Data-driven Bayesian network modelling to explore the relationships between SDG 6 and the 2030 Agenda

Evaluating complementaries among urban water, energy, infrastructure, and social Sustainable Development Goals in China

Urban areas' performance in water, energy, infrastructure, and socio-economic sectors is intertwined and measurable through Sustainable Development Goals (SDGs) 6-13. Effective synergy among these is critical for sustainability. This study constructs an indicator framework that reflects progress towards these urban SDGs in China. Findings indicate underperformance in SDGs 8-11, suggesting the need for transformative actions. Through network analysis, the research reveals complementarities among these SDGs. Notably, the SDG space divides into socio-economic and ecological clusters, with SDG 6 (Clean Water and Sanitation) central to both. Additionally, SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure) act as bridges, while greater synergies exist between SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action). An in-depth view at the indicator-level shows a core-periphery structure, emphasizing indicators like SDG 6.2 (Wastewater Treatment Rate) and SDG 6.6 (Recycled Water Production Capacity per capita) as pivotal. This study confirms the urban SDG space's stability and predictiveness, underscoring its value in steering well-aligned policy decisions for sustainable growth.

Modelling the availability of water, energy, and food resources in transboundary river basins to achieve Sustainable Development Goals 2, 6, and 7

The Water-Energy-Food Nexus (WEFN) has gained international attention as an approach for managing water more holistically, building on the progress made by the Integrated Water Resources Management (IWRM) approach. However, modelling the availability of water, energy, and food and their interconnections is complex, with major barriers that include the availability of both data and modelling platforms capable of assessing the interconnected systems of the WEFN. There have been attempts to model resource availability in each sector generally, but few attempts to consider the WEFN in complex transboundary basins, especially considering Sustainable Development Goals (SDGs). Here, a water, energy, and food availability model was developed using a combination of remotely sensed, national government reported, and global datasets. The model explores the complex interactions between the physical availability and production of water, energy, and food for several subbasins representing different states. Results showed the potential impacts of socioeconomic development, population changes and transboundary cooperation on resources. Transboundary cooperation in the case study Ma Basin in Southeast Asia, under existing resources and operations could improve monthly food security and reduce coal power operations using excess hydropower in the basin during the dry season. These findings show that transboundary cooperation improves access to energy and food, whilst potentially reducing demands for water. Furthermore, the research has highlighted ways in which transboundary cooperation can further assist in attaining SDGs 12 and 13 on responsible production and climate action, respectively. The modelling framework is easily transferable and can support similar analysis in other basins, contributing to global attainment of several SDGs.

Acosta L, Lee S, Nzimenyera I, Sebestyén V, Abonyi J. Network science and explainable AI-based life cycle management of sustainability models

Model-based assessment of the potential impacts of variables on the Sustainable Development Goals (SDGs) can bring great additional information about possible policy intervention points. In the context of sustainability planning, machine learning techniques can provide data-driven solutions throughout the modeling life cycle. In a changing environment, existing models must be continuously reviewed and developed for effective decision support. Thus, we propose to use the Machine Learning Operations (MLOps) life cycle framework. A novel approach for model identification and development is introduced, which involves utilizing the Shapley value to determine the individual direct and indirect contributions of each variable towards the output, as well as network analysis to identify key drivers and support the identification and validation of possible policy intervention points. The applicability of the methods is demonstrated through a case study of the Hungarian water model developed by the Global Green Growth Institute. Based on the model exploration of the case of water efficiency and water stress (in the examined period for the SDG 6.4.1 & 6.4.2) SDG indicators, water reuse and water circularity offer a more effective intervention option than pricing and the use of internal or external renewable water resources.

Peace engineering and compassionate operations: a framework for leveraging social good

Purpose

Peace engineering and compassionate operations can unlock the potential of emerging technologies for social good. This work aims to investigate the integration of peace engineering and compassionate operations by proposing an integrative framework and identifying the main drivers regarding social good, considering the Sustainable Development Goals (SDGs) landscape.

Design/methodology/approach

The authors used a two-stage methodology by employing a narrative literature review in the first stage to identify the relationships and drivers and propose an original framework. In the second stage, the authors utilized an expert panel to validate the framework’s drivers.

Findings

The authors identified five main categories related to peace engineering and compassionate operations, which were then used to support the categorization of the drivers. In the second stage, the authors validated the drivers with a panel of academicians and experienced industry practitioners.

Practical implications

The proposed framework can provide insightful directions for practitioners and governments to develop strategies and projects in different contexts, including humanitarian logistics, climate change crises, supply chain disruptions, etc.

Originality/value

This work makes unique contributions by reinvigorating an amalgamation of the peace engineering and compassionate operations arenas and their integration with the SDGs to enable enhanced social good, supported by cutting-edge technologies. Thus, this framework’s contributions encompass essential theoretical, managerial, and social implications.

The role of context in identifying linkages between SDG 2 (food) and SDG 6 (water)

The Sustainable Development Goals (SDGs) of the United Nation's Agenda 2030 are formulated to promote the development of integrated, multisectoral policies that explicitly consider linkages across SDGs. Although multiple recent studies have tried to identify linkages across SDGs, the role of contextual factors in identifying SDG linkages is neither well described nor understood. For the case of SDG 2 and SDG 6, this study aims to (i) identify linkages-at country and SDG target level-through the application of various quantitative and qualitative identification methods, and (ii) explore contextual factors to explain the differences across identified linkages. Hereto, we first conducted a text analysis of 195 Voluntary National Reviews (VNRs) reported by 159 countries from 2016 to 2020. Next, we synthesized linkages reported by previous qualitative studies and conducted a quantitative (correlation) analysis on the UN's SDG database. Last, we compared identified linkages across methods, paying special attention to the role of context. From the text analysis, we identified 221 country-specific linkages between 25 SDG target pairs and observed that countries increasingly report SDG linkages in their VNRs over time. Comparing text analysis, existing qualitative studies, and our quantitative correlation analysis, we found substantial differences between the number and nature of linkages identified. These differences can be explained in part by methodological considerations, but to a significant extent also by contextual factors, such as project design, technology application, phase of interventions, and project scale. We conclude by discussing the strengths and limitations of the methods involved, and suggestions for future studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11625-022-01158-3.

Sustainable development goals: conceptualization, communication and achievement synergies in a complex network framework

In this work we use a network-based approach to investigate the complex system of interactions among the 17 Sustainable Development Goals (SDGs), that constitute the structure of the United Nations 2030 Agenda for a sustainable future. We construct a three-layer multiplex, in which SDGs represent nodes, and their connections in each layer are determined by similarity definitions based on conceptualization, communication, and achievement, respectively. In each layer of the multiplex, we investigate the presence of nodes with high centrality, corresponding to strategic SDGs. We then compare the networks to establish whether and to which extent similar patterns emerge. Interestingly, we observe a significant relation between the SDG similarity patterns determined by their achievement and their communication and perception, revealed by social network data. The proposed framework represents an instrument to unveil new and nontrivial aspects of sustainability, laying the foundation of a decision support system to define and implement SDG achievement strategies.

The Contribution of Data-Driven Technologies in Achieving the Sustainable Development Goals

The United Nations’ Sustainable Development Goals (SDGs) set out to improve the quality of life of people in developed, emerging, and developing countries by covering social and economic aspects, with a focus on environmental sustainability. At the same time, data-driven technologies influence our lives in all areas and have caused fundamental economical and societal changes. This study presents a comprehensive literature review on how data-driven approaches have enabled or inhibited the successful achievement of the 17 SDGs to date. Our findings show that data-driven analytics and tools contribute to achieving the 17 SDGs, e.g., by making information more reliable, supporting better-informed decision-making, implementing data-based policies, prioritizing actions, and optimizing the allocation of resources. Based on a qualitative content analysis, results were aggregated into a conceptual framework, including the following categories: (1) uses of data-driven methods (e.g., monitoring, measurement, mapping or modeling, forecasting, risk assessment, and planning purposes), (2) resulting positive effects, (3) arising challenges, and (4) recommendations for action to overcome these challenges. Despite positive effects and versatile applications, problems such as data gaps, data biases, high energy consumption of computational resources, ethical concerns, privacy, ownership, and security issues stand in the way of achieving the 17 SDGs.

Understanding Recent Trends in Global Sustainable Development Goal 6 Research: Scientometric, Text Mining and an Improved Framework for Future Research

The fulfilment of Sustainable Development Goal (SDG) 6, concerning water and sanitation, is critical in itself and also conditional for the other 16 SDGs being met. The purpose of this study was to understand the scientific research trajectories, spatiotemporal development, scientific collaboration, ongoing research themes, and gaps related to SDG 6. We propose a coupling of bibliometric and text mining methods in this work, to statistically portray the impact of water research on the accomplishment of SDG 6. Through the Web of Science database, we focused on a single UN SDG goal (i.e., six related publications that were current (2015–2021)). The study was performed on the chosen 289 publications. With the analysis of Keywords Plus, abstracts, titles, as well as author keywords, we looked at the performance of authors, publications, journals, institutions, and nations in terms of publishing. To obtain an insight into the water and sanitation study topic, we used co-citation, co-occurrence, cooperation networks, theme networks and cluster analysis, word dynamics, thematic evolution, and other techniques. We filtered out five distinguishing themes using text mining and showed their temporal trends. The main outcome is that participation, as well as collaboration with countries of the Global South, is still lacking in the SDG 6 research sphere. Therefore, as an insight from this study, we proposed a conceptual framework, the sustainable development of water and sanitation (SDWS) framework, to classify the research domain of water and sanitation regarding its connections to the environment, economy, and society (i.e., sustainable development). The scientometric and text analysis results provide the contemporary state and overview of the water and sanitation research field, whereas the second, conceptual framework section, provides a better understanding of qualitative contents, by revealing the insights gained, as well as the important work to be done in future water and sanitation studies.

Educational Resources for Geoethical Aspects of Water Management

Global water resources are a critical value for the future of humankind. Conflicts and wars seem to rise because of such critical resources. While water-scarce countries are under extreme pressure on the long-term scale, also water-rich countries in Europe, such as Austria, face local conflicts of interest between water supply, tourism, agriculture, hydropower and ecology, for instance. Higher Education must address these conflicts and the new concepts of geoethics offer the conceptional thinking to do so. Based on educational resources for Higher Education that have been developed in the field of “Geoethics and Water Management” under the Erasmus+ co-funded project GOAL (Geoethics Outcomes and Awareness Learning), selected water-related conflicts are discussed. The cases selected for developing the educational resources are water use conflicts and geoethical aspects of hydropower plants. The educational resources include a subsequent procedure for applying them with students. Outcomes from the educational resources show that issues related to water management often create geoethical conflicts and dilemmas, and an interconnection between several Sustainable Development Goals can be established. Applying the educational resources shall enable geoscientists to contribute towards sustainable development of Earth’s future by a more holistic view.

A natural language processing model for supporting sustainable development goals: translating semantics, visualizing nexus, and connecting stakeholders

Sharing successful practices with other stakeholders is important for achieving SDGs. In this study, with a deep-learning natural language processing model, bidirectional encoder representations from transformers (BERT), the authors aimed to build (1) a classifier that enables semantic mapping of practices and issues in the SDGs context, (2) a visualizing method of SDGs nexus based on co-occurrence of goals (3) a matchmaking process between local issues and initiatives that may embody solutions. A data frame was built using documents published by official organizations and multi-labels corresponding to SDGs. A pretrained Japanese BERT model was fine-tuned on a multi-label text classification task, while nested cross-validation was conducted to optimize the hyperparameters and estimate cross-validation accuracy. A system was then developed to visualize the co-occurrence of SDGs and to couple the stakeholders by evaluating embedded vectors of local challenges and solutions. The paper concludes with a discussion of four future perspectives to improve the natural language processing system. This intelligent information system is expected to help stakeholders take action to achieve the sustainable development goals.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11625-022-01093-3.

Going beyond Global Indicators—Policy Relevant Indicators for SDG 6 Targets in the Context of Austria

Bringing forward sustainable transformation as envisioned within the Agenda 2030 requires comprehensive monitoring of the 17 Sustainable Development Goals (SDGs) formulated therein. To monitor and report progress on goal 6 on clean water and sanitation and its eight pertinent targets, 11 indicators were stipulated in an elaborated process. Yet, through continuous scientific and public scrutiny and debate several gaps and weaknesses were identified. Amongst others, these globally defined indicators are found to reflect weakly the diversity of national realities, capacities and levels of development. To translate the targets into national contexts and fully cover all aspects of the SDG 6 targets, the utilization of complementary indicators is recommended. Within this paper, following a critical appraisal of the SDG 6 indicators, possible complementary indicators are collected from literature and screened based on their quality, relevance for the national context and data availability. A deepened status quo of the SDG 6 targets and corresponding problem areas are outlined for the context of Austria, where water and sanitation infrastructure as well as regulation and governance of water bodies are widely established. Despite increasing the monitoring effort, it is concluded that complementary indicators are practicable to support coherent policy-making and ultimately contribute to the Agenda 2030’s aspiration that all countries take action.

A network approach to rank countries chasing sustainable development

In 2015, the United Nations established the Agenda 2030 for sustainable development, addressing the major challenges the world faces and introducing the 17 Sustainable Development Goals (SDGs). How are countries performing in their challenge toward sustainable development? We address this question by treating countries and Goals as a complex bipartite network. While network science has been used to unveil the interconnections among the Goals, it has been poorly exploited to rank countries for their achievements. In this work, we show that the network representation of the countries-SDGs relations as a bipartite system allows one to recover aggregate scores of countries' capacity to cope with SDGs as the solutions of a network's centrality exercise. While the Goals are all equally important by definition, interesting differences self-emerge when non-standard centrality metrics, borrowed from economic complexity, are adopted. Innovation and Climate Action stand as contrasting Goals to be accomplished, with countries facing the well-known trade-offs between economic and environmental issues even in addressing the Agenda. In conclusion, the complexity of countries' paths toward sustainable development cannot be fully understood by resorting to a single, multipurpose ranking indicator, while multi-variable analyses shed new light on the present and future of sustainable development.

A Robust Approach for Identifying the Major Components of the Bribery Tolerance Index

The paper aims to emphasize the advantages of several advanced statistical and data mining techniques when applied to the dense literature on corruption measurements and determinants. For this purpose, we used all seven waves of the World Values Survey and we employed the Naive Bayes technique in SQL Server Analysis Services 2016, the LASSO package together with logit and melogit regressions with raw coefficients in Stata 16. We further conducted different types of tests and cross-validations on the wave, country, gender, and age categories. For eliminating multicollinearity, we used predictor correlation matrices. Moreover, we assessed the maximum computed variance inflation factor (VIF) against a maximum acceptable threshold, depending on the model’s R squared in Ordinary Least Square (OLS) regressions. Our main contribution consists of a methodology for exploring and validating the most important predictors of the risk associated with bribery tolerance. We found the significant role of three influences corresponding to questions about attitudes towards the property, authority, and public services, and other people in terms of anti-cheating, anti-evasion, and anti-violence. We used scobit, probit, and logit regressions with average marginal effects to build and test the index based on these attitudes. We successfully tested the index using also risk prediction nomograms and accuracy measurements (AUCROC > 0.9).

Sustainability-Oriented Model to Decide on Concrete Pipeline Reinforcement

The design of sustainable sewerage infrastructure is fundamental for achieving long-term sustainability goals. Piping systems are essential components in the water supply chain and in waste disposal systems worldwide. Among possible designs for concrete pipes, steel cages consisting of curved rebars have been predominantly used as reinforcement. However, structural fibres have emerged as an attractive technical and economical alternative for substituting steel cages. Due to increasing urbanisation, thousands of kilometres of pipes will be constructed in the near future. At present, decisions regarding reinforcement of concrete pipes are primarily cost-driven. To consider other aspects, it is fundamental to identify and quantify potential sustainability issues properly. Hence, this paper focuses on the sustainability analysis of reinforced concrete pipes using a multi-criteria decision-making method. A model based on criteria, indicators, weights and value functions is developed and calibrated by assessing various concrete reinforcement strategies (steel bars or steel/synthetic fibres). The main contributions of the article are the proposal and application of a model for the case of concrete pipes which can be adapted for other case studies; determining how different typologies of pipes contribute to the overall sustainability of infrastructure systems; and the use and application of a robust and interesting multi-criteria decision-making methodology. The results show that fibre reinforced concrete pipes are promising alternatives in social, economic and environmental terms. Both the model and results are expected to be useful to stakeholders in decision-making processes.

Sociological modeling of smart city with the implementation of UN sustainable development goals

The COVID-19 pandemic before mass vaccination can be restrained only by the limitation of contacts between people, which makes the digital economy a key condition for survival. More than half of the world's population lives in urban areas, and many cities have already transformed into "smart" digital/virtual hubs. Digital services ensure city life safe without an economy lockout and unemployment. Urban society strives to be safe, sustainable, well-being, and healthy. We set the task to construct a hybrid sociological and technological concept of a smart city with matched solutions, complementary to each other. Our modeling with the elaborated digital architectures and with the bionic solution for ensuring sufficient data governance showed that a smart city in comparison with the traditional city is tightly interconnected inside like a social "organism". Society has entered a decisive decade during which the world will change by moving closer towards SDGs targets 2030 as well as by the transformation of cities and their digital infrastructures. It is important to recognize the large vector of sociological transformation as smart cities are just a transition phase to human-centered personal space or smart home. The "atomization" of the world urban population raises the gap problem in achieving SDGs because of different approaches to constructing digital architectures for smart cities or smart homes in countries. The strategy of creating smart cities should bring each citizen closer to SDGs at the individual level, laying in the personal space the principles of sustainable development and wellness of personality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11625-020-00889-5.

Water-related challenges in nexus governance for sustainable development: Insights from the city of Arequipa, Peru

Peru has one of the fastest-growing economies in Latin America, but there are concerns regarding how long this can be sustained. Negative environmental impacts are increasing due to the pressures of a growing urban population and competition for natural resources. This study explores stakeholder perceptions linked to nexus governance in the context of integrated management of natural resources, particularly water, and the environmental, socio-economic and governance challenges constraining the achievement of UN Sustainable Development Goals (SDGs). Our analysis focused on the urban and rural areas associated with the city of Arequipa, an economically dynamic region subject to extreme levels of water stress. Face-to-face interviews with key informants were conducted to identify mechanisms that have enhanced successful multi-sectoral collaboration, and to assess challenges in promoting sustainable economic development. A workshop prioritised the identified challenges and an online survey was then used to assess stakeholder interest in and influence over nexus governance of water with other natural resources. Stakeholder mapping revealed a complex network of actors involved in nexus governance, where successful collaboration could be promoted through formal and informal mechanisms, including exemplar policies and initiatives across sectors and actors. Shared visions between stakeholders were identified as well as contradictory priorities relating to the sustainable management of natural resources. A key finding that emerged was the need to promote adaptation in water and land management (SDG 6) due to perceived impacts of extreme climate events (SDG 13), urban population growth (SDG 11), and increased sectoral water demands. This situation in combination with poor governance and lack of planning has exposed the vulnerability of Arequipa water supply system to future shocks. Urgent action will be needed to raise stakeholder awareness, strengthen governance and enforcement, and agree on a collective vision for integrated land and water planning if the SDGs are to be achieved.