Measurement of Adenosine Triphosphate (ATP) concentration is used as a proxy for total active biomass in a sample. Once that ATP concentration is calculated from the raw output of Relative Light Units (RLU), sample amount, and calibration standard, the next question is “what does this value mean?”. This is where interpretation guidelines are useful. What constitutes high, medium, and low contamination levels can differ depending on your sample type and operating conditions. All LuminUltra 2nd Generation ATP test kits include generic interpretation guidelines to provide a frame of reference for your data. For example, see Table 1 for the interpretation guidelines for samples high in organic content. These interpretation guidelines are designed for generic risk management guidance, however users are encouraged to establish their own control ranges on which to base alarm settings and process decisions.
Table 1: Interpretation Guidelines for samples with high organic content.
Establishing a baseline:
To develop your own control ranges, a baseline must be established to identify what “good control” looks like in your system. To establish a system baseline, samples should be taken and tested over time with as much consistency as possible in your workflow (for example, the same sampling practices from the sample sampling port at a similar time of day for x number of days).
There is no “hard and fast” rule for the number of data points to use to establish a baseline, though the more data you have, the more reliable the baseline will be. Ideally, utilize 10 or more ATP data points to understand the day-to-day fluctuation in your data and to build a baseline. See Figure 1 for example baseline trending.
Figure 1: Sample ATP concentration baseline data over 24 days of monitoring.
Alarm settings for contamination thresholds:
To utilize the baseline data to establish alarm samples consider the following questions:
- Does the data fluctuate within the same order of magnitude?
- Are there undesirable impacts of microbial growth that trend with ATP concentration?
- Does your treatment program have an impact on the order of magnitude of your data? (i.e. how does biocide application impact the ATP concentration?)
These kinds of considerations can help to establish what levels to set your alarms at. Microbial growth happens at an exponential or logarithmic scale due to the nature of cell division (2 cells become 4, 4 become 8, 8 become 16, and so on). For this reason, alarm settings for microbial contamination levels can be made based on order of magnitude. Using the same example as in Figure 1, Figure 2 proposes the alarm settings for this sample data set.
Figure 2: Sample alarm levels (<100 pg/mL good control, 100 pg/mL -1000 pg/mL preventative action, >1000 pg/mL corrective action).
Use this guidance material to help you establish your own alarm settings. For technical support from our experts, visit my.luminultra.com and create a support ticket.