Analysis Of Spatio-temporal Distribution Drivers Of CO₂ In Shanxi Province Based On Geographically Weighted Regression Model

With the innovation of science and technology and the rapid development of productivity,environmental problems caused by human activities have become increasingly prominent.The increase in anthropogenic carbon emissions,led by fossil fuel combustion and land use changes,has broken the original carbon balance process,resulting in a sharp increase in the concentration of atmospheric carbon dioxide（CO₂）,which in turn leads to global warming and triggers a series of extreme climate events.Shanxi Province is a province with large coal resources in my country and an important coal supplier.The long-term mining,processing and transportation of coal resources has brought enormous pressure to the emission reduction work of Shanxi Province.Since 2002,China has carried out carbon capture and storage（CCS）experiments in the Qinshui Basin.The fault zones in the Qinshui Basin in Shanxi Province may have potential CO₂ geological storage leakage.Therefore,analyzing the spatio-temporal differentiation process,influencing factors and driving effects of atmospheric CO₂ in Shanxi Province provides an important theoretical basis and data support for the formulation of emission reduction policies in Shanxi Province.In this thesis,the OCO-2 satellite CO₂ observation data,vegetation coverage data,meteorological monitoring data of Shanxi Province from 2015 to 2019,as well as the geological survey data of the Qinshui Basin and digital elevation data are processed with digitization,accuracy reconstruction and overlay analysis.After processing,a geographically weighted regression model（GWR）was used to analyze the spatio-temporal variation,influencing factors and driving effects of atmospheric CO₂in Shanxi Province.The specific content is divided into the following three aspects:（1）Various data analysis and preprocessing.Through screening,digitization,gridding,precision reconstruction,cropping,and superposition analysis,vector data of Shanxi provincial boundary,Qinshui boundary,fracture zone,injection wells,and meteorological stations were obtained,along with monthly average,seasonal average,and annual average values of atmospheric CO₂ observations and Normalized Difference Vegetation Index（NDVI）data from 2015-2019.（2）Spatio-temporal distribution characteristics of atmospheric CO₂.Based on the annual,seasonal and monthly mean values of atmospheric CO₂ concentration from2015 to 2019,the annual,seasonal and monthly variations of the spatio-emporal distribution of atmospheric CO₂ concentration in Shanxi Province were analyzed.（3）Analysis of the drivers of spatio-temporal distribution of atmospheric CO₂.The driving factors of the spatio-temporal distribution of atmospheric CO₂ were analyzed from topographic,geological,vegetation and meteorological factors,and the driving effects of terrain relief and NDVI on the spatio-temporal distribution of atmospheric CO₂ were quantitatively analyzed by using a geographically weighted regression model.The results show that atmospheric CO₂ in Shanxi Province has obvious pattern of annual,seasonal and monthly variations.Generally,the spatio-temporal distribution of atmospheric CO₂ concentration is negatively correlated with topographic relief and NDVI,and the wind speed and direction have a certain effect on the spatial pattern change of atmospheric CO₂.However,the distribution of fault zones and injection Wells in Qinshui basin has no significant correlation with atmospheric CO₂ concentration change.Finally,comparing the fitting results of Ordinarily Linearity Regression（OLR）and GWR model,it is found that GWR model is more accurate.