The Dynamic Evolutionary Analysis on Carbon Emissions in Yangtze Delta

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1 ISSN (print), (online) International Journal of Nonlinear Science Vol.10(2010) No.3,pp The Dynamic Evolutionary Analysis on Carbon Emissions in Yangtze Delta Rulei Jin, Lixin Tian, Jialing Qian, Yating Liu Energy development and environmental protection strategy research center, Jiangsu University Zhenjiang, Jiangsu, , P.R. China (Received 10 June 2010, accepted 29 November 2010) Abstract:Based on the present situation of carbon emissions in Yangtze Delta, this paper builds a nonlinear dynamic system model by using the nonlinear least-square method and regression analysis method. In addition, we discusses and evolutionary analyzes on the total carbon emissions in Yangtze Delta by using the dynamic system model. Finally, we predict the long-term total carbon emissions evolution trend in this area. Keywords: dynamic evolutionary analysis; carbon emissions; forecast 1 Introduction Climate change is one of the hottest issue all around the world. China, as the second biggest co 2 emission country, is facing more and more severe pressure to reduce co 2 emission. Yangtze Delta is the largest economic core area in China. It is also the forefront for China entering the field of international economic competition. These years, growing energy consumption and over-reliance on fossil fuels have resulted in the rapid increase of co 2 emissions. Based on these, study on co 2 in Yangtze River Delta has been a matter of urgent. There have been a lot of researches on the carbon emissions both at home and abroad. Based on the identity of carbon emissions, Guoquan Xu, Zeyuan Liu, Zhaohua Jiang[1] set up a decomposition model of carbon emissions per capita for China by using adopting Logarithmic Mean Weight Divisia LMD method. Ying Fan, Qiaomei Liang, Yiming Wei, Norio Okada[2] introduced a model and corresponding software for modeling China s Energy Requirements and the co 2 Emissions Analysis System. Mei Sun, Lixin Tian, Jun Xu[3] investigated the control of energy resource chaotic system by using time-delayed feedback control (TDFC) method. The controllability and the stability of the equi-libriums of the system were varied and several stabile periodic orbits were got in the numerical simulations. Mei Sun, Lixin Tian, Jian Yin[4] studied the Hopf bifurcation of the energy resource chaotic system by using an analytical method. Chris P. Tsokos, Yong Xu[5] modeled carbon dioxide emission data with a system of differential equations. Andrew Ford[6] described a computer simulation analysis of carbon dioxide emissions in the electric power system in the western United States. Reyer Gerlagh[7] developed an endogenous growth model with capital, labor and carbon-energy as production factors and three technological variables that measure accumulated innovations for carbon-energy production, carbon-energy savings, and neutral growth. Andreas Loschel and Vincent M. Otto.[8] analyzed energy and co 2 emission trends of Mexico s iron and steel industry during the period , using international comparisons and Log mean Divisia index, to examine co 2 emissions related to energy use and production process. Beibei Zhang and Lixin Tian[9] gave a new model of energy intensity. Parameters in the model were estimated by the estimation method for statistical test, and China s energy intensity was predicted. Lixin Tian and Jing Liu[10] used the Solow production function model and constructed the relationship between energy prices and energy intensity. Lixin Tian and Seng Bao[11] proposed a Two-component model to adjust and optimize the energy resources structure reasonably and scientifically. The energy production and consumption-related coefficients were predicted and estimated by the estimation method for statistical test. There have also been some researches in Yangtze Delta. Wei Huang and Yuedong Sheng[12] analyzed the idea and approaches of promoting low-carbon economy in the Yangtze Delta based on the regional development characteristics and advantages. Jianyi Hu[13] put forward to some principles and suggests that fossil energy consumption total deal control, for the Yangtze Delta sustainable development and sciences decision offering consult basis. Minjie Yu[14] analyzed economic growth and energy using in different situations of 16 cities in the Yangtze Delta and discribed the economic structure. Kaiyao Wu and Qigui Zhu[15]analyzed Corresponding author. address: kirstem@126.com Copyright c World Academic Press, World Academic Union IJNS /415

2 260 International Journal of Nonlinear Science, Vol.10(2010), No.3, pp the different stages of energy flow in the Yangtze Delta area; examined indicators of the quantity, structure, dynamics and intensity of energy use; illustrated the structural characteristics, regional differences and trend of energy consumption based on data analysis; demonstrated the unique relationship between energy, resources and economy in the Yangtze Delta. Bohong Lin and Ye Wu[16] developed a model to simulate energy consumption and co 2 emissions from automobile sector in Yangzi Delta. Yangtze Delta is the largest economic core area in China. It is also the forefront for China entering the field of international economic competition.based on the rapid increase of co 2 emissions which have been caused by the growing energy consumption and over-reliance on fossil fuels, this paper builds a dynamic system model by using the least-square method,and works out the growth rate and growth prospects of carbon emissions in Yangtze Delta. In addition, this paper analyzes on the evolutionary model by using regression analysis method, and illustrates that this model matches well with the actual status of Yangtze Delta s carbon emissions. This method can reflect timely-change information of carbon emissions more clearly than the scenario analysis method. According to this method, we predict the long-term total carbon emissions trend in 2020, 2035, 2050 in this area. The outline of this paper is organized as follows. In section 2, we introduce a dynamic evolutionary model of carbon emissions in Yangtze Delta and its total carbon emissions are being evolutionary analyzed. The main conclusions are presented in Section 3. 2 Dynamic evolution model of carbon emissions and it s evolution analysis in Yangtze Delta 2.1 Dynamic evolution model of carbon emissions in Yangtze Delta Carbon emissions in Yangtze Delta mainly relies on fossil fuels, including raw coal(a), coke(b), coke oven gas(c), crude oil(d), gasoline(e), kerosene(f), diesel oil(g), fuel oil(h), PLG(liquefied petroleum gas)(i), refinery gas(j),which are the carbon sources of this area.in order to quantitatively calculated and analyzed,we obtain the calculation formula of carbon emissions based on the scientific, comparability, representative, operability principles. Total co 2 emission is estimated based on energy consumption, fuel value, carbon emission factors and the fraction of oxidized carbon by fuel as follows. CE t = CEi t = Ei t V i EF i O i 44/12 (1) i i where CE t represents total CO 2 emission in year t (in tons, t); CE t i represents total CO 2 emission based on fuel type i in year t; E t i represents total energy consumption based on fuel type i in year t (t); V i represents fuel value based on fuel type i; EF i represents carbon emission factor of the ith fuel (t-c/tj); O i represents the fraction of carbon oxidized based on fuel type i. The fuel value(v), carbon emission factors(ef) and the fraction of carbon oxidized(o) are given in Table 1. These values are assumed to be constant over the time period of the study. Table 1: Fuel value, carbon emission factors and fractions of carbon oxidized Fuel A B C D E F G H I J V(kJ/kg) EF(t-C/TJ) O According to the actual situation, this paper establishes a model carbon emission of Yangtze Delta d(q) = f( d(a), d(b), d(c), d(d), d(e), d(f ), d(g), d(h), d(i), d(j) ) (2) According to the actual data, this paper draws a scatter diagram of recently carbon emissions in Yangtze Delta (Figure.1). Using least-square method, this paper builds an actual carbon emission dynamic model of Yangtze Delta Q(t) = t t t (3) where r represents years in equation (3).A graphical display of the actual data and the solution of the equation (3) are given by Figure.2, which show Yangtze Delta s carbon emissions have a power series growing trend. IJNS for contribution: editor@nonlinearscience.org.uk

3 R. Jin, et al. : The Dynamic Evolutionary Analysis on Carbon Emissions in Yangtze Delta Figure 1: Total carbon emissions in Yangtze Delta(Units:Mt) Figure 2: Model of carbon emissions in Yangtze Delta From Figure.1, we can find out that carbon emissions in Yangtze Delta have obvious classes,representing from smooth growth to rapid growth, and stabilize at last. This is because China s energy consumption starts to drop from1996 to 1999, leading to smooth movements of carbon emissions in Yangtze Delta. However, Yangtze Delta, as China s biggest economic core, its rapid economic development leads to the consumption of energy has a significant growth.because of its carbon emissions mainly depend on fossil fuels, the carbon emissions in Yangtze Delta rise dramatically after From Figure.2,we can find our that our carbon emissions dynamic model of Yangtze Delta matches well with the actual status of carbon emissions in Yangtze Delta,presenting from smooth growth to rapid growth, and stabilize at last. 2.2 The instantaneous variation of carbon emissions in Yangtze Delta Q (t) = t t (4) We can find out that the instantaneous variation of carbon emissions is negative before 1998, but the amount of reducing trend appears relatively stable.that is to say,the decreasing trend in Yangtze Delta was gradually slower before1998. After 1998, carbon emissions instantaneous variation is positive and carbon emissions grow rapidly. Striving for realizing the goal that carbon emissions per unit of GDP will fall by percent, we need to predict the carbon emissions in Yangtze Delta.Our goal is making the instantaneous variation of carbon emissions keeps appearing negative,which means carbon emissions in Yangtze Delta keeps decreasing year by year.thus we need through carbon emissions prediction, control strategy,policy implementation and technical innovations to achieve the goal of low carbonization and to make system to the ideal direction, reflecting the low carbonization development of high carbon energy.(figure.3) Figure 3: The instantaneous variation of carbon emissions in Yangtze Delta 2.3 Regression analysis IJNS homepage:

4 262 International Journal of Nonlinear Science, Vol.10(2010), No.3, pp In order to show the tendency of the dynamic evolution model of carbon emissions clearly and reveal the dynamic evolutive mechanism and characteristics, this paper adopts a regression analysis method as a tool for evaluating the model. Using the regression analysis method, we calculate the existing data of carbon emissions in Yangtze Delta from 1997 to 2008 and obtain the data of dynamic evolutionary of carbon emissions. Then we compare the date with the empirical data, and obtain residual, average residual.we directly evaluate the model is bad or good through the residual data. The coefficient of determination reflects the fact whether we have identified a good model. The closer coefficient of determination to 1, the better model is. The smaller residual is, the closer model data and the original data. Table 2: Residual analysis on the model of carbon emissions in Yangtze Delta Year Empirical rate of change The instantaneous variation of carbon emissions Residual Average residual Coefficient of determination Results: From the table2, we can find out that the residuals which between the empirical rate of change and the instantaneous variation of carbon emissions are very small. That means the fact that we have identified a good model. Thus, we can predict total carbon emissions and the instantaneous variation of carbon emissions in Yangtze Delta in Medium-Short Term. We get total carbon emissions in Yangtze Delta in 2020,2035 and 2050 are Mt, Mt and Mt respectively. And the instantaneous variation of carbon emissions in Yangtze Delta in 2020,2035 and 2050 are , and respectively. 3 Conclusion Based on the present situation of carbon emissions and ten kinds of main carbon sources in Yangtze Delta, including raw coal, coke, coke oven gas, crude oil, gasoline, kerosene, diesel oil, fuel oil, PLG, refinery gas, this paper builds a dynamic system model by using the least-square method and gives an evolutionary analysis on it.we can find out that carbon emissions in Yangtze Delta have obvious classes,representing from smooth growth to rapid growth, and stabilize at last.and the instantaneous variation of carbon emissions is negative before 1998, but the amount of reducing trend appears relatively stable.after 1998, carbon emissions instantaneous variation is positive and carbon emissions grow rapidly. Thus, we work out the growth rate and growth prospects of carbon emissions in Yangtze Delta. In addition, we analyzes on the evolutionary model by using regression analysis method, and illustrates that this model matches well with the actual status of Yangtze Delta s carbon emissions. Finally, we predict the long-term total carbon emissions trend in this area. We can find out that the total carbon emissions in Yangtze Delta began to rise dramatically after 2000 because of its excessive dependence on fossil fuels. With the tendency, the total carbon emissions in Yangtze Delta will be Mt in 2020, which is hard to realize the goal that carbon emissions per unit of GDP will fall by percent. Adjusting carbon emissions strategies and policies are required urgently to restrain the rapid increasing carbon emissions in Yangtze Delta. It provides a theoretical basis for the further study on the situation of carbon emissions in this area. IJNS for contribution: editor@nonlinearscience.org.uk

5 R. Jin, et al. : The Dynamic Evolutionary Analysis on Carbon Emissions in Yangtze Delta 263 Acknowledgments Research was supported by the National Nature Science Foundation of China (No , ), the Ph.D. Programs Foundation of Ministry of Education of China (No ), the Humanities, Social Sciences Research general project of Ministry of Education (No. 08JA790058), the College of Philosophy and Social Sciences key research base of major project of Jiangsu (No ) and Scientific Research Project of Jiangsu University (No. 09A105). References [1] Guoquan Xu, Zeyuan Liu, Zhaohua Jiang. Decomposition model and empirical study of carbon emissions for China, China population resources and environment, 16(2006)(6): [2] Ying Fan,Qiaomei Liang,Yiming Wei,Norio Okada. A model for China s energy requirements and CO2 emissions analysis. Environmental Modelling & Software, 22(2007)(3): [3] Mei Sun, Lixin Tian, Jun Xu. Time-delayed Feedback Control of the Energy Resource Chaotic System. International Journal of Nonlinear Science, 1(2006): [4] Mei Sun, Lixin Tian, Jian Yin. Hopf Bifurcation Analysis of the Energy Resource Chaotic System. International Journal of Nonlinear Science, 1(2006): [5] Chris P. Tsokos, Yong Xu. Modeling carbon dioxide emissions with a system of differential equations. Nonlinear Analysis, 71(2009)(12): [6] Andrew Ford. Simulation scenarios for rapid reduction in carbon dioxide emissions in the western electricity system. Energy Policy, 36(2008), [7] Reyer Gerlagh. A climate-change policy induced shift from innovations in carbon-energy production to carbonenergy savings. Energy Economics, 30(2008)(2), [8] Andreas Loschel, Vincent M. Otto. Technological uncertainty and cost effectiveness of co 2 emission reduction. Energy Economics, 31(2009)(1),S4-S17. [9] Beibei Zhang, Lixin Tian. Analysis of China s Energy Intensity and Its Forecast. International Journal of Nonlinear Science, 9(2010)(3): [10] Lixin Tian, Jing Liu. Empirical Analysis of Energy Prices in the Research of the Energy Intensity. Journal of Natural Resources, 25(2010)(9):1-6. [11] Lixin Tian, Seng Bao. Trend Forecast of Energy Production and Consumption in China and Research of Carbon Emissions. Journal of Natural Resources, 25(2010)(8): [12] Bohong Lin, Ye Wu. Oil consumption and co 2 emissions from automobile sector in Yangzi River Delta Region of China. Sciencepaper Online, 6(2010)(6): [13] Kaiyao Wu, Qigui Zhu. Energy Flow Analysis for Energy Consumption in Yangtze River Delta. Journal of SJTU(Philosophy and Social Science), 6(2009): [14] Minjie Yu. Yangtze Delta s economic growth and energy utilization analysis. Price Issue, 388(2009)(9): [15] Jianyi Hu. Concern the Basic Situation of Saving Energy and Reducing Emission in the Yangtze Delta. Shanghai Energy Conservation, 10(2008): [16] Wei Huang, Yuedong Sheng. Thoughts about development of low-carbon economy in the Yangtze Delta. Shanghai Electric Power, 1(2010): IJNS homepage: