Lifestyles and Energy Consumption in Households

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1 East-west Center, Honolulu, HI, USA Feb. 4-5, 23 Lifestyles and Energy Consumption in Households Toru Matsumoto The University of Kitakyushu

2 1. Introduction CONTENTS 2. Lifestyles and energy consumption 3. Modeling for energy demand of res/com sectors 4. Projection of energy consumption and CO2 emission 5. Future directions

3 1. Introduction

4 Introduction Further expansion of Asian mega-cities Urbanization Increase in per capita income synergistic effect Energy consumption by residential and commercial sectors will drastically increase. Not even considering air population issues in urban areas, urban activities hold an important key for future global warming issues also.

5 Comparison of 4 Cities on Population, Area and Population Density Tokyo Seoul Beijing Shanghai Population (1 3 ) 12,59 1,373 12,78 13,216 Area ( sq.km ) 2, ,88 6,341 Population density (persons/sq.km) 5,737 17, ,84 Data Source: Tokyo Statistical Yearbook 21, Statistical Yearbook Seoul 21, Statistical Yearbook of Beijing 21, Statistical Yearbook of Shanghai 21.

6 2. Lifestyles and Energy Consumption

7 Trends in GRP per Capita (USD at 1995 price) 9, 8, 7, 6, 5, 4, 3, 2, 1, Tokyo Seoul Beijing Shanghai

8 Trends in Flour Space and Size of Household (m 2 /hds.) 16 Shanghai (Rural) Beijing (Rural) 8 6 Tokyo 4 Beijing (Urban) 2 Shanghai(Urban) (persons/hds.) Seoul Beijing (Urban) Tokyo Shanghai Beijing (Rural)

9 Trends in Ownership Rate of Home Electric Appliances Refrigierator (/ 1 households) Beijing (urban) Beijing (rural) 6 4 Shanghai (urban) 2 Shanghai (rural) Color TV (/1 households) Tokyo Beijing (urban) Shanghai (urban) 8 6 Beijing (rural) 4 2 Shanghai (rural) Air condition (/1 households) Tokyo 8 Shanghai (urban) 6 4 Beijing (urban) Microwave oven (/1 households) Tokyo 5 Shanghai (urban) Beijing (urban)

10 Trends in Share of Household Using Town Gas and LPG Tokyo (town gas) Tokyo (LPG) Beijing (coke gas) Beijing (LPG) Beijing (natural gas) Shanghai (coke gas) Shanghai (LPG)

11 Trends of Energy Efficiency COP (Coefficient of Performance) (case of Tokyo) Heating Cooling Electric energy consumption of Refrigerator stock (kwh/? )

12 Trends of Housing Property (case of Tokyo) ( %) Detached house Apartment Share of insulating housing

13 Energy Consumption in (1 6 TOE) Residential Sector Tokyo Seoul Beijing Shanghai per Household (TOE/y Tokyo 1.6 Seoul 1.4 Beijing Shanghai

14 Compositional Changes of Residential Energy Consumption 1% 8% 6% 4% 2% % Electricity Heat Diesel Heavy oil Kerosene Natural gas LPG Coke gas Town gas Coal Tokyo Seoul Beijing Shanghai

15 Trends in Commercial Energy Consumption per Unit of Tertiary GRP (TOE/ mil. 1995USD) 1,8 1,6 1,4 1,2 1, Tokyo Seoul Beijing Shanghai

16 Trends in Total Commercial Energy Consumption ( Tokyo Seoul Beijing Shanghai

17 Compositional Changes of Commercial Energy Consumption 1% 8% 6% 4% 2% % Tokyo Seoul Beijing Shanghai Others Electricity Heat Other oil prod. Diesel Gasoline Heavy oil Kerosene Natural gas LPG Coke gas Town gas Coal

18 3. Modeling for Energy Demand of Residential & Commercial Sectors

19 Data Availability for Residential Sector Energy consumption Residential building property Tokyo Seoul Beijing Shanghai By usage types and energy types? By energy types???? By usage types and energy types? Floor space???? Insulated rate Detached?? Note? Note? Note Apartment?? Note? Note? Note Energy consumption Possession rate appliance Energy efficiency factor Water consumption for residential use per household Energy price By energy types By usages Climate factor Cooling degree day Heating degree day Note: intrusive rate of heat?????????????????????

20 Data Availability for Commercial Sector Energy consumption Floor space Business activity By building usage types By energy types By building usage types and energy types Total By building usage types Total Tokyo Seoul Beijing Shanghai?????????????? GDP of tertiary industry???? No. of employee of tertiary sector???? Office No. of computers? Hospital No. of patients???? No. of students???? School No. of computers? Energy price By energy types???? Cooling degree day Climate factor???? Heating degree day????

21 Basic Concept of Analysis Input Data Forward linkage from - external module - external parameters Service Unit Quantity of Service driving force -Residential: number of households -Commercial: floor space Energy Intensity per unit of Service -Service per driving force -Energy demand by service device -Share of service device Energy demand Policy Options

22 Analytical Flows for Tokyo and Other Cities in Residential Sector <Tokyo> Data collection & composition of variable multiple regression Estimation of energy demand per basic unit by demand types Projection of energy demand by demand types Divide into fuel types basic unit * <Others> Data collection & composition of variable multiple regression Estimation of energy demand per basic unit by fuel types basic unit * Projection of energy demand by fuel types Projection of CO2 emission Projection of CO2 emission Scenario analysis for CO2 reduction * Basic unit = household Scenario analysis for CO2 reduction * Basic unit = flour space or household

23 Matching Demand Type to Energy Type (case of Beijing) Cooling Final Energy Primary Energy Lighting/Power Electricity Coal Urban Individual Heating DHS Cooking/Hot water Coal Heat Gas Oil LNG LNG LPG Coking gas Rural Cooling Lighting/Power Individual Heating Cooking/Hot water Electricity Coal Coal Oil LNG

24 Matching Demand Type to Energy Type (case of Shanghai) Final Energy Primary Energy Cooling Lighting/Power Electricity Coal Coal Oil LNG Urban and Rural Cooking/Hot water Gas LNG LPG Coking gas

25 Matching Demand Type to Energy Type (case of Seoul) Final Energy Primary Energy Cooling Lighting/Power Heating/ hot water Individual DHS Electricity Coal Oil Heat Coal Oil LNG Cooking Gas LNG LPG

26 Flow Chart of the Estimation of Energy Consumption for heating possession of device climate insulated housing energy price employees income per household size of household Floor space per household Energy consumption per floor space Number of household Energy consumption for heating diffusion of town gas Future forecasting energy demand matrix electricity town gas LPG kerosene

27 Flow Chart of the Estimation of Energy Consumption for Cooling possession of device climate efficiency of device employees income per household size of household Floor space per household Energy consumption per floor space Number of household Energy consumption for cooling Future forecasting electricity

28 Flow Chart of the Estimation of Energy Consumption by Hot-water Supply insulated housing energy price water consumption per household Energy consumption per household Number of household Energy consumption for hot-water diffusion of town gas Future forecasting energy demand matrix electricity town gas LPG kerosene

29 Flow Chart of the Estimation of Energy Consumption for Lighting, driving, etc. possession of device energy price efficiency of device employees income per household size of household Floor space per household Energy consumption per floor space Number of household Energy consumption for lighting, etc. diffusion of town gas Future forecasting energy demand matrix electricity town gas LPG kerosene

30 Analytical Flow of Commercial Sector Data Collection Prediction Prediction Energy Consumption per Unit of Tertiary Industry GDP Total GDP Share of Tertiary Industry GDP to Total GDP Total Commercial Energy Consumption Matrix of Energy Consumption Commercial Energy Consumption by Fuel Types Prediction of CO2 Emission

31 4. Projection of Energy Consumption and CO2 emissions

32 Setting up the Exogenous Variable (case of Tokyo) Degree: average ( ) Energy price: average ( ) Water consumption: Straight line approximation of water consumption per capita ( ) Number of household: estimated by National Institute of Population, Japan Size of household : estimated by National Institute of Population, Japan Employees income: average of increasing rate ( )

33 Projection of GRP per Capita (USD, 1995price) 9, 8, 7, 6, 5, 4, 3, 2, 1, Tokyo Seoul Beijing Shanghai

34 Projection of Residential Energy Consumption per Household (TOE/hds.) Tokyo Seoul Beijing Shanghai

35 Projection of Total Residential Energy Consumption (1 6 TOEs) 7 Tokyo 6 Seoul 5 Beijing Shanghai

36 Projection of Residential Energy Consumption (1 6 TOEs) Tokyo 7 6 Tokyo Kerosene LPG Town gas Electricity (1 6 TOEs) 7 Tokyo 6 Seoul Electricity Diesel Heavy oil Kerosene LPG Town gas Coal (1 6 TOEs) 7 Tokyo 6 Beijing Electricity Heat Nautural gas LPG Town gas Coal (1 6 TOEs) 7Tokyo 6 Shanghai Electricity Natrual Gas Town gas LPG Kerosene Coal

37 Estimated and Actual Values of Total Residential Energy Consumption (case of Shanghai) (1 6 TOEs) Estimated Actrual

38 CO2 Emission Factor by Energy Types Heat (China) Heat (Korea) Electricity (China) Electricity (Korea) Electricity (Japan) Heavy oil Kerosene Diesel Gasoline Coke-oven gas LPG Natural gas Town gas General coal (1 6 t-co2/toe)

39 Projection of Total CO2 Emission of Residential Energy Consumption Tokyo Seoul Beijing Shanghai

40 Trends and Projection of Share of Tertiary GRP to Total GRP (%) Tokyo Seoul Beijing Shanghai

41 Projection of Energy Consumption per Unit of Tertiary GRP (TOE/ mil. 1995USD) Tokyo Seoul Beijing Shanghai

42 Projection of Total Commercial Energy Consumption (1 6 TOEs) Tokyo Seoul Beijing Shanghai

43 Projection of Commercial Energy Consumption (1 6 TOEs) 7 Tokyo Electricity Town Gas LPG Heavy Oil Kerosene (1 6 TOEs) 7 6 Seoul Others Heat Electricity Town Gas LPG Other Oil Heavy Oil Kerosene Diesel Gasoline Coal (1 6 TOEs) 7 6 Beijing Others Electricity Heat Coke gas NG LPG Disel kerosene gasoline Fuel oil Coal (1 6 TOEs) Shanghai Others Electricity Coke Other Oils Disel Kerosene Gasoline Fuel oil Coal

44 Projection of Total CO2 Emission due to Commercial Energy Consumption (1 6 t-co2) Tokyo Seoul Beijing Shanghai

45 5. Future Directions

46 Future Directions Improvements in data and model structures Two directions can be considered 1. to aim at more simplified model to deal with same structure as other mega-cities 2. to aim at a complete, bottom-up model which model variables can be closely based on policy options. Scenario analysis Scenarios can be described in the area of 1. household attributes and lifestyle factors 2. architectural characteristics 3. characteristics of energy devices 4. carbon intensity in energy consumption

47 Thank you!

48 Concept of Scenario Analysis BaU 45 4 energy consumption by demand types 35 (Tcal/year) ( 1 3 kcal/m 2 /year Scenario generator Energy consumption per floor space (heating) lighting hot-water cooling heating (Tcal/year) Reflection of scenario energy consumption by demand types lighting hot-water cooling heating 1 actual estimated

49 Example of scenarios Improvements in energy efficiency of appliances & equipments Improvements in Insulated performance of buildings Improvements in carbon intensity of energy etc.

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