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Calculate Mould Growth Rate Limits (Zeng et al.)

Source: R/calcMould_Zeng.R
calcMould_Zeng.Rd

This function calculates the Lowest Isoline for Mould (LIM) based on temperature and relative humidity, using the model developed by Zeng et al. (2023).

The LIM is the lowest envelope of the temperature and humidity isoline at a certain mould growth rate (u). LIM0 is the critical value for mould growth, if the humidity is kept below the critcal value, at a given temperature, then there is no risk of mould growth.

Usage

calcMould_Zeng(Temp, RH, LIM = 0, label = FALSE)

Arguments

Temp

Temperature (°Celsius)

RH

Relative Humidity (0-100%)

LIM

The specific LIM value to calculate. Must be one of 0, 0.1, 0.5, 1, 2, 3, or 4. Default is 0.

label

Logical. If TRUE, returns a descriptive label instead of a numeric value. Default is FALSE.

Value

If label is FALSE, returns the calculated LIM value as Relative Humidity (0-100%). If label is TRUE, returns a character string describing the mould growth rate category.

Details

The function calculates LIM values for mould genera including Cladosporium, Penicillium, and Aspergillus. LIM values represent different mould growth rates:

  • LIM0: Low limit of mould growth

  • LIM0.1: 0.1 mm/day growth rate

  • LIM0.5: 0.5 mm/day growth rate

  • LIM1: 1 mm/day growth rate

  • LIM2: 2 mm/day growth rate

  • LIM3: 3 mm/day growth rate

  • LIM4: 4 mm/day growth rate

  • Above LIM4: Greater than 4 mm/day growth rate (9 mm/day theorectical maximum)

References

Zeng L, Chen Y, Ma M, et al. Prediction of mould growth rate within building envelopes: development and validation of an improved model. Building Services Engineering Research and Technology. 2023;44(1):63-79. doi:10.1177/01436244221137846

Sautour M, Dantigny P, Divies C, Bensoussan M. A temperature-type model for describing the relationship between fungal growth and water activity. Int J Food Microbiol. 2001 Jul 20;67(1-2):63-9. doi: 10.1016/s0168-1605(01)00471-8. PMID: 11482570.

Examples

calcMould_Zeng(20, 75)
#> [1] 75.61875
calcMould_Zeng(20, 75, LIM = 0)
#> [1] 75.61875
calcMould_Zeng(20, 75, label = TRUE)
#> [1] 0

calcMould_Zeng(20, 85)
#> [1] 75.61875
calcMould_Zeng(20, 85, LIM = 2)
#> [1] 86.58875
calcMould_Zeng(20, 85, label = TRUE)
#> [1] 2

head(mydata) |>
   dplyr::mutate(
      RH_LIM0 = calcMould_Zeng(Temp, RH),
      RH_LIM1 = calcMould_Zeng(Temp, RH, LIM = 1),
      LIM = calcMould_Zeng(Temp, RH, label = TRUE)
   )
#> # A tibble: 6 × 8
#>   Site   Sensor Date                 Temp    RH RH_LIM0 RH_LIM1   LIM
#>   <chr>  <chr>  <dttm>              <dbl> <dbl>   <dbl>   <dbl> <dbl>
#> 1 London Room 1 2024-01-01 00:00:00  21.8  36.8    75.1    83.1     0
#> 2 London Room 1 2024-01-01 00:15:00  21.8  36.7    75.1    83.1     0
#> 3 London Room 1 2024-01-01 00:29:59  21.8  36.6    75.1    83.1     0
#> 4 London Room 1 2024-01-01 00:44:59  21.7  36.6    75.1    83.1     0
#> 5 London Room 1 2024-01-01 00:59:59  21.7  36.5    75.1    83.1     0
#> 6 London Room 1 2024-01-01 01:14:59  21.7  36.2    75.1    83.1     0