Data logger analysis

Data loggers are a useful means of identifying the root cause of damp.

File downloads

London external data

The latest .csv file

We publish updated data for London – be careful to line up with your data loggers start date – such as by cutting a pasting only relevant data.

Excel spreadsheets .xlsx

1. The latest Excel spreadsheet for analysing damp requires Excel 365.

2. A larger and more complex example spreadsheet can be downloaded, without 365 functions, so should work in earlier version of excel.

3. A 10 data loggers comparison without 365 functions

Understanding data

Occupiers will know their habits, changes and movements. Dataloggers can help the own, landlord and damp expert identify the main issues.
Key elements to consider and look for as:

Surface %RH

• Relative humidity (%RH) is a function of both temperature and vapour pressure, so where the data logger is placed can make a huge difference to it’s temperature and therefore relative humidity, but little difference to the dew point.
• Rough every drop of 1°C increases % relative humidity (%RH) by about 5%RH.
• To compensate for the temperature difference between the data logger and cold surface:
  1. Measure the temperature of the coldest part of the damp wall and compare it to the temperature on the data logger.
  2. The 365 version of the excel file includes a calculation of the surface relative humidity on the interface tab.
  3. Use a laser thermometer or infra-red lens, with accurate temperature sensor to identify the coldest part of a wall.
• For ease, the graph assumes a constant temperature difference – it would be more accurate if the logger was placed on the coldest part of the wall, although it is hard to find and difficult to measure the very coldest surface.

Dew point differential

Dew point is a proxy for vapour pressure, or quantity of vapour in the air. Comparing the vapour pressure between two data logger can identify where vapour is generated or removed (through ventilation or condensation / dehumidification).

External data

• The dew point and temperature within a similar nearby location is fairly constant across the area, such as London.
• Comparing internal dew point to external dew point helps determine the benefit of ventilation.
• Comparing temperature helps determine heat loss, such as through poor insulation is a factor.
• We don’t normally show external relative humidity as it is not relevant and can distort the perceived benefits of ventilation, which should be through comparing internal to external dew points).

Temperature

• Ideally there should be a fairly constant temperature across a property and over the 24 hour cycle. This is hard to achieve.
• Some people like to zone their house so as to conserve heat, or keep wine chilled. In this case you should increase ventilation out of the source of vapour (bathroom, kitchen, laundry) and in the cold zone, or used dehumidifiers, constantly piped out.

Relative humidity

• If the surface relative humidity is at or close to 100%, then water is almost certainly condensing on or in the wall.
• The dew line is where a wall is cold enough for condensation to take place within the building building material – known as interstitial condensation.
• If the surface is above 85%RH for 6 or more hours then it is likely to become mouldy. Mould is omnipresent, however, spore will be far greater in properties where mould is growing. Therefore it is wise to keep washing away mould with bleach or anti-mould products and reduce relative humidity by:
  1. Extracting vapour at source (bathroom, kitchen, laundry).
  2. Keep doors closed in vapour generating rooms.
  3. Keep balanced heating.
  4. Improve installation and anti-mould products.
  5. Use dehumidifiers, regularly decanting water.
  6. Consider making the bathroom scrifical y keeping it colder, and wash away mould regularly.

How to use

1. The simplest way to use the data loggers is to open a .csv file, copy and paste the data into the data sheet, making sure that the start times line up.
2. We can’t support the use of file. Tip, use YouTube to better understand excel.
3. Do share concerns, issues and tips amongst each other in the comments below.

Known issues

These analytical excel files will keep evolving, issues are time consuming to resolve, so sometimes are left in a slightly user-unfriendly state – sorry.

1. When opening the data logger file:
   Excel may say: “Excel found a problem with one or more formula references in this worksheet.”
   Why: Because a formula runs from the start and finish data.
   Solution: Go to interface and select start and finish date.
2. Importing data is easy, but occasionally a file is corrupted.
   Why: The date column is out of line and Excel recognises the temp (temperature), humidity (%RH) and time as text. It needs a quick find and replace (Command H – Mac / Control H – Windows).
   Solution: Find and replace % with % and : with : and remove ° by replacing with nothing.
3. Make sure the data is align.
   Why: A datalogger may have been started at a different time.
   Solution: Cut and paste appropriately – note an offset is automatically set up for external data.
4. Do post other issues in comments, we can’t help with excel, but contributors may be able to help.