Urban Climate最新文献_第2页

Developing local-climate-zone-based logarithmic law wind profile considering urban morphology

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-18 DOI: 10.1016/j.uclim.2024.102246

Shuai Kong, Lin Liu, Junliang Cao

{"title":"Developing local-climate-zone-based logarithmic law wind profile considering urban morphology","authors":"Shuai Kong, Lin Liu, Junliang Cao","doi":"10.1016/j.uclim.2024.102246","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102246","url":null,"abstract":"The spatial heterogeneity of building clusters creates a highly complex urban wind environment, making it difficult for traditional wind profile models to capture the spatial characteristics of urban wind. This study aims to investigate the impact of complex urban morphology on the wind environment characteristics, and thereby to establish an urban wind profile at local scale. Firstly, the Weather Research and Forecasting (WRF) model combined with Local Climate Zone (LCZ) method was used to simulate the urban wind field. Subsequently, the simulated data was validated against wind speed data from meteorological stations and sounding data. Finally, the logarithmic law wind profile parameters were analyzed corresponding to each LCZ type (LCZ1-LCZ6) within varying spatial extent by statistical methods, and thus the optimal parameters were obtained applicable to these types. The results indicated that roughness length and friction velocity were strongly correlated with the LCZ type; based on the spatial layout, the optimal ranges for each LCZ type were determined, with roughness length ranging from 5.70 m to 11.95 m and friction velocity ranging from 0.783 m/s to 0.883 m/s. Logarithmic law wind profiles were established applicable to each LCZ type.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"88 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867486","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

Quantifying urban hydrological processes effects on urban climate: A perspective from a novel parameterization scheme

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-17 DOI: 10.1016/j.uclim.2024.102232

Miao Yu, Jianping Guo, Guiqian Tang

引用次数: 0

Understanding the origins of urban particulate matter pollution based on high-density vehicle-based sensor monitoring and big data analysis

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-14 DOI: 10.1016/j.uclim.2024.102241

Yiheng Liang, Xiaohua Wang, Zhongzhen Dong, Xinfeng Wang, Shidong Wang, Shuchun Si, Jing Wang, Hai-Ying Liu, Qingzhu Zhang, Qiao Wang

{"title":"Understanding the origins of urban particulate matter pollution based on high-density vehicle-based sensor monitoring and big data analysis","authors":"Yiheng Liang, Xiaohua Wang, Zhongzhen Dong, Xinfeng Wang, Shidong Wang, Shuchun Si, Jing Wang, Hai-Ying Liu, Qingzhu Zhang, Qiao Wang","doi":"10.1016/j.uclim.2024.102241","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102241","url":null,"abstract":"This study presents an innovative method for air quality monitoring and identifying pollution sources in Rizhao, a coastal city in northern China, by deploying a network of low-cost sensors mounted on 102 taxis. Over a one-year period, we collected a set of high-resolution PM<ce:inf loc=\"post\">10</ce:inf> and PM<ce:inf loc=\"post\">2.5</ce:inf> data. Using big data analysis, including downwind-calm wind analysis, hotspot detection, and time-series clustering analysis, we traced the pollution back to the urban origins of pollutant. Our extensive study uncovered significant spatial and seasonal variations in PM<ce:inf loc=\"post\">10</ce:inf> and PM<ce:inf loc=\"post\">2.5</ce:inf> concentrations, pinpointing substantial PM<ce:inf loc=\"post\">10</ce:inf> emissions from steel plants and a notable influence of industrial activities on ambient PM<ce:inf loc=\"post\">2.5</ce:inf> concentrations. Through the application of bivariate polar plots and hotspot mapping, we linked major particulate matter sources to industrial activities especially steel plant emissions, and road traffic, which significantly elevated the particulate matter levels in residential and industrial zones. Our time-series clustering analysis further distinguishes traffic and industrial activities as key contributors to particulate matter pollution. This study advances the application of low-cost sensor technologies in urban air quality management and offers a detailed insight into the pollution sources and their diverse impacts on particulate matter levels in urban settings.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"7 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867578","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

Harnessing geographic information system and street view imagery for thermal gradient distribution auditing

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-14 DOI: 10.1016/j.uclim.2024.102248

Lang Zheng, Weisheng Lu, Jianxiang Huang, Fan Xue

{"title":"Harnessing geographic information system and street view imagery for thermal gradient distribution auditing","authors":"Lang Zheng, Weisheng Lu, Jianxiang Huang, Fan Xue","doi":"10.1016/j.uclim.2024.102248","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102248","url":null,"abstract":"Assessing and managing the thermal environment within urban streetscapes is of paramount importance for the health, livability, and ecological sustainability of metropolitan regions. However, due to a scarcity of high-precision historical street thermal environment data for prediction and modeling, existing urban thermal environment classification assessment studies suffer from low resolution (> 30 m) or limited research scope (e.g., community-level), resulting in less accurate and comprehensive insights. This study introduces an innovative framework for constructing large-scale urban street-level thermal gradients using classified samples derived from the spatial structural features of street points. The core of this framework lies in the k-means unsupervised classification algorithm. This approach integrates detailed local geographic information system (GIS) data with street view features, calculated through semantic segmentation of Google Street-View-Panorama using the DeepLabV3 model. This allows for the categorization of a vast array of high-precision street points based on spatial structural similarity, a key factor influencing the similarity of street thermal environment features. By selecting appropriate samples for on-site thermal environment measurements within each category and subsequently extrapolating this knowledge to the thermal environment classification of each category, this framework facilitates the rapid creation of high-precision street-level thermal gradient models across extensive urban areas.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"268 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867587","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

A novel ensemble framework based on intelligent weight optimization and multi-model fusion for air quality index prediction

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-14 DOI: 10.1016/j.uclim.2024.102233

Shijie Qian, Tian Peng, Rui He, Jie Chen, Xuedong Zhang, Muhammad Shahzad Nazir, Chu Zhang

{"title":"A novel ensemble framework based on intelligent weight optimization and multi-model fusion for air quality index prediction","authors":"Shijie Qian, Tian Peng, Rui He, Jie Chen, Xuedong Zhang, Muhammad Shahzad Nazir, Chu Zhang","doi":"10.1016/j.uclim.2024.102233","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102233","url":null,"abstract":"The accuracy of air quality prediction is crucial for public health and environmental management. This paper proposes a hybrid deep learning model based on TimesNet, Crossformer and Modified Honey Badger Algorithm (MHBA) for air quality prediction. First, the original air quality index (AQI) series is decomposed using Seasonal-Trend decomposition based on Loess (STL). Then, the decomposed three components are predicted separately using TimesNet and Crossformer, while the hyperparameters of TimesNet and Crossformer are optimized using the Metis algorithm. In addition, half uniform initialization and Levy flight are added to the original HBA algorithm to make up for its shortcomings of slow optimization search speed and the tendency to fall into local optimal position, and the MHBA algorithm is obtained. Finally, the MHBA algorithm is used to weight the component prediction results of the two models, and compare the advantages and disadvantages of different weighting methods, and select the optimal weighting method to get the final AQI prediction results. The experimental results show that the STL-Metis-MHBA-TC model reduces RMSE, MAE, and MAPE by 19–34 %, 22–38 %, and 22–44 %, respectively, compared to the Transformer model. Therefore, the STL-Metis-MHBA-TC hybrid model proposed in this paper can effectively improve the AQI prediction accuracy.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"24 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867579","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

Transboundary air pollution in coastal urban area in Japan: Transport model and positive matrix factorization analysis for SPM-PM2.5 and PM2.5

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-13 DOI: 10.1016/j.uclim.2024.102237

Kazunari Onishi, Keiya Yumimoto, Tomoaki Okuda, Akira Fukuike, Teruya Maki, Masanori Nojima, Masato Shinoda, Takeo Nakayama, Youichi Kurozawa, Zentaro Yamagata, Yasunori Kurosaki

{"title":"Transboundary air pollution in coastal urban area in Japan: Transport model and positive matrix factorization analysis for SPM-PM2.5 and PM2.5","authors":"Kazunari Onishi, Keiya Yumimoto, Tomoaki Okuda, Akira Fukuike, Teruya Maki, Masanori Nojima, Masato Shinoda, Takeo Nakayama, Youichi Kurozawa, Zentaro Yamagata, Yasunori Kurosaki","doi":"10.1016/j.uclim.2024.102237","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102237","url":null,"abstract":"Transboundary air pollutants have raised serious health concerns, particularly in regions with minimal local pollution sources. Distinguishing between local pollution and transboundary contributions is crucial for accurately assessing the health risks to local populations. This study aimed to analyze the differences in coarse and fine particulate matter and develop methods to obtain exposure data for epidemiological studies, thereby providing a scientific basis for public health interventions. We collected SPM-PM<ce:inf loc=\"post\">2.5</ce:inf> (physically excluded PM<ce:inf loc=\"post\">2.5</ce:inf> from SPM) and PM<ce:inf loc=\"post\">2.5</ce:inf> samples in Yonago City, a coastal urban area in Tottori Prefecture, Japan, from 19 October 2015 to 25 July 2016 using a novel slit jet impactor (MCAS-SJ). Positive matrix factorization analysis used heavy metal, ion, and carbon concentrations to identify pollutant sources. This study identified four major air pollution events during the sampling period, primarily attributed to transboundary transport. Episode I was dominated by nitric aerosols, Episodes II and III by Asian dust, and Episode IV by sulfate aerosols. An analysis using global chemical transport models and backward trajectories confirmed that these events verified the contribution of transboundary pollution. In conclusion, identifying the impact of transboundary pollution on local air quality enables an accurate risk assessment of populations. This study provides scientific evidence for developing effective public health strategies and preventive measures. Additionally, the methodology used in this study holds the potential for international contributions and future research applications, helping to address air pollution challenges on a broader scale.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"114 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867580","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

Analysis of ozone pollution causes under influence of extreme high temperatures and power rationing measures: Chengdu, China

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-11 DOI: 10.1016/j.uclim.2024.102239

Lijuan Lei, Miao Feng, Yi Zhang, Wei Li, Shishi Yang, Danlin Song, Yang Chen, Junjie Wang

{"title":"Analysis of ozone pollution causes under influence of extreme high temperatures and power rationing measures: Chengdu, China","authors":"Lijuan Lei, Miao Feng, Yi Zhang, Wei Li, Shishi Yang, Danlin Song, Yang Chen, Junjie Wang","doi":"10.1016/j.uclim.2024.102239","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102239","url":null,"abstract":"Ozone(O<ce:inf loc=\"post\">3</ce:inf>) pollution has become increasingly severe and persistent in recent years. A persistent O<ce:inf loc=\"post\">3</ce:inf> pollution event occurred in Chengdu in 2022 during a period of extreme high-temperature weather. In response, the government implemented power rationing measures to restrict industrial electricity consumption. Based on the observational data, an observation based model (OBM) and probability mass function (PMF) are used to study the effect of power rationing on the O<ce:inf loc=\"post\">3</ce:inf> formation mechanism. After power rationing, the temperature increased by 1.7 °C,despite the conditions for O<ce:inf loc=\"post\">3</ce:inf> generation were more favorable, the O<ce:inf loc=\"post\">3</ce:inf> concentration was reduced. This is mainly because the power rationing measures reduced non-methane hydrocarbons (NMHCs) by about 22.71 % and reduced the generation of organic peroxide radicals (RO<ce:inf loc=\"post\">2</ce:inf>), thereby suppressing O<ce:inf loc=\"post\">3</ce:inf> generation. The reduced NMHCs primarily came from solvent use sources. In recent years, extreme high-temperature days have occurred frequently, and the O<ce:inf loc=\"post\">3</ce:inf> pollution situation has become grim. This study seeks to understand the influence of human activities on O<ce:inf loc=\"post\">3</ce:inf> in Chengdu under extreme high-temperature conditions, emphasizes that O<ce:inf loc=\"post\">3</ce:inf> pollution prevention and control measures in Chengdu should consider addressing solvent use sources, reducing the NMHC, and the adopting of regional joint preventive and control measures, and provides references for other regions.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"22 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816599","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

Investigating the cooling impacts of Green Hearts in summer: A case study in the Changsha-Zhuzhou-Xiangtan urban agglomeration based on Weather Research Forecasting (WRF) simulations

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-10 DOI: 10.1016/j.uclim.2024.102235

Yipu Chen, Ran Hu, Komi Bernard Bedra

{"title":"Investigating the cooling impacts of Green Hearts in summer: A case study in the Changsha-Zhuzhou-Xiangtan urban agglomeration based on Weather Research Forecasting (WRF) simulations","authors":"Yipu Chen, Ran Hu, Komi Bernard Bedra","doi":"10.1016/j.uclim.2024.102235","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102235","url":null,"abstract":"Numerous studies have established that green spaces are crucial in combating urban heat islands (UHI). As ecological Green Hearts have been adopted in many multipolar urban agglomerations, this study questions their long-term impact on urban heat mitigation. Taking the “Green Heart” area of the Changsha-Zhuzhou-Xiangtan urban agglomeration, and utilizing land use datasets between 1990 and 2020, numerical simulations of near-ground air temperatures were conducted to analyze the temperature variations induced by the spatial dynamics and the land-use change inside the Green Heart. The findings reveal a 0.4 °C increase in urban temperatures caused by urban expansion. A “cool island effect” by the Green Heart is observed but the temperature difference achieved (2 °C to 4 °C) is no more significant than in city-scale parks and the cooling extent beyond the Green Heart's perimeter was insignificant. Doubling the construction land inside the Green Heart increased daytime and nighttime temperatures by 1.5 °C and 2.6 °C, respectively, suggesting the importance of maintaining forests. The long-term urban temperature fluctuations are arguably influenced more by the spatial transformations inside the cities than changes inside the Green Heart. These results imply that combating urban heat should prioritize city-centered cooling strategies and land-use control.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"86 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816600","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

Net impact of London Strand-Aldwych pedestrianisation project on air quality and noise

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-06 DOI: 10.1016/j.uclim.2024.102231

Arnout van Soesbergen, Mark Mulligan

{"title":"Net impact of London Strand-Aldwych pedestrianisation project on air quality and noise","authors":"Arnout van Soesbergen, Mark Mulligan","doi":"10.1016/j.uclim.2024.102231","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102231","url":null,"abstract":"Pedestrianisation in urban areas has the potential to reduce air and noise pollution but may lead to increased pollution in surrounding streets. To date, there are very few long-term monitoring studies that assess the net impacts of pedestrianisation on air quality and noise. This study uses a dense low-cost particulate matter and environmental noise monitoring network to assess the net impacts of the Strand-Aldwych pedestrianisation project (SAPP) in central London on particulate matter and noise pollution. Monitoring started before traffic was excluded from the Strand in June 2021 and continued through re-development works in 2022 and post-works in 2023. Collected particulate matter data was complemented with data from the Automatic Urban and Rural Network and London Air Quality Network sites. Results show a statistically significant decrease in NO<ce:inf loc=\"post\">x</ce:inf> and environmental noise pollution on the Strand between summer 2021 and summer 2023. PM<ce:inf loc=\"post\">2.5</ce:inf> levels have also decreased at street level on the Strand but have increased on Aldwych and other surrounding streets relative to concurrent background levels measured at roof level. PM<ce:inf loc=\"post\">2.5</ce:inf> is mostly driven by larger scale background inputs in central London and meteorological conditions while NO<ce:inf loc=\"post\">x</ce:inf> and environmental noise are more directly related to local sources at street level. The latter are therefore stronger indicators of improved air quality and reduced noise after pedestrianisation.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"52 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816603","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

How does land resource mismatch affect urban energy low-carbon transition?

IF 6.4 2区工程技术

Urban Climate Pub Date : 2024-12-06 DOI: 10.1016/j.uclim.2024.102236

Hao Zhang, Yan Song, Ming Zhang

{"title":"How does land resource mismatch affect urban energy low-carbon transition?","authors":"Hao Zhang, Yan Song, Ming Zhang","doi":"10.1016/j.uclim.2024.102236","DOIUrl":"https://doi.org/10.1016/j.uclim.2024.102236","url":null,"abstract":"Optimizing land resource allocation is an inevitable requirement for achieving urban energy low-carbon transition. This paper explores the impact mechanism of land resource mismatch on urban energy low-carbon transition by utilizing actual land market transaction data and panel data of 284 prefecture-level cities in China obtained from China Land Market Network using crawler technology. The results show: (1) Land resource mismatch significantly inhibits the performance of urban energy low-carbon transition, and the conclusion still holds after a series of robustness tests such as replacing explanatory variables and endogeneity analysis. (2) Land resource mismatch mainly affects the urban energy low-carbon transition by inhibiting industrial structure upgrading, low-carbon technology innovation and weakening industrial agglomeration effects. (3) The disincentive effect of land resource mismatch is more pronounced in resource-based cities, cities with low cleaning potential and small-scale cities. (4) Hard constraints on local governments' economic growth targets will strengthen the inhibitory effect of land resource mismatch on the city's energy low-carbon transition, while the environmental performance assessment mechanism will weaken the negative impact of land resource mismatch.","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"10 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816602","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