Carbon footprint (CF) is nowadays one of the most widely used environmental indicators. The scope of the CF assessment could be corporate (when all production processes of a company are evaluated, together with upstream and downstream processes following a life cycle approach) or product (when one of the products is evaluated throughout its life cycle). Our hypothesis was that usually product CF studies (PCF) collect corporate data, because it is easier for companies to obtain them than product data. Six main methodological issues to take into account when collecting corporate data to be used for PCF studies were postulated and discussed in the present paper: fugitive emissions, credits from waste recycling, use of “equivalent factors”, reference flow definition, accumulation and allocation of corporate values to minor products.ududA big project with 18 wineries, being wine one of the most important agri-food products assessed through CF methodologies, was used to study and to exemplify these 6 methodological issues.ududOne of the main conclusions was that indeed, it is possible to collect corporate inventory data in a per year basis to perform a PCF, but having in mind the 6 methodological issues described here. In the literature, most of the papers are presenting their results as a PCF, while they collected company data and obtained, in fact, a “key performance indicator” (ie., CO2eq emissions per unit of product produced), which is then used as a product environmental impact figure.ududThe methodology discussed in this paper for the wine case study is widely applicable to any other product or industrial activity.
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机译:碳足迹(CF)如今最广泛使用的环境指标之一。 CF评估的范围可以是企业(当公司的所有生产过程以及在生命周期方法之后的上游和下游过程中,产品(当在整个生命周期中评估其中一个产品时)。我们的假设通常是产品CF研究(PCF)收集公司数据,因为公司更容易获得产品数据。在本文提出并讨论了收集用于PCF研究的企业数据时要考虑的六种主要方法问题:逃避排放,废物回收的信用,使用“相同因素”,参考流程定义,积累和分配企业价值观到次要产品。 ud uda大项目有18个葡萄酒厂,葡萄酒是通过CF方法评估的最重要的农药之一,用于研究并举例说明这6个方法问题。 ud udone主要结论是,实际上,可以以每年收集企业库存数据,以执行PCF,但却考虑到这里描述的6个方法问题。在文献中,大多数论文正在将它们的结果作为PCF呈现,而他们收集了公司数据并获得了“关键绩效指标”(即,每单位生产的CO2EQ排放),然后使用作为产品的环境影响数字。 UD UD本文讨论的方法,用于葡萄酒案例研究是广泛适用于任何其他产品或工业活动。
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