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ORIGINAL ARTICLE
Int J Env Health Eng 2020,  9:8

Long-term health impact assessment of PM2.5 and PM10: Karaj, Iran


1 Department of Environmental Engineering, Islamic Azad University, West Tehran Branch, Tehran, Iran
2 Student Research Committee, Iran University of Medical Sciences, Tehran, Iran
3 Research Center of Environmental Health Technology; Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran

Date of Submission24-Feb-2020
Date of Acceptance15-Jun-2020
Date of Web Publication31-Jul-2020

Correspondence Address:
Majid Kermani
Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran
Iran
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijehe.ijehe_16_20

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  Abstract 


Aim: This study was conducted to evaluate the effects of ambient concentrations of PM2.5 and PM10 on the health-related aspects including the total mortality, respiratory and cardiovascular diseases, and hospital admissions due to respiratory and cardiovascular diseases in Karaj, Alborz Province, Iran, during 2012–2016 using the AirQ2.2.3 software. The effects of meteorological parameters on the PM2.5 and PM10 levels were also investigated. Materials and Methods: Meteorological parameters, population, and the pollutant data were obtained from the Department of Environmental Protection, Karaj (Alborz, Iran). Statistical analysis was performed using the SPSS 24 software to study the relationship between the PM2.5 and PM10 concentrations and the meteorological parameters. Results: Our results showed a direct relationship between the PM10 concentration and the temperature (r = 0.34, P < 0.018) and relative humidity (r = 0.37, P < 0.5). However, there was a negative relationship between the PM10 concentration with wind speed (r < −0.328, P < 0.014) and precipitation (r < −0.179, P < 0.327). Similarly, there was a direct relationship between the PM2.5 concentration and the temperature (r = 0.41, P < 0.014) and relative humidity (r = 0.37, P < 0.05). On the other hand, a negative relationship was observed between the PM2.5 concentration with wind speed (r < −0.138, P < 0.010) and precipitation (r < −0.12, P < 0.201). The total number of death, death due to cardiovascular and respiratory diseases, and hospital admissions due to cardiovascular and respiratory diseases were equal to 1619, 1096, 306, and 4822, respectively. Conclusions: The results of this study showed that the concentrations of PM2.5 and PM10 should be reduced through applying the management strategies to improve the health of the residents in Karaj city.

Keywords: Air pollution, AirQ2.2.3 software, meteorological parameters, mortality, PM10, PM2.5


How to cite this article:
Vahidi MH, Fanaei F, Kermani M. Long-term health impact assessment of PM2.5 and PM10: Karaj, Iran. Int J Env Health Eng 2020;9:8

How to cite this URL:
Vahidi MH, Fanaei F, Kermani M. Long-term health impact assessment of PM2.5 and PM10: Karaj, Iran. Int J Env Health Eng [serial online] 2020 [cited 2020 Oct 28];9:8. Available from: https://www.ijehe.org/text.asp?2020/9/1/8/291247




  Introduction Top


The throughput of modern life has been influenced by air pollution, due to the advances in the sciences, so it can be said that there is absolutely no healthy air.[1] Nowadays, air pollution has passed over the boundaries of regions, villages, cities, and countries, and it has turned into a global concern.[2] Air pollution has natural causes, such as sandstorms, particulate pollution, or is caused due to the reasons that are entirely humanmade, such as the presence of cars, buses, and old trucks producing a lot of smoke.[3] Therefore, these agents present in the air produce pollutants.[4] Contaminants in the air contain dangerous and carcinogenic compounds, and the World Bank and the World Health Organization (WHO) have classified air pollution into the category of the carcinogens.[5] Totally 87% of the world population lives in countries where the level of air pollution is higher than the WHO guidelines.[6] The issue of air pollution is also linked to the internal policies of a country, so that the pollution problem can be controlled to a large extent if it is part of the state budget.[7] For instance, according to the report released by the World Bank, the cost associated with the death caused by air pollution is 0.57 of gross domestic product in Iran.[8] Fine particles are a serious threat that could endanger human health.[9] According to the WHO, nearly 7 million deaths and 3.7 million premature deaths occur in the rural and urban areas annually due to exposure to these fine particles.[10] Understanding the health effects following exposure to air pollution fosters our knowledge on air pollution-associated diseases.[11] However, air pollution can influence the skin, eyes, or other body systems. However, it mostly influences the respiratory system. Deaths due to heart disease, lung cancer, and chronic obstructive pulmonary disease most likely result from the exposure to the small particles. Although other factors influence them, one should not overlook the effect of air pollution.[12] The vulnerability of some people, especially sensitive age groups, is much higher than the others when they are exposed to air pollution.[13] Studies conducted over the past two decades have shown that one in every eight deaths occurs due to air pollution.[14] It is estimated that about 10,000 people die annually due to air pollution in Iran.[15] Meteorological parameters such as wind speed, relative humidity, annual precipitation, and air temperature can influence the particle concentrations positively and negatively.[16] Ansari and Ehrampoush studied the effect of the change in the trend of meteorological parameters by the PM2.5 concentration in 2017–2018. They found a weak correlation between the PM2.5 concentration with the mean monthly temperature (r = 4, P < 0.05) and the mean relative humidity (r = 0.37, P < 0.05).[17] Zhang et al. showed that the relative humidity and precipitation are negatively correlated with the concentration of air particles, and temperature and wind speed are positively correlated with the concentration of particles in the air.[18] In India, the concentration of particles has been reported to have a negative effect on the wind speed and relative humidity.[19] Aguilera Sammaritano et al., in a study conducted in Austria, reported the highest concentration of air particles in the winter.[20]

According to the abovementioned reasons, this study was conducted to (i) investigate the effect of the meteorological parameters including the temperature, relative humidity, wind speed, and precipitation on the concentrations of PM2.5 and PM10 in the ambient air of Karaj (Alborz, Iran) and (ii) estimate the total mortality, mortality due to cardiovascular and respiratory diseases, and hospital admissions due to respiratory and cardiovascular diseases (HARD and HACD) using the AirQ2.2.3 software (World Health Organization) during 2021–2016 in Karaj, Alborz Province, Iran.


  Materials and Methods Top


Geographical location of the study area

Karaj, as a bustling metropolis in the center of Alborz Province with a population of nearly 3 million people, is located at 48 km northwest of Tehran (Capital of Iran). The city has 16 km length and is 1300 m above the sea level, with a total area of 175.5 km 2. It is located at the latitude of 35.4845 and longitude of 51.030 in the northern hemisphere. In general, its climate is similar to other parts of Alborz Province so that, in cold seasons, the weather is influenced by the north, northwest, and west, especially southwest climates with atmospheric rainfall from November and August continuing until May. It experiences a huge volume of public and personal transportation daily due to its communication path with more than 15 provinces of Iran and suffers from severe air pollution where the emission by the cars contributes to almost 75% of the pollution.

Air pollution data

The air quality data were collected from the Department of Environmental Protection (Karaj, Alborz, Iran) measured by the Transportation, Air Quality, and Climate Change Committee stations from July 2012 to February 2016. Urban areas of the Karaj city are divided into 14 districts for urban services. Three citywide air pollutant-monitoring stations monitor the air quality daily [Figure 1]. Daily concentrations of PM2.5 and PM10 were obtained from the Department of Environmental Protection (Karaj, Alborz, Iran) for 5 years, and EXCEL software was used to remove the invalid data. Then, the valid data were entered into the software. The AirQ2.2.3 protocol was followed for calculating the daily mean concentrations of PM2.5 and PM10.
Figure 1: Map of the study area

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AirQ2.2.3 Software

The WHO has recommended the use of AirQ2.2.3 software to estimate the health effects of long- and short-term exposure to air pollutants. All the calculations performed by the AirQ2.2.3 software were based on the methodologies and functions regarding the concentrations of PM2.5 and PM10. The AirQ2.2.3 software calculates the total mortality, respiratory mortality, hospital admissions due to respiratory disease, mortality caused by cardiovascular diseases, hospital admissions due to cardiovascular diseases related to being exposed to the PM10, and total mortality related to being exposed to the PM2.5. This software builds a relationship between the air quality data in various ranges of concentration with epidemiological parameters such as relative risk (RR), baseline incidence (BI in 105 people), and attributable proportion (AP) and shows its results as the mortality. The AP is calculated according to the following formula by the software:

where RR is the relative risk reflecting the rate of a pollutant's effect on human health as a result of an increase in the pollutant's concentration andP(c) is the proportional population in the target group. Notably, the attributable values for the population contract (IE) were calculated through the following formula before the estimation of BI for population target:

IE = BI × AP.

After calculation of the population size, the number of cases attributable to the exposure (NE) can be estimated based on the following formula: NE = IE × N.

AirQ software is consisted of two analysis parts: estimating the number of health consequences attributed to air pollution and estimating the burden attributed to air pollution using the age table method. In short, AirQ is a set of pages or screens where the information is entered and the health effects are estimated. The four main pages in the first part of AirQ are (1) supplier page related to the information organization that is responsible for data import, (2) location page where the specific information of each pollutant is entered before recording the air quality information on this page, (3) air quality data where the concentration data are entered in this page, and (4) parameter page showing the parameters required to evaluate the effects (including the health consequences, threshold, RR, and the incidence of the desired outcome in the community under study).

Statistical analysis

In the present study, the relationship between the PM2.5 and PM10 concentrations with the meteorological parameters such as the relative humidity, temperature, precipitation, and wind speed was calculated. On the other hand, the total mortality, death due to cardiovascular and respiratory diseases, HARD, and HACD were investigated using the AirQ2.2.3 software. In the first part of the study, the Pearson correlation coefficient was calculated by the SPSS (version 24) software Statistical Package for the Social Sciences (SPSS) to determine the relationship between the meteorological parameters and concentrations of the particulate matters (PM2.5 and PM10). The mortality rate was determined by the AirQ2.2.3 software (provided by the WHO). The graphs used in this study were also obtained from the EXCEL and R software.


  Results Top


Meteorological parameters and concentration of the pollutants

[Figure 2] shows the average monthly temperature (°C), total monthly precipitation (cm), mean wind speed (m/s), and average relative humidity (%) in Karaj city from 2012 to 2016. The minimum and maximum relative humidity occurred in May and November (33.82%–64.51%), the minimum and maximum temperatures occurred in December and June (3.82–28.1), the minimum and maximum wind speed belonged to July and May (10–17.4), and minimum and maximum precipitation were in March and July (4.23°C–0.05°C), as shown in [Figure 2]. According to [Figure 2], the mean annual and standard deviation were equal to 16.03 (±8.81), 47.19% (±10.16), 13.08 (s 2.41), and 16.9 (±19.78) mm for temperature, relative humidity, wind speed, and pressure, respectively. The relationship between these parameters will be discussed in the Discussion Section.
Figure 2: Average monthly temperature, total monthly precipitation, average monthly wind speed, and average monthly relative humidity for the period of study

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[Table 1] shows the relationship between the mean annual concentrations of PM2.5 and PM10 with the meteorological parameters. As shown in [Table 1], there was a positive relationship between the mean annual PM10 and PM10 concentrations with the temperature (r = 0.34, P < 0.018, and r = 0.41, P < 0.14) and humidity (r = 0.31, P < 0.05, and r = 0.37, P < 0.05), respectively, during the study period in Karaj city. In addition, a negative relationship was observed between the precipitation with PM10 and PM2.5 concentrations (r = −0.179, P < 0.327, and r = −0.12, P < 0.201) and wind speed with PM10 and PM2.5 concentrations (r = −0.328, P < 0.014, and r = −0.138, P < 0.010), respectively, in Karaj city during 2012–2016.
Table 1: Bivariate correlations between PM2.5 and PM10 with climatic parameter in Karaj from 2012-2016

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[Figure 3] shows the changes in the PM2.5 and PM10 concentrations. As demonstrated in [Figure 3], the highest and lowest mean concentrations of PM10 were observed in May 2012 (123.491) and March 2013 (35.41 μg/m 3), respectively. Furthermore, for PM2.5, these values were observed in May 2012 (61.75 μg/m 3) and March 2014 (17.57 μg/m 3), respectively. Furthermore, during the study period (2012–2016), the concentration of PM10 particles was equal to 64.26 μg/m 3 and it was equal to 32.41 μg/m 3 for PM2.5 particles.
Figure 3: Average monthly concentrations of PM2.5 and PM10 in ambient air of the study area (2012–2016)

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Mortality attributed to being exposed to the particles

Based on the AirQ2.2.3 model estimates, the total number of deaths, deaths due to cardiovascular and respiratory diseases, HARD, and HACD due to the exposure to PM2.5 and PM10 particles were calculated in Karaj city during the study period, as shown in [Table 2]. Approximately 1619 total deaths occurred due to the exposure to PM10(RR = 1.06), and 1096, 306, 4822, and 1895 death cases were reported due to cardiovascular diseases, respiratory diseases, HARD, and HACD, respectively, during the study period in Karaj city (2012–2016). Furthermore, 436 deaths per 100,000 people in Karaj city were related to the exposure to PM2.5 particles during the study period, which is eight times the average death toll in the world.
Table 2: Estimated number of excess, relative risk, and baseline incidence of endpoint mortality due to PM10 exposure, Karaj (2012-2016)

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  Discussion Top


Industrialization in Asian countries has created many environmental problems including the production of hazardous pollutants in the air in the recent decades. On the other hand, meteorological parameters can influence the amount of air pollution. The concentration of airborne particulate matters depends on several factors including the temperature, humidity, precipitation, and wind speed. It can be said that the concentration of particles is higher in the cold seasons of the year due to more fuel consumption, heating, and stagnant wind speeds. The results of this study are consistent with the study conducted by Ghanbari Ghozikali et al., who reported the highest concentration of particles in the winter.[21] Miri et al. also found a higher concentration of PM2.5 in the winter than the other seasons.[22] In addition, Mohammadi et al., in a study, showed the highest seasonal concentration of the particles in the winter.[23] However, Bahrami reported the highest concentration of the particles during the summer when the temperature was at the maximum point and the wind speed was at the lowest level. Of course, dust storms also occur in the summer.[24] The results of the study showed that the residents of Karaj city are exposed to the fine particles (susceptible to air pollution) 3.5 times more than the WHO guidelines (10 μg/m 3).

The Relationship between the PM2.5 and PM10 and Meteorological Parameters

In this descriptive-analytical study, the relative humidity, temperature, precipitation, and wind speed were investigated among the factors influencing the particle concentration. However, one should not overlook the effect of other factors. As shown in [Table 1], there was a positive relationship between the PM10 and PM2.5 concentrations and temperature in the present study (r = 0.34, P < 0.018, and r = 0.41, P < 0.014), respectively, which is consistent with the study by Achakulwisut (r = 0.42, P < 0.5).[25] In addition, Zhang et al. observed that PM2.5 and PM10 concentrations were significantly and positively associated with the rest of the seasons except the winter.[26] In some cases, particle concentrations and ambient temperatures can be inversely correlated. For instance, Wang showed a negative relationship between the particles and ambient temperature.[27] Xue et al. found a positive relationship between the seasonal mean PM2.5 and PM10 concentrations and temperature.[28] In this study, the concentration of PM10 particles changed seasonally with respect to the ambient air temperature in a direct but not very positive relationship. In addition, Hou et al. found a positive relationship between the PM10 concentration and temperature.[29] Furthermore, our results showed a positive relationship between the PM2.5 and PM10 concentrations with monthly mean relative humidity (r = 0.31, P < 0.5, and r = 0.37, P < 0.05), respectively, in Karaj city during 2012–2016, which is consistent with the studies by Ansari and Ehrampoush,[17] Alvarez et al.,[30] and Huang et al.[31] Lou et al. investigated the effect of relative humidity on the PM2.5 and PM10 concentrations over 2 years and showed that the relative humidity was positively associated with the particle concentration.[32] However, Zhang, in a study conducted in Beijing, found that the relative humidity had a negative effect on the particulate matter and PM10 concentration.[33] An increase in the volume of the clouds in the air reduces the amount of sunlight, and as a result, the temperature drops and subsequently the rainfall or atmospheric rainfall increases.[34] Topographic conditions in the area also influence the amount of sunlight and the concentration of the pollutants.[35] However, in this study, a weak or inverse relationship was observed between the PM2.5 and PM10 concentrations and precipitation during the study period (2012–2016) in Karaj city, which is in line with the study by Erener et al., regarding the concentrations of PM10 and PM2.5(r = −0.18 P < 0.314, and r = −0.19, P < 0.241).[36] Rosenfeld et al. also found a negative relationship between the particle concentration and precipitation (r = −0.19, P < 0.5).[37] The average rainfall was equal to 16.92 mm in Karaj city during the study period (2012–2016), with an average downward trend. The results of this study are consistent with the study by Lin et al., who showed that the PM2.5 and PM10 concentrations were inversely and negatively associated with the precipitation.[38] Statistical analysis revealed a negative relationship between the PM2.5 and PM10 concentrations with wind speed (r = −0.138, P < 0.010, and r = −0.328, P < −0.014), respectively. Similar to the study by Lin et al., a negative relationship was observed between the wind speed and particle concentration.[39] Most of the winds also occurred in the northwest of Karaj city during the study period. Wind speed can also influence the particle concentrations through eliminating the particulate matters, resulting in the reduction of the particle concentrations, as reported in the study by Jafari et al.[40]

Total mortality

The number of deaths reported in this study was higher than those of the study by Mohammadi et al., (409 deaths). Although, this study has been conducted over 1 year.[23] The highest number of deaths in our study reported over 1 year occurred in 2012 (397 deaths). Orru et al. reported 296 premature deaths due to the exposure to the PM2.5 particles and 312 premature deaths due to the exposure to the PM10 particles per 100,000 people in Tallinn city (Estonia).[41] Results of a study carried out in Tehran on four air pollutants (SO2, NO2, O3, and PM10) introduced the PM10 as the most frequent cause of early death and respiratory diseases.[42] Studies conducted in Tabriz and Shiraz cities have also indicated the high potential of PM10 for mortality and morbidity.[43],[44] The mortality rate in our study was lower than that of the study conducted in Tehran possibly due to the fact that Tehran has a higher density, and as a result, more people are exposed to the particles than Karaj city. Furthermore, results of a study conducted in Tehran showed that 5073 deaths occurred due to the exposure to the PM2.5 particles.[45]

Cardiovascular diseases

In addition, an association was observed between the PM10 concentrations and cardiovascular disease. Xie et al. reported a nonlinear relationship between the PM10 concentration and mortality caused by cardiovascular diseases.[46] As illustrated in [Table 2] 4, 1096 people may have died due to the exposure to the PM10 in Karaj city during 2012–2016. Cardiovascular diseases vary in different age groups, and it can be said that the particles are the main cause of cardiovascular diseases.[47] Mohammadi et al. reported 543 deaths due to cardiovascular diseases as a result of being exposed to the PM10.[48]

Respiratory diseases

Our results showed that 60% of deaths in Karaj city were due to respiratory and heart problems.[49] Studies conducted in San Diego, Chile, and Hong Kong have reported a significant association between air pollution and respiratory and cardiovascular diseases.[50] Gholizadeh et al. reported 7477 deaths due to respiratory diseases in Tehran city during 2002–2005.[51] The development of respiratory diseases also depends on the topographic conditions of the area. For example, proximity to the deserts in some cities can increase the burden of these diseases due to occurrence of the thunderstorms.[52] In the present study, 306 deaths (r = 1.013) occurred due to respiratory diseases during the study period in Karaj city. Godarzi et al, in a study reported that 95% of deaths were due to respiratory diseases.[53]

Hospital admissions due to respiratory and cardiovascular diseases

In the present study, 4822 and 1895 death cases were due to the HARD and HACD, respectively, in Karaj city during 2012–2016. Goudarzi et al. showed a significant relationship between the particle concentrations with HARD and HACD.[53] Geravandi et al. reported 1438, 1945, and 1393 death cases due to the HARD, respectively, in Ahvaz city during 2010–2012.[54]


  Conclusions Top


The results of the current study indicated that the residents of Karaj city are 3.2 and 2–3 times more likely to be exposed to the PM2.5 and PM10 particles than the Environmental Protection Agency standard. Subsequently, it was found that the temperature and relative humidity increased the concentrations of PM2.5 and PM10 and the rate of precipitation and wind speed reduced their concentration. Therefore, the residents of Karaj city are likely to be exposed to a variety of diseases caused by air pollution and its pollutants. According to the results of this study, high concentrations of PM2.5 and PM10, and the harmful effects of these pollutants on the health of residents in Karaj city, there is a need for better and accurate planning and follow-up by the officials to control or reduce this environmental dilemma.

Acknowledgments

This article is the result of MSc approved thesis, Research Project No. 22840404962011. Thus, the authors are thankful for the funding provided by the Department of Environmental Health Engineering, Islamic Azad University, Tehran Branch, Ethics Code No. 22840404962011.

Financial support and sponsorship

Islamic Azad University, Tehran Branch, Tehran, Iran.

Conflicts of interest

There are no conflicts of interest.



 
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