城乡建设用地增减挂钩节余指标跨县域交易定价研究

挂钩节余指标交易符合促进土地要素市场化配置和城乡统筹协调发展的基本要求,探索挂钩节余指标跨县域交易是诱致性的制度创新。作为市场化交易机制的前提和关键,节余指标价格的合理确定意义重大。基于地租地价理论、土地发展权转让理论和相关政策法规,厘清了节余指标价格的形成机理,结合指标的生产和使用两个阶段,分别从成本和收益两个角度尝试选用成本法和剩余法理论构建节余指标价格测算模型。利用德州市和即墨市相关数据进行实证测算,确定买卖双方的交易保留价,以期为节余指标定价、跨县域流转制度建立与健康运行提供理论依据和现实指导。     

基于双系统理论的消费者价格判断决策模型

参考价格理论是构建价格判断模型的传统理论,其价格判断模型是一种典型的推理性模型.根据双系统理论,人们的决策应是推理性和直觉性两类过程的交互作用,心理账户理论正是描述直觉性决策的基本理论之一.构建了基于参考价格与心理账户的双系统价格判断决策模型,对不同心理账户数据进行分析发现,被试者的目标价格决策过程具有显著差异.     

试论企业环境业绩与财务业绩指标的结合

用环境业绩和财务业绩指标结合后的环境业绩指标,可以预测环境问题和对未来财务业绩的影响,帮助投资者做出更好的投资决策。     

不确定条件下矿产资源的最优开采

通过一个连续时间的随机动态规划模型,探讨了市场需求、资源存量的不确定性以及勘探活动对矿产资源价格和开采速度的影响,并给出了随机条件下Hotelling法则的表达形式.模型结果显示:不确定性对资源价格变化速度的影响主要取决于开采成本,如果相对于资源存量来说开采成本是不变的或者开采的规模成本是不变的,则不确定性对资源价格的变化速度没有影响.反之,如果开采的规模成本是递增的,则不确定性会加速资源价格的变化.此外,不确定性的存在将加快资源的开采速度.至于勘探活动,它一方面降低了地质条件的不确定性,另一方面增加了资源的存量,所以勘探活动降低了资源价格和开采速度的变化率,减少了不确定性对资源开采的影响.     

地价模型在农用地基准地价评估中的应用--以宿州市土甬桥区为例

以土甬桥区农用地为研究对象,基于农用地分等定级成果,建立不同的地价模型并进行统计检验,得到农用地综合质量和农用地价格之间的最佳关系模型,揭示农用地的综合质量和农用地价格的统计规律.研究认为,在市场交易案例很少的情况下,建立地价模型进行基准地价的评估是科学的,在此基础上对农用地基准地价进行评估和实证分析.     

武汉东湖风景区对周边住宅价格影响的研究

城市开放空间对城市住宅环境质量具有明显改善作用并进而影响房价已成共识,但就定量分析开放空间对住宅价值的距离梯度影响仍较薄弱.运用特征价格模型和GIS,针对武汉东湖风景区对周边住宅价格的影响进行量化分析表明,东湖对周边住宅价格有显著正向影响,离东湖距离每减少100m,住宅价格的单价将增加5.8％.该结论可为房产税政策制定和城市基准地价体系建立以及城市规划、环境保护提供科学依据,以促进城市的有序发展.     

国际棉花现货价格波动及短期预测研究

随着棉花市场化改革的不断深入,我国棉花市场与国际棉花市场的联系日益紧密,同时我国棉花现货价格受国际棉花现货价格的影响不断加深。以2004/2005—2015/2016年国际棉花现货价格(Cotlook FE-A)月度数据为依据,理论分析了国际棉花现货价格的波动情况。基于ARIMA模型实证预测了短期内国际棉花现货价格的波动趋势,模型相对误差在5%以下,预测值精度较高。模型预测结果显示,短期内国际棉花现货价格呈缓慢上涨趋势,2017年5月将上升到12812.02元/t,比2016年12月增加了688.83元/t。基于国际棉花现货价格的波动趋势,提出防范国际棉花价格波动冲击和保障中国棉花产业可持续发展的对策建议。     

煤用脱硫助燃剂在燃煤锅炉中的应用与探讨

对不同吨位燃煤锅炉在添加和不添加煤用脱硫助燃剂的情况下,对大气环境指标和锅炉热工等项指标进行综合测试,其结果表明脱硫助燃剂能有效降低污染,改善大气环境质量,对提高燃煤热值及锅炉综合使用效果有益。     

遗址旅游影响因素实证研究——以河南商丘古城为例

综述了国内外遗址旅游的影响因素.结合案例地旅游发展现状,归纳了遗址旅游的影响因素,构建了遗址旅游影响因素模型,结果验证了模型假设,影响因素各维度对遗址旅游的贡献大小依次是:内部设施、人文环境、遗址资源、游客需求和价格因素.在此基础上,对案例地未来的旅游发展提出了对策.     

碳达峰、碳中和目标下我国污泥耦合发电产业发展战略的破局研究——基于中电环保股份有限公司的案例分析

基于SCP产业组织理论和资源价值流理论的经济效益、环境效益模型分析可知,利用电厂余热干化污泥与电厂燃煤耦合发电是一种高效的可再生能源利用方式,能带来余热再利用、污泥热值节煤、粉煤灰综合利用等经济效益,污泥与燃煤掺烧可从源头减少CO2排放,实现烟气超低排放、废水循环利用等,并可全面消纳城市污泥。由此,污泥耦合发电产业可实现经济效益、社会效益和环境效益的统一。     

基于DEA技术的污水处理定价模型

应用DEA方法评价污水处理厂相对效率，并将评价结果用于污水处理定价，得到了基于DEA方法的污水处理定价模型。该模型克服了现有定价模型的不足，体现了政府对污水处理厂生产效率的要求，能够促使企业提高效率并降低成本。     

Developing of a pricing model for Turkish lignite used in thermal plants

The objective of this paper is to develop a general pricing model for Turkish Lignite, which is mainly sold to thermal plants. This model will contribute to the development of coal mining within the scope of privatization efforts of the Turkish energy market. The paper consists of two stages. First, data of 10 thermal plants have been evaluated by using hedonic pricing analysis to determine influential price parameters. The results of hedonic regression analysis indicate the effect and importance of calorific value and electricity price on lignite prices. Second, a general coal-pricing model has been developed by taking into account the results of hedonic analysis. Comparison of the coal prices estimated by the developed pricing model and the coal prices obtained from thermal plants indicates an acceptable relation.     

An economic and environmental assessment of carbon capture and storage (CCS) power plants: a case study for the City of Kiel

In the not too distant future several power plants throughout Europe will have to be replaced and the decision has to be made whether to build coal-fired power plants with carbon capture and storage (CCS). In a study for the city of Kiel in northern Germany only an 800 MW coal power plant reaches a required minimum for rentability. This study looks at an additional economic and environmental evaluation of a coal plant with CCS. We find that in two out of three carbon and energy price scenarios integrated gasification combined cycle (IGCC) plants with CCS have the greatest rentability. Pulverised coal (PC) plants with CCS can only compete with other options under very favourable assumptions. Life-cycle emissions from CCS are less than 70% of a coal plant – compared with at least more than 80% when only considering direct emissions from plants. However, life-cycle emissions are lower than in any other assessed option.     

International coal prices

The place coal will occupy among the world's energy supplies depends on many factors, including its price trends. This paper reviews recent price trends and supports the thesis that future coal prices are independent of oil prices, and that they will fluctuate between two limits which are based on production and transport costs in the USA and Australia.     

Optimal planning of co-firing alternative fuels with coal in a power plant by grey nonlinear mixed integer programming model

Energy supply and use is of fundamental importance to society. Although the interactions between energy and environment were originally local in character, they have now widened to cover regional and global issues, such as acid rain and the greenhouse effect. It is for this reason that there is a need for covering the direct and indirect economic and environmental impacts of energy acquisition, transport, production and use. In this paper, particular attention is directed to ways of resolving conflict between economic and environmental goals by encouraging a power plant to consider co-firing biomass and refuse-derived fuel (RDF) with coal simultaneously. It aims at reducing the emission level of sulfur dioxide (SO(2)) in an uncertain environment, using the power plant in Michigan City, Indiana as an example. To assess the uncertainty by a comparative way both deterministic and grey nonlinear mixed integer programming (MIP) models were developed to minimize the net operating cost with respect to possible fuel combinations. It aims at generating the optimal portfolio of alternative fuels while maintaining the same electricity generation simultaneously. To ease the solution procedure stepwise relaxation algorithm was developed for solving the grey nonlinear MIP model. Breakeven alternative fuel value can be identified in the post-optimization stage for decision-making. Research findings show that the inclusion of RDF does not exhibit comparative advantage in terms of the net cost, albeit relatively lower air pollution impact. Yet it can be sustained by a charge system, subsidy program, or emission credit as the price of coal increases over time.     

The impact of commodity price risk management on the profits of a company

It is well recognized that for the producing companies hedging the commodity price using financial products like forwards or futures has become an important part of the company's production process. But apart from the direct impacts of hedging on the production and hedging costs the use of financial products affects the financing of the company: hedging the volatile commodity prices leads to a reduction of the risk premium the company has to pay for its debt capital, since hedging contributes to more confidence of the investors in the redemption of the debt. In this paper we therefore analyze this dependency of hedging and financing and derive optimal hedging extents for companies in different market situations based on a long-term model. By hedging the commodity price, companies can realize a surplus in profits. Thereby, the optimal hedging extent for a monopolist is often up to 100%, whereas for companies in a polypolistic market the optimum is always less than 100%. These results are illustrated by examples for a producing company.     

Assessing the value of CO2 capture ready in new-build pulverised coal-fired power plants in China

Making new plants CO₂ capture ready (CCR) would enable them to retrofit to capture CO₂ at a later date at lower cost when the appropriate policy and/or economic drivers are in place. In order to understand the economic value and investment characteristics of making new plants CCR in China, a typical 600 MW pulverised coal-fired ultra-supercritical power plant, locating in Guangdong province, was examined. Combined with an engineering assessment, costs were estimated for different CCR scenarios. To analyze CCR investment opportunities, the paper applies a cash flow model for valuing capture options and CCR investment. Results were obtained by Monte-Carlo simulation, based on engineering surveys and an IEA GHG CCR study, as well as plant performance information and expert projections on carbon prices, coal prices and electricity prices.CCR investments are justified by factors such as higher retrofitting probabilities, lower early closure probabilities and fair economic return. However, the economic case for CCR largely depends on two factors: (a) whether the original plant is retrofittable without CCR; and (b) the type of investments made, for example, investments essential to CCR tend to be more economic than additional non-essential CCR features such as clutched low pressure turbines. The carbon price and discount rate were found to have significant impacts on the economics of CCR. Overall, it appears that the value of the ‘capture options’ that CCR generates for retrofitting CCS is significant, and so could justify a modest CCR investment, even assuming the original plant is retrofittable without CCR. It was also found the value of CCR might be significantly understated if the range of potential retrofitting dates is artificially constrained.     

An empirical analysis of productivity: Welsh coal industry

A non-homogeneous variable-elasticity-of-substitution production function is estimated using data for the Welsh coal industry. From 1961 to 1976 output declined, returns to scale increased and the elasticity of substitution fell. At the end of the period, the elasticity of substitution between capital and labour in the coal industry is still large and there may be room for greater employment in the industry at a time of high and rising unemployment, subject to other overall considerations. While marginal productivity of labour in physical terms has been stagnant, price rises in the industry in recent years have been in excess of what was needed to finance wage settlements. Perhaps price rises granted to the coal industry by the UK government were justified, but they require closer scrutiny.     

MODELING WATER UTILITY FINANCIAL PERFORMANCE1

ABSTRACT: The purpose of this paper is to present a theory and model for assessing the financial health of public water systems. Using financial information from 25 water utilities in Georgia, the paper seeks to identify the causal relationships between the financial performance of a water utility and its fiscal position. The need for a theoretical understanding of water utility financial health is the result of the increasingly stringent performance requirements under the Safe Drinking Water Act (SDWA). The issue has become particularly important for small water systems that will be exposed to significant financial demands. A set of financial ratios were developed and tested in a model that was based on liquid asset theory. The model contained five variables designed to account for the size of liquid assets, current debt, cash-flow, and the level of expenses. The variables fit the need of water utilities: to provide an adequate level of operation and maintenance to meet current and future system needs as well as SDWA standards.     

Use of artificial neural network black-box modeling for the prediction of wastewater treatment plants performance

A reliable model for any wastewater treatment plant is essential in order to provide a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. This process is complex and attains a high degree of nonlinearity due to the presence of bio-organic constituents that are difficult to model using mechanistic approaches. Predicting the plant operational parameters using conventional experimental techniques is also a time consuming step and is an obstacle in the way of efficient control of such processes. In this work, an artificial neural network (ANN) black-box modeling approach was used to acquire the knowledge base of a real wastewater plant and then used as a process model. The study signifies that the ANNs are capable of capturing the plant operation characteristics with a good degree of accuracy. A computer model is developed that incorporates the trained ANN plant model. The developed program is implemented and validated using plant-scale data obtained from a local wastewater treatment plant, namely the Doha West wastewater treatment plant (WWTP). It is used as a valuable performance assessment tool for plant operators and decision makers. The ANN model provided accurate predictions of the effluent stream, in terms of biological oxygen demand (BOD), chemical oxygen demand (COD) and total suspended solids (TSS) when using COD as an input in the crude supply stream. It can be said that the ANN predictions based on three crude supply inputs together, namely BOD, COD and TSS, resulted in better ANN predictions when using only one crude supply input. Graphical user interface representation of the ANN for the Doha West WWTP data is performed and presented.