Source characterization of atmospheric heavy metals in industrial/residential areas: a case study in Oman

Total suspended particulate matter (TSP) was collected from two districts: the Sohar industrial estate (SIE) and a residential area in the case study area in Oman. The TSP collected from SIE was taken from 19 different industrial activities, whereas those collected from the residential area were taken from 12 houses. The samples were analyzed for nine heavy metals: chromium (Cr), copper (Cu), manganese (Mn), nickel, lead (Pb), zinc (Zn), cadmium, vanadium, and molybdenum. The results were used to assess the source classes responsible for TSP and heavy metal levels in the atmosphere of the two districts. At each district, principal component analysis was applied to the concentrations of TSP and heavy metals to obtain the number of principal components. At SIE, three groups of elements were determined. The first component contained large factor loadings in Cu and Mn (Cu industrial processes and reinforcement steel production). The second presented most of the variance of Cr, Pb, and Zn (black and galvanized iron pipes production, mechanical industries, and vehicle construction). The third component was composed of Zn and Pb that probably reflected contributions from motor-vehicle tire wear or was associated with municipal incineration. On the other hand, results from the village showed that only one factor was able to explain the main part of the data variance, and the industrial site was polluting air quality in the village with Cu, Cr, Pb, nickel, and Mn.     

Predicting ozone levels

This paper presents a statistical model that is capable of predicting ozone levels from precursor concentrations and meteorological conditions during daylight hours in the Shuaiba Industrial Area (SIA) of Kuwait. The model has been developed from ambient air quality data that was recorded for one year starting from December 1994 using an air pollution mobile monitoring station. The functional relationship between ozone level and the various independent variables has been determined by using a stepwise multiple regression modelling procedure. The model contains two terms that describe the dependence of ozone on nitrogen oxides (NOx) and nonmethane hydrocarbon precursor concentrations, and other terms that relate to wind direction, wind speed, sulphur dioxide (SO₂) and solar energy. In the model, the levels of the precursors are inversely related to ozone concentration, whereas SO₂ concentration, wind speed and solar radiation are positively correlated. Typically, 63 % of the variation in ozone levels can be explained by the levels of NOx. The model is shown to be statistically significant and model predictions and experimental observations are shown to be consistent. A detailed analysis of the ozone-temperature relationship is also presented; at temperatures less than 27 °C there is a positive correlation between temperature and ozone concentration whereas at temperatures greater than 27 °C a negative correlation is seen. This is the first time a non-monotonic relationship between ozone levels and temperature has been reported and discussed.     

Assessment of indoor and outdoor particulate air pollution at an urban background site in Iran

The relationship between indoor and outdoor particulate air pollution was investigated at an urban background site on the Payambar Azam Campus of Mazandaran University of Medical Sciences in Sari, Northern Iran. The concentration of particulate matter sized with a diameter less than 1 μm (PM_1.0), 2.5 μm (PM_2.5), and 10 μm (PM₁₀) was evaluated at 5 outdoor and 12 indoor locations. Indoor sites included classrooms, corridors, and office sites in four university buildings. Outdoor PM concentrations were characterized at five locations around the university campus. Indoor and outdoor PM measurements (1-min resolution) were conducted in parallel during weekday mornings and afternoons. No difference found between indoor PM₁₀ (50.1 ± 32.1 μg/m³) and outdoor PM₁₀ concentrations (46.5 ± 26.0 μg/m³), indoor PM_2.5 (22.6 ± 17.4 μg/m³) and outdoor PM_2.5 concentration (22.2 ± 15.4 μg/m³), or indoor PM_1.0 (14.5 ± 13.4 μg/m³) and outdoor mean PM_1.0 concentrations (14.2 ± 12.3 μg/m³). Despite these similar concentrations, no correlations were found between outdoor and indoor PM levels. The present findings are not only of importance for the potential health effects of particulate air pollution on people who spend their daytime over a period of several hours in closed and confined spaces located at a university campus but also can inform regulatory about the improvement of indoor air quality, especially in developing countries.     

SO2 Dispersion and Monthly Evaluation of the Industrial Source Complex Short-Term (ISCST32) Model at Mina Al-Fahal Refinery,Sultanate of Oman

Modeling of air pollutant dispersion has been undertaken for emissions of sulfur dioxide (SO₂) at the Mina Al-Fahal refinery in the Sultanate of Oman. The study was conducted during the period of November 1999 to October 2000. The Industrial Source Complex Short-Term (ISCST32) air pollution model was adopted to predict the ground level concentration of SO₂ in and around the refinery. The modeling results were validated against measured data during the study period. The comparison, based on the monthly average measurements, showed that the model underestimates the observed SO₂ concentrations. However, the predicted ground level concentrations of SO₂ during the months of September, October, November, and June were in better agreement with the observations. The predicted SO₂ values are presented in the form of concentration contours to determine the spatial distribution of SO₂ and to assess the impact on air quality over the survey area. Predicted SO₂ concentrations were found lower than the World Health Organisation (WHO) guideline value of 365 μg/m³, with the maximum ground level concentrations being found to occur relatively close to the sources of emission. Moreover, concentration contour patterns for the modeled area vary with changes in meteorological conditions. On the basis of this study, the refinery is not likely to cause any significant deterioration in air quality, and predicted concentrations of SO₂ are well below those likely to influence health.     

Impact of NOx Emissions Released from a Gas Turbine-Based Power Plant on the Ambient Air Quality

The number of gas turbine- (GT-) based power plants is rapidly increasing to meet the world’s power demands. Until a few years ago, fossil fuel, and specifically fuel oil, was considered the major energy source for gas turbine operation. Due to the high amount of pollution that fuel oil generates, natural gas has become a popular source of energy due to its lower emissions compared to fuel oil. As a result, many GTs have switched to natural gas as an alternative to fuel oil. However, pollutants expelled from GT-based power plants operating on natural gas impact surrounding air quality. The objective of this study was to examine the dispersion of nitrogen oxides (NO_x) emitted from a GT-based power plant located in the Sultanate of Oman. Supported by CALPUFF dispersion modeling software, six scenarios were investigated in this study. The first four scenarios considered a case where the GT-based power plant was operating on natural gas during winter and summer and for open and combined cycle modes. The remaining two scenarios considered, for both open and combined cycle modes, the case where the GT-based power plant was operating on fuel oil. Whether run by natural gas or fuel oil, CALPUFF simulation results for both seasons showed that NO_x concentrations were higher when GTs were used in the combined cycle mode. The concentrations were still lower than the allowable concentrations set by the United States Environmental Protection Agency (U.S. EPA) standards. In contrast, for the case where the power plant operated on fuel oil, the NO_x one-hour average simulated results exceeded the allowable limits only when the combined cycle mode was activated.     

SO2 dispersion and monthly evaluation of the industrial source complex short-term (ISCST32) model at Mina Al-Fahal refinery,Sultanate of Oman

Modeling of air pollutant dispersion has been undertaken for emissions of sulfur dioxide (SO(2)) at the Mina Al-Fahal refinery in the Sultanate of Oman. The study was conducted during the period of November 1999 to October 2000. The Industrial Source Complex Short-Term (ISCST32) air pollution model was adopted to predict the ground level concentration of SO(2) in and around the refinery. The modeling results were validated against measured data during the study period. The comparison, based on the monthly average measurements, showed that the model underestimates the observed SO(2) concentrations. However, the predicted ground level concentrations of SO(2) during the months of September, October, November, and June were in better agreement with the observations. The predicted SO(2) values are presented in the form of concentration contours to determine the spatial distribution of SO(2) and to assess the impact on air quality over the survey area. Predicted SO(2) concentrations were found lower than the World Health Organisation (WHO) guideline value of 365 microg/m(3), with the maximum ground level concentrations being found to occur relatively close to the sources of emission. Moreover, concentration contour patterns for the modeled area vary with changes in meteorological conditions. On the basis of this study, the refinery is not likely to cause any significant deterioration in air quality, and predicted concentrations of SO(2) are well below those likely to influence health.     

Lead,cadmium, copper,zinc, iron,and calcium in human hair as a function of gender,age, smoking,and hair dyeing

Hair samples were collected randomly from 110 subjects (55 male and 55 female) ranging in age from (<15–60) years. Each subject was asked to complete a personal questionnaire describing his/her sex, age, general health, smoking, use of hair dyes, occupational area, and living habits. Concentrations of Pb, Cd, Cu, Zn, Fe, and Ca in human hair samples were evaluated using atomic absorption spectrometry. Results indicated that concentrations of Pb, Cd, Cu, and Zn in the hair of smokers were higher than those in the hair of non-smokers, whereas, Fe and Ca concentrations in hair of smokers were lower than those in hair of non-smokers. Moreover, the concentrations of these elements are higher in dyed hair compared with undyed hair.     

Determination of selected heavy metals in air samples from the northern part of Jordan

In this work, the atmospheric concentrations of selected heavy metals including lead (Pb), iron (Fe), cadmium (Cd), copper (Cu), nickel (Ni), manganese (Mn), and zinc (Zn) were measured for two different sampling sites (urban and rural) in the northern part of Jordan (Irbid city). Samples were collected according to a certain schedule for 1 year. High volume air samplers and glass fiber filters were used to collect the samples. Collected samples were digested using a mixture of analytical grade nitric acid and analytical grade hydrochloric acid, and analyzed to evaluate the levels of heavy metals by atomic absorption spectrophotometry. Six heavy metals (Pb, Fe, Cu, Ni, Mn, and Zn) were measured in all samples; the concentrations of Cd and Co were not detected in Irbid atmosphere by atomic absorption spectroscopy. The results were used to determine the levels of heavy metal pollutants in air, possible sources, and to compare the levels of selected heavy metals in the two studied sites. Aerosols from the rural site have lower concentrations for all the metals compared to those from the urban site. The daily and monthly variations of the elements were investigated. All heavy metals in urban and rural sites reached maximum concentrations in June, July, and August. This is consistent with the increased activities leading to particulate matter emission during the summer period. The enrichment factors with respect to earth crust and correlation coefficients of heavy metals were investigated to predict the possible sources of heavy metals in air.     

An Application and Evaluation of the CAL3QHC Model for Predicting Carbon Monoxide Concentrations from Motor Vehicles Near a Roadway Intersection in Muscat,Oman

The CAL3QHC model was used to predict carbon monoxide (CO) concentrations from motor vehicles at an existing urban intersection (Star Cinema in Muscat area, Oman). The CO concentrations predicted from the model were compared with those measured in the field. Predicted average CO concentrations were found to compare favorably with measured values obtained at all eight receptors considered within the modeled intersection. In general, the comparison indicates good agreement with some underprediction for CO. For receptor 6, the model overpredicts the average CO concentration. This overprediction is associated with the presence of trees and green area in the location of receptor 6. In general, the measurements and the model results indicated that the highest CO concentrations were found to occur close to the intersection and, hence, a decrease in the concentration levels was seen as the distance from the road increased. The results indicated that the levels of CO were well below the ambient air quality standard and that probably no health risk was present in areas adjacent to the star cinema intersection. However, the predicted worst-case 1-h CO concentrations assuming inversion atmospheric stability conditions (class F) and wind speed of 1 m/s indicated that the levels of CO were close to or higher than the Omans National Ambient Air Quality Standards (NAAQS) value of 35 ppm at all receptors considered. The results of this study are useful in transport development and traffic management planning.Published online.