{"title":"Stochastic analysis for comparing life cycle carbon emissions of hot and cold mix asphalt pavement systems","authors":"","doi":"10.1016/j.resconrec.2024.107881","DOIUrl":null,"url":null,"abstract":"<div><p>Uncertainties cause inconsistency in comparing the carbon emissions of hot mix asphalt (HMA) and cold mix asphalt (CMA) pavement systems and misinform the choice of more sustainable pavement recycling techniques. This research integrates sensitivity analysis, Pedigree Matrix, and Monte Carlo simulation into a robust stochastic Life cycle Assessment (LCA) for comparing carbon emissions of HMA and CMA pavement systems. First, influential inputs are identified by a sensitivity analysis and assessed by the Pedigree Matrix to obtain data quality scores. Second, the transformative relationship between quality scores and Beta distribution quantifies the uncertainty of influential inputs. Third, the Monte Carlo simulation propagates uncertainty from influential inputs to stochastic results. Stochastic simulations demonstrate that the probability of life cycle carbon emissions of the HMA exceeding the CMA pavement system is 99.74 % in the investigated case. This study enables the evaluation of confidence intervals to determine more sustainable alternatives in comparative pavement LCA.</p></div>","PeriodicalId":21153,"journal":{"name":"Resources Conservation and Recycling","volume":null,"pages":null},"PeriodicalIF":11.2000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Resources Conservation and Recycling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921344924004749","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Uncertainties cause inconsistency in comparing the carbon emissions of hot mix asphalt (HMA) and cold mix asphalt (CMA) pavement systems and misinform the choice of more sustainable pavement recycling techniques. This research integrates sensitivity analysis, Pedigree Matrix, and Monte Carlo simulation into a robust stochastic Life cycle Assessment (LCA) for comparing carbon emissions of HMA and CMA pavement systems. First, influential inputs are identified by a sensitivity analysis and assessed by the Pedigree Matrix to obtain data quality scores. Second, the transformative relationship between quality scores and Beta distribution quantifies the uncertainty of influential inputs. Third, the Monte Carlo simulation propagates uncertainty from influential inputs to stochastic results. Stochastic simulations demonstrate that the probability of life cycle carbon emissions of the HMA exceeding the CMA pavement system is 99.74 % in the investigated case. This study enables the evaluation of confidence intervals to determine more sustainable alternatives in comparative pavement LCA.
期刊介绍:
The journal Resources, Conservation & Recycling welcomes contributions from research, which consider sustainable management and conservation of resources. The journal prioritizes understanding the transformation processes crucial for transitioning toward more sustainable production and consumption systems. It highlights technological, economic, institutional, and policy aspects related to specific resource management practices such as conservation, recycling, and resource substitution, as well as broader strategies like improving resource productivity and restructuring production and consumption patterns.
Contributions may address regional, national, or international scales and can range from individual resources or technologies to entire sectors or systems. Authors are encouraged to explore scientific and methodological issues alongside practical, environmental, and economic implications. However, manuscripts focusing solely on laboratory experiments without discussing their broader implications will not be considered for publication in the journal.