摘要: 目的核算我国森林资源碳储量和价值量，摸清我国森林资源家底，了解森林资源状况，合理制定林业发展规划。预测森林碳储量及碳汇潜力，提高森林经营管理水平，为我国实现碳达峰碳中和的林业发展目标提供参考、�/sec> 方法利用1973�?018年间9次森林资源清查数据，采用森林蓄积量法核算我国森林资源总碳储量及其变化情况，并按照不同林种分类核算森林资源的碳储量和价值量。采用GM�?,1）灰色预测模型和幂函数模型联合预测我国森林资源碳汇发展潜力，并通过构建林分单位面积生长量和碳储量的回归模型，分析不同经营管理水平下碳汇量的变化率、�/sec> 结果�?�?0多年来中国森林资源单位面积蓄积量平均�?3.56 m ³/hm ²，林木碳储量�?976年的51.96 × 10 ⁸t增加�?018年的87.90 ×10 ⁸t，年均增�?.855 7 × 10 ⁸t/a，森林资源总碳储量（包括林木、林地和林下植被）由125.06 × 10 ⁸t增加�?14.39 × 10 ⁸t；其中，人工林碳储量增速明显，年均增加5.05%。（2）我国林木碳储量价值量�?976年的1 482.09 × 10 ⁸元增加到2018年的8 823.85 × 10 ⁸元，年均增加174.80 × 10 ⁸元，年复合增长率达到4.34%；其中，人工林碳储量价值年均增�?.24%。（3）GM�?,1）灰色模型预�?030年森林碳储量达到100.13 × 10 ⁸t�?018�?030年年均增�?.59 × 10 ⁸t/a，预�?030年森林蓄积量可达�?10.80 × 10 ⁸m ³�?060年中国森林碳储量将达�?80.32 × 10 ⁸t�?018�?060年年均增�?.36 × 10 ⁸t/a。幂函数模型预测�?030年中国森林碳储量达到108.00 × 10 ⁸t�?018 ~ 2030年平均年碳汇量为2.25 ×10 ⁸t/a，预�?030年森林蓄积量可达�?27.38 × 10 ⁸m ³�?060年中国森林碳储量达到212.27 × 10 ⁸t�?018�?060年年增汇3.12 × 10 ⁸t/a。（4）在�?5年的森林碳储量平均基准上，森林经营管理水平提�?%，森林碳储量将增�?.30% ~ 6.86%；提�?0%，森林碳储量将增�?.89% ~ 12.47%；提�?5%，森林碳储量将增�?5.48% ~ 18.09%；提�?0%，森林碳储量将增�?0.96% ~ 21.07%、�/sec> 结论在不考虑经济、政策等外部因素的影响下，基于森林生物量和蓄积量的变化，中国森林碳储量和价值量都是增加的。按照这个发展趋势，可以实现2030�?060年碳达峰碳中和时中国林业的预期发展目标。如果目前森林经营管理水平再提高，森林碳储量的变化率将逐步增加，碳汇潜力巨大、�/sec>

关键诌�
• 碳储野�/a> /
• 蓄积野�/a> /
• 森林碳汇潜力/
• GM�?,1）灰色模垊�/a> /
• 碳达峰碳中和

Abstract: ObjectiveCarbon reserves and value of forest resources in China should be calculated to understand the status of forest resources and formulate a reasonable forestry development plan. Through the prediction of forest carbon stocks and carbon sequestration potential, it can improve the level of forest management and provide reference value for China to achieve the goal of carbon emission peak and carbon neutralization. MethodBased on the data of 9 forest inventories from 1973 to 2018 in China, the total carbon stocks of forest resources in China were calculated using forest volume method, and the carbon stocks and values of forest resources were calculated according to different forest types. This paper uses GM (1,1) grey model and power function model to predict the development potential of forest carbon sequestration in China, and analyzes the changing rate of carbon sequestration under different management levels by constructing the regression model of forest growth per unit area and carbon storage. Result(1) Over the past 40 years, China’s average unit area volume of forest resources is 73.56 m ³/ha, forest carbon stocks increased from 5.196 billion t in 1976 to 8.790 billion t in 2018, with an average annual increase of 0.085 57 billion t/year. The total carbon stocks of forest resources (including forest, woodland and understory vegetation) increased from 12.506 billion t to 21.439 billion t; among them, carbon stocks of plantation increased significantly, with an average annual increase of 5.05%. (2) The values of forest carbon stocks in China increased from 148.209 billion CNY in 1976 to 882.385 billion CNY in 2018, with an average annual increase of 17.480 billion CNY and a compound annual growth rate of 4.34%. Among them, the values of plantation carbon stocks increased by 8.24%. (3) The GM (1,1) grey model predicted that the forest carbon stocks will reach 10.013 billion t in 2030, the average annual increase of carbon sequestration will be 159 million t/year from 2018 to 2030, and the forest volume will reach 21.080 billion m ³in 2030; the forest carbon stocks in China will reach 18.032 billion t in 2060, and the average annual increase of carbon sequestration will be 236 million t/year from 2018 to 2060. The power function model predicted that China’s forest carbon stocks will reach 10.8 billion t in 2030, the average annual carbon sequestration will be 225 million t/year from 2018 to 2030, and the forest volume was expected to reach 22.738 billion m ³in 2030; China’s forest carbon stocks will reach 21.227 billion t in 2060, and the annual increase of carbon sequestration will be 312 million t/year from 2018 to 2060. (4) Based on the average benchmark of forest carbon stocks in recent 15 years, if the forest management level increase by 5%, the forest carbon stocks will increase by 4.30% � 6.86%; if increase by 10%, the forest carbon stocks will increase by 9.89% � 12.47%; if increase by 15%, the forest carbon stocks will increase by 15.48% � 18.09%; and if the forest management level increase by 20%, the forest carbon stocks will increase by 20.96% � 21.07%. ConclusionWithout considering the influence of external factors such as economy and policy, based on the changes of forest biomass and volume, forest carbon stocks and values in China are increased. According to this development trend, China can achieve the expected development goal of carbon emission peak and carbon neutralization for forestry in 2030 and 2060. If the current forest management level is further improved, the changing rate of forest carbon stocks will gradually increase, and the carbon sequestration potential will be huge.

Key words:
• carbon stock/
• stock volume/
• carbon sequestration potential of forest/
• GM (1,1) grey model/
• carbon emission peak and carbon neutralization

�?nbsp; 1不同经营管理水平下我国森林碳储量的变化率

Figure 1.Changing rate of forest carbon storage in China under different management levels

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�?nbsp; 1基于森林资源清查数据计算的中国森林资源碳储量及其变化

Table 1.Carbon stocks and changes of forest resources in China based on forest inventory data

时期 Period	森林单位面积蓄积�? （m3·hm�?（�br/>Stock volume per unit area of forest/(m3·ha�?)	林木碳储野�br/>Forest carbon storage/108t	森林资源碳储野�br/>Carbon storage of forest resources/108t	碳密�?(t·hm�?) Carbon density/ (t·ha�?)	碳汇�?�?08t·a�?（�br/>Carbon sequestration/ (108t·year�?)
1976�?973�?976（�/td>	71.27	51.96	125.06	42.64
1981�?977�?981（�/td>	78.32	55.84	134.53	48.44	0.776 3
1988�?984�?988（�/td>	73.33	57.50	138.59	46.13	0.237 5
1993�?989�?993（�/td>	67.97	58.37	140.71	43.66	0.173 9
1998�?994�?998（�/td>	70.89	59.32	144.68	37.32	0.189 5
2003�?999�?003（�/td>	71.21	64.69	157.77	36.98	1.074 0
2008�?004�?008（�/td>	73.67	69.13	168.61	38.11	0.888 0
2013�?009�?013（�/td>	77.24	76.35	186.22	39.90	1.444 0
2018�?013�?018（�/td>	78.17	87.90	214.39	40.28	2.310 0
总平� Total mean	73.56				0.855 7
注：碳汇量核算以林木碳储量为基准，下文表格中均以核算的节点年份表述。Notes: carbon sequestration accounting is based on forest carbon reserves, and the following tables are expressed in the node year of accounting.

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�?nbsp; 2按林木构成计算的中国森林资源碳储量及其变匕�/p>

Table 2.Carbon stocks and change of forest resources in China based on forest composition 10 ⁸t

指标 Index		1976	1981*	1988	1993	1998	2003	2008	2013	2018
林木总碳储量 Forest total carbon storage		51.96	55.84	57.50	58.37	59.32	64.69	69.13	76.35	87.90
森林碳储� Forest carbon storage		47.44	49.27	49.87	49.59	53.52	59.17	63.47	70.20	81.03
按林龄划� Classification by stand age	幼龄� Young forest	4.18	4.89	6.64	6.61	5.48	6.10	7.07	7.74	10.16
	中龄� Middle-aged forest	11.41	15.48	13.61	15.34	14.77	16.27	18.34	19.50	22.90
	近熟� Near-mature forest	32.05	25.63	6.42	7.67	9.88	10.67	12.59	14.41	16.69
	成熟� Mature forest	3.12	1.16	14.45	12.90	13.64	14.33	15.00	16.93	19.05
	过熟� Over mature forest	1.16	1.16	7.79	11.70	9.75	10.09	10.47	11.61	12.22
按起源划� Classification by origin	天然� Natural forest	45.42	42.22	41.46	45.79	43.10	50.32	54.16	58.41	64.94
	人工� Plantation	2.03	2.61	3.98	4.95	4.81	7.15	9.31	11.79	16.09
按用途划� Classification by use	防护� Protection forest	5.46	5.87	8.62	10.63	11.62	21.30	34.91	37.75	41.89
	特用� Special-use forest	1.52	1.92	3.57	3.80	3.58	4.46	8.29	10.31	12.44
	用材� Timber forest	42.38	37.83	34.06	37.10	31.42	25.24	20.08	21.86	25.72
	薪炭� Fuel forest	1.40	1.53	1.51	1.53	0.42	0.26	0.19	0.28	0.27
	经济� Economic forest	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.71
疏林 Open forest		4.12	4.05	4.07	4.06	0.65	0.61	0.54	0.50	0.48
散生� Scattered forest		2.15	4.06	4.86	5.27	3.34	3.37	3.54	3.75	4.17
四旁� Four-side tree		1.86	1.94	2.18	2.93	1.81	1.54	1.58	1.90	2.23
注：*表示在第2次（1977�?981）森林资源清查数据中，由于台湾和西藏自治区的森林资源单独分开统计，研究中采用的全国合计数据不包括台湾省和西藏自治区实际控制线外的森林资源统计数据，可能计算结果相对偏小。Notes:*, in the second forest resources inventory data (1977�?981), since the forest resources of Taiwan and Tibet Autonomous Region are separately counted, the national total data used in the study does not include the forest resources statistics outside the actual control line of Taiwan Province and Tibet Autonomous Region, and the possible calculation results are relatively small.

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�?nbsp; 3中国森林碳储量价值量核算� 10⁸兂�/p>

Table 3.Monetary accounting table of forest carbon sinks in China 10 ⁸CNY

指标 Index		1976	1981	1988	1993	1998	2003	2008	2013	2018
林木总碳储量价值量 Forest total carbon storage value		1 482.09	1 449.14	3 254.98	5 102.15	7 449.81	8 122.44	7 286.51	7 176.10	8 823.85
森林碳储量价值量 Forest carbon storage value		1 353.29	1 278.66	2 823.16	4 334.23	6 721.49	7 429.27	6 690.06	6 597.97	8 133.92
按林龄划� Classification by stand age	幼龄� Young forest	119.19	126.79	375.70	577.76	688.48	766.42	744.86	727.88	1 020.01
	中龄� Middle-aged forest	325.45	401.60	770.40	1 340.40	1 854.76	2 043.27	1 933.24	1 833.08	2 298.98
	近熟� Near-mature forest	914.30	665.15	363.44	670.11	1 240.95	1 339.33	1 326.65	1 354.70	1 675.73
	成熟� Mature forest	88.92	30.03	818.07	1 127.69	1 712.84	1 799.25	1 581.43	1 590.94	1 912.63
	过熟� Over mature forest	33.00	30.03	440.88	1 022.79	1 223.95	1 267.35	1 103.87	1 091.37	1 226.56
按起源划� Classification by origin	天然� Natural forest	1 295.59	1 095.67	2 346.67	4 002.57	5 412.42	6 318.25	5 708.51	5 489.42	6 518.60
	人工� Plantation	57.99	67.85	225.34	432.79	604.31	897.38	981.55	1 108.51	1 615.32
按用途划� Classification by forest use	防护� Protection forest	155.72	152.24	487.73	929.37	1 459.09	2 674.75	3 679.98	3 548.30	4 204.75
	特用� Special-use forest	43.38	49.84	202.18	332.48	449.43	560.46	874.19	968.77	1 248.55
	用材� Timber forest	1 208.96	981.84	1 927.80	3 242.42	3 946.38	3 168.84	2 116.29	2 054.51	2 582.21
	薪炭� Fuel forest	39.80	39.66	85.29	133.35	53.17	33.04	19.59	26.34	27.02
	经济� Economic forest	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	71.39
疏林 Open forest		117.64	105.00	230.16	354.96	81.14	76.44	57.19	47.19	47.81
散生� Scattered forest		61.29	105.34	275.02	460.49	419.57	423.68	372.83	352.06	418.68
四旁� Four-side tree		53.13	50.23	123.12	255.85	227.42	192.79	166.43	178.88	223.44
注：美元兑人民币汇率平均值为�?976年为1.880 3�?981年为1.710 7�?988年为3.731 4�?993年为5.761 8�?998年为8.279 0�?003年为8.277 4�?008年为6.948 0�?013年为6.195 6�?018年为6.617 4[23]、�br/>Notes: the average exchange rate of USD to RMB is: 1.880 3 in 1976, 1.710 7 in 1981, 3.731 4 in 1988, 5.761 8 in 1993, 8.279 0 in 1998, 8.277 4 in 2003, 6.948 0 in 2008, 6.195 6 in 2013, 6.617 4 in 2018[23].

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�?nbsp; 4GM�?,1）预测模型预测结果对照表

Table 4.Comparison table of prediction results of GM (1,1) prediction model

年份 Year	森林碳储量实际倻�br/>Actual value of forest carbon stock/108t	森林碳储量预测倻�br/>Predicted value of forest carbon stock/108t	残差 Residual	相对误差 Relative error $(\varepsilon) $/%
1976	47.44
1981	49.27
1988	49.87	49.870 0	0
1993	49.59	48.410 2	1.179 8	2.38
1998	53.52	53.397 3	0.122 7	0.23
2003	59.17	58.898 2	0.271 8	0.46
2008	63.47	64.965 9	�?.495 9	2.36
2013	70.20	71.658 6	�?.458 6	2.08
2018	81.03	79.040 8	1.989 2	2.45
平均相对误差Average relative error				1.66
后验差检� Posterior error test＇�i>C（�/td>	0.1096

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�?nbsp; 5中国森林面积及林木碳储量预测

Table 5.Prediction of forest area and forest carbon stocks in China

年份 Year	森林面积实际�? 104hm2 Actual value of forest area/104ha	林木碳储量实际倻�br/>Actual value of forest carbon storage/108t	GM�?,1）模� GM (1,1) model			幂函数模� Power function model
			森林面积预测�?104hm2 Predicted value of forest area/104ha	林木碳储量预测倻�br/>Predicted value of forest carbon storage/108t		森林面积预测�?104hm2 Predicted value of forest area /104ha	林木碳储量预测倻�br/>Predicted value of forest carbon storage/108t
1976	12 186.00	47.44
1981	11 527.74	49.27
1988	12 465.28	49.87	12 465.28	49.87		12 358.99	49.53
1993	13 370.35	49.59	14 084.08	48.41		13 930.07	50.56
1998	15 894.09	53.52	15 341.53	53.40		15 443.59	53.36
2003	17 490.92	59.17	16 711.24	58.90		16 936.12	57.81
2008	18 138.09	63.47	18 203.25	64.97		18 415.17	63.82
2013	19 133.00	70.20	19 828.46	71.66		19 884.29	71.36
2018	21 822.05	81.03	21 598.78	79.04		21 345.54	80.40
2023			23 527.15	87.18		22 800.28	90.89
2028			25 627.69	96.16		24 249.46	102.83
2033			27 915.77	106.07		25 693.81	116.19
2038			30 408.13	117.00		27 133.88	130.95
2043			33 123.01	129.05		28 570.10	147.11
2048			36 080.28	142.35		30 002.84	164.64
2053			39 301.58	157.01		31 432.39	183.54
2058			42 810.49	173.19		32 859.01	203.79
2063			46 632.67	191.03		34 282.91	225.38
C			0.174 7	0.109 6
R2						0.973 48	0.994 02
平均绝对误差百分毓�br/>Average absolute error percentage (MAPE)/%			3.08	1.66		2.68	1.17
2030			26 542.92	100.13		24 827.75	108.00
2060			44 339.36	180.32		33 428.88	212.27

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