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1
Optimizing the Local Embedding of Renewable Energy Plants

Michael Krug,Dörte Ohlhorst 한국환경정책학회 2019 環境政策 Vol.27 No.S
- 원문보기 2
  DBpia
  
  KISS
- 복사/대출신청
In this article we ask about the factors that promote acceptance of local renewable energy plants and about the specific role nature conservation plays in the concert of other acceptance factors. We explored to what extent trade-offs between climate protection, nature and species protection, protection of local residents and local value creation can be realigned. The article provides an overview of the key acceptance factors identified and derives a set of trust and acceptance building measures. It has a specific focus on wind energy. Our findings suggest that nature conservation rationales have definitively a role to play as a local acceptance factor, but other acceptance factors are closely linked or more important. Particularly, economic factors, the attitudes towards the energy transition, trust in key actors and planning and development processes were identified as key preconditions for local acceptance.
2
Conditions Enhancing the Socially Inclusive and Environmentally Sound Uptake of Wind Energy: The Case of Germany

Maria Rosaria Di Nucci,Michael Krug 한국환경정책학회 2018 環境政策 Vol.26 No.S
- 원문보기 2
  DBpia
  
  KISS
- 복사/대출신청
This paper discusses the framework conditions to promote the socially inclusive and environmentally sound uptake of renewable energy with a special focus on wind power in Germany and on the policy framework of the European Union (EU). The analysis of these aspects relates to the achievement of one of the Sustainable Development Goals, namely SDG 7 (affordable and clean energy). Wind power plays an important role for mastering the energy transition, but in many countries of the EU, wind energy has become a subject of contested debates. Besides geographic, market, policy, and other factors which affect the implementation of wind energy projects, low levels of market deployment can also be attributed to a diminishing social acceptance and growing local opposition. This is mostly due to the visual impact, noise annoyance, public perception of health risks, local environmental disruption harming local fauna and flora, potentially negative impact on recreation and tourism, or land and real property values as well as to perceived procedural or distributional injustice including affordability of electricity prices, and insufficient public participation. The paper provides insights from an ongoing research project supported by the European Commission under the research programme Horizon 2020. The WinWind Project identifies similarities and differences between regions in five EU countries and in Norway highlighting barriers and drivers for the uptake of wind energy. The paper analyses the European and the German policy frameworks, social acceptance barriers and drivers in two regions of East Germany, and describes promising approaches that drive social acceptance and enhance the environmentally sound uptake of wind energy projects.
3
antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

Weber, Tilmann,Blin, Kai,Duddela, Srikanth,Krug, Daniel,Kim, Hyun Uk,Bruccoleri, Robert,Lee, Sang Yup,Fischbach, Michael A,Mü,ller, Rolf,Wohlleben, Wolfgang,Breitling, Rainer,Takano, Eriko,Medema, Oxford University Press 2015 Nucleic acids research Vol.43 No.w1
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AbstractMicrobial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software.