Changes in agricultural carbon emissions and factors that influence agricultural carbon emissions based on different stages in Xinjiang, China

Xiong, Chuanhe; Yang, Degang; Xia, Fuqiang; Huo, Jinwei

doi:10.1038/srep36912

Cited by 73 publications

(50 citation statements)

References 24 publications

(58 reference statements)

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“…For instance, Wang et al followed the IPCC guidelines [6] released in 2006 to estimate the greenhouse gas emission intensity of rice, wheat, and maize yields in China from 1985-2010 [7]. According to the IPCC guidelines, Xiong et al and Tian et al estimated the carbon emissions of agricultural production in Hunan and Xinjiang, respectively [8,9]. In addition, Han et al measured carbon emissions from the entire agricultural sector as a whole in China during the period from 1997-2015 [10].…”

Section: Measurement Of Agricultural Carbon Emissionsmentioning

confidence: 99%

Spatial-Temporal Characteristics of the Driving Factors of Agricultural Carbon Emissions: Empirical Evidence from Fujian, China

Chen

et al. 2019

Energies

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With the development of agricultural modernization, the carbon emissions caused by the agricultural sector have attracted academic and practitioners’ circles’ attention. This research selected the typical agricultural development province in China, Fujian, as the research object. Based on the carbon emission sources of five main aspects in agricultural production, this paper applied the latest carbon emission coefficients released by Intergovernmental Panel on Climate Change of the UN (IPCC) and World Resources Institute (WRI), then used the ordered weighted aggregation (OWA) operator to remeasure agricultural carbon emissions in Fujian from 2008–2017. The results showed that the amount of agricultural carbon emissions in Fujian was 5541.95 × 103 tonnes by 2017, which means the average amount of agricultural carbon emissions in 2017 was 615.78 × 103 tonnes, with a decrease of 13.13% compared with that in 2008. In terms of spatial distribution, agricultural carbon emissions in the eastern coastal areas were less than those in the inland regions. Among them, the highest agricultural carbon emissions were in Zhangzhou, Nanping, and Sanming, while the lowest were in Xiamen, Putian, and Ningde. In addition, this paper selected six influencing variables, the research and development intensity, the proportion of agricultural labor force, the added value of agriculture, the agricultural industrial structure, the per capita disposable income of rural residents, and per capita arable land area, to clarify further the impacts on agricultural carbon emissions. Finally, geographically- and temporally-weighted regression (GTWR) was used to measure the direction and degree of the influences of factors on agricultural carbon emission. The conclusion showed that the regression coefficients of each selected factor in cities were positive or negative, which indicated that the impacts on agricultural carbon emission had the characteristics of geospatial nonstationarity.

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Section: Measurement Of Agricultural Carbon Emissionsmentioning

confidence: 99%

Spatial-Temporal Characteristics of the Driving Factors of Agricultural Carbon Emissions: Empirical Evidence from Fujian, China

Chen

et al. 2019

Energies

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“…In this study, we employed the factor decomposition model 55,56 to distinguish the roles of CCT components in the spatiotemporal variations of CCT, which helped to illustrate the difference in the drivers of spatial and temporal varitions. The factor decomposition model separated specific variables, regarded as the multiplication of some parts, into its components using a logarithm way.…”

Section: Methodsmentioning

confidence: 99%

Divergent drivers of the spatial and temporal variations of cropland carbon transfer in Liaoning province, China

Zhu

Zhang

Zhao

et al. 2017

Sci Rep

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Spatial and temporal variations are important points of focus in ecological research. Analysing their differences improves our understanding on the variations of ecological phenomena. Using data from the Liaoning Statistical Yearbook, we investigated the spatial and temporal variations of cropland carbon transfer (CCT), an important ecological phenomenon in quantifying the regional carbon budget, in particular, the influencing factors and difference. The results showed that, from 1992 to 2014, the average CCT in Liaoning province was 18.56 TgC yr−1 and decreased from northwest to southeast. CCT spatial variation was primarily affected by the ratio of planting area to regional area (RPR) via its effect on the magnitude of carbon transfer (MCT), which depended mainly on fertilizer usage per area (FUA). From 1992 to 2014, CCT exhibited a significantly increasing trend with a rate of 0.48 TgC yr−1. The inter-annual variation of CCT was dominated by carbon transfer per planting area (CTP) through its effect on MCT, which significantly correlated with FUA but showed no significant correlation with climatic factors. Therefore, the factors affecting the spatial variation of CCT differed from those that affected its inter-annual variation, indicating that the spatial and temporal variations of ecological phenomena were affected by divergent factors.

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“…Yao et al [43] conducted a decomposition study on the factors affecting the changes of AH carbon emissions based on the LMDI method and found that AH production efficiency improvement was the most important factor to restrain the sustained growth of the AH carbon emissions. Xiong et al [40,42] used the same decomposition method to draw conclusions that the economy factor was the critical factor to promote the increase in agricultural carbon emissions in Xinjiang province of China, while the main inhibiting factor was the efficiency factor. These research results have enriched the body of work on GHG emissions reduction in China's AH sector from different perspectives.…”

Section: Introductionmentioning

confidence: 99%

Study on the Vertical Linkage of Greenhouse Gas Emission Intensity Change of the Animal Husbandry Sector between China and Its Provinces

et al. 2018

Self Cite

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China's carbon intensity (CI) reduction target in 2030 needs to be allocated to each province in order to be achieved. Thus, it is of great significance to study the vertical linkage of CI change between China and its provinces. The existing research on the vertical linkage focuses more on energy-related economic sectors in China; however, attention has not been paid to China's animal husbandry (AH) sector, although the role of the China's AH sector in greenhouse gas (GHG) reduction is increasingly important. This study firstly established a vertical linkage of change in greenhouse gas emission intensity of the animal husbandry sector (AHGI) between China and its 31 provinces based on the logarithmic mean Divisia index (LMDI) decomposing method from the perspective of combining emission reduction with economic development, and quantified the contributions of each province and its three driving factors of environmental efficiency (AHEE), productive efficiency (AHPE), and economic share (AHES) to reducing China's AHGI during the period of 1997-2016. The main results are: (1) The AHGI of China decreased from 5.49 tCO 2 eq/10 4 yuan in 1997 to 2.59 tCO 2 eq/10 4 in 2016, showing a 75.25% reduction. The AHGI in 31 provinces also declined and played a positive role in promoting the reduction of national AHGI, but there were significant inter-provincial differences in the extent of the contribution. Overall, the provinces with higher emission levels contributed the most to the reduction of China's AHGI; (2) The AHPE and AHEE factors in 31 provinces cumulatively contributed to the respective 68.17% and 11.78% reduction of China's AHGI, while the AHES factors of 31 provinces cumulatively inhibited the 4.70% reduction. Overall, the AHPE factor was the main driving factor contributing to the reduction of China's AHGI. In the future, improving the level of AHEE through GHG emissions reduction technology and narrowing the inter-provincial gap of the level of AHPE are two important paths for promoting the reduction of China's AHGI.

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Changes in agricultural carbon emissions and factors that influence agricultural carbon emissions based on different stages in Xinjiang, China

Cited by 73 publications

References 24 publications

Spatial-Temporal Characteristics of the Driving Factors of Agricultural Carbon Emissions: Empirical Evidence from Fujian, China

Spatial-Temporal Characteristics of the Driving Factors of Agricultural Carbon Emissions: Empirical Evidence from Fujian, China

Divergent drivers of the spatial and temporal variations of cropland carbon transfer in Liaoning province, China

Study on the Vertical Linkage of Greenhouse Gas Emission Intensity Change of the Animal Husbandry Sector between China and Its Provinces

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