Energy demand in China : overview report

CHINA 23800 Issuecs and Options in Gr-eenhiouse Gas Emissions Control L 7 ENERGY DEMAND IN CHINA: OVERVIEW REPORT SUBREPORT NUMBER 2 Li Junfeng, Todd M. Johnson, Zhou Changyi, Robert P. Taylor, Liu Zhiping, and Jiang Zhongxiao February 1995 FILE COPY CHINA Issues and Options in Greenhouse Gas Emissions Control ENERGY DEMAND IN CHINA: OVERVIEW REPORT Report Number 2 by Li Junfeng, Todd M. Johnson, Zhou Changyi, Robert P. Taylor, Liu Zhiping, and Jiang Zhongxiao February 1995 Supported by the Global Environment Facility ii The views expressed herein are those of the authors and do not necessarily represent those of the World Bank. Copyright 1995 Additional copies of this report may be obtained from The World Bank Industry and Energy Division China and Mongolia Department East Asian and Pacific Regional Office 1818 H Street, NW Washington, DC 20433 OTHER SUBREPORTS IN THIS SERIES: Estimation of Greenhouse Gas Emissions and Sinks in China, 1990, August 1994. Report 1. Energy Efficiency in China: Technical and Sectoral Analysis, August 1994. Report 3. Energy Efficiency in China: Case Studies and Economic Analysis, December 1994. Report 4. Alternative Energy Supply Options to Substitute for Carbon Intensive Fuels, December 1994. Report 5. Greenhouse Gas Control in the Forestry Sector, November 1994. Report 6. Greenhouse Gas Emissions Control in the Agricultural Sector, September 1994. Report 7. Valuing the Health Effects ofAir Pollution: Application to Industrial Energy Efficiency Projects in China, October 1994. Report 8. Potential Climate Change Impacts on China, September 1994. Report 9. Residential and Commercial Energy Efficiency Opportunities: Taiyuan Case Study, September 1994. Report 10. Pre-Feasibility Study on High Efficiency Industrial Boilers, August 1994. Report 11. iii FOREWORD This report is one of eleven subreports prepared as inputs to the United Nations Development Programme (UNDP) technical assistance study, "China: Issues and Options in Greenhouse Gas Emissions Control," supported by the Global Environment Facility and executed by the Industry and Energy Division, China and Mongolia Department of the World Bank. This subreport is a joint effort of the State Planning Commission, the National Environmental Protection Agency, and the World Bank. This report was prepared by a joint team of experts from the Energy Research Institute, State Planning Commission of China, the Chinese Academy of Sciences, and the World Bank. Li Junfeng (World Bank Energy Economics Consultant) and Liu Zhiping (Senior Researcher of the Energy Research Institute of the SPC) are the principal authors of the sectoral and overall energy demand scenarios (chapters 4 and 5), and were responsible for integrating this work into the overall study. Zhou Changyi, Dai Yande and Shen Deshun of the SPC study group, and Robert Taylor and Todd M. Johnson of the World Bank study team made important contributions to the energy demand analysis. Zhou Fengqi, Director of the Energy Research Institute of the SPC and Zhu Liangdong, Deputy Director of the Department of Resource Conservation and Comprehensive Utilization of the SPC, also offered valuable advice. The macro modeling work (chapter 3) was organized by the National Environmental Protection Agency of China and the World Bank. The principal contributors to this analysis included Chen Xikang of the Institute of Systems Science of the Chinese Academy of Sciences, Lawrence J. Lau of Stanford University, and Jiang Zhongxiao and Todd M. Johnson of the World Bank study team. Todd M. Johnson, Robert Taylor, and Liu Feng edited the final report. This study was a collaborative effort of experts from Chinese and international institutions. The opinions expressed represent the views of the experts involved, and do not necessarily represent the official views of the institutions where they work. iv CURRENCY EQUIVALENTS I USS = 4.7 Chinese Yuan (1990) WEIGHTS AND MEASURES 1 ton of coal = 0.7143 tce, average I ton of crude oil = 1.43 tce 1,000 i of natural gas = 1.33 tce Kilo(Watt) = 10, (Watts), Mega = 106, Giga = 10', Tera = 1012 ABBREVIATIONS AND ACRONYMS CO2 - carbon dioxide EIRR - economic internal rate of return EEIRR - environmental economic internal rate of return FIRR - financial internal rate of return GEF - Global Environment Facility GHG - greenhouse gas GWh - gigawatt-hour kcal - kilocalories kgce - kilogram of coal equivalent kW - kilowatt kWh - kilowatt-hour LPG - liquified petroleum gas mtce - million tons of coal equivalent MW - megawatt NEPA - National Environmental Protection Agency of China NH3 - ammonia NOx - oxides of nitrogen NPV - net present value S02 - sulfur dioxide SPC - State Planning Commission of China t - metric ton tce - ton of coal equivalent TSP - total suspended particulate TVE - township and village enterprise UNDP - United Nations Development Programme v CONTENTS 1. INTR ODUCTION . ............................................................ ..................... .................I 2. OVERVIEW OF RECENT DEMAND TRENDS ......................................... 3 A. ENERGY CONSUMPTION IN 1990 ................................................................... ........................................ 3 China's High Energy Intensity per Unit GDP......................................................................................3 Recent Energy Consumption Trends .................................................................................................... 6 3. MACROECONOMIC MODELING AND ANALYSIS.................................................... .... A. OBaJE E............................................................................................................................................ 9 B. BACKGROUND AND STRUCTURE OF THE M ODEL......................................................................................9 The China M acroeconomic M odel.....................................................................................................10 Input-output analysis......................................................................................................................... 11 Emissions..........................................................................................................................................13 C. KEY M ODELING AssumpToNs ............................................................................................................ 17 Population ......................................................................................................................................... I7 Economic growth............................................................................................................................... 18 D. KEY RESULTS......................................................................................................................................19 Baseline Scenario.............................................................................................................................. 19 Economic Structure........................................................................................................................... 19 Slower Growth Scenario.................................................................................................................... 21 4. DEVELOPMENT OF FUTURE ENERGY DEMAND SCENARIOS................N.O.....................23 A. M ETHODOLOGICAL OVERVIEW ..................................................................................................23 B. SUBSECTOR ENERGY DEM AND COEFFICIENTS .......................................................................24 Agriculture (1)................................................................................................................................... 24 Coal M ining (2)................................................................................................................................. 24 The Petroleum Industry (3)................................................................................................................25 The Natural Gas Industry (4).............................................................................................................26 The Electric Power Industry (5)......................................................................................................... 26 Ferrous M etals (6)............................................................................................................................. 27 Non-Ferrous M etals (7).....................................................................................................................29 Chemical Fertilizers (8).....................................................................................................................29 Other Chemicals (9).........................................................................................................................30 Cement (10)......................................................................................................................................31 Other Building M aterials (1)3 ..........................................................................................................32 M achinery and Electronics (12) ........................................................................................................33 Light Industry (13)............................................................................................................................. 33 Construction (14) .............................................................................................................................. 35 Freight Transportation and Postal and Communication Services (15) ...............................................35 Commerce (16)................................................................................................................................. 36 Passenger Transportation (17) ..........................................................................................................36 Other Services (18)............................................................................................................................ 37 Residential Sector............................................................................................................................. 37 Vi & SIMM ARY A ND CtNCItS 9 A. KEY FACTORS INFLUENCING ENERGY DEMAND ....................................................................40 B. ENERGY DEMAND SCENARIOS.................................................................................................... 42 Baseline Ca .................................................................................................................................... 42 Slower Growth Ca4.......................................................................................................................... 44 High Efficiency Case......................................................................................................................... 45 Summary ........................................................................................................................................... 45 6. REFERENCES ............................ .. . ..... List of Tables TABLE 2.1 ENERGY BALANCE, 1990...........................................................................................................4 TABLE 2.2 MACROECONOMIC STRUCTURE, 1990........................................................................................5 TABLE 2.3 ENERGY EFFICIENCY INDICATORS, 1980-92 ..............................................................................7 TABLE 3.1 AN INPuT-OUTPUT TABLE ....................................................................................................... 1 TABLE 3.2 SECTORS IN THE CHINA GHG MODEL ...................................................................................... 13 TABLE 3.3 CO2 (CH ) EMISSION M ATR ................................................................................................ 14 TABLE 3.4 S02 (TSP) EMISSION MM ATR ................................................................................................. 16 TABLE 3.3 POPULATION PRojE n S...................................................................................................... 17 TABLE 3.6 GDP PER CAPITA OF CHINA. US ............................................................................................19 TABLE 3.7 STRUCTURE OF CONSUMPTION:................................................................................................20 TABLE 4.1 CHINA: ELECTRICITY USE PER TON OF COAL.............................................................................25 TABLE 4.2 FUEL CONSUMPTION PER UNIT OF ELECTRICITY .........................................................................26 TABLE 4.3 ENERGY USE PER TON OF STEEL PRODUCTION (KGCF)2N) ........................................................27 TABLE 4.4 STEEL INDUSTRY OUTPUT AND ENERGY USE BY PLANT SiZE.......................................................2 TABLE 4.5 NON-FERROUS METALS INDUSTRY: PER UNIT ENERGY USE.........................................................29 TABLE 4.6 ACTUAL AND PROJECTED TRENDS IN RESIDENTIAL ENERGY USE .................................................37 TABLE 4.7 ENERGY USED FOR COOKING ...................................................................................................3 TABLE 4.8 SHARE OF COOKING FUEL (PERCENT) .......................................................................................38 TABLE 4.9 ENERGY EFFICIENCY FOR COOKING (PERCENT).........................................................................38 TABLE 5.1 TOTAL ENERGY DEMAND: BASELINE CASE...............................................................................43 TABLE 5.2 TOTAL ENERGY DEMAND: No FURTHER CHANGE SCENARIO*...................................................44 TABLE 5.3 TOTAL ENERGY DEMAND: SLoWER GROWTH SCENARIO ..........................................................44 TABLE 5.4 TOTAL ENERGY DEMAND: HIGH EFFICIENCY SCENARIO...........................................................45 TABLE 5.5 SUMMARY OF ENERGY PROJECTIONS FOR 2020........................................................................46 Annexes 1. sECTORAL COMPOSITION OF THE INPUT-OU Pur TABLE ............................................................. 4 2. RESULTS OF THE MACROECONOMIC AND INPUT-OUTPUT ANALYSIS......................................................... 50 3. ENERGY COEFFICIENT CACLULATIONS7.................................................................................................. 74 vii 1. INTRODUCTION 1.1 This report presents the energy demand scenarios prepared for China for the year 2000, 2010 and 2020 for the overall China Greenhouse Gas (GHG) Study. These scenarios of future energy demand were not prepared as an attempt to provide a definitive forecast of China's future energy use. Rather, they were prepared to (i) provide a reference point for gauging the relative importance of different means to reduce the growth of greenhouse gas emissions in China, and (ii) assess the relative importance of the variety of different factors influencing China's future energy demand. 1.2 The analysis draws heavily on other detailed studies on energy demand and energy conservation in China also completed under the direction of the SPC and World Bank as part of the overall China GHG Study. These include, in particular, Subreport 3, Energy Efficiency in China: Technical and Sectoral Analysis, which provides detailed analysis of energy use and conservation prospects in 15 major subsectors, and Subreport 4, Energy Efficiency in China: Case Studies and Economic Analysis, which reviews the feasibility and economics of about 25 types of energy conservation projects with widespread dissemination potential in China. These studies were completed by SPC and Chinese line ministry experts together with international consultants. 1.3 The chief purpose of this report is to outline the methodology and assumptions used for the energy demand scenarios of the China GHG Study. The methodology and models used were specially prepared for this study, in an approach that the analysts feel is best suited for the Chinese case. Macroeconomic models were used to prepare internally consistent growth projections for 18 economic subsectors. Associated energy demand projections were then prepared in a bottom-up approach, through preparation of demand projections by fuel type for each subsector. The authors recognize that the resulting scenarios represent just one view of possible future trends. The authors feel that the true value of the analysis lies not in the detailed assumptions used for each subsector, where there are clearly a range of views among experts, but in the completeness of the analysis, and the ability of the framework to assess the relative impact of different assumptions on total energy demand. 1.4 Chapter 2 provides a brief review of the recent energy demand trends in China. Further detailed information on that topic can be found in numerous other studies prepared by the Energy Research Institute of the SPC and in the World Bank's China Energy Conservation Study (February 1993). Chapter 3 provides an overview of the macroeconomic modeling work, including a description of the China GHG Model, that formed the basis for the energy demand projections. Chapter 4 reviews the assumptions used for forecasting energy demand in the various subsectors of the Chinese economy. I Chapter 5 provides a brief overview of the factors responsible for future energy demand in China, and the results of the various scenarios. The full conclusions of this analysis for policy and investment, however, are presented in the Summary Report for the overall study.' Annexes I and 2 provide additional detail on the macroeconomic conclusions, while Annex 3 provides the detailed assumptions and results of the baseline energy demand scenario. 1 China: Issues and Options in Grwenhouse Gas Enissions Control, Swumary Repo"t, A joint report of UNDP, the State Planning Commission of China, the Chinese National Enviremnental Protection Agency, and the World Bank, Washington, December 1994. 2 2. OVERVIEW OF RECENT DEMAND TRENDS A. ENERGY CONSUMPHON IN 1990 2.1 China is the third largest energy user in the world after the U.S. and Russia. In 1990 total primary energy consumption in China, including traditional biomass fuels, reached 1,245 million tons of coal equivalent (mtce) which was three times as much as in India and five times as much as in Brazil. Total primary commercial energy use was about 961 mtce in 1990. Table 2.1 summarizes China's energy balance in 1990, the last year for which a comprehensive energy balance has been prepared by the State Statistical Bureau. 2.2 China relies on coal for most of its energy use. Coal provides 76 percent of primary commercial energy demand and shares 74 percent of primary commercial energy production. About one-quarter of the coal was used in power generation, while almost all of the remainder was used directly. The massive consumption of coal as a direct fuel in industry and residences is a central and unique aspect of China's energy economy. Coal use accounts for almost 60 percent of industrial energy consumption, and an exceptionally high 79 percent of urban household energy use. 2.3 Another significant feature of energy use in China is the relatively high share of industry in total consumption. Industry accounts for about 65 percent of final commercial energy use; a share similar to that in Hungary or South Korea, which have much higher per capita income levels. Even after taking differences in energy accounting into consideration, energy use in transport amounts to less than 6 percent of final commercial energy use. 2.4 Per capita energy consumption is low but energy use per unit output value is high, reflecting China's status as a low-income developing country with an unusually large industrial sector. Currently per capita energy use in China is about 870 kilograms of coal equivalent (kgce) which is 40 percent of the world's average level. However, energy use per unit gross domestic product (GDP) in China is several times higher than that of the industrialized countries. China's High Energy Intensity per Unit GDP 2.5 Energy use per unit GDP in China is exceptionally high compared with the industrialized countries and many developing countries. It is difficult to measure precisely how the energy intensity of China's economy compares with other countries, due to differences in energy and GDP accounting; internal inconsistencies in the official GDP estimates for China in U.S. dollar terms in various years, for example, mean that energy 3 Table 2.1 Energy balance, 1990 (million tons of coal equivalent) Total Commercial Total Coal Oil Gas /a Power Energy Biomass Energy Primary Energy Production 771.8 197.6 20.3 49.7 1,039.4 284.0 1,323.4 Net trade (13.0) (33.6) - 0.7 (45.9) - (45.9) Change in inventory (31.6) (1) (0.6) 32.2 - (32.2) Total Primary Enerrv Use 727.2 163.4 20.3 50.4 961.3 284.0 1,2453 Power generation (174.8) (17.6) (1.5) 193.8 0.0 - 0.0 Power station and transmission losses - - - (33.8) (33.8) - (33.8) Other conversions and losses (30.6) (11.9) (15.6) - (27.0) - (27.0) Statistical discrepancies 24.7 0.7 0.0 0.0 25.4 - 25.4 Total n and Losses (19.7) (M 14.1 160.0 354) - (35.4} Agriculture 16.7 9.0 0.0 16.7 42.4 - 42.4 Industry 356.7 57.5 28.5 157.2 599.9 - 599.9 Construction 3.4 2.6 1.4 2.5 10.0 - 10.0 Transport/communication 16.5 48.8 0.1 4.2 69.5 - 69.5 Commerce 8.2 0.3 0.1 3.0 11.6 - 11.6 Public sector (non- production) 15.3 11.2 0.3 7.9 34.7 - 34.7 Urban residential 70.4 3.8 4.1 10.7 89.0 - 89.0 Rural residential 59.5 1.4 0.0 8.2 69.0 284.0 353.0 Total Final Energy Consumption 546.5 134,5 34.3 210.4 925.8 284.0 1,209.8 /a Includes both natural and manufactured gas. Excludes liquefied petroleum gas, which is included under oil. Source: World Bank, Energy Conservation Study (1993), adapted from Chinese State Statistical Bureau. intensity comparisons vary substantially depending on the year of calculation. The relatively high position of China's commercial energy intensity, however, is unmistakable. 2.6 The following are some of the most important factors causing China's high energy intensity with respect to GDP. (a) Industrial output accounts for a high share of GDP. Unlike other low- income countries, China has a large industrial base. Industrial value-added contributed 44 percent of GDP in China in 1990, compared with the 29 percent share in India and shares of 10-25 percent in other low-income 4 countries. Even compared with medium-income countries and industrialized countries, industry's share of GDP in China is high (see Table 2.2). Energy use per unit output value of Chinese industry is about ten times as much as that of agriculture. Currently, agriculture, industry and services account for about 5 percent, 70 percent, and 10 percent of the total commercial energy consumption in China, respectively. (b) Residential energy use per unit GDP is high. Residential energy use per unit GDP in China is higher than those of medium-income countries and is even higher than those of some industrialized countries. High residential energy use (including non-commercial fuels) per unit GDP is typical of low-income countries. Per capita residential energy use in China is about half of that in Japan, but residential energy use per unit GDP in China is ten times as much as that in Japan. This disparity contributes about half of the difference in total energy use per unit GDP between China and Japan. Table 2.2 Macroeconomic structure, 1990 (Percent of total GDP) Country Agriculture Industry Services Korea 9.0 45.0 46.0 Japan 3.0 42.0 56.0 China 28.0 44.0 28.0 Upper-middle income 9.0 40.0 51.0 Brazil 10.0 39.0 51.0 Middle-income 12.0 37.0 50.0 Low-income 31.0 36.0 35.0 Mexico 9.0 30.0 61.0 India 31.0 29.0 40.0 Source: World Bank, World Development Report, 1992. (c) The current structure of industrial output value leads to high energy intensity. The energy intensity of China's industrial sector is several times higher than that of most other countries. One key reason is that the industrial product mix is weighted towards relatively low-value goods which are relatively energy-intensive to product for the output value gained. The major difference with most other countries does not stem from any major abnormalities in the share of "heavy" versus "light" industry, or in the relative shares of the major industrial subsectors in total industrial output. Rather, most of the difference stems primarily from the structure of output within the major industrial subsectors of China. The key issues include: (i) less diversity and specialization in the product mix of industry, compared to that in the more mature industrial sectors of developed countries, and hence less "depth" in sources of value-added, (ii) greater 5 dominance of basic, intermediate industrial goods (e.g., ordinary carbon steel or cement), compared with most other countries, and (iii) the low quality of most industrial products, which greatly reduces the value side of the energy intensity equation. (d) The mix of fuels consumed is inferior. The predominance of coal and small shares of oil and gas cause low energy efficiency in residential energy use and in producing industrial processing heat and steam. For example, typical household coal-burning stoves in China only have 20-30 percent effective heat efficiency while kerosene stoves can reach 40 percent and natural gas stoves have 50-60 percent heat efficiency. Coal-burning industrial boilers and furnaces are typically 20 percent less efficient than gas or oil-burning ones. (e) Industrial technologies are backward and management is mediocre. Energy use in the production of major energy-intensive products is some 30-100 percent higher in China than in the developed countries. Outdated and low-efficiency technologies are still widely used. Many industrial enterprises fail to achieve critical economies of scale. Although it is improving, energy management is still poor in many enterprises. Recent Energy Consumption Trends 2.7 Primary commercial energy use grew from 616 mtce to 962 mtce (4.6 percent per year) between 1980 and 1990. GDP more than doubled over the same period, growing at an average rate of 8.9 percent per year in real terms. The energy/GDP growth elasticity during 1981-90 was 0.52, a dramatic break from the elasticity of 1.4 witnessed during the pre-reform years of 1966-80. 2.8 Table 2.3 shows the steady decline in the energy intensity of the economy in recent years. Between 1981 and 1990, energy use per unit of GDP fell by about 30 percent. Energy use per unit of net industrial output fell by roughly the same amount. 2.9 Changes in economic structure and sources of industrial value-added were the most important causes of the decline in energy intensity, accounting for an estimated 55- 65 percent of the total decline in energy intensity over the period. Improvements in physical energy efficiencies accounted for the remaining 35-45 percent. Changes in macroeconomic structure, e.g., the relative shares of agriculture, industry and services in GDP, worked against the trend, as the share of industry increased sharply over the period, causing the decline in energy intensity to be less than it otherwise might have been. Changes in the structure of output between industrial subsectors (e.g., the shares of the metallurgy industry, chemical industry, machine building industry, etc. in industrial output) contributed significantly to the decline in overall energy intensity during the early 1980s, but much less so during the latter 1980s. The most important structural factor behind the energy intensity decline clearly was change in the structure of value-added within the 6 industrial subsectors. This was especially true in the chemicals and machine building 2 industries, where growth in output was very strong. Table 2.3 Energy efficiency indicators, 1980-92 Energy Use per Unit GDP Energy Use per Unit Net (tce/Y'000 Industrial Output Value Year in 1980 Constant Prices) (tce/Y'000 in 1980 Constant Prices) 1980 0.764 1.336 1981 0.721 1.262 1982 0.692 1.211 1983 0.667 1.167 1984 0.625 1.092 1985 0.600 1.048 1986 0.584 1.022 1987 0.564 0.987 1988 0.544 0.952 1989 0.544 0.951 1990 0.532 0.930 1991 0.521 0.911 1992 0.485 0.845 Average 0.603 1.055 Source: China State Statistical Bureau. 2.10 During the ten years from 1981 to 1990, unit energy consumption levels declined for 67 of the 83 key products routinely assessed by the government. Coal consumption per kWh of electricity delivered decreased from 0.448 to 0.427 kgce, a reduction of 4.7 percent. Overall energy consumption per ton of crude oil in oil refining decreased from 129 to 103 kgce, a reduction of 21 percent. Comprehensive energy consumption per ton of crude steel decreased by about 21 percent. Electricity consumption per ton of electrolysis aluminum decreased from 20,342 to 16,223 kWh, a reduction of 20 percent. Fuel consumption per ton of cement clinker decreased from 207 to 185 kgce, a reduction of 10 percent. Overall energy consumption per ton of synthetic ammonia produced by small enterprises decreased from 3.0 to 2.3 tce, a reduction of 25 percent. Comprehensive energy consumption by railway engines decreased from 14.7 to 8.4 kgce per thousand ton- kilometer, a reduction of 42.9 percent. 2.11 The decline in energy intensity slowed somewhat during 1989 and 1990, with the temporary overall slowdown in China's economic growth. With the 1991-1993 boom in the economy and further reform in the economic system, however, the energy intensity of China's economy has continued to fall sharply--even more sharply than during the 1980s. During 1991-93, China's energy/GDP growth elasticity fell to under 0.4. Coal demand, in 2 See The World Bank, China: Energy Conservation Study, February 1993. 7 particular, has grown far more slowly than growth in the economy as a whole, and industry in particular. The shift to market-based coal prices is believed to have been one important factor, but it also is clear that changes in the structure of industrial value-added, spurred on through steady economic reform, has continued to be a driving force. 8 3. MACROECONOMIC MODELING AND ANALYSIS A. ORIEcTIvE 3.1 The China Greenhouse Gas (GHG) Model was constructed specifically for this project for the purpose of assessing the relationship between economic growth and greenhouse gas emissions in China. Because the majority of China's GHG emissions come from energy consumption (an estimated 82 percent in 1990), a major focus of the study is to estimate the amount of energy needed by the Chinese economy under various scenarios. The time period of interest is the coming 2-3 decades, since there is likely to be a large addition to China's capital stock during this period as a result of economic growth. In addition to growth of the economy and the consequent investment in new capital equipment, other factors that were presumed to have a large effect on GHG emissions and were therefore evaluated within the model include: (i) the structure of the economy, (ii) the energy efficiency of various sectors, particularly industry, and (iii) the mix of fuels (including renewables). 3.2 As noted in the introduction, the estimates of future energy use and GHG emissions that are generated by the China GHG Model are not projections or expected outcomes but rather, scenarios. As with most macroeconomic modeling, the primary objective is the identification of the key variables related to a specific outcome and the analysis of effective macroeconomic policy measures. In this case, the objective was to identify the key variables affecting GHG emissions in China under various scenarios, and to assess what measures could be taken to limit GHG emissions. B. BACKGROUND AND STRUCTURE OF THE MODEL 3.3 The China GHG Model combines a macroeconomic regresssion model with an IS- sector input-output (I-0) table of the Chinese economy. The macro model "drives" the model by estimating the demand for goods and services. The technical efficiency of the economy is reflected in the I-0 coefficients. GHG emissions from energy production and consumption are calculated by sector and by fuel from the input-output table as are the non-energy related GHG emissions, including CO2 from cement manufacture, methane from rice fields, and methane from ruminant animals. Increases in the share of non-carbon fuels in the economy is handled by changes in fuel mix of the energy sectors and by changes in the emission coefficients.3 The model can be used to estimate total savings and 3 A more detailed analysis of alternative fuels was done in a separate altenative energy model. See Subreport Number 5, Alternative Energy Supply Options to Substitute for Carbon Intensive Fuels, December 1994. 9 investment required for different scenarios, but unfortunately cannot be used to calculate the amount of investment needed under different strategies to reduce GHG emissions.' 3.4 The key components of the model are shown in Figure 3.1. Figure 3.1 Schematic of the China GHG Model mom, > GHG Tabletm EIIisSions 3.5 Most of the energy demand modeling work done in China in recent years has not provided a detailed description of sectoral energy use, nor has a consistent macroeconomic framework been used--such as the role of the money supply, aggregate savings, or foreign exchange reserves. A key variable used in some of these models is the energy-output ratios for individual sectors (such as transportation and industry) and for the economy as a whole.' While energy-output ratios are indeed important in determining total energy use and GHG emissions, the adjustment of these ratios without an accompanying description of the final demand for commodities by sector, the specific new energy-efficiency technologies employed, and the accompanying monetary requirements, can be viewed as rather arbitrary. To avoid these criticisms, the China GHG Model was designed to provide both a macroeconomic (top-down) and microeconomic (bottom-up) perspective. The China Macroeconomic Model 3.6 The macroeconomic model used for this study was originally built under a collaborative project begun in the early 1980s between Stanford University, the University of Pennsylvania, and the Chinese Academy of Social Sciences. The China macro model is econometric, consisting of roughly 250 equations, 140 of which are regression equations based on Chinese economic and social statistics (1965-1992). Together, the equations describe the Chinese economy, such as the production of goods, population and labor 4While the estimation of capital requirements was originally planned to be included in the analysis, this required data in input-output form on capital capacity. The so-called "B-Matrix," which shows the amount of inputs required to build an additional unit of production capacity, was ultimately not able to be compiled due to a lack of data. 3 See for instance, He Jiankun, et. al. (1991). Long-term forecast of energy demand and supply of China. China Forecasts, Vol. 1, No. 1, 1991, and Wu, Siddiqi, and Street (1993). especially chapters 3 and 4. 10 force, income determination, consumption, capital formation, public finance, money and banking, prices, international trade, and balance of payments.' 3.7 The two primary functions of the macro model for this study are (i) to project final demand (Y)--the demand for goods and services, investment, government expenditures, and net exports--in China over the coming two-and-a-half decades, and (ii) to provide an internally-consistent picture of China's macroeconomy based on historical trends, including the monetary situation, international trade, and the effect of relative price changes. 3.8 Several modifications of the China Macroeconomic Model were made for its use in the China GHG Study. The heavy industry sector was disaggregated into non-energy and energy sectors, with the latter including coal, oil, natural gas, and electric power. In addition, energy (E) was added to capital (K) and labor (L) as an additional factor of production in the production function equations for each sector. Using 1990 as the base year, bridge equations were estimated for two other GHG emissions: methane from rice and from ruminant animals. Rice and livestock production for future years were estimated as a function of the gross value of agricultural production. Finally, bridge equations were built linking the China Macro Model with an input-output table of China. Input-output analysis 3.9 An input-output (1-0) table represents the structure of the economy and the efficiency with which goods and services are produced. The 1-0 coefficients, referred to as the "A" matrix, represent the inputs required from each sector to produce a unit of output. (Table 3.1) For example, to produce a unit of steel may require inputs from the coal, heavy machinery, and metallurgy sectors. Table 3.1 An in ut-output table Intermediate Final Demands Gross Output Products 1 2... n C I X-M Total Sector 1 Intermediate 2 X4 ("A" Yi Inputs ... matrix) n Primary Deprec. D Inputs Wages V I Tax/Profit M Total Input Xi Emissions ]E Ho - 6 A complete list of the equations (version 9406) can be obtained from the authors: Professor Lawrence J. Lau, Economics Department, Stanford University and Jiang Zhongxiao, Institute of Quantitative and Technical Economics, Chinese Academy of Social Sciences, Beijing. 11 1. X + = X,i j=1 2. ±X +DJ +V +MJ = Xj 3. X, / Xi = aj technical coefficients 4. aX, +Y = Xi j=1 5. AX+Y= X=> X- AX = Y=> (I- A)X= Y 6. X=(I-A)'Y 3.10 Once equation (6) is obtained, it is possible to determine the total inputs (X) required by the economy-such as labor, energy, steel and cement-to produce a given mix of final demands (Y). For a given GDP growth rate, 1-0 analysis can be used to determine the requirements for inputs, such as energy and capital capacity. Once the 1-0 table is constructed, it is also fairly straightforward to see which inputs are placing constraints on the economy or which sectors need to expand their output and/or capital capacity to meet a given level of production. 3.11 For this study, China's 1987 input-output table was aggregated into 18 sectors (14 material, 4 non-material) and updated to the base year 1990 using both the 1987 and 1981 Chinese 1-0 tables.7 While theoretically all 117 sectors of China's 1987 input-output table could have been used in the model, this would have required estimating final demands (Y) for 117 sectors. It was necessary to reduce the number of sectors in the input-output table to a number small enough to be estimated by the China Macroeconomic Model. A list of the 18 sectors is provided in Table 3.2, with the classification of subsectors given in Annex 1. 3.12 To use 1-0 analysis for future projections, it is necessary to estimate how the 1-0 coefficients change over time. I-0 coefficients for China were projected to the years 2000, 2010, and 2020 using Chinese historical 1-0 tables, cross-sectoral analyses of Chinese provincial 1-0 tables, and by reviewing historical changes in 1-0 coefficients for other countries. China's 1981 and 1987 input-output tables were reconstructed to 18 sectors and converted to 1990 constant prices; the base year 1990 (in current prices) was also constructed. Seven regional input-output tables (1987) representing provinces at 7 The input-output work was caMed out under the direction of Professor Chen Xikang, Institute of Systems Science of the Chinese Academy of Sciences. Professor Chen is a leading expert in the field of input-output analysis and was responsible for building Chinas national input-output tables during the 1970s. He presently forecasts economic indicators for China, such as national grain production, using WO analysis The original table was from 1987 Zhongguo Tourn Chanchu Biao (1987 Input-Output Table of China), Beijing: China Statistical Publishing House. 12 different stages of economic development were also aggregated into 18 sectors and analyzed. The 1-0 tables covered developed provinces (Guangdong, Beijing, Shanghai), average provinces (Henan and Shaanxi), and less developed provinces (Ningxia and Inner Mongolia). Japan was used as the primary example of how I-0 coefficients change over time as an economy develops. Input-output tables for Japan were collected and reconstructed for the years 1965, 1970, 1975, 1980 and 1985. For important energy- consuming sectors, the changes in input-output coefficients over time for other developed countries were also observed. Such information was taken from input-output tables for West Germany (1965, 1970, 1975), the US (1939, 1947, 1958), and the UK (1965, 1970, 1975). Table 3.2 Sectors in the China GHG Model Sector # Name Codes * 1 Agriculture 01 2 Coal 02+13 3 Petroleum 031+12 4 Natural Gas 032 5 Electric Power 11 6 Ferrous Metals 041+161 7 Non-Ferrous Metals 041+162 8 Chemical Fertilizer 14102 9 Heavy Chemicals 14101+14103+14104+14106+14401+14501 10 Cement 15001+15002 11 Other Building Materials 051+15003+15004+15005+15005+15006+15009 12 Heavy Machinery & Electronics (17-17002)+(18-18005)+19+(20-20002)+ (21-21002) 13 Light Industry 052+053+054+06+07+08+09+10+14105+ 14109+14200+14300+14402+14502+17002+ 18005+20002+21002+24002 14 Construction 25 15 Cargo Transport and Posts 26 /Communications 16 Commerce 27+28 17 Passenger Transport 29 18 Other Services 30+31+32+33 * See Annex 1 for a list of codes and subsectors. Emissions 3.13 Global Pollutants. The China GHG Model generates emissions matrices of both global and local air pollutants for each level of economic output. The primary GHG estimated by the model is CO2 from energy consumption. The model assumes that the percentage of carbon oxidized for each fuel is the same in all fuel combustion applications; thus, once the quantity of energy consumed is determined, the amount of CO2 emitted can 13 be readily calculated. In addition to CO2 from energy consumption, the model also estimates CO2 emissions from cement, and CH4 emissions from rice fields, coal mining, and animal husbandry. Together, the sources of GHGs estimated in the model account for approximately 98 percent of China's total GHG emissions in 1990. Forestry emissions/sequestration are generated "off-line" in a separate forestry model.' 3.14 CO2 from energy use is calculated for each sector directly from fuel consumption. For the base year (1990), the 1-0 coefficients are in value terms (yuan/yuan) and there is a corresponding row in physical terms for the energy commodities (coal, oil, gas, electricity). Although future coefficients are expressed in value terms, physical units are obtained by assuming the same proportions as in 1990; all values are in 1990 constant prices. The changing quality of fuels in each sector is captured in the emissions matrix coefficients. For example, a growing percentage of cleaned or processed coal used by the steel industry means that the industry consumes less coal in coal equivalent terms. Table 3.3 CO2 (CH4) emission matrix "A" Matrix Final Dem ads (* Sector 1 2 3 ... 18 C, C, Ct Coal C02/ton C Oil C02/ton 0 Gas C02/cm G Electricity C02/kWh E % Coal % % Oil % % Gas % % Electricity % Direct Non-energy Emissions** C02/X * Final Consumption Demand = C = C. + C, + C,, where: C.= consumption by urban households C, = consumption by rural households Ci = consumption by government departments. ** Includes direct emissions of CO2 from cement, and CI4 from agriculture and the energy sector. 3.15 There are four pollutant rows in the 1-0 table: two for greenhouse gases (CO2 and CH4), and two for local pollutants (SO2 and TSP). To compute total emissions for each sector, a matrix is constructed for each pollutant with emissions directly related to the quantity and type of fuel consumed by that sector. The fuel-specific emission coefficient for each sector contains the carbon content of the fuel. For example, the oil coefficient for each sector is computed based on the relative amount of petroleum products consumed by SSee Johnson et al. (1994). 14 the sector, such as gasoline, diesel, fuel oil, or crude. To compute the total emissions of each sector it is also necessary to know the percentage of the fuel to total energy use by the sector. Multiplying these two numbers will result in the total emissions for each sector. An example of the emission matrix for CO2 is given in Table 3.3 which shows emissions from each sector (from A matrix) and from final demand (H matrix). Total GHG emissions are the sum of the two matrices. In addition to the base year (1990), emission matrices are constructed for the year 2000, 2010, and 2020. 3.16 Local Emissions. Particulate levels in many parts of China exceed the recommended limits of the World Health Organization (WHO) during much of the year. TSP concentrations are most severe in northern China in the winter, when households burn coal for space heating. The highest SO2 concentrations in China are in Sichuan (Chengdu and Chongqing) and Guizhou Provinces, due primarily to the high sulfur content of local coals. A particularly severe sulfur problem exists in Chongqinq, which has some of the highest concentrations in the world, due to a variety of factors: the use of high-sulfur coal with little washing or post-combustion treatment, the concentration of industry, and, geographic features that inhibit atmospheric dispersion. 3.17 China currently collects statistics on total suspended particulates (TSP) and sulfur dioxide (SO2) concentrations for all provinces and for 82 major cities. Statistics on other pollutants, such as NOx, CO, NMHC, and 03, are not consistently collected nationwide and are generally available only for the largest cities. Local pollutants estimated by the model include TSP and SO2 only. For local pollutants, emission factors were estimated for each of the 18 sectors based on the average ash and sulfur content in the fuel consumed by that sector, and on the emission rate and current level of control within that sector.9 3.18 Local emissions are calculated by the China GHG Model in a manner similar to global emissions (Table 3.4). Total local emissions can thus be expressed as the sum of two matrices, representing emissions from energy use, and emissions from final consumption: Local Emissions = Ei+ H 3.19 Emission coefficients used in the model are computed for each sector, based on the type and quantity on fuel consumed. For instance, the local emission coefficient for the steel industry depends on the quantity of coal, oil and other fuels consumed, the average quality of these fuels for the steel sector, and the degree to which post-combustion gases are treated to remove SO2 and TSP. Over time, the SO2 and TSP emission coefficients for each industry can be adjusted to account for changes in (i) the average quality of each fuel consumed, and (ii) for the addition of new combustion or flue-gas treatment technologies. ' The sectoral emission coefficients for 1990 were estimated by Chinese energy and environmental specialists from line ministries and were reviewed and modified by experts from the National Environmental Protection Agency. Given the mandate of this project to look at global pollutants, the current version of the China GHG Model does not take into account improvements in TSP and SO2 control by new equipment or the adoption of specific control devices for TSP or SO2. As such, the emission levels of SO2 and TSP for future years can be regarded as a worst-cm scenario. These deficiencies are expected to be corrected in later versions of the model. 15 3.20 There are two shortcomings of the current China GHG Model in dealing with local pollutants. While it is known that damages are related to atmospheric concentrations and to exposure, the model calculates only emissions. Although the conversion of emissions to atmospheric concentrations is a complicated process, a simplified methodology has been used in another component of the overall China GHG Study for assessing the benefits of local pollution reduction.o A second, and perhaps more serious problem, is that the emission coefficients in the model were only calculated for the base year, 1990. Given uncertainty and resource constraints, it was not possible to estimate emission coefficients for future years, even though it is clear that new technologies will be installed in many sectors (e.g. particulate control in power stations) and that this trend will continue to lower the emission coefficients. It should be stressed, therefore, that the future estimates of S02 and TSP generated by the China GHG Model are not necessarily realistic, and reflect only what would happen if there were no change in fuel quality and technologies from 1990 (see footnote 8). Table 3.4 SO2 (TSP) emission matrix "A" Matrix Final Deman s (H) Sector 1 2 ... 18 C. C c, Coal S02/ton Coal Oil S02/ton Oil Gas S02/cm Gas Electricity S02/kWh E Coal/total % Oil/total % Gas/total % Electricity/total % Direct Non-energy Emissions S02/X _ _ * Final Consumption Demand = C = C. + C, + C., where: C.= consumption by urban households C, = consumption by rural households C,= consumption by government departments. ** Includes direct emissions of S02 from industrial use. 'o See Subreport Number 7, Valuing the Health Effects ofAirPollution: Application to Industrial Enericeny Projects in China, October 1994. 16 C. KEY MODELING AsSnwPTIONS Population 3.21 China is the most populous country in the world and the population will continue to grow for the coming three decades, albeit at slower rates than for most developing countries. The China GHG Model assumes that China's population will reach 1.45 billion by the year 2020 (Table 3.5). The population growth rates used in the model are 1.1 percent, 0.8 percent and 0.6 percent for the decades 1991-2000, 2001-2010 and 2011- 2020, respectively. Given the lack of arable land and other scarce resources, China's large population will pose difficulties for food production and the provision of other goods and services. It is therefore imperative that the country's family planning policy be continued; this assumption has been used in the population projections." 3.22 Age Structure. China has a relatively young population. In 1990, about 6 percent of total population was 65 and older. The percentage of this cohort in the total population increases to about 12 percent in 2020 according to estimates by the United Nations, a level similar to that of Japan and the U.S. in 1990. In 1990, the percentage of China's labor force in the total population was 61 percent; within the China GHG Model, this percentage rises to 66 percent, 71 percent, and 74 percent in the years 2000, 2010 and 2020, respectively. This trend is a result of both the current population distribution and the assumption that China's birth control policy continues. 3.23 Urbanization. As China's economy grows, urbanization will be accelerated. The model assumes that the percentage of urban residents rises from 26 percent in 1990, to 31 percent, 37 percent and 42 percent in 2000, 2010 and 2020, respectively. If China's household registration system, which has placed limits on urban migration, were completely abandoned, the pace of urbanization in China could be faster than assumed in the model. Table 3.5 Population projections 1990 2000 2010 2020 Population (million) 1,140 1,280 1,370 1,450 Growth rate (%/yr) 1.1 0.8 0.6 Labor force ratio (%) 61 66 71 74 Urban resident ratio (%) 26 31 37 42 Source: China Statistical Yearbook, 1993; GHG group estimates " The population growth rate assumptions used in the model are fairly conservative, and are below the figures used in the most recent World Bank report, World Development Report. 17 Economic growth 3.24 From 1978 to 1990, the average annual GDP growth rate in China was 9 percent. In the early 1990s, the economic growth rate accelerated. GDP grew 8 percent in 1991, 13.2 percent in 1992, and 13.4 percent in 1993; the average annual growth rate for the three years was 11.5 percent. Although China's economy may not sustain the 10 percent annual growth rate for the remainder of the decade, even moderate growth of 8 percent per annum will result in an average growth rate for 1990s above 9 percent. 3.25 Average growth in excess of 8 percent per year over several decades is not unprecedented among East Asian economies. Korea's economy grew at approximately 10 percent per year between 1965 and 1990, while economic output in Taiwan increased nearly 9 percent per year between 1951 and 1991. The Japanese economy grew an average of 8.7 percent between 1946 and 1976, and its annual GDP growth was in excess of 10 percent between 1950 and 1970. 3.26 There are a number of factors specific to China's economy that are conducive to high growth in the coming decades. The economic reform program, which is likely to continue and deepen, will create new opportunities and incentives for expansion of the domestic market and international trade. According to the China Macro Model, the economic reform program initiated by China in 1978 raised the GDP growth rate in China by 1.5-2 percent per year between 1979 and 1993. 3.27 China's high savings rate, which has increased since the 1980s, is essential for providing investment funds to continue the economic expansion. It is assumed that the ratio of capital formation to GDP in China will follow that of its Asian neighbors. Without exception, the savings rate of Japan and the other fast-growing economies of Asia were all relatively high during their growth period, at times surpassing 40 percent. Though relatively poor, China's saving rate is already very high; in 1990 it was over 30 percent. It is assumed that China's savings and investment rate will average 36 percent during the 1990s, increasing to 37-40 percent from 2000-2010, before slowing to 35 percent from 2010-2020. The reform of housing, health care, retirement, education, and other social programs as a result of China's economic reform program will also require that Chinese citizens save more. 3.28 As noted above, the age structure of China's population is very young. Japan, Korea, and Singapore all had similar population age structures during their economic booms. Compared to industrialized countries' 24 percent, less than 12 percent of China's population is over 65 year of age from now until 2030, which is similar to Japan from 1950-1970. A young population means an ample supply of workers and relatively few retirees for the active workforce to support. There are currently 100-200 million surplus labors in rural China that will provide a relatively low-cost pool of workers for the industrial and services sectors. 3.29 The sheer size of China's economy represents an almost limitless market for goods and services. By conservative estimates, China will have a over 4 trillion dollars (1990) of purchasing power by 2020, the second largest in the world. Therefore, unlike other 18 developing nations of Asia, domestic demand will be important for sustaining China's development and the country will not be as dependent on the growth of other economies. Nevertheless, export-led growth has been important to China over the past decade and will continue to be beneficial during the current phase of development. 3.30 The growth rate of the economy is assumed to decline in next century, especially after 2010. The reasons are that: (i) industrial growth falls off; (ii) the supply of energy and other raw materials becomes a constraint; (iii) the incremental capital output ratio (ICOR) increases; and (iv) the high savings rate gradually declines. D. KEY RESULTS Baseline Scenario 3.31 The baseline scenario assumes that China is able to sustain rapid economic growth over the long term, driven, in particular, by continued high savings rates and the strength of the country's domestic market. GDP is assumed to grow by 9.5 percent during 1991- 2000, 8.0 percent during 2001-2010, and 6.5 percent during 2011-2020. The average growth over the three decades is 8 percent. 3.32 Under the baseline scenario, total GDP in China reaches 17.8 trillion yuan in constant 1990 prices by the year 2020 (3.8 trillion US$), or roughly ten times the level in 1990. This is about 1.4 times the size of Japan's economy and nearly three-quarters the size of the U.S. economy in 1990. Per capita GDP reaches USS 2,600 (in 1990 dollars) by 2020 (details are provided in Annex 2). Table 3.6 GDP per capita of China, US$ Year 1990 2000 2010 2020 Method 1990 Exchange Rate 330 734 1,469 2,608 Economic Structure 3.33 Structure of consumption. At a per capita income of $2,600, material goods will dominate household consumption in China. The model predicts that by the year 2020, the share of agricultural products (grain, vegetables, meat, and fish) in final demand will fall for household consumers while the share of services (public utilities, health care, education, housing rental) will increase. The share of light industrial products as a share of total consumption will remain roughly the same between 1990 and 2020. 19 Table 3.7 Structure of consumption: share of household expenditures 1990 2000 2010 2020 Agricultural products 34% 21% 15% 11% Light industrial products 40% 45% 41% 37% Services 14% 21% 29% 35% Source: China GHG Model, joint study team. 3.34 Although the China GHG Model cannot provide details on the consumption of specific commodities, it is likely that the composition of light industrial products would shift away from basic clothing and processed foodstuffs toward more high-quality consumer goods. If the distribution of income in 2020 remains roughly the same as in 1990, some upper-income households will be able to afford automobiles and a range of high-valued services. However, at a per capita income of less than $3,000 (constant 1990), the consumption basket of the average Chinese household will still be composed largely of material goods such as household appliances (refrigerators, washing machines, air conditioners) and housewares (furniture, carpeting). 3.35 Structure of the macroeconomy. The structure of China's economy in 2020 will be largely determined by the pattern of household consumption. As shown in Figure 3.2, little change is expected in the share of heavy and light industry in total economic output over the next three decades. Industrial growth must remain strong for China to satisfy the demand for light industrial products by household consumers, for construction, and for heavy industrial producer goods for the manufacturing sector itself. The share of the tertiary or services sector, however, is expected to increase sharply, largely offsetting a fall in agriculture's contribution to GDP. The overall effect of this macroeconomic structural change on GHG emissions is not large, because neither agriculture nor services are relatively energy-intensive sectors. 3.36 The major sectoral conclusions from the model are the following: (a) Agriculture will grow rather slowly, due to the declining potential for further agricultural productivity gains. (b) The tertiary or services sector will grow the fastest, ahead of both agriculture and industry. China's tertiary sector grew very slowly over the past forty years. In 1990, the share of the services sector in China was below all of the high- and middle-income economies, but also as much as 20 percent lower than other low-income economies. (c) The industrial sector will remain the largest contributor to GDP growth in 1990s. Unlike in the 1980s, however, heavy industry will grow faster than light industry because: (i) investment demand, consisting mainly of construction and machinery equipment, will grow faster than GDP, and therefore, more capital goods are needed; (ii) with improvements in living 20 standards, light industrial products (such as household appliances) which require heavy industrial materials, will increase as a share of consumption; and (iii) the capital/labor ratio will increase as the Chinese economy develops, so that more heavy industrial products are needed. FIgure 3.2 Macroeconomic structural change 50% 45% 40% 35% 0 1990 30% 2000 25% U 2010 20% 15% I F 02020 15% 10% 5 %I Source: China GHG Model, joint study team Slower Growth Scenario 3.37 Whether caused by government policy or market forces, slower economic growth results in somewhat lower energy consumption and GHG emissions. Under the slower growth case, China's economy is assumed to grow 1 percent slower during the 1990s than under the high growth case and 1.5 percent slower for the decades between 2000 and 2020. Accordingly, GDP growth is 8.0 percent per year during 1991-2000, 6.5 percent during 2001-2010, and 5 percent during 2011-2020. Total GDP under the slower growth case reaches only US$2.5 trillion by the year 2020, while per capita income in 2020 only attains US$1,760. While total GDP is over 30 percent less in 2020 compared to the high growth case, GHG emissions from energy consumption under the slower growth case are reduced by about 14 percent. When the economy grows more slowly, the transformation of the economy proceeds at a slower pace, and there is less capital investment in newer, more efficient plants and equipment. 21 Statistical Data 3.38 A portion of the macroeconomic modeling results are presented in Annex 2. Included are the input-output coefficients for the three scenarios-baseline, high efficiency, and slower growth--for the years 2000, 2010, and 2020. Also appended are tables of physical energy demand scenarios that were used to calculate local emissions-TSP and S02-and the physical output of variables such as cement, livestock, and rice used to calculate the non-CO2 GHG emissions. Local emission scenarios are presented. Total GHG emissions and CO2 emissions are dealt with elsewhere2 and are not presented here. '2 See the Summary Report (Johnson et al., 1994). 22 4. DEVELOPMENT OF FUTURE ENERGY DEMAND SCENARIOS 4.1 This chapter outlines the methodology used for preparing the energy demand scenarios for 2000, 2010, and 2020, and summarizes the assumptions used in preparing the detailed unit energy consumption coefficients for each of the 18 subsectors of the input-output table. A. METHODOLOGICAL OVERVIEW 4.2 A bottom-up, subsector-by-subsector approach was used to develop future energy demand scenarios. As described in the previous chapter, internally consistent projections of net output value for 18 subsectors were obtained from the macro model. The input- output coefficients were estimated based on a review of past trends in China, trends in other countries, and discussions with industry experts (see paras. 3.11 - 3.12). Given their importance for GHG emissions, special attention was given to the energy coefficients. The energy coefficients in the input-output tables were estimated for each of the 18 sectors in terms of tce per million 1990 constant yuan of net output value. Coefficients were prepared for coal, oil, gas, and electric power use for the years 2000, 2010, and 2020. Separate matrices of coefficients were prepared for the various scenarios: "baseline," "slower growth," "high efficiency," and "no further change." Residential energy use was projected separately, based on a review of population, standard of living, and heating and household appliance efficiency trends. 4.3 Coefficients for the major subsectors were prepared by further breaking down the subsectors into different components. Where requisite data on both unit energy consumption and output value were available, estimates of future energy demand for energy-intensive industrial commodities were first prepared in physical terms (e.g., energy per ton of output), and then converted to energy use per unit output value coefficients. Energy-intensive commodities projected in this fashion accounted for nearly 80 percent of total industrial energy consumption in China (1990). For a number of key energy- intensive commodities (e.g., steel, cement, nitrogen fertilizers, thermal power, among others), energy use coefficients were prepared by projecting relative shares of future production in different processes or scale of plant, projecting energy use per physical unit of output for each process or plant type, and then calculating industry averages. Where requisite data on either energy use or output value was not available to prepare estimates in physical terms, estimates were prepared only in terms of energy use per unit of output value. Annex 3 provides the detailed calculations for each of the subsectors for the baseline scenario as well as overview energy demand tables for all scenarios. 23 B. SUBSECTOR ENERGY DEMAND COEFFICIENTS 4.4 This section provides a general overview of the assumptions used in developing energy demand coefficients for the 18 subsectors of the macro model. Unless otherwise noted, assumptions refer to the baseline scenario. Agriculture (1) 4.5 Agriculture is a vital economic sector for meeting the demand of food and clothing of China's huge population. Yields of grain and cotton need to increase in order to accommodate population growth. Due to the scarcity of arable land and other natural resources in China, future increases in the production of food and other agricultural goods must depend largely on productivity improvements, which, among other things, will require more energy. In the past decades, energy use in agriculture has increased steadily. It is assumed that further increases in energy use are required, but that the energy intensity--energy use per unit of output value--of agricultural production gradually declines, from 66 tce per million yuan in 1990 to 53 tce per million yuan in 2020, largely because of increases in the value of the overall agricultural product mix. The energy demand elasticity of the agricultural sector is assumed to be 0.8. Agriculture's share of energy use decreases from about 4.9 percent in 1990 to about 3.7 percent in 2020, although total agricultural energy demand continues to increase. The incremental energy use is mainly for meeting the demand for petroleum products for tractors and fishing boats, electricity for irrigation and food processing, and coal and natural gas for animal husbandry and intensive hothouse vegetable and fruit production. Coal Mining (2) 4.6 By the year 2020, coal still accounts for more than 60 percent of China's primary energy supply and provides fuel for 76 percent of the total power generation in the baseline scenario. Output of coal continues to increase from 1.1 billion tons in 1990 to about 2.5 or 3.1 billion tons in 2020 depending on the scenario. Since the level of mechanization is low in China's coal mines, mining energy intensity, especially electricity intensity, is also low (Table 4.1). 24 Table 4.1 China: Electricity use per ton of coal produced (kWh/t) National state-owned coal mines 44 Local state-owned coal mines 25 Township & village coal mines 2 Average 30 Former USSR 55.5 West Germany 100.6 Japan 85.9 4.7 Electricity intensity is expected to increase as coal mines increase their mechanization level and as mines get deeper. It is assumed that the average power use per ton of coal mined increases from 30 kWh in 1990 to 55 kWh in 2020, roughly matching the level in the former USSR. 4.8 Coal consumption by national state-owned coal mines is very high in China and thus reduces the amount of coal available for sale. Given the potential to reduce internal coal use, little increase in the overall energy intensity of coal mining in the national mines is anticipated, even with the increase in unit electricity consumption. The overall energy intensity of coal production in local state-owned and township and village coal mines are assumed to increase significantly, from 34 kgce/t in 1990 to 45 kgce/t in 2020 for local state-owned mines, and from 19 kgce/t in 1990 to 27 kgce/t in 2020 for township and village mines. The share of large coal mines in total output increases from 43 percent in 1985 to 65 percent in 2020. Accordingly, the national average coal mining energy intensity increases from 35 kgce/t in 1990 to 43 kgce/t in 2020. 4.9 The quality of coal supply is expected to improve due to large increases in the share of beneficiated coal in total output. The unit output value of coal supplied to the market is therefore expected to increase substantially. As a result, energy use per unit of output value in the coal mining industry is expected to decline. The Petroleum Industry (3) 4.10 Energy use in the petroleum industry accounted for about 3 percent of total energy use in 1990. There may be little opportunity to decrease energy use per ton of output in oil extraction and refining because of the increasingly marginal nature of reserves and more complicated processing in the oil refining sector. However, increasing sophistication in oil refining will mean a larger share of light products, which will increase the output value of oil products. Thus, it is assumed that energy use per unit output value in the petroleum sector increases only moderately, from 356 tce/million yuan in 1990 to 417 tce/million yuan in 2020. 25 The Natural Gas Industry (4) 4.11 The baseline scenario assumes that China successfully discovers major new reserves of natural gas, enabling an increase in production of about seven-fold between 1990 and 2020. Given the conjectural nature of this estimate, lack of detailed data on energy use in this industry, and the fact that energy use in the gas industry is relatively small, energy use per unit of output value was assumed to follow the same trend as the oil industry. The Electric Power Industry (5) 4.12 Improvements in the efficiency of thermal power generation can have a critical impact on the overall energy demand level in China in the future. The electric power sector is the fastest growing segment of the energy industry. In 1990, generation totaled 621 TWh, and installed capacity reached 138 GW. Thermal power plants make up about 74 percent of the total installed capacity and contribute about 80 percent of the total electricity generation. Coal used for thermal power generation accounted for about 23 percent of the country's total coal consumption in 1990. The average heat rate in thermal power generation was 395 gce/kWh, an efficiency of 31 percent. 4.13 In the electricity consumption forecast of the baseline scenario, derived from the subsector-by-subsector estimates, electricity generation reaches 3,844 TWh by 2020. Thermal power generation is assumed to meet about 71 percent of power demand. Even with efficiency gains, thermal power production accounts for 42 percent of China's coal use in 2020 in the baseline scenario. The average heat rate is estimated to drop to 323 gce/kWh, an efficiency of 38 percent. This efficiency gain, if it can be achieved, results in an annual coal savings of some 390 million tons by the year 2020. 4.14 The most important means to improve efficiency in thermal power generation in China is to increase the average scale of generating facilities. In 1990, only 14.8 percent of thermal power generating capacity was in large-size units ( 250 MW and above), while 31.6 percent was in medium-size units (100 MW to 250 MW but not including 250 MW), and 53.6 percent was in small-size units (below 100 MW). Table 4.2 Fuel consumption per unit of electricity production (ce/kWh) Large size 345 gce Medium size 375 gce Small size 421.5 gce Average 395.3 gce 4.15 In the baseline case, 71 percent of total thermal power capacity is assumed to be in large units, while 22 percent is in medium-sized units and 6 percent in small units. Substantial gains in the efficiency of generation in each size category through adoption of more advanced technology also are important. In the baseline case, fuel use per kWh of 26 thermal electricity generation falls to 310 gce in large plants, 350 gce in medium-sized plants, and 370 gce in small plants. 4.16 Only very modest further improvements are assumed in the high efficiency case. Heat rates follow the assumptions for the baseline case, however, there is a growing contribution of power from large-scale plants. The share of large plants in 2020 does not exceed 75 percent, as it is assumed that at least some small and medium-sized plants will continue to be constructed during the 1990s, and will remain serviceable. The average heat rate in 2020 under the high efficiency case is estimated at 321 gce/kWh. Ferrous Metals (6) 4.17 The ferrous metal industry includes enterprises involved in mining, metal smelting, and casting and rolling processes for the production of iron and steel products. In 1990, total energy used in iron and steel production was about 107 million tce, accounting for about 11 percent of the total commercial energy use in China, or 16.5 percent of total industrial energy use. 4.18 Increasing steel output has been a top priority in China's industrial development strategy for decades. In 1993, the total output of steel reached 88.7 million tons. Per capita steel consumption in China is currently about 90 kilograms, higher than other low- income developing countries, such as India, and similar to levels in middle-income developing countries, such as Brazil and Mexico. If the production of steel were to increase proportional to GDP, total steel output would reach about 700 mt by 2020 under the baseline GDP scenario, higher than total world steel production in 1990. If all production was consumed domestically, per capita steel consumption would be 500 kg by 2020, 4 times as much as the world average in 1990 and higher than levels in most industrialized countries in 1990. This is considered implausible and unnecessary, given the vast potential for reducing steel use through industrial restructuring and through the use of higher valued substitutes. Steel output in 2020 is assumed to be in the range of 200 to 220 million tons. 4.19 Compared with other major steel producers in the world, the energy intensity of iron and steel production is high in China, as shown in the following table. Table 4.3 Energy use per ton of steel production (kgce/ton) Large Plants 1,200 Medium Plants 1,440 Small Plants 2,000 National Average 1,330 Japan 629 USA 757 USSR 809 Germany 680 27 4.20 Statistics in China often report a comprehensive energy consumption level per ton of steel produced, which inflates the real energy consumption used for making steel because it also includes household energy use of plant employees and energy use in non- steel-making-related activities such as the production of plant and equipment. The energy intensity figures listed in Table 4.3 above have been adjusted to correct for such factors. 4.21 As in the thermal power industry, plant scale is critical for improving energy efficiency and the adoption of advanced technology. As shown in Table 4.4, a substantial portion of China's steel industry remained in medium- and small-sized plants in 1990. Even in the large-scale category, much of China's capacity remains below optimal scale. Table 4.4 Steel industry output and energy use by plant size Share of Output Energy Use (percent) (kgce/ton-steel) Large Plants 68.41 1,200 Medium Plants 22.50 1,440 Small Plants 9.09 2000 Total Industry 100.00 1330 4.22 Since the life of steel plants is long and upgrading technologies and processes is usually difficult and costly after plants are set up, cost-effective opportunities for energy efficiency improvements in existing production capacity are relatively limited. In new production capacity, however, there are many opportunities to adopt modem and high efficiency technologies and processes. 4.23 For the years 2000, 2010 and 2020, the baseline and high efficiency scenarios assume different degrees of shifting in plant scale up towards the large-scale category, and different average efficiency levels for each scale category. In the baseline case, 70 percent of steel output in 2020 is produced in large plants, at a unit energy consumption level of 1.05 tce/ton. About 24 percent is produced in medium-scale plants, at an efficiency of 1.30 tce/ton, and 6 percent is produced in small plants, at 1.50 tce/ton. Average unit consumption falls from 1.33 tce/ton in 1990 to 1.14 tce/ton in 2020, a reduction of about 14 percent (see Annex 3, Table 6). 4.24 Unit energy consumption in large plants approaches advanced international levels in 2020 in the high efficiency case, at 0.68 tce/ton. Large plants are assumed to contribute 83 percent of output. Medium-sized plants contribute 14 percent, at 1.06 tce/ton, while small plants contribute just 3 percent, at 1.5 tce/ton. Average unit consumption falls to 0.76 tcelton, a decline of 43 percent. 4.25 Output from China's steel industry today is dominated by low-quality, simple carbon steel products. The baseline scenario assumes greater diversification in product types, improvements in quality, and increasing output of specialty steel. Value-added per ton of crude steel produced is assumed to increase by 1.5 percent per year, compared to a rate of 2.7 percent per year achieved during 1986-90. 28 Non-Ferrous Metals (7) 4.26 Many kinds of non-ferrous metals are produced in China. The four major products--copper, aluminum, lead, and zinc--account for about 80 percent of the total energy use in the subsector. Output of the ten major non-ferrous metals are projected to roughly quadruple in the coming 30 years. The production of aluminum is estimated to increase from 0.85 million tons in 1990 to 4.0 million tons in 2020. 4.27 The production of non-ferrous metals is highly electricity intensive. Electricity intensities of the four major non-ferrous metals are (1990 data): aluminum -- 17,675 kWh/t, copper -- 5,895 kWh/t, and lead & zinc -- 2,475 kWh/t. Potential for reducing electricity intensity in non-ferrous metal production is small because of the unique processing techniques adopted by the industry. Future trends in electricity intensity are depicted in Table 4.5. Table 4.5 Non-ferrous metals industry: per unit energy use 2000 2010 2020 Aluminum (kWh/t) 17,000 16,500 16,000 Copper (kWh/t) 5,800 5,800 5,800 Lead & Zinc (kWh/t) 2,475 2,475 2,475 4.28 Substantial fuel savings can be achieved in the non-ferrous metal sector through the renovation of industrial kilns and furnaces. Value-added per ton of ore processed also should increase. Accordingly, energy use per unit of output value is estimated to decline by about 14 percent for the major products by 2020. The same assumptions are used in all scenarios; because of the industry's small share in total energy consumption, this assumption has little effect on the overall projections of energy consumption Chemical Fertilizers (8) 4.29 Use of chemical fertilizers in general and nitrogen fertilizers in particular in China is much higher than world average levels, both in terms of total use and use per hectare of farm land. In 1990, nitrogen fertilizer use was about 148 kg per hectare, compared with the world average of about 54 kg per hectare. At this point, there are sharply diminishing returns to increased application, especially for nitrogen fertilizers. Thus there is little likelihood of a major future increase in total consumption of relatively energy-intensive nitrogen chemical fertilizer. Accordingly, production of ammonia, the basic material for producing nitrogen fertilizer, is estimated to increase modestly from 22.5 mt in 1990, to 26.7 mt in 2000, 33.6 mt in 2010 and 37.8 mt in 2020. If the domestic nitrogen fertilizer market is opened up to foreign competition, the production increase may be even smaller because of high domestic production costs and shortages of the most efficient feedstock- natural gas. 29 4.30 In 1990, total energy use for chemical fertilizer production was about 59.3 million tce, accounting for about 50 percent of total energy use in the chemical industry, or 10 percent of total industrial energy use in China. Ammonia production accounts for about three-quarters of energy use in nitrogen fertilizer production. Ammonia plants are classified into three types. The large plants, which accounted for 18.7 percent of total ammonia output in 1990, use oil and natural gas as feedstock. The medium and small-size plants mainly use coal or coke as feedstock. Only about 10 percent of the ammonia produced by small plants in China is based on natural gas. Average energy use per ton of ammonia is about 1,343 kgce for large plants, 2,176 kgce for medium-sized plants, and 2,254 kgce for small plants. 4.31 In the baseline scenario, the projected increase in ammonia output comes mainly from the renovation of existing plants. There are about 1,000 small ammonia plants with capacities of 20-50 thousand tons per year each. Currently, these plants account for 59 percent of total ammonia production, and the baseline case assumes that the small plants continue to play a dominant role, accounting for about 58 percent of output in 2020. By closing the most inefficient plants and renovating and expanding the more efficient ones, the average energy intensity of the small plants could fall to about 1,700 kgce per ton or less by 2020. The output share of the medium-size plants was 22 percent in 1990 and it is assumed to remain unchanged during the next 30 years, given ample opportunities to increase capacity and improve energy efficiency in existing medium-sized plants. For example, the Shijiazhuang Chemical Fertilizer Plant was recently able to increase ammonia production from 80 to 180 thousand tons and reduce energy intensity from 2,100 to 1,700 kgcelton-ammonia through renovation efforts. The output share of large plants in China is assumed to increase only slightly from 18.7 percent to 20 percent. 4.32 The high efficiency scenario assumes a radical restructuring of the industry to achieve better economies of scale. Whereas the output shares of the different size categories of plants remain basically unchanged in the baseline scenario, the high efficiency scenario assumes that the share of large plants increases steadily to 60 percent of total production in 2020, while the share of medium-sized plants remains at 22 percent, and the share of small plants falls steeply to just 18 percent. With only minor differences in unit energy consumption assumptions for each plant size between the two scenarios, changes in plant size yield a total average unit energy consumption level of 1,258 kgce/t in the high efficiency scenario, compared to 1,538 kgce/t in the baseline scenario. Other Chemicals (9) 4.33 Other chemical products include basic chemical materials, pesticides, organic chemical materials, synthetic materials, rubber, plastic materials, and related products. Together, they accounted for the other half of total energy use in the chemical industry in 1990. Growth in the total output value of these products is expected to be very strong, but growth is expected predominantly in the thousands of relatively high value-added, less energy intensive products. For example, aside from the chemical fertilizer industry, discussed previously, a large share of energy consumption in the chemical industry today is concentrated in the production of basic chemical materials, including various kinds of 30 soda, acid, calcium carbide, and raw materials for synthetic chemical products such as ethylene. These basic chemical materials accounted for about 26 percent of total energy use in the non-fertilizer chemical industry. Their share in output value, however, was just 8.7 percent in 1990, a sharp decline from 11 percent in 1985. The share of these basic chemicals in output value is expected to continue to fall, to a level ofjust 1.5 percent by the year 2020, while the output of high-value chemicals is assumed to increase. The share of the basic chemicals in energy use falls from 26 percent to about 6 percent in 2020 in the baseline scenario. This shift in industrial structure, coupled with the very slow growth in chemical fertilizer output described earlier, is a key factor in the overall energy intensity decline in the chemical industry. 4.34 Caustic soda (NaOH). Total output of caustic soda (sodium hydroxide), which is widely used in the chemical and refining industries, was 3.35 mt in 1990. Output is assumed to reach 7.5 mt in 2020. Steam and electricity are the two main sources of energy used in the production of caustic soda. In traditional processes in China, production of one ton of caustic soda requires about 1,790 kgce of energy, including about 5 tons of steam (equivalent to about 700 kgce) and about 3,000 kWh of electricity. Using the membrane process, which is widely used abroad, only about 1,000 kgce/t are required, including about 0.06 tons of steam and about 2,500 kWh electricity per ton. All scenarios assume adoption of the membrane technology in new plants, due to its overall cost advantages. In the baseline scenario, existing plants using the older technology continue to play an important role, so that the membrane technology accounts for only 59 percent of output in 2020. In the high efficiency scenario, the membrane technology is used for all caustic soda production. Accordingly, energy use per ton of caustic soda falls from 1,790 kgce in 1990 to 1,325 kgce in 2020 in the baseline scenario, and to 1,000 kgce in 2020 in the high efficiency scenario. 4.35 Soda ash. Soda ash output is assumed to grow from 3.8 mt in 1990 to about 8.5 mt by 2020. The potential for energy efficiency improvement in soda ash production is considered to be small. Both scenarios assume a decrease in unit energy consumption of about 7 percent. Cement (10) 4.36 Cement is the only industrial product for which China has a higher per capita consumption level than the world average. In 1990, total production of cement was about 210 mt and in 1993 it was about 360 mt. The continuation of large scale infrastructure construction in China is expected to drive the demand for cement output. Similar to the case for steel, however, the growth rate of cement production will be substantially lower than that of GDP. Cement production in 2020 is assumed to be in the range of 700-800 mt (780 mt in the baseline scenario). 4.37 Total energy use in cement production was about 45 million tce in 1990, accounting for 36 percent of energy use in the building material sector, or 4.46 percent of total energy use in China. Energy efficiency and cement quality in China vary by 31 production process and plant scale. Energy efficiency in different sizes of plants and with different technologies is depicted in Annex 3. 4.38 Great changes are not expected in the overall energy intensity of cement making because of trade-offs between rising electricity intensities and declining fuel intensities. In the baseline scenario, the overall energy intensity of large plants is assumed to decrease from 208.6 kgce/ton-cement in 1990 to 167 kgce/ton-cement in 2020, and the overall energy intensity of small plants is assumed to decrease from 208.5 kgce/ton-cement in 1990 to 195 kgce/ton-cement in 2020. 4.39 Long distance overland transportation of cement is often not justified economically. Thus, regional demand patterns will have important impacts on plant scale, especially where the highest quality is not required. Even though the long-term trend is to develop large-scale cement plants, small and locally-oriented plants will have a role, although technology change in the small plants will remain critical. The baseline scenario assumes that large plants will account for about 36 percent of the cement production in 2020, while in the high efficiency scenario they command a 48 percent market share. Other Building Materials (11) 4.40 In 1990, the production of other building materials consumed about 78 mtce of energy, of which 73 percent was used for producing bricks, tiles, and flat glass. Increasing the share of new building materials to replace traditional materials, such as bricks and tiles, is considered the major source of energy savings in this segment of the building material industry. It is assumed that by 2020, energy-intensive products, such as bricks and tiles, will contribute only about 6.5 percent of the total value-added of this group of products, compared with 48 percent in 1990. 4.41 Bricks. The current energy intensity of brick making in China is about 110 kgce/1,000 bricks. Using a state-of-the-art process, energy intensity is about 100 kgce/1,000. Therefore the potential for energy saving in brick making in China is moderate. Even though hollow bricks can save about 25 percent of energy compared with solid bricks, their usage in China is limited. Assuming that hollow bricks account for about 25 percent of total brick making in 2020, the overall energy intensity of brick making could be reduced to about 95 kgce/l,000. 4.42 Flat Glass. Output of flat glass grew at over 10 percent per year during the 1980s. Output is projected to reach about 15 million standard cases (sc) in 2000, 18 million sc in 20 10, and 22 million sc in 2020. Energy intensity of flat glass production is assumed to be reduced from 38.8 kgce/sc in 1990 to 31 kgce/sc in 2020. 4.43 Future energy savings in the building material industry will depend on the introduction and output growth of new types of materials that are less energy intensive and have higher value-added than traditional materials. In 1990, energy use per unit output value for non-traditional building materials was about 363.84 tcelmillion-yuan, only about one of third of that for bricks and flat glass. The share of output value of non- 32 traditional building materials (eg. aluminum and plastics) is projected to increase from 51.7 percent in 1990 to 97 percent in 2020, while the share of energy use of these materials is estimated to increase from 21.05 percent to about 77 percent. Because of these shifts, the overall energy intensity of this segment of the building materials industry (excluding cement) will drop from 697.73 tce/million-yuan in 1990 to 177 tce/million-yuan in 2020 (see Table 11, Annex 3). Machinery and Electronics (12) 4.44 The machinery and electronics (ME) industry is one of China's largest industrial subsectors, accounting for 17 percent of GDP in 1990. The lack of sophistication and technological backwardness in the ME industry is a also to blame for the mediocre energy efficiency of the Chinese economy. In light of the experiences of other developing countries, the ME industry is expected to grow rapidly in China, including the automobile, telecommunications, special equipment, and the electronics industries. The growth rate of the ME industry is also expected to be higher than that of other industrial sectors. Based on the macroeconomic model, the average annual growth rate of the ME industry is estimated to be 12.84 percent from 1990 to 2000, 8.42 percent from 2000 to 2010, and 6.61 percent from 2010 to 2020; this is about 2 percent higher than the respective growth rates for the industrial sector as a whole. 4.45 In 1990, total energy use in the ME industries was 55.21 mtce, about 5.5 percent of the total energy consumption in China. It is estimated that the ME industry's share of total national energy use will increase to 7 percent by 2020 and the share of GDP will increase to about 26 percent. 4.46 In terms of energy use per ton of product, the major energy-intensive products in the ME industry include automobiles, special equipment, and machine tools. Limited energy saving potential exists in improving reheating furnaces. It is considered that the production of high quality and high value-added equipment will generate the largest energy savings for the ME industries. Thus, energy saving in these industries will largely rely on the improvement of technologies, production processes, and management (see Table 12, Annex 3). Light Industry (13) 4.47 The light industrial sector consists of a wide range of industries, including paper and paper products, beverages and food, and apparel. Light industry currently accounts for about 50 percent of total industrial output value. In 1990, total energy use in the light industry sector was 134.43 mtce, about 17 percent of total industrial energy use, or about 13.6 percent of total energy use in China. 4.48 The major energy intensive products produced by light industry include pulp and paper, wine and beer, sugar, and textile products. In 1990, energy use for these products accounted for about 22 percent of the total energy use in the light industry sector. Paper :33 making, in particular, accounted for about 13 percent of the total energy use in the sector, while its share of output value was only about 4 percent. 4.49 Energy saving potential in the light industry sector lies in quality improvements and changes in product mix. During the 1980s, light industrial output grew rapidly while maintaining an energy consumption elasticity of about 0.4; similar to that for the industrial sector as a whole. From 1990 to 2020, it is assumed that the energy demand growth of the light industry will follow the general pattern for industry as a whole. In the baseline scenario, the energy intensity of light industry declines at about 2 percent per year. In the high efficiency scenario, the rate of energy intensity reduction is about 3 percent per year. The difference in total energy demand by light industry in the two scenarios is about 13 mtce in 2000, 64 mtce in 2010, and 117 mtce in 2020 (see Table 13, Annex 3). 4.50 Paper and Paper Products. Consumption of paper products is expected to grow rapidly in China in the future. Because raw materials for paper making are scarce in China, imports of pulp have grown in recent years. The energy efficiency of China's pulp industry is very low due to the use of low-grade raw materials and backward technologies. Energy use per ton of paper in 1990 was 1,245 kgce, which is considerably above international averages. For comparison, energy use per ton of paper is only about 200 kgce in Finland. Under the baseline scenario, the total demand for paper in 2020 is estimated to be 43 mt, at least half of which will be made from imported pulp. The use of imported pulp will help to reduce the unit energy use of paper-making to about 900 kgce/ton-paper. 4.51 Textiles. The textile industry is an important part of China's economy. In 1990, the output value of the textile industry accounted for about 24 percent of the total value of light industry, or about 12 percent of the gross output value of the economy. Energy use in the textile industry was about 30 mtce, about 20 percent of the total energy use in light industry, or about 5 percent of total industrial energy use. Electricity is the primary energy source for the textile industry. Among all industries in China, only the textile industry compares favorably against industrialized countries in product energy intensity, especially in product electricity intensity. However, the reasons have little to do with energy efficiency. Rather, there is a lack of mechanization in China's textile industry, and mills often have inadequate lighting, ventilation, and air conditioning. Assuming that conditions in textile factories will improve in the future, electricity intensities of major textile products are estimated to increase about 30 percent between 1990 and 2020. Electricity use for the production of yarn is estimated to increase from 2,129 kWh/t in 1990 to 3,458 kWh/t in 2020, and fabric from 252 kWh/km to 320 kWh/km. The rapid increase in the production of high-value textile products, such as fashionable clothing, will override the increase in electricity consumption. Under the baseline scenario, energy use per unit output value declines from 107 tce/million-yuan in 1990 to 42 tce/million-yuan in 2020, and to 33 tce/million-yuan in 2020 in the high efficiency scenario. 4.52 Beer and Wine. China is the largest alcoholic beverage producer in the world, producing 13.86 mt of beer and wine in 1990. The output of beer and wine quadrupled in the 1980s, and demand is expected to continue to follow the rise in income levels. Output is assumed to double again by the year 2020. Current energy use in producing beer and 34 wine is about 170 kgce per ton of product, and this figure is assumed to drop to about 140 kgce in 2020 under the baseline scenario. Total energy use for beer and wine production is expected to remain small: 2.4 mtce in 1990 and about 3.5 mtce in 2020. Construction (14) 4.53 The construction sector, especially housing and road construction, has been expanding rapidly since the early 1980s. The development of the real estate market will have a major impact on energy consumption in the construction sector, due to the increase in the stock of high-value buildings. 4.54 Currently, average per capita living space is about 8 square meters in urban areas and about 14 square meters in rural areas. Based on projections by the Ministry of Construction (MoC), by the year 2020 average per capita living space will reach about 14 square meters in urban areas while the figure for rural areas will remain unchanged. The quality of housing, and housing value, is expected to improve over time. According to MoC projections, in addition to new housing construction, 70 percent of existing rural housing and 50 percent of existing urban housing will be rebuilt by 2020. 4.55 Before 2000, the priority of the sector will be to expand construction to satisfy current residential and commercial space demands. After 2000, the priority will shift to quality improvements. Although new building floor area will not quadruple, the output value of the construction sector is estimated to, due to the improved quality of new buildings. Energy use per unit of output value will therefore decline. In the baseline scenario, the energy elasticity for the construction sector is projected to be 0.68, 0.69 and 0.70 percent for the three decades between 1990 and 2020, while in the high efficiency scenario, the energy elasticities are 0.60, 0.63 and 0.63 (see Table 14, Annex 3). Freight Transportation and Postal and Communication Services (15) 4.56 Between 1985 and 1990, freight transportation volume increased by 7.6 percent per year. In the baseline scenario, freight transportation is estimated to increase at about 4 percent per year from 1990 to 2020, rising from 2,621 billion ton-km to 8,598 billion ton- km. Even though the energy efficiency of each transport mode will improve, overall energy intensity of freight transportation will not change significantly because of the shift to more energy-intensive road and air traffic modes. If energy use per ton-km remains unchanged at its 1990 level of 14 tce/million-ton-km, total energy use in freight transportation would be about 120 mtce, which is 3.3 times the 1990 level. 4.57 Energy use per unit output value in postal and communication services is low and is expected to remain so in the coming decades. The sector will see a rapid decline in energy intensity because of the expected large increase of value-added in postal and communication services. In the baseline scenario, the combined energy intensity of the sector will decrease from 239 tce/million-yuan in 1990 to 107 tce/million-yuan in 2020. 35 Total energy demand of the sector will be about 169 mtce in 2020 (see Table 15, Annex 3). Commerce (16) 4.58 Energy use in the commerce sector was 12.5 mtce in 1990, accounting for about 1.3 percent of the total energy use in China. Although the commerce sector is expected to grow quite rapidly over the coming decades, its share of total energy use will remain small. In the baseline scenario, total energy use in the commerce sector is projected to be about 22 mtce by the year of 2000, accounting for about 1.4 percent of China's total energy use. 4.59 No special assumptions were made for energy efficiency improvements in the commerce sector. The baseline scenario assumes an annual 2 percent improvement in energy efficiency for the commerce and services sector and a 3 percent per year improvement under the high efficiency scenario (see Table 16, Annex 3). Passenger Transportation (17) 4.60 All major modes of motorized passenger transportation--railways, highways, and urban transit--are seriously overcrowded in China. Before the turn of the century, this overcrowding will not be substantially reduced, but the situation is expected to gradually improve thereafter. Energy use per passenger-kilometer is thus expected to decrease slightly until the year 2000, and then increase as overcrowding is reduced. It is also assumed that the output value of passenger transportation will increase faster than the total movement of passenger transportation as a result of improvements in the quality of service. The amount of energy per unit output value of passenger transportation is therefore expected to fall continuously over the coming three decades. 4.61 Passenger transportation energy use depends critically on the mode of transportation. Over the next 30 years, it is assumed that public transportation will remain the primary mode of motorized passenger transportation in China. The use of private motorized vehicles (cars, trucks, motorcycles) are expected to increase dramatically in the future. However, even with rapid growth in per capita income, the percentage of the population that will be able to afford motorized vehicles will be rather limited, especially if taxes and other fees continue to be used to raise the costs. Due to a number of factors, including domestic shortages of oil products, the use of electric transportation systems is expected to increase in China. In large cities, buses (both diesel and electric) and metro systems will be the primary passenger carriers. In smaller cities and rural areas, buses and railways will be the dominant mode of passenger transportation. 36 Other Services (18) 4.62 As noted above in para. 4.59, no detailed analysis of future energy intensity was conducted for the commerce and services sectors; both were assumed to decrease at 2 percent per year in the baseline scenario and at 3 percent in the high efficiency scenario (see Table 18, Annex 3). Residential Sector 4.63 The residential sector is the second largest energy user in China after industry. Under the baseline scenario, household energy use reaches about 448 mtce by 2020, which is three times the level in 1990 (excluding biomass energy). There are three major factors behind the growth of household energy demand. (a) Population Growth. By 2020, the total population will be about 1,450 m-ilion; a net increase of about 200 million compared with 1990. It is assumed that 65 percent will still be living in rural areas and 35 percent in urban areas. Even if per capita energy use did not increase, total household energy use would rise by about 70 mtce by the year 2020 through population growth alone. (b) Living Condition Improvement. Serious fuel shortages still exist in many rural areas. Therefore, even with energy efficiency improvements, per capita residential energy use in China is expected to increase. There is large growth potential for space heating from both currently underheated and unheated households, as well as air conditioning among higher income households. (c) Private Vehicle Use. There are very few private automobiles in China today. It is assumed that the ownership of private motor vehicles (cars, trucks, motorcycles) will grow significantly over the next 25 years, 'With the private car population reaching about 40 million in 2020. Table 4.6 Actual and projected trends in residential energy use 1985 1990 2000 2010 2020 Coal (mt) 156 167 163 196 164 Oil &gas(mtoe) 2 3 6 15 48 Power (TWh) 22 48 169 299 600 Biomass (mtce) 225 225 225 225 225 Total (mtce) 348 368 418 507 653 Per capita use (kgce) 329 322 334 373 451 :37 4.64 The quantity of energy used for cooking is assumed to remain relatively constant over the coming decades, however, the energy mix is expected to change. Currently, the predominant cooking fuel in urban areas is coal and in rural areas is biomass. Gas and electricity are expected to play increasingly important roles in urban household cooking, while coal use is expected to play a larger role for cooking in rural areas. Table 4.7 Energy used for cooking 1985 1990 2000 2010 2020 Coal (Mt) 104 112 108 98 82 Oil & gas (Mtoe) 1 2 2 5 8 Power (TWh) nil nil 2 15 60 Biomass (Mtce) 169 169 169 169 169 Total (Mtce) 244 251 250 247 246 Per capita use (kgce) 231 219 200 182 170 4.65 Per capita cooking energy use is assumed to decrease from 283 kgce in 1990 to 208 kgce in 2020. Because of the improvement in both energy efficiency and fuel quality (more gas and electricity), per capita useful cooking energy will increase from 32 to 43 kgce in the same period. The share of high quality energy such as gas and electricity in cooking energy use will increase from 0.5 percent in 1990 to about 8 percent in 2020. Overall cooking energy efficiency is projected to increase from about 14 percent to 25 percent from 1990 to 2020. Table 4.8 Share of cooking fuel (percent) 1985 1990 2000 2010 2020 Coal 30.5 31.7 31 28 24 Oil & gas 0.3 1.0 1 3 5 Power 0 0 0 1 3 Biomass 69.2 67.3 68 68 68 Total 100.0 100.0 100 100 100 4.66 Biomass is expected to remain an important fuel source for cooking in China over the next 25 years. Therefore, improving the efficiency of biomass stoves will be important for increasing overall cooking energy efficiency. Without improvements in biomass stoves, overall cooking energy efficiency would be less than 22 percent instead of over 25 percent in 2020 in the baseline scenario. Table 4.9 Energy efficiency for cooking (percent) 1985 1990 2000 2010 2020 Coal 5 18 20 22 25 Oil & gas 60 60 60 60 60 Power 95 95 95 95 95 Biomass 13 15 17 18 20 Average 13.8 16.4 18.5 20.8 25.3 Useful energy per capita (kgce) 32 36 37 38 43 38 4.67 The demand for residential and commercial space heating and cooling is expected to increase significantly over the coming decades, largely as a result of rising living standards. In northern China, coal is expected to be the primary energy source for space heating, while in southern China, electricity is assumed to be the primary fuel for space conditioning. The amount of electricity used for household appliances and air conditioning will increase in all Chinese households. By the year 2020, per capita electricity use is projected to be about 414 kWh for the country as a whole: 700 kWh for urban, and 260 kWh for rural areas (see Table 19, Annex 3). 39 5. SUMMARY AND CONCLUSIONS A. KEY FACTORS INFLUENCING ENERGY DEMAND 5.1 This chapter summarizes the key factors that will influence energy demand trends in China. How these factors interplay to define future energy consumption levels, in turn, is greatly influenced by macroeconomic policies, energy pricing policy, policies towards trade in energy-intensive commodities, progress in technology transfer from abroad, progress in enterprise reforms to strengthen cost-consciousness, and other variables. 5.2 Structural factors are expected to continue to play the largest role in further reductions in the energy intensity of China's economy, and include the following. (a) Rate of economic growth. Faster economic growth can be expected to result in faster growth in energy use. The relationship between the two, however, is not linear. Energy/GDP growth elasticities are expected to be significantly lower if China's economy continues to grow fast than if the economy grows slowly. Faster growth is not expected to result in correspondingly higher energy consumption levels. One reason is that faster industrial growth provides an opportunity for a more rapid increase in the contribution of new, more efficient industrial plants. Another reason is that faster growth is generally expected to be driven by more rapid structural change-much of the incremental value-added in industry under a higher growth scenario is expected to come from more specialized products that are less energy- and material-intensive. If this does not occur, the prospects for rapid growth are dim. (b) Population growth. The rate of population growth is another important factor, but the range of future population growth estimates of most experts is relatively narrow. (c) Macroeconomic structure. At this broad level, the key issue is the relative role of industry in GDP, compared with agriculture and services, as the energy intensity of industrial production is many times greater than that of the other sectors. (d) The role of residential sector energy use. Total energy use by households increases substantially slower than GDP as countries develop from lower income to middle- and high-income countries. Electricity use by households tends to grow very fast, but the larger energy demands for solid or liquid fuels for cooking and heating tend to grow much more slowly than the orders-of-magnitude increases in GDP implied by sustained rapid economic growth. This trend has been a significant factor in past declines in China's energy intensity, and the trend is expected to continue, 40 especially under higher growth scenarios, and especially with the expected concurrent improvements in the efficiency of cooking and heating in Chinese households. (e) Structural changes in industry. The nature of changes in the structure of industrial production is a critical determinant of future energy demand levels. With rapid growth, the most important issue is the characteristic of new capacity, rather than the rehabilitation of existing capacity. An important element is the extent to which the efficiency in the use of energy- intensive products, such as steel, can be increased. The most important shifts in industrial structure will come about through changes in the product mix of individual sectors due to changing market conditions. The energy per unit output value is expected to fall due to large increases in value- added due to quality improvements, specialization, and higher technological content. (f) Structural changes in other sectors. Structural changes in agriculture and various tertiary industries, such as construction, are expected to result in modest declines in energy use per unit of output value, primarily due to increases in the value side of the equation, especially through quality improvements. 5.3 The extent to which China can increase technical energy efficiency, usually measured in terms of energy use per physical unit of output, will also have a major bearing on future energy consumption levels. Some of the key factors include: (a) Economies of scale. Most industries in China suffer serious energy efficiency penalties because they do not operate at optimal scale. For example, the average production capacity of paper mills in China is about 2,000 tons while in other major paper-making countries, the average capacity is about 60,000 tons. About 80 percent of China's cement output is produced by medium and small plants. In the electric power sector, less than 15 percent of the thermal power capacity is supplied by 300 MW units or larger. Other industrial sectors have similar conditions. Without a minimum production scale, many modem technologies or equipment can not be adopted. For example, BOF and continuous casting technologies are most suitable for furnace capacity of 3 million tons or more of steel per year. Currently, only a few steel plants in China have such a capacity. Traditional energy conservation projects cannot close the efficiency gap caused by differences in production scale. With market-oriented reforms, capital market development, and efforts to reduce regional protectionism, China's economy clearly should be able to take better advantage of scale economies in key industries. (b) Improvements in industrial equipment and process technologies. The level of sophistication in industrial technologies and equipment affects overall energy intensity both in terms of the value produced, especially 41 value derived from quality, and the energy efficiency of production processes. Because of the backwardness of domestic manufacturing technologies, domestically made energy-consuming equipment, such as industrial boilers, fans, pumps, and motors, generally have lower energy efficiency than those made in the developed countries. On the user side, due to poor operation and management, the actual utilization efficiency of this equipment is often even lower. Improving the technological sophistication of the machinery and electric equipment industry will not only raise the overall energy efficiency level in China but will also enhance the competitiveness of China's machinery and electric equipment industry in the world market. Improvements in the equipment and processes used for new capacity is by far the most important, as new plants will soon dominate industrial capacity, given the rapid industrial growth envisaged. (c) Improving the fuel mix and industrial raw material inputs. China's historical emphasis on self-reliance has caused many industries to adopt high cost and low efficiency processes. For example, the use of low quality domestic iron ore is one of the major factors responsible for the high energy intensity in Chinese iron and steel making. Compared to Japan, the Chinese steel industry uses 130 kgce more energy to make one ton of iron and 400 kgce more energy to make one ton of steel. In addition to the benefits of greater scale and efficient equipment, high quality iron ore is also a reason for the low energy intensity of Japan's steel industry. Another example is in ammonia production. China is one of the few countries using coal as feedstock for ammonia production. Currently, coal- based ammonia production in China uses about one hundred times more electricity per ton of ammonia than natural gas-based ammonia production. Such inefficient production processes are quite common in the chemical and paper industries as well. As China's economy becomes more open to the world market, Chinese industry can take advantage of the competitiveness of international energy and raw material markets to restructure industrial production. Discoveries and development of new supplies of domestic natural gas also could yield substantial energy efficiency gains. B. ENERGY DEMAND SCENARIOS Baseline Case 5.4 The baseline case was developed as a benchmark energy demand scenario to assess the relative importance of different factors and potential interventions on total greenhouse gas emissions. It is intended to show how energy demand might evolve under "business- as-usual" conditions. Energy is priced at economic cost, implying some relatively modest adjustments from current pricing policy, but no large new energy taxes (e.g., a carbon tax) are imposed. Major gains in economic efficiency are achieved through implementation of 42 the economic reform program in general, and enterprise and capital market reform in particular, which affects the structure of the economy and the behavior of enterprises. The country's efforts to improve technical energy efficiency levels continue as during the 1980s and early 1990s, realizing significant benefits. Table 5.1 Total energy demand: baseline case 1990 2000 2010 2020 Total primary energy use (million tce) 987 1,561 2,377 3,301 Coal (million t) 1,053 1,574 2,376 3,100 Oil and gas (million toe) 112 182 285 442 Natural gas (109 cubic meter) 15 29 67 114 Power (TWh) 126 362 508 871 Total final energy use (million tce) 987 1,561 2,377 3,301 Coal (million t) 802 1,135 1,503 1,791 Oil (million toe) 101 170 274 433 Natural gas (109 cubic meter) 15 27 62 107 Power (TWh) 623 1,302 2,429 3,845 Per capita use (tce) 863 1,201 1,698 2,276 Coal (kg) 702 873 1,073 1,236 Oil (kgoe) 89 130 196 299 Natural gas (cubic meter) 13 21 44 74 Power (kWh) 545 1,002 1,735 2,651 Source: China Statistical Yearbook; Joint Study Team. 5.5 The broad structure of GDP changes in the baseline scenario, with a large increase in the share of the services sector, and a large decrease in the share of agriculture. The share of industry--a critical determinant of a country's energy intensity--rises slightly from its currently high level of 44 percent to 45 percent by 2000, and then falls to 41 percent in 2010 and 37 percent in 2020. Growth in industrial output must continue to be strong, in order to provide the wide range of material goods which will be demanded by the population as per capita incomes move to the middle-income range. The absence of a steady and strong increase in the share of industry in economic output, however, marks an important break with past trends. As mentioned in Chapter 2, the growth of industry was a major factor working against the trend towards lower energy intensity of the economy- without the large increase in the share of industry, the energy intensity decline witnessed during the 1980s would have been substantially greater. 5.6 The relative share of different industrial sectors in industrial output also changes markedly under the baseline scenario. Growth is relatively modest in the coal, oil, ferrous and non-ferrous metal, chemical fertilizer, and cement industries; the share of these industries in total output all fall markedly. Growth is especially strong in the machinery and electronics industry; the share of this industry is projected to increase from about 17 percent of net industrial output in 1990 to about 26 percent in 2020. Growth in light industry, non-cement building materials, and chemicals other than fertilizers also exceeds the average for industry as a whole. 43 5.7 The baseline case is by no means a simple extrapolation based on the current economy; the baseline case results in further major declines in energy intensity. If the rapid economic growth of the baseline case is assumed with an energy/GDP elasticity of 1.0 (e.g., energy use grows as fast as economic output), China's energy demand would reach about 10 billion tce by 2020, which is roughly equivalent to total world energy use in 1990. This situation is shown in Table 5.2, and referred to as the "no further change" scenario. Such an extrapolation would also imply that per capita commercial energy use in China would be more than 7.5 tce in 2020, which is three times the world average level of 1990, and higher than the OECD average level of 7.4 tce in 1990. Clearly, an economic growth pattern which represents a rapidly growing extension of the current economy is not feasible. Without major economic and energy efficiency gains, primarily through economic system reform, rapid economic growth over the medium term is not viable. Table 5.2 Total energy demand: no further change scenario* 1990 2000 2010 2020 Primary Energy Use (million tce) 987 2,446 5,281 9,913 1. Coal (mt) 1,051 2,610 5,636 10,579 2. Oil (mtoe) 113 278 601 1,128 3. Gas (bcm) 15 38 82 153 4. Power (TWh) 126 313 676 1,269 Per Capita Energy Use (kgce) 863 1,882 3,772 6,837 * Assumes same growth of the economy to the year 2020 as under the baseline scenario, but there are no changes from 1990 in either the input-output table or the final demand structure. Slower Growth Scenario 5.8 In the slower growth case, GDP grows by one percentage point less per year than in the baseline case during the 1990s, and 1.5 percent less per year during 2001-2020. Total GDP in 2020 reaches only US$2.5 trillion (1990 prices), which is about 35 percent less than in the baseline scenario. 5.9 Assumptions concerning economic structural change and population growth are the same as in the baseline scenario. Subsector energy use coefficients were revised upwards modestly, to reflect the factors influencing energy demand discussed in the previous section. Table 5.3 Total energy demand: slower growth scenario 1990 2000 2010 2020 Primary Energy Use (million tce) 987 1,535 2,226 2,879 1. Coal (mt) 1,051 1,551 2,226 2,671 2. Oil (mtoe) 113 176 257 370 3. Gas (bcm) 15 28 63 104 4. Power (TWh) 126 362 508 871 Per Capita Energy Use (kgce) 863 1,180 1,590 1,985 Source: China Statistical Yearbook; Joint Study Team. 44 5.10 While total GDP is over 30 percent less in 2020 compared to the high growth case, energy consumption is only 10 percent less. When the economy grows more slowly, the transformation of the economy proceeds at a slower pace, and per unit energy consumption falls at a slower pace. There also is less capital investment in newer, more energy efficient plants and equipment. Compared to the high growth case, GHG emissions from energy consumption under the slower growth case are reduced by about 14 percent. High Efficiency Scenario 5.11 The high efficiency case is designed to assess the potential impact of a more aggressive effort to achieve advanced levels of technical energy efficiency. Compared with the baseline scenario, the high efficiency scenario assumes that advanced international levels of energy efficiency in selected key industrial sectors are achieved in China more rapidly. More effective adoption of high efficiency energy-using industrial equipment also is assumed. In the baseline scenario, China does not fully meet international efficiency levels in a number of industries because of difficulties in achieving economies of scale. This constraint is largely lifted in the high efficiency case. Other key assumptions--on economic growth, population growth and structural change--remain the same as in the baseline case. Table 5.4 Total energy demand: high efficiency scenario 1990 2000 2010 2020 Primary Energy Use (million tce) 987 1,474 2,136 2,841 1. Coal (mt) 1,051 1,467 2,078 2,530 2. Oil (mtoe) 113 174 267 410 3. Gas (bcm) 15 29 65 110 4. Power (TWh) 126 362 508 871 Per Capita Energy Use (kgce) 863 1,134 1,526 1,960 Source: China Statistical Yearbook; Joint Study Team. Summary 5.12 To support the growth of the economy, energy consumption will need to increase substantially in China over the next 30 years. The energy demand elasticity of the economy is projected to stay in the range of 0.5 to 0.6, similar to the situation in the 1980s. Under the baseline scenario, China will surpass the U.S. as the largest energy- consuming country in the world around 2010. 5.13 The growth of energy demand is affected by both the level and pace of economic development. Economies at high levels of development generally need less energy to generate each unit of economic output due to the high share of services and low share of energy-intensive primary industries in GDP. The speed of development also affects energy demand. In China, energy efficiency is likely to improve more rapidly with a moderate to 45 high rate of economic growth as compared to a slow rate; i.e. the energy demand elasticity will be higher when economic growth is slower. 5.14 Changes in broad macroeconomic structure--the relative shares of agriculture, industry, and services--is not expected to have a significant impact on China's energy demand over the coming 25 years. Although agriculture's share of GDP will decline and that of services will increase, both the heavy and light industrial sectors are expected to maintain their approximate shares to satisfy the consumer demand. Under the baseline scenario, the overall level of energy efficiency as well as total energy demand will depend critically on the efficiency of new capital stock since the Chinese economy would be 10 times as large in the year 2020 as it was in 1990. 5.15 The efficiency of production processes is an important factor affecting overall energy demand. However, optimizing resources allocation and utilization and efficiently organizing production have been found to be the key to reducing future energy demand. Sustained energy conservation programs are important, but the most important energy conservation measures will be achieved through the modernization and reform of China's economy. Table 5.5 Summary of energy demand projections for 2020 1990 2020 Baseline High Slower Efficiency Growth Total Energy Demand 987 3,301 2,841 2,879 Energy Demand Per Capita 863 2,276 1,959 1,985 Energy Use Per Unit GDP 0.56 0.19 0.16 0.24 Energy/GDP Elasticity (over 0.53 0.56 0.49 0.58 previous decade) Source: China Statistical Yearbook; Joint Study Team. 46 6. References China State Statistical Bureau, Zhongguo touru chanchu biao, 1987 (1987 Input-Output Table of China), Beijing: China Statistical Publishing House. China State Statistical Bureau, Zhongguo tongii nianjian (China Statistical Yearbook), 1990-1994, Beijing: China Statistical Publishing House. He Jiankun, et al. (1991). "Long-term forecasts of energy demand and supply of China," China Forecasts, Vol. 1, No. 1, Beijing. Johnson, Todd M. et al. (eds.) (1994), China: Issues and Options in Greenhouse Gas Emissions Control, Summary Report, Joint Report of the World Bank, the United Nations Development Programme, the Chinese National Environmental Protection Agency and the Chinese State Planning Commission, Washington. ---------, Lampietti, Julian, Xu, Deying, and Blomkvist, Lars (1994). Greenhouse Gas Emissoins Control in the Forestry Sector, Subreport No. 6, China GHG Study, Washington, The World Bank. Lau, Lawrence and Jiang, Zhongxiao (1994), "The China Macroeconomic Model (version 9406)," Stanford University, mimeo. Tunnah, Barry, et al. (eds.) (1994) Energy Efficiency in China: Technical and Sectoral Analysis, Subreport No. 3, China GHG Study, Washington, The World Bank. Ward, William A., et al. (eds.) (1994), Energy Efficiency in China: Case Studies and Economic Analysis, Subreport No. 4, China GHG Study, Washington, The World Bank. Wells, Gary J., Johnson, Todd M., and Xu, Xiping (1994), Valuing the Health Effects of Air Pollution: Application to Industrial Energy Efficiency Projects in China, Subreport No. 8, China GHG Study, Washington, The World Bank. World Bank (1993), China: Energy Conservation Study, Washington. World Bank (1992, 1994), World Development Report, Washington. Wu, Changlun, et al. (eds.) (1994), Alternative Energy Supply Options to Substitute for Carbon Intensive Fuels, Subreport No. 5, China GHG Study, Washington, The World Bank. Wu, Zongxin, Siddiqi, Toufiq, and Streets, David (eds.) (1993). National Response Strategy for Global Climate Change: People's Republic of China, Manila, Asian Development Bank. 47 Annex1 Sectoral Composition of the Input-Output Table Sector 1 01 Agriculture Sector 2 02 Coal Mining and Washing 13 Coking, Coal Gas, and Coal Products Sector 3 031 Oil Exploration and Drilling 12 Oil Refinery Sector 4 032 Natural Gas Exploration Sector 5 11 Electric Power, Steam, Hot Water Production and Supply Sector 6 041 Ferrous Metal Mining 161 Ferrous Metal Smelting and Rolling Sector 7 042 Non-Ferrous Metal Mining 162 Non-Ferrous Metal Smelting and Rolling Sector 8 14102 Chemical Fertilizer Production Sector 9 14101 Basic Chemical Raw Material Production 14103 Chemical Pesticide Production 14104 Organic Chemical Products Manufacturing 14106 Synthetic Chemical Material Production 14401 Rubber Products for Manufacturing Use 14501 Plastic Products for Manufacturing Use Sector 10 15001 Cement Production 15002 Cement Products and Asbestos Cement Production Sector 11 051 Building Materials and Other Nonmetallic Mining 15003 Bricks and Tiles, Lime, and Light Building Material Production 15004 Glass and Glass Products 15005 Ceramic Products 15006 Refractory Products 15009 Other Nonmetallic Mineral Products Sector 12 17001 Metallic Products for Manufacturing Use 18001 Boiler and Motive Engine Manufacturing 18002 Metal Processing Machinery Manufacturing 18003 Industrial Specialized Equipment Manufacturing 48 Annex 1 18004 Agricultural Machinery Manufacturing 19 Transport Equipment Manufacturing 20001 Electric Motor Manufacturing 21001 Electric Computer Manufacturing 23 Machinery Equipment Repair 24001 Other Products for Manufacturing Use Sector 13 052 Salt Extraction 053 Timber and Bamboo Logging and Transport 054 Water Production and Supply 06 Food Processing 07 Textile 08 Sewing and Leather Products 09 Timber Processing and Furniture Manufacturing 10 Papermaking and Articles for Cultural and Educational Use 14105 Chemical Products for Civil Use 14109 Other Chemicals 14200 Medical Industry 14300 Chemical Fiber Industry 14402 Rubber Products for Civil Use 14502 Plastic Products for Civil Use 17002 Metal Products for Civil Use 18005 Civil Machinery Manufacturing 20002 Civil Electric Appliance Manufacturing 21002 Civil Electronic Device Manufacturing 24002 Other Products for Civil Use Sector 14 25 Construction Sector 15 26 Cargo Transport and Posts/Communications Sector 16 27 Commerce 28 Food and Drink Sector 17 29 Passenger Transport Sector 18 30 Public Utilities and Services 31 Culture, Education, Health, and Scientific Research 32 Finance and Insurance 33 Government 49 Annex2 Annex 2. Macroeconomic and Input-Output Results Input-Output Coefficients by Sector Macroeconomic Projections: Output Value, Value-Added Energy Use and Local Emissions by Sector 50 WORKING DATE: JUNE 9,1994 YEAR 2000 Direct Input Coefficients ( 18 Secters) [At 1990 Producer's Prices (ECONOMIC GROWTH RATE: 9.5%,8%,6.5%; BASELINE SCENARIO) 1 2 3 4 5 6 7 Units 83Al 84Al 85Al 86Al 87Al 88Al 89AI 1 Agriculture Yuan/Yuan 1001 0.140000 0.006508 0.000086 0.000151 0.000405 0.000608 0.002170 2 Coal Yuan/Yuan 1002 0.000811 0.062083 0.002716 0.003479 0.183559 0.047680 0.011515 3 Oil & Refineries Yuan/Yuan 1003 0.008052 0.013465 0.287900 0.061986 0.025182 0.006299 0.007343 4 Natural Gas Yuan/Yuan 1004 0.000022 0.000187 0.000000 0.062315 0.002067 0.000926 0.000147 5 Electricity Yuan/Yuan 1005 0.003867 0.057303 0.036167 0.017601 0.016414 0.040008 0.049984 6 Ferrous Metals Yuan/Yuan 1006 0.001448 0.022412 0.017586 0.039792 0.007270 0.233474 0.012125 7 Non-ferrous Metals Yuan/Yuan 1007 0.000078 0.001006 0.000325 0.000333 0.001038 0.014213 0.304327 8 Chemical Fertilizers Yuan/Yuan 1008 0.055978 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9 Chemical Industries Yuan/Yuan 1009 0.014668 0.032519 0.043069 0.058499 0.014554 0.017684 0.037886 10 Cement Yuan/Yuan 1010 0.000849 0.011130 0.005503 0.015915 0.004183 0.002066 0.002875 11 Building Materials Yuan/Yuan 1011 0.003658 0.010300 0.010133 0.017541 0.006580 0.036859 0.018674 12 Heavy Mach. & Electronics Yuan/Yuan 1012 0.012328 0.168914 0.147951 0.252046 0.093161 0.114132 0.061121 13 Light Industy Yuan/Yuan 1013 0.076366 0.081434 0.029502 0.038307 0.043383 0.026566 0.036110 14 Construction Yuan/Yuan 1014 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 15 Transport & Communications Yuan/Yuan 1015 0.031066 0.025419 0.091939 0.023016 0.051967 0.030033 0.023638 16 Commerce Yuan/Yuan 1016 0.031640 0.038953 0.051732 0.032663 0.043538 0.040918 0.053530 17 Passenger Transport Yuan/Yuan 1017 0.000388 0.003575 0.001657 0.005117 0.004157 0.001096 0.001890 18 Other Services Yuan/Yuan 1018 0.027000 0.034157 0.027729 0.059892 0.020180 0.025397 0.027297 Sub-total Yuan/Yuan 0.408220 0.569366 0.753995 0.688653 0.517639 0.637960 0.650633 --- --- --- --- --- --- --- -- --- ------- --- --- .. ... .. --- --- --- --- --- --- --- --- --- -- --- --- 8 9 10 11 12 13 14 15 16 17 18 90AI 91A1 92A1 93A 94AI 95AI 96A1 97A 98A 99A 100A1 0.000070 0.016426 0.000026 0.000332 0.000247 0.185500 0.001136 0.000064 0.027891 0.000008 0.003394 0.052897 0.002225 0.050286 0.011400 0.002299 0.002185 0.000619 0.005337 0.001635 0.003493 0.001327 0.032161 0.017077 0.000000 0.013180 0.002998 0.002559 0.005231 0.055935 0.007959 0.039487 0.010922 0.012171 0.002232 0.000000 0.000191 0.000069 0.000091 0.000661 0.000113 0.000047 0.000000 0.000118 0.082872 0.013238 0.051982 0.010116 0.009304 0.010122 0.002400 0.008978 0.007671 0.006158 0.009285 0.009381 0.005841 0.051181 0.017977 0.093940 0.011000 0.055985 0.004216 0.001959 0.003235 0.001630 0.001303 0.010559 0.000827 0.008424 0.047146 0.006798 0.003027 0.000441 0.000787 0.000328 0.000418 0.010613 0.003517 0.000004 0.000372 0.000043 0.000170 0.000026 0.000000 0.000023 0.000000 0.000042 0.071676 0.360000 0.007428 0.076396 0.048064 0.078572 0.045610 0.033226 0.002890 0.012751 0.008789 0.002066 0.000528 0.052000 0.008265 0.001848 0.000292 0.072937 0.001472 0.004315 0.000992 0.004117 0.088909 0.010598 0.131282 0.112789 0.017413 0.006189 0.211600 0.002888 0.008275 0.002289 0.015464 0.042675 0.036587 0.056751 0.068707 0.330467 0.080504 0.125937 0.081900 0.021466 0.093281 0.0488% 0.066144 0.091585 0.062130 0.060929 0.038261 0.273229 0.061693 0.028630 0.157765 0.025092 0.095710 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.040000 0.021696 0.080120 0.058000 0.016077 0.024000 0.029541 0.012582 0.010521 0.009848 0.025700 0.055581 0.052874 0.039569 0.042453 0.036752 0.045293 0.034340 0.021584 0.028007 0.013416 0.012765 0.001358 0.000987 0.001786 0.001938 0.001776 0.000825 0.000792 0.002574 0.005248 0.004061 0.020922 0.022015 0.024229 0.025859 0.037793 0.041251 0.032000 0.019581 0.081953 0.184911 0.082738 0.058032 0.591892 0.670200 0.611232 0.529262 0.687955 0.759330 0.671114 0.341893 0.471371 0.297177 0.317532 ----- - --- --- --- .. ... .... -- --- ---. -- - - --- ---.. - --- --- --- ... ... ... ... ... ... . --- ---- -- ... ... WORKING DATE: JUNE 9,1994 YEAR 2010 Direct Input Coefficients ( 18 Secters) (ECONOMIC GROWTH RATE: 9.5/,8%,6.5%; BASELINE SCENARIO) 1 2 3 4 5 6 7 Units 93Al 94Al 95Al 96Al 97AI 98Al 99Al I Agriculture Yuan/Yuan 1101 0.139942 0.005463 0.000064 0.000115 0.000308 0.000505 0.001649 2 Coal Yuan/Yuan 1102 0.000684 0.053231 0.002782 0.002687 0.193098 0.035111 0.009929 3 Oil & Refineries Yuan/Yuan 1103 0.006776 0.012652 0.381400 0.047884 0.016253 0.004366 0.005933 4 Natural Gas Yuan/Yuan 1104 0.000098 0.000176 0.000000 0.048138 0.005145 0.000909 0.000189 S Electricity Yuan/Yuan 1105 0.003781 0.063762 0.042745 0.013597 0.015973 0.037015 0.044108 6 Ferrous Metals Yuan/Yuan 1106 0.001253 0.021416 0.014885 0.034425 0.006289 0.220375 0.010490 7 Non-ferrous Metals Yuan/Yuan 1107 0.000067 0.000955 0.000273 0.000286 0.000892 0.013328 0.261563 8 Chemical Fertilizers Yuan/Yuan 1108 0.049500 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9 Chemical Industries Yuan/Yuan 1109 0.024200 0.035560 0.032031 0.057914 0.014409 0.019101 0.037507 10 Cement Yuan/Yuan 1110 0.000611 0.008851 0.003877 0.011459 0.003012 0.001623 0.002070 11 Building Materials Yuan/Yuan 1111 0.003182 0.009895 0.008624 0.015257 0.005724 0.034980 0.016243 12 Heavy Mach.& Electronics Yuan/Yuan 1112 0.015829 0.167649 0.073488 0.226482 0.083712 0.131896 0.054922 13 Light Industry Yuan/Yuan 1113 0.094037 0.099884 0.020188 0.042539 0.045176 0.030187 0.040099 14 Construction Yuan/Yuan 1114 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 15 Transport & Communications Yuan/Yuan 1115 0.031333 0.028318 0.070989 0.023214 0.052413 0.033049 0.023841 16 Commerce Yuan/Yuan 1116 0.048078 0.045000 0.066909 0.049633 0.040000 0.067839 0.054000 17 Passenger Transport Yuan/Yuan 1117 0.000488 0.004965 0.002038 0.006434 0.005226 0.001503 0.002377 13 Other Services Yuan/Yuan 1118 0.030067 0.067495 0.031031 0.107145 0.039102 0.049573 0.048833 Sub-total Yuan/Yuan 0.449927 0.625271 0.751323 0.687209 0.526732 0.681360 0.613753 :3 x [ At 1990 Producer's Prices I 8 9 10 11 12 13 14 15 16 17 18 100al 101al 102a1 103a1 104a1 105al 106a1 107a1 108al 109a1 iloal 0.000055 0.012485 0.000020 0.000253 0.000188 0.160994 0.000863 0.000049 0.021199 0.000006 0.002580 0.044213 0.001536 0.041448 0.007676 0.001589 0.001468 0.000481 0.002037 0.000884 0.001150 0.000612 0.019827 0.014687 0.000000 0.004931 0.001427 0.001681 0.003647 0.046585 0.005792 0.029986 0.006693 0.010005 0.003049 0.000000 0.000643 0.000052 0.000134 0.000461 0.000094 0.000219 0.000000 0.000458 0.073634 0.010548 0.048259 0.006836 0.007537 0.008551 0.002236 0.011424 0.006788 0.004053 0.009130 0.008428 0.005053 0.042928 0.015552 0.079919 0.010000 0.047084 0.003647 0.001695 0.002798 0.001410 0.001163 0.009076 0.000711 0.007240 0.040521 0.005843 0.002602 0.000379 0.000676 0.000282 0.000360 0.008817 0.002814 0.000003 0.000298 0.000034 0.000136 0.000020 0.000000 0.000018 0.000000 0.000034 0.073688 0.370000 0.007353 0.075632 0.047583 0.077786 0.035454 0.032894 0.002861 0.012624 0.008702 0.001545 0.000380 0.045000 0.030000 0.001330 0.000211 0.040300 0.001060 0.003107 0.000715 0.002964 0.080309 9.009219 0.114192 0.092362 0.015146 0.005384 0.200000 0.002512 0.007198 0.001991 0.013451 0.039821 0.032876 0.050995 0.061738 0.330000 0.072339 0.113164 0.073593 0.019288 0.083820 0.053937 0.076275 0.101702 0.068993 0.067660 0.039156 0.282000 0.067403 0.031793 0.145000 0.027863 0.096283 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.040000 0.021882 0.080808 0.057000 0.016215 0.024000 0.040000 0.012690 0.010612 0.009932 0.025920 0.055000 0.053000 0.060126 0.043000 0.040000 0.052000 0.062180 0.032798 0.042557 0.020387 0.019397 0.001773 0.001241 0.002246 0.002436 0.002233 0.001038 0.000996 0.003237 0.006598 0.005105 0.026305 0.040899 0.043346 0.046262 0.067611 0.073798 0.053272 0.047140 0.107000 0.230000 0.118000 0.103818 0.575453 0.692894 0.609344 0.540867 0.696729 0.756836 0.664030 0.361791 0.504494 0.318712 0.372053 e WORKING DATE: JUNE 9,1994 YEAR 2020 Direct Input Coefficients ( 18 Secters) [At 1990 Prod (ECONOMIC GROWTH RATE: 9.5%,8%,6.5%; BASELINE SCENARIO) 1 2 3 4 5 6 7 Units 2003Al 2004Al 2005Al 2006Al 2007Al 2008Al 2009Al 1 Agriculture Yuan/Yuan 1201 0.128882 0.004808 0.000057 0.000101 0.000271 0.000444 0.001451 2 Coal Yuan/Yuan 1202 0.000628 0.049022 0.002822 0.002323 0.195075 0.027937 0.008919 3 Oil & Refineries Yuan/Yuan 1203 0.005894 0.011938 0.458800 0.041390 0.011687 0.003039 0.005305 4 Natural Gas Yuan/Yuan 1204 0.000181 0.000166 0.000000 0.041609 0.005755 0.001085 0.000239 5 Electricity Yuan/Yuan 1205 0.003732 0.069521 0.041185 0.011753 0.015729 0.036465 0.040981 6 Ferrous Metals Yuan/Yuan 1206 0.000680 0.019917 0.013843 0.032015 0.005849 0.220000 0.005245 7 Non-ferrous Metals Yuan/Yuan 1207 0.000060 0.000860 0.000246 0.000257 0.000803 0.011996 0.240000 8 Chemical Fertilizers Yuan/Yuan 1208 0.043500 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9 Chemical Industries Yuan/Yuan 1209 0.024200 0.035560 0.032031 0.057914 0.006550 0.019101 0.037507 10 Cement Yuan/Yuan 1210 0.000501 0.007258 0.003179 0.0093% 0.002470 0.001331 0.001698 11 Building Materials Yuan/Yuan 1211 0.003182 0.009895 0.008624 0.015257 0.005724 0.034980 0.016243 t- 12 Heavy Mach.& Electronics Yuan/Yuan 1212 0.017253 0.160000 0.026121 0.246865 0.058312 0.131924 0.036966 13 Light Industry Yuan/Yuan 1213 0.115300 0.049942 0.009069 0.038285 0.043358 0.028968 0.022285 14 Construction Yuan/Yuan 1214 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 15 Transport & Communications Yuan/Yuan 1215 0.031902 0.046337 0.072279 0.023636 0.053366 0.033650 0.024275 16 Commerce Yuan/Yuan 1216 0.062324 0.049000 0.069697 0.064339 0.038362 0.087939 0.054344 17 Passenger Transport Yuan/Yuan 1217 0.001464 0.011160 0.002649 0.008364 0.006794 0.001954 0.003090 18 Other Services Yuan/Yuan 1218 0.036080 0.080994 0.037237 0.089728 0.079538 0.059488 0.058600 Sub-total Yuan/Yuan 0.475765 0.606376 0.777838 0.683233 0.529642 0.700302 0.557148 N ccr's Prices I 8 9 10 11 12 13 14 15 16 17 18 2010AI 2011AI 2012A1 2013A1 2014A1 2015AI 2016A1 2017A1 2018Al 2019AI 2020A1 0.000110 0.008503 0.000010 0.000210 0.000418 0.149071 0.000760 0.000043 0.018655 0.000005 0.002270 0.034118 0.000838 0.036349 0.005295 0.001173 0.001114 0.000393 0.000000 0.000766 0.000000 0.000375 0.007734 0.014552 0.000000 0.002727 0.000756 0.001240 0.002641 0.039127 0.003534 0.021951 0.005104 0.008781 0.004279 0.000000 0.000533 0.000039 0.000170 0.000334 0.000079 0.000172 0.000000 0.000449 0.059188 0.008709 0.044001 0.004928 0.006595 0.008109 0.002131 0.015352 0.005943 0.003709 0.008392 0.004214 0.002914 0.025996 0.008394 0.064981 0.008323 0.040000 0.003392 0.001576 0.002603 0.001311 0.000581 0.006492 0.000668 0.005211 0.032494 0.003197 0.001301 0.000341 0.000609 0.000253 0.000324 0.010138 0.002768 0.000002 0.000191 0.000023 0.000180 0.000021 0.000000 0.000019 0.000000 0.000035 0.108648 0.380000 0.004325 0.080000 0.040541 0.080000 0.055454 0.015729 0.002861 0.012624 0.008702 0.000773 0.000190 0.042394 0.025180 0.000670 0.000106 0.027976 0.000869 0.002547 0.000586 0.002431 0.048231 0.007752 0.130337 0.101553 0.012110 0.005279 0.185000 0.002512 0.007198 0.001991 0.013451 0.036120 0.027018 0.042759 0.055889 0.352300 0.059028 0.093080 0.080216 0.021024 0.091363 0.038000 0.082852 0.094469 0.041877 0.064809 0.030776 0.307031 0.061663 0.028614 0.128241 0.025077 0.095655 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.040000 0.021988 0.084601 0.056000 0.026907 0.018672 0.049034 0.012920 0.019000 0.010113 0.026391 0.063300 0.052313 0.059868 0.045305 0.045638 0.057812 0.067641 0.042516 0.055167 0.026427 0.017000 0.001117 0.001372 0.002587 0.002639 0.002561 0.001477 0.012258 0.004208 0.016258 0.006637 0.034196 0.052658 0.054186 0.074183 0.070778 0.086000 0.053994 0.076000 0.127322 0.253648 0.128500 0.137033 0.558563 0.688341 0.589956 0.529642 0.703981 0.754803 0.675686 0.373240 0.537219 0.331839 0.391120 lrg WORKING DATE: JUNE 9,1994 YEAR 2000 Direct Input Coefficients ( 18 Secters) (ECONOMIC GROWTH RATE: 9.5%,8%,6.5%, HIGH EFFICIENCY SCENARIO) 1 2 3 4 5 6 Units 83Al 84Al 85Al 86Al 87Al 88Al I Agriculture Yuan/Yuan 1001 0.140000 0.006508 0.000086 0.000151 0.000405 0.000608 2 Coal Yuan/Yuan 1002 0.000811 0.063598 0.002743 0.004409 0.183559 0.042120 3 Oil & Refineries Yuan/Yuan 1003 0.008052 0.013793 0.297871 0.078564 0.027822 0.005564 4 Natural Gas Yuan/Yuan 1004 0.000022 0.000192 0.000000 0.078981 0.002283 0.000818 5 Electricity Yuan/Yuan 1005 0.003867 0.058701 0.035425 0.022308 0.018009 0.035343 6 Ferrous Metals Yuan/Yuan 1006 0.001448 0.022412 0.017586 0.039792 0.007270 0.233474 7 Non-ferrous Metals Yuan/Yuan 1007 0.000078 0.001006 0.000325 0.000333 0.001038 0.014213 8 Chemical Fertilizers Yuan/Yuan 1008 0.055978 0.000000 0.000000 0.000000 0.000000 0.000000 9 Chemical Industries Yuan/Yuan 1009 0.014668 0.032519 0.033069 0.058499 0.014554 0.017684 10 Cement Yuan/Yuan 1010 0.000849 0.011130 0.005503 0.015915 0.004183 0.002066 11 Building Materials YuanfYuan 1011 0.003658 0.010300 0.010133 0.017541 0.006580 0.036859 12 Heavy Mach. & Electronics Yuan/Yuan 1012 0.012328 0.168914 0.147951 0.252046 0.093161 0.114132 13 Light Industry Yuan/Yuan 1013 0.076366 0.081434 0.019502 0.038307 0.043383 0.026566 14 Construction Yuan/Yuan 1014 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 15 Transport & Communications Yuan/Yuan 1015 0.031066 0.025419 0.071939 0.023016 0.051967 0.030033 16 Commerce Yuan/Yuan 1016 0.031640 0.038953 0.051732 0.032663 0.043538 0.040918 17 Passenger Transport Yuan/Yuan 1017 0.000388 0.003575 0.001657 0.005117 0.004157 0.001096 18 Other Services Yuan/Yuan 1018 0.027000 0.034157 0.037729 0.059892 0.020180 0.025397 Sub-total Yuan/Yuan 0.408220 0.572610 0.733251 0.727535 0.522090 0.626892 ... --- --- --- --- --- --- --- --- --- -- --- --- - - ---- -- --- --- --- --- --- ---- --- --- --- -- --- -- [ At 1990 Producers Prices ] 7 8 9 10 11 12 13 14 is 16 17 Is 89Al 90Al 91Al 92Al 93Al 94Al 95Al 96Al 97Al 98Al 99Al IOOAI 0.002170 0.000070 0.016426 0.000026 0.000332 0.000247 0.185500 0.001136 0.000064 0,027891 0.000008 0.003394 0.011515 0.047538 0.001902 0.042345 0.010777 0.002068 0.002067 0.000557 0.005327 0.001635 0.003449 0.001260 0.007343 0.038578 0.014599 0.000000 0.012459 0.002697 0.002421 0.004711 0.055828 0,007959 0.038982 0.010366 0.000147 0.014600 0.001908 0.000000 0.000180 0.000062 0.000086 0.000595 0.000112 0.000047 0.000000 0.000112 0.049984 0.070670 0.011318 0.051460 0.009563 0.008370 0.009577 0.002161 0.008961 0.007671 0.006080 0.008813 0.012125 0.009381 0.005841 0.051181 0.017977 0.093940 0.011000 0.065985 0.004216 0.001959 0.003235 0.001630 0.304327 0.001303 0.010559 0.000827 0.008424 0.047146 0.006798 0.003027 0.000441 0.000787 0.000328 0.000418 0.000000 0.010613 0.003517 0.000004 0.000372 0.000043 0.000170 0.000026 0.000000 0.000023 0.000000 0.000042 0.037886 0.071676 0.360000 0.007428 0.076396 0.048064 0.078572 0.045610 0.033226 0.002890 0.012751 0.008789 0.002875 0.002066 0.000528 0.052000 0.008265 0.001848 0.000292 0.072937 0.001472 0.004315 0.000992 0.004117 0.018674 0.088909 0.010598 0.131282 0.112789 0.017413 0.006189 0.211600 0.002888 0.008275 0.002289 0.015464 0.061121 0.042675 0.036587 0.056751 0.068707 0.330467 0.080504 0.125937 0.081900 0.021466 0.093281 0.048896 0.036110 0.066144 0.091585 0.062130 0.060929 0.038261 0.273229 0.061693 0.028630 0.157765 0.025092 0.095710 oo 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.023638 0.040000 0.021696 0.080120 0.058000 0.016077 0.024000 0.029541 0.012582 0.010521 0.009848 0.025700 0.053530 0.055581 0.052874 0.049569 0.042453 0.036752 0.045293 0.034340 0.021584 0.028007 0.013416 0.012765 0.001890 0.001358 0.000987 0.001786 0.001938 0.001776 0.000825 0.000792 0.002574 0.005248 0.004061 0.020922 0.027297 0.022015 0.024229 0.035859 0.037793 0.051251 0.032000 0.019581 0.081953 0.184911 0.082738 0.058032 0.650633 0.583176 0.665156 0.622769 0.527355 0.696482 0.758525 0.680228 0.341758 0.471371 0.296549 0.316430 --- --- --- - - --- --- -- --- -- -- --- -- --- . ... ... .. .. .. ... ... . ... .. ... ... .. ... .. .. ... .. .. .. . .... . --- -- WORKING DATE: JUNE 9,1994 YEAR 2010 Direct Input Coefficients ( 18 Secters) (ECONOMIC GROWTH RATE: 9.5%,8%,6.5%; HIGH EFFICIENCY SCENARIO) 1 2 3 4 5 6 Units 93Al 94Al 95Al 96Al 97Al 98Al I Agriculture Yuan/Yuan 1101 0.139942 0.005463 0.000064 0.000115 0.000308 0.000505 2 Coal Yuan/Yuan 1102 0.000684 0.056600 0.002800 0.003368 0.207413 0.026575 3 Oil & Refineries Yuan/Yuan 1103 0.006776 0.013453 0.332100 0.060002 0.017457 0.003304 4 Natural Gas Yuan/Yuan 1104 0.000098 0.000187 0.000000 0.060320 0.005526 0.000688 S Electricity Yuan/Yuan 1105 0.003781 0.067797 0.042041 0.017037 0.017200 0.028017 6 Ferrous Metals Yuan/Yuan 1106 0.001253 0.021416 0.014885 0.034425 0.006289 0.220375 7 Non-ferrous Metals Yuan/Yuan 1107 0.000067 0.000955 0.000273 0.000286 0.000892 0.013328 8 Chemical Fertilizers Yuan/Yuan 1108 0.049500 0.000000 0.000000 0.000000 0.000000 0.000000 9 Chemical Industries Yuan/Yuan 1109 0.024200 0.035560 0.032031 0.057914 0.014409 0.019101 10 Cement Yuan/Yuan 1110 0.000611 0.008851 0.003877 0.011459 0.003012 0.001623 11 Building Materials Yuan/Yuan 1111 0.003182 0.009895 0.008624 0.015257 0.005724 0.034980 12 Heavy Mach. & Electronics Yuan/Yuan 1112 0.015829 0.167649 0.073488 0.226482 0.083712 0.131896 13 Light Industry Yuan/Yuan 1113 0.094037 0.099884 0.021188 0.042539 0.045176 0.030187 14 Construction Yuan/Yuan 1114 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 15 Transport & Commrnications YuanL/Yuan 1115 0.031333 0.028318 0.080989 0.023214 0.052413 0.033049 16 Commerce Yuan/Yuan 1116 0.048078 0.045000 0.076909 0.049633 0.040000 0.067839 17 Passenger Transport Yuan/Yuan 1117 0.000488 0.004965 0.002038 0.006434 0.005226 0.001503 18 Other Services Yuan/Yuan 1118 0.030067 0.067495 0.051031 0.107145 0.036102 0.059573 Sub-total Yuan/Yuan 0.449927 0.633488 0.742337 0.715631 0.540860 0.672544 x At 1990 Producer's Prices] 7 8 9 10 l1 12 13 14 15 16 17 18 99AI 100ai 101al 102al 103al 104al loSal 106a1 107al 108a1 109al 110al 0.001649 0.000055 0.012485 0.000020 0.000253 0.000188 0.170994 0.000863 0.000049 0.021199 0.000006 0.002580 0.009929 0.035064 0.001227 0.031854 0.007138 0.001289 0.001288 0.000411 0.002029 0.000884 0.001119 0.000523 0.005933 0.027774 0.011737 0.000000 0.004585 0.001157 0.001475 0.003120 0.046405 0.005792 0.029178 0.005727 0.000189 0.014015 0.002436 0.000000 0.000598 0.000042 0.000118 0.000394 0.000093 0.000219 0.000000 0.000392 0.044108 0.052430 0.008430 0.047485 0.006357 0.006113 0.007500 0.001913 0.011380 0.006788 0.003944 0.007812 0.010490 0.008428 0.005053 0.042928 0.015552 0.079919 0.010000 0.057084 0.003647 0.001695 0.002798 0.001410 0.261563 0.001163 0.009076 0.000711 0.007240 0.040521 0.005843 0.002602 0.000379 0.000676 0.000282 0.000360 0.000000 0.008817 0.002814 0.000003 0.000298 0.000034 0.000136 0.000020 0.000000 0.000018 0.000000 0.000034 0.037507 0.073688 0.370000 0.007353 0.075632 0.047583 0.077786 0.035454 0.032894 0.002861 0.012624 0.008702 0.002070 0.001545 0.000380 0.045000 0.030000 0.001330 0.000211 0.040300 0.001060 0.003107 0.000715 0.002964 0.016243 0.080309 0.009219 0.114192 0.092362 0.015146 0.005384 0.200000 0.002512 0.007198 0.001991 0.013451 0.054922 0.039821 0.032876 0.050995 0.061738 0.330000 0.072339 0.113164 0.073593 0.019288 0.083820 0.043937 0.040099 0.076275 0.101702 0.068993 0.067660 0.039156 0.282000 0.067403 0.031793 0.145000 0.027863 0.106283 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.023841 0.040000 0.021882 0.080808 0.057000 0.026215 0.024000 0.040000 0.012690 0.010612 0.009932 0.025920 0.054000 0.065000 0.053000 0.060126 0.043000 0.040000 0.052000 0.062180 0.032798 0.042557 0.020387 0.019397 0.002377 0.001773 0.001241 0.002246 0.002436 0.002233 0,001038 0.000996 0.003237 0.006598 0.005105 0.026305 0.048833 0.050899 0.043346 0.066262 0.067611 0.073798 0.043272 0.047140 0.107000 0.230000 0.118000 0.103818 0.613753 0.577057 0.686905 0.618977 0.539460 0.704725 0.755381 0.673043 0.361559 0.504494 0.317763 0.369615 .... ... .... . . . ... . . ... .... . - - ----- --- -- -- ---- - x* WORKING DATE: JUNE 9,1994 YEAR 2020 Direct Input Coefficients ( 18 Secters) (ECONOMIC GROWTH RATE: 9.5%,8%,6.5%; HIGH EFFICIENCY SCENARIO) 1 2 3 4 5 6 Units 2003AI 2004AI 2005AI 2006A1 2007Al 2008A1 I Agriculture Yuan/Yuan 1201 0.128882 0.004808 0.000057 0.000101 0.000271 0.000444 2 Coal Yuan/Yuan 1202 0.000628 0.054904 0.002786 0.002724 0.183412 0.018521 3 Oil& Refineries Yuan/Yuan 1203 0.005894 0.013370 0.408800 0.048532 0.010988 0.002015 4 Natural Gas Yuan/Yuan 1204 0.000181 0.000186 0.000000 0.048790 0.005411 0.000719 5 Electricity Yuan/Yuan 1205 0.003732 0.077863 0.042607 0.013781 0.015585 0.024174 6 Ferrous Metals Yuan/Yuan 1206 0.000680 0.019917 0.013843 0.032015 0.005849 0.220000 7 Non-fenrous Metals Yuan/Yuan 1207 0.000060 0.000860 0.000246 0.000257 0.000803 0.011996 8 Chemical Fertilizers Yuan/Yuan 1208 0.043500 0.000000 0.000000 0.000000 0.000000 0.000000 9 Chemical Industries Yuan/Yuan 1209 0.024200 0.035560 0.032031 0.057914 0.006550 0.019101 10 Cement Yuan/Yuan 1210 0.000501 0.007258 0.003179 0.009396 0.002470 0.001331 11 Building Materials Yuan/Yuan 1211 0.003182 0.009895 0.008624 0.015257 0.005724 0.034980 12 HeavyMach.& Electronics Yuan/Yuan 1212 0.017253 0.150000 0.026121 0.246865 0.058312 0.131924 13 Light Industry YuandYuan 1213 0.115300 0.049942 0.009069 0.038285 0.043358 0.028968 14 Construction Yuan/Yuan 1214 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 15 Transport& Communications YuanfYuan 1215 0.031902 0.046337 0.080228 0.023636 0.053366 0.033650 16 Commerce Yuan/Yuan 1216 0.062324 0.049000 0.099697 0.064339 0.038362 0.087939 17 Passenger Transport Yuan/Yuan 1217 0.001464 0.011160 0.002649 0.008364 0.006794 0.001954 18 Other Services Yuan/Yuan 1218 0.036080 0.080994 0.037237 0.089728 0.079538 0.059488 Sub-total YuanfYuan 0.475765 0.612053 0.767173 0.699985 0.516792 0.677204 e x w [ At 1990 Ртnдиоа'в Prices ] 7 8 9 10 11 12 13 14 15 16 17 18 2009А1 2010А1 2011А1 2012А1 2013А1 2014А1 2015А1 2016А1 2017А1 2018А1 2019А1 2020А1 0.001451 0.000110 0.008503 0.000010 0.000210 0.000418 0.159071 0.000760 0.000043 0.018655 0.000005 0.002270 0.008919 0.021979 0.000654 0.026502 0.005252 0.000859 0.000911 0.000Э 19 0.000000 0.000766 0.000000 0.000289 0.005305 0.014172 0.011371 0.000000 0.002705 0.000553 0.001014 0.002147 0.038$30 0.003534 0.021191 0.003942 0.000239 0.016091 0.003344 0.000000 0.000529 0.000028 0.000139 0.000271 0.000078 0.000172 О.ООООо0 0.000347 о.оао981 о.0289аа о.ообвоб о.оаз2оо о.ооав88 о.ооа827 о.ообб29 о.оо17з2 О.оlsгзб о.ооs94з о.оозsво о.ообавl 0.005245 0.004214 0.002914 0.025996 0.008394 0.064981 0.008323 0.040000 0.003392 0.001576 0.002603 0.001311 0.240000 0.000581 O.G06492 0.000668 0.005211 0.032494 0.003197 0.001301 0.000341 0.000609 0.000253 0.000324 0.000000 0.010138 0.002768 О.ОООо02 0.000191 0.000023 0.000180 0.000021 0.000000 0.000019 0.000000 о.000035 о.037507 0.108648 0.380000 0.004325 0.080000 0.0�10541 0.080000 0.055454 0.015729 0.002861 0.012624 0.008702 0.001698 0.000773 0.000190 о.042394 0.015180 0.000670 0.000106 0.027976 0.000869 0.002547 0.000586 0.002431 0.016243 0.048231 0.007752 0.130337 0.101553 0.012110 0.005279 0.185000 0.002512 0.007198 0.001991 0.013451 0.036966 0.036120 0.027018 0.032759 О.о45889 0.352300 0.059028 0.о93080 0.080216 0.021024 0.091363 0.038000 N 0.022285 0.082852 0.064469 0.041877 0,054809 0.030776 0.307031 0.061663 0.028614 0.128241 0.025077 0.095655 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.024275 0.040000 0.021988 0.084601 0.056000 0.026907 0.018672 0.049034 0.012920 о.019000 0.010113 0.026391 0.054344 0.063300 о.052313 0.059868 0.045305 0.0456Э8 0.057812 0.067641 0.042516 0.055167 0.026427 0.019000 0.003090 0.001117 0.001372 0.002587 0.002639 0.002561 0.001477 0.012258 0.004208 0.016258 0.006637 0.034196 0.058600 0.062658 0.054186 0.084183 0.070778 0.086000 0.053994 0.076о00 0.127322 0.253648 0.128500 0.137033 0.557148 0.539929 0.652138 0.579309 0.499532 0.701686 0.762863 0.674657 0.372826 о.537219 0.330951 0.389859 а � � А х nr WORKИG DATB: JUNE Y.1YW 2000 DУве9 У�рА СадllдвгRв (18 алеbгв ) ( А110У0 Ргодисг/s Rieп j (ЕСОИОМIС GROYViH RATE: 6.5%.в.5ц. 5х: s!t �вf�(rR �,.�T1i 1 z з в s е 7 а я 1о 11 и и 11 и 1е 17 1е Urih ааА1 ыА1 85А1 авА1 а7А1 ааА1 8УА1 ооА1 о1А1 92А1 УаА/ а1А1 У5А1 96А1 У7А1 9вА1 УУА1 100А1 + Аак,lаг. rи�n�и ро/ о.lвоооо о.оовsоа оооооев о.оооцl o.ooaos о.аооеоа o.ooz»о о.оооо7о ооlы2е о.оооо2е о.оооап o.oooza o.lassoo о.ооllх о.аооов4 о.оz7ая/ о.ооооое о.аоnвl z гА.1 r�wr�м aoz о.оооаll о.овцяе о.оо2iно о.оы7а7 о.lяяив о.омsао о.о12в2о o.os2n2 о.ооz2в7 o.osolee о.оlаам о.оа�zап о.оа�хи2 o.ooaesz o.aossвo о.аоlаlа о.оозsая о.ооип а а1 а кии�мг. rwrvrw, ат о.аоеоц о.оlз7яа о2а7яоо о.оацяа о.ог7жг о.оовм7 о.оо7о2о o.mzoal о.оnзое о.оооооо о.оlsв2я о.аохяа о.оа�гаео o.oosslo o.oseo7o o.aoeaze о.омs71 o.oпlts + и.аг.1 с.. 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X m 118 0.04904 0.00283V 0.003W 0.177070 0.029801 0.010442 0,037289 0.00000S 0.037963 0.009047 0.001827 0.001533 0.0004SS 0.000000 0.001042 0.000000 0.000510 3 01 A IRS&WAVS Yuawyumn 1203 0.00S894 0.013370 0.380000 0.088522 0.010609 0.003221 0.000210 0.008453 0.015029 0.0000W 0404GS9 0.001177 0.001707 0.003051 0.044324 0.0048477 0.025030 0.008W 4 Nakwal Gas YuwVYumn tM4 0.000181 0.000188 0.000000 0.06M 0.00=4 0.001149 0.000280 O.OM97 0.004419 0.0000W 0.000911 0.000081 0.0002" 0.000M 0.090M 0.000233 0A00= 0.000611 5 EWctAdty Yuwy/YLan M 0.003732 0.077863 0.04671111 0.019457 0.015313 0.03037 0.047970 0.06090 0.00899S 0.04400S 0.009420 0.010270 0.011160 0.002486 0.017301 0.0081*6 0.004230 0.0114" 6 FwroLm M&Ws Yuwtlyumn 20 0.000660 0.019917 0.00643 0.0320IS 0.005"9 0200000 0.00524S 0.004214 0,002914 0.03SM 0.006394 0.074951 0.008:123 0.050000 0.003392 0.001S70 O.OMM 0.001311 7 Non4mmus I I YunnfYumn 1207 0.000080 0.000600 0.01=48 0.000257 0.000603 0.0111995 0,240000 0.000$81 0.008492 0.000088 O.OOS21 1 0.032494 0.003197 0.001301 OA00341 0.0000419 OA002S3 0.000324 a ChOmIcel Fwskws YuwVYLwn 2W 0.043SOO 0.000000 0,000000 0.000000 0.000000 0.000000 0.000000 0.010138 0.002768 0.000002 0.000191 0.000023 0.000130 0. 1 0.00ww 0.000019 0.000wo 0. 9 Chem" Irw6nirfes Yumfl/yumn 1209 0.024200 0.03S590 0.0= 1 0.067914 0.006SW 0.019101 0.03TSQ? 0.1005" 0.390NO 0.004325 0.060000 0.040641 0.080000 0.0554S4 0.915rA 0.00201111 0.012SZ4 0.009M 10 C*m0rlt YUDWYU&n 1210 0. 1 0.007258 0.003179 0.009M 0,002470 0.001331 0.001698 0.000773 0.000190 0.042394 0.01IS1180 0.000070 0.000100 0.027976 0.000089 0.002547 0.000511111 0.002431 ON I Bumm I I wis Yu&WYLwn 1211 0.003182 0.009M 0,008024 0.0lS2S? 0.005744 O.O3.4M 0.016243 0.048231 0.0077S2 0.130337 OAOISS3 0.0121 tO 0.005279 0.1 0.002512 0.007198 0.001901 0.013451 "'ll 2 HesW Mach. S, ElwWorics Yu*WYusn 1212 0.0172S3 0,160000 0.028121 0.24ONS 0059312 0.0711924 0.0309010 0.028120 0.027018 0.032TS9 0,04SON 0.323000 0.059026 0.093000 0.08=10 0.021024 0.001383 0.038m 13 Ughl kWuWy Yuw"umn 1213 0.115300 0.049942 0.009009 0.03628S 0.043358 0.0280168 0.022295 O.OS2852 0.054469 0.041877 0.054809 0.030770 02703110 0.09110011 0.028614 0.120241 0.025W 0.09501115 14 Canaludon Yusr"umn 04 0.000000 0.000M 0.000000 0.000000 0.000000 0.0009W 0,000000 0.000000 0.000000 0.000000 0.000000 0.000000 0. 0.0000w 0.000m 0.000m 0.0001m 0.000000 15 Trt & Commmilesilms Yu&Wumn 1215 0.031M 0.046"7 0.072279 0.0236M 0.053306 0.033050 0.02427S 0.040000 0.021M 0.08MI 0.036M 0.010907 0.010072 0.049M 0.012020 0.019= OA10113 0.02=1 Is Conmem YuwtfYusn 1216 0,002324 0.0490W 0.099097 0.064339 0.036M 0.087939 0.054344 0.053300 0.052313 0.049M 0.04S305 0.049M 0.057612 0.06MI 0.042516 0.055W 0.02SW 0.017000 17 Passerw TmneW YUWVYuan 1217 0.001404 0.011100 0,0029,19 0.089304 0.006794 0.0019S4 0.003090 0.001117 0.0013n 0.002547 0.002630 0.002561 0.001477 0.012258 0.004206 0.0116256 0.0060111 0,034106 Is Olher SmIce's Yuwtfyum 1218 0.030080 0.000994 0.037237 0.009rA 0.07" O.OS94" 0.0SIDW 0.011209 O.OS4189 0.054193 0.070778 0.08M 0.053004 0.089M 0.1121 0253846 0.1121111500 0.137033 SLSIAWW YusWusn 0.475M 0.622M 0."6413 0.748M 0.50911111 0.624384 0.501111112 0.51111M 0.650VII 0.5111163S 0.50194 0.679M 0.7112063 0A 1 0-410487 0-40111711 0.335440 9-398200 tv31. x TO macroeconomic Projections Under Three Scenarios Baseline Scenario 1990 2000 2010 2020 1990 2000 Indus. % Output Value by Sector (100 million yuan) Outpui Shar I. Agriculture 7662 11795 19134 28081 17.98% 11.00% II. 1. Coal industry 2.73% 654 1.61% 980 1.16% 1443 0.89/ 1976 1.53% 0.91% 2. Oil industry 4.14% 989 2.06% 1256 1.30% 1627 0.90% 2001 2.32% 1.17% 3. Natural gas 0.09% 22 0.09% 53 0.12% 149 0.14% 306 0.05% 0.05% 4. Power 2.99% 714 2.48% 1510 2.27% 2839 2.16% 4798 1.68% 1.41% 5. Ferrous 6.12% 1464 4.44% 2703 4.04% 5040 3.34% 7424 3.43% 2.52% 6. Non-ferrous 2.95% 705 2.69% 1635 2.34% 2923 1.79% 3970 1.65% 1.52% 7. Fertilizer industry 1.59% 380 0.88% 535 0.63% 791 0.48% 1068 0.89% 0.50% 8. Chemical industry 6.31% 1510 6.62% 4027 6.87% 8569 7.43% 16507 3.54% 3.76% 9. Cement industry 1.97% 471 1.85% 1126 1.40% 1747 1.12% 2484 1.11% 1.05% 10.Other building materials 4.69% 1123 5.77% 3510 5.82% 7259 5.99% 13308 2.64% 3.27% 11. Machinery & Electric 17.05% 4079 22.44% 13644 24.57% 30657 26.14% 58040 9.57% 12.73% Heavy Industry 50.63% 12111 50.94% 30978 50.52% 63043 50.39% 111883 28.42% 28.90% 12. Light industry 49.37% 11811 49.06% 29830 49.48% 61745 49.61% 110167 27.72% 27.83% Industry total 100% 23922 100% 60808 100% 124788 100/* 222049 56.14% 56.72% 1.Construction 3009 11462 26660 52%1 7.06% 10.69% II. Secondary Industry 26931 72270 151449 275011 63.20% 67.42% III. 1. Communication 1535 3765 7986 15768 3.60% 3.51% 2. Commercial sector 1742 4693 12991 27469 4.09% 4.38% 3. Passenger transportation 340 726 2081 6130 0.80% 0.68/ 4. Other service sector 4400 13952 41198 91612 10.33% 13.01% III. TERTIARY 8017 23136 64256 140980 18.82% 21.58%M Total 42610 107201 234838 444071 100% 100% x WC Macroeconomic Projections Under Three Scenarios 2010 2020 2000 2010 2020 1990 2000 2010 2020 of 18 sectors Growth Rate of Each Sector Value-added and its Share in GDP of Each Sector 8.15% 6.32% 4.41% 4.96% 3.91% 4983 28.18% 6980 15.92% 10525 11.12% 14721 8.27% 0.61% 0.44% 4.14% 3.94% 3.19% 290 1.64% 422 0.%9% 541 0.57% 778 0.44% 0.69% 0.45% 2.41% 2.63% 2.09% 235 1.33% 309 0.70% 405 0.43% 445 0.25% 0.06% 0.07% 9.28% 10.86% 7.50% 2 0.01% 16 0.04% 46 0.05% 97 0.05% 1.21% 1.08% 7.77% 6.52% 5.39% 340 1.92% 728 1.66% 1343 1.42% 2257 1.27% 2.15% 1.67% 6.33% 6.43% 3.95% 476 2.69% 979 2.23% 1606 1.70% 2225 1.25% 1.24% 0.89% 8.78% 5.98% 3.11% 204 1.15% 571 1.30% 1129 1.19%. 1758 0.99% 0.34% 0.24% 3.49% 4.00% 3.04% 81 0.46% 218 0.50% 336 0.35% 471 0.26% 3.65% 3.72% 10.30% 7.84% 6.78% 424 2.40% 1328 3.03% 2632 2.78% 5145 2.89% 0.74% 0.56% 9.10% 4.49% 3.58% 168 0.95% 438 1.00% 682 0.72% 1018 0.57% 3.09% 3.00% 12.07% 7.53% 6.25% 438 2.48% 1652 3.77% 3333 3.52% 6259 3.52% o. 13.05% 13.07% 12.83% 8.43% 6.59% 1156 6.54% 4257 9.71% 9297 9.82% 17181 9.66% 26.85% 25.19% 9.85% 7.36% 5.90% 3814 21.57% 10919 24.91% 21350 22.5% 37634 21.15% 26.29% 24.81% 9.71% 7.55% 5.96% 3049 17.25% 7179 16.38% 15014 15.86% 25911 14.56% 53.14% 50.00% 9.78% 7.45% 5.93% 6863 38.82% 18099 41.28% 36364 38.41% 63545 35.72% 11.35% 11.93% 14.31% 8.81% 7.10% 867 4.91% 3770 8.60% 8957 9.46% 17176 9.65% 64.49% 61.93% 10.38% 7.68% 6.15% 7730 43.72% 21868 49.88% 45322 47.87% 80721 45.37% 3.40% 3.55% 9.39% 7.81% 7.04% 920 5.20% 2478 5.65% 5096 5.38% 9883 5.55% 5.53% 6.19% 10.42% 10.72% 7.78% 794 4.49% 2481 5.66% 6437 6.80% 12712 7.15% 0.89% 1.38% 7.87% 11.11% 11.41% 198 1.12% 510 1.16% 1418 1.50% 4096 2.30% 17.54% 20.63% 12.23% 11.44% 8.32% 3057 17.29% 9522 21.72% 25870 27.33% 55781 31.35% 27.36% 31.75% 11.18% 10.75% 8.17% 4968 28.10% 14991 34.19% 38822 41.01% 82472 46.35% 100% 100% 9.67% 8.16% 6.58% 17681 43839 94668 177914 GDP GROWTH RATE 9.51% 8.00% 6.51% Macroeconomic Projections Under Three Scenarios Slower Growth Scenario 1990 2000 2010 2020 1990 2000 Indus. % Output Value by Sector (100 million yuan) Output Shar I. Agriculture 7662 11231 15666 21338 17.98% 11.48% II. 1. Coal industry 2.73% 654 1.76% 986 1.35% 1379 1.05% 1649 1.53% 1.01% 2. Oil industry 4.14% 989 2.26% 1260 1.77% 1809 1.64% 2579 2.32% 1.29/6 3. Natural gas 0.09% 22 0.09% 51 0.13% 132 0.15% 243 0.05% 0.05% 4. Power 2.99% 714 2.67% 1492 2.62% 2678 2.67% 4191 1.68% 1.52% 5. Ferrous 6.12% 1464 4.76% 2661 4.29% 4391 3.48% 5478 3.43% 2.72% 6. Non-ferrous 2.95% 705 2.59% 1448 2.24% 2291 1.67% 2619 1.65% 1.48% 7. Fertilizer industry 1.59% 380 0.91% 509 0.62% 630 0.50% 791 0.89% 0.52% 8. Chemical industry 6.31% 1510 6.56% 3666 6.77% 6923 7.32% 11507 3.54% 3.75% 9. Cement industry 1.97% 471 1.74% 973 1.27% 1295 0.93% 1468 1.11% 0.99% 10.Other building materials 4.69% 1123 5.50% 3075 5.36% 5486 5.54% 8709 2.64% 3.14% 11. Machinery & Electric 17.05% 4079 20.75% 11597 22.17% 22679 21.98% 34553 9.57% 11.85% Heavy Industry 50.63% 12111 49.60% 27718 48.57% 49693 46.93% 73787 28.42% 28.33% 12. Light industry 49.37% 11811 50.40% 28168 51.43% 52612 53.07% 83442 27.72% 28.79% Industry total 100% 23922 100% 55886 100% 102305 100% 157229 56.14% 57.11% 1. Building sector 23922 3009 55886 9723 102305 19002 157229 31780 7.06% 9.94% II. Secondary Industry 26931 . 65609 121307 189010 63.20% 67.05% III. 1. Communication 1535 3492 6586 6.57 10842 3.60% 3.57% 2. Commercial sector 1742 4354 10462 19098 4.09% 4.45% 3. Passenger transportation 340 662 1636 4132 0.80% 0.68% 4. Other service sector 4400 12507 31872 62204 10.33% 12.78% Ill. TERTIARY 8017 21014 50555 96276 18.82% 21.48% Total 42610 97854 187528 306623 100% 100% Macroeconomic Projections Under Three Scenarios 2010 2020 2000 2010 2020 1990 2000 2010 2020 of 18 sectors Growth Rate of Each Sector Value-added and its Share in GDP of Each Sector 8.35% 6.96% 3.90% 3.38% 3.14% 4983 28.18% 6646 16.61% 8617 11.46% 11186 9.14% 0.74% 0.54% 4.20% 3.41% 1.80% 290 1.64% 425 1.06% 517 0.69% 649 0.53% 0.96% 0.84% 2.45% 3.68% 3.61% 235 1.33% 310 0.77% 450 0.60% 573 0.47% 0.07% 0.08% 8.90% 9.95% 6.27% 2 0.01% 16 0.04% 41 0.05% 77 0.06% 1.43% 1.37% 7.65% 6.02% 4.58% 340 1.92% 720 1.80% 1268 1.69% 1971 1.61% 2.34% 1.79% 6.16% 5.14% 2.24% 476 2.69% 963 2.41% 1399 1.86% 1642 1.34% 1.22% 0.85% 7.47% 4.70% 1.35% 204 1.15% 506 1.26% 885 1.18% 1160 0.95% 0.34% 0.26% 2.98% 2.16% 2.29% 81 0.46% 208 0.52% 268 0.36% 349 0.29% 3.69% 3.75% 9.27% 6.56% 5.21% 424 2.40% 1209 3.02% 2126 2.83% 3586 2.93% 0.69% 0.48% 7.51% 2.90% 1.27% 168 0.95% 378 0.94% 506 0.67% 602 0.49% 2.93% 2.84% 10.60% 5.96% 4.73% 438 2.48% 1447 3.62% 2519 3.35% 4096 3.35% 12.09% 11.27% 11.0 1% 6.94% 4.30% 1156 6.54% 3619 9.04% 6878 9.15% 10228 8.36% 26.50% 24.06% 8.63% 6.01% 4.03% 3814 21.57% 9801 24.49% 16856 22.42% 24934 20.38% 28.06% 27.21% 9.08% 6.45% 4.72% 3049 17.25% 6779 16.94% 12793 17.02% 19625 16.04% 54.55% 51.28% 8.86% 6.23% 4.39% 6863 38.82% 16580 41.42% 29649 39.45% 44559 36.43% 10.13% 10.36% 12.44% 6.93% 5.28% 867 4.91% 3198 7.99% 6384 8.49% 10307 8.43% 64.69% 61.64% 9.31% 6.34% 4.53% 7730 43.72% 19778 49.41% 36033 47.94% 54866 44.85% 3.51% 3.54% 8.57% 6.55% 5.11% 920 5.20% 2298 5.74% 4203 5.59% 6795 5.56% 5.58% 6.23% 9.59% 9.16% 6.20% 794 4.49% 2301 5.75% 5184 6.90% 8838 7.23% 0.87% 1.35% 6.89% 9.47% 9.71% 198 1.12% 465 1.16% 1114 1.48% 2761 2.26% 17.00% 20.29% 11.01% 9.81% 6.92% 3057 17.29% 8536 21.33% 20014 26.63% 37875 30.96% 26.96% 31.40% 10.12% 9.18% 6.65% 4968 28.10% 13600 33.98% 30515 40.60% 56269 46.00% 100%A 100% 8.67% 6.72% 5.04% 17681 40024 75165 122321 GDP GROWTH RATE 8.51% 6.50% 4.99% Macroeconomic Projections Under Three Scenarios High Efficiency Scenario 1990 2000 2010 2020 1990 2000 Indus. % Output Value by Sector (100 million yuan) Output Shar I. Agriculture 7662 11798 19826 28810 17.98% 10.98% 11. 1. Coal industry 2.73% 654 1.53% 933 1.07% 1335 0.74% 1614 1.53% 0.87% 2. Oil industry 4.14% 989 2.06% 1250 1.53% 1913 1.21% 2643 2.32% 1.16% 3. Natural gas 0.09% 22 0.07% 42 0.09% 114 0.11% 245 0.05% 0.04% 4. Power 2.99% 714 2.37% 1440 2.06% 2579 1.88% 4106 1.68% 1.34% 5. Ferrous 6.12% 1464 4.68% 2847 4.22% 5268 3.30% 7184 3.43% 2.65% 6. Non-ferrous 2.95% 705 2.69% 1637 2.31% 2886 1.79% 3890 1.65% 1.52% 7. Fertilizer industry 1.59% 380 0.88% 535 0.66% 821 0.50% 1090 0.89% 0.50% 8. Chemical industry 6.31% 1510 6.60% 4017 6.88% 8590 7.48% 16292 3.54% 3.74% 9. Cement industry 1.97% 471 1.85% 1126 1.40% 1745 1.06% 2308 1.11% 1.05% 10.Other building materials 4.69% 1123 5.78% 3517 5.81% 7252 6.08% 13232 2.64% 3.27% 11. Machinery & Electric 17.05% 4079 22.43% 13645 24.09% 30091 26.23% 57127 9.57% 12.70% Heavy Industry 50.63% 12111 50.95% 30989 50.11% 62594 50.38% 109730 28.42% 28.85% 12. Light industry 49.37% 11811 49.05% 29839 49.89% 62318 49.62% 108078 27.72% 27.78% Industry total 100% 23922 100% 60828 100% 124912 100% 217809 56.14% 56.62% 1. Building sector 3009 11462 26661 52962 10.67% 11.31% II. Secondary Industry 26931 72290 151572 270771 66.81% 67.94% III. 1. Communication 1535 3746.04 8381.83 15654 3.60% 3.49% TERTIA 2. Commercial sector 1741.99 4703.49 12998.78 27375 4.09% 4.38% 3. Passenger transportation 340.137 729.697 2070.433 6104 0.80% 0.68% 4. Other service sector 4400.26 14155.4 40799.45 91280 10.33% 13.18% III. TERTIARY 8017 23335 64250 140413 18.82% 21.72% Total 42610.2 107423 235649 439993.9 100% 100% 9.69% 8.17% 6.44% Macroeconomic Projections Under Three Scenarios 2010 2020 2000 2010 2020 1990 2000 2010 2020 of 18 sectors Growth Rate of Each Sector Value-added and its Share in GDP of Each Sector 8.41% 6.55% 4.41% 5.33% 3.81% 4983 28.18% 6982 15.92% 10906 11.51% 15103 8.47% 0.57% 0.37% 3.62% 3.65% 1.92% 290 1.64% 399 0.91% 489 0.52% 626 0.35% 0.81% 0.60% 2.37% 4.35% 3.28% 235 1.33% 333 0.76% 493 0.52% 615 0.35% 0.05% 0.06% 6.75% 10.53% 7.96% 2 0.01% 11 0.03% 32 0.03% 74 0.04% 1.09% 0.93% 7.26% 6.00% 4.76% 340 1.92% 688 1.57% 1184 1.25% 1984 1.11% 2.24% 1.63% 6.88% 6.35% 3.15% 476 2.69%/ 1062 2.42% 1725 1.82% 2319 1.30% 1.22% 0.88% 8.80% 5.83% 3.03% 204 1.15% 572 1.30% 1115 1.18% 1723 0.97% 0.35% 0.25% 3.49% 4.39% 2.87% 81 0.46% 223 0.51% 347 0.37% 501 0.28% 3.65% 3.70% 10.28% 7.90% 6.61% 424 2.40% 1345 3.07% 2689 2.84% 5667 3.18% 0.74% 0.52% 9.10% 4.47% 2.84% 168 0.95% 425 0.97% 665 0.70% 971 0.54% o 3.08% 3.01% 12.09% 7.50% 6.20% 438 2.48% 1662 3.79% 3340 3.52% 6622 3.71% 12.77% 12.98% 12.83% 8.23% 6.62% 1156 6.54% 4142 9.44% 8885 9.38% 17042 9.55% 26.S6% 24.94% 9.85% 7.28% 5.77% 3814 21.57% 10863 24.77% 20965 22.13% 38144 21.38% 26.45% 24.56% 9.71% 7.64% 5.66% 3049 17.25% 7205 16.43% 15244 16.09% 25629 14.37% 53.01% 49.50% 9.78% 7.46% 5.72% 6863 38.82% 18068 41.20% 36209 38.21% 63773 35.75% 12.04% 7.06% 14.31% 8.81% 7.10% 867 4.91% 3665 8.36% 8717 9.20% 17231 9.66% 65.04% 56.56% 10.38% 7.68% 5.97% 7730 43.72% 21733 49.56% 44926 47.41% 81004 45.41% 3.56% 3.56% 9.33% 8.39% 6.45% 920 5.20% 2466 5.62% 5351 5.65% 9818 5.50% 5.52% 6.22% 10.44% 10.70% 7.73% 794 4.49% 2486 5.67% 6441 6.80% 12669 7.10% 0.88% 1.39% 7.93% 10.99% 11.42% 198 1.12% 513 1.17% 1413 1.49% 4084 2.29% 17.31% 20.75% 12.39% 11.17% 8.39% 3057 17.29% 9676 22.06% 25719 27.14% 55694 31.22% 27.27% 31.91% 11.27% 10.66% 8.13% 4968 28.10% 15142 34.53% 38924 41.08% 82264 46.12% 100% 100% 9.69% 8.17% 6.44% 17681 100% 43857 100% 94756 100% 178372 100% GDP GROWTH RATE 9.51% 8.01% 6.53% Energy Use and Local ~msmn by Seetor (Ruent= Scenario) (units: kmBuon tons, biion cubic meers, kWh) 1990 2000 COAL S02 TSP OIL GAS ELEC COAL SO2e TSP* OIL GAS ELEC nit 000 % 000t % nt bem kwh nrt 000t % 000t % nit bem kwh I. Agguure 22.7 438.7 2.5% 635 4.1% 10.6 0.0 42.7 28.4 548.9 2.1% 794 3.4% 15.4 0.2 61.9 i. Indusr 1. Coal industry 44.7 883.7 5.0% 637 4.1% 0.8 0.1 40.7 63.7 1259.2 4.8% 908 3.9% 1.2 0.1 75.7 2. Oil industy 3.9 78.8 0.4% 63 0.4% 13.2 4.2 19.7 10.3 205.9 0.8% 164 0.7% 14.8 7.3 31.8 3. Natural gas 0.1 2.4 0.0% 1 0.0% 0.6 0.3 1.0 0.2 4.4 0.0% 2 0.0% 1.1 0.6 1.9 4. Power 250.9 5239.0 29.8% 4800 31.1% 10.8 0.3 91.1 438.9 9163.4 34.6% 8395 35.9% 12.0 1.4 175.7 5. Ferous 103.0 912.2 5.2% 1174 7.6% 5.0 0.7 62.7 135.4 1199.8 4.5% 1544 6.6% 6.4 1.2 114.0 6. Non-ferou 10.3 210.4 1.2% 144 0.9% 0.7 0.0 26.0 18.0 368.3 1.4% 252 1.1% 1.3 0.2 52.1 7. Fertilizer industry 52.1 583.0 3.3% 437 2.8% 2.5 4.4 31.8 58.2 652.0 2.5% 489 2.1% 1.8 5.7 36.8 8. Chemical industry 24.6 178.5 1.0% 295 1.9% 9.0 0.5 47.3 37.9 274.6 1.0% 454 1.9% 22.1 2.6 94.2 9. Cemeot industry 50.0 228.9 1.3% 900 5.8% 0.0 0.0 22.0 102.9 471.2 1.8% 1852 7.9% 0.0 0.0 49.0 10.Oher building materials 99.2 1673.7 9.5% 1071 7.0% 3.0 0.3 6.9 166.8 2813.6 10.6% 1801 7.7% 5.0 0.6 14.8 11. Machinery & Electronic Equipmen 42.0 840.8 4.8% 504 3.3% 4.7 0.4 44.7 75.3 1505.0 5.7% 903 3.9% 6.8 0.8 106.4 12. Light indutry 116.0 2291.8 13.0% 1392 9.0% 9.0 0.9 93.4 170.8 3375.3 12.7% 2050 8.8% 14.0 1.7 192.2 1. Building ector 4.1 84.8 0.5% 52 0.3% 3.6 1.1 6.5 11.2 229.1 0.9% 140 0.6% 8.3 2.4 19.0 Iu. Ter 1. Comnuniction 17.5 346.0 2.0% 219 1.4% 14.3 0.2 8.6 26.8 529.8 2.0% 335 1.4% 24.3 0.3 23.7 2. Commercial ector 10.7 219.0 1.2% 128 0.8% 1.2 0.0 7.6 14.1 288.4 1.1% 169 0.7% 3.0 0.2 19.4 3. Passengertransportaton 14.5 285.5 1.6% 181 1.2% 13.4 0.0 2.0 12.7 251.9 1.0% 159 0.7% 24.5 0.0 3.4 4. Other ervike wtor 19.8 406.3 2.3% 238 1.5% 8.6 0.1 20.2 32.8 671.7 2.5% 393 1.7% 18.5 1.0 54.3 Sub-total 886.1 14903.5 84.8% 12871 83.5% 111.0 13.4 575.0 1404.3 23812.5 89.8% 20806 89.0% 180.5 26.5 1126.4 Reuidetial 167.3 2664 15.2% 2541 16.5% 0.3 1.9 40.1 169.0 2692 10.2% 2567 11.0% 0.8 2.3 175.5 Total 1053 17568 100.0% 15412 100.0% 111 15 615 1573 26505 100.0% 23373 100.0% 181 29 1302 * Noe thst SO2 and TSP entisios for 2000, 2010, and 2020 us 1990 coefficienta and that the corremponding esnimates are therefore likely to be high. IN? 2010 2020 COAL 8020 Tsp OIL GAS E.EC COAL 82* TSP OI GAS ELEC it 000: % 000 % et bom kwh SM 000t % 000 t at bem kwh 38.8 751.6 1.8% 1088 2.8% 21.1 1.2 98.1 52.3 1012.9 1.8% 1466 3.0% 26.9 3.2 142.1 83.4 1648.3 4.0% 1189 3.0% 1.7 0.2 128.6 108.3 2140.2 3.9% 1543 3.2% 2.3 0.2 197.6 13.0 259.2 0.6% 207 0.5% 19.1 9.5 49.6 15.3 306.7 0.6% 245 0.5% 23.4 11.6 56.8 0.5 9.4 0.0% 5 0.0% 2.4 1.4 4.1 0.8 15.7 0.0% 8 0.0% 4.1 2.3 6.8 872.6 18219.6 44.1% 16693 42.3% 10.2 4.7 320.5 1307.4 27299.4 49.6% 25011 51.6% 9.1 6.5 488.2 184.5 1635.0 4.0% 2104 5.3% 8.2 2.2 195.2 216.1 1914.3 3.5% 2463 5.1% 8.4 3.9 283.0 27.7 567.9 1.4% 388 1.0% 1.8 0.4 82.2 33.8 692.8 1.3% 473 1.0% 2.2 0.6 103.7 69.8 781.2 1.9% 586 1.5% 1.6 6.9 47.7 69.9 782.7 1.4% 587 1.2% 0.8 8.0 50.9 52.4 379.6 0.9% 628 1.6% 40.5 7.7 159.9 83.1 602.5 1.1% 997 2.1% 60.4 16.2 253.8 128.4 588.3 1.4% 2312 5.9% 0.0 0.0 70.2 155.0 709.3 1.3% 2789 5.8% 0.0 0.0 90.5 231.9 3913.0 9.5% 2505 6.3% 3.9 4.2 20.7 293.9 4958.2 9.0% 3174 6.6% 4.0 6.4 27.4 116.9 2337.6 5.7% 1403 3.6% 7.2 1.4 193.7 163.4 3267.1 5.9% 1960 4.0% 7.3 1.9 320.9 231.1 4566.0 11.1% 2773 7.0% 18.5 5.0 326.8 302.1 5970.1 10.9% 3626 7.5% 23.5 10.8 534.2 20.2 413.7 1.0% 252 0.6% 13.4 4.0 41.2 32.3 671.5 1.2% 410 0.8% 19.3 5.7 78.0 21.7 429.7 1.0% 272 0.7% 43.0 0.6 64.1 0.0 0.0 0.0% 0 0.0% 70.1 0.9 167.2 21.1 431.7 1.0% 253 0.6% 6.0 2.1 47.4 38.6 791.0 1.4% 463 1.0% 7.7 3.6 87.8 11.9 235.9 0.6% 149 0.4% 50.7 0.0 10.6 0.0 0.0 0.0% 0 0.0% 112.8 0.0 30.0 44.6 914.1 2.2% 535 1.4% 33.5 12.0 157.8 60.8 1245.7 2.3% 730 1.5% 56.7 26.1 322.5 2170.5 38081.9 92.2% 36403 92.2% 282.8 63.1 2018.3 2933.6 52380.7 95.3% 45946 94.9% 439.0 107.9 3241.3 201.6 3211 7.8% 3062 7.8% 1.1 3.4 406.0 163.9 2610 4.7% 2489 5.1% 1.9 5.8 600.3 2372 41293 100.0% 39465 100.0% 284 67 2424 3097 54991 100.0% 48435 100.0% 441 114 3842 Macroeconomic variables used to forecast non-energy related GHG emissions 1990 2000 2010 2020 Cement Production (million tons) 210 456 623 783 Coal production (million tons) 1079 1574 2376 3100 Livestock (million head) 130 147 175 208 Urban Population (million) 302 406 513 613 Rice Production (million tons) 189 208 264 320 Fertilizer Production (million tons) 18.81 23.60 30.00 33.40 N. 14.64 18.35 23.10 26.00 P. 4.12 5.16 6.50 7.32 K. 0.05 0.06 0.07 0.08 Annex 3 Annex 3. Energy Coefficient Calculations Sectoral Energy Coefficient Calculations (Baseline Scenario) Total Energy Demand Projections Energy Savings Calculations 74 Energy coefficients calcuiation (Baseline Scenario) 1:: Table 1. Agriculture 1985 1990 2000 2010 2020 1. Share in total output value(%) 22.87 17.98 11.00 8.15 6.32 2. Annual output value (billion Yuan) 607.43 766.19 1180.05 1914.76 2810.58 3. Annual growth rate (%) 4.75 4.41 4.96 3.91 4. Unit energy use (tce/million Yuan) 66.59 63.32 57.27 51.79 47.55 in which: a. Coal 40.93% 33.38% 30.00% 28.00% 28.00% b. Oil & gas 27.37% 31.08% 33.00% 32.00% 32.00% c. Power 31.70% 35.54% 37.00% 40.00% 43.00% 5. Total energy use (million tee) 40.45 48.52 67.58 99.16 133.65 a. Coal (million t) 23.17 22.67 28.38 38.87 52.39 b. Oil & gas (million toe) 7.75 10.56 15.61 22.21 29.94 c. Power (TWh) 31.74 42.68 61.89 93.18 142.25 6. Annual growth rate (%) 3.71 3.37 3.91 3.03 7. Elasticity factor 0.78 0.76 0.79 0.77 8. Energy saving rate (%) 1.00 1.00 1.00 0.85 75 Energ coeffdents caculatiom (Sa~Dne Scenaro) Annex 3 l:- Table 2. Coal 1985 1990 2000 2010 2020 1. Share in toal output vau(%) 3.22 2.74 1.61 1.19 0.89 2. Annual output value (billion Yuan) 41.54 65.46 98.06 148.12 197.74 3. Annual growth rate (%) 9.52 4.13 4.21 2.93 4. Unit energy use (tce/million Yuan) 734.85 758.94 795.04 791.39 813.56 in which: 41.54 65.46 98.06 148.12 197.74 a. Coal 72.09% 64.30% 58.40% 52.19% 48.13% b. Oil & gu 2.65% 2.57% 2.37% 2.32% 2.20% c. Power 25.26% 33.13% 39.23% 45.49% 49.67% Energy saving rate (%) -0.65 -0.47 0.05 -0.28 5. Total tnergy use (million te) 30.52 49.68 77.98 117.22 160.88 a. Con! (million 1) 30.81 44.72 63.76 85.64 108.41 b. Oil & gam (million toe) 0.57 0.89 1.30 1.91 2.47 c. Power (TWh) 19.06 40.74 75.71 131.99 197.80 Annual energy use inreaed ra~ (%) 4.35 3.85 4.20 2.70 6. Coal yield in variout mine (million) 872.00 1079.00 1573.97 2375.73 3100.07 la which: a. Lazg 43.00% 45.17% 50.00% 60.00% 65.00% b. Medium 30.00% 24.50% 20.00% 20.00% 20.00% c. Smal 27.00% 30.33% 30.00% 20.00% 15.00% d. Output value(Yuan/t) 42.87 50.91 50.91 50.91 50.91 e. Total output value (billion Yumn) 37.38 54.93 82.39 124.42 166.10 f. Share in total 90.00% 83.92% 84.00% 84.00% 84.00% 7. Other products <billion Yuan) 4.15 10.52 15.69 23.70 31.64 a. Coking 2.82 8.21 9.00 14.00 20.00 b. Coal products 1.34 2.31 6.69 9.70 11.64 c. Share in total 10.00% 16.08% 16.00% 16.00% 16.00% 8. Unit products energy use for major products a. Lange (kg~elt) 45.35 45.34 46.94 46.01 46.60 a. Coal (kg/) 41.10 37.30 35.00 32.00 30.00 b. Oil & gu ØrgoeA) 0.65 0.65 0.65 0.65 0.65 c. Power (kWh/)* 37.29 43.98 52.00 55.00 60.00 b. Medium (kgceh) 32.95 36.03 38.05 38.52 42.56 a. Coal (kg/t) 36.35 35.00 35.00 30.00 30.00 b. Oil & g (kgo/t) 0.65 0.65 0.65 0.65 0.65 c. Power (kWh/t) 15.00 25.00 30.00 40.00 50.00 c. Small (kgceh) 20.81 22.49 26.87 23.29 23.29 a. Coal (kg/t) 25.00 23.40 25.00 20.00 20.00 b. Oil & gas (kgoe/) 0.65 0.65 0.65 0.65 0.65 c. Power (kWh/t) 5.00 12.00 20.00 20.00 20.00 d. Total engy ube (million en) 30.52 38.98 61.60 94.95 131.11 a. Coi (million t) 30.81 35.09 50.37 69.37 88.35 b. Oil & gaS(milio t) 0.57 0.70 1.02 1.54 2.02 c.Power (TWh) 19.06 31.97 59.81 106.91 161.20 e. Shar in toal 77.40% 78.47% 79.00% 81.00% 81.50% f. Unit energy (tec/million Yan) 816.52 709.62 747.72 763.13 789.34 g. Energy saving rate (M) 2.85 -0.52 -0.20 -0.34 9. Other producta -ry u~e (million te) 8.91 10.70 16.38 22.27 29.76 a. Shar in total co] idu~y 22.60% 21.53% 21.00% 19.00% 18.50% b. Unit efergy mil ( lee/minio Yuan) 2145.18 1016.46 1043.49 939.78 940.67 e. E~ergy aving at (M) 16.11 -0.26 1.05 -0.01 76 Energy coeffidents calculation (Baseline Scenario) Am= j:: Table 3. Oil industry 1935 1990 2000 2010 2020 1. Share in total output value (%) 5.53 4.14 2.06 1.30 0.90 2. Annual output value (billion Yuan) 71.38 98.95 25.63 162.13 200.31 3. Annual growth raw (%) 6.75 2.42 2.63 2.09 4. Unit energy use (twelmillion Yuan) 382.73 356.46 410.20 428.76 416.98 in which: a. Coal 4.04% 7.99% 14.28% 13.27% 13.12% b. Oil & gas 78.13% 69.39% 59.95% 57.16% 58.48% c. Power 17.83% 22.62% 24.96% 28.75% 27.49% Energy saving raw (%) 1.41 -1.41 -0.44 0.28 5. Total energy use (million toe) 27.32 35.27 51.53 69.31 33.52 a. Coal (million t) 1.55 3.94 10.30 12.97 15.35 b. Oil A gas (million toe) 14.94 17.13 21.63 27.93 34.19 c. Power (TWh) 12.06 19.75 31.84 49.69 56.84 Annual energy use increased rate (%) 2.06 1.78 1.94 0.96 Elasticity factor 0.31 0.74 0.74 0.46 6. Oil sector 6.1 Production a. Yield (million t) 124.90 138.31 165.00 200.00 220.00 b. Output value (Yuantt) 344.54 344.54 344.54 344.54 344.54 c. Total output value (billion Yuan) 43.03 47.65 56.85 61.91 75.30 d. Share in total 60.29% 41.16% 45.25% 42.32% 37.84% e. Annual growth rate (%) 2.06 1.78 1.94 0.96 6.2 Energy use a. Coal (kg/t) 7.87 9.59 41.16 40.38 40.81 b. Oil & gas (kgoelt) 62.13 63.32 63.00 63.00 63.00 c. Power (kWh) 68.21 104.55 150.00 200.00 200.00 d. Total (kgce/t) 121.94 139.54 180.00 200.00 200.00 e. Total (million te) 15.23 19.30 29.70 40.00 44.00 f. Share in total 55.75% 54.72% 57.63% 57.30% 52.68% g. Annual growth rate (%) 4.85 4.40 3.02 0.96 h. Elasticity factor 2.35 2.47 1.56 1.00 i. Energy saving rate (%) -2.66 -2.51 -1.05 0.00 7. Oil processing 7.1 Production a. Yield (million t) 14.52 107.24 143.78 196.34 260.29 b. Output value (Yuanlt) 335.41 478.35 478.35 478.35 478.35 c. Total output value (bilios Yuan) 23.35 51.30 68.78 93.92 124.51 d. Share in total 39.71% 51.84% 54.75% 57.68% 62.16% e. Annual growth rate (%) 4.88 2.98 3.16 2.86 7.2 Energy use a. Coal (kg/t) 6.67 24.41 24.41 24.41 24.41 b. Oil & gas (kgoe/t) 84.96 78.10 71.10 78.10 78.10 c. Power (kWh) 41.16 49.33 49.33 49.33 49.33 d. Total (kgce/t) 143.04 14.94 151.35 151.85 151.85 c. Total (million tce) 12.09 15.97 21.83 29.81 39.52 f. Share in total 44.25% 45.28% 42.37% 42.70% 47.32% g. Annual growth rate (%) 5.73 3.18 3.16 2.16 b. elasticity factor 1.17 1.07 1.00 1.00 i. Energy saving rate (%) -0.31 0.19 0.00 0.00 77 Tale 4. Na Zu ga idusty 195 1990 2000 2010 200 1. Sha aloutpatvale(%) 0.10 0.09 0.09 0.12 0.14 2. Aua output valu (billion Yua) 1.26 2.18 5.30 14.86 30.64 3. Ama gow (%) 11.61 9.29 10.86 7.50 4. Uait o~ergy use (te/miilio Yua) 1251.34 855.10 643.92 492.24 397.91 in which: a. Cosd 4.61% 4.61% 4.61% 4.61% 4.61% b. Oit & gas 72.79% 72.79% 72.79% 72.79% 72.79% c. Powew 22.60% 22.60% 22.60% 22.60% 22.60% Ergy sing rot. (%) 7.33 2.80 2.65 2.10 5. Total egy ue (milliou tew) 1.58 1.87 3.41 7.32 12.19 a. Cod (aiffia t) 0.10 0.12 0.22 0.47 0.79 b. Oil & ga (milfio too) 0.80 0.95 1.74 3.73 6.21 c. Power (TWh) 0.88 1.04 1.91 4.09 6.82 Ananal energy ue increaed rte (%) 3.42 6.23 7.92 5.24 Eicity factor 0.29 0.67 0.73 0.10 6.1 Production a. Yeld (109 m3) 12.93 15.30 28.00 60.00 100.00 b. Output vale (Yaa/000 m3) 97.44 142.60 18936 247.72 306.44 c. Total ouput val. (biUlon Yua) 126 2.18 5.30 14.86 30.64 d. Am...l growh rtc (%) 11.61 9.29 10.86 7.50 6.2 Emegy e a. Cosi (g000 =^3) 787 7.87 7.87 7.87 7.87 b. i & gas ( /000 m3) 6.13 6.13 62.13 42.13 42.13 c. Power (kWh/000 M'3) 68.21 68.21 68.21 68.21 68.21 d. Total '000 m'3) 121.94 121.94 121.94 121.94 121.94 a. Total (milon t".) 1.58 1.87 3.41 7.32 12.19 t. Sre ia l ~oil & gidus r 9.38% 8.81% 10.31% 15.46% 21.70% 78 Energy coefdicients calculation (Baseline Scenario) An I 1:: Table 5. Power sector 1985 1990 2000 2010 2020 1. Share in total output value(%) 3.63 2.99 2.48 2.27 2.16 2. Annual output value (billion Yua) 46.36 71.42 151.05 284.06 480.25 3. Annual growth rate (%) 8.80 7.78 6.52 5.39 4. Unit energy use (tcelmillion Yuan) 505.96 515.52 470.24 456.14 411.01 in which: 100.00% 100.00% 100.00% 100.00% 100.00% a. Coal 83.82% 91.88% 94.26% 96.77% 97.73% b. Oil & gas 16.18% 8.12% 5.74% 3.23% 2.27% c. Power Energy saving rate (%) -0.38 0.92 0.30 1.04 5. Total eargy use (million tee) 126.62 195.21 333.47 645.53 957.86 Annual energy use incresed rate (%) 9.04 5.50 6.83 4.03 a. Coal (million t) 148.46 250.91 439.08 873.21 1303.60 b. Oil & gas (million toe) 14.33 11.06 13.38 14.57 15.18 c. Power (TWh) 58.68 91.14 175.51 320.72 488.59 6. Total yield of power (lh) 410.70 621.30 1302.46 2423.88 3844.52 In which: a. Thermal 77.50% 79.66% 72.20% 79.10% 77.34% a). Coal based 77.50% 79.66% 71.28% 73.36% 76.80% b). Gas based 0.00% 0.00% 0.92% 0.74% 0.55% b. Hydro 22.50% 20.34% 25.72% 19.14% 16.10% c. Nuclear 1.98% 1.56% 5.42% d. New mergy based 0.10% 0.20% 1.13% Annual generation increased rate (%) 8.63 7.68 6.43 4.70 Power elasticity factor 0.87 0.79 0.79 0.71 7. Thermal power energy use (million tee) 126.07 194.37 331.87 642.67 953.47 7.1 Coal use (million t) 147.34 249.96 437.45 370.06 1303.93 7.2 LNG ase (10'9 cubic meters) 0.00 0.00 2.47 3.75 4.40 7.3. Oil use (million te) 14.33 11.06 11.08 11.08 11.08 8. Thermal power energy use (gctkWh) 431.38 427.16 383.61 363.59 348.54 a). Coal based 431.38 427.16 384.38 363.96 348.71 b). Gas based 324.00 324.00 324.00 9. Thermal power eorgy saving factor a. Enterprise scale (%) 100.00% 100.00% IOD.00% 100.00% 100.00% a) Large 6.00% 14.80% 41.03% 60.92% 71.21% b) Medium 41.00% 32.00% 29.71% 25.77% 21.96% c) Small 53.00% 53.20% 29.27% 13.30% 6.83% b. Generation coal use (gckWh) a) Large 353.00 345.00 325.00 320.00 310.00 b) Medium 378.00 375.00 365.00 355.00 350.00 c) Small 420.00 421.50 390.00 330.00 370.00 d) Average 398.76 395.30 355.91 337.00 322.88 c. Power use rate in plant 6.11% 6.61% 5.50% 5.20% 4.71% a) Thermal 7.80% 3.22% 7.50% 6.50% 6.00% b) Others 0.28% 0.30% 0.30% 0.30% 0.30% d. Line loss 8.18% 8.06% 8.00% 8.00% 8.00% e. Total thermal capacity (GW) 60.63 101.84 18.07 384.26 594.70 f. Total hydro capacity (GW) 23.93 32.49 36.14 126.70 168.66 10. Unit products value (YuaMWh) 112.95 113.81 113.81 114.84 120.87 11. Other production value (billios Yuan)* 0.47 0.71 1.51 2.84 4.80 12. Other production energy use (million toe) 0.44 0.68 1.16 2.25 3.34 Note: : Steam, heat water supply and others 79 Energy c0efdcdents calculation (Baseline Smario) Ann 3 I:: Table 6. Iron & Stee 1985 1990 2000 2010 2020 1. Share in total output value (%) 7.00 6.12 4.44 4.04 3.34 2. Annual output value (bitlion Yu~a) 90.37 146.35 270.41 504.39 743.09 3. Annual growh rak (%) 10.12 6.33 6.43 3.95 4. Unit enery use (tcsemillion Yuan) 904.14 730.37 568.06 447.03 384.94 in which: 100.00% 100.00% 100.00% 100.00% 100.00% a. Cod 72.10% 68.80% 63.00% 58.50% 54.00% b. Oil 7.50% 7.50% 7.00% 6.50% 6.00% c. Power 20.40% 23.70% 30.00% 35.00% 40.00% Energy saving rate (%) 4.18 2.48 2.37 1.48 5. Total ecnegy ue (million ten) 81.70 106.89 153.61 225.48 286.05 a. Coal (million t) 82.47 102.96 135.48 184.67 216.25 b. Oil (million to) 4.29 5.61 7.53 10.26 12.01 c. Power ( h) 41.26 62.70 114.07 195.34 283.21 d. Anual growth rate (%) 8.73 6.17 5.53 3.78 6. Total yieid of ron & Steel (million t) 46.80 66.35 102.78 163.84 221.06 Annual growth rate (%) 7.23 4.47 4.77 3.04 7. Energy uoe for iron & ~meel 7.1 Unit products energy use (leeh) 1746.00 1610.99 1494.52 1376.23 1293.98 a. Coal 72.10% 68.80% 63.00% 58.50% 54.00% b. Oil & gas 7.50% 7.50% 7.00% 6.50% 6.00% c. Power 20.40% 23.70% 30.00% 35.00% 40.00% Energy saving raft (%) 1.62 0.75 0.83 0.62 7.2 Total energy use ( million tce) 81.70 106.89 153.61 225.48 286.05 8. Energy saving factor in iron & uteel a. Re of ron & Steel 0.94 0.94 0.91 0.88 0.80 b. Rate of Opcn-hearth (%) 26.29 19.83 9.50 2.80 0.00 c. Enlige cale. (%)* 100.00 100.00 100.00 100.00 100.00 a) Lrge 69.32 68.41 68.97 69.36 69.52 b) Medium 20.55 22.50 23.39 23.99 24.25 c) Small 10.13 9.09 7.64 6.66 6.23 d. Rate of continue cas~ig 10.83 22.37 50.00 60.00 60.00 e. Ohers 9. Unit producu vu (Yua/t) 1931.11 2205.71 2630.91 3078.63 3361.49 10. Added value increasing factors a. Ra~e of P & S 78.90% 77.60% 79.00% 82.00% 85.00% b. Rae of pipe& plat 34.30% 36.96% 40.00% 40.00% 40.00% c. Rate of high quality teel 29.60% 30.40% 32.00% 35.00% 40.00% 11. Olher products output value (billion Ywae) 12. Yield of odher produc (000) a. Alay of iroa. 1491.80 2382.27 3423.53 5025.28 6375.21 b. Refractoy 5461.00 S073.80 11602.77 17031.28 21606.34 c. Carbon materialb 673.20 912.70 1311.63 1925.30 2442.48 13. Otker producta energy lu a. Aloy of iro 2500.00 2500.00 2338.40 2176.80 2096.00 a) Coal (gceA) 480.00 480.00 480.00 480.00 480.00 b) Power (kWh) 5000.00 5000.00 4600.00 4200.00 4000.00 b. Refractory 200.00 200.00 200.00 200.00 200.00 a) Co. f(keIi) 200.00 200.00 200.00 200.00 200.00 b) Power kWh) c. Cabon materials 2828.00 3128.00 3027.00 2926.00 2724.00 a) Cod] (gee~t) 300.00 300.00 300.00 300.00 b) Power (kWh) 7000.00 7000.00 6750.00 6500.00 6000.00 d. Total energy for ehers (mlion ten) 11.31 18.88 24.30 29.96 34.34 Nole: Total enrgy um per ion ee (wc/t) a) Large 1.30 1.20 1.15 1.10 1.05 b) Medium 1.72 1.44 1.40 1.35 1.30 c) Small 2.50 2.00 1.80 1.60 1.50 d) Average 1.50 1.33 1.26 1.19 1.14 e) Ohr energy u'n 0.24 0.28 0.24 0.18 0.16 80 Energy coeicients calculation (Baseline Scenario) Anx 1:: Table 7. Non-ferrous 1985 1990 2000 2010 2020 1. Share in total output value(%) 3.26 2.94 2.69 2.34 1.79 2. Annual output value (billion Yuan) 42.09 70.45 163.56 292.55 397.36 3. Annual growth rate (%) 10.85 8.79 5.99 3.11 4. Unit energy use (tce/million Yusn) 325.64 268.41 219.68 191.94 176.47 in which: a. Coal 39.52% 38.78% 35.75% 35.28% 34.47% b. Oil & gas 5.77% 5.71% 5.66% 5.54% 5.72% c. Power 54.71% 55.51% 58.59% 59.18% 59.80% Energy saving rate (%) 3.79 1.98 1.34 0.84 5. Total energy use (million tee) 13.71 18.91 35.93 56.15 70.12 a. Coal (million t) 7.58 10.27 17.98 27.74 33.84 b. Oil & gas (million toe) 0.55 0.76 1.42 2.18 2.81 c. Power (TWh) 18.56 25.98 52.11 82.25 103.80 Annual energy use increased rate (%) 6.65 6.63 4.57 2.25 6. Major products annual yield ('000 t) 1520.30 2392.00 5336.74 8811.35 11369.70 Inwichz: a. Cu 372.50 556.90 1242.49 2051.44 2647.07 b. Al 524.70 854.30 1906.01 3146.96 4060.68 c. Lead & Zn 528.70 848.30 1892.62 3124.36 4032.16 d. Other 94.40 132.50 295.62 488.09 629.80 6.1 Major products unit output value (Yuan It) 18824.33 19920.79 19920.79 19920.79 19920.79 a. Cu 22802.71 24130.90 24130.90 24130.90 24130.90 b. Al 9299.56 9841.23 9841.23 9841.23 9841.23 c. Lead & Zn 6907.01 7309.33 7309.33 7309.33 7309.33 d. Other 122811.52 129964.93 129964.93 129964.93 129964.93 6.2 Major products total output value (billion Yuan) 21.62 47.65 106.31 175.53 226.49 6.3 Share in total non-ferrous industry 68.00% 67.64% 65.00% 60.00% 57.00% 7. Other products (billion Yuan) 13.47 22.80 57.24 117.02 170.86 7.1 Share in total non-ferrous 32.00% 32.36% 35.00% 40.00% 43.00% 8. Unit products energy use for major products a. Cu 6250.00 53338.00 5330.00 5330.00 5330.00 a. Coal (kgh) 4423.79 3146.99 3381.52 3481.52 3481.52 b. Oil & gas (kgoe/t) 496.00 496.00 400.00 350.00 350.00 c. Power (kWh/t)* 53895.00 5895.00 5800.00 5800.00 5800.00 Energy saving rate (%) 3.20 0.01 0.00 0.00 b. Al 10960.00 11420.00 10000.00 9500.00 9000.00 a. Coal (kgt) 4707.02 5351.02 3744.80 3327.60 2910.40 b. Oil & gas (kgoelt) 320.00 320.00 320.00 320.00 320.00 c. Power (kWh/t) 17675.00 17675.00 17000.00 16500.00 16000.00 Energy saving rate (%) -0.82 1.34 0.31 0.54 c. Lead & Zn 2567.00 2567.00 2567.00 2567.00 2567.00 a. Coal (kg/t) 2085.66 2085.66 2085.66 2085.66 2085.66 b. Oil & gas (kgoelt) 54.00 54.00 54.00 54.00 54.00 c. Power (kWt) 2475.50 2475.50 2475.50 2475.50 2475.50 Energy saving rate (%) 0.00 0.00 0.00 0.00 d. Total energy use (million tee) 9.44 14.91 30.54 48.85 61.01 a. Coal (million t) 5.22 8.09 15.29 24.13 29.44 b. Oil & gas (million t) 0.38 0.60 1.21 1.89 2.44 c. Power (TWh) 12.78 20.48 44.29 71.56 90.31 e. Share in total 68.85% 78.83% 85.00% 87.00% 87.00% f. Unit energy (toe/million Yuan) 329.72 312.83 287.28 278.31 269.35 g. Energy saving rate (%) 1.06 0.86 0.32 0.33 9. Other products energy use (million tee) 4.27 4.00 5.39 7.30 9.12 a. Share in total 31.15% 21.17% 15.00% 13.00% 13.00% b. Unit energy use (tec/million Yuan) 316.93 175.58 94.15 62.38 53.35 c. Energy saving rate (%) 12.54 6.43 4.20 1.58 *. Power uses from mining to fine Cu. 81 Eaegy coef~chemto cnenulan (B8seine Scenario) Ann Table 8. Fetilizer 1985 1990 2000 2010 2020 1. Sare intoal output valuc (%) 1.61 1.59 0.88 0.63 0.48 2. Annual output valuc (billion Yaan) 20.77 37.95 53.51 79.20 106.86 3. Annual groweh rae (%) 12.81 3.50 4.00 3.04 4. Unit eergy ue (tcemillion Ymaa) 2226.61 1562.57 1245.57 1017.30 770.93 in which: 100.00% 100.00% 100.00% 100.00% 100.00% a. Coal 61.92% 62.70% 62.42% 61.88% 60.65% b. 00i & ga 15.66% 15.67% 15.27% 14.20% 14.36% c. Power 22.42% 21.63% 22.31% 23.92% 24.99% Energy saving r~c (%) 6.84 2.24 2.00 2.74 5. Total energy u*e (million tce) 46.25 59.30 66.65 80.57 82.38 Aual c~eegy use increased rae (%) 5.10 1.18 1.91 0.22 in whick: a. Coal (mllion t) 40.09 52.05 58.24 69.80 69.95 b. Oil & gas (million too) 5.07 6.50 7.12 8.01 8.28 c. Power (TWh) 25.67 31.75 36.81 47.70 50.96 6. Total yid of fetilizer (mitlion t) 12.92 18.8 1 23.57 29.66 33.39 In which: a. N 11.14 14.64 18.35 23.09 26.00 b. P 1.76 4.12 5.16 6.50 7.32 c. K 0.02 0.05 0.06 0.07 0.01 Annual yield inceased rae (%) 7.80 2.29 2.32 1.19 7. Unit product energy us (kgeh) 3579.57 3153.08 2827.45 2716.19 2466.96 a. N 3987.12 3781.52 3372.69 3235.74 2922.01 b. P 1000.00 920.00 890.00 870.00 850.00 8. Ammonia energy saving factor 8.1 Share of plant size Ammonia yied (millioa t) 16.41 21.29 26.69 33.58 37.81 a. Large 23.70% 18.70% 20.00% 20.00% 20.00% a) Coål based b) Gas & oi baed 100.00% 100.00% 100.00% 100.00% 100.00% b. Medium 20.40% 22.10% 22.10% 22.10% 22.10% a) Coal bused 80.00% 80.00% 85.00% 87.00% 87.00% b) Gas & oil bsd 20.00% 20.00% 15.00% 13.00% 13.00% c. Small 55.90% 59.20% 57.90% 57.90% 57.90% a) Con: bsed 89.00% 89.00% 89.00% 89.00% 89.00% b)Gas&oilbmed 11.00% 11.00% 11.00% 11.00% 11.00% 4. Total 100.00% 100.00% 100.00% 100.00% 100.00% a) Coal basd 66.07% 70.37% 70.32% 70.76% 70.76% b) Gas & oil bused 33.93% 29.63% 29.68% 29.24% 29.24% 8.2 Per ton ammaia ergy u se (kgcth) a. Large 1368.00 1343.00 1167.86 1070.00 1000.00 iwhich power ue (kWht) 10.00 11.30 11.30 11.30 11.30 b. Medium 2236.00 2176.00 2000.00 1800.00 1600.00 in which power me (kWAf ) 1385.00 1385.00 1385.00 1385.00 1385.00 c. Small 2358.00 2254.00 2069.33 1884.67 1700.00 in which power nue OWhh) 1330.00 1330.00 1330.00 1330.00 1330.00 d. Av~rage 2098.48 2066.41 1873.72 1703.02 1537.90 la wich: a) Coal (kgA) 1737.80 1758.62 1583.19 1408.50 1221.44 b)Oil & g(kgoe) 392.31 345.87 302.17 270.02 247.97 c) Power (kWhA) 1028.38 1095.56 1078.42 1078.42 1078.42 *. Total eergy u (millio tee) 34.44 43.99 50.00 57.19 58.14 .m la tialm e ~tilir iadmsry 74.46% 74.19% 75.02% 70.98% 70.57% g. Eaergy aviag ra of am- fi(%) 0.31 0.98 0.96 1.03 9. Unit producs~ va. (Yuaa1) 1607.63 2017.89 2270.00 2670.00 3200.00 Share of various fegtilizer .N a). Lower om~nmatio 85.00% 74.00% 70.00% 50.00% 40.00% b). Higer coccaration 15.00% 26.00% 30.00% 50.00% 60.00% b. Complexfkutilizer 0.30% 0.60% 1.50% 3.00% 5.00% . Fetilizer pr~meiom beuides -ammia 82 Enry coedewts calculadon (Baselne Scenarlo) AgAgin 1:: Table 9. Caemical sector 1985 1990 2000 2010 2020 1. Share in total output value (%) 6.38 6.31 6.62 6.87 7.43 2. Annual output value (billion Yuan) 82.40 151.01 402.88 857.50 1652.18 3. Annual growth rate (%) 12.88 10.31 7.85 6.78 4. Unit energy use (tee/million Yua) 395.99 332.71 248.81 19339 163.45 in which: 100.00% 100.00% 100.00% 100.00% 100.00% a. Coal 45.40% 35.00% 27.00% 22.00% 22.00% b. Oil & gas 27.00% 27.00% 35.00% 40.00% 40.00% c. Power 27.60% 38.00% 38.00% 38.00% 38.00% Energy saving rae (%) 3.42 2.86 2.24 1.92 5. Total energy use (million tee) 32.63 50.24 100.24 170.12 270.05 a. Coal (milion t) 20.74 24.62 37.89 52.40 83.18 b. Oil A gas (million toe) 6.17 9.50 24.56 47.63 75.62 c. Power (TWh) 22.29 47.26 94.29 160.02 254.01 Annual energy use increased rate (%) 9.02 7.15 5.43 4.73 6. Major products yield ('000 t) 1) Basic chemical materials ('000 t) a. NaOH 2349.00 3352.00 6000.00 7000.00 7500.00 (1) Membrane 0.00% 9.00% 49.16% 56.42% 59.33% (2) Others 100.00% 91.00% 50.84% 43.58% 40.67% b. Sods 2009.00 3793.00 6350.00 8000.00 3500.00 C. CaC 1933.00 2281.00 2300.00 2000.00 1500.00 2) Pesticide 116.00 226.60 320.00 400.00 400.00 3) Other chemical products ('000 t) a. Ethylene 652.10 1572.10 3000.00 3500.00 3500,00 b. Plastic material 1234.00 2270.00 4500.00 9500.00 12500.00 c. Rubber 131.10 317.60 500.00 700.00 1000.00 d. Others 8. Basic chemical materials energy use (kgce/t) a. NaOH 1800.00 1790.00 1406.71 1343.61 1325.37 (1) Membrane 1185.00 1185.00 1000.00 1000.00 1000.00 (2) Other 1800.00 1350.00 1300.00 1800.00 1800.00 b. Soda 489.00 517.00 480.00 480.00 430.00 c. CaC 2300.00 2200.00 2000.00 2000.00 2000.00 d. Ethylene a) Real energy use (kgcelt) 2000.00 15380.00 1450.00 1450.00 1450.00 b) As raw material (kgoelt) 4154.00 3600.00 3500.00 3300.00 3200.00 9. Energy use for basic chemical materials (million tec) 9.66 12.93 17.33 17.28 17.02 Share in total chemical industry 29.59% 25.83% 17.29% 10.16% 6.30% Per unit output value caergy use (tee/million Yuan) 1070.65 992.26 304.10 743.24 712.89 9.1 Energy use for ethylene (million tee) 1.30 2.48 4.35 5.08 5.08 Oil as raw materials (million t) 2.71 5.66 10.50 11.55 11.20 10. Output value of major basic materials (billion Yuan) 9.02 13.08 21.55 23.25 23.33 Share in total chemical industry 10.95% 8.66% 5.35% 2.71% 1.45% 11. Other products energy use (million tce) 21.67 34.78 73.56 147.77 247.96 Share in total chemical industry 66.41% 69.22% 78.37% 36.86% 91.82% Per unit output value energy use (telmillion Yuan) 295.30 252.15 206.03 177.13 152.23 Energy conservation rate (%) 3.11 2.00 1.50 1.50 10. Output value of other products (billion Yuan) 73.38 137.93 381.33 834.25 1628.30 Share in total chemical industry 89.05% 91.34% 94.65% 97.29% 98.55% 83 E^ry cofdm kd~ calehton (B ehO Sunro) Tal **. eC- sector as whole 1. Total output value 103.17 18.96 456.39 936.71 1759.04 a. Partii 20.77 37.95 53.51 79.20 106.86 b. Basic echical materials 9.02 13.01 2».55 23.25 23.88 c. Fe & other product 73.38 137.93 381.33 834.25 162.30 2. Share a. Perlir 20.13% 20.06% 11.72% .46% 6.0% b. Basic chemical aaterilal 8.74% 6.92% 4.72% 2.48% 1.36% c. Pe & o r products 71.13% 73.00% 33.55% 89.06% 92.57% 3. aEy use 751.89 566.55 356.15 262.22 197.47 a. Pertilizer 2226.61 1562.57 1245.57 1017.30 770.93 b. Basic ch~e mateuials 1070.63 992.26 04.10 743.24 712.89 C. Pine & other products 295.30 252.15 206.03 177.13 152.28 84 Energy c0efidens cauladon (Ra~eline Senario) Ane 3 1:: Table 10. Cement metor 1985 1990 2000 2010 2020 1. Share in total output value (%) 1.96 1.97 1.85 1.40 1.12 2. Anmal output value (billion Yuan) 25.25 47.14 112.67 174.81 248.61 3. Annal growth rte (%) 13.30 9.10 4.49 3.58 4. Unit energy use (tce/million Yuan) 1306.01 946.28 828.43 687.53 592.81 in which: 100.00% 100.00% 100.00% 100.00% 100.00% a. Coal 30.35% 80.03% 78.77% 76.39% 75.17% b. Oil & gas c. Power 19.65% 19.97% 21.23% 23.61% 24.83% Energy aaving re (%) 6.24 1.32 1.85 1.47 5. Total energy use (million tCe) 32.98 44.61 93.34 120.18 147.38 a. Coal (million t) 37.10 49.98 102.93 128.53 155.11 b. Oil & gau (million toe) 0.00 0.00 0.00 0.00 0.00 c. Power (TWh) 16.04 22.05 49.05 70.23 90.56 Annual cergy use increaed rate (%) 6.23 7.66 2.56 2.06 6. Annual yield (million t) 145.95 209.70 455.61 622.74 783.20 In which: a. Large scale 20.27% 20.27% 22.82% 30.12% 36.24% a) Dry procea~ 32.69% 32.69% 79.10% 88.41% 92.34% b) Wet & old dry proccs 51.14% 51.14% 20.90% 11.59% 7.66% c) Half dry 16.17% 16.17% 6.80% 0.00% 0.00% d) Reolution out of kiln 16.58% 16.58% 66.25% 80.00% 80.00% b. Small scale 79.73% 79.73% 77.18% 69.88% 63.76% a) Old Vertical 18.04% 18.04% 5.00% 0.00% 0.00% b) Machinery vertical 70.00% 70.00% 1000% 80.00% 75.00% c) Horizontal 11.96% 11.96% 15.00% 20.00% 25.00% c. Share of quality 100.00 100.00% 100.00% 100.00% 100.00% a) Normal 33.84% 83.34% 70.37% 59.40% 50.60% b) High 16.16% 16.16% 29.63% 40.60% 49.40% 7. Per ton cement nergy use 7.1 Coal (kgce/t) a. Large scale 162.27 162.27 142.38 117.53 114.98 a) Dry process 120.00 120.00 120.00 110.00 110.00 b) Wec & old dry proce 190.00 190.00 175.00 175.00 175.00 c) Half dry 160.00 160.00 160.00 160.00 160.00 d) Re~olution out of kilo 120.00 120.00 110.00 100.00 100.00 b. Small scale 183.70 169.59 163.00 158.00 153.75 a) ol Vertical 200.00 180.00 180.00 180.00 180.00 b) Machnery Veticai 175.00 160.00 155.00 150.00 145.00 c) Horizonal 210.00 210.00 200.00 190.00 180.00 7.2 Power use (kWh/t) a. Large *cale 114.66 114.66 132.57 126.52 127.70 a) Dry proceaa 130.00 130.00 130.00 130.00 130.00 b) Wet & old dry proceu 100.00 100.00 100.00 100.00 100.00 c) Half dry 130.00 130.00 130.00 130.00 130.00 d) Resolution out of kilo 135.00 135.00 135.00 135.00 135.00 b. Small scale 101.49 96.19 98.25 100.00 101.25 a) old Vertical 95.00 85.00 85.00 85.00 85.00 b) Machinery Vertical 100.00 95.00 95.00 95.00 95.00 c) Horizontal 120.00 120.00 120.00 120.00 120.00 7.3 Total energy (kgce/t) 221.43 208.48 201.15 189.44 184.48 Share of power 19.65% 19.97% 21.23% 23.61% 24.83% a. Large 208.59 208.59 195.94 168.65 166.57 Share of power 25.13% 25.18% 26.80% 31.14% 31.53% b. Small 224.70 208.45 202.69 198.40 194.66 Share of power 18.25% 18.64% 19.58% 20.36% 21.01% 7.4 Total energy ue for cement (million tce) 32.32 43.72 91.65 117.97 144.48 a) Normal 27.09 36.65 64.49 70.07 73.10 b) High 5.22 7.07 27.15 47.90 71.38 8. Total output value (billion Yuan) pice (ylt) 18.21 31.81 73.23 104.88 136.73 a) Normal 140.00 15.76 27.16 44.89 51.78 55.48 b) High 210.00 2.45 4.65 28.35 53.10 81.26 C) Average price (Yuan/t) 124.77 151.69 160.74 168.42 174.58 9.1 Unit output value energy ue (tcelmillion Yuan) 1774.74 1374.33 1251.41 1124.79 1056.67 85 E~g ad ~ ak~ a ømei Scark) a) Nmaa 1719.21 1349.48 1436.79 1333.14 75.90 b) High 2131.93 1519.48 957.86 9 o.09 1138.35 9.2 Egy ving r~ (%) e) 0upu value 5.25 0.94 1.07 0. b) Product 1.21 0.36 0.60 0.27 10. C~eat produc ouput va~ (bilionYua ) 7.04 15.33 39.43 69.92 111.47 are in toWal buiig am~eials 27.88% 32.52% 35.00% 40.00% 45.00% 11. Bwegy s for cem products (uilio. tco) 0.66 0.89 1.69 2.21 2.89 ~are im tai ces idustry 2.00% 2.00% 1.64% 1.72% 1.86% 12. Unit argy um of ce pr~ducts ace ~illion Yua) 93.8 58.19 42.91 31.64 25.86 Eaergy sving ra~ (s) 9.99 3.09 3.09 2.04 86 Tble 11. Odber building ma~erials 1985 1990 2000 2010 2020 1. Sh in otal output valu (%) 3.55 4.69 5.77 5.82 5.99 2. Anmasd output valu (billio~ Yum) 45.81 112.31 351.22 726.38 1331.96 3. Aaalgrowth me(%) 19.64 12.06 7.54 6.25 4. Uait ergy usa (te/million Yu»a) 1167.77 697.73 379.20 255.09 176.68 in which: a. Coal 90.87% 90.43% 89.49% 89.48% 89.28% b. Oil & gas 6.00% 6.00% 6.00% 6.00% 6.00% c.Power 3.13% 3.57% 4.51% 4.52% 4.72% BaErgy -sving te (%) 9.79 5.92 3.89 3.61 5. Total emergy use (million tce) 53.50 78.36 133.18 185.29 235.34 a. Codi (mifiom t) 68.07 99.21 166.86 232.12 294.17 b. Oi & gas (miin te) 2.25 3.29 5.59 7.78 9.88 c. Power (Wh) 4.14 6.92 14.86 20.74 27.47 Anmual ergy ue icreased å te (%) 7.93 5.45 3.36 2.42 6. Major product anna yield la which: a. Brick & tiles (10^8 piece) 3247.00 4966.00 6500.00 7000.00 5000.00 b. Glass (0000 box) 4942.00 8067.00 15000.00 18000.00 22000.00 6.1 Major products unit output vsatu a. Brick & tilea (Yuaa000piece) 53.00 9.00 96.00 96.00 96.00 b. Glass (YmaaPbox) 82.00 82.00 100.00 140.00 160.00 6.2 Major producs total output vaea~ (billion Yua) 21.26 54.29 77.40 92.40 83.20 6.3 Share in tal other buildigg mmeils 46.41% 48.34% 22.04% 12.72% 6.25% 7. Other products (biflion Yua«) 24.55 58.02 273.82 633.96 1248.78 7.1 Share in total building materals 53.59% 51.66% 77.96% 87.28% 93.75% 8. Unit products eergy n e for major pr~-t a. Brick & tiles 136.27 110.43 96.90 96.90 %.90 a. Cowi (kg/'000 piece) 185.01 149.50 130.00 130.00 130.00 b. Oil & gas c. Power (kWh/'000 piece) 10.21 9.00 10.00 10.00 10.00 Energy saving rat. (%) 4.30 1.32 0.00 0.00 b. Glass 50.40 38.80 35.00 33.00 31.00 a. Coal (kgce/box) 38.00 28.59 25.79 24.32 22.84 b. Oil & gas (kgbox) 7.18 5.08 4.58 4.32 4.06 c. Power (kWhbox) 5.30 7.30 6.59 6.21 5.83 E-ergy ~sving rate (%) 5.37 1.04 0.59 0.63 c. Total ergy un (milliom te.) 46.20 57.31 67.13 72.52 53.83 a. Coni (milli t) 61.95 76.55 88.37 95.38 70.03 b. Oil & gas (millio t) 0.35 0.41 0.69 0.78 0.89 c. Power (TWh) 3.58 5.06 7.49 3.12 6.28 d. Share in total other building makeria 86.36% 73.13% 50.40% 39.14% 22.87% c. Umit energy (t~emiUlon Yun) 2173.00 1055.63 867.29 784.82 647.03 9. Other products emergy uie (millio. te) 7.30 21.05 66.05 112.78 181.51 a. Share in total other building materiha 13.64% 26.87% 27.17% 30.00% 45.00% b. Umit eergy us. (tceliulion Ysa) 297.30 362.84 241.23 177.89 145.35 c. Eergy sviag tate (%) -3.91 4.17 3.09 2.04 87 Fвс9рг оое!lieieвb aьwWioa (вв9дlве ScaaeЫ �во�L.3 1� т,ы. ». аи�..�;.а ма«...Уьом 1. То1в1 оwрц w1Ye 71.07 l!l.43 163.i{ 901.19 1St0.19 а. Савевt 25.23 47.14 112.67 174.i1 24t.61 Ь. Вгiгt !�1w 21.2б 54.29 77.�0 92.10 �7.20 а Рiве < аЬег р.оам. ц.ss s9.a�3 27з.а взэ.ю 12и.n 2.� в. С,авевt ц.33� 29.37� ц.29� 19.10� 13.73� b. Briгt! ilва 29.92� 34.03� 1б.б9� 10.23� 3.?b� с. Rве! оlУиреодваtв ц.33� 36.99� 39.Ofi� 70.33� Я.01� 3. Еварr we 1216.i9 771.21 1if.91 33i.97 242.1� в. Сюаt 1306.O1 916.2i iц.4� 6t7.33 S9Z.E1 Ь. 8псk L �1w 2173.OD 1063.63 t67.Z9 7ц.i2 647.03 е. Roe � аУх р,одУсд 297.90 >�.i4 цt.23 177.l9 143.33 8S EDergy codndeft cakulmdon ghwellw SwDado) Anux 3 1:: Table 12. Machinery 1995 Im 2000 2010 2MO 1. Share in total output value (%) 16.53 17.05 22.44 24.54 26.14 2. Annual output value (billion Yuan) 213.44 497.% 1365.03 3064.19 580.20 3. Annual growth rate (%) 13.93 12.94 8.42 6.61 4. Unit energy use (tcelmillion Yuan) 2".72 135.35 78.79 56.73 44.69 in which: a. Coal 33.31% 54.39% 50.00% 48.00% 45.00% b. Oil & gas 15.56% 12.93% 10.00% 7.00% 5.00% C. Power 31.13% 32.69% 40.00% 45.00% 50.OD% Energy saving rate (%) 11.1.7 5.27 3.23 2.36 5. Total energy use (million tce) 32.23 55.21 107.36 173.94 259.53 a. Coal (Million t) 38.98 42.04 75.29 116.32 163.50 b. Oil & gas (million we) 5.69 5.00 7.53 8.52 9.09 C. Power (M ) 4025 44.68 106.49 193.63 321.20 Annual energy use increasad rate (%) 1.12 6.90 4.92 4.09 Elasticity factor 0.08 0.54 0.59 0.62 6. Major products a. Machine tools ('ODO sets) 234.10 190.80 150.00 150.00 150.00 b. Travaportalion equipment 79166.21 119374.09 1248M.13 136196.12 21"93.45 a) Car ('000 sets) 168.20 224.30 2100.00 3500.00 5000.00 b) Truck ('000 acts) 269.00 299.70 350.00 1000-00 15W.00 C) ship ('000 t) 2219.40 1410.00 1410.OD 1410.W 1410.00 c. Spocial equipment ('000 9) 1192.70 1563.60 2101.33 2924.04 3795.27 d. Generation equipment (MW) 3636.00 12254.00 13997.91 23674-52 25240." 7. Output value 0) Sham in total a. Metal products 6.23% 8.21% 7.00% 6.00% 5.00% b. Machinery building 45.56% 42.91% 33.12% 33.00% 29.00% c. Transportation equipment 20.27% 19.98% 29.00% 25.OD% 30.00% d. Electrical equipment 14.76% 14.48% 14.90% 20.00% 22.00% 6. Others 13.18% 15.52% 16.98% 16.00% 15.00% b) Billion Yuan a. Metal products 13.30 33.49 95.55 133.95 290.46 b. Machinery building 97.24 175.05 452.10 1011AS 1626.59 c. Transportation equipment 43.26 77.02 382.21 766.05 1742.76 d. Electrical eWipment 31.30 59.07 20S.39 612-84 1278.02 C. Calms 28.13 63.31 231.78 490.27 971.39 9. Energy use 8) Unit energy use (tcotmillion Yuan) a. Metal products 290.51 127.79 76.51 36.42 46.10 b. Machinery building 263.14 147.93 88.57 65.32 53.37 c. Transportation equipment 139.92 97.07 59.12 42.96 35.M d. Electrical equipment 106.64 66.16 39.61 29.21 23.87 C. Others 449.21 215.67 129.13 95.22 77.81 b) Total (million tee) a. Metal products 3.73 4.29 7.31 10.37 13.39 b. Machinery building 25.59 25.90 40.04 66.05 96.81 c. Transportation equipment 6.92 7.48 22.21 32.93 61.03 d. Electrical equipmeat 3.36 3.91 8.06 17.90 30.50 e. Others 12.64 13.65 29.93 46.69 67.30 89 Easy coeficdieta m.td~ (Bu.ea Srewao) Ae~3 |:: Table 13. Light industy 1983 1990 2000 2010 2020 1. Skarc intotal output valu (%) 47.26 49.37 49.06 49.48 49.61 2. Aa ~al outputvalue (bimie Yuam) 610.30 1181.10 29m4.49 6178.93 11026.45 3. Aamal growh rme (%) 14.12 9.71 7.55 5.96 4. Unit emrgy s (tec/milia Yuaa) 166.44 113.99 74.37 53.46 43.33 is which: a. Coal 61.13% 61.53% 55.00% 50.00% 45.00% b. Oil & get 12.79% 10,45% 10.00% 10.00% 10.00% c. Power 26.08% 28.02% 35.00% 40.00% 45.00% Energy saving rae (%) 7.29 4.18 3.25 2.03 5. ToWal energy ime (million te) 101.58 134.63 221.95 330.34 480.00 a. Coml (miliom ) 86.93 115.98 170.90 231.24 302.40 b. OiU & gas (miffiom lo) 9.09 9.85 15.54 23.12 33.60 c. Power CW) 65.57 93.38 192.28 327.07 534.65 Anal energy se increased rae (%) 5.80 5.13 4.06 3.81 E~aay fackor 0.41 0.53 0.54 0.64 6. Major mergy incsivo producs 6.1 Yeld (0i~ t) a. Paper 9.11 13.72 22.04 31.93 42.83 b. Texile products a) Yareå 3.54 4.63 6.00 6.00 6.00 b) Pabrica (bilio. m) 14.67 18.88 24.50 30.00 33.00 c) Dying (biflion m) 7.53 9.16 12.50 18.00 22.00 c. Sgar 4.51 5.44 7.91 11.52 16.75 d. Wime& beer 8.51 13.86 15.00 20.00 25.00 6.2 Energy nu (kgce/) a)Paper 1420.46 1245.33 1071.70 915.21 908.07 a. Coml (kg) 1375.50 1184.69 1010.00 860.00 850.00 b. Oil & gas (kgoet) 55.43 32.45 28.00 24.00 24.00 c. Power (kWh) 888.04 873.18 768.00 660.00 660.00 d. ToWal (kgcolt) 1420.46 1245.33 1071.70 915.21 908.07 e. Toal (miGioa to) 12.94 17.09 23.63 29.22 38.90 . Shamre in total light induty 12.74% 12.69% 10.64% 8.85% 8.10% g. Output valu (Yuhalt) 3000.00 3200.00 5200.00 7500.00 8500.00 b) Textil producta a. Yara (kWhl) 1983.00 2129.00 2500.00 3000.00 3458.00 b. Pabrica (kWh/1000 m) 230.70 252.40 270.00 300.00 320.00 c. Dying fabric (Ogce/ 000.) 444.30 438.80 420.00 400.00 400.00 d. Toal (m~iliam tco) 7.54 9.92 13.98 18.11 21.45 e. Shar. in tal light iadmtay 7.43% 7.37% 6.30% 5.48% 4.47% f. Shae in textil 31.73% 32.85% 27.56% 23.86% 19.38% c) Sugar (kgell) 125.00 120.00 115.00 100.00 100.00 d) Winae beer (gce/t) 198.00 171.00 150.00 145.00 140.00 e) Toal (miflion teo) 22.73 30.03 40.77 51.38 65.52 i) Shae im tal 22.38% 22.31% 18.37% 15.55% 13.65% 7. Major wector 7.1 Output valse a) Shae im talat a. Textil 29.08% 23.90% 23.90% 23.90% 23.90% b. Paper 3.91% 4.37% 3.84% 3.88% 3.30% c. Pod & drink 27.36% 23.78% 23.78% 23.78% 23.78% d. Ceusicul fiber 1.84% 2.39% 2.39% 2.39% 2.39% o. Medicim 2.60% 3.20% 3.20% 3.20% 3.20% f. Oheru 35.21% 42.36% 42.89% 42.85% 43.43% b) Billio Yam a. Textil 177.47 282.28 713.29 1476.76 2635.32 b. Peper 23.86 51.61 114.63 239.48 364.09 c. Pood & drink 166.98 280.87 709.71 1469.35 2622.09 d. Cemical ier 11.23 28.23 71.33 147.68 263.53 e. Mediciae 15.87 37.80 95.50 197.73 352.85 . Oher~ 214.89 500.31 1280.02 2647.94 4788.57 7.2 Energy u a) Unit emergy s (celaillion Yman) a. Textil 134.00 107.00 71.14 51.39 41.99 b. Paper 542.28 331.03 206.10 122.03 106.93 90 Emw c et Calulatin (a~eine Scenaro) Ann 3 e. Pood & drink 143.00 117.00 77.79 57.36 46.87 d. Chemical Gber 459.00 266.00 176.85 130.41 106.55 e. Medicie 280.00 173.00 115.02 84.82 69.30 f. Others 146.03 80.82 53.73 39.62 32.37 b) Total (willioa tce) a. Textile 23.78 30.20 50.74 75.89 110.65 b. Papr 12.94 17.09 23.63 29.22 38.90 c. Fond & drink 23.38 32.36 55.21 84.28 122.89 d. Chemical fiber 5.15 7.51 12.61 19.26 28.08 e. Medicine 4.44 6.54 10.98 16.77 24.45 f. Othesn 31.38 40.44 68.78 104.92 155.03 91 Euery coemelents caicula (Ditasalk ~ S Amanmi 1:: Table 14. Building ector 1985 1990 2000 2010 2020 1. Sbau in oal output valuc(%) 9.48 7.06 10.69 11.35 11.93 2. Annal ouput value (billion Yuan) 251.92 300.90 1146.81 2667.96 5300.84 3. Amaum growt (%) 3.62 14.32 8.81 7.11 4. Uait cwgy um (tWe/milioa Y-un) 51.68 40.31 26.80 20.81 17.00 in wich: a. CodI 29.77% 24.39% 26.00% 26.00% 26.00% b. Oil & gas 48.14% 53.96% 49.00% 44.00% 39.00% c. Power 22.09% 21.65% 25.00% 30.00% 35.00% Ensr saving rat (%) 4.85 4.00 2.50 2.00 5. ToW cargy usm (million te) 13.02 12.13 30.74 55.51 90.12 a. Coa (million t) 5.43 4.14 11.19 20.21 32.80 b. 001 & gas (million too) 4.39 4.58 10.54 17.10 24.60 c. Power(TWh) 7.12 6.50 19.02 41.22 78.07 6. Annumal growt rate (%) -1.41 9.74 6.09 4.96 7. Elaticity factor -0.39 0.68 0.69 0.70 Table 15, Comumnicatiom 1985 1990 2000 2010 2020 1. S in toal output valu (%) 3.58 3.60 3.51 3.40 3.55 2. Annual output value (billian yuan) 95.17 153.50 376.73 799.14 1578.24 3. Annual growth rte (%) 10.03 9.39 7.81 7.04 4. Unit eergy use (tc/million Yunn) 340.35 239.02 169.53 129.69 107.10 in which: a. Comf 44.52% 34.08% 30.00% 15.00% 0.00% b. 4l2 & gas 48.58% 56.49% 55.00% 60.00% 60.00% c. Power 6.90% 9.43% 15.00% 25.00% 40.00% Enorgy saviag rae (%) 6.82 3.38 2.64 1.90 5. Total emergy usm (miflion tco) 32.39 36.69 63.87 103.64 169.02 a. Comf (Milli= t) 20.19 17.51 26.82 21.76 0.00 b. Oil & gas (millio too) 11.01 14.51 24.59 43.53 70.99 c. Power (TWh) 5.53 8.56 23.71 64.13 167.35 6. Anualgrowthrate(%) 2.52 5.70 4.96 5.01 7. elsicity factor 0.25 0.61 0.64 0.71 8. Enegy saving rate (%) 9. Cargo transpaotaeio (10-8 t.km) 18126.00 26207.00 41472.17 60130.36 85982.29 10. Enrgy ue per unit (tce/million t.km) 17.87 14.00 14.00 14.00 14.00 11. Total c~ergy ue (milliou te) 32.39 36.69 58.06 85.16 120.38 12. Share of pcst & coem=ucaion 12.27% 12.27% 20.00% 30.00% 40.00% 13. Output vue of post (million Yuan) 11.68 18.83 75.35 239.74 631.29 14. Energy ue for post & oom~uaication (milliom to) 0.00 0.00 5.81 18.47 48.65 15. Unit energy use for P&C (ce/Million Yuan) 77.06 77.06 77.06 92 Energy coefficients calculation (Baseline Scenario) Annex Table 16. Commercial sector 1985 1990 2000 2010 2020 1. Share in total output value (%) 5.44 4.09 4.38 5.53 6.19 2. Annual output value (billion Yuan) 144.56 174.20 469.53 1300.04 2749.30 3. Annual growth rate (%) 3.80 10.42 10.72 7.78 4. Unit energy use (toemillion Yuan) 53.01 71.60 47.60 35.10 28.68 in which: a. Coal 69.18% 61.22% 45.00% 33.00% 35.00% b. Oil & gas 10.78% 14.09% 20.00% 25.00% 20.00% c. Power 20.04% 24.69% 35.00% 42.00% 45.00% Energy saving rate (%) -6.20 4.00 3.00 2.00 5. Total energy use (million tee) 7.66 12,47 22.35 45.64 78.86 a. Coal (million t) 7.42 10.69 14.08 21.08 38.64 b. Oil & gas (million to) 0.58 1.23 3.13 7.99 11.04 c. Power (TWh) 3.80 7.62 19.36 47.44 87.84 6. Annual growth rate (%) 10.23 6.01 7.40 5.62 7. Elasticity factor 2.69 0.58 0.69 0.72 Table 17. Passenger Transportation 1985 1990 2000 2010 2020 1. Share in total output value (%) 0.79 0.80 0.68 0.89 1.38 2. Annual output value (billion Yuan) 21.09 34.01 72.60 208.28 613.58 3. Annual growth rate (%) 10.03 7.88 11.11 11.41 4. Unit energy use (teelmillion Yuan) 1256.09 890.20 627.40 409.74 282.60 in which: a. Cost 44.52% 34.08% 20.00% 10.00% 0.00% b. Oil & gas 52.78% 63.22% 77.00% 85.00% 93.00% c. Power 2.70% 2.70% 3.00% 5.00% 7.00% Energy saving rate (%) 6.65 3.44 4.17 3.65 5. Total energy use (million tee) 26.49 30.28 45.55 85.34 173.40 a. Coal (million t) 16.51 14.45 12.75 11.95 0.00 b. Oil & gas (million too) 9.79 13.40 24.55 50.78 112.88 c. Power (TWh) 1.77 2.02 3.38 10.56 30.04 6. Annual growth rate (%) 2.71 4.17 6.48 7.35 7. Elasticity factor 0.27 0.53 0.58 0.64 8. Energy saving rate (%) 9. Amount passenger transportation (10'S person.km) 4437.00 5628.00 8281.68 14223.39 24771.29 10. per car energy use (tce/104 person 'km) 5.97 5.38 5.50 6.00 7.00 11. Total energy use (million tee) 26.49 30.28 45.55 85.34 173.40 93 Energy coeftdents cakulation (asefline Scenarlo) Anne Table 18. Other service sector 1985 1990 2000 2010 2020 1. Share in total output value (%) 9.21 10.33 13.01 17.54 20.63 2. Annual output value (billion Yuan) 244.67 440.18 1395.89 4122.73 9169.37 3. Annual growth rate (%) 12.46 12.23 11.44 8.32 4. Unit energy use (twelmillhon Yuan) 100.95 73.89 52.45 38.68 31.60 in which: a. Coal 45.76% 40.79% 32.00% 20.00% 15.00% b. Oil & gas 34.34% 35.66% 38.00% 40.00% 40.00% c. Power 19.91% 23.55% 30.00% 40.00% 45.00% Energy saving rate (%) 4.81 4.00 3.00 2.00 5. Total energy use (million tee) 24.70 34.73 73.21 159.45 289.76 a. Coal (million t) 13.82 19.83 32.80 44.65 60.85 b. Oil & gas (million toe) 5.94 3.67 19.47 44.65 81.13 c. Power (TWh) 22.17 20.24 54.36 157.87 322.76 6. Annual growth rate (%) 7.05 7.74 3.09 6.16 7. elasticity factor 0.57 0.63 0.71 0.74 94 Energy coeffkcents calculation (Baseline Scenarlo) Annex 3 I:: Table 19. Houseold uoc 1985 1990 2000 2010 2020 1. Total populaion 1058.58 1143.33 1300.00 1400.00 1450.00 2. Annual growth rate (%) 1.55 1.29 0.74 0.35 3. Share of population &.Rural 79.75% 78.36% 75.00% 70.00% 65.00% b. U~ban 20.25% 21.64% 25.00% 30.00% 35.00% 4. Per capita cnergy use a. Rurul (kgcc) 56.52 60.09 98.03 167.23 191.47 a) Coal (kg) 69.58 68.64 90.00 120.00 120.00 b) Oil & gas (kgoe) 1.42 1.16 1.00 0.50 0.50 c) Power (kWh) 11.85 23.28 80.00 200.00 260.00 b. Urban (kgce) 352.12 359.50 309.77 359.14 375.66 a) Coal (kg) 455.86 427.45 250.00 200.00 100.00 b) Oil & gas (kgoe) 2.40 6.82 7.00 10.00 15.00 c) Power (kWh) 57.14 110.01 300.00 500.00 700.00 c. Average 116.38 124.89 150.97 224.80 255.93 a) Coal (kg) 147.81 146.29 130.00 144.00 113.00 b) Oil & gas (kgoe) 1.63 2.59 2.50 3.35 5.58 c) Power (kWh) 21.02 42.05 135.00 290.00 414.00 5. Total enegy use a. Rurl (million tcc) 47.71 53.84 95.58 163.88 180.46 a) Col (million t) 58.74 61.50 87.75 117.60 113.10 b) Oil & ga (million te) 1.20 1.04 0.98 0.49 0.47 c) Power (Wh) 10.00 20.86 78.00 196.00 245.05 b. Urban (million tee) 75.49 88.95 100.68 150.84 190.65 a) Coai (million t) 97.73 105.76 81.25 84.00 50.75 b) Oil & gas (million toe) 0.51 1.69 2.28 4.20 7.61 c) Power (Wh) 12.25 27.22 97.50 210.00 355.25 c. Family car ~tock ('000 Wta) 10.00 231.00 3000.00 10000.00 40000.00 d. Oil use for car (million toe) 0.01 0.23 3.00 10.00 40.00 d. Total (million en) 123.21 143.12 200.54 329.01 428.25 a) Coal (million t) 156.47 167.26 169.00 201.60 163.85 b) Oil & gas (million toe) 1.72 2.96 3.25 4.69 8.08 c) Power (TWh) 22.25 48.08 175.50 406.00 600.30 e. Share of total a) CoaJ 90.71% 83.48% 60.19% 43.77% 27.33% b) Oil & gas 2.00% 2.95% 2.32% 2.04% 2.70% c) Power 7.30% 13.57% 35.35% 49.85% 56.63% d) Total 100.00% 100.00% 97.86% 95.66% 86.66% 95 Energy coeffdents calculation (Baseline Scenario) Anmog3 Tables for Energy Coefficient Calculations Table I. The Sectoral Share of Total Output Value 1985 1990 2000 2010 2020 (1). Total output value (billion Yuan) 2656.30 4261.24 10725.42 23500.72 44446.58 (2). Annual growth rate (%) 9.91 9.67 8.16 6.58 (3). Sectors share of output value (%) I. Agriculture 22.87 17.98 11.00 3.15 6.32 II. lndustry 43.62 56.14 56.72 53.14 50.00 1. Cod industry 3.22 2.74 1.61 1.19 0.89 2. Oil industry 5.53 4.14 2.06 1.30 0.90 3. Natural gas 0.10 0.09 0.09 0.12 0.14 4. Power 3.63 2.99 2.48 2.27 2.16 S. Ferrous 7.00 6.12 4.44 4.04 3.34 6. Non-ferrous 3.26 2.94 2.69 2.34 1.79 7. Fertilizer industry 1.61 1.59 0.88 0.63 0.48 8. CUemical industry 6.38 6.31 6.62 6.87 7.43 9. Cement industry 1.96 1.97 1.35 1.40 1.12 10. Other building materials 3.55 4.69 5.77 5.32 5.99 11. Machinery & Electric 16.53 17.05 22.44 24.54 26.14 12. Light industry 47.26 49.37 49.06 49.48 49.61 13. Sub-total 100.00 100.00 100.00 100.00 100.00 III. Building sector 9.48 7.06 10.69 11.35 11.93 IV. Communication 3.58 3.60 3.51 3.40 3.55 V. Commercial sector 5.44 4.09 4.38 5.53 6.19 VI. Passenger trmsportation 0.79 0.80 0.68 0.89 1.38 VII. Other Nervice setor 9.21 10.33 13.01 17.54 20.63 Total 100.00 100.00 100.00 100.00 100.00 In which: 1. First industry 22.87 17.98 11.00 3.15 6.32 2. Second industry 58.10 63.20 67.42 64.49 61.93 3. Third industry 19.03 18.82 21.58 27.36 31.75 96 Enery coefficients calculation (Basellne Scenario) Anmx 3 I.- Table II. Sectoral Annual Growth Rate (%) 1985 85-90 90-2000 2000-2010 2010-2020 1. Agriculture 4.75 4.41 4.96 3.91 II. Industry 13.12 9.78 7.46 5.93 1. Coal industry 9.52 4.13 4.89 3.56 2. Oil industry 6.75 2.42 3.30 2.72 3. Natural gas 11.61 9.29 11.58 8.16 4. Power 8.80 7.73 7.22 6.03 5. Ferrous 10.12 6.33 7.13 4.58 6. Non-ferrous 10.85 8.79 6.68 3.74 7. Fertilizer iadustry 12.81 3.50 4.63 3.67 8. Caemical industry 12.83 10.31 8.55 7.43 9. Cement industry 13.30 9.10 5.17 4.22 10.Other building materials 19.64 12.08 3.24 6.90 11. Machinery & Electric 13.83 12.84 9.13 7.26 12. Light industry 14.12 9.71 8.25 6.61 M. Building sector 3.62 14.32 8.31 7.11 IV. Communication 10.03 9.39 7.81 7.04 V. Commercial sector 3.80 10.42 10.72 7.78 VI. Passenger transportation 10.03 7.8 11.11 11.41 VII. Other service sector 12.46 12.23 11.44 8.32 Total 9.91 9.67 8.16 6.58 In which: 1. First industry 4.75 4.41 4.96 3.91 2. Second industry 11.78 10.33 7.68 6.15 3. Third industry 9.67 11.13 10.76 8.18 97 E a w ~ f e ake. on al~ Se~n I:: T.le M. .a.y m..b~ ,... 1985 1990 2000 2010 2020 1. Coal (million tæc) 30.52 49.68 77.98 117.22 160.88 i. Con! (milion i) 30.8I 44.72 63.76 85.64 10.41 b. Oil & gas (million (cm) 0.57 0.89 1.30 1.91 2.47 c. Powor (Wh) 19.01 40.74 75.71 131.99 197.80 2. Oil (milion lli 27.32 35.27 51.53 69.81 33.52 n. Coa (million t) 1.55 3.94 10.30 12.97 15.35 b. Oil & gas (million &oc) 14.94 17.13 21.63 27.93 34.19 c. Power (Wh) 12.06 19.75 31.84 49.69 56.84 3. Naural gas (million te) 1.58 1.37 3.41 7.32 12.19 a. Cai (million t) 0.10 0.12 0.22 0A7 0.79 b. Oil & gas (million ioc) 0.80 0.95 1.74 3.73 6.21 c. Powr TWh) 0.18 1.04 1.91 4.09 6.82 4. Powr (million tec) 23.71 36.82 71.03 129.57 197.39 a. Coal (million t) 148.46 250.91 439.06 973.21 1308.60 b. Oil & gis (million toe) 14.33 11.08 13.38 14.57 15.18 c. Power (TWM) 58.68 91.14 175.81 320.72 488.59 5. Ferrus (million te) 81.70 106.89 153.61 223.48 286.05 a. Coed (million t) 82.47 102.96 135.48 184.67 216.25 b. Oil & ga (million toc) 4.29 5.61 7.53 10.26 12.01 c. Pwr (TWh) 41.26 62.70 114.07 195.34 283.21 6. Non-ferrous (million tc) 13.71 18.91 35.93 56.15 70.12 a. Coel (million t) 7.58 10.27 17.98 27.74 33.84 b. Oil & gas (million tog) 0.55 0.76 1.42 2.18 2.81 c. Powr (TWh) 18.56 25.98 52.11 82.25 103.80 7. Chemical fkstilizer (milion &wc) 46.25 59.30 66.65 80.57 82.38 a. Cod (million t) 40.09 52.05 58.24 69.80 69.95 b. Oil & gS (million to~) 5.07 6.50 7.12 8.01 l.28 c. Power(TWh) 25.67 31.75 36.81 47.70 50.96 8. Cheical industr (million tot) 32.63 50.24 100.24 170.12 270.05 a. Coni (million t) 20.74 24.62 37.89 52.40 83.18 b. Oil & gas (million fmc) 6.17 9.50 24.56 47.63 75.62 c. Powr (TWh) 22.29 47.26 94.29 160.02 254.01 9. Ceo~nt (million t"e) 32.98 44.61 93.34 120.18 147.38 a. Cont (million t) 37.10 49.98 102.93 128.53 155.11 b. Oil & gS (million toc) 0.00 0.00 0.00 0.00 0.00 c. Power (TWh) 16.04 22.05 49.05 70.23 90.56 10. Oher building md*ais (minlion e) 53.50 78.36 133.18 185.29 235.34 a. Ca (million t) 68.07 99.21 166.86 232.12 294.17 b. Oil & gA (million toc) 2.25 3.29 5.59 7.78 9.18 o. Power (TWh) 4.14 6.92 14.86 20.74 27.47 11. M & E I"dusr (million "ee) 52.23 55.21 107.56 173.84 259.53 6. Co~ (million t) 38.98 42.04 75.29 116.82 163.50 b. Oil & gas (million e) 5.69 5.00 7.53 8.52 9.08 c. Power CWh) 40.25 44.68 106.49 193.63 321.20 12. Light iodu&sy (million twc) 101.58 134.63 221.95 330.34 480.00 i. Coi (million t) 86.93 115.98 170.90 231.24 302.40 b. Oil & gas (million %oe) 9.09 9.85 15.54 23.12 33.60 C. Power (TWh) 65.57 93.38 192.28 327.07 534.65 13. Toual (million tc) 497.70 671.79 1116.41 1665.90 2214.3 a. Co~i (millicn t) 562.18 796.19 1278.94 2015.61 2751.54 b. Oil & as (million toc) 63.75 70.56 107.33 155.64 209.34 c. Power CWh) 324.48 487.39 945.23 1603.46 2415.91 14. Shar of energ a. Con] 55.36% 55.61% 52.06% 47.77% 44.19% b. Oil & gas 18.30% 15.01% 13.73% 13.35% 13.09% c. Power 26.34% 29.31% 34.21% 38.89% 42.72% 98 Eaery coefrodents calculation (Basellne Scenario) ADne. 1:: Table IV. Total Industry Output Value & Energy use 1985 1990 2000 2010 2020 A. Output value (illion Yua) 1. Agriculture 607.43 766.19 1180.05 1914.76 2810.58 1I. Industy 1. Coal industry 41.54 65.46 98.08 148.12 197.74 2. Oil industry 71.38 98.95 125.63 162.83 200.31 3. Natural gas 1.26 2.18 5.30 14.86 30.64 4. Power 46.86 71.42 151.05 284.06 480.25 5. Ferrous 90.37 146.35 270.41 504.39 743.09 6. Non-ferrous 42.09 70.45 163.56 292.55 397.36 7. Fertilizer industry 20.77 37.95 53.51 79.20 106.86 8. Chemical industry 82.40 151.01 402.83 857.50 1652.18 9. Cement industry 25.25 47.14 112.67 174.81 248.61 10.Other building materials 45.81 112.31 351.22 726.38 1331.93 11. Machinery & Electric 213.44 407.94 1365.03 3064.19 5809.20 12. Light industry 610.30 1181.10 2984.49 6178.93 11026.45 Sub-toal 1291.46 2392.26 6083.82 12487.82 22224.66 1. Building sector 251.92 300.90 1146.81 2667.96 5300.84 M. Third industry 1. Communication 95.17 153.50 376.73 799.14 1578.24 2. Commercial sector 144.56 174.20 469.53 1300.04 2749 30 3. Passenger transportation 21.09 34.01 72.60 208.28 613.58 4. Other service sector 244.67 440.18 1395.89 4122.73 9169.37 Sub-total 505.49 801.89 2314.75 6430.19 14110.49 IV. Total 2656.30 4261.24 10725.42 23500.72 44446.53 B. Energy use (million tec) 1. Agriculture 40.45 48.52 67.58 99.16 133.65 I. Iadustry 1. Coal industry 30.52 49.68 77.98 117.22 160.88 2. Oil industry 27.32 35.27 51.53 69.81 83.52 3. Natural gas 1.58 1.37 3.41 7.32 12.19 4. Power 23.71 36.82 71.03 129.57 197.39 5. Ferrous 81.70 106.89 153.61 225.48 286.05 6. Non-ferrous 13.71 18.91 35.93 56.15 70.12 7. Fertilizer industry 46.25 59.30 66.65 80.57 82.38 8. Chemical industry 32.63 50.24 100.24 170.12 270.05 9. Cement industry 32.98 44.61 93.34 120.18 147.38 10.Other building materials 53.50 78.36 133.18 115.29 235.34 I1. Machinery & Electric 52.23 55.21 107.56 173.84 259.53 12. Light industry 101.58 134.63 221.95 330.34 480.00 Sub-total 497.70 671.79 1126.41 1665.90 2284.83 1. Building sector 13.02 12.13 30.74 55.51 90.12 III. Third industry 1. Communication 32.39 36.69 63.87 103.64 169.02 2. Commercial sector 7.66 12.47 22.35 45.64 78.86 3. Passenger transportation 26.49 30.28 45.55 85.34 173.40 4. Other service sector 24.70 34.73 73.21 159.45 289.76 Sub-total 91.24 114.17 204.98 394.07 711.04 IV. Household use 123.21 143.12 200.54 329.01 428.25 V. Total for production 642.41 846.61 1419.70 2214.64 3219.63 VI. Total 765.63 989.73 1620.24 2543.65 3647.38 5.27 5.05 4.61 3.67 99 Energy c eilat.lenatl0m (liean Scenari0) able V. Sh~. of e~pg une & perg ela~icity faco A. Shmr of mary am. L Agricutur 5.28% 4.90% 4.17% 3.90% 366% U. Industry 1. Con imdusy 3.99% 5.2% 4.81% 4.61% 4.41% 2.Oi indusry 3.37% 3.56% 3.18% 2.74% 2.29% 3. Naurl ga 0.21% 0.19% 0.21% 0.29% 0.33% 4. Power 3.10% 3.72% 4.38% 5.09% 5.41% 5. Frou 10.67% 10.80% 9.48% s.86% 7.84% 6. No-forous 1.79% 1.91% 2.22% 2.21% 1.92% 7. Fertiizrindusy 6.04% 5.99% 4.11% 3.17% 2.26% 8. rCta indury 4.26% 5.03% 6.19% 6.69% 7.40% 9. Cea~w induty 4.31% 4.51% 5.76% 4.72% 4.04% 10.Odher building e*arials 6.99% 7.92% 8.22% 7.28% 6.45% i1. mwceaq &Electic 6.82% 5.58% 6.64% 6.33% 7.11% 12. Light industy 13.27% 13.60% 13.70% 12.99% 13.16% Sub-tota 65.01% 67.88% 68.90% 65.49% 6263% 1. Boilding weor 1.70% 1.23% 1.90% 2.18% 2.47% M. Third i~dusty 5. Commmnicatom 4.23% 3.71% 3.94% 4.07% 4.63% 2.Comutcialoseco 1.00% 1.26% 1.38% 1.79% 2.16% 3. Pa~sengr ~taporttion 3.46% 3.06% 2.81% 3.36% 4.75% 4. Oher ervice m~ctor 3.23% 3.51% 4.52% 6.27% 7.94% Su ea~ 11.92% 11.54% 12.65% 15.49% 19.49% IV. Household u 16.09% 14.46% 12.38% 12.93% 11.74% V. Total 83.91% 35.54% 87.62% 87.07% 88.26% B. Enery eluuticity factor 1. Agricultur 0.73 0.76 0.79 0.77 11. Indutry 1. Col iadutry 1.07 1.12 0.99 1.10 2. Oil indutry 0.78 1.60 1.17 0.86 3. Natural ga 0.29 0.67 0.73 0.70 4. Power 1.05 0.37 0.95 0.80 5. PCrrous 0.55 0.58 0.61 0.61 6. No~-feo~s 0.61 0.75 0.76 0.72 7. P~rtilizr indusry 0.40 0.34 0.48 0.07 g. Ckn indusy 0.70 0.69 0.69 0.70 9. cc~ induty 0.47 0.84 0.57 0.7 10.Oher building aei 0.40 0.45 0.45 0.39 11. gachiny & Electric 0.03 0.54 0.56 0.62 12. .ight lad~atsy 0.41 0.53 0.54 0.64 Sub.ota 0.47 0.53 0.55 0.54 1. Building seor -0.39 0.68 0.69 0.70 M. Thitd i~dss 1. Coaumuicaion 0.25 0.61 0.64 0.71 2. Comeni wetor 2.69 0.58 0.69 0.72 3. Pasegertanwpostatio. 0.27 0.53 0.538 0.64 4. Other servic ser 0.57 0.63 0.71 0.74 Sub4etal 0.47 0.54 0.63 0.74 IV. Total 0.57 0.55 0.56 0.58 100 Energy coeftkcents calculation (Baseline Scenarlo) Analo..3 Table VI. Unit energy use & energy conservation rate 1985 1990 2000 2010 2020 A. Unit energy use (tccimillion Yuan) 1. Agriculture 66.59 63.32 57.27 51.79 47.55 U. Industry 1. Coal industry 734.85 758.94 795.04 791.39 813.56 2. Oil industry 382.73 356.46 410.20 428.76 416.98 3. Natural gas 1251.34 855.10 643.92 492.24 397.91 4. Power 505.96 515.52 470.24 456.14 411.01 5. Ferrous 904.14 730.31 563.06 447.03 384.94 6. Non-ferrous 325.64 268.41 219.68 191.94 176.47 7. Fertilizer industry 2226.61 1562.57 1245.57 1017.30 770.93 8. Chemical industry 395.99 332.71 248.81 198.39 163.45 9. Cement indmssty 1306.01 946.28 828.43 687.53 592.81 10.Other building materials 1167.77 697.73 379.20 255.09 176.68 11. Machinery & Electric 244.72 135.35 78.79 56.73 44.63 12. Light industry 166.44 113.99 74.37 53.46 43.53 Sub-total 385.38 280.82 113.50 133.40 102.81 1. Building sector 51.63 40.31 26.80 20.81 17.00 M. Third industry 1. Comamuication 340.35 239.02 169.53 129.69 107.10 2. Commercial sector 53.01 71.60 47.60 35.10 28.68 3. Passenger transportation 1256.09 890.20 627.40 409.74 282.60 4. Otber service sector 100.95 78.89 52.45 33.68 31.60 Sub-total 110.50 142.37 8.55 61.28 50.39 IV. Total 288.23 232.26 151.07 108.24 82.07 241.14 191.68 132.37 94.24 72.44 B. Energy conservatioute (%) 1. Agriculture 1.00 1.00 1.00 0.85 11. Industry 1. Coal industy -0.65 -0.47 0.05 -0.23 2. Oil industry 1.41 -1.41 -0.44 0.23 3. Natural gas 7.33 2.10 2.65 2.10 4. Power -0.38 0.92 0.30 1.04 5. Ferrous 4.18 2.41 2.37 1.48 6. Not-l(efous 3.79 1.91 1.34 0.14 7. Fertilizer industry 6.84 2.24 2.00 2.74 8. Cemical induatry 3.42 2.16 2.24 1.92 9. Cement inlustry 6.24 1.32 1.85 1.47 10.Other building materials 9.79 5.92 3.89 3.61 11. Machinery &Electric 11.17 5.27 3.23 2.36 12. Light industry 7.29 4.18 3.25 2.03 Sub-total 6.13 4.17 3.14 2.57 1. Building sector 4.15 4.00 2.50 2.00 III. Third industry 1. Commasicatiom 6.32 3.38 2.64 1.90 2. Commercialsector .6.20 4.00 3.00 2.00 3. Pasenger transportation 6.65 3.44 4.17 3.65 4. Other searvice sector 4.11 4.00 3.00 2.00 Sub-total 4.64 4.64 3.61 1.94 IV. Total 4.23 4.21 3.28 2.73 3.86 3.98 3.34 2.60 101 Energy coefficents calculadon (Baseline Scenario) Anns 3 |:: Table VII. Total energy unc in type 1985 1990 2000 2010 2020 1. Agriculture (million Ice) 40.45 48.52 67.58 99.16 133.65 a. Coal (million t) 23.17 22.67 28.38 38.87 52.39 b. Oil & gas (million toe) 7.75 10.56 15.61 22.21 29.94 c. Power (TM) 31.74 42.68 61.89 98.18 142.25 2. Industry (million tee) 497.70 671.79 1116.41 1665.90 2284.83 a. Coal (million t) 562.88 796.79 1278.94 2015.61 2751.54 b. Oil * gas (million toe) 63.75 70.56 107.33 155.64 209.34 c. Power TWh) 324.48 487.39 945.23 1603.46 2415.91 a. Building ~ector (million tee) 13.02 12.13 30.74 55.51 90.12 a. Coal (million t) 5.43 4.14 11.19 20.21 32.80 b. Oil a gas (million toe) 4.39 4.58 10.54 17.10 24.60 c. Power C(TW) 7.12 6.50 19.02 41.22 78.07 3. Third industry (million tce) 91.24 114.17 204.98 394.07 711.04 a. Con (million t) 59.95 62.47 86.46 99.44 99.49 b. Oil & gat (million tøe) 27.31 37.81 71.74 146.94 276.05 c. Power CWh) 23.27 38.45 100.82 280.01 607.98 A. Commaic*tion (million tce) 32.39 36.69 63.87 103.64 169.02 a. Conl (million t) 20.19 17.51 26.82 21.76 0.00 b. Oil & gas (million toe) 11.01 14.51 24.59 43.53 70.99 c. Power CWh) 5.53 8.56 23.71 64.13 167.35 b. Commercial metor (million toe) 7.66 12.47 22.35 45.64 78.86 a. Coal (million t) 7.42 10.69 14.06 21.08 38.64 b. Oil & ga (million toe) 0.58 1.23 3.13 7.99 11.04 c. Pow (TWb) 3.80 7.62 19.36 47.44 87.84 c. Pasenger transpotation (million le) 26.49 30.28 45.55 85.34 173.40 a. Coal (million t) 16.51 14.45 12,75 11.95 0.00 b. Oil & gu (million we) 9.79 13.40 24.55 50.78 112.88 c. Power (TWh) 1.77 2.02 3.38 10.56 30.04 d. Other service scctor (million te) 24.70 34.73 73.21 159.45 289.76 a. Con (million t) 15.82 19.83 32.80 44.65 60.85 b. Oil & gaS (million toe) 5.94 8.67 19.47 44.65 81.13 c. Power CWh) 12.17 20.24 54.36 157.87 322.76 4. Household usc (million tet) 123.21 143.12 200.54 329.01 428.25 a. Coå[ (million t) 156.47 167.26 169.00 201.60 163.85 b. Oil & gas (million toe) 1.72 2.96 3.25 4.69 8.01 c. Power (TWh) 22.25 48.01 175.50 406.00 600.30 5. Total (million te) By added up 765.63 989.73 1620.24 2543.65 3647.88 By conert factor 766.64 987.18 1560.99 2376.63 3300.78 a. Coal (million ) 807.89 1053.34 1573.97 2375.73 3100.07 b. Oil & gan (million toe) 104.93 126.46 208.48 346.58 548.01 c. Power (TWh) 40.87 623.10 1302.46 2428.88 3844.52 8.79 7.65 6.43 4.70 6. Share of energy type 0.89 0.79 0.79 0.71 EAd ute a. Conl 58.85% 56.31% 49.14% 41.96% 35.96% b. Oil & ga 19.58% 18.25% 18.38% 19.46% 21.46% c. Power 21.57% 25.43% 32.48% 38.58% 42.58% Primary energy a. Coal 75.81% 76.19% 72.02% 71.40% 67.09% b. Oil & gat 19.34% 18.68% 19.08% 20.83% 23.72% c. Power 4.85% 5.13% 8.90% 7.77% 9.20% 102 Energy coeffidenis calculation (Baseline Scenario) Table VIII. Unit Output Value Energy Use by Sector 1985 1990 2000 2010 2020 A. Coal use (t/million Yuaa) 1. Agriculture 38.15 29.59 24.05 20.30 18.64 II. Industry 1. Coal industry 741.65 683.16 650.05 578.21 548.22 2. Oil industry 21.66 39.86 81.99 79.64 76.61 3. Natural gas 80.76 55.19 41.56 31.77 25.68 4. Power 3168.46 3513.06 2906.94 3074.09 2724.82 5. Ferrous 912.64 703.49 501.03 366.11 291.02 6. Non-forrous 130.16 145.73 109.96 94.81 85.17 7. Fertilizer industry 1930.26 1371.60 1088.45 881.33 654.57 8. Cemical industry 251.69 163.03 94.05 61.11 50.34 9. Cement industry 1469.08 1060.27 913.57 735.30 623.90 10.Other building materials 1485.66 883.37 475.10 319.55 220.85 11. Machinery & Electric 182.65 103.04 55.16 31.12 28.15 12. Light industry 142.44 98.19 57.26 37.42 27.42 Subtotal 320.89 228.13 138.05 91.48 64.93 1. Buildingsector 21.54 13.77 9.76 7.57 6.19 II. Third industry 1. Communication 212.15 114.04 71.20 27.23 0.00 2. Commercial sector 51.34 61.37 29.99 16.22 14.05 3. Passenger transportation 782.96 424.73 175.67 57.36 0.00 4. Other service sector 64.67 45.05 23.50 10.83 6.64 Sub-total 118.59 77.91 37.35 15.46 7.05 IV. Total 189.35 149.06 90.06 55.36 36.62 Bl. Oil& gas use (toe/million Yuan) 1. Agriculture 12.76 13.78 13.23 11.60 10.65 11. Induay 1. Coal industry 13.65 13.65 13.20 12.87 12.30 2. Oil industry 209.31 173.15 172.14 171.56 170.69 3. Natural Sas 637.60 435.70 328.10 250.81 202.75 4. Power 305.83 155.13 88.58 51.29 31.60 5. Perrous 47.47 38.34 27.83 20.34 16.17 6. Non-ferrous 13.16 10.72 3.70 7.44 7.07 7. Fortilizer industry 244.03 171.40 133.11 101.13 77.49 8. Chanical industry 74.84 62.88 60.96 55.55 45.77 9. Cement industry 0.00 0.00 0.00 0.00 0.00 10.Other building materials 49.05 29.30 15.93 10.71 7.42 I1. Machinery & Electric 26.66 12.25 5.52 2.73 1.56 12. Light industry 14.90 8.34 5.21 3.74 3.05 Subotal 38.27 24.86 15.44 11.30 3.74 1. Building sector 17.42 15.23 9.19 6.41 4.64 III. Third industy 1. Communicatiou 115.74 94.52 65.27 54.47 44.98 2. Commercial sector 4.00 7.06 6.66 6.14 4.02 3. Passenger transportation 464.04 393.95 338.17 243.79 183.97 4. Other service sector 24.26 19.69 13.95 10.83 8.85 Subtotal 54.04 47.15 30.99 22.85 19.56 IV. Total 33.46 26.38 17.89 13.93 11.81 B2. Oil use (toelaillion Yuan) L Agriculture 12.76 13.78 13.10 11.02 9.59 II. Industry 1. Coal industry 13.30 12.52 12.10 11.80 11.46 2. Oil industry 163.05 133.58 117.79 117.40 116.80 3. Natural gas 378.98 286.35 215.63 164.84 133.25 4. Power 293.36 151.16 79.72 35.91 18.96 5. Ferrous 42.11 33.89 23.66 16.27 11.32 6. Non-ferrous 11.39 10.32 7.33 6.32 5.65 7. Fertilizer industry 80.87 64.68 33.28 20.23 7.75 8. Chemical industry 69.19 59.80 54.36 47.22 36.61 103 Eney coefients calculation (Baseline Scenario) Annex 3 9. Cement indusry 0.00 0.00 0.00 0.00 0.00 10.Ofher buMlding mtrials 45.39 27.15 14.33 5.36 2.97 11. Machiy & Electric 24.08 11.41 4.96 2.36 1.25 12. Light idstry 13.53 7.65 4.69 2.99 2.13 Sub-~tal 30.37 20.19 12.02 8.07 5.87 . Building sector 12.21 11.95 7.21 5.03 3.64 MI. Third industry 1. Commnicatiou 114.95 93.36 64.47 53.80 44.43 2. Commercial sector 4.00 7.06 6.33 4.61 2.81 3. Panseger trnsportation 464.04 393.95 338.17 243.79 183.97 4. O~ter service sector 24.07 19.44 13.25 8.12 6.19 SUb-~ctal 53.80 46.79 30.38 20.72 17.54 IV. Total 28.93 23.05 15.39 11.29 9.42 C. Unit output nat~rl gas us (000 cubic eter/m1llioa Yua) 1. Agriulmtre 0.00 0.00 0.14 0.62 1.14 DI. iadusr 1. Coal industry 0.37 1.22 1.18 1.15 1.12 2. Oit i~uatry 49.69 42.50 58.38 58.18 57.89 3. Naural gas 277.79 160.42 120.80 92.35 74.65 4. Power 13.39 4.17 9.51 16.53 13.58 5. Peros 5.75 4.78 4.48 4.37 5.21 6. NoS-ferrous 1.90 0.43 0.93 1.20 1.52 7. ertiizer idusty 175.25 114.63 107.23 86.90 74.91 8. Chemical industry 6.07 3.31 6.55 8.95 9.83 9. Cement industry 0.00 0.00 0.00 0.00 0.00 10.Otbr buitding materials 3.93 2.32 1.71 5.75 4.78 11. Machinery & Electric 2.76 0.91 0.59 0.45 0.34 12. Light industry 1.47 0.74 056 0.80 0.98 Sub-o~aI 8.48 5.02 3.67 3.47 3.08 1. Buiiag sector 5.60 3.52 2.13 1.48 1.07 M. Third industry 1. Comuaicatom 0.84 1.24 0.85 0.71 0.59 2. Conmercia sector 0.00 0.00 0.36 1.65 1.29 3. Passeuger trmnsportaion 0.00 0.00 0.00 0.00 0.00 4. Other service sector 0.20 0.27 0.75 2.91 2.85 Su~.etal 0.26 0.39 0.66 2.29 2.17 IV. Total 4.86 3.58 2.69 2.83 2.56 D. Unit output power use (MWh/milliom Yuan) . Agriculture 52.25 55.70 52.45 51.28 50.62 1I. Industry 1. Coal isdury 459.43 622.44 771.93 891.08 1000.27 2. 0i industry 168.92 199.60 253.47 305.15 283.76 3. Natur l gas 699.99 478.34 360.21 275.35 222.59 4. Power 1252.38 1276.04 1163.96 1129.06 1017.35 5. Ferrous 456.55 428.46 421.83 387.28 381.13 6. Nos.errous 441.00 368.82 318.61 281.16 261.22 7. Petilizer industry 1235.75 836.61 687.98 603.22 476.92 8. Cle.u.~u industry 270.53 312.94 234.03 186.61 153.74 9. ce~e.. imdustry 635.31 467.69 435.36 401.78 364.27 10.Oher buildimg mateuals 90.38 61.60 42.30 28.55 20.62 11. Machimery & Electric 188.57 109.52 78.01 63.19 55.29 12. Light industry 107.44 79.06 64.43 52.93 48.49 Su~.ta5 251.25 203.74 155.37 128.40 108.70 1. Building sector 28.26 21.60 16.58 15.45 14.73 m. Third iedusay 1. Coamnidion 58.11 55.80 62.94 80.25 106.04 2. Conmercial sector 26.30 43.75 41.24 36.49 31.95 3. Pasaeger tranportatioo 83.95 59.49 46.59 50.71 48.97 4. Other service sector 49.74 45.98 38.95 38.29 35.20 Sub-otal 46.04 47.95 43.56 43.55 43.09 IV. Total 145.55 134.94 105.07 86.08 72.99 104 Energy coefficients calculation (Business as usual) Table 25. Total Energy Demand Projection (06-10-1994) (Final) Items 1985 1990 2000 2010 2020 1. Total primary energy use (million tce) 766.82 987.03 1560.99 2376.63 3300.78 1. Coal (million t) 807.89 1053.34 1573.97 2375.73 3100.07 2. Oil and gas (million toe) 92.90 112.27 181.65 284.62 442.04 3. Natural gas (10 ^ 9 cubic meter) 12-92 15.25 28.82 66.55 113.82 4. Power (TWh) 92.41 126.37 362.10 507.60 871.00 2. Total final energy use (million tce) 766.82 987.03 1560.99 2376.63 3300.78 1. Coal (million t) 659.43 802.42 1134.89 1502.52 1791.47 2. Oil (million toe) 79.15 101.47 169.60 274.42 432.93 3. Natural gas (10^ 9 cubic meter) 12.29 14.95 27.38 61.86 107.30 4. Power (TWh) 408.87 623.10 1302.46 2428.88 3844.52 3. Per capita use (tce) 724.39 863.29 1200.76 1697.59 2276.40 1. Coal (kg) 622.94 701.83 872.99 1073.23 1235.50 2. Oil (kgoe) 74.77 88.75 130.47 196.02 298.57 3. Natural gas (cubic meter) 11.61 13-07 21.06 44.19 74.00 4. Power (kWh) 386.24 544.99 1001.89 1734.91 2651.39 :D X Energy coefficients calculation (Low growth rate) Table 25. Total Energy Demand Projection (06-10-1994) (Final) Items 1985 1990 2000 2010 2020 1. Total primary energy use (million tce) 766.82 987.03 1534.51 2225.96 2878.74 1. Coal (million t) 807.89 1051.23 1550.88 2225.98 2670.61 2. Oil and gas (million toe) 92.90 113.32 175.52 257.38 369.80 3. Natural gas (10^ 9 cubic meter) 12.92 15.25 27.75 62.59 103.51 4. Power (TWh) 92.41 126.37 362.10 507.60 871.00 2. Total final energy use (million tce) 766.82 987.03 1534.51 2225.96 2878.74 1. Coal (million t) 659.43 800.31 1122.81 1426.39 1592.58 2. Oi (million toe) 79.15 102.53 163.48 247.18 360.70 3. Natural gas (10 ^ 9 cubic meter) 12.29 14.94 26.31 57.90 96.99 0 01 4. Power (TWh) 408.87 623.10 1279.04 2267.64 3319.55 3. Per capita use (kgce) 724.39 863.29 1180.40 1589.97 1985.34 1. Coal (kg) 622.94 699.98 863.70 101885 1098.33 2. Oil (kgoe) 74.71 89.67 125.75 176.56 248.76 3. Natural gas (cubic meter) 11.61 13.07 20.24 41.36 66.89 4. Power (kWh) 386.24 544.99 983.88 1619.74 2289.35 'I Energy coefficients calculation (High efficiency) Table 25. Total Energy Demand Projection (06-10-1994) (Final) Items 1985 1990 2000 2010 2020 1. Total primary energy use (million tce) 766.82 987.03 1473.85 2136.39 2841.28 1. Coal (million t) 807.89 1051.23 1466.83 2077.77 2529.84 2. Oil and gas (million toe) 92.90 113.32 174.29 267.39 410.29 3. Natural gas (10 ^ 9 cubic meter) 12.92 15.25 28.83 65.34 110.05 4. Power (TWh) 92.41 126.37 362.10 507.60 871.00 2. Total final energy use (million tee) 766.82 987.03 1473.85 2136.39 2841.28 1. Coal (million t) 659.43 800.31 1065.25 1328.95 1493.13 2. Oil (million toe) 79.15 102.53 162.25 257.19 401.19 3. Natural gas (10 ^ 9 cubic meter) 12.29 14.94 27.39 60.65 103.53 0 4. Power (TWIl 408.87 623.10 1227.58 2174.83 3255.26 3. Per capita use (kgee) 724.39 863.29 1133.73 1525.99 1959.51 1. Coal (kg) 622.94 699.98 819.42 949.25 1029.74 2. Oil (kgoe) 74.77 89.67 124.81 183.71 276.68 3. Natural gas (cubic meter) 11.61 13.07 21.07 43.32 71.40 4. Power (kWh) 386.24 544.99 944.29 1553.45 2245.01 :3p Table 1. Total Energy Savings by Economic Sector, 1990-2020 (Chain Method) (1) Items 1986-1990 1991-2000 2001-2010 2011-2020 1990-2020 mtce % nt. % mtce % mtce mtoe % Material production 229.82 111.28 446.72 77.53 523.33 73.73 612.12 69.97 1582.17 73.22 Agricuture 2.28 1.10 5.91 1.03 8.48 1.19 10.05 1.15 24.44 1.13 Industry 205.47 99.49 390.22 67.72 453.78 63.93 525.31 60.04 1369.32 63.37 Construction 3.18 1.54 5.73 1.52 11.07 1.56 14.93 1.71 34.73 1.61 Traport/Post 21.58 10.45 34.59 6.00 39.55 5.57 49.09 5.61 123.23 5.70 Commerce -2.69 -1.30 7.26 1.26 10.45 1.47 12.74 1.46 30.45 1.41 0 Nonmaterial production 7.55 3.66 22.31 3.87 35.62 5.02 45.87 5.24 103.79 4.80 Household use 45.06 21.82 104.80 18.19 78.13 11.01 145.44 16.62 328.36 15.20 Subtotal 282.43 136.76 573.83 99.58 637.08 89.75 803.42 91.83 2014.33 93.21 Due to structure change -75.91 -36.76 2.40 0.42 72.76 10.25 71.47 8.17 146.63 6.79 Total 206.52 100.00 576.22 100.00 709.84 100.00 874.69 100.00 2160.96 100.00 Detailed In Industrial Sectors Total Savings 390.22 100.00 453.78 100.00 525.31 100.00 1369.32 100.00 Due to: Structure Change Between Industrial Sectors 116.90 30.47 127.11 28.01 160.47 30.55 406.47 29.68 Strature Changes Within Industrial Sectors 197.27 50.55 233.29 51.41 250.63 47.71 681.18 49.75 Technical improvement 74.06 18.98 93.39 20.58 114.21 21.74 281.66 20.57 High Energy Intensive Produces (2) 47.44 12.16 56.92 12.54 61.52 11.71 165.69 12.11 Boilers & Motors(3.4) 26.61 6.82 36.46 8.04 52.69 10.03 115.77 8.45 Note: 1. 'Chain Method" is used during calculations 2. Based 6 kinds ol energy Intensive products' *ton to ton" savings 3. Boiler eliciency Is considered as 60% in 1990, and 70% In 2020 with gradually Incresed year by year 4. Motors efficleony Is considered as 85% In 1990 and 90% in 2020 with gradually Increased. Table 2. Total Energy Savings by Economic Sector. 1990-2020 (Fixed Comparison Method) (1) Items 2000:1990 2010:2000 2020:2010 2020:1990 mtos % mice % mtoe % mtce % Material production 677,01 77.74 724.73 72.01 798.46 68.66 4682.54 70.15 Agfcuture 7.15 0.82 10.48 1.04 11.91 1.02 44.33 0.66 Industry 592.04 67.98 625.67 62.16 679.99 58.47 3956.27 59.27 Construtiork 15.50 1.78 15.99 1.59 20.18 1.73 12357 1.85 Trsport/Post 51.08 5.88 56.34 560 68.73 6.91 440.37 660 Commerce 11.27 1.29 16.25 1.61 17.65 1.52 118.00 1.77 Nonmaterial production 36.91 4.24 56.78 5.64 64.87 5.58 433.60 6.50 Household use 159,68 18.34 110,41 10.97 194.00 16.68 1064.56 15.95 Subtotal 873.61 100.31 891.92 88.62 1057.34 90.92 6180.69 92.59 Due to structure change -2.74 -0.31 114.58 11.38 105.55 9.08 494.69 7,41 Total 870.57 100.00 1006.50 100.00 1162.89 100.00 6675.38 100.00 Detailed In Industrial Sectors Total Savings 592.04 100.00 625.67 100,00 679.99 100,00 3956.27 10000 Due to: Structure Change Between Industrial Sectors 171.15 28.91 179.86 28.75 213.58 31.41 564.59 14.27 Streture Changes Within Industrial Sectors 328.14 55.43 330.64 52.85 332.51 48.90 2864.10 72.39 Technical Improvement 92.75 15.67 115.17 18.41 133.90 19.69 527.58 13.34 High Energy Intensive Produces (2) 60.69 10.25 71.71 11.46 71.80 10.56 333.00 8.42 Boilers & Motors (3,4) 32.06 5.41 43.46 6.95 62.09 9.13 194.58 4.92 Note: 1. 'Fxed Comparison Method' is used during calculations 2, Based 6 kinds of energy Intensive products "ton to ton* savings 3. Boiler efficiency is considered as 60% in 1990, and 70% In 2020 with gradually Incresed year by year 4. Motors efficiecny is considered as 85% In 1990 and 90% In 2020 with gradually increased. Annex 3 Files for Technical Energy Conservation Calculations Table 1. Assumptions for Technical improvement (2020) Items DNT BAU HES 1. Thermal Power (TWh) 3309.44 2973.52 2719.69 Energy use (kgce/MWh) 395.30 322.60 319.42 Coal use (kgce/MWh) 363.20 315.31 312.20 Oil & gas (kgce/MWh) 32.10 7.29 7.22 Power use (kWh/MWh) 146.70 127.10 127.10 2. Steel (million t) 221.06 221.06 221.06 Energy use (kgce/t) 1610.99 1293.98 857.31 Coal use (kgce/t) 1108.36 698.75 462.95 Oil & gas (kgce/t) 120.82 77.64 51.44 Power use (kWh/t) 945.06 1281.17 848.82 3. Ammonia (million t) 34.17 34.17 34.17 Energy use (kgce/t) 2066.41 1537.00 1257.90 Coal use (kgce/t) 1295.64 872.46 497.02 Oil & gas (kgch/t) 494.10 354.24 679.44 Power use (kWh/t) 1095.56 1078.42 282.20 4. Caustic soda (million t) 7.50 7.50 7.50 Energy use (kgoe/t) 1790.00 1325.37 1000.00 Coal use (kgce/t) 1109.80 821.73 620.00 Oil & gas (kgce/t) 0.00 0.00 0.00 Power use (kWh/t) 1683.66 1246.64 940.59 5. Cement (million t) 783.20 783.20 783.20 Energy use (kgce/t) 208.48 184.48 162.40 Coal use (kgce/t) 166.85 138.67 104.98 Oil & gas (kgce/t) 0.00 0.00 0.00 Power use (kWh/t) 103.05 113.38 142.14 6. Paper (million t) 42.83 42.83 42.83 Energy use (kgoe/t) 1245.33 908.07 908.07 Coal use (kgce/t) 846.21 607.14 607.14 Oil & gas (kgce/t) 46.36 34.29 34.29 Power use (kWh/t) 873.18 660.00 660.00 Sub-total Sub-total 2288.31 1679.52 1443.81 Coal use (mt) 2625.11 1906.02 1637.95 Oil & gas (mtoe) 31.90 21.52 25.24 Power use (TWh) 862.58 824.42 689.60 Subtotal 877.76 643.13 506.03 7. Others Coal use 0.43 0.49 0.51 Oil & gas 0.95 1.00 1.05 Power use 0.71 0.78 0.81 Note: DNT, Do nothing; BAU. Business as Usual and MES. High Efficiency Situation 110 Annex 3 Table 2. High Energy Intensive Products Energy Use (2020) Items ONT BAU HES 1. Thermal Power Total (mtce) 206.93 131.73 119.19 Coal use (mt) 1682.79 1312.61 1168.72 Oil & gas (mt) 74.36 15.18 13.74 Power use (TWh) 485.50 377.93 345.67 2. Steel Total (mtce) 360.77 270.34 178.41 Coal use (mt) 343.02 216.25 143.27 Oil & gas (mt) 18.70 12.01 7.96 Power use (TWh) 208.92 283.22 187.64 3. Ammonia Total (mte) 77.11 54.76 43.52 Coal use (mt) 61.98 41.74 23.78 Oil & gas (mt) 11.82 8.47 16.25 Power use (TWh) 37.44 36.85 9.64 4. Caustic soda Total (mtce) 13.71 9.42 7.08 Coal use (mt) 11.65 8.63 6.51 Oil & gas (mt) 0.00 0.00 0.00 Power use (TWh) 12.63 9.35 7.05 5. Cement Total (mtce) 165.07 139.56 120.60 Coal use (mt) 182.94 152.05 115.10 Oil & gas (mt) 0.00 0.00 0.00 Power use (TWh) 80.71 88.80 111.32 6. Paper Total (mtce) 54.17 37.32 37.22 Coal use (mt) 50.74 36.41 36.41 Oil & gas (mt) 1.39 1.03 1.03 Power use (TWh) 37.40 28.27 28.27 Sub-total (TCE) Total (mtce) 877.76 643.13 506.03 -0.00 Coal use (mt) 2333.13 1767.68 1513.79 Oil & gas (mt) 106.26 36.69 38.98 Power use (TWh) 862.58 824.42 689.60 7. Others (mtce) Total (mtce) 3265.32 2734.78 2610.30 Coal use (mt) 1515.20 1332.39 1280.03 Oil & gas (mt) 538.23 511.32 486.97 Power use (TWh) 3317.86 3020.10 2901.08 8. Total Total 4040.75 3300.78 3047.28 Coal use (mt) 3848.33 3100.07 2793.83 Oil & gas (mtoe) 644.49 548.01 525.95 Power use (TWh) 4180.44 3844.52 3590.69 111 Annex 3 Table 3. High Energy Intensive Products Energy Savings (2020) Items BAU vs HES vs HES vs DNT DNT BAU 1. Thermal Power Total (mtce) 391.48 494.77 100.94 Coal use (mt) 370.18 494.07 123.89 Oil & gas (mt) 59.18 60.62 1.43 Power use (TWh) 107.56 139.82 32.26 2. Steel Total (mtoe) 70.72 166.42 88.75 Coal use (mt) 126.77 199.75 72.98 Oil & gas (mt) 6.68 10.74 4.05 Power use (TWh) -74.30 21.27 95.57 3. Ammonia Total (mtce) 19.47 31.94 10.49 Coal use (mt) 20.24 38.20 17.96 Oil & gas (mt) 3.35 -4.43 -7.78 Power use (TWh) 0.59 27.79 27.21 4. Caustic soda Total (mtce) 3.46 5.88 2.25 Coal use (mt) 3.02 5.14 2.12 Oil & gas (mt) 0.00 0.00 0.00 Power use (TWh) 3.28 5.57 2.30 5. Cement Total (mtce) 18.87 36.36 19.13 Coal use (mt) 30.89 67.84 36.95 Oil & gas (mt) 0.00 0.00 0.00 Power use (TWh) *8.09 *30.61 -22.52 6. Paper Total (mtoe) 14.37 14.37 0.00 Coal use (mt) 14.33 14.33 0.00 Oil & gas (mt) 0.36 0.36 0.00 Power use (TWh) 9.13 9.13 0.00 Sub-total Total (mtoe) 518.37 749.74 221.57 Coal use (mt) 565.45 819.34 253.89 Oil & gas (mt) 69.57 67.28 -2.29 Power use (TWh) 38.16 172.98 134.82 7. Others (mtoe) Total (mtce) 286.73 405.96 110.57 Coal use (mt) 182.82 235.17 52.35 Oil & gas (mt) 26.91 51.26 24.35 Power use (TWh) 297.76 416.78 119.02 8. Total Total 805.10 1155.69 332.14 Coal use (mt) 748.26 1054.50 306.24 Oil & gas (mtoe) 96.49 118.54 22.06 Power use (TWh) 335.92 589.76 253.83 112 Annex 3 Table 4. Position of Technical Improvement In Total Energy Savings BAU vs HES vs HES vs Items DNT DNT SAU Total Savings (Mtoe) 6675.36 7134.85 459.50 Due to: High energy Intensive products 518.37 749.74 221.57 1. Thermal Power 391.48 494.77 100.94 2. Steel 70.72 166.42 88.75 3. Ammonia 19.47 31.94 10.49 4. Caustic soda 3.46 5.88 2.25 5. Cement 18.87 38.36 19.13 6. Paper 14.37 14.37 0.00 Others 286.73 405.96 110.57 Total from technical Improvement 805.10 1155.89 332.14 Contributions Due (%): 100.00 100.00 100.00 High energy intensive products 7.77 10.51 48.22 1. Thermal Power 5.86 6.93 21.97 2. Steel 1.06 2.33 19.31 3. Ammonia 0.29 0.45 2.28 4. Caustic soda 0.05 0.08 0.49 5. Cement 0.28 0.51 4.16 6. Paper 0.22 0.20 0.00 Others 4.30 5.89 24.06 Total from technical improvement 12.06 16.20 72.28 Note: 1 Coal use efficiency assumptions are as: Boilers: 60% in DNT. 70% In BAU, 72.8% in HES Others: 30% in DNT, 33% BAU. 35% in HES 2. Oil & gas effloisony improvement assumptions are as: 5% each case 3. Electricity use effloleony assumption are as: Motors: 85% in DNT. 90% in BAU, 92% in HES Others: 50% In DNT. 80% in BAU. 65% In HES 113