A model for predicting endotoxin concentrations in metalworking fluid sumps in small machine shops.
METHODS
In British Columbia, Canada, nineteen small machine shops which used water-based metalworking fluids (MWF) were examined. One bulk MWF sample was taken from each independent sump (N=140) and tested for endotoxin using the Limulus Amoebocyte Lysate assay. Factors that might influence the MWF sump endotoxin concentration were investigated using mixed effect multiple regression modelling to control for repeated measures within shops.


RESULTS
The geometric mean (GM) endotoxin concentration was 6791 EU/ml. Contamination of MWF with tramp oil, MWF pH, MWF temperature, and MWF type were significant predictors of sump fluid endotoxin concentration (model P=0.0001, ordinary least squares R(2) =0.36). Concentrations of endotoxin in sump fluids were increased by MWF contamination with tramp oils such as hydraulic oils, preservative oils, spindle oils, slidway lubricants, gear lubricants, and greases (model predicted GM=17400 EU/ml vs. 1600 EU/ml without tramp oil). Concentrations were also elevated where pH was lower than 8.5 (predicted GM=10600, vs 3600 EU/ml for pH 8.5 to 9.5), where soluble fluids were used (predicted GM=11800 vs. 2800 EU/ml for synthetic fluids), and where sump fluid temperatures were higher (predicted GM=2600 EU/ml at 11 degrees C vs. 21500 EU/ml at 32 degrees C). The within-shop correlation of sump bulk fluid endotoxin concentrations was 38%.


CONCLUSIONS
Minimizing tramp oil contamination, using synthetic fluids, and monitoring pH and temperature would be valuable tools for controlling endotoxin contamination in MWF sumps. In addition, since there was correlation within-shop, contamination of one sump in a shop may suggest changing the fluids in all.
Park
D
D
Department of Environmental Health, Korea National Open University, Dongsung-dong, Jongro-ku, Seoul, South Korea, 110-791.
Teschke
K
K
Bartlett
K
K
D004731:Endotoxins / Q000032:analysis*; D006801:Humans; D007219:Industrial Oils / Q000009:adverse effects / Q000032:analysis; D008033:Limulus Test / Q000379:methods*; D008669:Metallurgy; D015233:Models, Statistical; D016273:Occupational Exposure / Q000009:adverse effects / Q000032:analysis*; D011237:Predictive Value of Tests; D014865:Waste Disposal, Fluid; D014867:Water / Q000032:analysis*; D014871:Water Microbiology
D004731:Endotoxins; D014867:Water