Environmental Impact Assessment Review最新文献

{"title":"Quantifying the non-linear response of bird diversity to landscape features in metropolitan areas: A machine learning-based analysis","authors":"Ziyi Chen ,&nbsp;Weizhen Xu ,&nbsp;Zhengyan Chen ,&nbsp;Ruixiang Shi ,&nbsp;Jing Chen","doi":"10.1016/j.eiar.2025.108029","DOIUrl":"10.1016/j.eiar.2025.108029","url":null,"abstract":"<div><div>Understanding the relationship between urban bird diversity and landscape features is essential for effective biodiversity conservation and sustainable urban development. This study utilizes bird observation data collected from a citizen science platform in Nanjing, China, to explore the spatial scales most appropriate for assessing urban bird diversity (species richness and functional diversity) and their non-linear associations with various landscape features. Advanced machine learning models, such as Boosted Regression Trees (BRT), eXtreme Gradient Boosting (XGBoost), and SHapley Additive exPlanations (SHAP), were employed to analyze these relationships. Key findings include: (1) A sum of 275 bird species were recorded in Nanjing's main urban area, with <em>Passeriformes</em> (77.06 %) being the dominant order. Both indices increased in average value as the scale size expanded (300 m, 500 m, 700 m, 900 m, 1100 m, 1300 m, and 1500 m). Statistical analysis indicated a more random spatial distribution of bird richness at smaller scales (300–700 m, Moran's <em>I</em> = 0.24), while functional diversity remained largely stable across scales. (2) The BRT results indicated that the relationship between bird diversity indices and landscape features peaked at the 900 m scale, which was thus identified as the optimal spatial scale. (3) Excessive nighttime lighting (values &gt;62), high building density (&gt; 0.15), and road density (&gt; 5) were found to suppress bird diversity, while favorable terrain conditions, such as moderate elevation (50–150 m), aspect angles (100°–200°), and gentle slopes (&lt; 5°), along with enhanced ecological conditions (RSEI &gt;0.5) promoted it. Interaction analyses further demonstrated that the effects of terrain variables, building density, and road density attenuated the negative impacts of urban nighttime lighting. These findings offer practical implications for urban planning and design by identifying scale-sensitive and threshold-based strategies to support bird biodiversity and promote harmonious coexistence between humans and nature in metropolitan landscapes.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 108029"},"PeriodicalIF":9.8,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate-driven spatiotemporal variation of soil erodibility in China","authors":"Lili Qu ,&nbsp;Zheng Sun ,&nbsp;Zhiyuan Tian ,&nbsp;J.M. Schoorl ,&nbsp;Rui Ma ,&nbsp;Yan Zhao ,&nbsp;Yihang Wu ,&nbsp;Yin Liang","doi":"10.1016/j.eiar.2025.107998","DOIUrl":"10.1016/j.eiar.2025.107998","url":null,"abstract":"<div><div>Understanding the long-term variation of soil erodibility is essential for effectively addressing the risk of soil degradation and erosion, particularly against the backdrop of global climate change. However, the climate change-driven variation in soil erodibility (<em>K</em> factor) has not been studied yet. This research utilized 9579 historical soil sample data from China collected in the 1980s and 2010s, along with the future climate data from Coupled Model Inter-comparison Project phase 6 (CMIP6) under SSP1–2.6 and SSP5–8.5 scenarios, to investigate spatiotemporal change of soil erodibility in China from 1980 to 2100. The Erosion-Productivity Impact Calculator (EPIC) model and Quantile Regression Forest (QRF) were employed to calculate and predict <em>K</em> values for the 0–30 cm topsoil, respectively. The QRF prediction model achieved acceptable accuracy, with an R² of 0.485. Spatially, the distribution pattern of the <em>K</em> factor from 1980 to 2100 remained relatively consistent, with higher values in the central-eastern, northeastern regions, and lower values in the northwestern, southern regions. Historically, a decreasing trend was observed in the <em>K</em> factor between the 1980s and 2010s. In the future, the <em>K</em> factors are projected to increase in northern China and decrease in southern China under both scenarios, with more pronounced changes under the SSP5–8.5 scenario. Elevation and climate variables have been identified as the most important factors influencing the spatial and temporal changes of the <em>K</em> factor. Land use conversion and economic factors also influence the <em>K</em> factor changes. This study provides new insights into the impacts of climate change on soil resources and offers scientific support for the development of adaptive soil conservation policies, indicating that policymakers must adopt region-specific land management strategies to mitigate future changes in soil erodibility.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 107998"},"PeriodicalIF":9.8,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Allocation of pollution and carbon emission reduction targets for city clusters: Empirical evidence from China's Yangtze River Delta city cluster based on cost optimization","authors":"Hao Zhang,&nbsp;Feng Wang,&nbsp;Wenna Fan,&nbsp;Yaxin Zhao,&nbsp;Ying Wang,&nbsp;Jing Xiao,&nbsp;Congxin Wu","doi":"10.1016/j.eiar.2025.108018","DOIUrl":"10.1016/j.eiar.2025.108018","url":null,"abstract":"<div><div>The rational allocation of pollution and carbon emission reduction targets for city clusters, particularly the Yangtze River Delta (YRD), which has the largest economic scale in China, is critical for fostering regional economic growth, facilitating coordinated emission reductions, and improving environmental quality. This study integrates the principles of fairness, capacity, and efficiency. It utilizes the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model and planning models to develop the lowest-cost allocation scheme for pollution and carbon emission reduction based on the reduction targets for the YRD city cluster. The results indicate the following. (1) The integrated air pollutant emissions in the YRD city cluster exhibit a fluctuating upward trend, with population size having the greatest impact. (2) Regional development within the YRD city cluster is uneven, with coastal cities generally exhibiting higher maturity than inland cities. Shanghai has the highest maturity, while Chizhou exhibits the lowest. (3) The emission reduction targets for the city cluster and the high, medium, and low maturity groups are 2,200,753 tons of equivalent, 1,035,610 tons of equivalent, 572,800 tons of equivalent, and 592,343 tons of equivalent, respectively. Although the use of the maturity indicator causes an allocation of more emission reduction tasks to cities in the high maturity group, most cities in the low maturity group require a larger proportion of emission reductions. The research findings have significant policy importance for establishing a fair and effective emission reduction target allocation mechanism, achieving regional total emission control, and stimulating collaborative emission reduction efforts.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 108018"},"PeriodicalIF":9.8,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing market mechanisms for greenhouse gas reduction: A comprehensive review","authors":"Wonhee You ,&nbsp;Doojin Ryu ,&nbsp;Robert I. Webb ,&nbsp;Qing (Clara) Zhou","doi":"10.1016/j.eiar.2025.107974","DOIUrl":"10.1016/j.eiar.2025.107974","url":null,"abstract":"<div><div>We provide a comprehensive review and analysis of greenhouse gas (GHG) reduction policies that leverage market mechanisms to incentivize behavior. These mechanisms are classified into <em>price-based mechanisms</em>, which directly affect emission prices, and <em>quantity-based mechanisms</em>, which indirectly influence them. Many countries focus on carbon dioxide emissions, using carbon taxes and subsidies to affect prices, while regulating quantities through carbon credits and offsets to allocate pollution rights. Effective market mechanisms require features that promote compliance. We assess the impact of these policies on GHG reduction and categorize challenges into primary—related to market characteristics and policy design—and secondary, arising from the unequal distribution of policy impacts.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 107974"},"PeriodicalIF":9.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of digitization on ecological environment governance capacity: Evidence from China","authors":"Bangzhu Zhu ,&nbsp;Shuangshuang Li ,&nbsp;Julien Chevallier","doi":"10.1016/j.eiar.2025.108014","DOIUrl":"10.1016/j.eiar.2025.108014","url":null,"abstract":"<div><div>Improving ecological environment governance capacity is crucial for achieving environmental sustainability, and the potential benefits of digitalization should be fully leveraged. This study is distinguished by its innovative development of a composite index aimed at evaluating governance capacity in ecological environment. Additionally, we conduct an empirical analysis to explore the causal relationship between digitalization and ecological environment governance capacity while identifying the mechanisms that underpin this relationship. Based on provincial data from China, the research reveals that digitalization significantly enhances ecological environment governance capacity. The finding remains robust following a series of robustness tests. More specifically, for every one unit increase in digitalization, ecological environment governance capacity can be enhanced by 0.06 units. Furthermore, the enhancement effect is more pronounced in the eastern region, big data pilot zone, high carbon emission and high innovation resource endowment regions. The coefficients of digitalization in these areas are 0.123, 0.130, 0.080, and 0.137 respectively. Mechanism analysis shows that digitalization improves ecological environment governance capacity by fostering renewable energy development and facilitating knowledge spillover. Further spatial analysis presents significant spatial spillover effects of digitalization on ecological environment governance capacity. These findings provide valuable insights for enhancing ecological environment governance capacity and promoting environmental sustainability through digitalization.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 108014"},"PeriodicalIF":9.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practice of the integration of climate change considerations into environmental impact assessment for policy in China","authors":"Qingyang Wang ,&nbsp;Xinyi Zhang ,&nbsp;Jiandong Bai ,&nbsp;Jing Wu ,&nbsp;I-Shin Chang","doi":"10.1016/j.eiar.2025.108011","DOIUrl":"10.1016/j.eiar.2025.108011","url":null,"abstract":"<div><div>Environmental impact assessment for policy (Policy EIA) is an important and effective means to couple with climate change (CC) mitigation and adaptation during the policy-making process by systematically integrating CC considerations. As the world's largest carbon emitter and a member of the Parties of the Paris Agreement, China plays a vital role in reducing and neutralizing greenhouse gases emissions. To demonstrate the determined attitude and progressive actions to confront global warming, in China, 17 pilot Policy EIA cases were initiated from 2021 to 2023, where CC considerations are required to be integrated into Policy EIA. Adapted from the best available international practices, 22 focusing and streamlined criteria covering CC mitigation and adaptation are assembled to prudentially scrutinize CC considerations in these pilot cases. In addition, direct content analysis is applied to identify and analyze text references related to the evaluation criteria, and correlation analysis is employed to refine and validate the research findings. Overall, the results indicate that while climatic factors are considered to some extent, the integration of CC considerations into Policy EIA is in an unsatisfactory manner, with dissimilar performance across different subjects and categories. Besides, much more effort was put into mitigation consideration than into adaptation consideration. Moreover, there is a lack of applicable quantitative methodologies to measure CC impacts, while the absence of accessible, robust, and quality-assured data has become a major obstacle to CC assessment. Correspondingly, some recommendations are proposed to further improve the integration of CC considerations into Policy EIA. The research framework provides a reasonable and effective approach to evaluating the integration of CC considerations into Policy EIA, with potential applicability worldwide.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 108011"},"PeriodicalIF":9.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal patterns and driving factors of ecological restoration regions: Insights from multi-scale analysis","authors":"Yuhang Zhang ,&nbsp;Zhenqi Hu ,&nbsp;Jiazheng Han ,&nbsp;Xizhao Liu ,&nbsp;Zhanjie Feng ,&nbsp;Xi Zhang","doi":"10.1016/j.eiar.2025.108020","DOIUrl":"10.1016/j.eiar.2025.108020","url":null,"abstract":"<div><div>Mapping ecological restoration regions (ERRs) is essential for assessing restoration progress and evaluating ecological projects. Traditional methods often face biases due to incomplete data. This study introduces a unified framework that integrates vegetation index evolution and land cover change, enabling precise pixel-level ERR identification across subtypes from 1991 to 2019. By enhancing spatial analysis through quantitative and geometric dimensions, we developed an ecological restoration index and utilized the SHAP model to uncover multi-scale driving factors. Results show ERRs in the Yellow River Basin expanded significantly from 2001 to 2010, averaging 2199.07 km²/a, with gradual vegetation restoration dominating (61.9 %). Key drivers of ecological restoration were identified as precipitation, temperature, and GDP, with mean SHAP values of 0.42, 0.52, and 0.34 at the provincial, municipal, and grid scales, respectively. This study advances ERR identification methodologies and explores the complex interactions between ecological restoration and its drivers at various scales. These insights are vital for the systematic planning and phased adjustment of ecological restoration initiatives.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 108020"},"PeriodicalIF":9.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing ozone formation impact through SHAP interaction redistribution analysis: A novel framework for evaluating VOC photochemical loss and source interactions","authors":"Sen Yao ,&nbsp;Hongyuan Jia ,&nbsp;Fengjuan Fan ,&nbsp;Na Zhao ,&nbsp;Yujia Kuang ,&nbsp;Xianda Tang ,&nbsp;Qiqian Huang ,&nbsp;Xindong Wang","doi":"10.1016/j.eiar.2025.108017","DOIUrl":"10.1016/j.eiar.2025.108017","url":null,"abstract":"<div><div>Despite extensive research on tropospheric ozone (O₃) formation, quantifying the impact of photochemical processes on source contributions remains challenging. This study developed a SHAP interaction redistribution analysis (SIRA) framework that systematically analyzes and reallocates machine learning interpretation results to quantify photochemical impacts on O₃ formation and source contributions. Based on improved photochemical age parameterization method, the mean VOC photochemical loss concentration was 7.44 ± 10.36 ppb, with alkenes, aromatics, and OVOCs showing the highest ratios of photochemical loss to observed concentrations (1.35, 0.90, and 0.66, respectively). SHAP analysis revealed meteorological factors and NO as primary contributors to O₃ formation (50.82 % and 12.24 %, respectively). The importance ratio of TVOCs to NO_x was 1.5 during the study period and increased to 2.4 during O₃ pollution episodes, indicating VOC-limited O₃ formation with enhanced VOC sensitivity during pollution periods. The SIRA framework identified secondary generation (48.38 %), biogenic emissions (13.87 %), and industrial emissions (9.33 %) as major O₃ contributors under photochemical loss conditions. After redistributing secondary generation through source interaction analysis, biogenic emissions and biomass burning showed the highest increases in SHAP importance (41.18 % with mean |SHAP values| = 1.87 and 40.27 % with mean |SHAP values| = 0.98, respectively), identifying them as the primary precursor sources for secondary generation. Among anthropogenic sources, vehicle emissions became the dominant contributor with a 17.0 % increase in contribution. This framework offers an innovative approach for quantifying the photochemical impacts on source contributions, enabling more targeted and effective strategies for O₃ pollution control.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 108017"},"PeriodicalIF":9.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lagged and cumulative effects of drought on global vegetation greenness, coverage, and productivity","authors":"Lei Zhang ,&nbsp;Xia Jia ,&nbsp;Yonghua Zhao ,&nbsp;Lishan Shan ,&nbsp;Yang Zhang ,&nbsp;Zenghui Sun ,&nbsp;Peng Zhang ,&nbsp;Shaocheng Si","doi":"10.1016/j.eiar.2025.108019","DOIUrl":"10.1016/j.eiar.2025.108019","url":null,"abstract":"<div><div>Vegetation dynamics have been greatly altered by the rising frequency of drought events. However, the response of various vegetation characteristics to the lagged and cumulative effects of drought remains poorly understood. Therefore, the lagged and cumulative effects of drought on global vegetation greenness (NDVI), coverage (LAI), and productivity (GPP) were investigated based on diverse vegetation characteristics and standardized precipitation evapotranspiration index (SPEI). And they were analyzed under different water balance gradients, climate zones, and vegetation types. The findings revealed that the lagged response of NDVI to drought was more timely, at 4.29 months. The cumulative response of GPP to drought was more timely, at 4.23 months. Cumulative responses to drought were generally stronger than lagged responses. Across different water balance gradients, the lagged months of NDVI displayed the most significant U-shaped distribution with increasing SPEI, whereas the cumulative months of GPP exhibited the most significant inverted U-shaped distribution. In addition, the arid zone experienced the strongest drought impacts on all vegetation characteristics. Grasslands and shrublands were more vulnerable to drought than forests. Among the three vegetation characteristics, NDVI accounted for the highest percentage of minimum lagged months, at 19.29 %. GPP had the highest percentage of minimum cumulative months, at 15.92 %. This study revealed the complexity of vegetation dynamics under drought stress, which could help us further understand the vegetation response in climate change, and thus provide a critical foundation for ecosystem management and climate change adaptation strategies.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 108019"},"PeriodicalIF":9.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is market mechanism a reasonable path for agricultural emission reduction? Evidence from China carbon emission trading scheme","authors":"Xin Zhao ,&nbsp;Rui Wang ,&nbsp;Andrea Gatto ,&nbsp;Chuanming Liu ,&nbsp;Xiaomin Wei","doi":"10.1016/j.eiar.2025.107972","DOIUrl":"10.1016/j.eiar.2025.107972","url":null,"abstract":"<div><div>We examine the mechanism of the carbon emissions trading pilot to lower the <span><math><msub><mi>CO</mi><mn>2</mn></msub></math></span> emissions of agriculture using empirical data from China, from the viewpoints of market mechanisms and spatial spillover effects. We use the DID to assess the pilot program's effectiveness in curtailing GHG emissions. We find a significant advantage in limiting <span><math><msub><mi>CO</mi><mn>2</mn></msub></math></span> emissions, using carbon emission data from 30 Chinese provinces from 2011 to 2022. The results are as follows: (1) An inhibitory effect is detected, showing that introducing a carbon trading program could reduce agricultural carbon emissions by 0.167 %; this finding passed the robustness test. (2) The results of the intermediate impact model demonstrate that carbon emissions trading may play a role in influencing agricultural carbon emissions via technological innovation. (3) Meanwhile, regional resource allocation efficiency adjusts the carbon reduction effect. (4) Pilot regions demonstrate joint emission reduction effects with neighboring regions, which show a positive spillover effect. Therefore, scientific and agricultural technology innovation should be fostered to realize technological research, gradually form a market governance mechanism for agricultural soils, and comprehensively enhance the carbon sink capacity of agricultural soils. This will ensure the sustainable and steady development of food systems.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"115 ","pages":"Article 107972"},"PeriodicalIF":9.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}