Marginal Generation Technology in the Chinese Power Market towards 2030 Based on Consequential Life Cycle Assessment

Zhao, Guangling; Guerrero, Josep M.; Pei, Yingying

doi:10.3390/en9100788

Cited by 10 publications

(7 citation statements)

References 28 publications

(27 reference statements)

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“…The review indicates that the coupling of dynamic model and LCA is applied for one sector. This coincides with Beaussier et al's study, which clarified that ABM-LCA was frequently used for one (or several) product(s) of one sector [43], with one product in [74,75,78,79] and four products in [76,77].…”

Section: Dynamic Modellingsupporting

confidence: 88%

A Conceptual Review on Using Consequential Life Cycle Assessment Methodology for the Energy Sector

et al. 2020

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Energy is engaged in the supply chain of many economic sectors; therefore, the environmental impacts of the energy sector are indirectly linked to those of other sectors. Consequential life cycle assessment (CLCA) is an appropriate methodology to examine the direct and indirect environmental impacts of a product due to technological, economic or social changes. To date, different methodological approaches are proposed, combining economic and environmental models. This paper reviews the basic concept of CLCA and the coupling of economic and environmental models for performing CLCA in the energy sector during the period 2006–2020, with the aim to provide a description of the different tools, highlighting their strengths and limitations. From the review, it emerges that economic modelling tools are frequently used in combination with environmental data for CLCA in the energy sector, including equilibrium, input-output, and dynamic models. Out of these, the equilibrium model is the most widely used, showing some strengths in availability of data and energy system modelling tools. The input-output model allows for describing both direct and indirect effects due to changes in the energy sector, by using publicly available data. The dynamic model is less frequently applied due to its limitation in availability of data and modelling tools, but has recently attracted more attention due to the ability in modelling quantitative and qualitative indicators of sustainability.

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Section: Dynamic Modellingsupporting

confidence: 88%

A Conceptual Review on Using Consequential Life Cycle Assessment Methodology for the Energy Sector

et al. 2020

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“…According to the characteristics of control engineering fundamental, such as abstract content , complex calculation, huge drawing quantity and complicated system principle block diagram and so on [5]. It is difficult for students to understand by using the traditional teaching method.…”

Section: Exploration On Teaching Practicementioning

confidence: 99%

Teaching Practice for Control Engineering Fundamental Based on Solving Complicated Mechanical Engineering Problems

Xu¹,

Cai²,

Cui³

2017

Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)

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Abstract. In order to meet the requirements of engineering education accreditation, aiming at the important basic course of Control Engineering Fundamental, a teaching model is put forward, which combine with the case teaching, multimedia, MATLAB professional software. It enables students to have a deep understanding of theoretical knowledge in this teaching practice model, and their ability of using knowledge to analyze and solve complicate problems in mechanical engineering field is improved. So it proves the feasibility of the teaching mode.

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“…More than 80% of energy consumption is related to coal in some provinces such as Inner Mongolia, Ningxia, Guizhou, and Shaanxi, all of which are located in the western region [2]. However, the developed provinces have more electrical demand and are shifting to use renewable energy instead of coal [78].…”

Section: So 2 Emission Inequalitymentioning

confidence: 99%

Air Pollution Inequality and Its Sources in SO2 and NOX Emissions among Chinese Provinces from 2006 to 2015

2018

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This paper investigates inequality in SO 2 and NO X emissions, by observing their extraordinary levels and uneven distribution in China during the period of the 11th and 12th Five-Year Plans (FYPs, 2006(FYPs, -2015. This provincial and regional analysis utilizing the Theil index and Kaya factors help us to find the trajectory of inequality and its primary sources. Based on our analysis, we conclude the driving factors behind emissions inequalities are as follows. There are four economic factors of per capita SO 2 emission: SO 2 emission intensity of coal consumption, coal intensity of power generation, power intensity of GDP, and per capita GDP. Additionally, there are four urban development factors of per capita NO X emission: NO X emission intensity of gasoline consumption, proportion of gasoline vehicles, vehicle use in urban population, and urbanization rate. The SO 2 emission results represent an increase of 6% in overall inequality where the inequality of power intensity of GDP is the main contributor. In terms of NO X emission, the 3% growth in total inequality is related to the high effect of NO X emission intensity of gasoline consumption. We also examine the effect of other factors affecting the trajectory of inequalities. To apply these results in practice, we compare the 11th and 12th FYPs and give some policy suggestions.

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Marginal Generation Technology in the Chinese Power Market towards 2030 Based on Consequential Life Cycle Assessment

Cited by 10 publications

References 28 publications

A Conceptual Review on Using Consequential Life Cycle Assessment Methodology for the Energy Sector

A Conceptual Review on Using Consequential Life Cycle Assessment Methodology for the Energy Sector

Teaching Practice for Control Engineering Fundamental Based on Solving Complicated Mechanical Engineering Problems

Air Pollution Inequality and Its Sources in SO2 and NOX Emissions among Chinese Provinces from 2006 to 2015

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