摘要
Abstract
Cities are the epicenters of human activities,industrial production,transportation,and construction development,and are the focal points of high energy consumption and carbon emissions.Statistics indicate that 80%of global greenhouse gas emissions stem from urban areas.Clarifying the distribution of carbon emissions in urban space has important reference value for promoting low-carbon economy and comprehensive green transformation of social development.As an important cold coastal city in the Bohai Bay region,Dalian is affected by the ocean and its climate,and the spatial carbon emissions of the city in different seasons are also characterized by regional characteristics.In this paper,it combines high-resolution remote sensing and social perception data,SDGSAT-1 Glimmer Imager(10 m)and Baidu Map Wise Eye Date,to spatially simulate the carbon emissions of the cold coastal city blocks in the winter,utilizing spatial autocorrelation analysis to identify the spatial distribution of key carbon emission blocks and low-carbon emission potential blocks,combining land use data to explore the patterns of land use types in corresponding blocks of cold coastal cities,and finally determining the key spatial elements affecting blocks carbon emissions through correlation analysis.The results indicate that the carbon emission spatialization simulation method employed in this paper can reasonably and effectively simulate the carbon emission pattern and detailed differences.This method can be employed to study the spatial distribution of carbon emissions across different time periods.When viewed from the perspective of land use classification,the level of blocks carbon emissions in winter and the results of carbon emission intensity exhibit similarities,yet spatial distribution perspectives reveal discrepancies.The high carbon emission levels and intensities of city blocks in winter are predominantly associated with land designated for commercial services,public management and public services,and transportation.The city blocks with low carbon emission levels and intensity are primarily residential areas.Blocks exhibit spatial clustering characteristics from both the levels and intensities of carbon emissions,with the spatial clustering characteristics being more pronounced from the perspective of carbon emission intensity.Key blocks for high carbon emission are primarily commercial and service land,as well as public management and public service land,while blocks with low carbon emission potential are mainly residential areas adjacent to mountains and coastal areas.The area of the block,the floor area ratio of the block,and the average height of the building have different degrees of impact on the carbon emissions of the block.In key carbon emission blocks,there is a significant positive correlation between block area,total building surface area,and block carbon emission levels.Similarly,in blocks with low carbon emission potential,there is also a significant positive correlation between block area,floor area ratio,total building surface area,and block carbon emission levels.This indicates that an increase in the aforementioned indicators will lead to higher carbon emission levels in both types of typical blocks.In key carbon emission blocks,there is a significant positive correlation between floor area ratio,average building height,and block carbon emission intensity.Similarly,in blocks with low carbon emission potential,there is also a significant positive correlation between floor area ratio,average building height,total building surface area,and block carbon emission intensity.This indicates that an increase in the aforementioned indicators will lead to higher carbon emission levels in both types of typical blocks.And the low-carbon development focus of the block can be divided according to the shortest distance from the block to the sea.On this basis,a more accurate carbon emission reduction optimization strategy is constructed to help Dalian achieve the"Carbon Peaking and Carbon Neutrality Goals"in an orderly and efficient manner.关键词
寒地滨海城市/街区碳排放/空间化模拟/SDGSAT-1卫星微光影像/百度慧眼Key words
cold coastal city/blocks carbon emission/spatialization simulation/SDASAT-1 Glimmer Imager/Baidu Map Wise Eye分类
建筑与水利
