Land/Agriculture Modeling of GRAPE Preliminary Results Atsushi - - PowerPoint PPT Presentation

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Land/Agriculture Modeling of GRAPE Preliminary Results Atsushi KUROSAWA The Institute of Applied Energy (IAE), JAPAN Energy Modeling Forum Meeting Tsukuba, Japan December 2006 The views are solely those of the individual author and do

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SLIDE 1

Land/Agriculture Modeling of GRAPE – Preliminary Results

Atsushi KUROSAWA

The Institute of Applied Energy (IAE), JAPAN

Energy Modeling Forum Meeting Tsukuba, Japan December 2006

The views are solely those of the individual author and do not represent organizational views of IAE.

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SLIDE 2

Outline

1.EMF22 runs 2.Coupling of Mitigation and Adaptation

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SLIDE 3

Outline

1.EMF22 runs 2.Coupling of Mitigation and Adaptation

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SLIDE 4
  • Reg. Landuse & Food Bal.

FOREST (FRS) CROPLAND (CRP) GRASSLAND (GRS) URBAN (URB) OTHER AREA (DSR)

CEREAL GRASS

  • FED

MEAT GRASS

  • FED

LIVESTOCK CROP

  • FED

LIVESTOCK HUMAN BEING OTHER FOOD PROTEIN CALORIE CROP

  • FED

MEAT LANDUSE LIVESTOCK & FOOD NUTRITION TRADABLE GOODS

function of per capita GDP function of per capita GDP

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SLIDE 5

EMF22 runs – 4 scenarios w/o CO2 and climate feedbacks * Modeler’s reference (REF) * High yield (HI) * Low yield (LO) Common food nutrition intake (Calorie, Protein) Different yield growth with upper limit * Coordinated Scenario (CS) Designated GDP, Population >>> Changes in Food Nutrition Intake IFPRI Yield Growth

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SLIDE 6

EMF22 runs (cont.) * Food habit Difficult to change food habit and agriculture protection in a short timeframe. * Ratio of crop-fed and grass-fed animal meat REF and HI – constant LO and CS – gradual changes (grass-fed meat, -2% per decade)

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SLIDE 7

GDP and Population

REF,HI,LO CS

GDP 50 100 150 200 250 300 2000 2020 2040 2060 2080 2100 (2000 TR$) FSEE LAMR SSAF MENA SEAS CPAS OCEA JAPN WEUR NAMR GDP 50 100 150 200 250 300 2000 2020 2040 2060 2080 2100 (2000 TR$) FSEE LAMR SSAF MENA SEAS CPAS OCEA JAPN WEUR NAMR

Population (Coordinated Scenario) 2000 4000 6000 8000 10000 12000 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 (million) FSEE LAMR SSAF MENA SEAS CPAS OCEA JAPN WEUR NAMR Population 2000 4000 6000 8000 10000 12000 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 (million) FSEE LAMR SSAF MENA SEAS CPAS OCEA JAPN WEUR NAMR

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SLIDE 8

Crop Yield

REF HI LO CS

Cereal Yield 1 2 3 4 5 6 7 8 2000 2020 2040 2060 2080 2100 (ton/ha) NAMR WEUR JAPN OCEA CPAS SEAS MENA SSAF LAMR FSEE Cereal Yield 1 2 3 4 5 6 7 8 2000 2020 2040 2060 2080 2100 (ton/ha) NAMR WEUR JAPN OCEA CPAS SEAS MENA SSAF LAMR FSEE Cereal Yield 1 2 3 4 5 6 7 8 2000 2020 2040 2060 2080 2100 (ton/ha) NAMR WEUR JAPN OCEA CPAS SEAS MENA SSAF LAMR FSEE Cereal Yield 1 2 3 4 5 6 7 8 2000 2020 2040 2060 2080 2100 (ton/ha) NAMR WEUR JAPN OCEA CPAS SEAS MENA SSAF LAMR FSEE

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SLIDE 9

Crop-Fed Meat Yield

REF HI LO CS

Chiken and Pork Yield 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2000 2020 2040 2060 2080 2100 (ton/ton-feed) NAMR WEUR JAPN OCEA CPAS SEAS MENA SSAF LAMR FSEE Chiken and Pork Yield 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2000 2020 2040 2060 2080 2100 (ton/ton-feed) NAMR WEUR JAPN OCEA CPAS SEAS MENA SSAF LAMR FSEE Chiken and Pork Yield 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2000 2020 2040 2060 2080 2100 (ton/ton-feed) NAMR WEUR JAPN OCEA CPAS SEAS MENA SSAF LAMR FSEE Chiken and Pork Yield 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2000 2020 2040 2060 2080 2100 (ton/ton-feed) NAMR WEUR JAPN OCEA CPAS SEAS MENA SSAF LAMR FSEE

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Yield Growth in Agriculture Production * Crop Production Yield = (Fertilizer Applied) * (Other Factors) Management Gene Tech., etc. * Meat Production Yield = (Feed required) * (Other Factors) Grassland Area Management Feed Amount Growth Hormone

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Food Production

REF HI LO CS

Food Supply (World) 0.5 1 1.5 2 2.5 3 2000 2020 2040 2060 2080 2100 (Gton) CHIKEN & PORK BEEF & MUTTON CEREAL FOR FEED CEREAL FOR FOOD Food Supply (World) 0.5 1 1.5 2 2.5 3 2000 2020 2040 2060 2080 2100 (Gton) CHIKEN & PORK BEEF & MUTTON CEREAL FOR FEED CEREAL FOR FOOD Food Supply (World) 0.5 1 1.5 2 2.5 3 2000 2020 2040 2060 2080 2100 (Gton) CHIKEN & PORK BEEF & MUTTON CEREAL FOR FEED CEREAL FOR FOOD Food Supply (World) 0.5 1 1.5 2 2.5 3 3.5 2000 2020 2040 2060 2080 2100 (Gton) CHIKEN & PORK BEEF & MUTTON CEREAL FOR FEED CEREAL FOR FOOD

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SLIDE 12

Global Landuse

Landuse (World) 2 4 6 8 10 12 14 2000 2020 2040 2060 2080 2100 (Gha) URB DSR CRP GRS FRS

REF HI LO CS

Landuse (World) 2 4 6 8 10 12 14 2000 2020 2040 2060 2080 2100 (Gha) URB DSR CRP GRS FRS Landuse (World) 2 4 6 8 10 12 14 2000 2020 2040 2060 2080 2100 (Gha) URB DSR CRP GRS FRS Landuse (World) 2 4 6 8 10 12 14 2000 2020 2040 2060 2080 2100 (Gha) URB DSR CRP GRS FRS

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SLIDE 13

CH4 from Agriculture

REF HI LO CS

CH4 Emissions (World) 100 200 300 2000 2020 2040 2060 2080 2100 (Tg-CH4) Rice CP BM CH4 Emissions (World) 100 200 300 2000 2020 2040 2060 2080 2100 (Tg-CH4) Rice CP BM CH4 Emissions (World) 100 200 300 2000 2020 2040 2060 2080 2100 (Tg-CH4) Rice CP BM CH4 Emissions (World) 100 200 300 2000 2020 2040 2060 2080 2100 (Tg-CH4) Rice CP BM

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SLIDE 14

N2O from Agriculture

REF HI LO CS

N2O Emissions (World) 5 10 15 20 2000 2020 2040 2060 2080 2100 (Tg-N2O) CP BM Fert N2O Emissions (World) 5 10 15 20 2000 2020 2040 2060 2080 2100 (Tg-N2O) CP BM Fert N2O Emissions (World) 5 10 15 20 2000 2020 2040 2060 2080 2100 (Tg-N2O) CP BM Fert N2O Emissions (World) 5 10 15 20 2000 2020 2040 2060 2080 2100 (Tg-N2O) CP BM Fert

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SLIDE 15

Discussions Needed

* Food Culture Inertia Crop - Rice in Asia, etc. Protein – Meat, Fish, Milk,,, Food Safety Gene Tech., * Food Service Industry Dine Out & Food Waste * Other Issues

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SLIDE 16
  • Reg. Landuse & Food Bal.

FOREST (FRS) CROPLAND WHEAT (CRP_WHT) GRASSLAND (GRS) URBAN (URB) OTHER AREA (DSR) OTHER CEREAL B&M MEAT Cattle&Sheep Poultry&Swine HUMAN BEING OTHER FOOD PROTEIN CALORIE C&P MEAT LANDUSE LIVESTOCK & FOOD NUTRITION TRADABLE GOODS WHEAT RICE CROPLAND RICE (CRP_RCE) CROPLAND OTHER CEREAL (CRP_OTH)

Possible Future Extension (1) Crop Disaggregation

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SLIDE 17
  • Reg. Water Bal.

PRECIP (PRCIP) (Constant) (Green Water) (used in plants) Population (Blue Water) Surface - River Groundwater, etc. Other Agr. Usage (OAG) INDUSTRY (IND) AGRICULTURE(AGR) SUPPLY Water Distribution DEMAND HOUSEHOLD (DOM) Irrigated Cropland (Rice, Wheat, Other Cereals) Rainfed Cropland (Rice, Wheat, Other Cereals) GDP Water for Oth. Cereal Prod. (OCR) Water for Rice Prod. (RCE) Water for Wheat Prod. (WHT) Water for

  • Oth. Ag. Prod.

(OAG) Rice Production Wheat Production Other Cereal Production Other Ag. Production FOSSIL Groundwater (Exhaustible) Total Potential (Internal and External) Natural > Actual > Exploitable

Possible Future Extension (2) Water Availability

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SLIDE 18
  • Reg. Water Bal.

PRECIP (PRCIP) (Constant) (Green Water) (used in plants) Population (Blue Water) Surface - River Groundwater, etc. Other Agr. Usage (OAG) INDUSTRY (IND) AGRICULTURE(AGR) SUPPLY Water Distribution DEMAND HOUSEHOLD (DOM) Irrigated Cropland (Rice, Wheat, Other Cereals) Rainfed Cropland (Rice, Wheat, Other Cereals) GDP Water for Oth. Cereal Prod. (OCR) Water for Rice Prod. (RCE) Water for Wheat Prod. (WHT) Water for

  • Oth. Ag. Prod.

(OAG) Rice Production Wheat Production Other Cereal Production Other Ag. Production FOSSIL Groundwater (Exhaustible) Total Potential (Internal and External) Natural > Actual > Exploitable

Possible Future Extension (2) Water Availability

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SLIDE 19

Outline

1.EMF22 runs 2.Coupling of Mitigation and Adaptation

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SLIDE 20

Motivation

* Existing Frameworks

  • Integrated assessment models (IAMs) to analyze

climate change mitigation strategies.

  • Life cycle impact assessment (LCIA) to make

comprehensive analysis of environmental effects of product life cycle. * Application to Adaptation Study Coupling of IAM and LCIA can provide common and consistent framework basis for bottom-up and top-down integration in climate change impact assessment.

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SLIDE 21

GRAPE output and “Impact Categories” &”Safeguard Subjects” of LIME

LIME GRAPE output (Inventories in LIME) Impact Categories Safeguard Subjects 6 Kyoto GHGs Global Warming Human health, Social Assets SOx Acidification, Urban Air Pollution Human health, Social Assets, Primary Productivity Land Use (LU) Land Use Primary Productivity Land Use Change (LUC) Land Use Primary Productivity, Biodiversity

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SLIDE 22

2 4 6 8 10 12 14 2000 2020 2040 2060 2080 2100 year External costs in percentage GDP [%] 2,000 4,000 6,000 8,000 10,000 12,000 14,000 External Costs [Billion $/yr] Land Use Change Land Use SOx GHG %GWP

Global Total External Costs by Inventories

Tokimatsu, Itsubo, Kurosawa, Kosugi, Yagita and Sakagami, A simulation study of merging a lifecycle impact assessment (LCIA) with integrated assessment model (IAM) – a optimal economic growth via interlizing external costs by environmental impacts – (in Japanese), Kankyo Kagaku Kaishi, vol.19 no.1, pp25-36, 2006.

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SLIDE 23

2 4 6 8 10 12 14 2000 2020 2040 2060 2080 2100 year External costs in percentage GDP [%] 2,000 4,000 6,000 8,000 10,000 12,000 14,000 External Costs [Billion $/yr] Biodiversity Primary Production Social Assets Humal Health %GWP

Global Total External Costs by Safeguard Subjects

Tokimatsu, Itsubo, Kurosawa, Kosugi, Yagita and Sakagami, A simulation study of merging a lifecycle impact assessment (LCIA) with integrated assessment model (IAM) – a optimal economic growth via interlizing external costs by environmental impacts – (in Japanese), Kankyo Kagaku Kaishi, vol.19 no.1, pp25-36, 2006.

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SLIDE 24

Global Sustainable Development Indices Global Sustainable Development Indices for the Future: for the Future:

A Simulation Study Linked IAM with LCIA

Takanobu Kosugi*1, Koji Tokimatsu*2, Atsushi Kurosawa*3, Norihiro Itsubo*2,4, Ryota Ii*5, Hiroshi Yagita*2,6, Masaji Sakagami*7

*1 College of Policy Science, Ritsumeikan University *2 Research Center for Life Cycle Assessment, National Institute of Advanced Industrial Science and Technology *3 The Institute of Applied Energy *4 Musashi Institute of Technology *5 Pacific Consultants Co., Ltd. *6 Nippon Institute of Technology *7 Nihon Fukushi University

The 7th International Conference on EcoBalance

  • Nov. 14-16, 2006, at EPOCHAL TSUKUBA, Tsukuba, JAPAN
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SLIDE 25

Objective Objective

  • Presenting

– a methodology to assess energy and materials systems from a viewpoint of sustainable development in the future; – preliminary results giving insights on energy and material- related policies for sustainable development in 21st century.

  • Core methodology: extension and application of

GRAPE/LIME model, which merges an IAM GRAPE and a LCIA method LIME.

– GRAPE is extended to be coupled with a new submodel that explicitly deals with the materials supply and demand systems including mining, refining and recycling of iron and steel, aluminum and copper.

Kosugi, Tokimatsu, Kurosawa, Itsubo, Ii, Yagita, Sakagami, Global Sustainable Development Indices for the Future:A simulation study of merging a lifecycle impact assessment (LCIA) with integrated assessment model (IAM), The 7th International Conference on EcoBalance, 2006, Tsukuba, JAPAN

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SLIDE 26

Human health, Social Assets, Biodiversity, Primary Productivity Carbon(Deforestation) CH4(Livestock,Rice) N2O(Fertilizer),etc

ENERGY& MATERIAL CLIMATE IMPACT(LIME) LAND USE ECONOMY

CO2,CH4,N2O (Fossil Fuel) Energy&Material Cost Energy&Material Trade G H G e m i s s i

  • n

O D S e m i s s i

  • n

Landuse Related Cost Food/Wood Trade

f(K,L,E,N,M)

  • Energy
  • Material
  • landuse
  • externalities

Carbon Trade Biomass Energy Land Degradation Landuse&change

Structure of GRAPE/LIME linkage Structure of GRAPE/LIME linkage

Kosugi, Tokimatsu, Kurosawa, Itsubo, Ii, Yagita, Sakagami, Global Sustainable Development Indices for the Future: A simulation study of merging a lifecycle impact assessment (LCIA) with integrated assessment model (IAM), The 7th International Conference on EcoBalance, 2006, Tsukuba, JAPAN

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SLIDE 27

LIME LIME –

– A Life Cycle Impact Assessment Method A Life Cycle Impact Assessment Method

Damage Assessment Fate Analysis Quality Analysis Weighting Exposure Analysis Inventory Concentration Impact Category Category Endpoint Safeguard Subjects Single Index Single index (yen)

Thermal/Cold Stress Malaria Skin Cancer Cancer Respiratory Disease Cataract Terrestrial Aquatic Plant Benthos Fishery Crop Energy Materials

Global Warming Acidification Human toxicity

(chemicals/metals)

Ecotoxicity Ozone Depletion Eutrophication Oxidant Creation Land use CO2 NOx SOx Benzene NMVOC TCDD Lead Total N Total P Oil Waste Copper ore Land HCFCs

GHS in Air

  • Toxic. In Water
  • Toxic. In Soil

ODS in Stratosphere

  • Toxic. In Air
  • Conc. Oxidant

Consumption of DO

  • Dep. of

Acidifying sub.

Resource Consumption

Cost DALY

Primary Productivity Ecosystem Biodiversity

Extinct Species Dry weight

Human life Waste

Dengue Favor

Human health Social welfare Air Pollution

Disaster

Kosugi, Tokimatsu, Kurosawa, Itsubo, Ii, Yagita, Sakagami, Global Sustainable Development Indices for the Future: A simulation study of merging a lifecycle impact assessment (LCIA) with integrated assessment model (IAM), The 7th International Conference on EcoBalance, 2006, Tsukuba, JAPAN

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SLIDE 28

Model extension: from Energy module Model extension: from Energy module to Energy & Materials module to Energy & Materials module

Ore (iron, bauxite, copper) Scrap (steel, aluminum, copper) Blast Furnace + Basic Oxygen Furnace Direct reduction process + Electric furnace Aluminum refinery Copper refinery Steel for electric machinery and automobiles Steel for construction Refined aluminum Refined copper disposal Electricity Heat excluding that for materials production Electricity excluding that for materials production Transportation

Energy Systems Module

Coal, oil, gas Demand

Kosugi, Tokimatsu, Kurosawa, Itsubo, Ii, Yagita, Sakagami, Global Sustainable Development Indices for the Future: A simulation study of merging a lifecycle impact assessment (LCIA) with integrated assessment model (IAM), The 7th International Conference on EcoBalance, 2006, Tsukuba, JAPAN

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SLIDE 29

GRAPE/LIME linkage GRAPE/LIME linkage

Integrated assessment model for energy/economy (GRAPE) Japanese version of lifecycle impact assessment (LIME)

Margining two models of GRAPE and LIME, and carrying out of

  • ptimal growth simulation by internalizing externalities

yr rg yr rg t yr rg

I T K K

, , 1 ,

) 1 ( ⋅ + ⋅ − =

+

δ

yr rg yr rg yr rg

LUC EMC M N E L K f Y

, , ,

) , , , , ( − − =

yr rg yr rg yr rg

I Y C

, , ,

− = ( )

max log 1

, , ,

→ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ ⋅ ⋅ + = ∑∑

⋅ − yr rg yr rg yr rg yr rg T yr

L C L r U

yr rg yr rg yr rg yr rg

EXT LUC EMC M N E L K f Y

, , , ,

) , , , , ( − − − =

( )

∑ ∑ × =

i s S i S

IF Inv EXT

,

.

EXT：total amount of environmental impacts: externalities Invs：inventory of environmental impact substance IFis：monetary value of environmental impact for a unit of the substance

Kosugi, Tokimatsu, Kurosawa, Itsubo, Ii, Yagita, Sakagami, Global Sustainable Development Indices for the Future: A simulation study of merging a lifecycle impact assessment (LCIA) with integrated assessment model (IAM), The 7th International Conference on EcoBalance, 2006, Tsukuba, JAPAN

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SLIDE 30

Other topic Japanese Energy Technology Roadmap Long-Term FY2004-2005 Short- and Medium- Term Started Oct. 2006

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SLIDE 31

Strategic Technology Roadmap (Energy Sector) ∼ Energy Technology Vision 2100 ∼ http://www.iae.or.jp/2100.html

* Contract Research from METI, Japan * One of the Strategic Tech. Roadmaps of METI * Identify Long Term Energy Tech. Role under Climate (CO2/GDP) and Energy Resource Constraints * Detail Roadmaps incl. Tech. Performance Targets Transformation (Prim. Supply & Conversion (Elec. &H2)) Demand / Industry, Residential & Commercial, Transport

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SLIDE 32

Energy Supply Which Direction Should We Go?

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SLIDE 33

Energy Technology Roadmap – Example of Res/Com please see the website for detail.

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SLIDE 34
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SLIDE 35

Thank you for the kind attention.