Urban Climate最新文献

{"title":"Performance of PALM-4U/WRF model for simulating the urban meteorology of King Abdullah University of Science and Technology (KAUST), Saudi Arabia","authors":"Rakesh Perumudi Thiruridathil ,&nbsp;Hari Prasad Dasari ,&nbsp;Abdulilah Khalid Alduwais ,&nbsp;Rama Krishna Karumuri ,&nbsp;C. Venkata Srinivas ,&nbsp;Ibrahim Hoteit","doi":"10.1016/j.uclim.2024.102162","DOIUrl":"10.1016/j.uclim.2024.102162","url":null,"abstract":"<div><div>This study evaluates the performance of the PALM-4U model nested within the WRF mesoscale model (with and without the chemistry module coupling, WRF-Chem) for simulating air temperature, humidity, and wind speed at 2 m in the semi-urban region of the King Abdullah University of Science and Technology (KAUST), Kingdom of Saudi Arabia (KSA). Microscale simulations were conducted using PALM-4U for two typical days (one day in summer and one day in winter) based on the boundary and initial conditions from WRF and WRF-Chem models for both meteorological and soil parameters. The model's performance was evaluated using measurements available at two weather stations in the study domain. The simulations indicate that PALM-4U performs better when driven by WRF-Chem outputs with global initialization from ERA5 in summer and NCEP-FNL in winter. The results also suggest that PALM-4U performs markedly better than WRF and WRF-Chem in simulating temperature and relative humidity at the KAUST urban scale in both summer and winter based on the overall error metric.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102162"},"PeriodicalIF":6.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438219","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":"Diesel vehicle emissions: Dissecting the multi-factorial effect on variations of VOC-component concentrations","authors":"Chang Wang ,&nbsp;Xueyao Li ,&nbsp;Xiaohan Miao ,&nbsp;Jingyuan Li ,&nbsp;Yong Li ,&nbsp;Congbo Song ,&nbsp;Zhiwen Yang ,&nbsp;Jingyu Qi ,&nbsp;Taosheng Jin","doi":"10.1016/j.uclim.2024.102157","DOIUrl":"10.1016/j.uclim.2024.102157","url":null,"abstract":"<div><div>As emission standards tighten, addressing Volatile Organic Compounds (VOCs) has become more urgent. The VOC emissions from diesel vehicles are underestimated in transportation, emphasizing the need to reexamine their emission characteristics. Our study analyzed four diesel vehicles and found that aromatics and alkanes were the dominant categories of VOCs, which accounted for approximately 24 % and 19 %, respectively. Tetrahydrofuran, acetone, and toluene were identified as the main components of VOCs, accounting for 78 % of the total emissions. Specifically, the implementation of tighter emission standards for diesel vehicles resulted in a reduction in the contribution of alkanes to VOC emissions, while that of aromatics increased notably. As the driving speed increased, emissions of aromatics and Volatile Halogenated Hydrocarbons (VHCs) experienced a decreasing trend. In addition, Selective Catalytic Reduction (SCR) has the significant impact on aromatics and VHCs, while cold and hot starts phases affect aromatic emissions mostly, as confirmed by Criteria Importance Through Intercriteria Correlation (CRITIC) analysis.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102157"},"PeriodicalIF":6.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433351","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":"Seasonal outdoor PM10 changes based on the spatial local climate zone distribution","authors":"Mahsa Mostaghim ,&nbsp;Ayman Imam ,&nbsp;Ahmad Fallatah ,&nbsp;Amir Reza Bakhshi Lomer ,&nbsp;Mohammad Maleki ,&nbsp;Junye Wang ,&nbsp;Iain D. Stewart ,&nbsp;Nabi Moradpour","doi":"10.1016/j.uclim.2024.102148","DOIUrl":"10.1016/j.uclim.2024.102148","url":null,"abstract":"<div><div>Air pollution changes in urban and non-urban areas depend highly on the seasons and winds. However, it is scant to evaluate the effects of seasonality on air pollution, such as particulate matter (PM) using remote sensing data in Iran. Therefore, investigating the impacts of seasonal changes on PM₁₀ is imperative to mitigate its adverse effect. Local Climate Zone (LCZ) is a new approach in classification of urban land use and climate zones to estimate seasonal PM₁₀ changes in urban regions. In this article, seasonal PM₁₀ distribution changes were evaluated in terms of seasonality and spatial LCZ distribution in Tehran city. Machine learning and Random Forest algorithm were used to classify LCZs and Saraswat algorithm was used for evaluating spatial PM₁₀ distribution. The results showed that seasonality could significantly affect PM₁₀ levels in Tehran region. PM₁₀ levels in autumn and winter are much higher than that in spring and summer. There was the highest PM₁₀ level due to a low average precipitation in autumn while the lowest levels in summer. It is also found that the summer-autumn change caused substantial increases in all LCZs except for LCZ G of large water area. The largest percentage of increases in Tehran city was related to change of summer to autumn (93.9 %) while the largest decrease was in winter to spring (84.6 %). It was also found that PM₁₀ level changes more in the urban LCZs than in the non-urban LCZs.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102148"},"PeriodicalIF":6.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142416949","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":"Detecting topographic effect and urban signature in long-term summer rainfall trend in a complex urban environment","authors":"Chengwei Tong,&nbsp;Ruidong Chen,&nbsp;Long Yang,&nbsp;Yi Pan,&nbsp;Qiqi Yuan,&nbsp;Jingsong Ma,&nbsp;Lachun Wang","doi":"10.1016/j.uclim.2024.102159","DOIUrl":"10.1016/j.uclim.2024.102159","url":null,"abstract":"<div><div>The influence of topography and urbanization on long-term summer rainfall trends in a complex urban environment is poorly understood. In this study, we utilized high-resolution gridding data (CN05.1) from 2416 long-term station observations (1960–2022) to investigate such influences over Wuhan, China. A geostatistical and mathematical framework was proposed to identify topographic and urban rainfall modifications in complex urban environments. The findings indicated that the topographic effect influences the region by causing it to experience drier conditions in dry years and wetter conditions in wet years, as well as increasing the frequency of light rainfall. Urbanization slightly suppressed light rainfall but amplified the intensity of other forms of rainfall, especially extreme rainfall. As impervious surfaces expanded, the urban precipitation-enhancing (UPE) effect diminished in the later stages of urbanization, particularly in urban and upwind areas, due to factors such as reduced evaporation (ET) and decreased relative humidity (RH). The relative contribution of urbanization to long-term rainfall trends was enhanced as urbanization increased, with increases ranging from 7 % to 40 %. This study demonstrates the potential of geostatistical and mathematical analysis techniques in elucidating the contributions of topography and urbanization to long-term rainfall patterns, leading to a better understanding of rainfall anomalies in complex urban environments.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102159"},"PeriodicalIF":6.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415986","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":"Spoilt for choice - Intercomparison of four different urban climate models","authors":"Moritz Burger ,&nbsp;Moritz Gubler ,&nbsp;Achim Holtmann ,&nbsp;Stefan Brönnimann","doi":"10.1016/j.uclim.2024.102166","DOIUrl":"10.1016/j.uclim.2024.102166","url":null,"abstract":"<div><div>In recent years, different models to simulate urban climate variables have been applied to various cities. As the model outputs are usually validated individually, this raises the question about which urban climate model to choose for what specific purpose. The present study aims to find answers to this by intercomparing air temperature outputs of four different urban climate models that have been applied in the city of Bern, Switzerland. This includes a geostatistical land use regression model and the numerical models MUKLIMO_3, PALM, and FITNAH 3D. Using data from 70 stations of an urban air temperature measurement network, we intercompare the four models by focusing on the modeled urban air temperature variability. MUKLIMO_3 outputs show a weak urban air temperature variability, while strong small-scale temperature gradients are modeled by FITNAH 3D. PALM outputs are the only ones that reproduce the impact of a large-scale ventilation pattern, but have a large positive bias. The most accurate estimates of the urban air temperature variability are obtained from the land use regression model. For future applications of urban climate models, we reinforce the need of validation with in-situ measurements, since the outputs (and subsequent policies) depend substantially on the selection of the model.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102166"},"PeriodicalIF":6.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415988","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":"The changes in remoted land surface temperature (LST) triggered by natural and socioeconomic factors in typical Chinese cities","authors":"Xiaoyi Cao ,&nbsp;Wenqian Chen ,&nbsp;Yuxuan Xing ,&nbsp;Yang Chen ,&nbsp;Xiangyue Chen ,&nbsp;Xiaofan Wang ,&nbsp;Dongyou Wu ,&nbsp;Xiaoying Niu ,&nbsp;Wei Pu ,&nbsp;Jun Liu ,&nbsp;Xin Wang","doi":"10.1016/j.uclim.2024.102151","DOIUrl":"10.1016/j.uclim.2024.102151","url":null,"abstract":"<div><div>Land surface temperature (LST) is influenced by a variety of natural factors and urbanization processes. Using MODIS LST data and the Geodetector model, we compared the spatiotemporal variations of LST and their drivers in super megacities (Beijing, Guangzhou, Shanghai, and Shenzhen), a megacity (Xi'an), large cities (Urumqi and Harbin), and a small and medium-sized city (Lhasa). The LST of super megacities is primarily influenced by socioeconomic factors (11 %–61 %), whereas natural factors significantly impact the LST of large cities and small to medium-sized cities (15 %–58 %). Socioeconomic factors contributed more significantly to daytime LST in Xi’an (68 %). Elevation is a crucial factor influencing the spatial heterogeneity of LST, and the enhanced vegetation index predominantly dictates the spatial variation of LST through its interactions with other factors. The interaction between various factors significantly enhances their contributions to LST. According to the urban heat island ratio index, Lhasa exhibited the highest urban heat stress risk (&gt;0.83) during both day and night, whereas Harbin displayed the lowest (&lt;0.34). Beijing possessed the highest urban heat risk rating among the super megacities. Xi'an's risk level decreased significantly at night. Overall, cities generally exhibited higher levels of heat risk during the day compared to the night.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102151"},"PeriodicalIF":6.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415987","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":"Elaborating solutions for bringing sustainability in the air-polluted urban environment via use of plants' anticipated performance and air pollution tolerance indices","authors":"Aaiza Qamar ,&nbsp;Shahab Ali ,&nbsp;Shujaul Mulk Khan","doi":"10.1016/j.uclim.2024.102156","DOIUrl":"10.1016/j.uclim.2024.102156","url":null,"abstract":"<div><div>Plants in general and those which are susceptible to the environmental pollution in particular, can act as bio-indicators for assessing the air pollution. Moreover, the plants which show tolerance to environmental deteriorations can be helpful as bio-monitors and metigators for air pollution. The present study was conducted to evaluate the tolerance level of dominant plant species in the twin cities of Pakistan i.e., Islamabad (a model city) and Rawalpindi (an old city). Extensive fieldwork was done on roadsides of Rawalpindi and Islamabad (roads demarkating these cities). A total of 201 plants were documented out of which thirteen plant species were found as dominant i.e. <em>Alstonia scholaris</em> L. (Devil tree), <em>Ficus benjamina</em> L. (Weeping fig), <em>Melia azedarach</em> L. (chinaberry tree), <em>Rosa indica.</em> L. (Cyme rose), <em>Terminalia arjuna</em> (Roxb.) Wight &amp; Arn. (Arjuna), <em>Pongamia pinnata</em> L. Pierre. (Pongame oil tree), <em>Jasminum humile</em> L. Revolutum. (Jasmine), <em>Morus alba</em> L. (silkworm mulberry), <em>Robinia pseudoacacia</em> L. (black locust), <em>Ficus carica L.</em> (common fig), <em>Azadirachta indica</em> A. (neem), <em>Dalbergia sissoo</em> Roxb. (shisham). The biochemical, physiological, and socio-economic parameters, Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API) were evaluated. Our findings further showed that proline and sugar content were found higher in the plants of Rawalpindi than in Islamabad while few other physiological and biochemical parameters showed higher levels in the plants obtained from the Islamabad site as compared to Rawalpindi. The plant species <em>A. scholaris, T. arjuna, B. papyrifera,</em> and <em>R. pseudoacacia</em> serve as bio-monitors and are the most desirable and most effective tolerant species for air pollution and green belt developments of these cities. These plants can be recommended for metigation of air pollution and smog in other cities having the same climate.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102156"},"PeriodicalIF":6.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415991","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":"Spatial heterogeneity of meteorological elements and PM2.5: Joint environmental-meteorological effects on PM2.5 in a Cold City","authors":"Dongliang Han ,&nbsp;Mingqi Wang ,&nbsp;Tiantian Zhang ,&nbsp;Xuedan Zhang ,&nbsp;Jing Liu ,&nbsp;Yufei Tan","doi":"10.1016/j.uclim.2024.102160","DOIUrl":"10.1016/j.uclim.2024.102160","url":null,"abstract":"<div><div>To quantify the differences in winter thermal environment and air quality and to clarify the main factors influencing PM2.5 concentrations in cold regions, providing references for regional heating supply design and urban planning. In this study, pedestrian-level thermal environmental parameters and PM2.5 concentration were measured and compared across different urban functional zones (UFZs). Additionally, multiple linear regression (MLR), principal component analysis (PCA), and principal component regression (PCR) were employed to analyze the main controlling factors of PM2.5 and air temperature. The findings reveal that regional microclimate temperatures differ significantly, with variations of 2.68–4.31 °C compared to typical MET data. Notably, the Sky View Factor (SVF) emerged as the dominant influence on temperature variations, while PM2.5 concentrations were primarily driven by a combination of ENV (BD, SVF, GnPR) and MET factors (Ta, RH, TSr). The PCR model demonstrated superior predictive accuracy for PM2.5 concentrations (Adjusted R-squared = 0.78) compared to the MLR model (Adjusted R-squared = 0.63). This study not only deepens the understanding of ENV-MET interactions in cold regions, but also provides important recommendations for optimizing urban planning and heating strategies to improve air quality and thermal comfort.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102160"},"PeriodicalIF":6.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415993","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":"An evaluation of the WRF physical parameterizations for extreme rainfall simulation in the Yangtze River Middle Reaches Urban Agglomeration","authors":"Yuhua Luo ,&nbsp;Ming Zhang ,&nbsp;Qian Cao ,&nbsp;Lunche Wang","doi":"10.1016/j.uclim.2024.102149","DOIUrl":"10.1016/j.uclim.2024.102149","url":null,"abstract":"<div><div>With the increase in extreme precipitation events, the need for accurate and reliable extreme precipitation forecasting systems has become increasingly urgent. This study evaluates the performance of various physical parameterization schemes within the Weather Research and Forecasting (WRF) model for forecasting extreme precipitation in the Yangtze River Middle Reaches Urban Agglomeration (YRMRUA). Three assessment methods were employed: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Method for Object-based Diagnostic Evaluation (MODE), and Structure-Amplitude-Location (SAL) to assess four microphysics (MP) schemes and three cumulus parameterization (CP) schemes. The results indicate that for large-scale weather system event, the Lin (KF + EC) scheme performs the best, while for small-scale weather system event, the WSM6 (MSKF+EC) scheme is more effective. For MP schemes, Single-moment MP schemes are generally superior to double-moment MP schemes. For CP schemes, when the inner domain is within the gray resolution range, explicit convection is more effective. In the outer domain, the KF scheme shows better simulation performance for large-scale event, while the MSKF scheme performs better for small-scale event. These findings contribute to better simulation of extreme precipitation in the YRMRUA and serve a reference for generating numerical precipitation forecast ensembles with the WRF model.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102149"},"PeriodicalIF":6.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415994","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":"Spatial-temporal analysis of urban air pollution related exposure and health impacts: Driving human-centered regulation and control","authors":"Zeliang Bian ,&nbsp;Chen Ren ,&nbsp;Dawei Wang ,&nbsp;Shi-Jie Cao","doi":"10.1016/j.uclim.2024.102161","DOIUrl":"10.1016/j.uclim.2024.102161","url":null,"abstract":"<div><div>Climate change has resulted in frequent extreme disasters and scarce resources, leading to a massive population into cities for favorable survival conditions, and also increasing urban air pollution burdens. It is urgent to assess population health risks related with urban air pollution, which usually relies on census method and meteorological measurement data. However, health impacts may be underestimated, because of challenges to represent the dynamic population mobility and perform unified analysis of different pollution hazards. The contribution of this work is to combine census data with Location Based Service to identify the spatiotemporal mobility pattern of urban population, and then population-weighted exposure (PWE) and health impacts of various air pollution (PM_2.5, O₃, and NO₂) are synergistically evaluated. Taking Nanjing as the study area, it was found that the pollution peak areas correlated with population mobility in the study region, shifting from urban suburbs to the center during the daytime, with the maximum concentration exceeding 165 μg/m³. O₃ caused a relatively high PWE level and had a greater health impact than PM_2.5 and NO₂, adding the mortality by up to 5 % especially on weekdays. The annual health impact of O₃ was approximately twice that of PM_2.5 and NO₂. Human-centered regulation strategies of urban air pollution were proposed in terms of personnel behaviors, government control, and urban design towards mitigation of air pollution risk and sustainable urban development.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"58 ","pages":"Article 102161"},"PeriodicalIF":6.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415992","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}