Sustainable Cities and Society最新文献

{"title":"Exploring the cooling intensity of green cover on urban heat island: A case study of nine main urban districts in Chongqing","authors":"Ao Wang ,&nbsp;Yan Dai ,&nbsp;Maomao Zhang ,&nbsp;Enqing Chen","doi":"10.1016/j.scs.2025.106299","DOIUrl":"10.1016/j.scs.2025.106299","url":null,"abstract":"<div><div>With the acceleration of urbanization, the Urban Heat Island (UHI) effect has become one of the major environmental challenges faced by cities worldwide. This study investigates the cooling effect of green cover across nine urban districts in Chongqing and assesses its impact on the UHI effect. By integrating MODIS and Sentinel-2 data, a Random Forest(RF) model was employed to generate 10-meter resolution UHI data. OLS regression revealed a significant decline in cooling intensity in city centers from 2019 to 2024, with Yuzhong District averaging as low as 0.5, while peripheral districts such as Banan and Beibei maintained values above 0.8. Binomial regression demonstrated a lag effect between cooling intensity and UHI, with an R² of 0.71, highlighting the temporal interplay between these variables. Scenario analysis under SSP1-2.6 indicates that average AT can be limited to 22°C with sustained green cover, whereas SSP5-8.5 projects temperature increases nearing 28°C, exacerbating thermal stress. Feature importance analysis using the Principal Component Analysis (PCA) and LightGBM identified Normalized Difference Water Index(NDWI), building density, transportation networks, and population density as the primary drivers of UHI intensity. These findings underscore the critical role of urban greening in mitigating UHI effects and highlight the necessity of integrating green cover strategies into sustainable urban development to enhance climate resilience.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106299"},"PeriodicalIF":10.5,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Field measurement and CFD simulation study on UHI in high-density blocks of Shanghai based on street canyons","authors":"Yuzhu Deng ,&nbsp;Xiangfei Kong ,&nbsp;Haizhu Zhou","doi":"10.1016/j.scs.2025.106302","DOIUrl":"10.1016/j.scs.2025.106302","url":null,"abstract":"<div><div>The impact of urban heat island (UHI) on urban environments and residents has worsened, especially at the block-scale, drawing significant research attention to thermal issues. This study analyzes typical Shanghai blocks through field measurements and simulations. First, 12-day field measurements in summer and winter captured UHI spatiotemporal distribution. The average urban heat island intensity (UHII) was 3.19 °C in summer (daytime 2.25 °C, nighttime 4.13 °C) and 1.93 °C in winter (daytime 1.54 °C, nighttime 2.33 °C). The maximum temperature difference between points reached 10.8 °C in summer and 4.09 °C in winter, with greater temperature fluctuations in single-functional blocks than in multifunctional ones. Then, based on simulations, linear and curve fitting equations for UHII with changes in solar radiation intensity (SRI) or wind speed showed accurate results. For the linear fitting, <em>a</em> ± 10 % change in SRI or wind speed resulted in <em>a</em> ± 0.26 °C or ∓0.16 °C change in summer UHII, and <em>a</em> ± 0.14 °C or ∓0.10 °C in winter UHII. Quantitative analysis of wind direction changes showed that high-density areas downwind of green spaces or waterfronts saw summer UHII drop by up to 91.61 %. Multiple regression analysis of street canyon node temperatures showed good fits for six blocks. This study provides theoretical support and references for UHI mitigation and block-scale planning.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106302"},"PeriodicalIF":10.5,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the heat balance characteristics in Shanghai by using the WRF model coupled with Local Climate Zone scheme","authors":"Zheng Wang ,&nbsp;Yasuyuki Ishida ,&nbsp;Yifei Peng ,&nbsp;Jingyuan Ren ,&nbsp;Akashi Mochida","doi":"10.1016/j.scs.2025.106295","DOIUrl":"10.1016/j.scs.2025.106295","url":null,"abstract":"<div><div>Clarifying the characteristics of the heat balance mechanism of urban space atmosphere is crucial for developing effective countermeasures to mitigate urban heat island (UHI) effect. This study focused on Shanghai, using the Weather Research and Forecasting (WRF) model coupled with the local climate zone (LCZ) scheme to simulate the urban climate and analyze the characteristics of the sensible heat balance components—advection, turbulent diffusion, and anthropogenic heat release—within different regions of Shanghai. The key findings are: 1) the characteristics of advection components in different regions indicate that sea breezes and lake breezes both play significant roles in reducing the air temperature in Shanghai, with sea breezes being more effective; 2) the vertical gradient of wind velocity in the upper air of inland regions increases more than that of coastal regions, leading to a significantly lower net sensible turbulent diffusion component of urban space atmosphere in inland regions compared to coastal regions; 3) the distribution of sensible anthropogenic heat release (SAH) in Shanghai is generally correlated with LCZs, with the SAH is significantly higher in open high-rise and heavy industry types areas compared to other areas. Furthermore, this study determined the UHI mitigation countermeasures for different areas based on the heat balance characteristics of urban space atmosphere in different regions of Shanghai, contributing to the improvement of the urban thermal environment conditions.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106295"},"PeriodicalIF":10.5,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cancer risk and sick building syndrome in different regions of China: Potential hazard from particulate matter and phthalate pollutants","authors":"Chanjuan Sun ,&nbsp;Qinghao Wang ,&nbsp;Jialing Zhang ,&nbsp;Zhijun Zou ,&nbsp;Xuewen He ,&nbsp;Jianlei Niu ,&nbsp;Haidong Wang ,&nbsp;Chunxiao Su ,&nbsp;Rongchun Lu ,&nbsp;Beijia Huang ,&nbsp;Chen Huang","doi":"10.1016/j.scs.2025.106297","DOIUrl":"10.1016/j.scs.2025.106297","url":null,"abstract":"<div><div>Phthalates (PAEs), a class of synthetic chemicals, are harmful to human health and found in indoor particulate matter (PM), air and settled dust. Current risk assessments for indoor PAEs may not accurately reflect the risks for the Chinese population because they use parameters from the U.S. Environmental Protection Agency (U.S. EPA.). This study investigated the correlation among PAEs, PM and Sick Building Syndrome (SBS) in Shanghai. Chinese exposure parameters were then used to assess the lifetime incremental cancer risk (<em>ILCR</em>) of di(2-ethylhexyl) phthalate (DEHP) for different age groups across various Chinese regions. A significant positive correlation was found between indoor PAEs, PM concentrations (PM_2.5, PM₄ and PM₁₀) and SBS. Regional differences existed in the <em>ILCR</em> associated with non-dietary intake (<em>ILCR_intake</em>) and inhalation (<em>ILCR_inhale</em>) of DEHP. <em>ILCR_intake</em> posed a higher risk than <em>ILCR_inhale</em>, exceeding the U.S. EPA limit (1 × 10⁻⁶) in most regions (1.19 × 10⁻⁶ to 1.93 × 10⁻⁶) with the exception of North and South China. . <em>ILCR_inhale</em> remained below this threshold (ranging from 0.01 × 10⁻⁶ to 0.75 × 10⁻⁶). These findings highlight that cancer risks from DEHP intake via dust warrant particular concern.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106297"},"PeriodicalIF":10.5,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic optimization and interaction evaluation of water-energy-food-ecology nexus under uncertainty from the perspective of urban agglomeration","authors":"Zuowen Tan ,&nbsp;Han Li ,&nbsp;Qiran Song ,&nbsp;Zhaocai Wang ,&nbsp;Yongqiang Cao","doi":"10.1016/j.scs.2025.106291","DOIUrl":"10.1016/j.scs.2025.106291","url":null,"abstract":"<div><div>Faced with resource scarcity and accelerated urbanization, the synergistic optimization of water, energy, and food resources is crucial for urban agglomeration. This study focuses on the Chengdu-Chongqing Economic Circle (CCEC) with the aim of achieving the following three specific objectives: (1) constructing a synergistic optimization model for the Water-Energy-Food-Ecology Nexus (WEFEN) in urban agglomeration; (2) developing the Basic Trade-off Solution (BTS) to enhance social, economic, and ecological benefits; and (3) analyzing the impact of different factors within the water, energy, and food systems on the spatial distribution of ecological footprints and their interactions. To achieve these objectives, this study innovatively integrates water footprint theory, robust coefficients, multi-strategy meta-heuristic optimization algorithms, and compromise programming (CP) techniques, significantly improving the model's ability to allocate water and land resources under uncertainty. Furthermore, the Optimal Parameters-Based Geographic Detector (OPGD) is introduced, revealing that electricity consumption is the primary driver of the spatial distribution of ecological footprints. It is also found that the orthogonal interaction between food and energy system factors significantly amplifies the spatial response of ecological footprints. The results demonstrate that the proposed BTS, under the dual uncertainty of surface water supply and economic loss risks, can enhance social benefits, improve the economic efficiency of irrigation water, and reduce ecological footprints. This study provides a solution for optimizing water and land resource patterns under the trade-offs between social, economic, and environmental relations, supporting the achievement of SDG 11.a for the sustainable development of urban agglomeration.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106291"},"PeriodicalIF":10.5,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationship Between Urban Tree Diversity and Human Well-being: Implications for Urban Planning","authors":"Johanna Krischke ,&nbsp;Angela Beckmann-Wübbelt ,&nbsp;Rüdiger Glaser ,&nbsp;Sayantan Dey ,&nbsp;Somidh Saha","doi":"10.1016/j.scs.2025.106294","DOIUrl":"10.1016/j.scs.2025.106294","url":null,"abstract":"<div><div>Green spaces and trees are key elements for enhancing human well-being in cities. Despite recognizing the significance of urban greenery for human health, the role of urban biodiversity in shaping well-being remains poorly understood. This study focused on the interplay between tree genera diversity, perceived urban biodiversity, and the subjective well-being of urban residents in Karlsruhe, Germany. A map-based online questionnaire involving 302 participants investigated well-being locations and perceptions of biodiversity. Tree genera diversity was assessed for nine genera using remote-sensing and ground data. A novel approach of spatially correlating societal mapping results and tree genera cover maps revealed a clear preference for green spaces in the built-up urban environment. The relations between computed tree genera diversity and subjective well-being were unclear. However, there was a significant relationship between the perceived biodiversity of urban green spaces and subjective well-being. The amount of tree cover, the abundance of large trees, as well as the perceived species diversity beyond tree genera, lead to increased well-being of the urban population. At the same time, a perceived unkemptness of urban areas had a negative effect on the residents’ well-being. This should be considered in future research and the design of urban green spaces.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106294"},"PeriodicalIF":10.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Individual and mixed associations between fine particulate matter components and hospital admissions for hypertension: Insights from a large-scale South Chinese cohort study","authors":"Yuqin Zhang ,&nbsp;Jing Wei ,&nbsp;Shirui Chen ,&nbsp;Tarik Benmarhnia ,&nbsp;Kai Zhang ,&nbsp;Xiaowen Wang ,&nbsp;Xinlei Deng ,&nbsp;Haogao Gu ,&nbsp;Ziqiang Lin ,&nbsp;Yanji Qu ,&nbsp;Jianpeng Xiao ,&nbsp;Jie Jiang ,&nbsp;Zhicheng Du ,&nbsp;Wangjian Zhang ,&nbsp;Yuantao Hao","doi":"10.1016/j.scs.2025.106293","DOIUrl":"10.1016/j.scs.2025.106293","url":null,"abstract":"<div><div>Fine particulate matter (PM_2.5) pollution threatens urban sustainability. Few cohort studies have assessed hypertension risks linked to lagged and cumulative exposure to PM_2.5 components. Using data from a cohort study of 36,271 individuals in South China (2015–2020), we examined the individual associations between time-varying PM_2.5 and six components (NO₃⁻, SO₄²⁻, BC, CL⁻, NH₄⁺, and OM) with hypertension hospitalization through Cox proportional hazards regression. Mixed associations of simultaneous exposure to these components were analyzed at lag 0, lag 1, lag 2, lag 0–1, and lag 0–2 years using quantile-based g-computation models. Individual-effect analysis revealed strong associations, with each quantile increase in CL⁻, NH₄⁺, SO₄²⁻, and NO₃⁻ linked to 17 %–32 % higher hypertension risks across different time windows. Co-exposure to PM_2.5 components at different lag times increased hospital admissions for overall hypertension, with hazard ratios (95 % confidence intervals) of 1.151 (1.136–1.166), 1.221 (1.205–1.238), 1.257 (1.241–1.273), 1.087 (1.073–1.101), and 1.197 (1.182–1.212). Secondary water-soluble ions (NO₃⁻, SO₄²⁻, NH₄⁺, CL⁻) were major contributors. Increased susceptibility was observed among those under 45, men, individuals with lower education, unhealthy weight, or limited green space exposure. These findings highlight the lagged and cumulative impacts of simultaneous exposure to PM_2.5 component on hypertension.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106293"},"PeriodicalIF":10.5,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A surrogate machine learning modeling approach for enhancing the efficiency of urban flood modeling at metropolitan scales","authors":"Fatemeh Rezaei Aderyani ,&nbsp;Keighobad Jafarzadegan ,&nbsp;Hamid Moradkhani","doi":"10.1016/j.scs.2025.106277","DOIUrl":"10.1016/j.scs.2025.106277","url":null,"abstract":"<div><div>Urban drainage systems in metropolitan areas are highly complex, posing significant challenges for effective stormwater management. Traditional models like Storm Water Management Model (SWMM) are widely used but become inefficient at large scales with intricate drainage networks. This limitation is particularly critical for early warning systems, which require fast and simplified flood modeling methods. This study investigates surrogate machine learning (ML) models for efficient urban flood modeling at a metropolitan scale. Using SWMM as benchmark, the proposed model demonstrates its ability to replicate SWMM results, offering a more efficient alternative. We partition the system into hydrologically connected clusters, reducing 66,482 manholes to 363 manageable units. The approach combines this clustering strategy with ML modeling to predict key surcharge variables (flood duration, peak, and volume) for individual manholes across complex drainage system. Model validation demonstrates robust performance (R² &gt; 0.8 for extreme events) while reducing computational time by 92.6%. Feature importance analysis reveals depth and duration as primary drivers of flood prediction, with model accuracy correlating to infrastructure density. The surrogate models excel particularly at predicting extreme events, with varying performance across different rainfall conditions. This computational efficiency enables real-time prediction updates crucial for emergency response planning and flood management strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106277"},"PeriodicalIF":10.5,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigating urban heat island through urban-rural transition zone landscape configuration: Evaluation based on an interpretable ensemble machine learning framework","authors":"Shengyu Guan,&nbsp;Yiduo Chen,&nbsp;Tianwen Wang,&nbsp;Haihui Hu","doi":"10.1016/j.scs.2025.106272","DOIUrl":"10.1016/j.scs.2025.106272","url":null,"abstract":"<div><div>Research methods for mitigating urban heat islands (UHIs) have been widely documented. Nevertheless, the importance of mitigating UHIs through landscape allocation in urban-rural transition zones (URTZs) has rarely been emphasized in the context of intra-urban land scarcity and urban expansion in China. This study aimed to quantify the binary relationship between URTZ's landscape configuration and urban heat island intensity (UHII) by using an interpretable ensemble learning framework in Harbin, a megacity in China. After URTZ's identification, this study integrated Boruta algorithm, SHAP, ALE (interpretable machine learning techniques) and 7 tree-based machine learning models to assess the importance of URTZ's landscape configuration with both global and local angles. The results indicated that: construction land contributed most, with construction land ratio (23.20 %), separation degree (15.95 %), and maximum patch index (15.03 %) ranking highest. This was followed by agricultural land landscape shape index (10.31 %) and landscape diversity (9 %). Maintaining construction land ratio at 50–70 % can keep UHII unchanged; UHII at the grid landscape level can be alleviated when separation degree between construction land patches was above 0.7. The largest construction land patch within the grid was maintained at 20–40 or 50–70, which will not bring significant changes to UHII. The agricultural land landscape shape should be as simple as possible to reduce UHII; landscape diversity greater than 0.6 can reduce UHII, and &lt;0.6 can increase UHII. These findings provide valuable insights into UHI mitigation and offer strategic guidance for ecological planning to promote sustainable development of large cities in rapidly changing URTZs.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106272"},"PeriodicalIF":10.5,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global sensitivity analysis in a complex 1D-2D coupled hydrodynamic model: Flood hazard and resilience perspectives over an urban catchment","authors":"Kaustav Mondal ,&nbsp;Mousumi Ghosh ,&nbsp;Subhankar Karmakar","doi":"10.1016/j.scs.2025.106279","DOIUrl":"10.1016/j.scs.2025.106279","url":null,"abstract":"<div><div>The increasing frequency of flood-related disasters has led to adopting advanced flood models to improve preparedness and response. To ensure reliable model outputs, conducting a Global Sensitivity Analysis (GSA) of model parameters is crucial. This study proposes a GSA framework for static input parameters in a 1D-2D coupled hydrodynamic flood model. MIKE-11 &amp; MIKE-21 are coupled to simulate urban flooding in Mumbai's Mithi River catchment, considering rainfall and tidal influences. The model is simulated by perturbing various combinations of static input parameters to design test-scenarios. Outputs for an urban model setup are robust, complex, and gridded. Accordingly, GSA of static input parameters is also performed grid-wise to quantify sensitivity in terms of spatial variation of <em>Flood Hazard</em> and <em>Flood Resilience</em> across the catchment. Nonparametric probability density functions of flood depth at different locations are compared to calculate Kullback-Leibler divergence for quantifying sensitivity in the <em>Flood Hazard</em> context. Meanwhile, changes in <em>Flood Resilience</em> due to parameter perturbations are evaluated for resilience-based sensitivity. Results reveal varying impacts of input parameters across floodplain, with grid resolution and land use being most sensitive. The proposed novel GSA framework aligns with Sustainable Development Goal 11, aiming to make cities inclusive, safe, resilient, and sustainable, and equips flood management professionals with insights into key flood drivers, guiding data collection and monitoring. Proposed framework is versatile and can be integrated into any flood modeling software, offering resilient urban planning and risk mitigation strategies, contributing to sustainable urban development and better preparedness for flood risks in urban areas.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106279"},"PeriodicalIF":10.5,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}