Evidence map›Paper›PMID 37540680›Full record

ArticlePloS one2023

Measurement and driving factors of carbon productivity in China's provinces: From the perspective of embodied carbon emissions.

Changyi Liang, Peng Gao

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Changyi LiangSchool of Economics and Management, Southeast University, Nanjing, China.
Peng GaoSchool of Economics, Nanjing University of Posts and Telecommunications, Nanjing, China.ORCID 0000-0003-2341-1091

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon productivity incorporates economic development and carbon emissions within a unified framework for measuring the economic value per unit carbon emissions. In the context of climate change, improving carbon productivity is of great value for promoting low-carbon development in a country or region. From the perspective of embodied carbon emissions, this study constructs an embodied carbon productivity (ECP) index and uses the Logarithmic Mean Divisia Index decomposition method to study the evolution trends and driving factors of ECP in China's provinces based on China Interregional Input-Output Tables for 2002, 2007, 2012, and 2017. The following results were obtained: First, China's overall ECP showed a continuously increasing trend during the entire period, with the energy efficiency factor playing the largest role among all driving factors. Second, the ECP in 19 of the 30 Chinese provinces continued to increase and the contributions of energy emission ratio, ECP per capita, and population size factors to the increase in ECP presented evident disparities among different provinces. Third, the ECP in three major regions ranged from high to low in the order of East, Central, and West, with the largest growth in the Central, followed by the West, with the smallest in the East. Based on the analysis of research results, we proposed relevant policy recommendations to further improve China's ECP and achieve low-carbon economy.

Indexed as

CarbonCarbon DioxideChinaEconomic DevelopmentCarbonCarbon Dioxide

Identifiers

PMID37540680
PMCPMC10403082

What OpenQuestion holds

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Registered trials

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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.