Abstract There is about to be an abrupt step-change in the use of coastal seas around the globe, specifically by the addition of large-scale offshore renewable energy (ORE) developments to combat climate change. Developing this sustainable energy supply will require trade-offs between both direct and indirect environmental effects, as well as spatial conflicts with marine uses like shipping, fishing, and recreation. However, the nexus between drivers, such as changes in the bio-physical environment from the introduction of structures and extraction of energy, and the consequent impacts on ecosystem services delivery and natural capital assets is poorly understood and rarely considered through a whole ecosystem perspective. Future marine planning needs to assess these changes as part of national policy level assessments but also to inform practitioners about the benefits and trade-offs between different uses of natural resources when making decisions to balance environmental and energy sustainability and socio-economic impacts. To address this shortfall, we propose an ecosystem-based natural capital evaluation framework that builds on a dynamic Bayesian modelling approach which accounts for the multiplicity of interactions between physical (e.g. bottom temperature), biological (e.g. net primary production) indicators and anthropogenic marine use (i.e. fishing) and their changes across space and over time. The proposed assessment framework measures ecosystem change, changes in ecosystem goods and services and changes in socio-economic value in response to ORE deployment scenarios as well as climate change, to provide objective information for decision processes seeking to integrate new uses into our marine ecosystems. Such a framework has the potential of exploring the likely outcomes in the same metrics (both ecological and socio-economic) from alternative management and climate scenarios, such that objective judgements and decisions can be made, as to how to balance the benefits and trade-offs between a range of marine uses to deliver long-term environmental sustainability, economic benefits, and social welfare.
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Towards an Integrated Sustainability Evaluation of Energy Scenarios with Automated Information Exchange [Towards an Integrated Sustainability Evaluation of Energy Scenarios with Automated Information Exchange]
To reshape energy systems towards renewable energy resources, decision makers need to decide today on how to make the transition. Energy scenarios are widely used to guide decision making in this context. While considerable effort has been put into developing energy scenarios, researchers have pointed out three requirements for energy scenarios that are not fulfilled satisfactorily yet: The development and evaluation of energy scenarios should (1) incorporate the concept of sustainability, (2) provide decision support in a transparent way and (3) be replicable for other researchers. To meet these requirements, we combine different methodological approaches: story-and-simulation (SAS) scenarios, multi-criteria decision-making (MCDM), information modeling and co-simulation. We show in this paper how the combination of these methods can lead to an integrated approach for sustainability evaluation of energy scenarios with automated information exchange. Our approach consists of a sustainability evaluation process (SEP) and an information model for modeling dependencies. The objectives are to guide decisions towards sustainable development of the energy sector and to make the scenario and decision support processes more transparent for both decision makers and researchers.
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- Award ID(s):
- 1743772
- NSF-PAR ID:
- 10076123
- Date Published:
- Journal Name:
- Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems
- Volume:
- 1
- Page Range / eLocation ID:
- 188 to 199
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Despite broad consensus on the benefits of a nexus approach to multi-sector planning, actual implementation in government and other decision-making institutions is still rare. This study presents an approach to conducting integrated energy-water-land (EWL) planning, using Uruguay as an example. This stakeholder-driven study focuses on assessing the EWL nexus implications of actual planned policies aimed at strengthening three of Uruguay’s key exports (beef, soy, and rice), which account for more than 40% of total national export revenue. Five scenarios are analyzed in the study: a reference scenario, a climate impacts scenario, and three policy scenarios. The three policy scenarios include measures such as increasing the intensity of beef production while simultaneously decreasing emissions, increasing irrigated soybean production, and improving rice yields. This study supplements previous sector-specific planning efforts in Uruguay by conducting the first stakeholder-driven integrated multi-sector assessment of planned policies in Uruguay using a suite of integrated modeling tools. Key insights from the study are: as compared to a reference scenario, improving beef productivity could lead to cropland expansion (+30%) and significant indirect increases in water requirements (+20%); improving rice yields could lead to increases in total emissions (+3%), which may partially offset emissions reductions from other policies; expanding irrigated soy could have the least EWL impacts amongst the policies studied; and climate-driven changes could have significantly less impact on EWL systems as compared to human actions. The generalizable insights derived from this analysis are readily applicable to other countries facing similar multi-sector planning challenges. In particular, the study’s results reinforce the fact that policies often have multi-sector consequences, and thus policies can impact one another’s efficacy. Thus, policy design and implementation can benefit from coordination across sectors and decision-making institutions.
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Abstract Humanity is on a deeply unsustainable trajectory. We are exceeding planetary boundaries and unlikely to meet many international sustainable development goals and global environmental targets. Until recently, there was no broadly accepted framework of interventions that could ignite the transformations needed to achieve these desired targets and goals.
As a component of the IPBES Global Assessment, we conducted an iterative expert deliberation process with an extensive review of scenarios and pathways to sustainability, including the broader literature on indirect drivers, social change and sustainability transformation. We asked, what are the most important elements of pathways to sustainability?
Applying a social–ecological systems lens, we identified eight priority points for intervention (leverage points) and five overarching strategic actions and priority interventions (levers), which appear to be key to societal transformation. The eight
leverage points are: (1) Visions of a good life, (2) Total consumption and waste, (3) Latent values of responsibility, (4) Inequalities, (5) Justice and inclusion in conservation, (6) Externalities from trade and other telecouplings, (7) Responsible technology, innovation and investment, and (8) Education and knowledge generation and sharing. The five intertwinedlevers can be applied across the eight leverage points and more broadly. These include: (A) Incentives and capacity building, (B) Coordination across sectors and jurisdictions, (C) Pre‐emptive action, (D) Adaptive decision‐making and (E) Environmental law and implementation. The levers and leverage points are all non‐substitutable, and each enables others, likely leading to synergistic benefits.Transformative change towards sustainable pathways requires more than a simple scaling‐up of sustainability initiatives—it entails addressing these levers and leverage points to change the fabric of legal, political, economic and other social systems. These levers and leverage points build upon those approved within the Global Assessment's Summary for Policymakers, with the aim of enabling leaders in government, business, civil society and academia to spark transformative changes towards a more just and sustainable world.
A free
Plain Language Summary can be found within the Supporting Information of this article. -
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Abstract This special issue is the outcome of a workshop held at Purdue University in April 2022. It comprises thematic syntheses of five overarching dimensions of the Global-to-Local-to-Global (GLG) challenge to ensuring the long-term sustainability of land and water resources. These thematic dimensions include: climate change, ecosystems and biodiversity, governance, water resources and cyberinfrastructure. In addition, there are eight applications of GLG analysis to specific land and water sustainability challenges, ranging from environmental stress in the Amazon River Basin to groundwater depletion in the United States. Based on these papers, we conclude that, without fine-scale, local analysis, interventions focusing on land and water sustainability will likely be misguided. But formulating such policies without the broader, national/global context is also problematic – both from the point of view of the global drivers of local sustainability stresses, as well as to capture unanticipated spillovers. In addition, because local and global systems are connected to – and mediated by – meso-scale processes, accounting for key meso-scale phenomena, such as labor market functioning, is critical for characterizing GLG interactions. We also conclude that there is great scope for increasing the complexity of GLG analysis in future work. However, this carries significant risks. Increased complexity can outstrip data and modeling capabilities, slow down research, make results more difficult to understand and interpret, and complicate effective communication with decision-makers and other users of the analyses. We believe that research guidance regarding appropriate complexity is a high priority in the emerging field of Global-Local-Global analysis of sustainability.
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The increasing amount of data and the growing use of them in the information era have raised questions about the quality of data and its impact on the decision-making process. Currently, the importance of high-quality data is widely recognized by researchers and decision-makers. Sewer inspection data have been collected for over three decades, but the reliability of the data was questionable. It was estimated that between 25% and 50% of sewer inspection data is not usable due to data quality problems. In order to address reliability problems, a data quality evaluation framework is developed. Data quality evaluation is a multi-dimensional concept that includes both subjective perceptions and objective measurements. Five data quality metrics were defined to assess different quality dimensions of the sewer inspection data, including Accuracy, Consistency, Completeness, Uniqueness, and Validity. These data quality metrics were calculated for the collected sewer inspection data, and it was found that consistency and uniqueness are the major problems based on the current practices with sewer pipeline inspection. This paper contributes to the overall body of knowledge by providing a robust data quality evaluation framework for sewer system data for the first time, which will result in quality data for sewer asset management.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.5220/0006302101880199
