Optimising waste management technologies through statistical entropy analysis: A quantitative approach to enhanced resource recovery

IF 3.9

Cleaner Waste Systems Pub Date : 2025-08-25 DOI:10.1016/j.clwas.2025.100399

Ekaterina Korotenko , Josef Jadrný , Helmut Rechberger , Michal Šyc

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引用次数: 0

Abstract

The recovery of valuable materials from waste streams is essential to achieving global sustainability. Despite the variety of waste management technologies available, systematic and quantitative methods for evaluating and optimising their performance remain limited. This study addresses this gap by focusing on the optimisation of waste management technologies through the statistical entropy analysis (SEA).

For the case study, the FLUWA® (fly ash washing) technology for recovering Zn, Pb, and Cu from municipal solid waste incineration (MSWI) fly ash was chosen. Four technology configurations, varying in material intensity and metal recovery efficiency, were analysed. The assessment used a comprehensive dataset from long-term monitoring (2018–2022), complemented by laboratory and pilot-scale experiments. It included the chemical composition and properties of the technological streams. After statistical data treatment (removal of outliers, calculation of mean values and standard deviations), a material flow analysis (MFA) was performed. Subsequently, SEA was applied to quantify changes in statistical entropy (SE).

The results show that the basic configuration of FLUWA® increases SE (ΔH_METALS=+3.4 %), indicating dilution and loss of target metals. Optimisation of the extraction step led to substantial entropy reductions (ΔH_METALS =−16.3 % and ΔH_METALS=−23.8 % in two optimised cases), reflecting enhanced metal recovery and reduced dissipation. Additionally, coagulation and flocculation were found to have no effect on SE (ΔH_METALS=0), suggesting that these steps may be redundant from the perspective of metal recovery.

By identifying inefficiencies and opportunities for process enhancement, SEA supports the transition toward more effective waste management systems and promotes the circular economy.

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通过统计熵分析优化废物管理技术：提高资源回收的定量方法

从废物流中回收有价值的材料对实现全球可持续性至关重要。尽管现有的废物管理技术多种多样，但评价和优化其绩效的系统和定量方法仍然有限。本研究通过统计熵分析（SEA）来关注废物管理技术的优化，从而解决了这一差距。本研究选择FLUWA®（飞灰洗涤）技术从城市生活垃圾焚烧（MSWI）飞灰中回收锌、铅和铜。分析了不同材料强度和金属回收效率的四种工艺配置。该评估使用了长期监测（2018-2022年）的综合数据集，并辅以实验室和中试规模的实验。它包括工艺流的化学组成和性质。统计数据处理（去除异常值，计算平均值和标准差）后，进行物料流分析（MFA）。随后，应用SEA量化统计熵（SE）的变化。结果表明，FLUWA®的基本配置增加了SE （ΔHMETALS=+3.4 %），表明了目标金属的稀释和损失。萃取步骤的优化导致了大量的熵降低（ΔHMETALS =−16.3 %和ΔHMETALS=−23.8 %在两个优化的情况下），反映了金属回收率的提高和耗散的减少。此外，发现混凝和絮凝对SE没有影响（ΔHMETALS=0），从金属回收的角度来看，这些步骤可能是多余的。通过识别低效率和改进流程的机会，环境评估支持向更有效的废物管理系统过渡，并促进循环经济。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cleaner Waste Systems

CiteScore

2.60

自引率

0.00%

发文量