A Data-Driven Model for Rapid CII Prediction DOI Creative Commons
Markus Mühmer, Alessandro La Ferlita, Evangelos Maximilian Geber

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(11), P. 2048 - 2048

Published: Nov. 12, 2024

The shipping industry plays a crucial role in global trade, but it also contributes significantly to environmental pollution, particularly regard carbon emissions. Carbon Intensity Indicator (CII) was introduced with the objective of reducing emissions sector. lack familiarity performance is common issue among vessel operator. To address this aspect, development methods that can accurately predict CII for ships paramount importance. This paper presents novel and simplified approach predicting ships, which makes use data-driven modelling techniques. proposed method considers restricted set parameters, including operational data (draft speed) conditions, such as wind speed direction, provide an accurate prediction factor. extends state research by applying Deep Neural Networks (DNNs) deviation less than 6% over considered time frame consisting different operating states (cruising maneuvering mode). result achieved using limited amount training data, enables ship owners obtain rapid estimation their yearly rating prior receiving annual evaluation.

Language: Английский

Explaining differences in policy learning in the EU "Fit for 55” climate policy package DOI Creative Commons
Fredrik von Malmborg

European Policy Analysis, Journal Year: 2024, Volume and Issue: 10(3), P. 412 - 448

Published: May 31, 2024

Abstract Through learning, policy actors can maintain, reinforce, or revise their beliefs and positions about the design outcomes of policies. This paper critically analyzes factors influencing learning by comparing processes two EU laws recent “Fit for 55” climate package: (i) revised provisions on increasing energy efficiency in companies included recast Energy Efficiency Directive (ii) new FuelEU Maritime regulation provided decarbonizing maritime shipping. Learning across coalitions with competing was encountered first case but not other despite similar institutional settings. The difference is attributed to a more politicized debate shipping, leading consensus through bargaining instead deliberation, circumscribed leader one coalition, less flexible negotiation mandate. adds theory suggesting that levels politicization polarization, as well mandates coalition leaders, influence cross‐coalition learning.

Language: Английский

Citations

4
From Role Model to International Scapegoat: Analysing the Paradigm Shift in Swedish Climate Policy and Governance DOI Open Access
Fredrik von Malmborg

Published: May 17, 2024

Sweden has long been hailed as a role model in climate policy. But the new right-wing government supported by far-right populist party is undertaking paradigm shift Swedish policy and governance. This paper critically analyses this from perspectives of legitimacy, accountability justice. These are democratic norms important analysis just transition to neutrality. Severe deficits process policies proposed adopted identified. The explained neo-corporatist political system Sweden, dominance (neo)liberal discourse ecological modernization environmental policy, an ongoing autocratization driven anti-democratic parties throughout Europe. ends suggesting how governance can be democratized re-politicized, that also give room for justice advocates take part processes.

Language: Английский

Citations

2
Tapping the Conversation on the Meaning of Decarbonization: Discourses and Discursive Agency in EU Politics on Low-Carbon Fuels for Maritime Shipping DOI Open Access
Fredrik von Malmborg

Published: May 20, 2024

EU politics on decarbonizing shipping is an argumentative struggle in which actors try to make others see the problem and policy solutions according their views seek position other a specific way. This article critically analyses, by means of discourse analysis, process related recent adoption FuelEU Maritime regulation, world’s most ambitious legislation for maritime shipping. Different storylines discourses as well agency problems options defining meaning decarbonization are analysed. Two framed debates, focusing (i) incremental change technology neutrality meet moderate emission reductions maintain competitiveness, (ii) transformative specificity zero emissions gain competitiveness global leadership transition towards hydrogen economy. Policy successfully used discursive strategies such multiple functionality vagueness navigate between resolve conflicts two discourses. Both associated with overarching ecological modernization failed include issue just transition. The heritage creates lock-ins broader discourse, thus stalling

Language: Английский

Citations

1
Going beyond the Council as brake of EU energy policy: Analysing the internal process of the Council in the recast of the Energy Performance of Buildings Directive DOI Creative Commons
Martin Björklund, Fredrik von Malmborg, Lina La Fleur

et al.

Energy Policy, Journal Year: 2024, Volume and Issue: 195, P. 114388 - 114388

Published: Oct. 16, 2024

Language: Английский

Citations

0
A Data-Driven Model for Rapid CII Prediction DOI Creative Commons
Markus Mühmer, Alessandro La Ferlita, Evangelos Maximilian Geber

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(11), P. 2048 - 2048

Published: Nov. 12, 2024

The shipping industry plays a crucial role in global trade, but it also contributes significantly to environmental pollution, particularly regard carbon emissions. Carbon Intensity Indicator (CII) was introduced with the objective of reducing emissions sector. lack familiarity performance is common issue among vessel operator. To address this aspect, development methods that can accurately predict CII for ships paramount importance. This paper presents novel and simplified approach predicting ships, which makes use data-driven modelling techniques. proposed method considers restricted set parameters, including operational data (draft speed) conditions, such as wind speed direction, provide an accurate prediction factor. extends state research by applying Deep Neural Networks (DNNs) deviation less than 6% over considered time frame consisting different operating states (cruising maneuvering mode). result achieved using limited amount training data, enables ship owners obtain rapid estimation their yearly rating prior receiving annual evaluation.

Language: Английский

Citations

0