Evaluation of Hazard Quotient (Hq) of Toxic and Heavy Metal Concentration in Air Sediments Across Selected Cities in Nigeria

doi:10.21203/rs.3.rs-5105731/v1

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Evaluation of Hazard Quotient (Hq) of Toxic and Heavy Metal Concentration in Air Sediments Across Selected Cities in Nigeria

https://doi.org/10.21203/rs.3.rs-5105731/v1

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This study evaluates air quality index (HQ) from toxic and heavy metal concentration across selected cities in Nigeria. Gravitational sedimentation method was used to collect air sediments to extract toxic and heavy metals contained in air particulates. Funnel shaped collectors securely attached to clean empty containers were exposed in open spaces at designated locations within the city, for a period of nine months, covering the two major seasons in Nigeria. (January to September, 2023). Airborne particles were allowed to settle naturally in the container along with rainwater. Samples from various points in a city were put together for laboratory analyses. This procedure was repeated in five other cities covering various geographical and climatic regions in Nigeria. The cities include: Benin (S1), Kano (S2), Abuja (S3), Lagos (S4), Enugu (S5), and Calabar (S6). The average concentration of toxic and carcinogenic elements reveals that salinity exhibits the highest HQ at 21.25, followed by nickel (Ni) at 4.58, magnesium (Mg) at 4.43, lead (Pb) at 3.66, chlorine (Cl) at 1.83, and chromium (Cr) at 1.06. Conversely, elements such as; Ar:0.3, NH₃:0.042, Al:0.36, CO:0.02, Cu:0.11, Zn:0.01, K:0.36, NO₂:0.32, NO₃:0.042, Fe:0.31 and Na:0.18 have HQs below 1, indicating safe exposure levels. Cadmium (Cd) displays the highest HQ in Kano (S2) at 2.33, suggesting significant health risks, including cancer and kidney failure. Nickel’s highest HQ is recorded in Edo State, Benin (S1) at 5.5, linked to bronchitis, asthma, and skin irritation. Manganese (Mn) has the highest HQ in Enugu (S5) at 16, with potential for lung inflammation, liver damage, and cognitive impairment. Lead (Pb) shows the highest HQ in Kano (S2) and Calabar (S6) at 8, associated with kidney damage and developmental issues. Salinity’s highest HQ is found in Abuja (S3) at 32.74, impacting water quality and health. Chromium (Cr) exhibits the highest HQ in Kano (S2) at 1.3, potentially causing lung cancer and bronchitis. Potassium (K) exceeds an HQ of 1 only in Kano (S2) at 1.05, posing risks of hyperkalemia and kidney issues. Elements with HQs below 1, including aluminum, cobalt, copper, zinc, nitrite, fluoride, sodium, and conductivity, are deemed safe for human exposure. This study highlights the critical need for monitoring and mitigating exposure to elements with high HQs to protect public health in these urban areas.

Particulate matter

sources of PM

effects of PM

Health

life expectancy

hazard quotient

PM 2.5

Recent findings highlight the severe impact of air pollution on global health. The Special Report by the Health Effects Institute (HEI) on the State of Global Air (SOGA, 2020) ranks air pollution as the fourth leading cause of premature death, responsible for about twelve percent of global fatalities. On average, it shortens life expectancy by approximately 2.2 years, with an estimated seven million deaths occurring annually due to air pollution. In West Africa, over 80% of urban populations are exposed to air quality levels that exceed the limits set by the World Health Organization (WHO, 2016). In the Niger Delta Area of Nigeria, a study conducted by Udo and Ewona, supported by TET Fund, has revealed significant levels of pollution in the region (Udo et al., 2018b; 2018c; 2020b; 2020c). To assess air quality, the gravity settling method will be employed for collecting air samples, as detailed by Ewona et al. (2021) and Ewona et al. (2022).

The World Health Organization (WHO) has determined that exposure to air pollution results in millions of deaths and lost years of healthy life, annually. Cardiovascular diseases (CVDs) are the leading cause of death globally. An estimated 17.9 million people died from CVDs in 2019, representing 32% of all global deaths. And 85% of those casualties were attributed to heart attack and stroke (WHO, 2021). Air pollution is currently reported as the greatest environmental threat to human health.

Air pollution has to potential to cause Noncommunicable diseases (NCDs). Noncommunicable diseases (NCDs) are now the primary causes of death and disability globally. NCDs are diseases that cannot be transmitted directly from one person to another. These include Parkinson's disease, strokes, heart diseases, cancer, diabetes, chronic kidney disease, and osteoarthritis. NCDs encompass a wide range of diseases affecting the cardiovascular, neurological, respiratory, and other organ systems. Air pollution increases the incidence and severity of cardiovascular and respiratory diseases and lung cancer, with growing evidence of its effects on other organs (Ewona et al. 2024; Udo, S. O. 2020; Ewona et al. 2013).

Air pollution originates from numerous sources, both natural and man-made, with combustion being the primary contributor. Fossil fuels and biomass combustion for energy generation is a major source of pollution, which can come from both indoor and outdoor sources.

Indoor sources of air pollutants include heating with polluted fuels like coal, wood, or dung, unvented heating, cooking stoves, cooking gas, tobacco smoke, and combustion for religious and cultural practices. Other sources include the use of incense and kerosene lamps for religious purposes, house renovations, cleaning products like detergents and insecticides, and the operation of electrical devices such as printers.

Outdoor sources include transportation, power generation, construction activities, industries, biomass burning, and the long-range atmospheric transport of pollutants from distant sources. Pollutants can be emitted directly as primary pollutants or formed in the air as secondary pollutants through complex physiochemical processes, such as sulfates, nitrates, and organic carbon.

Airborne pollutants such as particulate matter (PM), measured as PM2.5 and PM10, and gaseous pollutants including ammonia (NH3), carbon monoxide, nitrogen dioxide, sulfur dioxide, ozone, and organic air pollutants, have significant adverse effects on human health and the environment.

Tamuno et al. (2022) noted that the visibility of soot in the Niger Delta region of Rivers State, Nigeria, has led to increased respiratory tract infections. Air pollution is believed to be a growing cause of morbidity and mortality in Nigeria, particularly in regions like Rivers State, which produces 60% of the country's crude oil (Whyte et al., 2020). There is a need to investigate and identify sources of soot and ways to mitigate its impact, along with public health campaigns to communicate the health risks of particulate matter from soot. Particulate matter pollution poses a serious health concern, especially at elevated concentrations. Its size determines its atmospheric persistence and deposition in the human respiratory system. Burning solid fuels such as coal and biomass is a significant source of anthropogenic particulate matter.

Chlorine gas is a well-known harmful gas, with even small amounts causing severe health issues such as pulmonary edema, pneumonitis, emphysema, bronchitis, and irritation of the eyes, throat, and nose. Particulate matter is a major driver of climate change and a source of health toxicity. In the upper atmosphere, it modifies the earth's radiation budget and cloud formation, while in the lower atmosphere, it affects visibility and alters biogeochemical cycles. Most critical effects are observed in ambient air, where particulate matter degrades human health (Arideep, 2017).

Sources of Emission and Exposure

Air pollution arises from numerous discharge sources, both natural and man-made, due to industrialization. According to the WHO, the combustion process to generate energy is the largest contributor to air pollution, including the burning of fossil fuels in unvented heating and cooking stoves, tobacco combustion, and for cultural or religious practices.

Other outdoor combustion sources include transportation, biomass burning, industry, power generation, forest and savannah fires, and agricultural waste burning, particularly in urban areas (US EPA, 2010, 2016, 2017, 2019, 2020).

Air pollution is a globally recognized issue. PM2.5 has been linked to human mortality, morbidity, asthma, chronic obstructive pulmonary disease (COPD), pulmonary fibrosis, cancer, type 2 diabetes, and neurodegenerative diseases. Developed countries have made progress in mitigating these issues due to accessible environmental quality documents, while developing countries have achieved less due to insufficient records (Abulude et al., 2022; Ekah, 2023).

The impacts of air contamination include premature mortality and various diseases, such as coronary heart disease, type 2 diabetes, breast cancer, and colon cancer (Slezakova et al., 2018).

To reduce greenhouse gas emissions, improving public transportation systems and encouraging non-motorized means of transportation, such as biking, walking, and horse-drawn vehicles, are essential. Planting trees along major roads to trap and absorb pollutants, and discouraging the use of older vehicles, which emit more pollutants, are also important measures (Tunde et al., 2022).

Below is a table representing air quality guidelines (AQG) for PM and ozone, designed to protect public health, including the most vulnerable populations such as children, the elderly, and those with preexisting health conditions. These guidelines are periodically reviewed and updated based on the latest scientific evidence.

The study at the University of Cross River State, Calabar, Nigeria, involved collecting dust samples from six indoor halls across four campuses, analyzing them for heavy metals such as zinc (Zn), copper (Cu), iron (Fe), manganese (Mn), chromium (Cr), cadmium (Cd), nickel (Ni), and lead (Pb) using standard laboratory techniques, and revealed significant contamination, particularly with cadmium, necessitating bioremediation to mitigate health risks (Ewona et al. 2024; Udo et al. 2020; Ewona et al. 2013).

Ewona & Okoli (2018) examined the trends in life expectancy in Nigeria from various demographic perspectives. The study analyzed data from the World Bank and WHO, revealing that life expectancy has increased over the last two decades but remains lower than the global average. The authors recommend strengthening health policies and community-based health initiatives to address the underlying causes of low life expectancy and improve access to healthcare services.

Raquel et al. (2016) examined the global mortality burden linked to anthropogenic ozone and PM2.5 using a global chemical transport model. Their simulations for 2005 estimated that 2.23 million deaths annually can be attributed to anthropogenic PM2.5, with the highest mortality rates in East Asia. They found that residential and commercial sectors contributed significantly to these deaths globally, and suggested targeted air pollution control strategies for different regions.

Ewona (2020) explored how various socioeconomic factors influence life expectancy among rural populations in Nigeria. The study utilized surveys and interviews, finding that access to education and healthcare resources is crucial in determining health outcomes. The research results indicated that areas with improved education and healthcare services showed higher life expectancy. The author recommends targeted interventions to enhance these factors, including community health initiatives and educational outreach programs.

Elisaveta et al. (2013) provide an overview of PM pollution in Africa, outlining published monitoring studies, identifying major themes, highlighting data gaps, and discussing strategies to address particulate air pollution in fast-growing cities.

Frank et al. (2020) discussed the need to safeguard human health from particulate matter (PM) pollution generated by four contrasting sources: household biomass combustion, wildfires, desert dust storms, and urban air pollution in rapidly growing megacities. The article highlights measures to protect populations in these urban areas and addresses the economic and behavioral challenges associated with sustainable energy use. Key areas of focus include locations affected by high concentrations of airborne particles, the importance of effective communication through public awareness campaigns, and empowering communities to enhance their health and air quality.

Van et al. (2010) estimate global ground-level PM2.5 concentrations from 2001 to 2006 using NASA satellite aerosol optical depth observations. Their findings indicate that the long-term average PM2.5 level across Africa is about 25 µg/m³, with concentrations reaching approximately 50 µg/m³ in Northern African countries, primarily due to desert dust.

Ewona & Olaniyan (2021) examined the critical link between healthcare access and life expectancy in developing countries, focusing on Nigeria. The paper utilized statistical analysis of healthcare access data, revealing significant barriers, such as economic constraints and geographical challenges, that hinder access to quality healthcare services. The authors advocate for policy reforms aimed at improving healthcare infrastructure and accessibility, along with the implementation of mobile health services, to enhance overall health outcomes and life expectancy in underserved regions.

Ala’a (2021) evaluated PM2.5 and PM10 concentration levels in Karbala, Iraq, over a 20-day period from June 1 to July 20, 2015. The observed concentrations exceeded WHO recommendations, with PM2.5 levels above the guideline by 16% and PM10 by 12%. The study suggested that reducing PM2.5 density to as low as 3 µg/m³ could significantly decrease risks associated with long-term exposure for lung cancer and cardiopulmonary mortality.

Ewona & Chukwu (2019) investigated the critical determinants of life expectancy in Nigeria, focusing on socioeconomic variables, environmental conditions, and healthcare access. The results indicated that higher income levels and education are significantly correlated with increased life expectancy. The authors suggest enhancing educational programs and improving economic conditions as effective methods to strengthen health outcomes and reduce disparities.

Oyewale et al. (2022) investigated health risks from PM10, sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) in an industrial area of Pretoria West, South Africa, using 2014 hourly ambient pollution data. The assessment indicated that normal exposure levels generally did not pose significant health risks, but chronic exposure to PM10, NO2, and SO2 could harm sensitive populations, especially infants and children.

The review emphasizes the critical role of air quality in urban development in Africa, linking it to rapid urbanization, social issues, health impacts, climate change, policy, and innovation. The high pollution levels, driven by low vehicle and fuel standards, reliance on solid fuels for cooking, and waste burning, pose severe health threats (Asmamaw et al., 2021).

Research indicates significant variability in PM composition and size over space and time. Despite this variability, the relative health risk estimates per unit PM mass remain consistent, suggesting that health effects result from a combination of different chemical species rather than a single dominant type. PM also contributes to visibility reduction and climate change. To mitigate PM's effects, the authors recommend integrated strategies involving scientists and policymakers from various disciplines to address these challenges holistically (Cliff et al., 2005).

A study assessing PM2.5 levels in Nairobi identified seven monitoring sites based on land use types, employing low-cost sensors and cyclone samplers for measurement. Results revealed that PM2.5 concentrations peaked in industrial areas (111.87 µg/m³) and were lowest in forested areas (21.25 µg/m³). The study found daily variations in PM2.5 levels correlated with human activities and atmospheric conditions, suggesting varying exposure risks among residents of different land use types (Caroline et al., 2021).

Airborne particulate matter presents a significant global environmental concern due to its detrimental effects on health and the environment. Many developing nations are establishing standards for PM to address its impacts. This review critically evaluates how PM affects visual air quality, human health, and damage to materials, vegetation, soil, and water bodies (Jimoda, 2012).

Gurusamy et al. (2021) studied the impact of Saharan dust events on PM concentrations in Mexico, comparing data from Saharan dust days to non-Saharan dust days. Their findings indicated that PM10 and PM2.5 levels increased significantly during dust events, correlating with COVID-19 case numbers and emphasizing the need for improved air quality measures post-pandemic.

In Korea, sand dust is a source of PM, raising concerns about its health effects. Studies have shown that PM can enter the respiratory system through various mechanisms, leading to oxidative stress, inflammation, and increased risks for respiratory and cardiovascular diseases, including lung cancer. Effective management strategies are necessary to mitigate PM exposure and its health implications (Jun, 2016).

Ambient air pollution, including PM and gaseous pollutants, is a major environmental risk factor affecting health. PM comprises a mixture of small particles and droplets, containing various components like acids, metals, and soil. Studies have linked PM inhalation to numerous health issues, including asthma, lung cancer, and cardiovascular diseases (An-Soo, 2014).

An investigation into how air pollution affects the competitiveness of cities in Africa showed that PM2.5 levels negatively impact firm performance in terms of employment and productivity growth. Data indicated that the relationship between pollution and productivity is initially positive but turns negative as pollution levels rise, with specific thresholds identified for significant effects (Donkelaar et al., 2016).

In Bosnia and Herzegovina, ambient PM2.5 pollution accounts for a substantial proportion of deaths, with estimates suggesting that reducing PM could significantly increase life expectancy in affected cities (Vlatka et al., 2020).

Using data envelopment analysis, researchers compared health systems in 140 countries regarding life expectancy, estimating potential improvements based on current efficiency levels. The analysis indicated that lower unemployment and income inequality could enhance life expectancy without increasing healthcare expenditures (Virginia et al., 2021).

A study examining the determinants of life expectancy in the world's most polluted countries found that environmental degradation poses a threat to health, while health expenditure, clean water access, and improved sanitation positively influence life expectancy. The results highlighted various causal relationships between carbon emissions and life expectancy (Mohammad et al., 2022).

Lastly, a review of global healthcare data revealed significant correlations between causes of death, healthcare quality, and socio-economic factors. This study contributes to the literature by analyzing global trends in mortality causes and their regional disparities, suggesting that socio-economic conditions impact health outcomes (Simona-Andree et al., 2021).

3.1 MATERIALS

Materials used for the research include field data.
Software used for statistical analysis include; Origin, MATLAB, SPSS and MS excel.
Funnels, Petri dish, sellotapes, plastic containers used for field work.

3.2 METHOD

Funnels were securely attached to clean, empty containers, which were placed outdoors for a duration of nine months, from January to September 2023 at different sample locations grouped as single locations across different geographical locations in Nigeria. The locations include; Edo state (Benin) (S1), Kano (S2), Abuja (S3), Lagos (S4), Enugu (S5), and Calabar (S6). Samples were collected using the gravitational settling method, allowing airborne particles to settle naturally into the container along with rainwater. Subsequently, the samples were treated and moved to air quality control laboratory for spectroscopic analysis

The sediments extracted from the liquid were dried through heating. The analysis focused on the following elements: arsenic (As), cadmium (Cd), manganese (Mn), ammonia (NH3), chromium (Cr), mercury (Hg), chloride (Cl), aluminum (Al), cobalt (Co), copper (Cu), iron (Fe), zinc (Zn), potassium (K), nitrite (NO2), nitrate (NO3), and fluoride (Fl).

Additionally, the salinity and conductivity of the collected liquid samples were tested. All results were compiled and organized into tables. The detailed analysis for each element is presented below.

DETERMINATION OF HAZARD QUOTIENT

The Hazard Quotient (HQ) is a numerical value used to assess the risk posed by exposure to a hazardous substance. It is a dimensionless ratio that compares the potential exposure to a substance with the level at which no adverse effects are expected. The HQ is commonly used in environmental health and risk assessments to evaluate the potential non-carcinogenic health effects of chemicals.

Interpretation of Hazard Quotient

HQ < 1: Indicates that the exposure level is less than the reference dose, suggesting that adverse health effects are unlikely.
HQ = 1: Indicates that the exposure level is equal to the reference dose, which is considered a threshold level where no adverse health effects are expected.
HQ > 1: Indicates that the exposure level exceeds the reference dose, suggesting a potential for adverse health effects and the need for further investigation or mitigation.

This can be determined by the relationship;

HQ = \(\:\frac{Air\:concentration\:exposure\:measured\:at\:the\:field\:\:\:EC}{Reference\:concentration\:as\:recommended\:by\:regulatory\:bodies\:\:\left(RFC\right)\:}\)

Where

HQ = Hazard Quotient is dimensionless

EC = Exposure air concentration (\(\:\mu\:\)g/m³)

RfC = Reference concentration (\(\:\mu\:\)g/m³)

Hazard Quotient finds applications in the following areas

Environmental Risk Assessment: HQ is used to evaluate the risk of non-carcinogenic effects from exposure to environmental contaminants, such as heavy metals in soil, water, or air.
Human Health Risk Assessment: HQ helps determine the risk associated with exposure to chemicals in consumer products, occupational settings, or contaminated sites.
Regulatory Standards: HQ is used by regulatory agencies to establish safety standards and guidelines for allowable exposure levels to various substances.

Hazard Quotient HQ for locations S1 to S6 was computed and the results were obtained and analyzed as shown below. Locations for the study include; S₁ (Edo state, Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River) and the total averaged HQ for the entire locations were displayed as well. Results of the tabulated values are shown on the figures from Fig. 1 to Fig. 16.

Figure 1 shows the HQ for air samples across; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ (Calabar).

The last bar with the Gray colour is the total average across the entire locations. We can see from Fig. 1 the following HQ Cl: 1.83, Ni: 4.58, Mg 4.43, Cr 1.06, Pb 3.66, Fe 1.31, salinity 21.25. We can see that Salinity had the highest HQ followed by N, Mg, Pb, Cl and Cr.

The HQ gives a clearer explanation of the magnitude of the level of concentration of the emitted elements and heavy metals which call for urgent attention. Excessive exposure to the following elements might expose residents to adverse health effects. The figure also shows that elements such as; Ar:0.3, NH₃:0.042, Al:0.36, CO:0.02, Cu:0.11, Zn:0.01, K:0.36, NO₂:0.32, NO₃:0.042, Fe:0.31 and Na:0.18 concentration had HQ less than 1, indicating that the exposure level to toxic / heavy metals six below the suggested dose and safe limit for human consumption.

Figure 2 represents HQ for cadmium for s1 Edo state Benin, S2 Kano, S3 Abuja, S4 Lagos, S5 Enugu and S6 Calabar (Cross River). Results show that HQ > 1, suggesting a potential for adverse effects and the need for further investigation and mitigation. S2 kano had the highest HQ with numerical value of 2.33 followed by s4 Lagos and s6 cross river with HQ of 2.0. other cities Like S3 Abuja, S5 Enugu and S1 Benin had HQ of 1.66, 1.66 and 1.33 respectively. Cadmium is highly toxic chemical element and could be one of the leading causes of cancer and kidney failure when consumed in excess. The red colour bars in an indication of hazard since the HQ of the element is greater than 1.

Figure 3 represents HQ for nickel, at; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ (Cross River). It was seen that HQ > 1. This indicates the potential for detrimental effects on human wellbeing. HQ of nickel was highest at S1 (Edo state, Benin with a numerical value of 5.5, followed by S2, kano and s3 Abuja with numerical value 4.9 each. Other locations like S6, Calabar(Cross River), S4 Lagos and S5 Enugu had HQ value of 4.8, 4.3 and 3.1. the bar is repented with red colour indicating injurious reactions to man. excessive exposure to nickel might result in bronchitis, asthma, skin irritation.

Figure 4 represents HQ for manganese across s1, Edo State, Benin, S2 (Kano), S3 (Abuja), S4 (Lagos), S5 (Enugu), And S6 Cross River. S5, Enugu had the highest HQ of 16. Other locations like S6, Calabar, s4 Lagos, S3 Abuja, S2 Kano and S1 Benin had HQ of 2.6, 2.4, 2.0, 2.0, 1.6 respectively. The HQ bar chart was made red indicating that HQ > 1 which could be unfriendly to humans. Exorbitant exposure to manganese might result in lung inflammation, liver damage, neurological symptom and cognitive impairment.

Figure 5 illustrates HQ for lead as a heavy metal at; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ (Calabar, Cross River). It was observed That S2 Kano S6 Calabar, Cross River. result detects that all the locations in consideration had HQ > 1. HQ was greatest at S2 Kano and S6 Cross River. Results detects that all the locations in consideration had HQ > 1. HQ was greatest at S2 Kano and S6 Calabar with numerical values of 8 then followed by S3 Abuja and S5 Enugu with HQ of 6 and 5. Other locations such as S1 Edo State, Benin and S4 Lagos had HQ of 4 and 3 individually. High amount of HQ of lead indicates deleterious effects like kidney damage and hypertension in adults and developmental issues and learning disabilities in children.

Figure 6 depicts HQ for salinity for the following locations; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ (Calabar). The results reveal that HQ for s1 to s6 had HQ > 1. This indicates that exposure level of salinity exceeds the reference dose. HQ for S1 To S6 exceeded the reference dose. The pictorial representation further reveals that S3 Abuja has the highest emission of HQ followed by S5 Enugu with HQ of 32.74. Other locations such as S1 Edo, Benin, S2 Kano and S6 Calabar, S4 Lagos had HQ of 19.86, 15.23, 9.45 and 1.04 respectively.

Figure 7 depicts HQ for chromium element at S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River). It was observed that S2 kano S6 cross river. It was observed that S2 kano and S6 Lagos had HQ OF 1.3, 1.2, and 1.1 respectively. Expressing that HQ > 1. S1 Edo, S2 Abuja, S4 Lagos and S6 cross river may experience high level of lung cancer, ulcer, bronchitis (inflammation of tubes which carries air to the lungs).

Figure 8 describes HQ for potassium for S1 Edo, Benin, S2 Kano, S3 Abuja, S4 Lagos, S5 Enugu and S6 Calabar (Cross River). Result demonstrates that HQ < 1 which is below the reference dose for S1, S3, S4, S5 and S6 while HQ > 1 with the value of 1.05. result further reveals that residents living in kano may be exposed to risk of hyperkalemia, nausea and vomiting, muscle weakness, paralysis, kidney issues.

Figure 9 delineates HQ for aluminum for S1 Edo State, Benin, S2 Kano, S3 Abuja, S4 Lagos, S5 Enugu, And S6 Calabar (Cross River). The entire locations had HQ < 1indicating exposure level less than reference dose suggesting that adverse effects are unlikely.

Figure 24 depicts HQ for cobalt for S1, Benin, S2 Kano, S3 Abuja, S4 Lagos, S5 Enugu and S6 Calabar (Cross River). The HQ for the above listed locations were below the reference dose and suggesting that detrimental effects is implausible. Results shows that HQ ranged between 0.02 to 0.01.

Figure 11 represents HQ for copper element for locations; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River). The HQ for the following locations were below the reference dose. HQ ranges between 0.16 to 0.07.

Figure 12 signifies HQ for zinc element for ; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River). Results portray that HQ < 1 and was within the reference dose suggesting effects and doubtful. HQ ranges between 0.02 to 0.008.

The figure illustrates HQ for nitrite for; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River). The results reveal that HQ < 1 below for cadmium for the locations S1 to S6 ranged between 0.51 to 0.26.

Figure 14 stipulates that the HQ for nitrite for; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River). Results shows that HQ for nitrite < 1, which was below the reference dose. HQ for cadmium ranged between 0.07 to 0.02.

The figure reveals that HQ for fluoride for locations; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River). Results shows that HQ for fluoride < 1, below the reference dose. HQ for fluoride ranges between 0.19 to 0.07.

Figure 16 depicts HQ for sodium for cities; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River). Results reveals that for sodium, HQ < 1 which is below the reference dose. HQ for sodium ranges between 0.56 to 0.04.

Figure 17 represents HQ for conductivity for; S₁ (Benin), S₂ (Kano), S₃ (Abuja), S₄ (Lagos) S₅ (Enugu), S₆ Calabar (Cross River). Result shows that HQ for the above listed cities/ locations was within the range of 0.315 to 0.09 and was within a safe reference dose.

The study identified the highest hazardous quotients (HQ) for various elements across Nigerian cities, with salinity having the highest HQ at 21.25, followed by nickel (Ni) at 4.58, magnesium (Mg) at 4.43, lead (Pb) at 3.66, chlorine (Cl) at 1.83, and chromium (Cr) at 1.06. In contrast, elements such as Ar, NH3, Hg, Cl, Al, CO, Cu, Zn, K, NO2, NO3, Fe, and Na had HQs below 1, indicating safe exposure levels. Cadmium (Cd) showed the highest HQ in Kano (S2) at 2.33, with potential health risks including cancer and kidney failure. Nickel's highest HQ was in Benin (S1) at 5.5, linked to bronchitis, asthma, and skin irritation. Manganese (Mn) had the highest HQ in Enugu (S5) at 16, with risks of lung inflammation, liver damage, and cognitive impairment. Lead (Pb) had the highest HQ in Kano (S2) and Calabar (S6) at 8, associated with kidney damage and developmental issues. Salinity's highest HQ was in Abuja (S3) at 32.74, affecting water quality and health. Chromium (Cr) had the highest HQ in Kano (S2) at 1.3, potentially causing lung cancer and bronchitis. Potassium (K) had an HQ above 1 only in Kano (S2) at 1.05, with risks of hyperkalemia and kidney issues. Elements with HQs below 1, such as aluminum, cobalt, copper, zinc, nitrite, fluoride, sodium, and conductivity, were deemed safe for exposure. This analysis underscores the need for urgent attention to elements with high HQs to protect public health in Nigerian cities.

4.1 SUMMARY AND CONCLUSION

This study examines the Hazard Quotients (HQ) of toxic elements and heavy metals in six Nigerian locations: Edo State, Benin; Kano; Abuja; Lagos; Enugu; and Cross River. The highest HQs were found for salinity, nickel (Ni), magnesium (Mg), lead (Pb), chlorine (Cl), and chromium (Cr), indicating significant health risks. Elements such as cadmium (Cd), manganese (Mn), and potassium (K) also showed concerning HQs in specific locations. Conversely, elements like aluminum, cobalt, copper, zinc, nitrite, fluoride, sodium, and conductivity had HQs below 1, suggesting safe exposure levels. The study underscores the urgent need to monitor and mitigate high HQ elements to safeguard public health in these cities.

4.2 Funding Declaration:

The authors gratefully acknowledge financial support from the Nigerian National Research Fund through the Tertiary Education Trust Fund (TETFUND), which enabled the successful completion of this project.

Author Contribution

I. O. Ewona provided crucial supervision and guidance throughout the research, ensuring adherence to methodological standards and scientific accuracy.B. J. Ekah contributed as an author, actively participating in field work, research compilation, and analysis, while also managing the overall research process.J. U. Akwagiobe was responsible for conducting the fieldwork, including the collection of air sediment samples from various cities.S. O. Udo offered supervision and expert advice on research methodologies and procedures, facilitating effective data analysis.B. Rabiu supplied the necessary instruments and data, which were essential for the successful completion of the study.

4.3 Acknowledgements:

We would like to express our gratitude to Penn State University for providing data on air quality over Nigeria. We also acknowledge the Centre for Atmospheric Research (CAR) at the National Space Research Development Agency (NASRDA) in Nigeria for their technical support. Special thanks are also extended to OPENAQ, an American-based organization, for donating low-cost air quality monitoring sensors in support of this project.

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Evaluation of Hazard Quotient (Hq) of Toxic and Heavy Metal Concentration in Air Sediments Across Selected Cities in Nigeria

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Abstract

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1.0 INTRODUCTION

2.0 LITERATURE REVIEW

3.0 MATERIALS AND METHODS

3.2 METHOD

4.0 RESULTS OF ANALYSIS

4.0 DISCUSSION

4.1 SUMMARY AND CONCLUSION

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Author Contribution

4.3 Acknowledgements:

References

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