Journal of School of Public Health and

---

Background and Aim: Problems related to conventional Fenton oxidation, including neccesity of having a low pH and production of considerable amounts of sludge, have prompted researchers to consider chelating agents to improve the pH operating range and iron nano-oxide particles to reduce excess sludge. The main objective of this study was to remove pyrene from contaminated soils by a modified Fenton oxidation method  at neutral pH.

Materials and Methods: Experiments were conducted using various concentrations of H2O2 (0-500 mM), iron nano-oxides (0-60 mM), reaction times (0.5-24 hours) and several chelating agents, namely, sodium pyrophosphate, ethylene diamine tetra-acetic acid, sodium citrate, fulvic and humic acids, to eliminate pyrene from soil (concentrations of 100-500 mg/kg).

Results: The efficiency of removal of pyrene at an initial concentration of 100 mg/kg was 99 % at the following reaction conditions: H2O2 and iron nano-oxide concentrations of 300 mM and 30 mM, respectively pH=3 and a reaction time of 6 hours. The initial pyrene concentration of 100 mg/kg decreased to 7 mg/kg at optimum conditions using sodium pyrophosphate as the chelating agent at pH 7.    

Conclusion: The modified Fenton oxidation method, using iron nano-oxide at optimum conditions as defined in this research, is an efficient alternative for chemical remediation or pre-treatment of soils contaminated wih pyrene at neutral pH. 

---

  Anderson, H.R., 2009. Air pollution and mortality: A history. Atmospheric Environment, 43, pp. 142-152 .

  Box, GEP. and Jenkins, G.M., 1976. Time series analysis: forecasting and control, San Francisco, Holden Day Pulications .

  Duenas, C., Fernandez, M.C., Canete, S., Carretero,Liger E, 2005. Stocastic model to forecast ground level ozone concentration at urban and rural areas . Chemosphere, 61(10), pp. 1379-1389 .

  Ghorbani, M. and Younesian, M., 1389. Research Projects in Air pollution Epidemiology. Iranian Epidemiology Journal . 5, pp. 44-52 [In Persian].

  Goyal, P., Chan, A.T. and Jaiswal, N., 2006. Statistical models for the prediction of respirable suspended particulate matter in urban cities. Atmospheric Environment, 40, pp. 2068-2077 .

  Hamilton, JD., 1994. Time series analysis, Princeton Publications, USA .

  Hosseinpour, A.R., Forouzanfar, M.H., Yunesian, M., Asghari, F., Holakouie Naieni, K. and Farhood, D., 2005. Air pollution and hospitalization due to angina pectoris in Tehran, Iran: A time-series study. Environmental Research, 99, pp. 126-131 [In Persian].

  Ingrisch, M., Sourbron, S., Reiser, M.F. and Peller, M., 2009. Model selection in dynamic contrast enhanced MRI: The Akaike Information Criterion. In Dössel, O. and Schlegel, WC. (Eds.) IFMBE Proceedings 25/IV

  Khosravi Dehkordi, A. and Modarres, R., 1386. Time Series analysis of the daily air pollution in Isfahan from the Petrolium Industry. Mohit shenasi. 33, pp. 33-42 [In Persian].

  Kumar, U. and De Ridder, K., 2010. GARCH modelling in association with FFT-ARIMA to forecast ozone episodes. Atmospheric Environment, 44, pp. 4252-4265.

  Lau, J.C., Hung, W.T., Yuen, D.D. and Cheung, C.S., 2009. Long memory characteristics of urban roadside air quality. Transportation Research Part D, 14, pp. 353-359 .

  Liang, W., Wei, H. and Kuo, H., 2009. Association between daily mortality from respiratory and cardiovascular diseases and air pollution in Taiwan. Environmental Research, 109, pp. 51-58 .

  Liu, P.G., 2009. Simulation of the daily average PM10 concentrations at Ta-Liao with Box–Jenkins time series models and multivariate analysis. Atmospheric Environment, 43, pp. 2104 - 2113 .

  López-Villarrubia, E., Ballester, F., Iñiguez, C. and Peral, N., 2010. Air pollution and mortality in the Canary Islands:a time-series analysis. Environmental Health, 9 .

  Lumbreras, J., Garcia-Martos, C., Mira, J. and Borge, R., 2009. Computation of uncertainty for atmospheric emission projections from key pollutant sources in Spain. Atmospheric Environment, 43, pp. 1557-1564 .

  Masjedi, M.R., Jamaati, H.R., Dokoohki, P., Ahmadzadeh, Z., Alinejad Taheri, S., Bigdeli, M., Agin, K., Ghavam, S.M., Rostiman, A. and Izadi S., 2001. The correlation between air pollution and acute respiratory and cardiac attacks. Pazhoohesh dar pezeshki, 25, pp. 25-33 [In Persian].

  Nasrollhi, Z. and Ghaffari Goolak, M., 2010. Air pollution and its effective factors. Faslnameh Pazhoohesh Eghtesadi, 3, pp. 375-395 [In Persian].

  Quintela-del-Rio, A. and Francisco-Fernandez, M., 2011. Nonparametric functional data estimation applied to ozone data: Prediction and extreme value analysis. Chemosphere, 82, pp. 800-808 .

  Rajarathnam, U., Sehgal M., Nairy S., Patnayak R.C., Chhabra S.K., Kilnani, K.V., R and Committee., HHR, 2011. Time Series study on air pollution and mortality in Dehli. Res Rep Health Eff Inst, Mar, pp. 47-74 .

  Samet, J.M., Dominici, F., Zeger, S.L., Schwartz, J. and Dockery, D.W., 2000. The national morbidity, mortality and air pollution study. Part 1: Methods and Methodologic Issues. Research Report 94 Cambridge, MA, Health Effects institute .

  Sharma, P., Chandra, A. and Kaushik, S.C., 2009. Forecasts using Box–Jenkins models for the ambient air quality data of Delhi City. Environ Monit Assess, 157, pp. 105–112 .

  Wagemakers, E. and Farrell, S., 2004. AIC model selection using Akaike weights. Psychonomic Bulletin and Review, 11, pp. 192-196 .

  Zhang, F., Wang, W., Lv, J., Krafft, T. and Xu, J., 2011. Time-series studies on air pollution and daily outpatient visits for allergic rhinitis in Beijing, China. Science of the Total Environment, 409, pp. 2486–2492 .

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  Scientific Journal of School of Public Health and Institute of Public Health Research /85

  Vol. 11, No. 2, Summer 2013

  

  Forecasting ambient air pollutants by time series models in Kerman, Iran

  

  Mansouri, F., MS.c. Student, Dept of Environmental Health Engineering, Faculty of Public Health, Kerman Medical University, Kerman, Iran

  Khanjani, N., Ph.D. Assistant Professor, Department of Epidemiology and Department of Environmental Health, Faculty of Public Health, Kerman Medical University, Kerman, Iran - Corresponding author: n_khanjani@kmu.ac.ir

  Rananadeh Kalankesh, L., MS.c. Student, Department of Environmental Health Engineering, Faculty of Public Health, Kerman Medical University, Kerman, Iran

  Pourmousa, R., MS.c. Lecturer, Department of Statistics, School of Mathematics and Statistics, Shahid Bahonar University, Kerman, Iran

 

  

  Received: Apr 3, 2012 Accepted: Feb 14, 2013

 

  ABSTRACT

 

  Background and Aim: Air pollution is one of the most important problems of big cities in developing countries and can have several negative health effects on humans. Therefore studying these pollutants can help in developing programs for air pollution control. The aim of this study was to estimate and predict the changes of air pollutants in Kerman, Iran.

  Materials and Methods: In this ecological study, data about seven important air pollutants in Kerman including NO, CO, NO₂, NO_x, PM₁₀, SO₂ and O₃ from March 2006 until September 2010 was inquired from the Kerman Province Environmental Protection Agency. Then the data was calculated as averages per month and by incorporating time series models, predictions were done for each pollutant.

  Results: All of the pollutants were steady in Kerman, except CO which is significantly decreasing and PM₁₀ which is increasing. All of the pollutants had a seasonal pattern. Time series models with a 12, 3, 8, 12, 12, 12 and 6 month seasonal pattern were fit for O₃ , SO₂ , PM₁₀ , NO_x , NO₂ , CO and NO consecutively.

  Conclusion: The production of ambient CO is decreasing in Kerman and one reason is probably replacing and retiring old automobiles. However PM₁₀ is increasing in Kerman and in most seasons it is above standard and therefore control initiatives should be implemented.

---

  Background and Aim: A ssociations between air pollution and morbidity have been reported in several studies. Due to limited publications in the literature for Iran, this study aimed to determine the association between air pollution and hospital admissions of respiratory disease patients in Tabriz, Iran.

  Materials and Methods: The methodology used in this study was case -crossover and the artificial neural network model. The variables of the model included air quality, hospital admission and air pollutants. Daily hospital admission data were collected from five hospitals in Tabriz, Iran based on the International Classification of Diseases (ICD-10) , air quality data including NO₂, SO₂, CO, PM₁₀ and O₃ from the six fixed online air quality monitoring stations, and the daily mean temperature and relative humidity data for the same period from the East Azerbaijan Meteorological Bureau.

  Results : P articulate matter with a median aerometric diameter <10 μm (PM₁₀) was found to be the most important pollutant affecting respiratory hospital admissions. The ANNs data showed that the most important causes of hospital admissions were for COPD NO₂, NO and CO, for respiratory infections PM_10, and for asthma PM₁₀, O₃ and CO. The highest associations were observed between hospital admissions due to COPD and asthma in females and those due to respiratory infections in males. The elderly (individuals over 65 years old) were at the highest risk.

  Conclusion: The results show a significant relation between air pollutants and respiratory hospital admissions in Tabriz, Iran. The importance and necessity of enforcement of existing regulations and enacting laws to prevent and control the adverse health effects of air pollution are confirmed.

---

Background and Aim:This research was conducted of determining and comparing the heavy metals of zinc, iron, manganese, copper, nickel and vanadium in summer in waters and sediments of Naseri wetland in Khuzestan province, 2017.
Material and Methods:Sampling of water and sediments from three areas of north, central and southern Naseri wetland was carried out in summer. In order to measure heavy elements, the ICP-OES model Varian 710-ES was used to measure the induction plasma (ICP) and its composition by mass spectrometry (ICP-MS).
Results:The average concentration of heavy metals in Naseri wetland water was obtained at station 3 above the first and second stations. Zinc, iron, copper and vanadium were lower in the wetland water than national and international standards, but higher levels of manganese and nickel were obtained. The average of the concentrations of the studied metals except the nickel in the surface sediments of the wetland in the second station was higher than the first and third stations. Ni was found higher in the sediments of the third station.
Conclusion:The results of calculating the contamination factor showed that heavy metals were zinc, iron, manganese, nickel, vanadium and copper in low pollution levels. The degree of contamination of the studied metals also showed that pollution of Nasseri wetland sediments was low. The degree of contamination of modified heavy metals indicates very low contamination of sediments of Naseri wetland. The ecological risk of zinc, iron, manganese, nickel, vanadium, and copper was in the low-risk category. The total ecological risk of heavy metals at the stations was also classified as low risk.

---

Background and Aim: Air Pollution Tolerance Index (APTI), as a criterion for assessing plants' resistance to air pollution, is one of the important tools for managing air quality around industrial complex buildings. The aim of this study was to determine air quality and the APTI of native plants grown around the Industrial Complex of Glass, Khak-e-chini, Tile and Ceramics and Glass in Ardakan, Iran.
Materials and Methods: This was a cross-sectional, descriptive-analytical study. First, the concentration of air pollutants in the industrial area was assessed. Then, APTI was determined as follows: measuring the pH of leaf extracts, relative water content, total chlorophyll and ascorbic acid contents of leaves in samples of native plant leaves. In addition, the concentrations of lead, chromium and cadmium were measured in plants by atomic absorption using the dry digestion method. For statistical analysis of the data the SPSS software version 22 was used.
Results: The mean plant concentrations of Co, O₃, NO₂, SO₂ and PM₁₀ in the industrial are were 2.06 ppm, 7.75 ppm, 3.28 ppm, 33.94 ppb and 70.55 µg/m³, respectively; these concentrations were all below the respective standards, as were those of lead, cadmium and chromium. The tolerance index of plants around the Industrial Complex was measured in the floor/parts sensitive to air pollution, proportional to low air quality pollutant and heavy metal concentrations in plants. Among the rangeland, tree and shrubs species, the following had the highest air pollution tolerance index, respectively:  Boiss.fortuynia (8.49), Punica granatum (16.80) and Albizia lebbeck (9.37).
Conclusion: Based on the Air Pollution Tolerance Index it is suggested that the nonproductive species Punica granatum be used as a more tolerant species and Artemisia species as a biomarker for the expansion of green space.

---

Background and Aim: Air pollution is currently one of the most important environmental issues. The most common effect of air pollution on plants is the gradual decomposition of chlorophyll and leaf yellowing, which may result in the reduction of photosynthetic capacity. This study aimed to investigate the effect of air pollution on the chlorophyll content and zonation of leaf chlorophyll content of two tree species in Malayer city, Iran.
Materials and Methods: Samples were collected from two tree species, namely, Platanus orientalis and Robinia pseudoacacia in different parts of Malayer city, Iran (clean and polluted areas), each with three replications. The concentration of pigments in the leaves was measured by the Lichtenthaler (1987) method, which is the modified Arnon method (1949), at 663 and 645 nm wavelengths, absorbance being measured using a spectrophotometer.
Results: Data analysis showed that the a, b and total chlorophyll contents in the acacia tree species in the southern parts (southwest) of the study area reached their maximums, while their contents were lowest in the eastern and north-western parts and low to medium in the central parts of the study area. On the other hand, as regards the sycamore species, in the eastern and north-western parts of the study area the a, b, and total chlorophyll contents were the highest and reached their minimums in the south-western parts. However, as in the case of the acacia species, in the central parts of the study area the contents of the tree chlorophylls were low to medium.
Conclusion: The results of this study show that the a, b and total leaf chlorophyll contents of the two acacia and plantain species were higher in the polluted areas as compared to those in clean areas. On this basis, it can be said that a higher physiological index, such as an increased chlorophyll content, indicates the plant's response for resistance to air pollutants.
 

---

Background and Aim: In recent years the interrelationships among environment, energy and health have attracted increasing attention due to their significant impact on human health. This study aimed to investigate the complex interactions among environment, economy, development, energy and the health outcomes in Iran.
Materials and Methods: In this research the annual national data in Iran between 1981 and 2021 were used, using the fully modified least squares cointegration. The following variables affecting life expectancy at birth were included in the analysis: renewable energy consumption, health costs, air pollution, female literacy rate, inflation rate, Gini coefficient, GDP per capita, financial development and fossil fuel consumption.
Results: Data analysis showed the following: 1. financial development positively affects life expectancy with a coefficient of 0.037 ; 2. CO2 emissions and fossil fuel consumption decrease life expectancy by 0.015 and 1.02, respectively; 3. Renewable energy consumption and health expenses have improved life expectancy in Iran with positive coefficients of 0.025 and 0.035, respectively.
Conclusion: To improve health care outcomes action should be taken in the following areas: increasing health expenditures, increasing the use of renewable energy, reducing the use of fossil fuels, strengthening long-term financial development for easier access to medical treatments, decreasing disease risk, healthier lifestyles, and environmental quality improvement. In addition, as regards policy-making, planning to improve economic indicators can provide the basis for demand for healthy and educational goods and improve the health status of the society.