Spatiotemporal characteristics and prediction of carbon emissions/absorption from land use change in the urban agglomeration on the northern slope of the Tianshan Mountains

城市化 环境科学 温室气体 城市群 土地利用 碳汇 碳纤维 土地利用、土地利用的变化和林业 集聚经济 自然地理学 环境保护 地理 气候变化 生态学 经济地理学 复合数 生物 经济增长 复合材料 经济 材料科学
作者
Bohao Wei,Alimujiang Kasimu,Rukeya Reheman,Xueling Zhang,Yongyu Zhao,Yimuranzi Aizizi,Hongwu Liang
出处
期刊:Ecological Indicators [Elsevier BV]
卷期号:151: 110329-110329 被引量:65
标识
DOI:10.1016/j.ecolind.2023.110329
摘要

Changes in land use significantly contribute to carbon emissions and other environmental problems. Regional carbon emissions changes from land use have been affected by rapid urbanization. To dynamically assess land use change and the spatiotemporal characteristics of carbon emissions from 1990 to 2020, this study used the PLUS, grey back-propagation neural network, and related carbon emission accounting models as well as four distinct 2030 scenario simulations. According to the findings, the urbanization of the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM) developed rapidly from 1990 to 2020 with a noticeable transfer of diverse types of land. In particular, the quantity of construction land and cropland belonging to carbon source land increased by 153.271% and 55.072% respectively. Simultaneously, carbon emissions showed a trend of continuous increase and demonstrated an S-shaped curve growth, with relatively rapid growth from 2000 to 2015, that has tended to be stable in recent years. If this carbon emission trend continues, an inflection point will appear around 2028. Land use simulations for 2030 reveal that the ecological security (ES) scenario, which slows the expansion of construction land and cropland while increasing ecological land, is most likely to reduce the negative environmental consequences of urbanization. This is because higher potential peak carbon emissions per unit area that may be obtained with carbon sink land. Consequently, the ES scenario of the study region is comparable to the future urban agglomeration development model. The results provide a reference for territorial space planning and dual carbon target recommendations in the UANSTM.

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