Next Article in Journal
Review and Extension of Suitability Assessment Indicators of Weather Model Output for Analyzing Decentralized Energy Systems
Next Article in Special Issue
Reconstructing Fire Records from Ground-Based Routine Aerosol Monitoring
Previous Article in Journal
An Assessment of the South Asian Summer Monsoon Variability for Present and Future Climatologies Using a High Resolution Regional Climate Model (RegCM4.3) under the AR5 Scenarios
Previous Article in Special Issue
Forecasting Urban Air Quality via a Back-Propagation Neural Network and a Selection Sample Rule
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Potential Sources of Trace Metals and Ionic Species in PM2.5 in Guadalajara, Mexico: A Case Study during Dry Season

Centro de Investigaciones Químicas, Instituto de Investigación en Ciencias Básicas y Aplicadas, Universidad Autónoma del Estado de Morelos, Av. Universidad 1001, Colonia Chamilpa, C.P. 62209, Cuernavaca, Morelos, Mexico
Cátedras, Consejo Nacional de Ciencia y Tecnología, Av. Insurgentes Sur 1582, Colonia Crédito Constructor, Del. Benito Juárez, C.P. 03940, Ciudad de México, D.F., Mexico
Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Av. Normalistas 800, Colonia Colinas de la Normal, C.P. 44270, Guadalajara, Jalisco, Mexico
Universidad de Guanajuato, Carretera Irapuato-Silao, Ex Hacienda El Copal Km 9, C.P. 36500, Irapuato, Guanajuato, Mexico
Comisión Ambiental de la Megalópolis, Calle el Oro 17, Colonia Roma Norte, Del. Cuauhtemoc, C.P. 06700, Ciudad de Mexico, D.F., Mexico
Facultad de Ciencias Agrarias, Departamento de Agronomía, Universidad Nacional de Colombia, Sede Bogotá, C.P. 111321, Colombia
Peace Corps, 1111 20th Street, NW Washington, DC 20526, USA
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Atmosphere 2015, 6(12), 1858-1870;
Submission received: 4 August 2015 / Revised: 18 October 2015 / Accepted: 20 November 2015 / Published: 1 December 2015
(This article belongs to the Special Issue Air Quality and Source Apportionment)


This study was conducted from May 25 to June 6, 2009 at a downtown location (Centro) and an urban sector (Miravalle) site in the Metropolitan Zone of Guadalajara (MZG) in Mexico. The atmospheric concentrations of PM2.5 and its elemental and inorganic components were analyzed to identify their potential sources during the warm dry season. The daily measurements of PM2.5 (24 h) exceeded the WHO (World Health Organization) air quality guidelines (25 μg·m−3). The most abundant element was found to be Fe, accounting for 59.8% and 72.2% of total metals mass in Centro and Miravalle, respectively. The enrichment factor (EF) analysis showed a more significant contribution of non-crustal sources to the elements in ambient PM2.5 in Centro than in the Miravalle site. Particularly, the highest enrichment of Cu suggested motor vehicle-related emissions in Centro. The most abundant secondary ionic species (NO3−; SO42− and NH4+) and the ratio NO3−/SO42− corroborated the important impact of mobile sources to fine particles at the sampling sites. In addition, the ion balance indicated that particles collected in Miravalle experienced neutralization processes likely due to a higher contribution of geological material. Other important contributors to PM2.5 included biomass burning by emissions transported from the forest into the city.

1. Introduction

In urban environments, epidemiological studies suggest that particulate matter (PM) is an environmental pollutant with adverse effects on human health. In addition, the more meaningful association between PM exposure and occurrence of diseases are found for smaller airborne particles [1]. Short- and long-term exposure to particles with an aerodynamic diameter less than 2.5 μm (PM2.5) is linked to an increased risk of cardiopulmonary and lung cancer mortality [2,3] and reduced life expectancy [4]. Also, associations between chemical characteristics and PM toxicity tend to be stronger for the smaller PM size fractions [5]. Although air quality standards are used to control and manage exposure to its concentrations and emissions, a detailed understanding of the chemical composition of PM2.5 is essential, since chemical substances not only play a crucial role in toxicity but also could be employed as a fingerprint to identify its origin [6].
PM2.5 is constituted as a complex mixture of many different chemical substances resulting from distinct origin, either natural or anthropogenic, and from both primary and secondary particles with diverse effects on human health. Because diverse sources and multiple atmospheric processes are involved in the formation of PM2.5, its chemical characterization must be based on simultaneous chemical analysis. Since occurrence of inorganic ions and heavy metals is due to multiple atmospheric routes, and many of them are primarily present in fine particles [7,8], these are very frequently analyzed to identify sources of PM2.5. In PM2.5, sulfate, nitrate and ammonium are the more abundant ionic species [9]; these can also indicate contribution either by direct emission or atmospheric reactions due to photochemical processes via gas-particle reactions involving their oxygenated precursors (NO and SO2) [10,11,12]. Their occurrence in the urban environment can influence bioavailability of metals and exposure to fine particles may increase deposition of toxic compounds in the lungs [13,14]. Conversely, trace metals are minor components, and their origin is mainly by direct emission, either anthropogenic or/and geological [15]. With respect to their toxicity, transition metals such as Fe and Cu contribute to the oxidative capacity of PM [16]. Indeed, the ferrous ions in particle matter (PM) play an important role in the generation of hydroxyl radicals [17], a reactive oxygen species (ROS) that act synergistically with other PM–related chemical species. They can damage membrane lipids, proteins and DNA, which can alter respiratory immune responses in exposed individuals [18] and result in cell death via either necrotic or apoptotic processes and eventually cause and/or aggravate lung diseases [19]. Moreover, the element Zn has shown correlation with pulmonary inflammation by inhalation toxicology studies using animal models [20], and those elements with the lowest atmospheric concentration, such as Cd, Co, Cr, Ni and Pb, are known to be animal or human carcinogens [21].
The Metropolitan Zone of Guadalajara (MZG) that comprises Guadalajara City is located in the Atemajac valley in the western Mexican territory and has the second largest population in Mexico with around 4.4 million inhabitants in an urban area of about 2734 km2 [22]. Because the industry and vehicular traffic activities have rapidly risen from the nineties, the city of Guadalajara currently experiences a high stress on the environment, particularly in urban and peri-urban areas. There are frequent episodes of poor air quality in its urban area due to high atmospheric concentrations of ozone and particulate matter exceeding the Mexican 24-h standards, mainly occurring during dry seasons [23]. Therefore, the identification of emission sources is essential to finding effective methods to control exposure to air pollutants [24]. In addition, this can contribute to a better understanding of their formation mechanism in urban areas. So far, the earliest studies undertaken to identify sources suggest that PM2.5 in Guadalajara results from a mixture of anthropogenic and biogenic sources [25,26,27,28]. However, analysis of information on how particles are specifically emitted and how they respond to variations in their environment during the warm dry season is scarce.
Hence, the present study aims, with a short and intensive campaign, to identify the potential emission sources of PM2.5 collected at a downtown site and an urban site in Guadalajara City, based on spatial variation and the elemental and inorganic ions composition analysis during a dry season.

2. Methods

2.1. Monitoring Sites and Meteorological Conditions

The PM2.5 measurements were made on the flat roofs of two local health facilities: Centro (CEN), situated in the downtown, and Miravalle (MIR), located to the southwest in the Metropolitan Zone of Guadalajara (Figure 1). Both sites have atmospheric monitoring stations operated by the Jalisco State Government. The meteorological parameters used in this study were obtained from those stations. Centro is an urban site with commercial and services activities and surrounded by heavily traveled paved curbed surface streets with light duty vehicles and heavy-duty diesel buses. In addition to infrastructure streets and similar types of vehicles as those traveling in Centro, Miravalle is located 100 m from a major arterial street with fast vehicular traffic and a rapid transport system for passengers, and is surrounded by dense residential areas and some industrial facilities. In addition, Miravalle is an urban site with nearby green areas and an inactive volcano, called Cerro del Cuatro, about 270 m above surrounding ground level, located to the south-southwest (~2 km).
Figure 1. Locations of the sampling sites, CEN (Centro) and MIR (Miravalle).
Figure 1. Locations of the sampling sites, CEN (Centro) and MIR (Miravalle).
Atmosphere 06 01834 g001
During the sampling period (May 25 to June 6, 2009), the climate presented dry–warm characteristics and moderate winds. While in Miravalle the wind speed ranged from 0.1–9.1 m·s−1, in the Centro station it was between 0.1–5.5 m·s−1. The relative humidity (RH) ranged 11%–82% and 16%–88% at Centro and Miravalle, respectively. In both, the temperature range was 17 °C–33 °C. It was observed that the wind came from the west and west-southwest at the CEN and MIR sites, respectively (Figure 2).
Figure 2. Wind roses during the study period in CEN (a) and MIR (b) sites. Wind speed (m/s): ≥3.6, 2.1–3.6 and 0.5–2.1.
Figure 2. Wind roses during the study period in CEN (a) and MIR (b) sites. Wind speed (m/s): ≥3.6, 2.1–3.6 and 0.5–2.1.
Atmosphere 06 01834 g002

2.2. Sampling and Chemical Analysis

In order to carry out the chemical characterization of PM2.5, the samples were obtained every third day using a Partisol 2300 sampler (Rupprecht and Patashnick Co.). The particles were collected simultaneously for 24 h (12:00–12:00) at 16.6 L·min−1 flow on Nylon (MAGNA) membrane filters and at 10 L·min−1 flow on PTFE (PALL) discs (47 mm diameter and 0.2 µm pore size) for ions and elements analysis, respectively. The respective field and laboratory blanks were included daily in each individual sample set. The filters were conditioned and stabilized under controlled relative humidity (45 ± 5%) and temperature (about 22 °C) before and after the sampling for about 24 h. The concentrations of PM2.5 in ambient air (µg·m−3) were obtained from the ratio of the particle weight on the PTFE filter to its corresponding air sampling volume drawn through a cartridge filter holder corrected to EPA´s [29] standard temperature and pressure (25 °C and 760 mm Hg). The mass of each filter, with and without samples, was accurately measured in triplicate on a micro analytical balance SE2F (Sartorius) with a readability of 0.1 µg. Only mass averaged measurements with a repeatability less than 0.01% were included. As the mass of particles was validated and successfully recorded, filters were put in Petri dishes and stored in polyethylene zip-lock bags at ~5 °C until chemical analysis.
The details of the samples’ chemical analysis are described in Saldarriaga et al. [27] and Hernández et al. [28]. Briefly, for the analysis of metals, the PTFE filters were extracted in an ultrasonic bath for 3 h at about 60 °C–70 °C, using 50 mL of HNO3–HCl (2.6:0.9 M). The determination of the elements was carried out by ICP-MS equipment (ELAN Model 6100, Perkin Elmer, USA). For the quantification a multicomponent calibration curve was used for Pb, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Sb, Se, Sr, Ti and Zn with determination coefficients (r2) greater than 0.999, performed on a range of 1.0 to 100 ng·mL−1. The concentrations of the elements in real samples were corrected with blanks and the recoveries (80%–120%) obtained by extraction from SRM 1648 (NIST) [27]. The ion analysis was performed with the Nylon filters; samples were extracted with Milli-Q water (18.2 MΩ) in an ultrasonic bath (Branson 5510) for 1 h. The aqueous extracts were passed through a nylon micropore membrane (0.45 μm diameter) and the ionic chemical species were separated and subsequently identified by an ion chromatographer (IC) 861-Advanced Compact with conductivity detector (Metrohm). The anions (SO42− , NO3 , Cl , PO43− and NO2) were analyzed by chemical suppression with a Metrosep A Supp5—150 column (Metrohm); the mobile phase used was a carbonate solution of sodium–sodium bicarbonate (8.0:4.0 mM). The cations (Na+, NH4+, K+, Ca2+ and Mg2+) were determined without chemical suppression in a Metrosep C2_150 (Metrohm) column; the mobile phase was a solution of tartaric–dipicolinic acid (4.0:0.75 mM). For quantification of all species, calibration curves were performed at a concentration ranging 0.0625–10 μg·mL−1 and with correlations coefficients (r2) also greater than 0.999.

2.3. Statistical Analysis

The normality of data per site was determined using the Shapiro-Wilk test. For the nonparametric and more robustness tests, the Mann-Whitney U and the Spearman correlation coefficient were employed to make comparisons between sites and for the evaluation of association between variables, respectively. These were only applied when at least three observations were obtained and validated. In addition to statistical analysis, the simple linear least squares regression was performed for the presence of neutralizing events between ions. All tests were conducted using the STATISTICS 6 software.

3. Results and Discussions

3.1. PM2.5 Levels

The epidemiological evidence has shown widely adverse effects of fine PM following both short-term and long-term exposures [30,31]. The results found in this study indicated that the urban population in Guadalajara was exposed to short–term PM2.5 concentrations highly hazardous to health. Although the PM2.5 Mexican ambient quality standard (65 µg·m−3) was only exceeded once (Table 1), almost all individual PM2.5 concentrations measured (99%) exceeded the WHO Air quality guidelines [32] for that air pollutant (25 µg·m−3 24-hour mean). For comparison, the PM2.5 average atmospheric concentrations in Guadalajara were higher than those in the Valley of Mexico (29 µg·m−3) and slightly higher than the ones found for the Monterrey (34 µg·m−3) Metropolitan Areas [33], which are Mexico´s first and third biggest urban zones, respectively. Nevertheless, spatial variation must also be taken into account before emission control actions, since the PM2.5 average air concentrations ± standard deviation found in Miravalle (58.0 ± 13.0 µg·m−3) were, on average, higher than those recorded in the Centro site (39.3 ± 12.0 µg·m−3). Saldarriaga-Noreña et al. [27] and Limon-Sanchez [34] similarly observed this spatial trend in May–Jun 2007 and 2008 in Guadalajara, indicating that, over that period, there has not been an effective action to mitigate this air pollution issue.
Since meteorological conditions reported by both monitoring stations were similar, it clearly shows that the high spatial variation could be attributed to differences between the emission sources in each study site. Thus, in addition to vehicular traffic intensity, in Miravalle those highest concentrations of PM2.5 could be attributed to the larger resuspension of dust from bare green areas surrounding the site during the dry season (Figure 1). The wind direction suggested emissions transport from the southwest. What most likely contributed to the ambient levels of PM2.5 found in Miravalle was either resuspended particles from the inactive volcano area located on this trajectory or the regional or long–range transport of air pollutants that traveled from areas situated to the southwest and southeast.
Table 1. PM2.5 (μg·m−3) and trace metals concentrations (ng·m−3) in Centro and Miravalle sites.
Table 1. PM2.5 (μg·m−3) and trace metals concentrations (ng·m−3) in Centro and Miravalle sites.
Cu3107.016.9108.889.2–122.9 1 **----
Ni 1 *----24.0--3.4–4.5
* 6.9 ng·m−3; ** 33 ng·m−3; n: sample size; SD: standard deviation; n.d.: not detected.

3.2. Metals in PM2.5

The elemental analysis was performed for 14 metals (Table 1). In both sites, iron was the element most abundance in the PM2.5. In the Centro site, Fe accounts for 59.8% of total elemental mass, followed by Cu (15.6%), Mg (9.5%) and Zn (5.9%), while in Miravalle it was 72.2%, followed by Mg (11.4%) and Zn (3.3%). The other metals account for 9.1% at Centro and 9.4% at Miravalle or sometimes were not quantified. The environmental levels of trace metals are of the same order of magnitude as those already reported in the earliest studies [27]. It is a concern to health, since the most abundant elements are heavy metals characterized by their toxicity.
Thus, the characterization and identification of potential sources of trace elements within the fraction of PM2.5 in the Guadalajaran atmosphere could provide scientific evidence for setting up an air control strategy to decrease health risks due to inhalation of suspended particles. The most abundant species indicated that both sampling sites have a mixture of natural and anthropogenic sources, since Fe and Mg are primarily crustal elements, while Zn and Cu are primarily anthropogenic elements [35]. Spatial variation analysis by the Mann-Whitney test showed that the contribution from natural sources to PM2.5 in the Miravalle site could be more important than anthropogenic ones, since the medians of crustal elements [36], such as Fe, Mg and Mn, were found to be significantly (p < 0.05) higher or higher (Ti) only in the Miravalle site. Close in proximity to Miravalle, surfaces devoid of vegetation may be one of the possible causes of high levels of particles and anthropogenic elements such as Fe and Mg at this site. On the other hand, the Centro site seems to have a more important contribution from anthropogenic sources because the median concentration of primarily anthropogenic Zn and two elements (Cd and Se) that are considered as partially anthropogenic [37] were greater here than in Miravalle (Table 1), although differences were not significant (p > 0.05). It might be due to the fact that the Centro site has a higher traffic intensity. The abundance of elemental species and the geological and anthropogenic origin coincides with those results previously found in 2007 at the same sites [27], including the atmospheric mean concentrations.
The analysis of potential sources contributing to metals in PM2.5 at both sites was based on the principle that the degree to which the trace elements are enriched or reduced in aerosols is related to a specific source. That Enrichment Factor (EF) is frequently used [38,39] and is a reliable analysis tool to determine the impact of the type of emission sources on the elemental composition of the particles. The estimation of EF is based on the average abundances of the elements in geological material. Iron is suggested to be used as a reference element [40]. The following expression (Equation (1)), proposed by Taylor [40], was used to calculate the EF:
EF = (Cxp/Cp)/(Cxc/Cc)
where Cxp and Cp are the concentrations of trace metal "x" and Fe in the aerosol, respectively, and Cxc and Cc are their average concentrations in soil. It has been established that a value of EF < 10 is an indicator of trace metal from the soil; if it is between 10–100, it is a natural and anthropogenic mixture. In contrast, a value of EF > 100 is considered to be of an anthropogenic origin [41,42].
The EF patterns were very similar at the two sampling sites, indicating that both non-crustal and crustal emissions are contributing to mass of PM2.5. The EF analysis (Table 2) showed that atmospheric concentrations of Fe, Mg, Mn, Sr and Ti found in PM2.5 are likely from natural sources (EF < 10). Furthermore, it is indicated that Cr and Zn may come from natural and anthropogenic sources (10 > EF < 100) and Se, Cd, Sb and Cu are mainly from anthropogenic sources (EF > 100). Most elements from anthropogenic sources were more highly enriched in Centro than those found in the Miravalle site, suggesting that the Centro site is being more impacted by non-crustal pollution emissions than Miravalle. The higher enrichment of elements in Centro by non-crustal sources could be explained by either industrial activities, since Cd comes from metallurgical processes [43], or traffic, because Zn and Pb are markers of vehicular emissions [44]. In urban areas, road traffic (diesel engines and brake wear) could be the most important source of Cu [45]. Conversely, an earlier study suggested that geological sources significantly influenced the generation of PM2.5 as much in Miravalle as they did in Centro [27].
Table 2. Estimated values for EF.
Table 2. Estimated values for EF.
Fe *0.10.1
* EF calculated with crustal concentration of Ca; n.c.: not calculated.

3.3. Potential Sources of Ionic Species in PM2.5

In both sampling sites, nitrate (NO3), sulfate (SO42−) and ammonium (NH4+) were the dominant inorganic ions species followed by Ca2+, K+, Cl (Table 3). The environmental levels of inorganic species are of the same order of magnitude as those already reported in an earlier study [28]. The statistical analysis, via the Mann-Whitney U test, showed that the higher median concentration of NO3 was in Miravalle. This is unlike the sulfate and ammonium species that showed similar median concentrations between sites (p > 0.05).
Table 3. Atmospheric concentrations (µg·m−3) for ionic species.
Table 3. Atmospheric concentrations (µg·m−3) for ionic species.
SiteMeanStandard DeviationMedianMinimumMaximum
In Miravalle, nitrate accounts for 68.2%, followed by sulfate (11.9%) and ammonium (11.9%) of the total mass of inorganic ionic species. In Centro, nitrate account for 57.3%, followed by sulfate (17.1%) and ammonium (14.5%). Overall, while the spatially similar abundance (Figure 3) indicated likely common sources, the most abundant anions showed the important role that secondary sources played in the chemical composition of PM2.5. This is due to oxidation processes in the atmosphere that mainly form in the particle phase involving their directly emitted precursors, nitrogen oxides (NOx), sulfur dioxide (SO2) and ammonia (NH3) [46]. However, the order followed by these major inorganic ions and the urban characteristics of the sites suggested that the contribution of vehicular emission to formation of nitrate is also important and substantial. Because a significant portion of nitrate came from the atmospheric conversion of nitrogen oxides (NOx) and ammonia (NH3) [47], the high emissions of nitrogen oxides from heavy traffic in the urban environment could enhance the formation of nitrate in both sites. In addition, vehicle emissions of NOx and local combustion processes have been suggested as the biggest sources of nitrate in urban areas [48].
Figure 3. Relative contributions of ionic species to PM2.5 in CEN (a) and MIR (b).
Figure 3. Relative contributions of ionic species to PM2.5 in CEN (a) and MIR (b).
Atmosphere 06 01834 g003
Furthermore, higher NO3 mass than SO42− suggested that the influences of motor vehicle emissions exceed those from coal combustion [49]. In this study, the average mass ratio (NO3/SO42−) at the Centro and Miravalle sites was 3.3 and 5.8, respectively. The high mass ratios indicated that mobile sources predominated significantly over stationary sources at both sites. These measured ratios were similar to those reported for urban areas such as Guangzhou (3.4–10.0), China [50] and for the city of Los Angeles (~2.0). The latter results emphasize that such findings may be due to no coal being used in this area [51]. These results were higher than the mass ratio observed for the city of Philadelphia (0.9), USA [52], which is due to that city having power plants that use coal as fuel. Nevertheless, the order of the less abundant ions Ca2+ > K+ > Cl also indicated a contribution to particles from natural sources either by geological origin or burning biomass, which could be attributed to the presence of Ca2+ and K+, respectively [53,54]. Therefore, the highest atmospheric concentration of Ca2+ in Miravalle could have resulted from dust resuspension due to surfaces being devoid of vegetation surrounding this sampling site, a frequent occurrence in the dry season. Conversely, higher K+ concentrations in Centro could have come from forest fires that occurred during the sampling period in the Primavera Forest located west of Guadalajara [55]. It was further noted that, during the sampling period, predominant westerly winds were observed, supporting the hypothesis that the K+ concentration could have been transported from the forest into the city.
The possible chemical forms of the ionic species were suggested by bivariate correlations with all the anions and cations analyzed. The correlation coefficients can be observed in Table 4. For Miravalle NH4+ with K+ and SO42− correlated significantly (p < 0.05), while in Centro SO42− and NO3 correlated with NH4+. This indicated that compounds such as (NH4)2SO4 and K2SO4 can coexist in Miravalle, while in Centro (NH4)2SO4 and NH4NO3 are possible [56]. For the Centro site, a good correlation was observed between SO42− and NO3 (0.76), which can likely be attributed to a similarity in formation conditions either from a shared emission source or a chemical conversion of their precursors through atmospheric processes [57].
Table 4. Correlation among inorganic ions (bold correlations are significant at p < 0.05).
Table 4. Correlation among inorganic ions (bold correlations are significant at p < 0.05).
To evaluate the acidic nature of particles, a balance of ions was realized. Figure 4 shows the sum of cations plotted versus the sum of anions for each one of the sites sampled during the period of study (µeq·m−3). In Centro, the slope < 1.0 indicated that the concentration of anions was higher than that of the cations. Thus, those atmospheric particles had acidic properties during this sampling period. These results are consistent with those previously reported [28] for the Centro site in 2007, taking into account the same ionic species, while in Miravalle a slope of about 1.0 (1.08) was obtained, indicating neutralization processes, which is different than that observed during a previous study [28]. Thus, there were enough cations to neutralize the sulfate and nitrate present in the Miravalle environment, which likely originated either by contribution of additional cations from resuspended particles (Ca2+, Mg2+) or from being buffered by the higher average concentrations of NH4+ found in Miravalle [58], which were almost two-fold of that measured in Centro (Table 4). Since NH4+ formation on particles responds to variations in environmental conditions and availability of precursors [59], the similar atmospheric conditions found in Centro and Miravalle during the study suggested that the highest average atmospheric concentration of ammonium in Miravalle could be controlled by factors other than temperature and relative humidity. Therefore, there could be a contribution by secondary particles transported from traveled areas situated to the southeast; although the volcanic hill is a geographic barrier for the air mass from that direction (southwest), its elevation and the geography of the area could be causing some turbulence and channeling of winds near the study area [34].
Figure 4. Ions balances for CEN (a) and MIR (b).
Figure 4. Ions balances for CEN (a) and MIR (b).
Atmosphere 06 01834 g004

4. Conclusions

The results of this study suggested that anthropogenic and natural sources influenced the measured PM2.5 in the Centro and Miravalle sites during the short warm dry season campaign realized in Guadalajara, Mexico. In addition to spatial variation, the chemical characterization of PM2.5 allowed us to identify and distinguish some of the main emission sources contributing to particles in each site in the warm dry season in Guadalajara. The enrichment factor analysis indicated that road traffic mainly contributed to the PM2.5 of Centro, and the highest abundance of K+ suggested that biomass burning is an important source from the Primavera Forest located to the west. Despite the ratio (NO3/SO42−) indicating that the influences of motor vehicle emissions exceed those from the coal combustion in both sites, in Miravalle the resuspended particles from an inactive volcano (Cerro del Cuatro) to the southwest was suggested as significantly contributing to the mass of PM2.5 and could have caused neutralization processes by a higher incorporation of cations on particles. Additionally, PM2.5 at the Miravalle site apparently undergoes an impact from secondary particles of ammonium transported from areas located to the southeast, favored by a channeled-wind effect caused by elevations located to the southwest. Therefore, actions to be taken must focus mainly on both vehicular activity to reduce the emission of fine particles and undertaking campaigns of reforestation in the southwest of Guadalajara. In addition, for future studies the sampling must be seasonally extended and include analysis of sources based on other chemical species such as organic components.


The authors would like to express their appreciation to Secretaría del Medio Ambiente para el Desarrollo Sustentable del Estado de Jalisco (SEMADES) and Universidad Autónoma de Guadalajara for allowing the installment of the equipment in their locations. Special thanks go to Silvia Montiel Palma (UAEM), who provided valuable assistance in organizing maps for this paper, and to Sandra Daniela Bravo (CIATEJ), Rosalva Cuevas (CIATEJ) and Ma. Gregoría Medina Píntor (UAEM) for their valuable assistance in laboratory analysis.

Author Contributions

All authors contributed equally to this work.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Englert, N. Fine particles and human health—A review of epidemiological studies. Toxicol. Lett. 2004, 149, 235–242. [Google Scholar] [CrossRef] [PubMed]
  2. Kappos, A.D.; Bruckmann, P.; Eikmann, T.; Englert, N.; Heinrich, U.; Höppe, P.; Koch, E.; Krause, G.H.M.; Kreyling, W.G.; Rauchfuss, K.; et al. Health effects of particles in ambient air. Int. J. Hyg. Environ. Health 2004, 207, 399–407. [Google Scholar] [CrossRef] [PubMed]
  3. Pope, C.A., III; Burnett, R.T.; Thun, M.J.; Calle, E.E.; Krewski, D.; Ito, K.; Thurston, G.D. Lung cancer, Cardiopulmonary Mortality, and long-term exposure to fine particulate air pollution. JAMA 2002, 287, 1132–1141. [Google Scholar] [CrossRef] [PubMed]
  4. Kampa, M.; Castanas, E. Human Health effects of air pollution. Environ. Pollut. 2007, 151, 362–367. [Google Scholar] [CrossRef] [PubMed]
  5. Ramgolam, K.; Favez, O.; Cachier, H.; Gaudichet, A.; Marano, F.; Martinon, L.; Baeza-Squiban, A. Size-partitioning of an urban aerosol to identify particle determinants involved in the proinflammatory response induced in airway epithelial cells. Part. Fibre Toxicol. 2009, 6, 1–12. [Google Scholar] [CrossRef] [PubMed]
  6. de Kok, T.M.C.M.; Driece, H.A.L.; Hogervorst, J.G.F.; Briedé, J.J. Toxicological assessment of ambient and traffic–related particulate matter: A review of recent studies. Rev. Mutat. Res. 2006, 613, 103–122. [Google Scholar] [CrossRef] [PubMed]
  7. Cabada, J.C.; Rees, S.; Takahama, S.; Khlystov, A.; Pandis, S.; Davidson, C.I.; Robinson, A.L. Mass size distributions and size resolved chemical composition of fine particulate matter at the Pittsburgh supersite. Atmos. Environ. 2004, 38, 3127–3141. [Google Scholar] [CrossRef]
  8. Pan, Y.; Tian, S.; Li, X.; Sun, Y.; Li, Y.; Wentworth, G.R.; Wang, Y. Trace elements in particulate matter from metropolitan regions of Northern China: Sources, concentrations and size distributions. Sci. Total Environ. 2015, 537, 9–22. [Google Scholar] [CrossRef] [PubMed]
  9. Young-Ji, H.; Tae-Sik, K.; Hakap, K. Ionic constituents and source analysis of PM2.5 in three Korean cities. Atmos. Environ. 2008, 42, 4735–4746. [Google Scholar]
  10. Sitaras, I.E.; Siskos, P.A. The role of primary and secondary air pollutants in atmospheric pollution: Athens urban area as a case study. Environ. Chem. Lett. 2008, 6, 59–69. [Google Scholar] [CrossRef]
  11. Sharma, M.; Kishore, S.; Tripathi, S.N. Role of atmospheric ammonia in the formation of inorganic secondary particulate matter: A study at Kanpur, India. J. Atmos. Chem. 2007, 58, 1–17. [Google Scholar] [CrossRef]
  12. Bari, A.; Ferraro, V.; Wilson, L.R.; Luttinger, D.; Husain, L. Measurements of gaseous HONO, HNO3, SO2, HCl, NH3, particulate sulfate and PM2.5 in New York, NY. Atmos. Environ. 2003, 37, 2825–2835. [Google Scholar] [CrossRef]
  13. Ghio, A.J.; Stoneheurner, J.; McGee, J.K.; Kinsey, J.S. Sulfate content correlates with iron concentration in ambient air pollution particles. Inhal. Toxicol. 1999, 11, 293–307. [Google Scholar] [PubMed]
  14. Friedlander, S.K.; Yeh, E.K. The submicron atmospheric aerosols as a carrier of reactive chemical species: Case of peroxide. Appl. Occup. Environ. Hyg. 1998, 13, 416–420. [Google Scholar] [CrossRef]
  15. Wang, X.; Sato, T.; Xing, B.; Tamamura, S.; Tao, S. Source identification, size distribution and indicator screening of airborne trace metals in Kanazawa, Japan. J. Aerosol Sci. 2005, 36, 197–210. [Google Scholar] [CrossRef]
  16. Clarke, R.W.; Coull, B.; Reinisch, U.; Catalano, P.; Killingsworth, C.R.; Koutrakis, P.; Kavouras, I.; Murthy, G.G.; Lawrence, J.; Lovett, E.; et al. Inhaled concentrated ambient particles are associated with hematologic and bronchoalveolar lavage changes in canines. Environ. Health Perspect. 2000, 108, 1179–1187. [Google Scholar] [CrossRef]
  17. Valavanidis, A.; Fiotakis, K.; Bakeas, E.; Vlahogianni, T. Electron paramagnetic resonance study of the generation of reactive oxygen species catalysed by transition metals and quinoid redox cycling by inhalable ambient particulate matter. Redox Rep. 2005, 10, 37–51. [Google Scholar] [CrossRef] [PubMed]
  18. Carter, J.D.; Ghio, A.J.; Samet, J.M.; Devlin, R.B. Cytokine production by human airway epithelial cells after exposure to an air pollution particles is metal-dependent. Toxicol. Appl. Pharm. 1997, 146, 180–188. [Google Scholar] [CrossRef] [PubMed]
  19. Brown, R.K.; Wyatt, H.; Price, J.F.; Kelly, F.J. Pulmonary dysfunction in cystic fibrosis is associated with oxidative stress. Eur. Respir. J. 1996, 9, 334–339. [Google Scholar] [CrossRef] [PubMed]
  20. Saldiva, P.H.N.; Clarke, R.W.; Coull, B.A.; Stearns, R.C.; Lawrence, J.; Murthy, G.G. Lung inflammation induced by concentrated ambient air particles is related to particle composition. Am. J. Respir. Crit. Care Med. 2002, 165, 1610–1617. [Google Scholar] [CrossRef] [PubMed]
  21. Agency for Toxic Substances and Disease Registry. Toxicological profile information sheet 2003. Available online: (accessed on 15 July 2015).
  22. Instituto Nacional de Estadística, Geografía e Informática (INEGI). Available online: (accessed on 15 May 2015).
  23. Sistema de Monitoreo Atmosférico de Jalisco (SIMAJ). Available online: (accessed on 9 July 2015).
  24. PROAIRE 1997–2001. Available online: (accessed on 17 June 2015).
  25. Hernández-Mena, L.; Murillo-Tovar, M.A.; Ramírez-Muñíz, M.; Colunga-Urbina, E.; de la Garza-Rodríguez, I.; Saldarriaga-Noreña, H. Enrichment Factor and Profiles of Elemental Composition of PM2.5 in the City of Guadalajara, Mexico. Bull. Environ. Contam. Toxicol. 2011, 87, 545–549. [Google Scholar] [CrossRef] [PubMed]
  26. Saldarriaga-Noreña, H.; Hernández-Mena, L.; Murillo-Tovar, M.A.; López-López, A.; Ramírez-Muñíz, M. Elemental contribution to the mass of PM2.5 in Guadalajara City, Mexico. Bull. Environ. Contam. Toxicol. 2011, 86, 490–494. [Google Scholar] [CrossRef] [PubMed]
  27. Saldarriaga-Noreña, H.; Hernández-Mena, L.; Ramírez-Muñíz, M.; Carbajal-Romero, P.; Cosío-Ramírez, R.; Esquivel-Hernández, B. Characterization of trace metals of risk to human health in airborne particulate matter (PM2.5) at two sites in Guadalajara, Mexico. J. Environ. Monitor. 2009, 11, 887–894. [Google Scholar] [CrossRef] [PubMed]
  28. Hernández, M.L.; Saldarriaga, N.H.; Carbajal, R.P.; Cosío, R.R.; Esquivel, H.B. Ionic species associated with PM2.5 in the City of Guadalajara, Mexico during 2007. Environ. Monit. Assess. 2010, 161, 281–293. [Google Scholar] [CrossRef] [PubMed]
  29. Environmental Protection Agency. Available online: (accessed on 6 June 2015).
  30. Dockery, D.W. Health effects of particulate air pollution. Ann. Epidemiol. 2009, 19, 257–263. [Google Scholar] [CrossRef] [PubMed]
  31. Polichetti, G.; Cocco, S.; Spinalia, A.; Trimarcoa, V.; Nunziatab, A. Effects of particulate matter (PM10, PM2.5 and PM1) on the cardiovascular system. Toxicology 2009, 261, 1–8. [Google Scholar] [CrossRef] [PubMed]
  32. World Health Organization. Air quality Guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide. Global up date 2005. Summary of risk assessment. Available online: (accessed on 10 July 2015).
  33. Cuarto Almanaque de datos y tendencias de la calidad del aire en 20 ciudades mexicanas. Available online: (accessed on 1 July 2015).
  34. Limon-Sanchez, M.T.; Carvajal-Romero, P.; Hernández-Mena, L.; Saldarriaga-Noreña, H.; López-López, A.; Cosío-Ramírez, R.; Arriaga-Colina, J.L.; Smith, W. Black carbón in PM2.5, data from two urban sites in Guadalajara, Mexico during 2008. Atmost. Pol. Res. 2011, 2, 358–365. [Google Scholar] [CrossRef]
  35. Odabasi, M.; Muezzinoglu, A.; Bozlaker, A. Ambient concentrations and dry deposition fluxes of trace elements in Izmir, Turkey. Atmos. Environ. 2002, 36, 5841–5851. [Google Scholar] [CrossRef]
  36. Haritash, A.K.; Kaushik, C.P. Assessment of seasonal enrichment of heavy metals in respirable suspended particulate matter of a sub-urban Indian city. Environ. Monit. Assess. 2007, 128, 411–420. [Google Scholar] [CrossRef] [PubMed]
  37. Fukai, T.; Kobayashi, T.; Sakaguchi, M.; Aoki, M.; Saito, T.; Fujimori, A.; Haraguchi, H. Chemical characterization of airborne particulate matter in ambient air of Nagoya, Japan, as studied by the multielement determination with ICP-AES and ICP-MS. Anal. Sci. 2007, 23, 207–213. [Google Scholar] [CrossRef] [PubMed]
  38. Guor-Cheng, F.; Yuh-Shen, W.; Shih-Yu, C.; Shih-Han, H.; Jui-Yeh, R. Size distributions of ambient air particles and enrichment factor analyses of metallic elements at Taichung harbor near the Taiwan Strait. Atmos. Res. 2006, 81, 320–333. [Google Scholar]
  39. Gao, Y.; Nelsonb, E.D.; Fielda, M.P.; Dinga, Q.; Lia, H.; Sherrella, R.M.; Gigliottib, C.L.; Van Ryb, D.A.; Glennb, T.R.; Eisenreich, S.J. Characterization of atmospheric trace elements on PM2.5 particulate matter over the New York–New Jersey harbor estuary. Atmos. Environ. 2002, 36, 1077–1086. [Google Scholar] [CrossRef]
  40. Taylor, S.R. Abundance of chemical elements in the continental crust: A new table. Geochim. Cosmochim. Acta 1964, 28, 1273–1285. [Google Scholar] [CrossRef]
  41. Chester, R.; Nimmo, M.; Alarcon, M.; Saydam, C.; Murphy, K.J.T.; Sanders, G.; Corcoran, P. Defining the chemical character of aerosols from the atmosphere of the Mediterranean Sea and surrounding regions. Oceanol. Acta 1993, 16, 231–246. [Google Scholar]
  42. Herut, B.; Nimmo, M.; Medway, A.; Chester, R.; Krom, M.D. Dry atmospheric inputs of trace metals at the Mediterranean coast of Israel (SE Mediterranean): Sources and fluxes. Atmos. Environ. 2001, 35, 803–813. [Google Scholar] [CrossRef]
  43. Pacyna, J.M. Source inventories for atmospheric trace metals. In Atmospheric Particles; IUPAC series on analytical and physical chemistry of environmental systems; Harrison, R.M., van Grieken, R.E., Eds.; Wiley: Chichester, UK, 1998; pp. 385–423. [Google Scholar]
  44. Huang, X.; Olmez, I.; Aras, N.K. Emissions of trace elements from motor vehicles: Potential marker elements and source composition profile. Atmos. Environ. 1994, 28, 1385–1391. [Google Scholar] [CrossRef]
  45. Rajšić, S.; Mijić, Z.; Tasić, M.; Radenković, M.; Joksić, J. Evaluation of levels and sources of trace elements in urban particulate matter. Environ. Chem. Lett. 2008, 6, 95–100. [Google Scholar] [CrossRef]
  46. Finlayson-Pitts, B.J.; Pitts, J.N. Upper and Lower Atmosphere: Theory, Experiments and Applications; Academic Press: San Diego, SD, USA, 2000; pp. 86–126. [Google Scholar]
  47. Seinfeld, J.H.; Pandis, S.P. Atmospheric Chemistry and Physics: from Air Pollution to Climate Change, 2nd ed.; John Wiley & Sons, INC: Hoboken, NJ, USA, 2006; pp. 33–38. [Google Scholar]
  48. Zhao, W.; Hopke, P.K.; Zhou, L. Spatial distribution of source locations for particulate nitrate and sulfate in the upper–midwestern United States. Atmos. Environ. 2007, 41, 1831–1847. [Google Scholar] [CrossRef]
  49. Arimoto, R.; Duce, R.A.; Savoie, D.L. Relationships among aerosol constitutes from Asia and the North Pacific During PEM-West A. J. Geophys. Res. 1996, 101, 2011–2023. [Google Scholar] [CrossRef]
  50. Yang, F.; Tan, J.; Zhao, Q.; Du, Z.; He, K.; Ma, Y.; Duan, F.; Chen, G.; Zhao, Q. Characteristics of PM2.5 speciation in representative megacities and across China. Atmos. Chem. Phys. 2011, 11, 5207–5219. [Google Scholar] [CrossRef]
  51. Kim, B.M.; Teffera, S.; Zeldin, M.D. Characterization of PM2.5 and PM10 in the south coast air basin of southern California: Part 1–Spatial variations. J. Air Waste Manag. Assoc. 2000, 50, 2034–2044. [Google Scholar] [CrossRef] [PubMed]
  52. Tolocka, M.P.; Solomon, P.A.; Mitchell, W.; Norris, G.A.; Gemmill, D.B.; Wiener, R.W.; Vanderpool, R.W.; Homolya, J.B.; Rice, J. East versus west in the US: chemical characteristics of PM2.5 during the winter of 1999. Aerosol Sci. Technol. 2001, 34, 88–96. [Google Scholar] [CrossRef]
  53. Na, K.; Cocker, D.R. Characterization and source identification of trace elements in PM2.5 from Mira Loma, Southern California. Atmos. Res. 2009, 93, 793–800. [Google Scholar] [CrossRef]
  54. Watson, J.G.; Chow, J.C. Source characterization of major emission sources in the Imperial and Mexicali Valleys along the US/Mexico border. Sci. Total Environ. 2001, 276, 33–47. [Google Scholar] [CrossRef]
  55. Comisión Nacional Forestal. Resumen Anual del reporte semanal 2009. Reportes semanales/esta- dísticos. Available online: (accessed on 15 July 2015).
  56. Khan, F.M.; Shirasuna, Y.; Hirano, K.; Masunaga, S. Characterization of PM2.5, PM2.5–10 and PM>10 in ambient air, Yokohama, Japan. Atmos. Environ. 2010, 96, 159–172. [Google Scholar] [CrossRef]
  57. Liu, G.; Li, J.; Wu, D.; Xu, H. Chemical composition and source apportionment of the ambient PM2.5 in Hangzhou, China. Particuology 2015, 18, 135–143. [Google Scholar] [CrossRef]
  58. Shen, Z.; Cao, J.; Arimoto, R.; Han, Z.; Zhang, R.; Han, Y.; Liu, S.; Okuda, T.; Nakao, S.; Tanaka, S. Ionic composition of TSP and PM2.5 during dust storms and air pollution episodes at Xi’an, China. Atmos. Environ. 2009, 43, 2911–2918. [Google Scholar] [CrossRef]
  59. Park, S.S.; Ondov, J.M.; Harrison, D.; Nair, N.P. Seasonal and shorter–term variations in particulate atmospheric nitrate in Baltimore. Atmos. Environ. 2005, 39, 2011–2020. [Google Scholar] [CrossRef]

Share and Cite

MDPI and ACS Style

Murillo-Tovar, M.A.; Saldarriaga-Noreña, H.; Hernández-Mena, L.; Campos-Ramos, A.; Cárdenas-González, B.; Ospina-Noreña, J.E.; Cosío-Ramírez, R.; Díaz-Torres, J.D.J.; Smith, W. Potential Sources of Trace Metals and Ionic Species in PM2.5 in Guadalajara, Mexico: A Case Study during Dry Season. Atmosphere 2015, 6, 1858-1870.

AMA Style

Murillo-Tovar MA, Saldarriaga-Noreña H, Hernández-Mena L, Campos-Ramos A, Cárdenas-González B, Ospina-Noreña JE, Cosío-Ramírez R, Díaz-Torres JDJ, Smith W. Potential Sources of Trace Metals and Ionic Species in PM2.5 in Guadalajara, Mexico: A Case Study during Dry Season. Atmosphere. 2015; 6(12):1858-1870.

Chicago/Turabian Style

Murillo-Tovar, Mario Alfonso, Hugo Saldarriaga-Noreña, Leonel Hernández-Mena, Arturo Campos-Ramos, Beatriz Cárdenas-González, Jesús Efren Ospina-Noreña, Ricardo Cosío-Ramírez, José De Jesús Díaz-Torres, and Winston Smith. 2015. "Potential Sources of Trace Metals and Ionic Species in PM2.5 in Guadalajara, Mexico: A Case Study during Dry Season" Atmosphere 6, no. 12: 1858-1870.

Article Metrics

Back to TopTop