A Holistic Approach for Estimating Carbon Emissions of Road and Rail Transport Systems

Dimoula, Vasiliki; Kehagia, Fotini; Anastasios, Tsakalidis

doi:10.4209/aaqr.2015.05.0313

Cited by 35 publications

(20 citation statements)

References 8 publications

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“…Howitt and Carruthers (2011) calculated the carbon dioxide (CO 2 ) emissions from international air freights in New Zealand. Dimoula and Kehagia (2016) estimated GHG emissions during construction and operation of main road and rail axis infrastructure in Greece. Under the recent rapid development of HSRs, the CF of HSRs has attracted increased attention.…”

Section: Introductionmentioning

confidence: 99%

A Carbon Footprint of High‐Speed Railways in China: A Case Study of the Beijing‐Shanghai Line

Lin

Huang

et al. 2018

J of Industrial Ecology

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A carbon footprint (CF) assessment of Chinese high-speed railways (HSRs) can help guide further development of the world's longest HSR network. In this research, a hybrid economic input-output and life cycle assessment (EIO-LCA) method was applied to estimate the CF of the Beijing-Shanghai HSR line. Specific CFs were analyzed of different subsystems of the line, different stages of production, and three calculation scopes. Results showed that the annual CF of the Beijing-Shanghai HSR is increasing, whereas the per-passenger CF constantly declined between 2011 and 2014. Scope 1 emissions account for an average of 4% of the total annual CF, Scope 2 contribute 71%, and Scope 3 comprise 25%. Among the different stages, operation contributes the largest (71%), followed by construction (20%) and maintenance (9%). In the construction stage, the bridges have the largest CF, followed by trains, and then rails. A trade-off exists between the increase in carbon emissions due to construction of bridges and the reduction in operation emissions affected by leveling changes in terrain. The Beijing-Shanghai HSR line has a relatively higher per-passenger CF than eight other HSR lines, which is largely due to China's coal-based carbon-intensive energy mix of electricity generation, high proportion of bridges, higher operating speed, and heavier train body. In the future, cleaner electricity supply options, more efficient raw material production, and improvement of trains are keys to reducing the CF of Chinese HSRs. Keywords:carbon footprint China high-speed railway (HSR) hybrid environmental input-output life cycle assessment (EIO-LCA) industrial ecology transportation Supporting information is linked to this article on the JIE website

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Section: Introductionmentioning

confidence: 99%

A Carbon Footprint of High‐Speed Railways in China: A Case Study of the Beijing‐Shanghai Line

Lin

Huang

et al. 2018

J of Industrial Ecology

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“…For example, Lin et al (2015) used the Organization for Economic Cooperation and Development (OECD) and Tapio methods to analyze the relationship between CO 2 emissions and the Gross Domestic Product (GDP) of South Africa for the period of 1990 to 2012. Dimoula et al (2016) used the conversion factor of 3.06 kg CO 2 per diesel liter in a freight road transport system. The U.S. Environmental Protection Agency (EPA) has developed a series of fact sheets to facilitate consistency of assumptions and practices in the calculation of emissions of greenhouse gases from EPA, 2005).…”

Section: Resultsmentioning

confidence: 99%

Emissions Study and Estimation of Carbon Dioxide Production from Jatropha Curcas Oil Biodiesel

Lin

Chang

2016

Aerosol Air Qual. Res.

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The goal of this study was to analyse the combustion characteristics and emissions of Jatropha curcas biodiesel (JCB) when run in a diesel engine. Jatropha curcas oil was used to produce Jatropha curcas biodiesel (JCB) through a transesterification process. The major fuel properties of JCB, including the acid value, kinematic viscosity, flash point, gross heating value, and iodine value, were determined and compared with that of soybean biodiesel (SBM), sunflower seed biodiesel (SFM), mackerel fish oil biodiesel (MB), and premium diesel (D). JCB had a higher density, acid value, kinematic viscosity, iodine value and flash point, but a lower gross heating value, than D. JCB was then used to analyze combustion characteristics, CO, CO 2, NO, NO x , SO 2 , and particulate matter (PM), under varied engine speeds and varied engine loads. The experimental results show CO 2 concentration increased with increasing engine loads for all fuels. Engine trials on D exhibited better combustion efficiency at lower engine loads (0 kW-4 kW) but engine trials on JCB exhibited better combustion efficiency for higher engine loads (5 kW-8 kW). JCB emitted more NO and NO x on a loaded engine. Engine trials on JCB emitted higher PM concentration when the engine was not loaded, while engine trials on MB produced higher PM concentration when the engine was loaded. The estimated CO 2 emissions for JCB, MB, and D are 9221.3, 9617.2, and 10185.0 g (gal fuel) -1 , respectively.

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“…Across the case studies, the rail infrastructure dimensions were obtained from Google Earth, Google Maps, Construction documents, and Preliminary bid documents available to the researchers (Infraestructuras 2015, Dimoula et al 2016, Shinde et al 2018. Embodied GHG emissions from the different case studies are converted to per kilometre for comparison below using the length of infrastructure reported in the paper or collected from publicly available data.…”

Section: Comparison Of Published Case Studiesmentioning

confidence: 99%

“…In cases where the functional unit was not explicitly stated, the implied unit of analysis is reported (e.g. one subway line) (Dimoula et al 2016, Saxe et al 2017.…”

Section: Functional Unitmentioning

confidence: 99%

Embodied emissions in rail infrastructure: a critical literature review

Olugbenga

Kalyviotis

Saxe

2019

Environ. Res. Lett.

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This paper investigates the state of knowledge in quantifying the embodied greenhouse gas (GHG) emissions in rail infrastructure and develops a sketch model for estimating the GHG impact of rail infrastructure based on the literature. A literature review identified 22 publications, containing 57 case studies, at least touching on the embodied GHG for different types of rail infrastructure. The cases studies include high speed rail, intercity rail, light rail, commuter rail, heavy rail, freight, and metro rail. The paper examines the GHG impact per kilometre of rail infrastructure reported across the case studies and compares the boundaries, functional units, methods, and data used. Most studies employed process-based LCA for an attributional analysis. The embodied emissions associated with the case studies range from 0.5 to 12 700 tCO 2 km −1 ; much of the variation is dependent on the proportion of the rail line at-grade, elevated, or in a tunnel. However, large ranges in GHG per kilometre remain after controlling for elevated and tunneled distance. Comparing the embodied emissions across the rail types was challenging, due to the large variations in system boundaries, study goals, and inventory methods adopted in the publications. This review highlights the need for standardization across the reporting of embodied GHG for rail infrastructure to better facilitate hot spot detection, engineering design and GHG policy decision making. The statistical model finds that overall ∼941(±168) tCO 2 e are embodied per kilometre of rail at-grade, and tunneling has 27 (±5) times more embodied GHG per kilometre than at-grade construction. The statistical model is based on the findings of published literature and does not explicitly consider function, geometry, specifications, emphasis on whole lifecycle, legislative constraints, socio-economic factors, or the physical and environmental conditions of the construction site.

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A Holistic Approach for Estimating Carbon Emissions of Road and Rail Transport Systems

Cited by 35 publications

References 8 publications

A Carbon Footprint of High‐Speed Railways in China: A Case Study of the Beijing‐Shanghai Line

A Carbon Footprint of High‐Speed Railways in China: A Case Study of the Beijing‐Shanghai Line

Emissions Study and Estimation of Carbon Dioxide Production from Jatropha Curcas Oil Biodiesel

Embodied emissions in rail infrastructure: a critical literature review

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