Study on the Vertical Linkage of Greenhouse Gas Emission Intensity Change of the Animal Husbandry Sector between China and Its Provinces
Abstract
:1. Introduction
2. Materials and Methods
2.1. Estimation of AHGI
2.2. Decomposition of AHGI
2.2.1. Decomposing Process
2.2.2. Calculating Method
2.3. Data Collection and Processing
3. Results and Discussion
3.1. Changes of AHGI in China and Its Provinces
3.2. Analysis of Provincial Contributions to the Reduction of China’s AHGI
3.3. Analysis of Driving Factors’ Contributions to the Reduction of China’s AHGI
3.3.1. AHPE Factor
3.3.2. AHEE Factor
3.3.3. AHES Factor
3.4. Advantages and Limitations of This Study
4. Conclusions
- (1)
- The AHGI of China decreased from 5.49 tCO2eq/104 yuan in 1997 to 2.59 tCO2eq/104 in 2016, showing a 75.25% reduction. Compared 2016 with 1997, the AHGI in 31 provinces also declined and played a positive role in promoting the reduction of the national AHGI, but there were significant differences among provinces in the extent of contribution. Henan, the largest contributor, contributed to a 7.11% reduction of China’s AHGI, and Tianjin was the smallest contributor (0.06%). The top ten provinces (Henan, Hebei, Shandong, Sichuan, Guangxi, Hunan, Anhui, Yunnan, Guangdong and Hubei) cumulatively contributed to a reduction of 46.22% in China’s AHGI, accounting for 61.42% of the total contributions by 31 provinces; while the bottom ten provinces (Tianjin, Ningxia, Beijing, Liaoning, Shanghai, Hainan, Fujian, Zhejiang, Chongqing and Gansu) cumulatively contributed to a reduction of only 6.45% in China’s AHGI, accounting for 8.57% of total provincial contributions. Overall, there was an inconsistency between the extent of the actual reduction of AHGI in each province and its contributions to the country. China’s progress in reducing AHGI was mainly made by provinces with a large GHG emissions from AH.
- (2)
- Three driving factors (environmental efficiency, productive efficiency, and economic share) comprehensively determine the reduction of China’s AHGI through two different contributions of positive promotion and negative inhibition, but the way in which the three driving factors exert their impact and the extent of their contributions vary significantly among provinces. The productive efficiency and environmental efficiency factors in 31 provinces cumulatively contributed to the respective 68.17% and 11.78% reduction of China’s AHGI, while the economic share factors of 31 provinces cumulatively inhibited the 4.70% reduction of China’s AHGI. Overall, the productive efficiency factors are the main driving factors contributing to the reduction of China’s AHGI. The reduction of China’s AHGI during the study period depended more on the substantial increase in the AH’s productive efficiency than on the improvement of AH’s environmental efficiency. The economic share factor was a weight with the nature of a “double-edged sword”, which can decrease or increase the contribution value of each province to the reduction of China’s AHGI. In the future, improving the level of AHEE through GHG emission 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. In terms of improving the level of AHEE, all provinces need to do this. However this is even more urgent in the seven provinces, including Tibet, Qinghai, Inner Mongolia, Ningxia, Gansu, Beijing and Shanghai. In terms of narrowing the inter-provincial gap of the level of AHPE, the gap is mainly reflected between the frontier grassland pastoral areas in the western and the agricultural areas in Central and Eastern China. The key provinces that need to improve the level of AHPE are located in grassland pastoral areas, including Tibet, Qinghai, Gansu, Xinjiang, Inner Mongolia, Ningxia, Guizhou, Yunnan and Guangxi.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Region | Dairy Cow | Cattle | Buffalo | Horse | Donkey | Mule |
North China | 7.46 | 2.82 | - | 1.09 | 0.60 | 0.60 |
Northeast China | 2.23 | 1.02 | - | 1.09 | 0.60 | 0.60 |
East China | 8.33 | 3.31 | 5.55 | 1.64 | 0.90 | 0.90 |
Central and Southern China | 8.45 | 4.72 | 8.24 | 1.64 | 0.90 | 0.90 |
Southwest China | 6.51 | 3.21 | 1.53 | 1.64 | 0.90 | 0.90 |
Northwest China | 5.93 | 1.86 | - | 1.09 | 0.60 | 0.60 |
Region | Camel | Sheep | Goat | Pig | Poultry | |
North China | 1.28 | 0.15 | 0.17 | 3.12 | 0.01 | |
Northeast China | 1.28 | 0.15 | 0.16 | 1.12 | 0.01 | |
East China | 1.92 | 0.26 | 0.28 | 5.08 | 0.02 | |
Central and Southern China | 1.92 | 0.34 | 0.31 | 5.85 | 0.02 | |
Southwest China | 1.92 | 0.48 | 0.53 | 4.18 | 0.02 | |
Northwest China | 1.28 | 0.28 | 0.32 | 1.38 | 0.01 |
Region | Dairy Cow | Cattle | Buffalo | Horse | Donkey | Mule |
North China | 1.846 | 0.794 | - | 0.330 | 0.188 | 0.188 |
Northeast China | 1.096 | 0.931 | - | 0.330 | 0.188 | 0.188 |
East China | 2.065 | 0.846 | 0.875 | 0.330 | 0.188 | 0.188 |
Central and Southern China | 1.710 | 0.805 | 0.860 | 0.330 | 0.188 | 0.188 |
Southwest China | 1.884 | 0.691 | 1.197 | 0.330 | 0.188 | 0.188 |
Northwest China | 1.447 | 0.545 | - | 0.330 | 0.188 | 0.188 |
Region | Camel | Sheep | Goat | Pig | Poultry | |
North China | 0.330 | 0.093 | 0.093 | 0.227 | 0.007 | |
Northeast China | 0.330 | 0.057 | 0.057 | 0.266 | 0.007 | |
East China | 0.330 | 0.113 | 0.113 | 0.175 | 0.007 | |
Central and Southern China | 0.330 | 0.106 | 0.106 | 0.157 | 0.007 | |
Southwest China | 0.330 | 0.064 | 0.064 | 0.159 | 0.007 | |
Northwest China | 0.330 | 0.074 | 0.074 | 0.195 | 0.007 |
Item | Descriptions |
---|---|
GHG | Greenhouse gas |
AH | Animal husbandry |
CI | Carbon intensity |
LMDI | The logarithmic mean Divisia index |
AHGI | Greenhouse gas emission intensity of animal husbandry sector (in tCO2 eq/104 yuan) |
AHGE | The sum of greenhouse gas emissions from animal husbandry sector (in tCO2 eq) |
AHGDP | Economic output value of animal husbandry sector (104 yuan) |
AHBS | The input of production factors in the animal husbandry sector (it can be replaced with the breeding scale of livestock by converting to standard cattle units) |
AHEE | The animal husbandry environmental efficiency (GHG emissions per unit of livestock) |
AHPE | The animal husbandry productive efficiency (livestock input per unit of AHGDP) |
AHES | The animal husbandry economic share (the provincial proportion of the AHGDP in the national AHGDP) |
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Livestock | Emission Factor | Livestock | Emission Factor | Livestock | Emission Factor |
---|---|---|---|---|---|
Buffalo | 55 | Mule | 10 | Sheep | 5 |
Dairy cow | 61 | Camel | 46 | Goat | 5 |
Cattle | 47 | Horse | 18 | Pig | 1 |
Donkey | 10 |
Livestock | Parameters | Livestock | Parameters | Livestock | Parameters |
---|---|---|---|---|---|
Buffalo | 1.3 | Mule | 1 | Pig | 0.3 |
Dairy cow | 2.6 | Camel | 1.75 | Poultry | 0.01 |
Horse | 0.8 | Goat | 0.2 | ||
Donkey | 0.6 | Sheep | 0.25 |
Province | The Decomposition Results of Three Driving Factors (%) | Province | The Decomposition Results of Three Driving Factors (%) | ||||||
---|---|---|---|---|---|---|---|---|---|
∆AHEE | ∆AHPE | ∆AHES | Total | ∆AHEE | ∆AHPE | ∆AHES | Total | ||
China | −11.78 | −68.17 | 4.70 | −75.25 | Jiangsu | −0.15 | −1.05 | −0.94 | −2.15 |
Henan | −2.17 | −6.93 | 1.99 | −7.11 | Heilongjiang | −0.34 | −3.29 | 1.63 | −2.00 |
Hebei | −0.52 | −4.96 | −0.09 | −5.58 | Qinghai | 0.07 | −1.82 | −0.15 | −1.90 |
Shandong | −1.25 | −4.62 | 0.32 | −5.55 | Shanxi | −0.29 | −1.25 | −0.01 | −1.55 |
Sichuan | −0.47 | −5.67 | 0.85 | −5.29 | Jilin | −0.15 | −1.97 | 0.57 | −1.55 |
Guangxi | −1.17 | −3.40 | −0.23 | −4.81 | Shaanxi | −0.23 | −1.13 | 0.06 | −1.31 |
Hunan | −0.27 | −2.96 | −1.05 | −4.29 | Gansu | 0.02 | −1.36 | 0.10 | −1.25 |
Anhui | −1.43 | −2.54 | −0.27 | −4.24 | Chongqing | −0.16 | −0.58 | −0.38 | −1.12 |
Yunnan | −0.53 | −4.74 | 1.96 | −3.31 | Zhejiang | −0.08 | −0.26 | −0.66 | −1.01 |
Guangdong | −0.26 | −2.08 | −0.88 | −3.23 | Fujian | −0.44 | −0.03 | −0.54 | −1.01 |
Hubei | −0.52 | −2.11 | −0.19 | −2.83 | Hainan | −0.30 | −0.72 | 0.43 | −0.59 |
Guizhou | −0.44 | −2.90 | 0.63 | −2.71 | Shanghai | 0.07 | −0.24 | −0.41 | −0.58 |
Jiangxi | −0.66 | −1.29 | −0.56 | −2.51 | Liaoning | −0.07 | −0.47 | 0.19 | −0.35 |
Tibet | 0.10 | −1.90 | −0.53 | −2.33 | Beijing | 0.04 | −0.11 | −0.27 | −0.34 |
Xinjiang | −0.22 | −3.00 | 0.91 | −2.31 | Ningxia | 0.06 | −0.44 | 0.25 | −0.14 |
Inner Mongolia | 0.02 | −4.14 | 1.86 | −2.26 | Tianjin | −0.02 | −0.20 | 0.16 | −0.06 |
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Cai, T.; Yang, D.; Zhang, X.; Xia, F.; Wu, R. Study on the Vertical Linkage of Greenhouse Gas Emission Intensity Change of the Animal Husbandry Sector between China and Its Provinces. Sustainability 2018, 10, 2492. https://doi.org/10.3390/su10072492
Cai T, Yang D, Zhang X, Xia F, Wu R. Study on the Vertical Linkage of Greenhouse Gas Emission Intensity Change of the Animal Husbandry Sector between China and Its Provinces. Sustainability. 2018; 10(7):2492. https://doi.org/10.3390/su10072492
Chicago/Turabian StyleCai, Tianyi, Degang Yang, Xinhuan Zhang, Fuqiang Xia, and Rongwei Wu. 2018. "Study on the Vertical Linkage of Greenhouse Gas Emission Intensity Change of the Animal Husbandry Sector between China and Its Provinces" Sustainability 10, no. 7: 2492. https://doi.org/10.3390/su10072492