The adsorption behaviour of Basic Red 12, Acid Orange 7 and Acid Blue 1 on zinc oxide nanoparticles (ZNP) has been investigated to understand the physicochemical process involved and to explore the possible use of nanoparticles in the treatment and management of textile waste matter. The dye removal capacity of ZNP towards Basic Red 12, Acid Orange 7 and Acid Blue 1 was found to be 15.64, 6.78 and 6.38 mg g?1, respectively. The adsorption process was pH dependent and optimum pH values of 9.0, 2.0 and 4.0 were obtained for Basic Red 12, Acid Orange 7 and Acid Blue 1, respectively. Equilibrium was established after 1.0 h for all dyes. Langmuir, Freundlich and Temkin isotherm models were applied to the system. The adsorbent ZNP was characterised using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) and Fourier transform infrared (FTIR) techniques. SEM analysis revealed the noticeable nanoporous morphology of the material. The results of FTIR spectroscopy showed that the process is driven by an electrostatic complexation mechanism. XRD studies revealed the nanocrystalline structure of ZNP. BET surface area measurement suggested a high pore volume and large surface area for the adsorbent. The kinetic measurements suggested pseudo-second-order kinetic processes with high regression coefficients and smaller standard error of estimate values and lower residual sum of squares. The thermodynamic measurements suggested that all processes were exothermic and accompanied by negative values for Δ G0, Δ S0 and Δ H0. 相似文献
Identifying source information after river chemical spill occurrences is critical for emergency responses. However, the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated. To fill this gap, stochastic analysis approaches, including a regional sensitivity analysis method, identifiability plot and perturbation methods, were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework. Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules. For example, the release load can be most easily inverted, and the source location is responsible for the largest uncertainty among the source parameters. The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty. The differences among the different objective functions are smaller for instantaneous release than for continuous release cases. Small monitoring errors affect the inversion results only slightly, which can be ignored in practice. Interestingly, the estimated values of the release location and time negatively deviate from the real values, and the extent is positively correlated with the relative size of the mixing zone to the objective river reach. These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.
