African dust particles over the western Caribbean – Part I: Impact on air quality over the Yucatán Peninsula

On a global scale, African dust is known to be one of the major sources of mineral dust particles, as these particles can be efficiently transported to different parts of the planet. Several studies have suggested that the Yucatán Peninsula could be influenced by such particles, especially in July, associated with the strengthening of the Caribbean low-level jet. Although these particles have the potential to significantly impact the local air quality, as shown elsewhere (especially with respect to particulate matter, PM), the arrival and impact of African dust in Mexican territory has not been quantitatively reported to date.

Two short-term field campaigns were conducted to confirm the arrival of African dust on the Yucatán Peninsula in July 2017 and July 2018 at the Mérida atmospheric observatory (20.98^∘ N, 89.64^∘ W). Aerosol particles were monitored at ground level using different online and off-line sensors. Several PM_2.5 and PM₁₀ peaks were observed during both sampling periods, with a relative increase in the PM levels ranging between 200 % and 500 % with respect to the normal background conditions. Given that these peaks were found to be highly correlated with supermicron particles and chemical elements typically found in mineral dust particles, such as Al, Fe, Si, and K, they are linked with African dust. This conclusion is supported by combining back trajectories with vertical profiles from radiosondes, reanalysis, and satellite images to show that the origin of the air masses arriving at Mérida was the Saharan Air Layer (SAL). The good agreement found between the measured PM₁₀ concentrations and the estimated dust mixing ratio content from MERRA-2 (Version 2 of the Modern-Era Retrospective analysis for Research and Applications) corroborates the conclusion that the degradation of the local (and likely regional) air quality in Mérida is a result of the arrival of African dust.

1 Introduction

The second largest natural contribution of atmospheric particles, worldwide, after sea spray, is mineral dust (Pey et al., 2013). Although volcanoes and soil dust from agricultural activities are significant sources of mineral dust (Walker, 1981; Tegen et al., 2004), the largest sources are the deserts that are distributed around the world (Goudie and Middleton, 2006). Africa is considered one of the most important of these sources as it emits ca. 800 Tg yr⁻¹, corresponding to ca. 70 % of the global dust (Prospero et al., 2014; Ryder et al., 2019). Therefore, African dust particles play a significant role in the climate system, as they can affect the planetary radiative balance and the hydrological cycle. Their optical properties, i.e., scattering and absorption, modulate radiative forcing, and these particles also impact cloud formation and evolution as they can act as cloud condensation nuclei and/or ice-nucleating particles (Zhang et al., 2007; Hoose and Möhler, 2012; DeMott et al., 2015; Kanji et al. 2017). Additionally, several studies have shown that the presence of mineral dust can influence tropical cyclone formation (Dunion and Velden, 2004; Evan et al., 2006) and human health, as these particles degrade air quality (Carlson and Prospero, 1972; Prospero, 1999; Prospero et al., 2014; Venero-Fernández, 2016).

African dust particles are efficiently transported far from their emission source (Perry et al., 1997; Chiapello et al., 1997). According to Middleton and Goudie (2001), there are different trajectories that African dust experiences around the world. Among the most important, African dust particles can be transported to the western Mediterranean and Europe (Karanasiou et al., 2012; Perez et al., 2008; Prodi and Fea, 1979; Salvador et al., 2014), to the eastern Mediterranean and the Middle East (Ganor and Mamane, 1982; Ganor et al., 2010; Athanasopoulou et al., 2016), and towards the southern African continent (d'Almeida, 1986; Resch et al., 2008). Additionally, African dust is transported across the Atlantic Ocean to the United States, Mexico, the Caribbean region, and South America (Prospero et al. 1981; Bravo et al., 1982; Perry et al., 1997; Chiapello et al., 1997; Prospero and Lamb, 2003; Venero-Fernández, 2016; Barkley et al., 2019; Kramer et al., 2020). The long-range transport of African dust over the Atlantic represents 25 % of the total emissions from the Saharan Desert (Shao et al., 2011). This transport is favored in the Northern Hemisphere during the summer (i.e., from June to September) within a dry and hot elevated layer called the Saharan Air Layer (SAL) (Carlson and Prospero, 1972; Prospero and Carlson, 1972; Karyampudi and Carlson, 1988; Tsamalis et al., 2013; Weinzierl et al., 2016).

During the summer, the SAL ascends to altitudes between 5 and 7 km through interactions with cool marine air masses (Adams et al., 2012; Chouza et al., 2016; Korte et al., 2018). Dunion and Velden (2004), Dunion and Marron (2008), and Dunion (2011) studied the characteristics of the air masses that reach the North Atlantic and the Caribbean region during the boreal summer months. They found that there are three distinct air masses: a moist tropical air mass (MT), the SAL, and midlatitude dry air intrusions (MLDAIs). Each type of air mass is associated with unique thermodynamic and kinematic characteristics, and they have a wide range of possible origins. However, the SAL and MLDAI air masses have distinct flow patterns across the North Atlantic, which allows one to differentiate between these masses by tracking their origin. In contrast, their distinctly unique moisture characteristics allow for the differentiation of the MT from SAL air masses (Dunion, 2011).

There are different methods for the detection of the long-range transport of African dust and its presence in different regions around the world. For several decades, the tracking of dust events has been studied using remote sensing (Chiapello et al., 1999; Dunion and Velden, 2004; Foltz and McPhaden, 2008; Prospero et al., 2002; Liu et al., 2008; Voss and Evan, 2020). Ground- and space-based tools such as light detection and ranging (LIDAR) and satellite sensors (e.g., the Moderate Resolution Imaging Spectroradiometer, MODIS, and the Visible Infrared Imaging Radiometer Suite, VIIRS) provide the aerosol spatial distribution with altitude in terms of the aerosol optical depth (AOD), mass concentration, and particle size distribution (Zhang and Reid, 2006; Jackson et al., 2013).

Another useful tool is the reanalysis from global climate models that assimilates, in a statistically optimal way, satellite and ground observations. The reanalysis produces continuous, four-dimensional fields of different atmospheric variables of interest, contrasting with the observations that may be spatially and temporally sparse (Cohn, 1997; Kalnay, 2003; Rienecker et al., 2011; Schutgens et al., 2010). The use of reanalysis, considering its inherent uncertainties, has become an essential tool in the atmospheric research community (Gelaro et al., 2017). For example, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model has been successfully used to track the transport of African dust particles (e.g., Ashrafi et al., 2014; Prospero et al., 2005). HYSPLIT uses meteorological data from different modeling sources, including the NCEP–NCAR (National Centers for Environmental Prediction–National Center for Atmospheric Research) reanalysis model (Stein et al., 2015).

The transport of African dust can also be evaluated with the NASA Global Modeling and Assimilation Office (GMAO) MERRA-2 reanalysis (Prospero et al., 2020). MERRA-2 (Version 2 of the Modern-Era Retrospective analysis for Research and Applications) is the first multidecadal reanalysis that assimilates both meteorological and aerosol data from various ground- and space-based remote sensing sources (Gelaro et al., 2017; Randles et al., 2017). Despite some deficiencies, previous studies have demonstrated that the MERRA-2 aerosol assimilation system does indeed show considerable skill in simulating numerous observable aerosol properties (e.g., Buchard et al., 2015, 2016, 2017; Randles et al., 2017). MERRA-2 has been previously used to study the effects of aerosol particles in the Earth system in several studies focused on dust-related phenomena. For example, Buchard et al. (2017) showed the benefit of the MERRA-2 assimilation for the retrieval of the seasonality, vertical distribution, and magnitude of the dust surface concentrations during an episode of dust transport from Africa to the Caribbean. Later on, Veselovskii et al. (2018) showed the consistency of the MERRA-2 aerosol products with Mie–Raman lidar observations performed in West Africa during a smoke and dust mixing event. Similarly, Grogan and Thorncrof (2019) studied the characteristics of African easterly waves and their relationship with synoptic-scale plumes of Saharan mineral dust. More recently, Bibi et al. (2020) studied atmospheric dust load and deposition fluxes along the North African coast of the Mediterranean Sea, and Aldhaif et al. (2020) studied dust events impacting the East Coast of the United States.

The in situ monitoring of aerosol properties, such as aerosol size and mass distribution, is very useful to determine their influence on local air quality and human health (Querol et al., 2019). Hence, different studies have been carried out in the Caribbean islands and Florida to quantify the impact of African dust on the local air quality (Prospero, 1999; Prospero and Mayol-Bracero, 2013; Prospero et al., 2014). In Barbados, the monitoring of the atmospheric aerosol mass began in 1965, whereas in Miami, Florida, it began in 1974 and continues to the present (Prospero and Mayol-Bracero, 2013). In Barbados, it is estimated that 50 % of the PM_2.5 (i.e., particulate matter with an aerodynamic diameter D < 2.5 µm) and ca. 90 % of the PM₁₀ (i.e., D < 10 µm) consist of African dust (Li-Jones and Prospero, 1998; Prospero et al., 2001; Reid et al., 2003a). In Miami, the mean daily mass concentration of mineral dust during the summer typically ranges between 10 and 100 µg m⁻³, with a large interannual variability (Prospero et al., 2001). During the Puerto Rico Dust Experiment (PRIDE) campaign, the mineral dust concentration at the ground level was found to exceed 70 µg m⁻³ (Reid et al., 2003b). In the aforementioned studies, the African dust particles transported over the Atlantic affected the local air quality, exceeding the World Health Organization (WHO) guidelines for PM_2.5 and PM₁₀. According to WHO, air pollution and its effects are considered a global health priority (WHO, 2002). Several studies have linked high concentrations of mineral dust (in terms of PM_2.5 and PM₁₀) to brain, skin, lung, cardiovascular, cerebrovascular, and respiratory diseases (Alessandrini et al., 2013; Goudie, 2014; Wilker et al., 2015; Brook et al., 2010; Dominici et al., 2006; Zhang et al., 2016). Additionally, African dust particles have been found to serve as carriers for biological material. Griffin et al. (2001) reported the presence of viable bacteria and fungi associated with the arrival of African dust over the Virgin Islands (United States). Similarly, Rodriguez-Gomez et al. (2020) found a higher concentration of viable bacteria and fungal propagules during summer than during winter on the Yucatán Peninsula, with summer being the season when African dust intrusions are more frequent.

The chemical and mineralogical composition of particles also plays an important role in the identification of African dust in the receptor regions (Nenes et al., 2014). The most abundant minerals present in these particles are silicates (quartz), clay minerals (kaolinite, illite, chlorite, palygorskite), feldspars (albite, anorthite), and carbonates (calcite) (Goudie and Middleton, 2006; Querol et al., 2019; Broadley et al., 2012). The major oxides in Saharan dust are SiO₂, Al₂O₃, Fe₂O₃, CaO, MgO, and K₂O, as well as (to a lesser extent) P₂O₅ and TiO₂ (Goudie and Middleton, 2006; Linke et al., 2006). Several studies in the Caribbean have identified high levels of Fe and Al in dust events (Prospero et al., 2001; Rosinski et al., 1988). Additionally, Rosinski et al. (1988) reported high percentages of Si and Mg in particles collected in the Gulf of Mexico (GoM) during July.

Although the arrival of African dust in Mexico has been suggested for decades (e.g., Bravo et al., 1982; Prospero, 1999; Lenes et al., 2012), to our knowledge, there has not been a comprehensive study, published in the open, peer-reviewed literature, that documents this atmospheric phenomenon. For the first time, in this study we document the arrival of African dust on the Yucatán Peninsula for two consecutive years (i.e., 2017 and 2018) using in situ and remote sensing measurements, reanalysis, back trajectory analysis, and complementary meteorological observations.

2 Materials and methods

2.1 Sampling site and field campaigns

The Yucatán Peninsula is located in the southeast of Mexico. It borders the GoM to the north; the Atlantic Ocean to the east; and the Caribbean Sea, Guatemala, and Belize to the south. The Yucatán has characteristics that are unique to this region (Plasencia, 1998). For example, its uniform terrain, the absence of rivers, and the type of soil, which is formed by Cretaceous sediments that do not present mineralization and are rich in calcium, commonly called “Laja de Yucatán” (Plasencia, 1998) sets the Yucatán aside from other regions of Mexico. The average temperature of the Yucatán Peninsula ranges from 25 to 35 ^∘C (World Resource Institute, 2018) with an average annual relative humidity of 79 % (INEGI, 2009). The Peninsula has a warm, semidry climate on the coast and a warm, subhumid climate throughout the rest of the region, with a rainy season between summer and autumn (June–October) (Orellana et al., 2009; ProAire, 2018). Precipitation in this region is mainly due to convective activity, and it is influenced by the moisture advection by the trade winds (Orellana et al., 2009; ProAire, 2018). In situ measurements were made in the city of Mérida, situated in the northeast sector of the Yucatán Peninsula (20.98^∘ N, 89.64^∘ W), which is the capital of the Yucatán state. Mérida has 892 363 inhabitants (INEGI, 2015) and is 23 km from the coast. The most representative activities in the region are tourism, commerce, and the textile industry (INEGI, 2017).

Figure 1 Location of the sampling site at the School of Chemistry of the Autonomous University of Yucatán (FC-UADY) and the three World Meteorological Organization (WMO) radiosonde stations located on the Yucatán Peninsula: Mérida International Airport, Mexico (WMO index: 76 644); Cancún, Mexico (WMO index: 76 595); and Philip S. W. Goldson International Airport, Belize (WMO index: 78 583).

Table 1 Summary of the measured variables and the instrumentation used.

Aerosol particles were continuously monitored with sensors installed at the School of Chemistry of the Universidad Autónoma de Yucatán (FC-UADY), located in the central-western part of the city (Fig. 1), as part of the African Dust And Biomass Burning Over Yucatan (ADABBOY) project. Table 1 lists the instrumentation used to characterize particle physical, optical, and chemical properties. The Partisol and MiniVol were installed on the rooftop of the FC-UADY, whereas the other instruments were maintained in an environmentally controlled area where they sampled from inlets connected to a ventilated chimney that extended approximately 1.5 m above the roof. This measurement site is part of the University Network of Atmospheric Observatories (RUOA) supported by the National University of Mexico (UNAM). Two intensive sampling periods were conducted between 11–31 July 2017 and 30 June–17 July 2018.

2.2 Aerosol concentration and particle size distribution

The particulate mass concentration was monitored continuously with PM_2.5 and PM₁₀ analyzers providing real-time measurements (FH 62 C14, Thermo Fisher Scientific Inc.) with a temporal resolution of 1 min at a sampling flow rate of 16.7 L min⁻¹ (Thermo Fisher Scientific Inc., 2007).

The total number concentration of particles with sizes approximately larger than 50 nm was measured by a condensation particle counter (CPC 3010, TSI) at a sampling rate of 1 Hz with a flow rate of 1.0 L min⁻¹, and the aerosol number concentration as a function of particle size was monitored by an optical particle counter (Lasair II 310A, MSP). The Lasair has six different size bins (0.3, 0.5, 1.0, 5.0, 10.0, and 25 µm), a flow rate of 28.3 L min⁻¹, and a time resolution of 11 s.

2.3 Aerosol collection and chemical composition analysis

PM_2.5 and PM₁₀ aerosol particles were collected for 24 h with a Partisol model 2525 (Thermo Fisher Scientific Inc.) and for 48 h with a Minivol (3380, Airmetrics) on 47 mm Teflon filters (Pall Science). The MiniVol and Partisol flow rates were 5.0 and 16.7 L min⁻¹, respectively. After the sampling periods, the filters were placed in 60 mm Petri dishes and stored at 4 ^∘C prior to the chemical analysis.

Elemental analysis was performed on each filter using X-ray fluorescence (XRF) with the X-ray spectrometer at Laboratorio de Aerosoles, Instituto de Física, UNAM (Espinosa et al., 2012). The X-ray tube was made by Oxford Instruments (Scotts Valley, CA, USA), and a Rh anode and an Amptek X-123 SDD spectrometer (Bedford, MA, USA) were used. The samples were irradiated for 900 s working with a current of 500 µA and resulting in a spectrum that was analyzed using the WinQXAS computer code (IAEA, 1997). The product of this analysis derived mass concentrations of Fe, Al, Si, Ca, Na, P, Mg, Mn, Ti, Cl, P, Zn, K, S, Cu, and Ni along with their associated uncertainties, as described by Espinosa et al. (2010).

2.4 Meteorological and satellite data

The local and regional meteorological conditions were monitored using different approaches. The RUOA meteorological sensors were placed at the rooftop of the FC-UADY (Table 1) and continuously measured the wind speed and direction, air temperature, relative humidity, solar radiation, and precipitation. To derive the regional and vertical distribution of meteorological conditions, radiosondes and reanalysis were used. The information provided by the radiosondes launched was from three World Meteorological Organization (WMO) stations on the Yucatán Peninsula, as shown in Fig. 1, located at Mérida (Mérida International Airport, Mexico (WMO index: 76 644), Cancún (WMO index: 76 595), and Belize (Philip S.W. Goldson International Airport, Belize; WMO index: 78 583). The processed radiosonde data were obtained from the University of Wyoming (http://weather.uwyo.edu/upperair/sounding.html, last access: 20 March 2020).

Hourly total precipitable water vapor and three-dimensional 3-hourly aerosol mixing ratio data were obtained from the MERRA-2 reanalysis (GMAO, 2015a, b). The aerosol properties in MERRA-2 were simulated with the Goddard Chemistry Aerosol Radiation and Transport model (GOCART), which takes the sources, sinks, and chemistry of 15 externally mixed aerosol mass mixing ratio tracers into account: dust (five noninteracting size bins), sea salt (five noninteracting size bins), hydrophobic and hydrophilic black and organic carbon (BC and OC, respectively; four tracers), and sulfate (SO₄) (Randles et al., 2017; Buchard et al., 2017).

The air mass back trajectories were calculated using the HYSPLIT model from the National Oceanic and Atmospheric Administration (NOAA). In conjunction with the in situ measurements, the back trajectories were calculated considering the maximum concentration of PM reported by the PM_2.5 and PM₁₀ analyzers. The trajectories were initiated at 250 and 500 m a.g.l. going backward in time for 13 d. Although Kramer et al. (2020) reported that mineral dust particles arrive in Miami ca. 10 d after they are produced in North Africa, they may take longer to reach the Yucatán Peninsula. The different heights of the HYSPLIT back-trajectory runs were chosen to determine the rate of descent of dust air masses to the surface. Also considered was the AOD measured with the MODIS instruments on the Aqua and Terra satellites.

Figure 2 Mass concentrations of PM_2.5 and PM₁₀ in (a) 2017 and (b) in 2018. The green horizontal line depicts the World Health Organization air quality guideline for 24 h mean PM_2.5 (right y axis) and PM₁₀ (left y axis) concentrations of 25 and 50 µg m⁻³, respectively (WHO, 2002). The pie charts represent the elemental composition from the XRF for the African dust peaks (ADPs).

3 Results and discussion

3.1 Local evidence

Several studies have shown that air quality (PM_2.5 and PM₁₀) significantly deteriorates upon the arrival of African dust plumes (Prospero and Lamb, 2003; Prospero et al., 2001, 2014; Prospero and Mayol-Bracero, 2013). Figure 2 shows the time series of the PM_2.5 and PM₁₀ concentrations for the July–August periods of 2017 and 2018. Some high-concentration PM peaks are clearly identified, with PM_2.5 and PM₁₀ values as high as 54 and 135 µg m⁻³, respectively. Henceforth these peaks will be referred to in our study as African dust peaks (ADPs). Note that the background concentration (defined as the lowest values within the sampling period where the chemical composition was available) of PM_2.5 is ∼ 4 µg m⁻³, and the background concentration of PM₁₀ is ∼ 10 µg m⁻³. The ADPs found in 2017 (i.e., 22–24 July, 27–28 July, and 4, 6–7 August) resulted in an increase of 300 % in PM_2.5 and 500 % in PM₁₀ with respect to background conditions. In 2018, the ADPs (i.e., 10–11 July, 13–15 July, 16–17 July, 23–26 July, and 9–10 August) exceeded 200 % and 300 % of the background levels of PM_2.5 and PM₁₀, respectively. The aforementioned ADPs not only exceeded the PM_2.5 and PM₁₀ thresholds suggested by WHO (i.e., PM_2.5 = 25 µg m⁻³ and PM₁₀ = 50 µg m⁻³, 24 h mean) but more than double them, as was the case for the 9–12 August 2018 event. Similar behavior has been previously observed in Puerto Rico, Miami, and Barbados upon the arrival of African dust particles (Reid et al., 2003b; Prospero et al., 2005, 2014). The mass concentrations of PM_2.5 and PM₁₀ were found to be 49 % and 54 % higher in 2018 than in 2017, respectively, suggesting a higher frequency or intensity of African dust plumes arriving over Mérida in 2018.

Figure 3 MERRA-2 precipitable water (black solid line) and precipitable water values estimated from radiosonde measurements (blue dashed line), for the three WMO radiosonde stations located on the Yucatán Peninsula for (a) July–August 2017 and (b) July–August 2018. The red areas represent the periods where precipitable water vapor (PWV) is less than 45 mm.

Figure 2 also shows the elemental composition obtained from the XRF analysis (16 elements) for five ADPs observed during the 2017 and 2018 field campaigns. In addition, 1 d from each field campaign was selected to determine the elemental background composition. The selected days are 10–11 July in 2017 and 6 July in 2018. These days were chosen because the PM_2.5 and PM₁₀ concentrations were within the mean background values and did not include any atypical peak nor apparent external influence.

High levels of sodium (Na, pink), chlorine (Cl, turquoise blue), sulfur (S, dark orange), and calcium (Ca, light green) were found in the background samples, corresponding to > 70 % of the total mass (Fig. 2). The presence of Na and Cl are expected in airborne particles at this site given the city's proximity to the GoM (i.e., 23 km away). Cerón et al. (2002) reported large concentrations of Na, Cl, and Mg that originated from sea salt, when analyzing the composition of rainwater from the Yucatán Peninsula. The high levels of S can be associated with local anthropogenic activities such as vehicular, ship, and industrial emissions (e.g., Corbett and Fischbeck, 1997; Cerón-Bretón et al., 2018). Additionally, given the short distance between Mérida and the GoM, it is possible that dimethylsulfide (DMS) production from plankton in the GoM could be a natural source of S, as has been shown in other studies (e.g., Rosinski et al., 1988; Kloster et al., 2006; Vallina and Simó, 2007). Finally, the presence of Ca could be related to the limestone soil prevalent on the Yucatán Peninsula and the resuspension of road dust (Plasencia, 1998; Querol et al., 2019).

Interestingly, the elemental composition of the airborne particles collected during the ADPs showed higher concentrations of silica (Si, dark yellow), aluminum (Al, light purple), and iron (Fe, dark purple) than those in the background particles (Fig. 2). While the Si concentrations are approximately 3 times larger than the baseline, Al and Fe increased by 8 and 12 times, respectively. To corroborate the relationship between the increase in PM and the African dust, each of the 16 elements analyzed by XRF were correlated with the PM_2.5 and PM₁₀ concentrations. Of the 16 elements Al, Si, K, and Fe were the only ones with correlation coefficients r>0.6 (p<0.05) for both years, as shown in Fig. S1. The present results are in agreement with previous studies that showed high correlation coefficients between the aforementioned elements (e.g., Caquineau et al., 1998; Guieu et al., 2002; Trapp et al., 2010). Also, the concentration of aerosol particles with diameters between 0.5 and 25 µm, as measured by the Lasair, were found to be highly correlated with the PM_2.5 and PM₁₀ concentrations, r=0.79 and r=0.87, respectively (Fig. S2). Finally, the typical background particle size distribution showed significant changes during the arrival of ADPs for particles ranging between 0.5 and 5.0 µm (Fig. S3). It is widely known that the typical size of African dust particles transported over long distances ranges from 0.1 to 20 µm (e.g., Bégue et al., 2012; Denjean et al. 2016). Overall, the high concentration of coarse particles and the increase in Al, Si, and Fe during the ADPs, together with the good correlations found between the PM_2.5 and PM₁₀ concentrations with Al, Si, K, Fe, and particles larger than 0.5 µm strongly suggests that the ADPs are mineral particles associated with dust transported from Africa to Mexico.

Additionally, it is important to note that Al, Si, K, and Fe are common oxides found in African dust composed of minerals and clays such as quartz (SiO₂), kaolinite (Al₂Si₂O₅(OH)₄), illite (K,H₃O)(Al,Mg,Fe)₂(Si,Al)₄O₁₀[(OH)₂,(H₂O)], chlorite (((MgFe)₅Al)(AlSi₃)O₁₀(OH)₈), palygorskite (Mg,Al)₂Si₄O₁₀(OH) ⋅ 4(H₂O), and feldspars such as albite (NaAlSi₃O₈), anorthite (CaAl₂Si₂O₈), and orthoclase (KAlSi₃O₈), among others (Goudie and Middleton, 2006; Linke et al., 2006; Broadley et al., 2012; Querol et al., 2019). Rosinski et al. (1988) reported that up to 90 % of the collected airborne particles in the presence of dust events in the GoM contained Al, Fe, and Si. In Puerto Rico, Reid et al. (2003b) found that the concentrations of Si and Al on aerosol particles (>0.74 µm) were above 10 and 5 µg m⁻³, respectively, during dust events that reached the island. Similarly, Prospero et al. (2001) reported concentrations of Al > 1.0 µg m⁻³ and Fe > 0.5 µg m⁻³ on PM_2.5 on days when high concentrations of African dust particles were reported in Miami.

Figure 4 The 3 h time series of the vertical profile of the estimated dust content from MERRA-2 for the 1 July–14 August period for (a) 2017 and (b) 2018 for the Mérida region.

To confirm that no aerosol sources other than the African dust were the origin of the high PM peaks observed in Mérida in July 2017 and 2018, the PM_2.5 and PM₁₀ concentrations were correlated with other measured variables. As shown in Figs. S2 and S4, PM_2.5 and PM₁₀ concentrations are poorly correlated (r<0.09) with local pollution emissions such as particle-bound polycyclic aromatic hydrocarbons (pPAHs), black carbon (inferred from the absorption coefficient), and nitrogen oxides (NO_x). Note that those gases and particles can be considered as proxies of anthropogenic pollutants generated by the incomplete combustion of fossil fuels and biomass burning, as previously demonstrated for Mérida (Muñoz-Salazar et al., 2020; Alvarez-Ospina et al., 2020). Also, correlation coefficients below 0.29 were found between O₃ and solar radiation with the PM_2.5 and PM₁₀ concentrations indicating that it is very unlikely that secondary organic particles could be the source of the ADPs observed in Mérida, as was the case in high particle concentration events shown by Muñoz-Salazar et al. (2020).

Figure 5 Daily mean of PM₁₀ estimated from MERRA-2 (black line), PM₁₀ measured by the RUOA station (blue line), and the estimated dust mixing ratio content from MERRA-2 (red line) for (a) 2017 and (b) 2018.

Finally, although none of the different meteorological variables monitored at the surface level were found to correlate with the PM_2.5 and PM₁₀ concentrations, as shown by the wind roses in Fig. S5, easterly winds were prevalent when ADPs were observed. This is relevant as African dust can only be transported by easterly winds.

3.2 Larger-scale observations

To evaluate the source of the ADPs observed in Mérida from a large-scale perspective, we focus on the classification of tropical air masses in the North Atlantic and the Caribbean region during the boreal summer months proposed by Dunion (2011). We used HYSPLIT to estimate the trajectories of different air masses that reached Mérida during the July–August periods of 2017 and 2018. HYSPLIT trajectories for the 2017 and 2018 ADPs point to an African origin and, therefore, suggest that these air masses are either MT or SAL (See Fig. S6). To differentiate the MT from SAL, we focused on their distinctly unique moisture characteristics. Dunion (2011) proposes that a threshold of 45 mm of total precipitable water vapor (PWV), which corresponds to the total amount of water vapor contained in the atmospheric column from the surface to the top of the troposphere (AMS, 2000), can be used to differentiate dry from moist air masses. This value is consistent with other studies that use PWV to identify dry-air days (e.g., Hankes and Marinaro, 2016), and as deep tropical convection begins to increase above a critical PWV value of 50 mm (Holloway and Neelin, 2009). Note that PWV is given by the vertical integral of the mixing ratio x(p) at the pressure level p in the layer bounded by pressures p1 and p2 and can be calculated using Eq. (1) (AMS, 2000):

$$\begin{array}{}\text{(1)}& \text{PWV}={\displaystyle \frac{\mathrm{1}}{\mathit{\rho }g}}\underset{p\mathrm{1}}{\overset{p\mathrm{2}}{\int }}xdp,\end{array}$$

where ρ represents the density of water, and g is the acceleration of gravity.

Figure 6 Dispersion diagrams of the surface dust mixing ratio from MERRA-2 (y axis) vs. the PM₁₀ from the RUOA station for the periods shown in Fig. 5 for (a) 2017 and (b) 2018.

Figure 3 shows the time series of PWV for the July–August 2017 and 2018 periods at each WMO radiosonde site. The black solid line shows PWV from MERRA-2, available from the Vertically Integrated Diagnostics (GMAO, 2015a), together with PWV estimated using Eq. (1) from the available radiosonde profiles shown as the dashed blue lines. One caveat is that there is a striking lack of radiosonde data in the periods of interest. Nevertheless, we can see good agreement between the available observed PWV and that of PWV from MERRA-2. Therefore, the latter can be used as a good approximation for PWV in the region to differentiate moist from dry air masses. In Fig. 3, the periods where PWV is less than 45 mm are highlighted in red. These periods show dry air masses that coincide with air mass trajectories with an African origin (i.e., 22–24 July, 27–28 July, and 4 and 6–7 August in 2017, and 10–12 July, 13–15 July, 16–17 July, 23–26 July, and 9–12 August in 2018), allowing us to conclude that these dry air masses have mainly SAL characteristics.

The arrival of African dust in Mérida was also explored from the MERRA-2 dataset. Figure 4 shows the time series of the estimated vertical profiles of the 3 h time series of the dust mixing ratio from MERRA-2 at Mérida for 2017 and 2018. It shows that the events corresponding to the arrival of dry air masses from Africa displayed in Fig. 3 nicely correlate with high dust mixing ratios, strongly supporting the hypothesis of SAL air reaching the Yucatán Peninsula. Figure 4 also shows that the July–August period of 2018 was particularly active with frequent arrivals of dust in the region, which is in agreement with the higher PM_2.5 and PM₁₀ concentrations measured in 2018, as depicted in Fig. 2. Figure S7 focuses on the vertical profiles of the dust mixing ratio for the periods of 21–25 July 2017 and 12–16 July 2018. These periods show the increase in dust in the atmospheric column in the studied region, supporting the hypothesis that the source of the ADPs shown in Fig. 2 is likely African dust.

Finally, the arrival of African dust plumes over the Yucatán Peninsula was confirmed by investigating the AOD detected by the MODIS Aqua and Terra satellites for July 2017 and 2018, as shown in Figs. S8 and S9. Although this information cannot be used to perform quantitative analysis, the AOD images allow us to confirm the arrival of African dust plumes on the Yucatán Peninsula. Additionally, as in Figs. 2, 3, and 4, the AOD images also show that the African dust plumes activity was higher in 2018 than in 2017. Previous studies have also used the AOD from MODIS to identify the arrival of African dust. For example, Koren et al. (2006) tracked the long-range transport of dust from the Bodélé Depression (north central Africa) to the Amazon Basin. Similarly, Kalashnikova and Kahn (2008) demonstrated that it is possible to observe the evolution of African dust plumes over the Atlantic Ocean with MODIS. Additionally, Kaufman et al. (2005) identified and quantified the transport and deposition of mineral dust over the Atlantic Ocean using MODIS data.

3.3 Comparison of in situ observations and reanalysis

The daily mean PM₁₀ from MERRA-2 was estimated using the method proposed by Provençal et al. (2017). The black line in Fig. 5 shows the estimated PM₁₀, which is compared to the PM₁₀ measured by the RUOA station in Mérida (blue line). The estimated surface dust mixing ratio from MERRA-2 is also shown in red. Figure 5 shows that MERRA-2 overestimates PM₁₀ compared with ground-based measurements. Nevertheless, it should be clarified that the reanalysis information corresponds to a $\mathrm{0.5}{}^{\circ }\times \mathrm{0.625}{}^{\circ }$ region, implying that MERRA-2 is estimating the regional average, whereas the station corresponds to a local measurement.

Despite these differences, Fig. 5 shows that the observations at the RUOA station have variations similar to those of MERRA-2. Figure 6 shows the dispersion diagram of the daily mean surface dust mixing ratio from MERRA-2 vs. PM₁₀ measured from RUOA station for the periods indicated in Fig. 5. It shows a good correlation between the estimated dust and the measured PM₁₀ – in particular for the 2018 period, which was especially active with constant arrivals of African dust to the region, as shown in Fig. 4. A similar analysis was performed for the 3 h estimated and measured PM₁₀, as shown in Figs. S10 and S11, with identical conclusions to those for 24 h averages.

4 Conclusions

For the first time, the arrival of African dust into Mexican territory is quantitatively verified. The arrival of African dust particles in Mérida significantly degraded the local air quality as PM_2.5 and PM₁₀ concentrations increased up to 500 % with respect to background conditions. Therefore, the presence of African dust in Mérida and the Yucatán Peninsula could be a potential health threat to their inhabitants. Although the African dust intrusions caused an increase in particulate matter in Mérida (Mexico), this increase is lower than those reported in other places closer to the Sahara, such as Barbados and the Mediterranean. In addition to the impacts on air quality, African dust particles can also be a serious health threat as they serve as a carrier of biological material originating in Africa, as reported by Rodriguez-Gomez et al. (2020). If the foreign biological particles are opportunistic pathogens, they can cause a variety of diseases in the receptor regions, such as the Yucatán Peninsula. Finally, these particles can impact the development of precipitation and affect the regional hydrological cycle when they serve as efficient ice-nucleating particles (e.g., Rosinski et al., 1988; Córdoba et al., 2020).

As shown in the present study, combining ground-based off-line and online sensors provides robust evidence of the arrival of African dust; however, we also show that the combination of back trajectories with radiosondes as well as the estimated surface dust mixing ratio from MERRA-2 are powerful tools that can be exploited when in situ information is missing, especially in developing countries where the necessary instrumentation is scarce.

Continuous monitoring of the arrival of African dust is of high importance not only in the Caribbean islands but also at other sites in Latin America such as Mexico, Belize, Guatemala, and Honduras. Additionally, epidemiological and statistical studies to track down the number of hospital admissions caused by respiratory issues before and after the arrival of African dust is urgently needed on the Yucatán Peninsula. This will allow policy-makers and local authorities to understand how strong the African dust impact is on local health and the need for better forecasting of such events.