| Issue |
E3S Web Conf.
Volume 275, 2021
2021 International Conference on Economic Innovation and Low-carbon Development (EILCD 2021)
|
|
|---|---|---|
| Article Number | 02005 | |
| Number of page(s) | 7 | |
| Section | Green Low-Carbon and Energy Saving and Emission Reduction Applications | |
| DOI | https://doi.org/10.1051/e3sconf/202127502005 | |
| Published online | 21 June 2021 | |
Study on Carbon Sequestration Benefit of Converting Farmland to Forest in Yan’an
School of Tourism & Research Institute of Human Geography, Xi’an International Studies University, Xi’an, China
* Corresponding author: hhz162@qq.com
This paper takes Yan’anas the study area, analyses the current situation of the policy, calculates the carbon sequestration value by using the afforestation area and woodland area in Yanan in 2019, and explores its carbon emission trading potential. The conclusions are as follows: (1) the amount of carbon sequestration increased by 203575.5 t due to the afforestation in 2019 in Yan’an. The green economy income of Yan’an can be increased by 5.8528 million RMB, because of it. The carbon sequestration value of total woodland is 120 million RMB, which can increase the forestry output value of Yan’an by 19.32%. (2) The new carbon sequestration benefit of northern area is higher than that of southern area in Yan’an; the highest carbon sequestration benefit of returning farmland to forest isWuqi County’s 35307.29t, and its value is 1.015 million RMB, it can be increased by 0.15% of the green economy income. (3) The industrial counties Huangling County and Huanglong County, the industrial counties Luochuan County and Yichuan County carry out carbon trading respectively, under the condition of ensuring the output value of the secondary industry in the industrial county, it can increase the green economy income of the total output value of Huanglong County and Yichuan County by 0.73% respectively.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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