Targeting for optimal grid-wide deployment of carbon capture and storage (CCS) technology

Carbon capture and storage (CCS) techniques are considered as one of the promising approaches to reduce carbon dioxide (CO₂) emissions from fossil fuel based power generation, which still accounts for a significant portion of greenhouse gas emissions in the world. CCS technology can be used to mitigate greenhouse gas emissions, with the additional advantage that it allows continuing use reliable and inexpensive fossil fuels. However, CCS retrofit entails major capital costs as well as a reduction of overall thermal efficiency and power output. Thus, it is essential for planning purposes to implement the minimal extent of CCS retrofit while meeting the specified carbon emission limits for the power sector. At the same time, it is necessary to plan for compensatory power generation capacity to offset energy losses resulting from CCS retrofit. In this paper, an algebraic targeting technique is presented for planning of grid-wide CCS retrofits in the power generation sector with compensatory power. The targeting technique is developed based on pinch analysis. In addition, the proposed methodologies are illustrated through case studies based on grid data in India and the Philippines. Sensitivity analysis is carried out to determine the suitable CCS technology and compensatory power source which satisfy emission limits.     

Optimizing the design of storage facilities through the application of ISD and QRA

Four strategies can be used to achieve safety in chemical processes: inherent, passive, active and procedural. However, the strategy that offers the best results is the inherent safety approach, especially if it is applied during the initial stages of a project. Inherently Safer Design (ISD) permanently eliminates or reduces hazards, and thus avoids or diminishes the consequences of incidents. ISD can be applied using four strategies: substitution, minimization, moderation and simplification. In this paper, we propose a methodology that combines ISD strategies with Quantitative Risk Assessment (QRA) to optimize the design of storage installations. As 17% of major accidents in the chemical industry occur during the storage process and cause significant losses, it is essential to improve safety in such installations. The proposed method applies QRA to estimate the risk associated with a specific design. The design can then be compared to others to determine which is inherently safer. The risk analysis may incorporate complex phenomena such as the domino effect and possible impacts on vulnerable material and human elements. The methodology was applied to the San Juanico tragedy that occurred in Mexico in 1984.     

Major accident management in the process industry: An expert tool called CESMA for intelligent allocation of prevention investments

A tool (called CESMA) was developed to carry out cost–benefit analyses and cost-effectiveness analyses of prevention investments for avoiding major accidents. A wide variety of parameters necessary to calculate both the costs of the considered preventive measures and the benefits related with the avoidance of accidents were identified in the research. The benefits are determined by estimating the difference in (hypothetical) major accident costs without and with the implementation of a preventive measure. As many relevant costs and benefits as possible were included into the tool, based on literature and expert opinion, in order to be able to deliver an all-embracing cost–benefit analysis and cost-effectiveness analysis to assist in the investment decision process. Because major accidents are related to extremely low frequencies, the tool takes the uncertainty of the unwanted occurrence of a major accident into account through the usage of a so-called ‘disproportion factor’. Compared with existing software, the CESMA tool is innovative by striving for an as-accurate-as-possible picture of costs and benefits of major accident prevention, and taking the uncertainties accompanying disastrous events into consideration. Furthermore, an illustrative example of CESMA is presented in the paper.     

Simulation-based fault propagation analysis—Application on hydrogen production plant

Recently production of hydrogen from water through the Cu–Cl thermochemical cycle is developed as a new technology. The main advantages of this technology over existing ones are higher efficiency, lower costs, lower environmental impact and reduced greenhouse gas emissions. Considering these advantages, the usage of this technology in new industries such as nuclear and oil is increasingly developed. Due to hazards involved in hydrogen production, design and implementation of hydrogen plants require provisions for safety, reliability and risk assessment. However, very little research is done from safety point of view. This paper introduces fault semantic network (FSN) as a novel method for fault diagnosis and fault propagation analysis by using evolutionary techniques like genetic programming (GP) and neural networks (NN), to uncover process variables’ interactions. The effectiveness, feasibility and robustness of the proposed method are demonstrated on simulated data obtained from the simulation of hydrogen production process in Aspen HYSYS^®. The proposed method has successfully achieved reasonable detection and prediction of non-linear interaction patterns among process variables.     

A mathematical approach for retrofit and optimization of total site steam distribution networks

This paper presents a generic mathematical model for retrofitting the steam power plants in an industrial site. The industrial sector under review consists of one steel mill, one oil refinery, and several petrochemical plants, where only small-scale steam integration has been implemented before this study. The relevant unit models in a typical steam power plant are established, and the steam plant retrofit problem is formulated as a mixed-integer nonlinear program (MINLP). Feasible retrofit alternatives suggested by experienced field engineers are investigated in sequence to examine the revenue of those possible modifications. The first scenario examines operational optimization of existent plants; the second option allows installation of one new turbine and replacement of several boilers and turbines with lower efficiency; the third scenario considers using a steam ejector to upgrade the disqualified import steam in the oil refinery. The significant merits from these three retrofit alternatives show that the proposed MINLP formulation has been a great help to enhance the inter-plant steam integration in an industrial sector.     

矿山环境质量评价指标体系及层次分析法评价

根据矿山环境评价指标体系设计的原则,利用模糊数学理论的分级别的隶属度量化对初选的指标体系进行优化,形成矿山环境质量评价指标体系．在此基础上运用层次分析法对指标权值进行确定,建立矿山环境质量评价体系模型,此模型为矿山环境的评价与治理提供决策支持服务。     

Principal sustainability components: empirical analysis of synergies between the three pillars of sustainability

Starting from the concept of three fundamental sustainability dimensions (environmental, social, and economic), this study investigated professional contributions to sustainability by means of principal component analysis (PCA). Graduates from the Environmental Sciences program (N?=?542) at ETH Zurich described their best professional contributions to sustainable development. Next, they evaluated whether their best practice example contributed to achieving any of the five environmental, social, and economic objectives of the Swiss national sustainability strategy. These judgments served as the basis for a PCA aiming to identify principal sustainability components (PSCs) covering typical synergies between sustainability objectives within and transcending the three fundamental dimensions. Three PSCs capturing important synergies were identified. PSC 1 Product and Process Development reflects how ecological innovation and modernization can generate social and economic benefits and at the same time facilitate the reduction in use of as well as the responsible use of natural resources. PSC 2 Education and Social Economics reflects how educational activities and sociocultural sustainability initiatives can simultaneously promote income and employment, social and human capital, and free personal development. PSC 3 Protection of Nature and Humans covers the synergetic benefits which protection of natural spaces and biodiversity and the reduction of environmental risks have for the protection of health and safety of the population. The study also revealed that integration of environmental, social, and economic aspects is often connected to conflicts between these dimensions. However, contributions which consider the economic situation of future generations or enhance social and human capital achieved considerable integration but showed no inclination toward such conflicts.     

城市污水厂活性污泥胞外聚合物的三维荧光特性分析

对厦门5个城市污水处理厂活性污泥溶解性有机物SMP,松散型胞外聚合物LB-EPS和紧密结合型胞外聚合物TB-EPS的三维荧光光谱分析表明,SMP,LB-EPS和TB-EPS都有3个明显的特征峰,其中Peak A(Ex/Em=225~230/335~350nm)和Peak B (Ex/Em= 275~280/330~350nm)都为类蛋白荧光物质,Peak C(Ex/Em=320~350/420~445nm)为腐殖酸类荧光物质.LB-EPS和TB-EPS荧光峰强度同其对应的TOC浓度有一定相关性.荧光强度综合指数FRI分析表明,微生物副产物更多的存在于TB-EPS中,其FRI总和同TOC浓度呈一定相关性.     

Techno-Economic Study of CO2 Capture from an Existing Cement Plant Using MEA Scrubbing

Carbon dioxide is the major greenhouse gas responsible for global warming. Man-made CO₂ emissions contribute approximately 63% of greenhouse gases and the cement industry is responsible for approximately 5% of CO₂ emissions emitting nearly 900 kg of CO₂ per 1000 kg of cement. CO₂ from a cement plant was captured and purified to 98% using the monoethanolamine (MEA) based absorption process. The capture cost was $51 per tonne of CO₂ captured, representing approximately 90% of total cost. Steam was the main operating cost representing 39% of the total capture cost. Switching from coal to natural gas reduces CO₂ emissions by about 18%. At normal load, about 36 MW of waste heat is available for recovery to satisfy the parasitic heat requirements of MEA process; however, it is very difficult to recover.     

基于多因子指数集成的流域面源污染风险研究

为掌握流域面源污染风险的整体趋势,基于风险评价时,单个因子对系统某种风险的贡献率可能大于1且因子对系统风险贡献呈一定结构性的问题,定义了风险标准值的概念和算法,建立了系统风险多因子集成评价方法,并在地理信息系统支持下对泸沽湖流域进行了案例研究.结果表明,泸沽湖流域面源污染流失风险处于较高的水平;系统风险多因子集成评价法在对多个同类系统间进行比较时,具有较大的优势;该方法可以与其他多种方法相结合对系统属性进行全面综合评价.