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This study investigated the characteristics of iron corrosion scales in pipes at tube well, overhead tank, and consumers’ end in older untreated water distribution system in Peshawar city, Pakistan. Effect of water quality conditions on corrosion scales and that of scales on drinking water quality in such systems was also assessed by undertaking a comparison with new piped distribution systems. The scales were analyzed for chemical composition and morphology using X-ray diffraction (XRD), inductively coupled plasma (ICP), and a scanning electron microscope (SEM), while water quality was examined for physicochemical and biological characteristics. The main crystalline phases of corrosion scales were goethite, magnetite, siderite, and quartz. From tube well to consumers’ end, goethite increased from 36 up to 48%, quartz declined from 22 to 15%, while magnetite fluctuated and siderite disappeared. Elemental composition of scales showed the deposition of Zn, Al, Mn, Cr, Pb, Cu, As, and Cd with Zn (13.9 g/kg) and Al (3.6 g/kg) in highest proportion. The SEM analysis illustrated the presence of microbial communities indicating the formation of biofilms in the corrosion scales. The significant difference (P <?0.05) in levels of dissolved oxygen (DO), Cl?, SiO44?, electrical conductivity (EC), SO42?, NO3?, alkalinity, hardness, and trace metals between old (DS-O) and new piped systems indicated their role in corrosion scale formation/destabilization and the effect of scale dissolution on water quality. In DS-O, EC, Cu, and Mn were significantly higher (P?<?0.05), whereas turbidity, EC, DO, and SiO44? significantly increased from source to consumers’ end implying a higher dissolution of scales and lowered corrosion rates in DS-O to utilize SiO44? and DO for iron oxidation.
相似文献Prediction of water quality is a critical issue because of its significant impact on human and ecosystem health. This research aims to predict water quality index (WQI) for the free surface wetland using three soft computing techniques namely, adaptive neuro-fuzzy system (ANFIS), artificial neural networks (ANNs), and group method of data handling (GMDH). Seventeen wetland points for a period of 14 months were considered for monitoring water quality parameters including conductivity, suspended solid (SS), biochemical oxygen demand (BOD), ammoniacal nitrogen (AN), chemical oxygen demand (COD), dissolved oxygen (DO), temperature, pH, phosphate nitrite, and nitrate. The sensitivity analysis performed by ANFIS indicates that the significant parameters to predict WQI are pH, COD, AN, and SS. The results indicated that ANFIS with Nash-Sutcliffe Efficiency (NSE = 0.9634) and mean absolute error (MAE = 0.0219) has better performance to predict the WQI comparing with ANNs (NSE = 0.9617 and MAE = 0.0222) and GMDH (NSE = 0.9594 and MAE = 0.0245) models. However, ANNs provided a comparable prediction and the GMDH can be considered as a technique with an acceptable prediction for practical purposes. The findings of this study could be used as an effective reference for policy makers in the field of water resource management. Decreasing variables, reduction of running time, and high speed of these approaches are the most important reasons to employ them in any aquatic environment worldwide.
相似文献Considering its richness in organic and inorganic mineral nutrients, the recycling of sewage sludge (SS) is highly considered as a soil supplement in agriculture. However, the fate of hazardous heavy metal accumulation in the crops cultivated in SS amended soils is always a source of concern. Since nanoparticles are widely recognized to reduce heavy metal uptake by crop plants; thus, the present experiment deals with okra (Abelmoschus esculentus L. Moench) cultivation under the combined application of SS and TiO2-nanoparticles (NPs). Triplicated pot experiments were conducted using different doses of SS and TiO2-NPs such as 0 g/kg SS (control), 50 g/kg SS, 50 g/kg SS?+?TiO2, 100 g/kg SS, and 100 g/kg SS?+?TiO2, respectively. The findings of this study indicated that among the doses of treatment combinations investigated, 100 g/kg SS?+?TiO2 showed a significant (p?<?0.05) increase in the okra plant yield (287.87?±?4.06 g/plant) and other biochemical parameters such as fruit length (13.97?±?0.54 cm), plant height (75.05?±?3.18 cm), superoxide dismutase (SOD: 110.68?±?3.11 μ/mg), catalase (CAT: 81.32?±?3.52 μ/mg), and chlorophyll content (3.12?±?0.05 mg/g fwt.). Also, the maximum contents of six heavy metals in the soil and cultivated okra plant tissues (fruit, stem, and root regions) followed the order of Fe?>?Mn?>?Cu?>?Zn?>?Cr?>?Cd using the same treatment. Bioaccumulation and health risk assessment indicated that foliar application of TiO2-NPs significantly reduced the fate of heavy metal accumulation under higher doses of SS application. Therefore, the findings of this study suggested that the combined use of SS and TiO2-NPs may be useful in ameliorating the negative consequences of heavy metal accumulation in cultivated okra crops.
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