Uncertainty And Sensitivity Analysis On Life Cycle Assessment Of Evaporators

As an indispensable equipment in the process of concentrating unit,the evaporator is widely used in the chemical industry.The falling film evaporator is usually used in dairy processing units due to the advantages of high heat transfer coefficient,reaction sensitive and easily control with changing operating conditions.The mechanical vapor recompression(MVR)evaporator has a significantly lower steam demand than the multiple-effect evaporator in the use phase and the electricity consumption for MVR evaporation during operation is apparently increased.However,the environmental impact of XVR evaporators in other stages such as manufacturing and recycling is not clear.Therefore,it is necessary for the application of these evaporators to analysis the resource use.energy consumption,and environmental emissions of two types of-evaporators from the perspective of the whole life cycle.The life cycle assessment(LCA),which is an environmental lanagement tool recognized by international standai-ds can be used to solve the above environmental assessment problems.Incomplete data results highly data uncertainty in LCA.Therefore,exploring the uncertainty transfer in LCA and using sensitivity analysis to determine the order of these uncertain factors are very important for determining reliable environmental assessment results.This paper is divided into three parts.The first part mainly establishes a matrix-based LCA model,which can be used to compute and analysis resources use,energy consumption,and environmental emissions for two kinds of falling film evaporators at all the stages.The second part creates a multiple-effect evaporator design model in the R environment,and uncertainty analysis that is aimed at epistemic uncertainties in the LCA nodel is carried out by using the evidence theory.The third part employs the multivariate adaptive regression spline method to analyze the sensitivity of the model and compare it with the multivariate linear regression lethod.The main conclusions are as follows:(1)The energy consumption and emissions of two types of evaporators are much higher in the usage than those from other three stages,accounting for more than 99%,because evaporators usually have a long working life.Five environmental impact indicators are selected,including primary energy consumption,global warming potential.acidification potential,eutrophication potential,and photochemical oxidation potential.The total environlental values of each index for MVR evaporators are lower than those from the multiple-effect evaporators in their whole life cycle.These five environmental indicators with MVR evaporators are reduced around 56.8%,59.4%,47.1%,48.3%,and 53.4%,respectively,The total environmental impact for MVR evaporators is reduced approximately 57.04%after quantification in comparison with multiple-effect evaporators.(2)The evidence theory method is used to propagate uncertainty and the results are two probability distribution functions,representing the upper and lower bounds,respectively.Among these two distribution functions,all values are possible and this method can better express result uncertainty of LCA analysis.The method not only improves the reliability of the results,but also provide a n?ew way to solve the epistemic uncertainty in LCA of evaporators.(3)There is no interaction in the evaporator LCA model,and the results of the two sensitivity analysis methods are consistent.The self-evaporation coefficient,heat utilization coefficient and total power consumption are the three most significant parameters that result in the variation of LCA results.These three factors should be focused on by improving data quality so as to enhance the reliability of LCA results.