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GSGS4610_FastFashion_FinalModel

Lanier Ellison

4 months ago

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

GEO4315 Final Project Evgeny Bogopolskiy

Jenya Bogopolskiy

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

Lab 13 Start

Gabe Bowen

232

Crusoe economics test

richardvdlinde

OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

OVERSHOOT GROWTH INTO TURBULENCE

Guy Lakeman

7

MONEY_People, Experts. Knowledge IPN_Model2_Oscillations_0.1.7

Bruce.Beihoff

Green lines: positive relationships

Red lines: negative relationships

Spill

Julian Blanc

Economic Model

Brenden Rawls

ISCI 360 Project - Stage 2

Our model examines the relationship between two straw types (plastic straws and biodegradable straws) and their impact on the environment and economics. Specifically, we are interested in figuring out whether biodegradable straws are a viable solution to plastic straws.

Our model is broken down into three aspects: Social, Environmental and Economic. Color coding is used to differentiate between the different aspects and is explained below:

Turquoise represents the social aspect.

Purple represents the economic aspects.

Green represents the environmental aspects.

Blue represents other crucial stocks and flows in the model that do not necessarily fit into the three aspects above.

In our model, the Canadian population is assumed to increase steadily until a carrying capacity is reached. This can be seen in the graph as the line increases linearly before plateauing indefinitely. We assumed that we will be able to maintain the population at our carrying capacity due to technological advances.

Social Aspect:

The social aspect refers to the impact that awareness of the detrimental costs of straws can have on the usage of straws. The two flows that contribute to awareness are word of mouth (i.e. your friends and family informing you about the effects of straws and influencing you to stop using them) and media coverage (i.e. the media highlights the effects of straws). Both of these flows are dependent on the Canadian population such that 25% of the Canadian population at any time will be impacted by word of mouth or media coverage. (Side note: since word of mouth and media coverage are dependent on the Canadian population, they will plateau when the population does.) This is an arbitrary number but was chosen to show what a change in perspectives of the Canadian population can do. These flows input into an 'awareness of detrimental effects of using plastic straws' stock that reduces the number of plastic straws being used.

Plastic Straws

According to data from the United States individuals usually use 1.6 straws everyday and thus, we have assumed that to be true in Canada as well. Plastic straws start at a base value (due to the previous straw usage) and grow with the Canadian population while subtracting the awareness component of the model.

Environmental Aspect

Since the decomposition of plastic versus paper is significantly different, the amounts that accumulate in the ocean and landfills can be monitored. In addition, the impact on the environment can be monitored. Since plastic straws take longer to decompose, they have a larger impact on wildlife in the ocean than biodegradable straws. Thus, as the plastic straw usage decreases, the amount of habitat loss occurring plateaus. We have also included the aspect of clean-up in which the plastic from the ocean can be moved to the landfill. You will notice that the habitat loss plateaus but does not decrease. This is because we cannot reverse the damage we have done (without additional rigorous clean-up) but can mitigate additional damage. (Please note that clean-up affects only the stock 'Plastic Straws in the ocean' and thus, does not affect the stock 'habitat loss.' Therefore, clean-up will reduce the number of plastic straws in the ocean and indirectly affect the stock 'habitat loss.' However, it will not clean up the plastic straws already impacting 'habitat loss.')

Economic Aspect

The economic aspect monitors the amount of money it takes to make plastic straws versus biodegradable straws and the amount of money the government needs to fund ocean clean-ups. It can be seen that a the usage of plastic straws decreases, the need for clean-up money from the government decreases. However, there is a base level of damage that has already been done by us and thus, larger scale clean-ups will be needed to reverse that. In other words, smaller clean-ups will mitigate the damage we are currently doing but not reverse the damage we have already done. We can also track the cost of making each straw; it can be seen that biodegradable straws are more expensive to make.

However, the energy required to make the straws is less for biodegradable straws than plastic straws. Thus, there are trade-offs for using biodegradable straws.

Although, biodegradable straws are more expensive, they require less energy to make, decompose faster, require less funding for clean-up and impact the wildlife in the ocean to a lesser degree.

Project Stage 2

Eisha Sharda

Regulation of resource allocation to production in response to inventory adequacy and delivery delay. A non-price-mediated resource allocation system. From Sterman JD Business Dynamics p172 Fig 5-27

Availability Balancing Loops

Geoff McDonnell

System Dynamics - Ludhiana

poorani balaji

Implementação do modelo Handy.

Referência:

Motesharrei, S.; Rivas, J.; Kalnay, E. "Human and nature dynamics (HANDY): Modelling inequality and use of resources in the collapse or sustainability of societies". Ecological Economics 101 (2014) 90-102

http://www.sciencedirect.com/science/article/pii/S0921800914000615

HANDY

Daniel Cunha

An initial study of the economics of single use coffee pods.

Nina Coffee Company Model *

Nina Strecker

this model shows the relationship between economic growth and government debt (just the bailout debt) and the mortgage default burden. At the current rates, the debt will never be paid off.

bailout debt, mortgage defaults and economic growth

James Fitzsimons

Overview:

The COVID-19 Outbreak in Burnie Tasmania shows the process of COVID-19 outbreak, the impacts of government policy on both the COVID-19 outbreak and the GDP growth in Burnie.

Assumptions:

We set some variables at fix rates, including the immunity loss rate, recovery rate, death rate, infection rate and case impact rate, as they usually depend on the individual health conditions and social activities.

It should be noticed that we set the rate of recovery, which is 0.7, is higher than that of immunity loss rate, which is 0.5, so, the number of susceptible could be reduced over time.

Adjustments: (please compare the numbers at week 52)

Step 1: Set all the variables at minimum values and simulate

results: Number of Infected – 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.

Step 2: Increase the variables of Health Policy, Quarantine, and Travel Restriction to 0.03, others keep the same as step 1, and simulate

results: Number of Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).

So, the increase of health policy, quarantine and travel restriction will help increase recovery, decrease confirmed cases, decrease death, but also decrease GDP.

Step 3: Increase the variables of Testing Rate to 0.4, others keep the same as step 2, and simulate

results: Number of Infected – 152 (down); Recovered – 243 (down); Cases – 1022 (up); Death – 17,625 (down); GDP – 824 (same).

So, the increase of testing rate will help to increase the confirmed cases.

Step 4: Change GDP Growth Rate to 0.14, Tourism Growth Rate to 0.02, others keep the same as step 3, and simulate

results: Number of Infected – 152 (same); Recovered – 243 (same); Cases – 1022 (same); Death – 17,625 (same); GDP – 6,632 (up).

So, the increase of GDP growth rate and tourism growth rate will helps to improve the GDP in Burnie.

COVID-19 Outbreak in Burnie Tasmania - Lin Ling 523592

Lin Ling

3

Overview:

The model shows the industry competition and relationship between Forrestry and Mountain Bike Trip in Derby, Tasmania. The aim of the simulation is to find a balance between the co-existence of these two industry.

How Does the Model Work?

Both industries will generate incomes. Firstly, income is generated from the sale of timber through logging. In addition, income is also generated from the consumption of mountain bike riders. Regarding to the Forrestry industry, people cut down trees because there is a market demand for timber. The timber is sold for profits. However, the experience of mountain biking tourism is largely affected by the low regeneration rate of trees and the degradation of the environment and landscape due to tree felling. People have better riding experiences when trees are abundant and the scenery is beautiful. People's satisfaction and expectations depend on the scenery and experience. Recommendations of past riders will also impact the tourists amount.

Interesting Insights

The income generated by logging can provide a significant economic contribution to Tasmania, but excessive logging can lead to environmental problems and a reduction in visitors. Excessive logging can lead to a decline in tourism in the mountains, which will affect tourism. Despite the importance of forestry, tourism can also provide a significant economic contribution to Tasmania. The government should find a balance between the two industries while maintaining the number of tourists.

Simulation of Derby Mountain bikes versus logging

nicole

Summary of UNEP ecosystems services CBA 2011 article by Wegner and Pascual

Value and cost benefit analysis

Geoff McDonnell

Fig 4. The Casual Loop Diagram of the Socio-Political and Economic Subsystems

Rony Zhu

State Goverment Fiscal Policy model

Eli Levine

EcoCinco_Deforestation_Land Changes

FU CHUANBAO _

10 months ago

Major Transition Exposition: Big Map of Choices

Robert L. Brown

30

This is a complex model of COVID-19 outbreak in Burnie Tasmania. It show the effect of government policy to local economic and the impact of Covid-19.

Assumptions

Government policy can reduce the number of infected, however also would reduce the economic growth.

Interesting insights

Based on changing the value of government policy, it show that the policy can help to reduce on the number of death and infection.

Covid-19 Out break

Wing Ki Ng

economic inequality

Vo Thi Hoang Anh

Simulation of MTBF with controls

F(t) = 1 - e ^ -λt

Where

• F(t) is the probability of failure

• λ is the failure rate in 1/time unit (1/h, for example)

• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime,
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life

If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life

The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.

Wearout

The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period.

BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

Guy Lakeman

8