Heavy aerosol pollution episode in Mexico City
The central part of Mexico during the dry-warm season is dominated by an anticyclonic system, which leads to sunny, warm weather and low precipitation in the MCMA 24,25. These hot and dry conditions favor the presence of dust and BB emissions from wildfires 12. Nearly 7,410 fires and almost 589,371 hectares burned were reported in Mexico during 2019 (CONAFOR, 2020) 26. Figure 1 shows the location of active fires in Mexico detected by the Visible Infrared Imaging Radiometer Suite (VIIRS) on May 11, 12, 14, and 15. Fires occur throughout Mexico but are concentrated in the western, central, and southwestern regions. Satellite imagery shows the dense smoke plumes emitted by the wildfires, which reached the central Mexico plateau. There were also a significant number of fires that occurred inside and around the Mexico City basin.
Figure 2 shows the 24-hour average PM2.5 concentration measured during May 2019 in four RAMA stations: CCA, GAM, MER, and TLA in MC. All stations located in different parts of the MC (see Fig. 11c), registered a drastic increase in 24-hour average PM2.5 from May 10 to 17. The 24-hour PM2.5 mean concentration at the CCA station during HAP days was 65.1 µgm-3, which significantly exceeded the Mexican national air quality standards of 45.0 µgm-3. That PM2.5 increment during the HAP episode began on May 10 reaching the maximum concentrations on May 12 and 13 with peak PM2.5 values of 81.9 and 86.8 µgm-3, respectively. The decrease in the concentration of these particles was observed from May 17, with average values < 40 µgm-3.
Aerosol optical depth and visibility
Figure 3 (a) shows the average AOD over daytime measurements at 6 different wavelengths (340, 380, 440, 500, 675, and 870 nm) during May 2019, with the highest AOD values observed from May 14 to 18. Due to technical failures, the sensor did not report data the second week of May, including the beginning of the HAP episode. Nevertheless, for the remaining days of the HAP episode (from 14 to 18) high AOD values were observed, with maxima of 0.90, 0.91, and 0.78 measured on May 15, 16, and 17, respectively. These maximum values are ~ 3 times higher than the annual mean AOD (0.32) registered during May 2019. These AOD peaks are caused by the high aerosol loading, evidenced by the PM2.5 measurements (Fig. 2). Although all aerosols contribute to the AOD increase, the SDA calculations suggest that the AOD variability in MC is dominated by FM particles. Fig. 3 (b) shows the trend of the FM and CM contribution to the AOD (500 nm) measured during May 2019. The FM AOD during the entire month ranges between ~ 0.20 and ~ 0.95, while CM AOD varies between 0.01 and 0.03. Carabali et al. (2017)10 reported similar SDA results in MC, demonstrating that fine particles highly contribute to AOD. Similarly, another study of aerosols in the MC during spring 2019 found that fine particles originate mainly from BB and local traffic emissions, while the primary source of coarse particles is dust from re-suspended soil dust 27.
A remarkable reduction in Va was also noted in MC during the HAP event. Figure 4 shows the scatter plot of AOD at 500 nm and both Va calculations (i.e., βext and AOD500), where a good correlation for Zi = 3.0 km was obtained. The impact of the atmospheric pollution on Va can be estimated for the 7 days of the HAP period, as seen in Table 1 for 24-hr averages, Va suffered a degradation greater than 80% during the HAP days, highlighting the high absorption of particles that affected MC in May 2019.
Table 1. Average values of PM2.5 concentration (CCA measurements), AOD, and Va during HAP days (from 10 to 17 May 2019), low-pollution days (01 – 09 and 18 – 31 of May 2019), and annual means.
|
PM2.5
(µgm-3)
|
AOD
|
VA from βext (km)
|
VA from AOD (km)
Zi = 1.0, 1.5, and 3.0
|
Highly polluted days
|
65.1 ± 13.6
|
0.80 ± 0.13
|
10.3±3.8
|
4.9±0.1, 7.3±1.2, and 14.7±2.4
|
Low pollution days
|
29.4 ± 7.2
|
0.43 ± 0.16
|
60.5±15.1
|
9.1±3.4, 13.4±5.1, and 27.3±10.1
|
Annual mean
|
20.9 ± 13.6
|
0.30 ± 0.12
|
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|
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|
Individual TEM analysis of the aerosol particles sampled in MC during the HAP episode confirms its strong absorbent feature (Fig. 5). TEM micrographs show particles with different sizes and morphologies. For example, Figure 5a shows spherical particles with diameters (dp ) <1 µm. These particles have an elemental composition dominated by a strong C signal and minor O (Fig. 5c), a characteristic composition of tarballs (TB), a type of particles that originate from the incomplete combustion of fossil fuels or biomass 16,28. Although it is difficult to know the origin of these TB particles, due to the various sources within MC, BB emissions may be the largest TB contributor. Fig. 5b shows the TEM image of a soot aggregate with a morphology very different from that exhibited by TB particles. The soot particles are composed of nanometric carbon spherules that join together to form chains and clusters with dp > 1 µm; its EDS spectra consist mainly of C, O, and high-intensity signals of K and S (Fig. 5d).
Aerosol effect on global solar irradiance
The influence of aerosols on daily solar irradiation is analyzed in Figure 6. The observed increase in PM2.5 concentrations from 10 to 17 May had an obvious effect on GHI (Fig. 6a, shaded period). The data indicate that GHI gradually decreases as PM2.5 levels increased, mainly due to the scattering and absorption of sunlight29. The significant reduction in irradiance occurs mainly between 11:00 h and 18:00 h LST (Fig. S1a), when maximum irradiance values are detected, coincides with the highest presence of smoke. To quantitatively estimate the PM2.5 impact on the solar irradiance, the maximum daily GHI measurements were subtracted from the monthly mean GHIm value. This difference (∆GHI = GHI – GHIm) taken as an anomaly in percent (or departures from the mean monthly value) has a direct impact on visibility. Figure 6b shows the ∆GHI and the PM2.5 trends, where it can be observed that the maximum GHI has a significant reduction due to the increase of the PM2.5 levels. This high load of aerosol particles during the HAP days resulted in a significant loss of 17 % in the GHI. The monthly mean value of the GHI measured experimentally (1130 ± 66 Wh/m²) fits well with the value calculated theoretically with the ESRA clear sky model 30 (i.e., 1108 Wh/m²) that represents the typical GHI value for this month in MC, according to the Linke turbidity value (equal to 4) reported for SODA web services (http://www.soda-pro.com/). Figure S1b shows the correlation between these quantities, with a correlation coefficient of 0.54. The negative tilt matches solar irradiation reduction, corresponding with the PM2.5 values increasing. The average values of the GHI and its anomaly during the HAP period and during the low polluted days of May 2019 are shown in Table S1.
Aerosol characterization at AAO
Vertical transport of pollutants within the mixing layer
Ceilometer measurements were used to estimate the height of the ML, required to infer the vertical distribution of aerosols. The derivation of the ML height during spring is reliable due to suitable meteorological conditions (low humidity, clear skies, and the absence of precipitation) and high aerosol loading in the atmosphere. Figure S2 shows the resulting profile of the ML height estimates for the MC on May 14, 2019. The sharp decrease in aerosol backscattering between the ML and FT (contrasting colors in Fig. S2a) indicates the boundary between the ML and the free troposphere. The ML time series starts in the early morning hours, with an average height of 900 m a.g.l, until midday when it increases rapidly, reaching heights > 3500 m a.g.l. due to turbulence and dry convective processes. The ML collapses after sunset, as seen in the height decrease around 18:00 LST. ML expansion was also evident with the increase in particle concentration at the AAO. Figure S2b shows the total particle concentration (sizes > 30 nm) measured with a condensation particle counter (CPC) at the AAO. A rapid increase in particle concentration was observed at 11:00 LST, and subsequently, the maximum value was reached at 11:30 LST. Similar results were published by Baumgardner et al. (2009) 22, who found that particulate matter concentration and other pollutants reach their maximum concentration at mid-afternoon.
Aerosol particle types at AAO
Analysis was carried out on 120 particles and based on the morphology and elemental composition as the main criteria, allowing the particle classification into five groups (Table 2): soot, organic, mineral dust, S-rich, and complex secondary particles. Statistical analysis of the spectra showed that 90% of the particles contain C and O, 50% of the particles contain Si, and 30% present S. Fe and Al were also detected although in a low number of particles with weak signals. Both elements (Fe and Al) were observed encapsulated by carbonaceous material, silicate coatings, or mixed with other minerals such as Ca and Na. Copper was not considered for this classification because this element is present in the TEM grids. Particle shape was considered the main factor for discriminating between soot (chain aggregates) and TB (spherical particles) particles, which were present in almost all analyzed TEM-grids.
Soot
Figure 7 shows TEM images of individual soot particles sampled at the AAO site within the FT (i.e., 12:00 – 05:00 h) during the HAP days. All images show chain-like agglomerated structures of nano-sized primary spherical particles with dp < 60 nm, a typical structure present in soot originated in combustion processes 18. Those soot particles sampled at the AAO could probably have been produced by BB events or were transported by the ML convective process. The soot particle in Fig. 7a has a dp of ~ 1.6 µm, while the particle in Fig. 7b with a dp ~ 0.7 µm is attached to the bigger one and more compact aerosol. EDS spectra in Fig. 7b consist mainly of three peaks; the most intense is the amorphous carbon signal (~ 0.28 Kev), Si and oxygen (~ 0.53 Kev). However, other peaks observed in the EDS (i.e., S and Cl) show the mixed state of the soot. Figure S3 shows an SEM image and the EDS elemental composition mapping of soot particles sampled in the AAO within the ML. The EDS map shows the presence of Si, Al, K, Ca, and Fe, homogeneously distributed throughout the particle which indicates that this particle is an aged aerosol. The high percentage of Si, Al, and O suggests the presence of material with a geological origin that resulted from the resuspension of soil dust.
Table 2. Aerosol groups observed in the AAO
Particle group
|
Particle type
|
Elemental Composition
|
Particle morphology
|
Soot
|
Soot or black carbon (BC)
|
Strong C signal in EDS spectra.
Minor O and S
|
Particle aggregate, chains formed by nanometric carbon spherules.
|
Mineral dust
|
Mineral
|
EDS spectra are dominated by the Si signal. Particles containing Al and Fe. Minor signals of K, S, C, and O are observed.
|
Compact and irregular particles.
|
S-rich
|
Mainly soot and particles with Si
|
Dominated by C, have an intense S signal. The signal of Si and O were common in this group.
|
Particles have very irregular shapes. These aerosols are sensitive to a strong electron beam.
|
Organic
|
TB
|
Mostly tarball particles. Intense C signal followed by a low signal of O.
|
Spherical particles.
|
Secondary
|
|
In this group, all particles present an S signal. They contained C, O, S, and minor K.
|
Irregular shape particles, susceptible to beam damage. Some Ca-S particles mix with mineral, and some mix with S-rich and K-rich particles.
|
Mineral dust particles
Mineral dust aerosol at the AAO comes mainly from the resuspension of soils and probably from rocks eroded by the wind. These particles with dp < 600 nm (Fig. 7 c y d) show compact shapes and are mixed with other inorganic materials. Figure 7d shows the elemental composition of a mineral particle where a high Si signal is observed, which dominates the composition of mineral particles in this region. Additionally, the mineral particles were found to be mixed with small amounts of aluminosilicates, iron-rich dust, K, and minor Ca. These elements could show the presence of feldspars whose main source could be the erosion of the rocks or could be the result of volcanic emissions 31. The volcanic ash emitted by the Popocatepetl is one of the main components of the soils that surround the AAO. Although during the sampling days there was no direct influence of the volcanic plumes, the soils surrounding the AAO are covered with material emitted previously. The elemental EDS map in Figure S4 for a dust particle shows a homogeneous distribution of Si, Al, Mg, and Fe which demonstrates the geological origin of that particle. The presence of C and K with a uniform distribution also indicates that this particle is covered with organic material possibly originated from BB.
S-rich particles
Sulfur is one of the most frequently observed elements in the EDS spectra of particles measured at the AAO. The S present in the particles mainly comes from three sources: gas emissions from the Popocatepetl volcano, anthropogenic emissions from MC, and BB emissions. Volcanic emissions are the most important due to the proximity of the AAO to the volcano, which is known as one of the largest sulfur dioxide (SO2) sources in the world 32,33. Volcanic plumes consist of gases and sub-millimeter particles32,33. Figures 7e and 7f show TEM images of S-rich particles sampled at the AAO during HAP days. S-rich particles present different morphologies with dp < 800 nm. All S-rich particles observed in this study suffered decomposition or evaporation as the microscope beam hit the particles, indicating that these particles are beam-sensitive and undergo some changes in their shape during analysis.
TB
Figure 8 shows TEM images (Fig. 8a) and the EDS spectrum (Fig. 8b) of the spherical organic particles with dp < 600 nm, which was common in all aerosol samples collected at the AAO site. Those TB are particles with a special morphology (near-spherical) and composition (amorphous carbonaceous material) which are quite abundant in biomass smoke plumes 16,34,35. These particles in the Altzomoni mountain could have two origins: anthropogenic emissions in nearby urban areas and emissions due to BB. EDS spectra in Fig. 8b confirmed the occurrence of TB at the AAO during the HAP episode. We believe that the main source of TB at the AAO is the wildfires near the sampling area. However, in previous studies, a possible large-scale transport of BB particles was evidenced 12,13.
Complex secondary particles
A significant number of secondary aerosol particles were also measured at the AAO. These particles are characterized by having complex elemental compositions and very irregular shapes (with dp between 0.5 µm and 1.6 µm). Two types of secondary particles predominated in the analysis: particles rich in K and S. Figures 8c and 8d show two examples of secondary particles, where one of them presented S and K (Fig. 8d). The main sources of these particles can be anthropogenic emissions in urban areas and BB emissions. Particles were observed to be easily damaged by the strong electron beam, which evidences the decomposition of volatile compounds. Figure 8d shows the EDS spectrum of a secondary particle in where S has a significantly high signal with an intense peak of K. Most of the particles analyzed in this study are internally mixed, which evidences the presence of aged particles. However, it also was observed aerosol assemblies externally mixed, during the FT hours. Fig. S5 shows an example of an externally mixed particle with a soot aggregate surrounded by other particles with different compositions (mainly S). The inset in Fig. S5 is a high magnification image of an internally mixed soot coated with S and K.
Elemental composition
A comparison of the elemental composition of PM2.5 particles sampled at the AAO and MC is shown as pie charts in Figure 9. The main elements detected with the XRF analysis were Al, Si, P, S, K, Ca, Mn, Fe, Ni, Cu, and Zn. Figure 9a shows the elemental analysis of the particles sampled at the AAO, where the composition is dominated by S and K with percent of 46% and 35%, respectively. The abundance of these elements suggested an important contribution of the emissions from wildfires, mainly the K, which is a tracer of BB 36,37. The existence of dust-like aerosol could be evidence by the presence of Si and Fe with significant contributions of 5% and 10%, respectively, in addition to minor contributions of Al, Mn, and Ca. Although the AAO is located in a remote rural area, small amounts (<1%) of Ni, Cu, and Zn were measured. These elements could be related to anthropogenic sources close to the sampling site (e.g., chimney of the TV-broadcast antenna facility). Figure 9b shows the elemental composition of particles sampled in MC, which presents values very similar to those measured in AAO, i.e., with S and K as the elements contributing more to elemental composition with percentages of 37% and 38%, respectively. Although S can be the product of BB, it can also come from other anthropogenic sources (i.e., motor vehicles), being the main element responsible for the production of secondary aerosol particles 37,38. Mineral-dust aerosol is generally a significant component during the dry-warm period 39,40. The presence of Fe and Si with percentages of 10 % and 7 %, respectively, is the primary evidence of mineral dust particles. That mineral fraction in MC is partially a result of the MC semi-arid areas (e.g., former Texcoco and Chalco lakes), arid hills, and unpaved roads within the MC basin 27,41. The significant Ca contribution could be due to fly ash emissions from two sources: construction activities and soil-dust resuspension 27. Furthermore, the trace elements with percentages less than 1% (Ni, Cu, and Zn), have been associated with the emissions generated by high traffic in the urban area. For example, most of the Zn detected could originate from the wear of vehicle tires, while Ni and is a typical element in motor fuel additives 27. The elemental compositions of the particles at both sites (AAO and MC) do not show significant differences. This similarity in the percentage composition could result from the influence of aerosols emitted in the MCMA, which are transported to the AAO by advective processes in the ML42 and orographic forcing. Note that the sampled PM2.5 for this analysis was collected every 24 hours, making it impossible to separate the TL and BL periods. Excluding the organic materials (not measured in this study), the elemental composition of the aerosol at both sites was dominated by S and K, contributing > 75%, which evidence the strong influence of BB emissions. The present results are consistent with those reported by Decarlo et al. (2008) 11, who observed elevated sulfate at the higher altitudes above MC. Similar studies of aerosol chemical composition conducted at other high-altitude sites in different parts of the world (in the absence of BB emissions) reveal that aerosols in the FT contain a high fraction of sulfates 11,43,44.
Air masses back-trajectories
BB smoke is one of the main atmospheric components affecting air quality and climate in Mexico due to massive plumes that can travel thousands of kilometers downwind 12,13. Tracking of these plumes is only possible through satellite measurements, e,g, by the VIIRS radiometer 45. The HYSPLIT model was used to identify the origin of the air masses reaching the sampling sites. Figure 10 shows the HYSPLIT back-trajectories computed at different heights (100, 500, and 1000 m a.g.l.) during the HAP days (May 14 – 17 2019). The HYSPLIT simulations show that during the HAP episode the air masses mainly originate in western and southwestern Mexico where most of the active fires are concentrated (see fire distribution in Fig. 1) to reach the AAO. However, these air masses also cross over Morelos State, where the cities of Cuautla and Cuernavaca are located, possibly indicating not only volcanic but also urban emissions in the air mass reaching the AAO. Only on May 17 there was a possible transport from north of the AAO, carrying particles emitted in CM.