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Urbanization and climate change are amongst the greatest challenges of the 21st century. In the "Low Carbon Future Cities" project (LCFC), three important problem dimensions are analysed: current and future GHG emissions and their mitigation (up to 2050); resource use and material flows; and vulnerability to climate change.
The industrial city of Wuxi has been the Chinese pilot city of the project. To establish the pathway for a low carbon future, it is crucial to understand the current situation and possible future developments. The paper presents the key results of the status quo analysis and the future scenario analysis carried out for Wuxi. Two scenarios are outlined. The Current Policy Scenario (CPS) shows the current most likely development in the area of energy demand and GHG emissions until 2050. Whereas the extra low carbon scenario (ELCS) assumes a significantly more ambitious implementation, it combines a market introduction of best available technologies with substantial behavioural change. All scenarios are composed of sub-scenarios for the selected key sectors.
Looking at the per capita emissions in Wuxi, the current levels are already high at around 12 tonnes CO2 per capita compared to Western European cities. Although Wuxi has developed a low carbon plan, the projected results under current policies (CPS) show that the total emissions would increase to 23.6 tonnes CO2 per capita by 2050. If the ELCS pathway was to be adopted, these CO2 emission levels could be reduced to 6.4 tonnes per capita by 2050.
Despite Germany's Paris Agreement pledge and coal exit legislation, the political debate around carbon-intensive coal remains heated. Coal power and mining have played an important, yet changing role in the history of German politics. In this paper, we analyze the entire parliamentary debate on coal in the German parliament (Bundestag) from its inception in 1949 to 2019. For this purpose we extract the more than 870,000 parliamentary speeches from all protocols in the history of the Bundestag. We identify the 9167 speeches mentioning coal and apply dynamic topic modeling – an unsupervised machine learning technique that reveals the changing thematic structure of large document collections over time - to analyze changes in parliamentary debates on coal over the past 70 years. The trends in topics and their varying internal structure reflect how energy policy was discussed and legitimized over time: Initially, coal was framed as a driver of economic prosperity and guarantee of energy security. In recent years, the debate evolved towards energy transition, coal phase-out and renewable energy expansion. Germany’s smaller and younger parties, the Greens and the Left Party, debate coal more often in the context of the energy transition and climate protection than other parties. Our results reflect trends in other countries and other fields of energy policy. Methodologically, our study illustrates the potential of and need for computational methods to analyze vast corpora of text and to complement traditional social science methods.