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Abstract:Understanding the linkages between multiple targets of Sustainable Development Goals (SDGs) may help to integrate different sectoral programmes and develop coherent cross-sectoral policy to explore synergies. Synergy is interaction among two or more actions, which will lead to an impact greater or less than the sum of individual effects. Therefore, synergy can be positive or negative (trade-off). This paper aims at developing an analytical framework to evaluate sectoral linkages and examine potential synergies and trade-offs among various SDGs' goals and targets. Synergies and trade-offs related to energy access (SDG7), clean water and sanitation access (SDG6), food security and sustainable agriculture (SDG2) and poverty alleviation (SDG1) have been evaluated from the perspective of developing countries using examples from South Asia (Bangladesh, Nepal, and Sri Lanka) and Sub-Saharan Africa (Ghana, Ethiopia and Rwanda), and historical data for the period between 1990 and 2012. The analytical framework includes both qualitative and quantitative methods. Network analysis technique has been used for exploring the conceptual linkage among different indicators, and capturing the targets associated with SDGs. Advanced Sustainability Analysis (ASA) developed under the European framework programme has been used for quantifying the synergies and trade-offs among sustainability indicators. The analysis showed strong synergy among various SDG targets. Interestingly, the potential synergy differs from country to country and over time. Ghana and Sri Lanka had relatively higher potential synergy, whereas Rwanda and Nepal had relatively lower potential synergy among the various targets. Higher synergy values were evidenced in those cases where the policy have recognized and emphasized on linkages among cross-sectoral targets.

Highlights Presenting an optimization model for the location of electric bus charging stations.  Model application to a large-scale case study for the bus network of Stockholm, Sweden.  Results show that low fuel costs for electricity can balance annual infrastructure costs.  Emissions decrease up to 51% and energy consumption up to 34% with electrification.  The model may assist decision-making for investments in public transport.Keywords electric bus; charging infrastructure; optimization; Mixed Integer Linear Programing; public transport; Sweden AbstractCharging infrastructure requirements are being largely debated in the context of urban energy planning for transport electrification. As electric vehicles are gaining momentum, the issue of locating and securing the availability, efficiency and effectiveness of charging infrastructure becomes a complex question that needs to be addressed. This paper presents the structure and application of a model developed for optimizing the distribution of charging infrastructure for electric buses in the urban context, and tests the model for the bus network of Stockholm. The major public bus transport hubs connecting to the train and subway system show the highest concentration of locations chosen by the model for charging station installation. The costs estimated are within an expected range when comparing to the annual bus public transport costs in Stockholm. The model could be adapted for various urban contexts to promptly assist in the transition to fossil-free bus transport. The total costs for the operation of a partially electrified bus system in both optimization cases considered (cost and energy) differ only marginally from the costs for a 100% biodiesel system. This indicates that lower fuel costs for electric buses can balance the high investment costs incurred in building charging infrastructure, while achieving a reduction of up to 51% in emissions and up to 34% in energy use in the bus fleet.

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a b s t r a c tIn sugarcane biorefineries, the lignocellulosic portion of the sugarcane biomass (i.e. bagasse and cane trash) can be used as fuel for electricity production and/or feedstock for second generation (2G) ethanol. This study presents a techno-economic analysis of upgraded sugarcane biorefineries in Brazil, aiming at utilizing surplus bagasse and cane trash for electricity and/or ethanol production. The study investigates the trade-off on sugarcane biomass use for energy production: bioelectricity versus 2G ethanol production. The BeWhere mixed integer and spatially explicit model is used for evaluating the choice of technological options. Different scenarios are developed to find the optimal utilization of sugarcane biomass. The study finds that energy prices, type of electricity substituted, biofuel support and carbon tax, investment costs, and conversion efficiencies are the major factors influencing the technological choice. At the existing market and technological conditions applied in the upgraded biorefineries, 300 PJ y À1 2G ethanol could be optimally produced and exported to the EU, which corresponds to 2.5% of total transport fuel demand in the EU. This study provides a methodological framework on how to optimize the alternative use of agricultural residues and industrial co-products for energy production in agro-industries considering biomass supply chains, the pattern of domestic energy demand, and biofuel trade.

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