产品碳足迹评价中不确定度与敏感度相结合的数据质量分析

产品碳足迹评价中,数据种类、来源、获取途径和量化方法的选择不同将直接影响到评价结果的可靠与否.本文建立了结合敏感度和DQI-Monte Carlo不确定度分析的产品碳足迹评价数据质量分析模型.首先通过敏感度分析识别出产品碳足迹评价中的主要数据,再采用DQI-Monte Carlo不确定度分析方法对主要数据进行数据质量判定,甄选出影响评价结果可靠性的关键数据,并由此有针对性地提出数据质量改进意见,从而有效地优化数据收集方案,减少碳足迹评价结果的不确定度.建立的方法应用于我国某塑料软包装印刷企业的印刷前阶段碳足迹评价中.

Data quality analysis with combination uncertainty and sensitivity for carbon footprint assessment of products.

The results of carbon footprint assessment of products depend on the selection of data types, sources, assessment approaches. The purpose of this study is to develop a new method which is combined DOI-Monte Carlo with sensitivity analysis and data quality analysis method for carbon footprint assessment of products. For this new approach, firstly, the primary data impacting on the assessment result were chosen through data sensitivity analysis; then, with DOI-Monte Carlo analysis the uncertainty of the primary data and the key data that affect the evaluation results were obtained. As a result, the accuracy of carbon footprint assessment could be improved more specific by optimizing data collection scheme according to the above data analysis method. As a case study, the developed method was applied to the carbon footprint assessment in the pre-printing stage of one plastic flexible packaging printing company in China. This approach can be used for carbon footprint assessment of many products by improving the uncertainty and data quality.