Spatial pattern and coordination division of carbon emissions of county land use in Hebei province
Land use change is the main driving force of regional carbon emissions change.Studying the impact of land use change on carbon emissions will help to formulate carbon emission policies.Based on the current land use data and energy consumption data,a carbon emission evaluation model was built to calculate the land use carbon emissions of Hebei province from 2000 to 2020.The standard deviation ellipse model was used to explore the spatial pattern distribution charac-teristics of carbon emissions in the study area.Based on the economic contribution coefficient of carbon emissions and the carbon ecological carrying coefficient,the carbon balanced zoning scheme and optimization countermeasures were proposed.The results showed that,from 2000 to 2020,the total carbon emissions of Hebei province showed an obvious upward trend,rised from 9.01×107 t to 2.75×108 t,the growth rate of carbon emissions from 2000 to 2010 im-proved rapidly,and the growth of carbon emissions from 2010 to 2020 was relatively slow.The carbon emission in-tensity of Hebei province presented a spatial distribution characteristic with multi-circle structure,mainly centered around the resource-based cities and spreaded outward in a circle structure,and the sub circle structure of Shijiazhuang and Cang-zhou core urban areas gradually became apparent.The spatial characteristics of the economic contribution coefficient of car-bon emissions of counties in Hebei province were low in four directions and were high in the middle,and the carbon ecolog-ical carrying coefficient was high in the northwest and was low in the southeast.Based on the carbon balance analysis,He-bei province was divided into carbon sink functional area,low carbon conservation area,economic development area,car-bon sink development area and high carbon optimization area,and corresponding development strategies were proposed.
land usecarbon emissioncarbon ecological carrying capacitybalanced partition
万方数据
维普
