The equa tion is modified as follows to account for the influence of (3) where a,b,c,d = constants. The model was applied to the data, resulting in 99 .115 % of the variance being explained, an R of 0.996 and a final loss of 0.00437. The determined constants were as follows: a = 1.693, b = 0.688, c = 396.056, d= 0.862, h = 0.301, and kmin = 0.0195. That is, the model is good for the range of PCPj from 1 mg/1 to 100 mg/1 and from 1 M to 0.001 M. Therefore, the model is only good for

DOI link for The equa tion is modified as follows to account for the influence of (3) where a,b,c,d = constants. The model was applied to the data, resulting in 99 .115 % of the variance being explained, an R of 0.996 and a final loss of 0.00437. The determined constants were as follows: a = 1.693, b = 0.688, c = 396.056, d= 0.862, h = 0.301, and kmin = 0.0195. That is, the model is good for the range of PCPj from 1 mg/1 to 100 mg/1 and from 1 M to 0.001 M. Therefore, the model is only good for

The equa tion is modified as follows to account for the influence of (3) where a,b,c,d = constants. The model was applied to the data, resulting in 99 .115 % of the variance being explained, an R of 0.996 and a final loss of 0.00437. The determined constants were as follows: a = 1.693, b = 0.688, c = 396.056, d= 0.862, h = 0.301, and kmin = 0.0195. That is, the model is good for the range of PCPj from 1 mg/1 to 100 mg/1 and from 1 M to 0.001 M. Therefore, the model is only good for