The solar photocatalytic degradation of diuron, which is one of the herbicides, has been studied by a solar pilot plant in heterogeneous solar photocatalysis with titanium dioxide. The pilot plant was made up of compound parabolic collectors specially designed for solar photocatalytic applications. The influence of different variables such as, H2O2 initial concentration, TiO2 initial concentration, and diuron initial concentration with their relationship to the degradation efficiency were studied. Hydrogen peroxide (H2O2) found to increase the rate of diuron degradation. The best removal efficiency of heterogeneous solar photocatalytic TiO2 system was found to be 46.65 % and for heterogeneous solar photocatalytic TiO2/ H2O2 system was fo

S Khalifa E, N Adil A, K Nabeel O…, 2008

KE Sharquie, AA Noaimi, S Al-Hashimy, IGF Al-Tereihi, The Iraqi Postgraduate Medical Journal, 2013 - Cited by 5

KE Sharquie, WS Al-Dori, IK Sharquie, AA Al–Nuaimy, Hospital, 2004 - Cited by 20

Various industrial applications include the dyeing of textiles, paper, leather, and food products, as well as the cosmetics industry. Physic-chemical methods are required to breakdown dyes because they are known to be harmful and persistent in the environment. Many companies' treated effluents contain small amounts of dyes. When it comes to removing dye from wastewater, adsorption has verified to be aneconomical alternative to more traditional treatment procedures. It's important to degrade color impurities in industrial effluents since they constitute a serious health and environmental concern. One way that's been tried is using clay minerals as an adsorbent. Using adsorption for removing

The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To