A significant obstacle to the incorporation of Nexus considerations in planning and policy design is the understanding and acknowledgement of cross-sectoral interdependencies. This chapter explores the importance of disseminating knowledge of the Nexus among key actors from policy, business and civil society, and in formal education contexts. Examples from capacity development activities and Nexus dialogues linked to the implementation of the Climate, Land, Energy and Water systems (CLEWs) framework are presented. Insights from the latter, as well as other initiatives with similar scope of action, are distilled to forward the importance of learning in such an approach. Additionally, the chapter highlights the main aspects to take into account when promoting these types of activities in new Nexus contexts.

The Climate, Land, Energy and Water systems (CLEWs) approach guides the development of integrated assess-ments. The approach includes an analytical component that can be performed using simple accounting methods, soft-linking tools, incorporating cross-systems considerations in sectoral models, or using one modelling tool to represent CLEW systems. This paper describes how a CLEWs quantitative analysis can be performed using one single modelling tool, the Open Source Energy Modelling System (OSeMOSYS). Although OSeMOSYS was pri-marily developed for energy systems analysis, the tool's functionality and flexibility allow for its application to CLEWs. A step-by-step explanation of how climate, land, energy, and water systems can be represented with OSeMOSYS, complemented with the interpretation of sets, parameters, and variables in the OSeMOSYS code, is provided. A hypothetical case serves as the basis for developing a modelling exercise that exemplifies the building of a CLEWs model in OSeMOSYS. System-centred scenario analysis is performed with the integrated model example to illustrate its application. The analysis of results shows how integrated insights can be derived from the quantitative exercise in the form of conflicts, trade-offs, opportunities, and synergies. In addition to the modelling exercise, using the OSeMOSYS-CLEWs example in teaching, training and open science is explored to support knowledge transfer and advancement in the field.

In the referenced article, Engström R, et al. (2018), the authors would like to report a calculation error. Correcting this error does not alter any of the overarching results or conclusions of the article, but changes the results in the original Table 3 and Figure 3. Two typographical errors were also found in the main article, and are corrected here. The supplementary material has also been updated to reflect these corrections.

Africa's economic and population growth prospects are likely to increase energy and water demands. This quantitative study shows that energy decarbonisation pathways reduce water withdrawals (WWs) and water consumption (WC) relative to the baseline scenario. However, the more aggressive decarbonisation pathway (1.5 degrees C) leads to higher overall WWs than the 2.0 degrees C scenario but lower WC levels by 2065. By 2065, investments in low-carbon energy infrastructure increase annual WWs from 1% (52 bcm) in the 2.0 degrees C to 2% (85 bcm) in the 1.5 degrees C scenarios of total renewable water resources in Africa compared to 3% (159 bcm) in the baseline scenario with lower final energy demands in the mitigation scenarios. WC decreases from 1.2 bcm in the 2.0 degrees C to 1 bcm in the 1.5 degrees C scenario, compared to 2.2 bcm in the baseline scenario by 2065, due to the lower water intensity of the low-carbon energy systems. To meet the 1.5 degrees C pathway, the energy sector requires a higher WW than the 2.0 degrees C scenario, both in total and per unit of final energy. Overall, these findings demonstrate the crucial role of integrated water-energy planning, and the need for joined-up carbon policy and water resources management for the continent to achieve climate-compatible growth.

Population growth, urbanization and economic development drive the use of resources. Securing access to essential services such as energy, water, and food, while achieving sustainable development, require that policy and planning processes follow an integrated approach. The 'Climate-, Land-, Energy- and Water-systems' (CLEWs) framework assists the exploration of interactions between (and within) CLEW systems via quantitative means. The approach was first introduced by the International Atomic Energy Agency to conduct an integrated systems analysis of a biofuel chain. The framework assists the exploration of interactions between (and within) CLEW systems via quantitative means. Its multi-institutional application to the case of Mauritius in 2012 initiated the deployment of the framework. A vast number of completed and ongoing applications of CLEWs span different spatial and temporal scales, discussing two or more resource interactions under different political contexts. Also, the studies vary in purpose. This shapes the methods that support CLEWs-type analyses. In this paper, we detail the main steps of the CLEWs framework in perspective to its application over the years. We summarise and compare key applications, both published in the scientific literature, as working papers and reports by international organizations. We discuss differences in terms of geographic scope, purpose, interactions represented, analytical approach and stakeholder involvement. In addition, we review other assessments, which contributed to the advancement of the CLEWs framework. The paper delivers recommendations for the future development of the framework, as well as keys to success in this type of evaluations.

The authors regret two instances of misinterpretation of input data and one formatting error in the previously published paper as titled above. First, the numerical estimates for water use in NYC electricity and natural gas supply were found to be incorrect due to a conversion error in a data file. This error has now been corrected and the estimates have been changed to correctly correspond to the references on which they are based on. These changes have led to a recalculation of indirect water use reduction potentials in the interventions studied in the paper. Second, two errors due to primary data misinterpretation related to the studied green roof intervention have been found and corrected. The first led to an overestimation of the green roofs’ energy use reduction potential in the previously published paper. The second led to an underestimation of their installation cost. These errors have also been corrected and all numerical results for the green roof intervention have been recalculated. In the updated sections 3 and 4 of the original publication (below), Table 2, Table 3, Fig. 2 and Fig. 3 are updated with the new results related to both indirect water use reductions and green roof performance and costs. The text in the below sections have been given minor adjustments to clarify this update. These changes make green roofs a less economically favourable intervention in comparison to the previously published results. It also makes indirect water use reductions relatively smaller compared to direct water use reductions. All other results as well as the conclusions of this paper are still valid and unchanged. Lastly, a typo in writing of Eq. (7) in the manuscript text has been corrected. There was no error in the equation used in the analysis; hence, no numerical results have been effected by this correction. The authors would like to apologise for any inconvenience caused. Corrected writing of Eq. (7), section 2.3.1: [Formula presented] Updated sections of the original publication.

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.

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.

Integrated Assessment Models (IAMs) are important tools to analyse cross-sectoral interdependencies and the use of global resources. Most current tools are highly detailed and require expert knowledge and proprietary software to generate scenarios and analyse their insights. In this paper, the complementary Global Least-cost User-friendly CLEWs Open-Source Exploratory (GLUCOSE) model is presented as a highly-aggregated global IAM, open and accessible from source to solver and using the OSeMOSYS tool and the CLEWs framework. The model enables the exploration of policy measures on the future development of the integrated resource system. Thanks to its relatively simple structure, it requires low computational resources allowing for the generation of a large number of scenarios or to quickly conduct preliminary investigations. GLUCOSE is targeted towards education and training purposes by a range of interested parties, from students to stakeholders and decision-makers, to explore possible future pathways towards the sustainable management of global resources.

The transition to a low carbon energy system as laid out in the Paris Agreement and the European GreenDeal presents challenges that involve society at all levels from planners to consumers. A key challenge isthe communication across these levels. Tools to foster engagement and discussion between the differentactors are open-source models with a low threshold for uptake. This paper presents the Open-Sourceelectricity Model Base for Europe an electricity sector engagement model covering all member statesof the EU, Norway, Switzerland and the United Kingdom. Built in OSeMOSYS and available on GitHub, themodel provides a starting point into energy systems modelling and can be further developed in acollaborative manner. It enables non-experts to develop an understanding of energy systems models andenergy planning. Thereby, it can serve as an engagement tool to carry the debate on the future of theEuropean power system beyond the academy, which might contribute to finding societal consensus onhow to decarbonise our energy system. The model allows dynamic power sector expansion analysis ofthe European power system till 2050. It can be used for scenario analysis and is expandable to othersectors to analyse the benefits of sector coupling.