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Título del libro: Global Surface Temperature Model Using Coupled Sugeno Type Fuzzy Inference Systems And Neural Network Optimization
Título del capítulo: Stabilizing global temperature through a fuzzy control on CO2 emissions

Autores UNAM:
CARLOS GAY Y GARCIA; BERNARDO ADOLFO BASTIEN OLVERA;
Autores externos:

Idioma:
Inglés
Año de publicación:
2015
Palabras clave:

Atmospheric temperature; Carbon dioxide; Chemical activation; Climate models; Economics; Fuzzy control; Temperature control; Carbon emissions; Carbon sequestration; Common ground; Current emissions; Economic growths; Global temperatures; Reduction of emissions; Surface temperatures; Climate change


Resumen:

In this research, we generated a fuzzy control of carbon emissions that acts increasing or decreasing the representative concentration pathway emissions proposed by the IPCC, in order to obtain a CO2 path that would stabilize the global average surface temperature to a desired level. We used a simple linear climate model that is driven primary by the Carbon emissions. We made simulations under the four RCPs activating the control at different times, which give us a broad knowledge on when is possible to stabilize the temperature, based in the current emissions path. We conclude that taking action earlier (via fuzzy control) will lead not only to reach stabilization, but also, in some cases, to have economic growth allowing to increase emissions at some points in time. Activating the control very late will initiate an oscillation on temperature which will include not only a reduction of emissions but also a necessary anthropogenic net carbon sequestration. This instrument is a common ground where specialists in diverse areas of climate change could contribute in order to set the parameters that we should explore and simulate so that the we can make the best decisions.


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