching the kilometer scale grid resolutions (1–4 km) and becoming increasingly relevant to understand the interactions of cities with the regional climate on timescales from decades up to a century. Therefore, the WCRP CORDEX Flagship Pilot Study “<em>URBan environments and Regional Climate Change (FPS URB-RCC)”</em> brings together the urban climate modelling community and the RCM community and focuses on understanding the interactions between urban areas and regional climate change, with the help of coordinated experiments with an RCM ensemble having refined urban representations. This paper presents the FPS URB-RCC, its main aims, as well as the initial steps taken. The FPS URB-RCC advances urban climate projections and information to support evidence-based climate action towards climate resilient cities.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102165"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Jason Ching and the development of an Urban Climate Science: An introduction to the special issue on the World Urban Database Access Portal Tools (WUDAPT)","authors":"Gerald Mills ,&nbsp;Saravanan Arunachalam ,&nbsp;Yuan Shi ,&nbsp;Alexander Baklanov","doi":"10.1016/j.uclim.2024.102179","DOIUrl":"10.1016/j.uclim.2024.102179","url":null,"abstract":"","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102179"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exposure to hourly ambient temperature and temperature change between neighboring days and risk of emergency department visits for cause-specific cardiovascular disease","authors":"Kun Yuan ,&nbsp;Xin Lv ,&nbsp;Yangchang Zhang ,&nbsp;Ruiyi Liu ,&nbsp;Tian Liang ,&nbsp;Zhenyu Zhang ,&nbsp;Wangnan Cao ,&nbsp;Lizhi Wu ,&nbsp;Shengzhi Sun","doi":"10.1016/j.uclim.2024.102197","DOIUrl":"10.1016/j.uclim.2024.102197","url":null,"abstract":"<div><div>Little is known regarding the association between hourly exposure to ambient temperature and temperature change between neighboring days (TCN) with the risk of emergency department (ED) visits for cardiovascular disease (CVD). We conducted a time-stratified case-crossover study among 1.03 million ED visits for CVD between 2016 and 2021 in Zhejiang Province, China. Our analysis reported a reversed J-shaped relationship between hourly ambient temperature and risk of total and cause-specific CVD, with cold having the most significant effects. The risk associated with extreme cold (2.5^th percentile of temperature distribution) peaked approximately 40 h after exposure, while the effects of extreme heat (97.5^th percentile) were most pronounced during the concurrent hour of exposure (lag 0 h). Additionally, a decline in TCN (negative TCN) was associated with a higher risk of CVD, hypertensive disease, and stroke. In contrast, an increase in TCN (positive TCN) was associated with a lower risk of cause-specific CVD. The risks of negative and positive TCN peaked on the day of exposure and two days after exposure, respectively. These findings suggest that exposure to non-optimal temperature and TCN may increase the risk of ED visits for total and cause-specific CVD shortly after exposure, primarily driven by cold and negative TCN.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102197"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The smarter the cleaner: Evaluating the impact of artificial intelligence on haze pollution","authors":"Changfei Nie ,&nbsp;Zhixiang Lu ,&nbsp;Yuan Feng","doi":"10.1016/j.uclim.2024.102202","DOIUrl":"10.1016/j.uclim.2024.102202","url":null,"abstract":"<div><div>This paper innovatively evaluates the level of artificial intelligence (AI) by counting AI firms and employs a two-way fixed-effects model to analyze the impact of AI on haze pollution (HP), using panel data of 264 Chinese cities from 2006 and 2021. It is found that AI is an effective means to reduce urban HP, and that for every 1 % increase in the number of urban AI firms, PM 2.5 is reduced by about 2.22 %. Regarding mechanisms, AI mainly reduces urban HP through two ways: stimulating technology innovation and promoting industrial structure upgrading. Heterogeneity tests show that the haze reduction effect of AI varies due to urban HP level, urban location and urban characteristics, and is more pronounced in cities with high HP, as well as in western cities, northern cities, cities of high administrative levels, and resource-based cities. Our findings provide new insights for policy makers to better utilize AI technology to reduce HP.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102202"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of modeling methods on urban flood processes at community scale","authors":"Jiahao Lv ,&nbsp;Jingming Hou ,&nbsp;Tian Wang ,&nbsp;Donglai Li ,&nbsp;Yuan Liu ,&nbsp;Shuhong Xue ,&nbsp;Guangzhao Chen ,&nbsp;Baojun Guan","doi":"10.1016/j.uclim.2024.102209","DOIUrl":"10.1016/j.uclim.2024.102209","url":null,"abstract":"<div><div>Constructing rainfall-runoff models at the community scale involves challenges due to varying data availability and the potential generalization of critical microtopographical features or the use of different modeling approaches. It is crucial and urgent that the differences among various modeling methods are understood under different external boundary conditions. This work examines the synergistic relationship between these modeling approaches and the LID facilities within communities, while also considering the impact of key microtopographical features on runoff processes. The study finds that: (1) Full hydrodynamic models exhibit significant biases at lower cumulative rainfall levels, which diminish as cumulative rainfall increases. Simulation errors reduce notably after accounting for downspouts, yet considering LID facilities cause overall increase in errors. (2) LID facilities enhance runoff control at lower cumulative rainfall levels but reduce it at higher cumulative rainfall levels. (3) Directly connecting downspouts to rain gardens significantly reduces inundated area, volume, and peak flow, enhancing the regulatory efficiency of LID facilities. (4) Surface and subsurface runoff processes at the community scale show limited sensitivity to changes in rain garden overflow well heights during lower cumulative rainfall levels. This study offers insights into selecting appropriate community-scale rainfall-runoff modeling methods under various boundary conditions.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102209"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Providing support for urban planning through investigating the cooling influence of park in Northern China: A case study of Xi'an","authors":"Kai Xin ,&nbsp;Jingyuan Zhao ,&nbsp;ZhaoXin Li ,&nbsp;Yujin Yang ,&nbsp;Tianhui Wang ,&nbsp;Weijun Gao","doi":"10.1016/j.uclim.2024.102221","DOIUrl":"10.1016/j.uclim.2024.102221","url":null,"abstract":"<div><div>Urban parks are widely acknowledged for their role in mitigating the urban heat island effect and primarily function as spaces for relaxation and recreation for nearby residents. This study aims to guide land use planning around parks by evaluating the coupling mechanism between spatial morphology, wind patterns, distance to the park boundary (DTPB) and Park cooling island (PCI) intensity. PCI intensity was investigated through field measurements and numerical simulations in Xi'an. Multiple regression and sensitivity analyses were conducted to identify factors influencing the park's cooling effect, with human thermal comfort assessed using Physiological Equivalent Temperature (PET). The main results indicate that the most pronounced PCI intensity occurs at night, reaching 0.83 °C. Additionally, the average degree of linear correlation between temperature and DTPB in the downwind area (R² = 0.82) is higher than that in the upwind area (R² = 0.33). In the downwind area, DTPB is the primary factor affecting PCI, surpassing wind speed and sky view factor (SVF), whereas SVF is the crucial element in reducing PCI intensity in the upwind area. This paper supplements the fundamental theoretical understanding of how factors influence the PCI effect in Northwest China, thereby supporting urban land use planning around urban parks.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102221"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revealing the future complexity of urban water scarcity and drought via support vector machine: Case from semi-arid Bursa urban area","authors":"Semanur Coskun ,&nbsp;Abdullah Akbas","doi":"10.1016/j.uclim.2024.102211","DOIUrl":"10.1016/j.uclim.2024.102211","url":null,"abstract":"<div><div>The Mediterranean Basin is a significant area will be affected by drought and water scarcity in future. In this context, Bursa urban area, the fourth largest city in terms of population in Türkiye was used for quantification. A high-resolution global climate model of MPI-ESM-MR based RCP4.5 and 8.5, and population projections based on arithmetic and exponential growth models until 2100 was utilised. Support Vector Machine (SVM) regression was established between observed precipitation, evapotranspiration, runoff and reservoir volume for the reference period. Climate model outputs like precipitation and derived outputs such as evapotranspiration based on Penman-Monteith, runoff from SCS-Curve Number were used for SVM future dam volume prediction. Reference (observed data) and near and distant future (projected) dam volumes were converted to the Standardized Reservoir Index (SRI), and water scarcity as water per capita was also calculated. As a result, increased droughts and extreme conditions are identified in the near and distant future compared to the reference period. In addition, decrease in water per capita was determined with respect to the reference period. Therefore, results demonstrate that water scarcity is worsened by both semi-arid climate and population in urban area. Hence, water management in urban areas should address climatic variability and economic processes together.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102211"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From thermal demand characterization to accurate evaluation: Exploring seasonal differences in outdoor thermal comfort of the elderly in China's communities","authors":"Yan Wang ,&nbsp;Liyuan Yin ,&nbsp;Qiwei Dong ,&nbsp;Fan Fei ,&nbsp;Wanxiang Yao ,&nbsp;Jiang Sun ,&nbsp;Zhongtian Jiang","doi":"10.1016/j.uclim.2024.102220","DOIUrl":"10.1016/j.uclim.2024.102220","url":null,"abstract":"<div><div>Influenced by rapid urbanization and an aging population, creating a healthy and comfortable outdoor environment for the elderly in urban residential communities has become increasingly important. This paper aims to investigate the outdoor thermal comfort characteristics of the elderly, using residential communities in Tianjin, China, as a case study. Initially, we clarified the differences in thermal demand between winter and summer of elderly residents through a combination of thermal environment measurements and thermal comfort questionnaires. Secondly, we developed a thermal comfort evaluation model for small-scale spaces in residential communities, identifying the intensity of multiple influences on the thermal environment. Thirdly, we created a new seasonal integrated thermal sensation evaluation model for the elderly using probit analysis. Finally, summarizing the above findings, we devised targeted strategies to enhance the microclimate for the elderly. The results show that: the percentage of the elderly who achieve comfort in winter is 17.2 % higher than in summer; the factors that had the greatest impact on the thermal environment in winter and summer were water bodies and greenery, respectively; and the new probability analysis model showed that the neutral temperature interval was 2.1 °C narrower than the conventional TSV-PET model in summer and 1.8 °C wider in winter.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102220"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}