基于ARCGIS的四川省分级退耕还林还草空间决策分析

首先,利用遥感和GIS技术建立土地利用、土壤侵蚀、数字高程模型、坡度、生态环境质量等级、植被指数、降雨、温度、植被分区、土壤类型和行政区、水体缓冲区、聚落缓冲区等栅格GIS数据库。其次,将旱地数据分别与坡度、土壤侵蚀、植被指数、生态环境质量等级、水体缓冲区和聚落缓冲区等栅格指标数据进行叠加分析。再次,利用各指标构建了基于ARCGIS的一、二级退耕决策模型及其空间复合模型,并得到一、二级退耕面积分别为724 495hm²和333 085hm²。然后,利用温度和降雨指标数据构建了基于ARCGIS的还林还草决策模型,并得到一、二级还林的面积分别为702 362hm²和331 357hm²,还草的面积分别为22 133hm²和1 728hm²。最后,将其分别与行政区、植被分区和土壤类型数据进行空间叠加统计分析,得到各行政区的退耕还林还草情况,以及每一个退耕栅格单元所处的植被分区和土壤类型情况。研究表明,该方法可以节约大量的人力、物力和财力。其研究结果对退耕还林还草工程的规划、实施和管理等具有较大的应用价值。     

地理信息系统在环境模型研究中的应用

结合国内外环境信息系统的研究现状和研究实例,首先分析了ＧＩＳ与环境模型研究结合的必要性和ＧＩＳ在环境模型研究中潜在的应用范围,然后剖析了ＧＩＳ与环境模型研究结合的三阶水平并介绍了ＧＩＳ在环境模型研究中的应用现状,最后分析了ＧＩＳ和环境模型研究结合的发展趋势并给出了ＧＩＳ、ＲＳ、ＥＳ与环境模型理想的结合框架。     

同行评议初探

探索了同行评议的定义及历史来源,从科学社会学的角度对同行评议的功能和意义进行了阐述,进而简单综述了同行评议的主要应用领域及研究现状。通过对同行评议的体制性和非体制性不足的探讨,指出了今后同行评议研究应该展开的方向。     

An integrated approach for the benchmarking of production facilities’ environmental performance: data envelopment analysis and life cycle assessment

Environmental impacts have become an important consideration in the manufacturing industry due to increasing public pressure for environment protection and the requirements of recently launched legislations. Data envelopment analysis (DEA) is a widely adopted methodological approach for the benchmarking of the relative efficiency of different production units. Changes in production efficiency may affect environmental impacts. DEA can be used for identifying the most efficient production facility and hence, the environmental impacts generated from the different production lines can then be benchmarked. Life cycle assessment (LCA) is carried out to quantify the full environmental impacts of a product from ‘cradle to grave’. The integration of LCA with DEA, efficiency and environmental impact of different production processes for a certain family of products can be evaluated and benchmarked. The proposed two-stage approach can help to reduce the aggregate environmental impacts of the manufacturing phase and is used to benchmark the environmental performance of several production lines in a manufacturing company.     

Sam Mannan and his scientific publications: A life in process safety research

Dr. M. Sam Mannan is one of the true pioneers in the process safety area, spending almost his entire lifetime in process safety and risk research. He was dedicated to ‘make safety second nature’ and published an impressive body of work. An overview of his research helps understanding the process safety area and provides insight in the legacy of this process safety pioneer. In this paper, 327 publications authored by Dr. Mannan from 1999 to 2019 in Web of Science core collection were downloaded and visually analyzed from four perspectives: his publication outputs, collaboration networks, topic areas, and highly cited papers and cited references. The results show a rapidly increasing trend in his research activity, mostly through journal publications. He published in 53 different outlets, with Journal of Loss Prevention in the Process Industries being most frequently selected. Dr. Mannan had a very active and diverse worldwide network, and collaborated with 18 different countries/regions, nearly 90 different institutions and 387 authors. His publications addressed process safety-related topics widely, including safety related to liquefied natural gas, explosions, runaway reactions, inherent safety, flammability and aerosol, and more recently resilience. Dr. Mannan's most cited paper focused on ‘fuzzy risk matrix’, whereas the most frequently cited reference in his work is ‘thermal hazard evaluation by an accelerating rate calorimeter’ by Townsend DI in 1980. Based on his most recent research activity, promising future directions for process safety research include resilience linked to risk assessment and management, for instance through the ‘safety triad’ concept he promoted shortly before passing away.     

Identification of Priority Areas for Integrated Management of Semiarid Watersheds in the Ecuadorian Andes

Integrated watershed management (IWM) is a priority, especially in semiarid regions that are concurrently affected by population growth, land use change, soil erosion, and poor governance. In developing countries, IWM is often done without any support tool, scientific data, or deep knowledge of territory characteristics. The aim of this study was to present a case study to apply a decision support tool to prioritize areas for territory management. A simple, quantitative multi‐criteria analysis was applied in a semiarid basin of the Ecuadorian Andes to identify the zones of greatest concern for implementation of resource conservation and management practices at a local and regional scale. In addition to describing the current state of the conditions of this basin, our results suggest scenarios of change in relation to official population projections based on spatial analysis of land use change. Analysis resulted in a scattered distribution of priority values within the watershed, so a hierarchical rule was incorporated to define priorities at the subwatershed (SW) scale. Our analysis identified four SW of very high priority and urgent need to implement management practices. Based on projections of future change due to population growth and land cover change, the number of subbasins that require more attention was doubled. Finally, this study includes zones for management or conservation of the land, according to the Sustainable Development Goals.     

资源循环科学与工程专业课程体系优化与教学内容创新实践的探索

针对资源循环科学与工程本科专业课程教学,以西安建筑科技大学该专业课程体系为案例,通过对毕业生和专业研讨会调研,分析了课程体系建设的现状和存在的问题。借鉴其他高校资源专业的课程体系和教学内容,通过梳理各门专业课程的教学内容和相互联系,构建了资源专业课程体系课程群,探索了课程体系优化的方法和增加创新实践环节的具体措施。     

环境DNA宏条形码监测水生态系统变化与健康状态

开展快速可靠的水生态监测并预测其变化趋势,对保护水生态环境具有重要的价值。近年来,环境DNA宏条形码技术(简称环境DNA技术)的快速发展弥补了传统形态学生物监测的缺陷,显著提升了水生生物群落的监测能力。与机器学习、遥感和云服务等技术结合,环境DNA技术不仅能大尺度、高频率、高灵敏度、自动化地获取生态监测信息,而且能准确地识别水生态系统的变化趋势,进而改变对水生态系统的认识与管理方式。因此,研究着重总结了环境DNA技术在水生态监测中的应用,分析了环境DNA技术与机器学习、卫星遥感等跨学科合作的潜在机遇,基于环境DNA技术简单、便捷的优势,提出了社会公民参与水环境保护的生态监测新思路。     

Sea-Level Rise in Public Science Writing: History,Science and Reductionism

Sea-level rise is a dramatic effect of climate change, with profound implications for societies around the world. In the past few years, a rush of literary non-fiction books have appeared that aim to explain the threat of rising seas to the public. This paper critiques how sea-level rise is framed in many of those books, on two accounts. First, anthropogenic sea-level change is frequently framed by accounts of natural variations of sea level in earth history, focusing on geological rather than societal processes. Second, single and sudden floods are often used to exemplify sea-level rise in ways that draw attention away from incremental environmental change in favour of fast-paced but de-contextualized events. The paper argues that both these frames de-politicize sea-level rise and may steer public understanding and discussion away from relevant social, cultural, and ethical considerations. As examples of climate reductionism, these depictions may obstruct rather than facilitate appropriate negotiations in response to predicted sea-level rise.     

A Short Survey Instrument to Segment Populations According to Their Attitudes Toward Science. Scale Development,Optimization and Assessment

ABSTRACT

Surveys play a key role in researching public perceptions of and attitudes toward science. Accordingly, there is a breadth of often-used survey instruments available which have also been adopted for segmentation analyses. Even though many of these segmentation solutions are similar in their aims, they often include a large numbers of variables, making it more difficult for other researchers to build on these solutions, as survey time is scarce. Therefore, we demonstrate how a large number of variables that were used for a comprehensive segmentation analysis can be reduced considerably without losing too much information. We develop and test a short survey instrument to segment populations according to their attitudes toward science. Results show that segmentation results can be replicated with over 90% accuracy by reducing the instrument from 20 to 10 variables. This reduction does not significantly affect the predictive power of segment attribution on three dependent variables, which suggests that many segmentation analyses could be similarly optimized, helping researchers save survey time and standardize segmentation analyses more.