Abstract

Air quality in West Africa is strongly influenced by interactions between anthropogenic and natural emissions of particulate matter (PM). In this study, we examine variations in carbon aerosol concentrations (organic carbon (OC) and elemental carbon (EC)) during the dry and wet seasons, focusing on OC/EC ratios. This study is based on sampling from 2018 to 2020 at five urban sites in Côte d’Ivoire, including three in Abidjan (A1, A2, and A3) and two in Korhogo (K1 and K2). The results show that in Abidjan, OC/EC ratios in PM_2.5 almost double between the wet season (WS) and the dry season (DS), reflecting a stronger organic contribution during the DS, while in PM₁₀, the ratios remain stable or decrease slightly, suggesting a higher proportion of elemental carbon in coarse particles. In Korhogo, seasonal contrasts are more pronounced: at the K1 and K2 sites, OC/EC ratios increase from around 2 - 3 during the wet season to values above 5 during the dry season, with extremes at K2 where ratios in PM_2.5 and PM₁₀ double vs. WS. This variability highlights the strong influence of biomass and domestic waste combustion during the dry season, as well as marked differences between northern and southern sites in the contribution of carbonaceous species to PM_2.5 and PM₁₀ aerosols. Overall, the results highlight the value of OC/EC ratios as indicators of combustion sources and the need for seasonal monitoring in West Africa.

Keywords

OC/EC Ratio, PM_2.5/PM₁₀ Ratio, Dry Season (DS), Wet Season (WS), West Africa

Share and Cite:

1. Introduction

Cities in West Africa, which are experiencing rapid urban and population growth, are facing increasing challenges in understanding air quality. These challenges are amplified by multiple sources of pollution, including biomass burning, domestic fires, waste burning, industrial emissions, and road traffic, which contribute to high concentrations of particulate matter [1]-[3]. The study of certain ratios, such as PM_2.5/PM₁₀ and OC/EC in PM_2.5 and PM₁₀, is of great importance to characterize the nature of particles and understand their origins [4]. Organic and elemental aerosols have opposite optical properties; OC is light scattering while EC is absorbing.

The OC/EC ratio, which is a powerful indicator of anthropogenic and natural combustion sources, is highly dependent on the size of PM₁₀ or PM_2.5 particles, from which carbonaceous species (OC and EC) originate. PM_2.5 is mainly emitted by anthropogenic activities [5]-[8]; its OC and EC content will be more anthropogenic in origin. These carbonaceous species can originate from savanna fires (regional fires), which are more noticeable in the north during the dry season, so their impact can vary depending on the season [8] [9].

It has also been suggested that the importance of the biological/inflammatory impact of aerosols could be related to the relative OC content in combustion aerosols (e.g., the OC/EC ratio) due to the higher water solubility properties of OC than EC [10]. However, despite their importance already demonstrated by numerous articles [11] [12], studies on the carbonaceous species in particulate matter, particularly carbonaceous aerosols, remain limited in West Africa. This study analyzes the seasonality of PM2.5/PM10 and OC/EC ratios in PM₁₀ and PM_2.5 in two geographical areas with different geographical, economic, and meteorological characteristics. It is based on original data from two years of in-situ observations at five measurement sites.

2. Methodologies

2.1. Study Areas

In this study, five urban sites spread over 2 cities were sampled. These are the cities of Abidjan, with sites A1, A2, and A3, and Korhogo, with sites K1 and K2. These 2 cities are being studied simultaneously as part of the PASMU project, as their characteristics are very different. Indeed, the two cities differ in terms of economic activities, modes of transport, types of roads, cooking fuels, demographic practices, and local weather. In addition, the population densities of these two cities are also very different, with the population of Abidjan being 10 times greater than that of Korhogo, as shown in [2] [4] [5].

2.2. Sampling and Measurement Sites

Measurements were carried out using aerosol-type samplers such as those of the INDAAF project [13], but also in the framework of the DACCIWA program [14]. This sampling method was described in [2]. Samples are collected weekly on quartz fiber filters to obtain mass concentrations and carbon content (OC and EC) in PM_2.5 and PM₁₀ aerosols after analysis.

Sampling begins in March 2018 for A1 and K1 and in December 2018 for A2, A3, and K2, and ends in March 2020 for all sites. The monitoring network includes five sites representing diverse urban environments (Table 1). In Abidjan, the A1 site in the Cocody area is an urban background located in a middle- and high-income residential area, influenced by the source of road traffic. The A2 site, located in the Plateau, captures the direct impact of heavy traffic in the city’s main business district. The A3 site in Treichville is in a low-income, high-density neighborhood exposed to significant sources of urban pollution. In Korhogo, the K1 site, at the entrance to the city, represents an urban background indirectly affected by various anthropogenic sources, while the K2 site, in the city center, is surrounded by transport stations and the main market, concentrating emissions from transport and commercial activity.

Table 1. Location of the Abidjan and Korhogo measurement sites.

2.3. Determination of the Mass and Concentration of Carbonaceous Aerosols

Gravimetric analysis and particulate carbon analysis of weekly samples collected from the 5 sites over the medium term were performed according to the protocols described in [12]. For each quartz filter, weighing was carried out before and after sampling using a high-precision balance (Sartorius MC21S). The difference in mass is used to obtain the mass of aerosols collected.

The analysis of the carbonaceous aerosols was carried out by the multi-phase thermal method, using a BRUKER G4 ICARUS analyzer and developed by Cachier et al. [15] and applied in many works [3] [6] [12]. An analytical scheme is provided by Gnamien et al. [12] in practice. Multipoint calibrations of the analyzer are performed using sucrose solution assays (1 μC/μL concentration), and regression lines have been drawn for low total carbon and high total carbon conditions, comparing the values of the resulting integrals with known sucrose concentrations. A sample tray is used to pass the filters for analysis and is initially cleaned in an analysis furnace at 1000˚C. Blanks (tray) and (tray + white filters) are carried out before each major series of analysis. Double analyses of the same sample and blanks give differences representing 1% to 6% of the carbon mass detected. A passage of a fraction of the filter is exposed to pre-combustion in a furnace heated to ∼340˚C under an oxygen stream for 2 h to remove organic carbon (OC), thus determining the elemental carbon mass (EC), while another fraction of the same filter is passed directly to the analysis, allowing the total carbon mass (TC) to be obtained. Finally, the difference in mass between TC and EC gave the OC mass.

The periods sampled include 2 dry seasons (DS) and 2 wet seasons (WS). For these 2 cities [12], it was shown that the 1st dry season (DS1) is defined from December 2018 to February 2019, and the 2nd (DS2), from December 2019 to February 2020. The first wet season (WS1) runs from March to November 2018, and the second (WS2) runs from March to November 2019. In the following, we will group DS1 and DS2 into DS and WS1 and WS2 into WS.

2.4. Meteorological Data and Environmental Pollution

Gnamien et al. [2] show daily variations in specific humidity and rainfall in Abidjan and Korhogo from 2028 to 2020. They highlight significant differences between the two localities, related to their distinct geographical and climatic contexts, while revealing similar seasonal dynamics due to the tropical climate. This study shows that in Abidjan, rainfall is scarce during the dry season (DS) period, but the specific humidity remains relatively high (15 to 20 g/kg) due to the maritime influence, as the city is located on the Atlantic coast. In Korhogo, the dry season (DS), from December to February, is characterized by low specific moisture levels (2 to 6 g/kg) and almost no rainfall. These conditions reflect the dominant influence of the harmattan winds, which carry dry air from the Sahara and create a particularly arid atmosphere. During the rainy season, from March to November, both localities record a marked increase in specific humidity and rainfall. In Abidjan, rainfall is more regular and sometimes more intense (up to 160 mm/day), particularly in June and November, and specific humidity reaches even higher levels (20 to 25 g/kg). In Korhogo, during the wet season (WS), the specific humidity reaches maximum values of 15 to 20 g/kg, accompanied by rainfall concentrated mainly between June and September, with episodes of intense rainfall. Abidjan has high ambient humidity throughout the year, even during the dry season (DS), and more regular rainfall during the wet season (WS). These differences underline the impact of geographical location (inland for Korhogo, coastal for Abidjan) on seasonal climatic dynamics, which in turn impacts atmospheric chemistry processes.

2.5. Statistical Analysis: Mann-Whitney U Test

An analysis of the seasonal variability of aerosol composition ratios was performed using the Mann-Whitney U [16]-[18] test to compare the distributions between the wet season (WS) and the dry season (DS) at all sites in Abidjan (A1, A2, A3) and Korhogo (K1, K2). This non-parametric test was chosen because it does not assume normality in the data and allows the difference in median between two independent groups to be assessed.

The results are expressed in terms of seasonal medians, DS/WS factor (median ratio), and p-values. The p-values were corrected using Benjamini-Hochberg’s false discovery rate (p_FDR) method to control for the risk of errors associated with multiple testing. A difference is considered statistically significant when p_FDR < 0.05. The conclusions of this statistical analysis will be presented in the results.

3. Results and Discussion

3.1. Analysis of PM_2.5 and PM₁₀ Concentrations and Their Carbon Content (OC and EC) in the Dry Season (DS) between the Wet Season (WS)

Figure 1 presents the median, mid-max, and average WS and DS concentrations of PM_2.5 and the elemental carbon (EC) and organic carbon (OC) content, obtained from sampling carried out in cities between 2018 and 2020, respectively, in Abidjan and Korhogo sites.

PM_2.5 shows particularly marked variability at A1, with values ranging from 7.55 to 127.59 μg/m³, more than six times the median (20.36 μg/m³), while A2 and A3 show narrower ranges of values. For EC, the maximum values were observed at the A2 site (3.20 - 19.30 μg/m³), while OC showed greater variability at A1 (0.24 - 23.85 μg/m³), followed by the A2 and A3 sites. This wide dispersion between minimum and maximum values may reflect isolated episodes of high pollution, characterized by sudden increases in organic and carbonaceous carbon inputs due to local anthropogenic sources.

In Korhogo, PM_2.5 shows wide variability in K1 (from 6.90 to 165.35 μg/m³) and K2 (from 10.18 to 168.60 μg/m³), with maximum values more than four times the median value, including intense and pollution peaks. For EC, variations remain significant but more contained, ranging from 0.52 to 10.04 μg/m³ at K1 and from 0.70 to 10.20 μg/m³ at K2. OC shows the greatest relative amplitude, particularly at K2 (0.10 - 54.40 μg/m³) and K1 (0.13 - 25.59 μg/m³), reflecting highly variable organic inputs, probably linked to biomass combustion and local activities [4].

The analysis of Figure 1 shows that the dry season (DS) is associated with a widespread and marked increase in PM₁₀, EC, and OC concentrations at all sites.

Figure 1. PM_2.5 and PM₁₀ concentrations between 2018 and 2020 at Abidjan (A1, A2, and A3) and Korhogo (K1 and K2) measurement sites.

Figure 2. Median, minimum, and maximum in WS and in DS of PM_2.5 and PM₁₀ concentrations between 2018 and 2020 at Abidjan (A1, A2, and A3) and Korhogo (K1 and K2) measurement sites.

Figure 2 shows median, minimum, and maximum values of PM_2.5 and PM₁₀, and their OC and EC content. The median of PM₁₀ concentration is lowest at A1 (45.90 μg/m³) and highest at A3 (69.28 μg/m³), but variability is greatest at A2, with a range from 34.20 to 485.91 μg/m³. EC follows this trend with greater variability at A2 (5.00 - 29.90 μg/m³), while OC varies greatly at all sites, reaching maximums of 20.49 μg/m³ at A1, 22.00 μg/m³ at A2, and 19.00 μg/m³ at A3. These significant amplitudes reflect marked episodes of pollution, as with PM_2.5. In Korhogo, PM₁₀ shows very high variability at both sites, with maximum concentrations reaching 666.20 μg/m³ at K1 and 517.83 μg/m³ at K2, more than 6 times their respective medians.

EC varies from 1.00 to 15.75 μg/m³ at K1 and from 0.80 to 31.09 μg/m³ at K2, reflecting episodes of pollution, as with PM_2.5. EC varies from 1.00 to 15.75 μg/m³ at K1 and from 0.80 to 31.09 μg/m³ at K2, reflecting marked fluctuations but less extreme than for PM₁₀. OC has the highest relative amplitude, particularly at K2 (0.10 - 244.40 μg/m³) and K1 (0.10 - 125.70 μg/m³), reflecting a highly variable organic contribution, probably linked to the intensity of biomass fires. This high variability in PM₁₀ concentrations, which is unrelated to that of EC, may therefore be due to very high dust levels during the Harmattan and to biomass fires, which are a significant contributor to OC.

3.2. Mann-Whitney U Test Results

Table 2. Main parameters derived from the Mann-Whitney U statistical analysis test.

n_WS and n_DS: number of observations used for the wet season and dry season, respectively. Median_WS and Median_DS: median values of the parameter considered for the WS and DS seasons. Factor_DS/WS: ratio of DS/WS medians, indicating the relative variation between seasons (values > 1 indicate an increase in the dry season). U: Mann-Whitney U test statistic, calculated from the ranks of observations for both seasons. p_value: raw probability associated with the test, indicating significance before correction. p_value_FDR: p-value adjusted according to Benjamini-Hochberg’s False Discovery Rate (FDR) method, allowing for the correction of the effect of multiple comparisons. Significant (FDR < 0.05): indicates whether the seasonal difference is statistically significant after correction (True = significant, False = not significant).

Table 2 presents the results of the Mann-Whitney U test, applied to compare the ratios between the wet season (WS) and the dry season (DS). It shows noticeable seasonal variability across all sites. In general, OC_PM2.5/EC_PM2.5 ratios show an upward trend in DS, which is more pronounced at northern sites (K1 and K2), where the differences are statistically significant after correction (p_FDR < 0.05). The OC_PM10/EC_PM10 ratios vary little according to the season, with the exception of site A2, which shows a significant difference. Finally, the PM_2.5/PM₁₀ ratios show the most marked contrasts, with the test revealing increases during DS in the south (A1 and A2) and decreases in the north (K1 and K2).

These results may suggest that seasonality influences the composition and particle size distribution differently depending on geographical location.

3.3. PM_2.5/PM₁₀ Ratio during the Wet and Dry Seasons

Figure 3 shows box plots of the PM_2.5/PM₁₀ ratio compared between the wet season (WS) and the dry season (DS) for the five measurement sites in this study. The PM_2.5/PM₁₀ ratio is an important indicator of the proportion of fine particulate matter (PM_2.5) to total or coarse particulate matter (PM₁₀). A high ratio indicates a dominance of fine particles, often associated with anthropogenic sources such as combustion, while a low ratio is usually related to coarser particles, such as dust or sand [19]-[21].

At site A1, the PM_2.5/PM₁₀ ratio is slightly higher during the dry season. In Abidjan (A1 and A2), the ratios increase significantly in DS, from 0.53 to 0.62 (p_FDR = 0.00) and from 0.32 to 0.48 (p_FDR = 0.01), respectively, with DS/WS factors of 1.16 and 1.49. This indicates a relative accumulation of fine particles during the dry season, linked to increased urban combustion emissions and road traffic [2] [14] [22], weather conditions that promote the stagnation of pollutants.

Site A3 shows significant variability during the wet season, with several outliers, which could indicate specific events or variable sources affecting fine particulate matter. On this site, there is no significant variation (p_FDR = 0.25), confirming a moderate seasonal influence in this urban area. In addition, this lack of significance reveals the permanent nature of the sources on this site, mainly anthropogenic, such as biomass fires, waste burning, and road traffic.

In the north (K1 and K2), the ratios PM_2.5/PM₁₀ decrease significantly in DS, from 0.53 to 0.29 (p_FDR = 0.05) and from 0.47 to 0.28 (p_FDR = 0.00), respectively. These decreases reveal an increase in the coarse fraction (PM₁₀), characteristic of Sahelian dust, resuspended dust, and agricultural activities [2] [23] [24].

The results show significant variations between seasons and sites, as shown by Léon et al. [25]. At the Abidjan site (A1 and A2), the PM2.5/PM10 ratio is higher during the dry season, suggesting a relative dominance of fine particles. This may be due to low humidity and the absence of precipitation, which promotes atmospheric stability. Indeed, according to Slinn [26], Petroff & Zhang [27], and Seinfeld & Pandis [28], dry deposition of atmospheric particles is favored by dry and windy weather conditions, characterized by low relative humidity, absence of precipitation, and increased turbulence near the ground, which increase the sedimentation rate of particles, particularly those that are large and dense.

In contrast, during DS at the Korhogo sites (K1 and K2), the ratio generally decreases, reflecting an increase in coarse particles due to the particular weather conditions during this period. The Harmattan winds carry Saharan dust, promoting a significant contribution of coarse particles [29]-[31].

Figure 3. PM_2.5/PM₁₀ concentration ratios observed for the dry season (DS) and wet season (WS) at A1, A2, A3, K1, and K2 sites.

3.4. OC/EC in PM_2.5 and PM₁₀

Figure 4 shows the OC/EC ratios in PM_2.5/PM₁₀ at WS and DS at the Abidjan and Korhogo sites. The data are available in Table S3 in the supplementary materials. In the wet season (WS), the OC/EC ratio at site A1 is 1.32 for PM_2.5 and 1.51 for PM₁₀, while in the dry season (DS) it reaches 2.36 for PM_2.5 (×1.79 WS value) and drops to 1.19 for PM₁₀ (×0.79 WS value). At site A2, it is 0.50 (PM_2.5) and 0.54 (PM₁₀) in WS, compared to 0.66 (PM_2.5, ×1.32) and 0.84 (PM₁₀, ×1.56 WS value) in DS. At site A3, the ratio OC/EC values increase from 0.89 (PM_2.5) and 1.18 (PM₁₀) in WS to 2.36 (PM_2.5) and 1.27 (PM₁₀) in DS, i.e., ×2.65 and ×1.08 WS values for respectively PM_2.5 and PM₁₀.

The OC/EC ratio increases significantly in the fine fraction (PM2.5) in A1 and A3, due to an increase in OC that may be linked to biomass combustion, waste burning [32], and contributions from secondary organic aerosols [9] [33]-[36].

In the wet season, the OC/EC ratio at the K1 site is 2.03 for PM_2.5 and 1.82 for PM₁₀, while in the dry season it reaches 3.02 for PM_2.5, according to Djossou et al. [36], and 2.42 for PM₁₀, which is 30 to 50% higher than the WS values. At the K2 site, the values are 2.60 (PM_2.5) and 3.80 (PM₁₀) in WS, compared to 5.20 (PM_2.5) and 7.09 (PM₁₀) in DS, almost 2 times the WS values.

The OC_PM2.5/EC_PM2.5 and OC_PM10/EC_PM10 ratios show an overall upward trend during the dry season (DS) at all sites, reflecting a higher proportion of organic carbon (OC) relative to elemental carbon (EC). However, this trend is more pronounced for the fine fraction (PM_2.5) than for the coarse fraction (PM₁₀).

The differences observed are statistically significant only at sites K1 and K2 for the OC_PM2.5/EC_PM2.5 ratio, with correlation coefficients R² with OC of 0.69 and 0.54 (p-value < 0.05), respectively, and at A2 for the OC_PM10/EC_PM10 ratio with a correlation R² = 0.76 (p-value < 0.05), thus an increase in OC in DS. This increase in the OC/EC ratio observed in Abidjan during the dry season can be attributed to more incomplete fuel combustion linked to heavy road traffic and the age of the vehicle fleet, conditions typical of large African cities, but also to biomass fires [33] [37].

Figure 4. Radar plot of OC/EC ratios in PM₁₀ and PM_2.5 at sites A1, A2, A3, K1, and K2.

4. Conclusions

The results highlight a clear but spatially variable seasonal pattern in particulate matter (PM_2.5 and PM₁₀) and carbonaceous aerosols (OC and EC). Overall, concentrations tend to increase during the dry season (DS), particularly in Korhogo sites, where biomass burning, local combustion activities, and meteorological conditions favor pollutant accumulation. The Mann-Whitney U test confirms that several ratios, especially OC/EC in PM_2.5, exhibit statistically significant differences between DS and WS, with more pronounced contrasts in Korhogo than in Abidjan. These findings suggest that OC sources, mainly from biomass combustion, dominate during the dry season, while urban emissions remain more stable throughout the year in coastal areas.

Such seasonal and regional variations are crucial for improving the parameterization of atmospheric models in West Africa. Accounting for these dynamics enhances the representation of emission sources, aerosol transformation processes, and seasonal effects on particle composition. Conversely, neglecting these variations could lead to biases in air quality simulations, radiative forcing estimations, and health exposure assessments in this climatically sensitive region.

Funding

This study was supported by the Ministry of Education and Research of Côte d’Ivoire as part of the Debt Reduction and Development Contracts (C2D), as well as AMRUGE-CI (Support for the Modernization and Reform of Universities and Grandes Écoles in Côte d’Ivoire) for its grant, managed by the French Research Institute for Sustainable Development (IRD). The research received financial support from the IRD’s Young Associated Team “Air Pollution and Impacts” (JEAI PATI).

Acknowledgements

The authors would like to thank all the members of the Aerosols and Pollution teams in Abidjan (LASMES, UFHB) and Korhogo (UPGC), as well as the scientific and technical staff of the Aerology Laboratory (LAERO, France).

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References