Figure 2 shows Langmuir, Freundlich andDubinin-Radushkevich adsorption isotherms of the four adsorbents by linear analysis;

Table 4 summarizes the corresponding isotherm parameters, their correlation coefficients (r

^{2}) and related standard errors (S.E.) for each parameter. According to the r

^{2} and related S.E. for each parameter in

Table 4, the Langmuir model fitted the experimental data best by linear analysis, while the Freundlich fitted worst. These results are in good agreement with the results indicated by nonlinear analysis. However, the r

^{2} (0.995, 0.999, 0.997 and 0.990 for M1, M2, M3, and M4, respectively) were all higher than the corresponding r

^{2} obtained by nonlinear analysis methods. Moreover, although the r

^{2} in Dubinin-Radushkevich model for M3 (0.980) is higher than that obtained by non-linear analysis (0.975), the r

^{2} for the other three adsorbents are lower. In particularly, the r

^{2} for M2 (0.688) is extremely lower than its corresponding r

^{2} by non-linear analysis (0.977). Meanwhile, all the S.E. values are much higher than those determined in non-linear analysis. These indicate that the linear fitting of experimental data into Dubinin-Radushkevich model may cause great fluctuation of r

^{2}, and the predicted parameters may induce deviation.

**Figure 2.**
Linear fitting plots of (**a**) Langmuir, (**b**) Freundlich, and (**c**) Dubinin-Radushkevich isotherm models for the four adsorbents (M1, M2, M3 and M4).