城市绿地乔木固碳能力及碳抵消效果评估

编号 lyqk011550

中文标题 城市绿地乔木固碳能力及碳抵消效果评估

作者 陈俊华  黎晓平  李羽洁  慕长龙  谢川  刘一丁  谢天资  简毅 

作者单位 1. 四川省林业科学研究院/森林与湿地生态恢复与保育四川重点实验室 成都 610081;
2. 南充市林业局 四川南充 637000;
3. 成都蜀舆科技有限责任公司 成都 610000

期刊名称 中国城市林业 

年份 2024 

卷号 22

期号 3

栏目名称 专题：城市森林声景观 

中文摘要 定量测算城市绿地乔木固碳能力及抵消碳排放,可为森林城市建设的树种选择和配置提供决策支持。基于高清卫星遥感影像数据和有关经济社会统计数据,结合实地调查,利用生物量模型法测算南充市主城区绿地乔木的固碳能力,探讨群落结构与固碳能力的影响;分析抵消城市能源CO₂排放的成效。结果表明:1)南充市主城区绿化植被中木本植物共269种,分属76科163属。出现频度最高的为桂花、银杏、黄葛树、天竺桂、樟木、樱花等10个树种。2)各类绿地林分平均密度677±425株·hm^-2,平均胸径21.01±7.15 cm,平均树高8.52±2.06 m。3)各类绿地碳密度按大小为广场用地>附属绿地>公园绿地>防护绿地;固碳速率最大的是附属绿地(2.54 t·hm^-2·a^-1),最小的是公园绿地(1.64 t·hm^-2·a^-1)。4)南充市主城区绿地乔木2020年碳固定量为9 347 t,能源CO₂总排放量为1 016.55万t,绿地乔木大约抵消城市能源0.09%CO₂的排放量。最后,建议南充市在城市森林营建过程中,应优先考虑多树种混合使用,并适时调整群落密度以优化林分结构、改善生境条件,促进林木整体水平的生长,进而提高群落的固碳能力;同时尽量采用近自然、较为粗放的经营方式,以减少碳排放。

关键词 城市绿地  乔木  碳密度  固碳速率  生物量  南充市 

基金项目 四川省创新团队岗位项目(2024LCTD0107),四川省林业科学研究院科技成果转化项目(川林研工咨2020025)

英文标题 Assessment of Carbon Sequestration Capacity and Carbon Offsetting Effect of Arbors in Urban Green Spaces

作者英文名 Chen Junhua, Li Xiaoping, Li Yujie, Mu Changlong, Xie Chuan, Liu Yiding, Xie Tianzi, Jian Yi

单位英文名 1. Sichuan Key Laboratory of Ecological Restoration and Conservation for Forest and Wetland, Sichuan Academy of Forestry, Chengdu 610081, China;
2. Nanchong Forestry Bureau, Nanchong 63700, Sichuan, China;
3. Chengdu Shuyu Technology Co., Ltd., Chengdu 610000, China

英文摘要 The quantitative measurement of carbon sequestration capacity and carbon offsetting effects of trees in urban green spaces can provide supports for the decision-makings on tree species' selection and configuration in forest city building. With high-definition satellite remote sensing image and relevant economic and social statistical data, combined with the data from field investigations, the paper uses the method of biomass model to calculate the carbon sequestration capacity of landscaping trees in the urban area of Nanchong, based on which the interactions of community structure and carbon sequestration capacity are explored, and also analyzes the effects of carbon offsetting the emission of the energy sector in the city. The results show that: 1) There are 269 species of woody plants in the green spaces of the urban area of Nanchong, belonging to 163 genera in 76 families. The 10 tree species with the highest presence are Osmanthus fragrans, Ginkgo biloba, Ficus virens Aiton, Cinnamomum japonicum, C. camphora, Prunus serrulata, F. concinna, P. cerasifera, F. atropurpurea, Acer palmatum Michelia × alba; 2) The average density of forest stands in various green spaces is 677 ± 425 plants·hm^-2, with an average diameter at breast height at 21.01±7.15 cm and an average tree height at 8.52±2.06 m; 3) The average carbon density of the trees in green spaces can be ranked as square >affiliated green spaces>park green [JP2]spaces>protective green spaces. Affiliated green spaces have the highest carbon sequestration rate (2.54 t·ha^-1·a^-1), while the lowest is in park green spaces (1.64 t·ha^-1·a^-1); and 4) The amount of carbon sequestrated by the trees in green spaces in the urban area of Nanchong City in 2020 is 9 347 t, and the total energy-related CO₂ emissions are 1 016.55×10⁴ t, which means that the trees in green spaces approximately offset 0.09% of carbon emitted by urban energy use. It is suggested that Nanchong should prioritize the mixed use of multiple tree species in its building of urban forest, and the tree community density should be adjusted in a timely manner to optimize the forest structure, improve habitat conditions, promote the growth of trees, and thereby enhance the carbon sequestration capacity. In addition, close-to-nature and extensive management methods should be adopted as much as possible to reduce the carbon emission.

英文关键词 urban green space;arbor;carbon density;carbon sequestration rate;biomass;Nanchong city

起始页码 26

截止页码 33

投稿时间 2023/8/17

作者简介 陈俊华(1972-),男,博士,研究员,研究方向为森林经营与城市森林。E-mail:295454166@qq.com

通讯作者介绍 简毅(1982-),男,博士,副研究员,研究方向为森林生态效益监测与评价。E-mail:163jianyi@163.com

E-mail 163jianyi@163.com

DOI 10.12169/zgcsly.2023.08.17.0001

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