【作者】 李飞；

【导师】 李方一；

【作者基本信息】 合肥工业大学 ， 管理科学与工程， 2024， 硕士

【摘要】 中国航空业近年来发展迅速,民航运输规模连续多年稳居世界第二,航空燃料消耗产生的碳排放持续增加。作为具有高增长潜力的重要碳排放源,民航网络形成于城市间的航空出行活动,是一个受到城市人口、经济、开放程度等因素影响的复杂系统。在全球减排目标与中国“双碳”目标的指引下研究民航网络碳排放的影响因素与发展趋势,对于评估相关政策与技术手段的可行性与减排潜力具有重要意义。本文以民航网络碳排放为研究主题,利用中国高分辨率排放网格数据库进行航班碳排放核算及空间分配,并通过线性回归模型与随机森林模型分析民航碳排放的影响因素。在此基础上,结合情景分析、神经网络、幂律模型构建民航碳排放预测模型,在城市层面进行长期预测并从多个角度评估减排潜力,为低碳航空政策制定与技术手段推广提供支撑。主要研究结论如下:(1)2019年中国民航网络涉及200个城市,3620条航线,民航碳排放达到1.369亿吨,其中中心城市排放占比达到82.3%。民航网络呈现中东部多中心、偏远地区几个副中心的城市空间格局,东西部航线在数量、密度及长度方面存在显著差异。(2)人口、GDP规模及城市在民航网络中的度中心性是影响民航碳排放的关键因素,具有较高的特征重要性,由此构建的预测模型经验证具有更好的预测性能。(3)通过对比基准情景与可持续发展情景下的结果,发现2040-2060年期间生物能源和合成燃料的推广将贡献60.5%的减排量。未来减排潜力主要集中在网络中处于关键位置的省级与副省级城市,在空间上呈东部>西部>中部的特征。本文创新点在于将网络特征纳入民航碳排放的影响因素,构建碳排放预测的机器学习模型,并结合幂函数分布规律实现城市尺度的情景预测与分析。所提出的研究方法与获得的研究结果可为航空公司及航空部门探索减排路径提供重要参考。建议航空部门结合民航网络指标与城市减排潜力设置面向航线与区域的减排目标,通过政策与市场机制引导航空公司进行减排,分地区分阶段推动减排措施的落实。更多还原

【Abstract】 China’s aviation industry has experienced rapid development in recent years,and the scale of civil aviation transportation has been the second largest in the world for many years,with carbon emissions from aviation fuel consumption increasing continuously.As a major source of carbon emissions,the civil aviation network is formed by air travel activities between cities,which is a complex system influenced by factors such as urban population,economy,and openness.Under the guidance of the global emission target and China’s dual carbon goal,the study of the influencing factors and development trend of carbon emissions from civil aviation networks is of great significance in evaluating the feasibility and emission reduction potentials of related policies and technological measures.This dissertation takes civil aviation network carbon emissions as the research theme and utilizes China’s high-resolution emission grid database for flight carbon emission accounting and spatial allocation.The study employs linear regression models and random forest models to analyze the influencing factors of civil aviation carbon emissions.On this basis,a civil aviation carbon emission prediction model is constructed by combining scenario analysis,neural network,and power law model to make long-term predictions at the city level and evaluate the potential of emission reduction from multiple perspectives,to provide support for the formulation of low-carbon aviation policies and the promotion of technical measures.The main conclusions of the study are as follows:(1)In 2019,China’s civil aviation network involved 200 cities and 3,620 routes,with civil aviation carbon emissions reaching 136.9 million tons.The proportion of emissions from central cities reaches 82.3%,and carbon emissions are primarily concentrated on routes between central cities.The spatial pattern of the civil aviation network shows a multi-center structure in the central and eastern regions,with several sub-centers in remote areas,with significant differences in the number,density,and length of routes between the eastern and western regions.(2)Population,GDP size,and degree centrality of cities in the civil aviation network are the key factors affecting civil aviation carbon emissions with high characteristic importance.The prediction model built on these factors has been empirically verified to demonstrate better forecasting performance.(3)By comparing the results of the baseline scenario with the sustainable development scenario,it is found that the promotion of bioenergy and synthetic fuels will contribute 60.5%of civil aviation carbon emission reduction in the period of 2040-2060.The future emission reduction potential is mainly concentrated in provincial cities and sub-provincial cities with higher status in the network,and spatially presents the characteristics of east>west>central.The innovation of this dissertation lies in incorporating network characteristics into the influencing factors of civil aviation carbon emissions,constructing a machine learning model for carbon emission prediction,and realizing city-level scenario prediction and analysis by combining the power function distribution law.The proposed research method and the obtained results can provide important references for airlines and aviation departments to explore the path of emission reduction,thus aiding in the deep decarbonization of the Chinese aviation industry.It is suggested that the aviation sector should set emission reduction targets for routes and regions by combining civil aviation network indicators and urban emission reduction potentials,guide airlines to reduce emissions through policies and market mechanisms and promote the implementation of emission reduction measures by region and by phase.更多还原