Research On The Simulation, Pattern And Mechanism Of The Spatial-temporal Characteristics Of Carbon Emission From Energy Consumption In Bohai Rim Region Using Nighttime Light Imageries

Global warming,as one of the most significant global environment problem,has been affecting and threatening the natural environment and human society.Greenhouse gases released by large-scale human activities,has been deeply disturbed the natural carbon cycle;and CO₂ from fossil fuel energy consumption accounts for as much as60%of the overall greenhouse gas emissions,known as the primary contributor of climate warming.Due to the lack of detailed statistical data,most of energy consumption research used to focus on large-scale,such as national,provincial level;this disadvantage brings about difficulties and challenges to establish regional,detailed and different CO₂ reduction strategy.As of 2008,CO₂ emissions of China was up to8.325 billion tones,surpassing the United States as the world's top carbon emitter.The Bohai Rim region is the third economic growth pole of China,as well as the energy consumption dense area with a high proportion of coal energy structure,a large proportion of heavy industry.All this led the region to become a main source of man-made carbon emissions.Nighttime light data makes it possible to observe human activities at night.Because of human activity is the main source of carbon emissions,and the nighttime light imageries can effectively reflect the intensity of human activities.Therefore,nighttime light imageries can be used to estimate carbon emissions.Based on multi-source data,such as DMSP/OLS nighttime light data,social and economic statistical data,and the basic geographic information data,we simulate and estimate CO₂ emissions in the Bohai Rim region at different scales through down scaling method.Then the time series changes,spatial distribution characteristics and spatial evolution patterns of CO₂ emissions are analyzed in sequence by the time change curve,spatial hierarchical division and spatial autocorrelation method.From the perspective of spatial heterogeneity and interaction of geographical factors,we use Geodetector software to reveal the influence mechanism of CO₂ emissions in the Bohai Rim region.The main conclusions are as follows:?1?A series of data processing are performed to correct DMSP/OLS nighttime stable data from 1992 to 2013,such as intercalibration,intra-annual composition and inter-annual series correction.Then we proposed"potential area"concept using NPP/VIIRS data,this method can effectively reduce the low value in non-light area.The correlation coefficients between the total DN value and CO₂ emissions of Beijing,Tianjin,Heibei,Liaoning,Shandong and the Bohai Rim region are increased by-0.00794,0.00396,0.01647,0.00396,0.00047,0.00403.The R² of one-dimensional linear regression of Beijing,Tianjin,Heibei,Liaoning and Shandong are increased by0.0146,0.0075,0.0320,0.0155,0.0001.In addition to Beijing,the correlation coefficients and the R² are all improved effectively,simulation become more realistic.?2?Time series change of CO₂ emissions:total CO₂ emissions,total CO₂ emissions has showed an increasing trend from 852.21 million tons to 852.21 million tons from1992 to 2013,about 3.8 times than the previous.Before 2000,total CO₂ emissions from high to low are Liaoning,Hebei,Shandong,Beijing and Tianjin respectively;and after2000,total CO₂ emissions from high to low are Shandong,Hebei,Liaoning,Tianjin and Beijing.Time phasing is obvious from 1992 to 2013.CO₂ emissions intensity per capita,it has been increasing continuously from 3.5 tons to 12.5 tons.In addition to Beijing,other units are all presents an increasing trend,Tianjin,Liaoning are higher than the average,while Hebei,Shandong are lower than the average.CO₂ emissions intensity per unit of GDP,it shows and evident decreasing trend from 10.0 tones/ten thousand yuan to 2.1 tones/ten thousand yuan from 1992 to 2013.Liaoning,Hebei are higher than the average,while Shandong,Tianjin,Beijing are lower than the average.?3?Spatial distribution characteristics of CO₂ emissions at municipal level,total CO₂ emissions,it continues to increase on the whole,and presents a high in the central region,low in the south and north region.CO₂ emissions intensity per capita,it shows a trend from low to high at municipal level,gradually forms the Shenyang-Dalian,Beijing-Tianjin-Tangshan,and Jinan-Qingdao three high value areas.CO₂ emissions intensity per unit of GDP,it shows a trend from high to low at municipal level,especially along Jing-Shen line and Shen-Da line.?4?Spatial distribution characteristics of CO₂ emissions at county level,total CO₂emissions,total CO₂ emissions increases year by year at county level from 1992 to 2013,develops from high values scattering in city center to concentrating in a wide strip.On the whole,the coastal orientation is obvious,presents an"C"distributed along Bohai bay;and forms three high CO₂ emissions areas,the"people"distribution with Beijing-Shenyang line and Shenyang-Dalian line,the"italic I"distribution with Beijing-Tianjin-Hebei area,and the"O"distribution with Jinan-Dongying and Qingdao-Weihai.The directivity in transportation is obvious.CO₂emissions intensity per capita,it shows a trend from low to high at county level from 2000 to 2010,develops from high-low values staggered distribution to High values spreading over the whole region,presents a core-periphery distribution structure.CO₂emissions intensity per unit of GDP,it shows a trend from high to low at county level from 2000 to 2010;High value areas shrinks from spreading over the whole region to concentrating on Shenyang,Tianjin,while low value areas gradually expand the entire Bohai Rim region.?5?Spatial pattern evolution of CO2 emissions:At municipal level,Global Moran's I are 0.0254,0.0676,0.0331 respectively in 1993,2003,2013;CO2 emissions has an obvious positive correlation feature;The LISA cluster did not change much,H-H clusters are Beijing,Tianjin,and L-L cluster is Chaoyang.At county level,Global Moran's I are 0.2135,0.2221,0.2014 respectively in 1993,2003,2013;CO2 emissions also has an obvious positive correlation feature,and the aggregation intensity increased;The LISA cluster changed obviously,H-H clusters expanded from Beijing,central Liaoning to Beijing-Tianjin,Jinan-Qingdao,L-L still distributed in the north and west of Hebei,quantity and range are both increased.?6?From the perspective of spatial heterogeneity and interaction of geographical factors,we use Geodetector software to reveal the influence mechanism of CO₂emissions in the Bohai Rim region.The q-statistic value of each factor from high to low are GDP?0.7671?>population?0.6415?>energy structure?0.4095?>energy intensity?0.2590?>urbanization rate?0.2254?>road density?0.1938?>industrial structure?0.1230?>fixed assets rate?0.1108?.The interaction which are over 9 are population-GDP?0.9116?,population-energy intensity?0.9101?,GDP-energy structure?0.9322?,GDP-industrial structure?0.9439?,GDP-fixed assets rate?0.9077?.As the"basic factors",GDP and population decide the main body of total CO₂emissions,while other"auxiliary factors",such as energy structure,energy intensity and urbanization rate,their individual effect is limited,only combined with"basic factors",can the interaction effect be maximized.