Whilst laboratory analysis is often regarded as the most important part of the process, the quality of sampling and sample preparation is paramount to making any subsequent analysis meaningful.

Obtaining a well-composed sample, representative of a material lot requires some effort. However, many of the considerations are simple enough and, if consistently followed and practised, will improve the quality of your sampling and the value of your analysis.

These factors include; the definition of the lot and sub-lot size, the consideration of the process and the material to be sampled, whether the fuel is static or moving, particle top and bottom size, sampling tools, sampling frequency, increment volume and more.

There are default values in the biomass sampling standard ISO 18135. However, in practice, it is best practice to determine these by measurement of PIV (Primary Increment Variance) and PTV (Primary Testing Variance). Thereby allowing lot size and increment number necessary to achieve your required precision in analysis.

WHAT IS PRIMARY INCREMENT VARIANCE?

Primary Increment Variance (PIV) refers to the variability or difference observed among individual samples, or primary increments, collected from a larger lot or batch of material.

By assessing the extent to which primary increments differ from each other in terms of their properties, characteristics or composition, you can gain insights into the homogeneity or heterogeneity of the material being sampled.

A high degree of variance among primary increments indicates that the material is heterogeneous, meaning that it exhibits significant variability in its properties across different sampling locations or depths. When a material is heterogeneous, dividing it into sublots and increasing the increment sampling will help compose a more representative sample. On the other hand, low variance indicates greater homogeneity, meaning that the material is more uniform in its properties.

Knowledge of the PIV is crucial for ensuring the representativeness and reliability of sampling results. By adjusting sampling accordingly, you can obtain more accurate and meaningful data for decision-making in various applications, including quality control, process optimisation and environmental monitoring.

WHAT IS PREPARATION AND TESTING VARIANCE?

Natural products are inherently heterogeneous, which means your fuel is likely to behave differently during sample preparation. This can result in variables in analytical results and therefore impact the performance and consistency of your power plant.

It is crucial to minimise variance during preparation and testing to ensure that your results are accurate, reliable and reproducible. By doing so, you can maintain quality control of your biomass fuel, optimise processes and monitor the performance of your fuels.

By combining both PIV and PTV, you can define sampling criteria by measurement. This is a much more robust sampling approach and can give you improved confidence.

WHAT IS BIAS TESTING DURING THE SAMPLING PROCESS?

Bias testing is an important method in detecting systematic errors in automatic sampling systems and is based on the comparison of results taken by a reference method against an autosampler.
This technique is not widely appreciated. However, it can be extended to manual sampling methods and is a useful aid in providing the validity of your sampling method, especially in discussions with regulators or disputes with third parties.

MAINTAINING QUALITY CONTROL AND ACCURACY DURING THE TESTING PROCESS

Consistency and accuracy are important when testing any material, but when it comes to testing your biomass fuel, quality control is key to helping you make informed improvements to your operational efficiency.

Quality control is hard to maintain unless a sample is both prepared and tested by the same party. There are however numerous techniques that can be utilised to ensure accurate and precise results are obtained during the testing process.

These techniques include the implementation and maintenance of a quality assurance system, audit programme, third-party audit and accreditation, industry-standard methodologies, quality control using reference materials, replicate analysis and proficiency testing.

All of these measures combined ensure that the sample analysis is typically much more precise than the initial primary sample. However, with some materials, fundamental heterogeneity of the sample may complicate this.

HOW CAN AHK HELP IN OBTAINING A REPRESENTATIVE SAMPLE?

With over 140 years of knowledge in materials analysis and a portfolio of work with major biomass clients worldwide, Alfred H Knight is well-placed to help you obtain a representative sample of your biomass. We utilise a wealth of experience in sampling and sample preparation to ensure all samples are collected, handled and tested in a quality manner, helping clients get the most accurate and reliable results.

If you would like to speak to one of our experts today about your sampling procedures, get in touch via our contact page.