Reducing Food Loss and Waste

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Urbanization:

An Integrated Study of

Reducing Food Loss and Waste Using Food-Energy-Water Nexus

Dr. Ching-Cheng Chang

Research Fellow, Institute of Economics, Academia Sinica and Professor, Dept. of Agricultural Economics, National Taiwan University

2016/9/5

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2| Team Members

Interdependence, Balance and Strategies

Prof. Shih-Hsun Hsu, Dept of Agricultural Economics, National

Taiwan University Prof. Huey-Lin Lee

Prof. Hsing-Chun Lin Main Project: An Integrated Study of the Water-Energy-Food Nexus and a Decision

Support System for Sustainable Urbanization in Taiwan

Dr. Ching-Cheng Chang, Institute of Economics, Academia Sinica

Regional Water Risk Management and Solution

Prof. Yih-Chi Tan, Graduate Institute of Bioenvironmental Systems

Engineering, National Taiwan University Dr. Kai-Yuan Ke

Prof. Yuan-Ching Chiang Investigation of Energy Consuming Element and Conservation

Technology

Prof. Sih-Li Chen, Dept of Mechanical Engineering, National Taiwan Univ

Establishing Tools of Policy Assessment and Indicators Toward Sustainable Development

Dr. Ching-Cheng Chang, Institute of Economics, Academia Sinica

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3|

1. Urbanization in Asia

2. Methodology and Database 3. A Case Study

4. Potential Consortium Members

Outline

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1. Urbanization in Asia

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5|

• UN FAO (2009) “How to Feed the World in 2050”

• The current global population of 7.3 billion habitants is anticipated to increase to 9.7

billion by 2050, which means 60% more food will be needed.

• Climate change is expected to have a

significant and negative impact on agriculture and fisheries, affecting global food production.

Challenges of Sustainably Feeding a

Growing Planet_1

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6|

• UN “World Water Development Report 2012”

• The world’s natural resources are under stress by degradation

• The amount of arable land will increase by less than 5%.

• Agricultural water consumption may rise from current levels of 70% to 89%.

Challenges of Sustainably Feeding a

Growing Planet_2

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• Emerging Issues (Hertel, 2015) - Urbanization

- Water scarcity

- Food waste/loss as new sources of supply - Climate regulation (Carbon tax)

Challenges of Sustainably Feeding a

Growing Planet_3

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8|

Estimated and Projected Urban and Rural

Population of the More and Less Developed

Regions, 1950–2050

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9| Changes in Urban and Rural Population by Major

Areas between 2011 and 2050 (in millions)

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10|

• UN ESCAP (2013)

Rapid urbanization has emerged in Asia-Pacific Since 1990.

 More than half of the world’s mega-cities (13 out of 22) are now found in Asia-Pacific

Economic growth in the Asia-Pacific region is led by cities

• Internal migration is the main factor behind urban growth

• Over 40% of the Asian-Pacific population which lives in cities contributes 80% of the region’s GDP.

Urbanization in Asia

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11| Problems with Urbanization

• Environmental Problems of Urban Slums

• Industrialization and Urban Air Pollution

• Problems of Congestion, Clean Water , and Sanitation

• Urban Development and Rural Development

• Food and Nutrition Security Problem

• Income Inequality

• Food Loss/Wastes

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Reardon et al. (2007) : Areas nearer cities experience more rapid transformation of food value chains, including the

development of the midstream and off-farm income.

Opportunities with Urbanization

Source: The Chicago Council on Global Affairs(2016)

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13

On-farm Income NT$224,858

(22%)

Off-farm Income NT$798,390

(78%)

Farm Household Income in Taiwan (NT$1,023,248, in 2014)

Due to:

Urbanization

Industrialization Globalization

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2. Methodology and

Database

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Life Supporting System for Sustainable Development

Joint Security Policy

(GEMTEE-WEF)

Water Security

Population, Urbanization, Public Health

Trade-off

Climate Change

Tradeoff

• Water for energy (cooling, hydro, extraction)

• Energy for water (extraction,

transport, treatment)

Trade-off

• Water for

ag/fishery/food

• Impact of land use on water resources

Trade-off

• Energy for ag/Fish/food

• Fiber for Energy production

• Crops for Energy vs Food ¹⁵

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Urbanization and Rural Development

(Goal: Sustainable Food and Nutrition Security)

Agri-Food-Nutrition System Consumers

Food Chain Actors

Farm Household

Biophysical environment: Water, Energy, Climate, Biodiversity, …

Rural(Farm Land) Land

Urban and Industry(City Land) Socioeconomic environment: Knowledge, Capital,Policies, Tenure, Culture, Legal system, Ethics, …

Off-Farm Income

Farm Income

16

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17| Methodology

Estimating the economic impact of food loss/waste ratio changes in APEC region and in Taiwan, in

particular, requires a solid computational core.

To achieve this goal, we use Computable General Equilibrium (CGE) model with water and energy modules to bring into focus the economy-wide assessment of reducing food loss and wastes.

CGE model is a multi-sectoral model based on neo- classical economic theory and national input-output table.

17

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GEMTEE

(General Equilibrium Model for Taiwan’s Economy

and Environment)

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GEMTEE: Model Framework and Database System

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20| Milestones of GEMTEE

20

2015

• Create a regional socio-economic impact assessment model and database for long-term baseline forecasting and policy simulations

2016

• Provide an integrated assessment framework to connect the socio-economic with the earth system modeling teams to assess climate and policy impacts

2017

• Analyze the interactive and feedback linkages

between socio-economic system and climate change as the basis to develop long-term pathways.

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21| Linkage with Water Sector in GEMTEE

Freshwater

Agriculture

Industrial

MNFCj MNFCj

CET/Linear

Public Water System

Services

CET/Linear

Households

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22|

Linkage with Energy Sector in GEMTEE

Renewable Energies

Low Carbon (Green) Technologies

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23|

The Core Input- output Database

Social Accounting Matrix: Efficiency v.s. Equity

Linkage with Policy in GEMTEE

(Regulation, Tax, Social Safety Net, Transfer …)

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Water Module

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25| Water Sector Identification

Industrial Water Use Water Use (2014)

1st Year

Historical Water Consumption

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26| Water Sector Identification

Chiayi Tainan

Identification of groundwater use for different water sectors

• Land use

• Well distribution

1st Year

Groundwater

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27| System Dynamic Modeling

^{1st Year}

 Data collection

 Hydrology

 Hydraulic facility

 Water and Power operation rules

 SDM construction

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28| System Dynamic Modeling

²^nd ^Year

 Link of GEMTEE, AIM/Enduse & SDM

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29| System Dynamic Modeling

³^rd ^Year

 Link of GEMTEE and SDM

 Strategy Assessment

• Reservoir dredging

• Low Impact

Development(LID)

• Plant Factory

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Energy Module

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31| Energy Module

Residential & commercial departments Industrial departments

Agricultural departments

Transportation departments

Parameters or Mathematical model

Detail items Solutions Nexus target

Low energy consumption plant factory

Greenhouse with natural light

Raft foundation integrated with rainwater harvesting

Water source heat pump

Low energy consumption refrigerated warehouse

Elements of Nexus Solutions of Nexus

EnergyPlus Building energy

consumption simulation

Water

(Second subproject)

Photovoltaic

Hydroelectric Biomass

Food

(Fourth subproject)

Energy

(Third subproject)

CO₂, GDP

(first subproject)

generating capacity/per area…

generating capacity/per ton of waste…

generating capacity/per unit water consumption…

AIM/Enduse Regional energy

engineering

Biogas power generation

e.g：

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• Models of different scales

• EnergyPlus: “Building” energy model

• AIM/Enduse: “Urban” energy model

• Connected and co-simulated

• to create a more comprehensive analysis of the urban scale.

Energy Consumption Simulation_1

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33| Energy Consumption Simulation_2

Socio-economic data

• Population

• Economic growth

Apparatus data

• Energy efficiency

• Operating time

Building data

• Appearance, use, structure

• Occupant density

Technical data

• Energy consumption of single building

• Energy efficiency

EnergyPlus

Model calibration

Calibration of energy services

AIM/Enduse Model

Output

• Single/regional building energy consumption

• Greenhouse gas emissions

• Cost-effectiveness

Technical data calibration

Bottom up

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34| Flowchart of Energy to F-W Links

Model Calibration and Validation Data collection and analysis for the

current situation of renewable energy application in Taiwan

Regional large-scale energy consumption simulation and

analysis

Modeling the total energy flow

Feedback coefficients of energy modeling to GEMTEE –WATER model

Future Energy supply and consumption condition change

First year

Second year

Third year

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• In view of the fact that 40% of all foods require

refrigeration, 15% of world fossil fuel energy is used in food transport refrigeration.

• Preserving food is prevalent as most households engage in these practices through refrigeration system.

• Energy consumption in cold chains has been predicted to rise significantly

• Of critical attention is the increasing number of road

transport refrigeration which is highly gaining enormous ground globally.

Connecting with Food Security_1

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36| Connecting with Food Security_2

Residential & commercial departments Industrial departments

Agricultural departments

Transportation departments

EnergyPlus Building energy

consumption simulation AIM/Enduse Regional energy

engineering

Cold chain transportation Cold chain storage

Land uses

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GTAP

(Global Trade Analysis Project)

Hertel (1997)

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38| The GTAP Model

• The GTAP model is an effort to map the intricacies and

interconnectedness of the global economy mathematically.

• GTAP9 data set, the version used for this analysis, encompasses:

• 140 countries and regions

• 57 industries

• 8 factors of production

Furthermore, the model allows for the interplay between households, industries, and the overall economy.

38

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• GTAP-E Data Base –

• Provides carbon dioxide (CO2) emissions data distinguished by fuel and by user for each of the 140 countries/regions in the GTAP 9 Data Base.

• GTAP Non-CO2 Emissions Data Base –

• Provides information on other Greenhouse gas (GHG) emissions such as Methane (CH4), Nitrous Oxide (N2O), Fluorinated gas (FGAS).

• GTAP-Power Data Base –

• An electricity-detailed extension including: transmission & distribution, nuclear, coal, gas, oil, hydroelectric, wind, solar, and other power technologies.

• GTAP Land Use Data Base

• Compiled following the agro-ecological zoning approach developed by FAO (2000) and IIASA (2002). Arable land is classified into 18 AEZ based on the length of growing period (LGP) .

• GTAP-Water Data Base

• based on the GTAP version 6 database (Dimaranan 2006) and on the IMPACT 2000 baseline data (Rosegrant et al. 2002).

GTAP 9 Satellite Data and Utilities

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3. A Case Study:

Reducing Food Loss and Waste

and FEW Nexus

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41| CRA (Collaborative Research Actions) of Belmont Forum

Purposes

1. Address the Belmont Challenge priorities

(i.e. societally relevant global environmental change challenges)

2. Leverage Belmont Forum members existing investments through international added value

3. Bring together new partnerships of natural scientists, social scientists, and users

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42| Reducing Food Losses and Waste is Gathering Increasing Global Interests and Actions!!

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43| APEC Multi-Year Project (2013~2018)

Title:

“Strengthening Public-Private Partnership to Reduce Food Losses in the Supply Chain” (APEC/PPFS & ATCWG Multi-Year Project M SCE 02 2013A)

Purposes

• Identify key issues on reducing food losses and wastes

• Seek best practices in private and public sectors

• Find practical solutions and enhance capacity-building

43 2013

• Preparation, Research, and Identification

2014/16

• Investigation of Food Losses and Waste

2017/18

• Action and Inter-linkages

Work Plan (2013-2018)

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Source: FAO

UN FAO: Save Food

Initiative, 2012

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45|

Source: FAO (2014). Direct impacts of food wastage and additional scarcity costs.

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46| Global and Regional Movement of Free Trade and Reducing FLW

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NAFTA

（27%）

CJK FTA

（21%）

Source： IMF, World Economic Outlook Databases (WEO), October 2013。

EU

FLW Protocol

Accounting/Reporting

TTIP

P12 (38%)TPP

P16 (29%)RCEP

US

Food Recovery Act Food Date Labeling Act

UN/SDG 12.3: 50% Reduction of Food Waste by 2030

APEC

Food Security Roadmap (10% Reduction of FLW by 2020)

46

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• New Plan was formulated in 2015, including quantitative targets for halving waste generation from its peak (FY2000) and new measures on waste reduction.

• Kyoto is the first city to set quantitative targets for reducing food loss.

FY 2000

(at a peak) FY 2013 FY 2020 (goal)

Waste processed by

the city

820 472 390

Incineration 760 444 350

Food loss 96 67 50

Paper waste 220 140 100

GHG from waste

management 270 120 80

Quantitative targets (unit: 1,000 tons)

Amount of waste at its peak…

Residents

Business operators

Administrative

bodies reduced

to half!

New Plan for Halving Waste Amount of Kyoto City for 2015-2020 (Junko Katsumi, 2016)

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48| Current Food Loss & Waste Ratios

Mass Flow Model (FAO, 2011)

48

APEC-wide Average Losses

Source: Hsu et al (2016)

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49| Scenario 1: Uniform

We consider 3 scenarios of food waste reduction:

1. A uniform reduction in food waste ratios by 10% in all APEC members.

The APEC Action Plan for Reducing Food Loss and Waste, 2014 established the goal of a 10% reduction in food loss and waste by 2020 (2012 base).

In this scenario we focus on food waste ratios and reduce them uniformly by 10% in distribution (retail) and

consumption (consumers) for all APEC economies.

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50| Scenario 2: Non-Uniform

2. A targeted food loss/waste reduction

In this scenario we apply a food loss or waste reduction at the stage of highest loss for each region.

• Supply: Production, Handling & Storage, Processing &

Packaging

• Demand: Distribution, Consumption

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Region Stages Reduction %

High Income Demand 10%

Upper Middle Income Demand and Supply 5% each

Lower Middle Income Supply 10%

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51| Scenario 3: Non-Uniform (H)

3. An ambitious targeted food loss/waste reduction

We chose 20% as an ambitious, yet feasible, level of food waste and loss reduction.

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Region Stages Reduction %

High Income Demand 20%

Upper Middle Income Demand and Supply 10% each

Lower Middle Income Supply 20%

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52| Food Security in

Lower Middle Income APEC

52

-5.00%

-4.00%

-3.00%

-2.00%

-1.00%

0.00%

1.00%

2.00%

3.00%

Household Food Demand

Food Demand for Domestic Food

Food Demand for Imported Food

Household Food Price

% Change in Food Demand and Prices by Source (APEC_LM)

10% Scenario Non-Uniform Non-Uniform (H)

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53| Welfare Gains

53

Income Region

Measure Uniform

Scenario

Mixed Scenario (10%)

Mixed Scenario (20%)

High Mil US$ (2011) 515.98 1169.13 2327.03

US$/Capita (2011) 0.69 1.57 3.12

Upper Middle

Mil US$ (2011) 645.81 9783.91 19302.18

US$/Capita (2011) 0.87 13.12 25.87

Lower Middle

Mil US$ (2011) 53.98 3337 6495.16

US$/Capita (2011) 0.07 4.47 8.71

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4. Potential Consortium

Members

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55|

• LEI Wageningen UR (FP7 FUSIONS; HORIZON 2020 REFRESH)

• GTAP (Prof. Thomas Hertel, Purdue University)

• IFPRI (Dr. Mark W. Rosegrant, International Food Policy Research Institute)

• Texas A&M Univ. (Prof. Bruce McCarl)

• USDA ERS (Dr. Jean C. Buzby)

• Kyoto University/Kyoto City

• NCAR (National Center for Atmospheric Research)

Potential Consortium Members

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56| EU H2020 Project: SUSFANS

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57|

• LEI-WUR_Netherlands_Agricultural Economics Research Institute

• UBO_Germany_University of Bonn

• INRA_France_French National Institute for Agricultural Research

• KU Leuven_Belgium_Catholic University of Leuven

• WU_Netherlands_Wageningen UR (University & Research center)

• UOXF_United Kingdom_University of Oxford

• IIASA_Austria_International Institute for Applied Systems Analysis (IIASA)

SUSFANS CONSORTIUM ^_1

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58|

• SZU_Czech Republic_National Institute of Public Health

• ANSES_France_French Agency for Food, Environmental and Occupational Health & Safety

• CRA_Italy_Agricultural Research Council_Ministry of Agriculture

• DTU_Denmark_National Food Institute_Technical University

• ILSI-EU_Belgium_International Life Sciences Institute, Europe

• SIK_Sweden_Swedish Institute for Food and Biotechnology

• JRC_Belgium_Joint Research Centre_Institute for Environment and Sustainability

• NTU_Taiwan_National Taiwan University

CONSORTIUM ^_2

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59| References

1. FAO, 2011. Global Food Losses and Food Waste—Extent, Causes and Prevention.

Rome, Italy: Food and Agriculture Organization of the United Nations.

2. Hertel, T.W., 1997, Global Trade Analysis: Modeling and Applications, New York:

Cambridge University Press.

3. Hsu, S.H. K.F. Mayr, S.M. Hsu, and C.C., Chang. 2016. “Impact Assessment of Reducing Food Waste by Households and in Retail in The APEC Region”, presented at the 2016 APEC Expert Consultation on Food Loss and Waste at Retail and Consumer Levels, Taipei.

4. Reardon, T. and C.P. Timmer. 2007. “Transformation of Markets for Agricultural Output in Developing Countries Since 1950: How Has Thinking Changed?”

chapter 55 in R.E. Evenson, and P. Pingali (eds). Handbook of Agricultural

Economics, 3: Agricultural Development: Farmers, Farm Production and Farm Markets. Amsterdam: Elsevier Press: 2808-2855.