Emissions trading systems with cap adjustments

Emissions Trading Systems (ETSs) with fixed caps lack provisions to address systematic imbalances in the supply and demand of permits due to changes in the state of the regulated economy. We propose a mechanism which adjusts the allocation of permits based on the current bank of permits. The mechanism spans the spectrum between a pure quantity instrument and a pure price instrument. We solve the firms׳ emissions control problem and obtain an explicit dependency between the key policy stringency parameter—the adjustment rate—and the firms׳ abatement and trading strategies. We present an analytical tool for selecting the optimal adjustment rate under both risk-neutrality and risk-aversion, which provides an analytical basis for the regulator׳s choice of a responsive ETS policy.     

A dynamic approach for evaluating the consequences of toxic gas dispersion in the chemical plants using CFD and evacuation modelling

Accidental releases of toxic gas in the chemical plants have caused significant harm to the exposed occupants. To evaluate the consequences of these accidents, a dynamic approach considering the gas dispersion and behavior evacuation modelling has been proposed in this paper. This approach is applied to a hypothetical scenario including an accidental chlorine release in a chemical plant. CFD technique is utilized to calculate the time-varying concentration filed and evacuation modelling is used to obtain the evacuation routes. The exposure concentrations in the evacuation routes are calculated by using the code of data query. The integrated concentration toxic load model and probit model are used to calculate the probability of mortality of each occupant by using the exposure concentrations. Based on this dynamic approach, a new concept of average probability of mortality (APM) has been proposed to quantify the consequences of different accidental scenarios. The results show that APM decreases when the required detection time decreases or emergency evacuation mode is implemented. The impact of the detection time on APM becomes small as the wind speed increases. The effect of emergency evacuation mode is more obvious when the release occurs in an outdoor space.     

Risk assessment of chemical process considering dynamic probability of near misses based on Bayesian theory and event tree analysis

With the development of modern automatic control systems, chemical accidents are of low frequency in most chemical plants, but once an accident happens, it often causes serious consequences. Near-misses are the precursor of accidents. As the process progresses, near misses caused by abnormal fluctuation of process variables may eventually lead to accidents. However, variables that may lead to serious consequences in the production process cannot update the risk in the life cycle of the process by traditional risk assessment methods, which do not pay enough attention to the near misses. Therefore, this paper proposed a new method based on Bayesian theory to dynamically update the probability of key variables associated with process failure risk and obtain the risk change of the near-misses. This article outlines the proposed approach and uses a chemical process of styrene production to demonstrate the application. In this chemical process, the key variables include flow rate, liquid level, pressure and temperature. In order to study the dynamic risk of the chemical process with consideration of near misses, according to the accumulated data of process variables, firstly the abnormal probability of the variables and the failure rate of safety systems associated with the variables were updated with time based on Bayesian theory. On the basis of the dynamic probability of key process variables, an event tree of possible consequences caused by variable anomalies was established. From the logical relationship of the event tree, the probability of different consequences can be obtained. The results show that the proposed risk assessment method based on Bayesian theory can overcome the shortcomings of traditional analysis methods. It shows the dynamic characteristics of the probability of different near misses, and achieves the dynamic risk analysis of chemical process accidents.     

Assessing the demand of solid waste disposal in urban region by urban dynamics modelling in a GIS environment

The twentieth century saw a dramatic increase in the production of urban solid waste, reflecting unprecedented global levels of economic activity. Despite some efforts to reduce and recover the waste, disposal in landfills is still the most usual destination. However, landfill has become more difficult to implement because of its increasing cost, community opposition to landfill siting, and more restrictive environmental regulations regarding the siting and operation of landfills. Moreover, disposal in landfill is the waste destination method with the largest demand for land, while land is a resource whose availability has been decreasing in urban systems. Shortage of land for landfills is a problem frequently cited in the literature as a physical constraint. Nonetheless, the shortage of land for waste disposal has not been fully studied and, in particular, quantified. This paper presents a method to quantify the relationship between the demand and supply of suitable land for waste disposal over time using a geographic information system and modelling techniques. Based on projections of population growth, urban sprawl and waste generation the method can allow policy and decision-makers to measure the dimension of the problem of shortage of land into the future. The procedure can provide information to guide the design and schedule of programs to reduce and recover waste, and can potentially lead to a better use of the land resource. Porto Alegre City, Brazil was used as the case study to illustrate and analyse the approach. By testing different waste management scenarios, the results indicated that the demand for land for waste disposal overcomes the supply of suitable land for this use in the study area before the year 2050.     

A model of the air traffic controller's picture

This paper reviews the development of a model of the air traffic controller's mental image, ‘picture’, or situation awareness, used for controlling air traffic. The computerised model's development, origins and theoretical basis are outlined, and the model is described in some detail in the context of current air traffic operations. The model can be utilised to explore the potential impacts of future automation on the cognitive performance of the air traffic controller. The general potential contributions of the area of cognitive modelling to system design and training in accelerating industries such as air traffic control, are also discussed.     

Dynamic failure probability analysis of urban gas pipeline network

The gas pipeline network is an essential infrastructure for a smart city. It provides a much-needed energy source; however, it poses a significant risk to the community. Effective risk management assists in maintaining the operational safety of the network. The risk management of the network requires reliable dynamic failure probability analysis. This paper proposes a methodology of condition monitoring and dynamic failure probability analysis of urban gas pipeline network. The methodology begins with identifying key design and operational factors responsible for pipeline failure. Subsequently, a causation-based failure model is developed as the Bowtie model. The Bowtie model is transformed into a Bayesian network, which is analyzed using operational data. The key contributory factors of accident causation are monitored. The monitored data is used to analyze the updated failure probability of the network. The gas pipeline network's dynamic failure probability is combined with the potential consequences to assess the risk. The application of the approach is demonstrated in a section of the urban gas pipeline.     

动态转盘过滤器去除城市生活污水中的SS及有机污染物COD的研究

本文主要对动态转盘过滤器对城市污水中SS及有机污染物COD的去除率进行了研究。     

Finite element modeling of microstructural changes in dry and cryogenic machining of AZ31B magnesium alloy

Unsatisfactory corrosion resistance is one of the major disadvantages of magnesium alloys that impede their wide application. Microstructural changes, especially grain sizes, of Mg alloys have significant influence on their corrosion resistance. Cryogenic machining was reported to effectively induce grain refinement on Mg alloys and has a potential to improve their corrosion resistance. It is important to model these changes so that proper machining conditions can be found to enhance the corrosion rate of Mg alloys. In this paper, a preliminary study was conducted to model the microstructural changes of AZ31B Mg alloy during dry and cryogenic machining using the finite element (FE) method and a user subroutine based on the dynamic recrystallization (DRX) mechanism of Mg alloys. Good agreement in terms of grain size and affected layer thickness was found between experimental and predicted results. A numerical study was conducted using this model to investigate the influence of rake angle on microstructural changes after cryogenic machining.     

Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France)

We examined changes in morphological and genomic diversities of viruses by means of transmission electronic microscopy and pulsed field gel electrophoresis(PFGE) over a nine-month period(April–December 2005) at four different depths in the oligomesotrophic Lac Pavin. We found that the majority of viruses in this lake belonged to the family of Siphoviridae or were untailed, with capsid sizes ranging from 30 to 60 nm, and exhibited genome sizes ranging from 15 to 45 kb. On average, 12 different genotypes dominated each of the PFGE fingerprints. The highest genomic viral richness was recorded in summer(mean = 14 bands per PFGE fingerprint) and in the epilimnion(mean = 13 bands per PFGE fingerprint). Among the physico-chemical and biological variables considered, the availability of the hosts appeared to be the main factor regulating the variations in the viral diversity.     

Dynamic material flow analysis of steel resources in Korea

Material flow analysis (MFA) is an evaluation technique that systematically identifies the flows and stocks of materials within predefined spatial and temporal boundaries. In this paper, the steel resources in Korea are investigated using dynamic MFA. Iron ore and steel scrap are added as raw material components during the production processes of steel, which is then used in a variety of product groups such as construction products, transportation equipment, machinery/metal products, electrical/electronic devices, and other products through fabrication and manufacturing processes. When such product groups are discarded, they are either recycled or landfilled. With consideration for the lifetimes of various product groups in conjunction with steel resource flows in Korea, dynamic MFA is conducted on the flows of steel stock change and annual scrap generation. By 2020, these two flows are expected to increase by as much as 40% and 30%, respectively, compared to 2008, with transportation equipment, in particular, envisaged to experience high growth. At the current recycling rate, however, it will be hard to meet future scrap demand. According to the scenario analysis, 100% of this future scrap demand can be supplied domestically if the recycling rate is increased to over 70% for all product groups, except construction products and transportation equipment, which already have high recycling rates. By 2020, the reduction in scrap importation costs is projected to offer a financial gain of 2.3 billion dollars.