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Since 2015, the intended climate actions of the Paris Agreement signatories have been reported as nationally determined contributions (NDC). These climate actions are fully aligned with the 13th Sustainable Development Goal (SDG) which calls for urgent action to combat climate change. The same, however, cannot be said for their relation to the other 16 SDGs of the 2030 Agenda for Sustainable Development, since climate action can either enhance or compromise the prospects for SDG implementation. In light of this challenge, this paper proposes a simple method for quantifying the synergies and trade-offs between national climate actions and the SDGs. The method, referred to as Q-SCAN, makes use of a seven-step scale and the SDG Climate Action Nexus tool. The effectiveness of the method has been demonstrated on a case study of North Macedonia, a non-Annex I, Western Balkan country with a coal-intensive energy system. Based on the experience in the preparation of the country’s enhanced NDC, the paper elaborates how the method can be used to contribute to the alignment of the national climate actions with the SDGs and how it can be used to improve stakeholder engagement.

The number of natural disasters is growing. A considerable number of them derives directly from climate changes and generates a deep impact on cultural heritages. As a result, the need for solutions able to cope with uncertain weather conditions and increased natural disasters is getting urgent. STORM is a European Research and Innovation Action co-funded in the H2020 framework that is aimed at creating intelligent tools which will gather data from libraries, sensors and crowd-sensing techniques in order to enable cultural heritage stakeholders (e.g., the organisations which have to manage the sites) to implement the most appropriate actions in the prevention, response and recovery phases of emergencies which could impact on cultural heritages. More specifically, the project aims at addressing those risks deriving from climate change, which in the near future is going to worsen most of the present hazards, as flash floods, heat waves and forest fires. As such, the approach adopted by the project is particularly fit for the purpose of being integrated with smart city systems which are increasingly growing in number and variety. Even if safety issues are not considered central in the overall concept of smart city, it’s plain that the huge quantity of data that can be gathered and processed in any future STORM-like urban cultural heritage compound should feed into the available smart city systems. On the other way round, the mass of data produced or processed by smart city systems have the potential to impact dramatically on emergency management and prevention activities to be implemented by cultural heritage stakeholders. The paper will illustrate the approach that the STORM project is adopting to mitigate the impact of climate changes on cultural heritages and the mutual benefits which could derive from an integration of the STORM outcomes with smart cities systems through the use of standard emergency data exchange protocols and an integrated framework aimed at improving existing processes related to the three identified areas: Prevention, Response and Policy

Abstract The feasibility of reusing waste materials as an inexpensive sorbent to remove volatile organic compounds from gaseous waste streams has been demonstrated. Ashes from wood-chips were tested as sorbent materials for VOCs removal with a PTR-ToF-MS instrument. Both scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX) and BET analysis were used to identify the structural characteristics, elemental composition and surface area of the tested ashes respectively. Most of the tentatively identified compounds were less strongly adsorbed by wet ash: thiols, siloxanes, carbonyl compounds and terpenes. Hydrogen sulfide and alcohols show improving removal performance in wet conditions. These results are related to the water solubility properties. Siloxanes were tentatively identified and monitored with PTR-ToF-MS. This demonstrates how this instrument is a suitable tool for simultaneously providing a multitude of analysis for rapid in situ monitoring of fuel contaminants. Considering the low cost, and the recycling of environmental pollutants, wood ashes are a possible choice for VOCs removal from biogas.

This study assesses the socio-economic impacts in terms of value added, imports and employment of sugarcane-derived bioethanol production in Northeast (NE) Brazil. An extended inter-regional Input–Output (IO) model has been developed and is used to analyse three scenarios, all projected for 2020: a business-as-usual scenario (BaU) which projects current practices, and two scenarios that consider more efficient agricultural practices and processing efficiency (scenario A) and in addition an expansion of the sector into new areas (scenario B). By 2020 in all scenarios, value added and imports increase compared to the current situation. The value added by the sugarcane–ethanol sector in the NE region is 2.8 billion US$ in the BaU scenario, almost 4 billion US$ in scenario A, and 9.4 billion US$ in scenario B. The imports in the region will grow with 4% (BaU scenario), 38% (scenario A) and 262% (scenario B). This study shows that the large reduction of employment (114,000 jobs) due to the replacement of manual harvesting by mechanical harvesting can be offset by additional production and indirect effects. The total employment in the region by 2020 grows with 10% in scenario A (around 12,500 jobs) and 126% in scenario B (around 160,000 jobs). The indirect effects of sugarcane production in the NE are large in the rest of Brazil due to the import of inputs from these regions. The use of an extended inter-regional IO model can quantify direct and indirect socio-economic effects at regional level and can provide insight in the linkages between regions. The application of the model to NE Brazil has demonstrated significant positive socio-economic impacts that can be achieved when developing and expanding the sugarcane–ethanol sector in the region under the conditions studied here, not only for the NE region itself but also for the economy of the rest of Brazil.

Abstract This paper examines three different governance approaches the European Union (EU) and Member States (MS) are relying on to reach a low carbon economy by 2050. Current governance literature explains the operational methods of the EU's new governance approach to reduce carbon emissions. However, the literature neglects to account for the perceived risks that inhibit the roll-out of new low carbon technology. This article, through a novel approach, uses a grounded theoretical framework to reframe traditional risk literature and provides a connection to governance literature in order to assess the ability of EU governance mechanisms to reduce carbon emissions. The empirical research is based on responses from European energy stakeholders who participated in a Delphi method discussion and in semi-structured interviews; these identified three essential requirements for carbon emissions to be reduced to near zero by 2050: (1) an integrated European energy network, (2) carbon pricing and (3) demand reduction. These features correspond to institutionalized responses by the EU and MS: the Agency for the Cooperation of Energy Regulators (ACER); European Union Emission Trading Scheme (EU ETS) and energy efficiency directives and policies integrated into existing MS institutions. The theoretical and empirical findings suggest that governance by facilitation (energy efficiency) fails to induce significant investment and new policy approaches and cannot be relied on to achieve requisite reductions in demand. Governance by negotiation (ACER) and governance by hierarchy (EU ETS) do reduce risks and may encourage the necessary technological uptake. The term ‘risk governance’ is used to explain the important role governance plays in reducing risks and advancing new technology and thereby lowering carbon emissions in the energy sector.

Abstract With climate change mainly originating from the extensive use of fossil fuels and having impacts on many aspects of life, changing the way energy is utilised constitutes a challenge that the world collectively must tackle. In this respect, all countries should implement a variety of measures focusing on energy efficiency and use of sustainable energy sources towards decarbonising their economies and achieving effective greenhouse gas emission reductions and sustainable development. Technological innovations, economic growth, societal compliance, and the regulatory and institutional frameworks constitute prominent factors that could promote, hinder or shape energy transitions as well as indicate the capacity of energy systems to be transformed. Therefore, investigating energy transitions and the extent to which countries are prepared to carry out such transitions requires the consideration of insights into multiple dimensions. This study outlines a multicriteria analysis framework to assess a country's sustainable energy transition readiness level, drawing from four pillars—social, political/regulatory, economic and technological—comprising a consistent set of eight evaluation criteria. The proposed decision analysis framework builds on the PROMETHEE II and AHP methods. Fourteen countries of different profile and level of progress towards sustainable development are evaluated and ranked, in an effort to highlight areas for improvement, and to support policymakers in designing appropriate pathways towards a greener economy.

Traditionally, Life Cycle Assessment (LCA) methodologies include four stages to assess the environmental impact of a product or process. These four stages are scope definition, life cycle inventory (LCI), life cycle impact assessment (LCIA) and interpretation of results. Data collection for the LCI requires substantial effort and may be considered the most critical phase of a LCA, as poor data availability and inconsistency of data may lead to unrealistic results and conclusions. In machine tools, this inventory definition effort is amplified by the inherent complexity of machine tools and their operational behaviour alternatives. This paper describes a LCI method for machine tools providing a new procedure, which improves the transparency and consistency of LCA data. The method is partially based on the developments and strategies described in the draft standard ISO/DIS 14955-1. In this paper, a detailed description of the new method is presented along with the demonstration of its applicability by its implementation in two different manufacturing cases. One of the cases involves the manufacturing of an aeronautic part, while the other case relates to a part manufactured for the household sector. The environmental impact of these two parts, which are produced by a traditional process and by an alternative process is considered, thus it is demonstrated that LCI method as part of a LCA, can be used as a decision support tool to assess the lifecycle impact of the manufacturing of a product using machine tools

Sustainability is an important concept for the whole world. Generally, in order to measure the sustainability of the environment, carbon dioxide emissions and ecological footprint indicators are used. However, these variables do not reflect the supply side of natural resources. Therefore, load capacity factor is an important environmental indicator for a sustainability. Environmental assessment based on the load capacity factor is more meaningful. Besides, improved access to financial services can contribute to environmental sustainability. The effect of financial inclusion on the load capacity factor in Türkiye has not been examined in the current literature. In this context, this study analyzes the impact of financial inclusion, hydropower energy consumption, and life expectancy at birth on environmental sustainability from a different perspective by focusing on load capacity factor. To this end, this study used the newly developed Augmented ARDL method to determine the cointegration relationship between the series and measure the values of the long-term coefficients. Based on the Augmented ARDL method, there is a cointegration relationship between the series. In the long run, hydropower energy consumption reduces pollution, while financial inclusion decreases load capacity factor. The effect of life expectancy at birth on pollution is not significant. Moreover, the results reveal that the load capacity curve hypothesis is valid in Türkiye. As a result, the Turkish government should promote renewable energy sources, especially hydropower energy consumption, align financial services with pollution reduction measures, and contribute to the creation of an environmentally conscious society.