Post on 26-Aug-2021
Introduction of waste Introduction of waste management in AIM/CGEmanagement in AIM/CGE
Toshihiko MasuiToshihiko Masui
National Institute for Environmental StudiesNational Institute for Environmental StudiesAPEIS Training WorkshopAPEIS Training Workshop
NIES, 8 December 2004NIES, 8 December 2004
AIM, NIES
How to introduce waste in AIM/CGEHow to introduce waste in AIM/CGE
Waste generation– by activity: agriculture, manufacture,
household– by waste type: scrap metal, waste paper, ...
Waste treatment– input for treatment (capital, labor, energy, ..)– output after treatment (recycling, reuse, ...)
Recycle demand– by activity: steel production sector, power
sector, ... – by recycling goods: paper, biomass, ...
AIM, NIES
Additional inputs for waste analysisAdditional inputs for waste analysis
productionsector
household
capitallabor
government
abroad
market
importexport
produced commodity
energyintermediate
CO2
energyfinal demand
CO2
pollutionpollution
management
energyintermediate
CO2
env. capitallabor
environmentalindustry/
investment
recycle
Structure of AIM/Material
AIM, NIES
Production of AIM/MaterialProduction of AIM/Material
commodity m
activity
input 1
energy
capital labor pollution 1
value added
input n
aggregatedintermediate input
…
input for pollutionmanagement
pollution p…
commodity 1 …
σ=0 σ=1 σ=0
σ=0
σ=0
electricityfuel 1 fuel e…
σ=0
virginmaterial
reusedmaterial
σ=0
σ:elasticity of substitute
env.capital
laborenergyintermediateinput
σ=0
selfmanagement
contracttreatment
emissions
σ=∞
Reused material share is defined as the diffusion of stock.
CO2 CO2
inputs for waste treatment
Selection of waste treatment
waste generation
AIM, NIES
Demand structure in AIM/MaterialDemand structure in AIM/Material
household
fin. cons.
non-energy energy
GOVAGR ELEOGL... ...
σ=0(energy: derived demand)
σ=1 σ=0(energy share is decided
from technology)
env. load
MWMSEW
σ=0
consumptionσ=0
wastegeneration
AIM, NIES
Classification of solid wastesClassification of solid wastes
ash animal and plants wastessludge waste rubberslush, waste oil metal trash, scrap metalwaste acid waste glasswaste alkali slagwaste plastics construction and demolition wastewaste paper dust, sootwaste wood animal excrementwaste fiber and textile animal carcass
•Yellow cells represent both industrial waste and municipal wasteclassification.
•White cells represent industrial waste classification.
AIM, NIES
recycle
production
18 industrialwastes
8 municipalwastes
household 8 municipalwastes
industrialwaste man.
sector
int. man.
dir. reuse
dir. disp.
self treatmentfin. disp.
municipalwaste man.
sector
int. man.
dir. reuse
dir. disp.
recycle
fin.disp.
recycle
fin.disp.
Progress in structure : Progress in structure : (2) Reproduction of detailed waste flow(2) Reproduction of detailed waste flow
AIM, NIES
Progress in structure: (1) Waste from stock and reuseProgress in structure: (1) Waste from stock and reusePurposePurpose
Direct reuse of waste is effective environmental policy or not?– It seems to be effective to solve waste
issues.– But, it seems to delay energy efficiency
improvement.In order to answer this question, following module is developed and integrated with AIM/Material
production/consumption (AIM/Material)stock (durable goods)waste (Weibull distribution)reuse / treatment
Sample 1Sample 1
AIM, NIES
Progress in structure: (1) Waste from stock and reuseProgress in structure: (1) Waste from stock and reuse
ModelModel
AIM/Material Waste generation model
Production
Household
Reuse Stock in t-1
Stock in t
Waste (stock)
Reuse
Stock in t+1
Othertreatment
Waste management service
Municipal waste (flow)
Recycle Final disposal
Durable goods
RepairLow energy efficiency
Sample 1Sample 1
AIM, NIES
equipment i consumed in t=tt t+1 t+2 .... t+x-1 t+x
total disposal rate: Weibull distribution
x=durable years
100%
50%
0%
Total disposal rate:
( ) 1 tF tα
β
⎧ ⎫⎛ ⎞⎪ ⎪= − −⎨ ⎬⎜ ⎟⎝ ⎠⎪ ⎪⎩ ⎭
equipment i consumed in t=t+1t+1 t+2 t+3 .... t+x t+x+1
total disposal rate: Weibull distribution
x=durable years
100%
50%
0%
Progress in structure: (1) Waste from stock and reuseProgress in structure: (1) Waste from stock and reuse
Waste generation modelWaste generation model
equipment j consumed in t=tt t+1 t+2 .... t+x-1 t+x
total disposal rate: Weibull distribution
x=durable years
100%
50%
0%
equipment j consumed in t=t+1t+1 t+2 t+3 .... t+x t+x+1
total disposal rate: Weibull distribution
x=durable years
100%
50%
0%
Sample 1Sample 1
AIM, NIES
Progress in structure: (1) Waste from stock and reuseProgress in structure: (1) Waste from stock and reuse
ScenariosScenarios
Reference caseReuse promotion scenarios– promotion of reuse in household
small scale expansion of reuse– expansion of reuse in government
large scale expansion of reuse– expansion of rental service– reduction of repair cost
Sample 1Sample 1
AIM, NIES
Progress in structure: (1) Waste from stock and reuseProgress in structure: (1) Waste from stock and reuse
Simulation resultsSimulation results
19951998
20012004
2007
-20
-15
-10
-5
0
5
10
15
20
bil
yen
at
1995 p
rice
small
large
rental
repair
Sample 1Sample 1
: GDP change: GDP change
1995 1998 20012004
2007
-12000
-10000
-8000
-6000
-4000
-2000
0
2000
ton small
large
rental
repair
Municipal wasteMunicipal wastedisposal changedisposal change
AIM, NIES
Progress in structure: (1) Waste from stock and reuseProgress in structure: (1) Waste from stock and reuse
Simulation resultsSimulation results
1995 1997 1999 2001 2003 2005 2007 2009
-40-20
020
40
60
80
100
120
140
160
MtC small
large
rental
repair
Sample 1Sample 1
CO2 emission changeCO2 emission change
AIM, NIES
Progress in structure: (1) Waste from stock and reuseProgress in structure: (1) Waste from stock and reuse
Messages from simulationMessages from simulation
Expansion of reuse will make quantity of municipal final disposal decrease. CO2 will increase in small expansion of reuse, because reuse delay energy efficiency improvement. On the other hand, CO2 will decrease in large amount of reuse, because economic structure itself will shift from manufacture to service industry such as repair. Please contact Ms. Miyashita (MHIR) for more detail!
Sample 1Sample 1
AIM, NIES
Direct link of topDirect link of top--down and bottomdown and bottom--upup
Elasticity of substitution in AIM/Material= 0 or ∞
to keep material balance
ex. produced pulp and waste pulp 0
produced energy and by-product energy ∞
Need scenarios on structural change
For support scenarios, bottom-up model to represent the technology change has been constructed.
Sample 2Sample 2
AIM, NIES
Overview of bottomOverview of bottom--up modelup model
Simple linear model (Sewage sludge treatment);
Minimizing Total Cost =initial cost + running cost + final disposal cost
s.t. D≦Σi Xi : service demand of sewage sludgeXi≦Ai・li : treated sewage sludgeRj=Xi・rij=rdj : Recycle demandΣiDi=Xi・di : final disposal
i: technologies, X: treated sludge, A: capacity of sludge treatment, R: recycled products, D: other residuall, r, rd, d: parameters
Sample 2Sample 2
AIM, NIES
Linkage of 2 modelsLinkage of 2 models-- sewage sludge treatment sewage sludge treatment --
AIM/Material
In 1995
Bottom-upModel
In 1995
Sewage sludge generationPrice of final disposalRecycle material demand
AIM/Material
In 1996
Productivity of sewage sludge treatmentGeneration of final disposal
Bottom-upModel
In 1996
Sample 2Sample 2
AIM, NIES
Results of 2 modelsResults of 2 models-- Marginal cost of pollutants Marginal cost of pollutants --
0
10000
20000
30000
40000
1995 2000 2005 2010
C O 2 em issions (yen/tC )
final disposal of solid w astes
(yen/ton)
Year
Sample 2Sample 2
AIM, NIES
Results of 2 modelsResults of 2 models-- technology change technology change --
0 %
2 0 0 %
1 9 9 52 0 0 02 0 0 52 0 1 0
new others conv. others new dryingconv. drying new compost conv. compostnew melt furnace conv. melt furnace new incinerationconv. incineration
0%
20%
40%
60%
80%
100%
1995 2000 2005 2010Year
With constraints case
0%
20%
40%
60%
80%
100%
1995 2000 2005 2010Year
No constraints case
Introduction of new technologies
Sample 2Sample 2
AIM, NIES
Results of 2 modelsResults of 2 models-- Economic impact of constraints & technologies Economic impact of constraints & technologies --
In 2010– Environmental constraints on CO2 emissions and
final disposal of solid waste will bring 1.8 trillion yen of GDP loss.
In case of no constraints, GDP in 2010 will be 638 trillion yen.– By introducing new technologies (systems) in
sewage sludge management, 10 billion yen of GDP will be recovered.
– Both increase of recycle material demand and introduction of new technologies will make GDP loss will be mitigated by 200 billion yen.
Sample 2Sample 2
AIM, NIES
Soft link of topSoft link of top--down & bottomdown & bottom--upupNecessary datasetNecessary dataset
Sample 3Sample 3
Consistent dataset: relationship between input and output
Investment of new technology➜Technology improvement in stock in the next
year➜Modification of production function
AIM, NIES
Procedure for assessing carbon tax Procedure for assessing carbon tax in Japanin Japan
Sample 3Sample 3
Reference scenario is baseline– Autonomous energy efficiency improvement will achieve
without additional cost.– From enduse model, energy demand per output in stock
is calculated every year. – Technology improvement in new investment is
estimated from stock average. ➜Scenario.xls
Policy scenario– From enduse model, energy demand per output in stock
and additional cost compared to reference case to introduce new technologies are calculated every year.
– Convert of technology efficiency in each sector from stock average to new investment
AIM, NIES
Inputs data from AIM/Inputs data from AIM/EnduseEndusereference 2000 2001 2009 2010 2011 2012
Agriculture coal 0 0 0 0 0 0oil 10,448 10,312 9,222 9,085 8,949 8,813
town gas 0 0 0 0 0 0electricity 334 330 295 291 286 282new energy 0 0 0 0 0 0
Mining coal 0 0 0 0 0 0oil 733 724 652 643 634 625
town gas 0 0 0 0 0 0electricity 167 165 149 147 145 143new energy 0 0 0 0 0 0
Construction coal 0 0 0 0 0 0oil 3,909 3,914 3,961 3,967 3,972 3,978
town gas 0 0 0 0 0 0electricity 96 96 97 97 97 97new energy 0 0 0 0 0 0
000000new energy
888991929696electricity
000000town gas
3,9783,9723,9673,9613,9143,909oil
000000coalConstruction
000000new energy
131135139142165167electricity
000000town gas
614625635646724733oil
000000coalMining
000000new energy
260268275283330334electricity
000000town gas
8,8138,9499,0859,22210,31210,448oil
000000coalAgriculture
201220112010200920012000policy case
Sample 3Sample 3
AIM, NIES
Inputs data from AIM/Inputs data from AIM/EnduseEnduse
sector process technology
total subsidy in 1st commitment period
(100M¥)annual subsidy
(100M¥/year)
cement production
waste plastic injection 1,174 235
steel production high efficient kiln cooler 9 2
waste power system 22 4
coal boiler 0 0
oil boiler 0 0
gas boiler 0 0agriculture
boiler conversion control
Additional cost to introduce options➜ It is regarded that this type of investment only contributes to improve
the energy efficiency, not enhancement of production capital. ➜ In the process of capital accumulation, this additional investment
is excluded.
Sample 3Sample 3