International passenger transport and climate change: A sector analysis in car demand and associated CO2 emissions from 2000 to 2050
International passenger transport and climate change: A sector analysis in car demand and associated CO2 emissions from 2000 to 2050
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国际客运与气候变化：2000 年至 2050 年汽车需求和相关二氧化碳排放的行业分析
DOI：
10.1016/j.enpol.2007.07.025
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发表时间：
2007
期刊：
影响因子：
9
通讯作者：
C. Jaeger
中科院分区：
文献类型：
--
作者：
I. Meyer;Marian Leimbach;C. Jaeger
该报告对全球11个地区的乘用车需求、使用量和相关的二氧化碳排放量进行了全球区域化预测。这项研究是基于经验数据，这些数据最初是从国际来源整理的，目的是对特定地区的汽车库存需求进行建模。派生需求是汽车相关燃料消耗和相关二氧化碳排放的指标，这些指标是根据行为和技术情景计算的。所获得的二氧化碳排放路径是部门基准情景，在假设当前趋势继续占上风的情况下，确定汽车引起的二氧化碳排放增长的区域特定潜力。这项研究采用了汽车需求的多模型方法，应用了两种植根于消费经济学的方法：效用最大化和单方程模型。汽车需求建模的效用最大化方法是由每个世界地区具有代表性的消费者的偏好驱动的，受制于外生的价格和收入轨迹。后者是从最优增长模型中采用的。这是一种预测全球地区化行业汽车需求的新方法。这项研究还应用了基于逻辑贡佩兹函数的单方程收入-消费模型和非线性回归技术来比较模型的结果。
The paper provides global regionalized projections of passenger car demand, use and associated CO2emissions from 11 world regions. The study is based on empirical data that have been originally collated from international sources for the purpose of modeling region-specific car stock demand. Derived demands serve as indicator of car related fuel consumption and associated CO2emissions, which are calculated on the basis of behavioral and technological scenarios. The obtained CO2emission paths are sectoral baseline scenarios that identify region-specific potentials of growth in car induced CO2emissions assuming that current trends continue to prevail. The study adopts a multi-model approach to car demand by applying two methodologies rooted in the economics of consumption: utility maximization and single equation models. The utility maximization method for modeling car demand is driven by the preferences of the representative consumers of each world region, subject to exogenous price and income trajectories. The latter is adopted from an optimal growth model. This is a novel approach to projecting global regionalized sectoral car demands. The study is complemented by the application of single equation income–consumption models based on logistical Gompertz functions and non-linear regression techniques to compare model results.