The current crop of models assessed by the Intergovernmental Panel on Climate Change (IPCC) to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, especially beyond the purely economic consequences of climate change. These climate-driven changes in human activities are critical to understanding the co-evolution of the climate and human systems. Earth System Models (ESMs) that represent the climate system and Integrated Assessment Models (IAMs) that represent the human system are typically separate, with assumptions that create coherency coordinated through RCPs and SSPs in ScenarioMIP, the core scenario analysis protocol. This divide limits understanding of climate-human feedback. An alternative aggregated approach, which couples human and natural systems (CHANS) such as the one used to build the Feedback-based knowledge Repository for IntegrateD Assessments “FRIDA” v2.1 IAM documented here, integrates climate and human systems into a unified global model, prioritizing feedback dynamics while maintaining interpretability. FRIDA represents the Earth's radiation balance, carbon cycle, and relevant portions of the water cycle alongside human demographics, economics, agriculture, and human energy use. Built using the System Dynamics method, it contains seven interconnected modules. Each subsystem is calibrated to data and validated to ensure structurally appropriate behaviour representation. FRIDA demonstrates that an aggregate, feedback-driven modelling approach, capturing CHANS interconnections with rigorous measurements of uncertainty, is possible. It complements conventional IAMs by highlighting missing feedback structures that affect future projections. Our work with FRIDA suggests SSP1-Baseline, SSP2-Baseline, and SSP5-Baseline are all overly optimistic on the prospects for future economic growth due to these feedbacks, while SSP3-Baseline and SSP4-Baseline, the SSPs with the highest challenges to adaptation, align more closely with our results. Future work will further refine climate impact representations, energy modelling, policy scenario creation, and stakeholder engagement for informed policymaking.

Ensuring sustainable management and an adequate supply of freshwater resources is a growing challenge around the world. Even in historically water abundant regions climate change together with population growth and economic development are processes that are expected to contribute to an increase in permanent and seasonal water scarcity in the coming decades. Previous studies have shown how policies to address water scarcity often fail to deliver lasting improvements because they do not account for how these processes influence, and are influenced by, human-water interactions shaping water supply and demand. Despite significant progress in recent years, place-specific understanding of the mechanisms behind human-water feedbacks remain limited, particularly in historically water abundant regions. To this end, we here present a Swedish case study where we, by use of a qualitative system dynamics approach, explore how human-water interactions have contributed to seasonal water scarcity at the local-to-regional scale. Our results suggest that the current approach to address water scarcity by inter-basin water transports contributes to increasing demand by creating a gap between the perceived and actual state of water resources among consumers. This has resulted in escalating water use and put the region in a state of systemic lock-in where demand-regulating policies are mitigated by increases in water use enabled by water transports. We discuss a combination of information and economic policy instruments to combat water scarcity, and we propose the use of quantitative simulation methods to further assess these strategies in future studies.

The transition to a bio-based economy is expected to deliver substantial environmental and economic benefits. However, bio-based production systems still come with significant environmental challenges, and there is a need for assessment methods that are adapted for the specific characteristics of these systems. In this review, we investigated how the environmental aspects of bio-based production systems differ from those of non-renewable systems, what requirements these differences impose when assessing their sustainability, and to what extent mainstream assessment methods fulfil these requirements. One unique characteristic of bio-based production is the need to maintain the regenerative capacity of the system. The necessary conditions for maintaining regenerative capacity are often provided through direct or indirect interactions between the production system and surrounding “supporting” systems. Thus, in the environmental assessment, impact categories affected in both the primary production system and the supporting systems need to be included, and impact models tailored to the specific context of the study should be used. Development in this direction requires efforts to broaden the system boundaries of conventional environmental assessments, to increase the level of spatial and temporal differentiation, and to improve our understanding of how local uniqueness and temporal dynamics affect the performance of the investigated system.

Feedbacks from the climate to other components of the coupled human-Earth system are expected to strongly influence the co-evolution of human society and its environment. Representing these feedback loops between climate and society, via the Earth system's response to human activities and the subsequent effect back onto social systems, is essential in order to fully explore the dynamics of the coupled system. However, focus on these feedbacks has traditionally been limited, or excluded, in prior Integrated Assessment Models (IAMs) and IAM-based modelling protocols. This limits the understanding of the effects of climate change and the response of the overall system to future emissions scenarios and policies. The new IAM Feedback-based knowledge Repository for IntegrateD Assessments version 2.1 (FRIDAv2.1), documented and explored within this paper collection, seeks to address this by internalising the feedbacks between subcomponents of the human-Earth system. Within this new IAM, these connections are therefore a key part of the structure, and are documented and discussed here. FRIDA represents these climate-to-society feedbacks, conceptualised as climate impacts, through global impact functions. Where possible, they are based on estimates from existing literature, reframed as functions of global climate variables to facilitate their representation within FRIDA. Other impact channels, with insufficient background literature to inform their structure and parameter values, are incorporated via the internal calibration of the IAM. Since the systematic representation of climate damages within an IAM is a relatively novel endeavour, the approach is constrained by literature limitations and necessary simplifications. In addition, the high level of abstraction of the FRIDA model imposes limits on the set of impacts which can reasonably be implemented, and the level of process detail amongst those included. Nevertheless, FRIDA's endogenous representation of climate feedbacks to human and natural systems enables valuable insights and intuition building on an underexplored topic. The general nature of the climate damage functions aggregated and documented here allows for their incorporation within other models and frameworks.

Feedbacks from the climate to other components of the coupled human-Earth system are expected to strongly influence the co-evolution of human society and its environment. Representing these feedback loops between climate and society, via the Earth system’s response to human activities and the subsequent effect back onto social systems, is essential in order to fully explore the dynamics of the coupled system. However, focus on these feedbacks has traditionally been limited, or excluded, in prior Integrated Assessment Models (IAMs) and IAM-based modelling protocols. This limits the understanding of the effects of climate change, and the response of the overall system to future emissions scenarios and policies. The new IAM Feedback-based knowledge Repository for IntegrateD Assessments version 2.1 (FRIDAv2.1), documented and explored within this collection, seeks to address this by internalising the feedbacks between subcomponents of the human-Earth system. Within this new IAM, these connections are therefore a key part of the structure, and are documented and discussed here. These feedbacks from the climate to human societies, conceptualised as climate impacts, are represented as global impact functions within FRIDA. Where possible, they are based on estimates from existing literature, reframed as functions of global climate variables to facilitate their representation within FRIDA. Other impact channels, with insufficient background literature to inform their structure and parameter values, are incorporated via the internal calibration of the IAM. Since the systematic representation of climate damages within an IAM is a relatively novel endeavour, the approach is constrained by literature limitations and necessary simplifications. In addition, the high level of abstraction of the FRIDA model imposes limits on the set of impacts which can reasonably be implemented, and the level of process detail amongst those included. Nevertheless, FRIDA’s endogenous representation of climate feedbacks to human and natural systems enables valuable insights and intuition building on an underexplored topic. The general nature of the climate damage functions aggregated and documented here allows for their incorporation within other models and frameworks.

Marginal cost curves (MCCs) are popular decision-support tools for assessing and ranking the cost-effectiveness of different options in environmental policy and management. However, conventional MCC approaches have been criticized for lack of transparency and disregard for complexity; not accounting for interaction effects between measures; ignoring ancillary benefits and costs; and not considering intertemporal dynamics. In this paper, we present an approach to address these challenges using a system dynamics (SD)-based model for producing dynamic MCCs. We describe the approach by applying it to evaluate efforts to address water scarcity in a hypothetical, but representative, Swedish city. Our results show that the approach effectively addresses all four documented limitations of conventional MCC methods. They also show that combining MCCs with behavior-over-time graphs and causal-loop diagrams can lead to new policy insights and support a more inclusive decision-making process.