Scoping carbon dioxide removal options for Germany–What is their potential contribution to Net-Zero CO2_{2}?

In its latest assessment report the IPCC stresses the need for carbon dioxide removal (CDR) to counterbalance residual emissions to achieve net zero carbon dioxide or greenhouse gas emissions. There are currently a wide variety of CDR measures available. Their potential and feasibility, however, depends on context specific conditions, as among others biophysical site characteristics, or availability of infrastructure and resources. In our study, we selected 13 CDR concepts which we present in the form of exemplary CDR units described in dedicated fact sheets. They cover technical CO2 removal (two concepts of direct air carbon capture), hybrid solutions (six bioenergy with carbon capture technologies) and five options for natural sink enhancement. Our estimates for their CO2 removal potentials in 2050 range from 0.06 to 30 million tons of CO2, depending on the option. Ten of the 13 CDR concepts provide technical removal potentials higher than 1 million tons of CO2 per year. To better understand the potential contribution of analyzed CDR options to reaching net-zero CO2 emissions, we compare our results with the current CO2 emissions and potential residual CO2 emissions in 2050 in Germany. To complement the necessary information on technology-based and hybrid options, we also provide an overview on possible solutions for CO2 storage for Germany. Taking biophysical conditions and infrastructure into account, northern Germany seems a preferable area for deployment of many concepts. However, for their successful implementation further socio-economic analysis, clear regulations, and policy incentives are necessary

Innovating in Krugman’s Footsteps – Where and How Innovation Differs in Europe: Static Innovation Indicators for Identifying Regional Policy Leverages

This paper introduces two indicators for innovation, showing the allocation of innovation and its inherent diversity. Both indicators can give insights for regional innovation policy conception. The first indicator measures the share of patents in research and development expenditure, proposing a locational innovation output indicator. It can show that innovation in Europe differs strongly among NUTS2-level regions, which points to regionally specific, place-based policies as a result of a strong dispersion in European innovation activity. The second measure, the innovation diversity indicator, shows the diversification of innovation in a region and is built upon Krugman’s locational Gini coefficients. Here, the share of patents belonging to a particular IPC class is related to the dispersion of all patents in a region. Possible implications for policy are the construction of place-based, technology-specific programs, on either national or subnational (NUTS2-) level, where each country or region has to be considered carefully. Analyses underline that innovation in Europe is a highly regionally and technically diversified concept.Dieses Papier stellt zwei Indikatoren für Innovation vor, die die Allokation von Innovation und ihre Vielfalt aufzeigen. Beide Indikatoren können Erkenntnisse für die Konzeption regionaler Innovationspolitik liefern. Der erste Indikator misst den Anteil von Patenten an den Forschungs- und Entwicklungsausgaben und schlägt einen Indikator für standortbezogenen Innovationsoutput vor. Er kann zeigen, dass sich die Innovation in Europa zwischen den Regionen der NUTS2-Ebene stark unterscheidet, was auf eine regionalspezifische, standortbezogene Politik infolge einer starken Streuung der europäischen Innovationsaktivitäten hinweist. Das zweite Maß, ein Indikator für Innovationsvielfalt, zeigt die Diversifizierung von Innovation in einer Region und baut auf Krugmans standortbezogenen Gini-Koeffizienten auf. Hier wird der Anteil der Patente, die zu einer bestimmten IPC-Klasse gehören, mit der Streuung aller Patente in einer Region in Beziehung gesetzt. Mögliche Implikationen für die Politik sind die Konstruktion ortsbezogener, technologiespezifischer Programme entweder auf nationaler oder subnationaler (NUTS2-) Ebene, wobei jedes Land oder jede Region individuell betrachtet werden sollte. Die Analysen unterstreichen, dass Innovation in Europa ein stark regional und technisch diversifiziertes Konzept ist

Nothing but hot air? A multimethod approach of the automotive industry's sustainability standpoints

The decarbonization of the transport sector is essential to meeting the goals of the Paris Agreement and the Net Zero Emissions strategies. In the automotive sector, this has led to increased momentum for sustainability and a recognition of the need to develop sustainable mobility alternatives. In the sector, there are certain players which appear to be far ahead in the transition, whereas there are others that are considered "laggards". We consider how the biggest global players in the automotive sector position sustainability and its subtopics on their agenda and the extent to which their actions match their positioning on sustainability. Moreover, the contrasting of actions with communication on sustainability will highlight discrepancies between sustainability performance and communication - e.g. are there certain players who are actually better at sustainability, but not good at communicating what they do?We adopt a multimethod approach, using a topic model which is complemented by a multi equation regression model. The topic model is applied to sustainability reports, using natural language processing to identify the focus of each manufacturer's sustainability strategies. The results from this model are then used to form the outcome variables in a seemingly unrelated regression model (SUR model). Further variables in the model are derived from quantitative data relating to e.g. proportion of zero-emission vehicles or indicators of sustainable production like energy consumption etc. This way, the model can compare the actual sustainability performance of the manufacturers to their communication. In combining both the topic model based on automated language processing techniques with a more traditional quantitative SUR model, this paper combines two different research approaches in a complementary way to address a complex research problem which has not been empirically investigated like this before

Chance in the challenge – Positive environmental externalities in the tourism sector through Covid-19

Due to the spread of Covid-19, a global pandemic situation has developed since December 2019, which has serious effects on the various economic sectors. The tourism sector with hotel, catering, transport, as well as secondary and tertiary industries in particular are massively affected, as the demand for tourism is very sensitive to crises (Fotiadis et al, 2021, p. 2). Like an external shock, Covid-19 shows a similar decline in demand for goods in the tourism sector as can be observed as a result of wars and natural disasters (Jin et al., 2021, p. 1).Contrasting the negative effects caused by the pandemic, there also occur other externalities which exhibit positive developments, especially from an environmental point of view. Less travel also means that less greenhouse gases (GHG) are emitted, less littering of vacation areas can be observed, and the natural habitats of animals recover through reduced tourism (Wieckowski, 2021, p. 9).It turns out, however, that the positive externalities on the environment cannot be observed to the same extent across all countries and regions and are strongly influenced by local tourism characteris-tics. Clusters and hot spots can be observed that are experiencing a particularly positive development, whereas other areas show less improvement (Newsome, 2020, p. 2).To analyze the effects of the European tourism sector on GHG emissions, we model multiple indicators (e.g. personnel employed in the tourism sector, number of nights spent at tourist accommodation es-tablishments, etc.) together with indicators for general economic activity and mobility. In a spatiotem-poral approach, we are able to account explicitly for regional and temporal autocorrelation and thus extracting these effects from the residuals. Additionally, we introduce the external shock of the pan-demic as further additive factor in the model. The model allows estimating the impact of the tourism sector on GHG emissions, distinguishing them from effects of the general economic development. We can furthermore identify in which regions additional factors seem to affect GHG emissions, thus illus-trating hotspots of GHG emission reduction created by a reduction in activity also beyond the tourism sector.According to Coase’s theory of internalization, tangible solution mechanisms are to be worked out that enable cost-benefit considerations. Which region can achieve the highest level of positive environmen-tal development at which costs? Should a redistribution mechanism take place here in order to achieve an overall improvement of the environment, whereby individual regions internalize less from an eco-nomic point of view due to higher costs and support other regions that can exploit high potential for improvement with the use of fewer monetary resources?Ultimately, classic tax solutions such as an environmental tax or tourism tax are to be compared with a negotiated solution based on pollution certificates as a solution mechanism. This is intended to weigh up the efficiency of the two methods

Chance in the challenge – Positive environmental externalities in the tourism sector through COVID-19

Due to the spread of COVID-19, a global pandemic situation has developed since December 2019, which has serious effects on the various economic sectors, affecting the tourism sector secondary and tertiary industries. To analyse the effects of the European tourism sector on CO2 emissions, we model emissions together with tourism indicators. The model allows esti-mating the impact of the tourism sector on greenhouse gas emissions, distinguishing them from time and space effects. The model’s results suggest a positive impact of tourism arrivals and tourism-related expenditure on CO2 emissions, meaning that the decrease in tourism con-tributed to the overall decrease in CO2 emissions to a significant extent. Analysing the spatial autocorrelation, data show that all countries we investigated are similarly affected by a reduc-tion in tourism and there appears to be no regional differentiation of impacts by COVID-19. To conclude the model’s results, the reduction in emissions can be explained to a part by the reduction in travel, which points to the potential in this relation that could be used as a lever-age in conceptionalising measures to reduce CO2, targeting the tourism sector

Spatial analysis of the effects of the dismantling of end-of-life wind turbines in Germany

Macroeconomic impacts being linked with construction and use of photovoltaic cells and wind power plants have been emphasized in many studies (e.g., Allan et al., 2020; Graziano et al., 2017; Mattes, 2014). Regarding impacts being related to the end-of-life (EOL) of these technologies, currently most studies focus on waste forecasts or impact analysis of investments and not on employment or changes in value added. (e.g., Costa & Veiga, 2021; Shoeib et al., 2021). Our study aims to contribute to close this research gap.The increased deployment of renewable energy and is linked with rising demand for production inputs such as concrete, steel, and fiberglass that have to be disposed of or recycled. Wind turbines, in particular, consist of several construction elements, which are renewed at certain intervals due to their limited technical service life or due to further technical development (repowering). If these construction elements cannot be reused at other locations, they must be disposed of as waste based on the regulations of the Closed Substance Cycle Waste Management Act. Still, the aforementioned components of wind turbines can be almost completely recycled. If the volume of wind turbines requiring disposal increases, experts assume that the disposal market will react to this and additional capacities may be made available. In our model, we focus on wind turbines, as many wind power plants will reach their EOL soon, particularly in Germany. After a lifespan of 20-25 years, parts of the wind turbines are currently disposed of either as landfill or are thermically reused in the cement industry, as recycling them in a sustainable manner is an option that is still left to be exploited. In Figure 1 the coverage and dispersion of wind turbines in Germany can be observed. Corresponding to wind power potential, most plants are located in Northern regions. Especially in these regions, the EOL and need for dismantling can create substantial effects for regional employment, which is why we look on these macroeconomic impacts being linked with dismantling of wind power plants

Spatial analysis of the effects of the dismantling of end-of-life wind turbines in Germany

Macroeconomic impacts being linked with construction and use of photovoltaic cells and wind power plants have been emphasized in many studies (e.g., Allan et al., 2020; Graziano et al., 2017; Mattes, 2014). Regarding impacts being related to the end-of-life (EOL) of these technologies, currently most studies focus on waste forecasts or impact analysis of investments and not on employment or changes in value added. (e.g., Costa & Veiga, 2021; Shoeib et al., 2021). Our study aims to contribute to close this research gap.The increased deployment of renewable energy and is linked with rising demand for production inputs such as concrete, steel, and fiberglass that have to be disposed of or recycled. Wind turbines, in particular, consist of several construction elements, which are renewed at certain intervals due to their limited technical service life or due to further technical development (repowering). If these construction elements cannot be reused at other locations, they must be disposed of as waste based on the regulations of the Closed Substance Cycle Waste Management Act. Still, the aforementioned components of wind turbines can be almost completely recycled. If the volume of wind turbines requiring disposal increases, experts assume that the disposal market will react to this and additional capacities may be made available. In our model, we focus on wind turbines, as many wind power plants will reach their EOL soon, particularly in Germany. After a lifespan of 20-25 years, parts of the wind turbines are currently disposed of either as landfill or are thermically reused in the cement industry, as recycling them in a sustainable manner is an option that is still left to be exploited. In Figure 1 the coverage and dispersion of wind turbines in Germany can be observed. Corresponding to wind power potential, most plants are located in Northern regions. Especially in these regions, the EOL and need for dismantling can create substantial effects for regional employment, which is why we look on these macroeconomic impacts being linked with dismantling of wind power plants

A spatiotemporal approach for the innovative activity in Europe

This paper provides exploratory empirical evidence on the innovation characteristics of the European countries using a spatiotemporal approach. Using Bayesian Additive Models for Location, Scale, and Shape (BAMLSS) a heteroscedastic Gaussian geoadditive model is specified. It incorporates different explanatory model terms for innovative activity, spatial autocorrelation, and a time effect and allows a flexible model fit close to the data observed. The timeframe of the dataset used in this paper covers the period from 2000 to 2012 and contains 224 regions. The main results show that spatial proximity and temporal considerations add to the explanatory content and provide insights about the innovative activity in Europe, supporting the importance of regionally differentiated considerations. The findings suggest that action schemes should focus on promoting cooperation among actors, facilitate R&D transfer, and consider spatial spillover effects

Spatio-temporal dynamics of European innovation—An exploratory approach via multivariate functional data cluster analysis

We apply a functional data approach for mixture model-based multivariate innovation clustering to identify different regional innovation portfolios in Europe, considering patterns of specialization among innovation types. We combine patent registration data and other innovation and economic data across 225 regions, 13 years, and eight patent classes. The approach allows us to form several regional clusters according to their specific innovation types and captures spatio-temporal dynamics too subtle for most other clustering methods. Consistent with the literature on innovation systems, our analysis supports the value of regionalized clusters that can benefit from flexible policy support to strengthen regions as well as innovation in a systematic context, adding technology specificity as a new criterion to consider. The regional innovation cluster solutions for IPC classes for ‘fixed constructions’ and ‘mechanical engineering’ are highly comparable but relatively less comparable for ‘chemistry and metallurgy’. The clusters for innovations in ‘physics’ and ‘chemistry and metallurgy’ are similar; innovations in ‘electricity’ and ‘physics’ show similar temporal dynamics. For all other innovation types, the regional clustering is different. By taking regional profiles, strengths, and developments into account, options for improved efficiency of location-based regional innovation policy to promote tailored and efficient innovation-promoting programs can be derived