AIM-Country Model
Analysis of GHG mitigation and co-benefits
Coverage of counties is over 20
Bottom-up type model using GAMS
Detailed technology / process representation
Integration of energy flows between supply anddemand sectors
User friendly interface (Reformed AIM-Local’s )1

GHG mitigation analysis
Global Warming

Air Pollutants

Gases

CO2 emission

SO2 emission
NO2 emission

Countermeasure

Energy saving
Renewable energyLifestyle change

Pre-combustion
In Site combustion
Post-combustion

PolicyRegulation (Emission & Energy consumption)
Tax (Emission & Energy)

2Linkage with other models
AIM-Trend / AIM-CGE
Projections of efficiency
improvements

Projections ofdriving forces
Consistency check

Projections ofservice demands

Projections oftechnology mix

AIM-Country3

Coverage of counties
AIMAIMTREND

AustraliaJapan
New Zealand
P.R.China
Korea, DPR
VietnamBangladeshIndonesia
India
Korea
Sri Lanka
Myanmar
Malaysia

D
D
D
D
D
D
D
D
D
D
D
D
D

AIMAIMCountry

D
DS
S
D
D

AIMAIMTREND

Nepal
Pakistan
Philippines
Singapore
Thailand
Chinese Taipei
IranKazakhstan
Kyrgystan
Tajikistan
Turkmenistan
Uzbekistan

AIMAIMCountry

D
D
D
D
D
D
D
D
DDDD

D : Detailed model , S : Simple model4

Two major problems of data
Sector level statistics• Standard technology database

Energy use statistics• International (e.g. IISI)• Domestic• Stock statistics• International• International (e.g. IEA)
• Domestic• Domestic

Data estimation methodology

Servicedemands

Technology data

Energy use and supply• Energy intensity• Stocks• Costs, Life, etc• Fuel-wise• Sector-wise• Technology-wise• Non-availability of disaggregated data
• Lack of consistency between data sources

5Estimation of disaggregated data
• International statistics• International stock statistics• Assumptions for device efficiency• International statistics (IEA)

Adjustment of Energy intensities and Shares/Stocks to calibrate with IEA
energy balance information and per capita figures for India/ChinaService
demands

Technology data

Energy use and supply• Energy intensity• Stocks• Costs, Life, etc• Fuel-wise• Sector-wise• Technology-wise• Lack of even minimum required disaggregated data for service
demands, particularly in residential and commercial sectors• Fuel and efficiency characteristics of technologies may differ acrosscountries, particularly in some industries, residential and commercial sectors• Energy per capita differs across countries due to difference in lifestyles, modernization, food-habits, availability of indigenous resources6

Tackling lack of consistency between data sources
Energy balance data

Service demand data

Stock data

• ‘Data Adjustment’ methodology comprising LP framework• ‘Initially estimates’ taken from various data sources or assumed• Simultaneously changes energy uses, service demands, and stock levels, tominimize weighted sum of deviations between initial and final estimates• Penalty weights assigned to ‘deviations’ depending on reliability of data
sources7

A more systematic idea of data estimation
Illustration for residential sector
Minimize [ ∑ {wshl * (DevSH l+ + DevSH -l )} + weuuc * (DevEUUC + + DevEUUC - ) +l

Similar deviations in other residential services + Deviation in total energy use in residential sector ]Energy intensity of technology
Final estimate ofShare of technology

Total Urban Household Cooking Hours

Final estimate of Energy
use in urban cooking∑ (TUHCH * EI * F_SH ) = F_EUUClll

Initial estimate of Energy
use in urban cooking

Deviation between Initial and Final estimates

F_EUUC = I_EUUC * (1 + DevEUUC+ - DevEUUC- )F_SH l = I_SH l * (1 + DevSH l+ - DevSH -l )… Similar equations for other residential services
8Future work for AIM-Country applications
Develop methodology for ‘robust data estimation’ for reference
year. The methodology will combine both quantitative andqualitative approaches. Development of this methodology andaccess to domestic data sources will be done in collaboration
with various experts.
Estimate reference year data of service demands, technology
efficiencies, stocks, etc, for all countries in Asia-Pacific.
Estimate other input data (New technologies, Future scenarios,Removal processes).
Set up detailed AIM-Country model for all countries in AsiaPacific.

9Additional information required for countries excluding J, C, I, K
SectorIndustry

Additional information required-Energy consumption by fuel in major industries like Iron & Steel,
Cement, Aluminium, Pulp & Paper, Nitrogenous Fertilizer,
Phosphatic Fertilizer, Textiles, Brick, Chemicals & allied (e.g.
Caustic Soda, Soda Ash), Petrochemicals
Above energy consumption information by major technologicalprocesses in each industry, OR Energy-intensity numbers foreach major technological process-Passenger demand (in MPKM) and Freight demand (in MTKM)
for Road
Energy consumption by fuel in Road-Passenger, Road-Freight,
Rail-Passenger, Rail-Freight, Air-Passenger, Air-Freight, OR
Average energy intensity numbers for 2-Wheeler, Car, Bus, Light
Truck, Heavy Truck, Electric Locomotive, Diesel Locomotive,
Steam Locomotive-Energy consumption by fuel in Urban residential and Rural
residential sectors
Energy consumption by fuel in Cooking, Lighting, Space heatingand Other Appliances, in Urban and Rural residential sectors, OR
Average energy intensity numbers for various devices ofCooking, Lighting, Space heating and Appliances.

--

Land area irrigated by energized pumps
No. of Electric pumps and Diesel pumps
Average energy intensity of Electric pumps and Diesel pumps--Building floor area in commercial sector, OR Value added inCommercial sector
Above information by major Commercial sector categories like
Hotel & Restaurants, Hospitals & Health Care, Offices, etc.

--Transport-Residential-

Agriculture

Commercial

Information available in international
statistics-----

Production data by product or industry(Industry Commodity Statistics)
Energy consumption data by fuel in aggregate
industry categories (e.g. Total industry, Nonmetallic minerals) (IEA Energy Balance)

Stock of 2-Wheelers, Cars, Buses and Trucks(World Road Statistics)
MPKM and MTKM demand data (WorldMarketing Data & Statistics)
Energy consumption by fuel in aggregate Road,
Rail, Air and Other Transport sectors (IEA
Energy Balance)
Urban and Rural population data (WorldDevelopment Indicators)
Energy consumption by fuel in aggregate
Residential sector (IEA Energy Balance)

Total irrigated land area (World Development
Indicators and FAOSTAT, FAO)
Energy consumption by fuel in aggregate
Agriculture sector (IEA Energy Balance)

Energy consumption by fuel in aggregate
Commercial sector (IEA Energy Balance)10

Feedback/suggestions welcome
National level sources of information on service
demands, energy intensity and share/stock oftechnologies, for Asia-Pacific countries.

Methodology for robust estimation of data forreference year.

11