Cracking the Achilles’ heel of energy performance contracting projects: the credit risk identification method for clients

ABSTRACT

A credit risk identification model is established to examine the credit status of Energy performance contracting (EPC) project clients (i.e., energy-using companies) in China based on rough set theory. The model is verified with data from 120 listed companies at different times. Study shows that lack of credit is one of the main obstacles to the implementation of EPC projects, and information asymmetry is the main reason for this lack of credit among potential clients in China. The credit risk identification method based on rough set theory can make up for the shortcomings of existing EPC projects in terms of credit risk identification, including redundant information and indicators, and unclear decision rules. Credit risk identification indicators of clients are dynamic. The research results can help energy service companies (ESCOs) determine the credit status of clients, facilitate cooperation between ESCOs and clients, and help explain the various dynamics of clients’ credit risk identification indicators over time.     

中国清洁生产的立法问题

清洁生产的立法需要突出针对性和循序渐进的原则。根据工艺技术的先进性和行业发展状况的不同，其法律规范分为四亿层次：禁止性规范，提倡性规范，鼓励性规范和强制性规范。灵活性和可操作性是清洁生产立法的特点。     

Statistical regression modeling for energy consumption in wastewater treatment

Wastewater treatment is one of critical issues faced by water utilities, and receives more and more attentions recently. The energy consumption modeling in biochemical wastewater treatment was investigated in the study via a general and robust approach based on Bayesian semi-parametric quantile regression. The dataset was derived from a municipal wastewater treatment plant, where the energy consumption of unit chemical oxygen demand (COD) reduction was the response variable of interest. Via the proposed approach, the comprehensive regression pictures of the energy consumption and truly influencing factors, i.e., the regression relationships at lower, median and higher energy consumption levels were characterized respectively. Meanwhile, the proposals for energy saving in different cases were also facilitated specifically. First, the lower level of energy consumption was closely associated with the temperature of influent wastewater, and the chroma-rich wastewater also showed helpful in the execution of energy saving. Second, at median energy consumption level, the COD-rich wastewater played a determinative role in the reduction of energy consumption, while the higher quality of treated water led to slightly energy intensive. Third, the higher level of energy consumption was most likely to be attributed to the relatively high temperature of wastewater and total nitrogen (TN)-rich wastewater, and both of the factors were preferably to be avoided to alleviate the burden of energy consumption. The study provided an efficient approach to controlling the energy consumption of wastewater treatment in the perspective of statistical regression modeling, and offered valuable suggestions for the future energy saving.     

浅谈清洁生产在山东焦化行业中的应用

阐述了在焦化行业开展清洁生产的必要性,结合焦化企业开展清洁生产的实例,从废物最小化和资源化等方面概述了清洁生产技术在焦化行业中的应用;并以山东焦化企业为例论述如何做好清洁生产工作。     

东北地区畜禽养殖业污染物总量减排对策分析

论述了东北地区畜禽养殖业的污染现状,针对东北地区畜禽养殖业污染物总量减排的需要,从政策引导、清洁生产和全过程控污等方面提出了相应的污染物总量减排对策,并推荐合理可行和适合当地实际情况的畜禽养殖废物综合处理与资源化利用技术,为环保和农业部门的畜禽养殖业污染物总量减排工作提供一定参考。     

清洁生产与企业组织创新

清洁生产是人类社会可持续发展的主要途径之一，已越来越受到各国政府与企业的重视。本文从企业文化、组织结构及企业战略等方面阐述了清洁生产对企业组织的影响。     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (− 0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

The potential for improvements in energy efficiency and CO2 emissions in the EU27 cement industry and the relationship with the capital budgeting decision criteria

This paper performs a cost-effectiveness analysis of some of the best available technologies (BAT) that can contribute to decreasing the energy consumption and CO₂ emissions in the European Union’s (EU27) cement industry. Several capital budgeting decision criteria have been used (the payback period, the net present value and the internal rate of return) to study whether or not an investment should be considered worthwhile. The results show that, independent of the capital budgeting decision criteria used, the number of cost-effective retrofitting possibilities available is large compared to the rate of improvements that the industry undertakes annually. This shows the insensitivity of the industry to financial criteria when it comes to making their investment decisions. The possible thermal energy improvement in the clinker production, if all these BATs were implemented, has been quantified to be around 10%. This achievement would place the cement industry in the upper bound of the benchmark range for clinker manufacture. However considering the delays observed nowadays in terms of diffusion of BATs in the cement industry, it requires a conducive policy environment that combines support for both technology development and to their deployment.     

清洁生产与炼油污水回用

该文分析了福建炼化公司炼油污水现状，提出炼油污水回用的可能方式，并进行了初步探讨。