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Open Access

Peer-reviewed

Research Article

Elemental composition and health risk assessment of PM10, PM2.5, at different microenvironments: Addis Ababa, Ethiopia

  • Asamene Embiale Taye ,

    Roles Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing

    asamene@wldu.edu.et

    Affiliation Department of Chemistry, College of Natural and Computational Sciences, Woldia University, Woldia, Ethiopia

    ⨯
  • Bhagwan Singh Chandravanshi,

    Roles Conceptualization, Supervision, Writing – review & editing

    Affiliation Department of Chemistry, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia

    ⨯
  • Feleke Zewge Beshah,

    Roles Conceptualization, Supervision, Writing – review & editing

    Affiliation Department of Chemistry, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia

    ⨯
  • Endalkachew Sahle-Demessie

    Roles Conceptualization, Writing – review & editing

    Affiliation Department of Chemistry, Missouri University of Science and Technology, Rolla, Missouri, United States of America

    ⨯

Abstract

This study was designed to evaluate the health risks faced by inhabitants living in the slum areas of Addis Ababa, Ethiopia. The levels of PM2.5 and PM10 and elemental composition of the PM10 were measured in indoors (in the kitchen and living room) and outdoors (at the roadside). A total of 75 sampling locations (45 indoor and 30 outdoor) were selected for the study. The levels of PM2.5 and PM10 were determined using an AROCET531S instrument, while an universal air pump was used for the sampling of PM10 for the determination of trace elements by inductively coupled plasma-optical emission spectroscopy (ICP‒OES). The health impacts of PMs on the inhabitants of twelve microenvironments (MEs), where they spend much of their daily time, were estimated. The total amounts of PM2.5 and PM10, and trace metals in PM10 found in the nine or twelve MEs ranged from 10.6–119, 128–185, and 0.007–0.197 μg m-3, respectively. According to the United States Environment Protection Agency (USEPA) guidelines, ten of the twelve MEs can cause significant health problems for inhabitants (HI > 1) due to PM2.5 and PM10. Thus, special attention should be given by stakeholders/inhabitants to minimize the health impacts on long-term exposure. This study assessed the risk of levels of trace elements on the inhabitants who spend most of their daily lives. The study revealed that the lifetime cancer risk values for the individual and cumulative trace elements were within the tolerable range set by the USEPA guidelines.

Citation: Taye AE, Chandravanshi BS, Beshah FZ, Sahle-Demessie E (2024) Elemental composition and health risk assessment of PM10, PM2.5, at different microenvironments: Addis Ababa, Ethiopia. PLoS ONE 19(10): e0309995. https://doi.org/10.1371/journal.pone.0309995

Editor: Worradorn Phairuang, Chiang Mai University, THAILAND

Received: July 3, 2024; Accepted: August 21, 2024; Published: October 25, 2024

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors declare that there are no conflicts of interest.

Introduction

Air pollution is major concern in the world due to its impact on the longevity of humans and ecosystems [1]. Although the world’s air quality has greatly improved, many regions, especially those in developing countries with dense populations, continue to experience poor air quality [2,3]. Indoor and outdoor air pollution in low- and middle-income countries accounts for 99% and 90%, respectively, of the total deaths worldwide [4]. Chronic and acute exposure to polluted air causes a variety of health complexities in humans, including premature death, neurological disorders, gastrointestinal discomfort, hematological disorders, increased cardiopulmonary morbidity and mortality, dermatitis, and cancer [1,2]. The World Health Organization (WHO) has recently released data showing that 17 people die from air pollution-related causes every minute. The data have also indicated that the life expectancy of populations exposed to high levels of PM2.5 decreased the average global life expectancy at birth by approximately 1 year, with decreases of 1.2 to 1.9 years in polluted Asian and African countries [5,6]. Inhabitants of urban areas are much more affected than the rural areas by air pollution due to the expansion of industries, increasing use of biomass as domestic energy, high population density, absence of a good road network, and prevalence of old and poorly maintained vehicles [7–10].

Air pollution in sub-Sahara African (SSA) countries is relatively high due to the use of large amounts of biomass as a fuel source for cooking, limited access to affordable clean fuels, the use of low-efficiency stoves, and the enormous number of old vehicles. The SSA uses approximately 500,000 tons of firewood daily for its daily energy needs [3]. Compared to higher-income homes with effective ventilation systems and a greater likelihood of utilizing high-efficiency stoves, low-income housing is more affected by indoor air pollution [11]. According to a WHO report, the use of inefficient stoves causes the death of 600,000 Africans per year [8,12].

There are variations in the chemical composition of air pollution even within a single nation. This heterogeneity may be caused by varying sociodemographic traits, cultural customs and perceptions, source types and locations, and meteorological circumstances [2,13]. Hence, exposure assessment based on age, sex, activity level, and socioeconomic status is a promising method for remedial action at the individual level. Furthermore, in daily practice, people in the modern world have a much more mobile lifestyle than in recent decades that can be a cause for variation in the contaminant levels of exposure to the inhabitants in multiple locations for different durations. The personal exposure assessment for such people considering a fixed site monitoring method may not be adequately characterized [3,13]. At the same time, the daily activity patterns of individuals have a substantial effect on the total daily intake of pollutants. Thus, spatiotemporal variations in the concentration of contaminants require dynamic cross-ponding measurements of contaminants. Consequently, personal exposure assessments in different microenvironments are a better solution for the determination of pollutants with spatiotemporal variability and for providing more detailed information on individual short-term exposure to indoor and outdoor air pollution [2,3,13]. Therefore, in this study, the individual daily activity patterns in different microenvironments where people spend most of their time are considered in the exposure assessment of the population.

Several studies related to PM2.5 and PM10 and trace metals bound in the particulate matter in developed and developing countries have been reported in the literature [14–20]. However, there are few studies on air pollution in Ethiopia, and that too without examining the synergetic effects of combined microenvironments on health impact [21–23]. Thus, the synergetic impact of combined MEs, as well as the information on the impacts of respirable air pollutants including PM2.5, PM10 and heavy metals bound in PM10 on inhabitants living in metropolitan city such as Addis Ababa is mandatory. Hence, assessment of exposure to air pollutants using the microenvironmental (ME) modeling approach (average exposure is calculated using time spent and time-averaged concentrations at various places) still needs to be implemented [13]. Moreover, health risk assessments (estimates or predictions) for staying and operating in different combined MEs have yet to be reported in Ethiopia. Therefore, the objectives of this study are as follows: (1) to investigate the levels of PM2.5 and PM10 and concentrations of trace elements in PM10, in the kitchen (during cooking time), living room (feeding time), and roadside (commuting time), (2) to calculate the total dose intake of PM2.5, PM10, and trace elements in PM10 at different combined MEs, and (3) to estimate the potential health risk to inhabitants due to PM2.5 and PM10, and trace elements in PM10 at combined MEs. The results of this study can inform policy options and mitigation strategies to reduce exposure to harmful pollutants effectively and efficiently.

Materials and methods

Study region

Addis Ababa, Ethiopia’s capital city, is 2,800 meters above sea level and is situated at 9°1’48"N and 38.74°E latitude and longitude. Addis Ababa city covers 500 km2 with 3,000 km of road network, 45.5% of which is asphalt, and 54.5% is a gravel road [22]. The city is the center of many diplomatic and international organizations (the African Union and the World Economic Commission). Human activities, including daily traffic flow, numerous urban constructions, and industrial activities, impact the overall air quality of the city [24,25].

Microenvironment information

The microenvironments under the study cover the living room (a place where inhabitants eat, study, watch television, discuss and play with their family members), kitchen (an area where inhabitants bake traditional staple food, Injera, using different traditional, improved, and clean stoves; cooking traditional sauce called ‘Wot’ using electricity, kerosene and charcoal of fuels) and roadside (a place where inhabitants are waking, waiting for a taxi and commuting to work during rush hours). These MEs were selected because inhabitants spend most of their daily lives in these places. The pollutant levels in kitchens and roadsides are also expected to be too high. Besides, although the pollutant level in the living room is expected to be low, inhabitants spend more time there than in the kitchen and roadside.

Furthermore, the type and location of the house selected for the study were mainly based on socioeconomic status, family size, altitude, population density, and the willingness of the owner to allow the researcher. Forty-five households from the three sub-cities (fifteen homes from each) were selected for kitchen and living room MEs. In contrast, thirty sampling locations near the city’s major transportation corridors and roadside locations near the downtown roadside were selected for roadside MEs. A purposive sampling method was employed for selecting houses and sampling locations where the level of pollutants is expected to be high. The determination of levels of PM2.5 and PM10, and the levels of trace elements in PM10 were performed at each ME. Then, the integrated exposure assessment based on the total exposure concentration of the pollutants was calculated using Eq 1. Accordingly, the exposure time and amounts of pollutants are considered [26]. The time spent and level of pollutants could vary by location, affecting the total exposure level of people in these MEs. Consequently, the total levels of exposure are calculated as the product of the sum of time spent by a person in different MEs and the time-averaged air pollution concentrations occurring in those MEs divided by the total time spent in all MEs. The mathematical representation of the concept is given in Eq 1 [13,26]: (1) where Cij is the concentration of the pollutant measured in the jth ME of the ith individual; Ei is the exposure concentration of the ith individual; T is the total time spent in all MEs; m is the number of different MEs; and tij is the time spent by the ith individual in the jth ME. Fig 1 displays the sampling region.

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Fig 1. Map showing the sampling area of the ten sub-cities (source: The GADM database).

https://doi.org/10.1371/journal.pone.0309995.g001

Statistical analysis

The Shapiro‒Wilk test was used to assess the normality of the concentrations of PM2.5 and PM10, and trace elements in PM10. The Kruskal‒Wallis test and analysis of variance (ANOVA) were used to test for significant differences in the concentrations of pollutants across each ME. All the statistical tests were reported by considering a p value of 0.05. PM2.5 and PM10 were reported as the geometric mean (GOM) and geometric standard deviation (GSD), while the concentration of trace elements in PM10 was reported as the arithmetic mean and standard deviation. All the statistical data analyses were performed using SPSS (Statistical Package for Social Sciences), Microsoft Excel 2016, and Microcal TM Origin version 8.

Measurement of PM2.5, PM10 and sampling of trace elements in PM10

The levels of PM2.5 and PM10 were determined using AROCET531S (Met One Instrument., OR 07526, USA) within 2 min intervals in each ME. Before entering the field, the instrument was calibrated based on the manufacturer’s operating procedures. The equipment placement was different in each ME’s depending on the inhabitants’ breathing zone. It was 1.5 meters above the ground and 1 m away from the stove during baking of Injera, 1 m above the ground, and 1 m away from the stove/seat during cooking of the Wot. Similar arrangement was also made in the living room.

An universal air pump (SKC 224-PCTX4 Model, SKC Ltd, U.K.) integrated with a glass microfiber filter (Whatman®, GE Healthcare U.K. Limited, Amersham Place, U.K.) inside was used for sampling PM10 for determination of trace elements by ICP‒OES. The sampling device was positioned 1.5 meters above the ground for kitchen (when baking Injera) and roadside MEs, which is the average breathing zone for inhabitants. The kitchen (during cooking) and living room MEs were raised to a height of 1 m. The manufacturer’s manual was used to calibrate the instrument’s flow rate [27]. To eliminate the humidity and VOCs on the filters, the filter paper was dried in an oven at 150°C for two hours before sampling. The PM10-loaded filters were folded and raped with aluminum foil after the sampling process was complete before being brought back to the laboratory. Finally, to extract the elemental makeup of PM10, the wet digestion method developed by the US EPA [28] was used. The literature provides the specifics of the process [27].

Method validation

The precision and accuracy of the method ensure the data quality. Thus, the instruments were calibrated, standard deviations were evaluated, and recovery tests were performed. A series of working standard solutions, 0, 0.5, 1, 2, 3, 4, and 5 μg mL-1 for Ni, Pb, Fe, Cr, Co Cu, Mn, As, Cd, and Sn and 0, 1, 2, 3, 6, 8, and 10 μg mL-1 for B, were prepared from a stock solution of 100 mg L-1. The linearity (r2) of the calibration curves ranged from 0.990 to 0.999, which are acceptable. The method detection limit was calculated using the standard deviation of seven replicate measurements multiplied by three (3 s), which ranged from 0.0001 to 0.003 μg m-3. The percent recovery, determined using the spiking method, was in the range of 92 to 110%, which are within the acceptable range. The details of the calibration curve equations and correlation coefficients for each are shown in S1 Table.

Inhabitants’ health risk assessment of PM2.5 and PM10

The health risk assessment of inhabitants due to PM2.5 and PM10 was performed by considering a method established by the U.S. EPA using the microenvironment (ME) modeling method [29]. Thus, MEs were classified based on type, frequency, and time spent for each activity. The most common activities performed by a particular adult are cooking Wot (two times per day), baking Injera (two times per week), seating in the living room (every day) and commuting to work or another purpose (every day). Consequently, twelve MEs were evaluated (nine possible MEs by considering all activities and three MEs by excluding baking Injera from all) to estimate the health risk of exposed inhabitants. The details of each ME and the parameters used in the risk assessment are given in Table 1. The hazard quotient (HQ) and hazard index (HI) values were used for estimating inhabitants’ cancer and noncancer risk. The average daily intake (ADD) in μg kg-1 day-1 of PM (PM2.5 and PM10) used for calculating HQ was calculated via Eqs 2 and 3. The HQ and HI values were obtained using Eqs 4 and 9, respectively. (2) (3) (4) where ADD is the average daily intake (μg kg-1day-1); ED is the exposure duration (days); IR is the intake rate (m3 day-1); C is the concentration of pollutant in the air (μg m-3); EF is the time spent in polluted ME (days year-1); TA is the exposure time spent for all activities (hours day-1); AT represents the averaging time (DE x 365 days year-1); EL is the length of the exposure period (years); 1 day per 24 h is used as the conversion factor; BW is the body weight of inhabitants (60.7 kg, which is the average weight of an African adult); and RfD for PM2.5 and PM10 are 10 μg m-3 and 20 μg m-3, respectively [12,28,30]. AT is the average time (67 years, which is Ethiopia’s current average life expectancy) [31].

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Table 1. The time required for all activity (TA), exposure frequency (EF), body weight (BW), exposure longevity (EL), average time (days), intake rate (IR) and exposure duration (ED).

https://doi.org/10.1371/journal.pone.0309995.t001

Assessment of the health risk of inhabitants due to trace elements in PM10

PM10 is a pollutant that significantly impacts human health, causing serious disease and premature death worldwide [32]. The air pollutants in general and the trace elements in PM10 can enter the human body through three main exposure routes: inhalation, ingestion, and dermal absorption [33]. The levels of carcinogenic trace elements, including Cd, As, Pb, Cr, and Ni, and noncarcinogenic elements, including Cu, Fe, Zn, and Mn, bound to PM10 were investigated in this study [34]. The U.S. EPA’s integrated risk analysis framework, as expressed in Eqs 5–10, has been implemented to estimate the cancer and noncancer risk of inhabitants by elements in PM10 via ingestion, inhalation, and dermal contact exposure routes [35]. (5) (6) (7) (8) (9) (10) where C refers to the concentration of elements in the air (μg m-3 or mg kg-1); Dinh refers to the daily dose by inhalation (mg kg-1 day-1); Dinge refers to the daily dose by ingestion (mg kg-1 day-1); Dder is the daily dose by dermal contact (mg kg-1 day-1); AT refers to the averaging time (years); inR refers to the ingestion rate (mg day−1, 100 for adult); InhR refers to the inhalation rate for adult (20 m3 day-1); EF refers to the exposure frequency (day.year-1, given in Table 1 for each ME); ED refers to the exposure duration in years (18250 days, assumed starting at age of 17); BW refers to the body weight (kg, 60.5 which average body weight of adult African, LCR or CR refers to the lifetime cancer risk due to carcinogenic elements; IUR refers to the inhalation unit risk ((μg m−3)−1); AF refers to the skin adherence factor (mg cm−2 day−1, 0.07 for adult adult), AT is the averaging time (ED x life expectence (67 years, for non-cancer risk) and ED x 70, years for cancer risk); RfD is the reference dose of each intake path (mg kg−1 day−1, give in Table 2 for each element); SF refers to the slope factor (mg kg−1 d−1, given in Table 2); ABS refers to the dermal absorption factor (unitless, 0.001 for Cd, 0.030 for As and 0.010 for other elements), SA refers to the surface area (cm2, 2011 for adult adult), and G refers to the gastrointestinal absorption factor, (unitless, give in Table 2). LCR or CR refers to the chance of an individual developing cancer [35]

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Table 2. The RfD at different exposure routes and the IUR, SF and G values for different elements [35–37].

https://doi.org/10.1371/journal.pone.0309995.t002

Results and discussion

Average levels of PM2.5 and PM10 at individual microenvironments

The levels of PM2.5 and PM10 in different MEs while performing various activities during the study period are given in Fig 2. The microenvironments included LR (living room), EF (kitchen during cooking Wot using electricity fuel), KF (kitchen during cooking Wot using kerosene fuel), CS (kitchen during cooking Wot using charcoal fuel), RS (roadside during commuting), CF (baking Injera using a clean stove), IS (baking Injera using an improved stove) and TS (baking Injera using a traditional stove). The geometric mean of PM2.5 was found to range from 17.0 (LR) to 190 (TS) in the following order: LR < EF < RS < KF < CS < VF < IS < TS. The PM10 concentration ranged from 77.6% (LR) to 547% (TS) in the following order: LR < EF < KF < CS < CF < RS < IS < TS. The highest amount was recorded at ME using the traditional stove for baking Injera due to the smoke coming from incomplete combustion of biomass [38]. Similar results were observed in previously studies that traditional stove has released more pollutants than improved and clean stove [39,40].

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Fig 2. The level of PM2.5 and PM10 at different microenvironments (CS, IS, TS, EF, CF, KF, LR and RS).

https://doi.org/10.1371/journal.pone.0309995.g002

The ADD and total exposure level at combined microenvironments

The ADD, total exposure level and health risk estimation of the inhabitants were carried out based on two scenarios. (1) When an adult spends her daily time baking Injera, cooking Wot, seating a living room and commuting (A, B, C, D, E, F, G, H and I MEs) and (2) when an adult spends her/his time in the same activity as in scenario 1, excluding baking Injera (AA, BB and CC MEs). The daily average time spent by an adult in each MEs was calculated, and the obtained results showed that an adult spent 10.1, 10.3, 10.5, 10.0, 10.3, 10.5, 10.0, 10.3, and 10.5 h in A, B, C, D, E, F, G, H and I MEs, respectively. The results confirmed that 42.0 to 44.0% of adults’ daily life was lost in these MEs. The total exposure levels of PM2.5 and PM10 in the A, B, C, D, E, F, G, H and I MEs were calculated based on the inhabitants’ exposure times, which ranged from 10.6 to 119 and 128 to 185 μg m-3, respectively. The highest value was observed in ME I, possibly due to the use of a large amount of biomass fuel for baking Injera and charcoal for cooking Wot. Similar result was reported in Kenya by [41], stating that traditional stoves have released large amounts of pollutant.

On the other hand, the total time spent by an adult in the AA, BB and CC MEs was 8.85, 9.28 and 9.08 h, respectively. Thus, the total time spent in the AA, BB and CC MEs accounts for 36.9%, 38.7% and 37.8%, respectively, of the adult’s daily time. The ADDs of PM2.5 and PM10 ranged from 0.860 to 1.59 and 15.6 to 19.4 μg m-3, respectively. The exposure levels of PM2.5 and PM10 in the AA, BB and CC MEs ranged from 7.08 to 156, with the maximum and minimum values occurring in the CC and AA MEs, respectively, as presented in Table 3. The detailed values for the average daily doses and total exposure levels of PM2.5 and PM10 at different MEs are given in Table 3.

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Table 3. The average daily dose (ADD) and total exposure level ([sum (Cijxtij)]/T) of PM2.5 and PM10 at different MEs.

https://doi.org/10.1371/journal.pone.0309995.t003

Health risk assessment of PM2.5 and PM10 at combined microenvironments

As inhabitants spend a larger proportion of their daily time in the studied MEs, they have high probability of getting non-cancer risk. Table 4 provides a summary of the HQ and HI calculations for the noncarcinogenic hazards of PM2.5 and PM10 for an adult depending on the total exposure level at each ME. The HQ values is calculated by taking into account of each pollutant’s separate effects. Thus, the HQs of PM2.5 and PM10 across the MEs (A, B, C, D, E, F, G, H, and I) ranged from 0.130 to 1.52 and from 0.777 to 1.15, respectively. The HQ values of PM2.5 and PM10 in the G’, H’, and I’ MEs were higher than those in the other units, which indicates that inhabitants in these MEs had a significant noncancer risk. The I and A MEs had the maximum and lowest HQ values, respectively. The combined effects of PM2.5 and PM10 were evaluated using HI, which was found to range between 0.907 (A) and 2.67 (I) MEs. An adult who spends more time in any of these MEs may be at risk for non-cancer health problems caused by PM2.5 and PM10, according to the results, which showed that all MEs, with the exception of MEs A and B, have an HI value greater than unit.

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Table 4. Hazard quotient (HQ) and hazard index (HI) results for PM2.5 and PM10 at different MEs.

https://doi.org/10.1371/journal.pone.0309995.t004

Furthermore, the noncancer health risk of an adult who did not bake Injera was estimated by considering the AA, BB, and CC MEs. The HQs of PM2.5 and PM10 at the AA, BB, and CC MEs were 0.265–0.677 and 2.38–2.96, respectively. Thus, the HQs of PM10 at the AA, BB, and CC MEs were higher than one, and hence inhabitants at these MEs might have a significant health problem. Similarly, the cumulative effects of the PM2.5 and PM10 concentrations on the AA, BB, and CC MEs ranged from 2.65–3.64, indicating that inhabitants in these MEs might have significant health effects. Therefore, minimize the staying in AA, BB and CC microenvironments is highly recommended to prevent the health impacts.

The level of trace elements across each microenvironment

The corresponding levels of Fe, Cu, Mn, B, Zn, Pb, Cr, Cd, Sn, As, Ni and Co were 0.013 (EF)– 0.254 (IS); BDL (CS, TS and IS)– 0.057 (RS); 0.001 (CF)– 0.444 (RS); 0.01 (LR)– 0.632 (IS); 001 (LR)– 0.351 (IS); 0.001 (LR)– 0.109 (RS); 0.02 (EF)– 0.013 (RS); 0.0007 (EF)– 0.027 (RS); 0.001 (EF)– 0.120 (RS); 0.002 (CF)– 0.036 (RS); 0.003 (LR)– 0.044 (RS); and 0.001 (EF)– 0.04 (RS). The results revealed that the highest levels of most of the trace elements were found in the outdoor microenvironment at the roadside (RS), except for boron and zinc, which were highest in the kitchen microenvironment during baking of Injera using an improved stove. This might be due to high traffic congestion, which releases more trace metals through smoke [38]. Similarly, the highest level of B and Zn in improved stove might be due to their micronutrient nature for a plant growth, and that burning of such plant sources resulted for high amount of the metals in particulate matter [42,43]. The general patterns of the investigated elements in different microenvironments are depicted in Fig 3.

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Fig 3. The level of trace elements at different microenvironments (CS, IS, TS, EF, CF, KF, LR and RS).

https://doi.org/10.1371/journal.pone.0309995.g003

Exposure level of trace elements in PM10

The exposure levels of the analyzed elements at the A, B, C, D, E, F, G, H, and I MEs ranged from 0.007 (Cr) to 0.179 (Zn), 0.007 (Cr) to 0.018 (Zn), 0.008 (Cr) to 0.197 (Zn), 0.007 (Cr) to 0.179 (Mn), 0.007 (Cr) to 0.175 (Mn), 0.008 (Cr) to 0.172 (Mn), 0.007 (Cr) to 0.180 (Mn), 0.007 (Cr) to 0.176 (Mn) and 0.008 (Cr) to 0.172 (Mn) μg m-3, respectively. The results revealed that the level of Cr was the lowest in all MEs, whereas the levels of Zn in A, B, and C and of Mn in E, F, G, H, and I were the highest. In addition, the total exposure level, regardless of the type of metal, ranged from 0.657 (H) to 0.796 (A) μg m-3 in the order of H < I < G < E < F < D < B < C < A. On the other hand, the total exposure levels of the elements in the AA, BB and CC MEs were calculated, and their corresponding values ranged from 0.007 (Cr) to 0.203 (Mn), 0.007 (Cr) to 0.193 (Mn) and 0.007 (Cr) to 0.198 (Mn), respectively. The overall metal exposure levels, regardless of the presence of trace elements, were 0.734, 0.694 and 0.744 μg m-3 for the AA, BB, and CC MEs, respectively. The exact values for the total exposure level of each element at each ME are summarized in Table 5.

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Table 5. The exposure levels of trace elements in combined MEs (mean ± SD μg m-3 per microenvironment).

https://doi.org/10.1371/journal.pone.0309995.t005

Health risk assessment of trace elements

Although baking Injera is not a daily routine for inhabitants, it has contributed to the intake of a large amounts of pollutants during the time of baking. As a result, the health risk of the adult was estimated by considering two scenarios: (1) when an adult was baking Injera A, B, C, D, E, F, G, H, and I MEs) and (2) when the adult was not baking Injera (AA, BB and CC MEs). Thus, inhabitants’ adverse carcinogenic and noncarcinogenic health risks are estimated using three exposure routes (ingestion, inhalation, and dermal contact) at each ME under two scenarios. The study results for scenarios 1 and 2 are shown in Tables 6 and 7, respectively.

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Table 6. Health risk assessment (for both carcinogenic and noncarcinogenic risks) of heavy metal exposure for inhabitants at different MEs.

https://doi.org/10.1371/journal.pone.0309995.t006

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Table 7. 1Health risk assessment (both carcinogenic and non-carcinogenic risks) form heavy metal exposure of woman via inhalation, ingestion, and dermal exposure pathways at ‘AA’, ‘BB’ and ‘CC’ MEs.

https://doi.org/10.1371/journal.pone.0309995.t007

Risk assessment at the A, B, C, D, E, F, G, H, and I microenvironment

The cumulative and individual elemental risk of inhabitants in each ME were assessed based on the method established by the U.S. EPA (i.e., using HQ and HI) [44]. The cancer and noncancer risks to inhabitants from exposure to trace elements were determined for each ME through ingestion, inhalation and dermal contact. The analysis was performed to determine the commutative and individual effects of trace elements using HQ, HI, and LCR values. The cumulative impact is calculated based on each route’s total element intake through all exposure routes (sum of HI of each element) and the total element intake (sum of HI of all elements in a single route). The individual element risk is based on the intake of a single element through each exposure route (HQinh, HQing and HQder) and the intake of a single element through the three exposure routes (sum of HQinh, HQing and HQder). The obtained results indicated that the adult had a negligible noncarcinogenic risk because the individual element HQ values in both cases for all the elements in all the microenvironments were less than 1. However, the cumulative effect in both cases showed that the HI was greater than one, which indicates that the analyzed elements had a significant health impact on the exposed inhabitants due to their cumulative effect. Different exposure pathways have different contributions to the total exposure level. The dermal contact pathway has the lowest subsidy. Inhalation is the dominant route, followed by ingestion and dermal contact routes, for all MEs. Regarding the individual elements, Mn, Cd and As account for the majority of the commutative effect. The general trends of the HI values followed a decreasing order of I > H > F > C > E > B > G > D > A.

An adult’s cancer risk due to carcinogenic elements was estimated as an individual and cumulative effect in a manner similar to that used for the noncancer risk assessment. LCR values for many individual elements at all MEs through inhalation and ingestion routes were within the tolerable range set by the U.S. EPA (1x10-6 to 1x10-4). However, except for Cr in dermal contact, the LCR values of all the tested elements are below the limit value (1x10-6). The ingestion route is the predominant exposure route, followed by inhalation and dermal contact. The cumulative LCR for all metals was within the tolerable range set by the USEPA. Thus, inhabitants have a low probability of developing cancer in their lifetime. Nevertheless, the LCR values for all the elements are tolerable and below the standard. Furthermore, Cr and Cd contribute more to the LCR. Hence, wearing masks might reduce the intake of PM10, minimizing its effect [28].

Similarly, the cancer and noncancer risk of inhabitants who spent time in the AA, BB and CC MEs were also estimated for the A, B, C, D, E, F, G, H and I MEs. The results revealed that both individual elements (a single element in each route and a single element in all routes) and the cumulative effect of trace elements (all elements in a single route and all elements in all routes) in the AA, BB and CC MEs were less than unity, which indicates that a adult in these MEs has limited potential health impacts from noncarcinogenic risk. Mn, Cr, and Cd contributed the most to the total exposure. In addition, although an adult is less likely to have a noncancer risk, inhabitants who spent more time in CC MEs were more likely to have a noncancer risk than inhabitants who spent more on BB or AA MEs. This might be due to charcoal fuel, which contributes to high levels of pollutants. Inhalation is the predominant route of exposure, in contrast to dermal and ingestion. At the same time, many individual elements and their cumulative values of LCR in all routes, except dermal contact, were found to be in the tolerable range (1x10-6 to 1x10-4) [28]. Cr and As are the two dominant elements for the total exposure routes.

Conclusion

The total exposure levels of PM2.5 and PM10 and the elemental composition of PM10 at different combined MEs A, B, C, D, E, F, G, H, and I, AA, BB and CC were assessed. The highest exposure levels were observed in I ME (cooking Wot using charcoal fuel, baking Injera using traditional stove, seating in living room for family discussion, and commuting to work in roadside), that the time spent in this ME should be minimized to reduce the health impacts. The HQs of PM2.5 for G, H, and I MEs, and PM10 for G, H, I, AA, BB and CC MEs are > 1, indicating that inhabitants at these MEs might have significant non-cancer health problems. The HI values of PM2.5 and PM10 for all MEs except ‘A’ and B, were >1, revealed that inhabitants at all the MEs, except at the A and B MEs, could have significant health problems due to the synergetic effect of the pollutants. Similarly, the individual metal non-cancer risk assessment showed no significant impact (HQ <1), while the cumulative impact of trace elements showed a significant impact (HI >1) in all MEs. The lifetime cancer risk assessment for carcinogenic elements in all MEs were found within the tolerable range set by U.S. EPA threshold values, which means 1 adult from a million inhabitants can be at risk of developing cancer in her lifetime. Moreover, among the activities, baking Injera using traditional stove is the highest pollutant contributor that an immediate alternative solution should be implemented.

Overall, awareness of the public and stakeholders on the health impacts of PM2.5 and PM10 and elements in PM10 at these MEs is highly recommended. The study also suggested that stakeholders look for alternative solutions to reduce air pollution, including promoting the use of clean fuels through minimizing costs, improving of the efficiency of existed stoves, promoting public bus transportation, and reducing taxation of electric cars. Inhabitants also recommended using more efficient and clean stoves, as well as well-ventilated kitchens. Moreover, minimizing the frequency and time spent at MEs with high levels of pollutants (such as G, H, I, AA, BB and CC) is another mechanism for mitigating health problems. Additional studies on the assessment of the toxic organic pollutants in the both indoor and outdoor air and the chemical composition of plant biomass, which is most commonly used as fuel for most Ethiopia, is highly recommended.

Supporting information

S1 Table. The calibration curve equation for the eleven elements in PM10.

https://doi.org/10.1371/journal.pone.0309995.s001

(DOCX)

Acknowledgments

The authors would like to express their sincere acknowledgement to all the participants.

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