Urban Climate最新文献

{"title":"Two-year monitoring of indoor/outdoor PM10 at 15 sites in an urban setting. Part II: source apportionment and oxidative potential","authors":"L. Massimi ,&nbsp;C. Perrino ,&nbsp;M.A. Frezzini ,&nbsp;S. Canepari","doi":"10.1016/j.uclim.2025.102466","DOIUrl":"10.1016/j.uclim.2025.102466","url":null,"abstract":"<div><div>Two-year monitoring of indoor and outdoor PM₁₀ was carried out at 15 residential sites in the urban area of Rome, Italy (May 2019–April 2021) through 12 continuous two-month samplings. PM₁₀ source apportionment identified nine emission sources: cigarette smoke, biomass burning, vehicular traffic, road dust, soil dust, heavy oil combustion, ammonium nitrate, and sulphate. The major contributions to outdoor PM₁₀ were from biomass burning in winter and from traffic, especially its non-exhaust component (i.e., brake and road dust), which showed high inter-site variability due to the different micro-locations of the 15 dwellings. Cigarette smoke, where present, was the major indoor source that caused high variability of indoor PM₁₀ among sites.</div><div>The indoor/outdoor ratio of the identified source contributions indicated that combustion sources showed a great ability to penetrate indoor environments, while coarse particles from road dust, soil dust, and sea spray showed a lower capacity to enter indoors.</div><div>Principal component analysis (PCA) allowed exploring relationships between the OP values and the chemical composition and sources of PM₁₀. Cigarette smoke, biomass burning-related sources, and non-exhaust traffic were found to be the major contributors to OP^DCFH, OP^DTT, and OP^AA, respectively, revealing the high potential health impact of PM released from some indoor sources.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102466"},"PeriodicalIF":6.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167421","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 distribution and driving factors of carbon emission in a furnace city using Luojia1–01 nighttime data and optimal parameters-based geodetector","authors":"Wang Liu ,&nbsp;Xupan Yue ,&nbsp;Xiaowen Wang ,&nbsp;Zhongli Lin ,&nbsp;Xiong Yao ,&nbsp;Zhanghua Xu","doi":"10.1016/j.uclim.2025.102462","DOIUrl":"10.1016/j.uclim.2025.102462","url":null,"abstract":"<div><div>Rapid urbanization has increased carbon dioxide (CO₂) emissions, exacerbating ecological issues and prompting global shift towards low-carbon development. However, current studies at the county-level face challenges such as incomplete monitoring systems and insufficient statistical granularity, which restrict the detailed analysis of carbon emission spatial distribution and driving mechanisms. To address this, the study utilized high-resolution Luojia1–01 nighttime light (NTL) data combined with the optimal parameters-based geographical detector (OPGD) model, taking Fuzhou, a typical “furnace city” as a case study to reveal the spatial differentiation characteristics and driving mechanisms of carbon emissions at the county-level. The results indicate that carbon emissions in Fuzhou exhibit a “core-edge” spatial differentiation pattern, with the central urban areas having higher emissions than the surrounding counties, and a positive spatial correlation was observed; the proportion of the tertiary production (PTP), the proportion of the primary production (PTP), the urbanization rate (UR), and the level of social capital (SC) are core driving factors of carbon emissions, with dual-factor interactions exhibiting significant bilinear enhancement effects. Based on the carbon emission differentiation characteristics, the study proposes a “five-zone differentiated” governance strategy, which includes low-carbon transformation of the service industry in the core urban areas, green industrial upgrading in high-emission zones, and strengthening the carbon sink function in ecological protection areas. This study provides methodological support and decision-making guidance for refined carbon emission management and low-carbon development planning at the county-level.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102462"},"PeriodicalIF":6.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167420","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":"Decoding spatiotemporal dynamic of atmospheric CO2 concentration under different urban development model","authors":"Yurong Zheng ,&nbsp;Wenbin Sun ,&nbsp;Zheng Guo","doi":"10.1016/j.uclim.2025.102474","DOIUrl":"10.1016/j.uclim.2025.102474","url":null,"abstract":"<div><div>Current research lacks fine-scale assessments of urban XCO₂ dynamics and carbon source/sink identification from spatiotemporal perspectives. Thus, a 1 km-resolution XCO₂ dataset (XCO₂_Cat) for mainland China from 2000 to 2020 was reconstructed using CatBoost model and multi-source data, incorporating spatial and temporal factors. It enabled an in-depth analysis of XCO₂ and XCO₂_ano, offering insights into carbon source-sink dynamics. Furthermore, a carbon risk identification matrix based on XCO₂ and XCO₂_ano was proposed to identify urban carbon risks. Results revealed significant spatiotemporal variations in China, with higher XCO₂ in the east and lower in the west, increasing at a rate of 2–3 ppm/year. Heterogeneity in XCO₂ and XCO₂_ano was observed across urban models. Growing cities had the highest XCO₂ levels. Potentially shrinking, continuously shrinking and smart shrinking cities had lower XCO₂, but still exhibited relatively high values, suggesting that urban shrinkage does not necessarily lead to decarbonization. Growing cities showing the highest XCO₂_ano in most years. Continuously shrinking cities initially exhibited higher carbon source intensity. Substantial regional heterogeneities were found in XCO₂ and XCO₂_ano, emphasizing the need for region-specific carbon reduction strategies. Cities were categorized into four types based on carbon risk identification matrix: HL-type (stable carbon source and constrained carbon sink), LH-type (carbon source to carbon sink and vice versa), HH-type (strong disturbance), and LL-type (weaker carbon source). Key regions and urban development models for each type were identified, and targeted carbon management strategies were proposed. These findings offer critical guidance for implementing effective carbon reduction policies at finer scales.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102474"},"PeriodicalIF":6.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of residential morphology on outdoor thermal comfort and building energy consumption in winter and summer: A case study","authors":"Minghao Wang ,&nbsp;Yichen Dong ,&nbsp;Wei Liao ,&nbsp;Bo Pan ,&nbsp;Sensheng Li ,&nbsp;Junchao Duan ,&nbsp;Shen Xu","doi":"10.1016/j.uclim.2025.102479","DOIUrl":"10.1016/j.uclim.2025.102479","url":null,"abstract":"<div><div>Urban morphology simultaneously influences outdoor thermal comfort (OTC) and building energy consumption (BEC). However, the quantitative impact of urban morphology parameters on OTC and BEC, especially taking into account demand differences across seasons, has not been systematically revealed. This study investigated the OTC and BEC of 25 representative residential cases on typical winter and summer days by coupled simulations, and quantitatively analyzed the impact of residential morphology on both. Results show that: 1) Average outdoor air temperature varies by up to 1.84 °C in summer and 0.80 °C in winter among different types of residential areas; 2) Heating energy consumption varies by up to 11.02 % and cooling energy consumption by up to 5.04 % among different types of residential areas; 3) The sky view factor (SVF) and greenery are key parameters affecting OTC in winter and summer. The shape factor (SF) and building density (BD) are closely related to heating energy consumption; SF and greenery are closely related to cooling energy consumption. Cooling energy consumption is more closely related to the outdoor microclimate than heating; 4) Floor area ratio (FAR), SF, and aspect ratio of the building plane have consistent impacts on energy consumption and are key parameters in residential design.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102479"},"PeriodicalIF":6.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167474","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":"Urbanization mitigates the intensification of summer wet heatwaves in China from 1970 to 2020","authors":"Hao Wen ,&nbsp;Decheng Zhou ,&nbsp;Jun Zhai ,&nbsp;Liangxia Zhang","doi":"10.1016/j.uclim.2025.102476","DOIUrl":"10.1016/j.uclim.2025.102476","url":null,"abstract":"<div><div>The urban heat island effect (UHI) exaggerates heat extremes, whereas the concurrent urban dry island effect (UDI) may mitigate heatwave risks. It remains unclear whether urbanization increases or decreases the risk of heatwaves at a large scale. Using daily meteorological observations provided by China Meteorological Data Service Center and urban-minus-rural method, this study analyzes the evolutionary characteristics of summer wet heatwaves at 382 urban meteorological stations in China during the period of 1970–2020. Results show that the frequency, duration, and intensity of summer wet heatwaves increased significantly in 83 % of the urban sites, with average growth rates of 0.016 times/year, 0.009 days/year, and 0.018 °C/year, respectively. South China experienced the fattest growth across China. Using the nearest rural site as a reference, the present research estimates that urbanization suppresses the trend of increasing summer wet heatwaves in 67 % of the urban stations. On average, urbanization reduces the frequency, duration, and intensity of wet heatwaves by 75.0 %, 55.5 %, and 38.9 %, respectively. The urban impacts on the frequency, duration, and intensity of wet heatwaves in Northeast China are approximately 9 %, 28 %, and 64 % of those observed in Central China, respectively. Additionally, the impact of urbanization on wet heatwaves extremes is primarily driven by changes in relative humidity. These findings underscore the widespread mitigating effect of urbanization on wet heatwaves, primarily through the UDI effect, and suggest that the urbanization effects on heatwave risk may be overstated if the UHI effect is considered in isolation.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102476"},"PeriodicalIF":6.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167428","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":"Approach of achieving urban environmental equity for the elderly by evaluating cooling effects from urban parks","authors":"Xukun Yan,&nbsp;Yupeng Wang,&nbsp;Dian Zhou","doi":"10.1016/j.uclim.2025.102471","DOIUrl":"10.1016/j.uclim.2025.102471","url":null,"abstract":"<div><div>Frequent extreme heat events pose a significant public health threat, particularly to the elderly. Urban parks have long been recognized for their role in mitigating heat impacts, underscoring the need for accurate evaluation of their cooling services. This study aims to enhance urban climate equity for the elderly by: 1) modifying a multiple accessibility framework with remote sensing data to quantify urban parks' cooling service, considering both their direct cooling range and the cooling benefits realized by elderly individuals traveling to parks; 2) comparing the spatial distribution of park cooling services; and 3) exploring the impact of park design and urban planning on park cooling effects. The study found that inner-city parks suffer from mismatches between the supply of cooling services and the demand from elderly. In contrast, outer-city parks, while offering greater cooling service, exhibit pronounced internal inequities in access and usage. Notably, 78.96 % of blocks with elderly residents require over 15 min to reach the nearest cooling park, while 60.81 % of blocks do not benefit from the cooling effects of nearby parks. Furthermore, the cooling effects of parks are shaped by both internal and external factors and suggesting that urban parks with small and flexible layouts should be given greater consideration. By addressing these disparities, this research contributes to advancing urban climate resilience and promoting environmental equity, highlighting the critical need for prioritizing the well-being of the most vulnerable.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102471"},"PeriodicalIF":6.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167430","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":"Are vulnerable neighbourhoods left behind? Urban cooling disparities from greenspace inequality in Antananarivo, Madagascar","authors":"Rui Han ,&nbsp;Robert A. Marchant ,&nbsp;Jessica P.R. Thorn","doi":"10.1016/j.uclim.2025.102467","DOIUrl":"10.1016/j.uclim.2025.102467","url":null,"abstract":"<div><div>The escalation of urbanisation contributes significantly to urban heat in both affluent and impoverished neighbourhoods. Community thermal vulnerability is often characterised by socio-demographic composition, with little consideration as places where people are unequally exposed to greenspace and how they associate with cooling disparities. Combining land surface temperature, this Antananarivo case study employed greenspace exposure Gini coefficient to map the locations of vulnerable neighbourhoods and evaluate how their cooling effect differ from others. Results show that nearly 25 % neighbourhoods were unequal where values of exposure to greenspace is disproportionately higher in some of grid cells than others, raising vulnerability to urban heat. These vulnerable neighbourhoods exhibited an average 0.01 °C greater cooling effect compared to the rest of more equal neighbourhoods. Specifically, main cooling role for vulnerable neighbourhoods is agricultural land with a 1 % coverage increase leading to a 0.02–0.03 °C temperature reduction in the day. Comparatively, the cooling effect for equal neighbourhoods relies on non-agricultural greenspace with 1 % coverage increase resulting in a 0.01–0.02 °C temperature reduction at night. Meanwhile, cooling models from 2017 and 2022 identified greenspace thresholds of 62% and 78% existing in equal neighbourhoods, which estimated to reduce average 0.78 °C, 1.24 °C nighttime temperature to bring equal neighbourhoods who were experiencing the high temperature to a more comfortable range regardless of any other factors. However, there was no thresholds detected in vulnerable neighbourhoods. Cooling disparities between vulnerable and equal neighbourhoods is influenced by factors of urbanisation, topology conditions, vegetation canopy, land cover, and day-to-night land surface temperature variations. These cooling disparities also depicted the trajectory of how neighbourhoods evolve from being equal to becoming vulnerable. Our findings emphasise the contributions of equitable greenspace distributions to urban heat mitigation and adaptation, implicating cooling strategies for marginalised communities in Antananarivo and other urban centres across Africa and beyond.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102467"},"PeriodicalIF":6.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154585","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":"Beyond land surface temperature: Identifying areas of daytime thermal discomfort in cities by combining remote sensing and field measurements","authors":"Julie C. Fahy ,&nbsp;Christoph Bachofen ,&nbsp;Reto Camponovo ,&nbsp;Peter Gallinelli ,&nbsp;Martin A. Schlaepfer","doi":"10.1016/j.uclim.2025.102460","DOIUrl":"10.1016/j.uclim.2025.102460","url":null,"abstract":"<div><div>Satellite images of land surface temperatures (LST) are commonly used to identify areas within cities most prone to diurnal thermal discomfort, but they may not reflect the experiences of pedestrians. Here, we developed predictive statistical models for Physiological Equivalent Temperature (PET), an indicator of thermal discomfort, with easily accessible spatial predictors. For this, we measured PET (<em>n</em> = 4472) along eight transects (range: 700–5000 m) using a multi-sensor instrument in the urban fabric of Geneva, Switzerland during periods of summer heat. We parametrised generalised additive models (GAM) and linear mixed models (LMM) with six commonly available predictor variables [<em>solar energy, Local Climate Zone (LCZ), albedo, LST, Normalized Difference Moisture Index (NDMI)</em> and <em>canopy cover</em>]. We found that LST, alone, explained &lt;2 % of observed variation in PET, whereas the GAM with all the 6 predictor variables had R² = 0.43. LCZ and solar energy explained most of the variability of PET across the city. PET values were lower in the densely built city centre than in the peri-urban environment. LST is poorly correlated with air temperature and PET in urban settings, and thus should not be used alone to predict outdoor thermal discomfort.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102460"},"PeriodicalIF":6.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154584","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":"Investigating the urban heat island effect: Impacts of diverse urban morphologies in semi-arid Marrakesh","authors":"Achraf Rachidi,&nbsp;Sanaa Hayani Mounir","doi":"10.1016/j.uclim.2025.102405","DOIUrl":"10.1016/j.uclim.2025.102405","url":null,"abstract":"<div><div>The Urban Heat Island (UHI) effect presents significant challenges to urban environments, leading to increased energy consumption, deteriorating air quality, and elevated health risks. This study provides a pioneering sensitivity analysis of the Urban Weather Generator (UWG) model—the first of its kind to comprehensively assess the impact of both irregular and traditional urban forms in a semi-arid Mediterranean context. Marking one of the most extensive simulations conducted in this region, our research investigates the complex interactions between urban morphology, including modern, traditional, and irregular configurations, and their impact on local air temperatures. We conduct an extensive solar exposure analysis, quantifying incident solar radiation (kWh/m²) and performing sky view simulations across various urban zones. Our findings reveal striking thermal differentials, with variations reaching 5 °C daily and 3.5 °C annually, closely tied to urban density and configuration. Additionally, we explore the interplay between UHI and Urban Cool Island (UCI) effects, uncovering untapped potential for urban design optimization to effectively mitigate thermal impacts. By addressing critical gaps in urban morphological data and incorporating irregular forms into the analysis, our innovative approach lays the groundwork for a paradigm shift in urban planning. This comprehensive study not only enhances the understanding of UHI dynamics in semi-arid climates but also provides valuable insights for developing sustainable, resilient urban environments.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102405"},"PeriodicalIF":6.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138022","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":"Satellite observations and spatial regression to assess geographical parameters on land surface temperature","authors":"Rami Al-Ruzouq ,&nbsp;Naseeb Asaad Albakri ,&nbsp;Waleed Zeiada ,&nbsp;Abdallah Shanableh ,&nbsp;Khaled Hamad ,&nbsp;Saleh Abu Dabous ,&nbsp;Nezar Atalla Hammouri ,&nbsp;Mohamed Barakat A. Gibril","doi":"10.1016/j.uclim.2025.102465","DOIUrl":"10.1016/j.uclim.2025.102465","url":null,"abstract":"<div><div>Urban and industrial expansion raises the land surface temperature (LST), posing challenges that require understanding for sustainable city planning. This study assesses variables influencing LST at Sharjah University City, UAE, a semi-arid area experiencing the reverse Urban Heat Island (UHI) effect. This study assess key factors like land use land cover (LULC), spectral indices, wind speed, and topography using meteorological records, Landsat 8 imagery, WorldView-3, Shuttle Radar Topography Mission (SRTM), and ERA5. The relationships among these variables are evaluated using the ordinary least square regression model. The study period spanned from October 2020 to January 2021 (winter) and from June 2021 to August 2021 (summer). The results demonstrate that different factors influence LST seasonally. In winter, the normalized difference built-up index (NDBI), normalized difference water index (NDWI), and wind speed significantly impact LST, with an R² of 0.67. Wind speed correlates positively with LST during the winter, with a correlation coefficient of approximately 4.95. During the summer, the normalized difference vegetation index (NDVI) emerges as a crucial factor alongside wind speed, resulting in an R² of 0.73. Conversely, wind speed is negatively correlated with the LST, with a correlation coefficient of −1.45 in the summer. The developed LST model provides high-resolution predicted LST maps that can fill data gaps due to cloud cover. The model discrepancies include overestimation in residential areas and underestimation on roads. This study highlights the importance of wind speed and informs urban planning by adding vegetation that could mitigate temperature rise.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102465"},"PeriodicalIF":6.0,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134246","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}