Life cycle assessment in road infrastructure planning using spatial geological data

Karlsson, Caroline; Miliutenko, Sofiia; Björklund, Anna; Mörtberg, Ulla; Olofsson, Bo; Toller, Susanna

doi:10.1007/s11367-016-1241-3

Cited by 18 publications

(11 citation statements)

References 13 publications

(17 reference statements)

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“…Even though the importance of construction machinery has been highlighted in the LCA community (Barandica et al 2013;Garbarino et al 2014;Barati and Shen 2016;Karlsson et al 2017), very few studies were found that focus on the issue of the environmental impacts of construction machinery. Instead, the LCA of machinery has been integrated into bigger systems, like construction projects, in an effort to provide an overarching perspective on the potential impacts in the studied systems (Park et al 2003;Cass and Mukherjee 2011;Barandica et al 2013;Melanta et al 2013;O'Born et al 2014).…”

Section: Comparison Of Resultsmentioning

confidence: 99%

Regionalized environmental impacts of construction machinery

Ebrahimi

Wallbaum

Jakobsen

et al. 2020

Int J Life Cycle Assess

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Purpose This study aims to establish a regionalized environmental impact assessment of construction machinery equipped with diesel engines certified by the European emission standard Stage V, and operated in cold climatic zones in Europe. Method The study quantifies potential environmental impacts associated with construction machinery over the entire lifecycle, from extraction of materials to the end-of-life. For the operation phase, a meso-level emission accounting method is applied to quantify tailpipe emissions for certain subcategories of construction machinery. This is achieved by determining the operational efficiency of each machine in terms of effective hours. The quantified emission data are then adjusted based on engine deterioration models to estimate the rate of increase in emissions throughout the lifetime of each machine. Finally, the CML impact assessment method is applied to inventory data to quantify potential environmental impacts. Results The study shows that tailpipe emissions, which largely depend on an engine's fuel consumption, had the largest contribution to environmental impacts in most impact categories. At the same time, there was a positive correlation between the operation weight and the impacts of the machinery. Also, machinery with similar operation weight had relatively similar impact patterns due to similar driving factors and dependencies. In addition, network, sensitivity, and uncertainty analyses were performed to quantify the source of impacts and validate the robustness of the study. Results of the sensitivity analysis showed that the responsiveness of the studied systems is very sensitive to changes in the amount of fuel consumption. In addition, the uncertainty results showed that the domain of uncertainty increased as the operation weight subcategory of machinery increased. Conclusion This study extends previous work on the life cycle assessment (LCA) of construction machinery, and the methodology developed provides a basis for future extension and improvement in this field. The use of effective hours as the unit of operational efficiency helps to resolve uncertainties linked to lifetime and annual operation hours. Also, the obtained results can be of use for decision support and for assessing the impacts of transition from fossil fuels to alternative fuel types.

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Section: Comparison Of Resultsmentioning

confidence: 99%

Regionalized environmental impacts of construction machinery

Ebrahimi

Wallbaum

Jakobsen

et al. 2020

Int J Life Cycle Assess

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“…Naturally, the variation in such default data is large (because, by necessity is has been collected from different other sources). For example, the assumed default diesel use for soil excavation is several times higher in Klimatkalkyl 3.0 than in the LICCER model and the assumed default quantity of explosives for rock blasting is twice as high (Karlsson et al, 2017). In terms of traffic, default data (for example fuel consumption) may vary between different roads depending on local conditions such as road incline and speed limit.…”

Section: Availability Of Project Specific and Default Input Datamentioning

confidence: 99%

“…The greatest opportunity to influence life cycle impacts of transport occurs in early planning stages (Hammervold, 2014;Karlsson et al, 2017;O'Born et al, 2016), such as choice of road corridor and construction type. The choice of road corridor influences route length and construction type and has thereby a large influence on environmental impacts from future traffic on the road and on impacts from road construction, operation, and maintenance.…”

Section: Introductionmentioning

confidence: 99%

Life cycle assessment as decision-support in choice of road corridor: case study and stakeholder perspectives

Liljenström

Miliutenko

O’Born

et al. 2020

International Journal of Sustainable Transportation

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Use of life cycle assessment (LCA) in choice of road corridor could reduce environmental impacts of traffic and infrastructure. This paper explores how the LCA model LICCER, designed to compare life cycle climate impact and energy use of alternative road corridors, fulfills practitioners' requirements concerning data availability and usefulness for decision-making. Results are based on a case study where the model was applied to a Swedish road reconstruction project and a workshop with potential users of the model. In the case study, the shorter construction alternatives had the lowest traffic related impacts and the highest infrastructure related impacts. Earthworks, soil stabilization, and pavement contributed most to infrastructure related impacts. For the stakeholders, the LICCER model was considered useful because it includes both traffic and infrastructure, includes default data that the user can replace by project specific data, identifies possible improvements, and presents results relative to a reference alternative. However, the model could be improved by including further nation specific default data, different traffic scenarios depending on the road corridor, more detailed traffic scenarios, and an uncertainty assessment of the model output. These findings may be useful in the development and improvement of LCA models and when evaluating the suitability of existing models for use in early planning.

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“…A conclusion of this is that if the purpose is to make road transports more energy efficient it can be better to accept higher energy use for the infrastructure if it leads to lower fuel use of vehicles since it can result in lower total energy use (Carlson, 2011). A proposed GIS-based approach shows promising results for usage in LCA at an early stage of road infrastructure planning (Karlsson et al, 2017).…”

Section: Roads and Pavementsmentioning

confidence: 99%

Life-cycle management for sustainable infrastructure planning and development in Africa

Assefa¹,

Ramjaewon²

2019

Transformational Infrastructure for Development of a Wellbeing Economy in Africa

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Paved road density (km per 100 km 2 of land area) 2 25 3 122 Railway line (km) 46 380 197 610 89 002 85 986 Power Electricity production (per capita kWh) 572 1 930 2 116 3 355 Electricity access (percent of total population) 46 88 97 100 Water and sanitation Improved water (percent of total population) 69 90 94 99 Improved sanitation (percent of total population) 39 61 82 93 ICT Fixed broadband (subscriptions per 100 population) 1 6 9 15 Mobile cellular (subscriptions per 100 population) 73 85 115 119 Africa has 15 percent of the world's population but only 3.2 percent of world electricity-generating capacity. More than half of the world's population without electricity are Africans. According to research from the World Bank Group, 48 countries of sub-Saharan Africa (with a combined population of 800 million) generate roughly the same amount of power as Spain (with a population of 45 million). Per capita, yearly consumption of energy in sub-Saharan Africa (excluding South Africa) is 180 kWh, against 13 000 kWh in the United States and 6 500 kWh in Europe (Dethier, 2015). Energy intensity and CO 2 intensity in the continent are also very high, thus giving evidence of unclean and inefficient energy supply chain (Saghir, 2017). It is estimated that only one-third of Africans living in rural areas are within two kilometres of an all-season road, compared with twothirds of the population in other developing regions. The African Development Bank, based on a set of targets for 2025, estimated Africa's needs of the total investment for infrastructure at $130 billion to $170 billion per year between 2018 and 2025 (Af DB, 2018) with a financing gap of $68 billion to $108 billion. Around two-fifths of the investment need is for water and sanitation that faces an ambitious target of 100 percent access in both urban and rural Africa.

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Life cycle assessment in road infrastructure planning using spatial geological data

Cited by 18 publications

References 13 publications

Regionalized environmental impacts of construction machinery

Regionalized environmental impacts of construction machinery

Life cycle assessment as decision-support in choice of road corridor: case study and stakeholder perspectives

Life-cycle management for sustainable infrastructure planning and development in Africa

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