Evidence map›Paper›PMID 36498004›Full record

ArticleInternational journal of environmental research and public health2022

Influencing Factors and Realization Path of Power Decarbonization-Based on Panel Data Analysis of 30 Provinces in China from 2011 to 2019.

Ning Ren, Xiufan Zhang, Decheng Fan

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ning RenCollege of Marxism, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Xiufan ZhangSchool of Economics and Management, Zhejiang Sci-Tech University, Hangzhou 310018, China.ORCID 0000-0002-0641-2853
Decheng FanSchool of Economics and Management, Harbin Engineering University, Harbin 150006, China.

Funding

Heilongjiang Province Philosophy and Social Sciences Research Project (18GLD291)Key projects of the National Social Science Fund (19AGL007)
6 · The paper itself

Abstract

2011-2019 was the critical period of the low-carbon transformation of the power industry, reflecting the deepening influence of market mechanisms. Decarbonization of the new power system is a systematic project that needs to strengthen the top-level design and overall planning. Therefore, the paper first evaluates the decarbonization of the existing power system and controls the grid architecture, power structure, energy utilization, supply chain, and trading market to further optimize the system by strengthening the basic theoretical research of the new power system, exploring the key elements of the low-carbon development of the power system, promoting the breakthrough of the key subjects, and formulating the new power system decarbonization path. In the international push for carbon neutrality goals, identifying key factors in the decarbonization of the power system is critical to achieving low-carbon development in the power sector. Combined with the characteristics and development trends of the power industry, the five dimensions of "Power generation decarbonization (SP)", "Energy utilization efficiency (EU)", "Supply chain decarbonization (SC)", and "Power grid decarbonization (PG)", and "the Trading system (TS)" are selected to construct an evaluation index system for the power decarbonization and identify the key factors. The Analytic Network Process (ANP) Method is used to calculate the index weight and measure the decarbonization level of the power industry in 30 provinces in China from 2011 to 2019. The evaluation results reveal that the overall decarbonization level of the power industry is on the rise and has stabilized after peaking in 2016. The regression results of the systematic GMM estimation show that "the intensity of cross-regional transmission", "the degree of carbon market participation", "technology innovation", and "policy support" can significantly promote power decarbonization, and different regions have heterogeneity. Therefore, we propose to achieve technological innovation and upgrading in the eastern region, strengthen the construction of smart grids in the central region, optimize the power structure in the western region, and improve the market mechanism as a whole, to form a low-carbon development path for the power industry.

Indexed as

Data AnalysisIndustryCarbonChinaEconomic DevelopmentHumansPolicyCarbonpower decarbonizationpower generationpower systemsupply chaintechnology innovation

Identifiers

PMID36498004
PMCPMC9735499

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.