Evidence map›Paper›PMID 36141923›Full record

ArticleInternational journal of environmental research and public health2022

Spatiotemporal Evolution and Influencing Factors of Carbon Emission Efficiency in the Yellow River Basin of China: Comparative Analysis of Resource and Non-Resource-Based Cities.

Yingqi Xu, Yu Cheng, Ruijing Zheng, Yaping Wang

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. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Do Environmental Regulations Facilitate a Low-Carbon Transformation in China's Resource-Based Cities?International journal of environmental research and public health · 2023
    Article
  2. Article
  3. Horizontal COInternational journal of environmental research and public health · 2023
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yingqi XuCollege of Geography and Environment, Shandong Normal University, Jinan 250358, China.
Yu ChengCollege of Geography and Environment, Shandong Normal University, Jinan 250358, China.ORCID 0000-0002-2510-6114
Ruijing ZhengCollege of Geography and Environment, Shandong Normal University, Jinan 250358, China.
Yaping WangCollege of Geography and Environment, Shandong Normal University, Jinan 250358, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comparing the carbon emission efficiency (CEE) of resource and non-resource-based cities in the Yellow River Basin (YRB) can guide their synergistic development and low-carbon transition. This study used the super-efficiency slacks-based measure (super-SBM) model to measure the CEE of cities in the YRB. Kernel density estimation and Theil index decomposition methods were used to explore the spatiotemporal evolutionary patterns, and a panel regression model was established to analyze the influencing factors of CEE. The research results showed that the CEE of the two types of cities have an overall upward trend in time, with a widening regional gap. Resource-based cities mainly displayed the characteristics of decentralized regional agglomeration, while non-resource-based cities mainly showed the characteristics of convergent regional agglomeration. Panel regression results showed that the levels of economic development, indus-trial structure, and population density are significantly positively correlated with CEE in the YRB, while foreign direct investment and resource endowment are significantly negatively correlated with CEE. Except for economic development and industrial structure, there is some variability in the contribution of the remaining influencing factors to the CEE of the resource and non-resource-based cities. The research results suggest developing classification measures for low-carbon transition in the YRB.

Indexed as

CarbonRiversChinaCitiesEconomic DevelopmentEfficiencyCarboncarbon emission efficiencynon-resource-based citiesresource-based citiessuper-efficiency SBM modelYellow River Basin

Identifiers

PMID36141923
PMCPMC9517066

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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.