Comprehensive Health Risk Assessment of PM_2.5 Chemical Composition in an Urban Megacity: A Case Study from Greater Cairo Area

Abstract

While many studies on the health effects of PM_2.5 exist, the risks of PM_2.5 species remain largely unexplored in Middle Eastern and North African countries. This study assesses, for the first time, the carcinogenic and non-carcinogenic health risks for elements, polycyclic aromatic hydrocarbons (PAHs), phthalates, polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (DL-PCBs) bound to PM_2.5 in the Greater Cairo Area. A total of 59 samples were collected from an urban site in Dokki (November 2019–January 2020). Chemical analysis showed higher concentrations of PCDFs (5418 fg/m³) than PCDDs (1469 fg/m³), with DL-PCBs being the most abundant (6577 fg/m³). Health risk assessment for inhalation showed non-carcinogenic risks for all age groups, especially for newborns. Manganese (Mn) and lead (Pb) posed the highest elemental non-carcinogenic risk, while the hazard quotient (HQ) for PAHs exceeded 1 across all ages. PCDDs, PCDFs, and DL-PCBs showed an estimated cancer risk reaching 10⁻⁶ in adults, indicating a significant health concern. Key contributors to cancer risk included arsenic (As), chromium (Cr(VI)), and vanadium (V), which accounted for over 80% of the total elemental cancer risk. Major and trace elements posed the highest lifetime cancer risk, nearly 37 times the acceptable level.

1. Introduction

Air pollution continues to be a critical environmental and public health threat [1]. Particulate matter (PM), especially PM_2.5, comprising particles with an equivalent aerodynamic diameter less than 2.5 μm, represents the foremost environmental contributor to morbidity and leads to high premature mortality on a global scale [2]. In recent decades, a robust body of epidemiological evidence has established a significant association between exposure to PM_2.5 and all-cause mortality, particularly cardiopulmonary illnesses, including lung cancer and a range of non-communicable diseases and metabolic disorders [3]. However, the strength of such an association varies considerably across different studies. This variability can be partially attributed to the reliance on bulk PM mass concentration as a primary exposure metric. But such an approach does not take into consideration the differences in PM’s physical and chemical properties, which are influenced by emission sources and the site’s typology [4,5,6]. Consequently, considerable research has attempted to identify specific PM components that may serve as more sensitive predictors of its health impact [7]. For instance, polycyclic aromatic hydrocarbons (PAHs) have received considerable attention in recent years due to their persistent, bio-accumulative, carcinogenic, and mutagenic characteristics. Several papers have linked PAHs exposure to various health issues, including cataracts, renal damage, as well as cancers of the skin, liver, lungs, and gastrointestinal tract [8]. Polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), and polychlorinated biphenyls (PCBs) constitute another class of persistent organic pollutants (POPs) of anthropogenic origins [9]. Due to their resistance to metabolic degradation, they accumulate in the fatty tissues of humans and animals [10]. Many of these compounds are associated with skin toxicity, immune system impairment, cancer, and adverse effects on reproduction, development, and endocrine functions [10]. Other components found in PM_2.5, such as phthalates, were also recognized as endocrine-disrupting compounds [11]. Furthermore, trace elements in PM_2.5 have been demonstrated to elevate the incidence of respiratory infections and exacerbate asthma conditions [3].

Megacities, with populations exceeding 10 million, face considerable air quality challenges. Rapid urbanization and increasing energy demand from transport, industrial, and commercial activities have led to high pollution levels, raising urban residents’ health risks and augmenting the socioeconomic burden [12]. Despite extensive research efforts, including air quality monitoring, field measurements, and modeling, the emission sources and processes driving high concentrations of key pollutants such as ozone and secondary particulate matter in these megacities remain insufficiently understood, limiting effective mitigation and accurate air quality forecasting [12]. The Greater Cairo Area (GCA), one of the world’s most polluted megacities, encompassing three governorates (Cairo, Giza, and Qalyubia), had a population of nearly 25 million residents with 4.06 million vehicles on the streets in 2019–2020 [13,14]. In addition, the surrounding desert and predominantly semi-arid surface soils in GCA contribute to frequent exceedance levels of PM_2.5 concentrations in the atmosphere, surpassing the PM_2.5 World Health Organization’s 24-h air quality standard (15 µg/m³), as well as its equivalent national Egyptian standard (80 µg/m³) [15,16].

Therefore, investigating the health risks associated with human exposure to various toxic components of PM_2.5 is of paramount importance; however, studies in this area remain limited, focusing on a limited family of pollutants. For instance, Hassan [17] found that inhabitants of El Giza and Ramsis Square areas in GCA were at a higher cancer risk due to exposure to heavy metals. In addition, Khairy and Lohmann [8] assessed the lifetime cancer risk posed by PAHs to both children and adults in Alexandria. Their analysis revealed that the incremental lifetime cancer risk exceeded the acceptable threshold of 10⁻⁶ through dermal and ingestion pathways at all sampling locations, while the inhalation route presented elevated risks specifically at industrial and traffic-affected sites. Furthermore, Shetaya et al. [18] calculated the carcinogenic and non-carcinogenic risks linked to toxic trace elements in PM_2.5 for residents of the GCA, revealing markedly increased risks attributable to 12 metal(loid)s. Notably, Pb emerged as the predominant contributor, accounting for 56% of non-carcinogenic and 83% of carcinogenic risks. It is noteworthy that Wheida et al. [19] conducted a health impact assessment in Greater Cairo, employing concentration-response functions and the WHO methodology to estimate excess mortality due to long-term exposure to PM_2.5, NO₂, and O₃. Their findings indicated that PM_2.5 and NO₂ pose major health risks, with 11% and 8% of non-accidental mortality in individuals over 30 years attributed to these pollutants, respectively. However, this assessment did not consider the chemical composition of PM_2.5, potentially underestimating the actual health impacts associated with its toxic components.

Therefore, assessing the cumulative health risks posed by different families of PM_2.5 is crucial for public health policy and prevention strategies. However, existing studies in Egypt have primarily focused on either PM_2.5 mass or limited pollutant classes, often overlooking the cumulative effects and age-specific exposure pathways. To our knowledge, this is the first study in GCA that comprehensively assesses both carcinogenic and non-carcinogenic health risks associated with inhalation across multiple pollutant families, including PAHs, phthalates, PCDDs, PCDFs, DL-PCBs, and elements, bound to PM_2.5. These findings are essential for guiding targeted air quality interventions and public health strategies in megacities like Cairo, where millions are chronically exposed to high pollution levels.

2. Materials and Methods

2.1. Sampling Site

The sampling site was previously described in Farah et al. [20] and is briefly presented in this section. The campaign was conducted between 26 November 2019, and 27 January 2020 (sampling was stopped at this date due to the COVID-19 pandemic-related restrictions settled for at least one year), on the roof of the National Research Centre (NRC) (30°02′11.0″ N 31°12′22.4″ E) in Giza (Dokki) (Figure 1). The NRC is situated approximately 3 km east-southeast of Cairo’s city center. The Dokki district is among GCA’s most active and densely populated areas, known for its dynamic urban activities and consistently heavy traffic throughout the year. The sampling equipment was installed on top of a six-level building, which offered a clear, unobstructed 360° view for data collection.

2.2. Sampling Strategy

PM_2.5 samples were collected continuously over 24 h, with filter replacements occurring daily at 10 a.m. throughout the sampling period. A high-volume sampler operating at a flow rate of 30 m³/h (CAV-A/mb, MCV S.A., Spain) was utilized, and 150 mm quartz microfiber filters were employed for particle collection. To ensure the removal of any organic impurities, filters were pre-baked at 550 °C for 12 h before use [21]. A total of 59 samples were collected, in addition to two blanks, and stored at −20 °C until further analysis.

2.3. Chemical Analysis

The analytical methodology for quantifying PAHs and phthalates was previously described by Farah et al. [20]. Briefly, this approach involved the extraction of compounds from quartz filters through sonication, using a mixture of acetone and dichloromethane solvents. The resulting extract was then concentrated to a volume of 300 μL under a gentle flow of nitrogen gas. Subsequent analysis was performed using gas chromatography coupled with mass spectrometry (ISQ 7000, Thermo Scientific, Waltham, MA USA). The detection limits ranged from 0.0002 to 2 ng/m³ (Table S1). Method accuracy was validated through recovery experiments, in which blank filters were spiked with known concentrations of standard solutions, resulting in recovery rates between 80% and 97%. Analytical precision was confirmed by assessing the repeatability of response factors across five successive injections of authentic standards, with relative standard deviations remaining below 10%. The analytical uncertainty is based on the compound quantification limit, repeatability, and concentration. The total uncertainty, which includes both analytical uncertainty and that associated with the mass flow measurement of the sampler, was found to be in the range of 9–30% at 2σ [22].

Major and trace elements (Al, V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Sb, and Pb) were analyzed in an Agilent 7500ce Inductively Coupled Plasma-Mass Spectrometer (ICP-MS) using the methodology described by Iakovides et al. [23]. Prior to analysis, punches of the quartz filters (2 × 1.5 cm²) were digested in a microwave oven (Speedwave Entry, Berghof) with 5 mL of 65% pure nitric acid (Suprasolv, Merck, Darmstadt, Germany), following a specific protocol [23]. Seven-level calibration curves (R² > 0.9999) were used to quantify each sample set (30 samples/batch) using certified standard solutions (CPA Chem). Ge, In, and Bi were used as internal standards to monitor the analytical response [23]. All concentrations reported herein were blank and recovery corrected. Method detection limits (MDLs) [23] ranged from 0.004 pg/m³ (Mn) to 7.65 (Al) ng/m³ (Table S1). Chemical analysis was routinely evaluated using predefined certified solutions, with absolute recoveries ranging between 90% and 105%. The validity of the entire protocol of analysis is assessed twice per year via proficiency testing organized by the International Atomic Energy Agency-IAEA (NSIL) and the European Monitoring and Evaluation Program (EMEP) (chemical coordinating center).

PCDDs, PCDFs, and DL-PCBs were analyzed using high-resolution gas chromatography coupled with high-resolution mass spectrometry. The analysis was conducted by MicroPolluants Technologie SA (Saint Julien Les Metz, France) following the methodologies established by the USEPA under methods 1613 and 1668 [4].

2.4. Health Risk Assessment Methodology

Health risk assessment methods and values used in the process integrated estimates of exposure intensity with appropriate toxicological values to determine the likelihood of adverse effects in potentially exposed populations in Cairo. In this study, we followed the United States Environmental Protection Agency (USEPA) approach [24,25,26], estimating both carcinogenic and non-carcinogenic risks through inhalation. Measured mean concentrations of chemical species were used to estimate exposure levels within the target population over a defined period. We also followed the Toxic Equivalent approach using toxic equivalent factors (TEFs) to determine the toxic potency of complex mixtures of PAHs, PCDDs, PCDFs, and DL-PCBs [27,28] (Tables S2 and S3). Specifically, B[a]P_eq, the benzo[a]pyrene equivalent, expresses the toxicity of PAH mixtures relative to benzo[a]pyrene, while TEQ, the toxic equivalent, quantifies the overall toxicity of PCDDs, PCDFs, and DL-PCBs relative to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). B[a]P_eq and TEQ were calculated as follows:

$${\mathrm{B}\left[\mathrm{a}\right]\mathrm{P}}_{\mathrm{e}\mathrm{q}}={\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{C}}_{\mathrm{i}}\times {\mathrm{T}\mathrm{E}\mathrm{F}}_{\mathrm{i}}$$

(1)

$$\mathrm{T}\mathrm{E}\mathrm{Q}={\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{C}}_{\mathrm{j}}\times {\mathrm{T}\mathrm{E}\mathrm{F}}_{\mathrm{j}}$$

(2)

The concentration of hexavalent chromium (Cr(VI)) was estimated as one-seventh of the total chromium concentration [18,29,30,31].

Exposure estimation schemes are described elsewhere. Briefly, the assumed average daily dose (ADD) (mg/kg/day) and exposure concentration (EC_inhalation) (mg/m³) for a specific toxicant were computed as follows:

$${\mathrm{A}\mathrm{D}\mathrm{D}}_{\mathrm{i}-\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}={\displaystyle \frac{{\mathrm{C}}_{\mathrm{i}}\times {\mathrm{I}\mathrm{R}}_{\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}\times \mathrm{E}\mathrm{D}\times \mathrm{E}\mathrm{F}\times \mathrm{C}\mathrm{F}}{\mathrm{B}\mathrm{W}\times \mathrm{A}\mathrm{T}}}$$

(3)

$${\mathrm{E}\mathrm{C}}_{\mathrm{i}-\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}={\displaystyle \frac{{\mathrm{C}}_{\mathrm{i}}\times \mathrm{E}\mathrm{T}\times \mathrm{E}\mathrm{D}\times \mathrm{E}\mathrm{F}\times \mathrm{C}\mathrm{F}}{\mathrm{A}\mathrm{T}\times 24}}$$

(4)

where C_i is the measured concentration expressed in ng/m³ for inhalation exposure. The definitions of the other parameters, along with their respective units and values, are summarized in

Table 1. Exposure factors utilized in the health risk assessment methodology.

Exposure Parameters	Abbreviation	Unit	Newborn	Child	Adolescent	Adult	Reference
			0 to <1 Year	1 to <12 Years	12 to <18 Years	18–70 Years
Inhalation intake rate	IRinhalation	m3/day	5.4	11.2	15.6	15.5	USEPA [26]
Body weight	BW	kg	7.8	25	61	72	USEPA [32]
Exposure frequency	EF	Days/year	350	350	350	350	USEPA [33]
Exposure time	ET	h/day	6	6	8	8	Dahmardeh Behrooz et al. [34]
Exposure duration	ED	Years	1	11	6	52	USEPA [26]
Average timing	AT	Days	AT = ED × 365 days for non-carcinogens AT = 70 years × 365 for carcinogens				USEPA [24]
Conversion factor	CF	kg/mg	10−6

for the various age categories relevant to this study: newborns (0 to <1 years), children (1 to <12 years), adolescents (12 to <18 years), and adults (18 to 70 years). Due to the absence of specific exposure factor data for Egypt (body weight, inhalation rate, and exposure duration), generic values obtained from the USEPA reports have been employed (Table 1).

2.4.1. Non-Cancer Risk Assessment

The estimation of non-cancer risks associated with inhalation for specific species was conducted using the hazard quotient (HQ_i) as follows:

$${\mathrm{H}\mathrm{Q}}_{\mathrm{i}}={\displaystyle \frac{{\mathrm{A}\mathrm{D}\mathrm{D}}_{\mathrm{i}}}{{\mathrm{R}\mathrm{f}\mathrm{D}}_{\mathrm{i}}}} \mathrm{or} {\mathrm{H}\mathrm{Q}}_{\mathrm{i}}={\displaystyle \frac{{\mathrm{E}\mathrm{C}}_{\mathrm{i}-\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}}{{\mathrm{R}\mathrm{f}\mathrm{C}}_{\mathrm{i}}}}$$

(5)

where ADD_i (in mg/kg/day) is the average daily dose, EC_i (in mg/m³) is the exposure concentration through inhalation, RfD (in mg/kg/day) and RfC (in mg/m³) are the USEPA reference dose and reference concentration, respectively. Values for RfD and RfC are presented in Table S4.

The Hazard Index (HI) for a specific chemical family was computed as follows:

$$\mathrm{H}\mathrm{I}\left(\mathrm{I}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\right)={\sum }_{\mathrm{i}}{\mathrm{H}\mathrm{Q}}_{\mathrm{i}}$$

(6)

When HQ_i and HI are equal to or less than 1, this indicates that adverse effects are not likely to occur. Conversely, when it exceeds 1, this indicates an exceedance of the non-cancer health guidelines [30,35].

2.4.2. Cancer Risk Assessment

The cancer risks (CR_i) associated with the inhalation exposure pathway were computed using the equations outlined below:

$${\mathrm{C}\mathrm{R}}_{\mathrm{i}-\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}={\mathrm{L}\mathrm{A}\mathrm{D}\mathrm{D}}_{\mathrm{i}-\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}\times {\mathrm{C}\mathrm{S}\mathrm{F}}_{\mathrm{i}}$$

(7)

$${\mathrm{C}\mathrm{R}}_{\mathrm{i}-\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}={\mathrm{E}\mathrm{C}}_{\mathrm{i}-\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}\times {\mathrm{I}\mathrm{U}\mathrm{R}}_{\mathrm{i}}$$

(8)

where LADD_i is the lifetime average daily dose, which differs from ADD primarily in terms of average timing (AT). LADD considers a total exposure duration of 25,500 days, based on an average human lifespan of 70 years multiplied by 365 days per year. CSF_i represents the cancer slope factor (mg/kg/day), and IUR is the inhalation unit risk (mg/m³). Values for CSF and IUR are presented in Table S5.

The cancer risk (CR) associated with multiple toxicants from a specific chemical family to which an individual may be exposed to is determined by summing the CR_i and can be calculated as follows:

$$\mathrm{C}\mathrm{R}\left(\mathrm{I}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\right)={\sum }_{\mathrm{i}}{\mathrm{C}\mathrm{R}}_{\mathrm{i}}$$

(9)

The calculation of the individual lifetime cancer risk (ILCR) adjusting for the different age groups was performed as follows:

$$\mathrm{I}\mathrm{L}\mathrm{C}\mathrm{R}={\mathrm{C}\mathrm{R}}_{\mathrm{n}\mathrm{e}\mathrm{w}\mathrm{b}\mathrm{o}\mathrm{r}\mathrm{n}}\times {\displaystyle \frac{1}{70}}+{\mathrm{C}\mathrm{R}}_{\mathrm{c}\mathrm{h}\mathrm{i}\mathrm{l}\mathrm{d}\mathrm{r}\mathrm{e}\mathrm{n}}\times {\displaystyle \frac{11}{70}}+{\mathrm{C}\mathrm{R}}_{\mathrm{a}\mathrm{d}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}}\times {\displaystyle \frac{6}{70}}+{\mathrm{C}\mathrm{R}}_{\mathrm{a}\mathrm{d}\mathrm{u}\mathrm{l}\mathrm{t}}\times {\displaystyle \frac{52}{70}}$$

(10)

3. Results

3.1. Atmospheric Concentrations

Table 2. Average, minimum, and maximum concentrations of compounds, reported in ng/m³, with values below the detection limit indicated as “<D.L.” The concentrations of PAHs and phthalates were retrieved from Farah et al. [20]. The detection limits of these compounds can be found in Table S1.

Pollutant	Mean (ng/m3)	Minimum (ng/m3)	Maximum (ng/m3)
Elements
Al	3861	1041	21359
Zn	322	39	1366
Pb	182	9.1	1473
Mn	83	20	320
Cu	69	8.5	353
V	12.1	2.9	42
Cr	8.7	2.3	34.1
Ni	8.2	2.3	23
As	4	0.5	12.5
Sb	3.6	0.3	14
Co	1.7	0.3	6.9
Cd	1.1	0.2	3.4
PAHs
∑PAHs	59	7.3	617
B[a]Peq	14	0.8	16
Phthalates
Bis(2-ethylhexyl)phthalate (DEHP)	598	99	2201
Dibutylphthalate (DnBP)	36	<D.L.	252
n-butylbenzylphthalate (BBP)	0.5	<D.L.	2

presents the average, minimum, and maximum concentrations of the studied compounds, including major and trace elements, PAHs, and phthalates. Among the elements assessed, Al exhibited the highest concentration at 3861 ng/m³. Among PAHs, indeno [1,2,3-c,d]pyrene, benzo[g,h,i]perylene, and benzo[a]pyrene were identified as the most abundant compounds, contributing to 55% of the total PAHs concentration [20]. The PAHs concentration measured in this study was significantly lower than the value reported by Hassan and Khoder (2310 ng/m³) for the GCA during the winter of 2007. In contrast, the observed PAHs levels were higher than those obtained in Lebanon at the Zouk site in winter (4.35 ng/m³) [22], as well as in Bab Ezzouar City, Algeria, at an urban site (10.3 ng/m³) [36]. Among phthalates, bis(2-ethylhexyl)phthalate (DEHP) had the highest concentration, accounting for 94% of the total.

Moreover, the total concentration of PCDDs was 1469.2 fg/m³, with octachlorinated dibenzo-p-dioxin (OCDD) emerging as the most abundant contributor at 645.6 fg/m³ (

Table 3. Averaged concentrations and TEQ of PCDDs, PCDFs, and DL-PCBs, expressed in fg/m³.

Compounds	Abbreviation	Mean (fg/m3)
PCDDs
2,3,7,8-tetrachlorinated dibenzo-p-dioxin	2,3,7,8 TCDD	11
1,2,3,7,8-pentachlorinated dibenzo-p-dioxin	1,2,3,7,8 PeCDD	60
1,2,3,4,7,8-hexachlorinated dibenzo-p-dioxin	1,2,3,4,7,8 HxCDD	52
1,2,3,6,7,8-hexachlorinated dibenzo-p-dioxin	1,2,3,6,7,8 HxCDD	110
1,2,3,7,8,9-hexachlorinated dibenzo-p-dioxin	1,2,3,7,8,9 HxCDD	72
1,2,3,4,6,7,8-heptachlorinated dibenzo-p-dioxin	1,2,3,4,6,7,8 HpCDD	519
octachlorinated dibenzo-p-dioxin	OCDD	646
Sum PCDDs	1469
TEQ PCDDs	99.5
PCDFs
2,3,7,8 tetrachlorinated dibenzofuran	2,3,7,8 TCDF	419
1,2,3,7,8 pentachlorinated dibenzofuran	1,2,3,7,8 PeCDF	348
2,3,4,7,8 pentachlorinated dibenzofuran	2,3,4,7,8 PeCDF	536
1,2,3,4,7,8 hexachlorinated dibenzofuran	1,2,3,4,7,8 HxCDF	612
1,2,3,6,7,8 hexachlorinated dibenzofuran	1,2,3,6,7,8 HxCDF	575
2,3,4,6,7,8 hexachlorinated dibenzofuran	2,3,4,6,7,8 HxCDF	521
1,2,3,7,8,9 hexachlorinated dibenzofuran	1,2,3,7,8,9 HxCDF	176
1,2,3,4,6,7,8-heptachlorinated dibenzofuran	1,2,3,4,6,7,8 HpCDF	1398
1,2,3,4,7,8,9-heptachlorinated dibenzofuran	1,2,3,4,7,8,9 HpCDF	213
octachlorinated dibenzofuran	OCDF	620
Sum PCDFs	5418
TEQ PCDFs	417.9
DL-PCBs
3,4,4′,5-tetrachlorobiphenyl	PCB 81	57
3,3′,4,4′-tetrachlorobiphenyl	PCB 77	157
2,3′,4,4′,5′-pentachlorobiphenyl	PCB 123	176
2,3′,4,4′,5-pentachlorobiphenyl	PCB 118	3336
2,3,4,4′,5-pentachlorobiphenyl	PCB 114	<D.L.
2,3,3′,4,4′-pentachlorobiphenyl	PCB 105	1485
3,3′,4,4′,5-pentachlorobiphenyl	PCB 126	<D.L.
2,3′,4,4′,5,5′-hexachlorobiphenyl	PCB 167	414
2,3,3′,4,4′,5-hexachlorobiphenyl	PCB 156	492
2,3,3′,4,4′,5′-hexachlorobiphenyl	PCB 157	131
3,3′,4,4′,5,5′-hexachlorobiphenyl	PCB 169	<D.L.
2,3,3′,4,4′,5,5′-heptachlorobiphenyl	PCB 189	220
Sum DL-PCBs	6577
TEQ DL-PCBs	4.5
Average Total TEQ for PCDDs, PCDFs, and DL-PCBs	521.9

). Among this class of compounds, TCDD, recognized for its toxicity, exhibited a concentration of 10.7 fg/m³. The total concentration of PCDFs (5417.8 fg/m³) was significantly higher than that of PCDDs, with the heptachlorinated dibenzofuran (1,2,3,4,6,7,8 HpCDF) being the most prominent species, accounting for 26% of the total species examined. Furthermore, DL-PCBs reached 6577.3 fg/m³, with PCB 118 representing the major contributor at 3335.8 fg/m³. The observed concentrations in this study were higher by almost three orders of magnitude than those reported for an urban site in Lebanon, where the levels of PCDDs, PCDFs, and DL-PCBs in PM_2.5 were measured at 26.6 fg/m³, 4.2 fg/m³, and 648 fg/m³, respectively [4]. Moreover, these values surpassed those reported at two urban sites under industrial influence in Lebanon; the Zouk site (PCDDs: 81.1 fg/m³, PCDFs: 82.5 fg/m³, and DL-PCBs: 454.8 fg/m³), and the Fiaa site (PCDDs: 52.0 fg/m³, PCDFs: 71.8 fg/m³, and DL-PCBs: 586.3 fg/m³) [31], and also higher than the values recorded at an urban site in Dalian, China during winter (PCDD/Fs: 1.46 pg/m³ and DL-PCBs: 0.20 pg/m³) [37].

3.2. Health Risk Assessment

Computed hazard quotients (HQ_i) and cancer risks (CR_i) for various compounds across the inhalation exposure pathway and the different age groups are summarized in Tables S6 and S7.

3.2.1. Non-Carcinogenic Risk Assessment

The total hazard index for the various examined families of compounds (∑HI) was 9.7 for newborns, 6.9 for children, 5.4 for adolescents, and 4.9 for adults (

Table 4. Hazard Index (HI) values for various classes of compounds, along with total Hazard Index (∑HI) values for these compound classes, categorized by age groups. Values are not reported for phthalates due to the absence of reference values (RfD and RfC).

Age Category	Class of Compounds	Inhalation
Newborns	PAHs	1.7
	Phthalates	-
	Major and trace elements	8.0
	PCDDs, PCDFs, and DL-PCBs	0.003
	∑HI	9.7
Children	PAHs	1.7
	Phthalates	-
	Major and trace elements	5.2
	PCDDs, PCDFs, and DL-PCBs	0.003
	∑HI	6.9
Adolescents	PAHs	2.2
	Phthalates	-
	Major and trace elements	3.2
	PCDDs, PCDFs, and DL-PCBs	0.004
	∑HI	5.4
Adults	PAHs	2.2
	Phthalates	-
	Major and trace elements	2.7
	PCDDs, PCDFs, and DL-PCBs	0.004
	∑HI	4.9

). These values indicate that, for each age group, a significant health risk exists, with the ∑HI surpassing the safety threshold of 1 by up to nearly an order of magnitude. These variations highlight the differing levels of risk exposure across the lifespan.

In this assessment of non-carcinogenic health risks, the families of compounds evaluated included major and trace elements, PAHs, PCDD/Fs, and DL-PCBs. In contrast, phthalates were not considered in this assessment, owing to the absence of established reference values for the non-carcinogenic risk calculation.

• Major and trace elements

Among the evaluated major and trace elements via the inhalation pathway, HQ_i values of Pb and Mn consistently exceeded the threshold in all age groups, indicating potential health concerns (Table S6). Specifically, Mn posed the greatest risk, with HQ_i values of 3.9 for newborns, 2.5 for children, 1.4 for adolescents, and 1.2 for adults. Pb also exhibited elevated HQ_i values, with newborns showing the highest value (3.4), followed by children (2.2), adolescents (1.3), and adults (1.1). The remaining elements, such as Al, V, Cr(IV), Co, Ni, Cu, Zn, As, Cd, and Sb, had HQi values below 1, suggesting a negligible probability of non-carcinogenic risk. Moreover, together Mn and Pb were the primary contributors to HI values, accounting for over 84% across all age groups. Prolonged exposure to Pb results in its accumulation within the bone matrix, leading to neurotoxicity, anemia, renal toxicity, and reproductive health effects, particularly in children and infants [38], while excessive Mn inhalation is linked to neurotoxic effects [39]. The findings of this study are consistent with those reported by Shetaya et al. [18] at an urban site in Dokki, GCA, indicating that Pb represents the highest non-carcinogenic risks for adults and children, while other elements, such as Cr(VI) and Cu, showed negligible risk.

The HI values via inhalation were 8.0 for newborns, 5.2 for children, 3.2 for adolescents, and 2.7 for adults (Table 4). In fact, children are particularly vulnerable due to mouth breathing and higher physical activity levels, which increase the penetration of airborne particles into the lungs [34]. In contrast, Motesaddi Zarandi et al. [40] reported in an urban area of Tehran, Iran, that the non-carcinogenic risk via the inhalation pathway was below unity. The observed differences can be primarily attributed to exposure parameters. Notably, the exposure frequency and the exposure duration employed in this study (350 days/year and 52 years, respectively) are considerably higher than the values reported in the latter study (180 days/year and 24 years, respectively). Furthermore, HI values in this study were higher than those reported by Shetaya et al. [18] and by Hu et al. [41] in Nanjing, China. These findings highlight ongoing risks from elemental contaminants, particularly for newborns and children, as vulnerable subgroups within the general population [40,42], emphasizing the need for targeted interventions to reduce exposure.

2.

PAHs

The total concentration of the 16 PM_2.5-bound PAHs in this study was 58.9 ng/m³, yielding a B[a]P_eq value of 14.0 ng/m³ [20]. Chronic exposure to PAHs has been associated with the development of respiratory diseases, cardiovascular disorders, and suppression of immune system function [43]. The HQ values for B[a]P_eq via inhalation were equal for newborns and children, with a value of 1.7, while adolescents and adults had a slightly higher HQ of 2.2 (Figure S1), all exceeding the threshold value of 1. This indicates potential non-carcinogenic risks across all age groups.

3.

PCDD/Fs and DL-PCBs

The total TEQ for PCDDs, PCDFs, and DL-PCBs yielded a total toxic equivalent concentration (TEQ) of 521.9 fg/m³ (Table 3). This value was 127 and 61 times higher than the values reported for sites in northern (4.1 fg/m³) and central Taiwan (8.5 fg/m³) [44], indicating significantly higher PCDDs, PCDFs, and DL-PCBs contamination in Cairo. Among these classes, PCDFs emerged as the predominant contributor to total TEQ (80%), followed by PCDDs (19%), and DL-PCBs (1%). The HQ for inhalation exposure was lower than 1 across all demographic groups, with values of 0.003 for newborns and children, and slightly higher at 0.004 for adolescents and adults (Table 4), indicating the absence of significant non-carcinogenic health risks in any age group.

3.2.2. Carcinogenic Risk Assessment

The total cancer risk (∑CR) for the various families of compounds across different age groups exhibited distinct trends. ∑CR values for each age group were as follows: 2.4 × 10⁻⁶ for newborns, 1.9 × 10⁻⁵ for children, 7.7 × 10⁻⁶ for adolescents, and 6.0 × 10⁻⁵ for adults (Figure 2). These values indicate that, for each age group, exposure to the various carcinogenic species highly exceeded the acceptable risk of 10⁻⁶. Notably, regulatory agencies have adopted de minimus and de manifestis risk limits of 10⁻⁶ and 10⁻⁴, respectively; risk values exceeding 10⁻⁴ are considered unacceptable [6,34].

In this context, and in our assessment in Cairo, none of the calculated ∑CR values surpassed the de manifestis limit of 10⁻⁴, and all age groups exhibited risks well above the de minimis threshold of 10⁻⁶. This places the estimated risks within the intermediate range between 10⁻⁶ and 10⁻⁴, which regulatory agencies typically interpret as indicative of potential concern and requiring further evaluation or risk management. Among the studied populations, adults and children showed the highest ∑CR values (6.0 × 10⁻⁵ and 1.9 × 10⁻⁵, respectively), reflecting a particularly elevated level of concern compared to newborns and adolescents. These findings suggest that, although the risks do not yet reach the level considered unequivocally unacceptable, they remain significantly above the level regarded as negligible, warranting careful attention and preventive action. To date, only a limited number of studies have assessed the cancer risk associated with various families of compounds.

• Major and trace elements

The CR_i was assessed for 7 key elements with available IUR and CSF across the different age groups (Table S7). When evaluating cancer risk associated with species via the inhalation pathway, results revealed that Cr(VI), As, and V exhibited noteworthy CR_i values, surpassing the safety limits of 10⁻⁶ for adults, children, and adolescents (Table S7), and highlighting a potential cancer risk. Specifically, As posed the greatest risk, with CR_i values above the threshold for all age groups, except for newborns, which exhibited a value of 5.7 × 10⁻⁷. The corresponding CR_i values were 4.1 × 10⁻⁶ for children, 1.3 × 10⁻⁶ for adolescents, and 9.3 × 10⁻⁶ for adults. Cr(VI) also demonstrated elevated CR_i values, with newborns showing the lowest risk at 4.8 × 10⁻⁷, followed by children (3.4 × 10⁻⁶), adolescents (1.1 × 10⁻⁶), and adults (7.8 × 10⁻⁶). V exhibited CR_i values of 3.4 × 10⁻⁷ for newborns, 3.8 × 10⁻⁶ for children, 2.7 × 10⁻⁶ for adolescents, and 2.4 × 10⁻⁵ for adults. The highest values were observed in children and adults (Table S7), highlighting the need for targeted interventions and regulatory measures to mitigate exposure to these carcinogenic substances. According to IARC, As and Cr(VI) are classified as Group 1 carcinogens to humans, while V is categorized as Group 2B, possibly carcinogenic to humans. Collectively, these elements represented 80% of the CR_i value in newborns, 82% in children, 87% in adolescents, and 88% in adults. Other elements, such as Co, Ni, Cd, and Pb, had CR_i values below the threshold, except for adults (and children, in the case of Co), suggesting minimal risk through inhalation for newborns and adolescents. For inhalation exposure, CR values were 1.8 × 10⁻⁶ for newborns, 1.4 × 10⁻⁵ for children, 5.9 × 10⁻⁶ for adolescents, and 4.7 × 10⁻⁵ for adults, exceeding the acceptable risk threshold (Table S8). Newborns have a marginally elevated risk, while children and adults face an approximately 8 and 26-fold increase, respectively. Shetaya et al. [18] reported significantly higher CR values in comparison to our study: 1.7 × 10⁻⁵ for children and 5.6 × 10⁻⁵ for adults. The observed discrepancies between the two studies can be primarily attributed to potential variations in the parameters employed in the methodology, such as variations in the exposure durations, exposure time, and body weight of different age categories.

The estimated ILCR associated with exposure to certain elements has been quantified at 3.7 × 10⁻⁵, markedly higher than the acceptable threshold of 10⁻⁶. This value exceeded those reported in various cities worldwide, including Milan, Thessaloniki, and Los Angeles (Figure 3). This finding indicates a considerable potential risk for cancer development linked to exposure to these elements, particularly As, Cr(VI), and V, which have the highest contribution to cancer risk among examined elements, and account for the majority of the CR_i across all age groups.

2.

PAHs

B[a]P and DiB[a,h] classified by the IARC as carcinogenic to humans (Group 1) and probably carcinogenic to humans (Group 2A), respectively, contributed the most significantly to the B[a]P_eq, accounting together for 82% of its value [45]. Among CR values for inhalation, all age groups except newborns (5.1 × 10⁻⁷) exceed the threshold value (Table S8), with adults having the highest risk (8.2 × 10⁻⁶), followed by children (3.6 × 10⁻⁶) and adolescents (1.1 × 10⁻⁶). The results of our study were higher than those reported in Khairy and Lohmann [8] for the inhalation pathway, where PAH-related cancer risks in residential/traffic sites in Alexandria, Egypt, ranged from 4.5 × 10⁻⁷ to 2.0 × 10⁻⁶.

The estimated individual lifetime cancer risk (ILCR) associated with exposure to PAHs is calculated to be 6.8 × 10⁻⁶, significantly surpassing the acceptable limits of 10⁻⁶. This value was higher than those reported in several other cities worldwide, such as Milan, Thessaloniki, and Los Angeles, but lower than those reported in Zouk, Peshawar, Xiamen, Changzhou, Karaj, and Nicosia (Figure 3). This finding indicates that individuals exposed to PAHs face a lifetime cancer risk that is approximately 7 times greater than the regulatory benchmark for acceptable risk. Such a deviation from the threshold suggests a pressing concern regarding public health and the need for mitigation measures. B[a]P and DiB[a,h]An are identified as the predominant contributors to the B[a]P_eq, as previously discussed. Therefore, it is imperative to prioritize managing these compounds by thoroughly investigating their respective sources and implementing stringent regulatory measures in GCA.

3.

Phthalates

At the cancer risk level from phthalates, DEHP was the sole compound among those examined for which a reference value was established for the inhalation route (Table S7). The CR values were below the threshold across all age groups. These results indicate that inhalation exposure to DEHP does not pose a significant cancer risk. The CR_i values for DEHP in this study were significantly higher than those reported in Dongying, China, where the values were 5.92 × 10⁻¹¹ for adults and 5.78 × 10⁻¹¹ for children [46]. Additionally, the CR_i values for DEHP exceeded those recorded at the Fiaa site in Lebanon (5.2 × 10⁻⁹ for newborns, 3.7 × 10⁻⁸ for children, 1.2 × 10⁻⁸ for adolescents, and 8.6 × 10⁻⁸ for adults) [31]. These results suggest a potential long-term carcinogenic concern associated with DEHP exposure, aggravated in children and adults, who exhibited the highest CR_i values.

The estimated ILCR associated with phthalate exposure was 6.4 × 10⁻⁷, which falls below the commonly accepted threshold of 10⁻⁶. This indicates that the lifetime cancer risk from phthalate exposure in this study can be considered negligible or within the range regarded as acceptable by regulatory standards. This value exceeded those reported for two sites in Lebanon (Zouk and Fiaa) [31] (Table S9). Notably, the primary contributor to this risk is DEHP, accounting for the CR values observed across all age demographics, due to its widespread use as a plasticizer [47]. A previous study by Farah et al. [20] has suggested a possible correlation between DEHP exposure and local environmental practices, particularly the open burning of municipal waste, since this practice is prevalent throughout Cairo. These results underline the need for public health interventions and regulatory measures to mitigate DEHP exposure, particularly in regions where such waste management practices are common.

4.

PCDD/Fs and DL-PCBs

Inhalation CR associated with TEQ varied across different age groups (Table S7), reflecting differences in exposure and vulnerability. CR values were above the threshold of 10⁻⁶ in adults (4.7 × 10⁻⁶), while lower values (below 10⁻⁶) were observed in children, adolescents, and newborns (Figure 2), suggesting that adults are more susceptible to potential carcinogenic risks compared to other age groups. This heightened risk could be attributed to cumulative lifetime exposure. Furthermore, newborns (6.8 × 10⁻⁸) and adolescents (5.4 × 10⁻⁷) have lower CR values compared to children and adults. Studies reporting CR values for TEQ are limited, making direct comparisons with other studies conducted in different regions challenging.

The estimated ILCR for inhalation linked to exposure to PCDDs, PCDFs, and DL-PCBs was 3.7 × 10⁻⁶, which was higher than the threshold of 10⁻⁶, indicating a considerable health risk. This value exceeded those reported for measurement sites such as Taipei, Zouk, and Fiaa (Table S9). Based on this estimate, approximately 4 excess cancer cases per 1 million exposed individuals might occur over a lifetime. PCDDs, PCDFs, and DL-PCBs are generated and released into the environment from various sources, including solid waste incineration and the combustion of agricultural residues such as rice straw [9]. The emissions raise considerable concerns for nearby populations in GCA, particularly due to the prevalent practice of waste burning [48]. This is particularly revealed by the significant difference between the estimated ILCR and the acceptable limit, which indicates that current exposure levels could be harmful to public health, necessitating interventions to reduce exposure to PCDDs, PCDFs, and DL-PCBs, thus safeguarding public health and the environment.

3.3. Limitations

Risk assessment is often associated with significant uncertainty, especially in ecological risk assessment, where single-point short-term estimates are used to assess population-level chronic risk. In addition, given the complexities of assessing risks from combined chemical exposure, we followed the USEPA default method in applying the additivity principle to quantify cancer risks within and between different examined families of pollutants, particularly when site-specific toxicity data for the combined exposures are lacking. This method is limited by assuming toxicological independence between and within the fractions, meaning it does not account for interactions. Although synergistic or potentiating effects could theoretically occur, such interactions are unlikely at the concentrations observed in our study. Moreover, with respect to toxicological reference values, uncertainties primarily arise from the reliance on animal data to predict human responses. Many substances identified as carcinogens in animal models may not necessarily pose the same risk to humans, and vice versa. To address this uncertainty, regulatory agencies generally adopt conservative assumptions, such as treating humans as at least as sensitive as the most sensitive animal species [49]. Additionally, uncertainty exists in estimating cancer risk from some compounds due to inconclusive evidence regarding their carcinogenicity to humans, such as those classified in IARC Groups 2A and 2B. In addition, the use of a no-threshold assumption for carcinogens introduces further uncertainty, as the hypothesis that any exposure above zero carries some cancer risk has not been conclusively proven, particularly for substances with non-genotoxic modes of action [49].

Figure 3. Carcinogenic risk examples for children (C), adults (A), and the whole population (P) across selected countries worldwide. ^a This study; ^b [18]; ^c [29]; ^d [31]; ^e [50]; ^f [51]; ^g [52]; ^h [53]; ⁱ [41]; ^j [54]; ^k [55]; ^l [56]; ^m [6]; ⁿ [23].

Figure 3. Carcinogenic risk examples for children (C), adults (A), and the whole population (P) across selected countries worldwide. ^a This study; ^b [18]; ^c [29]; ^d [31]; ^e [50]; ^f [51]; ^g [52]; ^h [53]; ⁱ [41]; ^j [54]; ^k [55]; ^l [56]; ^m [6]; ⁿ [23].

Furthermore, a key limitation lies in the use of concentration data averaged over a defined period, which may not capture temporal variability in pollutant levels over a longer period. Risk estimates are calculated for different age groups, including newborns, children, adolescents, and adults, with extrapolation to lifetime exposure. However, as ambient pollutant concentrations evolve, the associated risk estimates also change. Consequently, health risk assessments must be recalculated whenever updated concentration data become available to maintain accuracy and relevance. Because this data was unavailable, we instead used a concentration-based model combined with potency indicators, such as cancer slope factor or inhalation unit risk value, to estimate health risks [57]. Future studies in Cairo could benefit from cohort-based designs to better assess short- and long-term health effects associated with PM_2.5 components and to compare exposure and health outcomes across various geographic areas.

4. Conclusions

This study offers a thorough assessment of the health risks associated with PM_2.5-bound species, including major and trace elements, PAHs, phthalates, PCDDs, PCDFs, and DL-PCBs, collected in an urban location in the Greater Cairo Area. It is the first study to measure PCDDs, PCDFs, and DL-PCBs in Egypt. Moreover, it represents the first ecological risk assessment linked to exposure to these families of air pollutants in Cairo, Egypt.

Findings reveal significantly high atmospheric concentrations of various hazardous pollutants, with Al being among the most prevalent elements, DEHP being the predominant phthalate, and PCDFs making up the majority of the total toxic equivalent concentration of PCDDs, PCDFs, and DL-PCBs. Moreover, this risk assessment raises important concerns regarding both non-carcinogenic and carcinogenic risks. For all age categories, the total hazard index (∑HI) values exceeded the safety threshold of 1, with newborns and children being the most vulnerable. Pb, and Mn were linked to the most significant non-carcinogenic hazards. Similarly, carcinogenic risk assessments indicated that the total cancer risk (∑CR) surpassed the acceptable limit (10⁻⁶) across all demographics. The main contributions comprised As, Cr(VI), V, PAHs, and PCDDs/PCDFs/DL-PCBs. Notably, the highest individual lifetime cancer risk was found for major and trace elements, and PAHs, followed by PCDDs/PCDFs/DL-PCBs. These findings highlight the need for more stringent air pollution management measures in Cairo, with a particular focus on protecting at-risk populations. Effective mitigation strategies should prioritize key pollution sources by establishing a clear linkage between health risks and specific pollutant origins, enabling the reduction in exposure to the most hazardous air contaminants, and thereby minimizing the associated health burden. Ultimately, this study can serve as a baseline for policymakers in developing targeted interventions and implementing stricter regulatory measures to safeguard public health and the environment, thereby mitigating exposure.