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The world should redouble its efforts on the SDGs, not abandon them. Here's how to progress the United Nations' agenda towards 2050., QC 20240708

Access to electricity is a prerequisite for development, included in both the Agenda for Sustainable Development and the African Union’s Agenda 2063. Still, universal access to electricity is elusive to large parts of the global population. In Somalia, approximately one-third of the population has access to electricity. The country is unique among non-island countries as it has no centralized grid network. This paper applies a geospatial electrification model to examine paths towards universal access to electricity in Somalia under different timelines and with regard to different levels of myopia in the modeling process. This extends the previous scientific literature on geospatial electrification modeling by studying the effect of myopia for the first time and simultaneously presenting the first geospatial electrification analysis focused on Somalia. Using the Open Source Spatial Electrification Tool (OnSSET), the least-cost electrification options towards 2030 and 2040, respectively, are compared. We find that under the shorter timeline, a deployment of mini-grids and stand-alone PV technologies alone provides the least-cost option under all but one scenario. However, under the longer timeline, the construction of a national transmission backbone would lower overall costs if there is high demand growth and/or low cost of centralized grid electricity generation. We also compare different levels of myopia in the modeling process. Here, OnSSET is first run directly until 2040, then in five-year time-steps and annual time-steps. We find that running the model directly until 2040 leads to the lowest costs overall. Running the model myopically leads to a sub-optimal, more costly technology mix, with a lock-in effect towards stand-alone systems. On the other hand, the myopic approach does provide additional insights into the development of the system over time. We find that longer-term planning favors the centralized grid network, whereas short-sighted myopic planning ca, QC 20231030

As of 2021, 675 million people globally lack access to electricity. Geospatial electrification tools can be used to identify the mix of grid-extension, mini-grids and stand-alone technologies that can supply currently unelectrified areas at the lowest cost. Several such tools have been developed, at different levels of modelling detail and complexity. In this paper, we improve the Open Source Spatial Electrification Tool (OnSSET) to develop a flexible geospatial electrification tool that can still run lighter rapid assessments for a first estimate of the technology split, but now also more detailed analysis with higher spatial and temporal resolution used for grid routing, distribution network design and optimization of hybrid mini-grid generation introduced through new algorithms. We compare the existing light and new detailed versions of the tool through a case study of the north-western parts of the Democratic Republic of the Congo. We find that the new grid routing algorithm lead to more off-grid technologies, and that the detailed design of distribution networks lead to a reduction in stand-alone technologies. The detailed optimization of hybrid mini-grids display varying effects at different demand levels. Given the increased computational effort that is observed with higher modelling detail, we discuss the implications for scenario design and selection of geospatial electrification tool for future analyses aiming to support the achievement of SDG 7., QC 20231006

Understanding the progress of the Sustainable Development Goals (SDGs) proposed by the United Nations (UN) is important, but difficult. In particular, policymakers would need to understand the sentiment within the public regarding challenges associated with climate change. With this in mind and the rise of social media, this work focuses on the task of uncovering the sentiment of Twitter users concerning climate-related issues. This is done by applying modern natural-language-processing (NLP) methods, i.e. VADER, TextBlob, and BERT, to estimate the sentiment of a gathered dataset based on climate-change keywords. A transfer-learning-based model applied to a pre-trained BERT model for embedding and tokenizing with logistic regression for sentiment classification outperformed the rule-based methods VADER and TextBlob; based on our analysis, the proposed approach led to the highest accuracy: 69%. The collected data contained significant noise, especially from the keyword 'energy'. Consequently, using more specific keywords would improve the results. The use of other methods, like BERTweet, would also increase the accuracy of the model. The overall sentiment in the analyzed data was positive. The distribution of the positive, neutral, and negative sentiments was very similar in the different SDGs., QC 20230901

In this chapter we extend earlier work (Vinuesa et al., Nat Commun 11, 2020) on the potential of artificial intelligence (AI) to achieve the 17 Sustainable Development Goals (SDGs) proposed by the United Nations (UN) for the 2030 Agenda. The present contribution focuses on three SDGs related to healthy and sustainable societies, i.e., SDG 3 (on good health), SDG 11 (on sustainable cities), and SDG 13 (on climate action). This chapter extends the previous study within those three goals and goes beyond the 2030 targets. These SDGs are selected because they are closely related to the coronavirus disease 19 (COVID-19) pandemic and also to crises like climate change, which constitute important challenges to our society., Part of book ISBN 978-3-031-21147-8QC 20230725

QC 20230725

The 2030 Agenda of the United Nations (UN) revolves around the Sustainable Development Goals (SDGs). A critical step towards that objective is identifying whether scientific production aligns with the SDGs' achievement. To assess this, funders and research managers need to manually estimate the impact of their funding agenda on the SDGs, focusing on accuracy, scalability, and objectiveness. With this objective in mind, in this work, we develop ASDG, an easy-to-use Artificial-Intelligence-based model for automatically identifying the potential impact of scientific papers on the UN SDGs. As a demonstrator of ASDG, we analyze the alignment of recent aerospace publications with the SDGs. The Aerospace data set analyzed in this paper consists of approximately 820,000 papers published in English from 2011 to 2020 and indexed in the Scopus database. The most-contributed SDGs are 7 (on clean energy), 9 (on industry), 11 (on sustainable cities), and 13 (on climate action). The establishment of the SDGs by the UN in the middle of the 2010 decade did not significantly affect the data. However, we find clear discrepancies among countries, likely indicative of different priorities. Also, different trends can be seen in the most and least cited papers, with apparent differences in some SDGs. Finally, the number of abstracts the code cannot identify decreases with time, possibly showing the scientific community's awareness of SDG., QC 20230412

Universal clean cooking is a key target under Sustainable Development Goal (SDG) 7, with implications for several other SDGs, such as good health, gender equality and climate. Yet, 2.4 billion people globally still lack access to clean cooking. The situation is especially dire in sub-Saharan Africa (SSA), where only 17% use clean options. We develop OnStove, an open-source spatial tool comparing the relative potential of different cookstoves on the basis of their costs and benefits, and apply it to SSA. Our results suggest a severe market failure as the currently most used solution, traditional biomass, produces the lowest social net-benefits nearly everywhere in SSA. Correcting this failure, which stems from multiple market and behavioural obstacles, would deliver significant health, time and emission benefits but requires identification and promotion of policies to transform cooking energy use. Spatial mapping offers a more nuanced understanding of the costs needed to deliver cleaner cooking transitions than was previously possible, which is useful for improved targeting of intervention strategies., QC 20230626

The Water-Energy-Food (WEF) framework is widely used to address sustainability and resource management questions. However, many WEF methods miss engaging with stakeholders in the process. In this study, we intro-duce a stakeholder-driven and model-supported robust nexus decision-making framework. This methodology is exemplified by a case study in the Souss-Massa basin (SMB) which has significant importance for the agricultural sector in Morocco. However, the water scarcity exacerbated by climate change, overexploitation of groundwater and heavy use of fossil fuels for pumping is threatening the future of this fertile land. An integrated agriculture, water and energy model was developed to explore various potential solutions or scenarios such as desalination, wastewater reuse and improved water productivity. The analysis revealed that engaging with stakeholders and developing common robust nexus decision metrics is essential to establishing a shared and transparent approach to address the complicated nexus challenges. It also showed that no one solution can address all nexus challenges and highlighted the need for an integrated strategy that stimulates the contributions from different sectors. Fi-nally, the transition from fossil fuel groundwater pumping to solar pumping is shown to be economically and en-vironmentally viable., QC 20221024

The intersectoral impacts of the COVID-19 pandemic on humanity raises concerns about its implications for sustainable development. Here, we examine a global quantitative impact of COVID-19 pandemic on Sustainable Development Goals (SDGs) across all 17 goals using 65 proxy indicators across 72 countries collected from April 2020 to February 2021. Our data-driven analysis indicated that adverse impacts of the pandemic have been particularly concerned on gender equality (Goal 5), affordable and clean energy (Goal 7), decent work and economic growth (Goal 8), sustainable cities and communities (Goal 11), and responsible consumption and production (Goal 12) with global scores estimated to be-0.38,-0.21,-0.28,-0.22 and-0.16, respectively. Country income level was a variable that strongly differentiates the responses to the pandemic (e.g., lower in-comes had 14 negative goals compared to 11 and 4 negative goals assigned to middle-and high-income coun-tries, respectively). However, Goals 5 and 8 were highly impacted worldwide regardless of income status. Furthermore, countries that had already higher performance in SDGs were less impacted by the pandemic, highlighting the importance of progress on the SDGs in increasing societal resilience to pandemics. The findings provide insights into the reinforcement of recovery policies (e.g., protecting vulnerable groups and transitioning to a green economy) and a basis for a quantitative discussion on the sectors to be prioritized., QC 20220929

The international community has committed to achieve 169 Sustainable Development Goal (SDG) targets by 2030 and to enhance climate adaptation under the Paris Agreement. Despite the potential for synergies, aligning SDG and climate adaptation efforts is inhibited by an inadequate understanding of the complex relationship between SDG targets and adaptation to impacts of climate change. Here we propose a framework to conceptualise how ecosystems and socio-economic sectors mediate this relationship, which provides a more nuanced understanding of the impacts of climate change on all 169 SDG targets. Global application of the framework reveals that adaptation of wetlands, rivers, cropland, construction, water, electricity, and housing in the most vulnerable countries is required to safeguard achievement of 68% of SDG targets from near-term climate risk by 2030. We discuss how our framework can help align National Adaptation Plans with SDG targets, thus ensuring that adaptation advances, rather than detracts from, sustainable development. Without targeted climate adaptation, impacts of climate change threaten achievement of all 169 SDG targets. Fuldauer et al. provide an actionable framework to assess these impacts and help systematically align national adaptation plans with the SDGs., QC 20230328

This study aimed at supporting robust decision-making for planning and management of water-energy-food Nexus systems in the country of Jordan. Nexus priority challenges in Jordan were identified as (1) water scarcity, (2) agricultural productivity and water quality, and (3) shift to energy independence. We created a water-energy-food Nexus model that integrates three modelling frameworks: (1) the Water Evaluation and Planning system WEAP model to estimate water demands, supplies and allocation; (2) the MABIA model to estimate crop production, and, (3) a GIS-based energy modelling tool to estimate energy requirements of the water system. Through a set of scenario runs, results show how desalination is needed to address water scarcity, but it has to be coupled with low-carbon electricity generation in order to not exacerbate climate change. Improving water productivity in agriculture improves most of the studied dimensions across the water-energy-food security nexus; however, it does little for water scarcity at the municipal level. Reducing non-revenue water can have positive effects on municipal unmet demand and reduction of energy for pumping, but it does not improve agricultural water productivity and may have negative feedback effects on the Jordan Valleys aquifer levels. Energy efficiency can support energy-intensive projects, like desalination, by substantially reducing the load on the energy system, preventing increased emissions and achieving a more resilient water system. Finally, when all interventions are considered together all of the major drawbacks are reduced and the benefits augmented, producing a more holistic solution to the WEF Nexus challenges in Jordan., QC 20230920

Achieving the Sustainable Development Goals of the United Nations is the primary goal of the 2030 Agenda. A critical step towards that objective is identifying if the scientific production is going in this way. Funders must do a manual recognition, impacting accuracy, scalability, and objectiveness. For this reason, we propose in this work an AI-based model for the automatic classification of scientific papers based on their impacts on the SDGs. The training database consists of manually extracted texts from the UN page. After preprocessing these texts, we train three models: NMF, LDA, and Top2Vec. The output of these models is the probability of a paper being associated with each SDG. We then combine their scores by implementing a voting function to take advantage of their inherently different mathematical nature. To validate this methodology, we use the database provided by Vinuesa et al., Nature Communications 11, with more than 150 papers labeled with at least 1 SDG. Using only the abstracts, we correctly identify a of the SDGs presented in a paper, while a better is obtained when fetching the complete paper information. Moreover, we find that the other identified SDGs which were not labeled are also related to the text contents. We recognize that more training files are required for the other cases since they are based on more complex human reasoning. We open-source these databases and trained models to enable future investigation in this field and allow public institutions to use this tool., QC 20230614

Urban and peri-urban communities across the Global South face considerable energy access challenges with over one billion people living without adequate access to basic services such as energy, water, and healthcare. Lack of access to modern energy services has cascading effects on the United Nations 2030 Agenda and the achievement of the corresponding Sustainable Development Goals (SDGs). In this article we address this issue, using the SDGs as a framework to evaluate how policies and plans for local energy access can be coordinated with all SDG Targets. With a case study in Kibera, Kenya, we analyse how local energy access could enable or inhibit all local SDG Targets. Based on this knowledge, we propose a set of actions to achieve full modern energy access without compromising other local Sustainable Development Goals. We propose a new taxonomy to evaluate how actions affect the interlinkages between local energy access and the achievement of the SDGs. We find that the SDGs, applied as a framework to direct national policies and strategic projects, offer a holistic outlook, helping to unpack discrete thinking and support an integrated sustainable future for all., QC 20211206

Cities are vital for achieving the Sustainable Development Goals (SDG), but different local strategies to advance on the same SDG may cause different ‘spillovers’ elsewhere. Research efforts that support governance of such spillovers are urgently needed to empower ambitious cities to ‘account globally’ when acting locally on SDG implementation strategies., QC 20220223

Since the early phase of the artificial-intelligence (AI) era expectations towards AI are high, with experts believing that AI paves the way for managing and handling various global challenges. However, the significant enabling and inhibiting influence of AI for sustainable development needs to be assessed carefully, given that the technology diffuses rapidly and affects millions of people worldwide on a day-to-day basis. To address this challenge, a panel discussion was organized by the KTH Royal Institute of Technology, the AI Sustainability Center and MIT Massachusetts Institute of Technology, gathering a wide range of AI experts. This paper summarizes the insights from the panel discussion around the following themes: The role of AI in achieving the Sustainable Development Goals (SDGs); AI for a prosperous 21st century; Transparency, automated decision-making processes, and personal profiling; and Measuring the relevance of Digitalization and Artificial Intelligence (D&AI) at the indicator level of SDGs. The research-backed panel discussion was dedicated to recognize and prioritize the agenda for addressing the pressing research gaps for academic research, funding bodies, professionals, as well as industry with an emphasis on the transportation sector. A common conclusion across these themes was the need to go beyond the development of AI in sectorial silos, so as to understand the impacts AI might have across societal, environmental, and economic outcomes. The recordings of the panel discussion can be found at: https://www.kth.se/en/2.18487/evenemang/the-role-of-ai-in-achieving-the-sdgs-enabler-or-inhibitor-1.1001364?date=2020–08–20&length=1&orglength=185&orgdate=2020–06–30 Short link: https://bit.ly/2Kap1tE, QC 20220323

This paper presents the first application of the scenario discovery approach in geospatial electrification modelling. 1944 electrification simulations were constructed for Burkina Faso from a combination seven input levers, including four grid-extension strategies. The scenario discovery analysis identifies a scenario described by a high grid electricity generation cost in combination with an intensification strategy for grid-extension, as most likely to lead to a high cost of electricity in Burkina Faso. Thus, to avoid such a high cost, decisions in the country could be targeted either at lowering grid electricity generation costs or to choose one of the other two gridextension strategies, or both. For each of the grid-extension strategies, a number of drivers causing a high LCOE were identified. Common drivers for all strategies were the grid electricity generation cost and discount rate. The scenario discovery approach was used to identify the key drivers of high electrification costs and their interactions, providing useful information that might not be gained from a traditional scenario-axes approach. This approach provided a structured way to analyze more parameters than found in previous electrification studies for Burkina Faso. The paper discusses on the pros compared to a traditional scenario-axes approach, such as reduced risk of perceived bias and improved ability to deal with multiple uncertain parameters, but also notes the additional computational requirements., QC 20220120

The introduction of geospatial data into modelling efforts carries many advantages but also introduces numerous challenges. A common challenge is the Modifiable Areal Unit Problem (MAUP), describing how results change as the spatial aggregation of data changes. Here, we have studied MAUP in geospatial least-cost electrification modelling. We do this by assessing the effects of using 26 different population bases each for Benin, Malawi and Namibia. We use the population bases to generate 2080 electrification scenarios per country and conducting a global sensitivity analysis using the Delta Moment-Independent Measure. We identify population aggregation to be highly influential to the model results with regards to method of aggregation (delta values of 0.06-0.24 depending on output studied), administrative division (0.05-0.14), buffer chosen in the clustering process (0.05-0.32) and the minimum number of neighbours within the buffer required for clustering (0.05-0.19). Based on our findings, we conclude that geospatial electrification studies are not robust concerning the choice of population data. We suggest, that modelers put larger emphasis on different population aggregation methods in their sensitivity analyses and that the methods chosen to conduct sensitivity analysis are global in nature (i.e. moving all inputs simultaneously through their possible range of values)., QC 20220120Correction in Energy strategi reviews, volume 50, DOI: 10.1016/j.esr.2023.101262, WOS:001130293000001

Urban and peri-urban communities across the Global South face considerable energy access challenges with over one billion people living without adequate access to basic services such as energy, water, and healthcare. Lack of access to modern energy services has cascading effects on the United Nations 2030 Agenda and the achievement of the corresponding Sustainable Development Goals (SDGs). In this article we address this issue, using the SDGs as a framework to evaluate how policies and plans for local energy access can be coordinated with all SDG Targets. With a case study in Kibera, Kenya, we analyse how local energy access could enable or inhibit all local SDG Targets. Based on this knowledge, we propose a set of actions to achieve full modern energy access without compromising other local Sustainable Development Goals. We propose a new taxonomy to evaluate how actions affect the interlinkages between local energy access and the achievement of the SDGs. We find that the SDGs, applied as a framework to direct national policies and strategic projects, offer a holistic outlook, helping to unpack discrete thinking and support an integrated sustainable future for all., QC 20211206

Urban and peri-urban communities across the Global South face considerable energy access challenges with over one billion people living without adequate access to basic services such as energy, water, and healthcare. Lack of access to modern energy services has cascading effects on the United Nations 2030 Agenda and the achievement of the corresponding Sustainable Development Goals (SDGs). In this article we address this issue, using the SDGs as a framework to evaluate how policies and plans for local energy access can be coordinated with all SDG Targets. With a case study in Kibera, Kenya, we analyse how local energy access could enable or inhibit all local SDG Targets. Based on this knowledge, we propose a set of actions to achieve full modern energy access without compromising other local Sustainable Development Goals. We propose a new taxonomy to evaluate how actions affect the interlinkages between local energy access and the achievement of the SDGs. We find that the SDGs, applied as a framework to direct national policies and strategic projects, offer a holistic outlook, helping to unpack discrete thinking and support an integrated sustainable future for all., QC 20211206

Human settlements are usually nucleated around manmade central points or distinctive natural features, forming clusters that vary in shape and size. However, population distribution in geo-sciences is often represented in the form of pixelated rasters. Rasters indicate population density at predefined spatial resolutions, but are unable to capture the actual shape or size of settlements. Here we suggest a methodology that translates high-resolution raster population data into vector-based population clusters. We use open-source data and develop an open-access algorithm tailored for low and middle-income countries with data scarcity issues. Each cluster includes unique characteristics indicating population, electrification rate and urban-rural categorization. Results are validated against national electrification rates provided by the World Bank and data from selected Demographic and Health Surveys (DHS). We find that our modeled national electrification rates are consistent with the rates reported by the World Bank, while the modeled urban/rural classification has 88% accuracy. By delineating settlements, this dataset can complement existing raster population data in studies such as energy planning, urban planning and disease response., QC 20210609

The North Western Sahara Aquifer System stands out as one of the water scarcest regions in the world. Moreover, in recent decades agriculture activity has grown exacerbating the pressure on groundwater resources and pumping energy requirements. In this study, a water-energy-food Nexus approach was used to assess the effect of capturing, treating and reusing wastewater for irrigation. GIS-based tools were used to capture the systems spatial dimension, enabling to match wastewater supply and water demand points, identify demand hotspots and evaluate techno-economically viable wastewater treatment options. Moreover, the minimum energy requirements for brackish water desalination were estimated. Seven domestic wastewater treatment technologies and one irrigation tailwater treatment technology were evaluated, making use of a levelized cost of Water methodology to identify the least-cost system. Four scenarios were constructed based on water-consumption behaviour of farmers towards changes in irrigation water pricing. The identified least-cost wastewater treatment technologies showed clear trade-offs, as different technologies were more cost-effective depending on treatment capacity requirements of the spatially distributed agglomerations. The reuse of treated wastewater/tailwater in agricultural irrigation, showed improvement of groundwater stress, reducing on about 49% water abstractions and groundwater stress levels in the best case scenario. However, groundwater stress still fell on the extremely high category, highlighting the critical condition of the aquifer. Furthermore, reuse of wastewater/tailwater decreased dependency on groundwater pumping and the overall energy-for-water requirements, reducing by about 15% the total energy requirements in the best case scenario. However, to effectively preserve water resources and act holistically towards the sustainable development agenda, measures as better water pricing mechanisms, management strategies to improve water pr, QC 20210517

Here we discuss how personal carbon allowances (PCAs) could play a role in achieving ambitious climate mitigation targets. We argue that recent advances in AI for sustainable development, together with the need for a low-carbon recovery from the COVID-19 crisis, open a new window of opportunity for PCAs. Furthermore, we present design principles based on the Sustainable Development Goals for the future adoption of PCAs. We conclude that PCAs could be trialled in selected climate-conscious technologically advanced countries, mindful of potential issues around integration into the current policy mix, privacy concerns and distributional impacts., QC 20220517

The 2030 Agenda is an aspiring set of goals and targets that aims to prompt humanity towards a sustainable development by 2030. In order to achieve this, actions that mitigate trade-offs and enhance synergies within the Sustainable Development Goals (SDGs) need to be identified. However, for the energy sector these actions are dispersed across the scientific literature, which is a clear barrier to encourage practitioners to have a proactive and pragmatic approach towards the SDGs. For this reason, a set of actions for energy projects was compiled. This compilation addresses the synergies and trade-offs identified in the Sustainable Development Goals Impact Assessment Framework for Energy Projects (SDG-IAE). One case of application was used to test the actions, the lighthouse Project VARGA. Subsequently, an analysis was conducted to understand how possible actions can impact different technologies, project stages, actors and SDG targets. In this way, enabling policymakers and project developers to define areas of action when evaluating policies or considering specific interventions. This article aims to be the starting point of stakeholder discussions that consistently frame energy projects within the achievement of the SDGs., QC 20230714

Urban and peri-urban communities across the Global South face considerable energy access challenges with over one billion people living without adequate access to basic services such as energy, water, and healthcare. Lack of access to modern energy services has cascading effects on the United Nations 2030 Agenda and the achievement of the corresponding Sustainable Development Goals (SDGs). In this article we address this issue, using the SDGs as a framework to evaluate how policies and plans for local energy access can be coordinated with all SDG Targets. With a case study in Kibera, Kenya, we analyse how local energy access could enable or inhibit all local SDG Targets. Based on this knowledge, we propose a set of actions to achieve full modern energy access without compromising other local Sustainable Development Goals. We propose a new taxonomy to evaluate how actions affect the interlinkages between local energy access and the achievement of the SDGs. We find that the SDGs, applied as a framework to direct national policies and strategic projects, offer a holistic outlook, helping to unpack discrete thinking and support an integrated sustainable future for all., QC 20211206

Urban and peri-urban communities across the Global South face considerable energy access challenges with over one billion people living without adequate access to basic services such as energy, water, and healthcare. Lack of access to modern energy services has cascading effects on the United Nations 2030 Agenda and the achievement of the corresponding Sustainable Development Goals (SDGs). In this article we address this issue, using the SDGs as a framework to evaluate how policies and plans for local energy access can be coordinated with all SDG Targets. With a case study in Kibera, Kenya, we analyse how local energy access could enable or inhibit all local SDG Targets. Based on this knowledge, we propose a set of actions to achieve full modern energy access without compromising other local Sustainable Development Goals. We propose a new taxonomy to evaluate how actions affect the interlinkages between local energy access and the achievement of the SDGs. We find that the SDGs, applied as a framework to direct national policies and strategic projects, offer a holistic outlook, helping to unpack discrete thinking and support an integrated sustainable future for all., QC 20211206

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards., QC 20200302

Energy projects in pursuit of Sustainable Development Goal 7, which addresses affordable and clean energy, can have numerous synergies and trade-offs with all other SDGs and their targets. However, the identification of such interlinkages is both complicated and scattered in literature. To overcome this gap, this research presents the development and application of the Sustainable Development Goals Impact Assessment Framework for Energy Projects (SDGs-IAE) for qualitative assessment of SDG target synergies and trade-offs within the context of a given energy project. Two diverse case studies ‒ the Grand Ethiopian Renaissance Dam (GERD) and the Hinkley Point C Nuclear Power Station (HPC) ‒ are utilized to test the framework. Each case study highlights important SDG target interactions drawn out by this process. The GERD analysis shows the many synergies that result from energy access expansion while also bringing up trade-offs related to transboundary water rights and community relocation. In the case of the HPC, long-term ecosystem impacts of uranium mining and trade-offs related to future climate resilience and energy affordability are identified. The final resulting framework and corresponding excel-based tool can inform a dialog among stakeholders about the key areas of improvement related to the project´s social, environmental and economic sustainability., QC 20200622

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.

The international community has committed to combat climate change and achieve 17 Sustainable Development Goals (SDGs). Here we explore (dis)connections in evidence and governance between these commitments. Our structured evidence review suggests that climate change can undermine 16 SDGs, while combatting climate change can reinforce all 17 SDGs but undermine efforts to achieve 12. Understanding these relationships requires wider and deeper interdisciplinary collaboration. Climate change and sustainable development governance should be better connected to maximize the effectiveness of action in both domains. The emergence around the world of new coordinating institutions and sustainable development planning represents promising progress., QC 20190830

Circular economy (CE) is an emerging concept that contrasts the linear economic system. This concept is particularly relevant for cities, currently hosting approximately 50% of the world's population. Research gaps in the analysis and implementation of circular economy in cities are a significant barrier to its implementation. This paper presents a multi-sectorial and macro-meso level framework to monitor (and set goals for) circular economy implementation in cities. Based on literature and case studies, it encompasses CE key concepts, such as flexibility, modularity, and transparency. It is structured to include all sectors in which circular economy could be adopted in a city. The framework is then tested in Porto, Portugal, monitoring the circularity of the city and considering its different sectors., QC 20190521

QC 20190201

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors across the society requires an assessment of its effect on sustainable development. Here we analyze published evidence of positive or negative impacts of AI on the achievement of each of the 17 goals and 169 targets of the 2030 Agenda for Sustainable Development. We find that AI can support the achievement of 128 targets across all SDGs, but it may also inhibit 58 targets. Notably, AI enables new technologies that improve efficiency and productivity, but it may also lead to increased inequalities among and within countries, thus hindering the achievement of the 2030 Agenda. The fast development of AI needs to be supported by appropriate policy and regulation. Otherwise, it would lead to gaps in transparency, accountability, safety and ethical standards of AI-based technology, which could be detrimental towards the development and sustainable use of AI. Finally, there is a lack of research assessing the medium- and long-term impacts of AI. It is therefore essential to reinforce the global debate regarding the use of AI and to develop the necessary regulatory insight and oversight for AI-based technologies.

QC 20180522

The 2030 Agenda for Sustainable Development-including 17 interconnected Sustainable Development Goals (SDGs) and 169 targets-is a global plan of action for people, planet and prosperity. SDG7 calls for action to ensure access to affordable, reliable, sustainable and modern energy for all. Here we characterize synergies and trade-offs between efforts to achieve SDG7 and delivery of the 2030 Agenda as a whole. We identify 113 targets requiring actions to change energy systems, and published evidence of relationships between 143 targets (143 synergies, 65 trade-offs) and efforts to achieve SDG7. Synergies and trade-offs exist in three key domains, where decisions about SDG7 affect humanity's ability to: realize aspirations of greater welfare and well-being; build physical and social infrastructures for sustainable development; and achieve sustainable management of the natural environment. There is an urgent need to better organize, connect and extend this evidence, to help all actors work together to achieve sustainable development., QC 20180130

Energy for cooking is considered essential in achieving modern energy access. Despite this, almost three billion people worldwide still use solid fuels to meet their cooking needs. To better support practitioners and policy-makers, this paper presents a new model for comparing cooking solutions and its key output metric: the 'levelized cost of cooking a meal' (LCCM). The model is applied to compare several cooking solutions in the case study area of Nyeri County in Kenya. The cooking access targets are connected to the International Workshop Agreement and Global Tracking Framework's tiers of cooking energy access. Results show how an increased energy access with improved firewood and charcoal cookstoves could reduce both household's LCCMs and the total costs compared to traditional firewood cooking over the modelling period. On the other hand, switching to cleaner cooking solutions, such as LPG-and electricity, would result in higher costs for the end-user highlighting that this transition is not straightforward. The paper also contextualizes the results into the wider socio-economic context. It finds that a tradeoff is present between minimizing costs for households and meeting household priorities, thus maximizing the potential benefits of clean cooking without dismissing the use of biomass altogether., QC 20171201

The UN's Sustainable Energy For All initiative has made universal access to energy by 2030 a key target. Countries wherein budgets are constrained and institutions stressed are faced with the challenge of further extending energy services and doing so significantly. To meet this goal for the power sector in a cost-effective way, governments have to consider the deployment of a mix of stand-alone, mini-grid and grid-based solutions. To help inform analysis, planning and the decision process, this paper presents a simple, transparent, least-cost model for the electrification of rural areas. The approach builds on four key parameters, namely: (i) target level and quality of energy access, (ii) population density, (iii) local grid connection characteristics and (iv) local energy resources availability and technology cost. From an application perspective, this work can be used both for (1) fast assessments of specific energy access projects, and (2) to inform more complex regional studies using a geo-referencing software to analyze the results. Such applications are presented in the results using country case studies developed for Nigeria and Ethiopia. These show how the strategy for expanding energy access may vary significantly both between and within given regions of energy-poor countries., QC 20160319

Worldwide, approximately 1.2 billion people still lack access to electricity. Recognized by the Brazilian Government as a citizen's right, access to electricity was extended to almost 15 million people since 2003 as a result of the "Luz Para Todos" (Light for all - LPT) program. However, considerable parts of the Amazon region still lack access to electricity services, largely due to the long distances that need to be covered and to challenging topography. This paper explores electrification using selected renewable sources, both for new installations and for hybridization of existing diesel generators. We present results from a multi-criteria analysis that explores trade-offs associated with electrification options. Techno-economic, environmental, social and institutional criteria and attributes are explored. We find that renewable and hybrid systems present a number of advantages for application in isolated areas of the region., QC 20140624

Energy access metrics are needed to track the progress towards providing sustainable energy for all. This paper presents advancements in the development of the Multidimensional Energy Poverty Index (MEPI), as well as results and analysis for a number of developing countries. The MEPI is a composite index designed to shed light on energy poverty by assessing the services that modern energy provides. The index captures both the incidence and intensity of energy poverty. It provides valuable insights-allowing the analysis of determinants of energy poverty-and, subsequently insights into policy efficacy. Building on previous work, this paper presents results obtained as a result of both increased data availability and enhanced methodology. Specifically, this analysis (i) includes an increased number of countries, and (ii) tracks the evolution of energy poverty over time of energy poverty in selected countries is reported., QC 20131003

Access to clean cooking and electricity are both targets of Sustainable Development Goal 7 (SDG 7). While both targets are to be reached by 2030, the progress towards them is uneven. Peer-reviewed literature and policy documents have called for more integrated planning efforts accounting for both targets simultaneously. Here, we soft-link for the first time a geospatial electrification tool (OnSSET) with a geospatial clean cooking tool (OnStove) to allow for integrated planning in a case-study of Kenya. In 2021, 77% of Kenyans had access to electricity, but only 28% to clean cooking. The government has targeted universal electricity and clean cooking access by 2026 and 2028 respectively, and the country has a large potential for electric cooking. Our results show how incorporating cooking demand in the electricity model, favors centralized options as these benefit from economies of scale. Without soft-linking, 77% of the population benefit most from adopting an electric option. With an integrated approach, these shares increase to between 85 and 91%. We find that an integrated approach is important for understanding the best way forward towards the achievement of SDG 7., QC 20240122

The ´decade of action´ to achieve the ambitious 17 Sustainable Development Goals by 2030 is off to a very challenging start. With progress on the achievement of most SDGs already lagging behind even before the Covid-19 crisis – our analysis finds that the pandemic negatively affects the achievement of 144 targets (almost 90%) of the SDGs. However, 66 targets (ca. 40%) could potentially benefit from the changes spurred by the crisis, given that the appropriate decisions are made. Holistic response and leadership are needed to ensure an inclusive economic recovery while protecting the environment. Furthermore, our analysis of the literature documents the unprecedented speed of the international community to assess the impacts of the pandemic. Future research should gather data to better understand the impacts of the pandemic locally and globally, and produce long-term analyses to inform the sustainable recovery across all SDGs.

The ´decade of action´ to achieve the ambitious 17 Sustainable Development Goals by 2030 is off to a very challenging start. With progress on the achievement of most SDGs already lagging behind even before the Covid-19 crisis – our analysis finds that the pandemic negatively affects the achievement of 144 targets (almost 90%) of the SDGs. However, 66 targets (ca. 40%) could potentially benefit from the changes spurred by the crisis, given that the appropriate decisions are made. Holistic response and leadership are needed to ensure an inclusive economic recovery while protecting the environment. Furthermore, our analysis of the literature documents the unprecedented speed of the international community to assess the impacts of the pandemic. Future research should gather data to better understand the impacts of the pandemic locally and globally, and produce long-term analyses to inform the sustainable recovery across all SDGs.