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Charting pathways to climate change mitigation in a coupled socio-climate model
- Source :
- PLoS Computational Biology, Vol 15, Iss 6, p e1007000 (2019), PLoS Computational Biology
- Publication Year :
- 2019
- Publisher :
- Public Library of Science (PLoS), 2019.
-
Abstract
- Geophysical models of climate change are becoming increasingly sophisticated, yet less effort is devoted to modelling the human systems causing climate change and how the two systems are coupled. Here, we develop a simple socio-climate model by coupling an Earth system model to a social dynamics model. We treat social processes endogenously—emerging from rules governing how individuals learn socially and how social norms develop—as well as being influenced by climate change and mitigation costs. Our goal is to gain qualitative insights into scenarios of potential socio-climate dynamics and to illustrate how such models can generate new research questions. We find that the social learning rate is strongly influential, to the point that variation of its value within empirically plausible ranges changes the peak global temperature anomaly by more than 1°C. Conversely, social norms reinforce majority behaviour and therefore may not provide help when we most need it because they suppress the early spread of mitigative behaviour. Finally, exploring the model’s parameter space for mitigation cost and social learning suggests optimal intervention pathways for climate change mitigation. We find that prioritising an increase in social learning as a first step, followed by a reduction in mitigation costs provides the most efficient route to a reduced peak temperature anomaly. We conclude that socio-climate models should be included in the ensemble of models used to project climate change.<br />Author summary The importance of anthropogenic CO2 emissions on climate change trajectories is widely acknowledged. However, geophysical climate models rarely account for dynamic human behaviour, which determines the emissions trajectory, and is itself affected by the climate system. Here, using a coupled socio-climate model, we show how social processes can strongly alter climate trajectories and we suggest optimal intervention pathways based on the model projections. Steps to increase social learning surrounding climate change should initially be prioritised for maximum impact, making a subsequent reduction in mitigation costs more effective. Policymakers will benefit from a better understanding of how social and climate processes interact, which can be provided by socio-climate models.
- Subjects :
- 0301 basic medicine
Atmospheric Science
Social Sciences
Conservation of Energy Resources
Global Warming
0302 clinical medicine
Learning and Memory
11. Sustainability
Economics
Psychology
Social Change
Biology (General)
Climatology
Ecology
Geography
Simulation and Modeling
Physics
Social dynamics
Chemistry
Geophysics
Computational Theory and Mathematics
Modeling and Simulation
Physical Sciences
Research Article
QH301-705.5
Climate Change
Climate change
Research and Analysis Methods
03 medical and health sciences
Cellular and Molecular Neuroscience
Greenhouse Gases
Genetics
Learning
Environmental Chemistry
Humans
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Behavior
Global warming
Social change
Ecology and Environmental Sciences
Cognitive Psychology
Chemical Compounds
Biology and Life Sciences
Computational Biology
Environmental economics
Carbon Dioxide
Models, Theoretical
Social learning
Earth system science
030104 developmental biology
Climate change mitigation
Physical Geography
13. Climate action
Atmospheric Chemistry
Earth Sciences
Cognitive Science
Climate model
Anthropogenic Climate Change
030217 neurology & neurosurgery
Neuroscience
Earth Systems
Climate Modeling
Subjects
Details
- Language :
- English
- ISSN :
- 15537358
- Volume :
- 15
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- PLoS Computational Biology
- Accession number :
- edsair.doi.dedup.....0f41cbb82e3c64bad822a854cb88c04d