In 2015, the United Nations articulated the ambition to move toward a prosperous, socially inclusive, and environmentally sustainable future for all by adopting the Sustainable Development Goals (SDGs). However, little is known about the pathways that could lead to their concurrent achievement. We provide an overview of the current literature on quantitative pathways toward the SDGs, indicate the commonly used methods and indicators, and identify the most comprehensive pathways that have been published to date. Our results indicate that there is a need for more scenarios toward the full set of SDGs, using a wider range of underlying narratives.

Quantitative goal-seeking scenario studies could help to explore the needed systems' transformations to implement the 2030 Agenda for Sustainable Development by identifying enabling conditions and accounting for the synergies and trade-offs between the SDGs. Given that the SDGs were adopted some time ago, here, we review the existing global scenario literature to determine what it can offer in this context. We found only a few scenarios that address a large set of SDGs, while many more deal with specific clusters of 2–6 SDGs. We identified the most frequent clusters and compared the results of the most comprehensive sustainable development scenarios. The latter is complicated because of the diversity of methods, indicators, and assumptions used. Therefore, we suggest that an effort is needed to develop a wider set of scenarios that would achieve multiple SDGs, using a more standardized framework of targets and indicators.

This study reviews the current global pathways toward the SDGs and shows the need for a broader set of SDG scenarios.

Information on social aspects of climate change intervention, such as behavioral choices and public acceptance, are often not included in global climate models. As a result, they have been critiqued for not adequately reflecting ‘real world’ conditions. At the same time, these models are important and influential policy tools. To improve these models, calls are being made for more interaction – or integration – between the social science and modelling research communities. Yet, it remains unclear how to achieve this. Responding to this gap, we explore what kind of integration is currently taking place, how, and opportunities for further development.

The importance of social drivers of climate change interventions, or social aspects, is currently underrepresented in computational modelling projections. These parameters are largely excluded from estimates of technical mitigation potential, feasibility, and tools like integrated assessment models (IAMs) and other large-scale models that influence the development of climate policies and notable bodies like the Intergovernmental Panel on Climate Change. This paper contributes to calls being made within the research community to address this gap and strengthen linkages between modelling practices and social science insights. Using nature-based solutions (NbS) as a framing, we present the results of a critical literature review and interviews with multidisciplinary experts reflecting on the current state of integration around IAMs and opportunities to better capture social aspects within large-scale modelling processes. Our findings confirm the need to incorporate social aspects in IAMs, but highlight that how this happens in practice may depend on context, project objectives, or pragmatic choices rather than conceptual notions about what ‘good’ integration is. Nevertheless, some integration strategies are better than others, and concerns about data limitations and low capacity of the IAM community for engaging in integration can be overcome with sufficient support and complementary efforts from the broader research community.

Integrating social aspects in large-scale models requires complementary efforts from the broader research community.

To meet the UK's greenhouse gas (GHG) emissions targets, the Climate Change Committee (CCC) recommended to reduce current meat and dairy intake by 20% by 2030. In this study, we modelled the impact of potential dietary changes on GHG emissions and water use with the selected scenarios based on the trend of food purchase and meat and dairy reduction policy. We show that implementing fiscal measures and facilitating innovations in production of meat alternatives would accelerate existing positive trends, help the UK reach the CCC 2030 target of 20% meat and dairy reduction and increase fruit and vegetable intake.

We used 2001–2019 data from the Family Food module of the Living Costs and Food Survey (LCF), an annual UK survey of about 5,000 representative households recording quantities of all food and drink purchases, to model four 2030 dietary scenarios: Business as usual (BAU); two fiscal policy scenarios (‘fiscal 10%’ and ‘fiscal 20%’), combining either a 10% meat and dairy tax and a 10% fruit and vegetable subsidy, or a 20% tax and 20% subsidy on the same foods; and an ‘innovation scenario’ substituting traditionally-produced meat and dairy with plant-based analogues and animal proteins produced in laboratories. Compared to 2019 levels, we forecasted reductions in the range of 5–30% for meat and 8–32% for dairy across scenarios. Meat reductions could be up to 21.5% (fiscal20%) and 30.4% (innovation). For all scenarios we forecasted an increase in fruit and vegetables intake in the range of 3–13.5%; with the fiscal 20% scenario showing highest increases (13.5%). GHG emissions and water use reductions were highest for the innovation scenario (−19.8%, −16.2%) followed by fiscal 20% (−15.8%, −9.2%) fiscal 10% (−12.1%, 5.9%) and BAU (−8.3%, −2.6%) scenarios. Compared to average households, low-income households had similar patterns of change, but both past and predicted purchase of meat, fruit and vegetables and environmental footprints were lower.

Meat and dairy-reduction policies would help meet net zero targets and improve population health in the UK.