Crop Production and Agricultural Carbon Emissions: Relationship Diagnosis and Decomposition Analysis

Jianli, Sui; Lv, Wenqiang

doi:10.3390/ijerph18158219

Cited by 21 publications

(14 citation statements)

References 35 publications

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“…According to the EKC hypothesis, the economy-environment relationship follows an inverted U shape: in the process of economic growth, pollutant emissions rise from the beginning, peak in the middle, and fall at the end [2,[13][14][15][16][17][18]. In fact, many EKC studies show that there is also an N shape [19,20], a linear shape [21,22], or even an irregular shape [23,24]. Recently, an increasing number of EKC studies have expanded from traditional pollutant indicators (including atmosphere, water, and land) to new indicators (such as ecological footprint and carbon footprint) [25,26], from indicators of emissions per capita to total emissions [23].…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Agricultural CO2 Emissions in Henan Province, China, Based on EKC and Decoupling

Wang

2022

Sustainability

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Global warming caused by greenhouse gas emissions is highly concerning. Both the environmental Kuznets curve (EKC) hypothesis and decoupling analysis indicate a dynamic relationship between economic growth and environmental pollution, and each method has its own emphasis. The objective of this paper is to investigate the nexus between grain production and agricultural carbon emissions for the main grain-producing areas in China. Taking Henan Province, the second largest agricultural province, as an example, this paper examines the relationship between grain production and agricultural CO2 emissions during 2000–2019, using the EKC hypothesis and decoupling analysis. The results are as follows: (1) The estimation model of CO2 EKC shows the climbing stage of an inverted U-shaped relationship, which suggests that agricultural economic growth occurred at the cost of an increase in agricultural CO2 emissions in Henan Province during the past 20 years. (2) The results of the decoupling analysis show that incidences of weak decoupling and expansive coupling states took up most of the study period, accompanied by an occasionally strong decoupling state; decoupling and coupling states alternated irregularly, and no clear development trends were observed. (3) Considering the shape of the CO2 EKC and the decoupling state, environmental policies encouraged decoupling, but suffered from time lags and poor continuity; long-term incentives, such as an ecological compensation policy, could perhaps drive carbon emission reduction. On this basis, Chinese agricultural policy should combine environmentally targeted interventions with measures supporting production and farmers’ incomes, and environmental policy should also adapt to economic growth. Only when both supplement each other can sustainable agricultural goals be achieved.

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Section: Literature Reviewmentioning

confidence: 99%

Analysis of Agricultural CO2 Emissions in Henan Province, China, Based on EKC and Decoupling

Wang

2022

Sustainability

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“…The carbon emission coefficient of different crop types has certain differences, so the agricultural carbon emission and emission intensity in Hubei Province may also be related to the change of crop planting structure, but this paper does not discuss this problem [ 43 ]. The change of cultivated land use type is closely related to human activities [ 63 ]. In recent years, ecological protection activities such as returning cultivated land to forest, returning cultivated land to grassland and returning cultivated land to lake in Hubei Province have changed agricultural production, so the change of cultivated land use may also be an important factor in the change of agricultural carbon emissions, but this paper does not consider it.…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal Characteristics, Decoupling Effect and Driving Factors of Carbon Emission from Cultivated Land Utilization in Hubei Province

Xiao

Zhang

Qian

et al. 2022

IJERPH

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The carbon emission level and spatiotemporal characteristics in Hubei Province were estimated and studied using the Intergovernmental Panel on Climate Change (IPCC) carbon emission coefficient technique based on county data from Hubei Province from 2000 to 2020. The relationship between carbon emissions from cultivated land utilization and agricultural economic growth was examined using the Tapio decoupling index, and the factors influencing carbon emissions in Hubei Province were further examined using the Logarithmic Mean Divisia Index (LMDI model). The results demonstrate that: (1) Spatiotemporal variations in carbon emissions are evident. In terms of time, the volume of carbon emissions in Hubei Province is still substantial, and the transition to low-carbon land use is quite gradual. Geographically, the high-value region of the middle east coexists with the low-value zone of the west, with apparent regional contrasts. (2) The decoupling between carbon emissions and agricultural economic growth is becoming more and more obvious in Hubei Province. The number of counties and cities in a negative decoupling state has significantly decreased, and the majority of counties are now in a strong decoupling condition. (3) Agricultural production efficiency is the most significant driving factor for restricting carbon emission, according to the decomposition results of carbon emission driving factors based on the LMDI model. In addition, the results of sample decomposition based on topographic characteristics indicate that agricultural production efficiency is primarily responsible for the suppression of carbon emissions in flat regions. The increase in carbon emissions in hilly regions is primarily influenced by agricultural productivity. The increase in carbon emissions in mountainous regions is mostly influenced by agricultural labor intensity. This study′s finding has enlightening implications for the high-quality growth of agriculture.

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“…Luo et al (2017) explored the spatial and temporal heterogeneity of CO2 emissions in China's agricultural sector and its intensity, and used the Tapio decoupling model to examine the decoupling mechanism between agricultural economic growth and CO2 emissions in 30 Chinese provinces from 1997-2014, finding that CO2 emissions were severely decoupled from agricultural output for a longer period in eastern China. Wu et al (2019) decomposed the drivers of agricultural carbon emissions into four factors: energy mix, energy intensity, economic output, and population size based on the log-average divisor index (LMDI) approach, while Sui et al (2021) decomposed the drivers of agricultural carbon emissions into four factors: agricultural carbon intensity effect, structural effect, economic effect, and labor effect. Han et al (2018) used spatial autocorrelation analysis to explore the spatial correlation between China's agricultural carbon emission intensity and various indicators of the agricultural economy, and found that there is a positive spatial correlation between China's agricultural carbon emission intensity and agricultural GDP per unit arable area.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Drivers of Agricultural Carbon Emissions and Decoupling Effects in Jiangsu Province, China

Fan

2022

Preprint

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This paper measures and analyzes the characteristics of changes in agricultural carbon emissions, structure and intensity from 2005 to 2020 based on agricultural input-output data, explores the drivers of agricultural carbon emissions using the LMDI model, and uses the TAPIO decoupling model to explore the relationship between agricultural economic development and agricultural carbon emissions in Jiangsu province. The research indicate that: (1) From 2005 to 2020, the agricultural carbon emissions in Jiangsu Province showed a three-stage change of "decline - rise - decline", with an average annual decrease of 0.34%; Carbon emissions per 10,000 yuan of total agricultural output value decreased from 701.43 kg in 2005 to 215.96 kg in 2020, with an average annual decrease of 7.55%. (2) The factors of agricultural production efficiency, agricultural production structure and agricultural labor scale all contribute to agricultural carbon emission reduction to different degrees, while the factors of agricultural economic level and total population contribute to agricultural carbon emission reduction to different degrees. (3) The decoupling elasticity index of agricultural carbon emissions and agricultural economic level in Jiangsu Province lies between -3.3217 and 3.6546, and the decoupling types are mainly weak and strong decoupling. According to our research results, agricultural production efficiency should be improved, the structure of the plantation industry should be optimized, and the transfer of agricultural labor to secondary and tertiary industries should be promoted in order to promote high-quality development of agriculture.

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Crop Production and Agricultural Carbon Emissions: Relationship Diagnosis and Decomposition Analysis

Cited by 21 publications

References 35 publications

Analysis of Agricultural CO2 Emissions in Henan Province, China, Based on EKC and Decoupling

Analysis of Agricultural CO2 Emissions in Henan Province, China, Based on EKC and Decoupling

Spatiotemporal Characteristics, Decoupling Effect and Driving Factors of Carbon Emission from Cultivated Land Utilization in Hubei Province

Research on the Drivers of Agricultural Carbon Emissions and Decoupling Effects in Jiangsu Province, China

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