北京市森林碳汇能力评价研究

任云卯; 温志勇; 王敏男; 贾忠奎

doi:10.12171/j.1000-1522.20220436

北京市森林碳汇能力评价研究

doi: 10.12171/j.1000-1522.20220436

1.
北京市西山试验林场管理处，北京 100093
2.
北京市怀柔区园林绿化局，北京 101400
3.
北京市密云区园林绿化局，北京 101599
4.
北京林业大学森林培育与保护教育部重点实验室，北京 100083

基金项目: 国家自然科学基金项目（31870387）

详细信息

作者简介:
任云卯，高级工程师。主要从事森林资源管理工作。Email：renyunmao75@126.com　地址：100093 北京市西山试验林场管理处

计量
- 文章访问数: 103
- HTML全文浏览量: 34
- PDF下载量: 44
- 被引次数: 0
出版历程
- 收稿日期: 2022-10-31
- 修回日期: 2023-03-05
- 录用日期: 2023-07-07
- 网络出版日期: 2023-07-10

Study on evaluation of forest carbon sequestration capacity in Beijing

1.
Beijing Xishan Experimental Forest Farm Management Office, Beijing 100093, China
2.
Beijing Huairou District Landscape Greening Bureau, Beijing 101400, China
3.
Beijing Miyun District Landscape and Greening Bureau, Beijing 101599, China
4.
The Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China

摘要

摘要: 目的根据第8次园林绿化植物普查中森林资源二类调查数据，对北京市森林碳汇能力进行评估，为该市森林资源的科学管理提供理论依据。方法本研究采取森林蓄积量扩展法，计算北京市森林整体碳储量、碳密度及其变化，并采用造林成本法和碳税法对其碳储量经济价值进行评估。结果（1）北京市森林总碳储量为1934.59万t，碳密度为32.35 t/hm²，各区域中密云区、延庆区、顺义区的碳储量较大，占比分别为13.79%、12.73%和11.40%，而碳密度较大的为顺义区、大兴区、通州区；平原和山地的碳密度均表现为阔叶林 > 混交林 > 针叶林，且平原地区碳密度约是山地的3.3倍；山地和平原地区的碳储量均以阔叶树为主，且平原地区表现出更强的森林固碳能力；防护林是森林碳储量贡献的主体，其中水土保持林碳储量最多，为414.15万t，而碳密度最大为农田防护林（175.23 t/hm²）；优势树种碳储量大小排列为：其他杨树 > 栎树 > 油松 > 其他阔叶树 > 侧柏 > 刺槐 > 桦树 > 华北落叶松 > 山杨，碳密度大小排列为：其他杨树 > 桦树 > 华北落叶松 > 山杨 > 油松 > 刺槐 > 栎树 > 其他阔叶树 > 侧柏；不同起源中碳储量和碳密度均表现为：人工林 > 飞播林 > 天然林；龄组中碳储量大小：中龄林 > 幼龄林 > 成熟林 > 近熟林 > 过熟林，碳密度的总体规律为随着龄级的增大而增大。（2）从第1次到第8次森林资源调查，森林碳储量和碳密度持续增长；林种中特种用途林增长率最高，碳密度最大；落叶松、山杨的碳储量先增加再减少，而刺槐、桦树呈现先减少后增加的趋势，其他树种都呈增加趋势，而油松、落叶松、山杨的碳密度先增后减，侧柏、柞树、桦树先减后增，刺槐、阔叶树持续减小，杨树持续增大；天然林和人工林都呈增长趋势。（3）依据造林成本法和碳税法的不同碳价格估算，北京市森林碳储量经济价值在54.14 ~ 232.15亿元之间，碳税法下的森林碳储量经济价值较高。两种计算方法下北京市各区域中密云区、延庆区、顺义区碳储量经济价值最大；在所有优势树种中，杨树的碳储量经济价值最高；龄组中，中龄林对北京市的贡献最大。结论北京市森林具有明显的固碳潜力，但整体碳汇相对较低，今后应注重森林结构的搭配，加强林地的抚育管理，增强北京市森林碳汇的功能，提高碳汇价值，激发林业经营活力。
- 北京市 /
- 碳汇 /
- 森林碳储量 /
- 碳密度
Abstract: Objective Based on the existing survey data from the 8th Landscape Plant Census of Forest Resources Type II survey data , the forest carbon sink capacity of Beijing was assessed to provide a theoretical basis for the scientific management of forest resources in the city. Method In this study, we adopt the forest stock expansion method to calculate the overall carbon stock, carbon density and changes in Beijing’s forests, and use the afforestation cost method and carbon tax method to assess the economic value of their carbon stocks. Result (1) The total carbon stock of the total forest in Beijing is 19 345 900 t, and the carbon density is 32.35 t/ha, among the regions, Miyun District, Yanqing District and Shunyi District have larger carbon stocks, accounting for 13.79%, 12.73% and 11.40% respectively, while those with higher carbon density are Shunyi District, Daxing District and Tongzhou District; the carbon density of both plains and mountains showed broadleaf forests > mixed forests > coniferous forests, and the carbon density of forests in plains was about 3.3 times higher than that in mountains; the carbon stocks in both mountains and plains were dominated by broadleaf trees; protection forests are the main contributors to the forest carbon stock. The carbon stock of protection forest is the main contributor to forest stock, among which soil and water conservation forest has the largest carbon stock of 4 141 500 t, while the carbon density of farmland protection forest is the largest at 175.23 t/ha; the carbon stock of dominant species is ranked as follows: other Populus spp. > Quercus spp. > Pinus tabuliformis > broadleaf tree > Platycladus orientalis > Robinia pseudoacacia > Betula spp. > Larix principis-rupprechtii > Populus davidiana, the carbon density was ranked as follows: other Populus spp. > Betula spp. > Larix principis-rupprechtii > Populus davidiana > Pinus tabuliformis > Robinia pseudoacacia > Quercus spp. > broadleaf tree > Platycladus orientalis; the carbon stock and carbon density in different origins were: planted forests > flycasting forests > natural forests; the carbon stock size in age group: middle-aged forest > young forest > mature forest > near-mature forest > over-mature forest, and the overall pattern of carbon density increased with the increase of age class. (2) From the first to the eighth forest resources survey, forest carbon stock and carbon density continued to increase; among the forest species, special-purpose forest had the highest growth rate and the highest carbon density; carbon stock of larch and aspen increased and then decreased, while acacia and birch showed a trend of decreasing and then increasing, and all other tree species showed an increasing trend, while carbon density of oleander, larch and aspen increased and then decreased, side cypress, Quercus and birch decreased and then increased, acacia and broadleaf tree continued to decrease, and poplar continued to increase; both natural and planted forests showed an increasing trend. (3) Based on the different carbon prices estimated by the afforestation cost method and the carbon tax method, the economic value of forest carbon stocks in Beijing ranged from 5.414 to 23.215 billion RMB, and the economic value of forest carbon stocks under the carbon tax method was higher. The economic value of carbon stock in each region of Beijing under the two calculation methods varied greatly, with Miyun, Yanqing, and Shunyi districts having the largest economic value of carbon stock; among all dominant tree species, poplar had the highest economic value of carbon stock; and among age groups, middle-aged forests had the largest contribution to Beijing. Conclusion Beijing’s forests have obvious carbon sequestration potential, but the overall carbon sink is relatively low. In the future, we should pay attention to the matching of forest structure, strengthen the management of forest land cultivation, enhance the function of Beijing’s forest carbon sink, improve the value of carbon sink, and stimulate the vitality of forestry management.
- Beijing /
- carbon sequestration /
- forest carbon storage /
- carbon density

HTML全文

图 1 不同地貌森林碳储量和碳密度

Figure 1. Different geomorphological forest carbon storage and carbon density

下载: 全尺寸图片幻灯片

图 2 不同森林林种碳储量和碳密度对比

Figure 2. Different forest species carbon storage and carbon density comparison

下载: 全尺寸图片幻灯片

图 3 北京市碳储量和碳密度

Figure 3. Carbon storage and carbon density of Beijing

下载: 全尺寸图片幻灯片

图 4 不同龄组的森林碳储量和碳密度

Figure 4. Forest carbon storage and carbon density in different age groups

下载: 全尺寸图片幻灯片

图 5 北京市森林碳储量和碳密度动态变化

Figure 5. Dynamic changes of forest carbon storage and carbon density in Beijing

下载: 全尺寸图片幻灯片

图 6 不同优势树种森林碳储量和碳密度变化

Figure 6. Change of forest carbon storage and carbon density of different dominant tree species

下载: 全尺寸图片幻灯片

表 1 北京市各区域森林面积、碳储量和碳密度

Table 1. Forest area, carbon storage and carbon density in different regions of Beijing

区域 Region	林分面积/hm² Area of forest stand/ha	比重 Specific gravity/%	碳储量 Carbon stock/10⁴ t	比重 Specific gravity/%	碳密度/（t·hm⁻²） Carbon density/（t·ha⁻¹）
北京市 Beijing	598 054.41	100.00	1 934.59	100.00	32.35
东城区 Dongcheng District	552.44	0.09	0.00	0.00	0.00
西城区 Xicheng District	431.70	0.07	0.00	0.00	0.00
朝阳区 Chaoyang District	9 022.06	1.51	53.43	2.76	59.22
丰台区 Fengtai District	7 665.43	1.28	31.41	1.62	40.98
石景山区 Shijingshan District	2 344.72	0.39	10.94	0.57	46.68
海淀区 Haidian District	11 803.29	1.97	82.55	4.27	69.94
门头沟区 Mentougou District	54 248.02	9.07	145.83	7.54	26.88
房山区 Fangshan District	49 843.70	8.33	141.07	7.29	28.30
通州区 Tongzhou District	20 939.50	3.50	156.48	8.09	74.73
顺义区 Shunyi District	25 097.03	4.20	220.63	11.40	87.91
昌平区 Changping District	48 446.36	8.10	127.07	6.57	26.23
大兴区 Daxing District	18 699.55	3.13	152.60	7.89	81.61
怀柔区 Huairou District	98 121.85	16.41	191.12	9.88	19.48
平谷区 Pinggu District	36 888.89	6.17	108.51	5.61	29.41
密云区 Miyun District	111 458.32	18.64	266.69	13.79	23.93
延庆区 Yanqing District	102 491.55	17.14	246.27	12.73	24.03

下载: 导出CSV

表 2 不同起源林分碳储量和碳密度变化

Table 2. Changes of carbon storage and carbon density in stands of different origins

项目 Item	林分起源 Stand origin	第6次 Sixth	第7次 Seventh	第8次 Eighth	第6−7次变化量 Amount of change from sixth to seventh	第6−7次变化率 Rate of change from sixth to seventh/%	第7−8次变化量 Amount of change from seventh to eighth	第7−8次变化率 Rate of change from seventh to eighth/%
碳储量 Carbon stock/10⁴ t	合计 Total	1 500.62	1 629.05	1 934.59	128.43	8.56	305.54	18.76
	天然林 Natural forests	413.49	415.55	511.80	2.06	0.50	96.26	23.16
	人工林 Planted forests	1 068.70	1 192.16	1 407.35	123.46	11.55	215.19	18.05
	飞播林 Fly-sown forests	18.43	21.35	15.44	2.91	15.79	−5.91	−27.67
碳密度/（t·hm⁻²） Carbon Density/（t·ha⁻¹）	合计 Total	33.00	32.30	32.35	−0.70	−2.11	0.047 7	0.15
	天然林 Natural forests	9.19	8.52	8.98	−0.67	−7.29	0.463 9	5.45
	人工林 Planted forests	43.16	41.74	39.42	−1.42	−3.29	−2.318 8	−5.56
	飞播林 Fly-Sown Forests	3.34	4.67	8.51	1.34	40.12	3.835 2	82.04

下载: 导出CSV

表 3 分区域森林碳储量经济价值亿元

Table 3. Economic value of forest carbon stocks by region 10⁸ CNY

区域 Region	碳储量经济价值 Economic value of carbon stocks
	造林成本法 Afforestation cost method				碳税法 Carbon tax law
	260.9元/t 260.9 CNY/t	273.3元/t 273.3 CNY/t	305.0元/t 305 CNY/t	平均值 Mean value	1 200元/t 1 200 CNY/t
北京市 Beijing	50.47	52.95	59.01	54.14	232.15
朝阳区 Chaoyang District	1.39	1.46	1.63	1.50	6.41
丰台区 Fengtai District	0.82	0.86	0.96	0.88	3.77
石景山区 Shijingshan District	0.29	0.30	0.33	0.31	1.31
海淀区 Haidian District	2.15	2.26	2.52	2.31	9.91
门头沟区 Mentougou District	3.80	3.99	4.45	4.08	17.50
房山区 Fangshan District	3.68	3.86	4.30	3.95	16.93
通州区 Tongzhou District	4.08	4.28	4.77	4.38	18.78
顺义区 Shunyi District	5.76	6.04	6.73	6.17	26.48
昌平区 Changping District	3.32	3.48	3.88	3.56	15.25
大兴区 Daxing District	3.98	4.18	4.65	4.27	18.31
怀柔区 Huairou District	4.99	5.23	5.83	5.35	22.93
平谷区 Pinggou District	2.83	2.97	3.31	3.04	13.02
密云区 Miyun District	6.96	7.30	8.13	7.46	32.00
延庆区 Yanqing District	6.43	6.74	7.51	6.89	29.55

下载: 导出CSV

表 4 分树种森林碳储量经济价值亿元

Table 4. Economic value of forest carbon stocks by tree species 10⁸ CNY

树种 Tree species	碳储量经济价值 Economic value of carbon stocks
	造林成本法 Afforestation cost method				碳税法Carbon tax law
	260.9元/t 260.9 CNY/t	273.3元/t 273.3 CNY/t	305.0元/t 305.0 CNY/t	平均值 Mean value	1 200元/t 1 200 CNY/t
油松 Pinus tabuliformis	6.73	7.06	7.87	7.22	30.96
华北落叶松 Larix principis-rupprechtii	1.18	1.24	1.38	1.27	5.44
侧柏 Platycladus orientalis	4.16	4.36	4.86	4.46	19.14
栎树 Quercus	7.82	8.21	9.15	8.39	35.98
桦树 Betula spp.	1.26	1.32	1.47	1.35	5.78
刺槐 Robinia pseudoacacia	1.44	1.51	1.68	1.54	6.62
其他杨树 Other Populus spp.	21.30	22.34	24.90	22.85	97.96
山杨 Populus davidiana Dode	0.80	0.83	0.93	0.85	3.66
其他阔叶树 Other broadleaved tree	5.78	6.07	6.76	6.20	26.60

下载: 导出CSV

表 5 分龄组森林碳储量经济价值

Table 5. Economic value of forest carbon stocks by age group

龄组 Age groups	碳储量经济价值 Economic value of carbon stocks
	造林成本法 Afforestation cost method				碳税法 Carbon Tax Law
	260.9元/t 260.9 CNY/t	273.3元/t 273.3 CNY/t	305.0元/t 305.0 CNY/t	平均值 Average value	1 200元/t 1 200 CNY/t
幼龄林 Young forest	12.79	13.42	14.95	13.72	58.83
中龄林 Middle-aged forest	17.66	18.52	20.64	18.94	81.22
近熟林 Near-mature forest	7.99	8.38	9.34	8.57	36.74
成熟林 Mature forest	8.72	9.15	10.20	9.36	40.12
过熟林 Over-ripe forest	3.31	3.48	3.87	3.55	15.24

下载: 导出CSV

参考文献(33)

[1]	文勇军, 杨韩. 云南省“十三五”期间森林碳储量动态变化及碳汇潜力分析[J]. 林业建设, 2022(4): 22−25. Wen Y J, Yang H. Carbon sink potential analysis and dynamic changes of forest carbon storage in Yunnan Province during the 13th five-year plan period[J]. Forestry Construction, 2022(4): 22−25.
[2]	陆霁, 张颖, 李怒云. 林业碳汇交易可借鉴的国际经验[J]. 中国人口资源与环境, 2013, 23(12): 22−27. Lu J, Zhang Y, Li N Y. Forest carbon sink trade referenced to overseas experiences[J]. China Population, Resources and Environment, 2013, 23(12): 22−27.
[3]	Magnussen S, Köhl M, Olschofsky K. Error propagation in stock-difference and gain-loss estimates of a forest biomass carbon balance[J]. European Journal of Forest Research, 2014, 133(6): 1137−1155. doi: 10.1007/s10342-014-0828-0
[4]	Houghton R A. Aboveground forest biomass and the global carbon balance[J]. Global Change Biology, 2010, 11(6): 945−958.
[5]	Fang J. Changes in forest biomass carbon storage in China between 1949 and 1998[J]. Science, 2001, 292: 2320−2322. doi: 10.1126/science.1058629
[6]	朱建华, 田宇, 李奇, 等. 中国森林生态系统碳汇现状与潜力[J]. 生态学报, 2023, 43(9): 1−16. Zhu J H, Tian Y, Li Q, et al. The current and potential carbon sink in forest ecosystem in China[J]. Acta Ecologica Sinica, 2023, 43(9): 1−16.
[7]	于海群. 华北地区平原造林工程碳汇能力及碳汇价值研究: 以北京市东郊森林公园为例[J]. 生态经济, 2022, 38(2): 110−115. Yu H Q. Carbon Accounting for afforestation project in the plain area of Beijing: a case study of eastern suburb forest park, Beijing[J]. Ecological economy, 2022, 38(2): 110−115.
[8]	张峰, 彭祚登. 北京市森林碳储量和碳汇经济价值研究[J]. 林业资源管理, 2021(6): 52−58. Zhang F, Peng Z D. Biomass carbon stocks and carbon stock economic value of forests in Beijing[J]. Forest Resources Management, 2021(6): 52−58.
[9]	续珊珊. 森林碳储量估算方法综述[J]. 林业调查规划, 2014, 39(6): 28−33. Xu S. A Review of forest carbon storage estimation methods[J]. Forest Inventory and Planning, 2014, 39(6): 28−33.
[10]	范冶. 武汉市森林碳汇能力评价研究[D]. 武汉: 武汉轻工大学, 2019. Fan Y. Assessment of forest carbon sequestration capacity in Wuhan City[D]. Wuhan: Wuhan University of Light Industry, 2019.
[11]	Zhang H, Feng Z, Chen P, et al. Development of a tree growth dierence equation and its application in forecasting the biomass carbon stocks of Chinese forests in 2050[J]. Forests, 2019, 7(10): 582.
[12]	王会荣, 李爱琴, 王晶晶, 等. 基于第8次森林资源清查数据的安徽森林碳储量特征研究[J]. 西北农林科技大学学报(自然科学版), 2019, 47(7): 78−86. Wang H R, Li A Q, Wang J J, et al. Characteristics of forest carbon storage in Anhui based on the 8th forest inventory data[J]. Journal of Northwest A&F University (Natural Science Edition), 2019, 47(7): 78−86.
[13]	褚宏洋. 森林碳汇经济价值评估及影响因素研究[D]. 泰安: 山东农业大学, 2016. Chu H Y. Research on economic value assessment and influencing factors of forest carbon sinks: a case study in Shandong Province[D]. Tai’an: Shandong Agricultural University, 2016.
[14]	张娟, 陈钦. 森林碳汇经济价值评估研究: 以福建省为例[J]. 西南大学学报(自然科学版), 2021, 43(5): 121−128. Zhang J, Chen Q. Study on economic value assessment of forest carbon sequestration: taking Fujian Province as an Example[J]. Journal of Southwest University (Natural Science Edition), 2021, 43(5): 121−128.
[15]	陈晓凤. 北京市乔木林碳储量及其固碳潜力研究[D]. 北京, 北京林业大学, 2020. Chen X F. Study on carbon storage and carbon sequestration potential of arbor forest in Beijing[D]. Beijing, Beijing Forestry University, 2020.
[16]	樊登星, 余新晓, 岳永杰, 等. 北京市森林碳储量及其动态变化[J]. 北京林业大学学报, 2008, 30(S2): 117−120. Fan D X, Yu X X, Yue Y J, et al. Forest carbon storage and its dynamics in Beijing[J]. Journal of Beijing Forestry University, 2008, 30(S2): 117−120.
[17]	张颖, 李晓格. 碳达峰碳中和目标下北京市森林碳汇潜力分析[J]. 资源与产业, 2022, 24(1): 15−25. Zhang Y, Li X G. Carbon sink potential of Beijing’s forest under carbon peak and carbon neutrality[J]. Resources and Industry, 2022, 24(1): 15−25.
[18]	杨美丽, 褚宏洋, 庄皓明, 等. 森林碳汇经济价值评估研究: 以山东省为例[J]. 山东农业大学学报(社会科学版), 2017, 19(2): 77−84. Yang M L, Chu Y S, Chen L H, Liu S. A preliminary study on the ecosystem service functions and their values in the mountain forests of Beijing[J]. Acta Ecologica Sinica, 2017, 19(2): 77−84.
[19]	施溯筠, 李光, 张三焕. 长白山区森林固定CO₂价值的评估[J]. 延边大学学报(自然科学版), 2002(2): 134−137. Shi S Y, Li G, Zhang S H. Valuing the forestry of carbon fixation in Changbai Mountain[J]. Journal of Yanbian University (Natural Science), 2002(2): 134−137.
[20]	成克武, 崔国发, 王建中, 等. 北京喇叭沟门林区森林生物多样性经济价值评价[J]. 北京林业大学学报, 2000, 22(4): 66−71. Cheng K W, Cui G F, Wang J Z, et al. Evaluation on the economic value of the forest biodiversity in Labagoumen forest region[J]. Journal of Beijing Forestry University, 2000, 22(4): 66−71.
[21]	李奇, 朱建华, 冯源, 等. 中国森林乔木林碳储量及其固碳潜力预测[J]. 气候变化研究进展, 2018, 14(3): 287−294. Li Q, Zhu J H, Feng Y, et al. Carbon storage and carbon sequestration potential of the forest in China[J]. Climate Change Research, 2018, 14(3): 287−294.
[22]	刘淑琴, 夏朝宗, 冯薇, 等. 西藏森林植被乔木层碳储量与碳密度估算[J]. 应用生态学报, 2017, 28(10): 3127−3134. Liu S Q, Xia C Z, Feng W, et al. Estimation of vegetation carbon storage and density of forests at tree layer in Tibet, China[J]. Chinese Journal of Applied Ecology, 2017, 28(10): 3127−3134.
[23]	邵波, 燕腾. 四川省森林植被碳储量及碳密度估算[J]. 西南林业大学学报(自然科学), 2017, 37(2): 179−183. Shao B, Yan T. Study on carbon storage and carbon density of forest in Sichuan Province[J]. Journal of Southwest Forestry University, 2017, 37(2): 179−183.
[24]	王敏, 石乔莎. 城市绿色碳汇效能影响因素及优化研究[J]. 中国城市林业, 2015, 13(4): 1−5. Wang M, Shi Q S. A study of influencing factors to urban green carbon sequestration and its efficiency optimization[J]. Journal of Chinese Urban Forestry, 2015, 13(4): 1−5.
[25]	曹晓阳. 山西中南部主要造林树种固碳能力研究[D]. 北京: 北京林业大学, 2013. Cao X Y. Research on carbon sequestration ability of main afforestation tree species in central and southern Shanxi province, China[D]. Beijing: Beijing Forestry University, 2013.
[26]	于海群. 华北地区平原造林工程碳汇能力及碳汇价值研究: 以北京市东郊森林公园为例[J]. 生态经济, 2022, 38(2): 110−115. Yu H Q. Carbon accounting for afforestation project in the plain area of beijing: a case study of eastern suburb forest park, Beijing[J]. Ecological Economy, 2022, 38(2): 110−115.
[27]	李轶涛. 山西省森林生态系统碳汇特征及提升措施[J]. 山西林业, 2022(4): 10−11. Li Y T. Carbon sequestration characteristics and promotion measures of forest ecosystem in Shanxi Province[J]. Shanxi Forestry, 2022(4): 10−11.
[28]	郭忠升. 水资源紧缺地区土壤水分植被承载力论述[J]. 林业科学, 2011, 47(5): 140−144. doi: 10.11707/j.1001-7488.20110522 Guo Z S. A review of soil water carrying capacity for vegetation in water-limited regions[J]. Scientia Silvae Sinicae, 2011, 47(5): 140−144. doi: 10.11707/j.1001-7488.20110522
[29]	兰秀, 杜虎, 宋同清, 等. 广西主要森林植被碳储量及其影响因素[J]. 生态学报, 2019, 39(6): 2043−2053. Lan X, Du H, Song T Q, et al. Vegetation carbon storage in the main forest types in Guangxi and the related influencing factors[J]. Acta Ecologica Sinica, 2019, 39(6): 2043−2053.
[30]	陈周光, 龙飞, 祁慧博. 浙江省森林碳汇潜力及经济价值研究[J]. 黑龙江八一农垦大学学报, 2022, 34(4): 126−133. Chen Z G, Long F, Qi H B. Study on forest carbon sink potential and economic value in Zhejiang Province[J]. Journal of Heilongjiang Bayi Agricultural University, 2022, 34(4): 126−133.
[31]	杜好. 丽水市森林碳储量和碳汇经济价值研究[J]. 浙江林业科技, 2023, 43(3): 87−93. Du H. Study on forest carbon stock and carbon sink value in Lishui[J]. Journal of Zhejiang Forestry Science and Technology, 2023, 43(3): 87−93.
[32]	侯元兆, 王琦. 中国森林资源核算研究[J]. 世界林业研究, 1995(3): 51−56. Hou Y Z, Wang Q. A study on forest resource accounting in China[J]. World Forestry Research, 1995(3): 51−56.
[33]	刘凤芹, 陈波, 高琛, 等. 降水对沙地杨树人工林水分利用的影响[J]. 干旱区资源与环境, 2016, 30(10): 165−170. Liu F Q, Chen B, Gao C, et al. Effects of precipitation on water use strategy of poplar plantation in sandy area[J]. Journal of Arid Land Resources and Environment, 2016, 30(10): 165−170.