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Green hydrogen will play a key role in building a climate-neutral energy-intensive industry, as key technologies for defossilising the production of steel and basic chemicals depend on it. Thus, policy-making needs to support the creation of a market for green hydrogen and its use in industry. However, it is unclear how appropriate policies should be designed, and a number of challenges need to be addressed. Based on an analysis of the ongoing German debate on hydrogen policies, this paper analyses how policy-making for green hydrogen development may support industry defossilisation. For the assessment of policy instruments, a simplified multi-criteria analysis (MCA) is used with an innovative approach that derives criteria from specific challenges. Four challenges and seven relevant policy instruments are identified. The results of the MCA reveal the potential of each of the selected instruments to address the challenges. The paper furthermore outlines how instruments might be combined in a policy package that supports industry defossilisation, creates synergies and avoids trade-offs. The paper’s impact may reach beyond the German case, as the challenges are not specific to the country. The results are relevant for policy-makers in other countries with energy-intensive industries aiming to set the course towards a hydrogen future.

Extensive cost in the building industry comes from cooling and heating to create thermal comfort. Hence, it is necessary to utilize passive solutions, in addition to suitable design, in order to reduce energy consumption. This research attempts to investigate the impact of archetype patterns in office buildings on annual energy consumption for cooling, heating and daylight loads. For this purpose, the DesignBuilder software was used to compare the forms. In this study, four conventional construction forms were considered, including the single and dense form, central courtyard buildings, U form and linear form, and each was considered with two, four and six-stories. Forms were simulated in the three cities of Bushehr, Shiraz and Tabriz, with hot-humid, hot-dry and cold climates, respectively. The results revealed that the office building with a linear form in Bushehr had the lowest energy consumption in the two and four-story forms, and also in the six-story form, the central courtyard form had the lowest energy consumption. Additionally, the central courtyard forms in Tabriz and Shiraz had the lowest energy consumption in all cases. Finally, the linear form possessed the most natural daylight through all of the studied cases for the three cities in terms of natural light gain.

Electric vehicles require sufficient public charging infrastructure. This in turn necessitates detailed information on charging demand. In this paper we present a four-step approach to estimating public charging demand of electric vehicles. Previous methods are limited in their ability to provide differentiated results and adapt to future developments. Therefore, we account for user groups (private, carsharing, commercial), technical developments (vehicles, infrastructure), infrastructure availability, and carsharing development (operational area, business models, autonomous vehicles). Our approach also considers the interactions between these factors and allows for scenario analysis yielding the quantity and spatial distribution of public charging demand. We demonstrate our approach for Berlin, Germany. We find that the majority of public charging demand results from carsharing. This demand is concentrated in the city center, even when carsharing is available citywide. Public charging demand for commercial users is relatively low and located outside the city center. For private users, public charging demand shifts to the city center with an increasing market penetration of electric vehicles and technological advancements (increased range, charging speed). Public demand from private users increases dramatically when private infrastructure is absent. Finally, public charging demand shifts to the city center when private users do not have private infrastructure.

White storks (Ciconia ciconia) are birds that make annual long-distance migration flights from their breeding grounds in the Northern Hemisphere to the south of Africa. These trips take place in the winter season, when the temperatures in the North fall and food supply drops. White storks, because of their large size, depend on the wind, thermals, and orographic characteristics of the environment in order to minimize their energy expenditure during flight. In particular, the birds adopt a soaring behavior in landscapes where the thermal uplift and orographic updrafts are conducive. By attaining suitable soaring heights, the birds then use the wind characteristics to glide for hundreds of kilometers. It is therefore expected that white storks would prefer landscapes that are characterized by suitable wind and thermal characteristics, which promote the soaring and gliding behaviors. However, these same landscapes are also potential sites for large-scale wind energy generation. In this study, we used the observed data of the white stork movement trajectories to specify a data-driven agent-based model, which simulates flight behavior of the white storks in a dynamic environment. The data on the wind characteristics and thermal uplift are dynamically changed on a daily basis so as to mimic the scenarios that the observed birds experienced during flight. The flight corridors that emerge from the simulated flights are then combined with the predicted surface on the wind energy potential, in order to highlight the potential risk of collision between the migratory white storks and hypothetical wind farms in the locations that are suitable for wind energy developments. This work provides methods that can be adopted to assess the overlap between wind energy potential and migratory corridors of the migration of birds. This can contribute to achieving sustainable trade-offs between wind energy development and conservation of wildlife and, hence, handling the issues of human–wildlife conflicts.

Anaerobic digestion producing biogas is an important decentralized renewable energy technology used to mitigate climate change. It is dependent on local and regional feedstocks, which determine its sustainability. This has led to discussions on how to alter feedstock for biogas plants without compromising their GHG (Greenhouse gas) saving, one particular issue being the use of Maize silage (MS) as the dominant feedstock. To support this discussion, this paper presents an integrated life cycle assessment of energy crop cultivation for 425 biogas catchments in the region of Central Germany (CG). The simulations for the CG region showed that MS as an effective crop to mitigate GHG emissions per kilowatt hour (GHGculti) was context dependent. In some cases, GHGculti reductions were supported due to higher yields, and in other cases, this led to increased GHGculti. We show that the often-proposed strategy of substituting one crop for another needs to be adapted for strategies which take into account the crop mixtures fed into biogas plants and how they perform altogether, under the specific regional and locational conditions. Only in this way can the trade-offs for lower GHGculti be identified and managed.

How can citizen science projects advance the achievement of transformative air quality-related Sustainable Development Goals (SDGs) in Germany and Niger? We investigate the promise of using citizen-generated data (CGD) as an input for official SDG monitoring and implementation in a multidisciplinary project, based on activities undertaken in Niger and Germany ranging from surveys, action research, policy and legislative analysis and environmental monitoring in Niamey and Leipzig, respectively. We critically describe and evaluate the great potential, but very limited actual use of CGD sources for these global goals in both contexts from technical and policy perspectives. Agenda 2030 provides an opportunity to tackle indoor and outdoor air quality in a more integrated and transformative perspective. However, we find this agenda to be remarkably absent in air quality policy and monitoring plans. Likewise, we find no meaningful links of existing citizen science initiatives to official air quality policy. We propose how SDGs-aligned citizen science initiatives could make major contributions to environmental and health monitoring and public debate, especially in the wake of the COVID-19 pandemic. This however requires researchers to more strategically link these initiatives to policymakers and policy frameworks, such as SDG indicators and the governance structures in which they are embedded.