Search published articles


Showing 2 results for Carbon Monoxide

Fatemeh Mansouri, Narges Khanjani, Laleh Ranandeh Kalankesh, Reza Pourmousa,
Volume 11, Issue 2 (11-2013)
Abstract


  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, NOx, 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 , NOx , 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.


Mohammad Javad Golhosseini, Hossein Kakooei, Jamaleddin Shahtaheri, Kamal Azam,
Volume 13, Issue 1 (6-2015)
Abstract

  Background and Aim: Motor vehicles are an absolute necessity used extensively in all countries of the world. They are a major cause of air pollution with highly undesirable consequences. Thus, exposure to traffic pollution is a growing public health concern. Several studies indicate that people in the cabin of a vehicle inhale air with high concentrations of pollutants such as nitrogen oxides(NOx), particulate matter (PM), volatile compounds (VOCs) and carbon monoxide (CO).

  Materials and Methods: Eexposure of drivers inside motor vehicles to CO was assessed during one year in Tehran, Iran. For this purpose, the concentration of CO was measured in the breathing zone of 72 male taxi drivers using a portable real-time instrument equipped with electrochemical sensors. In addition, records of fixed air pollution monitoring stations in Tehran were examined and the CO concentration in those records were compared with those measured in the taxis.

  Results: The mean in-vehicle CO concentration was 19.91 ± 4.37ppm, while records of fixed air pollution monitoring stations showed the concentration of this pollutant in the air to be 3.69 ± 1.03ppm.

  Conclusion: It can be concluded that factors such as traffic density, weather conditions and vehicles lifespan affect the extent of exposure of taxi drivers to carbon monoxide.



Page 1 from 1     

© 2024 , Tehran University of Medical Sciences, CC BY-NC 4.0

Designed & Developed by : Yektaweb