Phosphate adsorption performance of a novel filter substrate made from drinking water treatment residuals

Phosphate is one of the most predominant pollutants in natural waters. Laboratory experiments were conducted to investigate the phosphate adsorption performance of a(NFS) made from drinking water treatment residuals. The adsorption of phosphate on the NFS fitted well with the Freundlich isotherm and pseudo second-order kinetic models. At p H 7.0, the maximum adsorption capacity of 1.03 mg/g was achieved at 15°C corresponding to the wastewater temperature in cold months, and increased notably to 1.31 mg/g at 35°C.Under both acidic conditions(part of the adsorption sites was consumed) and basic conditions(negative charges formed on the surface of NFS, which led to a static repulsion of PO43-and HPO42-), the adsorption of phosphate was slightly inhibited. Further study showed that part of the adsorption sites could be recovered by 0.25 mol/L Na OH. The activation energy was calculated to be above 8.0 k J/mol, indicating that the adsorption of phosphate on NFS was probably a chemical process. Considering the strong phosphate adsorption capacity and recoverability, NFS showed great promise on enhancing phosphate removal from the secondary treated wastewater in the filtration process.     

中国煤炭市场现状剖析与国际煤价走势研究

近年来我国己成为世界第一煤炭生产国、消费国和进口国.2013年实施电煤价格并轨后,我国国内煤价与国际煤价的波动趋势也将日趋一致.在国内煤炭供给过剩的情况下,我国煤炭进口却仍在大幅增加,对我国煤炭市场造成了较大影响.因此,准确预测国际煤炭价格既有利于择机进口煤炭,也有助于进一步完善国家煤炭应急储备机制.通过整体经验模态分解(EEMD),非平稳煤价序列被分解重组为正常市场波动、重大事件影响、长期趋势等具有不同经济含义的时间序列.这三项时间序列被用于支持向量机(SVM)组合建模对国际煤价进行了一年内短期预测.研究发现:2013年国际煤炭价格将呈整体下跌趋势,趋向长期趋势线,并处于低位小幅波动.     

抗差自适应Kalman滤波在动态变形监测中的应用研究

抗差自适应Kalman滤波算法中,抗差等价权矩阵和自适应因子的计算,要求观测信息具有多余观测量且准确可靠,但在动态变形监测应用中,通常滤波观测值仅为三维坐标且存在较强噪声和粗差的影响.为此,先对该算法中的自适应因子和抗差等价权矩阵的计算进行研究和改进,然后计算了某高速公路边坡的GPS动态监测数据.结果表明,抗差自适应K...     

A meteorologically adjusted ensemble Kalman filter approach for inversing daily emissions: A case study in the Pearl River Delta, China

The conventional Ensemble Kalman filter (EnKF), which is now widely used to calibrate emission inventories and to improve air quality simulations, is susceptible to simulation errors of meteorological inputs, making accurate updates of high temporal-resolution emission inventories challenging. In this study, we developed a novel meteorologically adjusted inversion method (MAEInv) based on the EnKF to improve daily emission estimations. The new method combines sensitivity analysis and bias correction to alleviate the inversion biases caused by errors of meteorological inputs. For demonstration, we used the MAEInv to inverse daily carbon monoxide (CO) emissions in the Pearl River Delta (PRD) region, China. In the case study, 60% of the total CO simulation biases were associated with sensitive meteorological inputs, which would lead to the overestimation of daily variations of posterior emissions. Using the new inversion method, daily variations of emissions shrank dramatically, with the percentage change decreased by 30%. Also, the total amount of posterior CO emissions estimated by the MAEInv decreased by 14%, indicating that posterior CO emissions might be overestimated using the conventional EnKF. Model evaluations using independent observations revealed that daily CO emissions estimated by MAEInv better reproduce the magnitude and temporal patterns of ambient CO concentration, with a higher correlation coefficient (R, +37.0%) and lower normalized mean bias (NMB, -17.9%). Since errors of meteorological inputs are major sources of simulation biases for both low-reactive and reactive pollutants, the MAEInv is also applicable to improve the daily emission inversions of reactive pollutants.     

Influence of influent on anaerobic ammonium oxidation in an Expanded Granular Sludge Bed-Biological Aerated Filter integrated system

Shortcut nitrification-denitrification, anaerobic ammonium oxidation (ANAMMOX), and methanogenesis have been successfully coupled in an Expanded Granular Sludge Bed-Biological Aerated Filter (EGSB-BAF) integrated system. As fed different synthetic wastewater with chemical oxygen demand (COD) of 300–1200 mg·L^-1 and NH4+-N of 30–120 mg·L^-1 at the outer recycle ratio of 200%, the influence of influent on ANAMMOX in the integrated system was investigated in this paper. The experimental results showed that higher COD concentration caused an increase in denitrification and methanogenesis but a decrease in ANAMMOX; however, when an influent with the low concentration of COD was used, the opposite changes could be observed. Higher influent NH4+-N concentration favored ANAMMOX when the COD concentration of influent was fixed. Therefore, low COD/NH4+-N ratio would decrease competition for nitrite between ANAMMOX and denitrification, which was favorable for reducing the negative effect of organic COD on ANAMMOX. The good performance of the integrated system indicated that the bacterial community of denitrification, ANAMMOX, and methanogenesis could be dynamically maintained in the sludge of EGSB reactor for a certain range of influent.     

HPF(高通数字滤波器)的电网谐波检测技术的研究与应用

为有效地消除电力谐波污染、确保电网运行安全,必须采用有源电力滤波技术;为改善有源电力滤波器的性能,必须采取先进的谐波检测方法、高效的逆变技术。笔者在研究有源电力滤波技术的基础上,对有源电力滤波的关键技术即谐波检测与分离技术,进行了探讨和深入研究,给出了一种HPF(高通数字滤波器)的谐波检测与分离方法,进行了理论验算,利用MATLAB仿真结果对该检测技术进行实验研究。仿真和实验结果表明:该法比常用的LPF(低通数字滤波器LowPassDigitalFilter)的谐波检测分离方法具有更好的检测实时性;在电网电压有畸变时也能达到很高的检测精度;该检测技术应用于混合有源电力滤波器后能大大改善滤波性能。     

Potential of the Conservation Reserve Program to control agricultural surface water pollution

The Conservation Reserve Program (CRP), initiated by the Conservation Title of the Food Security Act of 1985, is the primary federal program to control nonpointsource pollution in agricultural watersheds of the United States. However, the program is designed primarily to reduce soil erosion rather than to retire croplands in a manner optimal for controlling runoff of sediment and associated pollutants. This study estimates potential enrollment of streamside and floodplain croplands in this ten-year retirement program in order to gauge the potential of the CRP as a water-quality improvement policy. A contingent choice survey design was employed in Fayette County, Illinois, to demonstrate that there is substantial potential for retirement of streamside and floodplain croplands in the CRP. Enrollments in each program climb from less than 6% to over 83% of eligible croplands as the annual rental rate is increased from $20 to $200/acre. Potential retirement of streamside and floodplain croplands declines, however, if tree planting, drainage removal, or a 20-year contract are required. The potential of a CRP-based water-quality program to improve water quality and aquatic ecosystems in agricultural watersheds is thus substantial but constrained by the economic trade-offs that farmers make between crop production and conservation incentives in determining the use of their riparian lands.     

制备标准呼吸性粉尘滤膜样品的实验方法研究

介绍了自制的标准呼吸性粉尘发生装置制备含石英呼吸性粉尘滤膜样品的实验方法。经测试表明：该方法操作简便,制备的呼吸性粉尘样品石英含量均匀,样品质量可控制,粉尘粒度分布和现场样品一致,适用于实验室间或不同方法之间的石英含量比较性研究和质量控制。     

Soil Moisture Data Assimilation Using Support Vector Machines and Ensemble Kalman Filter1

Abstract: A hybrid data assimilation (DA) methodology that combines two state‐of‐the‐art techniques, support vector machines (SVMs) and ensemble Kalman filter (EnKF), is applied for soil moisture DA in this work. The SVM methodology provides a statistically sound and robust approach to solving the inverse problem, and thus to building statistical models. EnKF is an extension of the Kalman Filter (KF), a well‐known tool in prediction updating. In the present research, ground measurements were used to build a SVM‐type soil moisture predictor. Subsequent observations and their statistics were assimilated to update predictions from the SVM model by coupling it with EnKF. In this way, both model predictions and ground data, as well as their statistics, are fused thus minimizing the prediction error and making the predictions and observations statistically consistent. The results are shown for two approaches; one in which update is done at every time step and the other which assumes that data is only available at alternate time steps (in window of 10 time steps) and hence update is performed at those occasions. The SVM‐EnKF coupling is shown to improve soil moisture forecasts in an example using data from the Soil Climate Analysis Network site at Ames, Iowa.