Evidence map›Paper›PMID 35482771›Full record

ArticlePloS one2022

Analysis of regional agricultural carbon emission efficiency and influencing factors: Case study of Hubei Province in China.

Tengyu Shan, Yuxiang Xia, Chun Hu, Shunxi Zhang, Jinghan Zhang, Yaodong Xiao, Fangfang Dan

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

7 authors.

Tengyu ShanSchool of Chemistry and Environmental Engineering, Wuhan Polytechnic University, Wuhan, China.ORCID 0000-0001-8553-9715
Yuxiang XiaSchool of Chemistry and Environmental Engineering, Wuhan Polytechnic University, Wuhan, China.
Chun HuSchool of Chemistry and Environmental Engineering, Wuhan Polytechnic University, Wuhan, China.
Shunxi ZhangSchool of Chemistry and Environmental Engineering, Wuhan Polytechnic University, Wuhan, China.
Jinghan ZhangSchool of Chemistry and Environmental Engineering, Wuhan Polytechnic University, Wuhan, China.
Yaodong XiaoSchool of Chemistry and Environmental Engineering, Wuhan Polytechnic University, Wuhan, China.
Fangfang DanSchool of Chemistry and Environmental Engineering, Wuhan Polytechnic University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, China's industrial economy has grown rapidly and steadily. Concurrently, carbon emissions have gradually increased, among which agricultural production is an important source of greenhouse gas emissions. It is necessary to reduce agricultural carbon emissions by improving their efficiency to achieve the global goal of peak carbon dioxide emissions in 2030. From a dynamic and static point of view, this study puts agricultural carbon emissions into the evaluation index system of agricultural carbon emission efficiency and analyzes the agricultural carbon emission efficiency and its influencing factors in Hubei Province. First, the unexpected output Slacks-based measure (SBM) model in data envelopment analysis was used to evaluate the agricultural carbon emission efficiency of Hubei Province in 2018 and compared it with other provinces horizontally. Second, the Malmquist-Luenberger index was used to analyze the comprehensive efficiency of agricultural carbon emissions in Hubei Province from 2004 to 2018. The role of technological progress and technical efficiency change in the development of low-carbon agriculture in Hubei Province was analyzed. The results showed that agricultural production efficiency in Hubei Province improved from 2004 to 2018, and the overall level was slightly higher than the average level in China. However, agriculture has not eliminated the extensive development modes of high input, low efficiency, high emission, and high pollution. The efficiency of technological progress in agricultural resource utilization in Hubei Province was close to the optimal level. The improvement space was small. Hence, the low efficiency of agricultural technology is a key factor restricting the improvement of agricultural production efficiency. The results provide a reference for low-carbon agricultural policy formulation and expand the policy choice path. This has practical significance.

Indexed as

AgricultureGreenhouse GasesEfficiencyEnvironmental PollutionIndustryGreenhouse Gases

Identifiers

PMID35482771
PMCPMC9049529

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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.