Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model

The increase in income among Chinese residents has been accompanied by dramatic changes in dietary structure, promoting a growth in carbon emissions. Therefore, in the context of building a beautiful countryside, it is of great significance to study the carbon emissions of rural residents’ food cons...

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Autores principales:	Shuai Qin, Hong Chen, Haokun Wang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	food consumption carbon emissions spatial–temporal heterogeneity geographically weighted regression food low-carbon consumption Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/593f8c9f56d140b09f0020649b27703b
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id	oai:doaj.org-article:593f8c9f56d140b09f0020649b27703b
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spelling	oai:doaj.org-article:593f8c9f56d140b09f0020649b27703b2021-11-25T19:00:55ZSpatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model10.3390/su1322124192071-1050https://doaj.org/article/593f8c9f56d140b09f0020649b27703b2021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/22/12419https://doaj.org/toc/2071-1050The increase in income among Chinese residents has been accompanied by dramatic changes in dietary structure, promoting a growth in carbon emissions. Therefore, in the context of building a beautiful countryside, it is of great significance to study the carbon emissions of rural residents’ food consumption to realize the goal of low-carbon food consumption. In this paper, the calculation of food consumption carbon emissions of Chinese rural residents is based on the carbon conversion coefficient method, and the spatial heterogeneity of influencing factors is analyzed with the aid of the ESDA-GWR model. The results indicate that the per capita food consumption carbon emissions of rural residents have increased by 1.68% annually, reaching 336.73 kg CO<sub>2</sub>-eq in 2020, which is 1.32 times that of 2002. Carbon emissions generated from rural residents’ food consumption have significant spatial agglomeration characteristics, showing the spatial distribution characteristics of a north–south confrontation, with a central area collapse. The influencing factors of food consumption carbon emissions have significant spatial heterogeneity, among which, as the main force to restrain the growth of food consumption carbon emissions, the price factor has a regression coefficient between −0.1 and −0.3, and its influence has weakened from northwest to southeast in 2020. The education–social factor is the main driving force for the growth of food consumption carbon emissions, with a regression coefficient between 0.58 and 0.99, and its influence has increased from east to west. In the future, formulating food consumption optimization policies should be based on the actual situation of food consumption carbon emissions in various regions to promote the realization of low-carbon food consumption.Shuai QinHong ChenHaokun WangMDPI AGarticlefood consumption carbon emissionsspatial–temporal heterogeneitygeographically weighted regressionfood low-carbon consumptionEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12419, p 12419 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	food consumption carbon emissions spatial–temporal heterogeneity geographically weighted regression food low-carbon consumption Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	food consumption carbon emissions spatial–temporal heterogeneity geographically weighted regression food low-carbon consumption Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Shuai Qin Hong Chen Haokun Wang Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model
description	The increase in income among Chinese residents has been accompanied by dramatic changes in dietary structure, promoting a growth in carbon emissions. Therefore, in the context of building a beautiful countryside, it is of great significance to study the carbon emissions of rural residents’ food consumption to realize the goal of low-carbon food consumption. In this paper, the calculation of food consumption carbon emissions of Chinese rural residents is based on the carbon conversion coefficient method, and the spatial heterogeneity of influencing factors is analyzed with the aid of the ESDA-GWR model. The results indicate that the per capita food consumption carbon emissions of rural residents have increased by 1.68% annually, reaching 336.73 kg CO<sub>2</sub>-eq in 2020, which is 1.32 times that of 2002. Carbon emissions generated from rural residents’ food consumption have significant spatial agglomeration characteristics, showing the spatial distribution characteristics of a north–south confrontation, with a central area collapse. The influencing factors of food consumption carbon emissions have significant spatial heterogeneity, among which, as the main force to restrain the growth of food consumption carbon emissions, the price factor has a regression coefficient between −0.1 and −0.3, and its influence has weakened from northwest to southeast in 2020. The education–social factor is the main driving force for the growth of food consumption carbon emissions, with a regression coefficient between 0.58 and 0.99, and its influence has increased from east to west. In the future, formulating food consumption optimization policies should be based on the actual situation of food consumption carbon emissions in various regions to promote the realization of low-carbon food consumption.
format	article
author	Shuai Qin Hong Chen Haokun Wang
author_facet	Shuai Qin Hong Chen Haokun Wang
author_sort	Shuai Qin
title	Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model
title_short	Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model
title_full	Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model
title_fullStr	Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model
title_full_unstemmed	Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model
title_sort	spatial–temporal heterogeneity and driving factors of rural residents’ food consumption carbon emissions in china—based on an esda-gwr model
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/593f8c9f56d140b09f0020649b27703b
work_keys_str_mv	AT shuaiqin spatialtemporalheterogeneityanddrivingfactorsofruralresidentsfoodconsumptioncarbonemissionsinchinabasedonanesdagwrmodel AT hongchen spatialtemporalheterogeneityanddrivingfactorsofruralresidentsfoodconsumptioncarbonemissionsinchinabasedonanesdagwrmodel AT haokunwang spatialtemporalheterogeneityanddrivingfactorsofruralresidentsfoodconsumptioncarbonemissionsinchinabasedonanesdagwrmodel
_version_	1718410403471425536

Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model

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