Towards Efficient Mapping of Greenhouse Gas Emissions: A Case Study of the Port of Tallinn
Jonne Kotta (),
Mihhail Fetissov,
Ellen Kaasik,
Janis Väät,
Stanislav Štõkov and
Ulla Pirita Tapaninen
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Jonne Kotta: Estonian Maritime Academy, Tallinn University of Technology, Kopli 101, 11712 Tallinn, Estonia
Mihhail Fetissov: Estonian Maritime Academy, Tallinn University of Technology, Kopli 101, 11712 Tallinn, Estonia
Ellen Kaasik: Port of Tallinn, Sadama 25, 15051 Tallinn, Estonia
Janis Väät: Port of Tallinn, Sadama 25, 15051 Tallinn, Estonia
Stanislav Štõkov: Estonian Environmental Research Centre, Marja 4D, 10617 Tallinn, Estonia
Ulla Pirita Tapaninen: Estonian Maritime Academy, Tallinn University of Technology, Kopli 101, 11712 Tallinn, Estonia
Sustainability, 2023, vol. 15, issue 12, 1-13
Abstract:
Global, regional and national policies and regulations are providing incentives to reduce greenhouse gas (GHG) emissions in ports, and the first step in this effort is to obtain a detailed overview of the main sources of emissions. The rapid developments in port GHG mapping have led to the need for a case study to assess the effectiveness and practical use of these methodologies and to suggest best practices for ports just starting this mapping process. Here, we present the current state of the art in the assessment of GHG emissions in ports. This analysis enabled us to identify the most promising methodologies to assess GHG emissions in ports in an efficient, reliable and near real-time manner. We then tested the best methodologies and practices that emerged from the review articles to build a GHG assessment system in the Port of Tallinn. Finally, we assess the advantages and disadvantages of current approaches and suggest promising ways forward.
Keywords: climate change; GHG mapping; ports (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:12:p:9520-:d:1170439
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