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
This model implements the equations proposed by Ketchum in 1954. The rationale behind the concept is that only phytoplankton that grows above a certain rate will not be flushed out of an estuary.
For biological processes:
Pt = Po exp(kt)
Where Pt is the phytoplankton biomass at time t, Po is the initial biomass, and k is the growth rate.
For physical processes:
Pm = Po (1-r)^m
Where Pm is the phytoplankton biomass after m tidal cycles, and r is the exchange ratio (proportion of estuary water which does not return each tidal cycle).
By substitution, and replacing t by m in the first equation, we get:
Pm = Poexp(km).(1-r)^m
For phytoplankton to exist in an estuary, Pm = Po (at least), i.e. 1 / (1-r)^m = exp(km)
ln(1) - m.ln(1-r) = km
-m.ln(1-r) = km
k = -ln(1-r)
Ketchum (1954) Relation between circulation and planktonic populations in estuaries. Ecology 35: 191-200.
In 2005, Ferreira and co-workers showed that this balance has direct implications on biodiversity of estuarine phytoplankton, and discussed how this could be relevant for water management, in particular for the EU Water Framework Directive 60/2000/EC (Ecological Modelling, 187(4) 513-523).
Phytoplankton blooms in estuaries
This model represents a broad overview of the hydrological system of Lake Okeechobee and its surrounding areas of SWFL.
SE-Model (Lake Okeechobee & SWFL Watershed)
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
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
For my school assignment, I created a net showing what the ideal energy system would be like.
Ideal Energy System
Federal University UFRN , Brazil chemical Engineering
Analysis of Environmental Systems solid residuos for northeat brasil
Biogas to Energy 4 Eco city
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 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
About the usage of BPA and BPS
BPA/BPS
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
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
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
Working Draft of a model to simulate the effect on ecosystem service values of planting 10 billion oysters in the Chesapeake Bay by the year 2025.
Clone of Oysters and Ecosystem Services 1.1
Simple (Kind of) food web of the Cane Toad Species. Includes different levels of consumers including predators.
Clone of Cane Toad Food Web
A system dynamics model of a predator-prey lifecycle relationship
Predator-Prey relationship
Clone of HarperCollins - Supply Chain Group Verweij,
The Grate Barrier Reef Food Chain
This model uses simple functions (converters, cosine) to simulate the water balance inside a reservoir.
Clone of Water balance in a reservoir