Read this article to find out how Conserv uses IPI's mold risk KPI to help you interpret the environment in your spaces and take action.
Conserv cloud is a free, cloud-based environmental monitoring tool. You can create an account at https://app.conserv.io.
KPIs should help us answer the simple question "How are we doing?" -- read more about our KPI philosophy in our article "Understanding Preservation KPIs".
Take the example of the temperature and relative humidity chart so common in environmental monitoring reports.
This chart does very little to evaluate the risk of mold in your collection.
What if instead of the typical chart you could tell your team, "During most months our mold risk has been "Low" but over the last 30 days the mold risk has gone up to "High".
With an immediate sense of "How we're doing?" your team can then visually assess any mold risks based on data and work with the facilities team to improve the environment.
The data collected through your sensors can be used to calculate the mold risk factor, which is a model that was researched and developed by the Image Permanence Institute. This model can help you make decisions about your spaces.
The mold risk calculations
To calculate mold risk we have to understand the cumulative impact of many temperature and relative humidity readings over time.
Mold risk increases as the favorable conditions for mold growth persist over time, and mold risk decreases the more time spent in unfavorable conditions for mold.
As a rule of thumb, mold spores start to germinate above 65% RH, so one approach to handling mold is to keep the RH below the 65% level. (Note that other factors may also affect the risk for mold growth, such as airflow and history of past growth).
A bit of math is coming up now!
We start by calculating the mold risk score based on temperature and relative humidity for each sensor reading, one at a time. We consider "favorable" conditions to be temperatures between 2-45°C (35.6-113°F) and a relative humidity above 65%.
Using the same look up tables and calculations as IPI's Dew Point Calculator, we determine the Days to Mold (DTM) and then calculate the Mold Growth Rate (MGR) as 1/DTM.
Mold Growth Rate (MGR) = 1/Days to Mold (DTM)
The Mold Growth Rate is then multiplied by the reading time (in days) to give a time-weighted sum number that we are calling Growth over Reading Period (GoRP).
Growth over Reading Period (GoRP) = Mold Growth Rate (MGR) * Reading time (in days)
We add up the Growth over Reading Period (GoRP) over the chosen period of time to get the mold risk score (table below). As the number increases from 0, mold risks increase, and once the number gets over 1, it's likely that mold is active.
Note that you don't have to wait until you hit 1.0 or more for the possibility of mold in your spaces, as you can start expecting it at a mold risk score of 0.5 or more.
| Mold Risk Score | Mold Risk Status |
| 0 | None |
| 0 - 0.50 | Low |
| 0.50 - 1.00 | Medium |
| 1.0 | High |
| > 1.0 | Active |
Importantly, if the conditions have been unfavorable for mold for 24 straight hours, we reset the mold risk score to zero.
Be good to your future self and team by visually documenting mold with the Conserv observations feature - How to create an observation
Here's an example of a space that likely has active mold - it would be very difficult to eyeball this from the chart. The mold risk score quantifies our risk at a glance.
What's next?
With the mold risk KPIs you can get your team aligned on "how are we doing?" and begin to lead the conversation on what needs to be done to improve your collection.
The primary purpose of good metrics is not just to answer questions; Good metrics also help your organization ask better questions to address the root cause of problems.
Important note on mold risk and microclimates
Mold germination can be hyperlocalized. It is possible for you to have two sensors in the same space, one with active mold, and another displaying low or no risk for mold outbreaks. For this reason, we do not recommend aggregating spaces with multiple sensors in them when trying to determine mold risk.
We are evaluating next steps for improving the metrics in both the weekly email and our summary reports, but for now, the best place to assess mold risk is within the analytics at an individual sensor level.
Final tips: Remember that mold spores are in the air all the time, everywhere. They are sitting on surfaces waiting for the right conditions to germinate (darkness, humidity, warmth, organic matter to feed on).
While having had a past mold outbreak might mean you have more spores in your space and a higher risk of a mold outbreak, not having had a past outbreak does not mean you can't have one now.
It is also not true that inorganic surfaces cannot have mold growth on them. Mold will feed on organic debris (think dust and dirt) accumulating on inorganic surfaces.
If you are in a place where temperature and humidity control is difficult or impossible, and mold risk is high, maintaining good ventilation and cleanliness will help reduce your risk for mold growth.
Know your spaces
It is important to remember that your mold risk score is based on a model. The model takes into account some basic assumptions about mold spore germination and only looks at temperatures and humidity over time. This model is imperfect. Having a low mold score risk does not necessarily mean you will definitely not get mold. There are many variables this score is not accounting for.
We do not know if you have had previous outbreaks, how often or how well you dust your areas, how good your airflow and air purity are, etc.
For this reason, it is important that you stay vigilant and become familiar with your own spaces, your history, and your building. Mold risk, just like many other Key Performance Indicators (KPIs), is a quantified simplification to help you dig into your own data. It is not an absolute.