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作 者:杨省贵[1,2] 赵梓含 谭颖 YANG Shenggui;ZHAO Zihan;TAN Ying(College of Airport,Civil Aviation Flight University of China,Guanghan 618307,Sichuan,China;Chengdu Soft Innovation Intelligence Association,Chengdu 610023,Sichuan,China)
机构地区:[1]中国民用航空飞行学院机场学院,四川广汉618307 [2]成都市软创智业研究会,四川成都610023
出 处:《铁道运输与经济》2025年第2期89-99,共11页Railway Transport and Economy
基 金:中国民用航空局安全能力项目(MHAQ2024011);中国民用航空局教育科学研究项目(MHJY2024039);大学生创新训练项目(S202310624188)。
摘 要:随着我国民航业快速发展,碳减排压力持续增大。为探究民航业发展与碳排放之间的脱钩关系,基于IPCC碳排放系数法测算了民航业历史碳排放量,利用TAPIO脱钩模型和LMDI法分析了民航业碳排放脱钩状态及驱动因素,最后评估和预测了民航业碳排放变化趋势和脱钩进程。结果表明:2000—2019年民航业碳排放总量持续上升且保持较高增速;研究期内经济水平效应是促进行业扩张的首要动力,运输强度效应是推动碳排放脱钩的首要因素;“粗放情景”下民航业不会有碳排放峰值,其余5种情景均可在2035年之前出现碳达峰,但只有“绿色情景”可望如期实现碳达峰目标;在预测期内“绿色情景”脱钩状况最佳,“低碳节能情景”次之,“粗放情景”脱钩状况最差且无法达到强脱钩状态,其余3种情景均能在一定程度上优化脱钩趋势。With the rapid development of China’s civil aviation Industry,the pressure to reduce carbon emissions continues to increase.To explore the decoupling relationship between the development of the civil aviation industry and carbon emissions,historical carbon emissions were calculated based on the IPCC carbon emission coefficient method.The decoupling state and driving factors of carbon emissions in the civil aviation industry were analyzed by using the TAPIO decoupling model and LMDI method.Finally,the trend and decoupling process of carbon emissions in the civil aviation industry were evaluated and predicted.The results indicate that the total carbon emissions in the civil aviation industry have continued to rise and maintained a high growth rate from 2000 to 2019.The economic level effect during the research period is the primary driving force for promoting industry expansion,while the transportation intensity effect is the primary factor driving carbon emission decoupling.Under the“extensive scenario”,the civil aviation industry will not have a peak in carbon emissions.The other five scenarios can all achieve a peak in carbon emissions before 2035,but only the“green scenario”is expected to achieve the carbon peak target as scheduled.The“green scenario”has the best decoupling situation during the prediction period,while the“extensive scenario”has the worst decoupling situation and cannot achieve a strong decoupling state.The other three scenarios can optimize the decoupling trend to a certain extent.
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