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Zhang J.,Central South University | Zhang J.,Guangzhou Civil Aviation College | Chen Z.,Central South University | Chen W.,Central South University | And 2 more authors.
Journal of Information and Computational Science | Year: 2015

This paper combines the control variable technique and dual variable technique together, both of which are simple and flexible variance reduction techniques, and puts forward a compound technique method that is more effective variance reduction technique on Monte Carlo simulation method for pricing Asian options. Moreover, six usual control variables and the corresponding dual variables are selected to make some practical analysis by using an arithmetic Asian option. ©, 2015, Binary Information Press. All right reserved. Source

Wei J.,Beijing Forestry University | Huang K.,Beijing Forestry University | Yang S.,Hunan Academy of Social Science | Li Y.,Hubei Water Resources Research Institute | And 2 more authors.
Journal of Cleaner Production | Year: 2016

Low carbon dioxide (CO2) emissions are the foundation on which to realize the sustainable development of a green China. Recently in Beijing, the capital of China, serious environmental pollution-climate anomaly, severe haze and human sub-health have been accorded more importance. This study examines the energy-related CO2 emissions generated by Beijing industries from 2000 to 2010 by using an input-output analysis method. The direct, indirect and total CO2 emissions of sectors in Beijing were calculated. In addition, structural decomposition analysis (SDA) was conducted to evaluate the driving factors from the perspective of technology, sectoral connection, economic structure and economic scale. The results show that the growth rate of sectoral CO2 emissions in Beijing has drastically increased during this time with a moderate decline during 2007-2010. The metal and non-metal mining industries, the electric power, gas and water supply sector and the construction industry caused the most CO2 emissions. The economic structure change and the rapid economic growth led to the significant increase in CO2 emissions growth in Beijing. Thus, optimizing the economic structure and improving the technology are important to alleviate CO2 emissions. Although we can currently appropriately utilize fossil fuels, further research on new energy and clean development, as well as enhanced government management strength is required to reduce CO2 emissions. © 2016 Elsevier Ltd. Source

Wang Z.,Beijing Forestry University | Huang K.,Beijing Forestry University | Yang S.,Hunan Academy of Social Science | Yu Y.,Beijing Institute of Technology
Journal of Cleaner Production | Year: 2013

Water is scarce in Beijing, China, and rapid economic and societal development, as well as the dense population, causes severe pressure on local water resources. This paper involves the "water footprint", defined as the volume of water needed to produce the goods and services consumed, which quantifies the environmental impact of consumption. By combining an input-output model with intersectoral water flows, this paper describes a modified input-output model to calculate the direct, indirect and gross water footprint intensity and the gross water footprint of different sectors in Beijing in 2002 and 2007. The results show declines in the agricultural and industrial water footprints for these years. The grey water footprint, which reflects environmental pollution caused by human production and consumption, was also calculated and suggests that the shortage of water resources, rather than water pollution, is the main problem in Beijing. Evaluation of the virtual water trade, along with water savings in the various sectors, verified that Beijing is a net virtual water importer. Furthermore, the water footprint shows that Beijing is advanced in water use efficiency compared to other provinces in China. Finally, adjustments in the industrial structure, along with virtual water importing, should be prioritized as water-saving strategies for Beijing. © 2012 Elsevier Ltd. All rights reserved. Source

Huang K.,Beijing Forestry University | Wang Z.,Peking University | Yu Y.,Beijing Institute of Technology | Yang S.,Hunan Academy of Social Science
Water Policy | Year: 2015

Beijing is experiencing a shortage of water resources. Its rapid development and dense population have caused an extreme demand for water. This study quantifies the water footprint of Beijing at the sectoral level using a modified input-output model and estimates the impacts of freshwater use by life cycle impact assessment. The results suggest that the main water source of Beijing industries is groundwater, which is quite different from the main use of surface water in China. By coupling the input-output model with the eco-indicator 99 method, the environmental impact of the water footprint was quantified. The results show those sectors that introduced severe impacts in 2002 and continued to make large impacts in the following 5 years; the major impact of water use is resource depletion. In addition, the inconsistency of the eco-indicator points and the eco-indicator index of sectors leads us to control sectors with large eco-indicator points and develop those with small eco-indicator indexes. Furthermore, a regional comparison was conducted using the eco-scarcity method and verified that Beijing is under severe water pressure, with a value ranked fifth nationally. We conclude that the control of groundwater use and the externalization of local water pressure should be prioritized in water management in Beijing. © IWA Publishing 2015. Source

This paper describes an industrial energy combustion use and industrial process emissions accounting method. By utilizing three set of widely used energy combustion carbon emission factors, China's industrial energy consumption carbon emissions are calculated. By using the methods provided by the IPCC, the industrial process carbon emissions for extractive industries, chemical industries and metal industries are calculated. The results show that in 2010 China's industrial energy consumption carbon emissions reached approximately 6.91×108 t C (2.53×109 t CO2), 85% from coal burning. The industrial process emitted approximately 9.47×108 t C (3.48×109 t CO2). About 5.55×108 t C (2.04×109 t CO2) is emitted by providing heat and power to industrial processes. In addition, this paper also proposed an improved model coupling industrial carbon emissions data and input-output analysis. It will help to quantify and evaluate the trans-sector carbon emissions shift. © (2013) Trans Tech Publications, Switzerland. Source

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