Carbon dioxide methanation on heterogeneous catalysts: a review

Environmental Chemistry Letters - The Ukraine war has strongly accentuated the ongoing energy and environmental issues, thus requiring a fast development of alternative and more local fuels. For...     

Chemical,physical and biological methods to convert lignocellulosic waste into value-added products. A review

Environmental Chemistry Letters - Actual agricultural practices produce about 998 million tonnes of agricultural waste per year. Therefore, converting lignocellulosic wastes into energy, chemicals,...     

Accuracy improvement of various short-term load forecasting models by a novel and unified statistical data-filtering method

ABSTRACT

Time-series and machine-learning methods are being strongly exploited to improve the accuracy of short-term load forecasting (STLF) results. In developing countries, power consumption behaviors could be suddenly changed by different customers, e.g. industrial customers, residential customers, so the load-demand dataset is often unstable. Therefore, reliability assessment of the load-demand dataset is obviously necessary for STLF models. Hence, this paper proposes a novel and unified statistical data-filtering method with the best confidence interval to eliminate unexpected noises/outliers of the input dataset before performing various short-term load forecasting models. This proposed novel data-filtering method, so-called the data pre-processing method, is also compared to other existing data-filtering methods (e.g. Kalman filter, Density-Based Spatial Clustering of Applications with Noise, Wavelet transform, and Singular Spectrum Analysis). By using an SCADA system?-based database of a typical 22kV distribution network in Vietnam, NYISO database, and PJM-RTO database, case studies of short-term load forecasting have been conducted with a conventional ARIMA model, an ANN forecasting model, an LSTM-RNN model, an LSTM-CNN combined model, a deep auto-encoder (DAE) network, a Wavenet-based model, a Wavenet and LSTM hybrid model, and a Wavelet Neural Network (WNN) model, which are to validate the novel and unified statistical data-filtering method proposed. The achieved numerical results demonstrate which the accuracy of the aforementioned STLF models can be significantly improved due to the proposed statistical data-filtering method with the best confidence interval of the input load dataset. The proposed statistical data-filtering method can considerably outperform the existing data-filtering methods.     

Calculating of river water quality sampling frequency by the analytic hierarchy process (AHP)

River water quality sampling frequency is an important aspect of the river water quality monitoring network. A suitable sampling frequency for each station as well as for the whole network will provide a measure of the real water quality status for the water quality managers as well as the decision makers. The analytic hierarchy process (AHP) is an effective method for decision analysis and calculation of weighting factors based on multiple criteria to solve complicated problems. This study introduces a new procedure to design river water quality sampling frequency by applying the AHP. We introduce and combine weighting factors of variables with the relative weights of stations to select the sampling frequency for each station, monthly and yearly. The new procedure was applied for Jingmei and Xindian rivers, Taipei, Taiwan. The results showed that sampling frequency should be increased at high weighted stations while decreased at low weighted stations. In addition, a detailed monitoring plan for each station and each month could be scheduled from the output results. Finally, the study showed that the AHP is a suitable method to design a system for sampling frequency as it could combine multiple weights and multiple levels for stations and variables to calculate a final weight for stations, variables, and months.     

Simulated Impacts of Climate Change on Current Farming Locations of Striped Catfish (Pangasianodon hypophthalmus; Sauvage) in the Mekong Delta,Vietnam

In Vietnam, culturing striped catfish makes an important contribution to the Mekong Delta’s economy. Water level rise during rainy season and salt intrusion during dry season affect the water exchange and quality for this culture. Sea level rise as a consequence of climate change will worsen these influences. In this study, water level rise and salt water intrusion for three sea level rise (SLR) scenarios (i.e., +30, +50, and +75 cm) were simulated. The results showed that at SLR +50, the 3-m-flood level would spread downstream and threaten farms located in AnGiang, DongThap and CanTho provinces. Rising salinity levels for SLR +75 would reduce the window appropriate for the culture in SocTrang and BenTre provinces, and in TienGiang’s coastal districts. Next to increasing dikes to reduce the impacts, the most tenable and least disruptive option to the farming community would be to shift to a salinity tolerant strain of catfish.     

Occurrence, fate and antibiotic resistance of fluoroquinolone antibacterials in hospital wastewaters in Hanoi, Vietnam

Occurrence and behavior of fluoroquinolone antibacterial agents (FQs) were investigated in hospital wastewaters in Hanoi, Vietnam. Hospital wastewater in Hanoi is usually not treated and this untreated wastewater is directly discharged into one of the wastewater channels of the city and eventually reaches the ambient aquatic environment. The concentrations of the FQs, ciprofloxacin (CIP) and norfloxacin (NOR) in six hospital wastewaters ranged from 1.1 to 44 and from 0.9 to 17 micrgl(-1), respectively. Total FQ loads to the city sewage system varied from 0.3 to 14 g d(-1). Additionally, the mass flows of CIP and NOR were investigated in the aqueous compartment in a small wastewater treatment facility of one hospital. The results showed that the FQ removal from the wastewater stream was between 80 and 85%, probably due to sorption on sewage sludge. Simultaneously, the numbers of Escherichia coli (E. coli) were measured and their resistance against CIP and NOR was evaluated by determining the minimum inhibitory concentration. Biological treatment lead to a 100-fold reduction in the number of E. coli but still more than a thousand E. coli colonies per 100ml of wastewater effluent reached the receiving water. The highest resistance was found in E. coli strains of raw wastewater and the lowest in isolates of treated wastewater effluent. Thus, wastewater treatment is an efficient barrier to decrease the residual FQ levels and the number of resistant bacteria entering ambient waters. Due to the lack of municipal wastewater treatment plants, the onsite treatment of hospital wastewater before discharging into municipal sewers should be considered as a viable option and consequently implemented.     

Removal of estrogens by electrochemical oxidation process

Treatments of estrogens such as Estrone(E1), Estradiol(E2) and Ethinylestradiol(EE2) were conducted using an electrolytic reactor equipped with multi-packed granular glassy carbon electrodes.Experimental results showed that E1, E2 and EE2 were oxidized in the range of 0.45–0.85 V and were removed through electro-polymerization. Observed data from continuous experiments were in good agreement with calculated results by a mathematical model constructed based on mass transfer limitation. In continuous treatment of trace estrogens(1 μg/L), 98% of E1, E2 and EE2 were stably removed. At high loading rate(100 μg/L), removal efficiency of E1 was kept around 74%–88% for21 days, but removal efficiency reduced due to passivation of electrodes. However, removal efficiency was recovered after electrochemical regeneration of electrodes in presence of ozone. Electric energy consumption was observed in the range of 1–2 Wh/m3. From these results, we concluded that the present electrochemical process would be an alternative removal of estrogens.     

Determination of alkylamine permeation through protective gloves using aliphatic amine pads

A quantitative study of alkylamine permeation through a glove material using Permea-Tec aliphatic amine pads, used for the detection of chemical breakthrough of protective clothing, was performed for triethylamine following a microwave-extraction process and gas chromatographic analysis. Triethylamine exhibited > 99% adsorption on the pads at a spiking level of 729 ng (1.0 ml). Triethylamine showed recoveries from 63 to 90% (RSD < or = 5%) over the range 0.2-1.0 ml (146-729 ng) applied to pads. The ASTM F739 standard and direct permeability testing procedures were used to determine breakthrough times for five protective glove materials using triethylamine as a challenge chemical. Breakthrough times for six protective gloves were determined ranging from 40 s to > 4 h. The quantitative concentration of triethylamine on the pads following permeation through the gloves was also determined, ranging from 101 to 103 ng cm-2 (382-386 ng per pad).     

Plankton filtration with compressible crumb rubber packs

The experiments described provide insight into the feasibility of using compressible particulate packs to filter live plankton. The pore constriction sizes are controlled by subjecting the filter pack to isotropic confinement, thereby allowing for: (1) enhanced filtration upon confinement and (2) enhanced unclogging upon relaxation. Results show that filtration efficiency increases with increasing confinement; however, complete plankton retention is difficult to attain due to the plankton’s ability to pass through pore constrictions that are smaller than the plankton size. The results are anticipated to offer potential benefits to ballast treatment and aquatic filtration operations.     

微电网电压分层控制与补偿机制研究

微电网技术具有许多优点,然而微电网中的分布式电源自身的不稳定性会导致微电网的运行控制困难,特别是公共连接点处会出现电压不平衡。为了补偿此不平衡电压,提出了分层控制方法。该方法将电网运行控制分为.上下2层,由.上层控制发送控制信号,并由下层控制来实施,此控制信号与正序电压分量和负序电压分量有关;在dq旋转坐标下,依靠同步坐标系锁相环( SRF-PLL)和解耦的双同步坐标系锁相环(DDSRF-PLL)等并网同步技术将微电网同步地接入电网,并通过控制逆变器得到电压幅值。仿真结果表明:分层控制方法能够较好地实现对微电网的控制。