AIM/TREND MODEL USER`S MANUAL
Contents
1. t 1 AEEI t 100 PE t primary energy supply for energy e time period t GDP t GDP time period t AEEI t autonomous energy efficiency improvement for energy e time period e energy e OIL COL GAS ELC TRF t simulation time period t initial time period 5 Emission Factors Emission factors of NOx and SO are calculated from following way a Case of no information on total emissions The numbers of the emission factors are estimated based on Greenhouse Gas Inventory Reference Manual from IPCC b Case of available information on past emissions The numbers of emission factors of SOx and NOx are calculated by using the latest emission data The changes of the numbers of emission factors in the future and the definition of CO emission factors are the same as Model A ll 3 How to use Models 3 1 Installation of AIM Trend Model a Installation of AIM Trend Add In At the beginning AIM Trend Add In should be installed on your computer Please refer to AIM Trend Add In Manual for installation of this Add In for more detailed information b Installation of AIM Trend Models Please copy the directory AIMTrend in the CD ROM to your computer 3 2 Model A 1 File Open Open the excel workbook Model A xls in the directory AIMTrend In this workbook following sheets have been prepared Interface sheet GUI operational sheet for calculation Data sheets Hst2. are reflected by latest data change You can calculate above procedures with Projection all button 3 Future Parameter Future parameter can set as following processes On Pam sheet gt User sets population and GDP scenario gt Driving force will be projected with Projection of Driving Force button gt User can modify scenario by overwriting table Drv on Pam sheet gt User can modify scenario by overwriting table ELS and table AEET Final energy demand will be projected with Projection of Final Energy Demand button User can also modify table FE directly on Pam sheet On Ene user sheet gt Energy share will be projected with Projection of Energy Share button gt User can modify energy share scenario by overwriting each table on Ene user sheet gt User can modify other energy scenario by overwriting each table on Ene user sheet gt The button Energy related Parameter Setting will set energy scenario This process combines Ene user sheet and Ene trend sheet into Ene sheet The button Pam Set All will set all parameters following model calculation 4 Worksheet operation Ifyou push the button show program sheets the worksheets will be shown ATML controls the GUI program and has the country code P Eng has the program to prospect energy related scenario P Wat has the program t
3. past data except energy balance data Bal energy balance data Pam future scenario data Ene trend future energy scenario data calculated by past trend Ene user future energy scenario data set by the user Ene future energy scenario data used for projection Emf emission factor for GHG emissions WatPam future water scenario data Output sheets GPro projection figures of main indexes Pro projections related to energy 12 Model A Projection All Projection of Energy and Emission Projection of Water Use Population GDP 3 Write Output to gt Setting all parameters pa scenario setting Pro Sheet Trend setting show program sheets hide program sheets delete temporary sheets Projection of Driving Force and Energy Scenario Final Energy Demand Setting GUI of Model A 2 Operation of GUI 1 File operation Select the country which you want to calculate and write down the case name on the case blanket You can choose from 5 scenarios REF MF PR FW GT and your scenarios When you want to refresh the data please push Reload button The default data are set on each worksheet When you change several data on data sheets you can save those data If you write case name on the save blanket and push Save button data set are saved with case name You can see the data again by writing case name and pushing Reload button If you do not write anything on th
4. AGR OTH t simulation time period t initial time period NEU Non energy use demand is estimated from the following equations It is assumed that NEU consists of oil based on historical data NEU t FE IND OIL t FE IND OIL t x NEU t where FE t final energy demand for sector i energy e time period t e energy e OIL COL GAS CRW NUC HYD GEO NEW ELC HET 4 Estimation of future driving force To estimate the trajectory of driving force IND TPR TPO AGR and OTH IVASHR GDP share ae of IVA CARCPT car numbers per capita PFCSHR GDP share of PFC and AVASHR GDP share of AVA are estimated from regression analysis using GDP per capita for independent variables To estimate IVASHR in other way SVASHR GDP share of SVA service value added is also estimated 5 Share of energy in final energy demand Final energy demand consists of electricity heat and others a Share of electricity The share of electricity in each final energy sector is estimated by using the regression analysis using driving force for independent variable b Share of heat The share of heat in each sector is fixed at that in the latest year for which data are available in all sectors c Share of other energy The share of fossil fuel energy is estimated by using the regression analysis using driving force for independent variable 6 Fuel share and energy efficiency in energy conversion sector CHP and HTP a
5. AIM TREND MODEL A model for assessing environmental loads for Asia Pacific countries USER S MANUAL October 2002 AIM Project Team Table of Contents Le Introduction ss 0 9 ceiescdesdeeredsisewss eens enressinn ene iia EE R E ina lew dae EEE T E E e 3 2 Model structure s etodevac adit cl MAA Ee RETINE oe oles Sa de ede goats 4 2 1 Model Aer nos eea ee Gre ease NE RS eG hare A aiden 4 2 VA OVER Wa sca sia iia bev tes Ae ee a eet eae ees 4 Del 32 Coveted COUNTIES asite sessed e ete oes a a e a ah oh tte Masta aN 4 DPV eB Frere y MnO Cue AEEA EEEE dip cde cvages EEE EEE ip Seeds EEEE ETENE 4 1 Ener ey classi fiGatiom sss ssc veccukssd cveest ec eucie Sacks Wenevess E a ra aE EEE aE nE E AEE EES 4 2 EECOMOMIIGC SCCLOTSs 2 dic0lss efosds EEE OE E EEE ETE 5 3 Estimation of final energy demand cccceseseeseececsesseeeeeeseesecaecseceecesseseesaecaecneseeeneeeseeseeaees 5 4 Estimation of future driving force cececececescesceeseescesceseeseecseceeceeceeceseeseesaeesesreneeeseeeeaees 5 5 Share of energy in final energy demand 0 cc eccccececcescescesceeseeneeeceeceaeesceseeeeereeeeeaeeaeenaees 6 6 Fuel share and energy efficiency in energy conversion Sector eeceecesceseeseeteeseeseceeenseneensens 6 7 Total primary energy SUPPLY cccceeeeseeseeseeeseececsecseceeceseeseeeecaeceeceececeseeaeesaecsecneceeeaeeaeeatens 6 8 CO2 NOX SOX CH4 N20 CO emissions cceccescesseeseesecseceseeteeee
6. Rep Korea Dem Taiwan Central Asia Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan South Pacific Australia New Zealand Regression Assumption Regression Regression Assumption Assumption ARF Driving Force Elasticity Final Energy Demand Population IND IVA IND TPR TPO AGR OTH GDP TPR CAR IVASHR TPO GDP Electricity Share AVASHR AGR AVA Heat Share PFCSHR OTH PFC IND TPR TPO AGR OTH CARCAP Final Energy Demand Final Energy Demand Electricity and Heat IND TPR TPO AGR OTH excluding Electricity and Heat IND TPR TPO AGR OTH Assumed AAE share efficienc Scenario Input for Electricity plant Effici Assumed share aie IERE Heat plant and CHP IND Industry TPR Road transport TPO Other transport AGR Agriculture OTH Other Primary Energy Supply COL OIL GAS CRW NUC HYD GEO NEW TVA Industry Value Added AVA Agriculture Value Added PFC Private Final Consumption CARCAP Car numbers per capita COL Coal NUC Nuclear CRW Combustible HYD Hydro power and renewables GEO Geothermal NEW Wind PV and so on Calculation flow of detailed data model Model A 2 1 3 Energy module 1 Energy classification Following 10 energies are treated in this Model A COL coal OIL crude oil and petroleum products GAS gas CRW combustible re
7. Time series AEEI year AEEI 18
8. UI of Model B 2 Operation of GUI 1 File operation Worksheet operation Show program Hide program Delete temporary sheet Select the country which you want to consider When you want to refresh the data those you already changed please push Reload button The default data are set on each worksheet When you change several data on data sheets you can save those data If you write case name on the case blanket and push Save button data set are saved with case name You can see the data again by writing case name and pushing Load data button If you do not write anything on the case blanket and push Save button the data are saved in temp folder 17 2 Future projection Please push Project button on the sheet GUI to start projection 3 Worksheet operation Ifyou push the button show program sheets the worksheets ATMO index P Pro INDEX and PERIOD will be shown If you push the button hide program sheets the above worksheets will be hidden If you push the button delete temporary sheets the worksheets Wrk which are used for calculation will be deleted 3 Scenario setting Table Scenario variable of Model B Name of Variable Type of variable Descriptions Table name POP Time series Population 1000 DRV GDP_R Time series Economic growth rate DRV year AEEI
9. ati Nauru Palau Papua New Guinea French Polynesia Solomon Islands Tonga Vanuatu Samoa 3 Energy data e UN Energy Statistical Yearbook 2000 is used a Consumption of Commercial Energy Liquids Solids and Gas b Consumption of Commercial Energy Electricity c Consumption of Commercial Energy Total 3 1 Liquids Solids and Gas correspond to OIL COL and GAS in Model A respectively 2 Electiricity Electricity from geothermal hydro nuclear solar tide wind and wave imports exports 3 Total Liquids Solids Gas Electricity In UN Energy Statistical Yearbook 2000 3 is the same as the total primary energy supply in IEA Energy Balance Table Statistical Yearbook Energy Statistics Yearbook So we use the phrase Total Primary Energy Supply TPES for Total Consumption of Commercial Energy CCE The share of the each energy is fixed as that in 1995 4 Primary energy supply Energies are categorized as Liquids Solids Gas Electricity and Traditional fuelwood Liquids Solids and Gas correspond to OIL COL and GAS in Model A respectively Electricity ELC consists of supply from geothermal hydro nuclear solar tide wind wave import and export Traditional fuelwood TRF corresponds to CRW in Model A Each energy supply is assumed to be decided by GDP and AEEI This can be given by the following equation 10 PE t A t X PE t X GDP t GDP t A
10. ceeeseeseesaecsececeeeeaeeaeeneens 6 2 14 Water modile iane r e AEREE PENRE EEA E E A R ease 6 1 Model Feature Sienese a Kick eth GG Heh a E a RE 6 2 Domestic water withdrawal and consumption s ssssssssssseeessesseresessesesrsesresteesesseseseesesesses 7 3 Industrial water withdrawal and CONSUMPTION ccceeceeseesecsecseeeeeeeeeecaeessesesseeeeeesecaeeneens 8 4 Agricultural water withdrawal and consumption cceccessescesecsecescesceseescessecseceenseeaeeaeeneens 9 Ded MOG E E EEEE AE E EIE PE ENEA AN Gane ESS iba saad Gan E a ahaa bastion 10 DOVER VIE Wiis cxseeds exe ah cic sense Hake igh eae Ha ete aden hoes ihe ak el ee ed 10 2 Covered countries cc 24 heen Satake eat ae es A ee es 10 3 AaS ET E E veh taconite eset EAT 10 4 Primary energy SUpDl Ys coisa nii e nE E E E T ot See eee 10 5 Emission Factors EAEE AAE ATER IETEN OAE EOE to cues 11 3 Howto use OT l EE E E EEE EEEN EEI E 12 3 1 Installation of AIM Trend Model ecceceesesseesesseeeseeeecseceeceseeseeseeeeecaecseceeseseeaeeaeecaecseeeeneeeaes 12 BD MOd el reno a a a E E ER 12 EDANE E A E Sele es 12 2 Operation o GUT ae E E oe ee isk ee 13 3 Scenario Setting seren reaR arrer One aR ap prer ten Na Ea E ES E nT aRt 15 33 MOdeliB aeara a A AE RANE E E A AE OE E A A 17 1 File Opinies eonna a a A a keene ale 17 2 Operation of GUL rerni n a E eis He ee ees 17 3 Scenario Setting nreno EE T T R aioe E ETA a ts 18 1 Intro
11. d population total population in 1990 is higher than that in 1980 it is assumed that the ratio of water supplied population will continue to increase at the same pace Then the increased ratio is multiplied to the future population projected by the World Bank in order to estimate water supplied population This assumption stands on the consideration that quality of life will continue to improve if enough resource in this case water resource is available On the other hand for the country where ratio of water supplied population decreased during 1980s it is assumed that the water supplied population not the rate will change at the same pace Usually water supplied population still increases reflecting population increase even in the nation where ratio of water supplied population decreases This assumption stands on the consideration that decreasing ratio of water supplied population reflects the availability of water resources Woon t Wpom urs t Woo rur t Wpom 1990 WSPurs 1990 WSPrur 1990 WSPurs t WSPrur t AWEIpom t Woome t Wpom t RCONpom t Wopom t Domestic water demand Woom urs t Domestic water demand in urban area Woom rur t Domestic water demand in rural area WSPura t Water supplied population in urban area WSPrur t Water supplied population in rural area AWElpom t Water use efficiency improvement in domestic sector compared with 1990 Woomc t Domestic water c
12. duction AIM project team has been developing the model for assessing the future environmental loads based on the past socio economic trends and future scenarios By using this model the environmental trends through 2032 in the Asia Pacific countries have been estimated Following 2 types model have been developed because of accessibility to data sources e Model A Based on IEA International Energy Agency energy data e Model B Based on UN United Nations energy data In the following sections in this document we will introduce the structure of each model and describe how to use this model to prospect the future environmental trends Scenario generation amp AIM Trend past economic trend past environmental AIM Trend Future estimates ii Future scenarios A r n economic trend Future 3 Future environmental trend environmental trend Concept of AIM Trend model 2 Model structure 2 1 Model A 2 1 1 Overview Model A covers the countries that have the IEA energy balance table Model B is used for the countries that do not have the IEA energy balance table 2 1 2 Covered countries Model A covers the following 25 countries South Asia Bangladesh India Iran Sri Lanka Nepal Pakistan South East Asia Indonesia Myanmar Malaysia Philippines Singapore Thailand Vietnam East Asia China Japan Korea
13. e case blanket and push Save button data are saved in Temp folder UNEP published GEO 3 Global Environment Outlook 3 UNEP 2002 before Johannesburg Summit and prepared following 4 scenarios Market First scenario MF Policy First scenario PR Security First scenario FW and Sustainability First scenario GT The Market First scenario envisages a world in which market driven developments 13 coverage on the values and expectations that prevail in industrialized countries In the Policy First world strong actions are undertaken by governments in an attempt to reach specific social and environmental goals The Security First scenario assumes a world of great disparities where inequality and conflict prevail brought about by socio economic and environmental stresses and Sustainability First pictures a world in which a new development paradigm emerges in response to the challenge of sustainability supported by new more equitable values and institutions 2 Future projection Ifyou want to calculate future projections related to energy use please push Projection of Energy and Emission button If you want to calculate future projections related to water use please push Projection of Water Use button After that please push Write Output to Result Sheet button to write out the results The worksheets GPro and Pro will show the results related to energy emissions and water results that
14. ed area Since critical factors which govern irrigated area are different among countries it is not easy to project future irrigated area by multi factor regression approach In this example however irrigated area is projected as the function regressed with two factors logarithm of GDP per capita logarithm of population as a simplified method For more realistic projection factors used for regression should be selected separately for each country considering its background For future population and GDP projection by World Bank is derived from the database file Waar t Waar 1990 IRGAREA t IRGAREA 1990 AWElacr t IRGAREA t F log POP t log GDP t POP t Waarc t Waar t RCONaar t Wacr t Agricultural water demand IRGAREA t Irrigated area GDP t GDP POP t Population AWElacr t Water use efficiency improvement in agricultural sector compared with 1990 Wacrc t Agricultural water consumption RCONacgr t Agricultural water demand consumption ratio 2 2 Model B 1 Overview For the several countries for which IEA energy statistics data are not available Model B is constructed for estimation of environmental loads in the future 2 Covered countries Model B covers following 17 countries South Asia Afghanistan Bhutan Maldives South East Asia Brunei Cambodia Laos East Asia Mongolia Central Asia Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan South Pacific Fiji Kirib
15. fossil fuel and CRW power plant year ELP MXEFF J Time Series Maximum efficiency of generation ELPMXEFF J COL OIL GAS CRW efficiency for fossil fuel and CRW power plant EMS EME J L Parameter Initial value of NOx SO2 emission factors GHGI1 J COL OIL GAS CRW Gg NOx kTOE Gg SO2 kTOE L NOX SO2 EMS RDPNT M L Parameter When GDP per capita is achieved at this GHG1 M P1 P2 point emission factor is stating to reduce L NOX S02 1000US 15 Type of Name of variable i Descriptions Table variable EMS MXFCT L M Parameter Emission factor gt EMS EMFJ L GHGI1 L NOX SO2 EMS MXFCT L M M P1 P2 EMS RDR M L Parameter Reduction rate of emission factors year GHG1 L NOX SO2 M P1 P2 URAT Time Series Urbanization rate Urat m AWELI Time Series AWEI year AWEI I IND AGR DOM aT 3 3 Model B 1 File Open Open the excel workbook Model B xls in the directory AIMTrend In this workbook following sheets are prepared Interface sheet e GUI operational sheet for calculation Data sheets e Pam future scenario data e Hst historical data e PERIOD set for time period Output sheets e Pro projection results e GPro projection figures of main indexes Model B Program Project Format Case load Reload Future projection Format Pam Load data sheet Save data sheet Fig G
16. newables and waste NUC nuclear HYD hydro power GEO geothermal NEW wind PV and so on HET heat and ELE electricity 2 Economic sectors Energy conversion sector has following 5 sub sectors ELP power generation HTP heat supply system CHP combined heat and power plant DST distribution of energy and TFM transformation The final energy demand sector has following 6 sectors IND industry TPR transport on road TPO other transport AGR agriculture OTH other and NEU non energy use 3 Estimation of final energy demand Final energy demand except NEU is described as the function of driving force DRV Driving force of IND TPR TPO AGR and OTH is basically defined as industrial value added IVA numbers of car CAR GDP agricultural value added AVA and private final consumption expenditure PFC respectively Elasticity between each final energy demand and driving force is calculated by regression analysis using historical data If these data are not available GDP can be used for the driving force Following equation is assumed TFE t A t x TFE t x DRY t DRY t A t 1 AEEI t 100 where TFE t total final energy demand for sector i time period t DRV t driving force for sector i time period t ELS elasticity for sector i AEEI t autonomous energy efficiency improvement for sector i time period t i final energy demand sector i IND TPR TPO
17. o 14 prospect water related scenario P GHG has the program to calculate GHG emissions WATPAM is the worksheet for selecting data related to water projection 3 Scenario setting Each program is written in ATPL index has the codes which are used in each program If you push the button hide program sheets the above worksheets will be hidden If you push the button delete temporal sheets the temporal worksheets will be deleted The worksheets Pam and Ene have the important assumptions data about economy energy and emissions If there are blank data on the table they are interpolated at calculation Table Scenario variable of Model A Type of Name of variable Descriptions Table variable POP Time Series Population 1000 Basic GDP_R Time Series Economic growth rate year Basic AEEL I Time Series AEEI year AEEI I IND TPR TPO AGR OTH TPS SUP J Time Series TPES kTOE SUP NFOS J NUC HYD GEO NEW ELE HET ELE ELP CRW Time Series Electricity supply by CRW power plant SE CRW kTOE ELE CHP TOT Time Series Electricity supply by CHP plant kTOE ELE CHP TOT ELP SHR J Time Series Share of fossil fuel power plant in total SHR ELP FOS J COL OIL GAS fossil fuel power plant e ELP SHR J 1 ELP IMP J Time Series Improvement rate of generation efficiency ELP IMP J COL OIL GAS CRW for
18. onsumption RCONpom t Domestic water demand consumption ratio if WSPuyrs 1990 POPurn 1990 WSPurp 1980 POPurs 1980 gt 0 WSPurs 1990 POPura t min 1 WSPurp 1990 POPurs 1990 WSPurs 1980 POPurn 1980 10years t 1990 POPuyrsa t Population in urban area POPgur t Population in rural area if WSPuyrs 1990 POPurn 1990 WSPurs 1980 POPurs 1980 lt 0 WSPura t min A B A WSPurg 1990 WSPurs 1980 10 t 1990 WSPurg 1990 B POPyra t WSPurg 1990 POPurn 1990 3 Industrial water withdrawal and consumption Industrial water withdrawal is assumed to change proportionally to industrial value added IVA Since water saving technology is expected to improve in future in industrial sector future change of water use efficiency is assumed exogenously and multiplied by the withdrawal estimated from the change of IVA In order to project the IVA in future the time series trend of the share of IVA in GDP is multiplied by the GDP of the scenario Wwyp t W 1990 TVA t TVA 1990 AWEITnp 1990 Wwnnc t Winp t RCONmnp t Wwnp t Industrial water demand IVA t Industrial value added AWE p t Water use efficiency improvement in industrial sector compared with 1990 Wiwnpc t Industrial water consumption RCON p t Industrial water demand consumption ratio 4 Agricultural water withdrawal and consumption Agricultural water withdrawal is closely related to the size of irrigat
19. re only used in specific countries in Asia Pacific region Share of fuel input into HTP and share of fossil fuel input into CHP are assumed to be constant Share of fossil fuel input into ELP is calculated by regression analysis Non fossil fuel input into CHP and ELP are depended on scenario assumption The electricity generation efficiency of ELP and CHP with COL OIL GAS and CRW is assumed by using exogenous energy efficiency improvement parameter The generation efficiency of NUC HYD GEO and NEW are fixed as per IEA s definitions NUC 0 33 HYD 1 0 GEO 0 1 NEW 0 1 The heat generation efficiency is assumed to be fixed as that in initial simulation period 7 Total primary energy supply Primary energy supply is calculated with final energy demand energy conversion process and distribution loss Distribution loss of fossil fuel electricity and heat is assumed to be constant as that in initial simulation period 8 CO NOx SOx CH4 N20 CO emissions Energy related GHG emissions are calculated by simulation result and assumed emission factor NOx and SOx emissions are assumed to be reduced according to increase of GDP per capita known as Kuznets curve 2 1 4 Water module 1 Model Features Estimated variables Domestic water withdrawal Industrial water withdrawal Agricultural water withdrawal Domestic water consumption Industrial water consumption Agricultural water consumption Driving forces explanator
20. y variables of future water withdrawal Population Historical trend and projection GDP Historical trend and projection Share of industrial value added Projection Urban and rural population supplied water service Urbanization ratio Historical trend and projection Irrigated area Historical trend Current amount of water withdrawal in domestic industrial and agricultural sectors Assumptions of parameters related with technology improvement Annual ratio of water use efficiency improvement in domestic sector Annual ratio of water use efficiency improvement in industrial sector Annual ratio of water use efficiency improvement in agricultural sector 2 Domestic water withdrawal and consumption Domestic water withdrawal is assumed to change proportionally to population that has access to water supply service water supplied population Since water saving technology is expected to improve in future in domestic sector future change of water use efficiency is assumed exogenously and multiplied by the withdrawal estimated from the change of water supplied population Water supplied population is projected for urban and rural areas separately The current tendency of water supplied population change is considered to continue in future with saturation Based on the water supplied population in 1980 and 1990 trend of water supplied population change is decided For countries where ratio of water supplied population water supplie
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