SciELO - Scientific Electronic Library Online

vol.20 issue3Reduced in situ experimentation of the soil slip by effect of subsurface water flowVibration analysis system applied to fault detection in wind turbines author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand




Related links

  • Have no similar articlesSimilars in SciELO


Ingeniería, investigación y tecnología

Print version ISSN 1405-7743

Ing. invest. y tecnol. vol.20 n.3 México Jul./Sep. 2019  Epub Oct 15, 2019 


Geochemical characterization and spatial distribution of heavy metals from urban dust in Chetumal, Mexico

Caracterización geoquímica y distribución espacial de metales pesados del polvo urbano en Chetumal, México

José Gonzálo Zapata-Carbonell1

Francisco Bautista2

Jaime Rendón-Von Osten3

Luz del Carmen Lagunes-Espinoza4

David Jesús Palma-López5

Fredy Rubén Cejudo-Ruiz6

Avto Goguichaichvili7

Oscar Frausto-Martínez8

1Universidad de Quintana Roo, E-mail:

2Universidad Nacional Autónoma de México, Michoacán, Centro de Investigaciones en Geografía Ambiental, Laboratorio Universitario de Geofísica Ambiental, E-mail:

3Universidad Autónoma de Campeche, Instituto de Ecología, Pesquería y Oceanografía del Golfo de México, EPOMEX. E-mail:

4Colegio de Postgraduados, Campus Cárdenas, Tabasco. E-mail:

5Colegio de Postgraduados, Campus Cárdenas, Tabasco, E-mail:

6Universidad Nacional Autónoma de México, Michoacán, Instituto de Geofísica, Laboratorio Universitario de Geofísica Ambiental. E-mail:

7Universidad Nacional Autónoma de México, Michoacán, Instituto de Geofísica, Laboratorio Universitario de Geofísica Ambiental. E-mail:

8Universidad de Quintana Roo. E-mail:


The first diagnose of heavy metal (Cd, Cr, Cu, Fe, Mn, Ni and Pb) concentrations present in Chetumal, Mexico and its spatial distribution was carried out by analyzing 86 samples of urban dust through atomic absorption spectrophotometry. The assessment of the extent of pollution was undertaken by the use of the Mexican Residential Soil Guideline Values, the calculation of the contamination factor and the pollution load index. The results showed concentrations of heavy metals below the Mexican guidelines in the city, except for chromium and lead in a few samples. However, using the contamination factor the concentrations for chromium, lead and copper are exceeded in some samples. The map of pollution load index shows the areas requiring immediate attention from the decision makers.

Keywords: Contamination factor; spectrophotometry; pollution load index; geostatistics; indicator Kriging


El primer diagnóstico de concentraciones de metales pesados (Cd, Cr, Cu, Fe, Mn, Ni y Pb) presentes en Chetumal, México y su distribución espacial se realizó analizando 86 muestras de polvo urbano usando espectrofotometría de absorción atómica. La evaluación del alcance de la contaminación se realizó usando los Valores de la Norma Mexicana para Suelo Residencial (NMSR), el cálculo del factor de contaminación y el índice de carga contaminante. Los resultados mostraron concentraciones de metales pesados por debajo de las normas mexicanas, excepto para el cromo y plomo en unas pocas muestras. Sin embargo, usando los índices de contaminación los límites para cromo, plomo y cobre se exceden en varias muestras. El mapa del índice de carga contaminante muestra las áreas que requieren atención inmediata por parte de los tomadores de decisiones.

Descriptores: Factor de contaminación; espectrofotometría; índice de carga contaminante; geoestadística; indicador Kriging


In recent years, concerns about pollution levels of heavy metals in urban areas have risen, due to their relationship with cases of cancer, i.e. pulmonary, bronchial, among others, which are considered some of the main death causes in the U.S (Siegel et al., 2012) and the world (WHO, 2013).

The variety of sampled substrates used for heavy metal (HM) pollution assessments can include soil, as a measure of historical and former contamination; living organisms such as tree leaves, earthworms, lichens, etc. used as bio-monitors; suspended particular matters (PM10 and PM2.5) and urban dust as a measure of recent contamination (Bautista et al., 2011a; Aguilera et al., 2018; Delgado et al., 2019).

Urban dust is a heterogeneous mixture composed by combustion-related emissions, brake abrasion and tire wear particles (Adachi and Tainosho, 2004; Aguilera et al., 2018); weathering of paint, industrial emissions (Al-Khashman, 2004 and Morales et al., 2014); and other elements that get suspended and transported by air drafts to settle and mix with soil (Sánchez et al., 2015 and Cortés et al., 2015). These can then become harmful to humans due to its ease of being inhaled, ingested, or absorbed through skin (Donaldson et al., 2001; Cakmak et al., 2014 and Yann et al., 2014).

Chetumal has no record of former study related, therefore this study has aimed to obtain the first diagnosis of heavy metal contamination (Cd, Cr, Cu, Fe, Mn, Ni and Pb) in urban dust, assessment of the quantity of dust existent through the use of Mexican Residential Soil Guideline Values (MRSGV), calculation of contamination factors (CF) per metal and the pollution load index (PLI) for the metals mentioned in the latter part.

Methods and materials

Chetumal city is located southeast of Mexico, as the capital of Quintana Roo, it has 151,243 inhabitants (INEGI, 2010) and a number of motor vehicles close to 111,000 (INEGI, 2014). The state is mainly focused on touristic activities and very scarce industry (INEGI, 2016). The soil has generally been classified as Leptosol over limestone (Pacheco and Alonzo, 2003 and Bautista et al., 2011b).

Sampling in Chetumal was performed in May 2013 during the dry season, when particle mobility was considered greater. A systematic, homogenously distributed sampling was carried out with the idea of incorporating the greatest variation, as well as to be able to make a spatial analysis using geostatistical tools (Webster and Oliver, 1990; Aguilera et al., 2018; Delgado et al., 2019). Sampling covered homogeneously the urban area; 86 urban dust samples were collected. Each site was located the closest to the street intersection; logging in street names, observations, and coordinates using a GPS Garmin GPSmap 60C.

Sampling consisted on delimiting a 1 m2 surface at each site using a cotton string, then samples were swept and collected from the pavement (Wei and Yang, 2010; Aguilar-Reyes et al., 2011 and Bautista et al., 2011a; Aguilera et al., 2018). Samples were weighed, tagged and packed.

The samples were dried in the shade for two weeks, then ground and sieved through a 2 mm mesh and weighed (Aguilar-Reyes et al., 2011). The extraction was performed digesting 0.5 g of sample and 5 mL of HNO3 (CONC) in a MARS Xpress microwave CEM (USEPA, 2007a). For the heavy metal content, the atomic absorption spectrophotometry (AAS) technique (USEPA, 2007b) using a PERKIN-ELMER Analyst 700 spectrophotometer. Calibration curves were made with a standard IV multi-element Merck Millipore solution and HNO3 2% v/v. Dilutions being 100, 50, 30, 20, 15, 10 and 5 mg L-1. The calculated limit of detection was 0.0021 mg L-1.

Contamination indexes were calculated and used as a tool for contamination site and source location. The CF is the ratio between the heavy metal concentration and the background concentration in the area of interest (Tomlinson et al., 1980). Values below 1 indicate insignificant contamination in-situ, values from 1 to 3 show moderate contamination; from 4 to 6 considerable and >6 very high (Ihl et al., 2015).

The CF is calculated as follows (Tomlinson et al., 1980):

CF=CmSampleCmBackground (1)

Where Cm Sample represents the element concentration found in the sample and Cm Background is the natural metal content in the area of study. Cm Background values used were the lowest concentrations found in this study corresponding to sample P1, taking the following values: 23.8 mg kg-1 Pb; 21.4 mg kg-1 Cu; 13.3 mg kg-1 Cr; 2.5 mg kg-1 Cd; 21.5 mg kg-1 Ni; 76.7 mg kg-1Mn and 4240 mg kg-1 Fe. The PLI was calculated to merge the CF per metal of each sampled site (Chandrasekaran et al., 2015). The PLI is defined as “the n th root of the product of the n CF” (Bhuiyan et al., 2010):

PLI=CF1*CF2*CF3**CFnn (2)

A PLI equal to 0 indicates excellent quality, a value of 1 the presence of baseline concentrations of heavy metals, and above 1 means progressive degeneration of the quality (Tomlinson et al., 1980).

Results and discussion

The highest dust quantities were found in the central area of the city. The weighed dust in samples averaged 270±100 g m-2, going from 80 up to 820 g m-2. Published papers reporting dust quantities in Mexico are scarce, thus no comparison with other studies is possible. Regarding the exposition, chronic exposition to urban dust is as harmful as it is the exposition to very high heavy metal concentrations in dust (Cakmak et al., 2014).

In this regard, this study is one of the first reporting concentrations of heavy metal per area unit, among these: Pb (67.9±99.7 mg m-2), Cr (16.5±16.9 mg m-2), and Fe (3306±2889 mg m-2) and low quantities of Cu (28.1±61.5 mg m-2) and Mn (31.5±21.5 mg m-2) (Table 1). Particularly, Cr and Pb presented the highest per area unit in four samples (P7, P8, P12 and P13) located on the southeast part of Chetumal. As expected, the zone with governmental buildings (administrative downtown) contains the greatest quantity of dust, due to the presence of high-density traffic roads heading downtown. It is worth mentioning that the calculated means show a high variability, this may be due to the different HM sources.

Table 1: Descriptive statistics of concentration, amount, CF of heavy metals in urban dust. Variance (Var), standard deviation (SD), minimum (Min), maximum (Max), skewness (Sk), Kurtosis (Kt), contamination factor (CF) and Mexican legislation residential MRSGV (NOM) 

Heavy metals Mean Median Mode Var SD Min Max Sk Kt
Cd mg kg-1 3.8 3.6 3.5 0.7 0.9 1 9 2.6 14.8
mg m-2 1 11.5 - 0.4 0.6 0.3 3 3.4 15.9
CF 1 1 1 0.3 0.5 0 3 0.9 0.4
NOM 37 - - - - - - - -
Cr mg kg-1 65 52.2 - 7199 84.9 8 728 6.4 46.8
mg m-2 16.5 8.4 - 286 16.9 2.5 117 1.6 3.8
CF 5 4 3 41 6.4 1 55 6.4 46.6
NOM 280 - - - - - - - -
Cu mg kg-1 96 61.7 107 26223 161.9 7.4 1440 7 57.1
mg m-2 28 14.3 - 3782 61. 5 1.37 539 7.1 57.6
CF 5 3 3 57 7.5 0 67 7 56.8
Fe mg kg-1 11758 10360 - 3.4E+07 5834.5 130 27750 0.9 0.6
mg m-2 3307 37.7 - 8346321 2889 21 19820 4.2 19.3
CF 3 2 2 2 1.4 0 7 0.9 0.5
Mn mg kg-1 114.7 113.2 125.2 1466 38.3 0.75 229 0.2 0.9
mg m-2 31.5 24.6 - 462 21.5 0.12 134 2 5.6
CF 2 1 1 0.3 0.6 0 3 0.4 -0.4
Ni mg kg-1 37 35.3 33.9 91 9.5 19 106 4.6 32.2
mg m-2 10 2427.6 - 29 5.4 2.9 34 2.8 11.9
CF 2 2 2 0.2 0.5 1 5 2.6 21.9
NOM 1600 - - - - - - - -
Pb mg kg-1 257 158.6 - 157418 396.8 23.8 3396 6.2 47
mg m-2 68 0.8 - 9940 99.7 5.8 636 1.5 2.5
CF 11 7 5 279 16.7 1 143 6.3 86
NOM 400 - - - - - - - -

The concentrations of Cr, Cu, Pb and Fe are recognized as being of anthropic origin, that is to say contaminants, because they presented high values of standard deviation and are typically of non-Gaussian distribution. In contrast, heavy metal concentrations of natural origin, as Cd and Mn, have small standard deviations and a Gaussian distribution (Aguilera et al., 2018). In the case of Ni, some samples with high concentrations were found, which reveals contamination in some places (Table 1).

Notably, the average values of HM found in Chetumal do not exceed the MRSGV established by the NOM 147 for residential soils (Table 1); however, for samples P23 and P54, the limits of Pb (400 mg kg-1) were exceeded. These same samples show very high concentrations of total Cr, although the Mexican regulation only takes into account Cr (VI) concentrations in the MRSGV.

The Mexican regulations need to broaden the number of elements given in soil guideline values. Moreover, it is needed to establish in the legislation guideline values suitable for the heavy metal assessment in urban dust considering background values.

Cd and Mn were the heavy metals with the lowest contamination factor values, maps show areas with values close to 3 (Figure 1). Fe and Ni reached values greater than 6 of the contamination factor, these are considered high (Figure 2).

Figure 1: Maps of contamination factor of Cadmium and Manganese 

Figure 2: Maps of contamination factor of Iron and Nickel 

The analysis of contamination factor in metals such as Cr, Cu and Pb showed very high contamination levels with values up to 55, 67 and 143, respectively (Figures 3 and 4). For the case of Cu, 11 samples showed very high contamination, whereas Cr showed values of very high contamination in nine samples with the highest value in sample (P23). Finally, for Pb 51% (44 samples) showed CF>6, hence the city is considered as highly contaminated by Pb. For the case of Fe, only one sample (P82) showed a CF=7.

Figure 3: Maps of contamination factor of Chromium and Lead 

Figure 4: Maps of pollution load index and contamination factor of Cupper 

The average calculated PLI for the city was 3±0.9, showing that the overall sampled sites contain two-fold the background concentration of heavy metals of the area. Sample P54 expresses a value equal to 6.5 on the southeast of the city; this is the sample with the highest values in Cr and Pb (Figure 3). The probabilistic PLI map indicates that values greater than 0.8 are areas that exceed a value of 3 and are those that require immediate attention (Figure 4). If calculating the PLI can provide an idea of the pollution extent in an area (Tomlinson et al., 1980), it can also demonstrate the zones that require urgent attention. In this study it is shown that in the port terminal the higher PLI values were reached, so it is suggested that part of the contamination of the boats is in the urban dust, as was also reported by Cortés et al. (2015) for the case of the city of Ensenada. In conclusion to having found PLI values up to 3, it is very likely to find human health consequences in middle and long-term.

As mentioned by Padoan et al (2017) urban dust may be originated from either natural or anthropogenic activities. The former referring to natural weathering and the latter to wear and tear, caused by vehicle use, or inner combustion vehicles (Adachi and Tainosho, 2004).

Elements such as Fe may have been introduced by cargo trucks coming from rural areas rich in Vertisols and Luvisols (Kabata, 2011). Morever, for the cases of Pb and Cr, an often seen cause may be the weathering of leaded yellow road paint, which was observed in some samples. Some concentrations in Chetumal are comparable to those seen in streets of Plymouth, UK by Turner and Lewis (2018). Additionally, the deposition of atmospheric particles produced by car exhausts may also contribute to these concentrations. Finally, the origins of Cu have been tracked to brake dust (Adachi and Tainosho, 2004).

Since the zone with more abundant urban dust was located in the center of the city, two hypothesis can be proposed: the dust production is greater in this area or the high-density traffic in this area creates air drafts that accumulate the urban dust in only one site. This is debatable with studies of the air dynamics. Finally, for prevention it is recommended for the decision makers to plan strategically the urban transport routes, as well as the establishment of an urban dust-quality monitoring plan that will include some government guideline values. For mitigation, the implementation of buffer areas rich in clays might aid in the sequestration of cations contained in urban dust.

In agreement with Cortes et al. (2016), if we consider that "environmental pollution is the presence in the environment of any agent in places, forms and concentrations that can be harmful to the health, safety or well-being of the population", we can say that in this study we identified harmful agents, concentrations, amounts and polluted places, however, in future studies will be necessary the identification and evaluation of chemical forms of heavy metals, using techniques of sequential extraction and toxicity in the population (Bautista, 1999; Covelo et al., 2007).


Based on the residential soil guideline values proposed by the Mexican government, it can be concluded that there are signs of isolated sources of contamination in urban dust only; however, this conclusion is not completely representative given the lack of guideline values for urban dust. Also, considering the CF calculated, Chetumal has contamination problems with copper, chromium and lead in the south is the most polluted area. Preventive actions to counteract the air draft dynamics are strongly advised to avoid the increase in HM concentrations and mitigation actions are also advised to reduce the already high HM concentrations.


We would like to give a great thank you to the National Science and Technology Council (CONACYT) for the funding given to the project CB-2016-283135. The authors thank Luz Maria Chiu for her technical assistance.


Adachi, K. and Tainosho, Y. (2004). Characterization of heavy metal particles embedded in tire dust. Environment International, 30(8), 1009-1017. [ Links ]

Aguilar, B., Bautista, F., Goguitchaichvili, A., Morton, O. (2011). Magnetic monitoring of top soils of Merida (Southern Mexico). Studia Geophysica et Geodaetica, 55(2), 377-388. [ Links ]

Aguilera, A., Armendariz, C., Quintana, P., García-Oliva, F., Bautista, F. (2004). Influence of land use and road type on the elemental composition of urban dust in a mexican metropolitan area. Polish Journal of Environmental Studies, 28(3), 1535-1547. [ Links ]

Al, O.A. (2004). Heavy metal distribution in dust, street dust and soils from the work place in Karak Industrial Estate, Jordan. Atmospheric Environment, 38(39), 6803-6812. [ Links ]

Bautista, F. (1999). Introducción al estudio de la contaminación del suelo por metales pesados. Yucatán, México: Universidad Autónoma de Yucatán. [ Links ]

Bautista, F., Cram, S., Sommer, I. Suelos, in: Bautista, F., Palacio, J.L., Delfín, H. (2011). Técnicas de muestreo para el estudio del manejo de recursos naturales y el cuidado del ambiente, México: Centro de Investigaciones en Geografía Ambiental, Universidad Nacional Autónoma de México. 227-258. [ Links ]

Bautista, F., Palacio, G., Quintana, P., Zinck, J.A. (2011). Spatial distribution and development of soils in tropical karst areas from the Peninsula of Yucatan, Mexico. Geomorphology, 135(3-4), 308-321. [ Links ]

Bhuiyan, M.A.H., Parvez, L., Islam, M.A., Dampare, S.B., Suzuki, S. (2010). Heavy metal pollution of coal mine-affected agricultural soils in the northern part of Bangladesh. Journal of Hazardous Materials, 173(1-3), 384-392. [ Links ]

Cakmak, S., Dales, R., Kauri, L.M., Mahmud, M., Van Ryswyk, K., Vanos, J.,Weichenthal, S. (2014). Metal composition of fine particulate air pollution and acute changes in cardio respiratory physiology. Environmental Pollution, 189, 208-214. [ Links ]

Chandrasekaran, A., Ravisankar, R., Harikrishnan, N., Satapathy, K.K., Prasad, M.V.R., Kanagasabapathy, K.V. (2015). Multivariate statistical analysis of heavy metal concentration in soils of Yelagiri Hills, Tamilnadu, India-Spectroscopical approach: Spectrochimica Acta - Part A. Molecular and Biomolecular Spectroscopy, 137, 589-600. [ Links ]

Cortés, J.L., Bautista, F., Quintana, P., Aguilar, D., Goguichaishvili. (2015). The color of urban dust as an indicator of contamination by potentially toxic elements: the case of Ensenada, Baja California, Mexico. Revista Chapingo Serie Ciencias Forestales y delAmbiente, 21(3), 255-266. [ Links ]

Cortés, J.L. , Bautista, F. , Delgado, C., Quintana, P. , Aguilar, D. , García, A., Figueroa, C., Goguichaishvili , A. (2016). Spatialdistribution of heavy metals in urbandustfrom Ensenada, Baja California, Mexico. Revista Chapingo Serie Ciencias Forestales y del Ambiente, In press. [ Links ]

Covelo, E.F., Vega, F.A., Andrade, M.L. (2007). Simultaneous sorption and desorption of Cd, Cr, Cu, Ni, Pb, and Zn in acid soils: II. Soil ranking and influence of soil characteristics. Journal of Hazardous Materials , 147(3), 862-870. [ Links ]

Delgado, C. , Bautista, F. , Gogichaishvili, A., Cortés, J.L. , Quintana, P. , Aguilar, D. , Cejudo, R. (2019). Identificación de las zonas contaminadas con metales pesados en el polvo urbano de la Ciudad de México. Revista Internacional de Contaminación Ambiental, 35(1), 81-100. [ Links ]

Donaldson, K., Stone, V., Seaton, A., MacNee, W. (2001). Ambient particle inhalation and the cardiovascular system: Potential mechanisms. Environmental Health Perspectives, 109(SUPPL. 4), 523-527. [ Links ]

Ihl, T., Bautista, F. , Cejudo Ruíz, F.R., Delgado, M. del C., Quintana-Owen, P., Aguilar, D. , Goguitchaichvili, A. (2015). Concentration of toxic elements in topsoils of the metropolitan area of Mexico city: A spatial analysis using ordinary kriging and indicator kriging. Revista Internacional de Contaminación Ambiental , 31(1), 47-62. [ Links ]

Instituto Nacional de Estadística, Geografía e Informática (INEGI). Resultados del Censo de Población y Vivienda de Quintana Roo 2010. Recovered May 13, 2016 from Recovered May 13, 2016 from ]

Instituto Nacional de Estadística, Geografía e Informática (INEGI). Anuario estadístico y geográfico de Quintana Roo 2014. Instituto Nacional de Estadística y Geografía (México). Recovered May 13, 2016 from Recovered May 13, 2016 from ]

Instituto Nacional de Estadística, Geografía e Informática (INEGI). Información por Entidad: Quintana Roo. Instituto Nacional de Estadística y Geografía (México). Recovered May 13, 2016 from Recovered May 13, 2016 from ]

Kabata-Pendias, A. (2011). Trace elements in soils and plants. (4. ed.), New York: CRC Press, Boca Raton, London. ISBN 978-1-4200-9368-1. [ Links ]

Morales, S.S., Rodríguez, P.F., Jonathan, M.P., Navarrete, M., Herrera, M.A., Muñoz, N.P. (2014). Characterization of as and trace metals embedded in PM10 particles in Puebla City, México. Environmental Monitoring and Assessment, 186(1), 55-67. [ Links ]

Pacheco, J.I. and Alonzo, L.A. (2003). Caracterización del material calizo de la formación Carrillo Puerto en Yucatán. Ingeniería, 7(1), 7-19. [ Links ]

Padoan, E., Romè, C., Ajmone, F. (2017). Bioaccessibility and size distribution of metals in road dust and roadside soils along a peri-urban transect. Science of the Total Environment. 601-602, 89-98. [ Links ]

Sánchez, A., Bautista, F. , Goguitchaichvili, A. , Cejudo, R. , Reyes, J.A., Solís Dominguez, F.A., Morales, J.J. (2015). Evaluación de la contaminación ambiental a partir del aumento magnético en polvos urbanos-Caso de estudio para la ciudad de Mexicali, México. Revista Mexicana de Ciencias Geológicas, 32(3), 501-513. [ Links ]

Secretaría de Medio Ambiente y Recursos Naturales (SEMARNAT), Norma Oficial Mexicana que establece los criterios para determinar las concentraciones de remediación de suelos contaminados por arsénico, bario, berilio, cadmio, cromo hexavalente, mercurio, níquel, plata, plomo, selenio, talio y/o vanadio (NOM-147-SEMARNAT/SSA1): México, Diario Oficial de la Federación, 2 de marzo de 2007, 86, 2007. [ Links ]

Siegel, R., Naishadham, D.,Jemal, A. Cancer Statistics. (2012). CA. Cancer. J.Clin., 62, 10-29. [ Links ]

Tomlinson, D.L., Wilson, J.G., Harris, C.R., Jeffrey, D.W. (1980). Problems in the assessment of heavy-metal levels in estuaries and the formation of a pollution, index. Helgoländer Meeresuntersuchungen, 33(1-4), 566-575. [ Links ]

Turner, A. and Lewis, M. (2018). Lead and other heavy metals in soils impacted by exterior legacy paint in residential areas of south west England. Science of the Total Environment . 619-620, 1206-1213. [ Links ]

United States Environmental Protection Agency (US-EPA). Method 3051A: Microwave assisted acid digestion of sediments, sludges, soils and oils, in Test Methods for Evaluating Solid Waste Physical/Chemical Methods (SW-846). Washington, D.C., Environmental Protection Agency Publication, 30p, 2007a. [ Links ]

United States Environmental Protection Agency (US-EPA). Method 7000B: Flame atomic absorption spectrophotometry, in: Test Methods for Evaluating Solid Waste Physical/Chemical Methods (SW-846), Washington, D.C., Environmental Protection Agency Publication, 30p. 2007b. [ Links ]

Webster, R. and Oliver, M.A. (1990). Statistical Methods in Soil and Land Resource Surrey. New York: Oxford University Press, USA. Recovered from [ Links ]

Wei, B. and Yang, L. (2010). A review of heavy metal contaminations in urban soils, urban road dusts and agricultural soils from China. Microchemical Journal, 94 (2), 99-107. [ Links ]

World Health Organization (WHO). Global Health Observatory (GHO) data: Ambient air pollution. Recovered May 13, 2016 from ]

Yann, S., Galineau, J., Hulin, A., Caini, F., Marquis, N., Navel, V., Lepeule, J. (2014). Health effects of ambient air pollution: Do different methods for estimating exposure lead to different results? Environment International , 66, 165-173. [ Links ]

Recibido: 10 de Noviembre de 2017; Revisado: 14 de Febrero de 2019; Aprobado: 03 de Abril de 2019

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License