2018
DOI: 10.3390/su10072492
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Study on the Vertical Linkage of Greenhouse Gas Emission Intensity Change of the Animal Husbandry Sector between China and Its Provinces

Abstract: 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. … Show more

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Cited by 6 publications
(2 citation statements)
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“…In their paper, Cai et al [9] carry out a national level study on a reduction of the emission intensities (per unit of the monetary value of output) of non-CO 2 greenhouse gases arising from the livestock sector in China, through an analysis of the contribution of each province to the overall national emissions. They especially concentrate on the role of three "driving factors," i.e., environmental efficiency, productive efficiency and economic share, in determining the national greenhouse gas emission intensity.…”
mentioning
confidence: 99%
“…In their paper, Cai et al [9] carry out a national level study on a reduction of the emission intensities (per unit of the monetary value of output) of non-CO 2 greenhouse gases arising from the livestock sector in China, through an analysis of the contribution of each province to the overall national emissions. They especially concentrate on the role of three "driving factors," i.e., environmental efficiency, productive efficiency and economic share, in determining the national greenhouse gas emission intensity.…”
mentioning
confidence: 99%
“…Livestock production accounts for a significant share of the global greenhouse gas (GHG) balance, including carbon dioxide (CO 2 ), methane (CH 4 ), ammonia (NH 3 ), and nitrous oxide (N 2 O) released into the atmosphere (7). There are many calculation and assessment methods to study carbon emission efficiencies, such as the stochastic frontier model, regression model, data envelopment analysis (DEA) method, and unexpected output (Slack-Based Measure) model (8)(9)(10)(11). Most studies have adopted the unexpected output (Slack-Based Measure) model to calculate carbon emission efficiency.…”
mentioning
confidence: 99%