13.11.2014 Views

SUbstance flow analysis of the recycling of small waste electrical ...

SUbstance flow analysis of the recycling of small waste electrical ...

SUbstance flow analysis of the recycling of small waste electrical ...

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

60 Substance <strong>flow</strong> <strong>analysis</strong> <strong>of</strong> <strong>the</strong> <strong>recycling</strong> <strong>of</strong> <strong>small</strong> WEEE<br />

determine and express <strong>the</strong> uncertainty <strong>of</strong> any kind <strong>of</strong> measurements. Without <strong>the</strong><br />

specification <strong>of</strong> <strong>the</strong> uncertainty, measurement results cannot be compared with each o<strong>the</strong>r or<br />

with reference values (DIN V ENV 13005). According to this guide, <strong>the</strong> uncertainty <strong>of</strong> a<br />

measurement results consists <strong>of</strong> several components, which can be classified into two types<br />

according to <strong>the</strong> method used to quantify <strong>the</strong>m:<br />

A. Components calculated with statistical methods<br />

B. Components determined in ano<strong>the</strong>r way.<br />

The standard deviation (square root <strong>of</strong> <strong>the</strong> variance) is calculated to quantify <strong>the</strong> components<br />

<strong>of</strong> type A. For components <strong>of</strong> type B, a variable is determined to approximate <strong>the</strong> standard<br />

deviation, <strong>the</strong> existence <strong>of</strong> which is assumed.<br />

In this <strong>the</strong>sis, <strong>the</strong> standard deviation <strong>of</strong> every component used to calculate a mass <strong>flow</strong><br />

(mass, metal concentration, transfer coefficient) was ei<strong>the</strong>r calculated or estimated. If <strong>the</strong><br />

standard deviation could not be calculated, <strong>the</strong> radius (half <strong>the</strong> width) <strong>of</strong> <strong>the</strong> 95% confidence<br />

interval <strong>of</strong> <strong>the</strong> variable was estimated. Based on <strong>the</strong> assumption that <strong>the</strong> distribution <strong>of</strong> <strong>the</strong><br />

uncertainty was normal, <strong>the</strong> standard deviation <strong>of</strong> components was assumed to be half <strong>of</strong> <strong>the</strong><br />

radius <strong>of</strong> <strong>the</strong> 95% confidence interval. The variation coefficient, which is <strong>the</strong> standard<br />

deviation divided by <strong>the</strong> value <strong>of</strong> <strong>the</strong> variable, can also express <strong>the</strong> uncertainty. The<br />

uncertainties <strong>of</strong> <strong>the</strong> components were combined according to Gauss’s law <strong>of</strong> error<br />

propagation by summing <strong>the</strong> square <strong>of</strong> <strong>the</strong> standard deviations <strong>of</strong> <strong>the</strong> components (DIN V<br />

ENV 13005). The resulting uncertainty is also expressed as a standard deviation.<br />

3.4. Data compilation<br />

The compilation <strong>of</strong> <strong>the</strong> data ga<strong>the</strong>red through <strong>the</strong> methods presented in 3.3 requires <strong>the</strong><br />

following steps:<br />

1. A qualitative description <strong>of</strong> <strong>the</strong> system, defining <strong>the</strong> collection, treatment and reuse<br />

processes and modelling <strong>the</strong> material and substance <strong>flow</strong>s from one process to <strong>the</strong><br />

next one;<br />

2. The integration <strong>of</strong> <strong>the</strong> quantitative data on <strong>the</strong> <strong>flow</strong>s <strong>of</strong> sWEEE into <strong>the</strong> system model;<br />

3. Data reconciliation to calculate observable unknown quantities and to eliminate<br />

discrepancy <strong>of</strong> redundant information (Reuter et al. 2005);<br />

4. Calculation <strong>of</strong> <strong>the</strong> <strong>flow</strong>s <strong>of</strong> precious metals based on <strong>the</strong> concentration <strong>of</strong> precious<br />

metals in <strong>the</strong> material <strong>flow</strong>s.<br />

These four steps were realised by <strong>the</strong> STAN freeware (TU Vienna 2008), which helps to<br />

perform material <strong>flow</strong> <strong>analysis</strong> (Cencic & Rechberger 2008). After drawing <strong>the</strong> processes and<br />

material <strong>flow</strong>s in <strong>the</strong> graphical interface <strong>of</strong> STAN, <strong>the</strong> data on <strong>the</strong> <strong>flow</strong>s with <strong>the</strong>ir

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!