A lifecycle carbon emission evaluation model for urban underground highway tunnel facilities

Abstract

Anthropogenic greenhouse gas emissions stand as the primary catalyst of climate perturbations. A precise evaluation of these emissions holds paramount importance in realizing energy conservation and emission reduction goals. Urban underground highway tunnel facilities emerge as a promising recourse for ameliorating traffic congestion and advancing energy conservation and emission mitigation endeavours. Nonetheless, the methodologies for quantifying its carbon emissions remain scant. This study ventures into the realm of carbon footprint appraisal within the lifecycle paradigm of underground highway tunnel facilities. Tailored to the characteristics, functionalities, and design intricacies of urban underground highway tunnel facilities, the physical boundaries and scopes are meticulously calibrated. Subsequently, a carbon emission computational model adept at encapsulating the emission characteristics throughout the entire lifecycle is formulated. Meanwhile, a detailed database is established for emission factors of various carbon emission activities. Leveraging insights garnered from a specific project case, the overarching carbon emission profiles of the urban underground highway tunnel facility, both in aggregate and individual stages, are elucidated. Concomitantly, bespoke recommendations and strategies aimed at energy preservation and emission abatement are proffered, attuned to the idiosyncratic attributes of carbon emissions across distinct stages.

Keywords

Urban underground highway tunnel / Carbon emission / Entire lifecycle / Calculation model / Energy saving and emission reduction

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Guosheng Wang: Methodology, Conceptualization, Writing - review & editing. Dechun Lu: Funding acquisition, Writing - review & editing, Conceptualization. Gangao Ji: Writing - original draft, Methodology, Conceptualization. Xuhua Liang: Writing - review & editing. Qingtao Lin: Funding acquisition, Validation. Jirui Lv: Data curation. Xiuli Du: Resources, Project administration, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

Support for this study is provided by the National Natural Science Foundation of China (Grant Nos. 52025084, 52378471, and 52208396), and the National Key R&D Program of China (Grant No. 2022YFC3800901).

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