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START Advanced Institute August 2003

Systems Thinking/Modeling SessionsCraig Forster, Eric Scharff and Seth McGinnis

This document is HANDOUT.DOC on the systems session CD.

OVERVIEW OF SESSIONSUNIT 1 – Introduction to Systems Thinking

1.1 Background- descriptors- system behaviors- hypothesis testing- problem definition- storytelling- causal loop (influence) diagrams

1.2 Explore pre-constructed, simple, urban CO2 emissions model “CO2 Learn”- develop story and reference behaviors- identify problem and hypotheses to be tested - causal loop (influence) diagram- introduce STELLA® user interface level- introduce input-output features

- sliders and graphical input- buttons- graph manipulation

- experience hypothesis testing- change security and review model at map level

1.3 Evaluate strengths and weaknesses of model

UNIT 2 – Introduction to STELLA® for Building System Dynamics Models2.1 Introduction

- expand story for urban system with goal to reducing urban CO2 emissions- expand causal loop diagram (population with migration, sequestration, economic

output, pollution, CO2 emissions from energy use)

2.2 Population Model- review Population Model story and outline reference behaviors- build Population Model: a simple, two-stock population model with migration

driven by differentials in economic output- explore Population Model

2.3 Economic Model- review Economy Model story and outline reference behaviors- build Economy Model: a simple one-stock economic output model

driven by urban population growth. Growth in economic output is

START Advanced Institute, Aug. 2003 Systems Thinking/Modeling Sessions 1

assumed to cause growth in generic pollution flows that are reduced by pollution abatement strategies and technologies.

- explore Economic Model

2.4 Energy-to-CO2 Model- review Energy-to-CO2 Model story and outline reference behaviors- build Energy-to-CO2 Model: a simple, no-stock CO2 emissions model driven by

urban economic output- explore Energy-to-CO2 Model

2.5 CO2 Sequestration Model- review CO2 Sequestration Model story and outline reference behaviors- build CO2 Sequestration Model: a simple, one-stock CO2 sequestration model

driven by energy use- explore CO2 Sequestration Model

UNIT 3 – STELLA® for Building System Dynamics Models - Continued3.1 review story for full integrated system3.2 review the integration of the 4 models from UNIT 2 as 4 interacting model sectors3.3 explore final model3.4 evaluate strengths and weakness of model

WEDNESDAY NIGHT HOMEWORK (Highly Recommended)1. Explore models from Wednesday afternoon workshop 2. Review next steps in model evolution to be carried out on Thursday3. Review causal loop diagram for next step in model evolution4. Start mapping model structures required for next step in model evolution

ASSIGNMENT FOR REMAINDER OF INSTITUTE (Highly Recommended)1. Develop a story that approximates a system of interest to you2. Define problem to be addressed through model exploration3. Develop causal loop diagram for your system4. Reassess story and problem5. Develop a system model starting with simple sectors and expanding as appropriate6. Tune your system model with data from your system

Instructor/Tutor Availability During START InstituteCraig Forster August 3 to 9 and August 16 to 22: Hotel Room 921 Eric Scharff August 4 to 22: NCAR Room 2011 [[email protected]]Seth McGinnis August 4 to 22: NCAR Room 2011 [[email protected]]

Instructor Availability After START InstituteCraig Forster [email protected] (801) 581-3864


mailto:[email protected]

ResourcesIntroduction to Systems Thinking by High Performance Systems (HPS)

- the 1st few chapters are located in your binder- the complete PDF file and related STELLA® files are on your STELLA® CD from

HPS http://www.hps-inc.com

START Institute, Systems Thinking/Modeling CD with this document and accompanying STELLA® model files.

The system dynamics project at MIT maintains a Web server devoted to issues in system dynamics. This includes the Roadmap introduction to system dynamics that provides a step-by-step, self-taught course in systems thinking/modeling. http://sysdyn.mit.edu/

High Performance Systems web page has a number of resources http://www.hps-inc.com

“Modeling the Environment: Introduction to System Dynamics Modeling of Environmental Systems.” Andrew Ford. Island Press, 1999. Fundamental concepts and citations to important foundation literature.

“Understanding Urban Ecosystems”, Berkowitz, A.R., Nilon, C.H., and K.S. Hollweg, Springer-Verlag, pp. 328-342, 1999.

Acknowledgements & Software License

High Performance Systems generously provided the STELLA® software to the START Institute at reduced pricing. It is important to note that your license is a ‘Student Version’. Although there is no difference between this version and the regular software, you are not entitled to support from High Performance Systems – except as communicated through your instructor. The details of this arrangement are outlined on the HPS web page, http://www.hps-inc.com


http://www.hps-inc.com/

http://sysdyn.mit.edu/

UNIT 1 Background Information

1. Systems Descriptors (from Smith, 2003)

NETWORKS – Every component (part or relationship) is interconnected to every other component in some way. These interconnections can create interdependence and contribute to diversity and complexity. Example – road systems.

BOUNDARIES – The real or abstract separation between a system and its environment or between different levels of scale within systems – systems occur nested within other systems, each linked to the others across scales. Example – city borders

CYCLES – Reoccurring events within or between systems. Cycles allow for the flow of materials and the revitalization and repair of individuals and systems. Examples – seasonal change, economic cycles

FEEDBACK LOOPS – They are chains of events in which an “output” of the event influences the first link at the beginning of the chain, either slowing down or speeding up initiation of the next event in the chain. Examples – urban sprawl, democratic elections

FLOW – The flowing of such things as energy, matter, and information through systems of all sizes of scale. The flow creates an effect. The rates, amounts, and importance of flow-through varies greatly. Examples – water, energy, money, information, power

DEVELOPMENT – Processes at all levels of scale that create growth and generate new forms. Examples – fund-raising, organizational/community infrastructure

DYNAMIC BALANCE – Changes that are continually occurring around an unfixed central point or temporary state of “well-being”. These fluctuations may swing very widely or in small increments around this point. The focus of this phrase is on dynamic, rather than balance. Examples – population response to stresses (lack of food or water), financial market fluctuations

Smith, G.C., 1999. Systems Thinking and Urban Ecosystem Education, in “Understanding Urban Ecosystems”, (eds. Berkowitz, A.R., Nilon, C.H., and K.S. Hollweg), Springer-Verlag, pp. 328-342.

2. System Behaviors A principle use of system dynamics models is to compute future ‘behaviors’ of systems of interest. In many cases you might want to compare the consequences of different policy alternatives by comparing the patterns of dynamic change computed over the simulation period. Ultimately, the absolute value of the parameters graphed cannot match reality. Differences observed between the computed patterns, however, can be instructive. Simple behavioral types are shown in the following figures. Suggest ways that systems you know about might lead to the graphed behaviors.


In developing systems models it is important to identify a “Reference Behavior” that is typically your view of the “Business as Usual” case. Once a model is developed you will want to compute the Reference Behavior then change the model settings (representing policy implementations, technology changes, etc.) to map a suite of alternative futures.


Linear

0 500

1000

Time (years)

Exponential

00

1000

Time (years)

Logistic

0 500

1000

Time (years)

Overshoot and Collapse

0 500

1000

Time (years)

“Business as Usual”

00

Time (years)

1000

PreferredOutcome

50

50

3. Hypothesis TestingMapping the consequences of alternative futures is one form of hypothesis testing where you attempt to anticipate the outcome of a specific change in model settings. If the results don’t match your hypothesis then one or more of the following may have occurred:

- you have not conceptualized the system correctly when building the model- although conceptualize correctly, perhaps there is an error in the model code- you may have discovered an unanticipated consequence

4. Problem DefinitionBuilding a useful model requires a clear statement of the problem to be solved. Building a model of a system without a clear question to be addressed generally leads to unsatisfactory results because the model is not structured for optimal exploration of a specific question.

5. StorytellingUsing icon-based system dynamics model-building software enables users unfamiliar with the underlying mathematics and numerical methods to implement the ‘story’ of their system in a form that can be shared with others. The software enables one to illustrate a complex mental model that can be quantified and explored through hypothesis testing. Comparing different mental models and stories almost always leads to improved understanding of the system of interest.

6. Causal Loop DiagramsA useful step in model building is to construct causal loop (influence) diagrams that map out the key elements of the system story without building model structures. Examples of causal loop diagrams will be discussed in the session.

UNIT 1 - “CO2 Learn” Model Explanation

Problem An isolated metropolitan area is emitting CO2 at a rate that can be expressed as a per capita emissions rate. The per capita emissions rate has been increasing since 1950. If allowed to continue on the current non-linear trajectory, this growth in per capita emissions rate will lead to a substantial increase in CO2 emissions from the metro area. What reductions in per capita emissions rate and/or population growth must be accomplished beginning in 2000 if CO2 emissions are to be maintained at 2000 rates? A simple STELLA® model (CO2_learn.STM on your CD) has been constructed to aid in your strategy explorations.

FactsCity Population

- 1950 = 0.5 million


- grows only through natural growth – migration is assumed negligible- grows at a fixed growth rate from 1950 to 2000- future growth rates can be adjusted to fixed values for specified time increments

Per Capita CO2 Emissions- documented from 1950 to 2000 as shown in graphical input- accounts for all city-caused CO2 emissions internal, or external, to the city- emissions after 2000 are extrapolated assuming “worst case” conditions

Issues to Consider1. What are the reference behaviors of per capita CO2 emissions, total CO2 emissions

and population?2. What CO2 emissions trajectory is needed to solve the problem? 3. What impact does slowing population growth have on solving the problem?3. What causal loop diagram represents the system?4. What assumptions are made to simplify the system?5. How might the model be made more realistic?

Model Explorations A series of model explorations are required to assess the possible consequences of implementing alternative population growth and per capita CO2 emissions strategies. Consider the case where no regulatory limits are placed on CO2 emissions and the goal is to maintain emissions at the 2000 level.

Situation 1: no regulatory limit [USE CO2_learn.STM file]1. The first strategy to consider is to reduce future per capita CO2 emissions rates for

the 50 year period 2000 to 2050 by adjusting the graphical input without changing the natural population growth. Document the different strategies that you tested and report the strategy that achieves the desired goal. Does this seem feasible?

2. The second strategy to consider is to reduce future natural growth rate in order to reduce future populations. Start by assuming that you will maintain per capita CO2

emissions at 2000 levels. Are the necessary reductions in population growth rate feasible? Which strategies are most likely to achieve the desired result (reduced per capita emissions or reduced population growth)?

3. The third strategy is to find a balance between CO2 reductions through a pattern of reduced per capita CO2 emissions and reduced population growth.

UNIT 1 Learning Targets1. Develop abilities in telling stories about systems.2. Learn how to create the causal loop diagrams that underlie system stories. 3. Learn how to use STELLA® to explore strategy options.4. Become familiar with STELLA® input, output and control features.5. Become familiar with STELLA® programming icons (stocks, flows, converters,

information connectors) and model-building strategies6. Enhanced insight regarding possible strategies to pursue for reducing urban CO2

emissions


UNIT 2 – Urban System Stories and Models

Population Model Consider an isolated metropolitan area with surrounding rural region. As the urban center grows, the urban economic output increases and people migrate from the surrounding region. Thus, there are two population stocks to consider – the urban population and the regional population. We want to account for the way that urban birth and death rates might vary (due to improving or declining health) in addition to accounting for in-migration from the surrounding region. In the surrounding region, however, we consider net natural growth in population and out-migration to the nearby metro area. Migration from the regional to the urban community is assumed to be driven largely by differences in economic output between the regional and urban communities. Although this population model is destined to become one sector in a final urban system model, there are insights to be gained by exploring the dynamics between population and economic output in urban vs regional settings. For example, what level of economic development might be required in the surrounding region to reduce migration to a minimum? Should other factors that drive migration be considered in the model (e.g., social networking between migrants living in the metro area and others who are considering the move)?

Population Model: Step-by-Step 1. isolate relevant part of causal loop diagram2. introduce model building levels3. introduce map level icons and manipulation4. open new STELLA® worksheet and build regional population exponential

growth model (see figure below) Regional Population (stock)

- initial population = 2 million (expressed in millions)Regional natural growth rate default = 3.0 % (slider 0% to 4%)Time Period = 50 years

REGION POPULATIONRegion Natural Growth

Region Natural Growth Rate %

STELLA® CodeREGION_POPULATION(t) = REGION_POPULATION(t - dt) +

(Region_Natural_Growth) * dtINIT REGION_POPULATION = 2

INFLOWS:Region_Natural_Growth =

REGION_POPULATION*Region_Natural_Growth_Rate_%*0.01Region_Natural_Growth_Rate_% = 3


5. add user interface slider to control growth rate and graph results6. save model and remember file name [REGION POP.STM on CD]7. experiment briefly, but don’t close model

8. using previous STELLA® file add an urban population model withbirths/deaths (see figure below)Urban Population (stock)

- initial population = 2 million (expressed in millions)Urban Birth Rate default = 4.4% (slider 0 to 6%)Urban Death Rate default = 2.0 % (slider 0 to 4%)

URBAN POPULATIONUrban Births Urban Deaths

Urban Birth Rate %Urban Death Rate %

9. modify user interface with new sliders and run/restore buttons10. save model with NEW filename [URBAN POP.STM on CD]11. experiment briefly, but don’t close model

12. using previous STELLA® file add migration caused by movement from regional population to urbanPer Capita Output (see figure below)

- urban default = 15 monetary units per person (slider 0 to 40 MU)- regional default = 10 monetary units per person (slider 0 to 40)

Migration from region to urban is tied to Econ Output Ratio = (Urban Econ Output -

Regional Econ Output)/Urban Econ Output

Output Ratio Migration Change (%)0.0 0.3000.1 0.4500.2 0.6500.3 0.9000.4 1.2750.5 1.6750.6 2.1000.7 2.5000.8 2.7250.9 2.8751.0 3.025


13. modify user interface with new graphical input and sliders14. save model with NEW file name [MIGRATION POP.STM on CD]15. experiment briefly and close model

URBAN POPULATION

Urban Births Urban Deaths

Urban Birth Rate %Urban Death Rate %

Region Per Capita Econ Output

Migration Rate

Urban Econ Output

Regional EconOutput

Econ Output Ratio

~

Migration Change %

REGION POPULATIONRegion Natural Growth

Region Natural Growth Rate %

Change in Urban Pop

Natural Urban Growth Rate %

Urban per Capita Econ Output

Urban Population

Regional Population Growth

Regional to Urban Migration

Economy Model Population, energy use to CO2 emissions, and CO2 sequestration must be linked to an urban economic output model if we are to explore CO2 emissions reduction strategies for the fully integrated urban system. Urban Economic Output responds directly to changes in the National Economy because the two economies are assumed to be closely linked. Thus, any change in National Economy is transferred directly to a change in Urban Economic Output. Urban Economic Ouput is reduced by the expenditures required to


abate pollution/waste flows. As Urban Economic Output increases, pollution flows are assumed to increase. Expenditures used to abate pollution flows cause reduced pollution flows and reduced economic output which is, in turn, represented as a computed Net Urban Economic Output.

Economy Model: Step-by-Step 1. isolate relevant part of causal loop diagram2. open new model file and build economic output growth model

(see figure below)Time Period = 50 yearsUrban Economic Output (stock)

- initial output = 30 million MUs (expressed in millions)Growth in Urban Economic Output is a ‘biflow’ tied to National Economy

that is, in turn, specified graphically as a function of time.

Time(years)

National Economy(millions of MUs)

0 42505 470010 510015 515020 445025 380030 320035 265040 255045 305050 4100

Change in National Economy is computed using the ‘builtin’ derivative function DERIVN(National Economy,1)/National Economy where

‘1’ specifies the 1st derivative (d[National Econ]/dt).

URBAN ECON OUTPUT

~National Economy

Nat Change Urb Econ

Change Nat Econ

3. add graphical input for National Economy to user interface4. save model and remember filename [URBAN ECONOMY 1.STM on CD]


5. experiment briefly (NOTE: a version with a delayed response to changes in the National Economy is found in URBAN ECONOMY 1 delay.STM )

6. using previous STELLA® Economy file, add pollution abatement component Pollution Flow depends on the pollution technology funds expended

(expressed as a % of Urban Economic Output) Pollution

Technology Expenditures as % Urban Economic

Output

Pollution Flow(Pollution Units)

0 10010 7920 6630 5740 4950 4360 3770 3480 3190 30100 30

Pollution Technology Expenditures as % Urban Economic Output- default = 0 (slider 0 to 100 %)

Pollution Technol Expend as % Urb Econ Output

~Pollution Flow v s %

Urb Econ Output

Pollution Flow

URBAN ECON OUTPUT

~National Economy

Nat Change Urb Econ

Net Urban Econ OutputChange Nat Econ

7. modify user interface with new slider8. save model with NEW filename [URBAN ECONOMY 2.STM on CD]9. experiment briefly and close model

Energy Use to CO2 Emissions Gaseous CO2 emissions to be accounted for include those derived from electricity production, internal combustion engines, heating systems, open burning of waste,


decomposition of vegetation and combustion in industrial processes. The aggregate need for energy across all sectors of the metro area is driven by the Urban Economic Output. Energy use increases as output increases. Energy conservation strategies help to reduce energy required for each unit of economic output. Energy delivered as electricity is distinguished from energy delivered as the direct consequence of combustion processes. This enables changes in the portion of electricity that is produced by technologies that don’t involve burning fossil fuels (e.g., hydropower, renewable, solar, etc.) to be accounted for. This enables us to track the consequences of choices made in the generation of electrical energy. Can energy conservation or shifts in sources of electrical energy lead to significant cost savings while also reducing CO2 emissions?

Energy Use to CO2 Model: Step-by-Step 1. isolate relevant part of causal loop diagram2. open new model file and build economic output growth model

(see figure below)No StocksTime Period = 50 yearsEnergy Conservation %: default = 0 (slider 0 to 100 %)Ratio of Electrical vs Combustion (derived) Energy %: default = 80%

(slider 0 to 100%)Percent of Electricity from Combustion %: default = 75%

(slider 0 to 100%) Energy per output = 1.0 Energy Unit per million MUUrban Economic Output = 40 million MU (expressed as millions)CO2 emissions for energy used

- emissions per unit of direct combustion = 10 CO2 Units per Energy Unit

- emissions factor relating CO2 releases by combustion-derived electricity relative to CO2 releases by direct combustion only = 1.2

- emissions factor relating CO2 releases by non-combustion-derived electricity relative to CO2 releases by direct combustion only = 0.2

3.develop user interface with sliders4. save model with NEW filename [ENERGY TO CO2.STM on CD]5. experiment briefly and close model


CO2 Emissions Fctr f or Combustion Elec

CO2 Emissions Rate

CO2 Emissions Fctrf or NonCombustion Elec

CO2 Emissionsper Unit NonCombustion Elec

Energy Use

Energy Per Urban Output

Energy Conserv ation %

Elec Energy Use

Combust Energy Use

Ratio Elec v s Combust Energy %

Percent Elec f rom Combust

CO2 Emissions per Unit Combustion Elec

CO2 Emissions Elec

CO2 Emissionsper Unit Combust

CO2 Emissions Combust

Urban Econ Output

CO2 Sequestration Model We want to assess how to reduce gaseous urban CO2 emissions resulting from production of electrical energy and combustion of fossil, and other, fuels associated with the urban area. For this model-building exercise we will ignore other possible sources of gaseous CO2; except electricity generated outside the metropolitan area. Thus, we track the growth of total sequestered CO2 (a stock). Meanwhile, we must expect that some portion of the sequestered CO2 will leak back into the atmosphere over short to very long time frames. An exponential decline in sequestered CO2 is assumed with a fixed CO2

Loss Rate. In evaluating tradeoffs in emissions reduction strategies, the cost of sequestration must be accounted for. This simple CO2 sequestration model provides an opportunity to explore a fundamental question. Depending on the possible cost effectiveness of the various sequestration strategies, what expenditures (as a % of Urban Economic Output) will be required to make a significant reduction in urban CO2 emissions? Ultimately, these costs will have to be accounted for in the urban economic model and will lead to a reduced net urban economic output. How do the consequences of reducing CO2 emissions ripple throughout the system?

CO2 Sequestration Model: Step-by-Step 1. isolate relevant part of causal loop diagram2. open new model file and build CO2 sequestration model

(see figure below)Sequestered CO2 (stock): initial value = 0Time Period = 50 yearsCO2 emissions rate = 290 CO2 UnitsUrban Economic Output = 30 million Monetary Units (in millions)Sequestration Expenditures (default values)

- CO2 Units sequestered per million MUs = 5- CO2 sequestration expenditures as % of Urban Econ Output = 0

CO2 loss rate % default = 0.1 %


CO2 SEQUESTEREDsequestering CO2 losing CO2

CO2 Sequestration Rate

CO2 Loss Rate %

CO2 Sequest Expend as % Urb Econ Output

CO2 Seq per Unit Expend

CO2 Seq Expend

Net CO2 Emissions Rate

CO2 Emissions Rate

Urban Economic Output

3.develop user interface with slider4. save model with NEW filename [CO2 SEQ.STM on CD]5. experiment briefly and close model

UNIT 2 Learning Targets1. Develop basic STELLA® model building skills: interface building, icon

representation of stories, hypothesis testing, evaluating linkages, searching for feedback loops, and assessing role of delays.

2. Practice keeping the fully integrated system in mind while building individual model components that are no more complicated than necessary.

3. Enhanced insight regarding the way that urban CO2 emissions are influence by interacting factors in population, economy, energy use, and CO2 sequestration.

UNIT 3 – Integrated Urban System Model

The value of a system dynamics model comes to the fore when relatively simple sub-models are linked to create a complex interaction within an integrated system model. You have explored the individual behaviors of four models. Some of the simulations were ‘interesting’ and provided new insights. Some of the simulations produced the obvious; without providing new insight. It is anticipated, however, that integrating the four will lead to new insights because policies implemented in one part of the system affect other parts of the system. For example, will increased expenditures on pollution abatement lead to increased CO2 emissions because the urban death rate will be reduced as pollution is reduced? Can small advancements in energy conservation, or reduced fossil fuel consumption for electricity production, lead to improved output because the costs of sequestering CO2 are reduced as less CO2 is sequestered? What impact might economic development in the surrounding region have on urban CO2 emissions as a consequence of changes in migration flows? Will abatement of CO2 emissions impact regional population growth? If so, to what degree? What combination of strategies and policies implemented in all sectors might provide an optimal path for minimizing CO2 emissions at reduced cost? The story of the integrated model is the story outlined on


Wednesday afternoon and represented as sub-stories in each of the four models. The instructor’s pre-class version of the integrated causal loop diagram is on your CD as the graphic file integrated causal loop.GIF. The graphic can be viewed by inserting the picture into a Word document.

Clearly there are many questions that the integrated model cannot help us explore. For example, what might be the social and health consequences of various interventions? Would our insights differ if we integrated a more complete set of relationships for and between population growth, transportation choices and the dynamics of urban sprawl? What important feedbacks have been neglected? Should we compute the global warming effect that would result as computed CO2 emissions vary?

The following steps provide a very brief review of the way that the integrated model INTEGRATED.STM on the CD was created by merging the four models developed in UNIT 2. To really understand the steps in the process, you should ask the START instructor or tutors to help you work through the integration process.

Integrated Model: Step-by-Step 1. open a NEW model file and start building the integrated model by copying and

pasting each of the four models into a new model file. On some computers you can have two versions of STELLA running at the

same time. One with the NEW integrated worksheet while the other is used to open and close each of the other models for copying and pasting into the new file. Use the finished integrated model on your CD as a guide for completing the necessary relationships and rebuilding the user interface.

3. Start with the Population Migration model and add the second, undelayed Economic Output model. Before adding any more models, revise

the connections between the two models. - replace the relationships that were previously fixed with default values

by connecting the icons representing the equivalent computed values. For example, the Net Urban Economic Output converter should feed information directly to the Econ Output Ratio. Note that Urban per Capita Econ Output is now computed – not input.

- add a new relationship that represents the fact that population growth leads to growth in service and commercial output by

feeding information from Change in Urban Population to Nat Change in Urban Econ. Enhance the impact of population change by multiplying Change in Urban Population by Population Impact on Urban Economy multiplier of 1.02 within Nat Change Urb Econ.

- add impact of improved Urban Economic Output by causing urban birth rates and death rates to decline with simple graphical inputs

- add impact of Pollution Flow on urban death rate through an Urban Pollution Death Rate Factor implemented with a graphical input


4. Add the Energy Use to CO2 Emissions model and link the computed NetUrban Econ Output of the Economy model to Energy Use in the Energy

model.5. Add the CO2 Sequestration model and link the computed Net CO2 Emissions

Rate of the CO2 Sequestration model to the computed CO2 Emissions Rate of the Energy model. Also, feed Urban Economic Output of the Economy model into CO2 Sequestration Expenditures of the CO2 Sequestration model. Finally, reduce the Net Urban Output by the CO2 sequestration expenditures.

UNIT 3 Learning Targets1. Practice with STELLA® skills will lead to the ability to build more complicated

models.2. Exploring various combinations of ‘policy’ settings in the integrated model reveals

impacts between different parts of the urban system that cannot be explored using only individual model components.


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