12 research outputs found
Quantification of the Health Effects of Exposure to Air Pollution (no2)
International audienceEpidemiological studies show that long-term exposure to NO2/NOx is associated with an increased risk of cancer. The mortality and morbidity rates due to NO2 in the Tabriz city was determined considering the relative risk and baseline incidence provided by the World Health Organization (WHO) / European Center for Environment Health, Bilthoven Division using the AirQ(2.23) software to analyze the data. The results of this study showed that 0.85% (CI 95% 0.36 - 0.96) of acute myocardial infarction, 0.47% (CI 95% 0 - 0.94) of cardiovascular mortality and 9.28% (CI 95% 0.1 - 2.19) of hospital admissions for chronic obstructive pulmonary disease (COPD) can be attributed to NO2 concentrations over 10 mu g/m(3). According to this model, cases of cardiovascular deaths and acute myocardial infarction caused by NO2 in Tabriz were about 0.23 and 0.10% of the total mortalities, respectively. In addition, about 0.9% of the total hospital admissions related to chronic obstructive pulmonary disease (HA COPD) was caused by NO2. Therefore, due to this pollution, preventive measures and effective strategies for implementing policies related to reduce air pollution should be undertaken in Tabriz cit
A modeling study by artificial neural network on ethidium bromide adsorption optimization using natural pumice and iron-coated pumice
In this study, the potential of natural pumice (NP) and iron-coated pumice stone (Fe-CP) as novel low-cost adsorbents to remove ethidium bromide (EtBr) from aqueous solutions was investigated. The operational parameters affecting removal efficiency and adsorption capacity such as adsorbent dose, initial EtBr concentration, pH, and contact time were studied in order to maximize EtBr removal. The maximum amount of adsorbed EtBr (qm) using NP and Fe-CP was 40.25 and 45.08 mg g‒1, respectively. It was found that EtBr adsorption followed the Freundlich isotherm model and fitted the pseudo-second-order kinetics equation for both adsorbents. In addition, the experimental system could be easily modeled by artificial neural network calculations