Assessment of Damage of Marine Ecosystem Services Caused by Offshore Oil Spill Based on REA

人类对海洋石油资源的开发与利用日益扩大，频繁的海上运输和海上油田勘探开发导致石油泄漏事故屡屡发生。近年来石油污染正逐渐成为我国海洋环境中的主要污染物，且污染量呈上升趋势，其中近岸海域溢油事件频繁发生，且近岸海域生态系统敏感度高，故人类活动造成的溢油事故对近岸海域生态系统造成重大压力。海洋溢油事件所引发的生态损害之技术问题，已成为国内外该领域研究和政府管理部门制定相关规范的重大需求。然而，在中国目前完成的海洋溢油损害赔偿案例中，所获赔偿仍多集中于清污、渔业资源损失等直接费用，生态系统损害等间接影响则仍处于研究层面，研究内容则鲜少涉足生态系统服务功能损失评估。因此，开展近岸溢油对海洋生态系统服务功...The development and utilization of offshore oil resources are enlarging increasingly, because of the frequent maritime transport and oil exploration, the oil spill accidents occur frequently. Petroleum have become the main contaminant in seawater in China and the oil pollution is getting worse and worse. Among the oil spill accident, most of which occurred in coastal waters. Due to the highly sens...学位：理学硕士院系专业：海洋与地球学院_海岸带综合管理学号：2242011115136

生物质快速热解制取生物油研究现状探析

生物质快速热解制得的生物油可以用作燃料和化工产品,具有替代化石能源的巨大潜力,生物油的产率和组成取决于生物质组成和工艺操作参数。通过对生物质快速热解反应及热解反应器的介绍,着重讨论了生物质原料、热解反应温度、热解时间、升温速率、蒸气停留时间、进料率速度、颗粒大小、生物量组成、催化剂及其原料预处理对生物油产率的影响,以期为今后生物质热解的相关研究提供参考。国家自然科学基金面上项目(31670599)资助;;\n云南省教育厅科学研究基金研究生项目(2018Y115)资助;;\n云南省新能源重大科技专项(2015ZB001)资

木质生物质催化热解制备富烃生物油研究进展

生物油是木质生物质等原料经过热解获得的绿色产物,富含多种化学和生物活性物质,在石油替代方面具有发展潜力。生物质催化热解技术是制备高品质生物油的主要途径,但由于生物油含氧量比较高、目标产物选择性比较低、催化剂易结焦失活,限制了其应用。笔者从木质生物质热解机理及其反应途径、催化剂(金属氧化物、金属盐类、微孔催化剂、介孔催化剂)及其催化热解转化机理与产物调控机制、供氢试剂(四氢化萘、甲醇、废旧塑料、废弃油脂及其他供氢试剂)及其共催化热解转化机理等方面综述了木质生物质催化热解制备高品质生物油的进展,概述了催化热解过程中生物油的热解特性、产物组成以及转化机理,并对存在的问题及其解决方案进行了分析,展望了未来的发展方向,以期为木质生物质的高效转化利用提供依据和参考。国家自然科学基金(31670599,31870570);;厦门大学闽江学者特聘教授科研启动项目;;国家林业局“948”项目(2013-4-08);;云南省教育厅项目(ZD2014012,2018JS325

Assessment on the Ecosystem Service Losses Methods of Marine Oil Spill

当前,海洋溢油事件所引发的生态损害之技术问题,已成为国内外该领域研究和政府管理部门制定相关规范的重要需求。然而,在中国目前完成的海洋溢油损害赔偿案例中,所获赔偿仍多集中于清污、渔业资源损失等直接费用,生态系统损害等间接影响则仍处于研究层面,研究内容则鲜少涉足生态服务功能损失评估。本文归纳了生态服务功能概念的历史演化,概括了海洋溢油生态服务功能损失评估方法,通过评述和分析,为我国海洋溢油管理的研究与实践提供参考。At present,the technical problems of the ecological damage assessment caused by oil spill,has become a significant requirement for this research field and the government to formulate the relevant management measures.However,in the current cases of marine oil spill damage claim in China,most compensation focus on the direct losses including the loss of fishery resources,the cost of the rack cleaner,etc.; the indirect effects,like the ecosystem damage,have been concerned but still at the theoretical research phase.There was rare study about the assessment on the ecosystem service losses.This paper summarizes and analyzes the historical evolution of the ecological services,and the assessment methods of marine ecosystem service losses,in order to provide valuable references for the oil spill research and management in China.海洋公益性行业科研专项(编号:200805095); 国家海洋局海洋溢油鉴别与损害评估技术重点实验室2012年度开放基

智能家居中的边缘计算

近年来，智能音箱、扫地机器人已经成为很多用户生活中不可或缺的一部分.随着物联网技术的发展，越来越多的智能设备走进家庭场景，让用户的生活变得更加便捷和舒适.当种类繁多、功能细分的智能设备通过网络进行连接和控制时，为了解决网络延时、数据安全等诸多问题，基于边缘计算的智能家居成为未来趋势.探讨智能家居场景中的边缘计算，介绍围绕感知、通信和计算3个方向所展开的研究.在感知方面，关注边缘节点的泛在感知能力，介绍在非接触式呼吸监测上取得的进展；在通信方面，研究无线感知和无线通信的融合设计，在有限的频谱资源上兼顾感知和通信；在计算方面，关注基于边缘节点的个性化机器学习，在不泄露用户数据的前提下建立个性化机器学习模型. In recent years, smart speakers and robotic vacuum cleaners have played important roles in many people's daily life. With the development in technology, more and more intelligent devices will become parts of home infrastructure, making life more convenient and comfortable for residents. When different types of specialized intelligent devices are connected and operated over the Internet, how to minimize network latency and guarantee data privacy are open issues. In order to solve these problems, edge computing in smart homes becomes the future trend. In this article, we present our research work along this direction, covering the topics on edge sensing, communication and computation. As for sensing, we focus on the pervasive sensing capability of the edge node and present our work on contactless breath monitoring; as for communication, we work on the joint design of sensing and communication, so that sensing and communication systems can work harmoniously on limited spectrum resources; as for computation, we devote our efforts to personalized machine learning at the edge, building personalized model for each individual while guaranteeing their data privacy. © 2020, Science Press. All right reserved