中国城市碳排放强度的空间溢出效应及驱动因素探究（英文）

In this study, we adopt kernel density estimation, spatial autocorrelation, spatial Markov chain, and panel quantile regression methods to analyze spatial spillover effects and driving factors of carbon emission intensity in 283 Chinese cities from 1992 to 2013. The following results were obtained.(1) Nuclear density estimation shows that the overall average carbon intensity of cities in China has decreased, with differences gradually narrowing.(2) The spatial autocorrelation Moran's I index indicates significant spatial agglomeration of carbon emission intensity is gradually increasing; however, differences between regions have remained stable.(3) Spatial Markov chain analysis shows a Matthew effect in China's urban carbon emission intensity. In addition, low-intensity and high-intensity cities characteristically maintain their initial state during the transition period. Furthermore, there is a clear "Spatial Spillover" effect in urban carbon emission intensity and there is heterogeneity in the spillover effect in different regional contexts; that is, if a city is near a city with low carbon emission intensity, the carbon emission intensity of the first city has a higher probability of upward transfer, and vice versa.(4) Panel quantile results indicate that in cities with low carbon emission intensity, economic growth, technological progress, and appropriate population density play an important role in reducing emissions. In addition, foreign investment intensity and traffic emissions are the main factors that increase carbon emission intensity. In cities with high carbon intensity, population density is an important emission reduction factor, and technological progress has no significant effect. In contrast, industrial emissions, extensive capital investment, and urban land expansion are the main factors driving the increase in carbon intensity.     

广州市乡村发展类型及演化模式

采用广州市域范围内行政村2005,2013年人口、社会经济、空间等现状摸查数据,运用GIS,SPSS等分析手段,对比研究乡村发展类型、空间特征及其动态演变规律,归纳其演变动力机制。结果表明:(1)影响乡村分类的主因子具有可持续性,但其影响程度总体减弱,而非持续性因子则具有时代特征,影响乡村发展的因子多元化;(2)乡村类型演变呈现由低等级分异向着高等级分异的演变趋势;(3)广州市乡村发展的空间分布整体呈现"圈层状"的分布状态,随着城市副中心的建设,人口、产业、基础设施出现了大幅扩散,乡村发展逐步走向多中心协同发展的局面;(4)广州市乡村发展演化的模式主要有渐变模式、突变模式和惰性模式。     

蓝绿空间暴露对老年人健康的邻里影响

利用2018年广州社区问卷数据、遥感影像、城市街景、环境污染等多元数据,提取多种蓝绿空间指标,并使用多层模型、中介效应模型和倾向值匹配法,探讨中国城市背景下蓝绿空间暴露影响老年人健康的“生物?心理?社会”邻里影响路径和机制,以及对不同社会阶层间的差异。研究发现,社区层面的蓝绿空间暴露与老年人的身心健康均存在显著相关;周围蓝绿空间程度通过促进体育锻炼、缓解压力提升老年人的身体健康,可达性通过促进社会交往提升老年人的心理健康;蓝绿空间暴露对老年人健康的影响在不同阶层间存在差异。为健康老龄化、健康城市建设提供科学参考。