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Particulate matters and bioaerosols during Middle East dust storms events in Ilam, Iran
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Particulate matter and bioaerosols during Middle East dust storms events in Ilam, Iran Ali Amarloei , Mehdi Fazlzadeh , Ahmad Jonidi Jafari , Ahmad Zarei , Sajad Mazloomi PII: DOI: Reference:
S0026-265X(19)31460-2 https://doi.org/10.1016/j.microc.2019.104280 MICROC 104280
To appear in:
Microchemical Journal
Received date: Revised date: Accepted date:
15 June 2019 21 September 2019 22 September 2019
Please cite this article as: Ali Amarloei , Mehdi Fazlzadeh , Ahmad Jonidi Jafari , Ahmad Zarei , Sajad Mazloomi , Particulate matter and bioaerosols during Middle East dust storms events in Ilam, Iran, Microchemical Journal (2019), doi: https://doi.org/10.1016/j.microc.2019.104280
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HIGHLIGHTS
The concentrations of PM2.5 and PM10 and bacterial characteristics during dusty and nondusty days in the ambient air of Ilam was investigated. The concentrations of PM from June to September were higher than those measured in other months. The results showed that the average concentration of PM was higher during warm seasons compared to cold. The predominant bacterial colonies were Staphylococcus, Cryptococcus, Corynebacterium and Bacillus. During dusty days, higher number of microbial colonies were than non-dusty days.
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Particulate matter and bioaerosols during Middle East dust storms events in Ilam, Iran Ali Amarloei 1,2, Mehdi Fazlzadeh3,4, Ahmad Jonidi Jafari5, Ahmad Zarei6, Sajad Mazloomi 1,7* 1.
Department of Environmental Health, School of Public Health, Ilam University of Medical Sciences, Ilam, Iran
2.
Department of Environmental Health Engineering, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran
3.
Social Determinants of Health Research Center, Ardabil University of Medical Sciences, Ardabil, Iran
4.
Department of Environmental Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
5.
Department of Environmental Health Engineering, School of Public Health, Iran University of Medical sciences, Tehran, Iran
6.
Department of Environmental Health Engineering, Faculty of Health, Social Determinants of Health Research Center, Gonabad University of Medical Sciences, Gonabad, Iran
7.
Biotechnology and Medicinal Plants Research Center, Faculty of Medicine, Ilam University of Medical Sciences, Ilam, Iran
*Corresponding author: Sajad Mazloomi Tel.: +9821886079451;
Fax:
[email protected]
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+982188622707;
E-mail address:
Abstract Particulate matter can be transferred distances from their source regions. Due to different chemical and microbial characteristics, they can have a potential impact on public health and ecosystems. Therefore, in this study we aimed to study the concentrations of particulate matter (PM2.5 and PM10) and types of bacteria in the ambient air of Ilam city during dusty (PM10 ≥ 150 µg/m3) and non-dusty days from February 2012 to February 2013. Totally, there existed more dust storm events during warm and dry months. The Mann-Whitney test confirmed a significant relationship between dusty and non-dusty days (P<0.05). Totally, by increasing the PM concentrations, the number of bacterial colonies increased. Kruskal- Wallis test showed that there was a significant relationship between the number of bacterial colonies and season. The mostly observed bacterial colonies were Staphylococcus, Cryptococcus, Corynebacterium, Bacillus,
Actinosynnema,
Nocardioides,
Arthrobacter,
Flavimonas,
Paenibacillus,
Pseudomonas, Microbacterium, Planococcus, Streptomyces, Kurthia, Neisseria Agrococcus, Curtobacterium, Duganella, Ancylobacter, Paracoccus, Propionibacterium, Pseudomonas, Rhizobium and Enterococci. The predominant direction of dust plumes in Ilam city was from the west of Ilam from neighboring countries. The higher number of microbial colonies during dusty days obviously showed the important role of these events on microbial characteristics. Keywords: Air pollution, Dusty and non-dusty days, Bioaerosols, Ilam
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1. Introduction Gases and particulates in the air are generated both by natural processes, such as volcanos or sandstorms, and by human activities such as fossil fuel burning, transportation, and so on [1, 2]. Airborne particulate matter (PM) are among the important pollutants which are the indicator of air quality [3]. Particulate matter are among important criterion air pollutants which cause many types of cancer, cardiovascular and respiratory diseases, and even mortality [4-9]. Dust storms originated from deserts and arid lands are the major sources of PM [10]. Dust storms are generally occurs when wind (speed>5 m/s) lifts dust particles into the atmospheric boundary layer or above [11, 12]. Dust storm is the natural atmospheric phenomenon that has been considered as having numerous environmental and climate effects. Dust storms are frequent in Middle East during spring and autumn (from March to September) and greatly invade many countries, especially Iran. Strong wind raises soil, sand, and fine particles when a dust storm event occurs, and forms a dust which is transported over a long distances [13]. This storm can affect daily life of communities in downwind areas and is known as an independent risk factor for cardiovascular morbidity and mortality [14-16]. Dust particles in range 31–62 μm (coarse particles) can travel up to 320 kilometers from their source, particles in range 16–31μm (medium particles) can travel up to 1600 km, an particles below 16μm (fine) can be transported universally [17]. Results show that dust storms can transport pathogens and allergens with the potential to impact the health of downwind populations and ecosystems [18-20]. Recently, the frequency of dust storms and the associated damages have been increased dramatically in the western and south western parts of Iran [6, 21] and sometimes the PM concentrations regularly exceed the World Health Organization (WHO) guidelines. Airborne microorganisms are an abundant component of atmospheric aerosols, with thousands, or even millions, of cells in each 4
cubic meter of air [22, 23]. Generally, wind-borne bacteria are transported to less than 1 km from their source, however, dust-associated bacteria can be transported at distances above 5000 km [24]. Dust storms act as vehicles for bioaerosols transportation [25, 26]. Bioaerosols are a class of air particles (living and dead organisms) that are in the range of 0.001-100 µm [22]. They include algae, archaea, and bacteria, fungal spores and plant pollen, and plant debris and brochosomes [27, 28]. In previous studies, bacteria including Arthrobacter, Bacillus, Cryptococcus, Flavimonas, Paenibacillus, Pseudomonas, Staphylococcus, Corynebacterium, Microbacterium, Nocardioides, Planococcus, Streptomyces, Kurthia, Neisseria, Agrococcus, Curtobacterium, Duganella, Actinosynnema, Ancylobacter, Paracoccus, Propionibacterium, Pseudomonas, Rhizobium and Acinetobacter have been isolated from dust storms [29, 30]. Some meteorological parameters including air temperature, relative humidity, wind speed, and UV radiation play major roles in the concentrations of bioaerosol and their transportation [10, 31]. The large arid interior of the Iran and neighborhood countries including Iraq, Saudi Arabia, and Syria are the major sources of Iran atmospheric dust. Drought and overgrazing contribute to dust storms that affect many Iranian cities annually. [6, 32]. Due to their potential effects of pollution storms on the environment and on human health, many researches have focused on various pollution events [33-35]. However, no study has considered the bacteriological quality of pollution events in west of Iran. Considering the dispersal of bioaerosols associated with dust events, the importance of bioaerosols in the atmosphere is likely to be seriously underestimated. Therefore, in this investigation we aimed to study the concentrations of particulate matter and their microbial characteristics in the ambient air of Ilam city during dusty (when the PM10 ≥ 150 µg/m3) [6] and non-dusty days. This research provides useful information
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regarding characteristics of particulate matter transported by the Middle East dust storms for experts of environmental health, medical, and agriculture fields. 2. Materials and Methods 2.1. Study area description Ilam city, the capital of Ilam Province, is located in western Iran. At the 2011 census, its population was 172,000. Ilam is located in the cold mountainous region (Zagros Mountains) of Iran with an elevation of 1,319 m above sea level with coordinates 33.6350° N, 46.4153° E. The average temperature in Ilam is 18.8 °C. Average annual precipitation is 574 mm. August and January is the warmest and coldest month of year. Although this city is surrounded by mountains, its climate is also affected by deserts from the west and the south ]63[. As Fig. S1 shows, Ilam borders Iraq from the west. It is near Saudi Arabia and Kuwait as the major sources of the regional dusts [6]. The climate of the city is classified under the Köppen climate class as a Mediterranean climate (Csa) with some continental influences. Most of dust events start during February. This study is performed from February 2012 to February 2013. The selection of the location of sampling was based on the USEPA standards [37]. All the samples were taken in the roof of a building 7 m above the ground level and 1.4 m above the roof surface. 2.2. Sampling and analysis PM2.5 and PM10 samples were taken by using ENVIRO-check Environmental Dust Monitor (Model EDM180). Based on the USEPA standard, the samples were taken each 6 days during the study period [6]. Sampling was done during 24 h (9 am to 9 am tomorrow), and data were recorded every 30 min. In order to sample dust, the dust events were monitored during the study period based on the information taken from meteorological forecasts. Totally PM2.5 and 6
PM10 were sampled for 107 days. The SKC Quick Take (SKC, UK) was used for sampling bacterial bioaerosols. The bioaerosol sampling were conducted periodically (every 6 days) and during dusty days. So that, sampling was done according to the arrival time of new dust storm to the study area that was 16 samples. Totally, 72 samples were taken and studied for bioaerosols. For enumeration of bioaerosols, Tryptic Soy Agar (TSA) (Liofilchem, Italy) was used. To prevent from the growth of fungus, 150 mg/L of Nystatin as an antifungal medication were added to the culture. After sampling, the cultures were transferred to laboratory and incubated at 35-37 oC for 48 h. The data regarding wind speed (WS) and wind direction was gathered from Ilam meteorological center. The wind rose scheme during sampling is given Fig. 2 (B). The important meteorological parameters including air temperature (T), relative humidity (RH) and wind speed were also recorded. The plume dust formation and their movement toward Iran during the study period were monitored via European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). For this purpose, 24 photos were collected and checked on daily basis [38]. 3. Results and Discussion 3.1. Wind direction and speed In recent decades the role of desert dust has become increasingly important not only in global climate change but also in its impacts on human health and environment. The wind rose plot for the Ilam city is shown in Fig. S2. In the wind rose plot, the length of each directional line shows the percent frequency at which wind blows from that direction. The results showed that 79.45% of the wind pattern was in range of 146.25-303.75 degrees. 39 out of 83 (47 %) dust plumes entered Ilam city, were in range 303-326 degrees, 20 plume (24.1 %) in 258-281 degrees, 8
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(9.66%) in 213-236 degrees, 8 (9.64 %) in 236-258 degrees, and 7 (7.23 %) were in 281-203 degrees (Fig. S2A). Based on the results of wind rose (Fig. S2), all of the dusts plumes enter Ilam from the western side. Tracing of dust plums and their sources showed that deserts of Al Anbar Governorate, Ninewa Governorate, eastern Syria parts and Salah al-Din Governorate were contributed to 30.9, 32.1, 23.6, and 4.2 percent of dust masses entrance to the city of Ilam, respectively. 3.2. Particulate matter concentrations and temporal trends Fig. 1 and Fig. 2 depict the results of PM10 and PM2.5 during routine and provide dust storms and their comparison with Iranian air quality standard and national ambient air quality standards (NAAQS). June (6 days sampling) was the month with highest sampling days. The concentrations of PM from June to September were higher than those measured in other months. The highest average monthly concentration of PM10 (148.3 µg/m3) and PM2.5 (29.7 µg/m3) during non-dusty days was recorded in July. Furthermore, the lowest concentration of PM 10 (32.1 µg/m3) and PM2.5 (10.2 µg/m3) during periodically measuring of PM (every 6 days) was recorded in February and October, respectively (Fig. 1). The results showed that the average concentration of PM was higher during warm seasons compared to cold which can be attributed to the higher numbers of dust storms during these months (Fig. 1). Also, the presence of local dust and the lack of adequate rain for atmospheric wash out is another reason of the contaminated atmosphere in the warm season. Fig. 1. Average monthly concentration of periodically measured (every 6 days) of PM10 and PM2.5 during study period To determine the origin of dust events, the formation and direction of dust plumes were monitored by using satellite imagery. Totally, 83 dust plumes grew up during the study period
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and moved toward Iran. Accordingly, in 35 days (during 12 months) dust events was recorded in Ilam city (PM10>150 µg/m3) (Fig. 2). June (13 days sampling) was recorded as the highest sampling days. The numbers of dust events were highest during March to August. The results showed that the highest average monthly concentration of PM10 (343.9 µg/m3) and PM2.5 (72.3 µg/m3) during dusty days was recorded in April, whilst during September, October, November, and February any dust storm wasn’t recorded (Fig. 2). Fig. 2. Average monthly concentration of PM10 and PM2.5 during dusty days in the study period Fig. S3 and Fig. S4 show the trend of average and maximum PM10 and PM2.5 concentrations and their comparison with Iranian air quality standard and NAAQS during the study period. As can be seen in Fig. 1 and Fig. 2, the average concentration of PM10 was higher than of PM2.5 (both during dusty days and non-dusty days). During storm events, the maximum, minimum, average, and standard deviation values of PM10/PM2.5 were 5.84:1, 2.57:1, 4.38:1, and 1.09:1, respectively, and during non-dusty days, these values were 6.24:1, 4.12:1, 5.11:1, and 0.68:1, respectively. Based on the variation of PM10 and PM2.5 (Fig. 1, Fig. 2, and Fig. S3), the days with highest dust events were recorded in June (13 days), with average monthly PM 10 and PM2.5 concentrations 324.60 and 57.00 µg/m3, respectively. The second month with the highest dust days was April (6 days) which the concentration of PM10 and PM2.5 were 343.90 and 72.30 μg/m3 respectively. As the results revealed, the average concentration of PM was the highest as the maximum concentration of PM10 (802±255.70) and PM2.5 (151.4±49.60) were recorded during June. Similarly, Shahsavani et al. reported that highest concentration of PM during dust events in Ahvaz city (Khuzestan, Iran) was recorded during June [39]. In the present study, the highest hourly PM10 (1958.90 µg/m3) and PM2.5 (325 µg/m3) concentration was also observed
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during June. In a similar study in Ahvaz city (Khuzestan, Iran) by Shahsavani et al. in 2010, the highest hourly concentration of PM10 (5337.60 µg/m3) and PM2.5 (910.90 µg/m3) during dust storms was recorded during June [39]. In Goudarzi et al. study, performed in Ahvaz city (Khuzestan, Iran) during 2011-2012, most of dust events in Ahvaz city was during warm months, but the highest PM10 (4730.10 µg/m3) and PM2.5 (774.40 µg/m3) was recorded in February [23]. The results of these studies showed that season of year have an important role in the number of dust events occurred both in Ilam and Khuzestan from the dust plumes entering Iran from west. But the levels of dust in these provinces are different, mainly due difference in topography and distance from dust event sources. Based on the results of this study, there was no any dust events during September, October, November, and February. Based on the Mann–Whitney test, PM10 and PM2.5 concentrations did not show a significant relationship between dusty and non-dusty days (P<0.05). This is in agreement with the results obtained by Zhao et al. in China. Based on their study, the average values of PM10 and PM2.5 concentration during dusty days were 322±237.40 and 141.5±108.80 µg/m3, respectively, whilst during non-dusty days the average daily concentration of PM10 was 80 µg/m3 [40]. The ratio of PM2.5:PM10 during non-dusty and dusty days in this study was 0.248:1 and 0.191:1; respectively, that shows a natural origin for these pollutants and sources from crustal materials and dust re-suspension in dry climatic conditions. The study of Goudarzi et al. (2014) showed that the mean PM2.5:PM10 ratios were 0.67 and 0.65 for the winter and summer, respectively [41]. The results of spearman analysis showed that the levels of PM10 has a weak positive correlation (0.24), weak negative and insignificant positive (P<0.05) correlation with temperature, relative humidity and wind velocity, respectively. Furthermore, levels of PM 2.5 had a positive insignificant correlation with temperature and wind velocity. Levels of PM 2.5 also had an 10
insignificant negative correlation with relative humidity. The results indicated that strong wind velocity, low relative humidity and high temperature provide conditions for dust plume formation in June and August. 3.3. Concentrations and temporal distributions of total culturable airborne bacteria Table 1 shows the number of bacterial colonies in ambient air of Ilam city. In this study, the highest average colonies during non-dusty days were recorded in June (296.82 CFU/m3). For days with dust events, the highest average colonies were measured during November (669.96 CFU/m3). Table 2 shows the species of bacteria in samples collected from ambient air of Ilam city during non-dusty and dusty days. In all the samples, a variety of bacterial species were observed. Table 1. The average monthly concentration of bacterial colonies (CFU/m3) during study period Table 2. Comparison of concentration of bacterial colonies (CFU/m3) during non-dusty and dusty days The number and type of bacteria was different in different seasons of year. Table 3 shows the predominant species of isolated bacteria. Also, In Fig. 3 and Fig. 4, the trend of bacterial colonies variations associated with PM10 and PM2.5, relative humidity, temperature, and wind speed in the ambient air of Ilam is shown. As shown in Fig. 4, in most cases by increasing the levels of wind speed and relative humidity, the levels of PM2.5 and bacterial colonies increases. Table 3. Number of bacterial colonies during different seasons (CFU/m 6) Fig. 3. Variations of bacterial colonies associated with PM10, relative humidity, Temperature, and wind speed during the study period
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Fig. 4. Variations of bacterial colonies associated with PM2.5, relative humidity, Temperature, and wind speed during the study period The distribution and type of bioaerosols in the atmosphere varies greatly depending on the origin of dusts, ambient air temperature, geographical location, humidity, and precipitation [6]. Microorganisms in dust plumes generally die due to UV light, absence of nutrients, and dry conditions. But some of spores can survive in dry and hot conditions, low amount of nutrients, and exposure to UV light [42, 43]. The average annual value of bacterial colonies during the study period was 337.88 CFU/m3. The highest number of colonies (1484.1 CFU/m3) was observed in June. In this study, the highest (296.82 CFU/m3) and the lowest (21.23 CFU/m3) values of bacterial colonies during 6 day sampling period was observed in June and February, respectively. The highest number of bacterial colonies during dusty days was recorded in Jun (1020.03 CFU/m3), which was 5.6 times higher than the average monthly concentrations during non-dusty days (Table 1). The average annual ratio of the number of bacterial colonies during dusty to non-dusty days was 4.32:1. This is in agreement with the average monthly concentrations of particulate matter, indicating obviously the effect of dust events on the number of colonies (Fig. 3 and Fig. 4). Shahsavani et al. in 2010, reported an average annual number of 349 CFU/m3 for bacterial colonies in Ahvaz city (Khuzestan, Iran). The highest average monthly number of bacterial colonies was observed during March (1053 CFU/m3). The reason for higher average annual and monthly concentration of particulate matter in this study might be due to different environmental conditions including the number of dusty days, humidity, and temperature. In Soleimani et al. (2016) study regarding the Mediterranean dust storms in Ahvaz city (Khuzestan, Iran), the ratio of bacterial colonies during dusty days to non-dusty days was 423:329 [44]. In this study, the average concentrations of bacterial colonies during non-dusty and dusty days were 129.98 and 495.95 CFU/m3, respectively. Generally, the average of bacterial 12
colonies during dusty days was 3.66 times higher than that of non-dusty days. In Shahsavani et al. study, similarly the bacterial colonies were highest during dusty days [45]. Wu et al. in 2004 and Ho et al. in 2005 studies showed that the Chicness desert dusts increased the concentration of fungal bioaerosol in the atmosphere considerably [46, 47]. As shown in Fig.3 and Fig.4, when PM10 and PM2.5 concentrations increase the number of bacterial colonies increase too that indicates the significant relationship between PM10 and PM2.5 and bacterial colonies. Mann– Whitney test showed that the differences between the number of bacterial colonies in the dusty and non-dusty days was significant (P<0.05). Furthermore, in dusts plumes in Asia and Africa, the transfer of bacterial bioaerosols along with dust plumes is reported. the result of present study was in agreement with the results of Kellogg et al. (2004 ) in study of aerosolized bacteria during dust event of Mali and
study of Wu et al, (2004) in study of bioaerosol concentration
from dust storms in Tiwan [43, 47]. Kruskal–Wallis test showed significant relationship between the number of bacterial colonies and seasons of the year (P<0.05) [48]. According to ANOVA test, there was a significant relationship between different seasons (winter and spring) and number of bacterial colonies (P<0.05). The average highest bacterial colonies in this study were observed during highest PM10, PM2.5 concentrations warm semester (Figs. S3 and S4). The results of this study is similar to the results reported by Shahsavani et al. [49]. From the present study it can be concluded that dust events are the main factors affecting on the number of bioaerosols in the air. However, humidity is the next environmental factor affecting on bioaerosol concentration in the atmosphere [27]. There was insignificant positive correlation between the levels of bacteria and temperature based on the spearman analysis (P>0.05). This was due to the insignificant change of air temperature during dusty and non-dusty days (P>0.05) mainly because most of samples were taken during 9-10 am. The results showed an insignificant
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negative correlation between number of bacteria with relative humidity (P>0.05) in Ilam. Also, the results showed a significant positive correlation between number of bacteria with wind velocity (P<0.05). The most common bacterial species isolated in the non-dusty days of the present study were in order
Staphylococcus>
Streptomyces>
Corynebacterium>
Bacillus>
Enterococcus>
Actinosynnema> Nocardioides> Mycobacterium> Proteus (Table 3). The detected and concentration of bacterial species in dusty days were in order Staphylococcus> Streptomyces> Corynebacterium> Bacillus> Actinosynnema> Nocardioides> Enterococcus (Table 3). Staphylococcus and Micrococci are resistant to UV radiation due to the availability of pigments in their cells. Bacillus can survive more during transfer to long distances than other bacteria. Most of bacteria don’t survive under dry conditions and exposure to sunlight. However, spores of Bacillus is somewhat resistant to sunlight, low humidity and nutrients [30, 50]. The highest number of bacterial colonies in the atmosphere of Ilam was Staphylococcus with 30.64 and 146.96 CFU/m3 during non-dusty and dusty days, respectively. In Soleimani et al. the predominant bacterial species in dusts events were Bacillus spp, Micrococcus spp, Streptomyces spp and Staphylococcus spp [44]. In Griffin et al. study the predominant bacterial species during dusts events over the Turkish Mediterranean coastline were Alternaria, Cladosporium, Microsporum and Penicillium [51]. Also in Yuan et al. study in 2012 on the composition of bacterial strains during dust storm events in Beijing, the predominant strains belong to Firmicutes and Actinomycetes [52]. Like this study, the results of African dust plumes showed that the predominant species were gram positive and spore forming bacteria (Bacillus and Microbacterium) that are more resistant against harsh environmental conditions [46].
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Type and species of bacteria isolated from the dust plumes generally depend on the transport distance from the origin. Since some of dust plumes entering Ilam originate from Middle East deserts (Fig. S2), there is a similarity between the type and species of observed bioaerosols in this study with other related studies. The predominant type of bioaerosols colonies isolated form dust plumes in Kuwait were Bacillus, Arthrobacter, Arthrobacter, Cryptococcus, Kurthia, Neisseria, Flavimonas, Pseudomonas, Ralstonia and Staphylococcus [53]. In another study regarding dust plumes in Saudi Arabia, the predominant species were Bacillus, Pseudomonas, and Staphylococcus. The results of Mann–Whitney test of present study showed that the number of bacterial colonies including Actinosynnema, Nocardia, Staphylococcus and Corynebacterium during dusty and non-dusty days has a significant relationship (p<0.05), whilst the number of colonies including Bacillus, Streptococci, and other isolated colonies during dusty and non-dusty days were not significant (p>0.05). Therefore, it can be stated that dust plumes entering Ilam have increased the number of Actinomyces, Nocardia, Staphylococcus and Corynebacterium. As the Table 3 shows, the season of the year influences on the distribution of bacterial spores. Based on Kruskal–Wallis analysis, there was significant relationship between bacterial colonies (except Corynebacterium, Micrococci) and the season of year (p<0.05). 4. Conclusions Ambient air pollution caused by particulate matter is associated with a wide range of environment factors and human health. A better understanding of particulate matter and their effects are necessary for governmental agencies, decision makers, and health professionals to define and implement appropriate mitigation and adaptation policies. Every year, Ilam province is affected by many dust storm events originating from neighbor countries. The comprehensive monitoring of atmospheric PM concentrations and bioaerosol concentrations is vital, not only for 15
environmental management, but also to estimate the health effects of air pollution in the exposed communities. During the one-year study period, 35 dusty days were recorded (PM ≥ 150 µg/m3) in Ilam city. Furthermore, the high concentrations of particulate matter during dust events can have a verity of health effects including cardiovascular and respiratory problems on the residents in the study area. The presence of high levels of bacterial bioaerosols and their significant relationship with dust plumes necessitate the use of proper management strategies in local and regional scale to reduce the occurrence and amounts of dust storms. Acknowledgements This work is financially supported by Tarbiat Modares University. The authors of this study wish to express their sincere gratitude and deep appreciation to the Ilam Meteorological Organization for their help and support throughout this study. The author also would like to thank Prof. Mehdi Zarrei in Sickkids-Hospital in Toronto, Canada for valuable comments and suggestions, allowing us to improve this paper. Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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[38] M.A. Martínez, J. Ruiz, E. Cuevas, Use of SEVIRI images and derived products in a WMO Sand and Dust Storm Warning System, in: IOP Conference Series: Earth and Environmental Science, IOP Publishing, 2009, pp. 012004. [39] A. Shahsavani, K. Naddafi, N.J. Haghighifard, A. Mesdaghinia, M. Yunesian, R. Nabizadeh, M. Arahami, M. Sowlat, M. Yarahmadi, H. Saki, The evaluation of PM 10, PM 2.5, and PM 1 concentrations during the Middle Eastern Dust (MED) events in Ahvaz, Iran, from April through September 2010, Journal of Arid Environments, 77 (2012) 72-83. [40] J. Zhao, F. Zhang, Y. Xu, J. Chen, L. Yin, X. Shang, L. Xu, Chemical characteristics of particulate matter during a heavy dust episode in a coastal city, Xiamen, 2010, Aerosol and Air Quality Resarch, 11 (2011) 299-308. [41] G. Goudarzi, M. Shirmardi, F. Khodarahmi, A. Hashemi-Shahraki, N. Alavi, K.A. Ankali, A.A. Babaei, Z. Soleimani, M.B. Marzouni, Particulate matter and bacteria characteristics of the Middle East Dust (MED) storms over Ahvaz, Iran, Aerobiologia, 30 (2014) 345-356. [42] L. Song, W. Song, W. Shi, Study on airborne bacteria pollution in Shanghai, Shanghai Environmental Sciences, 18 (1999) 258-260. [43] C.A. Kellogg, D.W. Griffin, V.H. Garrison, K.K. Peak, N. Royall, R.R. Smith, E.A. Shinn, Characterization of aerosolized bacteria and fungi from desert dust events in Mali, West Africa, Aerobiologia, 20 (2004) 99-110. [44] Z. Soleimani, G. Goudarzi, A. Sorooshian, M.B. Marzouni, H. Maleki, Impact of Middle Eastern dust storms on indoor and outdoor composition of bioaerosol, Atmospheric Environment, 138 (2016) 135-143. [45] A. Amarloei, A.J. Jafari, H.A. Mahabadi, K. Asadollahi, The Evaluation of PM10, PM2.5 and PM1 Concentration during Dust Storm Events in Ilam city, from Mar 2013 through Feb 2014, Scientific Journal of Ilam University of Medical Sciences, 22 (2014) 240-259 (persian). [46] H.-M. Ho, C.Y. Rao, H.-H. Hsu, Y.-H. Chiu, C.-M. Liu, H.J. Chao, Characteristics and determinants of ambient fungal spores in Hualien, Taiwan, Atmospheric Environment, 39 (2005) 5839-5850. [47] P.-C. Wu, J.-C. Tsai, F.-C. Li, S.-C. Lung, H.-J. Su, Increased levels of ambient fungal spores in Taiwan are associated with dust events from China, Atmospheric Environment, 38 (2004) 4879-4886. [48] N.-P. Hua, F. Kobayashi, Y. Iwasaka, G.-Y. Shi, T. Naganuma, Detailed identification of desertoriginated bacteria carried by Asian dust storms to Japan, Aerobiologia, 23 (2007) 291-298. [49] A. Amarloei, Jafari, A. J., Mahabadi, H. A. & Asadollahi, K., The Evaluation of PM10, PM2.5 and PM1 Concentration during Dust Storm Events in Ilam city, from Mar 2013 through Feb 2014. 22(4):, Scientific Journal of Ilam University of Medical Sciences, 22 ( 2014)) 240-259. [50] A. Kwaasi, V. Parhar, F. Al‐ Mohanna, H. Harfi, K. Collison, S. Al‐ Sedairy, Aeroallergens and viable microbes in sandstorm dust: Potential triggers of allergic and nonallergic respiratory ailments, Allergy, 53 (1998) 255-265. [51] D.W. Griffin, N. Kubilay, M. Koçak, M.A. Gray, T.C. Borden, E.A. Shinn, Airborne desert dust and aeromicrobiology over the Turkish Mediterranean coastline, Atmospheric environment, 41 (2007) 40504062. [52] H. Yuan, D. Zhang, Y. Shi, B. Li, J. Yang, X. Yu, N. Chen, M. Kakikawa, Cell concentration, viability and culture composition of airborne bacteria during a dust event in Beijing, Journal of Environmental Sciences, 55 (2017) 33-40. [53] M. Lyles, Fredrickson, H., Bednar, A., Fannin, H. & Sobecki, T., The chemical, biological, and mechanical characterization of airborne micro-particulates from Kuwait. Abstr. In 8th Ann. Force Health Protect, Conf., session, Vol. 2586., ( 2005).
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180 147.8
160
148.3
Concentration (µg/m3)
140
PM2.5 PM10
120
Iran Air Clean Standard & NAAQS (PM10)
100.7
Iran Air Clean Standard & NAAQS (PM2.5)
100
76.6 80
63.5
62.9
60
59.6
52.7
56.6 39.8
60 29.7
40 25.3
20
32.1 18.9
14.5
15.3
14
Mar
Apr
May
Jun
Jul
4
5
4
6
5
16.7
21.2
Oct
Nov
5
5
11.5
10.2
Aug
Sep
5
5
11.5
12.5
Dec
Jan
Feb
5
5
5
0
Numbers of sampling days per month
Fig. 1. Average monthly concentration of periodically measured (every 6 days) of PM10 and PM2.5 during study period
20
400 PM2.5
343.9
350
PM10
324.6
Concentration (µg/m3)
300
Iran Air Clean Standard & NAAQS (PM10)
325
Iran Air Clean Standard & NAAQS (PM2.5)
240.8
250
203.9
200
207.2
214.8 150 100
72.3 52.1
50
44.1
57
48
40.3
50.3
0
Numbers of sampling days per month
Fig. 2. Average monthly concentration of PM10 and PM2.5 during dusty days in the study period
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Bacterial Colonies CFU/m3
100
PM10 Iran Air Clean Standard & NAAQS (PM10) wind speed
1300 1200 1100 1000 900 800 700 600
80
Relative Humidity Temperature
60
40
20
500 400 300
0
200 100 -20 Mar Mar Mar Mar Apr Apr Apr Apr Apr May May May May Jun Jun Jun Jul Jul Jul Jul Aug Aug Aug Aug Sep Oct Oct Oct Nov Nov Dec Dec Dec Jan Jan Feb
0 Date
Fig. 3. Variations of bacterial colonies associated with PM10, relative humidity, Temperature, and wind speed during the study period
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Relative Humidity (%), Temperature (°C)
bacterial colonies CFU/m3, PM10 (µgr/m3), wind speed (cm/s)
1600 1500 1400
100
Bacterial Colonies CFU/m3 PM2.5
1400 1300 1200 1100
Iran Air Clean Standard & NAAQS (PM10) wind speed
80
Relative Humidity
60
Temperature
1000 900 800 700 600
40
20
500 400 300
0
200 100 -20 Mar Mar Mar Mar Apr Apr Apr Apr Apr May May May May Jun Jun Jun Jul Jul Jul Jul Aug Aug Aug Aug Sep Oct Oct Oct Nov Nov Dec Dec Dec Jan Jan Feb
0
Relative Humidity (%), Temperature (°C)
bacterial colonies CFU/m3, PM10 (µgr/m3), wind speed (cm/s)
1600 1500
Date
Fig. 4. Variations of bacterial colonies associated with PM2.5, relative humidity, Temperature, and wind speed during the study period
Table 1. The average monthly concentration of bacterial colonies (CFU/m3) during study period month Mar Apr May Jun Jul Aug Sep Oct Nov Des Jan Feb
Samples 6 7 5 3 7 5 3 5 4 4 4 3
non-dusty days Ave Max Min SD 81.10 155.48 35.34 47.31 137.48 247.35 61.84 73.28 125.56 219.08 53 70.00 296.82 572.44 113.07 243.07 119.859 188.46 65.62 51.05 105.86 141.34 79.51 25.21 157.75 314.63 67.14 136.41 168.20 321.98 81.27 97.04 132.81 259.13 77.74 85.56 134.68 236.6 63.6 82.93 42.53 91.80 11.8 36.99 21.23 30.00 5.30 13.82
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dusty days Samples Ave Max 1 77.74 3 644.27 927.56 3 219.08 219.08 3 1020.03 1484.10 2 458.58 965.84 2 591.88 848.06 1 666.96 1 711.60 0
Min 137.48 219.08 530.04 162.54 335.69 -
SD 452.97 35.38 477.56 441.34 362.30 -
Table 2. Comparison of concentration of bacterial colonies (CFU/m3) during non-dusty and dusty days Non-dusty day samples Average Maximum SD Staphylococcus 30.64 141.34 28.33 Streptomyces 24.84 139.50 24.81 Corynebacterium 16.11 70.67 18.24 Bacillus 14.65 92.76 18.13 Enterococcus 10.68 77.74 16.51 Actinosynnema 10.21 74.91 17.89 Nocardioides 7.94 35.34 9.10 Mycobacterium 1.07 56.54 7.77 Proteus 0.17 2.40 0.6 others 9.79 70.67 15.38 Total 125.98 669.96 107.78 Bacteria
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dusty day samples Average Maximum 146.96 477.03 85.64 318.02 59.27 226.15 48.71 194.35 20 106 45.12 229.68 38.05 164.90 0 0 0 0 52.15 300.35 495.95 1484.10
SD 127.46 112.98 67.85 62 34.22 65.48 5.20 0 0 78.85 427.51
Bacteria Staphylococcus Streptomyces Bacillus Actinosynnema Nocardioides Corynebacterium Enterococcus Micrococci Proteus Others Total
Spring (25 samples) Ave Max SD 106.59 2.10 119.51 41.86 42.8 75.58 38.74 13 54.88 22.8 229.68 50.67 15.23 12.6 30.20 4.59 18.8 59.32 4.24 02.16 12.20 2.26 0.00 11.31 0.00 64.0 0.00 41.19 28.3 70.79 313.5 34.66 379.60
Sumer (18 samples) Ave Max SD 55.00 212.01 60.39 69.73 318.02 85.83 3.59 28.27 8.56 17.21 58.89 20.31 25.29 164.9 47.18 19.68 106.00 30.81 17.28 106.00 32.02 0.00 0.00 0.00 0.00 0.00 0.00 8.73 70.67 18.36 220.54 965.84 259.67
Table 3. Number of bacterial colonies during different seasons (CFU/m 6
25
Autumn (15 samples) Ave Max SD 41.25 139.15 40.16 34.93 139.5 36.40 32.47 92.80 27.60 29.35 185.90 50.25 14.79 35.34 10.94 33.10 92.80 31.10 20.30 71.27 20.67 0.00 0.00 0.00 0.00 0.00 0.00 18.46 62.00 19.35 224.26 711.60 20.73
Winter (14 Samples) Ave Max SD 10.20 35.10 10.48 8.42 49.50 13.36 13.00 42.40 14.28 0.51 70.07 1.89 6.12 35.34 10.13 8.18 28.30 10.63 16.02 77.74 22.04 0.00 0.00 0.00 0.64 2.40 1.06 3.28 24.70 6.99 66.34 236.60 62.65
Particulate matter and bioaerosols during Middle East dust storms events in Ilam, Iran Ali Amarloei , Mehdi Fazlzadeh , Ahmad Jonidi Jafari , Ahmad Zarei , Sajad Mazloomi PII: DOI: Reference:
S0026-265X(19)31460-2 https://doi.org/10.1016/j.microc.2019.104280 MICROC 104280
To appear in:
Microchemical Journal
Received date: Revised date: Accepted date:
15 June 2019 21 September 2019 22 September 2019
Please cite this article as: Ali Amarloei , Mehdi Fazlzadeh , Ahmad Jonidi Jafari , Ahmad Zarei , Sajad Mazloomi , Particulate matter and bioaerosols during Middle East dust storms events in Ilam, Iran, Microchemical Journal (2019), doi: https://doi.org/10.1016/j.microc.2019.104280
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HIGHLIGHTS
The concentrations of PM2.5 and PM10 and bacterial characteristics during dusty and nondusty days in the ambient air of Ilam was investigated. The concentrations of PM from June to September were higher than those measured in other months. The results showed that the average concentration of PM was higher during warm seasons compared to cold. The predominant bacterial colonies were Staphylococcus, Cryptococcus, Corynebacterium and Bacillus. During dusty days, higher number of microbial colonies were than non-dusty days.
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Particulate matter and bioaerosols during Middle East dust storms events in Ilam, Iran Ali Amarloei 1,2, Mehdi Fazlzadeh3,4, Ahmad Jonidi Jafari5, Ahmad Zarei6, Sajad Mazloomi 1,7* 1.
Department of Environmental Health, School of Public Health, Ilam University of Medical Sciences, Ilam, Iran
2.
Department of Environmental Health Engineering, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran
3.
Social Determinants of Health Research Center, Ardabil University of Medical Sciences, Ardabil, Iran
4.
Department of Environmental Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
5.
Department of Environmental Health Engineering, School of Public Health, Iran University of Medical sciences, Tehran, Iran
6.
Department of Environmental Health Engineering, Faculty of Health, Social Determinants of Health Research Center, Gonabad University of Medical Sciences, Gonabad, Iran
7.
Biotechnology and Medicinal Plants Research Center, Faculty of Medicine, Ilam University of Medical Sciences, Ilam, Iran
*Corresponding author: Sajad Mazloomi Tel.: +9821886079451;
Fax:
[email protected]
2
+982188622707;
E-mail address:
Abstract Particulate matter can be transferred distances from their source regions. Due to different chemical and microbial characteristics, they can have a potential impact on public health and ecosystems. Therefore, in this study we aimed to study the concentrations of particulate matter (PM2.5 and PM10) and types of bacteria in the ambient air of Ilam city during dusty (PM10 ≥ 150 µg/m3) and non-dusty days from February 2012 to February 2013. Totally, there existed more dust storm events during warm and dry months. The Mann-Whitney test confirmed a significant relationship between dusty and non-dusty days (P<0.05). Totally, by increasing the PM concentrations, the number of bacterial colonies increased. Kruskal- Wallis test showed that there was a significant relationship between the number of bacterial colonies and season. The mostly observed bacterial colonies were Staphylococcus, Cryptococcus, Corynebacterium, Bacillus,
Actinosynnema,
Nocardioides,
Arthrobacter,
Flavimonas,
Paenibacillus,
Pseudomonas, Microbacterium, Planococcus, Streptomyces, Kurthia, Neisseria Agrococcus, Curtobacterium, Duganella, Ancylobacter, Paracoccus, Propionibacterium, Pseudomonas, Rhizobium and Enterococci. The predominant direction of dust plumes in Ilam city was from the west of Ilam from neighboring countries. The higher number of microbial colonies during dusty days obviously showed the important role of these events on microbial characteristics. Keywords: Air pollution, Dusty and non-dusty days, Bioaerosols, Ilam
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1. Introduction Gases and particulates in the air are generated both by natural processes, such as volcanos or sandstorms, and by human activities such as fossil fuel burning, transportation, and so on [1, 2]. Airborne particulate matter (PM) are among the important pollutants which are the indicator of air quality [3]. Particulate matter are among important criterion air pollutants which cause many types of cancer, cardiovascular and respiratory diseases, and even mortality [4-9]. Dust storms originated from deserts and arid lands are the major sources of PM [10]. Dust storms are generally occurs when wind (speed>5 m/s) lifts dust particles into the atmospheric boundary layer or above [11, 12]. Dust storm is the natural atmospheric phenomenon that has been considered as having numerous environmental and climate effects. Dust storms are frequent in Middle East during spring and autumn (from March to September) and greatly invade many countries, especially Iran. Strong wind raises soil, sand, and fine particles when a dust storm event occurs, and forms a dust which is transported over a long distances [13]. This storm can affect daily life of communities in downwind areas and is known as an independent risk factor for cardiovascular morbidity and mortality [14-16]. Dust particles in range 31–62 μm (coarse particles) can travel up to 320 kilometers from their source, particles in range 16–31μm (medium particles) can travel up to 1600 km, an particles below 16μm (fine) can be transported universally [17]. Results show that dust storms can transport pathogens and allergens with the potential to impact the health of downwind populations and ecosystems [18-20]. Recently, the frequency of dust storms and the associated damages have been increased dramatically in the western and south western parts of Iran [6, 21] and sometimes the PM concentrations regularly exceed the World Health Organization (WHO) guidelines. Airborne microorganisms are an abundant component of atmospheric aerosols, with thousands, or even millions, of cells in each 4
cubic meter of air [22, 23]. Generally, wind-borne bacteria are transported to less than 1 km from their source, however, dust-associated bacteria can be transported at distances above 5000 km [24]. Dust storms act as vehicles for bioaerosols transportation [25, 26]. Bioaerosols are a class of air particles (living and dead organisms) that are in the range of 0.001-100 µm [22]. They include algae, archaea, and bacteria, fungal spores and plant pollen, and plant debris and brochosomes [27, 28]. In previous studies, bacteria including Arthrobacter, Bacillus, Cryptococcus, Flavimonas, Paenibacillus, Pseudomonas, Staphylococcus, Corynebacterium, Microbacterium, Nocardioides, Planococcus, Streptomyces, Kurthia, Neisseria, Agrococcus, Curtobacterium, Duganella, Actinosynnema, Ancylobacter, Paracoccus, Propionibacterium, Pseudomonas, Rhizobium and Acinetobacter have been isolated from dust storms [29, 30]. Some meteorological parameters including air temperature, relative humidity, wind speed, and UV radiation play major roles in the concentrations of bioaerosol and their transportation [10, 31]. The large arid interior of the Iran and neighborhood countries including Iraq, Saudi Arabia, and Syria are the major sources of Iran atmospheric dust. Drought and overgrazing contribute to dust storms that affect many Iranian cities annually. [6, 32]. Due to their potential effects of pollution storms on the environment and on human health, many researches have focused on various pollution events [33-35]. However, no study has considered the bacteriological quality of pollution events in west of Iran. Considering the dispersal of bioaerosols associated with dust events, the importance of bioaerosols in the atmosphere is likely to be seriously underestimated. Therefore, in this investigation we aimed to study the concentrations of particulate matter and their microbial characteristics in the ambient air of Ilam city during dusty (when the PM10 ≥ 150 µg/m3) [6] and non-dusty days. This research provides useful information
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regarding characteristics of particulate matter transported by the Middle East dust storms for experts of environmental health, medical, and agriculture fields. 2. Materials and Methods 2.1. Study area description Ilam city, the capital of Ilam Province, is located in western Iran. At the 2011 census, its population was 172,000. Ilam is located in the cold mountainous region (Zagros Mountains) of Iran with an elevation of 1,319 m above sea level with coordinates 33.6350° N, 46.4153° E. The average temperature in Ilam is 18.8 °C. Average annual precipitation is 574 mm. August and January is the warmest and coldest month of year. Although this city is surrounded by mountains, its climate is also affected by deserts from the west and the south ]63[. As Fig. S1 shows, Ilam borders Iraq from the west. It is near Saudi Arabia and Kuwait as the major sources of the regional dusts [6]. The climate of the city is classified under the Köppen climate class as a Mediterranean climate (Csa) with some continental influences. Most of dust events start during February. This study is performed from February 2012 to February 2013. The selection of the location of sampling was based on the USEPA standards [37]. All the samples were taken in the roof of a building 7 m above the ground level and 1.4 m above the roof surface. 2.2. Sampling and analysis PM2.5 and PM10 samples were taken by using ENVIRO-check Environmental Dust Monitor (Model EDM180). Based on the USEPA standard, the samples were taken each 6 days during the study period [6]. Sampling was done during 24 h (9 am to 9 am tomorrow), and data were recorded every 30 min. In order to sample dust, the dust events were monitored during the study period based on the information taken from meteorological forecasts. Totally PM2.5 and 6
PM10 were sampled for 107 days. The SKC Quick Take (SKC, UK) was used for sampling bacterial bioaerosols. The bioaerosol sampling were conducted periodically (every 6 days) and during dusty days. So that, sampling was done according to the arrival time of new dust storm to the study area that was 16 samples. Totally, 72 samples were taken and studied for bioaerosols. For enumeration of bioaerosols, Tryptic Soy Agar (TSA) (Liofilchem, Italy) was used. To prevent from the growth of fungus, 150 mg/L of Nystatin as an antifungal medication were added to the culture. After sampling, the cultures were transferred to laboratory and incubated at 35-37 oC for 48 h. The data regarding wind speed (WS) and wind direction was gathered from Ilam meteorological center. The wind rose scheme during sampling is given Fig. 2 (B). The important meteorological parameters including air temperature (T), relative humidity (RH) and wind speed were also recorded. The plume dust formation and their movement toward Iran during the study period were monitored via European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). For this purpose, 24 photos were collected and checked on daily basis [38]. 3. Results and Discussion 3.1. Wind direction and speed In recent decades the role of desert dust has become increasingly important not only in global climate change but also in its impacts on human health and environment. The wind rose plot for the Ilam city is shown in Fig. S2. In the wind rose plot, the length of each directional line shows the percent frequency at which wind blows from that direction. The results showed that 79.45% of the wind pattern was in range of 146.25-303.75 degrees. 39 out of 83 (47 %) dust plumes entered Ilam city, were in range 303-326 degrees, 20 plume (24.1 %) in 258-281 degrees, 8
7
(9.66%) in 213-236 degrees, 8 (9.64 %) in 236-258 degrees, and 7 (7.23 %) were in 281-203 degrees (Fig. S2A). Based on the results of wind rose (Fig. S2), all of the dusts plumes enter Ilam from the western side. Tracing of dust plums and their sources showed that deserts of Al Anbar Governorate, Ninewa Governorate, eastern Syria parts and Salah al-Din Governorate were contributed to 30.9, 32.1, 23.6, and 4.2 percent of dust masses entrance to the city of Ilam, respectively. 3.2. Particulate matter concentrations and temporal trends Fig. 1 and Fig. 2 depict the results of PM10 and PM2.5 during routine and provide dust storms and their comparison with Iranian air quality standard and national ambient air quality standards (NAAQS). June (6 days sampling) was the month with highest sampling days. The concentrations of PM from June to September were higher than those measured in other months. The highest average monthly concentration of PM10 (148.3 µg/m3) and PM2.5 (29.7 µg/m3) during non-dusty days was recorded in July. Furthermore, the lowest concentration of PM 10 (32.1 µg/m3) and PM2.5 (10.2 µg/m3) during periodically measuring of PM (every 6 days) was recorded in February and October, respectively (Fig. 1). The results showed that the average concentration of PM was higher during warm seasons compared to cold which can be attributed to the higher numbers of dust storms during these months (Fig. 1). Also, the presence of local dust and the lack of adequate rain for atmospheric wash out is another reason of the contaminated atmosphere in the warm season. Fig. 1. Average monthly concentration of periodically measured (every 6 days) of PM10 and PM2.5 during study period To determine the origin of dust events, the formation and direction of dust plumes were monitored by using satellite imagery. Totally, 83 dust plumes grew up during the study period
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and moved toward Iran. Accordingly, in 35 days (during 12 months) dust events was recorded in Ilam city (PM10>150 µg/m3) (Fig. 2). June (13 days sampling) was recorded as the highest sampling days. The numbers of dust events were highest during March to August. The results showed that the highest average monthly concentration of PM10 (343.9 µg/m3) and PM2.5 (72.3 µg/m3) during dusty days was recorded in April, whilst during September, October, November, and February any dust storm wasn’t recorded (Fig. 2). Fig. 2. Average monthly concentration of PM10 and PM2.5 during dusty days in the study period Fig. S3 and Fig. S4 show the trend of average and maximum PM10 and PM2.5 concentrations and their comparison with Iranian air quality standard and NAAQS during the study period. As can be seen in Fig. 1 and Fig. 2, the average concentration of PM10 was higher than of PM2.5 (both during dusty days and non-dusty days). During storm events, the maximum, minimum, average, and standard deviation values of PM10/PM2.5 were 5.84:1, 2.57:1, 4.38:1, and 1.09:1, respectively, and during non-dusty days, these values were 6.24:1, 4.12:1, 5.11:1, and 0.68:1, respectively. Based on the variation of PM10 and PM2.5 (Fig. 1, Fig. 2, and Fig. S3), the days with highest dust events were recorded in June (13 days), with average monthly PM 10 and PM2.5 concentrations 324.60 and 57.00 µg/m3, respectively. The second month with the highest dust days was April (6 days) which the concentration of PM10 and PM2.5 were 343.90 and 72.30 μg/m3 respectively. As the results revealed, the average concentration of PM was the highest as the maximum concentration of PM10 (802±255.70) and PM2.5 (151.4±49.60) were recorded during June. Similarly, Shahsavani et al. reported that highest concentration of PM during dust events in Ahvaz city (Khuzestan, Iran) was recorded during June [39]. In the present study, the highest hourly PM10 (1958.90 µg/m3) and PM2.5 (325 µg/m3) concentration was also observed
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during June. In a similar study in Ahvaz city (Khuzestan, Iran) by Shahsavani et al. in 2010, the highest hourly concentration of PM10 (5337.60 µg/m3) and PM2.5 (910.90 µg/m3) during dust storms was recorded during June [39]. In Goudarzi et al. study, performed in Ahvaz city (Khuzestan, Iran) during 2011-2012, most of dust events in Ahvaz city was during warm months, but the highest PM10 (4730.10 µg/m3) and PM2.5 (774.40 µg/m3) was recorded in February [23]. The results of these studies showed that season of year have an important role in the number of dust events occurred both in Ilam and Khuzestan from the dust plumes entering Iran from west. But the levels of dust in these provinces are different, mainly due difference in topography and distance from dust event sources. Based on the results of this study, there was no any dust events during September, October, November, and February. Based on the Mann–Whitney test, PM10 and PM2.5 concentrations did not show a significant relationship between dusty and non-dusty days (P<0.05). This is in agreement with the results obtained by Zhao et al. in China. Based on their study, the average values of PM10 and PM2.5 concentration during dusty days were 322±237.40 and 141.5±108.80 µg/m3, respectively, whilst during non-dusty days the average daily concentration of PM10 was 80 µg/m3 [40]. The ratio of PM2.5:PM10 during non-dusty and dusty days in this study was 0.248:1 and 0.191:1; respectively, that shows a natural origin for these pollutants and sources from crustal materials and dust re-suspension in dry climatic conditions. The study of Goudarzi et al. (2014) showed that the mean PM2.5:PM10 ratios were 0.67 and 0.65 for the winter and summer, respectively [41]. The results of spearman analysis showed that the levels of PM10 has a weak positive correlation (0.24), weak negative and insignificant positive (P<0.05) correlation with temperature, relative humidity and wind velocity, respectively. Furthermore, levels of PM 2.5 had a positive insignificant correlation with temperature and wind velocity. Levels of PM 2.5 also had an 10
insignificant negative correlation with relative humidity. The results indicated that strong wind velocity, low relative humidity and high temperature provide conditions for dust plume formation in June and August. 3.3. Concentrations and temporal distributions of total culturable airborne bacteria Table 1 shows the number of bacterial colonies in ambient air of Ilam city. In this study, the highest average colonies during non-dusty days were recorded in June (296.82 CFU/m3). For days with dust events, the highest average colonies were measured during November (669.96 CFU/m3). Table 2 shows the species of bacteria in samples collected from ambient air of Ilam city during non-dusty and dusty days. In all the samples, a variety of bacterial species were observed. Table 1. The average monthly concentration of bacterial colonies (CFU/m3) during study period Table 2. Comparison of concentration of bacterial colonies (CFU/m3) during non-dusty and dusty days The number and type of bacteria was different in different seasons of year. Table 3 shows the predominant species of isolated bacteria. Also, In Fig. 3 and Fig. 4, the trend of bacterial colonies variations associated with PM10 and PM2.5, relative humidity, temperature, and wind speed in the ambient air of Ilam is shown. As shown in Fig. 4, in most cases by increasing the levels of wind speed and relative humidity, the levels of PM2.5 and bacterial colonies increases. Table 3. Number of bacterial colonies during different seasons (CFU/m 6) Fig. 3. Variations of bacterial colonies associated with PM10, relative humidity, Temperature, and wind speed during the study period
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Fig. 4. Variations of bacterial colonies associated with PM2.5, relative humidity, Temperature, and wind speed during the study period The distribution and type of bioaerosols in the atmosphere varies greatly depending on the origin of dusts, ambient air temperature, geographical location, humidity, and precipitation [6]. Microorganisms in dust plumes generally die due to UV light, absence of nutrients, and dry conditions. But some of spores can survive in dry and hot conditions, low amount of nutrients, and exposure to UV light [42, 43]. The average annual value of bacterial colonies during the study period was 337.88 CFU/m3. The highest number of colonies (1484.1 CFU/m3) was observed in June. In this study, the highest (296.82 CFU/m3) and the lowest (21.23 CFU/m3) values of bacterial colonies during 6 day sampling period was observed in June and February, respectively. The highest number of bacterial colonies during dusty days was recorded in Jun (1020.03 CFU/m3), which was 5.6 times higher than the average monthly concentrations during non-dusty days (Table 1). The average annual ratio of the number of bacterial colonies during dusty to non-dusty days was 4.32:1. This is in agreement with the average monthly concentrations of particulate matter, indicating obviously the effect of dust events on the number of colonies (Fig. 3 and Fig. 4). Shahsavani et al. in 2010, reported an average annual number of 349 CFU/m3 for bacterial colonies in Ahvaz city (Khuzestan, Iran). The highest average monthly number of bacterial colonies was observed during March (1053 CFU/m3). The reason for higher average annual and monthly concentration of particulate matter in this study might be due to different environmental conditions including the number of dusty days, humidity, and temperature. In Soleimani et al. (2016) study regarding the Mediterranean dust storms in Ahvaz city (Khuzestan, Iran), the ratio of bacterial colonies during dusty days to non-dusty days was 423:329 [44]. In this study, the average concentrations of bacterial colonies during non-dusty and dusty days were 129.98 and 495.95 CFU/m3, respectively. Generally, the average of bacterial 12
colonies during dusty days was 3.66 times higher than that of non-dusty days. In Shahsavani et al. study, similarly the bacterial colonies were highest during dusty days [45]. Wu et al. in 2004 and Ho et al. in 2005 studies showed that the Chicness desert dusts increased the concentration of fungal bioaerosol in the atmosphere considerably [46, 47]. As shown in Fig.3 and Fig.4, when PM10 and PM2.5 concentrations increase the number of bacterial colonies increase too that indicates the significant relationship between PM10 and PM2.5 and bacterial colonies. Mann– Whitney test showed that the differences between the number of bacterial colonies in the dusty and non-dusty days was significant (P<0.05). Furthermore, in dusts plumes in Asia and Africa, the transfer of bacterial bioaerosols along with dust plumes is reported. the result of present study was in agreement with the results of Kellogg et al. (2004 ) in study of aerosolized bacteria during dust event of Mali and
study of Wu et al, (2004) in study of bioaerosol concentration
from dust storms in Tiwan [43, 47]. Kruskal–Wallis test showed significant relationship between the number of bacterial colonies and seasons of the year (P<0.05) [48]. According to ANOVA test, there was a significant relationship between different seasons (winter and spring) and number of bacterial colonies (P<0.05). The average highest bacterial colonies in this study were observed during highest PM10, PM2.5 concentrations warm semester (Figs. S3 and S4). The results of this study is similar to the results reported by Shahsavani et al. [49]. From the present study it can be concluded that dust events are the main factors affecting on the number of bioaerosols in the air. However, humidity is the next environmental factor affecting on bioaerosol concentration in the atmosphere [27]. There was insignificant positive correlation between the levels of bacteria and temperature based on the spearman analysis (P>0.05). This was due to the insignificant change of air temperature during dusty and non-dusty days (P>0.05) mainly because most of samples were taken during 9-10 am. The results showed an insignificant
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negative correlation between number of bacteria with relative humidity (P>0.05) in Ilam. Also, the results showed a significant positive correlation between number of bacteria with wind velocity (P<0.05). The most common bacterial species isolated in the non-dusty days of the present study were in order
Staphylococcus>
Streptomyces>
Corynebacterium>
Bacillus>
Enterococcus>
Actinosynnema> Nocardioides> Mycobacterium> Proteus (Table 3). The detected and concentration of bacterial species in dusty days were in order Staphylococcus> Streptomyces> Corynebacterium> Bacillus> Actinosynnema> Nocardioides> Enterococcus (Table 3). Staphylococcus and Micrococci are resistant to UV radiation due to the availability of pigments in their cells. Bacillus can survive more during transfer to long distances than other bacteria. Most of bacteria don’t survive under dry conditions and exposure to sunlight. However, spores of Bacillus is somewhat resistant to sunlight, low humidity and nutrients [30, 50]. The highest number of bacterial colonies in the atmosphere of Ilam was Staphylococcus with 30.64 and 146.96 CFU/m3 during non-dusty and dusty days, respectively. In Soleimani et al. the predominant bacterial species in dusts events were Bacillus spp, Micrococcus spp, Streptomyces spp and Staphylococcus spp [44]. In Griffin et al. study the predominant bacterial species during dusts events over the Turkish Mediterranean coastline were Alternaria, Cladosporium, Microsporum and Penicillium [51]. Also in Yuan et al. study in 2012 on the composition of bacterial strains during dust storm events in Beijing, the predominant strains belong to Firmicutes and Actinomycetes [52]. Like this study, the results of African dust plumes showed that the predominant species were gram positive and spore forming bacteria (Bacillus and Microbacterium) that are more resistant against harsh environmental conditions [46].
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Type and species of bacteria isolated from the dust plumes generally depend on the transport distance from the origin. Since some of dust plumes entering Ilam originate from Middle East deserts (Fig. S2), there is a similarity between the type and species of observed bioaerosols in this study with other related studies. The predominant type of bioaerosols colonies isolated form dust plumes in Kuwait were Bacillus, Arthrobacter, Arthrobacter, Cryptococcus, Kurthia, Neisseria, Flavimonas, Pseudomonas, Ralstonia and Staphylococcus [53]. In another study regarding dust plumes in Saudi Arabia, the predominant species were Bacillus, Pseudomonas, and Staphylococcus. The results of Mann–Whitney test of present study showed that the number of bacterial colonies including Actinosynnema, Nocardia, Staphylococcus and Corynebacterium during dusty and non-dusty days has a significant relationship (p<0.05), whilst the number of colonies including Bacillus, Streptococci, and other isolated colonies during dusty and non-dusty days were not significant (p>0.05). Therefore, it can be stated that dust plumes entering Ilam have increased the number of Actinomyces, Nocardia, Staphylococcus and Corynebacterium. As the Table 3 shows, the season of the year influences on the distribution of bacterial spores. Based on Kruskal–Wallis analysis, there was significant relationship between bacterial colonies (except Corynebacterium, Micrococci) and the season of year (p<0.05). 4. Conclusions Ambient air pollution caused by particulate matter is associated with a wide range of environment factors and human health. A better understanding of particulate matter and their effects are necessary for governmental agencies, decision makers, and health professionals to define and implement appropriate mitigation and adaptation policies. Every year, Ilam province is affected by many dust storm events originating from neighbor countries. The comprehensive monitoring of atmospheric PM concentrations and bioaerosol concentrations is vital, not only for 15
environmental management, but also to estimate the health effects of air pollution in the exposed communities. During the one-year study period, 35 dusty days were recorded (PM ≥ 150 µg/m3) in Ilam city. Furthermore, the high concentrations of particulate matter during dust events can have a verity of health effects including cardiovascular and respiratory problems on the residents in the study area. The presence of high levels of bacterial bioaerosols and their significant relationship with dust plumes necessitate the use of proper management strategies in local and regional scale to reduce the occurrence and amounts of dust storms. Acknowledgements This work is financially supported by Tarbiat Modares University. The authors of this study wish to express their sincere gratitude and deep appreciation to the Ilam Meteorological Organization for their help and support throughout this study. The author also would like to thank Prof. Mehdi Zarrei in Sickkids-Hospital in Toronto, Canada for valuable comments and suggestions, allowing us to improve this paper. Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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19
180 147.8
160
148.3
Concentration (µg/m3)
140
PM2.5 PM10
120
Iran Air Clean Standard & NAAQS (PM10)
100.7
Iran Air Clean Standard & NAAQS (PM2.5)
100
76.6 80
63.5
62.9
60
59.6
52.7
56.6 39.8
60 29.7
40 25.3
20
32.1 18.9
14.5
15.3
14
Mar
Apr
May
Jun
Jul
4
5
4
6
5
16.7
21.2
Oct
Nov
5
5
11.5
10.2
Aug
Sep
5
5
11.5
12.5
Dec
Jan
Feb
5
5
5
0
Numbers of sampling days per month
Fig. 1. Average monthly concentration of periodically measured (every 6 days) of PM10 and PM2.5 during study period
20
400 PM2.5
343.9
350
PM10
324.6
Concentration (µg/m3)
300
Iran Air Clean Standard & NAAQS (PM10)
325
Iran Air Clean Standard & NAAQS (PM2.5)
240.8
250
203.9
200
207.2
214.8 150 100
72.3 52.1
50
44.1
57
48
40.3
50.3
0
Numbers of sampling days per month
Fig. 2. Average monthly concentration of PM10 and PM2.5 during dusty days in the study period
21
Bacterial Colonies CFU/m3
100
PM10 Iran Air Clean Standard & NAAQS (PM10) wind speed
1300 1200 1100 1000 900 800 700 600
80
Relative Humidity Temperature
60
40
20
500 400 300
0
200 100 -20 Mar Mar Mar Mar Apr Apr Apr Apr Apr May May May May Jun Jun Jun Jul Jul Jul Jul Aug Aug Aug Aug Sep Oct Oct Oct Nov Nov Dec Dec Dec Jan Jan Feb
0 Date
Fig. 3. Variations of bacterial colonies associated with PM10, relative humidity, Temperature, and wind speed during the study period
22
Relative Humidity (%), Temperature (°C)
bacterial colonies CFU/m3, PM10 (µgr/m3), wind speed (cm/s)
1600 1500 1400
100
Bacterial Colonies CFU/m3 PM2.5
1400 1300 1200 1100
Iran Air Clean Standard & NAAQS (PM10) wind speed
80
Relative Humidity
60
Temperature
1000 900 800 700 600
40
20
500 400 300
0
200 100 -20 Mar Mar Mar Mar Apr Apr Apr Apr Apr May May May May Jun Jun Jun Jul Jul Jul Jul Aug Aug Aug Aug Sep Oct Oct Oct Nov Nov Dec Dec Dec Jan Jan Feb
0
Relative Humidity (%), Temperature (°C)
bacterial colonies CFU/m3, PM10 (µgr/m3), wind speed (cm/s)
1600 1500
Date
Fig. 4. Variations of bacterial colonies associated with PM2.5, relative humidity, Temperature, and wind speed during the study period
Table 1. The average monthly concentration of bacterial colonies (CFU/m3) during study period month Mar Apr May Jun Jul Aug Sep Oct Nov Des Jan Feb
Samples 6 7 5 3 7 5 3 5 4 4 4 3
non-dusty days Ave Max Min SD 81.10 155.48 35.34 47.31 137.48 247.35 61.84 73.28 125.56 219.08 53 70.00 296.82 572.44 113.07 243.07 119.859 188.46 65.62 51.05 105.86 141.34 79.51 25.21 157.75 314.63 67.14 136.41 168.20 321.98 81.27 97.04 132.81 259.13 77.74 85.56 134.68 236.6 63.6 82.93 42.53 91.80 11.8 36.99 21.23 30.00 5.30 13.82
23
dusty days Samples Ave Max 1 77.74 3 644.27 927.56 3 219.08 219.08 3 1020.03 1484.10 2 458.58 965.84 2 591.88 848.06 1 666.96 1 711.60 0
Min 137.48 219.08 530.04 162.54 335.69 -
SD 452.97 35.38 477.56 441.34 362.30 -
Table 2. Comparison of concentration of bacterial colonies (CFU/m3) during non-dusty and dusty days Non-dusty day samples Average Maximum SD Staphylococcus 30.64 141.34 28.33 Streptomyces 24.84 139.50 24.81 Corynebacterium 16.11 70.67 18.24 Bacillus 14.65 92.76 18.13 Enterococcus 10.68 77.74 16.51 Actinosynnema 10.21 74.91 17.89 Nocardioides 7.94 35.34 9.10 Mycobacterium 1.07 56.54 7.77 Proteus 0.17 2.40 0.6 others 9.79 70.67 15.38 Total 125.98 669.96 107.78 Bacteria
24
dusty day samples Average Maximum 146.96 477.03 85.64 318.02 59.27 226.15 48.71 194.35 20 106 45.12 229.68 38.05 164.90 0 0 0 0 52.15 300.35 495.95 1484.10
SD 127.46 112.98 67.85 62 34.22 65.48 5.20 0 0 78.85 427.51
Bacteria Staphylococcus Streptomyces Bacillus Actinosynnema Nocardioides Corynebacterium Enterococcus Micrococci Proteus Others Total
Spring (25 samples) Ave Max SD 106.59 2.10 119.51 41.86 42.8 75.58 38.74 13 54.88 22.8 229.68 50.67 15.23 12.6 30.20 4.59 18.8 59.32 4.24 02.16 12.20 2.26 0.00 11.31 0.00 64.0 0.00 41.19 28.3 70.79 313.5 34.66 379.60
Sumer (18 samples) Ave Max SD 55.00 212.01 60.39 69.73 318.02 85.83 3.59 28.27 8.56 17.21 58.89 20.31 25.29 164.9 47.18 19.68 106.00 30.81 17.28 106.00 32.02 0.00 0.00 0.00 0.00 0.00 0.00 8.73 70.67 18.36 220.54 965.84 259.67
Table 3. Number of bacterial colonies during different seasons (CFU/m 6
25
Autumn (15 samples) Ave Max SD 41.25 139.15 40.16 34.93 139.5 36.40 32.47 92.80 27.60 29.35 185.90 50.25 14.79 35.34 10.94 33.10 92.80 31.10 20.30 71.27 20.67 0.00 0.00 0.00 0.00 0.00 0.00 18.46 62.00 19.35 224.26 711.60 20.73
Winter (14 Samples) Ave Max SD 10.20 35.10 10.48 8.42 49.50 13.36 13.00 42.40 14.28 0.51 70.07 1.89 6.12 35.34 10.13 8.18 28.30 10.63 16.02 77.74 22.04 0.00 0.00 0.00 0.64 2.40 1.06 3.28 24.70 6.99 66.34 236.60 62.65