Le-Le Zou

Energy Economics: CO2 Emissions in China

Energy is essential to socio-economic development in modern society. China is the largest developing country and the second largest energy producer and consumer in the world, as well as the second largest producer of CO2 emissions after the USA. CO2 emissions in China has become a common focus of academic communities and governments worldwide. Therefore, the study of Chinas CO2 emissions is not only helpful in terms of fully implementing scientific development, but also significant in working towards the sustainable development of China and mitigating global climate change. Beginning with energy use and CO2 emissions, Energy Economics: CO2 Emissions in China discusses topical issues related to the present CO2 emissions status and its historical evolution. In addition, it analyzes CO2 emission reduction technologies, the CO2 market and CO2 emissions reduction strategies and policies, in the hope of providing a reference resource for decision making in future CO2 emission reduction and climate change resolution strategies and policies in China. The book focuses on several key issues, which are discussed further as below. 1) Energy use and CO2 emissions; 2) Characteristics of energy consumption and CO2 emissions in China; 3) Factors affecting CO2 emissions at different economic development levels; 4) Evolution characteristics of CO2 emissions in CO2-intensive sectors; 5) The analysis of regional CO2 emissions in China; 6) Potential for, and impacts of, CO2 emission reduction technologies; 7) Simulation research on CO2 emission reduction policies; 8) International CO2 trading mechanism and its impact on emission reduction; 9) Chinas CO2 emissions prospects.

Risk evaluation of China’s natural disaster systems: an approach based on triangular fuzzy numbers and stochastic simulation

To deal effectively with the evaluation problem of natural disaster risk system affected by many uncertain factors, a multivariate connection number expression is presented. This expression is based on the index samples and evaluation grade criterions of natural disaster risk system and is capable of describing the hierarchy property and fuzziness of membership relationship between index samples and evaluation grade criterions. In this proposed method, the fuzzy evaluation grade criterion problem is resolved by combining triangular fuzzy numbers with multivariate connection number theory, and triangular fuzzy numbers are used to express the discrepancy degree coefficients of connection number and evaluation index weights. Accordingly, a connection number-based evaluation method for the natural disaster system of China (named CN-TFN for short) is established using triangular fuzzy numbers and stochastic simulation. The application results show that the spatial distribution of natural disaster risk grades of China has the trend of aggrandizement from west to east of China. The economically developed and densely populated coastal areas are very likely to have a high level of natural disaster risk grade or above; thus, these areas are the key regions of the natural disaster risk management of China. The results also show that the CN-TFN is able to reflect practical conditions of the evaluation problem of natural disaster system and to provide more reliability information as compared to the existing evaluation methods. This is as a result of its comprehensive usage of various information of subjective and objective uncertainties in the evaluation process of natural disaster risk system and its expression by confidence intervals. Due to the simplicity and generalization, the CN-TFM is applicable to comprehensive risk grade evaluation of various natural disaster systems.

Forewarning of sustainable utilization of regional water resources: a model based on BP neural network and set pair analysis

Early warning for sustainable utilization of regional water resources is an important control measure for regional water security management. To establish operable and quantitative forewarning model, in this paper, a new forewarning model for sustainable utilization of water resources based on BP neural network and set pair analysis (named BPSPA-FM for short) was established. In the proposed approach, the accelerating genetic algorithm–based fuzzy analytic hierarchy process was suggested to determine the weights of evaluation indexes, back-propagation neural network updating model was used to predict the values of the evaluation indexes, and the set pair analysis was used to determine the function values of relative membership in variable fuzzy set of the samples. BPSPA-FM was applied to early warning for sustainable utilization of regional water resources of Yuanyang Hani terrace in Yunnan Province of China. The results show that the states of sustainable utilization in this system were near the critical value between nonalarm and slight alarm from 1990 to 2000, the states of the system fell into slight alarm and were rapidly close to intermediate alarm from 2001 to 2004, and the states of the system were predicted to be near the critical value between slight alarm and intermediate alarm from 2005 to 2010. The main alarm indexes of the system were utilization ratio of water in agriculture, control ratio of surface water, per capita water supply, per unit area irrigation water and per capita water consumption. BPSPA-FM can take full advantage of the changing information of the evaluation indexes in adjacent periods and the relationship between the samples and the criterion grades. The results of BPSPA-FM are reasonable with high accuracy. BPSPA-FM is general and can be applied to early warning problems of different natural hazards systems such as drought disaster.

The impacting factors of vulnerability to natural hazards in China: an analysis based on structural equation model

The vulnerability to natural hazard is one of the inner characteristics of social economic system, which is determined and impacted by various factors from almost all the aspects of the system. Although it is widely agreed that the economic development, the migration, and the equity of resource allocation are among the most important impacting factors in forming and developing of the vulnerability, their interrelationship is still unclear enough. The study in this paper employs the method of structural equation model to discover the interrelationship between different latent impacting factors, as well as their contributions to the vulnerability of the system to natural hazards. It is found that, among the factors relating social and economic development, the equity of income allocation is a key point. Also the impacts from industrialization are different for different development levels. The conclusions are expected to be helpful references for the decision consideration of the local development strategies.

The emission reduction effect and economic impact of an energy tax vs. a carbon tax in China : a dynamic CGE model analysis

Carbon tax and energy tax are among the hot discussions in China. This study conducts simulation studies on them with a CGE model and analyzes their economic impacts, especially on the energy-intensive sectors. The Chinese economy is affected at an acceptable level by the two taxes in different scenarios. The import and export of energy-intensive industries are changed, leading to improved domestic competitiveness. Compared with implementing a single tax, a combined carbon-energy tax reduces more emissions with relatively smaller economic costs. For China, the sooner such taxes are launched, the smaller the economic costs and the more significant emission reductions.