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1st January 2020 the global upper limit on the sulphur content of ships' fuel oil was reduced from 3.50% to 0.50%, which represents an ~86% cut (from [https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx](https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx)).\n\n![Ship image](https://wwwcdn.imo.org/localresources/en/MediaCentre/PressBriefings/PublishingImages/2019 images pb/Sulphur 2020 inside pic.jpg)\n\n*Image from [IMO 2020 - cleaner shipping for cleaner air, 20 December 2019](https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx)*\n\nAccording to the [International Maritime Organization (IMO)](https://www.imo.org/) the new limit should lead to a 77% drop in overall SOx emissions from ships. \n\nThe Figure below shows the 5 key beneficial changes from IMO's **Sulphur Limit** for Ships' fuel oil:\n\n![Sulphur key changes](https://wwwcdn.imo.org/localresources/en/MediaCentre/PressBriefings/PublishingImages/2019 images pb/5 changes - Sulphur 2020 - infographic web.jpg)\n\n*Five beneficial changes from IMO’s Sulphur Limit for ships’ fuel oil*\n\n\n## This Research Object's purpose\n\nIn this work we look as the **actual impact of these measures on air pollution along shipping routes in Europe** based on Copernicus air quality data. [Copernicus Atmosphere Monitoring Service (CAMS)](https://ads.atmosphere.copernicus.eu/cdsapp#!/home) uses satellite data and other observations, together with computer models, to track the accumulation and movement of air pollutants around the planet (see [https://atmosphere.copernicus.eu/air-quality](https://atmosphere.copernicus.eu/air-quality)).\n\n### Rohub - Adam plateform integration\n\n\nSome of this CAMS data is available from the [Adam platform](https://adamplatform.eu) and can be imported into a [Research Object](https://www.researchobject.org). \n\n![ADAM Platform](https://adamplatform.eu/wp-content/uploads/2021/03/adam-home-platfomr.png)\n\n*Example of data (here daily temperatures) displayed on the Adam plateform*\n\nIt is also possible, from the Research Object, to open the resource in the Adam platform, then interactively zoom into a particular geographical area (say to the right of the Strait of Gibraltar, along the track presumably followed by cargo ships to/from the Suez Canal) and change the date (for example between 2018-07-19 and 2023-07-19) to appreciate the change.\n\n#### To go further\n\nObviously **a more detailed statistical analysis** would be required to minimize the effect of external factors (meteorological condition, level of cargo traffic, etc.) over a longer period of time to derive meaningful conclusions, however it does not seem that the high level of sulfur dioxide concentration from the pre-IMO regulation was reached after.\n\n\n##### Looking at other pollutants\n\nBesides SOx the new regulation also contributed to decrease atmospheric concentrations in nitric oxides (NOx) as well as particulate matter (PM).\n\n### References\n\n- [IMO 2020 - cleaner shipping for cleaner air, 20 December 2019](https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx)" }, { "@value": "## Rationale\n\n\nFrom 1st January 2020 the global upper limit on the sulphur content of ships' fuel oil was reduced from 3.50% to 0.50%, which represents an ~86% cut (from [https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx](https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx)).\n\n![Ship image](https://wwwcdn.imo.org/localresources/en/MediaCentre/PressBriefings/PublishingImages/2019%20images%20pb/Sulphur%202020%20inside%20pic.jpg)\n\n*Image from [IMO 2020 - cleaner shipping for cleaner air, 20 December 2019](https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx)*\n\nAccording to the [International Maritime Organization (IMO)](https://www.imo.org/) the new limit should lead to a 77% drop in overall SOx emissions from ships. \n\nThe Figure below shows the 5 key beneficial changes from IMO's **Sulphur Limit** for Ships' fuel oil:\n\n![Sulphur key changes](https://wwwcdn.imo.org/localresources/en/MediaCentre/PressBriefings/PublishingImages/2019%20images%20pb/5%20changes%20-%20Sulphur%202020%20-%20infographic%20web.jpg)\n\n*Five beneficial changes from IMO’s Sulphur Limit for ships’ fuel oil*\n\n\n## This Research Object's purpose\n\nIn this work we look as the **actual impact of these measures on air pollution along shipping routes in Europe** based on Copernicus air quality data. [Copernicus Atmosphere Monitoring Service (CAMS)](https://ads.atmosphere.copernicus.eu/cdsapp#!/home) uses satellite data and other observations, together with computer models, to track the accumulation and movement of air pollutants around the planet (see [https://atmosphere.copernicus.eu/air-quality](https://atmosphere.copernicus.eu/air-quality)).\n\n### Rohub - Adam plateform integration\n\n\nSome of this CAMS data is available from the [Adam platform](https://adamplatform.eu) and can be imported into a [Research Object](https://www.researchobject.org). \n\n![ADAM Platform](https://adamplatform.eu/wp-content/uploads/2021/03/adam-home-platfomr.png)\n\n*Example of data (here daily temperatures) displayed on the Adam plateform*\n\nIt is also possible, from the Research Object, to open the resource in the Adam platform, then interactively zoom into a particular geographical area (say to the right of the Strait of Gibraltar, along the track presumably followed by cargo ships to/from the Suez Canal) and change the date (for example between 2018-07-19 and 2023-07-19) to appreciate the change.\n\n#### To go further\n\nObviously **a more detailed statistical analysis** would be required to minimize the effect of external factors (meteorological condition, level of cargo traffic, etc.) over a longer period of time to derive meaningful conclusions, however it does not seem that the high level of sulfur dioxide concentration from the pre-IMO regulation was reached after.\n\n\n##### Looking at other pollutants\n\nBesides SOx the new regulation also contributed to decrease atmospheric concentrations in nitric oxides (NOx) as well as particulate matter (PM).\n\n### References\n\n- [IMO 2020 - cleaner shipping for cleaner air, 20 December 2019](https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx)" } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/funder": [ { "@id": "http://w3id.org/ro-id/rohub/model#funder/b021cb50-9d2c-4f65-958f-785aa7bc445e" } ], "http://schema.org/funding": [ { "@id": "https://ror.org/10.13039/501100000780::101017501" } ], "http://schema.org/hasPart": [ { "@id": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa/folders/016d61d3-b7cb-4330-9fa1-ed59c97d8b24" }, { "@id": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa/folders/0af4cc1f-e3ec-4a08-8698-dbabcaa85c86" }, { "@id": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa/folders/39c8c0cf-db39-4fc4-82d7-952a72233958" }, { "@id": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa/folders/6f1862de-ef10-404a-92de-029c04c204be" }, { "@id": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa/resources/de7d67ed-dd70-41c1-b725-a8f1de4412af" }, { "@id": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa/resources/f5198e8a-882a-4755-ad2c-b41bf79eda37" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa" } ], "http://schema.org/keywords": [ { "@value": "Air pollution" }, { "@value": "sulphur" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/mainEntity": [ { "@value": "Data Cube Product" } ], "http://schema.org/name": [ { "@value": "Has the 2020 IMO fuel regulation had any noticeable impact on air pollution from shipping?" } ], "http://schema.org/publisher": [ { "@id": "https://ror.org/00vn06n10" }, { "@id": "https://ror.org/01xtthb56" } ], "http://w3id.org/ro-id/rohub/model#community": [ { "@id": "https://w3id.org/ro-id/communities/c019b3ba-6789-4d37-9e1a-66cf2c50662c" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], "http://www.opengis.net/ont/geosparql#hasGeometry": [ { "@id": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa/b7ea3b23-5650-42b3-bd1a-84f2fa8d7f5b" } ], "https://w3id.org/ro/terms/earth-science#template": [ { "@value": "https://w3id.org/ro/terms/earth-science#DataCentricResearchObjectTemplate" } ], "https://www.w3.org/ns/iana/link-relations/relation#cite-as": [ { "@value": "Iaquinta, Jean, Anne Fouilloux, and Raul Palma. \"Has the 2020 IMO fuel regulation had any noticeable impact on air pollution from shipping?.\" ROHub. Sep 11 ,2023. https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa." } ] }, { "@id": "mailto:rpalma@man.poznan.pl", "@type": [ "http://xmlns.com/foaf/0.1/Agent" ], "http://schema.org/affiliation": [ { "@value": "PSNC" } ], "http://schema.org/email": [ { "@value": "rpalma@man.poznan.pl" } ], "http://schema.org/name": [ { "@value": "Raul Palma" } ] }, { "@id": "https://w3id.org/ro-id/075e9430-5949-4a09-8622-d20916994eaa/folders/016d61d3-b7cb-4330-9fa1-ed59c97d8b24", "@type": [ "http://purl.org/wf4ever/wf4ever#Folder", "http://schema.org/Dataset" ], "http://schema.org/hasPart": [ { "@id": "https://atmosphere.copernicus.eu/air-quality" }, { "@id": "https://www.imo.org/en/MediaCentre/PressBriefings/pages/34-IMO-2020-sulphur-limit-.aspx" }, { "@id": "https://www.itf-oecd.org/sites/default/files/docs/potential-efuels-decarbonise-ships-aircraft-v2.pdf" }, { "@id": 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E-fuels like hydrogen, ammonia, e-methanol or e-kerosene can be produced from renewable\nenergy and feedstocks and are more economical to deploy in these two modes than direct electrification.\nThe analysis evaluates the challenges and opportunities related to e-fuel production technologies and\nfeedstock options to identify priorities for making e-fuels cheaper and maximising emissions cuts. The\nresearch also explores operational requirements for the two sectors to deploy e-fuels and how\ngovernments can assist in adopting low-carbon fuels" } ], "http://schema.org/encodingFormat": [ { "@value": "application/pdf" } ], "http://schema.org/keywords": [ { "@value": "e-fuels" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "The Potential of E-fuels to Decarbonise Ships and Aircraft" } ], "http://schema.org/sdDatePublished": [ { "@value": "2023-09-19 10:42:29.889446+00:00" } ] }, { "@id": "https://wwwcdn.imo.org/localresources/en/MediaCentre/PressBriefings/PublishingImages/2019%20images%20pb/5%20changes%20-%20Sulphur%202020%20-%20infographic%20web.jpg", "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro/terms/earth-science#Diagram" ], "http://schema.org/author": [ { "@id": "https://orcid.org/0000-0002-8763-1643" } ], 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Since there is a dearth in the literature regarding microplastic leachable compounds and overtourism-related pollutants, the project studied the Head Space-Solid Phase Micro Extraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC–MS) molecular fingerprint of volatile lagoon water pollutants, to gain insight into the extent of this phenomenon in August 2019. The chromatographic analyses enabled the identification of 40 analytes related to the presence of polymers in seawater, water traffic, and tourists habits. In Italy, on the 10th March 2020, the lockdown restrictions were enforced to control the spread of the SARS-CoV-2 infection; the ordinary urban water traffic around Venice came to a halt, and the ever-growing presence of tourists suddenly ceased. This situation provided a unique opportunity to analyze the environmental effects of restrictions on VOCs load in the Lagoon. 17 contaminants became not detectable after the lockdown period. 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Our results highlight the need to consider trade-offs between efforts to reduce far-field behavioural disturbance and near-field injury through ADD use." } ], "http://schema.org/license": [ { "@id": "https://data.norge.no/nlod/no/2.0" } ], "http://schema.org/name": [ { "@value": "Data from: Harbour porpoise responses to pile-driving diminish over time" } ], "http://schema.org/sdDatePublished": [ { "@value": "2023-03-18 15:48:46.831143+00:00" } ] }, { "@id": "https://orcid.org/0000-0002-1784-2920", "@type": [ "http://xmlns.com/foaf/0.1/Agent" ], "http://schema.org/affiliation": [ { "@value": "Simula Research Laboratory" } ], "http://schema.org/email": [ { "@value": "annef@simula.no" } ], "http://schema.org/name": [ { "@value": "Anne Fouilloux" } ], "https://w3id.org/dingo#orcid": [ { "@value": "0000-0002-1784-2920" } ] }, { "@id": "https://doi.org/10.5281/zenodo.3754481", "@type": [ "http://purl.org/wf4ever/wf4ever#Dataset", "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject" ], "http://schema.org/author": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/contentUrl": [ { "@value": "https://doi.org/10.5281/zenodo.3754481" } ], "http://schema.org/creator": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/dateCreated": [ { "@value": "2023-03-18 15:45:43.141299+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2023-03-18 15:46:52.776393+00:00" } ], "http://schema.org/description": [ { "@value": "The schema of the dataset is provided below:\n\n· t: the time at which the message was received (UTC)\n\n· shipid: the anonymized id of the ship\n\n· lon: the longitude of the current ship position\n\n· lat: the latitude of the current ship position\n\n· heading: (see: https://en.wikipedia.org/wiki/Course_(navigation))\n\n· course: the direction in which the ship moves (see: https://en.wikipedia.org/wiki/Course_(navigation))\n\n· speed: the speed of the ship (measured in knots)\n\n· shiptype: AIS reported ship-type\n\n· destination: AIS reported destination" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "Single Ground Based AIS Receiver Vessel Tracking Dataset" } ], "http://schema.org/sdDatePublished": [ { "@value": "2023-03-18 15:45:43.141299+00:00" } ] }, { "@id": "https://doi.org/10.5281/zenodo.5718284", "@type": [ "http://purl.org/wf4ever/wf4ever#Dataset", "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject" ], "http://schema.org/author": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/contentUrl": [ { "@value": "https://doi.org/10.5281/zenodo.5718284" } ], "http://schema.org/creator": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/dateCreated": [ { "@value": "2023-03-18 15:41:41.912053+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2023-03-18 15:43:25.836869+00:00" } ], "http://schema.org/description": [ { "@value": "Environmental and AIS data collected during the second phase of EUMR TNA experiments using the CMRE LOON testbed. Environmental data consists of temperature measured across the water column; sound velocity measured close to the surface and close to the sea bottom; meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain). The environmental dataset is complemented with Automatic Identification System (AIS) data for the ships transiting close to the LOON area (Gulf of La Spezia, Italy)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "Environmental and AIS data collected during the EUMarineRobots Trans-National Access activities experiments using the NATO STO-CMRE Littoral Ocean Observatory Network testbed (Release 2)" } ], "http://schema.org/sdDatePublished": [ { "@value": "2023-03-18 15:41:41.912053+00:00" } ] }, { "@id": "https://doi.org/10.5281/zenodo.6323416", "@type": [ "http://purl.org/wf4ever/wf4ever#Dataset", "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject" ], "http://schema.org/author": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/contentUrl": [ { "@value": "https://doi.org/10.5281/zenodo.6323416" } ], "http://schema.org/creator": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/dateCreated": [ { "@value": "2023-03-18 15:53:28.368823+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2023-03-18 15:54:45.934342+00:00" } ], "http://schema.org/description": [ { "@value": "The advent of Big Data and streaming technologies has resulted in a swarm of voluminous, heterogeneous information, especially in the domains of Internet of Things (IoT) and transportation. Focusing on the maritime field, we present a dataset that contains vessel position information transmitted by vessels of different types and collected via the Automatic Identification System (AIS). The AIS dataset comes along with spatially and temporally correlated data about the vessels and the area of interest, including weather information. It covers a time span of over 2.5 years, from May 9th, 2017 to December 26th, 2019 and provides anonymised vessel positions within the wider area of the port of Piraeus (Greece), one of the busiest ports in Europe and worldwide. The dataset consists of over 244 million AIS records, an average of more than 10,000 records per hour, which makes it an ideal input for large-scale mobility data processing and analytics purposes." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "The Piraeus AIS Dataset for Large-scale Maritime Data Analytics" } ], "http://schema.org/sdDatePublished": [ { "@value": "2023-03-18 15:53:28.368823+00:00" } ] }, { "@id": "https://doi.org/10.5281/zenodo.6402160", "@type": [ "http://purl.org/wf4ever/wf4ever#Dataset", "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject" ], "http://schema.org/author": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/contentUrl": [ { "@value": "https://doi.org/10.5281/zenodo.6402160" } ], "http://schema.org/creator": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/dateCreated": [ { "@value": "2023-03-18 15:50:58.144079+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2023-03-18 15:52:08.005277+00:00" } ], "http://schema.org/description": [ { "@value": "With an ever-increasing number of vessels at sea, the modelling, analysis and visualisation of maritime traffic are of paramount importance to support the monitoring tasks of maritime stakeholders. Sensors have been developed in this respect to track vessels and capture the maritime traffic at the global scale. The Automatic Identification System (AIS) is transmitting maritime positional and nominative information at highest frequency rate, making it a valuable source for maritime traffic modelling. From an original AIS dataset covering the area of Brest, France, we extracted a set of 17 maritime routes, connecting ports in this area. Two different representations for the routes are provided: (1) clusters of AIS contacts, and (2) route prototypes, representing the nominal trajectory of the vessels following the route. Additionally, a set of tracklets (built by five consecutive AIS contacts from the same vessel trajectory) has been extracted from the set of routes and the original dataset, and labelled either with the route name to which they belong or as off-route tracklets. This dataset provides thus some ground truth on the routes followed by vessels and is aimed at testing and validating vessel-to-route or track-to-route association algorithms." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "Maritime routes and vessel tracklet dataset for vessel-to-route association" } ], "http://schema.org/sdDatePublished": [ { "@value": "2023-03-18 15:50:58.144079+00:00" } ] }, { "@id": "https://en.wikipedia.org/wiki/Automatic_identification_system", "@type": [ "http://purl.org/wf4ever/wf4ever#Document", "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject" ], "http://schema.org/author": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], "http://schema.org/contentUrl": [ { "@value": "https://en.wikipedia.org/wiki/Automatic_identification_system" } ], "http://schema.org/creator": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ], 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Moreover, some differences were also observed in shapes and colours comparing the two sites. These differences are related to the different types of macro-litter that characterised the two areas. 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}, { "@id": "https://www.sciopen.com/article/10.1007/s11390-023-2907-5", "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/Article", "http://schema.org/MediaObject" ], "http://schema.org/author": [ { "@id": "https://orcid.org/0000-0002-8763-1643" } ], "http://schema.org/contentUrl": [ { "@value": "https://www.sciopen.com/article/10.1007/s11390-023-2907-5" } ], "http://schema.org/creator": [ { "@id": "https://orcid.org/0000-0002-8763-1643" } ], "http://schema.org/dateCreated": [ { "@value": "2024-01-16 16:05:31.945926+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2024-01-16 16:05:33.287119+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract The Slingshot interconnect designed by HPE/Cray is becoming more relevant in high-performance computing with its deployment on the upcoming exascale systems. In particular, it is the interconnect empowering the first exascale and highest-ranked supercomputer in the world, Frontier. It offers various features such as adaptive routing, congestion control, and isolated workloads. The deployment of newer interconnects sparks interest related to performance, scalability, and any potential bottlenecks as they are critical elements contributing to the scalability across nodes on these systems. In this paper, we delve into the challenges the Slingshot interconnect poses with current state-of-the-art MPI (message passing interface) libraries. In particular, we look at the scalability performance when using Slingshot across nodes.\nWe present a comprehensive evaluation using various MPI and communication libraries including Cray MPICH, OpenMPI + UCX, RCCL, and MVAPICH2 on CPUs and GPUs on the Spock system, an early access cluster deployed with\nSlingshot-10, AMD MI100 GPUs and AMD Epyc Rome CPUs to emulate the Frontier system. 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