• Energy Research

The 17 Sustainable Development Goals (SDGs) and 169 targets under Agenda 2030 of the United Nations map a coherent global sustainability ambition at a level of detail general enough to garner consensus amongst nations. However, achieving the global agenda will depend heavily on successful national-scale implementation, which requires the development of effective science-driven targets tailored to specific national contexts and supported by strong national governance. Here we assess the feasibility of achieving multiple SDG targets at the national scale for the Australian land-sector. We scaled targets to three levels of ambition and two timeframes, then quantitatively explored the option space for target achievement under 648 plausible future environmental, socio-economic, technological and policy pathways using the Land-Use Trade-Offs (LUTO) integrated land systems model. We show that target achievement is very sensitive to global efforts to abate emissions, domestic land-use policy, productivity growth rate, and land-use change adoption behaviour and capacity constraints. Weaker target-setting ambition resulted in higher achievement but poorer sustainability outcomes. Accelerating land-use dynamics after 2030 changed the targets achieved by 2050, warranting a longer-term view and greater flexibility in sustainability implementation. Simultaneous achievement of multiple targets is rare owing to the complexity of sustainability target implementation and the pervasive trade-offs in resource-constrained land systems. Given that hard choices are needed, the land-sector must first address the essential food/fibre production, biodiversity and land degradation components of sustainability via specific policy pathways. It may also contribute to emissions abatement, water and energy targets by capitalizing on co-benefits. However, achieving targets relevant to the land-sector will also require substantial contributions from other sectors such as clean energy, food systems and water resource management. Nations require globally coordinated, national-scale, comprehensive, integrated, multi-sectoral analyses to support national target-setting that prioritizes efficient and effective sustainability interventions across societies, economies and environments.

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.

Abstract Financial inclusion is a key policy for achieving the UN Sustainable Development Goals worldwide. However, emerging evidence has challenged the universal effectiveness of this policy. Combining a cross-sectional socio-economic and ecological survey with regional macro-economic and climatic data, we undertook an integrated causal analysis of the impact of financial inclusion policy on the Inner Mongolian herder social-ecological system. Exposure to economic globalization and climate change threatened herder livelihoods via increased feed costs and reduced livestock sales prices. Financial inclusion loans were beneficial for herders with large grassland plot size who used their traditional ecological knowledge to adapt via seasonal herd mobility. However, most herders were sedentary, constrained by small plot size, and used financial inclusion loans to reserve livestock and maintain high stocking densities. This strategy exposed them to inflated feed costs, increased their debt, and led to widespread grassland degradation. The results illustrate the limitations of financial inclusion policy in achieving sustainable development when people are trapped in poverty, subject to novel social-ecological contexts, and their ability to adapt is compromised. Transformative adaptations based on community cooperation, traditional knowledge and institutions, complementary public policies, and technological innovation are crucial to support financial inclusion policy and enhance sustainable development.

Vulnerability assessments have often invoked sustainable livelihoods theory to support the quantification of adaptive capacity based on the availability of capital--social, human, physical, natural, and financial. However, the assumption that increased availability of these capitals confers greater adaptive capacity remains largely untested. We quantified the relationship between commonly used capital indicators and an empirical index of adaptive capacity (ACI) in the context of vulnerability of Australian wheat production to climate variability and change. We calculated ACI by comparing actual yields from farm survey data to climate-driven expected yields estimated by a crop model for 12 regions in Australia's wheat-sheep zone from 1991-2010. We then compiled data for 24 typical indicators used in vulnerability analyses, spanning the five capitals. We analyzed the ACI and used regression techniques to identify related capital indicators. Between regions, mean ACI was not significantly different but variance over time was. ACI was higher in dry years and lower in wet years suggesting that farm adaptive strategies are geared towards mitigating losses rather than capitalizing on opportunity. Only six of the 24 capital indicators were significantly related to adaptive capacity in a way predicted by theory. Another four indicators were significantly related to adaptive capacity but of the opposite sign, countering our theory-driven expectation. We conclude that the deductive, theory-based use of capitals to define adaptive capacity and vulnerability should be more circumspect. Assessments need to be more evidence-based, first testing the relevance and influence of capital metrics on adaptive capacity for the specific system of interest. This will more effectively direct policy and targeting of investment to mitigate agro-climatic vulnerability.

AbstractChina’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.

High-Quality Development (HQD) can well meet human’s growing needs for a better life, and it is an important manifestation of efficient, fair and sustainable development. It is a crucial turning point for China from high-speed development to HQD. A better understanding the HQD from perspective of efficiency is very important for the development of China. Using prefecture-level city panel data of China from 2005 to 2019, this study built a model coupled with innovation, coordination, greenness, openness, sharing, and slacks-based measure (ICGOS-SBM) based on the Super-SBM model of slack variables. By introducing efficiency thinking, this study measured the HQD level of the Yangtze River Economic Belt (YREB, one of driving forces spearheading China’s HQD in a new era) from the perspective of development “quality”, and explored its spatial and temporal distribution characteristics. The results showed that (a) the temporal HQD levels of the YREB presented an “N”, pattern of rising first, then falling, and then rising; (b) the HQD levels exhibited noticeable regional heterogeneity a the different urban scale, and the development trend of the upper of YREB drove that of the middle and then that of the downstream; (c) the HQD levels of the YREB presented different degrees of spatial agglomeration, with an increasing trend over time, and the high-high agglomeration areas were mainly concentrated in the upper of the YREB with better natural endowments; and (d) the spatial HQD trajectory of the YREB mainly moved back and forth in the southwest-northeast direction, which may be due to its unstable development, showing a relatively obvious back-and-forth movement between Changde and Jingzhou. It aims to provide an innovative perspective for the measurement of HQD levels by introducing efficiency thinking.

In an earlier paper (Kirby et al. 2014a), we showed that climate change and a new policy which reallocates water to the environment will impact both the flow of water and the income derived from irrigation in the Murray–Darling Basin. Here, we extend the analysis to consider irrigator and environmental water management strategies to adapt to these new circumstances. Using an integrated hydrology-economics model, we examine a range of strategies and their impact on flows and the gross income of irrigation. We show that the adaptation strategies provide a range of flow and economic outcomes in the Basin. Several strategies offer significant scope to enhance flows without large adverse impacts on the gross income of irrigation overall. Some environmental water management strategies enhance flows in the Murray part of the basin even under the drying influence of a projected median climate change. Irrigator strategies that include carryover of water in storage from one year to the next provide for lesser year to year variability in gross income and may be regarded as more advantageous in providing security against droughts. Flows and the gross income of low value irrigation industries strategies are sensitive to climate change, irrespective of adaptation strategy. Should a projected dry extreme climate change be realized, no strategy can prevent a large reduction in flows and also in gross income, particularly of low value irrigation industries. Nevertheless, environmental water management strategies mitigate the impact on flows, and in some cases may also help mitigate the impacts on gross income. High value irrigation industries are less affected (in terms of gross income, though net income will reduce because of rising water prices) by projected climate change, consistent with observation in the recent long term drought.