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- W2034162196 abstract "Abstract In the process industries, hazardous materials can be released accidentally as vapor, gas or liquid and are dispersed in the atmosphere. Ammonia is one of the most extensively used industrial chemicals. It is highly soluble in water and has toxic and corrosive effects caused by its alkalinity. The evaporation of ammonia may cause extreme cooling when spilled on the skin or eyes; cold burns may result. When inhaled, ammonia dissolves in upper airways and small amounts also in the lower respiratory tract; damage to upper airways is therefore more severe. In this paper, simple predictive tool, which is easier than existing approaches, less complicated with fewer computations and suitable for environmental experts, is presented here for the estimation of aqueous ammonia vapor pressure as a function of ammonia molar fraction in aqueous phase and temperature. The proposed predictive tool works for temperatures in the range of 273 to 373 K. The proposed method is superior owing to its accuracy and clear numerical background, wherein the relevant coefficients can be retuned quickly if more data are available in the future. Estimations are found to be in excellent agreement with the reliable data in the literature with average absolute deviation being around 1.74%. The tool developed in this study can be of immense practical value for the engineers and scientists to have a quick check on the vapor pressure of aqueous ammonia solution at various conditions without opting for any experimental measurements. In particular, chemical engineers and environmental scientists would find the approach to be user-friendly with transparent calculations involving no complex expressions." @default.
- W2034162196 created "2016-06-24" @default.
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- W2034162196 date "2012-08-06" @default.
- W2034162196 modified "2023-09-23" @default.
- W2034162196 title "A Simple Regression-Based Approach for Prediction of Aqueous Ammonia Vapor Pressure" @default.
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- W2034162196 doi "https://doi.org/10.2118/163021-ms" @default.
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