A better approach is needed to assess potential impact and feasibility of proposals.

National efforts to implement the Sustainable Development Goals (SDGs) are falling short of what is needed to meet the transformative agenda. An important implementation gap relates to inadequate national SDGs assessment and reports which have been too descriptive and lacked analytical depth and policy orientation to inform transformative action. This study addresses this gap by presenting the approach and findings from a third generation SDGs assessment for Australia. The approach combines a comprehensive assessment of the evolution of progress on the SDGs, analyses forward-looking policy pathways, evaluates policy interactions and spillovers and explores causal dynamics and feedbacks that drive diverse outcomes for the SDGs. By synthesising these pieces of analysis, three policy priorities for Australia are identified: (1) Addressing areas of persistent underperformance (poverty and inequality goals) and recent backsliding (health and education goals) where progress is foundational to broader SDGs achievement; (2) Leveraging momentum in the renewable energy transition to catalyse broader systemic shifts in green manufacturing and net zero transitions in hard to abate sectors (e.g., transport, buildings, industry and land-use) and (3) Building long-term resilience of SDGs progress and anticipating trade-offs and reinforcing synergies across the goals. Overall, the study demonstrates a broadly transferable approach for designing national SDGs assessments that inform integrated, forward-looking strategies and offer a more robust foundation for future policy action. It also offers a timely contribution to emerging discussions around the design of a post-2030 sustainable development agenda and improvements to national implementation and reporting.

Degrowth policies have been proposed as a way to reduce environmental pressures and advance social equity. While such policies have been discussed extensively in qualitative terms, a proper quantification of their socioeconomic and environmental impacts is fundamental to assessing their effectiveness. We use the iSDG-Sweden system dynamics model to study the impacts and dynamics of combined degrowth policies in the macroeconomic context of a high-income country, for the years 2026 to 2050. Our results indicate that the simulated policies are effective only when applied as a coherent package; when implemented in isolation, trade-offs emerge. The model simulations show how downscaling production with high footprints, combined with reducing working hours and redistributing income and wealth, causes rapid reductions in environmental pressures while reducing poverty, inequality and unemployment. Fiscal analysis indicates short-term feasibility of financing the simulated policy package through increased tax revenues, but highlights long-term risks of rising government debt, requiring complementary reforms or deeper structural changes to reduce debt vulnerability. These findings demonstrate how system dynamics modelling can integrate environmental and socio-economic dimensions of post-growth pathways, and suggest policy coherence is critical for a sustainable and just degrowth transition.

For countries in South-East Asia, air pollution presents a complex challenge that has proven difficult to effectively address. Policy action needs to be informed by a clear understanding of the most important drivers and sources of air pollution in local contexts, and the costs and benefits of different measures in mitigating these sources. Here, we present the findings from a participatory system dynamics modelling study which aimed to support policy and decision-making to manage the transboundary air pollution challenge in Thailand and Lao PDR. The research included two participatory modelling projects undertaken at the subnational level for Chiang Rai Province and Vientiane Prefecture which developed and applied an integrated air pollution (IAP) model. The participatory model development process undertaken with governments, private sector and civil society stakeholders identified key sources of air pollution (PM2.5 emissions), socioeconomic drivers and impacts, and potential policy interventions which were incorporated into the IAP model. Model projections for 2030 identified key sources of emissions for Chiang Rai as waste burning, cooking/heating and small vehicles, while for Vientiane they were cooking/heating, cement production, waste burning, small vehicles and petrochemical sources. Through group-based scenario gaming exercises, stakeholders gained insights on the cost and efficacy of different policy options by testing alternative investment scenarios. For both Chiang Rai and Vientiane, the largest reductions in PM2.5 emissions were projected from policies that targeted the waste burning, household cooking and transport sectors. This contrasted somewhat to stakeholder perceptions regarding the dominance of air pollution sources such as open burning of agricultural residues and forest fires. We highlight key insights and implications of the study for policy and research including the use of participatory systems dynamics modelling as a method for understanding and addressing complex sustainability challenges such as air pollution.

Climate mitigation policies have broad environmental and socioeconomic impacts and thus underpin progress towards the United Nations Sustainable Development Goals (SDGs). Through national-scale integrated modeling, we explore the spillover effects of China's long-term climate mitigation pathways (CMPs) on achieving all 17 SDGs, and then identify a cost-effective CMP for China with co-benefits for sustainability. Our analysis indicates that the 9 original CMPs and 180 bundled CMPs can both substantially boost the SDGs, resulting in an increase of 6.33-8.86 and 5.90-9.33 points in overall SDG score (0=no progress, 100=full achievement) by 2060, compared to the Reference pathway of 70.75 points, respectively. The identified cost-effective CMP deals with the trade-offs among sustainability, CO2 emissions and mitigation cost, and maximizes the synergies between them. This CMP can inform future directions for China's policy-makers to maximize the potential synergies between carbon neutrality and long-term sustainable development. Climate mitigation have broad effects on achieving Sustainable Development Goals. This paper explores the spillover effects of China's climate mitigation pathways and identify a cost-effective pathway with co-benefits for sustainability.

There is an urgent need to accelerate progress on the Sustainable Development Goals (SDGs) and recent research has identified six critical transformations. It is important to demonstrate how these transformations could be practically accelerated in a national context and what their combined effects would be. Here we bridge national systems modelling with transformation storylines to provide an analysis of a Six Transformations Pathway for Australia. We explore important policies to accelerate progress, synergies and trade-offs, and conditions that determine policy success. We find that implementing policy packages to accelerate each transformation would boost performance on the SDGs by 2030 (+23% above the baseline). Policymakers can maximize transformation synergies through investments in energy decarbonization, resilience, social protection, and sustainable food systems, while managing trade-offs for income and employment. To overcome resistance to transformations, ambitious policy action will need to be underpinned by technological, social, and political enabling conditions.

The integrated and indivisible nature of the SDGs is facing implementation challenges due to the silo approaches. We present the three interconnected foci (SDG interactions, modeling, and tools) at the science-policy interface to address these challenges. Accounting for them will support accelerated SDG progress, operationalizing the integration and indivisibility principles.

China's long-term sustainability faces socioeconomic and environmental uncertainties. We identify five key systemic risk drivers, called disruptors, which could push China into a polycrisis: pandemic disease, ageing and shrinking population, deglobalization, climate change, and biodiversity loss. Using an integrated simulation model, we quantify the effects of these disruptors on the country's long-term sustainability framed by 17 Sustainable Development Goals (SDGs). Here we show that ageing and shrinking population, and climate change would be the two most influential disruptors on China's long-term sustainability. The compound effects of all disruptors could result in up to 2.1 and 7.0 points decline in the China's SDG score by 2030 and 2050, compared to the baseline with no disruptors and no additional sustainability policies. However, an integrated policy portfolio involving investment in education, healthcare, energy transition, water-use efficiency, ecological conservation and restoration could promote resilience against the compound effects and significantly improve China's long-term sustainability.

The Kingdom of Bhutan aspires to move to 100 percent organic agriculture and improve self-sufficiency in its most important cereal crop, rice. Unfortunately, simulations conducted by Feuerbacher et al. (2018) suggest that a full conversion to organic agriculture as currently practiced in Bhutan would result in diminished self-sufficiency in cereal crops. Widespread adoption of agroecology, which improves yields by building soil organic matter and nurturing ecosystem services, could potentially achieve both 100 percent organic production and improved self-sufficiency in cereal production; however, perceived costs and risks may impede farmers’ willingness to adopt agroecology. In the current research we develop an integrated systems model to explore policies for bringing agroecology to scale, focusing specifically on rice production in Bhutan. Simulations show that a feebate (fee and rebate) policy coupled with promotion and training in agroecological farming methods could incentivize widespread adoption of agroecology, achieving both 100 percent organic production and greater self-sufficiency for rice in Bhutan. The model developed for this research can readily be adapted to examine various feebates or other policies for incentivizing agroecology for other geographies and crops.

The COVID-19 pandemic is causing unprecedented damage to our society and economy, globally impacting progress towards the SDGs. The integrated perspective that Agenda 2030 calls for is ever more important for understanding the vulnerability of our eco-socio-economic systems and for designing policies for enhanced resilience. Since the emergence of COVID-19, countries and international institutions have strengthened their monitoring systems to produce timely data on infections, fostering data-driven decision-making often without the support of systemic-based simulation models. Evidence from the initial phases of the pandemic indicates that countries that were able to implement effective policies before the number of cases grew large (e.g. Australia) managed to contain COVID-19 to a much greater extent than others. We argue that prior systemic knowledge of a phenomenon provides the essential information to correctly interpret data, develop a better understanding of the emerging behavioural patterns and potentially develop early qualitative awareness of how to react promptly in the early phases of destructive phenomena, eventually providing the ground for building more effective simulation models capable of better anticipating the effects of policies. This is even more important as, on its path to 2030, humanity will face other challenges of similar dynamic nature. Chief among these is Climate Change. In this paper, we show how a Systems Thinking and System Dynamics modelling approach is useful for developing a better understanding of these and other issues, and how systemic lessons learned from the COVID-19 case can help decision makers anticipate the destructive dynamics of Climate Change by improving perceptions of the potential impacts of reinforcing feedback and delays, ultimately leading to more timely interventions to achieve the SDGs and mitigate Climate Change risks.

Background: The UK was one of the countries worst affected by the COVID-19 pandemic in Europe. A strict lockdown from early 2021 combined with an aggressive vaccination programme enabled a gradual easing of lockdown measures to be introduced whilst both deaths and reported case numbers reduced to less than 3% of their peak. The emergence of the Delta variant in April 2021 has reversed this trend, and the UK is once again experiencing surging cases, albeit with reduced average severity due to the success of the vaccination rollout. This study presents the results of a modelling exercise which simulates the progression of the pandemic in the UK through projection of daily case numbers as lockdown lifts. Methods: A simulation model based on the Susceptible-Exposed-Infected-Recovered structure was built. A timeline of UK lockdown measures was used to simulate the changing restrictions. The model was tailored for the UK, with some values set based on research and others obtained through calibration against 16 months of historical data. Results: The model projects that if lockdown restrictions are lifted in July 2021, UK COVID-19 cases will peak at hundreds of thousands daily in most viable scenarios, reducing in late 2021 as immunity acquired through both vaccination and infection reduces the susceptible population percentage. Further lockdown measures can be used to reduce daily cases. Other than the ever-present threat of the emergence of new variants, the most significant unknown factors affecting the profile of the pandemic in the UK are the length and strength of immunity, with daily peak cases over 50% higher if immunity lasts 8 months compared to 12 months. Another significant factor is the percentage of unreported cases. The reduced case severity associated with vaccination may lead to a higher proportion of unreported mild or asymptomatic cases, meaning that unmanaged infections resulting from unknown cases will continue to be a major source of infection. Conclusions: Further research into the length and strength of both recovered and vaccinated COVID-19 immunity is critical to delivering more accurate projections from models, thus enabling more finely tuned policy decisions. The model presented in this article, whilst by no means perfect, aims to contribute to greater transparency of the modelling process, which can only increase trust between policy makers, journalists and the general public.

Non-technical summary The Sustainable Development Goals (SDGs) provide an integrated and ambitious roadmap for sustainable development by 2030. National implementation will be crucial and there is an urgent need to understand the scale and pace of transformations to achieve the goals. There is also concern that achieving socio-economic objectives will undermine longer-term environmental sustainability. This study uses modelling to explore how different policy and investment settings can enable the necessary transformations, adopting Fiji as a use-case. Modest investment over the coming decade can deliver improved performance. However, far more ambitious actions are needed to accelerate progress while managing long-term trade-offs with environmental objectives. Technical summary This paper presents the results from a national scenario modelling study for Fiji with broader relevance for other countries seeking to achieve the SDGs. We develop and simulate a business-as-usual and six alternative future scenarios using the integrated ( iSDG-Fiji ) system dynamics model and evaluate their performance on the SDGs in 2030 and global planetary boundaries (PBs) and the ‘safe and just space’ (SJS) framework in 2050. Modest investment over the coming decade through a ‘sustainability transition’ scenario accelerates SDG progress from 40% to 70% by 2030 but fails to meet all SJS thresholds. Greatly scaling up investment and ambition through an SDG transformation scenario highlights possibilities for Fiji to accelerate progress to 83% by 2030 while improving SJS performance. The scale of investment is highly ambitious and could not be delivered without scaled-up international support, but despite this investment progress still falls short. The analysis highlights where key trade-offs remain as well as options to address these, however closing the gap to 100% achievement will prove very challenging. The approach and findings are relevant to other countries with similar characteristics to increase the understanding of the transformations needed to achieve the SDGs within PBs in different country contexts. Social media summary How can countries accelerate progress on the SDGs by 2030 while ensuring longer-term coherence with climate and sustainability thresholds?

The Sustainable Development Goals (SDGs) of the UN 2030 Agenda are today's global roadmap to sustainable development. Adopted in 2015, the SDGs are the culmination of 50 years of debate and consensus building on the imperatives of sustainable development. The 2030 Agenda explicitly calls for integrated methods for SDG achievement. Two multisector modeling frameworks have emerged to address integration in SDG policy: the system dynamics based Integrated Sustainable Development Goal (iSDG) model and the multimethod International Futures (IFs) model. Both are feedback rich and thoroughly integrated, and we term them as Integrated Systems Models (ISMs). ISMs enable quantification of policy impacts across SDG sectors, helping identify policies that benefit numerous SDGs as well as potential trade-offs. These benefits have been witnessed in countries where these ISMs have been put to task on SDG policy. As the sustainable development paradigm becomes increasingly integrated, a central role is being created for further development of ISMs. (c) 2020 System Dynamics Society

The Sustainable Development Goals (SDGs) combine complex interlinkages, future uncertainty and transformational change. Recent studies highlight that trade-offs between SDG targets may undermine achievement of the goals. Significant gaps remain in scenario frameworks and modelling capabilities. We develop a novel approach nesting national SDG scenario modelling within the global Shared Socioeconomic Pathways, selecting Australia as a use case. The integrated SDG–Australia model is used to project four alternative scenarios that adopt different development approaches. Although we find that Australia is off-track to achieve the SDGs by 2030, considerable progress is possible by altering Australia’s development trajectory. A ‘Sustainability Transition’ scenario comprising a coherent set of policies and investments delivers rapid and balanced progress of 70% towards SDG targets by 2030, well ahead of the business-as-usual scenario (40%). A focus on economic growth, social inclusion or green economy in isolation foregoes opportunities for greater gains. However, future uncertainty and cascading risks could undermine progress, and closing the gap to 100% SDG achievement will be very challenging. This will require a shift from ‘transition’ to ‘transformation’.

Purpose The purpose of this papers is to highlight the applicability of integrated simulation models for national development planning to different issues and contexts. Specifically, the authors describe one such model, the Millennium Institute’s T21 model, which is used to support planning in various countries, and explore in detail the case of Swaziland to demonstrate the model’s usefulness at different levels in the planning process. Design/methodology/approach Integrated sustainable development planning models using the system dynamics (SD) modeling method have been designed to help overcome these obstacles and support decision-makers in the assessment of alternative policies. Such models are laboratory replicas of the critical mechanisms driving development in a country while being grounded in the historical data available. They can be used to perform simulation-based policy experiments that are otherwise impossible in the real world. Findings The proposed approach has facilitated the reporting on the Millennium Development Goals (MDGs), as well as on the cross-sector long-term ex ante evaluation of the country’s “Economic Recovery Strategy” and a proposed “Fiscal Adjustment” policy. These assessments provided essential information for improving the quality of the decisions made. Such information cannot be obtained by the application of purely economic models or sectoral tools, that are not including the fundamental feedback structures that shape development in the long run and determine its sustainability. Research limitations/implications The new generation of global long-term Sustainable Development Goals (SDGs) covers a far broader range of issues and indicators than the MDGs. The T21-Swaziland model only offers a limited subset of such issues, and future research will focus on achievements and challenges in expanding its scope to encompass the SDGs. Practical implications The T21 model has become one of the fundamental planning instruments of the country, and it has been used to evaluate national planning documents and other suggested strategies with respect to whether they are sufficient for reaching the long-term goals. Such information is then used as a basis for revision of development plans and adoption or rejection of suggested policy packages. Originality/value The MDGs (and their expanded follow-up, the SDGs) have been important step toward better governance, as they quantify key indicators of development and thereby allow for an evaluation of the degree to which these quantified aspirations are actually achieved. In addition to such hind-sight evaluations, ex ante evaluations are equally important for improvement of the quality of the decisions made. The authors propose and test a tool to support such type of evaluation, supporting integrated planning and model-based governance.

Significance The sustainable development goals (SDGs) offer the global community a compelling vision and universally agreed-upon framework to achieve a sustainable and equitable future—but present a costly undertaking in the short term. Our research suggests that synergetic effects arising from appropriately designed policy mixes can bring significant cost savings and improve SDG attainment. Identifying and quantifying synergies requires innovative and unorthodox approaches to policy analysis such as those operationalized in our 3 pilots. The synergy assessment method and typology introduced in this paper are widely applicable, even though the patterns of synergies vary considerably between countries. Our pilot studies focus on national policy for the SDGs. Our approach is nevertheless generalizable to integrated planning at other scales and time horizons.

In combination, policies for sustainable development can work together and synergize. In so doing, the resulting impact of a strategic policy mix can be greater than the sum of the individual policies of its individual parts. That synergetic potential can be utilized to attain strategic objectives. This is the case when it comes to achieving the Sustainable Development Goals (SDGs) of the United Nations 2030 Agenda. However, identifying and quantifying these synergetic interactions is infeasible with traditional approaches to policy analysis. In this paper we present a method for identifying these interactions and assessing them quantitatively. We also introduce a typology of five classes of synergy that enables an understanding of their structures. We operationalize the typology by the use of pilot studies of SDG strategies undertaken in Senegal, Cote d’Ivoire, and Malawi. In the pilots, the Integrated Sustainable Development Goal (iSDG) model was used to simulate the effects of policies over the SDG time horizon. In each case, synergetic interactions contribute to potential SDG attainment. We estimate the value of these interactions to be 2.8% of GDP for Cote d’Ivoire, 4.4% for Malawi, and 0.7% for Senegal. We conclude that enhanced understanding of synergies in sustainable development planning can contribute to progress on the SDGs – and set free substantial amounts of resources.

With the adoption of the United Nations 2030 Agenda, countries face the challenge of implementing strategies to achieve sustainable development goals (SDGs). To support the Ivory Coast Government in this process, we have developed the Treshold21-iSDG model, which integrates long-term social, economic and environmental policy analyses for SDG attainment. Specifically, we assess the impact of the implementation of the National Prospective Study (NPS) on achievement of the 17 SDGs, and identify necessary strategic adjustments. We compare SDG attainment under three scenarios: business-as-usual, NPS, and an "SDG" scenario that includes adjustments for critical aspects of SDGs not sufficiently covered by the NPS. The analysis identifies cross-sector impacts of policies and highlights the benefits of coordinated implementation of comprehensive and coherent SDG strategies. Such findings emphasize the importance of integrated simulation models to support planning of SDG strategies and to complement information provided by stakeholder engagement and other sector-specific or qualitative tools.

Coherently addressing the 17 Sustainable Development Goals requires planning tools that guide policy makers. Given the integrative nature of the SDGs, we believe that integrative modelling techniques are especially useful for this purpose. In this paper, we present and demonstrate the use of the new System Dynamics based iSDG family of models. We use a national model for Tanzania to analyse impacts of substantial investments in photovoltaic capacity. Our focus is on the impacts on three SDGs: SDG 3 on healthy lives and well-being, SDG 4 on education, and SDG 7 on energy. In our simulations, the investments in photovoltaics positively affect life expectancy, years of schooling and access to electricity. More importantly, the progress on these dimensions synergizes and leads to broader system-wide impacts. While this one national example illustrates the anticipated impact of an intervention in one specific area on several SDGs, the iSDG model can be used to support similar analyses for policies related to all the 17 SDGs, both individually and concurrently. We believe that integrated models such as the iSDG model can bring interlinks to the forefront and facilitate a shift to a discussion on development grounded in systems thinking.

Developing coherent plans to achieve food and nutrition security is complicated by the multi-disciplinary, interconnected and complex nature of the food systems that must be managed. To support such a planning process in Senegal, we analyse the impact of alternative interventions targeting food security through an integrated socioeconomic-environmental framework (the Millennium Institute’s Threshold-21 model) that allows the assessment of multisectoral long term impacts of alternative policies. Based on the System Dynamics method, T21 is well suited to capture the elements of dynamic complexity that make public policy analysis in this area particularly difficult. Our study explores and evaluates two scenarios representing two competing paradigms in agricultural policy and farming practices, and their implications for availability and access to food. In the first scenario government support is mainly directed towards subsidizing the intensive use of high external inputs and large-scale farming; while in the second scenario the government mainly supports a transition towards high agro-ecological knowledge intensity, less intensive use of external input and small-scale farming. Results indicate that, in terms of food availability, the first scenario yields better results in the short term, while the second scenario shows more desirable results in the long run. The agriculture system that emerges from the second scenario is also more resilient and thus less susceptible to changes in the price of external factors. The development of social indicators and consequently access to food are also substantially better in the second scenario, which supports more equitable socio-economic progress. Our work highlights how the non-linear response of the system to the policies implemented lead to worse-before-better dynamics, and how a failure to account for the interconnected and complex nature of the food-development nexus can lead to sub-optimal strategies.