Analysis of Evolution Characteristics and Driving Factors of Carbon Emission from Animal Husbandry in Shandong Province

doi:10.13304/j.nykjdb.2024.0827

Abstract

Abstract:

The evolution characteristics and driving factors of carbon emissions from animal husbandry in Shandong province were analyzed by using the life-cycle assessment method and the generalized divisia index method. The results showed that the total carbon emissions from animal husbandry in Shandong province decreased from 6 360.91×10⁴ t in 2011 to 5 576.21×10⁴ t in 2022， with an average annual growth rate of -1.19%. The proportion of carbon emissions from enteric fermentation and manure management gradually decreased， and the proportion of feed consumption system in 2019 exceeded that of gastrointestinal fermentation and manure management system， and becomed the most important source of carbon emissions. In terms of livestock species， poultry carbon emissions accounted for the largest share， and the total amount of poultry carbon emissions showed growing trend. From the perspective of spatial and temporal series， Linyi， Weifang and Heze had larger total carbon emissions， while Tai’an， Qingdao and Jining had lower carbon intensity. In terms of comprehensive driving factors， the carbon intensity of total mechanical power consumption and carbon intensity of economic output were the main contributing factors， and the contributing effect of the intensity of total mechanical power consumption was relatively low. Above results showed that adjusting the industrial structure and improving the efficiency and effectiveness of livestock and poultry production were effective way to improve the resource utilization efficiency of the livestock industry in the future， and improving the efficiency of livestock machinery while introducing advanced and low-carbon livestock machinery and equipment was an important direction for the green development of the animal husbandry industry in Shandong province in the future.

Key words: animal husbandry, carbon emission, life-cycle assessment, generalized divisia index method, driving factor

摘要：

运用生命周期评价法和广义迪氏分解法，对山东省畜牧业碳排放的演变特征以及驱动因素进行分析。结果表明，2011—2022年山东省畜牧业碳排放总量由6 360.91万 t下降到5 576.21万 t，年均增长率为-1.19%。其中肠道发酵和粪便管理系统碳排放量的占比逐渐减少，2019年饲料消耗系统的占比超过胃肠发酵与粪便管理系统，成为最主要的碳排放来源。从畜种来看，禽碳排放占比最大，且其碳排放总量呈增长趋势。从时空序列来看，临沂、潍坊、菏泽的碳排放总量较大，泰安、青岛和济宁的碳排放强度较低。综合驱动因素来看，机械总动力消耗碳强度及经济产出碳强度是主要的促降因素，机械总动力消耗强度的促降效应相对较低。综上表明，调整产业结构、提高畜禽生产效率和效益是未来畜牧业提高资源利用效率的有效途径；在引进先进低碳畜牧业机械设备的同时，提高畜牧机械利用效率是未来山东省畜牧业绿色发展的重要方向。

关键词: 畜牧业, 碳排放, 生命周期评价法, 广义迪氏指数, 驱动因素

CLC Number:

F326.3

Xiao WANG, Xiangfei XIN, Yan YAN, Jimin WANG. Analysis of Evolution Characteristics and Driving Factors of Carbon Emission from Animal Husbandry in Shandong Province[J]. Journal of Agricultural Science and Technology, 2025, 27(8): 155-167.

王潇, 辛翔飞, 闫琰, 王济民. 山东省畜牧业碳排放演变特征及驱动因素分析[J]. 中国农业科技导报, 2025, 27(8): 155-167.

Figures/Tables 10

Fig. 1 Carbon emission system of animal husbandry in Shandong provinceNote： CO2 is also produced during manure accumulation and anaerobic degradation， but is not included in the methodology.

Table 1 Carbon emission coefficient of enteric fermentation and manure management of each animal species

物种 Species	肠道发酵 Enteric fermentation	粪便管理 Manure management		参考来源 Reference source
物种 Species	CH₄	CH₄	N₂O	参考来源 Reference source
猪Swine	1.000	3.50	0.53	［13］
禽Poultry	0.000	0.02	0.02	［13］
牛Cattle	55.000	2.00	1.34	［28］
羊Sheep	5.000	0.16	0.33	［13］
兔Rabbit	0.254	0.08	0.02	［13］

Table 2 Carbon emission coefficient of each system by the life cycle assessment method

系统边界 System boundary	符号 Sign	指标 Index	值 Value	参考来源 Reference source
饲料粮种植消耗 Feed and grain planting consumption	e_j1	小麦碳排放系数 Carbon emission coefficient of wheat	1.22	［16］
饲料粮种植消耗 Feed and grain planting consumption	e_j1	玉米碳排放系数 Carbon emission coefficient of corn	1.5
饲料粮加工消耗 Feed and grain processing consumption	e_j2	小麦碳排放系数 Carbon emission coefficient of wheat	0.031 9
		玉米碳排放系数 Carbon emission coefficient of corn	0.010 2
		大豆碳排放系数 Carbon emission coefficient of soybean	0.101 3
畜禽饲养消耗 Livestock and poultry feeding consumption	price_e	畜禽养殖用电单价/（元·kW^-1·h^-1）Unit price of livestock and poultry breeding electricity consumption/（yuan·kW^-1·h^-1）	0.427 5	［17］
	price_c	畜禽养殖用煤单价/（元·t^-1） Unit price of coal used for livestock and poultry breeding/（yuan·t^-1）	800	［17］
	e_f	电能消耗碳排放系数 Carbon emission coefficient of electricity consumption/（t·MW^-1·t^-1）	0.971 4	［29］
	e_c	煤炭消耗碳排放系数 Carbon emission coefficient of coal consumption	1.98	［17］
畜禽加工消耗 Consumption of livestock and poultry processing	MJ _u	牛肉屠宰加工耗能系数 Energy consumption coefficient of beef slaughtering and processing/（MJ·kg^-1）	4.37	［16］
		猪肉屠宰加工耗能系数 Energy consumption coefficient of pork slaughtering and processing/（MJ·kg^-1）	3.76
		羊肉屠宰加工耗能系数 Energy consumption coefficient of mutton slaughtering and processing/（MJ·kg^-1）	10.4
		禽肉屠宰加工耗能系数 Energy consumption coefficient of poultry slaughtering and processing/（MJ·kg^-1）	2.59
		禽蛋屠宰加工耗能系数Energy consumption coefficient of poultry egg slaughtering and processing/（MJ·kg^-1）	8.16

Table 2 Carbon emission coefficient of each system by the life cycle assessment method

系统边界

System boundary

符号

Sign

指标

Index

值

Value

参考来源

Reference source

畜禽加工消耗

Consumption of livestock and poultry processing

MJ _u

牛奶屠宰加工耗能系数

Energy consumption coefficient of milk slaughtering and processing/（MJ·kg^-1）

1.12

［16］

单位电热值

Unit electric heat value

3.6

其他转换系数

Other conversion coefficients

G W H C H 4

CH₄全球升温潜能值

CH₄ global warming potential value

［14］

G W H N 2 O

N₂O全球升温潜能值

N₂O global warming potential value

310

Table 2 Carbon emission coefficient of each system by the life cycle assessment method

系统边界

System boundary

符号

Sign

指标

Index

值

Value

参考来源

Reference source

畜禽加工消耗

Consumption of livestock and poultry processing

MJ _u

牛奶屠宰加工耗能系数

Energy consumption coefficient of milk slaughtering and processing/（MJ·kg^-1）

1.12

［16］

单位电热值

Unit electric heat value

3.6

其他转换系数

Other conversion coefficients

G W H C H 4

CH₄全球升温潜能值

CH₄ global warming potential value

［14］

G W H N 2 O

N₂O全球升温潜能值

N₂O global warming potential value

310

Fig. 2 Total carbon emission of Shandong province from 2011 to 2022Note： Because the carbon emissions of feed processing and livestock and poultry breeding are relatively small and negligible from other carbon emission sources， they are not listed in the figure.

Fig. 3 Total carbon emission of all livestock breeds in Shandong province from 2011 to 2022Note： Because rabbits have carbon emissions of rabit is relatively low， and is it negligible to other livestock species， it is not listed in the figure.

Fig. 4 Spatial distribution diagram of carbon emission from animal husbandry in Shandong provinceNote：Based on the standard map GS（2024）1158 of the National Resources Ministry’s standard map service website， the base map has not been modified.

Fig. 5 Spatial distribution diagram of carbon emission intensity in animal husbandry in Shandong provinceNote：Based on the standard map GS（2024）1158 of the National Resources Ministry’s standard map service website， the base map has not been modified.

Table 3 Contribution rate of carbon emission drivers of animal husbandry in Shandong Province from 2012 to 2022

年份 Year	经济发展水平 Level of economic development	经济产出碳强度 Carbon intensity of economic output	机械总动力水平 Total prime mover power capacity	机械总动力消耗碳强度 Carbon intensity per unit of prime Mover power consumption	人口规模 Population size	人均碳排放量 Per capita carbon intensity	人均产值 Per capita output	机械总动力消耗强度 Prime mover power consumption intensity
2012	0.009 0	0.000 7	0.033 5	-0.022 7	0.001 5	0.008 3	-0.000 2	-0.001 0
2013	0.011 7	-0.013 9	0.041 6	-0.041 3	0.001 3	-0.003 3	-0.000 3	-0.001 5
2014	0.003 2	-0.007 8	0.004 5	-0.009 1	0.002 1	-0.006 8	0.000 0	0.000 0
2015	0.007 4	-0.017 1	0.004 4	-0.014 3	0.001 9	-0.011 8	0.000 0	0.000 0
2016	0.014 1	-0.025 0	0.006 0	-0.017 4	0.003 5	-0.015 0	-0.000 1	-0.000 1
2017	-0.010 0	0.008 8	0.006 8	-0.008 2	0.002 0	-0.003 5	-0.000 1	-0.000 4
2018	-0.016 7	0.003 6	0.008 0	-0.021 1	0.001 4	-0.014 9	-0.000 4	-0.000 9
2019	-0.012 8	0.008 4	0.020 6	-0.024 5	0.001 0	-0.006 0	-0.000 1	-0.001 7
2020	0.011 7	-0.042 0	0.0158	-0.045 9	0.001 8	-0.032 7	-0.000 2	0.000 0
2021	0.038 3	-0.015 1	0.055 6	-0.031 4	0.000 2	0.023 2	-0.002 6	-0.000 7
2022	0.005 6	-0.000 1	0.013 0	-0.007 2	-0.000 2	0.005 8	-0.000 1	-0.000 1

Fig. 6 Cumulative contribution values of the factors affecting carbon emissions in Shandong Province from 2012 to 2022Note： The cumulative contribution value is based on 2011， and the contribution value of each factor to the carbon emission of animal husbandry in Shandong province is added up year by year.

References 35

[1]	SUBSCRIBE H, CONTACT A, FOCUS T, et al.. Growing greenhouse gas emissions due to meat production [J]. Environ. Dev., 2013, 5: 156-163.
[2]	GERBER P J, STEINFELD H, HENDERSON B, et al.. Tackling Climate Change Through Livestock——A Global Assessment of Emissions and Mitigation Opportunities [M]. Rome: FAO, 2013:1-256.
[3]	中华人民共和国国家统计局.中国统计年鉴2022 [M].北京:中国统计出版社, 2022: 1-936.
[4]	LIU G, MÜLLER D B. Addressing sustainability in the aluminum industry: a critical review of life cycle assessments [J]. J. Clean. Prod., 2012, 35: 108-117.
[5]	马于清,曹丁戈,罗文海,等.基于生命周期的我国畜禽养殖业碳排放核算[J].中国环境科学, 2024, 44(5): 2799-2810.
	MA Y Q, CAO D G, LUO W H, et al.. The evaluation of the livestock and poultry production of carbon emissions in China based on life cycle assessment [J]. China Environ. Sci., 2024, 44(5): 2799-2810.
[6]	AKIFUMI O, KAZATO O, AKIRA S, et al.. Life cycle assessment of sustainable broiler production systems: effects of low-protein diet and litter incineration [J/OL]. Agriculture, 2021, 11(10): 921 [2024-09-20]. .
[7]	ROSEN R A. Is the ipcc’s 5^THASSESSMENT a denier of possible macroeconomic benefits from mitigating climate change? [J/OL]. Clim. Change Econ., 2016, 7(1): 1640003 [2024-09-20]. .
[8]	梁耀文,王明利.中国生猪产业碳排放经验解构与动态达峰路径选择[J].农业经济问题, 2023, 44(10): 101-115.
	LIANG Y W, WANG M L. Deconstructing the experience of China’s pig industry carbon emissions and choosing a dynamic path to peak [J]. Issu. Agric. Econ., 2023, 44(10): 101-115.
[9]	LESSCHEN J P, VAN DEN BERG M, WESTHOEK H J, et al.. Greenhouse gas emission profiles of European livestock sectors [J]. Anim. Feed. Sci. Technol., 2011, 166: 16-28.
[10]	HENDERSON B, GODDE C, MEDINA-HIDALGO D, et al.. Closing system-wide yield gaps to increase food production and mitigate GHGs among mixed crop-livestock smallholders in Sub-Saharan Africa [J]. Agric. Syst., 2016, 143: 106-113.
[11]	熊学振,韩振,孙雨萌,等.中国畜产品进口格局及其资源环境效应研究[J].自然资源学报, 2023, 38(5): 1378-1392.
	XIONG X Z, HAN Z, SUN Y M, et al.. Study of China's animal products import pattern and its resource and environmental effects [J]. J. Nat. Resour., 2023, 38(5): 1378-1392
[12]	LI S, QIN Y, SUBBIAH J, et al.. Life cycle assessment of the U.S. beef processing through integrated hybrid approach [J/OL]. J. Clean. Prod., 2020, 265: 121813 [2024-09-20]. .
[13]	胡向东,王济民.中国畜禽温室气体排放量估算[J].农业工程学报, 2010, 26(10): 247-252.
	HU X D, WANG J M. Estimation of livestock greenhouse gases discharge in China [J]. Trans. Chin. Soc. Agric. Eng., 2010, 26(10): 247-252.
[14]	吴强,张园园,张明月.中国畜牧业碳排放的量化评估、时空特征及动态演化:2001—2020[J].干旱区资源与环境, 2022, 36(6): 65-71.
	WU Q, ZHANG Y Y, ZHANG M Y. Quantitative assessment, temporal and spatial characteristics and dynamic evolution of China’s animal husbandry carbon emissions [J]. J. Arid Land Resour. Environ., 2022, 36(6): 65-71.
[15]	孟祥海,程国强,张俊飚,等.中国畜牧业全生命周期温室气体排放时空特征分析[J].中国环境科学, 2014,3 4(8): 2167-2176.
	MENG X H, CHENG G Q, ZHANG J B, et al.. Analyze on the spatialtemporal characteristics of GHG estimation of livestock's by life cycle assessment in China [J]. China Environ. Sci., 2014, 34(8): 2167-2176.
[16]	姚成胜,钱双双,李政通,等.中国省际畜牧业碳排放测度及时空演化机制[J].资源科学, 2017, 39(4): 698-712.
	YAO C S, QIAN S S, LI Z T, et al.. Provincial animal husbandry carbon emissions in China and temporal-spatial evolution mechanism [J]. Resour. Sci., 2017, 39(4): 698-712.
[17]	戴小文,李金花,何艳秋,等.2000—2020年中国畜牧业区域碳排放公平性与排放效率[J].资源科学, 2023, 45(1): 62-76.
	DAI X W, LI J H, HE Y Q, et al.. Regional equity and efficiency of carbon emissions of China's livestock industry in 2000—2020 [J]. Resour. Sci., 2023, 45 (1): 62-76.
[18]	何小田.山东省农业碳排放时空特征及趋势预测[J].黑龙江粮食, 2023(8): 124-126.
[19]	曹海琳.山东省畜牧业碳排放测算及影响因素研究[D].长春:吉林农业大学,2023.
[20]	陈苏,胡浩.中国畜禽温室气体排放时空变化及影响因素研究[J].中国人口·资源与环境, 2016, 26(7): 93-100.
	CHEN S, HU H. Study on the spatial-temporal changes and influence factors of greenhouse gases emission from livestock and poultry in China [J]. China Popul. Resour. Environ., 2016, 26(7): 93-100.
[21]	尚莉媛,崔姹,赵慧峰.京津冀畜牧业碳排放效率时空演变特征及影响因素分析[J].中国农业资源与区划, 2023, 44(12): 190-199.
	SHANG L Y, CUI C, ZHAO H F. Spatial-temporal evolution characteristics and influencing factors of carbon emission efficiency of animal husbandry in Beijing-Tianjin-Hebei region [J]. Chin. J. Agric. Res. Region. Plan., 2023, 44(12):190-199.
[22]	白雪冰,胡浩,周应恒,等.中国畜牧业碳排放的时空演进及其影响因素分析[J].中国农业大学学报, 2023, 28(9): 260-274.
	BAI X B, HU H, ZHOU Y H, et al.. Study on space-time evolution and influence factors of carbon emissions in China's animal husbandry [J]. J. China Agric. Univ., 2023, 28(9):260-274.
[23]	HE D, DENG X, WANG X, et al.. Livestock greenhouse gas emission and mitigation potential in China [J/OL]. J. Environ. Manage., 2023, 348: 119494 [2024-09-20]. .
[24]	闫庆友,尹洁婷.基于广义迪氏指数分解法的京津冀地区碳排放因素分解[J].科技管理研究, 2017, 37(19): 239-245.
	YAN Q Y, YIN J T. Factor decomposition of carbon emissions in Beijing, Tianjin, Hebei: a study based on generalized divisia index method [J]. Sci. Technol. Manage. Res., 2017, 37(19): 239-245.
[25]	VANINSKY A. Factorial decomposition of CO₂ emissions: a generalized divisia index approach [J]. Energy Econ., 2014, 45: 389-400.
[26]	邵帅, 张曦, 赵兴荣.中国制造业碳排放的经验分解与达峰路径:广义迪氏指数分解和动态情景分析[J].中国工业经济,2017(3): 44-63.
	SHAO S, ZHANG X, ZHAO X R. Empirical decomposition and peaking pathway of carbon dioxide emissions of China's manufacturing sector: generalized divisia index method and dynamic scenario analysis [J]. China Ind. Econ., 2017(3): 44-63.
[27]	谢鸿宇,陈贤生,杨木壮,等.中国单位畜牧产品生态足迹分析[J].生态学报, 2009, 29(6): 3264-3270.
	XIE H Y, CHEN X S, YANG M Z, et al.. The ecological footprint analysis of 1kg livestock product of China [J]. Acta Ecol. Sin., 2009, 29(6): 3264-3270.
[28]	陈胜涛,张开华,张岳武.农业碳排放绩效的测量与脱钩效应[J].统计与决策, 2021, 37(22): 85-88.
[29]	全国温室气体自愿减排注册登记系统及信息平台.2021年度减排项目中国区域电网基准线排放因子[EB/OL].(2023-11-17)[2024-09-20]..
[30]	GARNIER J, LE NOË J, MARESCAUX A, et al.. Long-term changes in greenhouse gas emissions from French agriculture and livestock (1852—2014): from traditional agriculture to conventional intensive systems [J]. Sci. Total Environ., 2019, 660: 1486-1501.
[31]	胡川,韦院英,胡威.农业政策、技术创新与农业碳排放的关系研究[J].农业经济问题, 2018, 39(9): 66-75.
	HU C, WEI Y Y, HU W. Research on the relationship between agricultural policy, technological innovation and agricultural carbon emissions [J]. Issues Agric. Econ., 2018, 39(9): 66-75.
[32]	汪开英,李鑫,陆建定,等.碳中和目标下畜牧业低碳发展路径[J].农业工程学报, 2022, 38(1): 230-238.
	WANG K Y, LI X, LU J D, et al.. Low-carbon development strategies of livestock industry to achieve goal of carbon neutrality in China [J]. Trans. Chin. Soc. Agric. Eng., 2022, 38(1): 230-238.
[33]	励汀郁,王明利.畜牧业助力"双碳"目标实现路径研究:基于不同国家的经验比较与启示[J].世界农业, 2023(1): 5-16.
	LI T Y, WANG M L. Research on the realization path of carbon peaking and carbon neutrality goals assisted by animal husbandry: based on the experience comparison and enlightenment of different countries [J]. World Agric., 2023(1): 5-16.
[34]	辛翔飞,王潇,王济民.肉鸡产业高质量发展:问题挑战、趋势研判及政策建议[J].中国家禽, 2024, 46(1): 1-10.
	XIN X F, WANG X, WANG J M. High-quality development of broiler industry: challenges, trend and policy [J]. China Poult., 2024, 46(1): 1-10.
[35]	农业农村部,财政部. 2024—2026 年农机购置与应用补贴实施意见[EB/OL]. (2024-04-22)[2024-09-20]..