The combined influence of natural conditions and the dense spatial distribution of elements at risk (EaRs) during rapid urbanization further intensifies the potential for cascading flood impacts. Comprehensive assessment of urban disaster risk and dynamic simulation of risk evolution are therefore essential for enhancing urban natural disaster risk governance capacity. In this study, an improved Implicative Interdependency Model (IIM) is employed to construct an interlayer and intralayer multilevel interrelation network to systematically characterize the geographical and functional interrelations among EaRs. From the perspective of EaRs, a disaster-scenario simulation model is then developed grounded in disaster propagation dynamics, and flood risk in the main urban districts of Changzhou is simulated under varying initial hazard intensity settings. The results demonstrate that incorporating functional interrelations increases the network efficiency of the EaRs interrelation network to 0.1760, exhibiting enhanced connectivity and transmission performance, and strengthening the potential for risk propagation. In addition, flood risk in the study area exhibits a distinct pattern characterized by lower risk in central districts and higher risk in peripheral areas. The disaster evolution process follows a pattern of short-term recovery in the early stage, deterioration in the middle stage, and stabilization in the final stage. Significant differences are also observed among functional zones in terms of response patterns, state evolution trajectories, and resilience thresholds. In particular, the agricultural zone and ecological zone experience relatively severe damage. This study provides decision support and technical reference for identifying high-risk urban flood areas and formulating risk governance strategies.

Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance. Multi-objective spatial collaborative optimization is a powerful method for achieving sustainable regional development. Previous studies on multi-objective spatial optimization do not involve spatial corrections to simulation results based on the natural endowment of space resources. This study proposes an Ecological Security–Food Security–Urban Sustainable Development (ES–FS–USD) spatial optimization framework. This framework combines the non-dominated sorting genetic algorithm II (NSGA-II) and patch-generating land use simulation (PLUS) model with an ecological protection importance evaluation, comprehensive agricultural productivity evaluation, and urban sustainable development potential assessment and optimizes the territorial space in the Yangtze River Delta (YRD) region in 2035. The proposed sustainable development (SD) scenario can effectively reduce the destruction of landscape patterns of various land-use types while considering both ecological and economic benefits. The simulation results were further revised by evaluating the land-use suitability of the YRD region. According to the revised spatial pattern for the YRD in 2035, the farmland area accounts for 43.59

Reducing shipborne carbon emissions is essential for achieving global decarbonization goals and improving coastal environmental management. This study develops an integrated framework combining AIS data with the STEAM model to quantify ship emissions in China's coastal waters and evaluate their spatiotemporal characteristics and carbon reduction potential. A standardized AIS data processing approach was established to estimate emissions from main engines, auxiliary engines, and boilers, with uncertainties controlled below 6%. Results show that total ship emissions increased by 75% from 2021 to 2023. Regionally, emissions continued to grow in the Yangtze River Delta, stabilized in the Pearl River Delta, and changed only slightly in the Bohai Rim. Spatial analysis indicates that emissions were highly concentrated in major hub ports, particularly Shanghai and Ningbo-Zhoushan. Significant regional heterogeneity was identified in carbon reduction potential, with the Yangtze River Delta exhibiting the highest mitigation potential, followed by the Pearl River Delta, while the Bohai Rim showed relatively limited potential. These findings provide scientific evidence for developing region-specific emission reduction policies and sustainable management strategies for China's maritime sector.

Rapid urbanization intensifies landscape fragmentation, making the optimization of ecological networks essential for maintaining landscape connectivity. Effective optimization needs a diagnostic understanding of a network’s internal cluster structure. However, clustering methods cannot simultaneously reconcile spatial adjacency with interaction strength, often yielding results that are either geographically fragmented or ecologically incomplete. The objective is to generate spatially coherent clusters while preserving critical functional connections, thereby enabling the identification of structural weaknesses for targeted conservation. The main contribution of this study is developing a spatially constrained method of ecological network clustering and optimization, which involves constructing a Maximum Spanning Tree (MaxST) under Voronoi-based adjacency rules and employing a Genetic Algorithm (GA) to optimally partition this structure. The framework begins by constructing a MaxST under strict spatial adjacency rules to form a contiguous network backbone. A GA then optimally partitions this backbone by maximizing modularity, incorporating interaction strengths from both adjacent and non-adjacent corridors. The method successfully identified ecologically meaningful and spatially contiguous clusters. It revealed that corridors between clusters, despite their greater length, constituted the network's most vulnerable links due to their lower interaction strength. The analysis pinpointed high-priority structural weaknesses for intervention, including key ecological pinch points, barrier areas, and critical bridging corridors. This study introduces a practical method that explicitly addresses the spatial-functional trade-off in ecological network analysis. It shifts the conservation focus from isolated landscape elements to diagnosing and repairing cluster-based structural weaknesses, offering a targeted pathway for enhancing connectivity in fragmented urban landscapes.

The ongoing reform of China’s spatial planning system significantly influences the achievement of Sustainable Development Goals. By fostering positive economic, social, and environmental interactions among cities, China has gradually established a coupled-networks to coordinate economic and ecological development. However, the current planning evaluation research usually focuses on the interior of the city, and lacks the evaluation of the planning convergence between different cities the integrity of this coupling deployment across different cities remains unclear. We conducted a systematic evaluation of China’s territorial spatial planning documents (encompassing 2715 county-level administrative units), constructing inter-urban socio-ecological networks by employing cities and districts as nodal units, with development-oriented partnerships and conservation-focused alliances explicitly stipulated in planning policies serving as social and ecological edges respectively. These networks were subsequently compared against multiple networks derived from land use/cover change (LUCC) analyses through multidimensional comparative analysis. Results show that 69.5% of the planned networks are supported by LUCC data; however, 10.4% of county nodes were overlooked by the spatial plans. Therefore, a broader city/county network should be constructed with a focus on poverty-stricken counties that have fewer opportunities, while also strengthening cooperation with bordering countries to improve the stability and completeness of the intercity network. This study provides a reference blueprint for sustainable city construction worldwide, particularly in developing countries.

This paper reviews the context and prospects for markedly improved sustainability of marine ecosystems and resources in China, based on accounting of marine ecosystem services and natural capital along with supporting policy and governance frameworks, in turn based on existing approaches in China's terrestrial social-ecological systems. Such integrated accounting, policy, and governance would provide a unique, novel, and innovative approach to regional-scale, sustainable ocean management. China is uniquely placed to implement such accountability, given the extensive adoption of accountability in terrestrial landscapes and the strong commitment to "ecological civilization" at the highest levels of national policy. Specifically, the paper outlines: The current, seriously degraded state of marine ecosystems and resources in China, largely due to economic drivers that ignore the valuable economic services provided by healthy marine ecosystems;The critical context of, and high-level commitment to, China's considerable development of environmental accounting, implementation and governance frameworks in terrestrial landscapes;Existing approaches for assessing marine natural capital in China, and the relationships between them;Currently available assessments;Current governance arrangements for marine ecosystem management in China.The paper then provides a potential implementation pathway for a system of standardised, nationally integrated, provincially-implemented marine environmental accounts, policy and governance, adapted from existing terrestrial arrangements. Such accounting, if embedded in rigorous governance and policy structures to drive real-world implementation, could generate a major improvement in sustainability of China's marine ecosystems. Given the extent of China's marine jurisdiction, and severity of ongoing degradation, such improvement could have enormous environmental and economic benefits within China, and at a global scale.

Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable development. This study analyzed the spatiotemporal evolution and landscape pattern change of construction land in the Yangtze River Delta(YRD) region from 1990 to 2018 by integrating Geographical Information System(GIS) spatial analysis and landscape pattern indices, and revealed its driving mechanism by XGBoost and SHapley Additive ex Planations(SHAP). Moreover, we compared the disparities in the core driving factors for construction land evolution in cities with diverse development orientations within the YRD region. Results show that: 1) development intensity of construction land continued to increase from 7.54% in 1990 to 13.44% in 2018, primarily by occupying farmland. The landscape fragmentation of construction land in the YRD region decreased, and landscape dominance increased. Spatially, the eastern part of the YRD exhibits a high degree of spatial agglomeration of construction land, whereas the western part shows a high degree of fragmentation, revealing distinct spatial gradient differentiation characteristics. The landscape dominance of the construction land in the eastern region of the YRD is higher than that in the western and northern regions. 2) Transportation and infrastructure exert the highest contribution rate on development intensity changes of construction land in the YRD. The industrial structure significantly influences the conversion of farmland to construction land. Additionally, infrastructure plays a crucial role in shaping the spatial agglomeration patterns of construction land. Population distribution is the dominant factor determining the regularity of the landscape shape of construction land.3) The core driving factors for the development intensity of construction land in central cities primarily lies in transportation, whereas for non-central cities, besides transportation, the year-end balance of per capita savings deposits of urban and rural residents also play a significant role. The area change of construction land occupying farmland in central and non-central cities is mainly driven by industrial structure and economic level, respectively. This study informs refined spatial optimization and regional high-quality integrated development.

As a significant contributor to global greenhouse gas emissions, researches focusing on greenhouse gas emissions from crop production have garnered substantial attention. The spatial variability in emission intensity means that changes in cropland location (cropland displacement) can significantly impact greenhouse gas emissions. However, there remains a notable lack of research in this critical area. Therefore, this study employed the LMDI model and multi-source data to estimate the contribution of cropland displacement to greenhouse gas emissions, comparing this driver with two others: the net change in cropland area and the greenhouse gas emissions intensity of unchanged cropland. Our results suggest that between 2000 and 2020, the cropland centroid in China shifted approximately 61.66 km to the northwest, and increased 36.49 Mton crop production greenhouse gas emissions. Cropland displacement accounted for about 19.8 % of this increase. Additionally, the increased emission intensity of unchanged cropland contributed to a 117.3 % rise in emissions, whereas cropland loss resulted in a 37.1 % decrease. Given the global trend of cropland displacement, the insights presented in this paper have far-reaching implications. We recommend that future cropland management and protection policies incorporate the greenhouse gas emission impacts of cropland displacement to effectively balance food security with environmental sustainability.

High-intensity land use and fragmented habitats are becoming more prevalent with urbanization, thereby accelerating the demand for maintaining and improving the ecological connectivity of habitat patches in high-density built-up areas. Previous studies have shown that small dispersed patches are crucial for enhancing connectivity across an entire landscape. However, as an important component of urban green space, residential green space in high-density built-up areas is often overlooked in ecological connectivity analysis. Taking Futian district, Shenzhen, as a case study, we explored the ecological connectivity in high-density built-up areas considering not only habitat patches but also green areas in residential quarters. We identified ecological patches and green areas in the residential areas of the study area. This was followed by a functional connectivity analysis under different scenarios. Several protection suggestions for improving ecological connectivity have been proposed based on functional connectivity analyses under different scenarios. The results show: 1) The area of residential green space in Futian district is 3.86 km2, covering 26.9% of the total green space in the study area, with the western part being sparser than other regions. The total area of the ecological patches was 14.34 km2, and the importance of the patches was not consistent with their size. The ecological connectivity of Lianhuashan Park in the central region, Lichi Park in the eastern region, and Huanggang Park in the southern region is greatly affected by the contiguous or continuously distributed strips of residential green space around them. 2) Residential green spaces affect eco-connectivity primarily by lowering corridor resistance, creating connectors for regions that require protection, and supporting biological flow. In particular, it had the largest effect on middle-resistance corridors (the unit cost distance was reduced by 29.2%) and alleviated the situation of pinch points formed in narrow low-resistance channels in high-density built-up areas. 3) The ecological pinch points that recurred in the ecological network under different scenarios of connecting residential green spaces and different resistance thresholds were identified as the most valuable primary pinch points for protection. It is recommended to strengthen the intersection of Xinzhou Road and Fumin Road and prioritize the protection of residential green spaces located near the ecological patches and on the topological connection between the ecological patches, with a scale exceeding the average size of 5,920.22 m2. Through the analysis of pinch points in various scenarios, it was found that 21 pinch points, including those close to Lianhuashan Park, could be used as substitute green spaces for urban renewal projects when nearby residential green spaces are destroyed or occupied. This supports the preservation of functional connectivity in urban renewal projects. It is increasingly difficult to construct significant habitat patches in high-density built-up areas to compensate for habitat fractures. The results identified the significant location and proportion of residential green spaces as critical bio-flow carriers in Futian District. These findings could encourage more comprehensive urban conservation plans that incorporate both sizable habitat patches and residential green spaces. These findings can be used to create more effective sustainable development plans that encourage biodiversity in urban renewal planning.

Urbanization in China has led to land-use changes resulting in landscape fragmentation, natural habitats loss and ecological connectivity decline. Aiming to support sustainable landscape planning, we proposed an integrated method for ecological structure assessment and optimization including morphological spatial pattern analysis (MSPA), minimal cumulative resistance (MCR) model and circuit theory to assess landscape fragmentation and ecological connectivity change at regional scale. A modified connectivity index is also proposed by employing the index of relative quality of ecological patches and corridors. We applied the combined methods to Jiangsu province in eastern China for multi-temporal landscape analysis and optimization. The results showed that the combined analysis revealed both fragmentation trend of ecological patches and ecological connectivity reduction with regard to all the species as a whole in the study area from 2000 to 2018. While, the trend has been slowed down to a certain extent lately, which is related to a series of ecological protection policies implemented in the study area, including ecological redlines policy, national park construction and returning marginal farmland into forest or grassland. Furthermore, suggestions for improving the ecological network in the study area were proposed. We proposed to improve the ecological network by fostering twenty-five potential ecological sources, maintaining twenty-five pinch points, restoring eleven dredging corridors and planning fifty-three stepping stones. Overall, we argue that the combined method can reveal both structural connectivity and functional connectivity, and the time series analysis can provide dynamics situation for better understanding and planning landscape process. It can also provide planners with a valuable strategic tool that advances the practical utility of landscape ecology techniques for spatial planning, and the combined application of the method helps to reduce some of the limitations of each individual method.

With rapid urbanization, urban functional zones have become important for rational government and resource allocation. Points of interest (POIs), as informative and open-access data, have been widely used in studies of urban functions. However, most existing studies have failed to address unevenly or sparsely distributed POIs. In addition, the spatial adjacency of analysis units has been ignored. Therefore, we propose a new method for identifying urban functional zones based on POI density and marginalized graph autoencoder (MGAE). First, kernel density analysis was utilized to obtain the POI density and spread the effects of POIs to the surroundings, which enhanced the data from unevenly or sparsely distributed POIs considering the barrier effects of main roads and rivers. Second, MGAE performed feature extraction in view of the spatial adjacency to integrate features from the POIs of the surrounding units. Finally, the k-means algorithm was used to cluster units into zones, and semantic recognition was applied to identify the function category of each zone. A case study of Changzhou indicates that this method achieved an overall accuracy of 90.33% with a kappa coefficient of 0.88, which constitutes considerable improvement over that of conventional methods and can improve the performance of urban function identification.

[目的]分析景观生态风险的发生机制,改善风险评估框架进而评估长三角地区各类景观生态风险,为长三角地区生态风险管控和生态文明建设提供参考.[方法]基于适应性循环理论"潜力-连通性-恢复力"三维视角构建生态受损概率指标体系,以生态系统服务为评价终点,从生态系统服务和生态受损概率两方面综合评估了长三角地区2000年、2010年、2020年景观生态风险,并判定研究区所处的风险适应性阶段.[结果](1)长三角地区生态系统服务指数总体表现为升高趋势,并呈现南高北低的空间格局;(2)生态受损概率呈现南低北高、西低东高的空间特征,时序变化特征为围绕城市建成区先扩展后收缩;(3)景观生态风险总体较低,中低风险区域占大比例,高风险区集中在城市建成区周围,部分快速发展城市的生态风险值逐渐升高;(4)从适应性循环阶段来看,长三角地区部分地区已开始从快速发展向稳定可持续发展转变,处于开发阶段的区域减少,处于释放阶段的区域增加.[结论]适应性循环理论能够阐明生态本底、景观格局和动态过程之间的关系及其对景观生态风险的作用机制,可以较好地融入生态风险预测框架,提高景观生态风险预测的有效性、准确性.

高精地图为自动驾驶定位、感知、规控等模块提供诸多超感知范围的车道级地图要素,是L3 及以上自动驾驶中不可或缺的一部分.高精地图精度高且数据量大,而通常自动驾驶车端算力有限,因此离不开高精地图数据引擎对要素的快速解析与动态提取.本文提出了一种面向自动驾驶的高精地图数据引擎模型,通过对高精地图进行数据转换、要素获取、地图匹配、路网构建、数据播发、车载以太网传输、路网重建与应用适配,持续高效地为自动驾驶提供所需的静态与动态要素信息,以满足车辆在行驶过程中对高精地图的实时需求.

Quantitative ecosystem services valuation (ESV) is the key to effective environmental protection and ecosystem restoration. Studies have focused on terrestrial ecosystems and are mainly based on static analyses, excluding marine ecosystem service values and their variability. In this study, we comprehensively evaluated terrestrial and offshore ecosystem service values in Jiangsu Province in 2010 and 2018 using a table of unit area value equivalence factors and a vertically generalized production model (VGPM) to estimate marine primary productivity. The results showed that the terrestrial ESV in Jiangsu Province was 322.740 and 477.798 billion yuan in 2010 and 2018, respectively. The ESV of hydrological regulation in water areas was the highest, whereas that of unutilized land was the lowest. The ESV in different prefectural-level cities exhibited significant spatial heterogeneity and were highly correlated with the proportion, protection, and rational utilization of urban water areas. The offshore ESV in Jiangsu Province was 426.011 and 460.438 billion yuan in 2010 and 2018, respectively; the farther from land, the lower the ecosystem service value. The value of ecological regulation services is the dominant factor in the comprehensive services of terrestrial and offshore ecosystems in Jiangsu Province (accounting for 80% of ESV). From 2010 to 2018, the overall terrestrial and offshore ESV in Jiangsu Province rose by 188.901 billion yuan, increasing by 25.28% from 2010. In future, boundaries of development in production activities should be controlled, the protection and restoration of the ecological environment promoted, and regulatory functions and cultural services of ecosystems rationally exploited.

The rapid development of economy and society leads to the rapid expansion of cities, resulting in the atrophy of urban ecological space and the decline of ecological function, as well as a serious threat to urban ecological security. It is of great significance for the sustainable development of a city to systematically analyze the structure of urban ecological space and put forward targeted protection and optimization measures. Taking Changzhou City as the research area and considering the natural ecological function and social service function of urban ecological space, we constructed two ecological networks, the "source-corridor" ecological network based on natural ecology and the "supply-demand" ecological network based on human ecology. For the "source-corridor" ecological network, quantitative analysis was mainly carried out from the importance of nodes, network connectivity and stability. For the "supply-demand" ecological network, quantitative analysis was mainly carried out from the importance of nodes, supply-demand equilibrium and stability. The results showed that the levels of connectivity and stability of the "source-corridor" ecological network in the main urban area of Changzhou were not high, the stability level of the "supply-demand" ecological network was general, and there was spatial mismatch between service supply and demands. From the perspective of connectivity and stability improvement, an optimization scheme of "source-corridor" ecological network with 12 additional source nodes and 57 corridors was proposed. From the perspective of supply-demand balance and stability improvement, an optimization scheme of "supply-demand" ecological network with 22 new supply nodes was proposed. Compared with the original "source-corridor" ecological network, the connectivity level of the optimized network was improved by 10%, and the network stability was improved by 0.05. Compared with the initial "supply-demand" ecological network, the service level of the optimized network was improved by 4%, and the network stability was improved by 0.10. Finally, we integrated the two ecological networks, and formulated the implementation plan of protection and management for both the current protected patches and the new ecological nodes.

城市活力是城市可持续发展的保障,基于人口格网、夜间灯光、兴趣点和土地利用等数据,利用熵值法、空间句法和双变量空间自相关分析等方法开展常州市城市活力研究.研究发现:常州城市活力空间差异明显,活力总体上"中心高、外围低"并呈现沿规划发展轴向外延伸的趋势;全局来看,完善功能设施配置、提高局部可达性有助于吸引人的聚集活动、提升活力水平,提高全局可达性则可能会降低活力水平;局部来看,人的分布活动与空间功能设施存在一定的不匹配,部分城中村及老旧街区人口密集、活动强度大但功能设施配置不足,城区外围的小型商业、产业及居住活动中心的功能设施密度较大但服务的人口和范围有限.研究初步揭示了常州市不同维度活力的空间分布特征和相关关系,识别了人的分布活动与承载空间的匹配情况,可为常州市城市活力营造、资源配置和规划管理提供参考.

基于图斑尺度的耕地细碎化评价及整治有利于耕地布局优化,促进农业规模化与集约化发展.该研究以耕地图斑为基本评价单元,引入聚合分析来量化图斑间空间位置关系,围绕耕地细碎化内涵选取评价指标;运用热点分析和二步聚类算法来对研究区功能分区,在功能分区基础上,基于带轮廓系数的k-means聚类算法,评价耕地图斑的细碎化程度.结果表明:1)根据功能分区的聚类结果,新北区被划分为不显著区、连片规整区、离散复杂区;2)评价结果将新北区耕地图斑分为3类:类别一,离散破碎类,包含图斑17332块,平均图斑面积过小,连片度低,图斑面积集中在0～10000 m2,面积占比21.98％,连片度集中在1～4,主要分布在新北区中心区域;类别二,形状复杂类,包含图斑4535块,图斑形状复杂不规整,面积占比9.65％,形状指数集中在1.5～2.5,均匀分布在全区;类别三,连片规整类,包含图斑4091块,图斑集中连片、形态规整,面积占比68.37％,连片度集中在5～10,形状指数集中在1～1.5,主要分布在外围区域;并基于各类别耕地细碎化属性差异,提出相应的优化模式和整治意见.研究结果可以为耕地细碎化整治提供一定参考.

选择长三角为研究区,构建生态空间质量评价体系,结合可达性分析、统计分析方法,通过人口、GDP、土地开发强度反映生态需求程度,分析生态空间质量的空间分布和生态空间满足人类需求程度的空间分异及演变特征.结果 表明:(1)通过融合可达性分析、统计分析方法建立的生态空间供需平衡指数,能很好地识别生态空间供需"短板".(2)长三角生态空间质量从北向南逐渐升高,1995-2015年生态空间质量较差的区域从各大城市中心部分扩大到城市周边地区.(3)长三角生态空间供需平衡的空间分布具有明显的时空差异,供给不足的区域主要是在经济和城市化发展较快的城市,供大于需的区域主要是在生态高质量区域.

Accurate urban morphology provided by Local Climate Zones (LCZ), a universal surface classification scheme, offers opportunities for studies of urban heat risk, urban ventilation, and transport planning. In recent years, researchers have attempted to generate LCZ maps worldwide with the World Urban Database and Access Portal Tools (WUDAPT). However, the accuracy of LCZ mapping is not satisfactory and cannot fulfill the quality demands of practical usage. Here, we constructed a high-quality sample dataset from Chinese cities and presented a patch-based classification framework that employs chessboard segmentation and multi-seasonal images for LCZ mapping. Compared with the latest WUDAPT method, the overall accuracy for all LCZ types (OA) and urban LCZ types (OA(u)) of our framework increased by about 10% and 9%, respectively. Furthermore, based on the analysis of population distribution, we first gave the population density of different built-up LCZs of Chinese cities and found a hierarchical effect of population density among built-up LCZs in different size cities. In summary, this study could serve as a valuable reference for producing high-quality LCZ maps and understanding population distribution patterns in built-up LCZ types.

良好的健康和人类福祉是联合国提出的可持续发展目标之一,提高人口预期寿命是迈向此目标的重要一步.由于中国城市在自然环境和社会发展方面有所差异,因此理解不同城市居民的预期寿命主要受何种因素的影响是制定城市公共卫生策略的关键.本研究基于2015年中国286个城市的有效数据,利用探索性回归、普通最小二乘回归、地理加权回归筛选与预期寿命最相关的影响因素并探索其空间差异,再通过二阶聚类将城市分类,以针对性地提出每类城市政策建议.结果 显示:①经济发展,教育条件和医疗设施条件对预期寿命有显著的积极影响,平均海拔和环境污染则具有负面影响;②东南地区的经济发展对当地居民的预期寿命影响程度更大;东北和西南地区的医疗设施条件对其居民预期寿命促进程度更高;北部地区的教育条件对当地居民预期寿命影响比其他地区更高;平均海拔对西部地区居民预期寿命的影响最大;西北地区居民的预期寿命则更易受到环境污染带来的负面影响;③根据空间差异将城市分为3类,其居民预期寿命关键影响因素依次是经济发展和环境污染、教育条件、医疗设施,每类城市的城市管理者应重点关注不同因素来提升居民的预期寿命.