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Consignment-level allocations of carbon emissions in road freight transport
Malmö högskola, Faculty of Technology and Society (TS). Malmö högskola, Internet of Things and People (IOTAP).ORCID iD: 0000-0002-6019-1182
Malmö högskola, Faculty of Technology and Society (TS). Malmö högskola, Internet of Things and People (IOTAP).ORCID iD: 0000-0002-9471-8405
2016 (English)In: Transportation Research Part D: Transport and Environment, ISSN 1361-9209, E-ISSN 1879-2340, Vol. 48, p. 298-315Article in journal (Refereed) Published
Abstract [en]

This paper presents and evaluates a new method for how emissions from freight transport routes with single or several points of loading and unloading, can be allocated to individual consignments. The method, called Dedicated Distance Proportional Allocation (DDPA), has been developed based on a literature review, discussions with logistics providers, and analysis. DDPA is designed to have low data processing requirements and be easy to explain to actors involved. Furthermore, it supports several levels of information availability, and accounts for any set of vehicle-limiting factors, as well as prepositioning/repositioning. DDPA has been evaluated in simulations with different levels of information availability, together with three existent allocation methods: the Equal profit method (EPM), the CEN EN16258:2011 standard and the Greenhouse gas (GHG) protocol. The simulations show that the GHG protocol under-allocates the total amount of emissions, on average. EPM and DDPA achieve equal relative savings, whereas for CEN EN16258:2011 and the GHG protocol, relative savings vary, on average. When DDPA is used with low level of information availability, an error is introduced which can be reduced by applying compensation factors. Since DDPA accepts low information availability, the Intelligent Products concept can be applied for computing and storing emissions allocations, at the time of unloading. The results from this study can be used for further development and implementation of consignment allocation methods. Furthermore, by combining DDPA with other environmental load approaches for other parts of a product’s life cycle, a complete life cycle assessment of the product’s environmental impact can be obtained.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 48, p. 298-315
Keywords [en]
Emission allocation, Transport, Intelligent Products, Simulation
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-2636DOI: 10.1016/j.trd.2016.08.001ISI: 000384853700022Scopus ID: 2-s2.0-84983750323Local ID: 21626OAI: oai:DiVA.org:mau-2636DiVA, id: diva2:1399399
Available from: 2020-02-27 Created: 2020-02-27 Last updated: 2024-02-05Bibliographically approved
In thesis
1. Toward intelligent goods: characteristics, architectures and applications
Open this publication in new window or tab >>Toward intelligent goods: characteristics, architectures and applications
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In the context of globalization, the requirements on transport logistics continuously rise. Often goods travel through many different countries, using several transport modes and involving a number of different actors. Implementing some level of intelligence on the goods, which provide them with the capabilities to assist in the logistical activities, is one of the instruments that can be used to improve control and efficiency in transports and goods-handling. The concept of intelligent goods both opens up for new types of services and may be used to improve currently available services. The research is mainly focused on the characteristics, possible architectures, and applications of intelligent goods systems. In this context, an intelligent goods system refers to a number of interacting components, e.g. on-board units, servers, and RFID tags, which together provide intelligent goods services. Intelligent goods refer to goods with a higher degree of intelligence than just providing the ID of the goods, and generally the concept involve information processing and/or storage on or close to the goods, acting on behalf of the goods throughout the whole transport. The purpose of the studies is to investigate how intelligent goods can be used to improve goods transports in terms of more efficient goods-handling as well as better control of the goods and the transportation process, but also in terms of more efficient information sharing, e.g. between different actors. This may in turn provide reduced costs, environmental impact and usage of infrastructure. The research is concentrated on the communication and processing of information before, during and after transport. Most of the research results are applicable to ii goods transport by any mode, whereas some of the research has an emphasis on road transport. A framework is presented which can be used to describe intelligent goods systems, including the capabilities of the goods, necessary information entities related to the goods, as well as a number of primitive services that can be used as building blocks when creating more advanced intelligent goods services. Furthermore, a new approach to service description is proposed, which can be used to, amongst others, define an intelligent goods service and to perform architecture analyses. By identifying architectures corresponding to different service solutions, intelligent goods can be compared with other types of solutions, for instance more centralized approaches. In particular, different situations and services put different requirements on a system and the benefits of using intelligent goods vary. In order to investigate how intelligent goods may be applied in practice, two services have been examined in more detail: a dynamic shelf- life prediction service, and a consignment-level emission allocation service. These studies involve field tests, interviews and simulations. Finally, an investigation of how intelligent goods systems can be modelled as multi-agent systems is also included.

Place, publisher, year, edition, pages
Malmö Högskola, Teknik och samhälle, 2014
Series
Studies in Computer Science ; 1
Keywords
Intelligent goods, Transportation, Decentralized freight intelligence
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-7779 (URN)17810 (Local ID)9789171046079 (ISBN)9789171046086 (ISBN)17810 (Archive number)17810 (OAI)
Public defence
2014-11-21, Hörsalen, Ubåtshallen, Östra Varvsgatan 11A, Malmö, 13:00 (English)
Opponent
Note

Note: The papers are not included in the fulltext online.

Paper IV and V in dissertation as manuscripts.

Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2024-03-13Bibliographically approved

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Jevinger, ÅsePersson, Jan A.

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