River environmental decision support system development for Suzhou Creek in Shanghai

The Suzhou Creek Rehabilitation Project (SCRP) is one of the largest water-related environmental rehabilitation schemes ever undertaken in the vicinity of Shanghai, China. This paper details the development and application of a River Environmental Decision Support System (REDSS) for scientific planning and decision-making on the Suzhou Creek project, and illustrates the flexibility of the REDSS framework. We developed the following components: (1) a GIS-based analysis employing Component technology; (2) a "data mart" for multi-dimensional, multi-level, integrated, dynamic, and flexible data querying; and (3) a set of hydrodynamic and water quality models which can simulate complex tidal river networks. In addition, we detail how a water quality assessment model is embedded into the REDSS by employing an Identification Index Method. With the REDSS, all GIS and non-GIS components are integrated seamlessly and data from different sources can be queried simultaneously. This allows for various scenarios to be simulated and analyzed in advance to predict and assess the effects of proposed engineering and management measures. Generated information can thus support effective decisions. All operations of the REDSS can be implemented conveniently through user-friendly interfaces. The function of the REDSS framework is demonstrated through an application to Suzhou Creek. Because the REDSS characteristics are quite general, it may be applied in different geographic regions.     

中国水资源利用效率评估及区域差异研究

水资源危机、水环境恶化已成为我国所面临的严峻挑战,对我国的水资源利用效率进行科学合理的评价,并且讨论造成区域差异的影响因素显得尤为迫切。在全要素生产框架下,将环境要素纳入到效率分析中,利用数据包络分析模型,采用省级层面统计数据,以资本、劳动力和水资源使用量为投入,以国内生产总值与废水排放量为产出,计算我国2000~2011年区域水资源利用效率。研究发现,在时间序列上,我国各省份之间的用水效率差距逐年增大;在空间上,我国的水资源利用效率存在明显的东、中、西部区域差异。进一步研究发现,产业结构、经济发展水平、水资源禀赋、水的基础设施投入对区域水资源利用效率均有显著影响,而水价并没有对水资源利用效率产生显著影响。     

A method for assisting the accident consequence prediction and cause investigation in petrochemical industries based on natural language processing technology

Risk analysis for production processes in the petrochemical industry is an important procedure for consequence prediction and investigation of accidents. The analyzer must grasp the correlations between the possible causes and consequences. From the potential cause and effect found in risk analysis reports, complete clarification should be obtained. Therefore, this study presents a method for assisting accident consequence prediction and investigation in the petrochemical industry based on risk analysis reports using natural language processing technology. First, a hazard and operability (HAZOP) historical data table is established by filling over 7200 HAZOP analysis data points. Both the causes and consequences in the table are classified into 20 categories each using the Latent Dirichlet Allocation (LDA) models. The LDA clustering results are assigned classification for the cause and consequence topics to the cause and consequences of the HAZOP analysis data. Based on part-of-speech (POS) tagging, all the words in each cause and consequence record are divided into subject and action words. Next, the word combinations of subject and action words with a higher occurrence are considered the key phrases for describing and representing the corresponding cause and consequence topic classifications. The Apriori algorithm is used to determine the frequent item sets, acquire the association rules, and calculate the association degree to obtain the sort order; it can highlight general trends in relational cause and consequence topics. According to the results, the most likely cause of the consequence and the most likely consequence that the cause may lead to are identified. Finally, a visual interface is developed to present the data for the consequence prediction and cause investigation of accidents. The results reveal that the quantity and quality of historic data are important factors that may influence the results. This method can contribute to predicting the accident evolution trend of an abnormal situation, taking preventive measures in advance, improving the accuracy of early warning, and supporting emergency response measures.     

人工湿地的氮稳定同位素特征及污染源解析

对2016年4,6,和8月合肥市塘西河人工湿地水体中的溶解态硝酸盐进行稳定氮同位素分析。通过不同的季节人工湿地内硝酸盐的稳定氮同位素值(δ~(15)N-NO_3~-)的变化情况来研究水体中氮的迁移、转变等生物地球化学过程,从而揭示其环境行为,同时对该人工湿地氮的循环机制进行探究。研究发现:该人工湿地的δ~(15)N-NO_3~-值分布在13.9‰~22.7‰,表明其硝酸盐氮的主要来源是人畜排泄物或城市生活污水。4,6,8月水体中的δ~(15)N-NO_3~-值都受硝化、矿化、植物同化作用的影响;6月水体中的δ~(15)N-NO_3~-值还受藻类同化吸收作用的影响;8月水体中的δ~(15)N-NO_3~-值还受雨水混合、藻类同化吸收与反硝化作用的影响。     

Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook

Observations and numerical models are mainly used to investigate the spatiotemporal distribution and vertical structure characteristics of aerosols to understand aerosol pollution and its effects. However, the limitations of observations and the uncertainties of numerical models bias aerosol calculations and predictions. Data assimilation combines observations and numerical models to improve the accuracy of the initial, analytical fields of models and promote the development of atmospheric aerosol pollution research. Numerous studies have been conducted to integrate multi-source data, such as aerosol optical depth and aerosol extinction coefficient profile, into various chemical transport models using various data assimilation algorithms and have achieved good assimilation results. The definition of data assimilation and the main algorithms will be briefly presented, and the progress of aerosol assimilation according to two types of aerosol data, namely, aerosol optical depth and extinction coefficient, will be presented. The application of vertical aerosol data assimilation, as well as the future trends and challenges of aerosol data assimilation, will be further analysed.     

A Technicoeconomic Approach for theSelection of a Site Remediation Strategy—Part B: Model Application

Different tools, such as a screening matrix or decision framework, are available to select a remediation technology to treat a contaminated site. However, unless these methods can point out the appropriate technology in regards to the decision-maker's knowledge about the contaminated site, they are less useful to evaluate both the technical effectiveness and the cost of the remediation, and to assess different remediation strategies from either future data acquisition or the use of an irreversible remediation technology. A model developed to allow such evaluations has been used to simulate the remediation of a virtual contaminated site. From this, four remediation recommendations have been made. These recommendations are guidelines for the build up of a remediation strategy that would both maximize the effectiveness of the decontamination and minimize its total cost.     

基于DEA模型的城市用地经济效益比较研究

运用数据包络分析方法（DEA），从城市土地的投入和产出角度，对全国30个省会城市的城市用地经济效益进行比较研究。研究结果表明：（1）在全国30个城市（包括直辖市和部分省会城市），仅上海、杭州、广州和昆明等4个城市为DEA有效城市，即在现有的经济、社会、技术条件下，投入产出达到最佳状态，其余26个城市为非DEA有效城市；（2）南京和哈尔滨处于规模效益递减的发展阶段，上海、杭州、广州和昆明处于规模效益不变的发展阶段，其余24个城市都处于规模效益递增的发展阶段；（3）30个省会城市的城市土地利用经济效益发展极不平衡，呈现东高西低的格局，且城市土地利用普遍不集约；最后对如何提高城市用地经济效益提出了相应的改进措施。     

Integrating high resolution soil data into federal crop insurance policy: Implications for policy and conservation

Well-designed and executed policies are critical for aligning sustainability incentives and enabling future agricultural productivity growth. In the U.S., government-administered crop insurance is the primary direct mechanism through which agriculture is subsidized and represents over $100 billion in liabilities annually. Despite the importance of soil properties in determining crop yield formation and risk, the Government does not consider any soil information in generating premium rates under the Federal Crop Insurance Program. The purpose of this study is to investigate the potential of integrating high-resolution soil data into modeling of field-level insurance rates in large-scale applications. Here, using the actual distribution of soil quality across crop fields in a high production region, models are developed to incorporate soil data into insurance rates and then evaluated to investigate the magnitude of risk differentials across different soil qualities. These soil-conditioned results were then compared to rates that would have been generated by the Government’s current soil-naïve methodology. This study indicates that the degree to which soils vary within a county is highly significant, leading to rating errors of 200% or greater. Implications of ignoring soil information and operational considerations of modifying this cornerstone program are discussed.     

基于GIS的交通事故信息空间数据库研究

笔者分析了建立基于GIS的交通事故信息空间数据库的紧迫性;探讨了完备的交通事故信息数据库的内容构成,认为应包括空间数据库、影响因素数据库以及元数据和数据字典库三大部分;研讨了交通事故空间数据库的重要应用价值,进而采用GIS的分层组织思想对交通事故信息空间数据库中的数据进行组织;详细设计了各个数据表以及数据表间的关系,建立了包含交通事故对象、人、车、路以及环境等要素的交通事故空间数据库,为交通事故研究提供完备的数据支持。     

基于Web of Science的1900～2012年长江研究文献计量分析

为了揭示有关长江研究的热点与发展动态,以Web of Science数据库为资料来源,利用文献计量学方法及TDA软件,对1900~2012年长江研究文献的发文量、国家、机构、作者、期刊、学科、关键词进行数据统计与分析。结果表明:(1)长江研究大致分为3个阶段:初步发展时期;探索时期;快速发展时期;(2)中国发表的关于长江研究的论文最多,国外主要国家及机构来自美国、日本、澳大利亚;(3)中国科学院是国内长江研究的主要机构;(4)国内外十分关注地质学、环境科学、水资源和气象学的研究。