摘要
针对不同城市碳排放达峰以及建设用地演变特点,差异化实施城市达峰策略具有重要意义,以安徽省16个地级市为例,在核算碳排放与分析建设用地演变特征的基础上,通过Kaya恒等式,对各地级市的碳排放峰值以及建设用地规模进行预测,并运用聚类分析对各类城市提出达峰管控对策。结果表明:1)合肥市、亳州市、蚌埠市、阜阳市、淮南市、芜湖市、宿州市、滁州市、六安市、池州市以及黄山市均有可能在2030年前达峰;马鞍山市、宣城市、铜陵市和安庆市在2030年前达峰存在一定的风险,而淮北市在2014年就已经出现碳排放峰值。2)安徽省各地级市碳排放与建设用地规模之间的回归拟合均有强相关性,可在此基础上进行城市建设用地规模预测。3)安徽省各地级市根据聚类特征可分为达峰攻坚型、达峰潜力型、达峰示范型以及达峰优势型4类。
According to the characteristics of carbon emissions peaking in different cities and the evolution of construction land,it is of great significance to implement the strategy of urban peaking differently.Taking 16 prefecture-level cities in Anhui Province as an example,based on the calculation of carbon emissions and the analysis of the evolution characteristics of construction land,Kaya identity was used to predict the peak carbon emissions of each prefecture-level city and the scale of construction land.Finally,cluster analysis is used to put forward countermeasures of peak management and control for various cities.The results show that:1)Hefei,Bozhou,Bengbu,Fuyang,Huainan,Wuhu,Suzhou,Chuzhou,Lu'an,Chizhou and Huangshan are all likely to reach the peak before 2030;Maanshan city,Xuancheng city,Tongling city and Anqing city are at certain risk of peaking before 2030,while Huaibei city already saw its carbon emissions peak in 2014.2)The regression fitting between carbon emission and construction land scale of prefecture-level cities in Anhui Province has a strong correlation,which can be used to predict the scale of urban construction land.3)According to the clustering characteristics,prefecture-level cities in Anhui Province can be divided into four categories:peak attack type,peak potential type,peak demonstration type and peak advantage type.
作者
程宏晟
於冉
汪沁
叶芸
魏露
CHENG Hongsheng;YU Ran;WANG Qin;YE Yun;WEI Lu(School of Economics and Management,Anhui Agricultural University,Hefei 230036;Institute of Land and Resources,Anhui Agricultural University,Hefei 230036)
出处
《安徽农业大学学报》
CAS
CSCD
2023年第2期310-318,共9页
Journal of Anhui Agricultural University
基金
国家自然科学基金(71873003)
安徽省教育厅人文社科重点项目(SK2019A0130)
安徽省自然科学基金项目(1908085QG310)
安徽省高等学校人文社会科学研究项目(YJS20210255)共同资助。
