Because the static evaluation is unable to reflect the dynamic features of economic benefits and the contribution of sustainable development of low-carbon new energy to economic benefits is huge,this article puts forw...Because the static evaluation is unable to reflect the dynamic features of economic benefits and the contribution of sustainable development of low-carbon new energy to economic benefits is huge,this article puts forward the dynamic evaluation model of economic benefits under the development of low-carbon new energy.Total energy,energy consumption structure,industrial structure,GDP,total population and energy supply structure were taken as independent variables,and the carbon intensity was taken as the dependent variable.Through t-test and decision coefficient,total energy,energy consumption structure,GDP and total population were determined as the main factors of influencing low-carbon economy.Based on these four main factors,the dynamic evaluation index system of economic benefits was constructed.Experimental results show that the proposed model can comprehensively reflect the economic benefit level and the contribution of low-carbon new energy.Therefore,this method has high evaluation accuracy,which can provide scientific reference for the economic benefit management of relevant management departments.展开更多
An accurate simulation of air temperature at local scales is crucial for the vast majority of weather and climate applications.In this work,a hybrid statistical–dynamical downscaling method and a high-resolution dyna...An accurate simulation of air temperature at local scales is crucial for the vast majority of weather and climate applications.In this work,a hybrid statistical–dynamical downscaling method and a high-resolution dynamical-only downscaling method are applied to daily mean,minimum and maximum air temperatures to investigate the quality of localscale estimates produced by downscaling.These two downscaling approaches are evaluated using station observation data obtained from the Finnish Meteorological Institute over a near-coastal region of western Finland.The dynamical downscaling is performed with the Weather Research and Forecasting(WRF)model,and the statistical downscaling method implemented is the Cumulative Distribution Function-transform(CDF-t).The CDF-t is trained using 20 years of WRF-downscaled Climate Forecast System Reanalysis data over the region at a 3-km spatial resolution for the central month of each season.The performance of the two methods is assessed qualitatively,by inspection of quantile-quantile plots,and quantitatively,through the Cramer-von Mises,mean absolute error,and root-mean-square error diagnostics.The hybrid approach is found to provide significantly more skillful forecasts of the observed daily mean and maximum air temperatures than those of the dynamical-only downscaling(for all seasons).The hybrid method proves to be less computationally expensive,and also to give more skillful temperature forecasts(at least for the Finnish near-coastal region).展开更多
The integration of urban agglomeration road networks is an inevitable trend of regional development.It is very important to build a scientific and reasonable evaluation system for the integration of urban agglomeratio...The integration of urban agglomeration road networks is an inevitable trend of regional development.It is very important to build a scientific and reasonable evaluation system for the integration of urban agglomeration road networks.The existing research may not be sufficient to evaluate the road network level reliably if the city unit in the region is not considered enough.It is necessary to evaluate the level of road network integration from a dynamic perspective,in consideration of the economic scale of urban population and the level of road network in developing countries such as China is in the stage of rapid development.Therefore,this paper constructs an analytic hierarchy process(AHP)-catastrophe progression method evaluation model by considering the equilibrium degree and the fitness degree of urban unit road network.This evaluation model combines the integration of road network quantity,shape,and quality to evaluate the level of urban agglomeration road network integration from dynamic and static ways.Taking Beijing—Tianjin—Hebei urban agglomeration and Yangtze River Delta urban agglomeration as examples,this paper uses the road network data of urban agglomerations in 2010,2015,and2020 to make a comparative study.The results show that the growing trend of Yangtze River Delta urban agglomeration is at a high level by 2020,while the trend of Beijing—Tianjin—Hebei urban agglomeration is at a general level.Compared with the previous evaluation models,this evaluation method has a good explanation and can emphasize the consideration of dynamic evaluation.The research results annotate the current situation of road network integration of Beijing—Tianjin—Hebei and Yangtze River Delta urban agglomeration that can satisfy the requirement of urban agglomeration development.And it provides decision-making reference for further optimizing of the road network planning and layout of urban agglomeration.展开更多
文摘Because the static evaluation is unable to reflect the dynamic features of economic benefits and the contribution of sustainable development of low-carbon new energy to economic benefits is huge,this article puts forward the dynamic evaluation model of economic benefits under the development of low-carbon new energy.Total energy,energy consumption structure,industrial structure,GDP,total population and energy supply structure were taken as independent variables,and the carbon intensity was taken as the dependent variable.Through t-test and decision coefficient,total energy,energy consumption structure,GDP and total population were determined as the main factors of influencing low-carbon economy.Based on these four main factors,the dynamic evaluation index system of economic benefits was constructed.Experimental results show that the proposed model can comprehensively reflect the economic benefit level and the contribution of low-carbon new energy.Therefore,this method has high evaluation accuracy,which can provide scientific reference for the economic benefit management of relevant management departments.
基金Botnia-Atlantica, an EU-programme financing cross border cooperation projects in Sweden, Finland and Norway, for their support of this work through the WindCoE project
文摘An accurate simulation of air temperature at local scales is crucial for the vast majority of weather and climate applications.In this work,a hybrid statistical–dynamical downscaling method and a high-resolution dynamical-only downscaling method are applied to daily mean,minimum and maximum air temperatures to investigate the quality of localscale estimates produced by downscaling.These two downscaling approaches are evaluated using station observation data obtained from the Finnish Meteorological Institute over a near-coastal region of western Finland.The dynamical downscaling is performed with the Weather Research and Forecasting(WRF)model,and the statistical downscaling method implemented is the Cumulative Distribution Function-transform(CDF-t).The CDF-t is trained using 20 years of WRF-downscaled Climate Forecast System Reanalysis data over the region at a 3-km spatial resolution for the central month of each season.The performance of the two methods is assessed qualitatively,by inspection of quantile-quantile plots,and quantitatively,through the Cramer-von Mises,mean absolute error,and root-mean-square error diagnostics.The hybrid approach is found to provide significantly more skillful forecasts of the observed daily mean and maximum air temperatures than those of the dynamical-only downscaling(for all seasons).The hybrid method proves to be less computationally expensive,and also to give more skillful temperature forecasts(at least for the Finnish near-coastal region).
基金supported by the Hebei Key Research and Development Program(22370801D)the Hebei Province Yanzhao Golden Terrace Talent Program Key Talent Project(Education Platform)(HJZD202514)the National Natural Science Foundation of China,China(52172304,52372302)。
文摘The integration of urban agglomeration road networks is an inevitable trend of regional development.It is very important to build a scientific and reasonable evaluation system for the integration of urban agglomeration road networks.The existing research may not be sufficient to evaluate the road network level reliably if the city unit in the region is not considered enough.It is necessary to evaluate the level of road network integration from a dynamic perspective,in consideration of the economic scale of urban population and the level of road network in developing countries such as China is in the stage of rapid development.Therefore,this paper constructs an analytic hierarchy process(AHP)-catastrophe progression method evaluation model by considering the equilibrium degree and the fitness degree of urban unit road network.This evaluation model combines the integration of road network quantity,shape,and quality to evaluate the level of urban agglomeration road network integration from dynamic and static ways.Taking Beijing—Tianjin—Hebei urban agglomeration and Yangtze River Delta urban agglomeration as examples,this paper uses the road network data of urban agglomerations in 2010,2015,and2020 to make a comparative study.The results show that the growing trend of Yangtze River Delta urban agglomeration is at a high level by 2020,while the trend of Beijing—Tianjin—Hebei urban agglomeration is at a general level.Compared with the previous evaluation models,this evaluation method has a good explanation and can emphasize the consideration of dynamic evaluation.The research results annotate the current situation of road network integration of Beijing—Tianjin—Hebei and Yangtze River Delta urban agglomeration that can satisfy the requirement of urban agglomeration development.And it provides decision-making reference for further optimizing of the road network planning and layout of urban agglomeration.
