排序方式： 共有35条查询结果，搜索用时 31 毫秒
21.
Degradation of trace aqueous 4-chloro-2-nitrophenol occurring in pharmaceutical industrial wastewater by ozone 总被引：1，自引：1，他引：0
P. Gharbani M. Khosravi Ph.D S. M. Tabatabaii Ph.D K. Zare Ph.D S. Dastmalchi Ph.D A. Mehrizad 《International Journal of Environmental Science and Technology》2010,7(2):377-384
Degradation of 4-chloro-2-nitro phenol by ozonation in aqueous solution was studied in a semi batch reactor under constant ozone dosage and variable pH conditions. The effectiveness of the process was estimated based on the degree of conversion of 4-chloro-2-nitro phenol. It was observed that ozonation is more effective at alkaline reaction of medium than other conditions. The degree of conversion achieved (at the first 5 minutes of the process)at pH 9 was 99.64% compared to 99.03% and 77.35% at pH 7 and 3, respectively. Another parameter used to quantify the 4-chloro-2-nitrophenol during ozonation was the pseudo first order rate constant k [min?1]. Results showed that the rate constant of the process was approximately much higher at the alkaline pH compared to acidic ones. A considerable improvement in chemical oxygen demand removal was observed at pH above 7. At pH 9, the reduction in chemical oxygen demand at the end of the process reached 56.9 %. The degree of organically bounded nitrogen conversion to nitrate was higher at pH 3. Of the total organic carbon reduction, 15.89 % was observed at pH 9. The 4-chloro-2-nitro phenol degradation intermediate products were analyzed by mass- spectrometry. The main intermediate product was chlorophenol. 相似文献
22.
Khabat Khosravi Rahim Barzegar Shaghayegh Miraki Jan Adamowski Prasad Daggupati Mohammad Reza Alizadeh Binh Thai Pham Mohammad Taghi Alami 《Ground water》2020,58(5):723-734
While it remains the primary source of safe drinking and irrigation water in northwest Iran's Maku Plain, the region's groundwater is prone to fluoride contamination. Accordingly, modeling techniques to accurately predict groundwater fluoride concentration are required. The current paper advances several novel data mining algorithms including Lazy learners [instance-based K-nearest neighbors (IBK); locally weighted learning (LWL); and KStar], a tree-based algorithm (M5P), and a meta classifier algorithm [regression by discretization (RBD)] to predict groundwater fluoride concentration. Drawing on several groundwater quality variables (e.g., concentrations), measured in each of 143 samples collected between 2004 and 2008, several models predicting groundwater fluoride concentrations were developed. The full dataset was divided into two subsets: 70% for model training (calibration) and 30% for model evaluation (validation). Models were validated using several statistical evaluation criteria and three visual evaluation approaches (i.e., scatter plots, Taylor and Violin diagrams). Although Na+ and Ca2+ showed the greatest positive and negative correlations with fluoride (r = 0.59 and −0.39, respectively), they were insufficient to reliably predict fluoride levels; therefore, other water quality variables, including those weakly correlated with fluoride, should be considered as inputs for fluoride prediction. The IBK model outperformed other models in fluoride contamination prediction, followed by KStar, RBD, M5P, and LWL. The RBD and M5P models were the least accurate in terms of predicting peaks in fluoride concentration values. Results of the current study can be used to support practical and sustainable management of water and groundwater resources. 相似文献
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N. Mansouriieh M. R. Sohrabi M. Khosravi 《International Journal of Environmental Science and Technology》2016,13(5):1393-1404
Bimetallic Fe/Ni nanoparticles were synthesized and used for the removal of profenofos organophosphorus pesticide from aqueous solution. These novel bimetallic nanoparticles (Fe/Ni) were characterized by scanning electron microscopy, energy-dispersive X-ray analysis spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy. The effect of the parameters of initial pesticide concentration, pH of the solution, adsorbent dosage, temperature, and contact time on adsorption was investigated. The adsorbent exhibited high efficiency for profenofos adsorption, and equilibrium was achieved in 8 min. The Langmuir, Freundlich, and Temkin isotherm models were used to determine equilibrium. The Langmuir model showed the best fit with the experimental data (R 2 = 0.9988). Pseudo-first-order, pseudo-second-order, and intra-particle diffusion models were tested to determine absorption kinetics. The pseudo-second-order model provided the best correlation with the results (R 2 = 0.99936). The changes in the thermodynamic parameters of Gibb’s free energy, enthalpy, and entropy of the adsorption process were also evaluated. Thermodynamic parameters indicate that profenofos adsorption using Fe/Ni nanoparticles is a spontaneous and endothermic process. The value of the activation energy (E a = 109.57 kJ/mol) confirms the nature of the chemisorption of profenofos onto Fe/Ni adsorbent. 相似文献
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Assessment of drought hazard impact on wheat cultivation using standardized precipitation index in Iran 总被引：1，自引：0，他引：1
Mohammad Reza Mansouri Daneshvar Ali Bagherzadeh Mahmood Khosravi 《Arabian Journal of Geosciences》2013,6(11):4463-4473
The assessment of drought hazard impacts on wheat cultivation as a strategic crop in Iran is essential for making mitigation plans to reduce the impact of drought. Standardized precipitation index has gained importance in recent years as a potential drought indicator and is being used more frequently for assessment of drought hazard in many countries. In the present study, the calculated standardized precipitation index for 48 stations dataset in the 30-year time scale fulfilled 30 statistical matrices. The drought hazard index map was produced by sum overlaying the spatial representations of 30 statistical matrices and categorized into four levels of low, moderate, high, and very high, which demonstrated probability of drought occurrences of 10–20 %, 20–30 %, 30–40 %, and 40–50 %, respectively. Finally, after the general division of zonal statistics in drought hazard index map of Iran, major drought hazard zones were geographically classified into five zones. The statistical analysis showed a significant correlation (R 2?=?0.701 to 0.648) between drought occurrences and wheat cultivation including surface area and total production for these drought hazard zones. 相似文献
26.
Binh T. Pham Indra Prakash Khabat Khosravi Kamran Chapi Phan T. Trinh Trinh Q. Ngo 《国际地球制图》2013,28(13):1385-1407
AbstractIn this study, the main goal is to compare the predictive capability of Support Vector Machines (SVM) with four Bayesian algorithms namely Naïve Bayes Tree (NBT), Bayes network (BN), Naïve Bayes (NB), Decision Table Naïve Bayes (DTNB) for identifying landslide susceptibility zones in Pauri Garhwal district (India). First, landslide inventory map was built using 1295 historical landslide data, then in total sixteen influencing factors were selected and tested for landslide susceptibility modelling. Performance of the model was evaluated and compared using Statistical based index methods, Area under the Receiver Operating Characteristic (ROC) curve named AUC, and Chi-square method. Analysis results show that that the SVM has the highest prediction capability, followed by the NBT, DTNBT, BN and NB, respectively. Thus, this study confirms that the SVM is one of the benchmark models for the assessment of susceptibility of landslides. 相似文献
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Sajad Zareie Kazem Rangzan Hassan Khosravi Vladimir Modestovich Sherbakov 《Arabian Journal of Geosciences》2018,11(14):391
Remote sensing data can be used as the basis for meteorological data. Due to the limitations of meteorological stations on the Earth, derivation of land surface temperature is one of the most important aspects of the remote sensing application in climatology studies. In the present study, Landsat-8 thermal infrared sensor data of the scene located over Khuzestan province with row/path of 165/38 were used to derive land surface temperature (LST). Normalized difference vegetation index (NDVI), fraction of vegetation cover, satellite brightness temperature, and land surface emissivity were calculated as the vital criteria to derive LSTs using the split window algorithms. LST determination was performed by nine different split window algorithms. Eventually, LST products were evaluated using ground-based measurements at the meteorological stations of the study area. The results showed that algorithm of Coll and Casselles had a highest accuracy with RMSE 1.97 °C, and Vidal’s method presented the lowest accuracy to derive LST with RMSE 4.11 °C. According to the results, regions with high density of vegetation and water resources have lowest diurnal temperature and regions with bare soils and low density of vegetation have a highest diurnal temperature. Results of the study indicated that LST algorithm accuracy is an important factor in the environmental and climate change studies. 相似文献
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Maharlu Lake with Na–Cl water type is the terminal point of a closed basin in southern Iran. A total of 10 water samples from two rivers discharging to the lake and 78 water samples of surface and pore brine of Maharlu Lake have been collected from different depths (surface, 20, 50 and 100 cm) of four sampling stations along the lake during a period of lake water-level fluctuation (November 2014–July 2015). To investigate chemical interaction between lake surface water and shallow pore water and to understand the major factors governing chemical composition of Maharlu brine, concentrations of major and minor (boron, bromide and lithium) solutes, pH and total dissolved solids have been measured in collected water samples. Saturation indices of evaporite minerals in collected water samples have been also calculated. The chemical behavior of dissolved solutes and evaporative evolution of the lake brine during a hydrological period have been simulated using PHREEQC. The results of our investigations indicated that chemical composition of lake surface water and pore brine of Maharlu Lake are mainly connected with lake water-level fluctuations and distance from input rivers (and depth), respectively. Hydrochemical investigations and statistical analysis showed that the brines chemistry of Maharlu is mainly controlled by three processes: brine evaporative evolution, dissolution–precipitation and diagenetic evolution of secondary carbonates. 相似文献
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Sinan Q. Salih Ahmad Sharafati Khabat Khosravi Hossam Faris Ozgur Kisi Hai Tao 《水文科学杂志》2020,65(4):624-637
ABSTRACTSuspended sediment load (SSL) is one of the essential hydrological processes that affects river engineering sustainability. Sediment has a major influence on the operation of dams and reservoir capacity. This investigation is aimed at exploring a new version of machine learning models (i.e. data mining), including M5P, attribute selected classifier (AS M5P), M5Rule (M5R), and K Star (KS) models for SSL prediction at the Trenton meteorological station on the Delaware River, USA. Different input scenarios were examined based on the river flow discharge and sediment load database. The performance of the applied data mining models was evaluated using various statistical metrics and graphical presentation. Among the applied data mining models, the M5P model gave a superior prediction result. The current and one-day lead time river flow and sediment load were the influential predictors for one-day-ahead SSL prediction. Overall, the applied data mining models achieved excellent predictions of the SSL process. 相似文献