利用随机优势测量空气和水污染

E. Agliardi, Mehmet Pinar, T. Stengos
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引用次数: 2

摘要

我们采用随机优势(SD)方法来分析导致环境退化的因素。考虑的变量包括来自世界银行数据集的各国温室气体(GHG)排放和水污染。我们的方法是基于成对SD检验。首先,我们研究了从1990年到2005年,在5年的时间跨度内,每个单独变量随时间的动态进展。然后,利用两两SD检验对任意时刻温室气体排放总量和水污染的主要行业贡献进行研究,揭示对排放总量和水污染贡献最大的行业。我们发现,随着时间的推移,CO₂排放量对温室气体排放的贡献最大,而且在一阶SD意义上在15年内增加。另一方面,水污染以二阶SD的方式增加。两类行业比较表明,产生二氧化碳排放的主要行业一直是电力和供热行业,而在1990年至2005年期间,运输行业一直是第二贡献者。最后,随着时间的推移,食品工业逐渐成为造成水污染的主要行业。
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Measuring Air and Water Pollution Over Time Using Stochastic Dominance
We employ a stochastic dominance (SD) approach to analyze the components that contribute to environmental degradation over time. The variables that are considered include countries' greenhouse gas (GHG) emissions and water pollution as from the data set of the World Bank. Our approach is based on pair-wise SD tests. First, we study the dynamic progress of each separate variable over time, from 1990 to 2005, within 5-year horizons. Then, pairwise SD tests are used to study the major industry contributors to the overall GHG emissions and water pollution at any given time, to uncover the industry which contributes the most to total emissions and water pollution. We find that CO₂ emissions not only contribute the most to the GHG emissions over time, but also increased within 15 year in the first-order SD sense. On the other hand, water pollution increased in a second-order SD sense. Pair-wise industry comparisons suggest that the major industry contributors to the CO₂ emissions have always been the electricity and heat production sectors, while the transport sector has been the second contributor between 1990 and 2005. Finally, the food industry gradually became the major contributing industry for water pollution over time.
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