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Analysis of the major drivers of the ecological footprint using the STIRPAT model and the PLS method-A case study in Henan Province, China

机译:基于STIRPAT模型和PLS方法的生态足迹主要驱动力分析-以河南省为例。

摘要

Taking Henan Province of China as an example, we computed and analyzed the ecological footprint (EF) in 1983-2006. The results showed that the EF in Henan Province quadrupled in the 23 years, but its ecological carrying capacity (EC) was rather low and was in a state of slow decline, indicating that Henan's ecological deficit (ED) had become a remarkable social problem. Therefore, the major drivers of the EFs change were analyzed. According to the simulations with STIRPAT model. the major drivers of Henan's EF were human population (P), GDP per capita (A(1)), quadratic term of GDP per capita (A(2)). percent of economy excluded in the service sector (Ta(1)) and percent of urban population (Tb(1)). However, these drivers themselves had strong collinearity, which might produce some uncertain impact to the final results. In order to avoid the impact of collinearity, the method of partial least squares (PLS) was used. The results showed that the major drivers of EF were P, A(1), A(2) and Tb(1). Ta(1) was excluded. Compared with the results by the STIRPAT model, which showed that P is the most dominant driver and the effect of the other drivers could almost be ignored, the results by PLS method were considered as more reasonable and acceptable because the impacts of the A (Affluence) and T (Technology) conditions to the regional EF were still too important to be ignored. In addition, the results acquired by both methods showed that the curvilinear relationship between economic development and ecological impact (EF) or the classical EKC hypothesis didn't exist in Henan Province. (C) 2009 Elsevier B.V. All rights reserved.
机译:以中国河南省为例,我们计算并分析了1983-2006年的生态足迹。结果表明,河南省的生态系统在这23年中增长了三倍,但其生态承载力却很低,并且处于缓慢下降的状态,这表明河南的生态赤字已成为一个突出的社会问题。因此,分析了EFs变化的主要驱动力。根据与STIRPAT模型的仿真。河南EF的主要驱动力是人口(P),人均GDP(A(1)),人均GDP的二次项(A(2))。服务业中被排除的经济百分比(Ta(1))和城市人口的百分比(Tb(1))。但是,这些驱动程序本身具有很强的共线性,这可能会对最终结果产生不确定的影响。为了避免共线性的影响,使用了偏最小二乘法(PLS)。结果表明,EF的主要驱动力是P,A(1),A(2)和Tb(1)。 Ta(1)被排除在外。与STIRPAT模型的结果(表明P是最主要的驱动因素,而其他驱动因素的影响几乎可以忽略)相比,PLS方法的结果被认为是更合理和可接受的,因为A的影响)和区域EF的T(技术)条件仍然非常重要,不容忽视。此外,两种方法的结果都表明,河南省不存在经济发展与生态影响(EF)或经典EKC假设之间的曲线关系。 (C)2009 Elsevier B.V.保留所有权利。

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