Environmental Pollution and Related Hazards at Agbara Industrial Area, Ogun State

Abstract

This study aimed at assessing the environmental pollution and related hazards of industries at Agbara, Ogun State, Nigeria. A total of five sampling points were identified and selected at random. Environmental samples were collected on a weekly basis for duration of 10 weeks. Air pollutants measured were CO₂, CO, NO, NO_x, VOCs, H₂S, SO₂, NH₃, PM_2.5 andPM₁₀ using standard procedure. Dust and plant samples were also collected and analyzed for heavy metals (Pb, Cr, Cd, Cu and Zn) using the Atomic Absorption Spectrophotometer (AAS). Data was evaluated for descriptive and inferential statistics using SPSS for Windows version 22.0. Air pollution data were also subjected to SPE-risk model. The results of highest measured air parameters were: CO (5.50 ± 2.32 ppm), CO₂ (3.00 ± 2.05%), NO_x (0.90 ± 0.32 ppm), NO (0.60 ± 0.52 ppm), PM₁₀ (0.40 ± 0.52 mg/m³) and PM_2.5 (0.20 ± 0.42 mg/m³). The results of heavy metal concentrations in dust samples were: 57.40 ± 13.28 mg/kg for Cu, 45.36 ± 12.37 mg/kg for Cr, 22.80 ± 17.36 mg/kg for Zn, 13.76 ± 3.08 mg/kg for Pb and 0.32 ± 0.36 mg/kg for Cd. Metal concentrations in plants were: Cu (70.07 ± 16.24 mg/kg), Zn (67.69 ± 14.50 mg/kg), Cr (22.46 ± 9.35 mg/kg), Pb (13.76 ± 3.08 mg/kg) and Cd (2.25 ± 3.04 mg/kg). This study revealed the concentrations of CO₂, NO_x and NO higher than the World Health Organization (WHO) permissible standards while Pb, Cu, Cr, Cd and Zn values in dust samples were also found above the National Environmental Standards and Regulations Enforcement Agency (NESREA) and the WHO standards. Results of SPE-RISK model indicated that CO₂, CO, Pb, Cu and Zn posed the greatest health risks, while the Principal Component Analysis (PCA) indentified pollutant sources from industrial and vehicle exhaust.

Introduction

Lithosphere and hydrosphere are natural resources that enhance agriculture and development of human race but are frequently subjected to great exploitation and degradation by natural and human factors¹. McGrath et al.² opined two kind of pollution sources are responsible for these degradation of land and water which include pollution from industrialization, agricultural activities and motorization usage while each of the sources affect plants and animals alike as well as posing great danger to human health. Most heavy metals are not easily degradable and thus find their ways into water body and soils, where they are bio-accumulated in food chain. Human are exposed to certain carcinogenic metals (As, Cd, Ni, Pb, Cr and Co) through ingestion of contaminated foods³. These metals thereby, pose great threat to human existence and the environment at large.

Exposure to environmental pollutants in the cities is of severe environmental and health concerns today in the world⁴. Studies have documented linkages between health effects and atmospheric pollution⁵ leading to serious health effects ranging from respiratory related diseases to chronic diseases that could lead to high mortality⁶. Bell et al.⁷ opined that poor hygiene and health care delivery are related to low income populations who are exposed to atmospheric pollution, because they live in blighted environment, industrial areas and roadsides to gain access to work place. They thereby exposed themselves to all sorts of environmental hazards; and in many cases denied access to health care delivery leading to death⁷. Exposure is particularly high among women and young children, who spend the most time near the domestic hearth. The World Health Organization is providing technical support to countries in their own evaluations and scale up of promoting safer stove technologies, as well as air quality guidelines to offer global guidance on reducing the health impacts of air pollution⁸.

In addition, industrialization, development and economic activities had increased globally over the years as a result of man quest to improved standard of living and these are manifested in fossil fuel production and usage for motorization. Ibeto et al.⁹ identified petrol chemical industry as main sources environmental pollution. Pb, Cd, Ni, Mn and Cr had been largely linked to many of these disease affecting man and its environment¹⁰. In general, heavy metals cause systemic toxicity, influences behavior, disrupts neurological system and mental function. Ibeto and Okoye¹¹, have identified heavy metals in soil and water body in large quantities as a result of industrial pollution.

Studies have shown that soils and dusts are contaminated by percolation and infiltration of heavy metals during industrialization, manufacturing, agriculture, mining, waste disposal, industrial effluents, and disposition from the atmosphere^12,13. In most cases, metals do not degrade by microbial of chemical means¹⁴, and persist once been introduced to the medium¹⁵ and severely prevent the biodegradation or deconcentration of any organic contaminants found within its immediate environment¹⁶. Consequently, they pose risks and hazards to man through the ecosystem or direct ingestion, inhalation or dermal contact. McLaughlin et al.¹⁷ viewed phytotoxicity to reduce land profitability and agricultural activities with resultant effects on food security and sustainable development. It is important to carry out a research on environmental pollution and its related hazards in order to proffer mitigating measures aimed at safeguarding the environmental and public health.

Materials and Methods

Study Area

Agbara industrial area is a fast growing town in Ogun State. The industrial area is a model integrated Town development on 454.1 hectares of land. It is situated approximately 31 kilometers west of Lagos on the Lagos-Badagry expressway on high ground above the Owo River and derives its name from the neighbouring Agbara village¹⁸. It center lies at 6°31′0″ North, 3°6′0″ East (www.gomapper.com) and it has an elevation of 37 meters above sea level. The industrial areas are made up of 41.55% (188.289 hectares) of the whole estate¹⁸. The location and accessibility of Agbara Estate makes the transportation of raw materials and finished goods. Figure (a) shows the study area and the sampling locations.

Sample Collection and Analysis

Air Measurements

Air pollutant samples (gaseous and particulate matter) were collected within a 30 m radius, between the hours of 10:00 am – 2:00 pm, from 14^th of August – 16^th of October, 2015 (10 weeks) at the 5 (five) sampling points (Fig. 1). The air quality indicators were measured and monitored in unconfined (outdoor) environment at the sampling locations. The sampling equipment is presented in Table 1. All samples were taken 3 times to minimize error from device readings.

Figure 1.

Area map of Agbara.

Table 1.

Equipment and their uses.

Equipment	Readings
Air borne particulate monitor, model – PDR-1200	%CO2, CO, SO2, NO and NOX
Industrial Scientific iTX Multi Gas Monitor Tester iSP Sample Pump	H2S, NH3 and VOC
Thermo Scientific pDR-1000AN (Personal Data Ram)	PM10 and PM2.5
eTrex Legend H – Garmin GPS Handheld device	GPS co-ordinates

Dust, Plant Sampling and Preparation

Dust was collected in triplicates from the road sides of the five (5) sampling points The samples were collected with a stainless steel spoon and placed in clean polyethylene bags to avoid contamination. Each of the samples was labeled with a paper tape and a pen. The samples were sun dried for two (2) weeks.

Plant samples were collected from the sampling points in triplicates. The plant species used was spear grass (Heteropogoncontortus (L.) due to its relative abundance at each sampling point. Each of the samples was uprooted and placed into polyethylene bags and were labeled using paper tape and a pen.

Chemical Analysis for Soil and Plant

A rapid nitric‐perchloric acid digestion method was used for the dust and plant analyses. The dust and plant samples were sieved with a 0.5 mm mesh sieve. The samples were pulverized and weighed (0.5 g) into a conical flask where 10 ml mixed acids (Perchloric acid and nitric acid in ratio of 1:2) was added and allowed to undergo heating on a digester hot plate at 105 °C for about 30 minutes until the colour changed. The digested sample was allowed to cool and then filtered and made up to 50 ml with distilled water. The digested sample was read using Bulk Scientific Atomic Absorption Spectrophotometer (model 210/211 Vap) to analyze the concentrations of Pb, Cd, Cr, Cu and Zn. The blank samples were also analyzed to determine the detection limit (3 × standard deviation of six blank samples), and limit of quantification (10 × detection Limit). All samples were analyzed in triplicates for good precision and accuracy. All chemicals used for analysis were of Analytical grade.

Statistical analysis

All data obtained from the earlier mentioned analysis were subjected to descriptive analysis, analysis of variance (ANOVA), the test of significance of the mean by Duncan’s Multiple Range (DMR) test, and Principal component Analysis (PCA) using SPSS for Windows version 16.0.

SPE – risk analysis

The SPE is a quick and dirty Risk Assessment process that can easily be used in the field

$$\mathrm{Risk}\left(\mathrm{R}\right)=\mathrm{Severity}\times \mathrm{Probability}\times \mathrm{Exposure}$$

Identify specific hazards and assign them a value for each elemental pollutants mentioned above.

The higher the number, the greater the Severity, Probability or Exposure.

Severity

Scored 1 to 5. Describes the potential loss or consequence or mishap. Protective devices or procedures are used to mitigate Severity.

$$1=\mathrm{none}\mathrm{or}\mathrm{slight}2=\mathrm{Minimal}3=\mathrm{Significant}4=\mathrm{Major}5=\mathrm{Catastrophic}$$

Probability

Scored 1 to 5. The likelihood that given the Exposure, the projected consequences will occur. Training situation awareness, morale and attitude change are used to mitigate Probability.

$$\begin{array}{l}1=\mathrm{Impossible}\mathrm{or}\mathrm{remote}\mathrm{under}\mathrm{normal}\mathrm{conditions}2=\mathrm{Unlikely}\mathrm{under}\mathrm{normal}\mathrm{conditions}3\\ =50/50\mathrm{chance}4=\mathrm{Greater}\mathrm{than}50\%\mathrm{chance}5=\mathrm{Very}\mathrm{likely}\end{array}$$

Exposure: Scored 1 to 4. The amount of time, number of cycles, number of people and resources (equipment) involved.

$$1=\mathrm{None}\mathrm{or}\mathrm{below}\mathrm{average}2=\mathrm{Average}3=\mathrm{Above}\mathrm{average}4=\mathrm{Great}$$

Results and Discussion

Air pollutant data

The air quality data, heavy metals in dust and plants at the five (5) different locations within Agbara industrial district are shown in Tables 2–4. Table 2 shows the concentrations of various air pollutants at the sampling sites. The highest concentrations of CO (5.50 ± 2.32 ppm), CO₂ (3.00 ± 2.05%), NO_x (0.90 ± 0.32 ppm), NO (0.60 ± 0.52 ppm) were measured at the monitoring sites SP1, SP4, SP2 and SP1, respectively. PM₁₀ (0.40 ± 0.52 mg/m³) and PM_2.5 (0.20 ± 0.42 mg/m³) were observed at the highest levels in SP2. These sites were dominated by many industries, which use heavy duty generators that run on fossil fuels to power their equipment.

Table 2.

Air pollutant concentrations at the various sampling points in Agbara industrial area.

Location codes	CO2 (%)	CO (ppm)	NO (ppm)	NOX (ppm)	H2S (ppm)	VOC (ppm)	SO2 (ppm)	NH3 (ppm)	PM2.5 (mg/m3)	PM10 (mg/m3)
SP1	2.20 ± 1.03a	5.50 ± 2.32a	0.60 ± 0.52a	0.70 ± 0.48a	<0.01	<0.01	<0.01	<0.01	0.0000	0.30 ± 0.48a
SP2	2.10 ± 1.00a	4.10 ± 2.88a	0.30 ± 0.48a	0.90 ± 0.32a	<0.01	<0.01	<0.01	<0.01	0.20 ± 0.42a	0.40 ± 0.52a
SP3	2.00 ± 1.49a	1.90 ± 1.45bc	0.40 ± 0.52a	0.60 ± 0.52a	<0.01	<0.01	<0.01	<0.01	0.01	0.20 ± 0.42a
SP4	3.00 ± 2.05a	3.90 ± 3.11ab	0.50 ± 0.53a	0.80 ± 0.63a	<0.01	<0.01	<0.01	<0.01	0.01	0.10 ± 0.32a
SP5	2.20 ± 1.23a	1.10 ± 0.88c	0.20 ± 0.42a	0.67 ± 0.50a	<0.01	<0.01	<0.01	<0.01	0.01	0.20 ± 0.42a
FEPA (1991) Standards	0.1	10	0.06	0.06	0.008	3	0.2	0.28	80
WHO (1990)				0.08						25

SP1- Industrial Roadside, SP2- Lagos Badagry express way, SP3-Market area, SP4-Banking district, SP5-Residential area, Different super scripts (alphabets) in the same column indicate significant difference at p < 0.05 according to Duncan Multiple Range Test.

Table 4.

Heavy metals concentration in plant samples.

Locations	Pb (mg/kg)	Cd (mg/kg)	Cr (mg/kg)	Cu (mg/kg)	Zn (mg/kg)
SP1	7.20 ± 1.77c	0.45 ± 0.14b	22.46 ± 9.35a	70.07 ± 16.24a	21.80 ± 7.51c
SP2	10.98 ± 1.77b	1.51 ± 0.37ab	7.75 ± 3.84c	54.56 ± 13.82bc	22.60 ± 6,03c
SP3	13.76 ± 3.08a	2.25 ± 3.04a	12.61 ± 2.14b	62.55 ± 6.90ab	67.69 ± 14.50a
SP4	4.15 ± 1.34d	0.26 ± 0.25b	8.35 ± 1.48c	48.01 ± 12.37c	36.40 ± 7.44b
SP5	7.36 ± 1.39c	0.23 ± 0.34b	2.88 ± 1.14d	28.56 ± 6.07d	43.40 ± 7.31b
WHO limits of Heavy Metals in Plants	2	0.02	1.3	10

SP1- Industrial Roadside, SP2- Lagos Badagry express way, SP3-Market area, SP4-Banking district, SP5-Residential area, Different super scripts (alphabets) in the same column indicate significant difference at p < 0.05 according to Duncan Multiple Range Test.

It was observed that PM_2.5 and PM₁₀, CO₂, NO and NO_x concentrations were all higher than the FEPA and WHO standards which poses serious health threat^19,20. These standards were based on permissible limits for work hour exposure (8 hours) and 24 hours for particles daily exposure. The H₂S, VOC, SO₂ and NH₃ values were measured below the equipment detection limit (<0.01 ppm).

It was also observed that there was no significant (P > 0.05) difference amongst the concentration of all air parameters measured except CO which had a significantly (P < 0.05) higher concentration. Furthermore, SP4 and SP2 are been dominated by heavy duty generators used by the residing manufacturing companies and banks while SP3 and SP5 had the least CO concentrations of 1.90 ± 1.45 and 1.10 ± 0.88 ppm, respectively must be attributed to the fact that the SP3 and SP5 are the market area and residential areas. The results depicted that NO, NO_x, and PM₁₀ all did not having any significant (P > 0.05) variations at the sampling sites. The presence of these pollutants at high concentrations in the atmosphere can be attributed to industrial processes such as combustion from furnace, smelting of metals, melting of glass and plastics.

Higher concentrations of CO₂ are likely to have on global climate and profound direct effects on the growth, physiology, and chemistry of plants, independent of any effects on climate²⁰. These effects result from the central importance of CO₂ to plant metabolism. CO is a weak greenhouse gas, but its influence on climate goes beyond its own direct effects. Its presence affects concentrations of other greenhouse gases including carbon dioxide, methane and tropospheric ozone. It readily reacts with the hydroxyl radical (OH) forming a much stronger, greenhouse gas CO₂. The finest of these particles penetrate to sensitive tissue through ingestion, inhalation or dermal contact and causing serious damages and eventually death. Inhalation may cause serious respiratory illness and diseases aggravating to heart disease²¹. Among the grievous kind of air pollutant are particulates matter due to their ability to penetrate deep into the lungs and blood streams unfiltered, causing permanent DNA mutations, cardiac attacks and subsequently death²². In 2013, in nine European countries study involving over three hundred thousand people reveals that the lung cancer rate rose by 22% and 36% for every increase of 10 μg/m³ in PM₁₀ and PM_2.5, respectively²³.

Dust samples

Table 3 presents the heavy metal concentrations in dust samples collected at different sampling points (mg/kg) in Agbara industrial area. It was observed that Pb, Cd, Cr, Cu and Zn concentrations were far above the FEPA and WHO permissible standards. Zn has the highest concentration (57.40 ± 13.28 ppm) at SP3, due to close proximity to two notable industries in the study area, which uses Zn as a raw material in their production processes. Cr had its highest concentration (45.36 ± 12.37 ppm) at SP1. The monitoring site SP1 was also very close to a Glass manufacturing industries that uses Cr for glass green colouration. Cr is a very powerful colourizing agent, yielding dark greenor in higher concentrations even black colour. Together with tin oxide and arsenic, it yields emerald green glass²⁴. Copper had its highest concentration at the market area, SP3 (22.80 ± 17.36 ppm), which was also close to a Cable and Wire Manufacturing Company in the study area. Among the measured metals, Pb and Cd had the highest concentrations at the highway sampling station. Major sources of lead in the air are ore and metals processing and piston-engine operating on leaded fuel. Other sources are waste incinerators, utilities, and lead-acid battery manufacturers. The nearby Plastic industry could also have contributed to high Cd concentrations in dust samples as Cd is also been used as a stabilizer in plastics¹⁹. Metals in dust samples were measured at the lowest concentrations at the residential area of the study area.

Table 3.

Heavy metal concentrations in dust samples.

Location	Pb (mg/kg)	Cd (mg/kg)	Cr (mg/kg)	Cu (mg/kg)	Zn (mg/kg)
SP1	9.00 ± 4.15a	0.17 ± 0.14bc	45.36 ± 12.37a	17.76 ± 1.82ab	32.43 ± 18.48b
SP2	12.33 ± 4.08a	0.49 ± 0.60a	30.37 ± 14.55bc	18.70 ± 26.34ab	26.31 ± 8.49b
SP3	10.79 ± 4.56a	0.32 ± 0.36ab	26.41 ± 12.93c	22.80 ± 17.36a	57.40 ± 13.28a
SP4	11.10 ± 3.03a	<0.01	39.40 ± 8.53ab	15.30 ± 4.24ab	33.40 ± 14.70b
SP5	9.40 ± 2.12a	<0.01	9.70 ± 3.09d	6.70 ± 2.54b	8.80 ± 2.30c
FEPA (1991) Standard	0.01	0.003	2	1	3
WHO (1984) Standards	0.05	0.005	0.05	0.05	1.5

SP1- Industrial Roadside, SP2- Lagos Badagry express way, SP3-Market area, SP4-Banking district, SP5-Residential area, Different super scripts (alphabets) in the same column indicate significant difference at p < 0.05 according to Duncan Multiple Range Test.

The order of abundance of heavy metals in dust samples are in the order: Zn > Cr > Cu > Pb > Cd. The data showed that lead concentration showed no significance (P > 0.05) at five (5) sampling points. The sources are either from generator exhaust, automobile exhaust or industrial chimneys. Zinc, chromium, copper and cadmium concentration were all significantly (P < 0.05) different from one another, because each sampling point had different emission sources that are unique to each sampling points.

Plant sample

The heavy metal concentrations in plant samples (Heteropogon contortus (L.) collected from the study area are presented in Table 4. The order of the heavy metal uptake by the plant samples were Cu > Zn > Pb >Cr > Cd. This is because copper is more available for plant absorption due to the addition of organic matter. The presence of humic substances could favour the absorption of heavy metals and competitions among them are well established²⁵. Studies of the competition for the absorption sites and type of ligand model of cadmium, copper and zinc showed that copper had a greater binding affinity than the other two metals^25,26. Bioavailability is influenced by physical factors such as temperature, adsorption, phase association and sequestration and can also be affected by chemical factors that influence speciation at thermodynamic equilibrium, lipid solubility, complexation kinetics, and octanol/water partition coefficients²⁷. Biological factors such as species characteristics, trophic interactions, and biochemical/physiological adaptation, also play an important role²⁸.

Principal Component Analysis (PCA)

Air sample analysis

Table 5 shows the rotated PCA data of the air pollutants. The essence of PCA model is to identify the possible sources of measured air pollutants. Three factors were identified with 65% of dataset explained. Factor1 with highest % variance of 27% has high positive loadings for CO, NO and NOx. This source indicates vehicular emission from mobile combustion of fossil fuel in line with published work²⁹. Factor 2 has a significant affinity for CO₂ and PM_2.5 and can be designated an industrial source. Factor 3 was only significant for PM₁₀, the possible emission source might be from road dust re-suspension²².

Table 5.

Principal component analysis of air pollutants.

Parameters	Factors			Communalities
	1	2	3
CO2	−0.013	0.698	0.156	0.511
CO	0.623	0.010	0.158	0.414
NO	0.757	−0.226	−0.287	0.706
NOX	0.819	0.115	0.046	0.686
PM10	0.042	−0.025	0.954	0.913
PM2.5	−0.003	0.818	−0.205	0.711
%Variance	27	20	18
Sources	Vehicular	Industrial 1	Road dust

Dust analysis

Table 6 presents the rotated PCA data of the metals in dust samples. Two factors were identified by the multivariate model explaining 66% of the total data variance. Factor 1 has high loadings for Pb, Cd and Zn while Factor 2 was highly loaded for Cr and Cu. The prominent emission sources were industrial and traffic, respectively. Taiwo et al.^30,31 had shown steel industry as major emitters of Pb, Cd and Zn, while Cu had been adopted as a signature for vehicular brake dust.

Table 6.

Principal component analysis of metals in dusts.

Parameters	Factors		Communalities
	1	2
Pb	0.841	0.153	0.731
Cd	0.653	0.221	0.475
Cr	−0.022	0.813	0.662
Cu	0.146	0.828	0.707
Zn	0.775	−0.340	0.716
%Variance	35	31
Sources	Engine exhaust	Industrial

The SPE-risk model is shown in Table 7. The model indicates that carbon dioxide and carbon monoxide have the greatest health risk, which needs to be regulated urgently. The major sources of these gaseous pollutants as indicated by the PCA model were industrial and vehicular emissions. The next health threat, which fell on the substantial range, was PM_2.5 and PM₁₀. These particulate pollutants originated from various sources and are accumulated along the major road networks as soil and road dust. Such sources include road re-suspended dust, industrial emission, construction materials used (sand and cement), sooth from cooking stoves, charcoal or generators which are deposited by wind to the high way. The next are nitrogen monoxide, oxides of nitrogen, volatile organic compounds and Sulphur dioxide that posed a significantly lower health threat due to lower exposure rate and lower concentration. The least health risks were observed for ammonia and hydrogen sulphide, probably due to their very low concentration in the area and weaker effects to human health. The SPE model of heavy metals indicated that copper, zinc and lead have the highest health risks, owing to their very high concentrations in the vicinity (Table 8). The least health threat was measured for cadmium because of its extremely lower concentration and low exposure rate.

Table 7.

Risk analysis of air pollutants on the environment and human at Agbara industrial district.

Parameter Measured	F. Identity Risk	Probability (P)	Severity (S)	Exposure (E)	Risk Calculation (SxPxE)	Risk Level	Risk
Carbon dioxide (CO2)concentration at Agbara industrial district	Exposure to its on-site concentration	Frequent (5)	Critical (3)	Great (4)	60.00	High	Immediate correction needed before proceeding. Worn-out control devices at industries should be replaced while VIO should be more proactive with vehicle emission inspection. Continuous oversight & re-evaluation is required. Risk controls must reduce the level of risk to one that is lower than initially calculated.
Carbon monoxide (CO) concentration at Agbara industrial district	Exposure to its on-site concentration	Frequent (5)	Catastrophic (4)	Above Average (3)	60.00	High	Immediate correction needed before proceeding. Worn-out control devices at industries should be replaced while VIO should be more proactive with vehicle emission inspection. Continuous oversight & re-evaluation is required. Risk controls must reduce the level of risk to one that is lower than initially calculated.
Nitrogen oxide (NO) concentration at Agbara industrial district	Exposure to its on-site concentration	Likely (4)	Critical (3)	Average (2)	24.00	Possible	Acceptable. Some attention needed. Implement risk reduction controls to further reduce the level of risk as appropriate.
Other oxides of nitrogen (NOx) concentration at Agbara industrial district	Exposure to its on-site concentration	Likely (4)	Critical (3)	Average (2)	24.00	Possible	Acceptable. Some attention needed. Implement risk reduction controls to further reduce the level of risk as appropriate.
Hydrogen sulphide (H2S) concentration at Agbara industrial district	Exposure to its on-site concentration	Rarely (1)	Minor (1)	Below average (1)	1.00	Slight	Acceptable
Volatile organic compounds (VOC) concentration at Agbara industrial district	Exposure to its on-site concentration	Occasional (3)	Catastrophic (4)	Average (2)	24.00	Possible	Acceptable. Some attention needed. Implement risk reduction controls to further reduce the level of risk as appropriate.
Ammonia (NH3) concentration at Agbara industrial district	Exposure to its on-site concentration	Likely (4)	Minor (1)	Above Average (3)	12.00	Slight	Acceptable
Sulphur dioxide (SO2) concentration at Agbara industrial district	Exposure to its on-site concentration	Occasional (3)	Significant (4)	Above Average (3)	36.00	Possible	Acceptable. Some attention needed. Implement risk reduction controls to further reduce the level of risk as appropriate.
Particulate matter (PM2.5) concentration at Agbara industrial district	Exposure to its on-site concentration	Frequent (5)	Critical (3)	Above Average (3)	45.00	Substantial	Correction and/or risk mitigation is required. Mitigation controls have to be implemented. Risk controls must reduce the level of risk to one that is lower than was initially calculated.
Particulate matter (PM10) concentration at Agbara industrial district	Exposure to its on-site concentration	Frequent (5)	Critical (3)	Above Average (3)	45.00	Substantial	Correction and/or risk mitigation is required. Mitigation controls have to be implemented. Risk controls must reduce the level of risk to one that is lower than was initially calculated.

Table 8.

Risk analysis of heavy metals in dust on the environment and human at Agbara industrial district.

Parameter Measured	F. Identity Risk	Probability (P)	Severity (S)	Exposure (E)	Risk Calculation (SxPxE)	Risk Level	Risk
Lead concentration at Agbara industrial district	Exposure to its on-site concentration	Likely (4)	Catastrophic (4)	Significant (4)	64.00	High	Immediate correction needed before proceeding. Worn-out control devices at industries should be replaced while VIO should be more proactive with vehicle emission inspection. Continuous oversight & re-evaluation is required. Risk controls must reduce the level of risk to one that is lower than initially calculated.
Chromium concentration at Agbara industrial district	Exposure to its on-site concentration	Occasional (3)	Critical (3)	Significant (4)	36.00	Possible	Acceptable. Some attention needed. Implement risk reduction controls to further reduce the level of risk as appropriate.
Cadmuim concentration at Agbara industrial district	Exposure to its on-site concentration	Rarely (2)	Catastrophic (4)	Below average (1)	8.00	Slight	Acceptable.
Copper concentration at Agbara industrial district	Exposure to its on-site concentration	Frequent (5)	Critical (3)	Great (4)	60.00	High	Immediate correction needed. Worn-out control devices at industries should be replaced. Continuous oversight & re-evaluation is required. Risk controls must reduce the level of risk to one that is lower than initially calculated.
Zinc concentration at Agbara industrial district	Exposure to its on-site concentration	Frequent (5)	Critical (3)	Significant (4)	60.00	High	Immediate correction needed. Worn-out control devices at industries should be replaced. Continuous oversight & re-evaluation is required. Risk controls must reduce the level of risk to one that is lower than initially calculated.

Conclusion

The study had assessed the environmental pollution and related hazards of industries at Agbara, Ogun State, Nigeria. Results showed that CO₂, NO and NOx concentrations were higher than the WHO and FEPA permissible standards for work exposure at all five sampling points. The high CO₂ value measured in this study is of great environmental concern due to its major contributor to the green house gas and climate change. The NO and NOx are also a big threat, which are formed during extremely high temperature combustion processes. Also, Pb, Cd, Cr, Cu and Zn all had concentrations above the WHO and FEPA standards at all five sampling points. The trend of heavy metals in dust at Agbara industrial district was Zn > Cr > Cu > Pb > Cd. The concentration of heavy metals found in plants followed the sequence: Cu > Zn > Pb > Cr > Cd. The principal component analysis revealed traffic and industrial emissions as major contributors to air pollution in the study area. The SPE model revealed carbon dioxide and carbon monoxide as important air pollutants with greatest health threats in the study area. For heavy metals, the SPE model showed copper, zinc and lead as most hazardous metals with the highest health risks. This study showed industries and traffic as the major threats to urban atmospheric environment.

Author Contributions

O.Z.O. Prepared the main manuscript and supervision of data collection, J.O.O.E. was responsible for data collections and analysis, A.T.A. make final proof reading and supervised the data analysis and T.A.M. was also responsible for data analysis and supervision of data collection.

Competing Interests

The authors declare no competing interests.