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| Data quality analysis with combination uncertainty and sensitivity for carbon footprint assessment of products. |
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Abstract 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.
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Received: 13 August 2013
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CHEN Cao-Cao, LIU Chun-Lan, WANG Hao, GUAN Jing, CHEN Long, WANG Hai-Hua, ZHANG Ji-Ping, LI Zheng, LIU Xiao-Jie. Examining the impact factors of energy consumption related carbon footprints using the STIRPAT model and PLS model in Beijing[J]. CHINA ENVIRONMENTAL SCIENCECE, 2014, 34(6): 1622-1632. |
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