Change impact analysis on the life cycle carbon emissions of energy systems – The nuclear example

Nian, Victor

doi:10.1016/j.apenergy.2015.01.003

Cited by 17 publications

(5 citation statements)

References 17 publications

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“…The findings indicate a reduction in carbon emissions from solar power generation with an increasing solar multiplier [8]. Victor Nian optimized carbon emissions accounting throughout the lifecycle of nuclear power generation using the "Kaya Identity" and "Process Chain Analysis" methods [9,10]. Mostafaei et al analyzed the carbon emissions in three stages of the lifecycle of a Concrete Gravity Dam by employing LCA and pointed out a potential 32% reduction in greenhouse gas (GHG) emissions by assuming a 20% concrete recycling rate [11].…”

Section: Introductionmentioning

confidence: 99%

Research on the Accounting and Prediction of Carbon Emission from Wave Energy Convertor Based on the Whole Lifecycle

Li,

Wang,

Wang

et al. 2024

Energies

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Wave energy, as a significant renewable and clean energy source with vast global reserves, exhibits no greenhouse gas or other pollution during real-sea operational conditions. However, throughout the entire lifecycle, wave energy convertors can produce additional CO2 emissions due to the use of raw materials and emissions during transportation. Based on laboratory test data from a wave energy convertor model, this study ensures consistency between the model and the actual sea-deployed wave energy convertors in terms of performance, materials, and geometric shapes using similarity criteria. Carbon emission factors from China, the European Union, Brazil, and Japan are selected to predict the carbon emissions of wave energy convertors in real-sea conditions. The research indicates: (1) The predicted carbon emission coefficient for unit electricity generation (EFco2) of wave energy is 0.008–0.057 kg CO2/kWh; when the traditional steel production mode is adopted, the EFco2 in this paper is 0.014–0.059 kg CO2/kWh, similar to existing research conclusions for the emission factor of CO2 for wave energy convertor (0.012–0.050 kg CO2/kWh). The predicted data on carbon emissions in the lifecycle of wave energy convertors aligns closely with actual operational data. (2) The main source of carbon emissions in the life cycle of a wave energy converter, excluding the recycling of manufacturing metal materials, is the manufacturing stage, which accounts for 90% of the total carbon emissions. When the recycling of manufacturing metal materials is considered, the carbon emissions in the manufacturing stage are reduced, and the carbon emissions in the transport stage are increased, from about 7% to about 20%. (3) Under the most ideal conditions, the carbon payback period for a wave energy convertor ranges from 0.28 to 2.06 years, and the carbon reduction during the design lifespan (20 years) varies from 238.33 t CO2 (minimum) to 261.80 t CO2 (maximum).

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Section: Introductionmentioning

confidence: 99%

Research on the Accounting and Prediction of Carbon Emission from Wave Energy Convertor Based on the Whole Lifecycle

Li,

Wang,

Wang

et al. 2024

Energies

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“…Including thermal power, 7,8 solar photovoltaic (PV) power, 9,10 hydropower, 11,12 wind power, [13][14][15] biomass power, 16 and nuclear power. 17,18 The second type of study aims to provide a basis for energy conservation and some policy suggestions on the development of electricity system based on the national data. Ding et al 19 assessed several major types of power and calculated the average power supply GHG intensities for each province in China in 2013 through LCA.…”

Section: Introductionmentioning

confidence: 99%

“…At present, most studies focus on the evaluation and calculation of single type or multiple types of power, and highlight the environmental advantages of specific power types. Including thermal power, 7,8 solar photovoltaic (PV) power, 9,10 hydropower, 11,12 wind power, 13–15 biomass power, 16 and nuclear power 17,18 . The second type of study aims to provide a basis for energy conservation and some policy suggestions on the development of electricity system based on the national data.…”

Section: Introductionmentioning

confidence: 99%

Life cycle analysis of greenhouse gas emissions of China's power generation on spatial and temporal scale

Zhu

Wang

2022

Energy Science & Engineering

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In this study, the “cradle‐to‐gate” greenhouse gas (GHG) intensities of six types of power generation in China are analyzed using a life cycle assessment approach, including wind power, solar photovoltaic power, nuclear power, hydropower, biomass power, and thermal power. According to the mix of regional power grids in China and GHG intensities of various types of power generation, the GHG intensities of hybrid power on regional power grid scale are calculated. The results show that they are closely corresponding to the grid mix of each region. Besides, the value of northeast China is the highest and the largest variation between regions is about twice. Furthermore, the efforts made by the Chinese government promoting energy shift are expected to accelerate the decrease of the electricity system GHG intensity to 376.9 gCO2‐eq/kW h by 2035, about 51.0% lower than that in 2017. And the total GHG emissions are predicted to reach 4.5 × 109 tCO2‐eq in 2035, while in “below 2°C” scenario this value will decrease to 3.6 × 109 tCO2‐eq. This study compiles the life cycle inventory of China's electricity generation on spatial and temporal scale, and can provide suggestions on the development of regional and national electricity systems.

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“…Electricity generation by using nuclear power reactors produces low greenhouse gases (GHG) emission in the whole life cycle, which substantiates nuclear energy as a clean electricity source (Nian, 2015;Hong, 2015;Alonso and del Valle, 2013). On the other hand, use of nuclear power requires regulatory structures that will provide very strict mechanisms of safety to reduce any possible risk due to ionizing radiation (Strupczewski, 2013).…”

Section: Introductionmentioning

confidence: 99%

Estimation of occupational compensation based on a linear-quadratic methodology for the nuclear industry

et al. 2018

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Change impact analysis on the life cycle carbon emissions of energy systems – The nuclear example

Cited by 17 publications

References 17 publications

Research on the Accounting and Prediction of Carbon Emission from Wave Energy Convertor Based on the Whole Lifecycle

Research on the Accounting and Prediction of Carbon Emission from Wave Energy Convertor Based on the Whole Lifecycle

Life cycle analysis of greenhouse gas emissions of China's power generation on spatial and temporal scale

Estimation of occupational compensation based on a linear-quadratic methodology for the nuclear industry

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