Respiratory Protection eTool
Respirator Change Schedules » Using a Math Model Table to Determine a Cartridge's Service Life
Keep In Mind
- The math models are usually only directly applicable for single contaminant exposures. If you have a multiple contaminant situation, you may need to use other methods to derive a schedule or increase the safety factors.
- The Wood Math Model is just one equation you can use. Also, because it is a predictive type of model (as opposed to a descriptive type), you should not rely on it without some experimental confirmation of the calculation or use of appropriate safety factors.
- The Yoon-Nelson Mathematical Model is an example of a descriptive math model.
Mathematical equations have been used to predict the service lives of organic vapor respirator cartridges when used for protection against single contaminants. Using an equation developed by G. Wood, OSHA has precalculated and presented some service lives in a table. You can calculate others using NIOSH's MultiVapor™ Version 2.2.3 Application. It is suggested that you reduce the service life estimate by some safety factor to give a change schedule that you should document in your written respiratory program.
Factors That Can Reduce Cartridge Service Life
Worker Exertion Level: a worker breathing twice as fast as another will draw twice the amount of contaminant through the respirator cartridge
The service life of a cartridge or canister respirator depends upon the total amount of contaminant captured by the absorbent. The total amount of captured contaminant is directly related to the work rate or breathing rate; i.e., a worker breathing twice as fast as another will draw twice the amount of contaminant through the respirator cartridge. Most cartridge studies have used a breathing rate, 50-60 liters per minute, that approximates a high end of moderate work rate. For work rates that exceed this level (e.g., heavy shoveling, running) you may need to apply or take into account a correction factor when determining a service life.
Respirator Cartridge Variability: some cartridges contain more activated charcoal than others
The service life of a respirator cartridge is directly related to the amount of active material in the cartridge. For instance, most dual cartridge organic vapor respirators contain between 35-50 grams of activated charcoal in each cartridge. If the specific cartridge being evaluated can be reproducibly determined to have a certain amount of active material, then modifications to the service life may be justified. You can obtain information on cartridge specifications from manufacturers.
Temperature: the hotter it is, the shorter the service life
High temperatures can adversely affect the adsorptive capacity of respirator cartridges and canisters. The high temperature may act by thermally loosening the attractive forces that make adsorption happen or may act in concert with humidity by increasing the moisture carrying capacity of air. This latter mechanism may represent the greatest likely effect on service lives of cartridges. Temperature effects alone have been reported to reduce the service life 1-10% for every 10 degrees Celsius rise depending on the specific solvent (Nelson, et. al., 1976). Corrections to cartridge estimated service life for this effect alone are probably not necessary under normal working temperatures.
Relative Humidity: water vapor will compete with the organic vapors for active sites on the adsorbent
Relative Humidity is a measure of the amount of water vapor the air will hold at a specified temperature and is expressed in percentage values. Since warmer air will hold more water than colder air, the same relative humidity at a higher temperature represents a significantly greater amount of moisture. High relative humidity is a significant negative factor in the capacity of organic vapor cartridges since the large quantity of water vapor will compete with the organic vapors for active sites on the adsorbent. Most of the laboratory work determining adsorbent capacity has been performed at a low relative humidity of 50% at approximately 70 degrees F.
If the actual use of the organic vapor respirators will take place in a significantly more humid environment, then you may need to apply or take into account a safety factor when determining a service life. The exact magnitude of the humidity effect is complex, dependent in part upon chemical characteristics and concentrations of both the contaminant and the water vapor. Based upon relatively few studies, a reduction by a factor of 2 in the cartridge service life originally estimated based upon 50 % relative humidity, may be made when the relative humidity reaches 65% (Nelson, et. al., 1976; Werner, 1985). If the relative humidity exceeds 85%, you should consider experimental testing or another method to more specifically determine the service life. Mathematical modeling may be an appropriate, albeit complex, approach to predict the effect of humidity at various chemical concentrations (Wood, 1987; Underhill, 1987).
Multiple Contaminants: predictions should be derived from the least well adsorbed compound
Multiple contaminants introduce a great deal of variability into the prediction of service life for respirator cartridges. Much of the laboratory testing and the mathematical models have utilized a single contaminant to determine service lives. Only a limited number of multiple contaminant situations have been studied and reported in the literature (e.g. Yoon, 1996; Jonas et. al., 1986). Cartridge service life for mixtures of compounds with significantly different chemical characteristics is probably best determined by experimental methods. Predictions based upon models without experimental data should probably be very conservative and ascribe the service life derived from the least well adsorbed compound to the total mixture concentration in terms of parts per million. The displacement of a less well adsorbed compound by a more highly adsorbed one may alter the actual service life from the estimated one in some cases.
The table below provides breakthrough times for 120 chemicals at various concentrations. OSHA derived these breakthrough times from the Gerry O. Wood math model (Wood, G.O., Estimating Service Lives of Organic Vapor Cartridges, American Industrial Hygiene Association Journal, 55:11-15, 1994).
Keep In Mind
If the conditions in your case are significantly different from these, in particular relative humidities greater than 65%, you will need to make the appropriate corrections to the time given by the table. Another section of this advisor provides a discussion of these factors.
OSHA used the following standard conditions:
- Number of respirator cartridges: 2
- Temperature: 72 degrees Fahrenheit (22 degrees Celsius)
- Sorbent: Activated charcoal
- Relative humidity: less than or equal to 50%
- Sorbent mass per cartridge: 26 g
- Breakthrough: 10%
- Flow rate: 53.3 liters per minute
How to use this Table:
Look down the left column to find the chemical and across the row to the column with the identified concentration, and there you will find the service life time in minutes.
Name | CAS # | Contaminant Concentration (ppm) | ||||
---|---|---|---|---|---|---|
50 | 100 | 200 | 500 | 1000 | ||
Aromatics | ||||||
Benzene | 71-43-2 | Work Shift | Limited to a maximum concentration of 50 ppm for negative pressure APR | |||
See the Benzene Standard [29 CFR 1910.1028(g)] | ||||||
Toluene | 108-88-3 | 1018 | 562 | 307 | 135 | 72 |
Ethylbenzene | 100-41-4 | 1133 | 604 | 319 | 135 | 70 |
m-Xylene | 108-38-3 | 1143 | 608 | 321 | 136 | 70 |
Cumene | 98-82-8 | 1122 | 586 | 304 | 126 | 64 |
Mesitylene | 108-67-8 | 1159 | 603 | 311 | 128 | 65 |
p-Cymene | 99-87-6 | 1104 | 566 | 289 | 117 | 59 |
Alcohols | ||||||
Methanol | 67-56-1 | This calculation is not applicable to this compound | ||||
Ethanol | 64-17-5 | 123 | 105 | 85 | 60 | 43 |
Isopropanol | 67-63-0 | 425 | 286 | 186 | 101 | 61 |
Allyl alcohol | 107-18-6 | 789 | 495 | 303 | 152 | 87 |
Propanol | 71-23-8 | 551 | 364 | 233 | 123 | 73 |
sec-Butanol | 78-92-2 | 773 | 464 | 272 | 130 | 72 |
Butanol | 71-36-3 | 1073 | 615 | 345 | 156 | 84 |
2-Pentanol | 6032-29-7 | 1091 | 601 | 327 | 143 | 75 |
3-Methyl-1-butanol | 123-41-3 | 1242 | 672 | 358 | 152 | 78 |
4-Methyl-2-pentanol | 108-11-2 | 1076 | 578 | 307 | 130 | 67 |
Pentanol | 71-41-0 | 1281 | 690 | 366 | 155 | 79 |
2-Ethyl-1-butanol | 97-95-0 | 1246 | 657 | 342 | 142 | 72 |
Monochlorides | ||||||
Methyl chloride | 74-87-3 | Not applicable, boiling point below ambient temperatures | ||||
Vinyl chloride | 75-01-4 | Not applicable, boiling point below ambient temperatures | ||||
See the Vinyl Chloride Standard [29 CFR 1910.1017(g)] | ||||||
Ethyl chloride | 75-00-3 | Not applicable, boiling point below ambient temperatures | ||||
2-Chloropropane | 75-29-6 | 224 | 150 | 99 | 54 | 34 |
Allyl chloride | 107-05-1 | 264 | 177 | 116 | 64 | 40 |
1-Chloropropane | 540-54-5 | 492 | 301 | 181 | 90 | 52 |
2-Chloro-2-methylpropane | 507-20-0 | 655 | 374 | 212 | 98 | 54 |
1-Chlorobutane | 109-69-3 | 733 | 422 | 239 | 111 | 61 |
2-Chloro-2-methylbutane | 594-36-5 | 705 | 398 | 222 | 101 | 55 |
1-Chloropentane | 543-59-9 | 852 | 474 | 260 | 116 | 62 |
Chlorocyclopentane | 930-28-9 | |||||
Chlorobenzene | 108-90-7 | 1327 | 709 | 376 | 160 | 83 |
1-Chlorohexane | 544-10-5 | 993 | 530 | 281 | 119 | 62 |
o-Chlorotoluene | 95-49-8 | 1297 | 682 | 356 | 148 | 76 |
1-Chloroheptane | 629-06-1 | 930 | 492 | 258 | 109 | 56 |
3-(Chloromethyl) heptane | 123-04-6 | 771 | 410 | 216 | 92 | 48 |
Dichlorides | ||||||
Dichloromethane | 75-09-2 | See the Methylene Chloride Standard [29 CFR 1910.1052(g)] | ||||
trans-1,2-Dichloroethylene | 156-60-5 | 296 | 198 | 129 | 71 | 44 |
1,1-Dichloroethane | 75-35-4 | 234 | 157 | 103 | 57 | 35 |
cis-1,2-Dichloroethylene | 156-59-2 | 356 | 236 | 152 | 82 | 50 |
1,2-Dichloroethane | 107-06-2 | 482 | 310 | 194 | 101 | 60 |
1,2-Dichloropropane | 78-87-5 | 776 | 452 | 259 | 121 | 67 |
cis-1,2-Dichloropropene | 6923-20-2 | |||||
trans-1,2-Dichloropropene | 7069-38-7 | |||||
1,4-Dichlorobutane | 110-56-5 | 846 | 475 | 263 | 118 | 64 |
o-Dichlorobenzene | 95-50-1 | |||||
Trichlorides | ||||||
Chloroform | 67-66-3 | 409 | 263 | 166 | 87 | 52 |
Methyl chloroform | 71-55-6 | 618 | 366 | 214 | 102 | 57 |
Trichloroethylene | 79-01-6 | 749 | 441 | 256 | 122 | 68 |
1,1,2-Trichloroethane | 79-00-5 | 976 | 558 | 314 | 143 | 77 |
1,2,3-Trichloropropane | 96-18-4 | |||||
Tetrachlorides | ||||||
Carbon tetrachloride | 56-23-5 | 677 | 398 | 231 | 109 | 61 |
Perchloroethylene | 127-18-4 | 1106 | 609 | 331 | 145 | 77 |
1,1,2,2-Tetrachloroethane | 79-34-5 | |||||
Pentachlorides | ||||||
Pentachloroethane | 76-01-7 | |||||
Acetates | ||||||
Methyl acetate | 79-20-9 | 182 | 131 | 92 | 55 | 36 |
Vinyl acetate | 108-05-4 | 389 | 251 | 158 | 82 | 49 |
Ethyl acetate | 141-78-6 | 483 | 299 | 182 | 91 | 53 |
Isopropyl acetate | 108-21-4 | 668 | 386 | 219 | 102 | 56 |
Isopropenyl acetate | 108-22-5 | |||||
Propyl acetate | 109-60-4 | 768 | 438 | 246 | 112 | 61 |
Allyl acetate | 591-87-7 | |||||
sec-Butyl acetate | 105-46-4 | |||||
Butyl acetate | 123-86-4 | 935 | 508 | 273 | 118 | 62 |
Isopentyl acetate | 123-92-2 | 1007 | 530 | 277 | 116 | 59 |
1,3-Dimethylbutyl acetate | 540-88-5 | |||||
Pentyl acetate | 628-63-7 | 1023 | 537 | 280 | 117 | 59 |
Hexyl acetate | 142-92-7 | |||||
Ketones | ||||||
Acetone | 67-64-1 | 118 | 92 | 69 | 44 | 30 |
2-Butanone | 78-93-3 | 423 | 271 | 170 | 88 | 52 |
2-Pentanone | 107-87-9 | 729 | 424 | 243 | 113 | 62 |
3-Pentanone | 96-22-0 | 744 | 433 | 248 | 115 | 63 |
4-Methyl-2-pentanone | 108-10-1 | 884 | 488 | 266 | 117 | 62 |
Mesityl oxide | 141-79-7 | 1063 | 581 | 314 | 136 | 71 |
Cyclopentanone | 120-92-3 | 1020 | 589 | 333 | 153 | 83 |
2,4-Pentanedione | 123-54-6 | 1103 | 612 | 335 | 147 | 78 |
3-Heptanone | 106-35-4 | 1061 | 561 | 294 | 123 | 63 |
2-Heptanone | 110-43-0 | 791 | 432 | 234 | 102 | 54 |
Cyclohexanone | 108-94-1 | 1257 | 683 | 366 | 157 | 81 |
5-Methyl-3-heptanone | ||||||
3-Methylcyclohexanone | 625-96-7 | |||||
Diisobutyl ketone | 108-83-8 | 963 | 496 | 254 | 103 | 52 |
4-Methylcyclohexanone | 589-92-4 | |||||
Alkanes | ||||||
Pentane | 109-66-0 | 332 | 205 | 124 | 63 | 37 |
2,3-Dimethylbutane | 79-29-8 | 533 | 307 | 175 | 82 | 45 |
Hexane | 110-54-3 | 585 | 334 | 189 | 87 | 48 |
Methylcyclopentane | 96-37-7 | 613 | 357 | 205 | 96 | 53 |
Cyclohexane | 110-82-7 | |||||
2,2,4-Trimethylpentane | 540-84-1 | 747 | 401 | 214 | 92 | 48 |
Heptane | 142-82-5 | 769 | 420 | 227 | 99 | 52 |
Methylcyclohexane | 108-87-2 | 842 | 463 | 252 | 111 | 59 |
1,3,5-Cycloheptatriene | 544-25-2 | |||||
2,2,5-Trimethylhexane | 3522-94-9 | 817 | 429 | 224 | 93 | 48 |
5-Ethylidene-2-orbornene | ||||||
Cyclooctane | 292-64-8 | 747 | 410 | 224 | 99 | 53 |
Nonane | 111-84-2 | 907 | 470 | 242 | 100 | 51 |
Decane | 124-18-5 | 902 | 461 | 234 | 95 | 48 |
Amines | ||||||
Methylamine | 74-89-5 | Not applicable, boiling point below ambient temperatures | ||||
Dimethylamine | 124-40-3 | Not applicable, boiling point below ambient temperatures | ||||
Ethylamine | 75-04-7 | Not applicable, boiling point below ambient temperatures | ||||
Isopropylamine | 75-31-0 | 167 | 117 | 80 | 46 | 30 |
Propylamine | 107-10-8 | 226 | 155 | 104 | 59 | 37 |
Diethylamine | 109-89-7 | 498 | 299 | 177 | 86 | 49 |
Butylamine | 109-73-9 | 580 | 349 | 207 | 100 | 57 |
Triethylamine | 121-44-8 | 747 | 412 | 225 | 100 | 53 |
Dipropylamine | 142-84-7 | 871 | 474 | 255 | 111 | 58 |
Diisopropylamine | 108-18-9 | 716 | 395 | 216 | 96 | 51 |
Cyclohexylamine | 108-91-8 | 1065 | 575 | 308 | 132 | 69 |
Dibutylamine | 111-92-2 | 980 | 507 | 261 | 107 | 54 |
Miscellaneous | ||||||
Methyl iodide | 74-88-4 | This calculation is not applicable to this compound | ||||
Acrylonitrile | 107-13-1 | Work Shift | 465 | Limited to a maximum concentration of 100 ppm | ||
See the Acrylonitrile Standard [29 CFR 1910.1045(h)] | ||||||
Dibromomethane | 74-95-3 | 947 | 565 | 331 | 158 | 89 |
Pyridine | 110-86-1 | 1031 | 599 | 342 | 158 | 87 |
Epichlorohydrin | 106-89-8 | 866 | 525 | 310 | 150 | 84 |
2-Methoxyethanol | 109-86-4 | |||||
1,2-Dibromoethane | 106-93-4 | 1252 | 699 | 384 | 170 | 90 |
1-Nitropropane | 108-03-2 | 933 | 548 | 315 | 147 | 80 |
2-Ethoxyethanol | 110-80-5 | 1105 | 624 | 345 | 154 | 81 |
Acetic anhydride | 108-24-7 | 1095 | 623 | 348 | 156 | 83 |
2-Methoxyethyl acetate | 32718-56-2 | 1092 | 594 | 319 | 137 | 71 |
Bromobenzene | 108-86-1 | 1448 | 761 | 397 | 165 | 84 |
2-Ethoxyethyl acetate | 111-15-9 | 1143 | 600 | 312 | 129 | 65 |
"Work Shift" Indicates that the service life for this contaminant is limited to a single workshift by the OSHA Standard. |
Steps | Example |
---|---|
1. Determine the concentration level of airborne contaminants in the work area. |
Grant owns a mid-size furniture company that paints with lacquers. They use a volatile solvent, toluene to quickly dry the lacquer. His several measurements of the toluene vapor reveal a worst case exposure of 200 ppm over an eight-hour day. |
2. Obtain access to a predictive table that is based on research. |
Grant surfs to the Wood Math Model Table, which lists cartridge service lives for 120 chemicals at varying concentrations. |
3. Use the table to come up with a cartridge service life estimate. |
Grant looks across the top of the table and finds the column for 200 ppm - the concentration equal to or above the level of toluene at his work place. Then he scrolls down the table and finds toluene in the aromatic group. He discovers that the service life estimate is 307 minutes. He writes down the number. |
4. Account for differences in the real work environment and those assumptions used by the math model:
|
Grant looks at the standard conditions given at the top of the table. He sees that the assumed relative humidity is 50% - much lower than the 75% humidity found in his work area. Grant is aware that such a high humidity will seriously affect organic vapor cartridge performance, so he applies a safety factor of two by cutting the estimate in half, giving him 154 minutes. The other standard conditions assumed by the table match his work environment. |
5. Create a written change schedule for the cartridges. |
Grant applies a further safety factor to the estimate and creates a change schedule requiring his employees to turn in their used cartridges for new ones every 2 hours. He also prints a copy of the Wood Math Model Table and circles the 307 minute value and notes the factor applied for humidity and the safety factor reduction to 2 hours, and includes them in his written respiratory program. |
The NIOSH MultiVapor™ Version 2.2.3 Application will do this calculation for you.
tb = (WeW⁄CoQ) - (Weρβ⁄kvCo) ln[(Co - Cx)⁄Cx]
- tb= breakthrough time (min)
- We = equilibrium adsorption capacity (g/g carbon)
- W = weight of carbon adsorbent
- rb = bulk density of the packed bed (g/cm3)
- Q = volumetric flow rate (cm3/min)
- Co = inlet concentration (g/cm3)
- Cx = exit concentration (g/cm3)
- Wood, Gerry O., Estimating Service Lives of Organic Vapor Cartridges, American Industrial Hygiene Association Journal, (1994, January), pages 11-15.
See the comparison of how the results of Wood's Equation compares with Experimental Tests.
Supporting Data:
We = WodL exp [-b′WoPe-1.8R2Τ2(ln{ρ⁄ρsat})2]
- Wo = carbon micropore volume (cm3/g)
- dL = liquid density of adsorbate (g/cm3)
- Τ = absolute temperature (°K = °C + 273)
- ρ = partial pressure corresponding to concentration Cx
- ρsat = saturation vapor pressure at temperature T
- Pe = molar polarization
- R = ideal gas constant (1.987)
- b′ = an empirical coefficient with value 3.56 x 10-5.
Pe = ((nD2 - 1)⁄(nD2 + 2) )Mw⁄dL
- Mw = molecular weight
- nD = refractive index
1⁄kV = ((1⁄VL) + 0.027)(I+S⁄Pe)
- Τ = 22 °C (295 °K).
- Pair of cartridges with a work rate of 53.3 L/min.
- Wo = 0.454 [determined from experimental data]
- dL = 0.6603 [available from scientific handbooks]
- Pe = 29.877 [calculated from available data]
- rsat = 121 torr [available from scientific handbooks]
- r = .38 torr (500 ppm challenge concentration) [calculated from available data]
- VL = 11.22 cm/s [calculated from available data]
- W = 70.6 g [calculated from available data]
- Co = .00178 g/cm3 [calculated from available data]
- kv = 4242 min-1
The Yoon-Nelson model is a descriptive model that uses experimental data to calculate parameters that are then entered into the model.
- † Yoon, Y.H., J.H. Nelson, Breakthrough Time and Adsorption Capacity of Respirator Cartridges, American Industrial Hygiene Association Journal, 53:303-316 (1992).
The basic equation for the model is:
t = Τ + 1⁄κ′ ln Ρ⁄1 - Ρ
- t = breakthrough time (min)
- Τ = 50% contaminant breakthrough time (min)
- κ′ = rate constant (min-1)
- Ρ = probability of contaminant breakthrough.
The value of Τ is determined from experimental data. The value of κ′ has been shown to be related to τ by the following formula:
κ′ = κ⁄τ
κ = proportionality constant that is constant independent of concentration and varies only slightly with humidity.
The value of τ is related to the contaminant concentration by the equation:
log τ = Κ″–a log CΙ
Κ″, a = constants that can be derived from experimental data. They vary with humidity, but for humidities ≤ 50% they are essentially constant.
CΙ = contaminant assault concentration. (ppm)
It is possible to determine the constants κ, Κ″, and a from a minimum of 3 experimental data points. However, the inclusion of additional data points increases the accuracy of the model.
See the comparison of how the results of Wood's Equation compares with Experimental Tests.
Steps | Example |
---|---|
1. Determine the following:
|
The lacquer-drying technique has been modified at Grant's shop, which has lowered the amount of airborne toluene to 125 ppm. While this is below the OSHA PEL, Grant still wants his painters to wear respirators. When Grant looks to the Wood table for this concentration to figure a service life estimate, he finds there is no column for 125. It gives data for 100 ppm and then jumps right up to 200 ppm. Grant understands that he must go with the 200 ppm estimate of 154 minutes to be safe, yet he thinks the cartridges should last longer than that. He determines to use the Wood calculation for his exact concentration of 125 ppm. So, Grant does a little research to come up with the required data. He calls the manufacturer to get data on its respirator cartridges. |
2. Put the information from Step 1 into a mathematical equation and calculate for the unknown service life. |
Grant hears that the NIOSH computer tool will perform the calculation for him. All he has to do is provide his information to NIOSH's MultiVapor™ Version 2.2.3 Application, which asks for the data one step at a time. Grant is delighted with how easy it is. |
3. Use the table to come up with a cartridge service life estimate. |
Grant looks across the top of the table and finds the column for 200 ppm - the concentration equal to or above the level of toluene at his work place. Then he scrolls down the table and finds toluene in the aromatic group. He discovers that the service life estimate is 307 minutes. He writes down the number. |