An Outdoor Air Quality at a Residential Environment in Lagos, Nigeria Using Airly Low-Cost Sensor

1. Introduction

A major threat to public health is ambient air pollution, of which particulate matter [1,2] is one of the air contaminants with the greatest proof of health effects. Of these, fine particulate matter (PM₁₀, PM_2.5, PM₁), which have aerodynamic diameters of less than 10, 2.5, and 1 micrometers, are the appropriate indicators for urban air quality [3] and have been identified risk factors for health. They breach the lung's defenses, enter the bloodstream, and compromise the blood-brain barrier, leading to neurological, cardiovascular, and respiratory disorders as well as early mortality [4,5,6].

Though their spatial coverage is typically constrained, data from ground monitors is favored for analysis globally. Many attempts have been made to measure PM_2.5 concentrations using alternative techniques, such as satellite-based imaging and atmospheric chemistry models, in order to get around this issue. These techniques, however, are meant to supplement surface ground-monitored data rather than completely replace it [7]. To fully utilize the advantages of each data source and provide more accurate estimates of PM_2.5 concentrations on a large scale, it is recommended to integrate data from satellite imaging, ground-based monitors, and other models [8]. Lagos has not yet been the subject of this kind of study.

A thorough analysis of the most recent research shows that ambient PM concentrations in Lagos and other places have produced a range of findings. Table 1 illustrates how the location, season, time period, and year of measurement all affect the PM concentrations. Satellite data was utilized in one article, although it wasn't calibrated using ground-level readings [9]. Other studies [10,11,12,13,14,15] gathered PM data using air samplers for brief periods of time, typically less than three months. The average yearly PM concentration in Lagos cannot be calculated using these attempts because of their short-term nature. The tools utilized are shown in Table 1 as follows: Microglass fiber, purpleAir sensor, Aerosol Mass Monitor, AQMesh, P-sensor, and handheld air tester (CW-HAT 200), in that order. No Airly low-cost sensor (LCS) was used in any of the studies.

There is currently no trustworthy estimate of the effects of ambient air pollution in Lagos using Airly LCS, particularly in the Mafoluku neighborhood, despite mounting worries about the city's air pollution problems. By giving a concise summary of the ambient PM₁₀, PM_2.5, and PM₁ pollution using Airly LCS and the toxicity potential of the region, this report fills in these gaps.

2. Materials and Methods

Sampling location Mafoluku, Lagos, in the Southwest area of Nigeria (6^o33'32.1'' N 3^o19'35.5'') was the urban site where the air quality was evaluated (Figure 1). The study is being conducted in Lagos, the former capital of Nigeria. It has both domestic and international airports, businesses, marketplaces, office and residential buildings, and a lot of traffic, both people and cars. Garbage is produced here. Residents have had trouble disposing of these trash. From this point of view, there is a reason for pollution from all the different activities. There is a lack of data in the Mafoluko area, Oshodi, where this study was conducted.

Meteorology of Lagos, Nigeria

One of the world's most crowded cities is Lagos, the former capital of Nigeria. There are almost 9 million people living in the 1,171.28 km² area. Lagos is situated on the Atlantic Ocean coast in Southwest Nigeria at 6°27′18′′N 3°23′03′′E. It is Nigeria's industrial and commercial hub. Nigeria generally has high temperatures and a humid climate. Nigeria has two distinct seasons based on its weather: the wet (raining) season (November to March) and the dry (harmattan) season (April to October). Lagos experiences hot, dry summers and moderate winters due to its Mediterranean climate. June through August is the ideal time osf year to visit Lagos if you enjoy the sun. With an average daily high of 28 ^oC and an average low of 19 degrees, July is the hottest month of the year.

Assessment

Using the standard particulate matter assessment technique, an assessment of air quality indicators was carried out from September to November of 2024. Data was collected in real time for a whole day. Figure 2 displays the Airly Sensor (GSM-PM-PTH 2965, Poland) that was utilized in this investigation. The sensor analyzes (real-time dashboard, report generator, social effect tracker), measures (PM₁, PM_2.5, and PM₁₀) each have a resolution of ± 1 µg/m³), and impacts (air pollution warning, mobile app, forecast, and air quality map). It weighs 440g, is made of stainless steel, and may be powered by a mobile battery, solar power, or commercial energy.

The sampling interval is 1-2 seconds, while the averaging and sending intervals are 5 minutes. Map.airly.org, the Airly website, provided access to the data. Since the research area was clear of obstructions, the sensor's accuracy was good. Using the manufacturer's handbook, installing the sensor was simple. It was suspended at least 1.8 meters above the ground and connected to a standard electrical outlet. Calibrated measurements appeared on the Airly Data Platform 48 hours later. The inexpensive sensor measured wind speed, wind bearing, and pressure, among other meteorological characteristics. CSV files of the results were downloaded.

Using the following formula, the toxicity potential (TP) for PM_2.5 and PM₁₀ at the outdoor sampling site is as follows [16,17]:

$$\mathrm{T}\mathrm{o}\mathrm{x}\mathrm{i}\mathrm{c}\mathrm{i}\mathrm{t}\mathrm{y} \mathrm{P}\mathrm{o}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{a}\mathrm{l}\left(\mathrm{T}\mathrm{P}\right)={\displaystyle \frac{Cp}{Sp}}$$

In this case, Sp is the usual recommendation value of 25 μg/m³ for PM_2.5 and 50 μg/m³ for PM₁₀, while Cp is the measured concentrations of the pollutants [18]. A TP score greater than one indicates that the chosen pollutant may pose a health concern in a certain area.

Backward air-mass trajectories analysis

In order to determine the origin of the particulate matter approaching the sampling location of the residential area in Lagos, Nigeria, a backward air-mass trajectory analysis that reached Lagos at 500 meters above ground level was computed using Hybrid Single-Particle Lagrangian Trajectory (HYSPLIT, NOAA/ARL) [19].

Statistical analysis

To evaluate the data at the location, the mean and standard deviation of each air quality indicator (PM_1.0, PM_2.5, PM₁₀, wind speed, wind bearing, and pressure) were computed. Statistically significant seasonal differences were evaluated at a 95% confidence level (p value = 0.05) using a paired t test. To determine whether PM levels and the meteorological parameter were related, the Pearson product correlation coefficient (r) was calculated. While Minitab software performed various computations, Excel 2013 was used to create the visual depictions.

3. Results

It is quite concerning how careless most people are with their air and air quality. Ambient air pollution has been largely caused by unmonitored human activity and noncompliance with preventive measures [12]. According to data (Table 2) gathered over a two-month period, the mean for PM₁₀, PM_2.5, and PM₁ was 36.32, 34.83, and 34.39 µg/m³, respectively. For Lugbe (11.42 – 156.73 µg/m³), Lagos – Ikeja and Maryland – 22–173 [9, and Lagos Mainland – 43.34 – 127.21 μg/m³, the results are consistent with PM₁₀ measured by Lawal and Mohammed, [12]. Although the maximum PM_2.5 in this study was higher than that of Obanya et al. [10], the mean PM_2.5 value (34.83 μg/m³) was higher than those reported by Alani et al. [11], Popoola et al. [14], and Yahaya et al. [13]. The study's mean results were lower than those published by Croitoru et al. [1]. The various activities, weather conditions, and assessment methods could all be contributing factors to the discrepancies. Kurtosis (11.38), Skewness (2.92), CV% (53.92), StD (18.54), and PM₁ mean are 34.39 μg/m³. The lowest and greatest values were in good agreement with those of Emekwuru and Ejohwomu [20], which ranged from 3.7 to 139.3 μg/m³.

The PM₁₀, PM_2.5, and PM₁ comparisons with WHO recommendations are displayed in Figure 3. Based on the averaged data for the study site, the average concentrations for PM₁₀, PM_2.5, and PM₁ were determined to be 36.12 μg/m³, 34.83 μg/m³, and 34.39 μg/m³, respectively. PM_2.5 was around 232.23% of the WHO air quality standard annual value (5 μg/m³), and PM₁₀ was over 80% of the WHO air quality standard annual value (45 μg/m³). The value for PM₁ was not computed since the WHO standard was not available. These values (36.12, 34.83, and 34.39 μg/m³) were higher than the annual average value from June 2021 and May 2022 at an urban site in Lagos (26 µg/m³), but they were close to the lower end of the annual mean values (from 40 to 135 μg/m³) at six sites in Lagos from August 2020 to July 2021 [21]. This implied higher local emission contributions at a particular industrial location in Lagos as opposed to the Mafoluku study site.

Particulate matter mass ratio of the PM indicators

The inter-particulate ratios were assessed in September and November to have a better knowledge of particulate matters in the outdoor environment (Figure 4). PM_1.0/PM_2.5, PM_2.5/PM₁₀, and PM_1.0/PM₁₀ had average ratios of 0.98, 0.95, and 0.93, respectively. In Hong Kong, Cheng et al. [22] found that PM_1.0 made up a significant amount of PM_2.5 and PM_2.5 made up a significant fraction of PM₁₀. According to their findings, PM_1.0 accounted for 68 to 84% of PM_2.5 and PM_2.5 for 73 to 82% of PM₁₀. Nonetheless, the ratios showed that mechanically generated aerosols or secondary aerosol particles contributed significantly to IAQ indicators, particularly for PM_1.0 and PM_2.5. During the assessment period, there was some variation in all three ratios (PM_1.0/PM_2.5, PM_2.5/PM₁₀, and PM_1.0/PM₁₀) at the sampling locations. The ratios do not significantly differ from one another.

Because PM₁-sized particles are more likely than PM_2.5 or coarse (PM₁₀)-sized particles to enter the lungs through the nose and throat, they are researched here because they are at least as dangerous. According to the measured mean PM₁/coarse particle concentration ratios (PM₁/PM₁₀), a significant fraction of the particulate concentrations in this region are caused by combustion and related processes that generate extremely small particles. Saetae et al. [15] found a ratio of 0.63, but this was over the course of 2.5 months during the dry season; these kinds of research are uncommon in this area. While fine particles are primarily created in the atmosphere by chemical reactions and organic substances, coarse particles are often created by mechanical processes like grinding or wind blowing. Accordingly, a high PM_2.5/PM₁₀ ratio suggests that fine particles, like those from combustion sources, contribute significantly to the PM concentration, while a low ratio suggests that coarse particles, like those from road dust or re-suspended soil, contribute more to the PM concentration [23].

Toxicity potential

According to Ayodele et al. [17], toxicity potential is a quantitative toxic equivalence that is helpful in determining the harmful impact that air pollution emissions from various hospital operations have on human health. A TP score greater than one indicates that the chosen pollutant may pose a health concern in a certain area. Both the annual and daily TP values of PM_2.5 and PM₁₀ were higher than 1 in the area. PM_2.5's values varied from 3.6 to 30.8 per year and daily from 1.2 to 10.27, while PM₁₀'s values ranged from 1.3 to 10.32 per year and daily from 0.43 to 3.44. Because standard guidelines were not available, the TP of PM₁ was not calculated (Figure 5). With the exception of a few number of instances in which the TP was less than 1, this indicated that the TP values for PM₁₀ daily were below 1.

The association between climatic characteristics and PMs concentrations in the outdoor sampling location during the assessment periods was examined using the Pearson product-moment correlation coefficient (PCC) (r value) at a 95% significance level. The relationships between particulate matter and meteorological parameters are displayed in Table 3 and Figure 6. There was an extremely high positive connection between PM_1.0, PM_2.5, and PM₁₀. Although they are weak, there are relationships between the PMs and the climatic data as well. The following is a presentation of the correlation coefficient threshold definitions that were modified from Schober et al. [24]:

Observed Correlation Coefficient, r    Interpretation

0.00 to 0.10          Negligible correlation

0.10 to 0.39           Weak correlation

0.40 to 0.69           Moderate correlation

0.70 to 0.89          Strong correlation

0.90 to 1.00          Very strong correlation

The three size fractions of particulate matter (PM_1.0, PM_2.5, and PM₁₀) have a strong positive connection, with r values ranging from 0.80 to 0.95 in the winter, according to comparable findings published by Abulude and Abulude [25] and Emekwuru and Ejohwomu [20].

The temporal trend of PM₁, PM_2.5, and PM₁₀ concentrations during a 24-hour period is displayed in Figure 7. The mean concentrations measured hourly on various days are used to compute the trend. In general, there is a greater fluctuation in particulate matter concentration during the day than at night. On the other hand, the nighttime concentration of particulate matter is higher than the daytime concentration. The reason for this could be that the atmosphere is more stable at night because of the lower temperatures, whereas during the day the planet is warmed by sunshine, which improves atmospheric mixing. At higher elevations, PM increases [26]. Additionally, the range of PM concentrations across different altitudes decreases at night when the mixing layer height (MLH) decreases [27]. Because particulate matter may more readily travel to higher altitudes in an unstable atmosphere, the difference in particulate matter concentration at different altitudes during the day is more noticeable, even though the concentration of particulate matter is larger at night.

Backward air-mass trajectories analysis

The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model [28,29] was used to calculate the directions and distances of the sources of the air parcel over the air pollutants measurement site in this study. The simulation results show that Southwestern desert winds contributed to the air mass over the site during the assessment. This difference between higher and lower PM levels were noted at Ile Ife, which is roughly 210 kilometers northeast of the Akoka Lagos sites [30]. According to Figure 8, the low-level air mass primarily arrives from the south and travels a comparatively short distance throughout the September–November season. Natural marine aerosols are abundant in the southerly air mass (originating from the Atlantic Ocean). Lower particle concentrations were observed throughout the research period as a result of the relatively fresh air mass and heavy rainfall, which considerably reduces the washout effect.