City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordi...City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management,realize sustainable development,and assist China in achieving the carbon peaking and carbon neutrality goals.This paper applies the improved gravity model and social network analysis(SNA)to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the Yangtze River Delta(YRD)city cluster in China and its influencing factors.The results demonstrate that:1)the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure.The network association number and density show an upward trend,indicating closer spatial association between cities,but their values remain generally low.Meanwhile,the network hierarchy and network efficiency show a downward trend but remain high.2)The spatial association network of carbon emissions in the YRD city cluster shows an obvious‘core-edge’distribution pattern.The network is centered around Shanghai,Suzhou and Wuxi,all of which play the role of‘bridges’,while cities such as Zhoushan,Ma'anshan,Tongling and other cities characterized by the remote location,single transportation mode or lower economic level are positioned at the edge of the network.3)Geographic proximity,varying levels of economic development,different industrial structures,degrees of urbanization,levels of technological innovation,energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster.Finally,policy implications are provided from four aspects:government macro-control and market mechanism guidance,structural characteristics of the‘core-edge’network,reconfiguration and optimization of the spatial layout of the YRD city cluster,and the application of advanced technologies.展开更多
Oilfield treated oil pipeline network is the link connecting the upstream oilfields and the downstream refineries.Due to the differences in operating costs and transportation fee between different pipelines and the fl...Oilfield treated oil pipeline network is the link connecting the upstream oilfields and the downstream refineries.Due to the differences in operating costs and transportation fee between different pipelines and the fluctuation in the demand and sales prices of the treated oil,there is an optimal flow allocation plan for the pipeline network to make the oilfield company obtain the highest social and economic benefit.In this study,a mixed integer nonlinear programming(MINLP)model is developed to determine the optimal flow rate allocation plan of the large-scale and complex treated oil pipeline network,and both the social and economic benefits are considered simultaneously.The optimization objective is the multi-objective which includes the largest user satisfaction and the highest economic benefit.The model constraints include the oilfield production capacity,refinery demand,pipeline transmission capacity,flow,pressure,and temperature of the node and station,and the pipeline hydraulic and thermal calculations.Python 3.7 is utilized for the programming of the off-line calculation procedure and the MINLP model,and GUROBI 9.0.2 is served as the MINLP solver.Moreover,the model is applied to a real treated oil pipeline network located in China,and three optimization scenarios are analyzed.For social benefit,the values of the user satisfaction of each refinery and the total network are 1 before and after optimization for scenarios 1,2,and 3.For economic benefit,the annual revenue can be increased by 0.227,0.293,and 0.548 billion yuan after the optimization in scenario 1,2,and 3,respectively.展开更多
基金Under the auspices of the National Natural Science Foundation of China (No.72273151)。
文摘City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management,realize sustainable development,and assist China in achieving the carbon peaking and carbon neutrality goals.This paper applies the improved gravity model and social network analysis(SNA)to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the Yangtze River Delta(YRD)city cluster in China and its influencing factors.The results demonstrate that:1)the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure.The network association number and density show an upward trend,indicating closer spatial association between cities,but their values remain generally low.Meanwhile,the network hierarchy and network efficiency show a downward trend but remain high.2)The spatial association network of carbon emissions in the YRD city cluster shows an obvious‘core-edge’distribution pattern.The network is centered around Shanghai,Suzhou and Wuxi,all of which play the role of‘bridges’,while cities such as Zhoushan,Ma'anshan,Tongling and other cities characterized by the remote location,single transportation mode or lower economic level are positioned at the edge of the network.3)Geographic proximity,varying levels of economic development,different industrial structures,degrees of urbanization,levels of technological innovation,energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster.Finally,policy implications are provided from four aspects:government macro-control and market mechanism guidance,structural characteristics of the‘core-edge’network,reconfiguration and optimization of the spatial layout of the YRD city cluster,and the application of advanced technologies.
基金the Natural Science Foundation of Chongqing,China (No.cstc2021jcyj-msxmX0918)the Science and Technology Research Program of Chongqing Municipal Education Commission (No.KJQN202101545)+1 种基金the National Natural Science Foundation of China (52302402)the Research Foundation of Chongqing University of Science and Technology (ckrc2021003)for providing support for this work.
文摘Oilfield treated oil pipeline network is the link connecting the upstream oilfields and the downstream refineries.Due to the differences in operating costs and transportation fee between different pipelines and the fluctuation in the demand and sales prices of the treated oil,there is an optimal flow allocation plan for the pipeline network to make the oilfield company obtain the highest social and economic benefit.In this study,a mixed integer nonlinear programming(MINLP)model is developed to determine the optimal flow rate allocation plan of the large-scale and complex treated oil pipeline network,and both the social and economic benefits are considered simultaneously.The optimization objective is the multi-objective which includes the largest user satisfaction and the highest economic benefit.The model constraints include the oilfield production capacity,refinery demand,pipeline transmission capacity,flow,pressure,and temperature of the node and station,and the pipeline hydraulic and thermal calculations.Python 3.7 is utilized for the programming of the off-line calculation procedure and the MINLP model,and GUROBI 9.0.2 is served as the MINLP solver.Moreover,the model is applied to a real treated oil pipeline network located in China,and three optimization scenarios are analyzed.For social benefit,the values of the user satisfaction of each refinery and the total network are 1 before and after optimization for scenarios 1,2,and 3.For economic benefit,the annual revenue can be increased by 0.227,0.293,and 0.548 billion yuan after the optimization in scenario 1,2,and 3,respectively.