基于灰色理论模型的山东省土地利用碳排放研究
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摘要
土地利用碳排放研究对合理配置土地资源、提高土地利用效率、实现节能减排具有重要意义。本文通过IPCC(Intergovernmental Panel on Climate Change)碳排放计算方法对山东省2009~2016年的土地利用碳排放进行测度,运用灰色关联分析方法论证耕地、园地、林地、居民点及工矿用地、交通运输用地、水利设施用地与碳排放的关联程度,并运用GM(1,1)灰色预测模型对山东省2017~2025年碳排放进行预测。结果表明,研究期2009~2016年碳排放总量、人均碳排放量、地均碳排放量呈上升趋势,碳排放强度呈下降趋势;六种地类与碳排放存在线性相关关系,对碳排放影响的主次程度分别为交通用地、居民点及工矿用地、水利设施用地、耕地、林地、园地;经预测到2019年,将实现单位GDP二氧化碳排放比2005年降低55%;到2025年,山东省碳排放总量约上升至59722万t,人均碳排放约5.684 t/人,地均碳排放量40.585 t/hm~2,碳排放强度约下降至0.376 t/万元。
The study on carbon emissions from land use is of great significance to the rational allocation of land resources,the improvement of land use efficiency and the realization of energy saving and emission reduction. In this paper, carbon emission from land use in Shandong Province from 2009 to 2016 was measured by IPCC(Intergovernmental Panel on Climate Change) carbon emission calculation method. The grey correlation analysis method was used to demonstrate the correlation degree between cultivated land, garden land, forest land, residential land, industrial and mining land,transportation land, water conservancy facilities land and carbon emission, and GM(1,1) grey prediction model was used to predict carbon emission of Shandong Province from 2017 to 2025. The results show that during the research period from2009 to 2016, the total carbon emissions, per capita carbon emission and per land carbon emission showed an upward trend,while the carbon emission intensity showed a downward trend. There is linear correlation between the six types of land and carbon emissions, the main and secondary impacts on carbon emissions are transportation land, residential land, industrial and mining land, water conservancy facilities land, arable land, forest land and garden land. By 2019, CO_2 emission per unit of GDP is projected to be 55% lower than in 2005, by 2025, the total carbon emission of Shandong Province will rise to59.722 million t, the per capita carbon emission will be about 5684 t/person, the per capita carbon emission will be about40.585 t/hm~2, and the carbon emission intensity will decrease to about 0.376 t/10,000 yuan.
The study on carbon emissions from land use is of great significance to the rational allocation of land resources,the improvement of land use efficiency and the realization of energy saving and emission reduction. In this paper, carbon emission from land use in Shandong Province from 2009 to 2016 was measured by IPCC(Intergovernmental Panel on Climate Change) carbon emission calculation method. The grey correlation analysis method was used to demonstrate the correlation degree between cultivated land, garden land, forest land, residential land, industrial and mining land,transportation land, water conservancy facilities land and carbon emission, and GM(1,1) grey prediction model was used to predict carbon emission of Shandong Province from 2017 to 2025. The results show that during the research period from2009 to 2016, the total carbon emissions, per capita carbon emission and per land carbon emission showed an upward trend,while the carbon emission intensity showed a downward trend. There is linear correlation between the six types of land and carbon emissions, the main and secondary impacts on carbon emissions are transportation land, residential land, industrial and mining land, water conservancy facilities land, arable land, forest land and garden land. By 2019, CO_2 emission per unit of GDP is projected to be 55% lower than in 2005, by 2025, the total carbon emission of Shandong Province will rise to59.722 million t, the per capita carbon emission will be about 5684 t/person, the per capita carbon emission will be about40.585 t/hm~2, and the carbon emission intensity will decrease to about 0.376 t/10,000 yuan.
引文
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[2]马晓哲,王铮.土地利用变化对区域碳源汇的影响研究进展[J].生态学报,2015,35(17):5898-5907
[3] Houghton RA, Hackler JL. Carbon Flux to the Atmosphere from Land-Use Changes:1850 to 1990[R]. Office of Scientific&Technical Information Technical Reports, 2001
[4] Singh MK, Astley H, Smith P, et al. Soil CO2-C flux and carbon storage in the dry tropics:impact of land-use change involving bioenergy crop plantation[J]. Biomass&Bioenergy, 2015,83:123-130
[5]曲福田,卢娜,冯淑怡.土地利用变化对碳排放的影响[J].中国人口·资源与环境,2011,21(10):76-83
[6]游和远,吴次芳.土地利用的碳排放效率及其低碳优化——基于能源消耗的视角[J].自然资源学报,2010,25(11):1875-1886
[7]杜官印.建设用地对碳排放的影响关系研究[J].中国土地科学,2010,24(5):32-36
[8]吴萌,任立,陈银蓉.城市土地利用碳排放系统动力学仿真研究——以武汉市为例[J].中国土地科学,2017,31(2):29-39
[9]张乐勤,陈素平,王文琴,等.安徽省近15年建设用地变化对碳排放效应测度及趋势预测——基于STIRPAT模型[J].环境科学学报,2013,33(3):950-958
[10]苏雅丽,张艳芳.陕西省土地利用变化的碳排放效益研究[J].水土保持学报,2011,25(1):152-156
[11]徐建华.现代地理学中的数学方法[M].北京:高等教育出版社,1996
[12]刘竹,耿涌,薛冰,等.城市能源消费碳排放核算方法[J].资源科学,2011,33(7):1325-1330
[13]李颖,黄贤金,甄峰.江苏省区域不同土地利用方式的碳排放效应分析[J].农业工程学报,2008(s2):102-107
[14]梁雪石,郭文栋,郑福云.黑龙江省建设用地变化对碳排放的影响[J].国土与自然资源研究,2014(4):15-17