1,560 research outputs found

    Urban air quality estimation study, phase 1

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    Possibilities are explored for applying estimation theory to the analysis, interpretation, and use of air quality measurements in conjunction with simulation models to provide a cost effective method of obtaining reliable air quality estimates for wide urban areas. The physical phenomenology of real atmospheric plumes from elevated localized sources is discussed. A fluctuating plume dispersion model is derived. Individual plume parameter formulations are developed along with associated a priori information. Individual measurement models are developed

    The simulation of dangerous gas diffusion in port area

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    Development of a livestock odor dispersion model

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    Livestock odour has been an obstacle for the development of livestock industry. Air dispersion models have been applied to predict odour concentrations downwind from the livestock operations. However, most of the air dispersion models were designed for industry pollutants and can only predict hourly average concentrations of pollutants. Currently, a livestock odour dispersion model that can consider the difference between livestock odour and traditional air pollutants and can account for the short time fluctuations is not available. Therefore, the objective of this research was to develop a dispersion model that is designed specifically for livestock odour and is able to consider the short time odour concentration fluctuations. A livestock odour dispersion model (LODM) was developed based on Gaussian fluctuating plume theory to account for odour instantaneous fluctuations. The model has the capability to predict mean odour concentration, instantaneous odour concentration, peak odour concentration and the frequency of odour concentration that is equal to or above a certain level with the input of hourly routine meteorological data. LODM predicts odour frequency by a weighted odour exceeding half width method. A simple and effective method is created to estimate the odour frequency from multiple sources. Both Pasquill-Gifford and Hogstr¨¯m dispersion coefficients are applied in this model. The atmospheric condition is characterized by some derived parameters including friction velocity, sensible heat flux, M-O length, and mixing height. An advanced method adapted from AERMOD model is applied to derive these parameters. An easy to use procedure is generated and utilized to deal with the typical meteorological data input as ISC met file. LODM accepts and only requires routine meteorological data. It has the ability to process individual or multiple sources which could be elevated point sources, ground level sources, livestock buildings, manure storages, and manure land applications. It can also deal with constant and varied emission rates. Moreover, the model considers the relationships between odour intensity and odour concentrations in the model. Finally, the model is very easy to use with a friendly interface. Model evaluations and validations against field plume measurement data and ISCST3 and CALPUFF models indicate that LODM can achieve fairly good odour concentration and odour frequency predictions. The sensitivity analyses demonstrate a medium sensitivity of LODM to the controllable odour source parameters, such as stack height, diameter, exit velocity, exit temperature, and emission rate. This shows that the model has a great potential for application on resolving odour issues from livestock operations. From that perspective, the most effective way to reduce odour problems from livestock buildings is to lessen the odour emission rate (e.g. biofiltration of exhaust air, diet changes)

    Location Optimization of a Coal Power Plant to Balance Coal Supply and Electric Transmission Costs Against Plant’s Emission Exposure

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    This research is focused on developing a location analysis methodology that can minimize the pollutant exposure to the public while ensuring that the combined costs of electric transmission losses and coal logistics are minimized. Coal power plants will provide a critical contribution towards meeting electricity demands for various nations in the foreseeable future. The site selection for a new coal power plant is extremely important from an investment point of view. The operational costs for running a coal power plant can be minimized by a combined emphasis on placing a coal power plant near coal mines as well as customers. However, this business strategy has produced a detrimental effect on the environment in various nations around the globe. In this new era of rapid urbanization, increased electric utility demand and environmental consciousness; the location analysis for a new coal power plant needs to include both the investment and environmental considerations. To provide a general background of the issue, a detailed literature review was conducted on the topics of Environmental Protection Agency (EPA) pollutant dispersion models, health effects due to exposure to pollutants, coal logistics, electric transmission technical losses, and location analysis models. Next, a methodology, based on dynamic programming, was formulated by combing the EPA’s pollutant dispersion models with the minimum spanning tree algorithm to calculate the combined costs of coal logistics and electric transmission losses for a given set of coal mines and customers present on a network. The subsequent simulation was developed based on the proposed methodology. The simulation successful ly proved that the selection of a site on a grid map provided the minimum of the combined cost of electric line losses and coal transportation, and no customers were exposed to pollutant concentration above the declared threshold for that pollutant. The resultant emission’s data were validated via comparing against the EPA Screen3 and Japanese Ministry of Economy, Trade, and Industry (METI-LIS) models. The minimum spanning tree for electric transmission lines and coal transportation were validated using R-software

    Using Geographical Information System (GIS) to Study The Impact of Chemical Pollutants Emerging From Industries

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    The purpose of this project is to analyze the impact of air pollution concentration unto the surrounding area of the industrial site. The analysis will be focused on the subject of air pollution modelling, simulation and computational methods using Geographical Information System (GIS) software. By using GIS, analysis of the impact in the scale of a digital map could be done in a much precise manner. Using the raw data input of the industrial site that being processed into air pollution modelling software called Point Source Dispersion (PSD), the output from PSD analysis could be used further as input for analysis in GIS. The results of GIS analysis will be appeared in multiple ring buffers that being characterized by the concentration of air pollution in proportional to the affected areas around the industrial site. By having these results, a risk and safety assessment of the industrial site could be done efficiently and in cost-saving manner

    Study of Impact of Dispersion of Gases From Stack on Environment Through CFD Simulation

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    The main objective is to analyse the dispersion of gases emitted under different conditions of mass flow rate at the exit and ambient crossflow velocity by using software ANSYS. Main focus id to find out whether designed boiler stack can disperse atmospheric pollutants away from city or surroundings where the boiler is installed. Dispersion modelling includes means of calculating ambient ground level concentrations of emitted substances, considering the information like meteor ological data, pollutants flow rates and terrain data of area. This modelling is done to assess that the Ground level concentrations (GLC) of atmospheric pollutants owing to emissions from boiler stack are less than applicable ambient air quality standard

    Emission inventories from Kuwait petroleum refineries and respective ground level concentration of pollutants in the neighboring residential area

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    The State of Kuwait has three large refineries, namely, Mina Al Ahmadi Refinery, Mina Abdullah Refinery and Shuaiba Refinery. These refineries process and refine Kuwait Crude Oil through different process units. There are many heaters, boilers and flares that form a part of the complicated equipment which enhance the different petroleum processes. Fuel gas is used as a firing fuel for those heaters and boilers. As a result, stack emissions like SO2, NOx, CO are predominantly present in the flue gases and this study focuses on those emissions and their impact on the surrounding residential area. The area of interest will be Umm Al-Hyman residential area. This study accumulates emission inventories from the three refineries and the respective ground level concentration of the pollutants in the neighboring residential area. It also focuses on the impact of emissions from the refinery operations on the ground level concentrations in the surrounding areas by using the inventory model and latest emission factors to provide accurate emission estimates. The models were developed and the results were verified with the actual data from the area of impact. As a result of the findings of the major pollutants, namely SO2, NOx & CO, it is found that SO2 and CO are not exceeding Kuwait EPA Ambient Air Quality Standards for Residential Areas normally. However, NOx is observed to exceed occasionally. Even though, NOx emissions from refineries sources represented by plume models were much less, there is a consistent increase in the measured NOx. Furthermore, in 2007, the measured hourly, daily and annual NOx concentration exceeded the international standard many times. The increasing trend in NOx is attributed to continuous increase in population and the number of motor vehicles. The study will go further step in recommending engineering solutions and best practices to reduce the pollutants concentrations which will help in the reduction of human health risks and protect the environment
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