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+ Simulation of
Global Warming
in the Continental
United States
Using AgentBased Modeling
By Marika Lohmus
Computer Systems Lab 2008-2009
TJSTAR Presentation
+
Purpose

What is the relationship
between population and
global warming?

Gaia Hypothesis


Does it apply to humans?
Population Size
Greenhouse Gases
Negative Feedback loop

Is there an equilibrium?
Temperature
+
Background

Sea levels predicted to rise by 18 – 59 cm by 2100 (IPCC,
2007)

Average surface temperature predicted to increase by 1.1 –
6.4°C (EPA, 2007)

From 1750 to 2005, greenhouse gases have increased (IPCC,
2007)




CO2 by 36%
CH4 by 148%
N2O by 18%
U.S. greenhouse gas emissions have increased by 17% from
1990 to 2007 (IPCC, 2009)
+
Background – CO2
•CO2
levels will keep on rising (U.S. Climate Change Science Program,
2007)
•Currently 387 ppmv
•Estimated increase from 541 to 963 ppmv by 2100 (Prentice, et al., 2001)
+
Methodology


Modeling environment: NetLogo

Simulation of natural and social phenomena

Uri Wilensky 1999

Written in Java for all major platforms
Components

Interface

Procedures

System Dynamics
+
Methodology
Agents and Patches



Agents (People)
 Salary
 Money
Patches (Land)
 Temperature
 Elevation
 Death Rate
Cities
 Average Salary
 Poverty Percent
 Name



Changeable Variables

Birth Rate

D(Death Rate)

Emissions Per Person
Dependent Variables

Total Emissions

Earth Temperature
System Dynamics

Atmospheric Absorption
Coefficient
+
Methodology
System Dynamics

Runs parallel with Interface

Atmospheric Absorption Coefficient (AAC)


Greenhouse Gas Effect (Kiehl & Trenberth, 1997)

60% H2O

26% CO2

8% O3

6% CH4 + N2O
AAC of .25628 through trial & error

Mean Earth Temperature: 287.89 K (GISS, 2006)

60% (.153768) remains constant
+
Methodology
Other Data Used

Birth Rate: .1418 / 10000
people per year (CIA, 2009)

Death Rate: .0827 / 10000
people per year (CIA, 2009)

U.S. Greenhouse Gas
Emissions in 2007: 7150.1
Tg CO2 Eq. (IPCC, 2009)


17% increase from 1990
Elevation Map from
Continental Divide project
(Wilensky, 2007)
+
Methodology
Creation of People and Moving

City Data


Percentage under the poverty line

$15,800 for a 2.5 person average family (US Census, 2000)

50% below and 50% above average annual salary
Move Method

Temperature > 25 C

Diameter of money/10000

Random spot, if favorable, move

Random number generator: move 1
+ Run With Current Data
Birth rate of .1418, d(death rate) of 101,
emissions per person of 1
+
Variables
D(death rate)

Higher temperatures mean higher death rates (IPCC, 2007)



What is the connection?
High d(death rate)

Technological improvements

Immunity to diseases
Low d(death rate)

Disaster hits

Chaos due to increasing population

New diseases and epidemics
D(Death Rate)
+
Turtles
Temperature
1
4371.685863
287.8327252
21
4544.982732
288.670742
41
4609.949897
288.9962363
61
4670.43662
289.2661846
81
4660.525752
289.2079459
101
4645.692383
289.1419626
121
4671.405155
289.2751383
141
4654.712342
289.216479
161
4670.492981
289.2954364
181
4721.683784
289.4841187
201
4679.209357
289.3124067
D(Death Rate) Data
•Clear
increase
•Dampened
•Better
•Chaos
Oscillation
technology = more people
due to population increase?
(IPCC, 2007)
+
Turtles
Temperature
Birth Rate
Birth Rate Data
•Clear
3819.053231
285.3336871
0
4478.013582
288.3251024
0.1
5077.232392
291.0630246
0.2
5864.339263
293.928724
0.3
6480.288649
296.6730886
0.4
7100.415135
299.564913
0.5
increase in both temperature
and number of turtles
•NOTE: D(Death
Rate) = 101
meaning that the population size
increases due to a slow increase in
the death rate
+
Emissions Data
•The
40% of AAC is not entirely
contributed to by humans
•Cold
weather – more deaths
•30%
of current emissions optimal
+
Emissions
•Cap
on temperature?
•People
die quickly at high
emissions
•Inverse
relationship with turtles
+
Conclusion
• Sudden drop in
temperature and population
at first, followed by a sharp
increase
•Shock value
•Adaptation
•Model does not show a system as change out of equilibrium
(Janssen, 1998)
•Humans have learned to adapt to changes
•Oscillations seem to level off
•Emissions kept at current level: Scenarios not too bleak
•From 1990, 1.3% annual increase in emissions (EPA, 2009)
+
Bibliography
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Software, 22, 649-655.
2. EPA (2009). Inventory of U.S. Greenhouse Gas Emissions and Sinks . Washington, DC: U.S.
Environmental Protection Agency.
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& Deangelis, D. (2005). Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from
Ecology. Science, 310(5750), 987-991.
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Third Assessment Report of the Intergovernmental Panel on Climate Change. New York: Cambridge
University Press.
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Press.
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University Press.
8. Janssen, M. (1998). Use of complex adaptive systems for modeling global change. Ecosystems, 1,
457-463.
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10.NASA GISS Surface Temperature Analysis. (n.d.). Retrieved May 27, 2009, from
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http://www.weatherbase.com