Multi-dimensional Evaluation And Scenario Analysis Of Urban Carbon Emissions

Cities are the main source of global energy consumption and carbon emissions,and they are the most direct and effective administrative units for implementing low-carbon emission reduction policies.City CO₂ emissions inventory compilation includes energy emissions and metabolism of carbon emissions,it expounds that the law of its time and space evolution,and quantitative description of the social economy and natural geographical factors jointly driven by the evolution of the trajectory,not only help to understand clearly urban scale carbon evolution,also for refinement and grid of the low carbon urban planning and management to provide decision-making basis.The traditional carbon inventory accounting method is not capable of spatial analysis,and limited by factors such as the availability of urban scale data.Existing carbon studies are focus more on emissions from energy consumption,so the distribution pattern of the carbon emissions in fine space within the city areas and how the urban carbon emissions are driven by multiple spatial and temporal factors need to be further analyzed.In this context,we select Shanghai as a case city to carry out the evaluation of urban carbon emissions from multiple scales of accounting boundary,time,space and driving factors.On the basis of integrating multi-source spatial and temporal data such as spatial points of interest,energy statistics and remote sensing images,this study developed an evaluation model for the intersection of carbon accounting,the method includes remote sensing and GIS spatial analysis techniques,and material flow analysis.In addition,this study not only compile the energy carbon emission inventory of urban sub-industries from 2000 to 2015,but also reveals its distribution pattern in the urban 30 m resolution space,and in this study,carbon emissions and their spatial distribution in six major types of urban infrastructure building materials are estimated.This study simulated and analyze the carbon emission development scenarios from the future to 2050.This study provides methods and data support for elucidating the temporal and spatial law of urban carbon emission to reveal future evolution trend,and also provides a decision basis for the application of theoretical research on urban carbon emissions to low-carbon urban planning.The main conclusions of the study include the following aspects.This research established a city carbon emission accounting framework,and the results showed that from 2000 to 2015,energy carbon emissions increased from 1.40×10⁸t to 2.84×10⁸ t,with an average annual growth rate of 4.36%.Among them,industrial energy accounted for the largest proportion of carbon emissions（47.76%）,emissions from commercial and transport energy grew even faster,they are 314.68%and 247.19%,respectively.From 2000 to 2015,the carbon emission per unit of industrial GDP decreased by 67.17%,while the carbon emission per capita increased by 35.22%.It shows that more attention should be paid to the energy emission reduction of the living sector while maintaining the industrial energy conservation and emission reduction in the future.From2000 to 2015,the implied carbon emissions increased from 0.92×10⁸ t to 3.34×10⁸ t,with an increase rate of 8.99%.Among them,residential housing accounts for the largest proportion（46.15%）,followed by non-residential housing（33.60%）.In terms of materials,the hidden carbon emissions in cement（51.18%）,steel（31.36%）and brick（10.45%）ranked the top three,while the hidden carbon emissions in steel grew the fastest,with an average annual growth rate of 10.14%.In this study,the spatial analysis model of urban energy carbon emissions is constructed,and the resolution of urban space is realized at 30 meters.The refined accounting and grid estimation of energy carbon emissions were divided into four sectors:industry,commerce,household and transportation.The spatial liquidity of the model results in the low value（the last 30%,0-3.68×10⁴ t）and the high value range（the first 30,8.58×10⁴ t-12.25×10⁴ t）was obviously superior to the night lighting method.Moreover,the spatial accuracy of this study was higher,and it can more accurately depict the spatial heterogeneity of carbon emissions within cities,and it is applicable to the research on the spatial pattern of energy carbon emissions in other cities.The energy carbon emissions of Shanghai are mainly concentrated in the 10-20 km region,but the growth rate was gradually expanding from the central city to the suburbs.The carbon emissions in the 10-20 km,30-50 km and 60-80 km regions from the downtown area increase by 41.53%,179.76%and 914.09%respectively.The implied carbon emissions are mainly concentrated in the 0-10 km region,but the annual growth rate of the implied carbon emissions within20-30 km from the city center was the fastest（13.95%）.In conclusion,Shanghai’s overall carbon emissions was shifting from the downtown area to the suburbs.Based on the analysis of driving forces of social economy and physical geography factors based on LMDI factor decomposition model,it was found that population,household consumption level and fixed asset investment are the most important driving factors of energy carbon emissions in Shanghai,and their contribution rates were 0.87,0.82and 0.85 respectively.In addition to population（39.12）and per capita GDP（100.81）,the variables of effective particle size index（MESH,131.01）and SPLIT index（131.03）also have significant effects on urban carbon emissions.Therefore,in addition to the regulation of socio-economic variables such as urban population,consumption behavior and fixed assets,reasonable planning of urban spatial form,such as moderate space compactness,will also play an important role in carbon emission reduction.The scenario analysis model of urban carbon emissions reveals that under the conventional scenario,urban energy carbon emissions will reach an inflection point in 2035,while the implied carbon emissions will show a trend of steady increase.The sensitivity of Shanghai’s overall carbon emissions to the life of infrastructure（1.05）was the highest,followed by residents’consumption level（0.52）,average household area（0.28）and population migration rate（0.16）.Policy recommendations for low-carbon city construction include extending the service life of infrastructure,advocating a low-carbon and environmentally friendly lifestyle and consumption habits of residents,regulating the rate of migrant migration,and increasing the use of low-carbon and environmentally friendly building materials.