Seasonal and spatial variability of PM2.5 concentration, and associated metal(loid) content in the Toluca Valley, Mexico.

doi:10.21203/rs.3.rs-1517308/v1

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Seasonal and spatial variability of PM2.5 concentration, and associated metal(loid) content in the Toluca Valley, Mexico.

https://doi.org/10.21203/rs.3.rs-1517308/v1

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The Toluca Valley Metropolitan Area (TVMA) is the fifth largest urban center in Mexico, located at high altitude, 2660 meters above sea level (m.a.s.l.) surrounded by mountain ranges. It is composed of heterogenous residential and industrial areas with dense vehicular traffic. This combination of geography and urbanization create a metropolitan area with high levels of air pollutants. The objective of this study was to provide evidence of the seasonal and spatial variation of metal(lloid)s in particulate matter minor to 2.5 microns (PM_2.5)in Toluca Valley. Four sites were sampled between 2013-2014, that include urban and industrial areas, in the dry-cold (November-February) and hot-dry (March-May) season; PM_2.5were collected using high and medium volume samplers. Metal and metalloids concentrations in PM_2.5were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Our results show the highest 24-hour PM_2.5 concentration in the northern area, followed by the southern industrial area, and the lowest concentrations was observed in the southwest area independent of the season. Metals and metalloids with a recovery percentage above 80% were Cobalt (Co), Chrome (Cr), Copper (Cu), Manganese (Mn), and Antimony (Sb). The maximum concentrations of them were observed during the dry-cold season, in the urban-industrial sites found in the north and southern areas. Co, Cr, Cu, Mn, and Sb concentrations were up to one hundred or thousand folded in the dry-cold season compared to dry-hot season due to weather and geographical features of TVMA. The 24-hour PM_2.5 and metal(lloid)s concentrations exceed national and international guidelines to protect population health.

PM2.5

Toluca valley

metals and metalloids

seasonal and site variation

Acute and chronic exposure to atmospheric particles less than 2.5 micrometers (PM_2.5) is considered an environmental risk to human health. There is a correlation between daily concentration of PM_2.5 in urban areas with an increase in morbidity and mortality associated to cardiovascular and lung diseases, pulmonary cancer, and low birth weight (Pope et al., 2002; Pope et al., 2004; Miller et al., 2007; Pope et al., 2009; WHO, 2013a; Pedersen et al., 2013; Straif et al., 2013).

To address this public health problem, various international environmental agencies proposed setting limits to PM_2.5 exposure. In 2013, the United States Environmental Protection Agency (EPA) updated the standard reference values to 35 µg/m³ for 24-hour exposure periods (US-EPA, 2013a). The World Health Organization (WHO) has also published guidelines for air quality, setting a 25 µg/m³ limit for the 24-hour average. However, the WHO has stated that "there are not yet safe values regarding PM_2.5 pollution" (US-EPA 2013 a, b). In Mexico the 24-hour average concentration limit is 45 µg/m³ (Official Mexican Standard, OMS-NOM-025-SSA1-2014).

Atmospheric particles are dynamic and polydisperse materials with a complex composition mainly of organic and inorganic compounds; one of the most common PM toxicity mechanisms is the promotion of oxidative stress which is related to their chemical composition, including the presence of transition metals and the metabolism of organic compounds. Metals and metalloids can catalyze or mediate reactive oxygen species (ROS) generation through mechanisms that involve both their soluble and insoluble forms and has been linked with biological effects of particles (Sørensen, M., Schins, R. P., Hertel, O., & Loft, S 2005; Hennigan, C. J., Mucci, A., & Reed, B. E., 2019).

The measurement of metal and metalloid PM_2.5 content provides an understanding of the sources of air pollution and PM_2.5 toxicity (Kendall et al., 2011). The metal and metalloid content in PM includes a large list of elements, which depends of the human socioeconomic activities and geography of the studied region. Additionally, the detection system and the extraction method used in the analytical method can influence their quantification.

Metals and metalloid exposure can affect health through induction of molecular reactions including the production of ROS, promoting the decline function of organs and tissues. For example, chronic exposure to total Cr increases the carcinogenesis risk (Hu et al., 2012); Co exposure is a contributing factor to developing interstitial lung disease (Wiseman and Zereini, 2014); Mn is neurotoxic, particularly in the immature central nervous system (ATSDR, 2012). In addition, Sb with high solubility and extreme reactivity can contribute to pulmonary toxicity (Hu et al., 2012; ATSDR, 2012; Wiseman and Zereini, 2014).

Previous air pollution studies in Mexico have been carried out in Mexico City, with focus on the metallic and non-metallic content of PM₁₀ and PM_2.5 samples (Aldape et al., 2005; Vega et al., 2010 and 2011; Martínez et al., 2012 and Herrera et al., 2012). The Toluca Valley Metropolitan Area (TVMA) is part of Estado de Mexico, one of 32 federal entities of the United Mexican States; it comprises twelve municipalities, it is the fifth metropolitan zone by size in Mexico and it produces 2.3% of the total gross country production suggesting high industrial and economic activities. TVMA is strongly influenced by great mountain ranges, which is a determinant factor of winds dynamics; among them Sierra Nevado de Toluca on the southeast, to the east Sierra de las Cruces and Sierra de Ocoyotepec; Sierra del Monte Alto to the northeast; and to the south Sierra Matlazinca (Del Campo et al., 2014; Huster, and Pierce, 2020). In addition to being surrounded by large mountains and volcanoes, the TVMA’s high altitude, between 2,560 and 2,740 m.a.s.l., and the surrounded large mountains and volcanoes favors three climate types; temperate-humid, semi-cold humid and cold. The minimum annual temperature is 0 ºC with a maximum annual temperature of 18 ºC. Such geographic and climatological characteristics contribute to physicochemical changes in particles and their chemical speciation, which can contribute to a detrimental effect on public health, as it has been suggested by environmental protection agencies and studies (US EPA, 1978; Bravo and Urone 1981; Bravo et al., 2013).

The measurement of environmental respirable particle concentration, such as fine gravimetric mass or PM_2.5, is important to decrease the health risk of population exposed to such particles. Additionally, the quantification of inorganic and organic chemical compounds can inform sources, bioavailability, solubility, geochemical process, and chemical speciation. This knowledge is crucial to understand the adverse effects on human health and give evidence to develop public policies to regulate environmental emissions. The aim of this study is to evaluate the seasonal and spatial variation of environmental PM_2.5 and the trace metal and metalloid content in this fraction in TVMA, that includes urban and industrial zones.

Sampling location

PM_2.5 samples were collected at four sites of TVMA (Fig. 1), located in Nueva Oxtotitlán (OX) as urban area nearly to Toluca de Lerdo downtown (19° 17' 0.40" − 99° 41' 0.56"), San Cristóbal Huichotitlán (SC) as urban-rural area with agriculture activity (19° 19' 38.0" − 99° 38' 3.44 "), Airport (AP), that includes runways and hangars, surrounded by industrial area (19° 20' 4.41" − 99° 34' 26. 3"), and San Mateo Atenco (SM) as urban area near the Lerma-Toluca industrial corridor with high activity of commercial and shoes manufacturing (19° 16' 49.5 '' − 99° 32' 30").

In OX site, PM_2.5 was collected on glass fiber filter (G653, 8 × 10 cm, Whatman, UK) using the high-volume air sampler (model TE-2.5I, Tisch Environmental equipment, US), at a flow rate of 28 L min^− 1. In the other three sites, 47 mm PTFE filters with PMP supporting rings (R2PJ047, Pall Corp, US) were used for sampling PM_2.5 using medium volume samplers (Echo TCR Tecora, Italy) with a flow rate 16.7 L min^− 1. Sampling was carried out simultaneously at the four sites, corresponding to four stations of Red Automática de Monitoreo Atmosférico of the Toluca Valley (RAMAT). Samples were collected in 24-hour periods with a six-day frequency spanning from November 28, 2013 to May 17, 2014. This included dry-cold season from November to February and dry-hot season, from March to May. The sampling equipment was calibrated at the sampling sites according to the Official Mexican Standard (NOM-035-SEMARNAT-1993).

Extraction And Elemental Chemical Analysis

Ambient air filters were weighed before and after sampling to determine the mass of particles collected by gravimetric analysis, which was performed at the Red Automática de Monitoreo Atmosférico of Mexico City. During this procedure quality controls were implemented in the gravimetric laboratory that include the laboratory blank filter, field sampling blank filter and collected filters. After sampling, the filters were weighted for gravimetric PM_2.5 determination according to the NOM-035-SEMARNAT-1993 and US-EPA, 2008.

The filters digestion was carried out using an acid method in a hot plate, adding an acid solution of HNO₃:HCL (5.5%:16.75%), in a 1:5 ratio area: volume, and heated at 44 ± 1°C, for 30 min, always preventing the drying of samples and allowing cooling to room temperature. The extracts were transferred to volumetric flask (25 mL) and the volume adjusted with acid solution for the analysis of elements by ICP-MS (Model ELAN 6100, Perkin Elmer, USA). Calibration curves were prepared using Perkin Elmer multi-element calibration standards in concentrations range between 0.01–100 ng/mL (US-EPA, 2008).

All the filters used for quality control were extracted and analyzed together with the sampling filters to determine background concentration and provide accuracy and precision in the detection of metal and metalloids concentrations. The quality control parameters calculated were limit of detection (LOD), limit of quantitation (LOQ), and percent recovery (%R). The LOD was calculated as the element concentration average in the blank filters extracts, per three times the standard deviation of each element (CENAM & EURACHEM, 2005). The LOQ was calculated as the average of each element concentration in blank filters extract per ten times the standard of each element. The efficiency of the method was assessed as the % R of the NIST 2783, a standard reference material, which was subjected to the same extraction process as the environmental samples. Quality controls by Perkin Elmer ELAN® ICP-MS equipment was with argon plasma gas, the daily performance check for analyzing masses: low beryllium 9.0122, medium magnesium 23.985, and high indium 114.904, as well as with the evaluation of the detection system.

Statistical Analysis

Data processing was performed using Microsoft Excel (Microsoft 365, ver. 2112, US) and summary statistics of sampling and chemical composition are presented by sampling site and season. Temperature and relative humidity are described from the mean, minimum and maximum values; the wind roses were stablished to each station by season using the WRPLOT View; wind rose Plots for Meteorological Data version 8.0.2^(C) 1998–2018 Lakers Environmental Software; gravimetric and chemical PM_2.5 data are presented with the median and range values.

The weather parameters can dictate the presence of contaminants in the air and their concentration. In the TVMA, the relative humidity (RH) in the four sampling sites was similar among them in both seasons. In the dry-cold season RH was 52.3% (20.36–79.07) in the SC-urban, and 56.12% (24.71–84.64) in the AP-industrial area; 54.0% (20.0–83.0) and 52.6% (23.61–74.89) for SM and OX, respectively. During the dry-hot season, the relative humidity shown statistical differences in all sampling sites. 42.9% (19.0—66.20) in the SC-urban, 47.9% (22.58—71.42) in the AP-industrial; 46.1% (22.15–69.54) and 42.9% (21.31–62.15) for SM and OX sites, respectively (Table 1).

Table 1

Temperature and relative humidity in Dry-cold and Dry-hot season during the PM2.5 sampling in Toluca Valley Metropolitan Area, Estado de México.
Sampling site	Dry-cold season		Dry-hot season
Sampling site	Temperature (°C)	RH (%)	Temperature (°C)	RH (%)
Nueva Oxtotitlán (OX)	10.41 (3.42–18.85)	52.59 (23.61–74.89)	14.11 (7.15–21.97)	42.97 (21.31–62.15)
San Mateo Atenco (SM)	11.49 (3.46–20.88)	54.04 (20.0–83.0)	14.90 (7.88–22.82)	46.15 (22.15–69.54)
Airport (AP)	10.79 (3.46–18.88)	56.12 (24.71–84.64)	13.89 (7.27–21.09)	47.90 (22.58–71.42)
San Cristóbal (SC)	11.07 (3.16–20.43)	52.31 (20.36–79.07)	14.81 (6.34–22.76)	42.97 (19.00–66.20)
Data are present as mean and the range values.

Mean temperature was similar among sampling sites and seasons, with a difference of approximately 4°C among the sites by seasons. Average temperatures during the dry-cold season varied from 10.41 to 11.49. During the dry-hot season, the mean temperatures varied from 13.89°C to 14.9°C (Table 1).

It was observed that the predominant wind direction, vector direction, in both seasons were similar in SM (Southeast), AP (East), and OX (Southwest); with the exception of SC with vector direction in southeast and northeast during cold and hot season, respectively (Fig. 2). Average wind speed (AWS) was similar in both seasons. The AWS for cold season follow the gradient AP (1.48 m/s) > OX (1.15 m/s) > SC (0.93 m/s) > SM (0.89 m/s). In the hot season the highest AWS was observed in SC (1.69 m/s) followed by OX (1.42 m/s) > AP (1.12 m/s) and the lowest AWS was observed in SM (1.06 m/s).

Calm winds were more frequent in the cold-dry season compared to the hot-dry season. In the cold season the calm winds followed the gradient SM (34.26%); SC (30.79%); OX (11.11%) and AP (8.1%), however, in the hot season the higher calm winds frequency is observed in the SM site (26.96%), AP being the second site with calm winds (21.47%) and the lowest frequency of calm winds were 5.45% and 0.32% corresponding to OX and SC, respectively.

The 24-hour PM_2.5 median (range) concentrations are summarized in Table 2. For both seasons, the highest PM_2.5 concentration was observed in SC station; followed by AP, SM and the lowest concentration was observed in OX. In the dry-cold season 54.58 µg/m³ (26.1–79.88) was observed in SC, followed by 41.3 µg/m³ (1.33–57.97) in AP, 41.16 µg/m³ (12.6–57.93) in SM; and 15.46 µg/m³ (9.46–51.25) in OX. In the dry-hot season the PM_2.5 concentration in SC station was 72.85 µg/m³ (23.48–102.84); followed by AP with 43.08 µg/m³ (24.1–86.36); SM with 37.28 µg/m³ (20.61–59.44); and the lowest PM_2.5 concentration was observed in OX with 10.88 µg/m³ (7.56–27.72). The SC site was the only one that exceeded the median 24-hour PM_2.5 concentration limit of 45 µg/m³ stablished by the Mexican government (NOM-025-SSA1-2014). However, according with the maximum gravimetric data all the stations showed at least one day over the 24-hour PM_2.5 concentration limit. The OX site did not exceed the concentration limit during the dry-hot season.

Table 2

24-hour PM2.5 air gravimetric concentrations in the Toluca Valley Metropolitan Area (TVMA)
PM_2.5 (µg/m³)
Sites	Dry-Cold	N	Dry-Hot	N
Nueva Oxtotitlán (OX)	15.64 (9.46–51.25)	18 (1)	10.88 (7.56–27.72)	13 (0)
San Mateo Atenco (SM)	41.16 (12.60–57.93)	5 (1)	37.28 (20.61–59.44)	13 (4)
Airport (AP)	41.30 (1.33–57.97)	14 (6)	43.08 (24.10–86.36)	12 (5)
San Cristobal (SC)	54.58 (26.10–79.88)	14 (10)	72.85 (23.48–102.84)	11 (8)
Data are shown as median following range of values in parenthesis. N indicates the number of samples, following by the number of samples, followed by the number of samples exceeding Mexican government guidelines, 45 µg/m³, NOM-025-SSA-2014 in parenthesis.

The metal and metalloid analysis by ICP-MS showed a recovery range of 95 − 80% for Co, Cr, Cu, Mn and Sb, whereas recovery for Zn and Pb were between < 80 to > 60%; and for Mg, Ba, Al, and Ti the recovery range were below 60% (Table 3).

Table 3

Quality Control Parameters in the determination of elements present in PM2.5, at the MATV, Mexico, 2013–2014
Limits			NIST 2783 air particulate standard filter
Element	LOD (µg/m³)	LOQ (µg/m³)	Certified (ng/filter)	Measured (ng/filter)	Recovery (%)
Cr	1.1X10^− 5	2.0X10^− 5	135 ± 25	127	94
Cu	1.1X10^− 5	2.6X10^− 5	404	368	91
Co	7.9X10^− 8	1.1X10^− 7	7.7	6.4	83
Mn	4.9X10^− 6	6.7X10^− 6	320 ± 12	267	83
Sb	1.7X10^− 7	3.2X10^− 7	71.8	59.6	83
Zn	1.6X10^− 2	2.2X10^− 2	1790 ± 130	1376	77
Pb	1.29X10^− 6	2.39X10^− 6	317 ± 54	213	67
Mg	7.3X10^− 4	9.8X10^− 4	8620	5018	58
Ba	2.1X10^− 2	2.7X10^− 2	335	190	57
Al	1.3X10^− 2	2.3X10^− 2	23210 ± 530	7548	33
Ti	1.10X10^− 5	2.5X10^− 5	1490	217	15
^(a) The %R could not be calculated for K,Ca,Ni.V, and Fe. Limit of detection, LOD; Limit of quantification, LOQ.

The highest concentrations of metal and metalloids were observed in the dry-cold season in all stations. Additionally, concentrations during the dry-cold compared to dry-hot season were above one hundred times in SM, AP, and SC, with the exception of OX where the concentrations were below four times (Table 4). Although, the highest PM_2.5 concentration was observed in SC in both seasons, the highest metal and metalloid concentration in dry-cold season was observed in SM station. On the other hand, in the dry-hot season the major metal and metalloid concentration was observed in the SC station, with the exception of copper concentration which was higher in OX station (Table 4).

In the SM station, the Co average concentration was 140 ng/m³ (14–231), following by SC site with 39.2 ng/m³ (0.38–68.6) and AP site with 35.8 ng/m³ (0.29–180). The lowest concentration was measurement in OX site, with 0.0297 ng/m³ (0.00652–11.7). During the dry-hot season the highest concentration was observed in SC station, 0.301 ng/m³ (0.051–0.354); this concentration was one hundred and thirty times below the concentration found in SC on the dry cold season. The Co concentration in SM station during the dry cold season was approximately nine hundred times below the SM dry hot season concentration (0.154 ng/m³ vs 140 ng/m³). The AP station showed a Co concentration in dry cold season three hundred and sixty times above the concentration found in dry hot season samples (35.8 vs 0.0986 ng/m³). The lowest Co concentration was observed in the OX station, with 0.00821 ng/m³ (0.00136–0.0571), which was 3.6 times below the concentration found during the dry-cold season at the same station (Table 4).

Cr concentrations were observed in the dry-cold season in all the stations. The highest concentration was measured in SM (17.33 µg/m³), however, it was detected in only one sample of five. AP was the second site with high Cr concentration, 6.32 µg/m³ (6.26–9.53), detected in three samples of fourteen. Cr in the SC station, 5.7 µg/m³ (5.55–5.85), was detected in eleven of fourteen samples. The lowest Cr concentration was observed in the OX site, 0.0046 µg/m³ (0.0024–0.0096), with twelve samples out of fourteen. Cr concentrations in the dry-hot season were only observed in the OX site, with a concentration of 0.00311 µg/m³ (0.0028–0.0032), in three samples of thirteen, this value was 1.5 times below the concentration found in the dry-cold season at the same site. Finally, the ambient Cr concentrations for the rest of the sampling stations were below the LOD (Table 4).

On the dry-cold season the highest copper Cu concentration was observed in SM station, 7.684 µg/m³ (7.4 -20.48), where Cu was quantified in four of five samples, following AP and SC, with 2.37 µg/m³ (0.23–27.0) and 2.07 µg/m³ (0.02–5.89), respectively. Cu was determined in twelve of fourteen and eight of fourteen, in AP and SC stations, respectively. The lowest Cu concentrations were observed in OX station, in four of eighteen samples, 0.0194 µg/m³ (0.0102–0.318); (Table 4).

The highest Mn concentrations were observed during the dry-cold season in SM in three of five filters, 7.68 µg/m³ (7.4 -20.48); followed by SC and AP, with 1.8 µg/m³ (0.021–14.22) and 1.43 µg/m³ (0.13–12.63), respectively. In all SC samples Mn was quantified, and in AP site, Mn was observed in thirteen of fourteen samples. The OX site had the lowest Mn concentration, 0.0031 µg/m³ (0.0009–0.0065); Mn was quantified in seventeen of eighteen samples for dry-cold season. On the other hand, in the dry-hot season the highest concentration was observed in SC site, 0.017 µg/m³ (0.00195–0.0262), and it was quantified in all the samples. Moreover, Mn was seventy-eight times lower in contrast to the dry-cold season. The Mn concentrations found in SM, and AP stations during the dry hot season where five hundred and ninety and one hundred times below the concentrations measured during the dry-cold season at the same stations (0.013 µg/m³, and 0.012 µg/m³ vs, 7.68 µg/m³, and 1.43 µg/m³ respectively). The lowest Mn concentration was measured in OX site, 0.0016 µg/m³ (0.00031–0.0051); Mn concentrations in OX site were detected in twelve of thirteen samples, and the Mn concentration in the dry-hot season was 2.7 times below the concentration found in the dry-cold season (Table 4).

The metalloid Sb concentration in the dry-cold season was highest in SM 6.39 µg/m³ (0.07–13.83); followed by SC 2.24 µg/m³ (0.02–3.79); then AP with 1.44 µg/m³ (0.39–3.74); and OX with 0.0022 µg/m³ (0.001–0.016). Our data correspond to the detection of Sb in seventeen, five, fourteen, and fourteen filters, respectively. The gradient of concentration for dry-hot season changes, and it showed the following gradient: SC 0.017 µg/m³ (0.002–0.026); AP 0.0076 µg/m³ (0.0023–0.018); SM 0.0064 µg/m³ (0.0017–0.017); and OX 0.00081 µg/m³ (0.0002–0.0041). Although, in dry-hot season the Sb concentrations were lower than dry-cold season, the presence of Sb was detected in all the filters of each sampling sites. In addition, the Sb concentration of dry-cold season fell in the hot season nearly to one thousand times at SM site, followed by SC and AP sites with around two hundred times, and OX with only 2.7 times (Table 4).

Table 4

Metal and metalloid concentrations of 24-hour PM2.5 collected in Toluca Valley Metropolitan Area (TVMA)
Cobalt (Co, ng/m³)
	Dry-Cold	DF	Dry-Hot	DF	Enrichment
OX	0.0297 (0.00652–11.7)	17/18	0.00821 (0.00136–0.0571)	9/13	3.6
SM	140 (14–231)	3/5	0.154 (0.0103–0.384)	7/13	912.9
AP	35.8 (0.29–180)	6/14	0.0986 (0.00903–0.266)	10/12	363.3
SC	39.2 (0.38–68.6)	7/14	0.301 (0.051–0.354)	8/11	130.2
Chromium (Cr, µg/m³)
	Dry-Cold	DF	Dry-Hot	DF	Enrichment
OX	0.0046 (0.0024–0.0096)	12/18	0.00311 (0.0028–0.0032)	3/13	1.5
SM	17.33	1/5	ND	0/13	-
AP	6.32 (6.26–9.53)	3/14	ND	0/12	-
SC	5.70 (5.55–5.85)	11/14	ND	0/11	-
Copper (Cu, µg/m³)
	Dry-Cold	DF	Dry-Hot	DF	Enrichment
OX	0.0194 (0.0102–0.318)	4/18	0.0085	1/13	2.3
SM	7.24 (5.43–11.58)	4/5	0.0044 (0.000343–0.0135)	12/13	1645.1
AP	2.37 (0.23–27.0)	12/14	0.00615 (0.00445–0.0226)	10/12	384.3
SC	2.07 (0.02–5.89)	8/14	0.00659 (0.00261–0.0346)	9/11	314.0
Manganese (Mn, µg/m³)
	Dry-Cold	DF	Dry-Hot	DF	Enrichment
OX	0.0031 (0.0009–0.0065)	17/18	0.0016 (0.00031–0.0051)	12/13	1.9
SM	7.68 (7.4–20.48)	3/5	0.013 (0.0031–0.058)	12/13	593.7
AP	1.43 (0.13–12.63)	13/14	0.012 (0.00017–0.064)	12/12	121.4
SC	1.8 (0.021–14.22)	14/14	0.0229 (0.00209–0.0282)	11/11	78.4
Antimony (Sb, µg/m³)
	Dry-Cold	DF	Dry-Hot	DF	Enrichment
OX	0.00222 (0.001–0.0167)	17/18	0.00081 (0.0002–0.0041)	12/13	2.7
SM	6.39 (0.07–13.83)	5/5	0.0064 (0.0017–0.017)	13/13	996.4
AP	1.44 (0.39–3.74)	14/14	0.0076 (0.0023–0.018)	12/12	189.5
SC	2.24 (0.02–3.79)	14/14	0.017 (0.002–0.026)	11/11	209.3
Abbreviations: OX, Nueva Oxtotitlán; SM, San Mateo Atenco; AP, Airport; SC, San Cristobal; DF indicate detection frequency, number of filters in which metal was detected over total filters collected. ND indicate Not-Detected.

Determination of PM_2.5 concentrations is critical for urbanized areas to evaluate the air quality and to prevent adverse effects on human health. Additionally, the chemical composition of particles has been suggested as finger print of the emission sources, and atmospheric chemical processes.

The PM_2.5 concentration and composition has been studied in many countries. There are factors that influence PM2.5 concentration, such as weather and topography. In our study area, as in others, topography plays a key role in atmospheric dynamics, impacting air quality of urbanized and industrialized areas; additionally, the predominant weather determines the atmospheric dynamics (Querol et al., 2007a). The season and climate parameters such as temperature, wind direction, relative humidity, rainfall, cloudiness (Kulshrestha et al., 2009), and some atmospheric phenomena such as thermal inversion, can modify the half-life, and concentration of pollutants in the air. Because of its diameter, the PM_2.5, remains longer in the atmosphere, and is efficiently transported; mountain systems can influence their transport and local deposit (Cheng Miao-Ching et al., 2012). Additionally, wind movement, its force, and direction must be considered in the displacement, distribution and final fate of air pollutants. Wind speed is not constant along each day, week, months, seasons, and also between years, because it undergoes variations due to the topographic and thermal features of a given area.

In our study area, we observed discrete differences between seasons, with approximately an increment of 4ºC in the average daily temperature between cold and hot seasons; average daily RH was approximately 10% higher in the dry-cold season compared to the dry-hot season. For AWS, differences were around 0.5 m/s; these discrete changes could be associated with the high altitude of TVMA (2660 m.a.s.l.).

The influence of air flow, direction, and calm winds was observed in our study. The AWS was quite different among sites between seasons. However, it seems that direction of air flow in OX displace the atmospheric particles and move the air pollutants to other site. In the rest of the sites, the influence of east winds flows from AP and SM sites to the SC site, where AP and SM can be considered industrial zones and SC the receptor site, a suburban zone with the highest PM_2.5 concentration. Additionally, we observed higher PM_2.5 concentration in the dry-cold season compared to dry-hot season in almost all sites. This can be explained by the frequency of calm winds during the cold-season, concomitant with the major frequency of thermal inversion according to the high altitude and recurrent in winter or fall seasons.

We observed different 24h-PM_2.5 concentrations among the four sites between the dry-cold and the dry-hot seasons. The SC site exceeded the 24-hour PM_2.5 concentration limit of 45 µg/m³, established by the Mexican government (NOM-025-SSA1-2014). However, at least one day in the sampling period was out of the concentration limit for the rest of the sampling sites. Nevertheless, according to international 24-hour PM_2.5 limit of 25 and 20 µg/m³, established by World Health Organization (WHO) and European Community (WHO 2013a, OJEU, 2008) respectively, only OX is under the international concentration limit, indicating that the rest of the population is breathing unhealthy air.

Differences among element concentrations between the two seasons were observed, likely due to the seasonal weather parameters mentioned above that determine the element distribution and its presence, such as temperature, WD and WS, as well as the topographical conditions of the region.

The highest metalloid (Sb) and transition metals (Co, Cu, Mn) concentrations were found at the SM site, which did not have the highest PM_2.5 concentrations. SM is located in the southeast of MATV, bordered by Lerma-Tenango del Valle and Toluca México highways, neighboring to the Lerma-Toluca industrial park, with the main economic activity being shoes and clothing manufacturing.

The AP and SC sites share a similar trend in metalloid (Sb) and transition metals (Co, Cu, Mn) concentrations. Both sites are located north of the Toluca valley, with different economic activities; in addition to airplane transit on AP site, there is an industrial settlement, land dedicated to agriculture, and San Antonio roadway. However, SC is considered an urban settlement without natural barriers, the predominant wind coming from the east, and with a vector wind in the dry-cold season from the southeast that is influenced by the emissions generated in Toluca downtown. It is possible that additional emissions, mainly produced by industrial plants located in the south and south-east AP and SM sites, as well as by the resuspension of road dust and biomass combustion (Quiterio et al., 2005; Mansha et al., 2012) contribute to local pollution.

The station with the lowest PM_2.5 concentration was OX site, located to the west of Toluca downtown, is characterized by high population density; it is considered a residential area with low levels of vehicular traffic, without industrial plants. The main difference from the rest of the sites was the air flow direction that comes from the southwest, opposite to the downtown and industrial areas. Near the area, at the north of OX site, there are mountain systems with elevations between 2800–3000 m.a.s.l. that run from west towards east to the limit of Toluca downtown that probably acting as a barrier to the pollutants that flow from Toluca downtown to OX. Additionally, the OX site is a place where calm winds are less frequent, suggesting an efficient removal of pollutants.

In the MATV we observed that in the dry-hot season the metal and metalloid concentrations had more important decrease compared to the dry cold-season. When calculating the enrichment of the element concentration of the dry-cold season in contrast to the dry-hot season, we detected that in some sites the increment was a hundred or thousand-fold. However, the PM_2.5 mass did not change in the same magnitude, suggesting that in the dry-cold season the frequency of calm winds and probably the thermal inversion at high altitude induce a major permanence of metals and metalloids, associated with the increment in the economic activity of the area.

Comparisons between PM_2.5 and element concentrations detected in our study, during the dry-hot season in the MATV, and those found in other countries showed that the concentrations are similar in range to those reported in other cities in the world (Table 5).

On the other hand, the content of metalloid and transition metals in PM_2.5 in the dry-cold season at the SM, SC, and AP sites were above those reported in all other cities around the world (Table 5) the concentrations of metalloid and transition metals observed in the MATV were in the order of micrograms with respect to other cities with concentrations expressed in nanograms. The concentrations observed in the dry-cold season were higher than the limits recommended by regulatory agencies (e. g. EPA) to prevent human health.

Our study has important methodological and study design differences respect local and international studies, including the sampling time, which are relatively short. Moreover, the metal(loid)s extraction method varies among the studies which define the chemical form of the elements and the biological availability (Espinosa et al., 2002). The use of efficient and alternative tools, such the ICP-MS, for the analysis of PM_2.5 can help to detect, quantify and design options to address pollution problems in large cities (Saldarriaga et al., 2009; Murillo et al., 2015), although the sensitivity of different detection systems of analytical methods can influence the data observed.

Cobalt (Co), which is a recurring pollutant of wastewater, is a metal that is released into the atmosphere as a particle, its main use is in the petrochemical and plastic industry as a catalyst, it can be released in scrap metal recycling, foundry and metal refining, additionally, Co can be released after burning fossil fuel. Co content in PM_2.5 samples from MATV in AP, SC and OX sites were observed in the occupational setting concentration reported (Kim et al., 2006), but Co speciation its needed to be determine to explain the human health adverse effect.

Chromium (Cr) is released in the commercial and residential fossil fuel, natural gas, oil and coal combustion in addition to emissions in the metallurgical industries (e.g. ferrochromium or chromium), chromium platers, and paper industry (Kimbrough et al., 1999; Xu, et al., 2013). The Cr content in MATV PM_2.5 is higher respect the annual standard stablished by WHO, and those reported to other countries (Table 5).

Copper (Cu) atmospheric emission sources include copper smelters, copper and iron ore processing, iron and steel production, combustion sources, municipal incinerators, copper sulfate production, brass and bronze production, carbon black production, cooling systems, brake wear particles, both by direct emissions and by suspended road dust (Georgopoulos et al., 2001; Keuken et al., 2013). According with the Cu concentration found in the PM_2.5 from MATV, this metal was under the maximum annual concentration and copper concentration for 24-hour period stablished by EPA (1987a), 30 and 100 µg/m³, respectively (Table 5).

Manganese (Mn) is part of particle component, the crustal rock is the major natural source, other sources include forest fires, vegetation (e.g. leaching from plant tissues and dead plants), volcanic activity, and animal excrement. Anthropogenic source includes mining and mineral processing (e.g. nickel), emission from alloy (e.g. steel), the combustion of fossil fuel and in minor degree from combustion of fuel additives. Mn compounds have many applications such as the production of dry-cell batteries, matches, fireworks, porcelain and glass-bonding materials, as a catalyst in the chlorination of organic compounds, in animal feed to supply essential trace minerals, among others (Howe et al., 2004). PM_2.5 collected in MATV has a higher contend in Mn respect other reported countries. However, concentrations are below annual standard limit stablished by WHO, but Mn content in PM_2.5 from MATV is upper respect the minimal risk level for neurological effects by chronic inhalation (ATSDR, 2012) (Table 5).

Antimony (Sb) is incorporated in textiles, paper and plastics as coadjutant of fire retardants; the primary emissions sources are related with plastic manufacturing, petroleum industry, and structural metal products (Belzile et al., 2011; Tian et al., 2012). Sb contend in PM_2.5 in SM, AP, and SC was > 1µg/m³, value referred as industrial area (Table 5), however, Sb has not been classified as carcinogenic in humans by U.S. EPA but ATSDR has placed antimony trioxide as possible human carcinogen. According with the high levels found of Sb in MATV further studies are need to describe the chemical speciation and the potential risk for human health.

Table 5
Comparison of element concentrations in PM2.5 air samples reported in different countries
Location	Site type	Altitude (m.a.s.l.)	PM_2.5 (µg/m³)	Metal(loid)s elements (ng/m³)					Method / sampling	Reference
Location	Site type	Altitude (m.a.s.l.)	PM_2.5 (µg/m³)	Co	Cr	Cu	Mn	Sb	Method / sampling	Reference
Toluca Valley, Mexico ꬷ	OX-Urban	2660	15.64	0.0297	4.6	19.4	3.1	2.22	ICP-MS / 24 h; every 6 days, > 8 weeks	Aztatzi et al., present study
	SM-subindustrial		41.16	140	17,330	7,240	7,680	6,390
	AP-industrial		41.3	35.8	6,320	2,370	1,430	1,440
	SC-Urban		54.58	39.2	5,700	2,070	1,800	2,240
Athens, Greece	Urban	129	4-100	-	-	7.2	3.4	-	ICP-MS / 24 h	Remoundaki et al., 2013
Dunkerque, France	Industrial	4	24.9 − 33.2	-	0.7	1.7	2.4	0.7	ICP-MS / 12 h	Kfoury et al., 2016
Dunkerque, France	Industrial	4	24.9 − 33.2	-	0.7	1.6	2.9	0.7	ICP-MS / 12 h	Kfoury et al., 2016
Athens, Greece	Urban	10	8.12–34.6	0.48	6.19	7.28	4.73	-	ICP-MS / 24 h; every 3 days	Manousakas et al., 2014
Athens, Greece	Urban	430	6.44–45.5	0.23	5.64	4.02	3.30	-	ICP-MS / 24 h; every 3 days	Manousakas et al., 2014
USA, 187 countries	-	-	14.0 ± 0.22	0.7	2.0	3.9	3.0	11.1	ICP-MS / five years/monitor frequency 3–12 days	Bell et al., 2007
Guadalajara, Mexico	Urban	1576	37–72	4.0	15.6	-	17.6	1.5	ICP-MS / 24 h; every 3 days	Murillo-Tovar et al., 2015
Guadalajara, Mexico	Urban	1576	16-49.2	-	10.2	108.8	10.2	-	ICP-MS / 24 h; every 3 days	Murillo-Tovar et al., 2015
Mexico City, Mexico	Urban	2250	39.4	0.2	16.0	65	16.7	4.9	ICP-MS / 24 h; every 6 days	Garza-Galindo et al., 2019
	Urban		16.2	0.3	20.0	25.0	18.0	2.8
	Urban		28.4	0.3	23.2	21.0	20.6	3.9
Manizales, Colombia	Urban	2200	-	-	38.0	5	-	-	ICP-OES	dos Santos Souza et al., 2021
Guangzhou, China	Urban	21	83.3–190	0.9	7.6	57.3	62.4	-	ICP-MS /24 h in 10 consecutive days	Feng et al., 2009
Shanghai, China	Industrial	4	103.0	-	22.0	22.0	92.0	-	ICP-AES / 48 h	Wang et al., 2013
Shanghai, China	Urban	4	62.2	-	31.0	29.0	132.0	-	ICP-AES / 48 h	Wang et al., 2013
Daejeon, China	-	80	5.4–63.3	-	2.4	6.5	3.1	1.8	ICP-MS / 24 h	Lee Jin-Hong et al., 2013
Hangzhou, China	Industrial	15	-	0.8	8.4	69.9	54.2	-	ICP-MS / 18–22 h	Dai et al., 2015
Hangzhou, China	Urban	5	-	0.5	4.4	69.8	16.8	-	ICP-MS / 18–22 h	Dai et al., 2015
Concentration Criteria or limits				† <1 to2 ng/m³; ⸸ 1×10⁴ to 1.7 × 10⁶ ng/m³	* 100 and ‡ 12 ng/m³	§ 30 and 100 µg/m³	* 52 and ⁑ 0.3 µg/m³	⸙ <20 ng/m³. > 1 µg/m³ for industry.
ꬷ Results of the dry-cold season of Metropolitan area from Toluca Valley, Mexico state, Mexico. † Unpulled sites ⸸ Air concentration range of Cobalt in occupational settings, Kim et al., 2006. ‡ EPA calculated inhalation unit risk estimate. § Copper maximum annual concentration and copper concentration for 24-hour period at a location within one-half mile of a major source, EPA 1987a. * Annual standard, WHO, 2016. ⁑ Minimal Risk Level, as an estimate of a chronic inhalation exposure that is likely to be without appreciable risk of adverse non-cancer effects during a lifetime; for Mn was based on impairment of neurobehavioral function in people, ATSDR (2012b). ⸙ antimony ambient air range, and in industry area observed data, ATSDR 1992.

The present study reports the content of metalloid and transition metals in the PM_2.5 fraction by ICP-MS. The airborne particles in each geographic area will depend on local anthropogenic source of emissions, season and weather variables such as temperature, altitude, humidity, wind velocity and air flow direction. This means that the study of atmospheric conditions for dispersion of pollutants must consider temporality and geography of the area to be studied. The levels of PM_2.5 and trace metal(loid)s found in the TVMA provide data for understanding the behavior of elements present locally and in other regions with similar features. This evidence can help to control and regulate emissions of constituents of airborne particles that constitute a potential risk for human health. The control, prevention, and minimization of the levels of these contaminants in the geographic area needs to be studied as well as their impact on human health.

Acknowledgements

The authors gratefully acknowledge the technical support of the Red Automática de Monitoreo Atmosférico (RAMA) from Mexico City, and to the Red Automática de Monitoreo Atmosférico from Toluca valley (RAMAT) for providing meteorological data, area localization, equipment calibration, and maintenance.

Statements and Declarations

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. The authors have no relevant financial or non-financial interests to disclose.

Data availability

The datasets generated during and/or analyzed during the current study are available in ww.figshare.com repository, https://figshare.com/s/cafed077bcfdf913e9a5, https://doi.org/10.6084/m9.figshare.19500569.v1

Authors’ contribution

A. L. Barbosa-Sánchez contributes in the present study to carried out sampling, equipment management, logistic, analytical data analysis and written the first manuscript. Sample analysis, and analytical method development were performed by C. Márquez-Herrera.

R. Sosa-Echeverria participates in monitoring and direction of sampling. R.V. Diaz-Godoy participates in sampling, provide resources to monitoring, and sample management. M.E. Gutiérrez-Castillo contribute in conception and design of the study, and monitoring planning, analytical method development. C. Escamilla-Núñez participates in data base curation, and statistical data management. A. M. Rule and M. P. Sierra-Vargas contribute in review and editing results and final manuscript. O. G. Aztatzi-Aguilar participates in data curation, and validation, visualization and result edition, and written final draft manuscript preparation. All authors read and approved the final manuscript.

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Seasonal and spatial variability of PM2.5 concentration, and associated metal(loid) content in the Toluca Valley, Mexico.

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Introduction

Materials And Methods

Sampling location

Extraction And Elemental Chemical Analysis

Statistical Analysis

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