Showing 4 results for Ozone
G Moussavi, A Jamal, H Asilian,
Volume 1, Issue 2 (3-2009)
Abstract
Background and Objectives: A conventional treatment to stabilize the excess activated sludge is the aerobic digestion process but due to long aeration time, it requires large equipments as well as high investment cost. Because of high oxidation potential of ozone, sludge ozonation enhances stabilization rate and reduces sludge treatment equipment size and cost. Therefore, in this study, the combination of pretreatment with ozone and aerobic digestion processes were investigated.
Materials and Methods: The experimental set-up consisted of an ozone generator and ozonation reactor with the total volume of 2 L. Removal percentages of TSS, VS, total and soluble COD, HPC, fecal coliform and settable solids were measured in integrated process compared to the single ones.
Results: The results of this research indicated that the aerobic digestion of waste activated sludge during 10 days could reduce 38% of volatile solids and thus obtaining the EPA standard. Also, the results of combined ozonation and aerobic digestion revealed that the pre-ozonation at 0.25 g O3/g TS or 0.5 g O3/g TS with 6 or 3 days aeration, respectively, could achieve 38% reduction in VS and hence the requirement set by EPA. Therefore, integration of pre-ozonation with aerobic digestion can significantly reduce the digestion time to attain the standards.
Conclusion: The sludge pre-ozonation with low dose of ozone due to solids disintegration can enhance the efficiency of aerobic digestion in waste activated sludge stabilization, and consequently decrease size of equipments, air requirement, investment and probably operation cost.
Mohammadali Ghorbani, Leila Naghipour, Vahid Karimi, Reza Farhoudi,
Volume 6, Issue 1 (5-2013)
Abstract
Background and Objectives: Weather pollution, caused by Ozone (O3) in metropolitans, is one of the major components of pollutants, which damage the environment and hurt all living organisms. Therefore, this study attempts to provide a model for the estimation of O3 concentration in Tabriz at two pollution monitoring stations: Abresan and Rastekuche.
Materials and Methods: In this research, Artificial neural networks (ANNs) were used to consider the impact of the meteorological and weather pollution parameters upon O3 concentration, and weight matrix of ANNs with Garson equation were used for sensitivity analysis of the input parameters to ANNs.
Results: The results indicate that the O3 concentration is simultaneously affected by the meteorological and the weather pollution parameters. Among the meteorological parameters used by ANNs, maximum temperature and among the air pollution parameters, carbon monoxide had the maximum effect.
Conclusion: The results are representative of the acceptable performance of ANNs to predict O3 concentration. In addition, the parameters used in the modeling process could assess variations of the ozone concentration at the investigated stations.
K Ezimand, Aa Kakroodi,
Volume 10, Issue 4 (3-2018)
Abstract
Background and Objective: Ground level ozone (O3) is one of most dangerous pollutants for human health in urban areas. The aim of this study was to identify the factors affecting the formation of ozone and modeling the spatial and temporal variations of ozone concentration in Tehran metropolitan area.
Materials and Methods: The data used in this research included meteorological data and pollution concentration data for 2014. First, we studied the impact and correlation of parameters to ozone concentration using the coefficient of Pearson, and then we did modeling of ozone concentration using a multivariate linear regression method.
Results: The developed model had the ability to describe 79% of the data changes for 2014. The temporal analysis of the ozone concentration showed that the best coefficient of determination of the model was R2 = 0.771 in the summer and R2 = 0.778 in July. These results also showed that among the air quality monitoring station of Tehran, station 4 had the lowest coefficient of determination (R2 = 0.6) and Aqdasieh station had the highest coefficient of determination (R2 = 0.79). Finally, the spatial distribution of the estimated ozone concentration was consistent with the measured ozone concentration at the station level.
Conclusion: According to the results, all the parameters related to air pollution concentration and meteorological parameters were effective parameters on modeling of ozone concentration on the ground level. The spatial distribution of ozone concentration in Tehran showed a greater concentration of ozone in the South and East than the North and West of the city.
Vahideh Barzeghar, Akbar Gholampour, Mohammad Sadegh Hassanvand,
Volume 14, Issue 2 (9-2021)
Abstract
Background and Objective: This study was conducted to investigate the long-term temporal trends and spatial variations of ambient PM10, PM2.5, O3, concentrations in Tabriz city during the years 2006-2017.
Materials and Methods: Real-time hourly concentrations of PM10, PM2.5, O3 measured at nine air quality monitoring stations (AQMSs) were obtained from the Tabriz Department of Environment (TDoE) during 2006-2017 and analyzed. Spatial and temporal variations of pollutants using the Mann-Kendall's test and Moran’s I index were analyzed.
Results: The results of this study showed that the annual trend of PM10, PM2.5 was decreasing but remained almost constant for O3 during the study period. During some of the studied days, PM10, PM2.5 levels were exceeded greater than the WHO AQG and National standard levels. Moreover, the highest monthly mean concentrations of PM10 in October (80.3 µg/m³), PM2.5 in January (42.9 µg/m³) and O3 in June (77.8 µg/m³) were observed. Comparison between the stations indicated that the Raste Kuche station was more polluted than other stations.
Conclusion: Effective control planning and implementation policies are essential to improve the air quality of the Tabriz environment. Hence, information provided in this research can be used as a key step for city managers, policymakers, and health officials to reduce the health impacts of air pollution.
