Department of Industrial Management. University of Seville, Camino de los Descubrimientos s/n, 41092 Sevilla, Spain.
J Environ Manage. 2010 Mar-Apr;91(4):1002-11. doi: 10.1016/j.jenvman.2009.12.009. Epub 2009 Dec 30.
Nowadays, there is a trend in many countries towards more environmentally benign products and processes. Life-Cycle Assessment (LCA) is a quantitative analysis tool developed and utilized for the evaluation of environmental impacts occurring throughout the entire life-cycle of a product, process or activity. LCA requires a large amount of data in its different phases and can also generate large amounts of results which may be hard to interpret. In order to uncover and visualize the structure of large multidimensional data sets, Multivariate Analysis techniques can help. Hence, in this paper, a methodology using Principal Component Analysis and Multi-Dimensional Scaling is proposed and illustrated by means of two case studies. The first case study evaluates the operation of several wastewater treatment plants. The second case study deals with the environmental evaluation of the cultivation, processing and consumption of mussels. In both case studies, the redundancy present in the data allowed a dimensionality reduction from seven and ten to two dimensions, with a small loss of information. Plotting the environmental impact data in these two dimensions can help visualize, interpret and communicate them.
如今，许多国家都出现了一种趋势，即倾向于使用对环境更友好的产品和工艺。生命周期评估（LCA）是一种定量分析工具，用于评估产品、工艺或活动整个生命周期中发生的环境影响。LCA 在其不同阶段需要大量数据，并且还可能生成大量难以解释的结果。为了揭示和可视化大型多维数据集的结构，可以使用多元分析技术。因此，本文提出了一种使用主成分分析和多维尺度分析的方法，并通过两个案例研究进行了说明。第一个案例研究评估了几个污水处理厂的运行情况。第二个案例研究涉及贻贝的养殖、加工和消费的环境评估。在这两个案例研究中，数据中的冗余性允许将数据从七个维度和十个维度减少到两个维度，而信息损失很小。在这两个维度中绘制环境影响数据有助于可视化、解释和交流这些数据。
