Carbon footprinting of railway infrastructure: a standardized, consistent data collection method
Greenhouse gas (GHG) emissions from the transport industry, comprised almost entirely of CO 2 , account for around 23% of global emissions. Reducing these emissions is crucial, if countries are to meet their carbon reduction targets. Given that net zero carbon emissions are beginning to be enacted i...
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Veröffentlicht in: | Carbon management 2024-12, Vol.15 (1) |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Greenhouse gas (GHG) emissions from the transport industry, comprised almost entirely of CO
2
, account for around 23% of global emissions. Reducing these emissions is crucial, if countries are to meet their carbon reduction targets. Given that net zero carbon emissions are beginning to be enacted into various countries' laws, transport infrastructure owners now have time bound targets to meet. The accurate measurement of carbon currently expended by transport infrastructure is the first, and most critical, step of infrastructure owners' journey towards carbon reduction, as this Business as Usual carbon expenditure will form the basis for both carbon reduction measures and expansion of carbon measurement from limited embodied and construction scopes though to whole life cycle carbon assessment. This article provides an overview of a transferable method for calculating the carbon footprint of railway infrastructure assets, based on a novel carbon calculation data form. Use of this form will ensure a standardized and consistent approach in data collection methods, enabling the creation of carbon footprints for small scale case studies of individual railway earthworks (around 100 m linear length) with a specific focus on the construction life cycle stages. These stages form the basis for future expansions to the whole life cycle and therefore accuracy in carbon footprinting is vital. These figures can also be used for aggregation across multiple interventions, and again accurate data are required to ensure inaccuracies are not amplified. |
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ISSN: | 1758-3004 1758-3012 |
DOI: | 10.1080/17583004.2024.2368839 |