京津冀城市群低碳经济联系强度分形特征分析
|
摘要
应用分形理论与方法,从低碳经济视角分析京津冀城市群特征,考量京津冀一体化进程的发展现状。首先,建立"全碳排"核算模型,测算京津冀城市群中单个城市在社会经济发展过程中的资源消耗与污染排放。然后,以单位CO2排放人口支撑、GDP产出和道路面积承载为主要因素,建立低碳经济联系强度引力模型和分维值测度模型,计算2006—2016年分别以北京和天津作为辐射中心源的低碳经济联系强度,并采用源强叠加原理计算"京–津"双中心源辐射的叠加效应,进而分析比较单源辐射与双源辐射叠加的差异。再后,选取代表性年份进行基于ArcGIS的低碳经济联系强度空间分析,旨在找出单源辐射联系强度空间分布的差异对双源辐射叠加分维值的影响规律。最后,以雄安新区作为第3个辐射中心源,计算并分析三源辐射叠加的情况。分维值计算和分析结果显示:2006—2016年京津冀城市群双源叠加的低碳经济联系强度分维值呈倒U型分布,峰值出现在2012年,说明2012年京、津双源对城市群内其他城市的低碳经济联合辐射效果最佳;2007和2014两个年份,分别以北京和天津作为中心源的低碳经济联系强度分维值差异较大,导致双源叠加后的分维值出现倒挂现象,即双源叠加后的分维值低于单源辐射能力较强者,说明双源联合辐射效果较差。基于ArcGIS的低碳经济联系强度空间分析结果显示:2012年"京–津"双中心源辐射的低碳经济联系强度源叠加结果呈现合理的空间分布——梯度有序且圈层分明,是分维值达峰的主要原因。雄安新区作为第3个中心源加入后,京津冀城市群低碳经济联系强度分维值明显提高。
Fractal theory and method is applied to analyze the characteristics of low carbon economy connectivity of Jing-Jin-Ji urban agglomeration. Firstly, a "full carbon emission" accounting model is established to calculate the resource consumption and pollution emissions of a single city in Jing-Jin-Ji urban agglomeration in the process of social and economic development. Secondly, the low carbon economic connectivity gravity model and the fractal dimension measurement model are set up to calculate and evaluate the low carbon economic connectivity which centered on Beijing and Tianjin in 2006–2016. There are three main factors in the connectivity gravity model: the population support, GDP output and the road bear of every unit CO2 emission. Furthermore, in order to compare and analyze the difference between the single-point radiation source and the double-point source radiation, the superposition effect of the "Jing-Jin" twin-city radiation is calculated according the principle of source superposition. Thirdly, in order to find out the law of the influence of the spatial distribution of single-point radiation connection intensity on the fractal dimension of the source superposition, the representative years are selected to carry out spatial analysis of low carbon economic connectivity based on the tool of ArcGIS. Finally,Xiong'an New Area is treated as the the third radiation center point to calculate and analyze the three-point source radiation superposition. The fractal dimension calculation and analysis results show that in 2006—2016, the low carbon economic connectivity of the Jing-Jin-Ji urban agglomeration have an inverted U-shaped distribution and the peak appears in 2012, which reflect that Beijing and Tianjin had the best combination of low-carbon economy radiation in the urban agglomeration in 2012. The differences of the fractal dimension of low-carbon economic connectivity are very large between Beijing as the central radiation source and Tianjin as the central radiation source in 2007 and 2014, and the inversion of the fractal dimension appears after the dual source superposition, that is the fractal dimension after superposition is lower than the one with higher radiation capacity in a single source,which means that the twin-city linkage is in low effect. The spatial analysis results of low carbon economic connectivity based on ArcGIS show that in 2012, the results of the "Jing-Jin" twin-city radiation low-carbon economic connectivity source superposition shows a reasonable spatial distribution—gradient order and distinct layers, which is the main reason for the peak value of fractal dimension. When Xiong'an New Area is added as the third central radiation source, the fractal dimension of the low carbon economic connectivity of the Jing-Jin-Ji urban agglomeration can be significantly improved.
Fractal theory and method is applied to analyze the characteristics of low carbon economy connectivity of Jing-Jin-Ji urban agglomeration. Firstly, a "full carbon emission" accounting model is established to calculate the resource consumption and pollution emissions of a single city in Jing-Jin-Ji urban agglomeration in the process of social and economic development. Secondly, the low carbon economic connectivity gravity model and the fractal dimension measurement model are set up to calculate and evaluate the low carbon economic connectivity which centered on Beijing and Tianjin in 2006–2016. There are three main factors in the connectivity gravity model: the population support, GDP output and the road bear of every unit CO2 emission. Furthermore, in order to compare and analyze the difference between the single-point radiation source and the double-point source radiation, the superposition effect of the "Jing-Jin" twin-city radiation is calculated according the principle of source superposition. Thirdly, in order to find out the law of the influence of the spatial distribution of single-point radiation connection intensity on the fractal dimension of the source superposition, the representative years are selected to carry out spatial analysis of low carbon economic connectivity based on the tool of ArcGIS. Finally,Xiong'an New Area is treated as the the third radiation center point to calculate and analyze the three-point source radiation superposition. The fractal dimension calculation and analysis results show that in 2006—2016, the low carbon economic connectivity of the Jing-Jin-Ji urban agglomeration have an inverted U-shaped distribution and the peak appears in 2012, which reflect that Beijing and Tianjin had the best combination of low-carbon economy radiation in the urban agglomeration in 2012. The differences of the fractal dimension of low-carbon economic connectivity are very large between Beijing as the central radiation source and Tianjin as the central radiation source in 2007 and 2014, and the inversion of the fractal dimension appears after the dual source superposition, that is the fractal dimension after superposition is lower than the one with higher radiation capacity in a single source,which means that the twin-city linkage is in low effect. The spatial analysis results of low carbon economic connectivity based on ArcGIS show that in 2012, the results of the "Jing-Jin" twin-city radiation low-carbon economic connectivity source superposition shows a reasonable spatial distribution—gradient order and distinct layers, which is the main reason for the peak value of fractal dimension. When Xiong'an New Area is added as the third central radiation source, the fractal dimension of the low carbon economic connectivity of the Jing-Jin-Ji urban agglomeration can be significantly improved.
引文
[1]张可云,蔡之兵.京津冀协同发展历程、制约因素及未来方向.河北学刊,2014,34(6):101-105
[2]王莹莹,童玉芬.首都圈劳动力空间分布格局的形成机制--基于新经济地理学的解释.人口与经济,2017(1):35-43
[3]Tan Feifei,Lu Zhaohua.Current status and future choices of regional sectors-energy-related CO2 emissions:the third economic growth pole of China.Applied Energy,2015,159:237-251
[4]何筠,何洋,江章学.我国地区间产业梯度转移的深层次影响因素研究--基于长江经济带的省际地区动态面板数据.生态经济,2018,34(6):117-121
[5]刘超,许月卿,刘焱序,等.基于系统论的土地利用多功能分类及评价指标体系研究.北京大学学报(自然科学版),2018,54(1):181-188
[6]Gefen Y,Mandelbrot B B,Aharony A.Critical phenomena on fractal lattices.Physical Review Letters,2016,45(11):855-858
[7]王海军,张彬,刘耀林,等.基于重心-GTWR模型的京津冀城市群城镇扩展格局与驱动力多维解析.地理学报,2018,73(6):1076-1092
[8]孟德友,赵文亮.基于时间距离的河南城市经济联系及其空间结构.城市发展研究,2011(6):104-110
[9]王海江,苗长虹,乔旭宁.黄河经济带中心城市服务能力的空间格局.经济地理,2017,37(7):33-39
[10]魏丽华.我国三大城市群内部经济联系对比研究.经济纵横,2018(1):45-54
[11]倪维秋,廖茂林.高速铁路对中国省会城市旅游经济联系的空间影响.中国人口·资源与环境,2018,28(3):160-168
[12]芦佩.京津冀城市群空间结构优化研究[D].秦皇岛:燕山大学,2017
[13]张雪花,郭怀成,张宏伟.区域经济联系强度的分维特征分析及其在我国西部地区的应用.北京大学学报(自然科学版),2007,43(2):245-250
[14]李泽宇,董春,张玉.东北三省城市区域经济联系强度.遥感信息,2018,33(2):108-113
[15]张雪花,李响,叶文虎,等.“全碳排”核算与碳绩效评价方法研究.北京大学学报(自然科学版),2015,51(4):639-646
[16]刘爽爽,王钧,许晔,等.基于建筑能耗特征的城市建筑碳减排研究--以深圳市为例.北京大学学报(自然科学版),2018,54(1):125-136
[17]张英华,于君涛,张建宇.京津冀区域制造业碳排放的现状与对策研究.天津师范大学学报(社会科学版),2016,5(1):41-45
[18]原青青,叶堂林.我国三大城市群发展质量评价研究.前线,2018,3(7):35-37
[19]杨洋,张倩倩.碳减排绝对量约束目标下京津冀低碳经济发展路径分析.软科学,2015,29(11):105-109
[20]白璐,赵增锋.低碳经济发展评价指标体系构建及实证研究--以京津冀城市群为例.江苏农业科学,2015,43(10):561-564
[21]Odum H T.Self-organization,transformity and information.Science,1988,242:1132-1139
[22]Fang Delin,Chen Bin.Linkage analysis for watercarbon nexus in China.Applied Energy,2018,225:682-695
[23]陈彬,杨维思.产业园区碳排放核算方法研究.中国人口·资源与环境,2017,27(3):1-10
[24]王少剑,苏泳娴,赵亚博.中国城市能源消费碳排放的区域差异、空间溢出效应及影响因素.地理学报,2018,73(3):414-428
[25]Odum H T,Odum E P.Trophic structure and productivity of a windward coral reef community on Eniwetok Atoll.Ecological Monographs,1955,25(3):291-320
[26]李日富,文光才.采动影响稳定区煤层气资源量分源叠加评估模型.煤炭科学技术,2015,43(10):116-121
[27]李后强,艾南山.具有黄金分割特征和分形性质的市场网络.经济地理,1992(4):1-5
(1)https://www.yicai.com/news/5350934.html
[2]王莹莹,童玉芬.首都圈劳动力空间分布格局的形成机制--基于新经济地理学的解释.人口与经济,2017(1):35-43
[3]Tan Feifei,Lu Zhaohua.Current status and future choices of regional sectors-energy-related CO2 emissions:the third economic growth pole of China.Applied Energy,2015,159:237-251
[4]何筠,何洋,江章学.我国地区间产业梯度转移的深层次影响因素研究--基于长江经济带的省际地区动态面板数据.生态经济,2018,34(6):117-121
[5]刘超,许月卿,刘焱序,等.基于系统论的土地利用多功能分类及评价指标体系研究.北京大学学报(自然科学版),2018,54(1):181-188
[6]Gefen Y,Mandelbrot B B,Aharony A.Critical phenomena on fractal lattices.Physical Review Letters,2016,45(11):855-858
[7]王海军,张彬,刘耀林,等.基于重心-GTWR模型的京津冀城市群城镇扩展格局与驱动力多维解析.地理学报,2018,73(6):1076-1092
[8]孟德友,赵文亮.基于时间距离的河南城市经济联系及其空间结构.城市发展研究,2011(6):104-110
[9]王海江,苗长虹,乔旭宁.黄河经济带中心城市服务能力的空间格局.经济地理,2017,37(7):33-39
[10]魏丽华.我国三大城市群内部经济联系对比研究.经济纵横,2018(1):45-54
[11]倪维秋,廖茂林.高速铁路对中国省会城市旅游经济联系的空间影响.中国人口·资源与环境,2018,28(3):160-168
[12]芦佩.京津冀城市群空间结构优化研究[D].秦皇岛:燕山大学,2017
[13]张雪花,郭怀成,张宏伟.区域经济联系强度的分维特征分析及其在我国西部地区的应用.北京大学学报(自然科学版),2007,43(2):245-250
[14]李泽宇,董春,张玉.东北三省城市区域经济联系强度.遥感信息,2018,33(2):108-113
[15]张雪花,李响,叶文虎,等.“全碳排”核算与碳绩效评价方法研究.北京大学学报(自然科学版),2015,51(4):639-646
[16]刘爽爽,王钧,许晔,等.基于建筑能耗特征的城市建筑碳减排研究--以深圳市为例.北京大学学报(自然科学版),2018,54(1):125-136
[17]张英华,于君涛,张建宇.京津冀区域制造业碳排放的现状与对策研究.天津师范大学学报(社会科学版),2016,5(1):41-45
[18]原青青,叶堂林.我国三大城市群发展质量评价研究.前线,2018,3(7):35-37
[19]杨洋,张倩倩.碳减排绝对量约束目标下京津冀低碳经济发展路径分析.软科学,2015,29(11):105-109
[20]白璐,赵增锋.低碳经济发展评价指标体系构建及实证研究--以京津冀城市群为例.江苏农业科学,2015,43(10):561-564
[21]Odum H T.Self-organization,transformity and information.Science,1988,242:1132-1139
[22]Fang Delin,Chen Bin.Linkage analysis for watercarbon nexus in China.Applied Energy,2018,225:682-695
[23]陈彬,杨维思.产业园区碳排放核算方法研究.中国人口·资源与环境,2017,27(3):1-10
[24]王少剑,苏泳娴,赵亚博.中国城市能源消费碳排放的区域差异、空间溢出效应及影响因素.地理学报,2018,73(3):414-428
[25]Odum H T,Odum E P.Trophic structure and productivity of a windward coral reef community on Eniwetok Atoll.Ecological Monographs,1955,25(3):291-320
[26]李日富,文光才.采动影响稳定区煤层气资源量分源叠加评估模型.煤炭科学技术,2015,43(10):116-121
[27]李后强,艾南山.具有黄金分割特征和分形性质的市场网络.经济地理,1992(4):1-5
(1)https://www.yicai.com/news/5350934.html