Carbon Model for sustainability
A storytelling of the nitrogen cycle.
Met Nederlandse teksten
Nitrogen Cycle - Nederlands
Simple model to illustrate oyster growth based on primary production of Phytoplankton as a state variable, forced by light and nutrients, running for a yearly period.
Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:
Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))
Pmax: Maximum production (d-1)
I: Light energy at depth of interest (uE m-2 s-1)
Iopt: Light energy at which Pmax occurs (uE m-2 s-1)
S: Nutrient concentration (umol N L-1)
Ks: Half saturation constant for nutrient (umol N L-1).
Further developments:
- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.
- Light limited by the concentration of phytoplankton.
- Temperature effect on phytoplankton and Oyster growth.
Clone of Clone of Clone of micro algae , biogas , bioelectrcidades
Electrical Vehicles Simulation
The Streeter-Phelps oxygen dynamics model was originally developed in 1925, almost a century ago.
Play
You can explore the model by hitting the simulate button, and you can use the three sliders below to (i) switch the spill on or off (1 or 0); (ii) define the day when the spill occurs (0 to 15); and (iii) make the model use a constant water temperature (20oC) or a (pre-defined) variable one.
A variable temperature affects oxygen saturation, and therefore also the oxygen deficit and oxygen concentration.
Every model element shows an = sign when you hover over it, and if you click the sign you can view the underlying equation.
If you want to edit the model, you need to create an account in InsightMaker and then clone the model and adapt it to your needs.
Study
Below is a detailed explanation of the model concept.
The model calculates the oxygen deficit (D), defined as Cs-C, where Cs is the saturation concentration of dissolved oxygen (based on temperature, and salinity if applicable), and C is the dissolved oxygen concentration.
Since D = Cs-C, it follows that:
dD/dt = -dC/dt
The rate of change of oxygen concentration with time (dC/dt) depends on two factors, organic decomposition and aeration.
dC/dt = Ka.D - Kd.L
The first term on the right side of the equation is aeration (which adds oxygen to the water), calculated by means of the temperature-dependent aeration parameter Ka.
Ka is also a function of Kr, which depends on wind speed (U) and water depth (z).
The sink term represents oxygen consumption through mineralization (bacterial decomposition) of organic matter.
The organic load L decays in time (or in space, e.g. along a river) according to a first order equation, i.e. dL/dt = -Kd.L
This equation can be integrated to yield L = Lo.exp(Kd.t), where Kd is the decay constant.
Streeter-Phelps Oxygen Model
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.
Ecocity model , Joanna
http://www.divaportal.se/smash/get/diva2:631144/FULLTEXT01.pdf
Clone of mass balace of bioreactor ofVollenweider model
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.
Clone of Air Pollution Dynamics - Firewood Combustion
Primitives for Watershed modeling project. Click Clone Insight at the top right to make a copy that you can edit.
The converter in this file contains precipitation for Phoenix only.
Primitives for Rainwater Harvesting -Phoenix ENVS 270 F21
Clone of moose-wolf exercise 2014.01.07
moose-wolf exercise 2014.01.07
Primitives for Watershed modeling project. Click Clone Insight at the top right to make a copy that you can edit.
The converter in this file contains precipitation for Phoenix only.
Rainwater Harvesting
Simple model to illustrate Steele's equation for primary production of phytoplankton.
The equation is:
Ppot = Pmax I/Iopt exp(1-I/Iopt)
Where:
Ppot: Potential production (e.g. d-1, or mg C m-2 d-1)
Pmax: Maximum production (same units as Ppot)
I: Light energy at depth of interest (e.g. uE m-2 s-1)
Iopt: Light energy at which Pmax occurs (same units as I)
The model contains no state variables, just illustrates the rate of production, by making the value of I equal to the timestep (in days). Move the slider to the left for more pronounced photoinhibition, to the right for photosaturation.
Clone of Phyto 1 - PI curve for phytoplankton
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.
Clone of Air Pollution Dynamics - Firewood Combustion
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.
Clone of Air Pollution Dynamics - Firewood Combustion
Simple model to illustrate oyster growth based on primary production of Phytoplankton as a state variable, forced by light and nutrients, running for a yearly period.
Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:
Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))
Pmax: Maximum production (d-1)
I: Light energy at depth of interest (uE m-2 s-1)
Iopt: Light energy at which Pmax occurs (uE m-2 s-1)
S: Nutrient concentration (umol N L-1)
Ks: Half saturation constant for nutrient (umol N L-1).
Further developments:
- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.
- Light limited by the concentration of phytoplankton.
- Temperature effect on phytoplankton and Oyster growth.
Clone of Clone of micro algae , biogas , bioelectrcidades
The time-variable solution to a step-function change in inflow concentration for an ideal, completely mixed lake.
Clone of ENVE 431 - HW5 - PROBLEM 7
Clone of HarperCollins - Supply Chain Group Verweij,
Simple model to illustrate oyster growth based on primary production of Phytoplankton as a state variable, forced by light and nutrients, running for a yearly period.
Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:
Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))
Pmax: Maximum production (d-1)
I: Light energy at depth of interest (uE m-2 s-1)
Iopt: Light energy at which Pmax occurs (uE m-2 s-1)
S: Nutrient concentration (umol N L-1)
Ks: Half saturation constant for nutrient (umol N L-1).
Further developments:
- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.
- Light limited by the concentration of phytoplankton.
- Temperature effect on phytoplankton and Oyster growth.
Clone of micro algae , biogas , bioelectrcidades
This story contains a conceptual model of phosphorus cycling in a dune-lake system in the Northland region of New Zealand. It is based on the concept of a stock and flow diagram. Each orange ellipse represents an input, while each blue box represents a stock. Each arrow represents a flow. A flow involves a loss from the stock at which it starts and an addition to the stock at which it ends.
Story of phosphorus dynamics in a shallow lake
FORCED GROWTH GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION
BEWARE pushing increased growth blows the system!
(governments are trying to push growth on already unstable systems !)
The existing global capitalistic growth paradigm is totally flawed
The chaotic turbulence is the result of the concept and flawed strategy 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)
FORCED GROWTH INTO TURBULENCE
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.
Clone of Air Pollution Dynamics - Firewood Combustion
This model describes the flow of energy from generation to consumption for neighborhoods in the metro Atlanta area. It also calculates the cost of energy production and the number of years it will take to recover that cost.
Clone of Microgrid with storage
Forcings and feedbacks based on Tom Fiddaman, James Hansen and other feedback and cycle diagrams
Climate change dynamics