Cargando…
Mitigating Portland Cement CO(2) Emissions Using Alkali-Activated Materials: System Dynamics Model
While alkali-activated materials (AAMs) have been hailed as a very promising solution to mitigate colossal CO(2) emissions from world portland cement production, there is lack of robust models that can demonstrate this claim. This paper pioneers a novel system dynamics model that captures the system...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589922/ https://www.ncbi.nlm.nih.gov/pubmed/33096714 http://dx.doi.org/10.3390/ma13204685 |
Sumario: | While alkali-activated materials (AAMs) have been hailed as a very promising solution to mitigate colossal CO(2) emissions from world portland cement production, there is lack of robust models that can demonstrate this claim. This paper pioneers a novel system dynamics model that captures the system complexity of this problem and addresses it in a holistic manner. This paper reports on this object-oriented modeling paradigm to develop a cogent prognostic model for predicting CO(2) emissions from cement production. The model accounts for the type of AAM precursor and activator, the service life of concrete structures, carbonation of concrete, AAM market share, and policy implementation period. Using the new model developed in this study, strategies for reducing CO(2) emissions from cement production have been identified, and future challenges facing wider AAM implementation have been outlined. The novelty of the model consists in its ability to consider the CO(2) emission problem as a system of systems, treating it in a holistic manner, and allowing the user to test diverse policy scenarios, with inherent flexibility and modular architecture. The practical relevance of the model is that it facilitates the decision-making process and policy making regarding the use of AAMs to mitigate CO(2) emissions from cement production at low computational cost. |
---|