Urban Climate最新文献

Comparison of PM2.5 around 1893 elementary schools and kindergartens in Tehran over different time windows

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-20 DOI: 10.1016/j.uclim.2024.102249

Mohammad Khanizadeh, Kazem Naddafi, Masud Yunesian, Gerard Hoek, Ramin Nabizadeh, Helen Suh, Sadegh Niazi, Reza Bayat, Fatemeh Momeniha, Mohammad Sadegh Hassanvand, Sasan Faridi

{"title":"Comparison of PM2.5 around 1893 elementary schools and kindergartens in Tehran over different time windows","authors":"Mohammad Khanizadeh, Kazem Naddafi, Masud Yunesian, Gerard Hoek, Ramin Nabizadeh, Helen Suh, Sadegh Niazi, Reza Bayat, Fatemeh Momeniha, Mohammad Sadegh Hassanvand, Sasan Faridi","doi":"10.1016/j.uclim.2024.102249","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102249","url":null,"abstract":"We employed a land use regression (LUR) model to estimate ambient fine particulate matter (PM<ce:inf loc=\"post\">2.5</ce:inf>) concentrations around elementary schools and kindergartens across Tehran, utilizing 138 predictor variables within buffers ranging from 100 to 2000 m. Among these, nine variables predicted the annual ambient PM<ce:inf loc=\"post\">2.5</ce:inf> concentration around elementary schools and kindergartens. The model demonstrated acceptable performance, as indicated by the magnitude of the coefficients of determination (R<ce:sup loc=\"post\">2</ce:sup> and adjusted R<ce:sup loc=\"post\">2</ce:sup>) and validation metrics such as K-fold cross-validation (K-foldCV) and leave-one-out cross-validation (LOOCV). R<ce:sup loc=\"post\">2</ce:sup>, adjusted R<ce:sup loc=\"post\">2</ce:sup>, K-foldCV R<ce:sup loc=\"post\">2</ce:sup> and LOOCV R<ce:sup loc=\"post\">2</ce:sup> were 0.74 and 0.68, 0.68, and 0.55, respectively. The predictor variables included green space, population density, the distance to secondary roads, water channels, fuel/gas stations, main squares, the number of parking lots and mosques. There is a substantial spatial inequality in annual concentration of ambient PM<ce:inf loc=\"post\">2.5</ce:inf> across Tehran as nearly all of the schools situated in the north experienced lower levels (< 35 μg/m<ce:sup loc=\"post\">3</ce:sup>) compared with those in the south (> 40 μg/m<ce:sup loc=\"post\">3</ce:sup>). This pattern observed for the Kindergartens across Tehran. Our findings highlight the importance of infrastructure design changes, such as expanding green spaces and relocating parking lots, to enhance air quality around schools and kindergartens.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"25 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867480","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}

引用次数: 0

Comparing extreme rainfall exposure to climate-focused planning efforts: A mixed methods analysis in the northeastern United States

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-20 DOI: 10.1016/j.uclim.2024.102258

Naomi Miller, Donovan Finn, Kevin A. Reed

{"title":"Comparing extreme rainfall exposure to climate-focused planning efforts: A mixed methods analysis in the northeastern United States","authors":"Naomi Miller, Donovan Finn, Kevin A. Reed","doi":"10.1016/j.uclim.2024.102258","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102258","url":null,"abstract":"This paper analyzes the motivation for climate planning at the local level in three states in the northeastern United States. Cataloging climate-focused plans in 461 coastal and riverine municipalities in New York, New Jersey, and Connecticut we compare these efforts to the incidence of extreme precipitation from 2000 to 2021 based on climatologies of precipitation derived from a large-scale meteorological dataset. Localities' experience with extreme precipitation and their climate planning status is also compared with a selection of socio-demographic indicators. For the region analyzed, climate-focused planning is relatively rare, but coastal communities experienced more frequent extreme precipitation events and appear to have engaged in more climate-focused planning relative to riverine communities and also are more likely to cite scientific evidence of climate change as justification for planning. Notably, some coastal communities engaged in climate-related planning despite having a higher proportion of Republican voters, who are typically more conservative and skeptical of both climate change and public policy efforts to address it. Finally, some storms, even when not climatologically extreme, nonetheless leave a lasting impression because of their impacts. These have significant implications for local efforts to address climate challenges, showing how extreme climatological events may drive government decisions and highlighting additional factors that may also amplify or impede planning for climate change.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"39 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867476","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}

引用次数: 0

Land-surface-physics-based downscaling versus conventional dynamical downscaling for high-resolution urban climate change information: The case study of two cities

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-20 DOI: 10.1016/j.uclim.2024.102228

Lingbo Xue, Quang-Van Doan, Hiroyuki Kusaka, Cenlin He, Fei Chen

{"title":"Land-surface-physics-based downscaling versus conventional dynamical downscaling for high-resolution urban climate change information: The case study of two cities","authors":"Lingbo Xue, Quang-Van Doan, Hiroyuki Kusaka, Cenlin He, Fei Chen","doi":"10.1016/j.uclim.2024.102228","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102228","url":null,"abstract":"This study for the first time examines the performance of the computationally-efficient land-surface-physics-based downscaling (LSP-DS) approach for high-resolution urban climate prediction by comparing it with the conventional dynamical downscaling (D-DS). LSP-DS utilizes the offline land-surface-modeling system HRLDAS, while D-DS employs the regional climate model WRF. Both approaches integrate the coupled land-surface and urban-canopy models. Simulations are driven by coarse-resolution reanalysis data to achieve 2-km climate downscaling, targeting two cities, Tokyo and Singapore. The findings reveal that LSP-DS can accurately reproduce the urban heat island (UHI) effect at high resolution, comparable with D-DS. LSP-DS even shows consistently better results for urban areas, across varying weather conditions such as heatwaves, non-heatwaves, dry, and rainy periods. Both methods show the same performance on the compound effects of heatwaves and UHI, with LSP-DS tending to simulate moderate UHI effects compared with D-DS. This study highlights the LSP-DS's potential as a computationally efficient and effective tool for urban climate downscaling, particularly to serve the next IPCC special report on climate change and cities. However, users should be mindful of the LSP-DS's limitations, such as the absence of two-way feedback with atmospheric physical and dynamical processes, when applying LSP-DS and explaining its results.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"26 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867482","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}

引用次数: 0

Evaluation of city-scale PALM model simulations and intra-urban thermal variability in Vienna, Austria using operational and crowdsourced data

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-20 DOI: 10.1016/j.uclim.2024.102245

Maja Žuvela-Aloise, Claudia Hahn, B. Hollósi

{"title":"Evaluation of city-scale PALM model simulations and intra-urban thermal variability in Vienna, Austria using operational and crowdsourced data","authors":"Maja Žuvela-Aloise, Claudia Hahn, B. Hollósi","doi":"10.1016/j.uclim.2024.102245","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102245","url":null,"abstract":"The PALM model system for urban applications is used to simulate the spatio-temporal thermal variability under heat wave conditions in Vienna, Austria. Model simulations covering the city area and its surroundings with a spatial resolution of 20 m are performed for four consecutive clear-sky hot days in August 2022. The results for hourly air temperature are evaluated with data from conventional weather stations of professional monitoring networks and quality-controlled data from private weather stations of the company NETATMO. The observations show high intra-urban variability during daytime and distinct spatial patterns at night with higher air temperatures in densely built city centre and lower temperatures in surrounding low-density urban region with prevailing green areas. The model shows lower variability than the observations, but similar large-scale spatial patterns. Direct comparison with observational data indicates a good model performance with a high coefficient of determination (R<ce:sup loc=\"post\">2</ce:sup> > 0.85), low bias (0.2 °C – 0.4 °C) and a root mean squared error (RMSE) of 1.8 °C. Evaluation of intra-urban thermal variability based on classification per land use and land cover type shows a statistically significant air temperature difference between the built-up areas and high vegetation surfaces during the night of about 1 °C in the observation and about 2 °C simulated by the model.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"53 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867481","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}

引用次数: 0

Examining urban agglomeration heat island with explainable AI: An enhanced consideration of anthropogenic heat emissions

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-20 DOI: 10.1016/j.uclim.2024.102251

Tianyu Sheng, Zhixin Zhang, Zhen Qian, Peilong Ma, Wei Xie, Yue Zeng, Kai Zhang, Zhuo Sun, Jian Yu, Min Chen

{"title":"Examining urban agglomeration heat island with explainable AI: An enhanced consideration of anthropogenic heat emissions","authors":"Tianyu Sheng, Zhixin Zhang, Zhen Qian, Peilong Ma, Wei Xie, Yue Zeng, Kai Zhang, Zhuo Sun, Jian Yu, Min Chen","doi":"10.1016/j.uclim.2024.102251","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102251","url":null,"abstract":"In the context of global warming and urbanization, regional economic concentration has increased anthropogenic heat emissions (AHE), posing significant threats to health and sustainability. The oversimplification of AHE in previous urban heat island studies hinders the development and implementation of AHE-reduction strategies aimed at mitigating high land surface temperature (LST). Therefore, this study reevaluates the regional heat island (RHI) effect in the Greater Bay Area (GBA) using multisource geo-big data. The analysis reveals that central RHI intensity (RHII) exceeds 3 °C, indicating a significant heat island. We constructed an integrated LightGBM model with four AHE and other classical indicators to fit LST, achieving an R<ce:sup loc=\"post\">2</ce:sup> of 0.8931. To improve the model's interpretability, we utilized SHapley Additive exPlanations (SHAP), which identified NDVI, DEM, and building AHE as significant indicators influencing LST in the GBA, each with SHAP values exceeding 0.25. Simulations of three intensity scenarios for tiered AHE reduction strategies show that a 10 % industrial AHE reduction in heavy industrial cities can cool 40 % of these areas and decrease RHII by more than 0.03 °C. This study provides actionable guidelines for targeted RHI mitigation in the GBA and provides valuable insights for evaluating RHI in other bay areas and urban agglomerations.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"13 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867478","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}

引用次数: 0

Vertical distribution analysis of PM2.5 concentration at urban highway intersections using low-cost sensors and unmanned aerial vehicles

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-19 DOI: 10.1016/j.uclim.2024.102243

Masoud Zarei, Bijan Yeganeh

{"title":"Vertical distribution analysis of PM2.5 concentration at urban highway intersections using low-cost sensors and unmanned aerial vehicles","authors":"Masoud Zarei, Bijan Yeganeh","doi":"10.1016/j.uclim.2024.102243","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102243","url":null,"abstract":"The high level of particulate matter (PM) is a critical issue in megacities and a major environmental challenge in urban management. Currently, the vertical distribution of PM concentration has been overlooked at traffic hot spots in the design and construction of high-rise buildings. This study assessed the vertical profile of PM<ce:inf loc=\"post\">2.5</ce:inf> concentration using low-cost sensors and drones to find the residents' exposure to PM<ce:inf loc=\"post\">2.5</ce:inf> at high-rise buildings. The results showed that the vertical pattern of the PM<ce:inf loc=\"post\">2.5</ce:inf> concentration on highways with lower traffic of light-duty vehicles (LDVs) was affected by height, with a 30 % increase in PM<ce:inf loc=\"post\">2.5</ce:inf> concentration at 15 m above the ground compared to ground-level concentration. In contrast, the concentration of PM<ce:inf loc=\"post\">2.5</ce:inf> on highways with more Heavy-Duty Vehicles (HDVs) traffic at ground levels was about 20 % higher than that at 15 m, gradually decreasing to 23 % at 30 m. The results revealed that PM<ce:inf loc=\"post\">2.5</ce:inf> concentration could increase with height in high-rise buildings near highway intersections instead of dilution, which would adversely affect the health of the residents. The findings of this study can be considered by urban planners and decision-makers to reduce PM<ce:inf loc=\"post\">2.5</ce:inf> exposure before settling the citizens in high-rise buildings.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"13 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867576","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}

引用次数: 0

Association between climate variability and injury-causing road traffic accidents in Singapore – A time-stratified case-crossover study

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-19 DOI: 10.1016/j.uclim.2024.102257

Rae Chua, Yih Yng Ng, Andrew F.W. Ho, Joel Aik

引用次数: 0

A systematic review of justice integration to climate resilience: Current trends and future directions

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-19 DOI: 10.1016/j.uclim.2024.102250

Virginia Pellerey, Sara Torabi Moghadam, Patrizia Lombardi

{"title":"A systematic review of justice integration to climate resilience: Current trends and future directions","authors":"Virginia Pellerey, Sara Torabi Moghadam, Patrizia Lombardi","doi":"10.1016/j.uclim.2024.102250","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102250","url":null,"abstract":"Climate resilience has been adopted as a systematic approach for facing climate change. Although the concept of resilience received criticism for failing to address the issues of power imbalance and conservatism, recent approaches include diverse justice perspectives as pathways to address these concerns. However, the lack of clarity regarding the diverse definitions of justice and their relationship to climate resilience hinders our understanding of how to effectively integrate urban climate resilience and justice. This study offers a systematic review of literature on justice and climate resilience in the urban context with the intent of (i) identifying articles addressing justice and climate resilience and classifying them according to the form of justice and resilience framing, (ii) studying trends in the current literature, (iii) identifying research gaps, and (iv) reflecting on the possibility for integration between justice and resilience in different phases of the resilience-building process and proposing future insights. In particular, the results emphasize the importance of (1) enhancing system thinking using people-centered approaches, (2) focusing on the social implications of climate actions, and (3) evaluating different timeframes. The study concludes by suggesting policymaking and research strategies for facilitating the transition toward just and climate-resilient cities.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"52 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867484","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}

引用次数: 0

Evidence on local climate policies achieving emission reduction targets by 2030

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-19 DOI: 10.1016/j.uclim.2024.102242

Camilo Franco, Giulia Melica, Valentina Palermo, Paolo Bertoldi

{"title":"Evidence on local climate policies achieving emission reduction targets by 2030","authors":"Camilo Franco, Giulia Melica, Valentina Palermo, Paolo Bertoldi","doi":"10.1016/j.uclim.2024.102242","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102242","url":null,"abstract":"Local governments play a crucial role in combating climate change. They directly engage with citizens, impact their daily lives, and implement local policies to meet mitigation goals. This paper focuses on identifying specific policy themes that significantly contribute to achieving 2030 mitigation targets, thereby supporting local governments in developing effective climate action plans. We developed an innovative machine learning methodology to extract policy topics and evaluate their impact on meeting committed mitigation targets. This approach includes a new stopping criterion for Structural Topic Modeling. We applied this methodology to a sample of 744 Global Covenant of Mayors signatories, each committed to reducing a percentage of their baseline emissions by 2030. Our findings reveal that policies addressing building integration and transport modal shift, among others, show a strong positive correlation with the likelihood of meeting emissions reduction targets. By leveraging machine learning techniques, our methodology effectively categorizes diverse individual policies into more cohesive topics, facilitating knowledge sharing among committed cities and enhancing the overall effectiveness of climate action strategies.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"268 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867485","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}

引用次数: 0

Ambient temperature-related attributable risk for emergency asthma hospitalizations and length of stay in Hong Kong

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-18 DOI: 10.1016/j.uclim.2024.102240

Hong Qiu, Shengzhi Sun, Tze-Wai Wong, Xing Qiu, Kin-Fai Ho, Eliza Lai-Yi Wong

{"title":"Ambient temperature-related attributable risk for emergency asthma hospitalizations and length of stay in Hong Kong","authors":"Hong Qiu, Shengzhi Sun, Tze-Wai Wong, Xing Qiu, Kin-Fai Ho, Eliza Lai-Yi Wong","doi":"10.1016/j.uclim.2024.102240","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102240","url":null,"abstract":"We aimed to examine the association of ambient temperature with asthma exacerbations and assess the temperature-attributable disease burden changes. Daily count of asthma emergency hospitalizations and corresponding length of hospital stay, daily mean temperature, relative humidity, and air pollution concentrations from 2004 to 2019 in Hong Kong were collected. Time-series quasi-Poisson model integrated with the distributed-lag-nonlinear model was used to examine the relationships of temperature with asthma hospitalizations and length of stay. Measures of the risk attributable to nonoptimal temperature were calculated to summarize the disease burden and hospital utilization for periods of 2004–2011 and 2012–2019, respectively, and compared the temporal changes. Significantly higher risks at cold/cool temperatures for both admission counts and bed-days were found. Around 19.7 % (95 % CI: 14.1–24.3 %) of hospitalization counts and 22.6 % (95 % CI: 15.5–28.4 %) of bed-days were attributed to ambient temperature, which mainly occurred on cold and cool days. Compared with the early period of 2004–2011, the cold temperature-related attributable fraction in 2012–2019 decreased from 11.0 % to 8.9 % (<ce:italic>p</ce:italic> = 0.005) for admission counts but increased from 10.8 % to 12.6 % (<ce:italic>p</ce:italic> = 0.003) for bed-days. Hospital utilization and expenditure due to the longer hospital stays during cold days would play an adverse role in the healthcare system.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"20 6 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867487","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}

引用次数: 0