scholarly journals Biological Potentiality to Remove Organic Solvents From Exhausted Air Emissions

2021 ◽  
Vol 8 ◽  
pp. 70-75
Author(s):  
Giovanni Cortella ◽  
Marcello Civilini
Keyword(s):  
Organic Solvents ◽  
Biological System ◽  
Weather Conditions ◽  
Air Emissions ◽  
Exhaust Gas ◽  
Sustainable Technology ◽  
Air Emission ◽  
Low Costs ◽  
Removal Efficiencies ◽  
Industrial Prototype

The performance of an industrial prototype of a biological system was investigated during more than two years, for the treatment of exhaust gas from air emission of wooden painting activities. Two different type of VOCs mixture were treated at different weather conditions. Removal efficiencies were sufficiently high to maintain the outlet emissions within the legal thresholds. Particularly low costs for management were experienced, confirming the biofiltration a sustainable technology.

Waste Discharge Reduction Program Overview – Monsanto Agricultural Company

1991 ◽  
Vol 24 (12) ◽  
pp. 29-32
Author(s):  
C. W. Keffer
Keyword(s):  
Emission Reduction ◽  
Hazardous Materials ◽  
Inorganic Materials ◽  
Air Emissions ◽  
Environmental Media ◽  
Waste Discharge ◽  
Air Emission ◽  
Reduction Program

Monsanto is committed to being a leader in reducing waste discharges to the environment. The Company announced in June 1988 a commitment to reduce air emissions of hazardous materials by 90% by the end of 1992. In addition, Monsanto Agricultural Company established a further goal to reduce the discharge of organic and hazardous inorganic materials to all environmental media. Projects have been identified for the Agricultural Company to achieve the 90% air emission reduction goal and to reduce projected 1995 waste discharges from 150 million pounds to 50 million pounds.

scholarly journals Air Emissions of Selected Substances from Particular Sectors Including Metallurgy in Poland

2017 ◽  
Vol 17 (1) ◽  
pp. 83-86 ◽  
Author(s):  
I. Kargulewicz
Keyword(s):  
Emission Inventory ◽  
Manufacturing Industries ◽  
Air Emissions ◽  
Metal Production ◽  
Transboundary Air Pollution ◽  
Lead And Cadmium ◽  
Air Emission ◽  
Dioxins And Furans ◽  
Total Suspended Particles ◽  
Climate Convention

Abstract This article presents data on the anthropogenic air emissions of selected substances (CO2, SO2, total suspended particles (TSP), dioxins and furans (PCDD/F), Pb and Cd) subject to reporting under the Climate Convention (UNFCCC) or the Convention on Long-range Transboundary Air Pollution (UNECE CLRTAP). It also presents the national emissions of these substances in 2014 by the major source categories and defines the share of metal production in these emissions. Analysis is based on national emission inventory reports. Most important source of air emission in case of CO2 and SO2 is 1.A.1 Energy industries category. TSP and PCDD/F are emitted mainly from fuel combustion in small sources (i.a. households). Emission of heavy metals (Pb and Cd) is connected mostly with 1.A.2. Manufacturing industries and construction category. Metallurgy is significant source of emission only for lead and cadmium from among all considered substances. The shares of particular sectors in the national emissions of given pollutants are important, in view of the possible reduction measures and the determination in which industries they could bring about tangible results.

scholarly journals PENGARUH PENERAPAN METODE CUL-DE-SAC (NOSE PINCHING) TERHADAP KLIEN DISGLOSIA.

2021 ◽  
Vol 3 (2) ◽  
pp. 60-69
Author(s):  
Riani Shopianty
Keyword(s):  
Oral Cavity ◽  
Emission Reduction ◽  
Research Method ◽  
Speech Therapy ◽  
Air Emissions ◽  
Single Subject ◽  
Experiment Data ◽  
Congenital Deformities ◽  
Air Emission ◽  
Subject Experiment

A speech disorder that occurs due to deformities of speech organs, especially articulators, is called dysglosia. The congenital deformities of speech organs of people around us result in various difficulties in communicating due to inaccuracies or inconsistencies in articulating words. One of the methods in the field of speech therapy being able to to overcome the problems including the abnormalities in sound resonance is Cul-de-sac (Nose Pinching) method. This study aimed to determine the effect of the application of the Cul-de-sac (Nose Pinching) method in increasing the awareness of Dysglosia clients about the differences in sound resonance in the nasal cavity and oral cavity when producing consonants and reducing nasal air emissions when producing consonant sibilant apicoalveolar / s. / at the Cleft Center Bandung. The research method used is single subject experiment. Data were collected through interviews with the client's parents, direct observation of the client, tests, and a document study of the client's medical record. After 15 sessions of therapy using the method, the client's ability had improved for about 65% and he was successfully able to pronounce the consonant of / s / in the presence of a nasal air emission between 1-2 cm. Therefore, based on the results it can be concluded that the Cul-de-sac (Nose Pinching) method has influenced as much as 65% of nasal air emission reduction.

Reducing Power Load Fluctuations on Ships Using Power Redistribution Control

2008 ◽  
Vol 45 (03) ◽  
pp. 162-174
Author(s):  
Damir Radan ◽  
Asgeir J. Sørensen ◽  
Alf Kåre Ådnanes ◽  
Tor A. Johansen
Keyword(s):  
Power Systems ◽  
Reducing Power ◽  
Weather Conditions ◽  
Exhaust Gas ◽  
Simulation Studies ◽  
Network Stability ◽  
Power Load ◽  
Wide Range ◽  
Simulation Results ◽  
Exhaust Gas Emissions

A new controller to reduce the load fluctuations generated by consumers operating in marine power systems is proposed. The controller redistributes the power from consumers that generate load fluctuations to thrusters that compensate for fluctuations. This provides a cancellation of load disturbances sensed by generators. The effectiveness of the proposed controller is demonstrated through simulation studies on a supply vessel power plant, using the SIMULINK/MATLAB software package. The simulation results show that the controller contributes significantly toward improving the network stability and the dynamic behavior of the system under a wide range of operating and weather conditions. This results in increased operational safety of the vessel, extended equipment life, and reduced fuel consumption, exhaust gas emissions, and maintenance costs on the engines.

Large Two-Stroke Marine Diesel Engine Operation with a High-Pressure SCR System in Heavy Weather Conditions

2020 ◽  
pp. 1-15 ◽  
Author(s):  
Michael I. Foteinos ◽  
George I. Christofilis ◽  
Nikolaos P. Kyrtatos
Keyword(s):  
High Pressure ◽  
Weather Conditions ◽  
Irregular Waves ◽  
Ship Motions ◽  
Exhaust Gas ◽  
Time Varying ◽  
Gas Temperature ◽  
Marine Diesel ◽  
Exhaust Gas Temperature ◽  
Scr System

The transient performance of a direct-drive large two-stroke marine diesel engine, installed in a vessel operating in a seaway with heavy weather, is investigated via simulation. The main engine of the ship is equipped with a selective catalytic reduction (SCR) after treatment system for compliance with the latest International Maritime Organization (IMO) rules for NOx reduction, IMO Tier III. Because of limitations of exhaust gas temperature at the inlet of SCR systems and the low temperature exhaust gases produced by marine diesel engines, in marine applications, the SCR system is installed on the high-pressure side of the turbine. When a ship sails in heavy weather, it experiences a resistance increase, wave-induced motions, and a time-varying flow field in the propeller, induced by ship motions. This results in a fluctuation of the propeller torque demand and, thus, a fluctuation in engine power and exhaust gas temperature, which can affect engine and SCR performance. To investigate this phenomenon and take into account the engine–propeller interaction, the entire propulsion plant was modeled, namely, the slow-speed diesel propulsion engine, the high-pressure SCR system, the directly driven propeller, and the ship's hull. To simulate the transient propeller torque demand, a propeller model was used, and torque variations due to ship motions were taken into account. Ship motions in waves and wave-added resistance were calculated for regular and irregular waves using a 3D panel code. The coupled model was validated against available measured data from a shipboard propulsion system in good weather conditions. The model was then used to simulate the behavior of a Tier III marine propulsion plant during acceleration from low to medium load, in the presence of regular and irregular waves. The effect of the time-varying propeller demand on the engine and the SCR system was investigated. 1. Introduction The effect of waves on a marine propulsion system is a complex phenomenon involving interactions between different subsystems of the propulsion plant, i.e., the prime mover, the propeller, and the ship's hull. Ships sailing in heavy weather conditions experience a resistance increase, wave-induced motions, and a time-varying flow field in the propeller. This leads to a fluctuation of the propeller torque demand which results in a fluctuation in engine-produced power and exhaust gas temperature.

Identification of the odour and chemical composition of alumina refinery air emissions

2004 ◽  
Vol 50 (4) ◽  
pp. 39-47 ◽  
Author(s):  
P.S. Coffey ◽  
M. Ioppolo-Armanios
Keyword(s):  
Refining Process ◽  
Air Emissions ◽  
Chemical Components ◽  
Emission Sources ◽  
Hedonic Tone ◽  
Emissions Inventory ◽  
Preliminary Identification ◽  
Air Emission ◽  
Alumina Industry ◽  
Western Australian

Alcoa World Alumina Australia has undertaken comprehensive air emissions monitoring aimed at characterising and quantifying the complete range of emissions to the atmosphere from Bayer refining of alumina at its Western Australian refineries. To the best of our knowledge, this project represents the most complete air emissions inventory of a Bayer refinery conducted in the worldwide alumina industry. It adds considerably to knowledge of air emission factors available for use in emissions estimation required under national pollutant release and transfer registers (NPRTs), such as the Toxic Releases Inventory, USA, and the National Pollutant Inventory, Australia. It also allows the preliminary identification of the key chemical components responsible for characteristic alumina refinery odours and the contribution of these components to the quality, or hedonic tone, of the odours. The strength and acceptability of refinery odours to employees and neighbours appears to be dependent upon where and in what proportion the odorous gases have been emitted from the refineries. This paper presents the results of the programme and develops a basis for classifying the odour properties of the key emission sources in the alumina-refining process.

scholarly journals Artificial Neural Network for Environmental Air Emissions Prediction Systems

2019 ◽  
Vol 70 (9) ◽  
pp. 3338-3342
Author(s):  
Danuta Matei ◽  
Bogdan Doicin ◽  
Diana Cursaru ◽  
Dorin Stanica Ezeanu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Weather Conditions ◽  
Air Emissions ◽  
Ann Model ◽  
Spatial Correlations ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Environmental Air ◽  
Air Quality Monitoring Stations

Artificial neural network ANN is an appropriate tool for predestining the different relationships across many scientific researches. Air emissions prediction is an effective method of securing public health by revealing the imminent danger of air pollutants. So far, the existing methods of air emissions concentration prediction became useless on long-term dependencies, and most neglect spatial correlations. In this study, an artificial neural network model, which also takes into account the spatial-temporal variable, is proposed for prediction of air emission. The ANN was used in order to take into account the historical data, auxiliary data such as environmental quality and weather conditions. Evaluation of the results revealed that the developed ANN model appears to be an appropriate tool in predicting environmental air emissions. The data were collected from 12 air quality-monitoring stations from a random county in Romania. The proposed model performed well and presented a relative error varies from 0 to 4.7%.

Sign in / Sign up

Export Citation Format

Share Document