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Articles by Sabah A. Abdul-Wahab
Total Records ( 2 ) for Sabah A. Abdul-Wahab
  Sabah A. Abdul-Wahab
  This study was conducted with the objective of evaluating the present status of environmental awareness of Omani citizens and their willingness to contribute to environmental protection. The focus of the study was to investigate the Omani public’s level of knowledge about general basic and current local and international environmental issues and to find out their environmental attitudes and behaviors towards their environment. This information was gathered through a survey questionnaire with its structure constructed for this purpose. The survey questionnaire consisted of various current topics regarding the environment. It was primarily designed to assess the level of residents’ environmental awareness from three aspects: environmental knowledge, environmental attitudes, and environmental behaviors. This questionnaire was administered to 425 respondents who were evenly distributed among all areas of the entire Muscat governorate in Oman during January 2007. The results of the survey showed that the basic environmental knowledge of the public was generally lacking, whereas their local and international environmental knowledge were found to be higher. In contrast, the study found that the public had a higher level of environmental attitudes and behaviors, but also noted that the public achieved a higher score in their environmental attitudes than in their environmental behaviors. The results of the survey and recommendations of the study are hoped to be used in the evaluation of the effectiveness of the current public awareness strategies and programmes and in the design future programmes by government authorities and civil service groups.
  Sabah A. Abdul-Wahab and aleh M. Al-Alawi
  In this investigation, two Artificial Neural Network (ANN) models were applied for predicting ground-level sulfur dioxide (SO2) in the Sultanate of Oman in order to provide an early warning advisory for the protection of public health. The objective of the first model (Model I) was to use ANN to predict sulfur dioxide (SO2) levels at certain receptors from the Mina Al-Fahal refinery in Oman. The artificial neural network was also used for predicting the first 3 maximum SO2 concentrations and their corresponding locations with respect to the refinery (Model II). The models were used to determine meteorological conditions that most affect SO2 concentrations. In assessing this aspect, five meteorological parameters that are expected to affect the SO2 concentrations were explored. They include wind speed, atmospheric stability class, wind direction, mixing height, and ambient temperature. The developed models showed good predictive success with, R-squared values above 0.96 indicating high accuracy for both the models development and generalization capability. The meteorological variables with the greatest influence on SO2 concentrations were also identified. It was found that wind direction was the variable most important to Model I while wind direction, stability, and wind speed were the highest contributing variables in Model II. The investigation indicated that the ANN models were well-suited for modelling SO2 levels. Additionally, the ANN models can be extended for other applications in which non-linear relationships are observed.
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