ISSN electrónico: 2007-2422   ISSN impreso: 0187-8336      Usted esta aquí: Inicio
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Kinetics and influential factors of nanoscale iron-facilitated nitrate-nitrogen removal
  • Yujia Song
  • Shoufa Song
In this paper, a new nanoscale iron adsorbent was prepared using the liquid phase reduction method. The effects of the initial nitrate-nitrogen concentration, pH, and reaction temperature on the nitrate-nitrogen removal efficiency of the nanoscale iron were investigated. The experimental results indicated that the initial nitrate nitrogen concentration significantly affected the reaction rate, but not the removal efficiency of the nanoscale iron. In addition, the optimal pH for the removal of nitrate-nitrogen was 2.0. As the temperature increased, the nitrate-nitrogen removal rate increased. A pseudo-second-order kinetic equation, in which the nitrate nitrogen concentration at reaction time t was used as the initial concentration, was developed in order to determine the reaction rate constant k at different temperatures. According to the results, the maximum value of k (0.014 mg/(l/min)) was observed at 50°C. The reaction activation energy Ea was approximately 17.18 kJ/mol. The reaction was primarily influenced by the mass transfer. In a neutral solution, in this
case water, the reduction product of the nitrate nitrogen was ammonia nitrogen.
Keywords: Nitrate nitrogen, water pollution, reaction kinetics, nanometer, adsorption.
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Research on the hydrologic cycle characteristics using stable isotopes of oxygen and hydrogen in the Jinxiuchuan Basin
  • Tong Wang
  • Zhenghe Xu
  • Shengdong Zhang
  • Lizhi Zhang
  • Zhiqiang Zhao
Stable isotopes of oxygen (δ18O) and hydrogen (δD) in water were used as important indicators to understand the hydrologic cycle or processes. To understand the hydrologic cycle characteristics of the Jinxiuchuan basin, we used the isotope labeling method and the industrial salt tracing technique in this research. Sixty-seven samples of different water bodies were collected at different sampling sites from July 2011 to July 2012. Water samples were measured for stable hydrogen and oxygen isotopes by using Liquid Water Isotope Analyzer (LWIA-24d) to examine the linkage between precipitation, river water, soil water, and groundwater of the Jinxiuchuan basin in Jinan. The results show that δD and δ18O varied from 35.6 to 128.3 ‰ and from 5.3 to 17.5‰, respectively. The meteoric water line was established in the Jinxiuchuan basin, e.g. δD = 7.16δ18O+4.35‰, which was in accordance with the global meteoric water line and the meteoric water line of China. The d-excess (deuterium excess) values vary with time and space, ranging from 5.1 to 22.3‰, and increase gradually from the southeast to the northwest. In addition, the exchange of different water bodies was determined preliminarily, the rates of precipitation transforming into river water, soil water, and groundwater are 43.76, 21.91, and 6.84%, and the remaining is 27.49% returned to the atmosphere. The results indicated the hydrologic cycle characteristics in the Jinxiuchuan basin. It has the reference value for precipitation isotopes research in semi-humid regions.
Keywords: Stable isotopes of hydrogen and oxygen, precipitation, deuterium excess, Jinxiuchuan basin.
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Simulation for non-point source pollution based on QUAL2E in the Jinghe River, Shaanxi Province, China
  • Jucui Wang
  • Aidi Huo
  • Anyan Hu
  • Xuezhen Zhang
  • Yanqing Wu

Water pollution in river basins is significantly influenced by point-source and non-point-source pollutants. Compared with point-source pollutants, the identification and quantification of non-point-source pollutants is a critical but difficult issue in water environmental pollution studies. The Jinghe River is one of the main tributaries of the Weihe River. However, the non-point-source pollution of this river is not well understood. In order to analyze the sources of point and non-point loads to river water, the river water quality model QUAL2E and Principal Component Analysis (PCA) & Factor Analysis (FA) were applied simultaneously to calculate the point- and non-point-source loads of ammonia nitrogen and nitrate nitrogen, respectively, in dry and wet seasons from 2002 to 2007. The results show that NO3--N can be associated with point-source pollution such as domestic sewage in dry seasons but non-point-source pollution generated by precipitation in wet seasons. NH4+-N can be associated with point-source pollution throughout the year. The methods applied in this research provide reliable results on non-point-source pollution caused by storm runoff.

Keywords: QUAL2E, degradation coefficient, source/sink term, non-point-source pollution.
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Improved online sequential extreme learning machine for simulation of daily reference evapotranspiration


  • Yubin Zhang
  • Zhengying Wei
  • Lei Zhang
  • Jun Du
The traditional extreme learning machine has significant disadvantages, including slow training, difficulty in selecting parameters, and difficulty in setting the singularity and the data sample. A prediction model of an improved Online Sequential Extreme Learning Machine (IOS-ELM) of daily reference crop evapotranspiration is therefore examined in this paper. The different manipulation of the inverse of the matrix is made according to the optimal solution and using a regularization factor at the same time in the model. The flexibility of the IOS-ELM in ET0 modeling was assessed using the original meteorological data (Tmax, Tm, Tmin, n, Uh, RHm, Φ, Z) of the years 1971–2014 in Yulin, Ankang, Hanzhong, and Xi’an of Shaanxi, China. Those eight parameters were used as the input, while the reference evapotranspiration values were the output. In addition, the ELM, LSSVM, Hargreaves, Priestley-Taylor, McCloud and IOS-ELM models were tested against the FAO-56 PM model by the performance criteria. The experimental results demonstrate that the performance of IOS-ELM was better than the ELM and LSSVM and significantly better than the other empirical models. Furthermore, when the total ET0 estimation of the models was compared by the relative error, the results of the intelligent algorithms were better than empirical models at rates lower than 5%, but the gross ET0 empirical models mainly had 12 to 64.60% relative error. This research could provide a reference to accurate ET0 estimation by meteorological data and give accurate predictions of crop water requirements, resulting in intelligent irrigation decisions in Shaanxi.
Keywords: Daily reference evapotranspiration, extreme learning machine, online learning, matrix singularity.
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Comparison on nitrosation and anaerobic ammonium oxidation between activated sludge and biofilm from an autotrophic nitrogen removal SBBR
  • Yu Qin
  • Jinsong Guo
  • Fang Fang
Activated sludge and biofilm from a Sequencing Biofilm Batch Reactor (SBBR) were studied to analyze their different roles in autotrophic nitrogen removal process. Results showed that under aerobic conditions, the ammonia oxidation rate of activated sludge was 100% and the maximum rate was 0.23 mgN mgVSS-1 d-1 during a 48 h test cycle. Under the same conditions, the ammonia oxidation rate of the biofilm was 72% and the maximum rate was 0.08 mgN mgVSS-1 d-1. The population of AOB (ammonium oxidizing bacteria) in activated sludge was 1.88 × 1011 cells/g, 10 times that in a biofilm. The TN (total nitrogen) removal rate of activated sludge and biofilm under anaerobic conditions were 37 and 83%, respectively. The rate of anaerobic ammonium oxidation by activated sludge was 0.09 mgN mgVSS-1 d-1 and that of biofilm was 0.22 mgN mgVSS-1 d-1. ANAMMOX (anaerobic ammonium oxidizing bacteria) were the dominant bacteria in terms of cell number in this system, with 2.66 × 1012 cells/g in biofilm—2.6 times more than in activated sludge. TN was removed mainly by anaerobic ammonium oxidation.
Keywords: Autotrophic nitrogen removal, biofilm, activated sludge, AOB, ANAMMOX.
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Revista Digital ISSN 2007-2422



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