In Chile,  60% of its population are exposed to levels of Particulate Matter (PM) above international standards . Air Pollution is causing  4,000 premature deaths per year , including health costs over US$8 billion.    The System Dynamics Causal Loop Diagram developed herein shows an initial study o
In Chile, 60% of its population are exposed to levels of Particulate Matter (PM) above international standards. Air Pollution is causing 4,000 premature deaths per year, including health costs over US$8 billion.

The System Dynamics Causal Loop Diagram developed herein shows an initial study of the dynamics among the variables that influences the accumulation of PM in the air, in particular the case of Temuco, in the South of Chile. In Temuco, 97% of the PM inventories comes from the combustion of low quality firewood, which in turns is being burned due to its low price and cultural habits/tradition.
This model implements the one-dimensional version of the advection-dispersion equation for an estuary.  It develops the basic 1D model by simulating the mass of salt rather than the concentration. This makes it straightforward to deal with multiple boxes of different volume.  The equation is:  dS/dt
This model implements the one-dimensional version of the advection-dispersion equation for an estuary.

It develops the basic 1D model by simulating the mass of salt rather than the concentration. This makes it straightforward to deal with multiple boxes of different volume.

The equation is:

dS/dt = (1/A)d(QS)/dx - (1/A)d(EA)/dx(dS/dx) (Eq. 1)

Where S: salinity (or any other constituent such as chlorophyll or dissolved oxygen), (e.g. kg m-3); t: time (s); A: cross-sectional area (m2); Q: river flow (m3 s-1); x: length of box (m); E: dispersion coefficient (m2 s-1).

For a given length delta x, Adx = V, the box volume. For a set value of Q, the equation becomes:

VdS/dt = QdS - (d(EA)/dx) dS (Eq. 2)

EA/x, i.e. (m2 X m2) / (m s) = E(b), the bulk dispersion coefficient, units in m3 s-1, i.e. a flow, equivalent to Q

At steady state, dS/dt = 0, therefore we can rewrite Eq. 2 for one estuarine box as:

Q(Sr-Se)=E(b)r,e(Sr-Se)-E(b)e,s(Se-Ss) (Eq. 3)

Where Sr: river salinity (=0), Se: mean estuary salinity; Ss: mean ocean salinity

E(b)r,e: dispersion coefficient between river and estuary, and E(b)e,s: dispersion coefficient between the estuary and ocean.

By definition the value of E(b)r,e is zero, otherwise we are not at the head (upstream limit of salt intrusion) of the estuary. Likewise Sr is zero, otherwise we're not in the river. Therefore:

QSe=E(b)e,s(Se-Ss) (Eq. 4)

At steady state

E(b)e,s = QSe/(Se-Ss) (Eq 5)

The longitudinal dispersion simulates the turbulent mixiing of water in the estuary during flood and ebb, which supplies salt water to the estuary on the flood tide, and make the sea a little more brackish on the ebb.

You can use the upper slider to turn off dispersion (set to zero), and see that if the tidal wave did not mix with the estuary water due to turbulence, the estuary would quickly become a freshwater system.

The lower slider allows you to simulate a variable river flow, and understand how dispersion compensates for changes in freshwater input.
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.  We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

This model uses simple functions (converters, cosine) to simulate the water balance inside a reservoir.
This model uses simple functions (converters, cosine) to simulate the water balance inside a reservoir.
Simple mass balance model for lakes, based on the Vollenweider equation:  dMw/dt = Min - sMw - Mout  The model was first used in the 1960s to determine the phosphorus concentration in lakes and reservoirs, for eutrophication assessment.
Simple mass balance model for lakes, based on the Vollenweider equation:

dMw/dt = Min - sMw - Mout

The model was first used in the 1960s to determine the phosphorus concentration in lakes and reservoirs, for eutrophication assessment.
Simple tragedy ​of the commons behavior model.
Simple tragedy ​of the commons behavior model.
Simple (Kind of) food web of the Cane Toad Species. Includes different levels of consumers including predators.
Simple (Kind of) food web of the Cane Toad Species. Includes different levels of consumers including predators.
Simple mass balance model for lakes, based on the Vollenweider equation:  dMw/dt = Min - sMw - Mout  The model was first used in the 1960s to determine the phosphorus concentration in lakes and reservoirs, for eutrophication assessment.
Simple mass balance model for lakes, based on the Vollenweider equation:

dMw/dt = Min - sMw - Mout

The model was first used in the 1960s to determine the phosphorus concentration in lakes and reservoirs, for eutrophication assessment.
 This stock and flow diagram is a working draft of a conceptual model of a dune-lake system in the Northland region of New Zealand.

This stock and flow diagram is a working draft of a conceptual model of a dune-lake system in the Northland region of New Zealand.

In Chile,  60% of its population are exposed to levels of Particulate Matter (PM) above international standards . Air Pollution is causing  4,000 premature deaths per year , including health costs over US$8 billion.    The System Dynamics Causal Loop Diagram developed herein shows an initial study o
In Chile, 60% of its population are exposed to levels of Particulate Matter (PM) above international standards. Air Pollution is causing 4,000 premature deaths per year, including health costs over US$8 billion.

The System Dynamics Causal Loop Diagram developed herein shows an initial study of the dynamics among the variables that influences the accumulation of PM in the air, in particular the case of Temuco, in the South of Chile. In Temuco, 97% of the PM inventories comes from the combustion of low quality firewood, which in turns is being burned due to its low price and cultural habits/tradition.
This model explains the primary production of phytoplankton, forced by light and nutrients over a year period.
This model explains the primary production of phytoplankton, forced by light and nutrients over a year period.


 This model describes nitrogen cycling in a dune-lake system in the Northland region of New Zealand. It is based on stock and flow diagrams where each orange oval represents an input, while each blue box represents a stock. Each arrow represents a flow. Flows reduce the stock at which they start and

This model describes nitrogen cycling in a dune-lake system in the Northland region of New Zealand. It is based on stock and flow diagrams where each orange oval represents an input, while each blue box represents a stock. Each arrow represents a flow. Flows reduce the stock at which they start and add to the stock at which they end.

Interactions between wolves and livestock depending on abundance
Interactions between wolves and livestock depending on abundance
Diagrams of theories of control of destiny at multiple scales as fundamental causes of social determinants of health from  Whitehead 2016 article  in Health and Place
Diagrams of theories of control of destiny at multiple scales as fundamental causes of social determinants of health from Whitehead 2016 article in Health and Place
Just recently, there was a huge problem that ended about C8, a deadly chemical, that was poured into lakes and rivers by DuPont, a company that sold nylon. This chemical caused a huge consensus, many birth defects, and cows with green insides spraying blood from many places.
Just recently, there was a huge problem that ended about C8, a deadly chemical, that was poured into lakes and rivers by DuPont, a company that sold nylon. This chemical caused a huge consensus, many birth defects, and cows with green insides spraying blood from many places.
Marine plastic is rapidly increasing due to increasing production and use of plastic in all economic activities, short use times and long life times of plastic, and large mismanagement of plastic waste. With this, the threat plastic poses to the marine biosphere is also increasing and will continue
Marine plastic is rapidly increasing due to increasing production and use of plastic in all economic activities, short use times and long life times of plastic, and large mismanagement of plastic waste. With this, the threat plastic poses to the marine biosphere is also increasing and will continue to increase over a long time into the future. Risk knowledge is limited and risk perception and awareness are not resulting in significant mitigation efforts. The case study will aim at modeling the use and life cycles of plastic and the transport paths that lead to plastic entering the ocean. The models will be used to simulate possible futures based on a scenario approach. The results of these efforts will be visualized with the goal to increase risk awareness.