This work was conducted to assess the impacts on workplace and ambient air quality due to release of sulfur dioxide (SO(2)) into the atmosphere at Al-Noor production station, located in southern desert of Sultanate of Oman. The SO(2) is released because of oxidation of H(2)S to SO(2) on flaring of H(2)S rich off gas at the Al-Noor. In the first phase of the study, CALPUFF modeling system was used to predict the ground level concentrations of SO(2) emissions from the flare stacks. The evaluation of the modeling system was carried out by comparing the predicted results with that of the measured. In the second stage of the study, the estimated results were compared with the air quality standards/guidelines set by Omani regulatory authorities as well as by World Health Organization (WHO). It was concluded on the basis of current study that the sensitive individuals in the workplace of the Al-Noor could experience adverse health effects due to short-term exposure of SO(2).
ABSTRACT:The objective of this study was to compare the effect of a selected convective parameterized scheme in a mesoscale model on the predicted precipitation using the fifth-generation Mesoscale Model (MM5). Four cumulus parameterization schemes in MM5, the Grell scheme, the Kain-Fritsch scheme, the Anthes-Kuo scheme and the Betts-Miller scheme were tested to predict the monthly accumulated precipitation in a south Asian region of complex topography during the summer monsoon season (July and August) for the years 1998 and 2001. The simulated results of precipitation were compared with the satellite-derived data of the Tropical Rainfall Measuring Mission (TRMM).Comparison of simulated precipitation patterns revealed that the Grell scheme realistically captured the rainfall patterns over the southern plain areas of the region which receive lesser precipitation throughout the year. This scheme was also in good agreement with the TRMM data for lesser amounts of precipitation over northern mountainous areas, though it showed underestimated results for heavy precipitation over the region. The rainfall patterns over the northern mountainous areas were captured well by the Kain-Fritsch scheme for heavy precipitation while this scheme slightly over predicted the precipitation trends in the southern plain areas. The Anthes-Kuo and the Betts-Miller schemes were not able to simulate the rainfall for this complex terrain satisfactorily. The set of physical options used in MM5 for precipitation in this study was also tested for some other meteorological parameters such as ambient temperature, potential temperature, relative humidity and the moist static energy and the results were validated against the Reanalysis data of US National Centre for Environmental Prediction (NCEP). It was found that the scheme that successfully simulated precipitation also predicted these other parameters well.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.