ABSTRACT
It is necessary to accurately calculate ship carbon emissions for shipping suitability. The state-of-the-art approaches could arguably not be able to estimate ship carbon emissions accurately due to the uncertainties of Ship Technical Specification Database (STSD) and the geographical and temporal breakpoints in Automatic Identification System (AIS) data, hence requiring a new methodology to be developed to address such defects and further improve the accuracy of emission estimation. Firstly, a novel STSD iterative repair model is proposed based on the random forest algorithm by the incorporation of13 ship technical parameters. The repair model is scalable and can substantially improve the quality of STSD. Secondly, a new ship AIS trajectory segmentation algorithm based on ST-DBSCAN is developed, which effectively eliminates the impact of geographical and temporal AIS breakpoints on emission estimation. It can accurately identify the ships' berthing and anchoring trajectories and reasonably segment the trajectories. Finally, based on this proposed framework, the ship carbon dioxide emissions within the scope of domestic emission control areas (DECA) along the coast of China are estimated. The experiment results indicate that the proposed STSD repair model is highly credible due to the significant connections between ship technical parameters. In addition, the emission analysis shows that, within the scope of China's DECA, the berthing period of ships is longer owing to the joint effects of coastal operation features and the strict quarantine measures under the COVID-19 pandemic, which highlights the emissions produced by ship auxiliary engines and boilers. The carbon intensity of most coastal provinces in China is relatively high, reflecting the urgent demand for the transformation and updates of the economic development models. Based on the theoretical models and results, this study recommends a five-stage decarbonization scheme for China's DECA to advance its decarbonization process. © 2022 Elsevier Ltd
ABSTRACT
It is necessary to accurately calculate ship carbon emissions for shipping suitability. The state-of-the-art approaches could arguably not be able to estimate ship carbon emissions accurately due to the uncertainties of Ship Technical Specification Database (STSD) and the geographical and temporal breakpoints in Automatic Identification System (AIS) data, hence requiring a new methodology to be developed to address such defects and further improve the accuracy of emission estimation. Firstly, a novel STSD iterative repair model is proposed based on the random forest algorithm by the incorporation of13 ship technical parameters. The repair model is scalable and can substantially improve the quality of STSD. Secondly, a new ship AIS trajectory segmentation algorithm based on ST-DBSCAN is developed, which effectively eliminates the impact of geographical and temporal AIS breakpoints on emission estimation. It can accurately identify the ships' berthing and anchoring trajectories and reasonably segment the trajectories. Finally, based on this proposed framework, the ship carbon dioxide emissions within the scope of domestic emission control areas (DECA) along the coast of China are estimated. The experiment results indicate that the proposed STSD repair model is highly credible due to the significant connections between ship technical parameters. In addition, the emission analysis shows that, within the scope of China's DECA, the berthing period of ships is longer owing to the joint effects of coastal operation features and the strict quarantine measures under the COVID-19 pandemic, which highlights the emissions produced by ship auxiliary engines and boilers. The carbon intensity of most coastal provinces in China is relatively high, reflecting the urgent demand for the transformation and updates of the economic development models. Based on the theoretical models and results, this study recommends a five-stage decarbonization scheme for China's DECA to advance its decarbonization process.
ABSTRACT
This study aims to investigate the coronavirus disease (COVID-19) pandemic effects and associated restrictive rules on ship activities and pollutant emissions (CO2, SOX, NOX, PM, CO, CH4) in four major seaports, namely the Ports of Singapore, Long Beach, Los Angeles, and Hamburg. We used 2019 as the baseline year to show the business-as-usual emission and compared with the estimated quantity during the July 2020-July 2021 pandemic period. We also project future ship emissions from August 2021-August 2022 to illustrate two potential port congestion scenarios due to COVID-19. The results show that the ship emissions in all four ports generally increased by an average of 79% because of the prolonged turnaround time in port. Importantly, majority of ship emissions occurred during the extended hoteling time at berth and anchorage areas as longer operational times were needed due to pandemic-related delays, with increases ranging from 27 to 123% in the total emissions across ports. The most affected shipping segments were the container ships and dry bulk carriers which the total emissions of all pollutants increased by an average of 94-142% compared with 2019. Overall, the results of this study provide a comprehensive review of the ship emission outlook amid the pandemic uncertainty.
ABSTRACT
The maritime industry plays a key role in reducing greenhouse gas (GHG) emissions, as an effort to combat the global issue of climate change. The International Maritime Organization (IMO) is targeting a 50% reduction in GHG emissions by 2050 compared to 2008. To measure Singapore's progress towards this target, we have conducted a comprehensive analysis of carbon dioxide (CO2) emissions from the Western Singapore Straits based on the voyage data from Automatic Identification System (AIS) and static information from Singapore Maritime Data Hub (SG-MDH). Two methodologies, the MEET and TRENDS frameworks were applied to estimate the emission volume per vessel per hour. The data analysis results were next aggregated and visualised to answer key questions such as: How did the carbon emission level change from 2019 to 2020, in general, and for specific vessel types? What are the top vessel types and flags that had the highest carbon emissions? Did the traffic volume and emission level decrease during the Circuit Breaker period in 2020? The results of this study can be used to review Singapore's emission control measures and will be of value to the Maritime and Port Authority (MPA) of Singapore responsible for managing CO2 emissions at the Singapore Port.
Subject(s)
COVID-19 , Carbon Dioxide , Carbon Dioxide/analysis , Humans , SARS-CoV-2 , Ships , SingaporeABSTRACT
This study aims to evaluate impacts of the COVID-19 epidemic on merchant ship activities and corresponding atmospheric pollutant emissions in Shanghai port waters. Comparing AIS data from February 2019 and from February 2020, it is found that the merchant ship count and utilization frequency are reduced during the epidemic period. The epidemic could result in longer ship turnaround times because of more operation time for berthing and anchoring activities. Ship emission comparison results reveal that the cargo ship emissions are significantly reduced while container ships and tankers produce a slightly decreased emissions resulting by strict COVID-19 quarantine measures. In addition, the unit ship emission intensity is greatly reduced for ships which are under the normal cruising status while berthing and anchoring operations are associated with increased ship emissions. This implies that it is urgent to promote the use of shore power equipment for merchant ships during the epidemic period.