武汉市土地利用碳排放的时序特征及影响因素研究

发布时间：2018-06-07 02:36

本文选题：土地利用 + 能源消费　；参考：《华中农业大学》2014年硕士论文

【摘要】：碳排放问题导致全球气候变暖,引起全世界的广泛关注,全球各国积极推行发展低碳经济。我国亦主动承担一定的降低碳排放任务,但是中国现阶段处于工业化以及快速城市化阶段,能源消费增加及建设用地扩张必然增加碳排放,因此,中国在碳减排方面压力巨大。近几年来,武汉市在经济、城市建设等各方面都发展迅速。但武汉市城市化的快速发展,吸引了更多的外来人口,导致武汉市城市规模迅速扩张,同时经济发展带来的土地需求增加也将增加武汉市碳减排的压力。研究武汉市土地利用碳排放的影响因素,可以从根本上找到降低武汉市土地利用碳排放的解决方法。本文首先根据武汉市2002-2012年各种土地利用类型数据以及能源消费数据,核算武汉市的净碳排放量及相关指标,并分析了武汉市碳排放总量、人均碳排放量等相关指标的时序特征,研究发现：建设用地与耕地为碳源,林地、水域、园地及草地为碳汇；建设用地碳排放变化决定武汉市净碳排放变化,同时建设用地碳排放来自于能源消费,即表明武汉市经济发展对于能源消费的依赖度很高。继而根据人均碳排放量和经济发展之间的关系进行了脱钩判断,发现武汉市在整个研究期内大都处于扩张脱钩水平以上其次,运用改进的Kaya恒等式及LMDI分解法对武汉市净碳排放进行了因素分解,分解为单位土地碳排放强度、上地利用结构、单位GDP用地强度、人均GDP和人口规模5个因素,然后运用LMDI分解方法计算各因素对碳排放的贡献值及贡献率,并分析在整个研究期内各个因素对碳排放的影响。研究结果表明,人均GDP、土地利用结构和人口规模是碳排放的拉动因素,其中,人均GDP对碳排放影响最大,土地利用结构次之,而人口规模相对较小。单位GDP用地强度和单位土地碳排放强度是碳减排的促进因素,其中单位GDP用地强度对碳减排促进极大,单位土地碳排放强度相对较小,但是其在整个研究期内波动较大。最后,依据前面的研究归纳主要结论,分别从经济发展、土地利用、人口规模以及政府宏观调控四个角度提出相应的政策建议。
[Abstract]:Carbon emissions cause global warming, cause widespread concern around the world, countries around the world actively promote the development of low-carbon economy. China is also taking the initiative to reduce carbon emissions, but China is now in the stage of industrialization and rapid urbanization, the increase of energy consumption and the expansion of construction land is bound to increase carbon emissions, therefore, China is under great pressure in terms of carbon emission reduction. In recent years, Wuhan City in the economy, urban construction and other aspects of rapid development. However, the rapid development of urbanization in Wuhan attracts more foreign population, which leads to the rapid expansion of urban scale in Wuhan. Meanwhile, the increase of land demand brought by economic development will also increase the pressure of carbon emission reduction in Wuhan. By studying the influencing factors of carbon emission from land use in Wuhan, we can find the solution to reduce carbon emission from land use in Wuhan. Based on the data of various land use types and energy consumption from 2002 to 2012, this paper calculates the net carbon emissions and related indicators of Wuhan, and analyzes the temporal characteristics of the related indicators, such as total carbon emissions, per capita carbon emissions, etc. The results show that: construction land and cultivated land are carbon source, woodland, water area, garden land and grassland are carbon sinks; carbon emissions from construction land determine the change of net carbon emissions in Wuhan, and carbon emissions from construction land come from energy consumption. That is to say, Wuhan's economic development is highly dependent on energy consumption. Then, according to the relationship between carbon emissions per capita and economic development, it is found that Wuhan is mostly above the level of expansion decoupling during the whole research period. Secondly, using the improved Kaya identity and LMDI decomposition method, we decompose the net carbon emissions of Wuhan into five factors: carbon emission intensity per unit land, land use structure, land intensity per unit GDP, GDP per capita and population scale. Then the contribution value and contribution rate of each factor to carbon emission were calculated by LMDI decomposition method, and the influence of each factor on carbon emission was analyzed during the whole study period. The results show that per capita GDP, land use structure and population scale are the driving factors of carbon emissions, among which, per capita GDP has the greatest impact on carbon emissions, followed by the structure of land use, while the population scale is relatively small. The land intensity per unit GDP and the carbon emission intensity per unit land are the promoting factors of carbon emission reduction. Among them, the land intensity per unit GDP promotes carbon emission reduction greatly, and the carbon emission intensity per unit land is relatively small, but it fluctuates greatly during the whole research period. Finally, according to the main conclusions of the previous research, this paper puts forward the corresponding policy recommendations from the four angles of economic development, land use, population scale and government macro-control.
【学位授予单位】：华中农业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F301.2;F205

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