Scenario Prediction And Critical Factors Of CO₂ Emissions In Pearl River Delta: A Perspective Of Urban Differences

As the world’s largest carbon emitter,China is under intense pressure to lower its CO₂emissions.Cities are the main drivers of socio-economic development,and also the primary contributors to CO₂ emissions in China.The Pearl River Delta（PRD）is one of China’s three major urban agglomerations,and its emission control is an important component in achieving emission reduction targets in China.However,the rapid urbanization and industrialization in this region has consumed intensive natural resources and generated large amounts of CO₂ emissions.Additionally,the PRD cities also differ in their level of economic and social development,resulting in geographically differential CO₂ emissions.Therefore,from the perspective of urban development differences,to formulate corresponding emission reduction strategies,it is of great practical significance to explore key influencing factor and forecast future results of CO₂ emissions for promoting reduction targets.Under its current development situation,from the perspective of urban development differences,this paper takes the PRD CO₂ emissions as the research object and analyzes their development trends and key factors.First,the current population,energy and economic development situation in the PRD is analyzed.The PRD is divided into four types based on economic development and CO₂ emissions:Guangzhou,Shenzhen,actively developing cities（ADCs）and potentially developing cities（PDCs）.Second,combined with backpropagation neural network（BPNN）,a CO₂ emission prediction model is established.According to literature analysis,five main influencing factors of CO₂ emission,namely GDP per capita,industrial structure,energy intensity,energy structure and urbanization rate,are used as the input to predict the future emission levels of four types of cities;After that,48 development scenarios are set up in combination with scenario analysis.CO₂ emissions are predicted under different scenarios by the constructed prediction model,and their key factors are derived from comparative analysis.Finally,specific reduction countermeasures of CO₂ emissions are proposed for the PRD government and enterprises in a targeted manner.Research results show that the average accuracy of the BPNN prediction model is97.35%,indicating that the constructed model has satisfactory accuracy and stability for predicting CO₂ emissions in this paper.According to the scenario analysis results,the urbanization rate is the major factor for the increase of CO₂ emissions in Guangzhou and PDCs,while the optimization of industrial structure is the main driver of CO₂ emission reduction in Shenzhen.In addition,the energy structure has the greatest promoting effect on ADCs.Overall,this paper provides a theoretical foundation and methodological support for CO₂ emission reduction in the PRD,and a new perspective for emission reduction in other urban agglomerations.