Harmful tipping points in the natural world pose some of the gravest threats faced by humanity. Their triggering will severely damage our planet’s life-support systems and threaten the stability of our societies.
In the Summary Report:
• Narrative summary
• Global tipping points infographic
• Key messages
• Key Recommendations
Executive summary
• Section 1
• Section 2
• Section 3
• Section 4
This report is for all those concerned with tackling escalating Earth system change and mobilising transformative social change to alter that trajectory, achieve sustainability and promote social justice.
In this section:
• Foreword
• Introduction
• Key Concepts
• Approach
• References
Considers Earth system tipping points. These are reviewed and assessed across the three major domains of the cryosphere, biosphere and circulation of the oceans and atmosphere. We then consider the interactions and potential cascades of Earth system tipping points, followed by an assessment of early warning signals for Earth system tipping points.
Considers tipping point impacts. First we look at the human impacts of Earth system tipping points, then the potential couplings to negative tipping points in human systems. Next we assess the potential for cascading and compounding systemic risk, before considering the potential for early warning of impact tipping points.
Considers how to govern Earth system tipping points and their associated risks. We look at governance of mitigation, prevention and stabilisation then we focus on governance of impacts, including adaptation, vulnerability and loss and damage. Finally, we assess the need for knowledge generation at the science-policy interface.
Focuses on positive tipping points in technology, the economy and society. It provides a framework for understanding and acting on positive tipping points. We highlight illustrative case studies across energy, food and transport and mobility systems, with a focus on demand-side solutions (which have previously received limited attention).
In smart homes, information and communication technologies (ICTs) are distributed throughout rooms, devices and systems (lighting, heating, energy management); they relay information to users and feed back users’ or automated commands to manage the domestic environment (Wilson et al., 2020). Smart homes and smart devices play an important role in demand-side mitigation options: they are the end-use node of the smart energy system that allows consumers to improve the use of energy as well as utilities to respond to real-time flows of information on energy demand fed back by smart metres from millions of homes (Hargreaves and Wilson, 2017; Baydia et al., 2021). Thanks to digital devices and technologies, measures aimed at influencing habits through information provision and feedback on energy consumption can in theory result in substantial household energy savings (Jensen et al., 2016; Malmodin and Coroama, 2016; Nilsson et al., 2018). Notwithstanding this high potential, demonstrated energy savings from the limited number of studies on this topic appears to be relatively small but significant (BIT, 2017, Khanna et al., 2022). In the UK, for instance, data from a large-scale trial of smart metres and in-home displays in the UK demonstrated around three per cent energy reductions on average (AECOM, 2011). Potential savings (or ‘shaving’) during peak times can be more pronounced (Pratt and Erickson, 2020), particularly if linked in-home displays communicating usage and cost information to end-users enable utilities to charge for electricity at its marginal cost, providing a price signal to shift or curtail demand when supply is expensive or in short supply (Srivastava et al., 2018). Yet, households’ appetite or capacity for reducing energy bills in response to information feedback and price incentives appears limited, and interest in information and price signals rapidly wears off and is subject to rebound effects that offset demand reductions (Azarova et al., 2020).
Embedding digital technologies and devices in homes turns them from ‘passive’ (i.e. non-responsive to network needs) end-user nodes in hub-to-spoke energy networks to ‘active’ (responsive, flexible and integrated) nodes in distributed energy networks. This switch supports the achievement of PTPs in the energy system, as it integrates significantly more renewable energy and faces increased challenges due to widespread electrification of all sectors and activities. This shift is enabled by digitalisation in the domestic environment, with emerging potential for AI applications to help accelerate positive trends (towards informed energy management without required user interventions, and control over distributed end-use, storage and generation resources throughout the building stock).