Tips to Boost Your Trace Analysis Skills

February 6, 2019

The Column

The Column, The Column-02-06-2019, Volume 15, Issue 2
Page Number: 2–5

Columns | <b>Column: Incognito</b>

Incognito recalls the words of wisdom from an “old-school” supervisor who mentored him on the art of effective trace analysis.

Incognito recalls the words of wisdom from an “old-school” supervisor who mentored him on the art of effective trace analysis.

“True trace analysis requires knowledge and skills which are not always present in your work, which often lacks the rigour required to produce high quality data” wrote my supervisor in 1993 following my annual performance review. He was very much of the old school; he could make a gas chromatography–mass spectrometry (GC–MS) system sing like no one else I have ever worked with and was meticulous to a fault, often taking far longer than was necessary to perform analyses in order to make sure everything was just as it should be. He obviously didn’t rate me at that time!

Of course, the skills, knowledge, and rigour required back then are just as necessary now, even though modern columns, sample extraction techniques, and analytical equipment have massively advanced, and the detection limits possible now are orders of magnitude lower. One very good thing that came out of that review back then was a set of notes that he gave me to follow as a guide to the requirements for trace analysis, which I have kept all these years and re-discovered recently. These guidelines are as relevant now as they were then, despite all the advances in our science, and I share them with you now as a checklist against which you can also rate your knowledge and skills, to benchmark yourselves against the young, apparently failing, Incognito. Naturally, I have made some updates over the years to reflect modern practices and advances, but largely they remain unchanged.

Trace (organic) analysis can be loosely defined as the measurement of components within a sample at or below a specified concentration level (ppm back then, probably ppb or ppt now!) or for which reproducible determination is difficult because of the limitations of analytical equipment, matrix interferences, or the complexity of the sample.

Most trace analysis requires careful sample manipulation and one should ensure the homogeneity of the sample before analysis, taking care to consider factors such as particle size or liquid viscosity and the possibility for phase separation prior to subsampling for analysis. Any issues identified should be dealt with only after careful consideration of the effects of sample manipulation on target analyte concentration, such as the loss of volatile trace analytes during particle size reduction of solid samples or the partition coefficient of analytes in bi‑phasic liquid samples when centrifuging or using phase separation methods.


Trace analysis will often require sample extraction to selectively isolate the target analytes from other matrix components (to remove potential interferents) and preconcentrate the analyte to a level at which instrumental determination at the required level of sensitivity is possible. The technique used for sample extraction should be as selective as possible with solid-phase extraction (SPE) using electrostatic interactions or mixed mode media being the most selective and simple liquid–liquid extraction the least selective. When using sample extraction, ensure that the most selective conditions are used in each step of the protocol, such as making pH adjustments to the sorbent before or after the washing steps of an SPE protocol to ensure optimum analyte retention or elution accordingly, or the use of pH adjustment or salting-out approaches when using liquid–liquid extraction.

The cleanliness of the environment used for trace analysis is of utmost important, especially where repeated analyses for the same target analyses are performed on an ongoing basis. Measures to ensure the cleanliness of the sample preparation and extraction areas are required as well as the proper cleaning of equipment, which can be verified using “blanks” that should be processed in exactly the same way as the sample. Airborne and surface contamination can be avoided through the proper use of fume hoods and good cleaning of the fume hood surfaces.

Consider the use of gloves to avoid sample contamination, but ensure that the gloves have been tested for extractables, and use powder-free varieties whenever possible. The degree of contamination of glassware post-cleaning needs to be verified and washing detergents should be carefully screened. Equipment such as needle (matrix) evaporators and SPE manifolds hold a high potential for cross‑contamination and their proper use and suggested cleaning regimes should be well known and properly implemented and gaskets and seals regularly replaced. When equipment cleaning is necessary, consider the polarity of the cleaning solvents against that of target analytes and interferents to provide the maximum cleaning efficiency. Common laboratory equipment, such as pipettes, filters, and funnels, should all be thoroughly cleaned, and the proper use of positive displacement pipettes should be adhered to at all times to avoid severe cross‑contamination. Cleaning detergents should be carefully selected so as to minimize the risk of contamination and blanks carefully scrutinized for poor cleaning or detergent residues.

The use of high-quality solvents is required to avoid interference from contaminants and to obtain the required signal-to-noise (S/N) ratio for most instrumental analytical techniques. This includes any water drawn from laboratory water purifiers. Typically, any issues will be revealed in the “blank” samples used; however, it is important to note that the proper and regular servicing of water purification systems is necessary to avoid microbial growth and water that does not meet the required levels of resistivity and chemical purity.


The appropriate choice of extraction, elution, or re-constitution solvents can avoid poor chromatographic peak shape and improve sensitivity of chromatographic methods.

Where analyte losses are possible during sample manipulation and extraction, suitable internal standards should be used, choosing deuterated variants of the analyte if available, where mass spectrometric detection is used. Internal standards should have similar chemical properties to the analytes of interest and their relative detector response versus the target analytes should be verified prior to any quantitative determinations. Solubility, LogP (D), and pKa of candidate internal standards should all be considered when assessing the suitability of internal standard candidates. Suitable internal standard concentration (ranges) should be verified according to the expected limits of detection and quantification of the target analytes.

Instruments should be properly maintained, and the most rigorous cleanliness applied when performing system maintenance, especially in GC analysis when changing components, such as columns, liners, inlet septa, and inlet seals. Wear gloves and use plastic tweezers, when required, during these operations.

Use blanks and standard solutions at the limits of detection (LODs) and quantification (LOQs) to determine the high performance liquid chromatography (HPLC) and GC system cleanliness prior to analysis. Reject the system if suitable limits are not met or if there is any suggestion of contamination.

Certified reference standards should be used wherever possible to create standard solutions for instrument calibration and their validity regularly checked or the standards replaced. A rigorous programme of quality control samples should be employed with check standards interspersed through the analytical campaign to check for instrument response drift. Pass and fail criteria need to be established and adhered to.

Chromatographic methods should be designed to achieve the maximum selectivity of the chosen analytes, even when MS detection may make spectral resolution possible. Insidious issues such as detector overload or common-ion interference in GC–MS or ion-suppression in LC–MS often cannot be identified until the data analysis phase and there is the risk that even at this later stage they are not properly identified. Stationary phases and column configurations should be designed to give maximum resolution and efficiency to aid with selectivity optimization, bearing in mind that the dispersion (and therefore reduced efficiency) associated with late elution can often drastically reduce the sensitivity of the method.


There are several strategies designed to optimize the instrument response in trace analysis including:


  • Splitless injection routines should be optimized in terms of solvent injection volume and splitless (purge-on) time.

  • Use of pressure-pulsed injection to achieve higher sample volume injection.

  • Use of programmed thermal vaporizing inlets to achieve high sample injection volumes and analyte preconcentration in the inlet.

  • Use of shorter, narrow-bore GC columns will improve efficiency and therefore resolution; however, care should be taken not to overload these columns (they have very limited stationary phase available) as a drastic reduction in efficiency may occur.

  • Use of selected ion monitoring detection in single quadrupole GC–MS systems; however, the judicious choice of the ions monitored and their relative dwell times within each group is required in order to avoid any interference effects and optimize sensitivity.

  • Use of triple-quadrupole detectors in GC–MS/MS; however, the careful selection of selective precursor and product ions as well as the optimization of ion measurement dwell times and the collision cell pressure should all be carefully optimized.

  • Consider chemical ionization (CI) as the ionization technique for GC–MS, especially when dealing with halogenated analytes.


  • Use of short, narrow-bore HPLC columns with superficially porous or sub-2-µm particles will increase peak efficiencies and therefore resolution, although stationary phase overload should be avoided.

  • Use of UV detectors with light pipe flow cell designs will appreciably improve signal-to-noise ratio.

  • Standard diode array detectors should be optimized in terms of data collection rate as well as the use of any reference wavelengths; light filtering or gating devices should be well understood in order to obtain maximum efficiency.

  • MS detection, particularly triple quadrupole detection, can vastly increase instrument sensitivity; however, precursor and product ions need to be carefully selected and the ion dwell times and collision cell pressures need to be fully optimized.

  • Atmospheric pressure ionization sources should be optimized for each analysis; this is especially true for capillary (ionizing) voltage as well as nebulizing and drying gas flow rates.

Be aware that MS detection strategies are inherently more selective and therefore can, when properly optimized, deliver lower limits of detection and quantification. However, also bear in mind that several analyte-specific GC detectors, such as nitrogen–phosphorous detectors (NPD) and electron ionization (EI) detectors, may also deliver very high levels of sensitivity.


Integration algorithms should be developed to accurately and repeatedly estimate peak area on an on-going basis. It is unlikely that “standard” integration parameter combinations will be successful and that some optimization is likely in order to achieve fit-for-purpose results, especially in trace analysis. Integration events such as “sensitivity” or “threshold” values should be carefully considered and optimized to ensure that peak start and end points are properly evaluated and smoothing, or minimum peak area events carefully checked in order to assess their impact on the accuracy and validity of peak area measurement. One should aim for an algorithm that successfully evaluates peak area at least 80% of the time.

Every trace analysis is associated with error in the determination of target analytes and this needs to be carefully assessed using the appropriate scientific and statistical methods to estimate and report the uncertainty associated with the quantitative result produced.

There ends the lesson in trace analysis from the early 1990s, with some updates from myself to bring things up to date. Whilst this is very much an overview of the important factors, I hope that it has served as a useful reminder of the rigour required for good trace analysis. Whenever undertaking any trace analysis, I like to bear in mind the words of Jim Rohn, the American entrepreneur, “Discipline is the bridge between goals and accomplishments”, and I urge you to ask yourself if your own trace analysis is as accomplished as it might be?


Contact Author: Incognito

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