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- 2022 (13) (entfernen)
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The worldwide decline of plant and insect species during the last decades has far-reaching consequences for the functionality of ecosystems and their inherent processes. Pollination as one of them is an indispensable ecosystem service for human wellbeing. However, an increasing number of pollinator and plant species are threatened by multiple, interacting, and sometimes synergistic causes that are becoming a growing threat to ecosystem functioning. Given the loss of plant species diversity, it is increasingly difficult for pollinators to find food throughout the year. Therefore, this study analyses the influence of plant diversity on pollinators. The study was conducted in the course of the Jena Experiment, which is a long-term biodiversity experiment (since 2002) with 60 plant species, common to Central European Arrhenatherum grasslands. With a plant diversity gradient of 1, 2, 4, 8, 16, and 60 plant species per plot, time-series data resulted from a wide range of ecosystem processes, ranging from productivity, decomposition, C-storage, and N-storage to herbivory, and pollination. These were studied to investigate the mechanisms underlying the relationships between biodiversity and ecosystem processes. Chapter 2 studies the spatio-temporal distribution of pollinators on flowers along an experimental plant diversity gradient. In particular, the spatial pollinator behaviour was examined. Chapters 3 and 4 continues on the chemical composition of flower nectar (nectar) of various plant species. The chemical composition of the nectar was analysed for the two most important macronutrients, carbohydrates (C) and amino acids (AA), using high performance liquid chromatography (HPLC). Subsequently, their contents were analysed in terms of concentration, proportional content and the ratio of carbohydrates to amino acids (C:AA). In Chapter 3, the nectar of 34 plant species from the grasslands of the Jena Experiment was compared. In Chapter 4, nectar was investigated in the context of diversity effects on the example of the plant species Field Scabious, Knautia arvensis. It was analysed to what extent the nectar quality (nutrient content) differs between plant individuals of one species. Overall, these studies indicate how fragile plant-pollinator interactions are but also how important plant species-rich grasslands are to support plant-pollinator interactions. Increased plant species diversity is essential to ensure the availability of flowering resources throughout the year. Pollinators, such as honeybees, bumblebees, solitary bees, and hoverflies can use the niches in time and in vertical space complementarily. However, in plant species-poor grasslands there may be more niche overlaps, which is probably due to a reduced availability of resources. This points to the need to include different plant species belonging to different plant families, whose nectar may have evolved in response to morphological flower traits and metabolic pathways. Therefore plant species diversity can supply pollinators with nectar differing in carbohydrate and amino acid content and thus differing in quality. Also C-AA ratios have proven to be a useful measurement to reveal differences between plant species. In addition, C:AA ratios were not differing in nectar of K. arvensis individuals growing in different plant species richness levels, although their nectar seemed to be more attractive in mixtures with 16 plant species, likely due to higher content of essential and phagostimulatory amino acids than in plant species-poor mixtures.
Crowdfunding is considered a promising instrument for transforming existing socio-technical regimes by financing radical innovations of such entrepreneurs. However, this potential has not yet been fully explored. Therefore, this dissertation addresses the overarching research question of how sustainable entrepreneurs can exploit the full potential of investment-based crowdfunding to develop from niche operators to actors in the socio-technical regime. Five journal articles and one book chapter are included in this PhD project, which use a wide range of quantitative methodologies. In the framework paper, the findings are conceptually evaluated on a meta-level by applying the multi-level perspective. The key insights can be assigned to four categories, including the financing and marketing function, the target group, and the project presentation. The analysis shows that investment-based crowdfunding is suitable to equally fund and market the business ideas of environmental entrepreneurs, since the quest for entering the mass market is highest for such ventures. In contrast, purely social entrepreneurs tend to conduct crowdfunding projects on a smaller scale and probably aim to stay in the niche. Nevertheless, profit-oriented social entrepreneurs are still encouraged to use investment-based crowdfunding for funding and marketing purposes. The prominent display of environmental effects (e.g. the amount of compensated greenhouse gases) and financial incentives (e.g. high interest rates) has a high impact on the investment decision of individuals on investment-based crowdfunding platforms. The case of fairafric is used as a best practice example to demonstrate how crowdfunding can be a stepping stone for sustainability-oriented niche actors to enter the mass market. The fair-trade and organic chocolate manufacturer has undergone six crowdfunding campaigns which enabled it to grow and build a strong community of supporters. The outcomes of this dissertation clarify how sustainable entrepreneurs can unleash the potential of investment-based crowdfunding for financing and marketing purposes.
Collaborative governance is a promising approach to address the difficult challenges of sustainability through global public and private partnerships between diverse actors of state, market and civil society. The textile and clothing industry is an excellent example where a variety of such initiatives have evolved to address the wicked sustainability challenges. However, the question arises whether collaborative governance actually leads to transformation. In this dissertation, the author therefore questions whether and how collaborative governance in the textile sector provides space for, or pathways to, sustainability transformation. In three scientific articles and this framework paper, the author uses a mixed-methods research approach and follows scholars of sustainability science towards transformation research. First, he conducts a systematic literature review on inter-organizational and governance partnerships before diving into a critical case study on an interactive collaborative governance initiative, the German Partnership for Sustainable Textiles (Textiles Partnership). The multi-stakeholder initiative (MSIs) was initiated by the German government in 2015 and brings together more than 130 organizations and companies from seven stakeholder groups. It aims at improving working conditions and reducing environmental impacts in global textile and clothing supply chains. In two empirical articles, the author then explores learning spaces in the partnership and the ways in which governance actors navigate the complex governance landscape. For the former, he uses a quantitative and qualitative social network analysis based on annual reports and qualitative interviews with diverse actors from the partnership. Then, he uses qualitative content analysis of the interviews, policy documents and conducts a focus group discussion to validate assumptions about the broader empirical governance landscape and the social interactions within. Finally, in this framework paper, he uses theories of transformation to distinguish forms of change and personal, political and practical spheres of transformation, and reflects on the findings of the three articles in this cumulative dissertation.
Urban areas are prone to climate change impacts. Simultaneously the world's population increasingly resides in cities. In this light, there is a growing need to equip urban decision makers with evidence-based climate information tailored to their specific context to adequately adapt to and prepare for future climate change. To construct climate information high-resolution regional climate models and their projections are pivotal. There is a need to move beyond commonly investigated variables, such as temperature and precipitation, to cover a wider breath of possible climate impacts. In this light, the research presented in this thesis is centered around enhancing the understanding about regional-to-local climate change in Berlin and its surroundings, with a focus on humidity. More specifically, following a regional climate modelling and data analysis approach, this research aims to understand the potential of regional climate models, and the possible added value of convection-permitting simulations, to support the development of high-quality climate information for urban regions, to support knowledge-based decision-making. The first part of the thesis investigates what can already be understood with available regional climate model simulations about future climate change in Berlin and its surroundings, particularly with respect to humidity and related variables. Ten EURO-CORDEX model combinations are analyzed, for the RCP8.5 emission scenario during the time period 1970-2100, for the Berlin region. The results are the first to show an urban-rural humidity contrast under a changing climate, simulated by the EURO-CORDEX ensemble, of around 6% relative humidity, and a robust enlarging urban drying effect, of approximately 2-4% relative humidity, in Berlin compared to its surroundings throughout the 21st century. The second part explores how crossing spatial scales from 12.5km to 3km model grid size affects unprecedented humidity extremes and related variables under future climate conditions for Berlin and its surroundings. Based on the unique HAPPI regional climate model dataset, two unprecedented humidity extremes are identified happening under 1.5°C and 2°C global mean warming, respectively SH>0.02 kg/kg and RH<30%. Employing a double-nesting approach, specifically designed for this study, the two humidity extremes are downscaled to the 12.5km grid resolution with the regional climate model REMO, and thereafter to the 3km with the convection-permitting model version of REMO (REMO NH). The findings indicate that the convection-permitting scale mitigates the SH>0.02kg/kg moist extreme and intensifies the RH<30% dry extreme. The multi-variate process analysis shows that the more profound urban drying effect on the convection-permitting resolution is mainly due to better resolving the physical processes related to the land surface scheme and land-atmosphere interactions on the 3km compared to the 12.5km grid resolution. The results demonstrate the added value of the convection-permitting resolution to simulate future humidity extremes in the urban-rural context. The third part of the research investigates the added value of convection-permitting models to simulate humidity related meteorological conditions driving specific climate change impacts, for the Berlin region. Three novel humidity related impact cases are defined for this research: influenza spread and survival; ragweed pollen dispersion; and in-door mold growth. Simulations by the regional climate model REMO are analyzed for the near future (2041-2050) under emission scenario RCP8.5, on the 12.5km and 3km grid resolution. The findings show that the change signal reverses on the convection-permitting resolution for the impact cases pollen, and mold (positive and negative). For influenza, the convection-permitting resolution intensifies the decrease of influenza days under climate change. Longer periods of consecutive influenza and mold days are projected under near-term climate change. The results show the potential of convection-permitting simulations to generate improved information about climate change impacts in urban regions to support decision makers. Generally, all results show an urban drying effect in Berlin compared to its surroundings for relative and specific humidity under climate change, respectively for the urban-rural contrast throughout the 21st century, for the downscaled future extreme conditions, and for the three humidity related impact cases. Added value for the convection-permitting resolution is found to simulate humidity extremes and the meteorological conditions driving the three impacts cases.
The transition of our energy system towards a generation by renewables, and the corresponding developments of wind power technology enlarge the requirements that must be met by a wind turbine control scheme. Within this thesis, the role of modern, model-based control approaches in providing an answer to present and future challenges faced by wind energy conversion systems is discussed. While many different control loops shape the power system in general, and the energy conversion process from the wind to the electrical grid specifically, this work addresses the problem of power output regulation of an individual turbine. To this end, the considered control task focuses on the operation of the turbine on the nonlinear power conversion curve, which is dictated by the aerodynamic interaction of the wind turbine structure and the current inflow. To enable a power tracking functionality, and thereby account for requirements of the electrical grid instead of operating the turbine at maximum efficiency constantly, an extended operational range is explicitly considered in the implemented control scheme. This allows for an adjustment of the produced power depending on the current state of the electrical grid and is one component in constructing a reliable and stable power system based on renewable generation. To account for the nonlinear dynamics involved, a linear matrix inequalities approach to control based on Takagi-Sugeno modeling is investigated. This structure is capable of integrating several degrees of freedom into an automated control design, where, additionally to stability, performance constraints are integrated into the design to account for the sensitive dynamical behavior of turbines in operation and the loading experienced by the turbine components. For this purpose, a disturbance observer is designed that provides an estimate of the current effective wind speed from the evolution of the measurements. This information is used to adjust the control scheme to the varying operating points and dynamics. Using this controller, a detailed simulation study is performed that illustrates the experienced loading of the turbine structure due to a dynamic variation of the power output. It is found that a dedicated controller allows wind turbines to provide such functionality. Additionally to the conducted simulations, the control scheme is validated experimentally. For this purpose, a fully controllable wind turbine is operated in a wind tunnel setup that is capable of generating reproducible wind conditions, including turbulence, in a wide operational range. This allows for an assessment of the power tracking performance enforced by the controller and analysis of the wind speed estimation error with the uncertainties present in the physical application. The controller showed to operate the turbine smoothly in all considered operating scenarios, while the implementation in the real-time environment revealed no limitations in the application of the approach within the experiments. Hence, the high flexibility in adjusting the turbine operating trajectories and structural design characteristics within the model-based design allows for efficient controller synthesis for wind turbines with increasing functionality and complexity.
Human activities have become a major driver of global change, so that global society and economy are facing consequences such as climate change, increasing scarcity of resources, environmental pollution and degradation as well as disturbances of ecosystem functioning and services.In order to meet these main challenges in an appropriate way, adequate starting points and solutions must be pursued at all levels to shift the current socio-economic pathway from an unsustainable to a safe operating and thus sustainable development within the planetary boundaries. One of the application concepts in industrial contexts is Industrial Symbiosis (IS), which deals with the set-up of advanced circular/cascading systems, in which the energy and material flows are prolonged for multiple material and energetic (re-)utilization within industrial systems in order to increase resource productivity and efficiency, while reducing environmental impacts. The overarching goal of the research project was to identify and develop approaches to enable the evolution of Industrial Symbiosis (IS) in Industrial Parks (IPs). IS is a collaborative cross-sectoral approach to connect the resource supply and demand of various industries in order to optimize the resource use through exchange of materials, energy, water and human resources across different companies, while generating ecological, technical, social and economic benefits. Many Information Communication Technology (ICT) tools have been developed to facilitate IS, but they predominantly focus on the as-is analysis of the IS system, and do not consider the development of a common desired target vision or corresponding possible future scenarios as well as conceivable transformation paths from the actual to the defined (sustainability) target state. This gap shall be addressed in this work, presenting the software requirements engineering results for a holistic IT-supported IS tool covering system analysis, transformation simulation and goal-setting. This study also aims to present the conceptual IT-supported IS tool and its corresponding prototype, developed for the identification of IS opportunities in IPs. This IS tool serves as an IS facilitating platform, providing transparency among market players and proposing potential cooperation partners according to selectable criteria (e.g. geographical radius, material properties, material quality, purchase quantity, delivery period). Therefore a quantitative indicator system was compiled and recurring patterns were identified to utilize this knowledge in the comprehensive IT-supported IS tool. So this IS tool builds the technology-enabled environment for the processes of first screening of IS possibilities and initiation for further complex business-driven negotiations and agreements for long-term IS business relationships.
Transformative learning is increasingly set to become an essential component in sustainability transformation. Despite, little has been done to systematically explore the contribution to sustainability transformation. This learning theory developed decades ago independently of sustainability discourses; however, it provides an analytical framework for understanding the learning processes, outcomes and conditions in individual and social learning towards sustainability transformation. Against this background, the following research question arises: To which extent can transformative learning lead to sustainability transformation? This doctoral work aims to explore transformative learning processes, outcomes, and conditions occurring and advancing towards sustainability transformation of the textile-fashion industry in Mexico. Taking an exploratory approach, the methods employed were literature reviews to untangle concepts and to construct theoretical pillars to support the empirical research design and data analysis. For data collection, snowball-sampling techniques were used to explore the practice field of the textile-fashion industry in Mexico. Qualitative interviews were employed to gather data about the learning experiences of actors. Qualitative and quantitative methods were required to perform the respective data analysis, the qualitative codification of interviewees' responses. Analysis of social media content was also utilised to understand the communication and business practices of projects involved in the transformation of the textile-fashion sector. As a result, this work comprises three articles, one a systematic literature review and two empirical research articles, investigating the transformative learning processes of entrepreneurs in the development of sustainability niches. As for the findings of this doctoral work, the use of transformative learning in sustainability transformation requires a careful study of the theory and its conceptual elements. Regarding the case study, transformative learning is inherent in forming and developing sustainability niches as entrepreneurs venture into them: It is individual prior learning, expectations and actions that initiate the path of sustainability transformation while disorienting dilemmas, critical reflection, and discourse accelerate them. Through these stages, it is when individual learning turns into social learning. On the other hand, based on the multi-level perspective, the interplay between the niche, regime and landscape levels generates a space for sustainability transformation and transformative learning.
The global coffee market is connected to many sustainability issues like the persisting poverty of coffee farmers, and degrading ecosystems. Many interventions, from state-led regulation to industry-led certification processes, exist, that try to change global value chains to shift societies back on more sustainable trajectories. To this date, it is still under debate if these interventions are an effective means to change global value chains. With climate change and persisting issues of social justice as strong accelerators, calls are increasingly made for a radical transformation of global production and consumption patterns. Many frameworks try to inform research and real-world policies for a transformation of global value chains. In this dissertation, the author uses the framework of the practical, political and personal sphere proposed by O'Brien and Sygna (2013) highlighting that the interactions between these three spheres bare the greatest potential for a transformation towards sustainability. However, in this dissertation, the author argues that it is exactly at the nexus between the three spheres of transformation where barriers towards a fundamental shift of systems occur. He, therefore, uses three perspectives to bring empirical nuance to the problems that arise on the interplay between the different spheres of transformation. (1) The scientific perspective: using a systematic review of alternative trade arrangements; (2) the producer perspective: facilitating a participatory network analysis of social-ecological challenges of Ugandan coffee farmers and their adaptive management practices; (3) the consumer perspective: through the use of a German consumer survey and a structural equation model to investigate into the Knowledge-Doing-Gap end-consumers are facing. Through the results from the scientific perspective, the author is able to show that most of the research is investigating the certified market and that the effectiveness of labels rarely exceeding the practical sphere. His empirical research on the producer perspective highlights that Ugandan coffee farmers facilitate a variety of on-farm crop management (practical sphere) but their support structures rarely exceed informal exchange with neighboring communities (political sphere). Exchange with governmental actors and global traders is happening but has been assessed as not sufficient to cope with the social-ecological challenges the producers are facing. Through the results of the consumer perspective, the author is able to highlight that even though end-consumers have pro-sustainable attitudes (personal sphere) they are facing situational constraints (political sphere) that create a gap between their attitudes and the respective behavior. Using these empirical insights about drivers and barriers for a transformation he proposes that frameworks, aiming to inform research and policies, need to include two aspects: (1) the notion of a forced transformation; and (2) the translational capacity of the frameworks to create meaningful interdisciplinary discourses in different contexts. The author, therefore, propose two approaches:(1) a fourth sphere, called the "planetary force" to include the notion of a forced transformation that is already happening in different contexts, highlighted by the producer perspective in this dissertation; and (2) the consequent use of methods that create interdisciplinary exchange and rigorous testing.
Rangelands are the most widespread land-use systems in drylands, where they often represent the only sustainable form of land-use due to the limited water availability. The intensity of the land-use of such rangeland ecosystems in drylands depends to a large extent on the climatic variability in time and space. Rangeland systems are seriously threatened by climate change, because climate change will alternate the availability of water in time and space. This dissertation therefore deals with the question which role climatic variability plays for the effects of grazing on vegetation in dry rangelands. The relatively intact steppes in central Mongolia were chosen as a model system. They are characterised by low precipitation and high climatic variability in the south (100mm annual precipitation), and comparatively high precipitation and low climatic variability in the north (250mm). The effects of grazing on vegetation on 15 grazing transects were investigated along the climatic gradient. The central elements were the plant species and their abundances on 10m x 10m areas, for which functional characteristics such as height, affiliation of functional groups or leaf nutrients were recorded. The main hypothesis of this dissertation is that grazing has a greater impact on vegetation communities with increasing rainfall. To test this hypothesis, three studies were carried out. In a first study, the research group found that the vegetation communities in the dry area differ strongly along the climatic gradient, while the plant communities in the wetter area differ more strongly along the grazing gradient. The results of the second study suggested that this difference can be explained by a functional environmental filter that becomes weaker from south to north as the niche spectrum increases. The third study has shown that this is likely a function of the higher availability of resources, which at the same time leads to higher grazing pressure, therewith stressing the vegetation especially in years with droughts. In summary, the author concludes that the climate gradient also represents an environmental filter that filters species for certain characteristics, thus having a significant influence on the vegetation. Climatic variability influences the effect of grazing on vegetation, which is particularly problematic where the grazing intensity is high and the species are less adapted to strong climatic fluctuations. Future scenarios predict increasing productivity and therefore increasing livestock density. This may lead to an increase in floristic and functional diversity across the climate gradient, but also to increasing grazing effects and therefore threads for overgrazing. Increasing climatic variability is likely to intensify this thread, especially in the moister regions, whereas the dry rangelands are likely to be more resilient due to the adaptation of the plants to non-equilibrium dynamics.
Design methods for collaborative knowledge production in inter- and transdisciplinary research
(2022)
This dissertation seeks to better understand how design methods facilitate collaborative knowledge production and integration in inter- and transdisciplinary sustainability research. Through five independent papers, this dissertation contributes to addressing the research question on four levels – conceptual-epistemological, empirical, methodological and practical. By exploring the linkages between design research and inter- and transdisciplinary research, a conceptual basis for the targeted use of design methods in collaborative processes of inter- and transdisciplinary research is laid and their spectrum of methods is expanded. This is followed by the development of a transformative epistemology in and for problem-oriented, collaborative forms of research, such as transdisciplinary sustainability research, called problematic designing. Based on a deeper understanding of integration and collaborative knowledge production, as well as its accompanying challenges, empirical research into applying design prototyping as a method in and for situations of collaborative research was conducted. To this end, the findings provide a fundamental basis for the facilitation of inter- and transdisciplinary research processes when dealing with complex problems. With its inherent openness and iterative approach in addressing the unknowns of complex phenomena, design prototyping contributes to the required form of imagination that enables to anticipate possible futures. Furthermore, by including visual-haptic modes of expression, design prototyping reduces the dominance of language and text in scientific negotiation processes and does justice to the diversity of cognitive modes. Finally, the empirical findings of this dissertation emphasise the importance of the visual-haptic dimension for collaborative knowledge production and the communication of knowledge, and provide insights into the visual structuring of human thought processes. The results on material metaphors, collaborative prototyping and material-metaphorical imagery contribute decisively to the basic knowledge of the epistemological quality of design and the importance of the visual and haptic for thought processes in general. The extension and adaptation of existing analysis methods in this dissertation add to the further development of analysis of visual-haptic data. The results are once again reflected in the synthesis of this framework paper as cross-cutting issues.
Food forests present a promising solution to address multiple sustainability challenges adaptable to local contexts. As biodiverse multi-strata agroforestry systems, they can provide several ecological, socio-cultural and economic services. They sequester carbon, limit soil erosion and regulate the micro-climate; they offer the opportunity for education on healthy diets and ecology, and they produce food and can create livelihood opportunities. However, despite their obvious benefits, food forests are still a niche concept. To date, research has focused on their ecological and social services; we lack an understanding of food forests as a comprehensive sustainability solution, including their economic dimension, and knowledge on how to develop them. Addressing these gaps, this qualitative research used a solution- and process-oriented methodology guided by transformational sustainability research. In a comparative case study approach, it created an inventory of 209 food forests, followed by interviews and site visits of 14 sites to understand their characteristics and assess their sustainability (Article 1). More indepth, it analyzed the implementation path of seven food forest for success factors, barriers and coping strategies (Article 2). Based on these insights, two experimental case studies were initiated to develop sustainable food forests with practice partners, one based in Phoenix, Arizona, U.S. and one in Lüneburg, Germany. Two studies analyzed the cases' outputs and processes highlighting success factors and challenges, including the role of a sustainable entrepreneurial ecosystem (Article 3, Phoenix case) and key features of productive partnerships to understand why one case succeeded and the other failed (Article 4). Findings include key features of existing and sustainable food forests as well as success factors on how to develop them; namely acquiring a complementary skill set that includes specialty farming and entrepreneurial know-how, securing sufficient start-up funds and long-term land access as well as overcoming regulatory restrictions. Supporting institutions are especially needed to integrate and professionalize the planning stage and provide know-how on alternative business practices. Key features of productive partnerships include an entrepreneurial attitude, access to support functions, long-term orientation and commitment to food system sustainability.
Companies increasingly use social and environmental accounting and reporting (SEAR) to measure, manage, and report their influence on ecological and social issues, i.e., climate change and human rights violations. Nowadays, there are many different tools, frameworks, and standards for SEAR that companies can use. Beyond the content presented in the tool itself, e.g., social and/or ecological information, these tools differ, among others, by the language used and the type of data collected (e.g., qualitative, quantitative, or monetary data). This dissertation aims to expand previous literature by clarifying the effects of SEAR on corporate decision-making and its influencing factors. Additionally, antecedents for implementation and use of SEAR in regard to supporting sustainability decision-making are discussed. For this purpose, the given dissertation investigates public sustainability reports by companies with different environmental orientation, conducts two survey-based case studies on the effects of different types of SEAR and one qualitative case study on the antecedents of institutionalizing management accounting change through SEAR. The results lead to seven criteria that practitioners and researchers should recognize for supporting successful SEAR regarding a company's environmental orientation, the role of employees and leadership as well as the specific SEAR tool itself.
Undertaking local actions, such as implementing public (sustainability) policy, plays a crucial role in achieving sustainable development (SD) at the municipal level. In this regard, indicator-based assessment supports effective implementation by measuring the SD process, based upon evidence-based outcomes that indicators produce. Over the last decade, using subjective indicators, which rely on an individual's self-perception to measure subjects, has gained its significance in sustainability assessment, in line with the increasing importance of signifying individual's and community's well-being (WB) in the context of SD. This study aims to discuss and clarify the scope and functions of subjective sustainable development indicators (SDIs) conceptually and theoretically while examining the usability of such indicators employed in the practice of assessing sustainability policy and action process in a Japanese municipality. Furthermore, the potential usability of using subjective SDIs in monitoring a municipal initiative of the United Nations’ Sustainable Development Goals (SDGs) is also explanatorily examined. The present paper consists of a framework paper and three individual studies. In the framework paper, Section 1 introduces the global transition of SD discourse and the role that local authorities and implementing public policy play in achieving SD while outlining how WB positions in the SD context. Section 2 provides a brief overview of the major scope of overall SDIs at the conceptual and theoretical levels. Section 3 defines WB in the study's own right while exploring the scope of indicators measuring WB. In addition, this study strives to further clarify the peculiar scope of SDIs, measuring WB by synthesising the findings. Section 4 overviews how SD at the municipal level in Japan is practiced while acknowledging the extent to which residents perceive WB and SDGs in policymaking. Section 5 provides a brief yet extensive summary of the three individual studies. Section 6 discusses the findings while presenting implications for further study and practices of subjective SDIs. Furthermore, the three individual studies provide a thorough and in-depth discussion of the study subject. Study 1 illustrates the SD trend at the municipal level in Japan and the growing recognition of using subjective SDIs in public (sustainability) policy assessment in exploring comparative SDI systems to municipality groups. The findings, in turn, raise the need for a further study on subjective SDIs. Study 2 extensively discusses the concept of WB as the overarching subject to be measured while examining varying approaches and scopes of SDIs. It identifies three differentiated WB (i.e., material and social objective WB as well as subjective WB) and distinctive approaches of subjective SDIs (i.e., expert-led and citizen-based approaches) alongside objective SDIs. The findings suggest that these SDIs identified are, conceptually, most capable of measuring associated WB; for instance, citizen-based subjective SDIs can most optimally measure subjective WB. Finally, Study 3 examines the usability of (citizen-based) subjective SDIs in a practice of assessing public policy, aiming at municipal SD, and the potential usability of using such indicators in monitoring a municipal SDG initiative. The findings highlight the determinants and obstacles of using subjective SDIs as well as signifying WB in measuring progress of a municipal SD practice.