Evidence map›Paper›PMID 36429559›Full record

ArticleInternational journal of environmental research and public health2022

Spatial-Temporal Characteristics and Influence Factors of Carbon Emission from Livestock Industry in China.

Dequan Hao, Rui Wang, Chaojie Gao, Xinyan Song, Wenxin Liu, Guangyin Hu

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

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

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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

6 authors.

Dequan HaoCollege of Economics and Management, Northwest A&F University, Yangling, Xianyang 712100, China.
Rui WangCollege of Economics and Management, Northwest A&F University, Yangling, Xianyang 712100, China.
Chaojie GaoCollege of Economics and Management, Northwest A&F University, Yangling, Xianyang 712100, China.
Xinyan SongCollege of Economics and Management, Northwest A&F University, Yangling, Xianyang 712100, China.
Wenxin LiuCollege of Economics and Management, Northwest A&F University, Yangling, Xianyang 712100, China.ORCID 0000-0003-0717-2043
Guangyin HuCollege of Economics and Management, Northwest A&F University, Yangling, Xianyang 712100, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Animal husbandry is an important source of carbon emissions. As a large country, China must measure the carbon emissions from animal husbandry to reveal the spatial and temporal characteristics and determine the influencing factors to realize low-carbon animal husbandry and carbon emission reduction. In this paper, the carbon emissions of the livestock industry in each province of China were calculated with the emission coefficient method, considering the temperature change factor. The spatial and temporal characteristics and influencing factors of livestock industry carbon emissions were analyzed using the kernel density model, the spatial autocorrelation model, and the Tobit model. The results indicated that: (1) From 2000 to 2020, carbon emissions from the livestock industry in China experienced four stages: rapid rise, rapid decline, slow rise, and fluctuating decline, with an overall downward trend. Carbon emissions in the eastern and central regions showed a downward trend, while carbon emissions in the western regions showed an upward trend. (2) In terms of time, the relative gap in carbon emissions among the provinces narrowed first and then widened; the spatial agglomeration of carbon emissions from livestock farming in China increased, gradually forming the characteristics of "high agglomeration, low agglomeration", and showing a gradually decreasing pattern from northwest to southeast. (3) Nationwide, industrial structure, population, and farmers' income levels have had significantly promoting effects on animal husbandry carbon emissions, and the urbanization and agricultural mechanization levels have had significant inhibitory effects on carbon emissions. Finally, based on the above factors, it can be concluded that recognizing the location conditions, promoting the upgrading of industrial structures, and adopting differentiated strategies will help to promote the reduction in carbon emissions in animal husbandry and achieve its high-quality development.

Indexed as

CarbonLivestockAnimalsCarbon DioxideIndustryUrbanizationCarbonCarbon Dioxidecarbon emissionsChinainfluence factorslivestock industryspatial featuretemporal variation

Identifiers

PMID36429559
PMCPMC9690071

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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.