Investigation variations of particulate matter and volatile organic compounds concentration in gorgan city and the effect of atmospheric factors in emission these pollutants: Estimation of spatial distribution of air quality index by GIS
Mina Ghahrchi1, Edris Bazrafshan1, Yousef Kor2, Mohammad Reza Khani3, Mohammad Sarmadi1, Yousef Dadban Shahamat4
1 Department of Environmental Health Engineering, School of Health; Health Sciences Research Center, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran
2 Environmental Health Research Center, Golestan University of Medical Sciences, Gorgan, Iran
3 Water Purification Research Center; Department of Environmental Health Engineering, Faculty of Health, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
4 Environmental Health Research Center, Department of Environmental Health Engineerin, Faculty of Health, Golestan University of Medical Sciences, Gorgan, Iran
|Date of Submission||23-Dec-2019|
|Date of Acceptance||18-Apr-2020|
|Date of Web Publication||31-May-2020|
Dr. Yousef Dadban Shahamat
Department of Environmental Health Engineering, Environmental Health Research Center, Golestan University of Medical Sciences, Km 4th Gorgan, Sari Road, Gorgan City, Golestan
Source of Support: None, Conflict of Interest: None
Aims: In this study, the concentration of particulate matter (PM)2.5and PM10particles and volatile organic compounds (VOCs) was measured from July of 2016 to June of 2017 in Gorgan City and the values of the air quality index (AQI) for particles were calculated and investigated. Materials and Methods: The concentrations of PM2.5, PM10, and VOCs were measured at eight stations in the city, and the relationship between different atmospheric conditions and the concentration of pollutants was assessed by statistical tests of variance analysis. Furthermore, the AQI values for the particles were measured, and based on the values of this index, using ArcGIS 10.3 software (ESRI Compony, USA), the zoning maps were prepared. Results: The average concentrations of PM2.5, PM10, and VOCs in the eight stations were 30.6 μg/m3, 41.3 μg/m3, and 0.82 ppm, respectively. The average concentration of PM2.5and VOCs is higher than Environmental Protection Agency and clean air standards. Analysis of variance test was showed that the concentration difference of particles in different stations was not significant (P > 0.05), but for VOCs concentration, there was a statistically significant difference between the station of Seyed Masoud restaurant and Terminal square (P < 0.05). Furthermore, the results were showed that the temperature has an inverse relationship with the concentration of pollutants. AQI values for PM2.5in the cold months of the year and in the central parts of the city were in the range of 101–150. The maximum AQI for PM10was equivalent to 55, which was in December 2016. Conclusion: The air quality of Gorgan City was not in desirable conditions due to the high concentration of pollutants, especially PM2.5and VOCs, and should be taken control proceedings.
Keywords: Air pollution, air quality index, atmospheric factors, GIS, particles, volatile organic compounds
|How to cite this article:|
Ghahrchi M, Bazrafshan E, Kor Y, Khani MR, Sarmadi M, Shahamat YD. Investigation variations of particulate matter and volatile organic compounds concentration in gorgan city and the effect of atmospheric factors in emission these pollutants: Estimation of spatial distribution of air quality index by GIS. Int J Env Health Eng 2020;9:3
|How to cite this URL:|
Ghahrchi M, Bazrafshan E, Kor Y, Khani MR, Sarmadi M, Shahamat YD. Investigation variations of particulate matter and volatile organic compounds concentration in gorgan city and the effect of atmospheric factors in emission these pollutants: Estimation of spatial distribution of air quality index by GIS. Int J Env Health Eng [serial online] 2020 [cited 2020 Oct 26];9:3. Available from: https://www.ijehe.org/text.asp?2020/9/1/3/285522
| Introduction|| |
With the industrialization of societies, air pollution has become a major issue in developed and developing countries., In many developing countries, public health concerns about air pollution are increasing because the population and industry are growing rapidly. On the other hand, many of recent studies have clearly shown that air pollution can be have adverse effects on human health.,, Among the pollutants in the air today, suspended particles and volatile organic compounds (VOCs), especially in large cities, are of great importance. The total suspended particles, the particles smaller than 2.5 μ and smaller than 10 μ, are called TSP, particulate matter (PM)2.5 and PM10, respectively., PM2.5 and PM10 are important in terms of health. Infection of the upper respiratory tract, pneumonia, pulmonary inflammation, cancer, bronchitis, dyspnea, and heart disorders are the major side effects of suspended particulates on humans., The VOC compounds are carbon contaminants that have high vapor pressure at room temperature. These compounds have a natural and artificial origin. The forest and volcano are natural resources and combustion, industrial, and pharmaceutical processes, and petroleum and gas industries are artificial sources. The benzene, toluene, ethylbenzene, and xylene (BTEX) compounds are from of the most hazardous VOCs, which come out of the car's exhaust. This compound contains BTEX hydrocarbons., Cancer, genetic mutation, eye irritation, dizziness, and headaches and even loss of short-term memory are the effects of prolonged exposure to VOCs. According to the Environmental Protection Agency (EPA) standard, the maximum annual permissible concentrations of PM2.5 and PM10 are 12 and 50 μg/m3, respectively. Furthermore, based on clean air standards, the maximum permissible concentration for 3-hexposure to VOCs is 0.24 ppm., EPA, in spite of the lack of uniformity and diversity of pollutants, in addition to determination of different standards, has set indexes for the expression of air quality and for public information purposes. One of these indicators is the air quality index (AQI), which used widely throughout the world over the last three decades. The level of AQI is determined with the measurement of six pollutants includes concentration SO2, NO2, O3, PM2.5, PM10, and CO.,
Given that the importance of air pollution issues, the aim of this study was to measure the concentrations of PM2.5, PM10, and VOCs in Gorgan City air and to investigate the effect of atmospheric factor on the concentration of these pollutants in 1 year (2016–2017). Furthermore, to determine the air quality of Gorgan, AQI, which is one of the conventional air quality indices, was calculated for the PM, and the results were presented as zoning maps.
| Materials and Methods|| |
Specifications of the area studied
Golestan Province with an area of 20437.77 km2 constitutes for 1.3% of the total area of the country. The climate condition in different regions of this province is variable so that in the Southern regions of the province, the climate is mild and humid, and in its middle and northern regions, the climate is dry and semi-arid. Gorgan is located in the Southern part of the province and has a moderate climate. The area of this city is 1615.8 km2 (7.91% of the province's area), and its longitude is 54°, 12.9´ to 54°, 44.9´ East and 36° 30.46´ to 36°, 58.8´ North latitude. The average temperature is in the range of 6°C–28.7°C, and the average annual precipitation is about 39.25 mm.,,
Research methodology and sampling method
To survey the variation of PM2.5, PM10, and VOC concentrations in the air of Gorgan, the eight measurement stations were considered in the study area, which are shown in [Figure 1].
|Figure 1: Location of Gorgan City relative to the whole country and sampling stations in Gorgan City|
Click here to view
This study was a descriptive cross-sectional wherein PM2.5, PM10, and VOCs concentrations were measured from July 2016 to June 2017. Sampling was performed momentary, which for each contaminant monthly three samples per station and a total of 288 samples were taken. It should be noted that the sampling time was 10 AM on the 10th, 20th, and last days of each month. According to the standard 1/1/2, the samples were taken at a distance of 1 m from the ground and at a distance of 1 m from environmental barriers for 2 h.
The samples of PM were taken in different atmospheric conditions using the HAZ-Dust Portable Device (EPAM-5000, SKC manufactured in the United States [USA]). This device has capable of sampling ambient dust at sizes of 1, 2, 5, and 10 mg/m3, and for this purpose, it has three fraternity sample filters in said sizes. First, we turn on the device with a button on the right side of the home screen. The home screen appears, and we select the Special Function option. The next page has four options that choose the system option. On the third page, we select an extended option. In the next step, we select size, and depending on the size of the sampling, we choose one of the sizes 1, 2, 5, and 10 mg/m3. Then, go to the next page and select Run and start sampling. By pressing the Enter key on the keyboard, the results are stored in memory by specifying the sample number. The VOCs were also the same way measured using a PhoCheck portable device (Made in Ireland).
Data analysis and statistical tests
The statistical population was the same samples taken from the air, which have been taken at different times and conditions. After doing the experiments and obtaining the results from the Excel, SPSS software was used to analyze the hypotheses and draw charts and data categorization. In this research, the significance level of the difference in concentrations of pollutants in different stations was determined using one-way analysis of variance (ANOVA test) and analyzed. Also, for determined correlation between of pollutants and some of the atmospheric condition was used from the ANOVA test. In this case, there is an independent qualitative variable (multilevel) and a dependent variable.
Furthermore, based on the normality of the data, the correlation between the groups of pollutants and their relationship with other meteorological factor, means temperature, was calculated with the Pearson Correlation test. This correlation coefficient, which is the most common type of correlation, indicates the linear relationship between the quantities.
Based on the results of the measurements for two particles PM2.5 and PM10 in the whole city of Gorgan, the urban AQI for these two particles was calculated using the AQI formula.
Preparation of zoning maps
Finally, due to the local specification of sampling stations, using GPS, the geographic coordinates of the sampling points were determined, and using the Arc GIS ver 10.3 software, contamination distribution according to the AQI, mapping was prepared. Furthermore, VOC annual concentrations were zoned at different stations in Gorgan. Due to station dispersal and sampling-restricted points, the inverse distance weighted model was selected.,
| Results|| |
PM2.5, PM10, and VOC concentrations at eight stations over a period of 1 year from July 2016 to June 2017 were measured, and the effects of various weather parameters such as sunny weather, wind speed, and air temperature on the concentration of these pollutants were studied. The results are shown in [Table 1], which were described in the following.
|Table 1: Average monthly concentration of PM2.5, PM10, and volatile organic compounds at different stations in Gorgan City|
Click here to view
Concentration of particulate matter2.5, particulate matter10, and volatile organic compounds in different station
The average particle concentration and VOC concentration at each station during a year are explained in [Figure 2], respectively. The average concentrations of PM2.5, PM10, and VOC contaminants have fluctuated at different stations. However, by doing the ANOVA test, it can be found that the concentration of PM2.5 and PM10 between different stations did not differ significantly (P value: 0.58 and 0.28 and degree of freedom [df]: 88). Totally, according to the results, the highest concentrations of PM2.5 were measured at the Shahrdary Square station in the city center, equivalent to 36 μg/m3, and the lowest in the Terminal Square in the North of the city, equivalent to 26 μg/m3, which is more than the amount of permissible determination by the EPA. Meanwhile, the highest concentration of PM10 was observed at Seyed Masoud restaurant station, equivalent to 52 μg/m3, and the lowest was at the Imamzadeh Abdullah station in the North of the city and equivalent to 32 μg/m3.
|Figure 2: (a) The average PM2.5 and PM10(as μg/m3) concentrations in sampling station, (b) The average volatile organic compounds (as mg/L) concentration in sampling station. PM: Particulate matter|
Click here to view
In the case of VOC concentration, the results were showed that the maximum concentration of these compounds was measured at Seyed Masoud restaurant station, about 0.94 ppm. The result of the ANOVA test for determination of VOCs concentrations difference at the eight stations was showed that there was a significant difference in the amount of VOC in different stations. By doing the Tukey test for various stations, this difference was Between to the Seyed Masoud restaurant station and terminal square (P < 0.05).
[Figure 3] shows the zoning of different stations in the city by GIS according to the average annual concentration of VOCs. Regarding [Figure 3], it can be finding that the Seyed Masoud restaurant station had the maximum and Terminal Square station had the minimum concentration of VOC.
|Figure 3: The zoning of different stations in Gorgan based on the annual concentration of volatile organic compounds with GIS|
Click here to view
The effect of meteorological parameters on the concentration of pollutants
In this section, using statistical analyzes, the relationship between atmospheric conditions with concentrations of PM2.5, PM10, and VOCs has been investigated, which the following is discussed in each case.
Effect of atmospheric conditions
The atmospheric conditions studied include sunny, cloudy, and semi-cloudy weather conditions. The ANOVA analysis with df 95 was showed that the atmospheric conditions do not affect statistically the concentration of particulate pollutants and VOCs (P > 0.05).
Effect of intensity of wind
The effect of wind intensity (no wind, a little wind 8–11 km/h, and high wind) on the concentration of PM2.5, PM10, and VOCs pollutants was evaluated using ANOVA test, which by performing this test, the amount of P value whit df 95 was obtained as 0.48, 0.84, and 0.82, respectively. These results have indicated that the intensity of the wind does not correlate with the concentration of pollutants. Furthermore, the annual wind roses of Gorgan City were prepared during this time period, which is visible in [Figure 4]. According to [Figure 4], the prevailing wind direction was from the West and Southwest, in which 31.3% of the wind was calm.
Effect of air temperature
Since temperature is a quantitative parameter, Pearson correlation test was used to determine its effect on the concentration of PM2.5, PM10, and VOCs. Furthermore, the correlation between pollutants was investigated by this analysis. The results were shown that the temperature has an inverse effect on the concentration of the three pollutants (P < 0.01). That's mean, by decreasing the temperature, the concentration of PM pollutant and VOCs was increased. Due to the values of the correlation coefficient for PM2.5, PM10, and VOC pollutants which are 0.3, 0.26, and 0.7, respectively, the intensity of temperature effect on VOCs was higher.
Another result that can be found from the Pearson correlation analysis was that the concentrations of PM2.5, PM10, and VOC pollutants are statistically related (P < 0.01).
The air quality index values for particulate matter2.5 and particulate matter10
The AQI index for PM2.5 and PM10 particles was calculated in different and the results are presented in [Figure 5]. According to the standard, to calculate the values of AQI, these two particle concentration is measured in μg/m3/day. As the results have shown, the highest AQI is for PM2.5 particles, which occurred in the months of November, December, and January. The AQI for these months was 117, 148, and 102, respectively, and according to [Table 2], these values are in the unhealthy range for sensitive groups.
|Figure 5: The city air quality index for PM2.5and PM10particles in different months in Gorgan city. PM: Particulate matter|
Click here to view
In this study, also the average annual concentration of PM2.5 and PM10 was measured at different stations in Gorgan City, then the AQI index for these two particles was calculated. Finally, by using the Arc GIS, zoning maps were prepared which is visible in [Figure 6].
|Figure 6: Zoning different stations based on air quality index values using GIS|
Click here to view
| Discussion|| |
Concentration of particulate matter2.5, particulate matter10, and volatile organic compounds in different stations
Recently, air pollution is a serious threat to humans and the environment. PM and VOCs are significant air pollutants that any creature is exposed to serious damage by breathing air containing these pollutants in amounts of more than permissible limit and long term.,
Based on the results, the maximum concentration of PM2.5 and PM10 was measured in the Center and Southern region of city, which are the busiest areas of the city. Since the transportation, fossil fuel motors, and traffic are from the main factors to create of PM, the results obtained were acceptable.
In this regard, Shahbazi et al., by monitoring the particle concentration in the Tehran air, reported increased concentrations of PM in the high-traffic areas of the city. Furthermore, according to the research of Hoek et al., the density of buildings and the type of land use have affected the amount of these pollutants. In addition to these reasons, the higher humidity in the Southern areas of the Gorgan City leads to in the formation of secondary aerosols, which may be the reason for the increase of PM10 in these areas. However, in cities with hot and dry climates such as Zahedan City, the adverse effect of humidity on air particle concentration has been reported.
As mentioned, the concentration of PM2.5, from the acceptable values, was exceeded. Due to the fact that the major particles that Precipitate in the alveolus and pass through the lung wall into the bloodstream is PM2.5, the concentration control of this pollutant in the air is essential. Therefore, concentration control of these particles is essential.
The reason for the increased concentration in Seyed Masoud restaurant VOCs can be attributed to forest density and fire in these areas that are natural sources of VOC production., However, in the city center, artificial resources such as transportation and traffic can be the main reasons for the increase in VOC concentration.
The effect of meteorological parameters on the concentration of pollutants
The results of the effects of atmospheric on the concentrations parameters such as sunny or cloudy weather, wind speed, and air temperature variations of PM2.5, PM10, and VOC were different.
The literature in different cities shows that variations in the concentration of pollutants are strongly dependent on the geographical location of the city, its topography, and the climate conditions. Gorgan is one of the Northern cities of Iran, which have temperate climate and sunny weather has no effect on the pollutant of PM and VOC concentration. However, increases in concentrations of PM10, VOC, and ozone on summer sunny days have been reported in some warm/dry cities such as Tehran by Golhosseini et al. and Hosseinibalam et al.,
Furthermore, the weather condition of Gorgan City has caused that the wind speed has no significant effect on the concentration of target pollutants. According to the wind roses of Gorgan, the amount of calm winds was considerable, which probably was the reason for no influence of wind speed on PM and VOCs concentration.
But Rashki et al., as a result of a study conducted in Zahedan city, reported that monsoon winds could increase the concentration of particles in this city's air. Therefore, the geographical location of the city can be an important factor in the effect of wind on pollutant concentrations.
Based on the results, the temperature was the parameter affecting the concentrations of PM2.5, PM10, and VOC pollutants, which its effect was inverse. Reducing of temperatures in cold seasons was increasing the use of automobiles as well as the use of fossil fuels for heating purposes which are sources of target pollutants. On the other hand, the reason for this increase in concentrations of pollutants in cold days can be attributed to the air temperature inversion that causes particle and hydrocarbons traps in the lower layer, which may be the reason of increased concentrations of these pollutants., The results of this study were similar to report of Gholampour et al. in Tabriz. However, according to other studies, in desert areas such as Zahedan city, which in the summer the monsoon winds are dominated, the increase in particle concentration is noticeable in these seasons.
Furthermore, the Pearson correlation test showed that the concentrations of PM2.5, PM10, and VOCs pollutants were statistically correlated so that the concentration of these three pollutants was increased or decreased simultaneously, this means that the cause of the increase in these pollutants has been a common factor, which seems this factor is urban vehicles. Other studies have obtained similar results.
The air quality index values for particulate matter2.5 and particulate matter10
According to the results, the best air quality is related to particles PM10, which in the months of February and April, AQI is the least for this pollutant and is equal to 25, this means that the air of the city of Gorgan has less problems with PM10 than of PM2.5. In Europe for decades, the concentration of PM2.5 has risen in urban areas. Cohort studies on this continent was Indicates the direct relationship between long-term exposure to PM2.5 with increased mortality rates and referral the people to hospitals due to heart and respiratory problems. According to studies carried out in Barcelona of Spain, Stockholm of Sweden, and Madrid of Spain, the total deaths per 10 μg/m3 concentration of PM2.5 particles increased by 1.4%, 1.5%, and 2.7%, respectively.,, Furthermore, studies have shown that exposure to PM2.5, on average reduces the collective life expectancy of 8.6 months. In a study conducted in 545 cities in the USA to reduce the concentration of suspended particles and increase the life expectancy of people in these cities between in the years 2000 and 2007, the results showed that for reducing of each 10 μg/m3 concentrations of PM2.5 particles, the average life expectancy increases to 0.35 years. In general, in this study, the average particle concentration, especially PM2.5, in the cold season was obtained more than in the other months due to the thermal inversion and increased fuel consumption for heating purposes. Therefore, control measures to reduce emissions of pollutants can significantly reduce mortality rates. The results from this study are similar to the results announced by other researchers such as Gu et al., which the reason of the increase in particle concentration in autumn and winter in the Tianjin city has explained thermal inversion.
By observing the zoning maps in [Figure 6], also it can be found that the highest AQI of PM2.5 was in the central regions of the city, namely the Shahrdary Square and Mazandaran Square. Furthermore, maximum AQI by PM10 particles was measured in the central part and as well as in the Southern part of the city. The cause of this event can be the congestion of cars in these areas, which is the most important factor in the production of particles in cities.
In this study, due to limited equipment, taking more samples and examining the concentrations of different types of pollutants were also limited. Due to the importance of the subject, it is recommended to concentrate other pollutants such as NO, NO2, NOx, SO2, and CO to be measured and check the air quality of Gorgan City in the level of existing standards in the country and the world.
| Conclusion|| |
The aim of this study was to determine the air quality of Gorgan City in terms of PM2.5, PM10, and VOCs concentrations. Measurement results of PM2.5, PM10, and VOCs concentrations in 1 year from July 2016 to June 2017 showed that the average concentration of PM2.5 was higher than the EPA and WHO standard values. Furthermore, the concentration of PM10 is high in the cold months of the year. About of VOCs, according to the clean air standard, the average annual concentration of VOCs in Gorgan City, which is about 0.81 ppm, is much higher than the declared permissible value. Statistical tests were showed that among the atmospheric parameters, only the air temperature was correlated with the concentration of pollutants, which was reverse. In general, the effect of temperature inversion in the cold months of the year can be led to the durability of air around the city and increase concentrations of these pollutants. AQI values for PM2.5 and PM10 also indicate unhealthy weather conditions for sensitive individuals, with a high concentration of PM2.5. Furthermore, the zoning of AQI values in the city using GIS software showed that in the central areas of the city where traffic was high, this index was also higher. The ban on the use of cars over 15 years of age in urban areas from 6:30 to 19:30 during 72 h in emergencies, prohibition of public and private buses with more than 8 years of age in the city within 72 h, preventing the burning of forest woods on the floor of Alang darreh and Naharkhoran areas and installing NO FIRE, and the use of personal protective equipment and masks in unhealthy days are the solutions for reducing air pollution and protecting people from polluted air.
This study is the result of a research project approved by the Department of Environmental Protection of Golestan Province with the contract code 1259/769. The authors are appreciated from the financial support of this organization for carrying out this project.
Financial support and sponsorship
This study was financially supported by Golestan Province Environment Protection Administration, Golestan, Iran.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Taieb D, Brahim AB. Methodology for developing an air quality index (AQI) for Tunisia. Inter J of Ren Energy Technol 2013;4:86-106.
Zare M, Toolabi A, Zare MR, Sarkhosh M, Mahvi AH, Rahmani A. Outdoor investigation of air quality around Bandar Abbas-Iran oil refinery. Int J Environ Health Eng 2012;1:9.
Hajat A, Hsia C, O'Neill MS. Socioeconomic disparities and air pollution exposure: A global review. Curren Environ Health Rep 2015;2:440-50.
Shen F, Ge X, Hu J, Nie D, Tian L, Chen M. Air pollution characteristics and health risks in Henan Province, China. Environ Res 2017;156:625-34.
Abdolahnejad A, Jafari N, Mohammadi A, Miri M, Hajizadeh Y, Nikoonahad A. Cardiovascular, respiratory, and total mortality ascribed to PM10 and PM2.5 exposure in Isfahan, Iran. J Educ Health Promot 2017;6:109.
Bashiri KR, Souri B. Evaluation of Physico-Chemical Properties of the Dustfall Particles Bigger Than 10 μm in Kurdistan Province, Western Iran; 2016.
Mirzaei N, Arfaeinia H, Moradi M, Mohammadi Moghadam F, Velayati A, Sharafi K. The statistical analysis of seasonal and time variations on trend of important air pollutants (SO2, O3, NOx, CO, PM10)-in western Iran: A case study. Int J Pharm 2015;7:9610-9622.
Cesari D, De Benedetto GE, Bonasoni P, Busetto M, Dinoi A, Merico E, et al
. Seasonal variability of PM2.5 and PM10; composition and sources in an urban background site in Southern Italy. Sci Total Environ 2018;612:202-13.
Lu F, Xu D, Cheng Y, Dong S, Guo C, Jiang X, et al
. Systematic review and meta-analysis of the adverse health effects of ambient PM2.5 and PM10 pollution in the Chinese population. Environ Res 2015;136:196-204.
Chen X, Qian W, Kong L, Xiong Y, Tian S. Performance of a suspended biofilter as a new bioreactor for removal of toluene. Biochem Eng J 2015;98:56-62.
Mudliar S, Giri B, Padoley K, Satpute D, Dixit R, Bhatt P, et al
. Bioreactors for treatment of VOCs and odours – A review. J Environ Manage 2010;91:1039-54.
Tamaddoni M, Sotudeh-Gharebagh R, Nario S, Hajihosseinzadeh M, Mostoufi N. Experimental study of the VOC emitted from crude oil tankers. Process Saf Environ 2014;92:929-37.
Nichols BG, Kockelman KM, Reiter M. Air quality impacts of electric vehicle adoption in Texas. Transport Res D-Tr E 2015;34:208-18.
Zhang H, Wang S, Hao J, Wang X, Wang S, Chai F, Li M. Air pollution and control action in Beijing. J Clean Prod 2016;112:1519-27.
Jiang W, Wang Y, Tsou MH, Fu X. Using social media to detect outdoor air pollution and monitor air quality index (AQI): A geo-targeted spatiotemporal analysis framework with Sina Weibo (Chinese Twitter). PLoS One 2015;10:e0141185.
Kumar A, Goyal P. Forecasting of air quality in Delhi using principal component regression technique. Atmos Pollut Res 2011;2:436-44.
Abdolahnejad A, Jafari N, Mohammadi A, Miri M, Hajizadeh Y. Mortality and morbidity due to exposure to ambient NO2
, and O3
in Isfahan in 2013–2014. Int J Prev Med 2018;9:11.
] [Full text]
Kermani M, Naddafi K, Shariat M, Mesbah AS. TSP and PM10 measurement and description of air quality index (AQI) in the ambient air in Shariati hospital district. J S Pub Health Inst Pub Health Res 2004;2:37-46.
Khorram A, Yusefi M, Fardad M. Assessment of light pollution in Bojnord city using remote sensing data. Int J Environ Health Eng 2014;3:19.
Farrokhzadeh H, Jafari N, Sadeghi M, Talesh Alipour M, Amin MM, Abdolahnejad A. Estimation of spatial distribution of PM10, lead, and radon concentrations in Sepahanshahr, Iran using Geographic Information System (GIS). J Ma Uni Med Sci 2018;27:84-96.
Mirhosseini SH, Birjandi M, Zare MR, Fatehizadeh A. Analysis of particulate matter (PM 10 and PM2.5
) concentration in Khorramabad city. Int J Environ Health Eng 2013;2:3.
Halek F, Kavousi-Rahim A. GIS assessment of the PM 10, PM 2.5 and PM 1.0 concentrations in urban area of Tehran in warm and cold seasons. Int Arch Photogramm Remote Sens Spat Inf Sci 2014;40:141.
Shahbazi H, Reyhanian M, Hosseini V, Afshin H. The relative contributions of mobile sources to air pollutant emissions in Tehran, Iran: An emission inventory approach. Emission Contr Sci Technol 2016;2:44-56.
Hoek G, Beelen R, Kos G, Dijkema M, van der Zee SC, Fischer PH, et al
. Land use regression model for ultrafine particles in Amsterdam. Environ Sci Technol 2011;45:622-8.
Gu J, Liu A, Wu L, Xie Y, Li W, Dong H, Zhang X. Characterization of atmospheric organic carbon and element carbon of PM2. 5 and PM10 at Tianjin, China. Aerosol Air Qual Res 2010;10:167-76.
Rashki A, Rautenbach CD, Eriksson PG, Kaskaoutis DG, Gupta P. Temporal changes of particulate concentration in the ambient air over the city of Zahedan, Iran. Air Qual Atmos Health 20131;6:123-35.
Borhani F, Mirmohammadi M, Aslemand A. Experimental study of benzene, toluene, ethylbenzene and xylene (btex) concentrations in the air pollution of Tehran, Iran. J Res Environ Health 2017;3:83-93.
Huang C, Chen CH, Li L, Cheng Z, Wang HL, Huang HY. Emission inventory of anthropogenic air pollutants and VOC species in the Yangtze river delta region, China. Atmos Chem Phys 2011;11:4105.
Golhosseini MJ, Kakooei H, Shahtaheri SJ, Azam K, Panahi D. Occupational exposure to carbon monoxide of taxi drivers in Tehran, Iran. Inter J Occup Hyg 2011:56-62.
Hosseinibalam F, Hassanzadeh S, Alizadeh R. Analysis and assessment of ground-level ozone measured at two stations in Tehran. Environ Monit Assess 2010;165:275-81.
Buonanno G, Stabile L, Morawska L. Personal exposure to ultrafine particles: The influence of time-activity patterns. Sci Total Environ 2014;468-469:903-7.
Malandrino M, Casazza M, Abollino O, Minero C, Maurino V. Size resolved metal distribution in the PM matter of the city of Turin (Italy). Chemosphere 2016;147:477-89.
Gholampour ANabizadeh R, Hassanvand MS, Taghipour H, Faridi S, Mahvi AH. Investigation of the ambient particulate matter concentration changes and assessing its health impacts in Tabriz. Iran J Health Environ 2015;7:541-56.
Zolfaghari G, Mohammadi M, Arab AF, Delsouz M. Measuring the concentration of volatile organic compounds (VOCs), carbon monoxide, and particulate matters in underpass of Emam Reza Holy Shrine, Mashhad (Shirazi Parking). J Natur Environ 2017;70:829-42.
Schwartz J. Assessing confounding, effect modification, and thresholds in the association between ambient particles and daily deaths. Environ Health Perspect 2000;108:563-8.
Jiménez E, Linares C, Rodríguez LF, Bleda MJ, Díaz J. Short-term impact of particulate matter (PM2.5) on daily mortality among the over-75 age group in Madrid (Spain). Sci Total Environ 2009;407:5486-92.
Guaita R, Pichiule M, Maté T, Linares C, Díaz J. Short-term impact of particulate matter (PM2.5) on respiratory mortality in Madrid. Int J Environ Health Res 2011;21:260-74.
Ostro B, Tobias A, Querol X, Alastuey A, Amato F, Pey J, et al
. The effects of particulate matter sources on daily mortality: A case-crossover study of Barcelona, Spain. Environ Health Perspect 2011;119:1781-7.
Strukova E, Golub A, Markandya A. Air pollution costs in Ukraine; 2006.
Correia AW, Pope III CA, Dockery DW, Wang Y, Ezzati M, Dominici F. The effect of air pollution control on life expectancy in the United States: An analysis of 545 US counties for the period 2000 to 2007. Epidemiology 2013;24:23.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
[Table 1], [Table 2]