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INRS Method: Qualitative Inhalation Risk Assessment

Overview

The INRS method is a qualitative control-banding approach for assessing the risk of inhalation of chemical agents, developed by the French National Research and Safety Institute (INRS). Unlike COSHH Essentials, which produces a categorical risk level, the INRS method calculates a continuous inhalation risk score as the product of five partial scores, each reflecting a different dimension of the exposure situation.

The final score is compared against three risk bands to determine the appropriate level of action.

The five-factor cascade

Factor Source Score range
Hazard potential Hazard class (1–5) from H/R phrases, process or VLA 1–10 000
Quantity × Frequency Exposure potential class (0–5) 1–10 000
Volatility / Dustiness Physical state and conditions 1, 10 or 100
Process type Degree of containment 0.001–1
Collective protection Ventilation or enclosure 0.001–10

The inhalation risk score is the product of all five:

Score = Hazard_potential × Volatility × Process × Protection × FC_VLA

Risk bands

Score Risk band Recommended action
≤ 100 Low No modifications needed a priori
101–1 000 Moderate Corrective measures or detailed assessment likely needed
> 1 000 Very high Immediate corrective action required

Step-by-step example

1. Hazard class

The hazard class (1–5) is determined from H phrases, R phrases, material and process type, or VLA. The method explores from class 5 downwards and returns the first match. If nothing matches classes 2–5, class 1 is assigned by default.

# From H phrases
inrs_hazard_class(h_phrases = "H336")
#> [1] "2"

# From VLA
inrs_hazard_class(vla = 0.05)   # <= 0.1 mg/m³ → class 5
#> [1] "5"
inrs_hazard_class(vla = 50)     # > 10 mg/m³   → class 1 (default)
#> [1] "2"

2. Quantity and frequency classes

inrs_quantity_class(5, "l")          # 5 litres → class 2
#> [1] "2"
inrs_frequency_class(3, "hours")    # 3 hours/day → class 3
#> [1] "3"

3. Exposure potential

inrs_potential_exposure_class("2", "3")   # → class 2
#> [1] "2"
inrs_potential_risk_score("2")        # → 10
#> [1] 10

4. Volatility (liquid)

Two approaches are available:

# From boiling point graph (official INRS Figure 2)
inrs_liquid_volatility_graph(use_temperature = 20, boiling_point = 111)
#> [1] "2"

# From vapour pressure (Table 8 thresholds: 0.5 kPa / 25 kPa)
inrs_liquid_volatility_pressure(vapour_pressure = 5)
#> [1] "2"

For solids, dustiness is classified by description:

inrs_solid_dustiness("Fine dust with little visible dispersion")
#> [1] "2"

5. Process and collective protection

inrs_process_type("Open")
#>   class score
#> 2     3   0.5
inrs_collective_protection("Moderate dispersion conditions")
#>   class score
#> 3     3   0.7

6. VLA correction factor

inrs_oel_correction_factor(vla = 50)    # VLA > 0.1 → FC = 1
#> [1] 1
inrs_oel_correction_factor(vla = 0.05)  # VLA <= 0.1 → FC = 10
#> [1] 10

7. Final inhalation risk score

inrs_inhalation_risk(
  potential_risk_score  = 10,
  volatility_score      = 10,
  procedure_score       = 0.5,
  protection_score      = 0.7,
  vla_correction_factor = 1
)
#> [1] 35

8. Risk characterisation

inrs_risk_characterisation(35)
#> [1] "1 - Risk appears low a priori (no modifications needed)"
inrs_risk_characterisation(500)
#> [1] "2 - Moderate risk (corrective measures and/or more detailed assessment likely needed)"
inrs_risk_characterisation(5000)
#> [1] "3 - Very high risk (immediate corrective action required)"

Full assessment in one call

inrs_evaluate(
  name             = "Toluene",
  h_phrases        = "H336",
  vla              = 50,
  quantity_value   = 5,
  quantity_unit    = "l",
  frequency_value  = 3,
  frequency_unit   = "hours",
  substance_type   = "liquid",
  liquid_method    = "graph",
  use_temperature  = 20,
  boiling_point    = 111,
  procedure        = "Open",
  protection       = "Moderate dispersion conditions"
)
#>   product hazard_class quantity_class frequency_class potential_exposure_class
#> 1 Toluene            2              2               3                        2
#>   potential_risk_class potential_risk_score volatility_dustiness_class
#> 1                    1                    1                          2
#>   volatility_dustiness_score procedure_class procedure_score protection_class
#> 1                         10               3             0.5                3
#>   protection_score vla_correction_factor inhalation_risk
#> 1              0.7                     1             3.5
#>                                     risk_characterisation
#> 1 1 - Risk appears low a priori (no modifications needed)

From Excel (no coding required)

ruta <- system.file("plantillas", "plantilla_inrs.xlsx", package = "expoquimR")
inrs_from_excel(ruta)

Language

expoquimr_lang("es")
inrs_risk_characterisation(35)
#> [1] "1 - Riesgo a priori bajo (sin necesidad de modificaciones)"
inrs_risk_characterisation(5000)
#> [1] "3 - Riesgo muy elevado (medidas correctoras inmediatas requeridas)"
expoquimr_lang("en")

Interactive application

run_inrs()

The INRS Shiny application allows the user to evaluate up to 10 products in a single session. Results are displayed in two panels: a summary table with the key classes and the final risk score, and a collapsible detail panel showing all intermediate scores for audit purposes.

References

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.