吉林省农业碳排放测度分析及影响因素研究

doi:10.3969/j.issn.2097-0706.2023.08.005

摘要/Abstract

摘要：

为践行我国对世界做出的“双碳”承诺，促进农业“碳减排”，精准测算农业碳排放总量及其时序变化规律、研究影响农业碳排放因素至关重要。以吉林省2000 —2021年的农业生产要素投入数据为基础，采用碳排放系数法对农业碳排放进行测算，以对数平均迪氏（LMDI）分解法分析农业碳排放的影响因素，对其影响机制进行深入剖析。阐述吉林省农业碳排放的时序变化规律及碳排放的影响因素，为吉林省农业碳排放“减排”“降碳”提供可行性政策建议。研究认为，为促进吉林省农业碳减排战略的实施，应注意发展精准农业，严格要素投入数量；完善秸秆资源多样化利用，“变废为宝”；加大农业机械化投入力度，加强劳动技能培训；强化农机改造，提高农业电气化水平；建立农业生产全过程数字化产业链，以“数字化”促进“低碳化”。

关键词: 碳减排, 碳排放, 时序效应, LMDI模型

Abstract:

To fulfil China's"dual carbon"commitment，it is crucial to alleviate and accurately calculate the carbon emissions from agriculture industry，and study the temporal variation and influencing factors of the carbon emissions.The agricultural carbon emissions are measured by emission coefficient method with agricultural production factors of Jilin province from 2000 to 2021 as the input data.And the influencing factors of agricultural carbon emissions are analysed by Logarithmic Mean Divisia Index（LMDI），and the influencing mechanism is studied intensively，based on which the feasible carbon reduction policy was recommended for Jilin province.The study suggests that，to implement the agricultural carbon reduction strategy in Jilin province， refined management should be executed on agriculture industry，for example，strictly control on the input quantity of factors of production. Furthermore，agriculture wastes，such as straws，should be turned into resources by diversified methods.And the investment in agricultural mechanization and skilled labour training should be increased.A full-process digital industrial chain is being establishing based on the agricultural electrification and updating of agricultural machinery，so as to drive the low-carbon development through digitization of agriculture industry.

Key words: dual carbon, carbon emissions, clocking effect, LMDI model

中图分类号:

TK01

李菲菲, 徐绘薇, 王舒泓, 崔金栋. 吉林省农业碳排放测度分析及影响因素研究[J]. 综合智慧能源, 2023, 45(8): 36-43.

LI Feifei, XU Huiwei, WANG Shuhong, CUI Jindong. Measurement analysis on carbon emissions from agriculture industry in Jilin province and the influencing factors[J]. Integrated Intelligent Energy, 2023, 45(8): 36-43.

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碳源			排放系数	文献
种植业	农资投入/（kg CO₂·kg^-1)	化肥	0.895 6	[14]
		农药	4.934 1	[14]
		农膜	5.18	[15]
	农田管理/ [kg CO₂·（hm²)^-1]	柴油	0.592 7	[16]
		灌溉	266.48	[17]
		翻耕	3.126	[18]
畜牧业	肠道发酵(CH₄)/ (kg·head·a)^-1	牛	80.46	省级温室气体清单编制指南（试行）
		羊	8.23
		猪	1
		家禽	-
	粪便管理(CH₄,NO₂)/ (kg·head·a)^-1	牛	5.14,1.29	省级温室气体清单编制指南（试行）
		羊	0.16,0.227
		猪	3.12,0.093
		家禽	0.02,0.007

项目	玉米	小麦	水稻
草谷比	2.0	1.366	0.623
秸秆露天焚烧比例	13.5	12.7	18.1
秸秆露天焚烧排放系数/CH₄	4.4	3.4	3.2
秸秆露天焚烧排放系数/CO₂	1 350	1 460	1 460
燃烧效率	0.92	0.93	0.93

年份	水稻种植		牲畜养殖		农地利用		秸秆焚烧		碳排放总量/万t
年份	碳排放量/万t	占比/%	碳排放量/万t	占比/%	碳排放量/万t	占比/%	碳排放量/万t	占比/%	碳排放总量/万t
2000	11.33	4.78	4.05	1.71	181.92	76.85	39.43	16.66	236.72
2001	10.89	4.12	4.32	1.63	198.89	75.17	50.50	19.09	264.60
2002	15.59	5.61	4.18	1.50	200.56	72.19	57.49	20.69	277.82
2003	12.66	4.47	4.72	1.66	206.69	72.97	59.18	20.89	283.24
2004	14.04	4.24	4.94	1.49	244.82	73.90	67.48	20.37	331.28
2005	15.30	4.83	5.19	1.64	228.10	71.99	68.25	21.54	316.84
2006	15.54	4.59	5.63	1.66	243.14	71.84	74.15	21.91	338.46
2007	15.68	4.53	6.24	1.80	256.59	74.18	67.40	19.49	345.91
2008	15.41	4.13	6.79	1.82	270.57	72.50	80.41	21.55	373.18
2009	15.45	4.14	4.58	1.23	284.50	76.30	68.35	18.33	372.88
2010	15.76	4.02	4.40	1.12	295.86	75.53	75.71	19.33	391.74
2011	16.18	3.80	4.15	0.98	315.22	74.09	89.91	21.13	425.46
2012	16.41	3.64	4.21	0.94	330.41	73.36	99.34	22.06	450.37
2013	17.00	3.61	4.25	0.90	341.51	72.43	108.74	23.06	471.50
2014	17.48	3.66	4.20	0.88	346.32	72.47	109.89	23.00	477.90
2015	17.82	3.60	4.36	0.88	357.57	72.25	115.12	23.26	494.89
2016	18.72	3.73	3.28	0.65	359.37	71.61	120.47	24.01	501.85
2017	19.21	3.82	3.35	0.67	360.66	71.74	119.49	23.77	502.72
2018	19.65	4.11	3.24	0.68	351.76	73.52	103.79	21.69	478.43
2019	19.67	4.08	3.26	0.67	347.42	72.00	112.21	23.25	482.55
2020	19.59	4.11	3.02	0.63	344.00	72.19	109.94	23.07	476.55
2021	19.59	4.09	3.55	0.74	338.60	70.61	117.78	24.56	479.52

年份	ΔC_EI	ΔC_SI	ΔC_EL	ΔC_P	ΔC_tot
2001—2000	-9.44	-0.02	32.15	-0.37	22.32
2002—2001	-2.84	-11.02	9.44	6.68	2.27
2003—2002	-13.50	0.64	15.80	5.50	8.44
2004—2003	-4.38	3.61	51.81	0.89	51.92
2005—2004	-57.74	-0.96	28.98	6.80	-22.92
2006—2005	4.70	-2.28	15.28	3.21	20.91
2007—2006	-45.40	2.63	56.79	4.40	18.43
2008—2007	-35.23	0.73	48.13	5.42	19.06
2009—2008	7.27	-6.65	12.07	6.05	18.74
2010—2009	1.58	-2.65	10.45	5.58	14.96
2011—2010	-50.49	1.28	66.98	8.11	25.88
2012—2011	-9.71	-1.31	29.93	1.70	20.61
2013—2012	-5.91	1.59	16.53	3.01	15.22
2014—2013	2.78	-1.45	4.30	1.02	6.64
2015—2014	17.53	-0.06	-3.63	1.71	15.55
2016—2015	32.56	-2.10	-22.45	-5.51	2.50
2017—2016	28.92	-2.52	-17.60	-6.99	1.80
2018—2017	-41.76	1.77	35.75	-8.03	-12.26
2019—2019	-64.64	4.96	62.79	-9.07	-5.96
2020—2019	-105.25	5.82	107.92	-13.23	-4.74
2021—2020	-3.75	-3.22	18.70	-19.29	-7.56
总量	-354.69	-11.21	580.13	-2.42	211.81