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Monitor toring ing and assessment sessment of ambient ient benzen zene e concentrati centration on and its ts health alth impact act in urban n area ea in Tehran ran Farideh Atabi, Ph.D. Assistant Prof., Graduate School of


  1. Monitor toring ing and assessment sessment of ambient ient benzen zene e concentrati centration on and its ts health alth impact act in urban n area ea in Tehran ran Farideh Atabi, Ph.D. Assistant Prof., Graduate School of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran & S. A. H. Mirzahosseini, Ph.D. U.S. – Iran Symposium on “Urban Air Pollution in Megacities” Beckman Center of National Academies of Sciences & Engineering Irvine, California September 3-5, 2013 1

  2. Outline • Background • Methodology • Field Measurement • Interpolation Using IDW Model • Cancer Risk Assessment • Conclusions 2

  3. Background 3

  4. Background Main sources of ambient Benzene [ATSDR, 2007] : The vehicles’ exhaust 1. 2. Gasoline evaporation 3. Leakage from natural gas 4. Emissions from the use of solvents and paints, Using as an additive to unleaded gasoline,… 5. Benzene is an aromatic volatile organic compound characterized by US EPA as a “known” human carcinogen for all routes of exposure and is clasified by the International Association on the Risks of Cancer [IARC, 1987] as class 1 carcinogen. 4

  5. Background Annual averages of Benzene concentration have been measured in various European regions (Cocheo et al. 2000; Skov et al. 2001). The annual average concentrations of benzene in metropolitans have ranged from a almost zero to more than 6.25 ppb (Anabtawi et al. 1996). In Japan, the ambient standard for benzene concentration has been set to be 0.69 ppb (Laowagul and Yoshizumi, 2009). Iran Department of the Environment (DoE) and US EPA have set the standard for the ambient Benzene concentration levels to be 1.56 ppb [Iran DOE, 2010]. 5

  6. Background Despite the regulations established, benzene concentrations and cancer risk assessment have not been investigated in Tehran due to the lack of data for ambient benzene concentration levels. This is the first time that such an extensive study about benzene has been carried out in Tehran city. 6

  7. Methodology 7

  8. The Studied Area Tehran is divided into 22 municipality districts, and District 1 with the area of 46 km 2 is located at the northern part of the city and heavy traffic flows along with densely populated areas are the main characteristics of this area with population of around 445000. In this study, ambient benzene concentration levels in 33 sampling locations including 4 gas stations, 9 roadsides, 5 busy roads, 8 residential areas and 7 traffic intersections in District 1 were monitored, during 4.00 – 8.00 pm, once a week, during 5 th April 2010 to 25 th March 2011. 8

  9. Identification codes and situations of the sampling locations in District 1 in Tehran Identification code Sampling Station name Geographic location Situation x y 1 6 sharghi-shadavar 536831 3961140 Residential area 2 Aghdasiyeh-golestan 543076 3962312 Roadside 3 Aghdaseyeh-park 542925 3962515 Roadside 4 Alef Sq. 537239 3961537 Busy road 5 Andarzgoo-Vatanpoor 541312 3962062 Roadside 6 Anjoman koshnevesan 540267 3962288 Residential area 7 Artesh-Ozgol 544945 3961872 Roadside 8 Baghe ferdos 538028 3962261 Busy road 9 Bolvar saba -pol roomi 539358 3961183 Traffic intersection 10 Darmangah Farmanieh 542765 3961758 Traffic intersection 11 Eskan Kareghari 535763 3960900 Roadside 12 Ghalandari-park Shadi 539858 3960349 Residential area 13 Ghods Sq. 539140 3962404 Traffic intersection 14 Gheitarieh 540801 3961133 Busy road 15 Hashemi alley 541058 3961971 Residential area 16 Hosseini alley 541028 3961960 Residential area 17 Jim-4shargi 536879 3961074 Residential area 18 Langari-havashenasi 543771 3961748 Roadside 19 Langari-Nobonyad 543342 3960920 Roadside 20 Movahed danesh-masjed 543724 3961961 Busy road 21 Park way 537576 3960854 Traffic intersection 22 Pashazahri-Kamranieh 541662 3962007 Traffic intersection 23 Pesian-Valiasr 537805 3961997 Traffic intersection 24 Sadr-Dastor 539864 3960218 Roadside 25 Salimi alley 541057 3961735 Residential area 26 Shariati-metro Sadr 539391 3960321 Roadside 27 Gas Station 134 - Aghdaseyeh 542780 3962124 Vicinity of gas station 28 Gas Station 139 -Baagh ferdos 538210 3962496 Vicinity of gas station 29 Gas Station 148 - Velenjak 536717 3961050 Vicinity of gas station 30 Gas Station 27 - Pastdaran 543017 3961455 Vicinity of gas station 9 31 Tajrish Sq. 538648 3962592 Traffic intersection 32 Chamran-Velenjak 536664 3960981 Busy road 33 Tapeh-Gheitarieh 539829 3961074 Residential area

  10. Busy road Andarzgoo-Vatanpoor Chamran-Velenjak

  11. Residential area Hashemi Alley Ghalandari-Parke Shadi

  12. Gas station Gas Station #148 - Velenjak Gas Station #27-Pasdaran

  13. Trafic Intersection Bolvar saba -Pole Roomi Tajrish Sq.

  14. Roadside Aghdasiyeh-Golestan Sadr-Dastor

  15. Locations of the 33 sampling stations in District 1 in Tehran, Iran. The sampling stations in the studied area are assigned as: RS= Roadside; GS= Gas Station; RA= Residential Area; TI=Traffic Intersection and BR= Busy Road 15

  16. Sampling Ambient Benzene Concentrations Sampling ambient benzene concentration levels was conducted using a portable Photo Ionization Detector (PID, Model PhoCheck 5000Ex, Ion Science Ltd. UK). ‘ PhoCheck ’ is a transportable gas -detector suitable for the detection of volatile organic compounds using a PID. The data were recorded at 10-minutes and the monitoring schedule in all stations followed 4-hourly samples during rush hours. Samplings were set up at about 1.5 m above the ground. 16

  17. Inverse Distance Weighting (IDW) Model Inverse Distance Weighting (IDW) as an spatial interpolation method was used to estimate the ambient benzene concentration levels in unmeasured areas. The IDW formulas are given as Equations 1 and 2. Z(x) = ∑ w i z i / ∑ w i (1) -p (2) w i = d i where Z(x) is the predicted value at an interpolated point, z i is the measured value at a known point, d i is the distance between point i and the prediction point, and w i is the weight assigned to point i . The greater weighting values are assigned to the values closer to the interpolated point, p is the weighting power that decides how the weight decreases by the distance increase [Xie Y. et al., 2011]. 17

  18. Assessment of Cancer Risk According to EPA’s IRIS, the aggregate population cancer risk of the total population in District1 was estimated using Eq. 3 [WHO,1993] [US EPA, 2007]: R = ( ∑ U C i P i ) / L (3) Where, R is the aggregate population excess cancer risk caused by one year exposure to benzene. U is the inhalation unit risk for benzene, C i is the individual exposure level in the region, P i is the population in each sampling station and L is the average lifetime, set as 70 years. 18

  19. Results and Discussion 19

  20. Monthly variation of ambient benzene concentration levels in District 1 in Tehran based on the field measurements 40 35 30 Concentrations of benzene (ppb) 25 20 15 10 5 0 Months Busy road Traffic Intersection Vicinity of the gas stations Residential area Roadside 20

  21. Seasonal average of ambient benzene concentration levels predicted by IDW model in District 1 in Tehran for Spring and Summer 21

  22. Seasonal average of ambient benzene concentration levels predicted by IDW model for District 1 in Tehran for Fall and Winter 22

  23. Annual average of ambient benzene concentration levels predicted by IDW model in District 1 in Tehran 23

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