Skip to main content
NCBI home page
Iranian Journal of Public Health logoLink to Iranian Journal of Public Health
. 2014 Apr;43(4):460–470.

Natural Airborne Dust and Heavy Metals: A Case Study for Kermanshah, Western Iran (2005–2011)

Meghdad PIRSAHEB 1, Aliakbar ZINATIZADEH 2, Touba KHOSRAVI 3, Zahra ATAFAR 4,5,*, Saeed DEZFULINEZHAD 6
PMCID: PMC4433727  PMID: 26005656

Abstract

Background

Dust pollution has become a serious environmental problem especially in recent decades. The present study aim was the investigation of the levels of PM10 concentration in Kermanshah, western Iran and also measured five important heavy metals (Pb, Cd, As, Hg and Cr) in some samples during 2005 to 2011.

Methods

A total 2277 samples were collected from air pollution measurement station belonging to the Department of Environment in Kermanshah. Furthermore, four samples were collected during dusty days to determine the selected heavy metals concentration. The samples were analyzed statistically using the SPSS Ver.16

Results

The highest seasonal average concentration in spring was recorded in 2008 with 216.63μg/m3, and the maximum values of 267.79 and 249.09μg/m3 were observed in summer and winter in 2009, respectively. The maximum concentration of 127.1μg/m3 was in autumn in 2010. The metals concentration (Pb, Cd, As, Hg and Cr) of samples were 42.32±5.40, 37.45±9.29, 3.51±2.07, 1.88±1.64 and 0μg/g in July, 2009, respectively.

Conclusion

According to National Ambient Air Quality of USEPA guidelines, the most days with non-standard, warning, emergency and critical conditions were related to 2009 (120 days) while the least polluted days were recorded in 2006 (16 days). There are concerns about the increasing frequency and intensity trend of dust storms in recent years as a result of special condition in neighboring Western countries which it could endanger public health and environment. All measured heavy metals except mercury was higher than the standard level of WHO and USEPA.

Keywords: Heavy metal, Dust, PSI, PM10, Iran

Introduction

In recent years, air pollution has become a serious environmental problem especially in industrialized and populated cities (1–3). Some activities such as solid waste burning, industrial processes, motor vehicles, fossil fuel combustion and other human activities can cause air pollution (4–6). Air qualities indexes (AQI) have been made for classifying the air quality measurements of several air pollutants. The index used by the United States Environmental Protection Agency (USEPA), which is ap proved by part 319 of the Clean Air Act, called the Pollutant Standards Index (PSI) (4, 7). The PSI is one of the environmental indicators used to express air quality by pollutants concentrations in the air. Environmental Protection Agency (EPA) uses the PSI measurements to inform the public about potential health effects due to air quality. PSI has been used all over the world since 1978 (8). The PSI is defined by five pollutants e.g. ozone (O3), particulate matter (PM10), carbon monoxide (CO), sulfur dioxide (SO2) and nitrogen dioxide (NO2) in which the National Ambient Air Quality Standards (NAAQS) have been established by the USEPA (4, 7).

Atmospheric particles (PM10) are significantly characterized by Air Quality Standards in many countries (9) (Table 1). It is clear that air quality can be influenced by the distribution of airborne ambient particulate matter in the environment. Therefore, the concentration of dust in the atmosphere is an essential parameter in climate variation. In Table 2, air quality is categorized into six types on the basis of dust concentration according to EPA guidelines (10). It is noted that air quality is also categorized into four groups on the basis of dust concentration according to the Environmental Protection Organization of Iran. In this basis, day of PSI>100 classified as non-standard quality, 100<PSI<250 indicates as warning, 250≤PSI<350 classified as emergency while PSI≥350 shows critical condition.

Table 1.

Annual mean PM10 of Iran cities in 2009, by WHO (http://envis.tropmet.res.in/Data_depository/annua_%20mean_concentrations)

Annual mean PM10 (Particulate matter with diameter of 10 μm or less), by city
Region Country City Annual mean PM10 (μg\m3) Year Number and location Temporal coverage Reference
EmrLMI Iran Tabriz 82 2009 2 urban traffic, 2 residential and commercial 67 Department of Environment (DOE)
EmrLMI Iran Mashhad 87 2009 3 urban trafiic, 2 residential and commerial, 1 urban and suburban 100 Department of Environment (DOE)
EmrLMI Iran Tehran 96 2009 9 urban traffic, 10 residential and commercial, 6 urban and suburban, 1 industrial 100 Department of Environment (DOE)
EmrLMI Iran Arak 102 2009 3 urbantraffic, 2 residential and commercial, 1urban and sub-urban 83 Department of Environment (DOE)
EmrLMI Iran Hamedan 103 2009 1 residential and commercial 57 Department of Environment (DOE)
EmrLMI Iran Esfahan 105 2009 2 urban traffic, 2 residential and commercial 100 Department of Environment (DOE)
EmrLMI Iran Qazvin 112 2009 1 urban traffic 20 Department of Environment (DOE)
EmrLMI Iran Kerman 125 2009 1 urban traffic, 1 residential and commercial 100 Department of Environment (DOE)
EmrLMI Iran Bushehr 125 2009 1 residential and commercial 20 Department of Environment (DOE)
EmrLMI Iran Ilam 129 2009 1 residential and commercial 100 Department of Environment (DOE)
EmrLMI Iran khoramabad 168 2009 1 urban traffic, 1 residential and commercial 48 Department of Environment (DOE)
EmrLMI Iran Qom 176 2009 1 urban traffic, 1 residential and commercial 15 Department of Environment (DOE)
EmrLMI Iran Uromiyeh 183 2009 1 urban traffic, 1 residential and commercial 100 Department of Environment (DOE)
EmrLMI Iran Yasouj 215 2009 1 urban green area 20 Department of Environment (DOE)
EmrLMI Iran Kermanshah 229 2009 1 residential and commercial 62 Department of Environment (DOE)
EmrLMI Iran Sanandaj 254 2009 1 urban traffic, 1 residential and commercial 35 Department of Environment (DOE)
EmrLMI Iran Ahwaz 372 2009 1 urban traffic and 3 residential and commercial 100 Department of Environment (DOE)
Open in a new tab

Table 2.

PM10 concentrations and its corresponding to PSI & Air Quality categories (15)

PM10 (µg/m3) PSI Category
0-54 0-50 Good
55-154 51-100 Moderate
155-254 101-150 Unhealthy for sensitive Groups
255-354 151-200 Unhealthy
355-424 201-300 Very Unhealthy
425-604 301-500 Hazardous
Open in a new tab

There are numerous sources which release aerosols to the atmosphere. On global scale, the major part of dust emission comes from arid and semi-arid regions (with annual rainfall under 200-250 mm) which is called ‘dust belt’(11) and it extends from the west coast of North Africa, the Middle East, central and south Asia to China(12). In recent years, the main sources of dust storms which influence the western and central regions of Iran are coming from the western and southern neighboring countries (Fig. 1) (13, 14).

Fig. 1.

Fig. 1

Open in a new tab

Sources of dust events in the west of Iran from 2000 to 2008(14)

Dust occurrences, are mostly the consequence of wind turbulent (16), which can move large amount of dust from arid regions and decrease visibility to less than 1km. This dust concentration can reach more than 6000 μg/m3 (17). According to WHO reports, Ahvaz and Sanandaj with PM10 concentration annual average of 372 and 254 μg/m3 were known as the first and the third polluted cities in all over the world, respectively (17).

Dust plays an important role in the atmosphere due to it’s severely effects on human health, environment and climate conditions (19–23). However, airborne dust is a significant issue in carrying and distributing pathogens, pollutants and heavy metals (5, 19–20).

Also it causes visibility reduction, possessions damage and human illnesses (24–25). Therefore, breathing dust particles can cause heart and respiratory troubles, acute and chronic headaches, allergies and skin diseases (23, 26). Some epidemi-ological studies revealed that the mortality rate in populated cities might be associated with PM10 and PM25 particles. Usually, every 10 μg/m increase in PM10 concentration could raise about 1% of the total daily mortality (9). Though, a certain level of heavy metals coupled with respirable PM10 is toxic and causes the health problems, because they can enter deeper parts of the lungs and are not washed out simply (21-22, 27). Thereby, some heavy metals, such as Pb, Co, Cd, Cu, and Cr, are recognized as a dangerous pollutant that it can accumulate in the body, a relatively long half-life. High concentrations of airborne heavy metals such as Pb, Cd, and certain persistent organic pollutants may also cause neurodevelopment and behavioral defects in children (23).

Therefore, the aim of this study was to investigate the levels of PM10 concentration in Kermanshah-Iran and compare the results with standard level, and also to measure five important heavy metals (Pb, Cd, As, Hg and Cr) in some samples, over a seven-year period (2005–2011).

Materials and Methods

Air quality data collection

A total 2277 samples (average of 24-hour) were collected daily from one air pollution measurement station (HORIBA model) inside Kermanshah City, Iran. The HORIBA’s Ambient Air Pollution station automatically determines and reports airborne particulate concentration amount utilizing the industry-proven beta ray reduction. This equipment has superior technology, field-proven reliability with outstanding sensitivity & accuracy at ppb levels belonging to the Kerman-shah’s Department of Environmental protection placed in the central part of the city determining the air quality principle over a seven-year period (April 2005-October 2011). A Small carbon-14 element releases a constant of high-energy electrons (known as beta rays) via a spot of clean filter tape, hourly. These beta rays are detected and counted by a sensitive scintillation detector to determine a zero reading. It repeatedly advances this spot of tape to the sample needle, where a vacuum pump pulls a measured amount of the air throughout the filter tape. Hourly, this spot is sited back among the beta source and the detector thereby causing a decrease of the beta ray signal which is used to measure the mass of the particulate matter on the filter tape (28).

The data files were collected through two-way serial port common terminal programs. Then, they were analyzed statistically for correlation between meteorological parameters and air pollution levels using SPSS Ver.16. To estimate air quality based on PM10, comparisons were performed with the USEPA standard index for month, season and year periods. Fluctuations in air quality indicated a significant difference (P<0.05) in PM10 emissions.

Analytical procedure

Four samples were collected during dusty days utilizing polyethylene wraps for determining the selected heavy metals concentration. The samples transferred to the laboratory in Public Health Faculty (Kermanshah Medical Sciences University) in order to analyze the heavy metals according to USEPA method for determining inorganic compounds in ambient air (29). Samples were digested on a hot plate for extracting heavy metals by adding 10 ml concentrated H2SO4 and 5 ml concentrated HNO3. Then, they were heated for 2 hours until the solution was cleared.

A blank filter paper was digested in the same way. The samples were filtered and diluted for measuring heavy metals using Inductive Coupled Plasma (ICP) (Perkin Elmer Inc, USA, Optima 7300 DV, optical Emission Spectrometer, serial number 077C9081402).

Results and Discussion

Figures 2-5 depicts the number of non-standard, warning, emergency and critical days during 7 years (2005–2011), respectively. As shown in Table 5, according to National Ambient Air Quality Standards (NAAQS) USEPA, the most days with non-standard, warning, emergency and critical conditions were related to 2009 by 120 days which is one third days of the year while the least polluted days were recorded for 2006 by 16 days. The results showed that from 2006 onwards, the intensity and frequency of non-standard days have been increased. Universally, many cities regularly monitor the air quality using accurate devices to measure and record air pollution concentrations every moment to show the level of population exposure to the pollutants. This strategy helps us to compare the air quality with standards, find a proper plan for pollution reduction and provide long term and short term controlling approaches, (30–32). However, the increased dust storm and intensification of the number of warning, emergency and critical days in western provinces particularly Kermanshah, have made living conditions difficult, which has caused an increase in migration from Kermanshah to the central regions and neighboring provinces that subsequently causes other social and economical problems.

Fig. 2.

Fig. 2

Open in a new tab

Number of non-standard days during 2005-2011.

Fig. 5.

Fig. 5

Open in a new tab

Number of critical days during 2005-2011

Table 5.

Number of non standard daysduring a 7-year period

Year Spring Summer Autumn Winter Total
2005 12 29 7 7 55
2006 4 9 2 1 16
2007 7 19 2 13 41
2008 46 40 9 17 112
2009 38 59 10 13 120
2010 27 19 18 9 73
2011 34 31 8 6 79
Total 168 206 56 66 496
Open in a new tab

Fig. 3.

Fig. 3

Open in a new tab

Number of warning days during 2005-2011

Fig. 4.

Fig. 4

Open in a new tab

Number of emergency days during 2005-2011

Table 3 shows monthly PM10 average concentration during a 7-year period. The PM10 daily mean concentration ranged from 6.96 in 2010 up to 2817 μg/m3 in 2009. Average monthly concentrations of particles showed that the dust concentration began to increase in late March so that its maximum level reached in July and gradually begins to decline and the lowest was observed in January (Table 4). The seasonal average concentration of dust also represented in Table 4. According to dust concentration changes from 2005 up to 2011 and seasonal mean concentration, the highest seasonal average concentration of dust in the spring recorded in 2008 with the concentration of 216.63 μg/m3. In summer and winter seasons, the maximum values were related to year 2009 with the concentration of 267.79 and 249.09 μg/m3 respectively, while the maximum concentration in autumn was obtained 127, 11 μg/m3 for 2010. The maximum seasonal mean concentration of dust occurred in summer, which was attributed to turbulent in the atmosphere, reduced precipitation and drought. So that strong winds transported the dust from Iraq and Kuwait to the west and south parts of Iran. Minimum dust concentration in terms of PM10 has been observed in autumn. It might be due to an increase in air relative humidity and rainfall. Statistic analysis also indicated that there were significant differences between dust concentration and saturated air humidity (P<0.05). According to NAAQS, annual maximum permissible concentration of PM10 is 50 μg/m3 (32).

Table 3.

Seasonal PM10 average concentration during a 7-year period

Season Year Total
2005 2006 2007 2008 2009 2010 2011
Spring 110.68 91.64 127.86 216.63 166.80 130.32 178.35 164.04±43.29
Summer 163.76 117.63 136.50 200.68 267.79 149.33 143.42 168.44±50.86
Autumn 111.69 76.29 102.61 101.45 96.54 127.11 84.02 99.95±16.88
Winter 84.70 66.83 121.07 111.51 249.04 83.55 102.15 116.98±61.05
Yearly Average 117.7± 33.14 88.09± 22.18 122.01 ±14.39 157.56 ±59.49 195.04 ±78.69 122.57 ±27.80 126.98 ±42.32 132.85±30.41
Open in a new tab

Table 4.

Monthly PM10 average concentration during a 7-year period

Month Sample frequency Average Maximum concentration Minimum concentration
April 186 139.94±194.10 1953 24.41
May 186 124.68±88.15 725.3 21.01
June 208 175.71±152.56 1003 54.01
July 209 222.12±291.67 2817 56.05
August 214 148.21±92.484 925.4 7.40
September 204 134.90±94.66 1061 6.96
October 210 128.05±47.73 416.2 50.06
November 210 91.11±37.92 223.1 19.99
December 205 80.20±39.68 384.1 14.71
January 155 66.26±24.74 152.7 18.11
February 122 88.92±76.57 464 13.25
March 168 157.72±217.23 2500 32.26
Total 2277 129.82±44.28 2817 6.96
Open in a new tab

In this basis, during the years 2005-2011, respectively 55, 16, 41, 112, 120, 73 and 79 days have been reported as un healthy monitoring period, the dust concentration was reported 2 to 3 times more than the annual maximum primary standard. However, it should be noted that PM10 24-Hour primary concentration was 10 to 20 times more than NAAQS (150 μg/m3). The records imply high air pollution level in Kermanshah. From an assessment reported in the literature, the rank of Kermanshah between 10 polluted cities in the world is 6th after Ahwaz (Iran), Ulan Bator (Mongolia), Sanadaj (Iran), Ludhiana (India), Quetta (Pakistan) (34). With a closer look it becomes clear that 4 cities from 10 polluted city in the world belongs to Iran. Considering that Kermanshah is an industrial city. The interaction between chemical pollutant and dust can be doubled concerning, especially in autumn and winter which inversion may occur frequently. Also as showed in Table 1 from the WHO database, annual mean PM10 concentration in 2009 in Kermanshah has been 229 μg/m3 (18). The world average PM10 levels by region ranged from 21 to 142 μg/m, by the way world average is 71 μg/m3. Hence Kermanshah is 3.2 times more polluted than the world average (35) . Most dust storms in south-west of Iran are originated from Iraq, Syria and north of Saudi Arabia during the recent decays (13). In addition they approved that from 2005 up to now, the frequency and the intensity of dust storms are increasing about 20 to 30 percent as a result of drought phenomenon, abuse of natural sources and dam construction on Tigris and Euphrates, especially in neighboring countries such as Iraq (36) . Similar findings were reported from different researches (36–39). Sudan, Iraq, Saudi Arabia and the Persian Gulf, are the areas that stated the most reported incidence of dust storms event. Dust storms in Iran, north-eastern of Iraq and Syria, the Persian Gulf and southern Arabian Peninsula are more common in summer (13). Dust storms originated from the north of Africa are increasing in the north of Saudi and Iraq and their developments reach the north of Persian Gulf and Khuzestan Province in Iran. Iraq and Turkey are the generation source of the dust storms which affect the west of Iran. The storm following a cold winter through Turkey entered Iraq and Kuwait and after it was greatly intensified, afflicted the western portions of Iran. Storms come from northern Africa and Saudi in summer and early autumn and affect the Khuzestan Province and the south of Iran (40).

According to the Zeng and Yoon forecasting, Central Africa, southwest of Saudi, northwest of Iran, the west of Caspian Sea, Iraq, Kuwait, and the east of Mediterranean Sea and some other areas of the world will transform into desert in the future. Therefore, dust storms from the west will be more in the future with many effects upon the western provinces of Iran (41).

Dust has a substantial role in the atmosphere; it intensely affects human health, natural ecosystems and climate. Wind-blown dust is an effective factor for the transport of pathogens and pollutants (18, 19). Another important aspect associated with the dust phenomenon which may be noticed less is the heavy metals contents of the particulate matters. They can diffuse into the lungs along with dust and seriously endanger people’s health. The metals concentration (Pb, Cd, As, Hg and Cr) of the dust samples in July of 2009 is shown in table 6. From the Table 6, average concentrations of the metals in the dust samples were 42.32±5.40, 37.45±9.29, 3.51±2.07, 1.88±1.64 and 0μg/g. It can be noted that the concentration of lead and chromium of all collected samples were the most whereas, the concentration of mercury was zero which it could be due to the volatility of this metal. The concentrations of all measured heavy metals except mercury were higher than the standard levels determined by WHO and USEPA (30-32, 36-39). Concentration of lead was very high among all measured metals that could be due to the area with lead background or Euphrates and Tigris rivers sediments with industrial origin or fertilizers and pesticide residues in farm land. Figure 6 shows the rate of intake for the heavy metals μg/h) received by humans.

Table 6.

Heavy metal concentration in the dust samples

Metal Sample µg/l Average±δ µg/g Average±δ
Cr 1 869.5 936.2±2.33 34.78 37.45±9.29
2 693.3 27.73
3 1250 50
4 932 37.28
Cd 1 13.47 47.09±41.09 0.54 1.88±1.64
2 10.3 0.41
3 75.5 3.02
4 89.1 3.56
Pb 1 992.5 1058.12±134.96 39.7 42.32±5.40
2 915 36.6
3 1099 43.96
4 1226 49.04
As 1 34.15 87.78±51.97 1.36 3.51±2.07
2 54 2.16
3 120 4.8
4 143 5.72
Hg 1 0 0 0 0
2 0 0
3 0 0
4 0 0
Open in a new tab

Fig. 6.

Fig. 6

Open in a new tab

Intake rate for heavy metals (April 2011)

From an estimation reported, 3.2 million people died in 2010 have been because of the poisonous effects of outdoor air pollution. Two-thirds of those killed by air pollution lived in Asia, where air quality continues to get worse (42). Thereby, uptake these toxic metals (Pb, Cr and Cd) through inhalation could be very harmful for human health especially in vulnerable groups (children and elderly people). These effects were discussed only on dust and heavy metals, but the effects of these particles and associated metals and other contaminants such as radioactive materials, bacteria, fungi and ... on the human health, economic, environmental, social (such as migration) and the psychological people need to be precisely studied.

Conclusion

The highest seasonal average concentration of PM10 pollutant was in the spring season in 2008, summer and winter in 2009 and autumn in 2010, respectively. Therefore, the decline in such releasing is crucial and requires extensive and substantial collaboration between the government of Iran and the neighboring countries to control dust in west part of the Iran by using suitable methods to maintaining soil moisture and lessen the spread of desertification.

Ethical considerations

Ethical issues (Including plagiarism, Informed Consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, etc) have been completely observed by the authors.

Acknowledgements

The authors wish to acknowledge the invaluable cooperating and supporting the deputy of Kermanshah’s Department of Environment and Meteorological Organization of the Kermanshah Province for facilitating the issue of this project. The authors declare that there is no conflict of interests and financial source for this study.

References

  1. Naddafi K, Nabizadeh R, Soltanianzadeh Z, et al. (2006). Evaluation of Dustfall in the Air of Yazd. Iranian Journal of Environmental Health and Sciences Engineering, 3(3): 161–168. [Google Scholar]
  2. Nikravan M, Husseini E, Hashemi SH (2010). Pollutant Standard Index (PSI), Comparing the published and real values in Tehran, 5th National Congress on Civil Engineering. Ferdowsi University of Mashhad, Mashhad, Iran: p. 8. [Google Scholar]
  3. Shah MH, Shaheen N, Jaffar M, et al. (2006). Spatial variations in selected metal contents and particle size distribution in an urban and rural atmosphere of Islamabad, Pakistan. Journal of Environmental Management, 78: 128–137. [DOI] [PubMed] [Google Scholar]
  4. Mayer H (1999). Air pollution in cities. Atmospheric Environment, 33: 4029–4037. [Google Scholar]
  5. Farahmandkia Z, Mehrasbi MR, Sekhavatjou MS (2010). Relationship between concentrations of heavy metals in wet precipitation and atmospheric PM10 particles in zanjan, Iran. Iranian Journal of Environmental Health and Sciences Engineering, 8(1): 49–56. [Google Scholar]
  6. Cairncross EK, John J, Zunckel M (2007). A novel air pollution index based on the relative risk of daily mortality associated with short-term exposure to common air pollutants. Atmospheric Environment, 41: 8442–8454. [Google Scholar]
  7. Vallero, D A (2008). Fundamentals of Air Pollution. 4th ed, Elsevier, San Diego, California, P. 942. [Google Scholar]
  8. Rovin J (1998). Laws of Order, What Is The Pollutant Standard Index?. available from: http://www.enotes.com/science/q-and-a/what-pollutant-standard-index-288639.: UXL Science Fact Finder, Gale Cengage; p. 246. [Google Scholar]
  9. Chen SJ, Hsieh LT, Tsai CC, et al. (2003). Characterization of atmospheric PM10 and related chemical species in southern Taiwan during the episode days. Chemosphere, 53: 29–41. [DOI] [PubMed] [Google Scholar]
  10. Agency, U.S.E.P (1998). Guideline for Reporting of Daily Air Quality - Pollutant Standards Index (PSI), Office of Air Quality Planning and Standards Research Triangle Park: North Carolina: p. 28. [Google Scholar]
  11. Prospero JM, Ginoux P, Torres O, et al. (2002). Environmental characterization of global source of atmospheric soil dust identified with the nimbus 7 total ozone mapping Spectrometer (TOMS) absorbing aerosol product. Journal of Geophysical Research, 40(1): 1002. doi: 10.1029/2000RG000095. [DOI] [Google Scholar]
  12. Escudero M, Stein A, Draxler RR, et al. (2006). Determination of the contribution of northern Africa dust source areas to PM10 concentrations over the central Iberian Peninsula using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) model. Journal of Geophysical Research: Atmospheres, 111(D6). [Google Scholar]
  13. Gerivani H, Lashkaripour GR, Ghafoori M, et al. (2011). The Source of Dust Storm in IRAN: A Case Study Based on Geological Information and Rainfall Data Carpathian. Journal of Earth and Environmental Sciences, 6(1): 297–308. [Google Scholar]
  14. Darvishi Boloorani A, Nabavi SM, Azizi R, et al. (2012). The investigation of dust storm entering the west of Iran using remotely sensed data and synoptic analysis, 1st International Forum On Natural Airborne Dust in Iran, Kermanshah. [Google Scholar]
  15. WHO (2006). Final Revision to the Ambient Air Quality Standards for Particulate Pollution. World Health Organization, United States of America. [Google Scholar]
  16. Miller SD, Kuciauskas AP, Liu M, et al. (2008). Haboob dust storms of the southern Arabian peninsula. Journal of Geophysical Research: Atmospheres, 113(D1). [Google Scholar]
  17. Song Z, Wang J, Wang S. (2007). Quantitative classification of northeast Asian dust events. Journal of Geophysical Research: Atmospheres, 112(D4). [Google Scholar]
  18. WHO (2011). Urban outdoor air pollution database. Department of Public Health and Environment, World Health Organization, Geneva, Switzerland: Available from: http://www.who.int/phe/health_topics/outdoorair/data-bases/OAP_database.xls [Google Scholar]
  19. Shinn EA, Smith GW, Prospero JM, et al. (2000). African dust and the demise of Caribbean coral reefs. Geology Research Letters, 27(19): 3029–3032. [Google Scholar]
  20. Wang Y, Zhuang G, Tang A, et al. (2007). The evolution of chemical components of aerosols at five monitoring site of China during dust storms. Atmospheric Environment, 41: 1091–1106. [Google Scholar]
  21. Wang Q, Bi XH, Wu JH, et al. (2013). Heavy metals in urban ambient PM10 and soil background in eight cities around China. Environ Monit Assess, 185(2): 1473–1482. [DOI] [PubMed] [Google Scholar]
  22. Fang GC, Huang YL, Huang JH, et al. (2012). Dry deposition of Mn, Zn, Cr, Cu and Pb in particles of sizes of 3 µm, 5.6 µm and 10 µm in central Taiwan. Journal of Hazardous Materials, 203–204: 158–168 DOI: 10.1016/j.jhazm-at.2011.11.098. [DOI] [PubMed] [Google Scholar]
  23. Leili M, Naddafi K, Nabizadeh R, et al. (2008). The study of TSP and PM10 concentration and their heavy metal content in central area of Tehran, Iran. Air Qual Atmos Health, 1(3): 159–166. [Google Scholar]
  24. Chan YC, Mctainsh G, Leys J, et al. (2005). Influence of the 23 October 2002 dust storm on the air quality of four Australian cities. Water, Air and Soil Pollution, 164(1–4): 329–348. [Google Scholar]
  25. Hacker R, Stull S, Sakiyama D, et al. (2001). Long-range transport of Asian dust to the Lower Fraser Valley, British Columbia, Canada. Journal of Geophysical Research, 106(D16): 18361–18370. [Google Scholar]
  26. Griffin DW, Kellogg CA (2004). Dust Storms and Their Impact on Ocean and Human Health: Dust in Earth's Atmosphere. EcoHealth, 1(3): 284–295. [Google Scholar]
  27. Chaudhari PR, Gupta R, Gajghate DG, et al. (2012). Heavy metal pollution of ambient air in Nagpur City. Environ Monit Assess. 184(4): 2487–2496. [DOI] [PubMed] [Google Scholar]
  28. Ananymous. HORIBA, Continuous Particulate Monitor, model APDA-371. Available from: http://www.deltatech.ch/up/ktml/files/produkte/Brochure%20APDA%20371_en.pdf [Google Scholar]
  29. USEPA United States EPA (1999). Method for the determination of inorganic compounds in ambient air. office of research and development, Washington, DC: Available from: http://www.epa.gov/ttnamti1/files/ambient/ino-rganic/iocompen.pdf [Google Scholar]
  30. Koenig JQ, Mar JF (2000). Sulphur dioxide: evaluation of current California air quality standards with respect to protection of children, Available from: www.oehha.ca.go-v/air/pdf/oehhaso2.pdf. [Google Scholar]
  31. World Health Organization Regional Office for Europe (2000). Air Quality Guidelines for Europe. 2nd ed. Copenhagen, Denmark: WHO Regional Publications, European Series, No. 91. [PubMed] [Google Scholar]
  32. Gent JF, Triche EW, Holford TR, et al. (2003). Association of low-level ozone and fine particulates with respiratory symptoms in children with asthma. J Am Med Ass, 290(14): 1859–1867. [DOI] [PubMed] [Google Scholar]
  33. Esworthy R (2013). The National Ambient Air Quality Standards (NAAQS) for Particulate Matter (PM): EPA's 2006 Revisions and Associated Issues, Congressional Research Service 7–5700, www.crs.gov, RL34762, 2010. Available from: http://www.fas.org/sgp/cr-s/misc/R42934.pdf [Google Scholar]
  34. Walsh B (2011). The 10 most air polluted cities in the world. Available from: http://science.time.com/2011/09/27/the-10-most-air-polluted-cities-in-the-world/ [Google Scholar]
  35. Anonymous (2012). 7 million deaths annually linked to air pollution. Available from: http://www.who.int/phe/health_topics/outdoorair/databases/en/ [PubMed] [Google Scholar]
  36. Jalali N, Davoudi MH (2008). Inspecting the originsand causes of the dust storms in the Southwest andWest parts of Iran and the regions affected. Internal reports of Soil Conservation and Watershed anagement Research Institute (SCWMRI), Iran. [Google Scholar]
  37. Esmaili O, Tajrishy M, Daneshkar Arasteh P (2006). Results of 50 year ground-based measurements in comparison with satellite remote sensing of two prominent dust emission sources located in Iran. Proceedings of SPIE Europe in Conference on Remote Sensing of Clouds and the Atmosphere XI, Stockholm, Sweden. 6362, 1–12. [Google Scholar]
  38. Ginoux PM, Chin M, Tegen I, et al. (2001). Sources and global distributions of dust aerosols simulated with the GOCART model. J Geophys Res, 106: 20255–20273. [Google Scholar]
  39. Kutiel H, Furman H (2003). Dust Storms in the Middle East: Sources of Origin and their Temporal Characteristics. SAGE journals, Indoor and Built Environment. 12(6): 419–426. [Google Scholar]
  40. Ghahroudi Tali M, Nezammahalleh M (2012). An Investigation On The Origins Of Dust Storms And Their Development Over Iran, 1st International Forum On Natural Airborne Dust in Iran, Kermanshah. [Google Scholar]
  41. Zeng N, Yoon J (2009). Expansion of the world's deserts due to vegetation-albedo Feedback under global warming. Geophysical Research Letters. 36(17): DOI: 10.1029/2009GL039699. [DOI] [Google Scholar]
  42. Upton J (2013). Where is the worst air in the world? Available: http://www.slate.com/articles/health_and_scienc-e/medical_examiner/2013/03/worst_air_pollution_in_the_world_beijing_delhi_ahwaz_and_ulaanbaatar.html [Google Scholar]

Articles from Iranian Journal of Public Health are provided here courtesy of Tehran University of Medical Sciences

RESOURCES