Evaluation of energy savings by using high efficiency motors in a thermal power station

This paper presents potential energy savings by installing high-efficiency motors instead of existing ones and their impact on greenhouse gases emissions reductions. This research study of the energy efficiency of electric motors has been performed in a typical thermal power plant. In the literature, the focus has been mainly on separate and away electric motors from operating facilities. The important advantage of this paper over other studies is that it uses the actual motors’ efficiency in the evaluation. The gains both in terms of electrical energy savings and in terms of financial economy by using high-efficiency motors have been discussed. As a result, the energy saving can be expected as 12.6% at the operating rate. This excellent result also reduces greenhouse gas emission by 1,423 tons every year. The analysis of the data provided an overview on energy losses often generated by the degradation and rewinding of electrical motors. This study represents very encouraging results that will help energy managers of industrial plants to become more involved in energy efficiency strategies.     

An experimental and a numerical study of horizontal earth-air heat exchanger in a hot climate

Earth-air heat exchangers (EAHE) are devices used in the geothermal technique in order to reduce energy consumption in buildings. In this study, a simulation was conducted through the computational fluid dynamics platform FLUENT 6.3 for the prediction of thermal performance of the EAHE that describes the variation of the air temperature inside the tube. For this, it was necessary to design the heat exchanger while respecting the design and the actual dimensions of the experimental set-up, and stating that the temperature of the wall of the horizontal tube of the exchanger is equal to that of ground at 3 m depth. It should be noted that in assessing the temperature along the two sections vertical (input and output) of the exchanger, opting for a function (UDF) the user define function. Finally, noting a good agreement between both experimental and numerical study, and showing that a significant reduction in temperature at the outlet of the exchanger to a difference of 20 °C, confirming the effectiveness of the heat exchanger.     

Privacy-preserving aggregation in life cycle assessment

Life cycle assessment (LCA) is the standard technique used to make a quantitative evaluation about the ecological sustainability of a product or service. The life cycle inventory (LCI) data sets that provide input to LCA computations can express essential information about the operation of a process or production step. As a consequence, LCI data are often regarded as confidential and are typically concealed through aggregation with other data sets. Despite the importance of privacy protection in publishing LCA studies, the community lacks a formal framework for managing private data, and no techniques exist for performing aggregation of LCI data sets that preserve the privacy of input data. However, emerging computational techniques known as “secure multiparty computation” enable data contributors to jointly compute numerical results without enabling any party to determine another party’s private data. In the proposed approach, parties who agree on a shared computation model, but do not trust one another and also do not trust a common third party, can collaboratively compute a weighted average of an LCA metric without sharing their private data with any other party. First, we formulate the LCA aggregation problem as an inner product over a foreground inventory model. Then, we show how LCA aggregations can be computed as the ratio of two secure sums. The protocol is useful when preparing LCA studies involving mutually competitive firms.     

Water quality soft-sensor prediction in anaerobic process using deep neural network optimized by Tree-structured Parzen Estimator

● Hybrid deep-learning model is proposed for water quality prediction. ● Tree-structured Parzen Estimator is employed to optimize the neural network. ● Developed model performs well in accuracy and uncertainty. ● Usage of the proposed model can reduce carbon emission and energy consumption. Anaerobic process is regarded as a green and sustainable process due to low carbon emission and minimal energy consumption in wastewater treatment plants (WWTPs). However, some water quality metrics are not measurable in real time, thus influencing the judgment of the operators and may increase energy consumption and carbon emission. One of the solutions is using a soft-sensor prediction technique. This article introduces a water quality soft-sensor prediction method based on Bidirectional Gated Recurrent Unit (BiGRU) combined with Gaussian Progress Regression (GPR) optimized by Tree-structured Parzen Estimator (TPE). TPE automatically optimizes the hyperparameters of BiGRU, and BiGRU is trained to obtain the point prediction with GPR for the interval prediction. Then, a case study applying this prediction method for an actual anaerobic process (2500 m³/d) is carried out. Results show that TPE effectively optimizes the hyperparameters of BiGRU. For point prediction of COD_eff and biogas yield, R² values of BiGRU, which are 0.973 and 0.939, respectively, are increased by 1.03%–7.61% and 1.28%–10.33%, compared with those of other models, and the valid prediction interval can be obtained. Besides, the proposed model is assessed as a reliable model for anaerobic process through the probability prediction and reliable evaluation. It is expected to provide high accuracy and reliable water quality prediction to offer basis for operators in WWTPs to control the reactor and minimize carbon emission and energy consumption.     

Organochlorine contamination in some marketable fish in Egypt

Ten organochlorine compounds were analyzed in four species of fish (Bouri Mugil spp., Denis Sparus auratus, Moza Boops boops and Mousa Pegusa lascaris), from four Egyptian governorates (South Sinai, Suez, Port-Said and Demietta). Although all fish studied are bottom or near-bottom feeders, remarkable variations between studied species were noticed. The grand total values recorded at the studied governorates were in descending order: Bouri>Denis>Moza>Mousa. The highest concentration of pesticides was recorded in Demietta governorate fish (20-211 ng/g of wet weight) and the p,p'-DDE dominated over the other p,p'-isomers in all studied fish, while dieldrin was the dominated in the studied cyclodiene compounds. However, hexachlorobenzene (HCB) occurred at all studied governorate fish except Mousa fish from South Sinai. Toxaphene was detected only in fish (Bouri, Denis, and Mousa) from Demietta governorate. Chlordane was not detected in any studied fish. The level of organochlorine pesticides contamination in fish from the studied governorates is relatively low and should not pose a health risk to consumers.     

Electrochemical analysis of endosulfan using a C18-modified carbon-paste electrode

Successful applications of different analytical procedures to determine quantitatively endosulfan and its metabolites in aqueous media can be found in recent literature. Fundamentally, they have made use of solid-phase extraction (SPE) and gas (GC) or liquid chromatography (LC), sometimes coupled to mass spectrometry (MS). In this paper, a new and alternative methodology to determine quantitatively endosulfan in aqueous media is reported. A C18-modified carbon-paste electrode has been used to determine voltammetrically endosulfan, despite its unfavourable electrochemical properties and behaviour. The methodology proposed is based on the decrease experienced by the peak intensity corresponding to voltammetric signals of Cu(II) when successive and constant additions of endosulfan are carried out. This decrease is directly proportional to the concentration of endosulfan what allows to perform an indirect quantification of the pesticide. The detection limit obtained is 40 ng l⁻¹, this value being under the limits specified by European norms and EPA reports.     

Natural radioactivity measurements in building materials in Southern Lebanon

Using gamma-spectroscopy and CR-39 detector, concentration C of naturally occurring radioactive nuclides (226)Ra, (222)Rn, (214)Bi, (228)Ac, (212)Pb, (212)Bi and (40)K, has been measured in sand, cement, gravel, gypsum, and paint, which are used as building materials in Lebanon. Sand samples were collected from 10 different sandbank locations in the southern part of the country. Gravel samples of different types and forms were collected from several quarries. White and gray cement fabricated by Shaka Co. were obtained. gamma-spectroscopy measurements in sand gave Ra concentration ranging from 4.2+/-0.4 to 60.8+/-2.2 Bq kg(-1) and Ra concentration equivalents from 8.8+/-1.0 to 74.3+/-9.2 Bq kg(-1). The highest Ra concentration was in gray and white cement having the values 73.2+/-3.0 and 76.3+/-3.0 Bq kg(-1), respectively. Gravel results showed Ra concentration between 20.2+/-1.0 and 31.7+/-1.4 Bq kg(-1) with an average of 27.5+/-1.3 Bq kg(-1). Radon concentration in paint was determined by CR-39 detector. In sand, the average (222)Rn concentration ranged between 291+/-69 and 1774+/-339 Bq m(-3) among the sandbanks with a total average value of 704+/-139 Bq m(-3). For gravel, the range was found to be from 52+/-9 to 3077+/-370 Bq m(-3) with an average value of 608+/-85 Bq m(-3). Aerial and mass exhalation rates of (222)Rn were also calculated and found to be between 44+/-7 and 2226+/-267 mBq m(-2)h(-1), and between 0.40+/-0.07 and 20.0+/-0.3 mBq kg(-1)h(-1), respectively.     

Degradation of the herbicide imazapyr by Fenton reactions

The degradation of the herbicide imazapyr has been carried out by three advanced oxidation processes involving iron ions as catalysts: Fentons reagent, photo-Fenton and electro-Fenton. We show that all processes are rapid and efficient. The kinetic rate constant was found to be k=5.4×10⁹ M^–1 s^–1. The mineralization of imazapyr is almost complete using the photo-Fenton and electro-Fenton processes.