November 24 Newsletter
December, February and April waste classification training courses
Statistics – How stats can help
Two new HWOL labs
Warning – Applying the correct moisture correction and MCERTS
New – Screening tools for Irish Soil Recovery Sites and EU/GB POPs
Increased PDF Report Security
Training courses & certification
Our web-based training courses are held every 2 months. Once completed, your classification reports will show that you are CERTIFIED in waste classification and the use of HazWasteOnline.
Information about the courses can be found here: www.hazwasteonline.com/training.
The next course dates are:
• 4th- 5th December 2024 – Hazardous waste classification.
• 3rd December 2024- Refresher – for those who completed our 2-day course more than 3 years ago
• 5th – 6th February 2025 – Hazardous waste classification.
• 6th February 2025 – Refresher – for those who completed our 2-day course more than 3 years ago.
• 1st – 2nd April 2025 – Hazardous waste classification.
• 3rd April 2025 – Refresher – for those who completed our 2-day course more than 3 years ago.
If you wish to book a place, please follow the link to our online booking form: https://app.hazwasteonline.com/Book-Training.
Statistics – How they can help
This article gives an example of the use of the tools in the statistics module to investigate whether a waste can be reliably classified as non-hazardous, even when it may have a number of samples that are classified as hazardous.
Introduction
One of WM3’s basic premises for classifying a waste as hazardous is that if any individual samples, in a population of n samples are hazardous, then the whole waste is considered hazardous; a worst-case approach.
To investigate whether this worst-case approach is reasonable, Appendix D of WM3 discusses the use of statistics to further examine the data. Statistical analysis can be used to show that;
- the waste can be reliably classified as hazardous,
- the waste can be reliably classified as non-hazardous, or
- the sampling has not provided a reliable answer and either the waste is classified as hazardous on a precautionary basis, or additional sampling is undertaken to provide a reliable answer.
Appendix D outlines two approaches for statistically analysing a data set:
- the parametric approach for normally distributed data, and
- a (basic) non-parametric approach utilised where the nature of the distribution is uncertain (we have utilised a more advanced approach using Efron’s Bootstrap Method (Efron 1979, 1987)).
Based on a statistical analysis, WM3 asks the classifier to determine whether the 90% confidence interval of the mean is below, crossing or above the threshold of concern (Figure 1)
Figure 1. Statistical reliability of the sampling mean (copied from WM3, page D13) showing the mean (horizontal line) and 90% confidence interval (grey rectangle) for four wastes, A, B, C, D drawn against a hazardous wase threshold shown by the dashed line. Waste A is non-hazardous, Waste D is hazardous, while Wastes B and C are inconclusive as the uncertainty of the mean spans the hazardous threshold.
[Please note that this article does not attempt to explain the statistical methods in detail – this information can be found in the HazWasteOnline Wiki under the heading Statistics Module. Information can also be found in the March 2024 newsletter
Demonstration
This example has copper and zinc results for thirteen samples gathered from a waste stream over a period of several months. Three of the thirteen samples in the population are classified as hazardous by the additive hazard property, HP14 (Figure 2).
Figure 2. Classification results for 13 samples, indicating that samples 1, 10 and 12 are hazardous (by HP14).
The question that can be answered by statistics is: Is it reasonable to still classify this waste as hazardous?
The statistical analysis of these data for the HP14 hazard property, is shown in the screen grab in Figure 3.
Figure 3. Screengrab of the statistical analysis for the hazard property HP14. The 90% confidence intervals of both the parametric mean (1) and the non-parametric (2) mean (as shown by the double headed arrows) are below the hazardous threshold (25%) for HP14.
The statistics demonstrate that the 90% confidence interval of the mean (for both the parametric (Arrow 1) and non-parametric (Arrow 2) methods) are below the hazardous threshold for HP14; so it is reasonable to determine that this waste stream (assuming the sampling plan is adequate) should be classified as a non-hazardous waste (equivalent to Waste A in Figure 1) and the mirror non-hazardous List of Waste code applied to the waste.
This conclusion can also be further examined by looking at a stack plot of the copper and zinc data (Figure 4) used for HP14’s Equation 3 calculation which shows the additive concentrations for each of the 13 samples relative to the HP14 threshold. We have also added a line to show the position of the mean.
Figure 4. Stack plot showing the contribution of the two HP14 determinands (copper carbonate-copper hydroxide(1:1), and zinc oxide), the HP14 threshold (red line) and the statistical mean (black line).
New HWOL Labs – Chemtech and SGS
We are pleased to announce that two new laboratories: SGS (Ireland, Netherlands) and Chemtech (UK) have joined the list of labs that are able to deliver the .hwol data delivery file (V2.1.1) with their normal deliverables.
Chemtech: +44 (0)1207 528 578
SGS Gas Analytical Services Ireland: +353 (0)861572358 or ie.ehs.sales@sgs.com
SGS Rotterdam: +31 (0)10 231 47 00
The full list of hwol labs can be found here
Note that for each “TPH” fraction in their PDF reports, the HWOL acronyms are published to make it easier for users of the data to understand the types of ”TPH” testing that were undertaken and whether they are fit for purpose.
Moisture Correction and MCERTS
Some lab reports state that “All results are expressed on a dry weight basis.” This phrase can be misleading because it actually only applies to the concentrations of the substances (metals, “TPH”, PAHs, SVOCs etc.) that are published in the laboratory’s report. In all but two of the HWOL labs, it does not apply to moisture.
Below is a summary of the moisture terms and moisture corrections for soils, extracted from each lab’s .hwol data files. This table can also be found in the HazWasteOnline Wiki.
The requirement to publish results (for soils) in dry weight terms comes from the 2018 MCERTS performance standard for laboratories undertaking the chemical testing of soils. Note however, that this document doesn’t mention the word moisture once.
New – Screening tools
We are currently Beta testing three new screening tools. Based on licenced countries and selected classification engine, users will also be able to screen and report on their data for :
- Soil Recovery Sites, Domains 1 to 7 – Ireland
- EU POPs – EU Nations and Northern Ireland
- GB POPS – England Wales & Scotland
Users will be able to create a PDF report which can be downloaded from the Documents tab. These screening tools will shortly be available in the Packages and Expert Editions of HazWasteOnline.
More information on POPs can be found in the Wiki.
PDF Report Security
We are implementing PDF security for our PDF classification reports following instances of some reports being found where selected pages had been removed. This will make it harder for the PDF reports to be manipulated. We are also adding the text “Report is invalid if pages are removed” to make sure readers of these reports check that all pages are present.