Assessment Of Industrial Carbon Emission Characteristics Based On Multi-Source Data

Industrial carbon emissions are the main source of China’s carbon emissions,and the increase of carbon dioxide（CO₂）concentration caused by industrial carbon emissions plays an important role in climate change.Fully understanding the spatial-temporal characteristics of industrial carbon emissions and its relationship with atmospheric CO₂change is a key prerequisite for formulating reasonable and effective emission reduction measures.However,statistical data related to industrial carbon emissions often have problems such as lack of data and accuracy verification.Therefore,it is urgent to build the evaluation model of industrial carbon emission characteristics based on multi-source data.This thesis aims to evaluate the characteristics of industrial carbon emissions from multiple dimensions,such as spatial-temporal distribution,emission intensity,emission efficiency and emission composition using the carbon emission inventory and multi-source satellite remote sensing data,and analyze and simulate the impact of industrial carbon emissions on atmospheric CO₂ column concentration（XCO₂）.Firstly,industrial carbon emissions were spatialized by using industrial land density distribution,so as to obtain the spatial and temporal distribution of industrial carbon emissions with high spatial resolution.Then,it is proposed to industrial carbon emission characteristics from the aspects of industrial carbon emission intensity,emission efficiency and emission composition by using the comprehensive satellite observation characteristics of XCO₂,SO₂,and NO₂.Finally,the gridded industrial emissions and GEOS-Chem atmospheric transport model were used to simulate the distribution of atmospheric XCO₂concentration in China under different conditions by scenario analysis,so as to quantitatively analyze the impact of industrial carbon emissions in different regions on atmospheric XCO₂.The main research contents and conclusions include:（1）The spatial decomposition of carbon emissions usually focuses on the total amount of carbon emissions,and there is still a lack of high spatial resolution gridded data of industrial carbon emissions.This thesis proposes a spatial decomposition method of carbon emissions based on industrial land density.and comparison is made with MIX inventory,China High Resolution Emission Database（CHRED）and Open-source Data Inventory for Anthropogenic CO₂（ODIAC）.The results show that the 1km resolution gridded industrial carbon emissions can effectively provide the fine spatial distribution of industrial carbon emissions,and significantly improve the underestimation of industrial carbon emissions.Secondly,GOSATCO₂ flux data is used to estimate industrial carbon emissions at the city level.The verification results show that the average relative error of182 cities is 56.11%,among which the relative error of 62 cities is less than 30%.Finally,the temporal and spatial characteristics of industrial carbon emissions from 2009 to 2017were analysed from the provincial level and grid level.And results show that,at the level of provinces and cities,the rapid growth of industrial carbon emissions is mainly located in the north of China,which corresponds to the high emission efficiency in the south.The number of cities with high industrial carbon emissions（>50Mt）experienced rapid growth from 2009 to 2012 and peaked in 2017.The autocorrelation and dispersion of municipal industrial carbon emissions have decreased during the twists and turns.The significant cold spots mainly concentrated in the southwest of China,and the centroid moved to the southeast,while the hot spots mainly concentrated in the northeast of China,and the centroid moved to the northwest.（2）In view of the lack of statistical data on industrial carbon emission characteristics.This paper proposes to evaluate the emission intensity,emission efficiency,industrial composition and energy composition of industrial carbon emissions by using the satellite observations of OCO-2 XCO₂,and OMI SO₂ and NO₂.The results show that the evaluation model of industrial emission characteristics based on the comprehensive air pollution characteristics is generally effective.Among them,the estimation effect of emission intensity,emission efficiency,the emission proportion of chemical industry,and the emission proportion of coal consumption is relatively good.From the spatial distribution,the distribution of high XCO₂ enhancement（△CO₂）is related to large emission sources.High NO₂ is mainly concentrated in the east,which is basically consistent with high emission intensity,while high SO₂ is mainly concentrated in the northeast,which is similar to the spatial distribution of low emission efficiency.At the provincial level,△CO₂ and NO₂ are correlated with emission intensity and the proportion of machinery industry emissions.SO₂ is related to the emission proportion of the chemical industry.SO₂/NO₂ is related to emission efficiency and emission proportion of light industry.（3）In order to quantify the impact of industrial carbon emissions on atmospheric XCO₂,the distribution of atmospheric XCO₂ in China under different conditions was simulated by using GEOS-Chem atmospheric transport model and the high resolution gridded industrial carbon emissions.The results show that the average difference between the simulated XCO₂ and OCO-2 XCO₂ is 2.38 ppm,and the daily average relative error is within 1%.The simulated XCO₂ is lower than that observed by satellite in spring and winter,and higher than that observed by satellite in summer.The average contribution of industrial emissions to the enhancement of atmospheric XCO₂ concentration is 90.50%.When the industrial emission efficiency of each province increases by another 30%,the simulated XCO₂ of each province decreased by 0.27 ppm on average.The contribution of industrial carbon emissions to the enhancement of atmospheric XCO₂ concentration is less affected by the proportion of industrial carbon emissions in total emissions.The regions with low contribution to industrial emissions and the regions with great difference before and after emission reduction by improving emission efficiency are mainly distributed in the southwest and usually have high industrial emission efficiency.By combining the carbon emission inventory and multi-source satellite remote sensing data,this thesis evaluated industrial carbon emissions characteristics from multiple dimensions,such as spatial-temporal distribution,emission intensity,emission efficiency and emission composition.A spatial decomposition method of industrial carbon emissions based on industrial land density was proposed,and evaluation models of industrial carbon emission characteristics based on multi-source satellite data were constructed,and the effects of industrial carbon emissions on atmospheric XCO₂ were quantitatively simulated.The research results effectively fill in the lack of statistical data on industrial carbon emissions,provide a new idea for rapid and efficient assessment of industrial carbon emission characteristics,and provide a scientific basis for formulating more reasonable energy conservation and emission reduction policies to mitigation of atmospheric environmental pollution.