A reduction in global meat consumption can significantly reduce the adverse environmental effects of the food system, but it would require widespread dietary changes. Such shifts to sustainable diets depend on several behavioural factors, which have not yet been addressed in relation to the food system. This study links a behavioural diet shift model to an integrated assessment model to identify the main drivers of global diet change and its implications for the food system. The results show that the social norm effectfor instance the extent of vegetarianism in the population that accelerates a further switch to a vegetarian dietand selfefficacy are the main drivers of widespread dietary changes. These findings stress the importance of value-driven actions motivated either by intrinsic identity or by group dynamics over health and climate risk perception in steering diet change dynamics. Main Lifestyle change is considered an important demand-side measure to mitigate climate change 1, 2. Lowering energy demand and the greenhouse gas (GHG) emissions of food consumption with climate-friendly lifestyle choices can be key to achieving 1.5°C pathways 3, 4. Besides issues related to land use and GHG emissions, the food system damages natural ecosystems 5 and pushes the Earth towards the planetary boundaries for freshwater use, deforestation, and ocean acidification 6, 7. Several studies have demonstrated that lowering global meat consumption can significantly mitigate the adverse environmental effects of the global food system 8, 9, 10, 11, 12. Diet change scenarios explored in previous studies, which are based on stylized diets or average consumption values, are promising to alleviate environmental degradation. Yet, they are difficult to achieve due to the scale of behavioural change required. For instance, if the world's average diet became flexitarian by 2050, meaning that red meat consumption is limited to one serving per week and white meat to half a portion per day, the GHG emissions of the agriculture sector would be reduced by around 50% 12. Currently, 1.8% of daily calories are obtained from red meat (beef and lamb) in the world's average diet 13. In a flexitarian diet, one serving of red meat per week constitutes only 0.5% of daily caloric intake. The difference is small, but it would require billions of consumers to change their diets for a global change.

Quantitative modelling is commonly used to assist the policy dimension of sustainability problems. Validation is an important step to make models credible and useful. To investigate existing validation viewpoints and approaches, we analyse a broad academic literature and conduct a survey among practitioners. We find that empirical data plays an important role in the validation practice in all main areas of sustainability science. Qualitative and participatory approaches that can enhance usefulness and public reliability are much less visible. Data-oriented validation is prevalent even when models are used for scenario exploration. Usefulness regarding a given task is more important for model developers than for users. As the experience of modellers and users increases, they tend to better acknowledge the decision makers’ demand for clear communication of assumptions and uncertainties. These findings provide a reflection on current validation practices and are expected to facilitate communication at the modelling and decision-making interface.

Negative emission technologies (NETs) underpin socioeconomic scenarios consistent with the Paris Agreement. Afforestation and bioenergy coupled with carbon-dioxide (CO2) capture and storage are the main land NETs proposed, but the range of nature-based solutions is wider. Here, we explore soil amendment with powdered basalt in natural ecosystems. Basalt is an abundant rock resource, that reacts with CO2 and removes it from the atmosphere. Besides, basalt improves soil fertility and thereby potentially enhances ecosystem carbon storage, rendering a global CO 2 removal of basalt substantially larger than previously suggested. Because this is a fully developed technology which can be co-deployed in existing land systems it is suited for rapid upscaling. Achieving sufficiently high net CO2 removal will require upscaling of basalt mining, deploying systems in remote areas with a low carbon footprint, and using energy from low carbon sources. We argue that basalt soil amendment should be considered a prominent option when assessing land management mitigation options for mitigating climate change, but yet unknown side-effects, as well as limited data on field-scale deployment, need to be addressed first. Rapid and massive deployment of negative emission technology (NETs) to remove carbon from the atmosphere is needed if we are to achieve the climate stabilization targets agreed at the 2015 Paris Agreement 1 . A range of nature-based NETs have been proposed which offer the advantage of low technological barriers and modest energy demands. However, their potential and scalability 2 are uncertain and some compete with other land uses for land, water and nutrients 3,4 .Nature-based land NETs rely on biomass carbon sequestration through interventions such as planting forests, sustainable forestry, soil carbon sequestration from increased inputs to agricultural soils and biochar additions, and the enhancement of weathering. Enhanced weathering offers the advantage that it can be deployed with other land uses. Yet, there are few studies about this NET 3-6 and to our knowledge, regional and global scalability were only investigated for arable land 8 , with co-benefits for biomass and soil carbon sequestration remaining largely omitted. Here, we focus on

Abstract:Qualitative data is an important source of information for system dynamics modeling. It can potentially support any stage of the modeling process, yet it is mainly used in the early steps such as problem identification and model conceptualization. Existing approaches that outline a systematic use of qualitative data in model conceptualization are often not adopted for reasons of time constraints resulting from an abundance of data. In this paper, we introduce an approach that synthesizes the strengths of existing methods. This alternative approach (i) is focused on causal relationships starting from the initial steps of coding; (ii) generates a generalized and simplified causal map without recording individual relationships so that time consumption can be reduced; and (iii) maintains the links from the final causal map to the data sources by using software. We demonstrate an application of this approach in a study about integrated decision making in the housing sector of the UK.

Mathematical models have become central to the public and policy debate about the recent COVID-19 pandemic. On the one hand, they provide guidance to policy-makers about the development of the epidemic and healthcare demand overtime; on the other hand, they are heavily criticized for their lack of credibility. This commentary reflects on three such models from a validity and usefulness perspective. Specifically, it discusses the complexity, validation, and communication of models informing the government decisions in the UK, US and Austria, and concludes that, although these models are useful in many ways, they currently lack a thorough validation and a clear communication of their uncertainties. Therefore, prediction claims of these models should be taken cautiously, and their merits on scenario analysis should be the basis for decisionmaking. The lessons that can be learned from the COVID models in terms of the communication of uncertainties and assumptions can guide the use of quantitative models in other policy-making areas.

The built environment is a key target of decarbonization policies. However, such policies often have a narrow objective and narrow focus, resulting in 'policy-resistance' and unintended consequences. The literature attributes these unintended consequences to a narrow financial focus, adverse incentives, and inadequate handling of knowledge, skills, communication and feedback gaps, but it provides little advice on how these complex interactions can be captured. This paper illustrates the development and application of an integrated approach to address these complex interactions with regard to housing performance, energy, communal spaces and wellbeing. In particular, it explores the dynamics created by these relationships with simulation modelling in participatory settings, and with a diverse group of stakeholders. The simulation results suggest that monitoring is key to improve the performance of the housing stock besides energy efficiency; and investments in communal spaces positively affect the adoption of energyefficiency measures and the wellbeing of residents. The evaluation results for participatory workshops show this approach was found useful by the stakeholders for supporting more integrated decision-making about housing. In future research, this approach can be implemented for policy problems in specific contexts.

The 17 Sustainable Development Goals (SDGs) represent a holistic and ambitious agenda for transforming the world towards societal well-being, economic prosperity, and environmental protection. Achieving the SDGs is, however, challenged by the performance of interconnected sectors and the complexity of their interactions which drive non-linear system responses, tipping points, and spillover effects. Systems modelling, as an integrated way of thinking about and modelling multisectoral dynamics, can help explain how feedback interactions within and among different sectors can lead to broader system transformation and progress towards the SDGs. Here, we review how system dynamics, as a prominent systems modelling approach, can inform and contribute to sustainability research and implementation, framed by the SDGs. We systematically analyse 357 system dynamics studies undertaken at the local scale where the most important SDG impacts and their initiators are often located, published between 2015 (i.e. SDGs’ inception) and 2020. We analyse the studies to illuminate strengths and limitations in four key areas: diversity of scope; interdisciplinarity of the approaches; the role of stakeholder participation; and the analysis of SDG interactions. Our review highlights opportunities for a better consideration of societal aspects of sustainable development (e.g. poverty, inequality) in modelling efforts; integrating with new interdisciplinary methods to leverage system dynamics modelling capabilities; improving genuine stakeholder engagement for credibility and impacts on the ground; and a more in-depth analysis of SDG interactions (i.e. synergies and trade-offs) with the feedback-rich structure of system dynamics models.

Highlights • We conduct citation and text-mining analyses on a broad model validation literature. • Data and predict are the most common words in the studied publication dataset. • The most-cited publications are not similar to the rest in terms of their content. • Validation practices of different modeling fields are closed to each other.