APPENDIX A - Springer978-94-010-0153-3/1.pdf · Dr., Head, Energy & Global Change Dept., ABB Corporate Research, Baden-Diittwil, ... Dianlin Li Scientist Environmental Impact Assessment

APPENDIX A

STRUCTURE OF CETP

Steering Committee

Stakeholder Technical Advisory Advisory

Group Program Director Board

Program Manager

12 Tasks 12 Principal Investigators

75 Scientists

Markus Bayegan

Baldur Eliasson

Paul T.P. Chan

David H. Marks

Tomonori Matsuo

Shuichiro Asao

Bjorn Stigson

Ulrich W. Suter

Roger Baud

Yam Y. Lee

APPENDIXB

STEERING COMMITTEE

Chairman Prof. Dr., Chief Technology Officer, Group R&D, ABB Ltd., Switzerland

Dr., Head, Energy & Global Change Dept., ABB Corporate Research, Baden-Diittwil, Switzerland

Senior Vice President, Communication and Sustainability Affairs, ABB China, Beijing China

James Mason Crafts Professor, Civil and Environment Engineering, Director, MIT Laboratory for Energy and The Environment, Cambridge, USA

Professor, Center,

Director, Environment The University of

Science Tokyo

AGS Coordinator(Replaced Prof. Matsuo as SC member February 2001), The University of Tokyo

President, World Business Council for Sustainable Development, Geneva, Switzerland

Professor, Polymer Chemistry, Dept. of Materials Institute of Polymers, ETH, Zurich, Switzerland Current Title: Vice President for Research and Industrial Relations

Finances Financial Administration, Alliance for Global Sustainability, ETH, Zurich, Switzerland Secretary Dr., Consultant, Energy & Global Change Dept., ABB Corporate Research, BadenDiittwil, Switzerland

752 APPENDIX B: CETP ORGANIZATION

STAKEHOLDER ADVISORY GROUP

RishengGuo

ZhenouHu

WenranLi

Dinghuan Shi

Huijiong Wang

Xiubin Xi

ZhonghuiZhan

KunZhang

Qingbo Zhao

Dadi Zhou

Deputy Director-General, the Administrative Center for China's Agenda 21, China

Deputy Director, Office of External Financing Bureau of International Cooperation, Chinese Academy of Sciences, China

Senior Consultant, former Vice Director, Environmental Protection Bureau of Shandong, China

Secretary General, Ministry of Science and Technology China

Senior Economist, Senior Engineer, Vice President of Academic Committee, Development Research Center, State Council, China

Shandong Economy and Trade Commission, China

Vice Director General, Department of Science & Technology and Environmental Protection, State Power Corporation of China

Director General, China-Japan Center for Environmental Protection, State Environmental Protection Agency, China

Senior Engineer, President of Shandong Electric Power Research Institute, China

Director General, Energy Research Institute, State Development Planning Commission, China

APPENDIX B: CETP ORGANIZATION 753

TECHNICAL ADVISORY BOARD

Jefferson W. Tester

Baldur Eliasson

Wolfgang Kroger

Chairman H.P. Meissner Professor of Chemical Engineering, MIT Cambridge, USA

Dr., Head, Energy & Global Change Dept., ABB Corporate Research, Baden-Diittwil, Switzerland

Prof. Dr., Head, Nuclear Energy and Safety Research Department, Paul Scherrer Institute, Switzerland

APPENDIXC

LIST OF CETP P ARTICIP ANTS

(Authors are marked with an *)

ABB Energy & Global Change Dept., Baden-Diittwil, Switzerland Name Function in CETP Tasks Baldur Eliasson * Program Director

Overall Management and Coordination All

Yam Y. Lee* Program Manager All Christopher Russo* Principal Investigator Database

JiangMa* Development

Coordination and Support Data Collection

ABB China Ltd., Beijing, China Name Paul Chan Shiwen Zheng

ABB China Ltd., Jinan, China Name

Tianpeng Liu (presently Shanghai) Victoria Su

Function in CETP Advisory Coordination China

Function in CETP

Coordination China Support (Jinan) Coordination China Support (Jinan)

Paul Scherrer Institute, Villigen, Switzerland Name Function in CETP Stefan Hirschberg* Principal Investigator

Principal Investigator

Roberto Dones* Principal Investigator Principal Investigator

Technical Coordinator

Tasks Data Collection Data Collection Support (Beijing)

Tasks

Data Collection

Data Collection

Tasks Risk Assessment Assessment of Environmental Impacts & External Costs DVD Life Cycle Assessment DVD

756 APPENDIX C: LIST OF CETP P ARTICIP ANTS

Socrates Kypreos*

Robert A. Krakowski *

Alexander Roeder*

Peter Burgherr* Thomas Heck*


Scientist

Scientist

Scientist Scientist

Energy Economy Modeling Energy Economy Modeling Energy Economy Modeling Risk Assessment Environmental Impact Assessment

Swiss Federal Institute of Technology (EPFL), Laboratory of Energy Systems (LASEN), Lausanne, Switzerland

Name Function in CETP Gerard Sarlos Advisory Pierre-Andre Haldi* Scientist

Jacques Pictet* Scientist

Tasks MCDA Output Integration (MCDA) Output Integration (MCDA)

(Current affiliation: Bureau d' Aide a la Decision Pictet & Bolliger) Edgard Gnansounou* Scientist Demand Forecasting Jun Dong* Doctoral student Demand Forecasting

Swiss Federal Institute of Technology (ETH) Zurich, Switzerland Name Function in CETP Tasks Adrian V. Gheorghe* Scientist Electric Sector

Warren W. Schenler* (Current affiliation: PSI)

Scientist

Stuttgart University, Stuttgart, Germany Name Function in CETP Wolfram Krewitt* Scientist (current affiliation: German Aerospace Center) Alfred Trukenmiiller* Scientist (Current affiliation: Hamburg University)

International Atomic Energy Agency, Vienna, Austria Name Function in CETP Joseph V. Spadaro* Scientist

Cazzoli Consulting, Switzerland Name Function in CETP Erik Cazzoli* Scientist

Simulation Electric Sector Simulation

Tasks Environmental Impact Assessment Environmental Impact Assessment

Tasks Environmental Impact Assessment

Tasks Risk Assessment

APPENDIX C: LIST OF CETP PARTICIPANTS 757

Vitty Consulting, Vitty, Slovakia Name Function in CETP Jirina Vitazek* Scientist

Massachusetts Institute of Technology, Cambridge, USA Name Function in CETP Stephen R. Connors* Principal Investigator

Chia-Chin Cheng* Doctoral student

Tasks Risk Assessment

Tasks Electric Sector Simulation Electric Sector Simulation

Energy Research Institute, State Development Planning Commission, Beijing China

Name Function in CETP Tasks Dadi Zhou* Principal Investigator Demand Forecasting Zhonghu Wu Advisory Demand Forecasting Shixian Gao* Scientist Demand Forecasting Xing shan Zhu Scientist Demand Forecasting Xiaoli Liu Scientist Demand Forecasting XinminXue Scientist Demand Forecasting Zhengming Su Scientist Demand Forecasting

China-Japan Friendship Center for Environmental Protection, State Environmental Protection Agency (SEP A), Beijing, China

Name Function in CETP Kun Zhang Advisory

Tasks Life Cycle Assessment Environmental Impact Assessment Risk Assessment

Policy research Center for Environment & Economy, State Environmental Protection Administration, Beijing, China

Name Function in CETP Tasks Guang Xia Advisory Environmental

Impact Assessment Lulian Cheng* Scientist Risk Assessment Yihong Zhao* Scientist Environmental

Impact Assessment Dianlin Li Scientist Environmental

Impact Assessment XinZhou* Scientist Life Cycle

Assessment Chunxiu Tian* Scientist Life Cycle

Assessment Xiangyang Xu Scientist Environmental

758 APPENDIX C: LIST OF CETP PARTICIPANTS

Zhongping Zhou

Yongqi Lu* (Tsinghua University)

Scientist

Scientist

Shandong Electric Power Group Corp., Shandong, China Name Function in CETP Zhenlin Xu Advisory Jianmin Hu Advisory

Impact Assessment Environmental Impact Assessment Environmental Impact Assessment

Tasks Data Collection Data Collection

Shandong Electric Power Group Corp., Shandong Electric Power Research Institute, Jinan, Shandong, China

Name Function in CETP Qingbo Zhao* Advisory Y ong Xu * Scientist Baoguo Shan Scientist Jingwei Shen Scientist Huijun Zhang Scientist

Universityo/Tokyo, Tokyo, Japan Name Function in CETP Kenji Yamaji*

Takeo Imanaka* (CRIEPI)


Scientist

Tasks Data Collection Data Collection Data Collection Data Collection Data Collection

Tasks Energy Transportation Modeling Energy Transportation Modeling

Tsinghua University, Global Climate Change Institute, Beijing, China Name Function in CETP Tasks Zhihong Wei* Scientist Energy Economy

Modeling Wenying Chen* Scientist Energy Economy

Modeling

APPENDIX C: LIST OF CETP P ARTICIP ANTS 759

Participants who left their participating institutions during the course of this work:

Alain Bill Bingzhang Xue* Jean Gao Urs Gantner* Gerard Spiekerman* Jennifer Barker Christopher Hansen* Nuko A. Iiiadis

Institution/organization ABB, Switzerland ABB, Switzerland ABB China Ltd., Beijing, China PSI, Switzerland PSI, Switzerland MIT, USA MIT, USA MIT, USA

1. Project Management

APPENDIXD (CHAPTER 1)

TASK DESCRIPTION

A main element of CETP is the program management by industry. A steering committee guides the program. An overall program coordinator is responsible for overseeing the running of the program, maintaining links to the steering committee and promoting outreach. A program manager is responsible for daily operation and coordination of the program. ABB was responsible for this task

2. Data Collection The data collection task was responsible for coordinating and orgamzmg the collection of data for different tasks from various sources and partners in CETP. ABB was responsible for this task

3. Database Development In order to organize and disseminate the data collected efficiently to the project participants, a database has been developed. Along with a database, a website at http://www.cetp.ch was also developed. ABB was responsible for this task.

4. Demand Forecasting To determine the strategy for energy planning, it is necessary to be able to forecast energy and electricity demand. The Energy Research Institute (ERI) of the SDPC of China is responsible for this task. They used the MEDEE-S model, which is a longterm, bottom-up final energy demand simulation model for developing countries in this study. EPFL worked closely with ERI and is responsible for performing an electricity demand and load forecasting using a bottom-up approach and the DEMELEC-PRO software.

Energy and Electricity Modeling Tasks

Tasks 5, 6 and 7 are three modeling activities relating to energy and electricity modeling. The approach is to investigate the energy mix options based on different economic and environmental constraints using both optimization and simulation techniques

762 APPENDIX D: TASK DESCRIPTION

5. EnergylEconomy Modeling The Energy Economics group of the Paul Scherrer Institute (PSI) was responsible for this task and worked closely with the Global Climate Change Institute of Tsinghua University. The Market Allocation Model (MARKAL) which is a processoriented engineering model that describes all energy transformations from primary sources to energy services was used to study the Shandong Province. PSI has also developed a multi-regional optimization model called the China Regional Electricity Trade Model (CRETM). The CRETM was used to examine a set of energyeconomic-environmental driven scenarios in order to quantify related policy implications.

6. Electric Sector Simulation This task involved bottom-up, engineering-based modeling of the Chinese electricity sector in Shandong. The task was the responsibility of the AGREA research group at the MIT Energy Laboratory. The comparative analysis of alternative strategies, under various uncertainties, is a requirement in the search for robust, long-term technological strategies and related policies. MIT has engaged the stakeholders' interaction in this task and used a simulation dispatch model (EGEAS) to simulate both technological and operational alternatives. ETHZ works closely with MIT for integration of this task with other analytic initiatives in CETP.

7. Energy Transportation Modeling The Energy Transportation Model developed at the University of Tokyo was used to simulate the electricity sector for Shandong Province in China. It is an optimization model used to study the least-cost expansion planning of the power system in Shandong Province taking into account the fossil fuel transportation to the power plants and the electricity transmission networks. It has investigated the configuration of power plants and electricity generation mix, power plant sites, expansion of transmission lines, coal flows and S02 and CO2 emission control measures.

Environmental, health and safety related Tasks

PSI was responsible for three environmental/health/safety related tasks (Tasks 8, 9 and 10). In carrying out these tasks, PSI worked closely with the Policy Research Center for Environment and Economy of the State Environmental Protection Administration of China

8. Life Cycle Assessment The Life Cycle Assessment (LCA) methodology was used to develop suitably complete environmental inventories for major present and future energy systems for the generation of electricity in Shandong. LCA provides input for the decisionmaking on energy choices by performing the full scope evaluation of the amounts of pollutants emitted into the environment from the entire chains of energy systems, including fuel mining, processing, power generation, transmission lines and waste management.

APPENDIX D: TASK DESCRIPTION 763

9. Environmental Impact Assessment Two modeling approaches were used in this task. Firstly, the RAINS-Asia model developed by IIASA was used in this study to help decision-makers analyze future trends in emissions, estimate regional impacts of resulting deposition levels, and to evaluate costs and effectiveness of alternative mitigation options. Secondly, applying the 'impact pathway approach', the environmental external costs associated with the various energy chains were estimated. The basic tool used in this analysis was the model EcoSense developed by the University of Stuttgart. It was adapted to the Chinese conditions.

10. Risk Assessment The objective of this task was to provide a balanced perspective on the severe accident risks specific for China. The assessment addressed fossil energy sources such as coal, oil and gas, nuclear power and hydropower. In addition to the power production step ofthese energy chains, whenever applicable, exploration, extraction, transports, processing, storage and waste disposal were also considered. Apart from focusing on the historical data, existing Probabilistic Safety Assessment approach was also used, particularly for the nuclear chain.

11. Integration, Decision Support and DVD ABB was responsible for integrating the results from different tasks and developed a coherent product for this study. Integration was a continuous process and conducted at various levels.

One of the goals of CETP was to develop a user-friendly decision supportaiding tool. A set of scenarios of interests was chosen from the electric sector simulation for the multi-criteria Decision Aiding (MCDA) analysis. EPFL has chosen ELECTRE III , an MCDA tool, for use in CETP since the objective of CETP was not to choose a 'best' solution but to compare different options from a sustainability standpoint.

In order to allow the stakeholders and users to fully utilize the results obtained from this study, an integrated software tool, DVD, has also been developed. The wide spectrum of targeted users was reflected in the modular design of the software, which should satisfy the needs of users having different backgrounds and interests. This task was the responsibility of PSI and was based on the contributions from all Principal Investigators and their collaborators.

12. Outreach and Technical Exchange Stakeholder involvement in CETP is essential to ensure that the results are applicable and will be used. The outreach activities were conducted to solicit inputs from stakeholders as well as inform the scientific community and various stakeholders about the progress of the program.

As CETP is an international cooperative program, technical exchange between the program participants played an important role in its activities. Technical exchange of personnel and visits to each other's institutions were encouraged as it strengthened the cooperative spirit, communication and technology transfer.

APPENDIXE (CHAPTER 1)

ABBINCHINA

ABB is one of the world's largest technology companies. Since ABB was created from the 1988 merger of Sweden's Asea and Switzerland's Brown Boveri, it has become the world leader in electrical engineering. In the last two years, ABB has pulled out of the capital-intensive and low-margin transportation and large-scale power generation businesses.

Currently, ABB is made up of two customer divisions responsible for serving end-users (ABB Website [2002] www.abb.com): The Power Technologies division serves electric, gas and water utilities as well as industrial and commercial customers, with a broad range of products, systems and services for power transmission, distribution and automation. PT produces transformers, switchgear, breakers, capacitors, cables and other products and technologies for high- and medium-voltage applications. The Automation Technologies division serves customers in the automotive, chemicals, consumer, electronics, life sciences, manufacturing, marine, metals, minerals, paper, petroleum, turbo-charging and utility industries.

ABB's friendship with China dates back to the beginning oflast century, when it supplied the country with a steam boiler in 1907. Responding to China's open policy, ABB China established its headquarter in Beijing in 1994. In 1997, China selected ABB as the major supplier to the Three Gorges Project. In 2002, ABB China had 5500 employees working in 22 branches and sales offices in China. In addition, it had 26 joint ventures and wholly owned companies. The annual revenue of ABB China is about $650 million, which accounts for about one-third of ABB's revenue in Asia.

ABB Corporate Research has been actively supporting research work in the areas of coal combustion, pollution control, and greenhouse gas emission reduction in top universities in China since the mid-1990s. In the spirit of technology transfer, ABB has established Joint Research Laboratories with Tsinghua University in Beijing and Tianjin University in Tianjin. The Greenhouse Gas Laboratory of the Energy and Global Change Department of ABB Corporate Research in Switzerland, which has trained about ten visiting Chinese scientists over the last 5 years, was transferred to the Chemistry Department at Tsinghua University and to the Chemical Engineering Department at Tianjin University. This is a pioneering step for ABB in transferring technology and research knowledge to developing countries.

In addition, ABB has supported conferences, seminars, and training courses at a number of Chinese Universities including Fudan University in Shanghai, Tsinghua University in Beijing, Tianjin University in Tianjin, Jiaotong University in Xian and

766 APPENDIX E: ABB IN CHINA

Zhejiang University in Hangzhou. In 1995, ABB scholarships were established to support the nation's development of young talent at a number of top universities in China.

APPENDIXF (CHAPTER 4)

ADDITIONAL TABLES OF DATA

Table 1. Physical value balance sheet of several types of energy of Shandong province in 1995 and 1999

Items Coal (Mt) Oil (Mt) Gas (Mm3)

1995 1999 1995 1999 1995 1999 Total energy available for consumption 111.19 108.94 13.44 15.76 1285 352

Storage at beginnin~ of year ~.72 16.87 0.56

Output 88.27 89.95 30.06 26.65 1285 733

Import from other province 23.62 25.02 0.08 0.6

Import from outside 2.57

Export to other province (-) -3.36 -4.88 -13.36 -12.37 -381

Export to outside (-) -0.06 -2.7 -1.88

Storage at end of year -18.02 -0.64 -0.37

Processing and transformation input (-) output (+) -71.02 -63.27 -12.94 -14.96 -44 -18

Thermal power -34.87 -36.82 -0.37 -0.27 -39 -18

Heat supply -4.74 -3.89 -5

Coal washing and dressing -30.13 -21.9

Coking -1.03 -0.47

Petroleum refining -12.57 -14.69

Gas production -0.25 -0.19

Losses in transportation 0.96 1.02 0.02 0.069

Total consumption 39.16 44.61 0.52 0.73 1241 334

Prim~ sector 1.77 5.03

Secondary sector 29.45 33.92 0.51 0.72 641 88

- Industry 29.1 32.16 0.49 0.69 641 88

- Construction 0.35 1.76 0.02 0.03

Tertiary sector 4.57 2.63 0.01 0.01

768 APPENDIX F: TABLES OF DATA

- Transport, ~Iecommunication, etc. 1.14 0.98 0.005 0.0083

-Commerce 1.73 1.07 0.005 0.0017

- Others 1.7 0.58

Household sector 3.37 3.03 600 246

- Urban 1.99 2.27 600 246

- Rural 1.38 0.76

Balance 0.05 0.04 -0.04 0.001 0 0 Source: Shandong Statistics Bureau

Table 2. Electricity balance sheet

Unit:TWh

Item 1985 1990 1995 1996 1997

Total energy available for consumption 26.29 44.99 74.04 79.63 85.53

Output 26.15 44.67 73.62 79.22 85.34

Thermal power 26.15 44.67 73.24 78.77 84.88

Heat supply 0.38 0.45 0.46

Import 0.15 0.32 0.42 0.43 0.2

Export (-) 0.014 0.004 0.02 0.011

Total consumption 24.67 44.76 74.1 79.68 85.46

Primary sector 2.22 3.45 4.28 4.62 4.91

Secondary sector 20.29 35.5 57.74 61.46 64.08

Industry 19.89 35.33 57.13 60.8 63.41

Construction 0.4 0.18 0.61 0.66 0.67

Tertiary sector 0.19 2.06 4.13 4.66 6.44

Transport, telecom, etc. 0.083 0.51 0.76 0.85 2.44

Commerce 0.Ql8 0.53 1.19 1.31 1.5

Others 0.089 1.02 2.18 2.5 2.5

Household sector 1.97 3.75 7.95 8.94 10.03

Urban 1.1 2.1 3.62 4.15 4.62

Rural 0.87 1.65 4.33 4.79 5.41

Balance 1.62 0.23 -0.06 -0.05 0.07

APPENDIX F: TABLES OF DATA 769

Source: Shandong Statistics Bureau

Note: There are some differences in the electricity statistics derived from the data sources of the Shandong Statistics Bureau and SEPCO. In the statistics of the Shandong Statistics Bureau, losses of electricity in transmission and distribution are included in the figures for consumption.

Table 3. Electricity consumption, growth rate and structure

Total Primary Industry Constructi Service Trans, House-on etc hold

Electricity 74.076 4.281 57.096 0.612 3.376 0.757 7.954 consumption in 1995,TWh Growth rate 11.4 5.6 11.1 8.9 15.5 5 16.2 in 1985-1995, %p.a. Electricity 94.586 5.392 69.054 0.753 5.95 1.182 12.255 consumption in2000,TWh Growth rate 4.8 3.66 3.76 4.07 11.95 8.07 8.61 in 1995-2000, %p.a. Electricity 100 9.7 78 0.6 3.2 1.7 6.8 structure in 1985, % Electricity 100 5.78 77.08 0.82 4.56 1.02 10.74 structure in 1995, % Electricity 100 5.7 73 0.8 6.29 1.25 12.96 structure in 2000, %


Table 4. Comparative Statistics among China, Shanghai and Shandong

In year 1995 China Shanghai Shandong GDP (Billion Yuan) 5847.81 246.26 500.2 GDP per capita (Yuan/person by end of year) 4828 18928 5746 Economic structure (%):

Primary sector 20.51 2.5 20.2 Secondary sector 48.8 57.3 47.4 Tertiary sector 30.69 40.2 32.4

Population 1211.21 13.01 87.05 (Million by end of year)

Urban 351.74 (29%) 9.57 (73.6%) 21.7 (24.9%) Rural 859.47(71%) 3.44 (26.4%) 65.35 (75.1 %)

Electricity consumption (TWh) 1002.34 37.92 74.1 Electricity structure (%):

Primary sector 5.81 3.14 5.78 Secondary sector 78.01 76.48 77.92 Tertiary sector 6.15 12.39 5.58 Household 10.03 7.99 10.72

Electricity growth (% p.a.) in 1986-1990: Total 8.64 11.1

Primary sector 8 Secondary sector 10.7 Tertiary sector 11.3 Household 18.4

Electricity growth in 1991-1995 (% p.a.): Total 10.16 8.33 12.3

Primary sector 10.6 2.3 Secondary sector 5.9 12.5 Tertiary sector 21.4 16.1 Household 17.8 16

Electricity growth in 1996 comparing to 1995 (%): Total 7.3 6.88 7.5

Primary sector 5.1 7.56 7.8 Secondary sector 5.78 3.62 6.4 Tertiary sector 11.3 21.49 12.7 Household 12.7 14.85 12.4

Electricity growth in 1997 comparing to 1996 (%): Total 4.4 6.14 5.4

Primary sector 5.6 -29 6.4 Secondary sector 2.9 5.52 4.3 Tertiary sector 10.5 15.76 6 Household 10.6 8.9 12.1

Electricity per capita (kWh/person 827.6 2914 851.3 by end of year) Electricity intensity (k WhIY uan)

Primary sector 0.049 0.193 0.042

APPENDIX F: TABLES OF DAT A 771

Secondary sector 0.274 0.206 0.243 Tertiary sector 0.034 0.047 0.026

Table 5. Assumptions for households

1995-2000 2000-2005 2005-2010 2010-2015 2015-2020 1985-1995 Population growth 0.8 0.68 0.58 0.42 0.21 1.36 (%p.a.) Year 2000 2005 2010 2015 2020 1995 Urbanization rate (% 26 35 42 47 50 25 at end of period) Family size (personslhousehold at end of period) Urban 3.1 3.06 3.04 3.03 3.02 3.19 Rural 3.9 3.8 3.65 3.4 3.23 4.07

1995-2000 2000-2005 2005-2010 2010-2015 2015-2020 1985-1995 Growth of average electricity per household (% p.a.) Urban 7 5 3 2 2 3.79 Rural 6 5.5 5 4 4 16.41


Table 6. Assumptions for production sectors

1995-2000 2000-2005 2005-2010 2010-2015 2015-2020 1985-1995

Economic growth 10 9 8 7.5 6.5 11.7 (Base1ine-E scenario), (% p.a.) Lower economic growth 9 8 7 6.5 5.5 (Lowgdp-E scenario), (% p.a.)

2000 2005 2010 2015 2020 1995

Economic structure (%) (Base1ine-E scenario)

Agriculture 16.5 14 12.4 11.5 11 20.2 Industry 43.8 44.2 43.6 42.8 41.6 42.2 Construction 3.7 2.8 2.2 1.7 1.4 5.2 Service 29.5 32 34 35.5 37 26.4 Transport, etc. 6.5 7 7.8 8.5 9 6

Changed economic structure (%) (Structure-E scenario)

Agriculture 16.5 14 12.4 11.5 11 Industry 42.8 43.2 42.6 41.8 40.6 Construction 3.7 2.8 2.2 1.7 1.4 Service 30.5 33 35 36.5 38 Transport, etc. 6.5 7 7.8 8.5 9

Quicker decrease of intensity year) (%p.a.) (Baseline-E scenario)

Agriculture 0.2 0.2 0.1 -1 -1 0.9 Construction -1 -1 -1 -1 -1 -1.6 Service 1 1 0.5 -1 -1 2.2 Transport, etc. -5 -4 -4 -3 -3 -4.8

Slower decrease of intensity (% p.a.) (Inefficient-E scenario)

Agriculture 0.7 0.7 0.6 -0.5 -0.5 Construction -0.5 -0.5 -0.5 -0.5 -0.5 Service 1.5 1.5 I -0.5 -0.5 Transport, etc. -4 -3 -3 -2 -2


Table 7. Assumptions for intensity change in industry subsectors

1 99S-2000 2000-200S 200S-201O 20IO-20IS 20IS-2020

Quicker decrease of intensity (% p.a.) (Baseline-E scenario)

Nonferrous -S -4.S -3 -2 -1 Textile -4.S -4 -3 -2 -1 Chemical -4.S -4 -3 -2 -1 Energy -3.S -2.S -2 -1 -1 Others -S -4.S -3 -2 -1

Slower decrease of intensity (% p.a.)(Inefficient-E scenario)

Nonferrous Textile -4 -3.S -2 -1 0 Chemical -3.S -3 -2 -1 0 Energy -3.S -3 -2 -I 0 Others -2.S -1.5 -I -O.S 0

-4 -3.S -2 -I 0

Table 8. Assumptions for intensity change for EIPs in industry sector

I 99S-2000 2000-200S 200S-201O 20IO-201S 20 I S-2020

Quicker decrease of intensity -S -4.S -3 -2 -1 (% p.a.) (Baseline-E scenario)

Slower decrease of intensity -4 -3.S -2 -I 0 (% p.a.)(Inefficient-E scenario)


Table 9. Energy demand forecast by sector and by fuel in the baseline scenario

Unit· ktoe Industry

1995 2000 2005 2010 2015 2020

Fossil Fuels 26050.89 25435.39 27660.44 30187.5 34449.38 37762.48

Coal 16636.96 16017.58 17380.73 18992.49 21245.4 23122.72

Charcoal 2443.05 2775.23 3065.91 3453.26 4295.58 4685.55

Fuel Oil 4593.55 3922.63 3724.05 3580.83 3676.17 3771.67

LPG 266.09 347.72 522.83 689.78 894.84 1050.78

Gas 2111.24 2372.24 2966.92 3471.15 4337.38 5131.76

Motor Fuels 705.69 902.8 1197.26 1466.93 1744.41 1944.11

Electricity 4909.33 6379.00 8823.99 11105.71 13939.31 16427.56

TOTAL 31665.91 32717.19 37681.69 42760.14 50133.10 56134.15

Subsector of 1995 2000 2005 2010 2015 2020 Industry

Fossil Fuels 18824.89 18039.06 19681.15 21575.21 24453.98 27145.15

Coal 12285.12 11760.44 12834.41 14091.42 15917.31 17640.47

Charcoal 330.92 556.52 832.97 1085.7 1378.09 1599.58

Fuel Oil 4082.88 3386.27 3125.94 2924.58 2906.8 2921.76

LPG 244.38 313.4 488.65 651.01 841.05 982.76

Gas 1881.59 2022.43 2399.19 2822.51 3410.72 4000.58

Motor Fuels 705.69 902.8 1197.26 1466.93 1744.41 1944.11

Electricity 4069.02 5443.01 7715.58 9726.97 12313.46 14489.43 TOTAL 23599.60 24384.87 28593.99 32769.11 38511.85 43578.69

TEXTILE 1995 2000 2005 2010 2015 2020

Motor Fuels 97.57 45.74 61.46 71.04 82.87 90.12

Electricity 367.03 321.77 423.87 496.56 588.65 726.54

Fossil Fuels 1586.56 687.01 691.08 781.46 902.88 1029.09

Coal 1499.66 507.45 502.31 563.40 657.71 675.74

Charcoal 1.67 2.28 2.72 3.39 4.08 4.25

Fuel Oil 8.57 39.20 42.05 50.83 56.04 165.36

LPG 76.66 138.08 144.00 163.84 185.05 183.74

TOTAL 2051.16 1054.52 1176.41 1349.05 1574.4 1845.76

CHEMICAL 1995 2000 2005 2010 2015 2020

Motor Fuels 55.85 67.24 72.88 81.14 87.94 89.12

Electricity 1084.94 1258.22 1569.06 1783.79 1970.84 2118.36

Fossil Fuels 10311.03 7892.22 6661.59 5791.11 5212.71 4695.46

Coal 5632.83 4545.80 3677.42 2984.44 2186.53 1538.17


Charcoal 153.87 107.95 108.64 115.73 122.59 128.52

Residual Fuel 3256.35 2436.50 2137.42 1828.12 1736.06 1725.61 Oil

LPG 34.05 0.00 0.00 0.00 0.00 0.00

Gas 1233.93 801.98 738.10 862.82 1167.54 1303.17

TOTAL 11451.81 9217.68 8303.53 7656.04 7271.5 6902.93

ENERGY 1995 2000 2005 2010 2015 2020

Motor Fuels 417.14 632.57 880.04 1110.37 1351.83 1531.24

Electricity 1701.37 2694.27 4213.63 5646.76 7535.36 9023.07 Fossil Fuels 2317.12 3572.45 5120.65 6888.9 9064.2 11273.82

Coal 1328.46 1863.96 3099.33 4561.58 6473.56 8328.98

Charcoal 4.04 6.44 8.26 9.70 10.85 10.99

Fuel Oil 426.70 575.49 621.00 690.45 720.93 660.87

LPG 15.26 21.56 31.06 41.45 54.10 66.06

Gas 542.66 1105.00 1361.01 1585.72 1804.77 2206.93

TOTAL 4435.63 6899.29 10214.32 13646.03 17951.39 21828.13

OTHERS 1995 2000 2005 2010 2015 2020

Motor Fuels 113.97 144.27 169.85 191.23 208.6 220.29

Electricity 685.41 972.7 1305.26 1588.84 1984.71 2364.08

Fossil Fuels 3952.3 5225.07 6558.27 7458.55 8628.18 9505.25

Coal 3366.06 4276.76 5001.09 5467.52 6102.96 6633.03

Charcoal 132.84 387.59 661.35 904.10 1196.66 1411.58

Residual Fuel 230.00 291.51 282.15 311.21 349.80 325.68 Oil

LPG 118.40 153.76 313.59 445.71 601.89 732.96

Gas 105.00 115.45 300.08 330.00 376.85 402.00

TOTAL 4751.68 6342.04 8033.37 9238.62 10821.48 12089.62

EIPs of Industry

1995 2000 2005 2010 2015 2020

Fossil Fuels 7226 7396.33 7979.28 8612.29 9995.4 10617.34

Coal 4351.84 4257.14 4546.32 4901.07 5328.09 5482.26

Charcoal 2112.14 2218.7 2232.94 2367.56 2917.49 3085.97

Fuel Oil 510.67 536.36 598.12 656.25 769.37 849.91

LPG 21.71 34.32 34.17 38.77 53.79 68.02

Gas 229.65 349.81 567.73 648.64 926.65 1131.19

Electricity 840.31 935.99 1108.41 1378.74 1625.85 1938.13

TOTAL 8066.31 8332.32 9087.69 9991.03 11621.25 12555.47

CEMENT 1995 2000 2005 2010 2015 2020

Electricity 144 175.5 193.79 224.61 249.71 282.31

Fossil Fuels 2645.85 2743.07 2865.77 2980.53 3096.46 3226.76


Coal 2352.5 2414.63 2498.32 2584.67 2645.25 2717.6

Fuel Oil 219.28 229.78 242.5 253.59 267.46 282.63

LPG 21.34 32.89 31.93 36.3 50.53 64.72

Gas 52.73 65.78 93.02 105.99 133.22 161.81

Total 2789.85 2918.58 3059.57 3205.14 3346.17 3509.07

GLASS 1995 2000 2005 2010 2015 2020

Electricity 229 256.9 294.2 325 357.9 388.7

Fossil Fuels 34.2 41.79 49.29 52.92 56.79 63.23

Coal 30.7 36.21 41.24 42.94 44.56 48.26

Fuel Oil 2.81 3.34 3.81 4.06 4.32 4.73

LPG 0.37 1.43 2.24 2.48 3.26 3.3

Gas 0.32 0.82 1.99 3.44 4.66 6.94

Total 263.2 298.69 343.49 377.92 414.7 451.93

PAPER 1995 2000 2005 2010 2015 2020

Electricity 164.15 193.5 276.02 441.35 587.75 750.54

Fossil Fuels 662.05 740.77 1020.96 1291.36 1685.4 2121.12

Coal 587.67 645.46 870.04 1092.5 1410.5 1756.81

Fuel Oil 74.38 82.15 113.1 144.08 183.36 235.1

Gas 0 13.17 37.82 54.77 91.54 129.22

Total 826.2 934.27 1296.98 1732.7 2273.15 2871.66

STEEL 1995 2000 2005 2010 2015 2020

Electricity 303.17 310.09 344.39 387.79 430.49 516.59

Fossil Fuels 3883.9 3870.69 4043.27 4287.48 5156.74 5206.23

Coal 1380.96 1160.85 1136.72 1180.95 1227.79 959.59

Charcoal 2112.14 2218.7 2232.94 2367.56 2917.49 3085.97

Fuel Oil 214.2 221.1 238.71 254.52 314.23 327.45

Gas 176.6 270.05 434.9 484.44 697.23 833.22

Total 4187.06 4180.78 4387.66 4675.27 5587.23 5722.81

Household Sector

1995 2000 2005 2010 2015 2020

Electricity 684.56 1051.13 1523.44 2099.51 2678.5 3097.16

Fossil Fuels 2518.37 2946.35 3447.52 3959.27 4445.73 4874.6

Coal 1688.22 2073.22 2482.78 2877.84 3193.51 3443.35

Kerosene 162.54 128.59 102.41 80.32 63.69 48.28

Gas 510.24 554.73 634.71 741.81 906.38 1080.83

LPG 157.37 189.81 227.61 259.3 282.15 302.14

TOTAL 3202.93 3997.48 4970.96 6058.78 7124.23 7971.76

CONSUMPTION BY USAGE


Cooking 2510.39 2952.74 3465.54 3985.46 4483.71 4926.23

Lighting 114.54 164.96 222.12 281.48 327.02 359.75

Elect. Appliances 571.12 855.76 1217.27 1662.84 2095.57 2364.46

Air Conditioning 6.88 24.02 66.03 129 217.93 321.3

TOTAL 3202.93 3997.48 4970.96 6058.78 7124.23 7971.76

Service Sector

1995 2000 2005 2010 2015 2020

Electricity 290.53 412.42 556.82 722.32 914.29 1131.97

Fossil Fuels 2798.48 3052.32 3363.5 3729.21 4144.2 4601.54

Coal 1902.37 1837.83 1787.11 1747.53 1708.53 1678.11

Diesel 887.14 1201.38 1561.09 1961.68 2410.87 2893.28

Fuel Oil 8.96 11.26 13.14 15.06 16.62 18.2

Gas 0 1.85 2.16 4.94 8.18 11.95

TOTAL 3089.01 3464.74 3920.32 4451.54 5058.49 5733.5

Transport Sector

1995 2000 2005 2010 2015 2020

Petrol 1986.16 2454.75 3347.14 3964.38 4716.83 5411.7

Diesel 1128.49 1261.22 1638.31 2048.54 2501.78 3115.38

Electricity 6.34 7.26 9.14 11.49 15.77 21.35

Coal 76.36 65.74 39.32 0 0 0

Jet Fuel 67.8 86.83 106.34 127.39 151.93 178.96

TOTAL 3265.15 3875.79 5140.25 6151.8 7386.32 8727.39

TRANSPORT SECTOR

1995 2000 2005 2010 2015 2020

PASSENGER TRANSPORT DOMESTIC AIR 67.8 86.83 106.34 127.39 151.93 178.96 TRANSPORT Jet Fuel PUBLIC 667.56 1019.51 1493.76 1871.23 2201.44 2473.55 TRANSPORT ROAD,BUSES 570.62 912.55 1368.73 1712.04 2051.11 2334.66

Petrol 515.24 819.73 1223.12 1513.9 1765.65 1943.76

Diesel 55.38 92.82 145.61 198.14 285.46 390.9

RAIL 89.58 96.35 110.57 143.27 133.04 120.4

Coal 15.24 14.38 8.88 0 0 0

Diesel 74.34 81.96 101.46 142.63 131.71 118.36

Electricity 0 0.01 0.23 0.64 1.33 2.05

WATER (Diesel) 7.36 10.61 14.47 15.92 17.29 18.49

PRIVATE CARS 82.94 226.58 413.27 591.94 801.16 1074.19 TRANSPORT Petrol 77.59 204.24 350.4 455.13 572.51 738.5

Diesel 5.35 22.34 62.86 136.82 228.65 335.69


TOTAL 818.3 1332.92 2013.37 2590.57 3154.53 3726.7

Freight Transport

1995 2000 2005 2010 2015 2020

ROAD 1818.82 1915.6 2437.31 2816.64 3452.02 4198.04

Petrol 1393.33 1430.78 1773.62 1995.35 2378.68 2729.45

Diesel 425.5 484.82 663.69 821.29 1073.35 1468.59

RAIL 359.29 344.06 378.91 406.93 423.44 427.1

Coal 61.12 51.36 30.44 0 0 0

Diesel 298.16 292.68 347.7 405.12 419.21 419.84

Electricity O.oI 0.03 0.78 1.82 4.23 7.26

WATERWAYS 262.4 275.99 302.53 328.62 346.11 363.51 I (Diesel) PIPELINE 6.33 7.23 8.13 9.03 10.22 12.04 i(Electricity) TOTAL 2446.84 2542.87 3126.88 3561.23 4231.79 5000.69

Agricultural Sector

1995 2000 2005 2010 2015 2020

MOTOR FUELS 919.53 1049.98 1190.72 1385.19 1540.56 1649.74

FOSSIL FUELS 887.19 1476.14 2238.96 2346.78 2415.18 2416.41

ELECTRICITY 369.22 489.94 734.78 1000.99 1239.1 1504.71

TOTAL 2175.94 3016.06 4164.46 4732.96 5194.84 5570.86

Construction Sector

1995 2000 2005 2010 2015 2020

MOTOR FUELS 101.45 136.13 182.06 240.34 290.38 364.05

ELECTRICITY 0.6 0.71 0.86 1.02 1.16 1.46 I(TWH) TOTAL 152.9 197.27 255.59 327.84 390.26 489.46


Table 10. Forecast of electricity demand in the different scenarios

Electricity (GWh) Scenarios 2000 2005 2010 2015 2020 Productive sectors Baseline-E Total 86677.53 110545.90 140102.00 178703.93 226101.39 Agriculture 5639.08 7435.73 9725.38 12314.05 15346.87 Industry 72850.71 89596.05 109488.38 137070.01 171462.53 Construction 680.34 753.34 827.08 872.56 936.26 Service 6494.40 11392.16 18234.09 25992.73 35297.94 Transport. etc. 1013.00 1368.62 1827.06 2454.59 3057.80

Lowgdp-E Total 83049.61 101062.05 122206.22 148719.32 179454.25 Awiculture 5387.38 6783.89 8469.58 10234.39 12167.33 Industry 69839.96 81948. 73 95545.61 114116.73 136135.39 Construction 649.97 687.30 720.29 725.20 742.29 Service 6204.52 10393.49 15879.60 21602.95 27984.96 Transport. etc. 967.78 1248.64 1591.14 2040.04 2424.29

Structure-E Total 85466.01 109104.18 138375.00 176515.50 223260.19 Agriculture 5639.08 7435.73 9725.38 12314.05 15346.87 Industry 71419.05 87798.33 107225.09 134149.38 167667.33 Construction 680.34 753.34 827.08 872.56 936.26 Service 6714.55 11748.17 18770.39 26724.92 36251.94 Transport, etc. 1013.00 1368.62 1827.06 2454.59 3057.80

Inefficient-E Total 90939.90 121464.79 160940.16 212989.50 281802.34 Agriculture 5781.19 7815.22 10479.57 13607.47 17391.44 Industry 76736.82 99369.57 127794.64 166688.30 219408.17 Construction 697.69 792.26 892.01 965.05 1061.93 Service 6656.75 11968.86 19638.46 28708.77 39980.80 Transport, etc. 1067.45 1518.87 2135.48 3019.90 3960.00

Household 2000 2005 2010 2015 2020 Total 11883.54 17784.41 23961.61 29897.11 35942.01 Urban 5673.89 10215.94 14724.88 18639.45 22197.15 Rural 6209.65 7568.47 9236.73 11257.65 13744.86

Total 2000 2005 20IO 2015 2020 Baseline-E 98561.07 128330.31 164063.60 208601.04 262043.40 Lowgdp-E 94933.15 118846.46 146167.83 178616.42 215396.26 Structure-E 97349.55 126888.59 162336.61 206412.61 259202.20 Inefficient-E 102823.44 139249.20 184901.77 242886.61 317744.35

APPENDIXG (CHAPTER 7)

MATHEMATICAL DESCRIPTION OF THE MODEL

As mentioned above, ETM is a linear-programming (LP) model minimizing the total system cost, which is sum of generation, power transmission and fuel transportation cost. In this section, variables in the LP are written in lower case.

Constraints

1. Total capacity of generating plants Total capacity of generating plants in the power system must cover the peak load in the system taking capacity reserve rate into account.

N BG N CG 1 N NG 1

(1 + CRR)PeakL1 ~ I I BGCn,bg,1 + I I I cigCn,cg,I' + I I I nigcn,ng,I' n=1 bg=1 n=1 cg=1 1'=1 n=1 ng=1 t'=1

(1)

where, n (=I, ... ,N) : indices of node, t (=1, ... ,1) : indices of period c (=I, ... ,C) : indices of coal production site bg (=I, ... ,BG) : indices of the coal-fired plant installed before the planning period

(existing coal plant) at each node. cg (=I, ... ,CG) : indices of coal-fired plant type installed in the planning periods

(new coal plant) ng (=I, ... ,NG): indices of plant type (other than coal-fired plant) installed in the

planning periods (non-coal plant) BGCn.bg,t : capacity of existing coal plant. cgicn.cg,t : capacity of new coal plant installed in period t ngicn,ng,t: capacity of the non-coal plant installed in period t PeakLt : peak load (including loss on T &D) CRR : capacity reserve rate

2. Existing plants constraints 2.1 Existing plants supplemented with FGD All the existing plants are assumed to be the plants without FGD, and can be the candidates for installing FGD. The closing of the existing plant have to be considered for the FGD installation capacity. It's not applied only for existing plant

782 APPENDIX G: MATHEMATICAL DESCRIPTION

but also for all the coal-fired plant, coal from any source can be used, changed, and mixed. And electrical energy output for instantaneous peak is set to be negligible in this model.

o ~ mbgcn,bg,1 ~ BGCn,bg,1 (2)

bgcmn,bg,1 ~ mbgcn,bg,1 for t = 1 (3)

bgcmn,bg,1 ~ mbgcn,bg,1 - mbgcn,bg,I_1 for t = 2, K,T C

Lmbgon,bg,C,I,h ~ mbgcn,bg,t (4) c=1

C H H

LL T' mbgon,bg,c,t,h ~ CFL T· mbgcn,bg,t (5) c=1 h=1 h=1

where, bgemn,bg,1 : exisiting plant capacity modified (supplemented with FGD) in period t. mgben,bg,t : modified existing plant capacity. h (=O, ... ,H) : indices of time zone (h=O: instantaneous peak, 1: peak, 2: middle, 3: off-peak) mbgon,bg,c,t,h : output of modified existing plant using coal e T : width of time zones CF : maximum capacity factor.

2.2 The other existing plants C

Lbgon,bg,c,t,h ~ BGCn,bg,1 -mbgcn,bg,t (6) c=1

C H H

L LT' bgOn,bg,c,t,h ~ CFL T' (BGCn,bg,1 - mbgcn,bg,l) (7) c=1 h=! h=!

where, bgOn,bg,c,t,h : output of existing plant (not modified) using coal e

3. New plants constraints 3.1 Pulverized Coal (PC) plants supplemented with FGD PC plants, which constructed with FGD are distinguished in the model description byeg. FGD installation to PC plants w/o FGD is allowed one period after the installation of the plant.

cgcmn I = 0 for t = 1 I-I I-I (8)

cgcmn,t ~ Lcgicn,cg=[Pc,w/o.FGDl,t' - Lcgcmn,t for t = 2, KT I' I'

C I

Lmcgon,c,l,h ~ Lcgcmn,I' (9)

c=1 1'=1

APPENDIX G: MATHEMATICAL DESCRIPTION 783

C H H /

LL1"mcgon,C,/,h ~ CFL 1"Lcgcmn,I' (10) c=1 h=1 h=1 1'=1

where, egemn,t: PC plant capacity modified (supplemented with FGD) in period t. megon,c,t,h : output of modified PC plant using coal e

3.2 The other PC plants

for eg = PC wlo FGD, C 1 1

Lcgon,cg,c,t,h ~ Lcgicn,cg,I' - Lcgcmn,t' (11) c=1 /'=1 /'=1

~ t. ~. ego.,,,",,., ,; eFt. ~ -( t egie .... ,,' - t egem •. ,. J (12)

where, cgon,cg,c,t,h output of PC plant using coal c

3.3 The other coal-fired plant for cg* PC wlo FGD

C 1

Lcgon,Cg,C,I,h ~ Lcgicn,cg,I' (13) c=1 /'=1 C H H /

LL 1"cgon,Cg,c,/,h ~ CFL 1" Lcgicn,cg,I' (14) c=1 h=1 h=1 /'=1

3.4 Longkou coal limitation As stated above, Longkou mine-mouth plant in Yantai can use the Longkou coal without rail or ship transportation, but the production amount from the Longkou mine is limited.

for c=Longkou, n=Yantai

BG H BG H

LL1'·bgon,bg,C,I,h + LL1"mbgon,bg,c,t,h bg=1 h=1 bg=1 h=1

(15) CG H H

+ LL 1"cgon,cg,c,t,h + L 1"mcgon,c,t,h ~ LongkouMaxGWh cg=1 h=1 h=!


3.5 The other plants

I <" . ngon.ng.l.h - L.... nglCn•ng .l, 1'=1

H H I

I ,,·ngon,ng,l,h ~ CFI ". Ingicn,I' h=1 h=1 1'=1

where, ngon,cg,c,t,h : output of non-coal plants

3.6 Plants' construction constraints

ngicn,ng,1 = 0 for t < Available periodng

. >LL' CglCn,cg,1 - CglCn,cg,1

(16)

(17)

(18)

(19)

Available periodng : the period generating technology ng become available. LLcgicn,cg.l: plants' installation lower bound (e,g. for the plants under construction)

4. Electric power transmission 4.1 Power flow equation This is an equation by DC method, assuming no loss on the modeled transmission network. The left side of the equation is the net output from the node, and the right side is the total power flow to other nodes. This equation also represents the supplydemand balance in the power system,

BG C BG C CG C C

IIbgon,bg,C,I,h + IImbgon,bg,C,I,h + IIcgon,Cg,C,I,h + Imcgon,c,l,h bg=1 c=1 bg=1 c=1 cg=1 c=! c=1

NG N 8 _8 + "ngo - L -" n,l,h m,l,h

L.... n,ng,l,h n,l,h - L.... X ng=! m=1 n,m

m:t:.n

Ln,l,h : electricity load at node, Un,t.h : phase angle at node,

(20)


Xn,m : reactance oftransmission line between node nand m (ifthere no transmission line (branch) between nand m, IIXn,m = 0)

4,2 Capacity constraints of transmission lines

o -0 n,l,h m,l,h (21 )

Xnm

b : indices of branch correspondence to a pair of nodes (e,g, nand m) r : maximum operation rate of transmission lines,

BBCb : capacity of transmission line installed before the planning period, ibch,t: transmission capacity installed in the planning periods,

5 Emission control

(1) Local SOx Emission Control

nsulfurn,t :::; nSELn (22 )

where, nsuljurn,t : SOx emission at nodes (Mt-S)

BG C H BG C H

= IIIr,bSEn,hg,C ,bgOn,bg,c,l,h + IIIr,mbSEn,bg,c ·mbgon,bg,c,t,h bg=1 c=1 h=1 bg=1 c=1 h=1 m C H C H

+ IIIr'eSEcg,c ·egon,cg,c,t,h + IIr.meSEc ·megon,c,t,h cg=1 c=1 h=1 c=1 h=1 NG H

+ I I r· nSEng . ngon,ng,t,h ng=1 h=l

(23)

bSEn,bg,n mbSEn,bg,c, cSEcg,c, mcSEn nSEng : SOx emission coefficient (S-t/kWh) nSELn : local (nodal) SOx emission control level

(2) provincial Total SOx Emission Control


N

L nsulfurn,t ~ SEL (24)

n=1

where, SEL : provincial SOx emission control level

(3) CO2 Emission Control

N BG C H N BG C H

LLLL'X"·bCEn,bg,e ·bgOn,bg,e,t,h + LLLL'X"'mbCEn,bg,e 'mbgon,bg,e,t,h n=1 bg=1 e=1 h=1 n=1 bg=1 e=1 h=1

N 00 C H N C H

+ LLLL'X"'cCEeg,e 'cgon,eg,e,t,h + LLL'X"·mcCEe 'mcgon,e,t,h n=1 eg=1 e=1 h=1 n=1 e=1 h=1 N NG H

+ LLL'X"·nCEng 'ngon,ng,t,h ~CEL n=1 ng=1 h=1

(25)

where, bCEn,bg,c, mbCEn,bg,e, eCEeg,e, meCEe, nCEng : CO2 emission coefficient (C-tlkWh) CEL : CO2 emission control level

(4) Sulfur dioxide Control Zone In Sulfur dioxide control zone, new plants burning coal of which sulfur content is over 1% must build FGD, and existing plant burning coal of which sulfur content is over 1 % must build FGD must be supplemented with FGD by 2010.

for n E S02 Control zone, cg=PC wlo FGD, e of sulfur contain;;::: 1 %

cgon,eg,e,t,h ~ 0

bgon,ng,e,t,h ~ 0 for t;;::: 2010

Objective function

J = Ic + tc + vc + cc + nc + tax ---t min

where, Ie : fuel cost, te : fuel( coal) transportation cost, ve: variable O&M cost ee : fixed cost of generating plants, ne : fixed cost of transmission cost

(26)

(27)


stax : SOx tax

Je = t,m-:( TVFt.~~t.~.bFC,.bg,' ·bgo.,g"" J

+ t,pvF,( TVFt.~~t.~.mbFC'bg, ·mbgo.,bg</.. J

+ t,PVF,(TVFt.~~t.~.eFC"" ·ego.,,,,,,,,b J (28)

+ t,PVF,( TVFt.~t.~.meFc,.mego."".) T ( N NG H J

+ ~PVF, TVF~~l~'Z"onFCng °ngon,ng,t,h

T ( NBGCH J tC= ~PVF, TVF~~~~'Z"obTCn'bg,C obgOn,bg,c,t,h

T ( NBGCH J + ~PVF, TVF~~~~'Z"ombTCn'bg,C ombgon,bg,c,t,h

( 29)

T ( NCGCH J + ~PVF, TVF~&;~~'Z"oCTCn,cg,c °cgon,cg,c,t,h

T ( N C H J + ~PVF, TVF~~~'Z"omcTCn,c °mcgon,c,t,h


ve = t PVf{ TVF t. ~ t. t. r b VOM bgo 'h'" J

+ tPVJ~( TVFt.~t.t.r.mVOM.mbgO'b"" J

+ tPVF,( TVFt.~t.t. r.cVOM •. " ·ego •. ,g.,.,.' J (30)

T ( N C H J + ~PV~ TVF~~~r.mVOMn ·mcgon,c,t,h

T ( N NG H J + ~PV~ TVF~,&;~r.nVOMng ·ngon,ng,t,h

T ( NBGt J cc= ~PV~ TVF~~~mbARCn ·bgcmn,bg,f'

T ( N BG J + ~PV~ TVF~~mbFOM ·mbgcn,bg,t

T ( N CG t J + ~PV~ TVF~~~CAFCn,cg 'cgicn,cg,t' (31)

T ( N t J + ~PV~ TVF~~mcAAFCn ·cgcmn,t'

T ( N NG t J + ~PV~ TVF~~~nAFCng ·cgicn,ng,t'

T ( B t J nc = ~PV~ TVF~~ATCb ·ibcn,b,t' (32 )

stax = fpV~(TVF' ISTAX. nsu!furn,t] t nESCzone

(33)


where,

PVE: = (_1_)1(1-1), TVF = t(_l_)Y-l l+R y=l l+R

bFCn.bg.e, mbFCn.bg.e, cFCeg.e, mcFCe, nFCng :fuel cost of generating plants ($/kWh) *coal transportation cost is not included. bTCn.bg,c. mbTCn.bg.e, cTCn.eg.e, mcTCn.e :coal transportation cost of generating plants ($/kWh) bVOM, mVOMn, cVOMn.eg, nVOMng :variable O&M cost of generating plants ($/kWh), mbARCn: annual recovery cost for FGD installation of existing plant ($/kW/yr.) mbFOM: fixed O&M cost of supplemented FGD in existing plant ($/kW/yr.) cAFCn.eg : annual fixed cost (annual recovery cost and fixed O&M cost) of new coal plant ($/kW/yr.) mcAAFCn : additional annual fixed cost for supplemented FGD in PC ($/kW/yr.) nAFCng : annual fixed cost of non-coal plant ($/kW/yr.) ATCb: annual fixed cost of transmission line ($/kW/yr.), ST AX: Emission Charge of SOx ($/t-S) I: period interval R : discount rate

ACRONYMS AND ABBREVIATIONS

A,AGI

ABB

ABWR ACS

ACTMCLSHHA

ACWCMSC

AFB

AFBC

AGP AGRIMAT

AGS AirPacts:

AIT

ALWR

APlOOO

AP600

APWR

AVLIS BASICS

BAU

BAU

BCM

BP

BWR

C

CACETC

CANDU

CB

CBM

Agricultural sector

Asea Brown Boveri

Advanced Boiling Water Reactor American Cancer Society

Accident Cases of Typical and Major Casualties on Labor Safety and Health at Home and Abroad

A Complete Work of Coal Mine Safety in China

Atmospheric Fluidized Bed Atmospheric Fluidized Bed Coal Combustion power plant

Agreement on Government Procurement Simplified impact assessment model included in the AirPacts package

Alliance for Global Sustainability A suite of simplified impact assessment programs

Asian Institute of Technology

Advanced Light Water Reactor

Advanced Pressurized water reactor 1000 MW

Advanced Pressurized water reactor 600 MW

Advanced Pressurized Water Reactor

Atomic Vapor Laser Isotope Separation British Association for Immediate Care. This database contains Details of more than 6350 disasters and incidents around the world.

Business As Usual (B, baseline, etc.)

Business As Usual (simulation case)

Billion Cubic Meter (natural gas)

British Petroleum

Boiling Water Reactor

Commercial, Constant (see Scenario)

Clean Air and Clean Energy Technology Cooperation Canadian Deuterium (pressurized heavy water nuclear reactor)

Coal Bureau

Coalbed Methane

792

CC

CC

CCGT

CCII

CCIY

CCPP

CDF CENTREL

CETP

CFC

CHEM CI

CIESIN

CISDOC

CLAB

CLSC

CM

CM

CMD

CNEIC CO

CO2

COD

COE

CON

COSHY

COST CAP

COY

CPIY

CRETM

CRIEPI

CT


Combined Cycle

CO2 Control (simulation case)

Combined Cycle Gas Turbine

China Coal Information Institute

China Coal Industry Yearbook

Combined Cycle Power Plant

Core Damage Frequency Regional group of Czech, Hungarian, Polish, and Slovak power companies

China Energy Technology Program

Chlorofluorocarbon

Chemical sector Statistical Confidence Interval (usually, 68% or 95%)

Center for International Earth Science Information Network International Occupational Health and Safety Centre Bibliographic Database by the International Labor Organization (ILO) Central interim storage facility for spent nuclear fuel, Sweden (Centralt Lager fOr Anviint Briinsle)

CO2 and Local SOx Control (simulation case)

Construction Materials

Coal Mine

Coal Mine District

China Nuclear Energy Industry Corp. Carbon monoxide

Carbon dioxide

Chemical Oxygen Demand

Cost Of Electricity

Conversion technologies

China Occupational Safety and Health Yearbook

Cost of Capital investment

China Ocean Yearbook.

China Petroleum Industry Yearbook

China Regional Energy Trade Model Central Research Institute of the Electric Power Industry (Japan)

Combustion Turbine

DC

DELECt

DEMELEC-PRO

DF

DM

DOE

DOE/EIA

DOM

DRAG

DSM DSO

Dt

E3

EcoSense

EE

EEC

EEM

EGEAS ElA

EIN

EIP

EIPs

ElS

ELASGDP

ELASPRC

ELECTRE

ENC

ENSAD


Direct Current

Electricity demand at time t DEM and of ELECtricity, a general model for electricity market study

Demand Forecasting

Demand

Department of Energy (US) Department of Energy/Energy Information Administration

Domestic (coal-fired plants)

Data Reliability Advisory Group

Demand Side Management Dam Safety Office, Bureau of Reclamation, US Department of Interior

Demand at time t

Energy-Economy-Environment Integrated Impact Assessment and External Cost Model (full impact pathway approach)

Electrical Energy Generation

European Economic Community

Energy Economy Modeling

Electric Generation Expansion System Environmental Impact Assessment

European Internet Network

Energy Intensive Sector

Energy Intensive Products

Energy Intensive Product

Income (GDP) elasticity of demand

Price elasticity of demand Elimination and Choice Reflecting the Reality (Elimination Et Choix TRaduisant la REalite)

Total discounted energy cost Energy-related .s.evere Accidents .Qatabase; this comprehensive database on severe accidents with emphasis on those associated with the energy sector has been established by the Paul Scherrer

793

794

EPA

EPB

EPFL

EPFL-LASEN

EPR

EPRI ERF

ERI

ES&H

ESBWR

ESP ESS

ETH

ETHZ

ETL

ETM

EU

EUE

EXP Fer

fer

FBC

FE

FeM

FGD

FYP

G&A

GAMS

GCC

GDP

GEN


Institute, Switzerland.

Environmental Protection Agency (US)

Electric Power Bureau Federal Institute of Technology, Lausanne (Ecole Polytechnique Federale de Lausanne, Switzerland) Laboratory of Energy Systems of EPFL, Ecole Polytechnique Federale de Lausanne (Switzerland)

European Pressurized Water Reactor

Electric Power Research Institute (USA) Exposure Response Function

Energy Research Institute (Beijing)

Environment, Safety, and Health

European Simplified Boiling Water Reactor

Electrostatic Precipitator Electric Sector Simulation

Federal Institute of Technology (Eidgenossische Technische Hochschule) Federal Institute of Technology, Zurich (Eidgenossische Technische Hochschule ZUrich)

Endogenous Technological Learning

Energy Transportation Modeling

European Union

End-Use Efficiency

Export Exposure response function

Exposure response function slope

Fluidized Bed Combustion coal power plant

Final Energy demand

Ferrous Metals

Flue Gas Desulfurization

Five Year Plan

General and Administrative

General Arithmetic Modeling System

Gas Combined Cycle power plant

Gross Domestic Product

electrical GENeration

GGDP GIS

GNP

GHG,GHGs GPCC

GPCP

GPRICEt

GT

GT

GWP

H,HH, HC:

REU

HFC

HLW

HM

HSE

HSELINE

HTGR HTM

HYDRO I

ISUWM

IAEA

ICOLD

lEA IEPE

IGCC

IIASA

ILO

ILW

IMP

IND,I


GDP Growth Geographical Information System

Gross National Product

Greenhouse Gas, Greenhouse Gases Global Precipitation Climatology Centre

Global Precipitation Climatology Project

fuel price growth rate at time t

GeoThermal

Gas Turbine

Greenhouse Warming Potential

High, higher, etc. Human Capital

Highly Enriched Uranium

Hydrofluorocarbons

High Level radioactive Waste

Heavy Metal (nuclear spent fuel)

Health and Safety Executive (UK).

Library and Information Services ofHSE

High Temperature Gas Reactor Harwell Trajectory Model, long-range atmospheric dispersion model for primary and secondary species

HYDROelectric Health impact

Simple Uniform World Model impact estimate

International Atomic Energy Agency (UN)

International Commission on Large Dams

International Energy Agency (OECD, Paris) Institute of Energy Policy and Economics of the University of Grenoble, France Integrated Gasification Combined Cycle coal power plant

International Institute for Applied Systems Studies

International Labor Organization

Intermediate Level radioactive Waste

Import

INDustry

795

796

IPA

IPCC ISC

ISL

ISO k:

kuru KWUIEDF

L,LL,LLL LAMSADE

LASEN

LCA

LCI

LCIA

LERF

LHV

LLP

LLW

LNG

LP

LPG

LSC

LWR M:

MARKAL

max

MCDA

MCDA

MED


Impact Pathways Approach (or Analysis)

Intergovernmental Panel on Climate Change (United Nations) Industrial Source Complex Model

In-Situ Leaching (chemical mining technique)

International Organization for Standardization Pollutant depletion or atmospheric removal velocity (usually, in cm/s); with "p" subscript for primary pollutant and "s" subscript for secondary species Primary to secondary pollutant chemical transformation velocity Uniform World Model (uni subscript) depletion velocity

KraftwerkunionlElectricite de France

Low, Lower, etc. Laboratory for the Analysis and Modeling of Decision Aid Systems, Paris (Laboratoire d' Analyse et Modelisation des Systemes pour I' Aide a la DEcision) Laboratory of Energy Systems (Laboratoire des Systemes ENergetiques), Switzerland

Life Cycle Assessment

Life Cycle Inventory assessment

Life Cycle Impact Assessment

Large Early Release Frequency

Lower Heating Value Lloyd's Casualty Week; formerly Lloyd's of London Press

Low Level radioactive Waste

Liquefied Natural Gas

Linear Programming

Liquefied Petroleum Gas

Local SOx Control (simulation case)

Light Water Reactor Pollutant removal flux along the earth's surface

MARket Allocation model

maximum

Multi-Criteria Decision Aid(ing)

Multi-Criteria Decision Analysis

Medium (capacity)

MEDEE-S MHIDAS

MIN

min

MIT

MOX

MRC NCAR

NCEP

NEA NFeM

NGCC NH3

NIOSHTIC NOx

NPIC

NPP

NPV

NUCL,NE

O&M

OECD Q QUERI

PC

PDS

PE

PFBC

PHWR

PI

PLM PMIO,PMIO


Modele d'Evaluation de la Demande En Energie Major Hazards Incidence Data Service of the UK Health and Safety Executive (HSE)

MINing

minimum

Massachusetts Institute of Technology, Cambridge, US

Mixed Oxide Fuel Mixed-refrigerant cycle (natural gas liquefaction process) National Center for Atmospheric Research

National Centers for Environmental Prediction

Nuclear Energy Agency (OECD)

Non-ferrous Metals

Natural Gas Combined-Cycle Ammonia

National Institute of Occupational Safety and Health (USA) Nitrogen Oxides

Nuclear Power Institute of China

Nuclear Power Plant

Net Present Value

Nuclear Energy

Operation and Maintenance Organization for Economic Cooperation and Development Pollutant annual emissions rate

Simplified impact assessment model included in the AirPacts package

Pulverized Coal combustion power plant

Plant Damage State

Primary Energy demand

Pressurized Fluidized Bed Coal Combustion

Pressurized Heavy Water Reactor (CANDU)


Peak Load Management Particulate Matter of aerodynamic diameter of 10 microns (0.001 mm) or less

797

798

PM2.5, PM2,5

PNNL

POP

PP PPPGNP

PRC PRCEE

PRIS

PSA

PSI

PSP

Pt

PV

PWR

QU R

R&D

RA RAINS

RC

RD&D

RES

RNW

ROM RUWM

S

SAC

SAG


Particulate Matter of aerodynamic diameter of2.5 microns(O.OOl mm) or less

Pacific Northwest National Laboratory

POPulations

Power Plant Purchasing Power Parity Gross National Product

Processes Policy Research Center for Environment and Economy, SEPA, China

IAEA's Power Reactor Information System

Probabilistic Safety Assessment

Paul Scherrer Institute, Villigen, Switzerland

Pre-Specified Pathway Program

Price at time t

Photo Voltaic

Pressurized Water Reactor

Qinghua University. Beijing, China (see TV) Downwind distance from source or source-receptor position vector

Research and Development

Risk Assessment Regional Air Pollution Information and Simulation

Raw coal

Research, Development, and Design

Reference Energy System

Renewables

Run-of-mine coal Robust Uniform World Model

Sulfur

Shandong Aluminum Company

Chinese Stakeholders Advisory Group

SC Steering Committee Scenarios (Region)-(Policy)(Discount Rate)(Demand)(Fossil Fuel)(Technology)

B

C

Business as usual (no specific emission controls); Baseline technology availabilities, costs, etc.

China (Region), Constant (fossil fuel prices)

E

H

L

S

S

SCIA

SCZ

SD

SDPC SEMA

SEPA

SEPCO

SEPRI SESAMS

SIB SIGMA

SPC, SPCC

SRC

SSB

STK SUWM

SWU

SX

T

T&D

TCH

TCM

TGP Trans,etc.


Environmental (S + C) Policy

High demand, discount rate, Increasing fossil fuel prices

Endogenous Technological Learning (ETL)

Sulfur control, Shandong Province (Region)

Services

State Coal Industry Administration, China

SOx Control Zones (simulation case)

Shandong Province, China

State Development Planning Commission, China French company, Paris (Societe d'etude et de mathematiques appJiquees)

State Environmental Protection Administration, China

Shandong Electric Power Group Company, China

Shandong Electric Power Research Institute, China Strategic Electric Sector Assessment Methodology Under Sustainability conditions

Siberia Sigma is published approximately eight times a year by SwissRe's Economic Research & Consulting team based in Zurich, New York and Hong Kong. Sulfur Dioxide

Sulfur Oxides

State Power Corporation of China

Source

State Statistical Bureau of China

Stocks Simple Uniform World Model

Separative Work Unit (for uranium enrichment)

Shanxi Province Time or tons (1 million grams)

Transportation sector

Transmission and Distribution

Technology (process, conversion, etc.)

Trillion Cubic Meter (natural gas)

Three Gorges Project Transport, telecommunication and other sectors in the demand forecasting

799

800

TSC

TSP

TU u(U)

UCTE

DE

UI

UN

UNDP UNSCEAR

URBAN

US

USDOE

USEPA

UT VLYL

VSL

VVER

WBCSD

WCD

WEC

WNA WTM

WTO WTP

WWW

XJ

YEARPP YOLL


Total SOx Control (simulation case)

Total Suspended Particulates

Tsinghua University, Beijing, China (see QU) Wind speed

Union for the Coordination of Transmission of Electricity

Useful Energy demand

Uranium Institute (now World Nuclear Association)

United Nations

United Nations Development Program United Nations Scientific Committee on the Effects of Atomic Radiation Simplified impact assessment model included in the AirPacts package

United States

United States Department of Energy

United States Environmental Protection Agency

University of Tokyo, Tokyo, Japan Value of a Life Year Lost, economic cost of one year of life lost Value of Statistical Life, amount of money society is willing to spend to avoid a premature death Light water pressurized reactor of Russian design (V odoVodyanoy Energeticheskiy Reactor) World Business Council for Sustainable Development, Geneva, Switzerland

World Commission on Dams

World Energy Council, London

World Nuclear Association (former UI) Windrose Trajectory Model, long-range atmospheric dispersion model for primary and secondary species

World Trade Organization, Geneva Willingness To Pay to achieve an environmental benefit

World Wide Web

Xinjiang Province (Autonomous Region), China

YEARs Per Period Years Of Life Lost (reduction in life expectancy)

GDP attimet Geometric median of lognormal distribution

Puni

P


Uniform World Model (uni subscript) receptor density

Receptor density

Geometric standard deviation of lognormal distribution

801

a

BCM

Bq

BYuan

EJ

eq/ha/year:

g(COz-equiv.)

gce

GJ

GW

GWeyr

GWh

Gy

ha

J

kA

keq/ha/year

kgoe

km

kt

ktoe

kV

kW

UNITS

annum, year

billion cubic meter = 109 cubic meter

1 Becquerel = amount of material which will produce I nuclear decay per second. The Becquerel is the more recent SI unit for radioactive source activity. The curie (Ci) is the old standard unit for measuring the activity of a given radioactive sample. It is equivalent to the activity of 1 gram of radium. 1 curie = 3.7 x 1010 Becquerels. Billion Yuan

ExaJoules = 1018 Joule

Unit for critical loads, 1 eq/ha/year corresponds to 1.6 mg/m2/year gram COz equivalent, calculated using IPCC (200 I) GWP

gram coal equivalent (coal with LHV = 29.3 MJt!lkg)

GigaJoule = 109 Joule

GigaWatt = 109 W

GigaWatt-electric-year; I GWeyr = 8.76 X 109 kWh

Giga Watthour = 109 Wh

Gray; SI unit of absorbed radiation dose in terms of the energy actually deposited in the tissue. The Gray is defined as I joule of deposited energy per kilogram of tissue. The old SI unit is the rad. 1 Gy = 1 J/kg = 100 rad.

hectare

1 J = 1 N m= 1 mZ kg S·2. The Joule is the SI unit of work or energy. 1000 Ampere

1000 eq/ha/year

kilogram oil equivalent = 42.1 MJ

kilometer

kilotonne = 103 tonne, also kiloton

kiloton oil equivalent = 42.1 TJ

kilovolt

kiloWatt = 103 W

804

kWh

kWhth

m

mg

MJ

MJth

MSWU

Mt

Mtoe

MVA

MW

MWdth

MWh

MYuan

Ryr

s

SWU

t

tce

TCM

TJ

tkm

toe

TW

TWh

Twhe, Tweh

USD

W

UNITS

kiloWatthour; I kWh = 3.6 MJ

kilo W atthourthermal

meter

milligram = 10.3 gram

Megajoule = 106 Joule

Megajoule thermal = 106 Joule thermal

millimeter

Million cubic meter

Million Separative Work Unit = 106 SWU

Megatonne = 106 tonne, also megaton

Million ton oil equivalent = 42.1 PJ

MegaVolt-Ampere

MegaWatt = 106 W

MegaWattdaythermal

Mega Watthour = 106 Wh

Million Yuan

Nautical mile = 1852 m

Normal cubic meter

Reactor*year

second

Separative Work Unit (for uranium enrichment)

tonne, metric ton (1 t = 1000 kg), also ton

tonne coal equivalent = 29.3 GJ

Trillion Cubic Meter = 1012 cubic meter

1012 Joule

tonne-kilometer

tonnes of oil equivalent = 42.1 GJ

TeraWatt = 1012 W

TeraWatthour = 1012 Wh

Tera Watthour, electrical = 3.6 MJ

US Dollar

Watt 1 W = 1 J/s = 1 m2·kg·s-3

YOLL

yr

Ilg

UNITS

Years Of Life Lost (reduction in life expectancy)

Year

microgram (10-6 grams)

64'000 or 64,000 64000 (sixty four thousand)

64.000 64 (sixty four)

805

INDEX

A

ABB ................................... 3-5, 11-12, 16-20, 25-29, 33-39, 198, 274, 318,483,666-67, 751-55, 759-64, 790

ABB Corporate Research Center ... 33 ABB-China Library ............ 20,34,36 Academia ........................ 5-11, 17,27 accidents

severe .............................. 24, 493, 587, 588, 593-98, 604-08, 611-13, 621-22, 627-28, 643-46,651-58, 735-36, 763

severe, causes ......................... 601 severe, coal mining ................. 604 severe, dams ........................... 619 severe, hydropower chain ...... 618 severe, natural gas chain ....... 609 severe, oil chain .. .................... 606 smaller ............................... 597-98 worst ....................................... 593

Acidification ......... 447,535, 576, 734 Advanced light water reactors

(ALWR) ................................... 283 AFBC. .......... 130, 132, 138, 162,230,

246, 320, 348-50, 355, 358, 362-64, 396, 405, 411-12, 416-18, 428-29, 432, 573, 716, 732-34, 738-39, 790

Aggregation Method ............................ 664, 673-74,701

AGS ............................. 3-5, 11, 16-19, 26-28, 434, 661, 700, 751, 790

air pollutants and other emissions ...................... 447

airborne emissions. ............ 345, 380, 389, 405, 411, 423-25, 430-31, 747

airborne pollutants ...................... 321, 334, 337-38, 375, 392-93, 399,407,427,441, 731

AirPacts Program ........................ 522 Alliance for Global

Sustainability ........... 3-4,197-98, 201-02, 661, 751, 790

ALWRSee Advanced Light Water Reactor

analysis of emission control scenarios ...... ............... ...... ..... 543

annual sulfur depositions ..... 558, 559 approach

bottom-up ................ 21-22, 48-49, 110,115,120,204,275,452, 665, 701, 707-10, 715, 761-62

cradle-to-grave ..................... 2, 12 top-down .. ......................... 48, 451

Argentina .............................. 521, 528 ascending distillation ................... 679 Asia Development Bank ......... 545-46,

579 Asian financial crisis ...................... 99 ATMOS model ............................. 556 Atmospheric Fluidized-Bed (AFB)

................................................ 283 atmospheric modeling ......... 469,507,

510 attributes .......... l11, 176,208,215-18

B

Banqiao dam ................................ 619 BAU ............... See Business-As-Usual Beijing .................................... 7-9, 12,

18,27, 30, 98, 102, 191, 198,214, 322, 339, 365-67, 435, 438-39, 472, 477, 520, 526, 542, 550, 580-81,584-85,590-91,620,657, 751, 755-59, 764, 793, 79-99

Beishan area ................................. 384

808

biomass ............ See renewable energy Bohai Sea ................. 43,96,103,366 bottom-up ..................... See approach Brazil ............................ 521, 529, 614 Business-As-Usual (BAU) ........... 290,

294,299-01,305,313-15 BWR ........................ 385, 390, 621-22,

627-31,634-36,641-42, 790

C

CANDU ................ 323, 381, 790, 796 carbon emission limits ................. 144 carbon emissions .......................... 108 carbon tax .................................... 133 carbon-caps .................................. 144 CB ........................... See Coal Bureau CBM ................ See coal-bed methane CCGT .................................. 138, 284,

296-98,301,304-13,316-18, 791 Ce group ....................................... 623 Cement Industry ................ 71-72, 104 CETP

analytic framework ................. 729 comparison and integration of

tasks .................................. 703 conclusions and

recommendations .............. 729 energy and electricity demand

.......................................... 730 energy supply and use ............ 736 environmental damage, health

and accident risk ............... 731 overall remarks and foture

outlook .............................. 747 recommendations ................... 745 sustainability and stakeholder

perspectives ...................... 743 CETP program management

program communications ....... 726 stakeholder interaction ........... 727 technical exchange and

outreach ............................ 727 CETP Website ................................ 39 CFCs ........................................ 4,389 CH4 •.••...••••••••••••.•.• 320,373,412,426

INDEX

Chalmers University of Technology ................................. 3, 11 Changdao Island ............................ 68 Changqingjield ............................ 366 chemical industry ........................... 65 Chernobyl accident .............. 621,645 China and Shandong ..................... 34,

102,127, 138, 153-55, 191, 290, 474, 507, 535, 555-56, 573, 719

China National Offshore Oil Corporation .............................. 96

China National Petroleum Corp .. 367 China Oil and Natural Gas

Corporation .............................. 94 China Regional Electricity Trade

Model ........................ 22, 120, 762 China Regionalized (Electrical)

Energy Trade Model. See CRETM Chinese-Manufactured

Technology ............................. 192 chlorofluorocarbons ......................... 4 chronic mortality .................. 456,463 Clean Coal Technologies ............. 192 "clean" generator ........................ 209 "clean supply" strategy ............... 260 "clean" versus "dirty"

strategies .................... 505, 516-17 CO2 emissions ...................... 1-2, 114,

144,147, 155, 165, 171-73, 178, 182-83, 186-87, 190-91, 218, 234, 241-47, 251, 256, 260, 270, 277, 291-94, 302, 305, 308, 315-16, 366,371, 713

CO2 versus S02 plots ................... 189 coal bed methane ............... ........... 138 Coal Bureau (CB) ........................ 327 Coal Bureau Electricity

Generation Company ............. 327 coal chain .............................. 23, 323,

326-27,344-48, 351, 354, 376, 398, 403, 407, 417, 423, 427-28, 492, 500, 573, 588, 592-601, 644-48,651-57, 731-36

coal consumption in China .......... 538 coal mines (CM) ........................... 327 coal preparation ........................... 329

coal transportation ....... 288, 332, 339 coalbed methane ......................... 331,

345, 35~36~ 604, 654 coal-by-wire ................................. 234 coking coal ................... 329, 330, 333 Combined-Cycle Gas-Turbine .......... .

SeeCCGT commercial primary energy

use by energy carriers ............ 541 use by sectors ......................... 540

comparisons of CO2 results ............................. 712 conclusions ............................. 716 cost ................................... 711-712 cost components by task ......... 711 methodologies ......................... 704 task conclusions ...... ................ 714

competitive nuclear power ........... 192 concordance test .................. 675, 677 confidence interval (CI) ............... 461 construction sector ... 76, 77, 115,432 Conventional Coal Plus .. 260, 265-69 cost-reduction relationship .......... 127 cradle-to-grave ........... See approach CRETM. .............. ...... 22, 100-02, 109,

113-14,120-27,137-41,144,147, 151, 156, 159-71, 175-76, 183, 187-96, 707-09, 715, 762, 791

critical load mapping ................... 562 crop production data ............ 474,476 Cs group ....................................... 623

D

damage costs due to outdoor air pollution ............................ 480

damage dependence on plant location and technology ......... 482

Data Collection .. ..................... 17, 20, 29,31-36, 755, 758, 761

data management ........................... 30 Data Reliability Advisory Group

(DRAG) ............................. 32, 792 Database Development .................. 37

INDEX 809

decision-making ............................ 20, 23-25, 390, 446, 451, 572, 661-63,666-68, 714, 733, 762

demand for electrical energy ....... 219 Demand Forecasting ............... 18, 21,

43, 48-53, 56, 89, 223, 281, 710, 729-30

scope ......................................... 51 demand-side management ... See DSM demand-side options ........ 236, 253-55 demand-side strategies ................. 256 DEMELEC-PRO ........................... 21,

49-51, 54, 761, 792 descending distillation ................. 679 "dirty" generator ... ..................... 209 discount rate ......... 113, 153, 228, 797 distribution of damages ................ 481 diversified fuels and

technologies ............................ 192 dominant hazards ......... 592, 605, 609 DSM .......................... 236-41,256-57,

260, 269-74, 413, 417, 423, 444, 714, 744, 792

dust emissions ................... 10, 108-09, 330-32, 342-43, 443, 592-93, 601

DVD ........ 6, 26, 704, 717-20, 724-28 general features ...................... 718 general information ................ 719 guided exploration .................. 719 individual technical tasks ....... 720 movie ....................................... 719 Shandong Electricity

OptionsRanking (SEOR) ... 723 structure and content .............. 718 targeted users ......................... 718 tool .......................................... 717

E

E3 ................................................ See energy-economic-environmental

economic development ................... 57 economic structure ......... 58, 769, 771 economic structure change ............ 55 EcoSens emission scenario

manager .................................. 466

810

EcoSense ................................ 452-54, 457-76, 482, 505-20, 524-29, 532-34, 543-45, 576, 721, 763, 792

EcoSense China/Asia model . ....... 453 EEM ............................. 99-04, 109-11,

119, 127, 169-72, 187, 194-96, 325-26,434,578, 703-04, 707-10, 713-16, 720-21, 736-42, 792

efficiency improvement ................. 74, 82,105, 117-18, 130, 192-94

EGEAS .............. 22, 211-13,762,792 EGEAS simulation ....................... 211 EU ........................................ 2, 24-25,

169,216,241,259,320,325,342, 366, 370-73, 383, 399, 410, 425, 434-36, 461, 492, 505, 510, 703, 707, 710, 717, 721-22, 731, 734, 742,792

ELECTRE ............................. 25, 664, 673-74, 677-78, 682, 763, 792

ELECTRE 111... ...................... 25, 673, 677-78,682, 763

electric sector methodologies discussion ............................... 707

Electric Sector Simulation .. 17,22-23, 35, 53, 201-02, 209-10, 214-15, 221, 229, 270, 273, 446-48, 499-01,574, 651, 669, 704, 762, 793

electricity consumption 44, 73, 77, 81, 329-30, 335-36, 576, 768-69

electricity demand .................... 21-22, 48-51, 56, 62, 83, 86-92, 98, 125-25, 139, 152-54, 170, 187-88, 195, 201-02, 210-13, 216-23, 237-43, 246, 253, 256, 260-61, 268-75, 280-81, 324, 334, 410, 414, 417, 445-46, 499, 707, 711, 730, 761, 778

electricity generation mix ............. 23, 277, 324, 762

Electricity Sector Simulation ............ . ......................................... SeeESS

electricity transmission ................ 194 electrostatic precipitators ..... See ESP

INDEX

emission caps .............................. 135, 175, 178, 191,277

emission database and modeling areas ...................................... 464

emissions and atmospheric modeling ................................. 453

endogenous modeling ........... 126, 160 end-use efficiency ................ 237, 240,

258,793 Energy and Global Change ...... 11-12,

20, 34, 274, 764 energy conservation ....................... 69 energy consumption ................... 9-10,

44-49, 52, 59, 62-66, 69-81, 84-85, 88, 100, 107, 135, 294, 439, 536-39, 544, 551, 576, 581-84

energy consumption in China ........ 44 Energy Economic Modeling

....................................... SeeEEM energy efficiency ................. 21, 45-50,

54-56, 69, 73-79, 82, 94-98, 105, 117,126,193,396,537,544,591, 657,714

energy infrastructure .. .............. 94, 97 energy intensity ........... 21, 54, 64, 69,

72, 82, 99, 103-06, 117, 125-26, 328, 372, 388-89, 402, 405-06, 426-28, 540, 576

Energy Research Institute (ERJ) .. 12, 17, 21, 101-02, 115-121, 125-30, 151, 175-77, 196, 501, 542, 621, 627-29, 658, 668, 752, 757, 761, 793

energy resources .......................... 105 energy supply ........... .................. 7-14,

22, 27, 34, 45-48, 79, 94, 97, 129, 194, 275-77, 419, 435, 536-41, 544, 576-78, 587, 708

Energy Transportation Model ........................................ SeeETM

energy use .................................... 107 energy-economic-

environmenta .......... 100, 122, 762 Energy-Economy Modeling

....................................... SeeEEM enrichment .... 386, 389, 435, 439, 443

ENSAD ...... 588-89, 594-96, 606, 792 environmental burdens ...... 23,320-21,

327, 334,-48, 351-57, 366-68, 374, 385-88, 391-92, 396, 402-10, 426,431-34,460-61, 710, 730-31

Environmental Impact Assessment See ......................................... EIA

Environmental Impact assessment and external costs. 17,

23 of air pollution ... ..................... 445

EPFL ........................... 12, 17, 21, 25, 50,664, 723, 756, 761-63, 793

ERI .... See Energy Research Institute ESP .............................. 140, 162,230,

236, 337-38, 342-43, 343, 350, 362, 399, 404-06, 793

ESS ......... 109, 155, 169,201,208-10, 214, 218-19, 223, 228, 230-31, 234, 245, 272, 321, 325, 347, 368, 395, 404, 410-15, 425, 429, 432-34, 441, 444-50, 493, 499, 502-04, 515, 543, 574-78, 651, 703-04, 707-16, 720-23, 736-43, 793

ESS Scenarios .............................. 214 ETH ......... 3, 11, 22, 751, 756-57, 793 ETHZ .. 12, 17, 23, 436, 574,762,793 ETM ................................ 109-10, 169,

275-87, 290-92, 315-17, 325-26, 347, 434, 578, 703-04, 708-10, 716, 720, 736-42, 780, 793

EU-15 ............................. 89, 527, 529 Europe ................................. 2, 17,24,

64, 202, 321-24, 349, 359, 363, 368, 387-89, 428, 438-42, 448, 452-53, 457, 461, 465, 473, 479, 492, 496, 507, 509-10, 514, 521-22,527-29, 532-33, 562, 568, 573, 579-82, 585, 589, 614, 620, 659, 732

evolution of electricity consumption ............................. 81

excess acid deposition .................. 564 exogenous energy demand ........... 151 Exposure-Response (ER) ............. 461

INDEX 811

exposure-response functions for crops ........... ....................... 511

exposure-response functions for human health .................... 509

exposure-response models ... ........ 454 external benefits ................... 450,451 External Costs

Assessment ....... 24, 114, 120, 195, 216,313, 320, 387, 445, 450-52, 474, 479-81, 484-85, 492-96, 500-05, 535, 572-78, 583-586, 658, 706, 733-34, 737, 739, 743-46, 755, 763

future electricity supply scenarios for Shandong ..................... 499

externalities .......................... 102,111, 192, 195, 439, 450-53, 575, 578, 580-83, 706, 717, 730, 742, 746

F

Fatalities and land contamination ......................... 631

FGD ............... See gas desulJurization final energy demand ....................... 83 five-year plan ........... 45, 98, 549, 665 Fly ash emissions ......................... 109 forecasting electric loads ... ............ 89 forecasting peaks loads .................. 92 fossil-fuel prices ............. 131-34, 141

constant .... ............................... 134 Framatome ........................... 381,385 frequency of exceedance ....... 637-640 frequency-consequence curves

........................................... 645-50 fuel cost uncertainties .................. 241 fuel fabrication ....................... xii, 390 fueltTransportation ...................... 194 fuel type ................................ 340, 341 Fujian ........... 382,562, 564, 610, 620 FYp .............................. .45-47, 59, 63,

66-68,77,87- 89, 582, 793

G

Gansu ............ 366, 383-384, 442,619 "gas-by-wire" ............. 234,368,406

812

gas combined cycle power plant .................... 373, 793

gas desulJurization .............. 137, 230, 235, 241, 254, 259, 273-75, 283, 290, 294, 297, 299-02, 316, 320, 715-17

gas leaks ...................................... 370 gaseous diffusion enrichmen

plant ....................................... 383 gaseous gmissions .................. ..... 108 Gazprom .................. 370, 437-39, 442 GCC plants ................... 193, 374, 377 GDP ........ 5,12-13,34,43-45,54-64,

74, 77-79, 82-83, 99-05, 110-19, 122-27, 141, 144, 151-52, 155-59, 169-70, 175-77, 191, 477-78, 538-40, 572, 769, 792-94,799

and population .......................... 57 growth rate ............... 99,119, 156

GHG emission rates ......................... 356-58,408,415

GHG emissions ...... 103, 325, 356-58, 366,374,377,396,403,405,415, 417, 427-30, 448, 500, 575, 732

glass industry ............................ 72-73 global warming ............ 2,4,102,126,

192, 325, 389, 461, 492, 495, 496, 500,573-75,578, 710

GNP per capita ...... .480,513-16,575 greenhouse effect ..................... 2, 450 greenhouse gas emission

rates .......... 357-59, 375, 397, 416 greenhouse gas emissions ......... 1, 11,

272, 378, 427, 432-33, 437, 714, 747

Guangdong .............. 60, 64, 198,323, 368, 381, 562-64, 610, 620

Guangxi ........................ 384,564,610 Guangzhou ................... 365, 610, 620

H

health and environmental impact cost studies for China ............ 476

INDEX

health effects .......................... 24,217, 320, 351, 362, 399, 408, 425-26, 433, 441-48, 454, 479, 489, 573, 578, 580, 583, 584-86, 604, 621-25,706,744

health impacts ............... 425,486-88, 49~ 523, 572, 68~ 733, 743

Henan Province ............. 43, 339, 557, 562, 597, 601, 619

high voltage direct current (DC) transmission line ........... 368

high-effiCiency power generation technology ............ 549

HongKong ...... 513-15, 586, 610,798 household appliance ownership .... 80,

81 Households .............................. 59, 79,

85, 88, 551, 767, 769, 775, 778 HTGR ................................... 271,794 Hubei .................................... 562, 564 hydro ................ See renewable energy hydro power ........ 614, 619, 652, 655 hydroelectric ....................... 105, 140,

162, 195, 659 hydropower potential ........... 215,270

I

!AEA ................. 382-83, 387, 438-40, 443,518, 620, 659-60, 794, 797

IEPE ................................. 21, 50, 794 IGCC ................ 130-32,137, 160-62,

192-94, 230, 233, 246-47, 256, 260-61, 273, 283-84, 296-98, 301, 304-07, 310, 313, 320, 348-50, 355,358,362-96,401-04,411-12, 418, 428-29, 432, 499, 549, 573, 716, 732-39, 744, 794

IIASA .............................. 100-01, 125, 508, 579, 583-585, 763, 794

income elasticity .............. 117-18, 128 increased power demand ............. 191 independent provincial

power grid ................................ 68 Indonesia ............................. 323, 367,

372-73,377-80, 430

industrial boilers and kilns .. 550, 553 industrial sector ....................... 62, 71 industrial wastewater ................... 109 industry .......................... , 5-11, 17-18,

21, 27, 35, 45, 51-52, 60-77, 83-87, 92, 95-97, 112, 117, 201-04, 224, 241, 270, 326-28, 364-65, 370-72, 381, 432, 437, 451-53, 489, 540, 545, 548, 551-53, 569, 577, 590-94, 598, 605-07, 654, 657, 726-27, 761, 772

inefficient scenario .................. 54, 56, 83,86,88,95, 116, 771-72, 778

Institute of Energy Policy and Economics ........... 21, 50, 794

integration of LCA and EIA ......... 492 Intergovernmental Panel on

Climate Change ............. See IPCC International Institute for Applied

Systems Analysis .......... See IIASA IPCC .................................... 320,340,

396, 437, 442, 795, 802 iron and steel industry ................... 76

J

Japan .................................. 11-12, 43, 64, 74, 214, 290, 318, 330, 367, 368, 372, 437, 557, 612, 752, 757-58, 791, 799

Jiangsu .................................... 60, 64, 381, 437, 557, 562-64, 578, 620

Jinan ............................ 12, 18,26, 65, 103, 283, 286, 321, 341-43, 472, 482-83, 486, 489-93, 496-98, 520, 526, 550, 573, 755, 758

Jincheng ............. 327-28, 333, 336-39 Jining ................................... 283, 286,

331,339-43,468,488,520,526

K

Korean Peninsula ........................... 43 Kyoto Protocol .... ................. 194, 441

INDEX 813

L

La Hague ...................................... 409 Laboratory of Energy Systems ...... 21,

756, 793, 795 large dams .................................. 590,

614-18,655,660, 735 risks and failures .................... 616

large point sources (LPS) ............ 568 largest power plants in

Shandong ................................ 467 LASEN ......... 21, 50, 664, 756, 793-95 LCA ................. 17, 23-25,30,34,169,

194, 259, 319-27, 328, 344, 347-69, 374, 381-97, 403-21, 425-36, 446-50, 492, 494, 499, 502-05, 512,516,583, 703, 710, 762, 795

LC/ ................................ 320, 399, 795 LCIA ..................................... 320, 795 Liaocheng ............................ 283,286,

331, 339-43, 468, 573 Life Cycle Assessment .......... See LCA Life Cycle Inventory assessment ....... .

......................................... SeeLCI Light Water Reactor ............. See LWR line reactance ............................... 280 Linear Programming (LP) ... 120, 795 liquefaction to LNG ..................... 372 Liquefied Petroleum Gas ..... See LPG Liquefied Petroleum Gas

chain ............................. See LPG LNG .......................... 96-97, 111, 133,

138, 192, 320, 323, 365, 366-68, 372-80, 406, 430, 433, 436, 795

load curve .............. 49-51, 89-92, 281 Local SOx Control (CLSC) .......... 291,

308,316 Longkou ....................... 285, 287, 288,

289, 322, 335, 339, 341, 348-50, 355,441-42,468,488, 782

losses due to pollution in China ... 477 Lotus Notes Database ............... 37-39 low level waste depository .......... 391 LP ............. See Linear Programming

814

LPG ....................... .46, 53,64, 71-73, 77, 80, 84, 94, 588, 592, 609, 612-13,644-46,649, 773-75, 795

LPS ................ See large point sources LWR ............................. 320, 323, 385,

387, 390, 396, 407-08, 430, 795

M

MACCS calculations ......................... . ........................... 624-25, 631, 641

MAGES ........................................... 21 marginal costs ..................... 119, 139,

145-49, 166, 192, 311, 450-51, 568, 585

MARKAL .......................... 22, 101-03, 109,112-30,134,137-41,169-70, 175-76, 183-97, 707-09, 715, 762, 795

MARKAL-China ........................... 175 Market Allocation Model

................................ SeeMARKAL Massachusetts Institute of

Technology (MIT) ............ See MIT mathematical formulation of

ETM ........................................ 279 MCDA ..................... 18, 25,194,215,

259-63, 267-68, 319-21, 325-26, 347, 368, 401-04, 408-31, 434, 446,499-00,574,651-52,661-75, 679-83, 686-87, 700-03, 707, 710, 721-23, 727, 756, 763, 795

MEDEE2 ........................................ 50 MEDEE3 ........................................ 50 MEDEE-S ........................ 21, 49, 54,

115,118-19,196, 761 methane emissions ................. 331-33,

.................................. 369-71, 379 middlings ......... 329-30, 333, 337, 405 milling .................................. 389, 443 mining .................... 225,327-29,344,

38~39~ 43~ 44~ 443, 59~ 594

INDEX

MIT ................................. 3, 11-12, 17, 22, 23, 27, 197, 201-02, 212-13, 273, 574, 669, 700, 751-53, 757-59,762,796

mixed coal .................................... 333 Modeling areas ......................... .... 465 Modernization strategies ............. 261,

........................................ 266, 269 monetary valuation ...... 452, 460, 583 monetized impacts ........................ 572 morbidity ................ .457, 458, 513-14 morbidity effects ........... 447, 458, 484 mortality ........................... 24, 399-00,

410-11, 425, 447, 450, 454-63, 479-97, 500, 506, 509-14, 523, 534, 572-75, 579, 584-85, 625, 672, 722, 734-44

mortality due to outdoor air pollution ............ 400,456,480

Multi-Attribute Tradeoff Analysis ................................... 202

Multi-Criteria Decision Aiding ...... 25 Multi-Criteria Decision Analysis

.................................... SeeMCDA

N

N20 .............................. 320, 352, 358, 373,406, 411-12, 426

Nanding .......................... 331, 337-39, 340-43, 468, 487, 492, 573

natural gas chain ........................ 325, 365-68, 375-80, 396-97, 406-08, 430, 433, 609-11, 646, 649-52, 655-56, 735

natural gas cost uncertainty ........ 226 natural gas markets ...................... 192 network power flow .............. 277, 279 new generation options ........ 246, 737 NGCC ........................... 247,261, 796 Ningxia ................. 366, 383, 442, 477 non-discordance test ............ 675, 677 nonferrous metals ........................... 63 NOx emission rates ...................... 143,

146, 149-51, 361, 396-98, 405, 408,419-20,429, 732

NOx emissions ............................. 141, 144, 218, 246-47, 261, 294, 362, 377, 392, 404-05, 420, 429, 447-48, 467, 506, 732

NPP ................................ 381, 384-85, 407, 443, 625-28, 629, 632-36, 639, 659, 796

nuclear chain ................................ 320-23, 381-91, 395-98, 401-02, 407-10,

422, 430-433, 443, 492, 588, 620, 646-47, 652, 763

energy ............................ 138,195, 753, 791, 796

power ......................... 67, 94, 130, 138,161,172,230,233,275, 283, 305, 308, 311, 316, 323, 381-82,387,390,407,411-12,418,438,448,492-93, 540,544,574,583,587-88, 620-21, 627, 645, 650-52, 656-60, 763

reactors in China ... ................. 620

o O&M cost ..... 278, 284, 287, 785, 788 Ocean Oil Corporation .................. 94 OECD ......................... l, 198, 437-39, 589,609,612,618,644-59, 794, 796 offshore wind ................... 270-71, 746 oil chain ................................ 605, 654 oil spills ........................................ 609 optimization modeling .................. 153 optimization of demand .................. 94 overall damage estimates ............. 479

p

paper industry .......................... 73-75, 437-39, 583, 660

Paraguay .............................. 521, 529 particle emission rates ...................... .

................ See TSP emission rates

INDEX 815

particulates emissions ................. 108, 217-18, 272, 320-22, 340, 350, 362, 392, 421, 426, 431-32, 447-48, 455, 463, 474, 481, 507-08, 533-34, 573, 579, 731-33, 745

Paul Scherrer Institute .. ......... See PSI PE ...................... See primary energy Peak Load Management (PLM} .... 68,

236-37, 258, 796

per capita residential energy consumption .................. 80

performance matrix ...... 661, 669, 681 petrochemical industry ................... 66 PFBC ............ 162, 322, 428, 549, 796 Pingyin Aluminum Plant ................ 63 pipeline transport ......................... 370 PM2.5 ..................................... 217-18,

448, 456-57,507-11, 521 PMI0 .............................. 216-17, 241,

246-48, 251-53, 256, 260, 448, 455-58, 467, 486-88, 506-07, 511, 520-23, 526-30, 533-34, 581, 584, 796

Poland .......... 328, 441, 521, 528, 658 Policy Research Centre for

Environment & Economy ................................... See PRCEE

pollution pontrol... ........ 191, 547, 549 pollution control costs .................. 451 population ................................ 57, 61,

64, 104, 473-75, 510, 580, 627, 632-33, 730, 736, 769-70

power generation in Shandong .... 340 power generation technologies ... 280,

282, 317, 573 power plants ....................... 109, 332,

340,348,551 power transmission network ........ 280 PPPGNP ................. .461, 526-29, 797 PRCEE .................................. 12, 322,

327, 334, 339-40, 352, 797 precipitation ................... .470-71, 794 prepared coal ....................... 235, 258 Pre-Specified Pathway (PSP)

program ................................. 212

816

pressurized fluidized bed combustion power plant .................. See PFBC

pressurized water reactor .... See PWR price of coal .......................... 47, 138,

166,225,287,432 primary sector .. 56, 57, 58, 61, 62, 82 primary-energy .............. 99, 128, 129 Principal Investigators ..... 26, 32, 763 probabilistic safety assessment ... 437,

582, 622, 624, 645-46, 650-51, 655-58, 763, 797

PROMETHEE .............................. 664 PSA ............................ 622-23, 643-46,

652, 655, 658-59, 797 PSI ................................ 12, 17, 22-26,

110, 115, 120, 127, 197,436-37, 453, 499, 578, 582, 588-89, 658, 681, 717, 724, 753-756, 759, 762-63, 797

pulverized coal .................... 192,230, 233, 236, 241, 246, 273, 283, 294, 297-02, 315-17, 320-22, 734, 738-39

Purchase Power Parity (PPP) ..... 513 PWR. ................ 323, 381--85, 390-92,

443,620-22, 627-38, 641-42, 797

Q

Qingdao ........................... 27, 78, 270, 283, 286, 323, 339-43, 365, 368, 372, 430, 468, 486, 520, 526, 622, 626-27, 632-42, 646, 650-52

Qinghai ......................... 366,597,619

R

RA ................................... 17,23, 169, 582, 587, 703, 707, 731,755-57, 763, 797

radiation ............................... 448, 799 radioactive solid wastes ....... 394, 433 radionuclide group ....... 629, 634, 635 RAINS ............................. 450, 508-09,

535-38,541-45,556,568-69,576, 579-85, 763, 797

INDEX

Rains-Asia impact assessment approach ................................ 561

raw coal .............................. 64-66, 69, 235-36, 287, 328-30, 333-38, 345-46, 551, 554

RD&D Technology Development ........................... 193

reference coal power plant ......... 485, 489, 492

Reference Energy System ............ 103, 112,118,121, 797

regasification....... ..... ... ... ..... ... ..... 373 regional air pollution information and simulation ..... 508, 535, 576, 797 release sequences ......................... 632 renewable energy

biomass 4, 5, 80, 108, 138, 273, 434, 446, 588

hydro 4-5, 15, 34, 234, 324, 356, 445, 496, 540-41, 544, 576, 587-90, 614-18, 644-46,650-51,655-58, 715

solar energy ................................ 4 sources .................................... 195 wind energy .......... 4, 15, 397, 433 wind power ....................... 15, 395 windfarms ................................. 15

RES ...... See Reference Energy System reservoirs in China ....................... 615 restricted activity days ................. 459 retirement of small and low

efficiency units ....................... 548 retrofit ................................... 235, 670 risk

conclusions ............................. 654 energy chain comparisons ...... 644

RiskAssessment ...................... See RA risks for the Qingdao and Yantai sites

................................................ 636 Robust Uniform World Model

(RUWM) ................................. 522 run-of-mine (ROM) ...................... 327 Russian natural gas ................ 97, 370 RUWM ............................................... .

See Robust Uniform World Model

s SAG

.. See Stakeholders Advisor Group Scenario Construction ................... 54 scrubbers ....................... 99, 130, 131,

137-38, 161-63, 166-67, 178, 193-94,230, 250, 332, 351, 399, 414,418-19,425, 428-29,432,444, 501,707,714-15, 722, 737-46

Sellafield ....................................... 409 Sensitivity analysis ....................... 402 SEPA ............................... 12, 17, 384,

459, 511, 549, 551, 584-85, 757, 797-98

SEPCO ......................... 12-13, 35, 41, 44, 87-92, 98, 215, 219, 228-29, 272, 274, 280, 318, 321-23, 337-41, 344, 348-62, 396, 421-23, 427-29, 467-68, 479, 621, 727, 768, 798

SEPRl ................................ 12, 26, 33, 35-36, 41, 321, 331-33, 337-44, 348-53, 668, 728,752, 798

SESAMS .............................. 212, 274, 664, 679, 700, 798

Shaanxi ......................... 366, 383, 442 Shandong Aluminum Company (SAC)

.................................................. 63 Shandong Electric Powe Group

Corporation ............... See SEPCO Shandong Electric Power Research

Institute ........................ See SEPRI Shandong electricity demand ....... 499 Shandong grid .................... 229,241,

325, 344, 351-52, 356, 385, 403, 406, 427-29, 732

Shandong Options and Strategies 227 Shandongpower plants ...... 321,327, 344, 347, 403, 428, 482, 732

INDEX 817

Shandong province .................. 43, 48, 52, 56-68, 73-75, 89, 94, 98, 178, 182,275, 276, 281, 299, 365, 385, 395, 433, 449, 467, 490, 493, 499, 525, 534, 542, 545, 562, 569, 570, 577, 592, 603, 621-22, 625, 632-33, 642, 650-52, 655, 667, 704, 707-08, 729, 735, 741, 745, 766

Shandong uncertainties ................ 218 Shandong's energy profile .............. 44 Shanghai ......................... 60, 82, 102,

214, 365-67, 381, 458, 478, 520, 526, 550, 557, 564, 606, 619, 755, 764,769

Shanxi .......................... 215, 224, 228, 275-76, 285-89, 294, 301-02, 308, 322-39, 345-49, 358, 361-62, 383, 403, 414, 423, 426-28, 432, 439, 441-43, 493, 500, 512, 557, 564, 597, 601-04, 619, 652-54, 707, 732,798

Shengli Oil Field .......... 68, 69, 94, 96 Shenyang ...................... 456, 457, 509 Shimantan dam ............................. 619 Sichuan ........................... 366, 383-84,

557, 564, 591, 610 Simple Uniform World Model

(SUWM} .................................. 518 Simplified Life Cycle Impact

Assessment ..................... See LClA S02 Emissions ............................. 122 S02 emission rates .......... 163-64, 175,

178, 182, 359, 360, 397-98, 405, 408,417-19,428

S02 emissions ...................... 131, 132, 144, 149, 153-58, 165, 173-74, 178, 183-86, 189-93,217,244-47, 254, 260, 266, 269, 290-91, 297, 311, 332, 349, 359, 375, 418-19, 428,447,462,479,497,506,512, 535, 545-55, 570, 577, 716, 720, 721, 732-34, 737-42

818

Social and Economic Development ............................. 59

Socio-economic Structure ........... 103 solar energy ..... See renewable energy Solid waste production ........... 363-64,

376, 400, 422 SOx Control Zones (SCZ)290, 301,

315 SOx emissions .............. 275, 277, 283,

287, 291-93, 297-99, 302, 305, 308,311,315-16, 716

Spentfuel disposal ...................... 391 Spontaneous combustion of

coal ........................................ 333 Sr group ........................................ 623

Stakeholders ........... 5-9,17-22, 25-27, 30, 53, 100-02, 152, 169, 196, 201-05,208- 210,215,271-73, 406, 574, 578, 661-63, 666-69, 677-80, 684, 687, 700, 704-06, 710, 714, 717, 723, 726-29, 744-48, 752, 762-63

Advisory Group .......... 17, 27,202, 204,666-69,680,687,797

community ................................ 11 meetings ...................... 7, 8, 26, 30 symposium ................................ 18

Standard of Living .............. 57, 59, 94 State Environmental Protection

Administrationxx, 12, 20, 23, 584, 668, 757, 762, 798

steam coal ........................... 192, 224, 323, 327-30, 333, 345-47, 351, 405, 413, 441

steam coal cost uncertainties ....... 224 Steering Committee ... 8,16, 751, 797 Sulfur chemistry ........................... 473 Sulfur dioxide emissions .............. 109 Sulfur Taxes .................................. 131 Sulfur-Caps .................................. 147 Surmesure .............. 682, 685, 688-700

INDEX

sustainability ....................... 2-11, 25, 274, 447, 574, 661-62, 66-67, 700, 751, 763, 798

sustainable development ............................. 47 economic growth ............... 57, 58 energy ............................... 11, 15,

27,201, 270, 663, 728 power generation .................. 663

Swiss Federal Institute of Technology ............. 3, 12, 756-57

Swiss LCA study ................... 328, 359 system peak load .................. 281, 282

T

TAB ..................................... 8, 16, 753 Tarim Basin .................................. 366 TAX Case .............................. 290, 297 Technical Advisory Board .... See TAB technology

assessment ...................... 13 7, 164 costs ................................ 159, 232 diffusion .................................. 195

textile industry .. ........................ 64, 65 TGP .......... See Three Gorges Project Thailand ............................... 521, 527 thermal grid .................................... 95 Three Gorges Project ... 614, 764, 798 Tianjin .................... 60, 214, 366, 764 Tibetan plateau ............................. 562 top-down ....................... See approach tradeoff analysis ..................... 201-12,

215-18,246 traffic ...................................... 78, 610 transmission lines .................... 23, 68,

277-82, 332, 344, 351-52, 406, 708, 762, 784

transportation sector ...................... 77 "true" cost of electricity generation

............. 446, 493-95, 572-74, 734 Tsinghua University ................ 12, 22,

101-02, 547, 581, 585, 758, 762-64,799

TSP emission rates ................. 362-63, 399,410,413,421

UCTE .......................... 328, 348, 356, 360, 391, 396, 415, 418, 427-29, 441-44,799

University o/Stuttgart ..... 581-82, 763 University of Tokyo ............. 3, 11, 12,

23, 751, 758, 762, 799 uranium ....................... 123,271, 323,

382-90, 393, 402, 407-09, 430-43, 798,803

uranium enrichment ............. 407,438 Uranium Institute (UI) ................. 382 urbanization ....... 57-60, 77-79, 83, 97 USA ............................ 11-12, 17, 328,

370, 428, 438, 443, 458, 521, 528, 556, 580-85, 590-94, 597, 609, 612-14, 658, 751-53, 757-59, 793, 796

Value of Statistical Life (VSL) .... 460, 514

vitrification facility ... .................... 384 VSL ......... See Value of Statistical Life VVER ........................... 381,384,390,

621, 627-30, 799 waste recovery................................ 74 waste-to-energy technologies ...... 271 weighting process ...... 18, 661, 679-80 Westinghouse ....................... 385, 443 willingness-to-pay ................ See WTP wind energy ..... See renewable energy windfarms ........ See renewable energy wind power ...... See renewable energy wind power potential in

Shandong ............................... 395 Windrose Trajectory Model .. ............ .

See ...................................... WTM World Bank ........................ 45, 95, 98,

437-39, 459, 478-79, 511-15, 545-46, 580-85

World Business Councilfor Sustainable Development ........ 16,

INDEX 819

751, 799 World Trade Organization .. See WTO WTM ............................... 454, 464-66,

469-72,510,525-29,585, 799 WTO ................. 61, 96, 272, 666, 799 WTP ................................ 460, 478-79,

506, 513-17, 572, 575, 799 Xegroup ....................................... 623 Xinjiang ......................... 15, 138, 323,

345, 366-68, 370, 373-74, 377-82, 40~ 43~442, 732, 799

Xinwen ............... 286-89, 327, 332-37 Xishan .............................. 327, 336-38 Yangjiang ............................. 381, 620 Yangquan ... 327,331-33,336-38,441 Yankuang ................. 328, 331, 335-37 Yantai .................................. 270, 283,

285, 339-43, 468, 488, 521, 526, 610, 622, 626-27, 632, 633, 636, 639, 642, 646, 650, 782

Yanzhou .......................... 286-89, 299, 327-29, 332-33, 335

Years of Life Lost ............... See YOLL Yellow River .......................... 43, 103,

215,270,273-74 Yellow Sea .............................. 43, 103 Yibin ........................................ 383-85 YOLL ................................... 320, 325,

399, 410-11, 425, 455-64, 479, 492-93,496,502-06,509-10,514, 523, 534, 572-74, 683, 733-34, 799,804

Yun-nan ................................ 547, 562 Zhejiang ............................... 381, 557,

562-64, 597, 601, 620, 765 Zhejiang Qinshan ......................... 381 Zhou-xian power plant ................. 568 Zhumadian Prefecture .................. 619 Zibo ................................. 283-89, 294,

299, 327-28, 331, 335-37, 340

Documents

APPENDIX A - Springer978-94-010-0153-3/1.pdf · Dr., Head, Energy & Global Change Dept., ABB Corporate Research, Baden-Diittwil, ... Dianlin Li Scientist Environmental Impact Assessment