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.

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

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.

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.