广东省种植业碳排放的测算及趋势预测

doi:10.11924/j.issn.1000-6850.casb2023-0796

摘要/Abstract

摘要：

为明确广东省种植业的碳排放特征及其与农业经济增长的脱钩状态，预测2022—2060年种植业碳排放趋势，为广东省制定农业减排增汇政策提供理论依据。基于农业物质投入和农田土壤利用两大类碳源，采用IPCC（政府间气候变化专门委员会）碳排放系数法，测算广东省1990—2021年种植业碳排放量、碳汇量、净碳排放量、碳排放强度、净碳排放强度，分析其动态演变趋势，运用Tapio脱钩模型分析种植业碳排放与农业经济增长的脱钩关系，并利用灰色预测模型GM (1，1)，预测2022—2060年广东省种植业碳排放量、净碳排放量。结果表明：（1）1990—2021年广东省种植业碳排放量、净碳排放量总体均呈波动下降趋势，下降幅度分别为25.23%、30.58%，排放构成方面，农田土壤利用碳排放量占比为63.94%~79.69%，农业物质投入碳排放量占比为20.31%~36.06%，化肥、农药、农膜是农业物质投入碳排放的前三来源，水稻、蔬菜种植是主要的农田土壤利用碳排放源；（2）1990—2021年广东省种植业碳汇量在波动中下降，下降幅度为22.23%，碳汇主要来源于稻谷、甘蔗和蔬菜，三者碳汇量占比为87.23%~94.03%；（3）1990—2021年广东省以农业产值为单位的碳排放强度、净碳排放强度均显著下降，下降幅度分别达93.20%、93.69%；（4）广东省种植业碳排放、净碳排放与农业经济的脱钩状态以强脱钩和弱脱钩为主，农业经济增长与种植业碳排放的协调状态较好；（5）以1991—2021、2001—2021、2011—2021年的数据为样本进行预测，均发现广东省种植业碳排放量、净碳排放量在2022年后呈持续降低趋势，但降低幅度有所不同，以2011—2021年数据为样本的预测值最小、降低幅度最大。基于此，提出持续实施化肥、农药、农膜减量增效措施，优化稻田管理，强化农业绿色低碳发展科技支撑等政策建议。

关键词: 广东省, 种植业碳排放, 种植业碳汇, Tapio脱钩模型, 碳排放预测

Abstract:

The study aims to clarify the carbon emission characteristics of planting industry in Guangdong Province and its decoupling status from agricultural economic growth, predict the carbon emission trend from 2022 to 2060, and provide theoretical basis for the formulation of agricultural carbon emission reduction and sink increase policies in Guangdong Province. Using the carbon emission coefficient method of IPCC (Intergovernmental Panel on Climate Change), this paper calculated the carbon emissions, carbon sinks, net carbon emissions, carbon emission intensity, and net carbon emission intensity of the planting industry in Guangdong Province from 1990 to 2021, based on two major types of carbon sources of agricultural material inputs and farmland soil utilization, then analyzed their dynamic evolution trends. The decoupling relationship between carbon emissions and agricultural economic growth was discussed by the Tapio decoupling model, the carbon emissions and net carbon emissions from 2022 to 2060 were predicted as well by the Grey prediction model GM (1, 1). The results showed that: (1) from 1990 to 2021, the total amount and net amount of carbon emissions of planting industry in Guangdong Province both showed fluctuating downward trend, with decrease of 25.23% and 30.58%, respectively. The carbon emissions from farmland soil utilization accounted for 63.94% to 79.69%, while the carbon emissions from agricultural material inputs accounted for 20.31% to 36.06%. Fertilizer, pesticides and agricultural film were the top three sources of carbon emissions from agricultural inputs, while rice planting and vegetable planting were the main sources of carbon emissions from farmland soil utilization. (2) From 1990 to 2021, the carbon sink decreased in fluctuation, with decrease of 22.23%. The carbon sink mainly came from rice, sugarcane, and vegetables plants, with the proportion of 87.23%-94.03%. (3) From 1990 to 2021, the carbon emission intensity and net carbon emission intensity in Guangdong Province measured by agricultural output value, significantly decreased by 93.20% and 93.69%, respectively. (4) The decoupling statuses were dominated by weak decoupling and strong decoupling, indicating good coordination between agricultural economic growth and carbon emissions from planting industry. (5) Using the data from 1991 to 2021, 2001 to 2021, 2011 to 2021 as samples for prediction, respectively, it was found that the carbon emissions and net carbon emissions of planting industry in Guangdong Province would both show continuous decreasing trend after 2022, but the reduction amplitude values were different. The prediction value of carbon emissions using the data from 2011 to 2021 as samples was the smallest and the reduction amplitude was the largest. Based on the above conclusions, this paper put forward relevant policy recommendations such as continuously implementing measures to reduce the amount and increase the efficiency of fertilizers, pesticides, and agricultural films, optimizing rice field management, and strengthening scientific and technological support for green and low-carbon agricultural development.

Key words: Guangdong Province, carbon emissions from planting industry, carbon sink of planting industry, Tapio decoupling model, carbon emission prediction

储霞玲, 叶高松, 郑林秀. 广东省种植业碳排放的测算及趋势预测[J]. 中国农学通报, 2024, 40(23): 81-91.

CHU Xialing, YE Gaosong, ZHENG Linxiu. Calculation and Trend Prediction of Carbon Emissions from Planting Industry in Guangdong Province[J]. Chinese Agricultural Science Bulletin, 2024, 40(23): 81-91.

图/表 9

参考文献 32

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作物	经济系数	含水率/%	碳吸收率/[g (C)/g]
稻谷	0.45	12	0.414
玉米	0.40	13	0.471
豆类	0.34	13	0.450
花生	0.43	10	0.450
薯类	0.70	70	0.423
甘蔗	0.50	50	0.450
蔬菜	0.60	90	0.450

作物	经济系数	含水率/%	碳吸收率/[g (C)/g]
稻谷	0.45	12	0.414
玉米	0.40	13	0.471
豆类	0.34	13	0.450
花生	0.43	10	0.450
薯类	0.70	70	0.423
甘蔗	0.50	50	0.450
蔬菜	0.60	90	0.450

年份	农业物质投入		农田土壤利用		碳排放量/ (×10⁴ t)	种植业碳汇量/ (×10⁴ t)	种植业净碳排放量/ (×10⁴ t)
年份	碳排放量/(×10⁴ t)	占比/%	碳排放量/(×10⁴ t)	占比/%	碳排放量/ (×10⁴ t)	种植业碳汇量/ (×10⁴ t)	种植业净碳排放量/ (×10⁴ t)
1990	804.80	20.31	3157.97	79.69	3962.78	2569.91	1392.86
1995	895.88	24.52	2757.17	75.48	3653.06	2292.99	1360.06
2000	833.19	25.01	2497.74	74.99	3330.94	2214.28	1116.65
2005	942.50	29.59	2242.58	70.41	3185.08	1824.05	1361.03
2010	1096.41	34.64	2069.06	65.36	3165.47	1877.91	1287.56
2015	1093.23	34.86	2042.68	65.14	3135.91	2055.37	1080.54
2020	1000.36	33.46	1989.12	66.54	2989.48	2001.14	988.34
2021	968.42	32.69	1994.43	67.31	2962.85	1995.98	966.86
增长率/%	20.33	60.94	-36.84	-15.53	-25.23	-22.33	-30.58

年份	农业物质投入		农田土壤利用		碳排放量/ (×10⁴ t)	种植业碳汇量/ (×10⁴ t)	种植业净碳排放量/ (×10⁴ t)
年份	碳排放量/(×10⁴ t)	占比/%	碳排放量/(×10⁴ t)	占比/%	碳排放量/ (×10⁴ t)	种植业碳汇量/ (×10⁴ t)	种植业净碳排放量/ (×10⁴ t)
1990	804.80	20.31	3157.97	79.69	3962.78	2569.91	1392.86
1995	895.88	24.52	2757.17	75.48	3653.06	2292.99	1360.06
2000	833.19	25.01	2497.74	74.99	3330.94	2214.28	1116.65
2005	942.50	29.59	2242.58	70.41	3185.08	1824.05	1361.03
2010	1096.41	34.64	2069.06	65.36	3165.47	1877.91	1287.56
2015	1093.23	34.86	2042.68	65.14	3135.91	2055.37	1080.54
2020	1000.36	33.46	1989.12	66.54	2989.48	2001.14	988.34
2021	968.42	32.69	1994.43	67.31	2962.85	1995.98	966.86
增长率/%	20.33	60.94	-36.84	-15.53	-25.23	-22.33	-30.58

年份	ΔCO₂/CO₂	NetΔCO₂/CO₂	ΔGDP/GDP	e₁	碳排放脱钩状态	e₂	净碳排放脱钩状态
1990	—	—	—	—	—	—	—
1991	-0.009	-0.078	0.082	-0.105	强脱钩	-0.955	强脱钩
1992	-0.054	-0.147	0.103	-0.527	强脱钩	-1.428	强脱钩
1993	-0.058	0.189	0.134	-0.434	强脱钩	1.408	扩张负脱钩
1994	0.039	0.160	0.291	0.133	弱脱钩	0.549	弱脱钩
1995	0.005	-0.099	0.238	0.020	弱脱钩	-0.415	强脱钩
1996	0.000	-0.041	0.062	0.001	弱脱钩	-0.670	强脱钩
1997	-0.019	-0.182	0.031	-0.611	强脱钩	-5.849	强脱钩
1998	-0.004	-0.049	0.012	-0.323	强脱钩	-3.901	强脱钩
1999	-0.029	0.117	-0.003	10.995	衰退脱钩	-43.750	强负脱钩
2000	-0.038	-0.015	-0.060	0.638	衰退连接	0.241	弱负脱钩
2001	0.033	0.178	0.012	2.653	扩张负脱钩	14.334	扩张负脱钩
2002	-0.091	-0.136	0.029	-3.112	强脱钩	-4.685	强脱钩
2003	0.005	0.066	0.012	0.428	弱脱钩	5.564	扩张负脱钩
2004	0.013	0.130	0.127	0.102	弱脱钩	1.025	增长连接
2005	0.000	-0.005	0.155	0.000	强脱钩	-0.032	强脱钩
2006	0.004	-0.052	0.114	0.036	弱脱钩	-0.459	强脱钩
2007	-0.049	-0.008	0.027	-1.810	强脱钩	-0.314	强脱钩
2008	0.019	0.056	0.103	0.181	弱脱钩	0.548	弱脱钩
2009	0.016	-0.032	0.031	0.511	弱脱钩	-1.015	强脱钩
2010	0.006	-0.016	0.157	0.036	弱脱钩	-0.100	强脱钩
2011	0.011	-0.032	0.145	0.079	弱脱钩	-0.219	强脱钩
2012	0.007	-0.055	0.079	0.086	弱脱钩	-0.691	强脱钩
2013	-0.008	-0.014	0.082	-0.097	强脱钩	-0.175	强脱钩
2014	0.006	-0.005	0.057	0.113	弱脱钩	-0.081	强脱钩
2015	-0.026	-0.066	0.056	-0.454	强脱钩	-1.163	强脱钩
2016	-0.035	0.089	0.110	-0.315	强脱钩	0.814	增长连接
2017	0.000	-0.033	0.046	0.009	弱脱钩	-0.716	强脱钩
2018	-0.010	-0.059	0.069	-0.144	强脱钩	-0.849	强脱钩
2019	-0.003	-0.071	0.143	-0.023	强脱钩	-0.498	强脱钩
2020	0.000	-0.007	0.068	0.004	弱脱钩	-0.109	强脱钩
2021	-0.009	-0.022	0.048	-0.185	强脱钩	-0.450	强脱钩