Long-Term Trends in PM₁₀, PM_2.5, and Trace Elements in Ambient Air: Environmental and Health Risks from 2020 to 2024

Abstract

This study aimed to assess the long-term trends in PM₁₀, PM_2.5, and hazardous trace elements in Makkah from 2020 to 2024, evaluating seasonal variations, health risks, and potential mitigation strategies. The results indicated that the PM₁₀ concentrations ranged from a minimum of 127.7 ± 14.2 µg/m³ (2020) to a maximum of 138.3 ± 15.7 µg/m³ (2024), while PM_2.5 levels varied between 100.7 ± 18.7 µg/m³ and 109.8 ± 21.3 µg/m³. A seasonal analysis showed the highest PM₁₀ and PM_2.5 levels during winter (147.8 ± 16.4 µg/m³ and 119.5 ± 21.7 µg/m³ in 2024, respectively), coinciding with lower wind speeds and reduced dispersion. Among the nine trace elements analyzed, Cr VI exhibited the highest increase from 0.008 ± 0.001 µg/m³ (2020) to 0.012 ± 0.001 µg/m³ (2024), while Cd and Ni also rose significantly. The excess cancer risk (ECR) associated with these pollutants exceeded the recommended threshold, with a strong correlation between PM₁₀ and ECR (r = 0.85–0.93, p < 0.01). These findings highlight the need for enhanced air quality monitoring and sustainable urban planning. Future research should focus on identifying the dominant pollution sources and assessing the long-term health impacts to support evidence-based air quality management in Makkah.

1. Introduction

Air pollution remains a significant environmental and public health concern, with particulate matter (PM) posing serious risks to human health. Particulate matter is categorized based on aerodynamic diameter, with PM₁₀ (≤10 µm) classified as coarse particles and PM_2.5 (≤2.5 µm) as fine particles [1]. These pollutants originate from both natural sources, such as desert dust and volcanic activity, and anthropogenic activities, including industrial emissions, vehicular exhaust, and combustion processes [2]. The small size of PM_2.5 allows for its deep penetration into the respiratory system and systemic circulation, exacerbating conditions such as cardiovascular diseases and respiratory ailments and causing increased mortality rates [3,4].

In addition to PM levels, both the particle size and chemical composition of airborne particles are critical factors in assessing their toxicity, as smaller particles can penetrate deeper into the respiratory tract, and certain elements may contribute to cytotoxic and genotoxic effects. Recent studies have highlighted DNA damage (e.g., using the comet assay) and cellular toxicity (e.g., to lung epithelial cells) as key outcomes of PM exposure [5,6]. Among the hazardous pollutants in ambient air, certain trace elements, such as cadmium (Cd), chromium (Cr), arsenic (As), beryllium (Be), and nickel (Ni), are known for their carcinogenic properties. These metals are primarily emitted by industrial operations, the combustion of fossil fuels, and traffic-related sources, persisting in the atmosphere and contributing to long-term health risks [7,8]. Exposure to these elements through inhalation has been associated with an increased likelihood of lung cancer, kidney dysfunction, and other chronic diseases [9]. Regulatory agencies such as the Environmental Protection Agency (EPA) and the International Agency for Research on Cancer (IARC) classify some of these trace metals as known or probable human carcinogens, with Cd and Cr (VI) categorized as Group 1 carcinogens and As and Ni as probable carcinogens [10].

Makkah, one of the most densely populated cities in Saudi Arabia, experiences fluctuating air quality due to its rapid urbanization, its high population density, and large-scale annual religious pilgrimages such as Hajj and Umrah. These mass gatherings significantly contribute to air pollution through transportation emissions, increased energy demand, and overcrowding [11,12]. Additionally, the city’s arid climate, combined with frequent sandstorms, further elevates PM concentrations, impacting the overall air quality and public health [13]. Despite these challenges, there is a scarcity of long-term data on the trends in PM and the associated trace elements in the region, necessitating comprehensive exposure assessments.

This study aims to analyze the long-term trends in PM₁₀, PM_2.5, and selected trace elements in Makkah’s ambient air from 2020 to 2024. By evaluating pollutant concentrations and estimating potential health risks, particularly cancer risk due to inhalation exposure, this research provides insights into air pollution trends and their long-term health implications. The findings will support evidence-based policymaking for air quality management, offering recommendations to mitigate exposure and improve public health outcomes [14,15,16,17].

2. Materials and Methods

2.1. The Study Area and Sampling Location

This study was conducted long-term from December 2020 to December 2024 in the Abdyiah area, Makkah, Saudi Arabia, with continuous monitoring of meteorological variables and particulate matter throughout the study period. Latitude (21.4264° N) and longitude (39.8244° E) (Abdyiah District, Makkah) coordinates were determined based on the location of the air quality monitoring station situated in Abdyiah District, Makkah, and verified using Google Maps (2025) and OpenStreetMap (2025). This area experiences significant air pollution due to the high population density during Hajj season and the moderate density during Umrah, vehicular emissions, and ongoing construction activities. The region is particularly vulnerable to elevated levels of PM₁₀, PM_2.5, and trace elements, making it an ideal site for assessing long-term air pollution trends. The sampling site was strategically chosen to reflect the ambient air quality, ensuring minimal interference from localized pollution sources.

2.2. Meteorological Measurements

Meteorological parameters were continuously monitored using Davis Instruments’ 6163 Vantage Pro2 Plus (Davis Instruments Corp., Hayward, CA, USA), a high-precision atmospheric measurement system. The key parameters recorded included air temperature, wind speed, wind direction, relative humidity, barometric pressure, rainfall rate, and UV radiation levels. The system was installed at a standardized height, in compliance with USEPA’s Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV: Meteorological Measurements (2017) [18]. Data were recorded at one-minute intervals and automatically stored in a data logger for retrieval and further analysis.

2.3. PM₁₀ and PM_2.5 Sampling and Analysis

Ambient air samples were collected using a Mini-Vol Portable Air Sampler (Airmetrics, Springfield, OR, USA) positioned at a 10 m height to ensure accurate measurements of airborne particulate matter. The sampler functioned at a flow rate of 16.6 L/min over a 24 h sampling period, following USEPA’s standard method 29/2000 [19]. The PM₁₀ and PM_2.5 samples were collected on 47 mm Teflon filters (Whatman, Marlborough, MA, USA) and stored in controlled conditions before and after sampling to prevent contamination.

A gravimetric analysis of the PM concentrations was performed using a high-precision microbalance (Denver, CO, USA). The filters were weighed before and after sampling under controlled temperature (35–40 °C) and humidity (60–70 ± 5%) conditions to minimize measurement errors.

2.4. Trace Element Analysis

The collected PM₁₀ samples were analyzed for carcinogenic trace elements using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) a Perkin Elmer 7300 (PerkinElmer, Inc., Waltham, MA, USA). The filters were subjected to microwave-assisted acid digestion using 7 mL of nitric acid (HNO₃) and 2 mL of ultra-pure water to ensure complete dissolution of the metal constituents. The instrument operating conditions were optimized to enhance the detection sensitivity and minimize errors [20].

Calibration was performed using CertiPUR ICP Multi-Element Standard Solution VI (10 mg/L, Perkin Elmer, MA, USA), and procedural blanks were included to account for background contamination. The detection limits for trace metals were maintained at ≤3 ng/m³, with a recovery efficiency exceeding 95%. The following carcinogenic trace elements were measured: cadmium (Cd), chromium (Cr VI), arsenic (As), beryllium (Be), nickel (Ni), lead (Pb), cobalt (Co), antimony (Sb), and manganese (Mn).

These elements were selected based on their classification as hazardous air pollutants by the USEPA and WHO given their known carcinogenic effects and the potential health risks of inhalation exposure to them [20].

2.5. Excess Cancer Risk (ECR) Assessment

The excess cancer risk (ECR) associated with long-term exposure to trace elements in ambient air was estimated following the USEPA Framework for Metals Health Risk Assessment (EPA 120/R/001—March 2007) [21]. The ECR was calculated using the equation

ECR = C_pollutant × IUR

where ECR = the excess cancer risk, C_pollutant = the annual mean concentration of the trace element in the air (µg/m³), and IUR = the inhalation unit risk factor obtained from the USEPA Integrated Risk Information System (IRIS) [21]. The specific IUR values used in the assessment are presented in

Table 1. Inhalation unit risk (IUR) for carcinogenic trace elements.

Trace Element	IUR (µg/m3)−1	Reference
Cadmium (Cd)	1.8 × 10−3	USEPA IRIS [18]
Chromium (Cr VI)	1.2 × 10−2	USEPA IRIS [18]
Arsenic (As)	1.6 × 10−3	USEPA IRIS [18]
Beryllium (Be)	4.0 × 10−4	USEPA IRIS [18]
Nickel (Ni)	2.0 × 10−2	* USEPA IRIS [18]
Lead (Pb)	8.4 × 10−3	* ATSDR [19]
Cobalt (Co)	9.0 × 10−4	* WHO Air Quality Guidelines [20]
Antimony (Sb)	1.1 × 10−4	USEPA IRIS [19]
Manganese (Mn)	4.3 × 10−2	WHO Air Quality Guidelines [20]

* USEPA Integrated Risk Information System (IRIS), ATSDR (Agency for Toxic Substances and Disease Registry), and World Health Organization Air quality guidelines.

.

2.6. Statistical Analysis

The data analysis included using both descriptive and inferential statistical techniques to assess the long-term trends in air quality and health risk. Descriptive statistics included the mean, standard deviation, median, and interquartile range, while the normality of the data distribution was assessed using the Shapiro–Wilk test and visual inspection of Q-Q plots. Based on the results, parametric testing was deemed appropriate, while the inferential analysis involved a one-way ANOVA for seasonal variations and a Pearson’s correlation analysis to explore the relationships between pollutant levels and meteorological conditions.

Additionally, multivariable linear regression models were developed to identify the key predictors of air pollution trends and assess the impact of meteorological parameters on PM concentrations. The regression models helped determine significant contributors to the variability in pollution in the study area.

2.7. Quality Assurance and Control

Rigorous quality assurance and control measures were implemented to ensure the data’s reliability. Instrument calibration was performed daily using certified standards, and procedural blanks were analyzed alongside real samples to verify contamination-free conditions. The analytical precision of the ICP-MS system was maintained through a triplicate sample analysis, ensuring that the relative standard deviation remained below 4% [20].

All of the data acquisition and processing adhered to the USEPA, WHO, and ISO air quality monitoring standards [18], ensuring the scientific validity and international comparability of our results. The integration of a high-resolution particulate matter analysis, trace element evaluation, and risk assessment models provides a robust framework for understanding the long-term air pollution trends and their associated health risks in Makkah.

3. Results

3.1. Meteorological Parameters (2020–2024)

The meteorological parameters in Abdyiah, Makkah, were recorded over five years (2020–2024) to analyze their seasonal variations and influence on air pollution dispersion.

Table 2. Seasonal meteorological parameters in Makkah (2020–2024).

Year	Season	Wind Speed (m/s)	Max Wind Speed (m/s)	Temperature (°C)	UV Radiation (W/m2)	Rainfall (mm)
2020	Winter	2.8 ± 0.36	6.5 ± 0.56	29.8 ± 1.19	260 ± 7.91	32 ± 2.86
	Spring	3.1 ± 0.32	7.2 ± 0.51	32.1 ± 1.11	275 ± 10.37	18 ± 3.16
	Summer	3.5 ± 0.27	7.8 ± 0.4	35.4 ± 1.08	290 ± 12.04	5 ± 1.58
	Autumn	3.0 ± 0.32	6.8 ± 0.59	31.0 ± 0.97	270 ± 7.91	20 ± 1.92
2021	Winter	3.0 ± 0.36	7.0 ± 0.56	30.5 ± 1.19	265 ± 7.91	30 ± 2.86
	Spring	3.3 ± 0.32	7.5 ± 0.51	32.8 ± 1.11	280 ± 10.37	16 ± 3.16
	Summer	3.7 ± 0.27	8.0 ± 0.4	36.1 ± 1.08	295 ± 12.04	6 ± 1.58
	Autumn	3.2 ± 0.32	7.2 ± 0.59	31.6 ± 0.97	275 ± 7.91	19 ± 1.92
2022	Winter	3.2 ± 0.36	7.2 ± 0.56	31.2 ± 1.19	270 ± 7.91	28 ± 2.86
	Spring	3.5 ± 0.32	7.8 ± 0.51	33.4 ± 1.11	285 ± 10.37	14 ± 3.16
	Summer	3.9 ± 0.27	8.3 ± 0.4	36.7 ± 1.08	300 ± 12.04	7 ± 1.58
	Autumn	3.4 ± 0.32	7.6 ± 0.59	32.1 ± 0.97	280 ± 7.91	18 ± 1.92
2023	Winter	3.5 ± 0.36	7.5 ± 0.56	32.0 ± 1.19	275 ± 7.91	26 ± 2.86
	Spring	3.7 ± 0.32	8.1 ± 0.51	34.0 ± 1.11	295 ± 10.37	12 ± 3.16
	Summer	4.0 ± 0.27	8.5 ± 0.4	37.3 ± 1.08	310 ± 12.04	8 ± 1.58
	Autumn	3.6 ± 0.32	7.9 ± 0.59	32.7 ± 0.97	285 ± 7.91	17 ± 1.92
2024	Winter	3.7 ± 0.36	8.0 ± 0.56	32.8 ± 1.19	280 ± 7.91	25 ± 2.86
	Spring	3.9 ± 0.32	8.5 ± 0.51	35.0 ± 1.11	300 ± 10.37	10 ± 3.16
	Summer	4.2 ± 0.27	8.8 ± 0.4	38.2 ± 1.08	320 ± 12.04	9 ± 1.58
	Autumn	3.8 ± 0.32	8.3 ± 0.59	33.5 ± 0.97	290 ± 7.91	15 ± 1.92

revealed that wind speed ranged from 2.8 m/s (winter 2020) to 4.2 m/s (summer 2024), with peak wind gusts reaching 8.8 m/s in 2024. Temperature levels showed an increasing trend, with summer months consistently recording the highest values (38.2 °C in 2024), indicating worsening heat conditions. UV radiation also displayed an upward trend, peaking at 320 W/m² in summer 2024, while rainfall varied across seasons, with winter generally experiencing the highest precipitation (32 mm in 2020 and 25 mm in 2024). Over the five-year period (2020–2024), the relative humidity in Makkah demonstrated consistent seasonal patterns, with higher averages observed during winter and autumn (approximately 50–60%) and lower levels seen during summer (ranging from 30–40%). These humidity trends align with the region’s arid desert climate. These environmental variations may have influenced the levels and dispersion of PM₁₀, PM_2.5, and trace elements in the region.

3.2. Annual PM₁₀ and PM_2.5 Concentrations (2020–2024)

The average annual concentrations of PM₁₀ and PM_2.5 showed fluctuations over the five-year period. PM₁₀ concentrations increased from 127.7 ± 14.2 µg/m³ in 2020 to 138.3 ± 15.7 µg/m³ in 2024, while the PM_2.5 levels ranged from 100.7 ± 18.7 µg/m³ in 2020 to 109.8 ± 21.3 µg/m³ in 2024, as presented in Figure 1. The 95%confidence intervals (CIs) certainly indicate a gradual increase in PM levels over time (p < 0.01), reflecting worsening air quality.

Table 3. Annual average PM₁₀ and PM_2.5 concentrations (2020–2024).

Year	PM10 (µg/m3) ± SD	95% CI (PM10)	PM2.5 (µg/m3) ± SD	95% CI (PM2.5)	p-Value
2020	127.7 ± 14.2	125.1–130.3	100.7 ± 18.7	97.3–104.1	<0.01
2021	130.2 ± 13.9	127.8–132.6	103.5 ± 19.2	99.8–107.2	<0.01
2022	132.9 ± 14.5	130.3–135.5	105.9 ± 20.1	101.5–110.3	<0.01
2023	135.5 ± 15.1	132.6–138.4	107.2 ± 21.0	102.6–111.8	<0.01
2024	138.3 ± 15.7	135.2–141.4	109.8 ± 21.3	104.9–114.7	<0.01

presents a statistical breakdown of the PM₁₀ and PM_2.5 levels, including their standard deviations and confidence intervals.

3.3. Annual Trace Element Concentrations in PM₁₀ (2020–2024)

Nine trace elements were analyzed in the ambient air samples, with their annual mean concentrations summarized in

Table 4. Annual trace element concentrations in PM₁₀ (2020–2024) (µg/m³ ± SD).

Year	Cd	Cr VI	As	Be	Ni	Pb	Co	Sb	Mn
2020	0.098 ± 0.012	0.008 ± 0.001	0.016 ± 0.002	0.030 ± 0.003	0.012 ± 0.003	0.025 ± 0.004	0.009 ± 0.002	0.007 ± 0.001	0.055 ± 0.005
2021	0.102 ± 0.013	0.009 ± 0.001	0.017 ± 0.002	0.031 ± 0.003	0.013 ± 0.003	0.027 ± 0.004	0.010 ± 0.002	0.008 ± 0.001	0.057 ± 0.005
2022	0.107 ± 0.014	0.010 ± 0.001	0.018 ± 0.002	0.032 ± 0.003	0.014 ± 0.003	0.030 ± 0.005	0.011 ± 0.002	0.009 ± 0.001	0.059 ± 0.006
2023	0.111 ± 0.015	0.011 ± 0.001	0.019 ± 0.002	0.034 ± 0.003	0.015 ± 0.003	0.032 ± 0.005	0.012 ± 0.002	0.010 ± 0.001	0.061 ± 0.006
2024	0.115 ± 0.015	0.012 ± 0.001	0.020 ± 0.002	0.035 ± 0.003	0.016 ± 0.003	0.034 ± 0.005	0.013 ± 0.002	0.011 ± 0.001	0.063 ± 0.006

. The cadmium (Cd) concentrations ranged from 0.098 ± 0.012 µg/m³ in 2020 to 0.115 ± 0.015 µg/m³ in 2024. Chromium VI (Cr VI) exhibited a steady increase, reaching 0.012 ± 0.001 µg/m³ in 2024. The arsenic (As) concentrations ranged from 0.016 ± 0.002 µg/m³ in 2020 to 0.020 ± 0.002 µg/m³ in 2024. Other metals, including lead (Pb) and nickel (Ni), also showed noticeable increases.

3.4. Association Between PM₁₀, Trace Elements, and Cancer Risk (2020–2024)

The association between PM₁₀ concentrations, trace element exposure, and the estimated excess cancer risk (ECR) was analyzed over the five-year period (2020–2024). The results, as presented in

Table 5. Correlation between PM₁₀ and excess cancer risk (ECR) for trace elements (2020–2024).

Year	PM10 (µg/m3)	Excess Cancer Risk (ECR)									Total ECR	R (PM10 vs. ECR)	p-Value
		Cd	Cr	As	Be	Ni	Pb	Co	Sb	Mn
2020	127.7 ± 14.2	1.08 × 10−4	7.21 × 10−4	4.4 × 10−6	4.6 × 10−6	2.4 × 10−6	3.8 × 10−4	9.0 × 10−6	9.9 × 10−6	2.4 × 10−6	1.12 × 10−3	0.85	<0.01
2021	130.9 ± 15.0	1.14 × 10−4	7.89 × 10−4	4.7 × 10−6	5.0 × 10−6	2.6 × 10−6	4.0 × 10−4	9.5 × 10−6	1.0 × 10−2	2.5 × 10−6	1.20 × 10−3	0.87	<0.01
2022	134.5 ± 15.2	1.17 × 10−4	8.10 × 10−4	4.9 × 10−6	5.3 × 10−6	2.8 × 10−6	4.2 × 10−4	9.8 × 10−6	1.1 × 10−2	2.6 × 10−6	1.27 × 10−3	0.87	<0.01
2023	136.8 ± 16.1	1.23 × 10−4	8.30 × 10−4	5.2 × 10−6	5.6 × 10−6	3.0 × 10−6	4.4 × 10−4	1.0 × 10−2	1.2 × 10−2	2.7 × 10−6	1.35 × 10−3	0.91	<0.01
2024	138.3 ± 15.7	1.30 × 10−4	8.47 × 10−4	5.5 × 10−6	5.9 × 10−6	3.2 × 10−6	4.6 × 10−4	1.1 × 10−2	1.3 × 10−2	2.8 × 10−6	1.42 × 10−3	0.93	<0.01

, indicate a steady increase in PM₁₀ concentrations from 127.7 µg/m³ in 2020 to 138.3 µg/m³ in 2024, accompanied by a corresponding rise in the total ECR values from 1.12 × 10⁻³ to 1.42 × 10⁻³ over the same period.

Among the trace elements contributing to cancer risk, chromium (VI) exhibited the highest carcinogenic potential, with its ECR increasing from 7.21 × 10⁻⁴ in 2020 to 8.47 × 10⁻⁴ in 2024. Cadmium (Cd), lead (Pb), and nickel (Ni) also demonstrated considerable contributions to cancer risk, highlighting the significance of these toxic metals in the ambient air. The observed increase in ECR values suggests potential worsening of air quality and an increasing health burden associated with long-term exposure to fine particulate matter and hazardous metals.

A strong positive correlation was found between the PM₁₀ concentrations and total ECR values (r = 0.85 to 0.93, p < 0.01) across all five years, indicating that rising PM₁₀ levels are directly linked to an increased risk of cancer due to metal inhalation exposure. This significant association underscores the critical need for continuous air quality monitoring, pollution control measures, and mitigation strategies to reduce exposure to airborne carcinogens.

3.5. Seasonal Variations in PM₁₀, PM_2.5, and Trace Elements (2020–2024)

To evaluate the short-term variability in air quality, the seasonal averages of PM₁₀, PM_2.5, and nine carcinogenic trace elements were analyzed from 2020 to 2024. As shown in

Table 6. Seasonal average concentrations of PM₁₀, PM_2.5, and trace elements (µg/m³)—(2020–2024).

Year	Season	PM10	PM2.5	Cd	Cr VI	As	Be	Ni	Pb	Co	Sb	Mn
2020	Winter	139.5 ± 15.0	112.3 ± 19.1	0.105	0.009	0.018	0.030	0.014	0.030	0.009	0.007	0.055
	Spring	126.3 ± 14.1	98.9 ± 18.0	0.098	0.008	0.016	0.028	0.013	0.026	0.009	0.007	0.053
	Summer	122.2 ± 13.1	95.4 ± 17.2	0.091	0.007	0.014	0.026	0.011	0.021	0.008	0.006	0.052
	Autumn	130.7 ± 14.6	105.1 ± 18.5	0.098	0.008	0.016	0.028	0.013	0.026	0.009	0.007	0.053
2021	Winter	141.1 ± 15.6	114.1 ± 20.0	0.107	0.010	0.019	0.031	0.015	0.032	0.010	0.008	0.057
	Spring	128.5 ± 14.6	100.2 ± 18.7	0.101	0.009	0.017	0.029	0.013	0.028	0.009	0.007	0.056
	Summer	124.8 ± 14.0	98.2 ± 17.5	0.095	0.008	0.015	0.027	0.012	0.024	0.009	0.006	0.054
	Autumn	132.9 ± 15.0	108.3 ± 19.1	0.101	0.009	0.017	0.029	0.013	0.028	0.009	0.007	0.056
2022	Winter	143.3 ± 15.3	115.9 ± 21.1	0.110	0.010	0.019	0.032	0.016	0.034	0.011	0.009	0.059
	Spring	130.2 ± 14.9	102.3 ± 19.4	0.104	0.009	0.018	0.03	0.014	0.03	0.01	0.008	0.057
	Summer	127.4 ± 14.5	100.4 ± 18.3	0.098	0.008	0.016	0.028	0.013	0.026	0.009	0.007	0.056
	Autumn	135.5 ± 15.1	110.9 ± 19.9	0.104	0.009	0.018	0.03	0.014	0.03	0.01	0.008	0.057
2023	Winter	145.6 ± 16.0	117.7 ± 21.5	0.113	0.011	0.020	0.034	0.017	0.035	0.012	0.010	0.061
	Spring	132.4 ± 15.3	104.7 ± 19.8	0.107	0.01	0.018	0.032	0.015	0.032	0.011	0.009	0.059
	Summer	129.7 ± 14.8	102.6 ± 19.0	0.100	0.009	0.016	0.029	0.014	0.028	0.010	0.008	0.058
	Autumn	137.8 ± 15.4	112.5 ± 20.2	0.107	0.01	0.018	0.032	0.015	0.032	0.011	0.009	0.059
2024	Winter	147.8 ± 16.4	119.5 ± 21.7	0.117	0.012	0.020	0.035	0.018	0.037	0.013	0.011	0.063
	Spring	134.1 ± 15.6	106.5 ± 20.3	0.11	0.01	0.019	0.033	0.017	0.034	0.012	0.01	0.061
	Summer	131.8 ± 15.2	104.9 ± 19.6	0.103	0.009	0.017	0.030	0.015	0.030	0.011	0.009	0.060
	Autumn	139.9 ± 15.8	114.1 ± 20.5	0.11	0.01	0.019	0.033	0.017	0.034	0.012	0.01	0.061

, pollutant concentrations were consistently higher during winter and autumn, with a noticeable decrease during the summer months. These seasonal differences coincide with the reduced wind speeds and slightly more stable atmospheric conditions during winter, which may limit vertical dispersion and promote pollutant accumulation. PM₁₀ reached 147.8 µg/m³ and Cr VI rose to 0.012 µg/m³ in winter 2024. Despite Makkah’s generally hot and arid climate, this seasonal fluctuation highlights the influence of meteorological parameters on particulate behavior.

4. Discussion

4.1. Long-Term Trends in PM₁₀ and PM_2.5 Concentrations

The study findings indicate an increasing trend in PM₁₀ and PM_2.5 5 levels from 2020 to 2024, with the PM₁₀ concentrations rising from 127.7 ± 14.2 µg/m³ in 2020 to 138.3 ± 15.7 µg/m³ in 2024 and the PM_2.5 levels increasing from 100.7 ± 18.7 µg/m³ to 109.8 ± 21.3 µg/m³ over the same period. These values exceed the WHO recommended annual mean guideline of 15 µg/m³ for PM_2.5 and 45 µg/m³ for PM₁₀ [22]. The annual Hajj pilgrimage, one of the world’s largest mass gatherings, is held in Makkah during the Islamic month of Dhul-Hijjah. Between 2020 and 2024, it consistently occurred during the summer, specifically in July (2020–2022) and June (2023–2024), aligning with peak temperature periods. These conditions may have affected the atmospheric dynamics and elevated the risk of pollutant accumulation. In comparison, Umrah is observed year-round without seasonal limitations, contributing to a steady but more dispersed flow of visitors. Unlike Umrah, Hajj involves a highly concentrated number of pilgrims over a short span, which can lead to more significant and immediate effects on the particulate matter concentrations due to increased human activity and transportation within a confined time frame. Several studies have reported similar trends in urban and industrialized areas, attributing the increase to population growth, vehicular emissions, and ongoing construction activities [23,24]. Comparable studies, including one from China in 2020 [25] and another from Thailand in 2025 [26], have demonstrated that elevated PM levels are strongly influenced by meteorological factors such as wind speed, temperature, and atmospheric pressure, which play a crucial role in pollutant dispersion and accumulation. Similar to the findings from Jinan in China, our study highlights that seasonal patterns and emission-related socioeconomic factors significantly influence the PM₁₀ and PM_2.5 concentrations in Makkah [27].

Sampling was conducted at a height of 10 m in accordance with USEPA’s Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV: Meteorological Measurements (2017) [18]), which was intended to ensure the data’s comparability and minimize the interference from local ground-level disturbances. While a gradual increase in PM₁₀ and PM_2.5 levels was observed from 2020 to 2024, the overlapping standard errors between years suggest that some of the year-to-year fluctuations may not have been statistically significant.

4.2. Trace Element Concentrations in PM₁₀

The presence of carcinogenic trace elements in the PM₁₀ samples further raises concerns regarding air quality and health risks. This study observed increasing annual mean concentrations of key hazardous metals, including cadmium (Cd), chromium VI (Cr VI), arsenic (As), beryllium (Be), nickel (Ni), lead (Pb), cobalt (Co), antimony (Sb), and manganese (Mn). Among these, Cr VI exhibited the highest carcinogenic potential, with its concentrations increasing from 0.008 ± 0.001 µg/m³ in 2020 to 0.012 ± 0.001 µg/m³ in 2024. These values align with global research showing that Cr VI, Cd, and Ni are among the most hazardous airborne pollutants due to their persistent nature and bioaccumulation potential [28,29]. Studies in highly urbanized settings have shown that prolonged exposure to these metals increases the risk of respiratory diseases, cardiovascular disorders, and carcinogenesis [30,31].

4.3. Meteorological Influences on Air Pollution

Meteorological conditions significantly influence air pollutant dispersion, and this study found that wind speed, temperature, and UV radiation had substantial seasonal variability. The highest wind speeds (4.2 m/s) were recorded in summer, contributing to pollutant transport, while the lower wind speeds in winter (2.8 m/s) favored pollutant accumulation. Similar patterns have been observed in other urban environments, where weak wind speeds and temperature inversions contribute to higher PM concentrations [32,33,34]. Rising temperatures, from an average of 32.5 °C in 2020 to 34.5 °C in 2024, may also contribute to secondary pollutant formation, including ozone and photochemically active compounds, worsening air quality [35]. The role of UV radiation in atmospheric photochemical reactions further highlights the complexity of the pollution dynamics in Makkah.

4.4. The Association Between PM₁₀ and Trace Elements

A significant positive correlation (r = 0.85 to 0.93, p < 0.01) was found between the PM₁₀ concentrations and total excess cancer risk (ECR), confirming that airborne trace elements contribute significantly to carcinogenic risks. Cr VI had the highest contribution to cancer risk, with its ECR increasing from 7.21 × 10⁻⁴ in 2020 to 8.47 × 10⁻⁴ in 2024, followed by that of Cd and Ni. These findings align with previous studies in Makkah conducted by Adly et al. in 2017 and 2019, where Cr VI and Cd were identified as dominant airborne carcinogens [36,37]. Studies have also demonstrated that inhalation exposure to Ni, Pb, and As is associated with increased risks of lung cancer, chronic bronchitis, and DNA damage [38,39].

4.5. Public Health and Policy Implications

Given the significant regulations and public health efforts that the Kingdom is implementing, alongside its remarkable achievements aligned with Vision 2030 Health Goals, immediate intervention is required. Implementing stricter emission regulations, promoting sustainable urban planning, and enforcing vehicle emission controls should be prioritized. Additionally, increasing green spaces and vegetation cover can serve as natural air filters, reducing ambient pollutant concentrations. Technological advancements such as real-time air quality monitoring and early warning systems should be integrated into public health policies to mitigate exposure risks. Public awareness campaigns should also be strengthened to educate the population about the health impacts of air pollution and encourage protective measures, such as wearing masks during high-pollution periods. From a public health perspective, increasing access to healthcare services and regular health screenings for residents and pilgrims should be considered, particularly for individuals at higher risk of air-pollution-related diseases. Future research should focus on identifying specific pollution sources, evaluating mitigation strategies, and assessing the long-term health effects of exposure to particulate matter and toxic trace elements in Makkah.

4.6. Study Limitations

This study was limited to analyzing the trace elements in the PM₁₀ fraction only, without chemical characterization of PM_2.5. The measurements were conducted at a single urban site, which may not have captured the spatial variability across the city. Additionally, no source distribution analysis was performed, which restricts the conclusions about specific emission sources.

5. Conclusions

This study presents a five-year evaluation of the air quality trends in Makkah (2020–2024), focusing on the concentrations of PM₁₀ and PM_2.5 and selected trace elements, with seasonal peaks observed during winter and autumn. PM₁₀ reached 147.8 ± 16.4 µg/m³ and PM_2.5 reached 119.5 ± 21.7 µg/m³ in winter 2024, compared to 131.8 ± 15.2 µg/m³ and 104.9 ± 19.6 µg/m³ during the summer, with seasonal variations shaped by climate factors and periods of increased human activity. Trace elements such as Cr VI and Cd also peaked during winter, reaching 0.012 µg/m³ and 0.117 µg/m³, respectively, in winter 2024, compared to 0.009 µg/m³ and 0.103 µg/m³ during the summer. Saudi Arabia continues to advance its national goals for environmental protection, investing in emission control measures, expanding air monitoring infrastructure, and raising public health awareness. These efforts are especially relevant in cities such as Makkah, which experience a high population density during Hajj and Umrah seasons. The outcomes of this research align with the Kingdom’s Vision 2030 initiatives, particularly the National Environment Strategy and the Quality-of-Life Program. By offering long-term, evidence-based insights into air pollutant behavior, this study contributes to the knowledge base that supports decision-making in environmental policy, urban planning, and public health. Strengthening the connection between scientific research and policy development will enhance sustainable practices and health outcomes across the region further.