Abstract
Particle emissions from vehicular traffic are one of the main sources of heavy metals in cities. During the COVID- 19 pandemic, mobility was reduced, which created the opportunity to measure baseline heavy metal pollution in cities. Citizens took urban dust samples at 25 sites inside and outside their homes, with four repetitions; 159 urban dust samples were analyzed. The elements analyzed with FRX equipment in triplicate were Mn, Ni, Cu, Pb, Rb, Sr, Y, Zn, K, Ca, Ti, Cr, Fe, Zr, Nb, Sn, Sb, V and Ag. The contamination factor and health risk indices were calculated, and the most contaminated sites were geographically identified. The highest average values for the contamination factor were those of copper, vanadium, and zinc. The other metals presented moderate contamination. The extreme contamination cases with values higher than CF > 6 were Cu indoors, Mn outdoors, Pb indoors, and Ni, V, and Zn in both cases. The health risk index, no danger was observed in adults and children. However, sites 2 and 6, located in the east and southeast of the city, were the most contaminated outdoors, while indoors, they were sites 1 and 20 in the southwest and west, respectively. The results of this study carried out under low mobility conditions allowed the identification of two possible background levels for heavy metals: (a) the first decile and (b) the median value of the concentrations of Cr, Cu, Fe, Mn, Ni, Pb, Sb, Sn, V and Zn, for tourist cities and industrial cities in karst areas.
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1 Introduction
According to the World Health Organization, approximately twelve million people die yearly due to environmental pollution, highlighting the urgency of addressing this problem [32]. Urban dust is one of the ignored pollutants, composed of a mixture of natural particles such as rocks and soil as well as anthropogenic sources such as the deterioration of urban infrastructure; domestic, automotive, and industrial gas emissions; and domestic waste, among others [4, 5]. Urban dust has the soil as its destination [9]. It has been reported in other cities from Mexico that urban dust contains lead (Pb), copper (Cu), zinc (Zn), nickel (Ni), manganese (Mn), iron (Fe), and other potentially toxic elements, for example, in Ensenada [14], Mexico City [5, 20], San Luis Potosí [3], and Mérida [8].
Heavy metals (HMs) can be the cause of severe health problems, mercury (Hg) can cause primarily various irreversible nervous system effects [7], Pb causes reproductive disorders, loss of intelligence quotient, hypertension, renal alterations, effects on development, endocrine and immunological disorders, as well as, also is potentially carcinogenic [19], cadmium (Cd) causes alterations in renal function in humans [7], and arsenic (As) is well known for its ability to cause cancer and malignant tumors [1, 11, 30]. HMs can enter the human body through inhalation, ingestion, and dermal contact, they cannot be created or degraded, neither through biological processes nor anthropogenically [33].
In the world there are no environmental regulations on the concentration of HMs in urban dust, as there are for soil and bodies of water. Therefore, promoting, proposing, and establishing an official Mexican standard for the contaminants contained in urban dust [5] and avoiding prolonged exposure to these contaminants is essential.
On the other hand, the city of Valladolid in the state of Yucatán is considered a “magical town” due to its natural and architectural wealth. It is near major tourist destinations such as Chichén Itzá and Quintana Roo [37]. During the COVID- 19 pandemic, the mobility of national and foreign tourists was limited, and local mobility was significantly reduced. This situation provided an ideal opportunity to measure basal pollution, which reached its minimum in an extreme case of the absence of industry and reduction of vehicular traffic. In this sense, this study aimed to evaluate heavy metal pollution in Valladolid in conditions of very low mobility and urban dust outdoors and indoors.
2 Materials and methods
2.1 Study zone
Valladolid is a municipality located in the state of Yucatán, Mexico, in the eastern region of the state between parallels 20°24'and 20°54'north latitude; the meridians 87°57'and 88°21'west longitude and at an altitude between 7 and 10 masl. Valladolid occupies 2.70% of the state's surface, has 176 localities and a total of 85,460 inhabitants [22]. Valladolid is part of the recent karst, plain with sinkholes and shallow soils of the Leptosol group, with a warm subhumid climate with rain in summer and medium humidity [9, 10, 21]. The main economic activity of Valladolid is tourism since it was granted recognition as a magical town [37]. The city of Valladolid, Yucatan, is very close to the highway that leads to Chichen Itza, Merida, and Cancun, which is why the city has a large influx of tourists who arrive by car and, recently, by plane. Hence, car emissions are one of the primary sources of HMs. During the pandemic, auto repair shops and public transport operated normally, essential activities were not halted completely. However, the influx of tourists stopped utterly.
2.2 Urban dust sampling
The sampling was conducted at 25 sites by participants who were residents of Valladolid (Fig. 1).
During May 2020, amid the COVID- 19 pandemic, four weekly dust samples were taken. These samples were obtained by sweeping 1 m2 of the sidewalk outside their homes with plastic utensils, separating large debris from dust. In addition, the entire interior of the homes was swept to obtain both an exterior and interior sample. Subsequently, the urban dust was packaged in 0.5 kg plastic bags and labeled with a code to identify them. We made a video with instructions for sampling urban dust, with the idea of good labeling of the samples and avoiding contamination from sources other than dust. A smartphone application previously developed in the laboratory captured citizen sampling information. This application contains blocks of information covering details of the participant, household, outdoor environment, and the characteristics of the urban dust samples, ensuring a good chain of custody of the urban dust samples.
2.3 Geochemical analyses
One hundred fifty-nine urban dust samples were sieved with a #60 mesh. Subsequently, 3.0 g of each urban dust sample was taken and placed in a Teflon container, and the sample was covered with a layer of Mylar film 3.6 µm thick. We use 60-s exposure, 45 kV voltage, and 40 µA current. The 6200-protocol proposed by the United States Environmental Protection Agency (EPA SW- 846) for portable spectroscopy [16, 17], was followed in the measurement process. The elements analyzed were Mn, Ni, Cu, Pb, Rb, Sr, Y, Zn, K, Ca, Ti, Cr, Fe, Zr, Nb, Sn, Sb, V and Ag. A total of 477 analyses were performed.
The contamination factor (CF) was calculated with the following equation:
where: Cn is the metal concentration obtained in the geochemical analysis of each metal, and Bn is the background value. This study established a local background value using decile 1 because there are no established background values for urban dust and the global background value for soils [24] to compare both values and sites (within and outside the home). A CF value < 1 indicates negligible contamination, while a value between 1 and 3 suggests moderate contamination. A CF between 3 and 6 indicates considerable contamination, and a value > 6 indicates high contamination [20].
The pollutant load index (PLI) was calculated using the following equation:
A PLI value < 1 indicates that the heavy metal load is below the background level, while a PLI > 1 indicates the presence of contamination [31].
2.4 Diagnosis of health risk
We use the human health risk assessment model established by the US Environmental Protection Agency [35, 36]. This model considers three exposure routes in which citizens can be exposed to HMs: ingestion (Ding), inhalation (Dinh), and dermal contact (Dder) [23].
The hazard index (HI) represents the sum of the hazard ratios (HQ) of the three exposure routes. If the HI is greater than 1, there could be non-carcinogenic effects on the health of the population; if it is less than 1, the opposite would be expected [36] so this was used to calculate non-carcinogenic risks in both children and adults, data for ingestion, inhalation and dermal contact (HQing/inh/derm) were obtained dividing the estimated daily intake (EDI) by the reference dose (RfD) as shown in the following Eq. (6):
Estimated daily intakes were calculated for each exposure route to estimate non-carcinogenic risk. The lifetime average daily dose (LADD) was also calculated to estimate carcinogenic risk as shown in Eqs. (3–7). The values taken as a reference to carry out the calculations are the same as those used in Aguilera et al. [4].
The LADD was multiplied by the slope factors to obtain a lifetime cancer risk index. The accepted or tolerable cancer risk ranges from 1E- 06 to 1E- 04 [36]. These values indicate that one case in a population of 1,000,000 and 10,000 is acceptable [27]. The analyses were performed with R Project software, version 3.52.
2.5 Data analysis and spatialization
The concentrations of HMs were analyzed sequentially using descriptive statistics and analysis of variance, taking the sampling location (inside and outside homes) as a factor. Only the HMs considered very toxic were graphed: Pb, Sb, Sn, and V; the toxic ones Cr, Cu, Ni, and Zn; and the emerging ones Fe and Mn. Pie charts were created and placed within the city map to make the differences between sampling sites evident. Each pie chart is segmented into different colors representing HMs. The maps were created with ArcGIS 10.5 software [18]. We use the UTM projection, the horizontal reference ellipsoid, and the World Geodetic System 84.
3 Results and discussion
Sr, Y, Ca, and Sn presented a Gaussian distribution with low asymmetry, kurtosis, coefficients of variation, and very close mean and median values, so it is deduced that they come from natural sources. On the other hand, Cu, Ni, Zn, Zr, K, and Nb present very different values between the mean and the median, high coefficients of variation, and non-Gaussian distribution (Table 1), so it is deduced that they come from anthropogenic sources due to pollution [4].
Mn, Rb, and Sn showed a Gaussian concentration distribution indoors but not outdoors, with a high range of values outdoors, so it is possible to deduce that there is anthropogenic contamination outdoors. Cr, V, and Sb showed Gaussian distributions but with high coefficients of variation outdoors due to some extreme values. Fe, Mn, and Ti did not differ significantly between indoor and outdoor sites. Ag was only found in two sites with low concentrations (Table 1).
Analysis of variance reveals no significant differences between the concentrations of Cr, Pb, Sb, Sn, and V indoors and outdoors, suggesting that the sources of these elements are the same. On the contrary, there are significant differences in Cu, Ni, Zn, Fe, and Mn concentrations between the indoor and outdoor samples, suggesting that the sources differ.
Concerning non-toxic elements, we found significant statistical differences in K and Rb with higher concentrations in the interior. In contrast, Ca concentrations were higher outdoors (Table 2).
3.1 Contamination factor
The contamination factor calculated with local background showed no major differences between the indoors and outdoors. However, Cu, Ni, Pb, and Zn CF were higher inside than outside. Only V and Zn reached considerable contamination outdoors and indoors, respectively. Cr, Cu, Fe, Mn, Ni, Pb, Sb, and Sn showed moderate contamination. The high contamination level (CF > 6) was reached and exceeded in some cases, such as in Cu, Mn, Ni, Pb, V, and Zn (Fig. 2).
When the global background values were used, there were more differences between the sites, particularly for Cu, Ni, Pb, and Zn. Sb and zinc reached high contamination levels (CF > 6), and Cu was only indoors. Other HMs like Pb and Ni reached considerable contamination (Fig. 2).
This result indicates that these elements from the dust indoors and outdoors come mainly from anthropogenic sources. It is essential to mention that Fe is not included in the global background graphic since this element has no established value [24]. Iron is vital for natural processes and is abundant in the Earth's crust, nevertheless, it has recently been considered an emerging pollutant [28].
Fe and Mn are found naturally in soils and have not been considered as contaminants despite being HMs. Recently, studies have reported the toxicity of these elements in urban populations [28]. Manganism and Alzheimer's are a health problem in some cities,for example, anthropogenic particles of magnetite (Fe oxide) have been reported in the brains of infants and adults in Mexico City [12, 28].
Iron can react to environmental conditions and with other HMs, forming respirable magnetic particles [13]. Recent studies show that magnetite (Fe₃O₄), a naturally occurring iron oxide compound that poses no risk in its natural form under standard conditions, has been found in abundance in human brains in the form of nanoparticles (diameter < 200 nm) that are formed by combustion or friction processes common in urban areas and that due to their size can easily enter the human body, mainly the brain, causing reactive oxygen species (ROS) that generate cellular damage and neurodegenerative disorders, especially when in contact with magnetic fields [28]. Therefore, it is crucial not to ignore the presence of excess Fe and Mn.
The low mobility conditions due to the COVID- 19 pandemic and the low industrial level of the city suggested that heavy metal pollution levels would be low outdoors. However, we did not imagine indoor pollution would be higher than outdoor pollution, as reported in Mérida [8] and Mexico City [6]. The explanation for this situation may be that the population's activities were carried out indoors, HMs could have increased due to cooking, wear, and tear on furniture and walls in houses, mainly with old infrastructure, as well as the presence of point sources of HMs such as bus stops and the presence of mechanical workshops.
When comparing the local background level with the global level, we can see that, although some sites exceed the high pollution range, some atypical values of HMs highlight the importance of monitoring this type of pollution.
3.2 Analysis of contamination by sites
Indoors, sites 1 and 20 showed the highest pollution load (PLI) in the west and southwest of the city. At site 20, there is a gas station 0.10 km away, and at site 1, there are two mechanic's workshops 0.21 and 0.28 km away, and between both sites, approximately 0.5 km away, there is a sinkhole. Site 20 was located on a busy main avenue. Site 19 had the highest Pb contamination inland, located in the southeast, 0.37 km from a blacksmith shop and 0.47 km from a mechanical workshop. For Sb, site 22 had the highest FC inland, located south of the city, 0.15 km from a blacksmith shop. V had the highest contamination with an FC > 6 at site 4 and inland, located 0.24 km from a construction materials factory and auto parts store 0.11 km away, in addition to being located on 41 st Street, one of the city's main traffic routes. Site 1 had the highest Ni CF. Site 16 had the highest Cu, and site 15 had the highest Zn value. Site 4 had the maximum Cr and V (Fig. 3).
Outdoors, we can see that sites 2 and 6 had the highest values of contaminant load. At site 2, the primary contaminant HMs were Cu, Ni, Pb, and Zn, and at site 6, they were Fe, Mn, and Cr. Pb was the most pollutant metal at site 2, located east of the historic center, with sources of contamination such as a tire shop 0.06 km away and a spare auto parts store 0.13 km away, as well as vehicular traffic. At site 14, Sb had a high contamination factor value. It is located near a bus stop 0.10 km south and 0.20 km north of an auto parts store. Site 15 had the highest V contamination and is located northeast next to an auto body shop. Site 6 presented the highest contamination factor values of Mn and Fe, both considered emerging pollutants. Possible polluting sources could be the bus stop 0.11 km away to the south and another 0.27 km to the north on 40 th Street, another vital avenue for city traffic mobility (Fig. 4).
The city is generally contaminated by HMs, with Pb, Ni, and Cu standing out in the interior and Zn and V in the exterior. There are places where it is a priority to pay attention due to the high concentrations of HMs present, especially those with a higher concentration in the interior, to implement preventive measures.
The maps show that sites with extreme Cu and Ni contamination values are considered dangerous in the medium and long term.
3.3 Risk to human health
The HI value indicates no health risk for adults or children (Fig. 5); however, in the case of children, there are two cases with HI values greater than 0.50 for Pb and Ni indoors. In these cases, improving the cleanliness and conditions of their homes should be recommended. Exposure to Pb indoors could be associated with the paint on houses or furniture.
Pb and Ni are two common toxic elements in Mexican cities [5].
Outdoors, the HI value for children is below one and even 0.4 for all elements, so HMs do not represent a risk to human health. In the case of Mn outdoors, for children, an extreme case of HI (0.4) is presented at site six near a green area (Fig. 5).
3.4 Background values proposal
Table 3 shows the concentration of HMs in different cities on karst areas, which are located in ecosystems vulnerable to contaminating aquifers due to their geological nature [2]. Mexican cities on karst areas have lower concentrations of Cu than Spain and Brazil and lower Pb concentrations than Spain and China but higher concentrations of Zn than karstic Chinese cities and Bosnia & Herzegovina.
Regarding outdoor pollution, it is suggested to pay attention to cleaning streets and houses near sites with high concentrations of HMs. Inside, it is recommended that cleaning and identifying the sources of HMs should be improved, and home maintenance should be promoted so that dust is not generated from the wear and tear of houses, walls, floors, and ceilings. Consider removing old, unused objects from the home and using different shoes outdoors and indoors.
The pollution concentrations of HMs outdoors should be considered as the"minimum expected baseline pollution,"from which the official Mexican standard for HMs (NOMMP) in urban dust in cities on karst areas could be suggested. The proposal for a NOMMP could be to consider decile 1 of this study as the background level for each heavy metal, but if the city were to become an industrial city in the future, then the median values of the HMs in this study could be used as background values. From these background levels, the thresholds for pollution factors 3 and 6 would be generated for considerable and high pollution, respectively. Other studies have already proposed pollution levels for Mexico City [6] and the City of Gomez Palacio Durango [34].
4 Conclusion
This study, carried out during the COVID- 19 pandemic with people confined to their homes and with the lowest possible level of mobility outdoors, allowed us to identify two possible background values for Cr, Cu, Fe, Mn, Ni, Pb, Sb, Sn, V and Zn (a) the first decile 24.2, 16.7, 8428, 131.6, 22, 16, 13, 10.9, 7.3 and 109 mg/kg, respectively, (b) the median value, 40, 30, 17971, 316, 46, 25, 30, 19, 23 and 258 mg/kg, respectively.
These background levels of HMs in urban dust will allow the establishment of an official Mexican standard for tourist and industrial cities in karst areas of the country, especially in the context of future developments or mitigation efforts or environmental quality standards that other cities should aspire to achieve.
The highest concentration of HMs occurs indoors, particularly for metals such as Zn, V, Ni, Pb, and Cu, but it is still among the lowest compared to other cities. However, although concentrations of HMs in urban dust in this city, in general, do not represent a health risk, since there is no safe concentration, it is necessary to establish reference values, especially for HMs considered toxic and very toxic.
Data availability
Data availability. The datasets generated during and/or analyzed during the current study are not publicly available due to ethical reasons but are available from the corresponding author on reasonable request.
References
Abdul KS, Jayasinghe SS, Chandana EP, Jayasumana C, De Silva PM. Arsenic and human health effects: a review. Environ toxicol pharmacol. 2015;40(3):828–46. https://doi.org/10.1016/j.etap.2015.09.016.
Aguilar DY, Bautista F, Mendoza ME, Delgado C. Vulnerabilidad y riesgo de contaminación de acuíferos. Trop Subtrop Agroecosyt. 2013;16(2):243–63.
Aguilera A, Morales JJ, Goguitchaichvili A, García OF, Armendariz AC, Quintana P, Bautista F. Spatial distribution of magnetic material in urban road dust classified by land use and type of road in San Luis Potosí, Mexico. Air Qual Atmos Health. 2020;13:951–63. https://doi.org/10.1007/s11869-020-00851-5.
Aguilera A, Bautista F, Gutierrez M, Ruiz E, Cisneros A, Cejudo R, Gogitchauchvili A. Heavy metal pollution of street dust in the largest city of Mexico, sources, and health risk assessment. Environ Monit Assess. 2021;193:193. https://doi.org/10.1007/s10661-021-08993-.
Aguilera A, Cortés JL, Delgado C, Aguilar Y, Aguilar D, Cejudo R, Quintana P, Goguitchaichvili A, Bautista F. Heavy metal contamination (Cu, Pb, Zn, Fe, and Mn) in urban dust and its possible ecological and human health risk in Mexican Cities. Front Environ Sci. 2022;10:195. https://doi.org/10.3389/fenvs.2022.854460.
Aguilera A, Gallegos Á, Luna V, Hernández L, Gutiérrez ME, Amaro D, Goguitchaichvili A, Quintana P, Bautista F. Higher heavy metal contamination indoors than outdoors during COVID-19 in Mexico City. Environ Sci Pollut Res. 2024;31:16696–709. https://doi.org/10.1007/s11356-024-32085-8.
Alloway BJ. Heavy metals in soils: trace metals and metalloids in soils and their bioavailability. 3rd ed. Dordrecht: Springer; 2013. https://doi.org/10.1007/978-94-007-4470-7.
Andrade A, Aguilera A, Gallegos Á, Aguilar Y, Quintana P, Bautista F. Heavy metals in urban dust inside and outside homes during the Covid-19 pandemic in Mérida, Yucatán, México. Air Qual Atmos Health. 2023;16:2337–49. https://doi.org/10.1007/s11869-023-01410-4.
Bautista F, Palacio-Aponte G, Quintana P, Zinck JA. Spatial distribution and development of soils in tropical karst areas from the Peninsula of Yucatan, Mexico. Geomorphology. 2011;135(3–4):308–21. https://doi.org/10.1016/j.geomorph.2011.02.014.
Bautista F, Frausto O, Ihl T, Aguilar Y. Actualización del mapa de suelos del Estado de Yucatán México: Enfoque geomorfopedológico y WRB. Ecosis recur agropec. 2015;2(6):303–15.
Berglund S, Davis RD, L’hermite P,. Utilization of sewage sludge on land: rates of application and long-term effects of metals. Dordrecht: D. Reidel Publishing; 1984.
Calderón-Garcidueñas L, Cejudo-Ruiz FR, Stommel EW, González-Maciel A, Reynoso-Robles R, Torres-Jardón R, Tehuacanero-Cuapa S, Rodríguez-Gómez A, Bautista F, Goguitchaichvili A, Pérez-Guille BE, Soriano-Rosales RE, Koseoglu E, Mukherjee PS. Single-domain magnetic particles with motion behavior under electromagnetic AC and DC fields are a fatal cargo in Metropolitan Mexico City pediatric and young adult early Alzheimer, Parkinson, frontotemporal lobar degeneration and amyotrophic lateral sclerosis and in ALS patients. Front Hum Neurosci. 2024;18:1411849.
Cornell RM, Schwertmann U (2003) The iron oxides: structure, properties, reactions, occurrences, and uses. New Jersey, USA: Wiley-VCH.
Cortés JL, Bautista F, Delgado C, Quintana P, Aguilar D, García A, Gogichaishvili A. Distribución espacial de los metales pesados en polvos urbanos de la ciudad de Ensenada, Baja California, México. Rev Chapingo Ser Cie. 2016;23(1):47–60. https://doi.org/10.5154/r.rchscfa.2016.02.005.
Delibašić Š, Đokić-Kahvedžić N, Karić M, Keskin I, Velispahić A, Huremović J, Pašalić A. Health risk assessment of heavy metal contamination in street dust of federation of Bosnia and Herzegovina. HERA Int J. 2020;27(5):1296–308.
EPA. SW-846 Test Method 6200: Field Portable X-Ray Fluorescence Spectrometry for the Determination of Elemental Concentrations in Soil and Sediment. Environmental Protection Agency. Manual. Washington, D.C., EUA. 2017; 32 p.
EPA (Environmental Protection Agency) [Internet]. Regional Screening Levels (RSLs) - Generic Tables; c2024 [cited 2023 Oct 8]. U.S. Environmental Protection Agency; [about 1 screen]. https://www.epa.gov/risk/framework-metals-risk-assessment.
ESRI. Environmental Systems Resource Institute (2012) ArcGIS Desktop Sofware, Release 10. Redlands, CA, USA.
Gidlow DA. Lead toxicity. Occup med. 2015;65(5):348–56.
Ihl T, Bautista F, Ruiz F, Delgado M, Owen P, Aguilar D, Goguitchaichvili A. Concentration of toxic elements in topsoils of the metropolitan area of Mexico City: a spatial analysis using ordinary kriging and indicator kriging. Rev Int Contam Ambie. 2015;31(1):47–62.
INEGI. Instituto Nacional de Estadística y Geografía. Compendio de información geográfica municipal de los Estados Unidos Mexicanos Valladolid, Yucatán clave geoestadística 31102. 2010.
INEGI (Instituto Nacional de Estadística y Geografía) [Internet]. Información Demográfica y Social Censo de Población y Vivienda 2020. c2020- [citado el 2 de Octubre de 2023]. Disponible en: https://www.inegi.org.mx/programas/ccpv/2020/.
Jahandari A. Pollution status and human health risk assessments of selected heavy metals in urban dust of 16 cities in Iran. ESPR. 2020;27(18):23094–107. https://doi.org/10.1007/s11356-020-08585-8.
Kabata-Pendias A. Trace elements in soils and plants. 4th ed. New York: Taylor and Francis Group, LLC.; 2011. https://doi.org/10.1201/b10158-25.
Li X, Cao Y, Qi L, et al. The distribution characteristics of heavy metals in Guiyang urban soils. Chin J Geochem. 2012;31:174–80. https://doi.org/10.1007/s11631-012-0564-4.
Lima LHV, do Nascimento CWA, da Silva FBV, Araújo PRM. Baseline concentrations, source apportionment, and probabilistic risk assessment of heavy metals in urban street dust in Northeast Brazil. Sci Total Environ. 2023;858:159750.
Lu X, Wu X, Wang Y, Chen H, Gao P, Fu Y. Risk assessment of toxic metals in street dust from a medium-sized industrial city of China. Ecotoxicol Environ Saf. 2014;106:154–63. https://doi.org/10.1016/j.ecoenv.2014.04.022.
Maher BA, Ahmed IA, Karloukovski V, MacLaren DA, Foulds PG, Allsop D, Mann DM, Torres-Jardón R, Calderon-Garciduenas L. Magnetite pollution nanoparticles in the human brain. PNAS. 2016;39:10797–801. https://doi.org/10.1073/pnas.1605941113.
Marín P, Sánchez A, Díaz E, Bautista F, Romero M, Delgado MJ. Assessment of heavy metals and color as indicators of contamination in street dust of a city in SE Spain: Influence of traffic intensity and sampling location. Sustainability. 2018;10(11):4105.
Martin S, Griswold W. Human health effects of heavy metals. Environ Sci Technol Briefs Citiz. 2009;15(5):1–6.
Mehr MR, Keshavarzi B, Moore F, Sharifi R, Lahijanzadeh A, Kermani M. Distribution, source identification and health risk assessment of soil heavy metals in urban areas of Isfahan province. Iran J Afr Earth Sci. 2017;132:16–26. https://doi.org/10.1016/j.jafrearsci.2017.04.026.
WHO (World Health Organization) [Internet]. An estimated 12.6 million deaths each year are attributable to unhealthy environments; c2025 [cited 2023 Oct 4]. World Health Organization; [about 1 screen]. https://www.who.int/es/news/item/15-03-2016-an-estimated-12-6-million-deaths-each-year-are-attributable-to-unhealthy-environments.
Reyes Y, Vergara I, Torres O, Lagos MD, Jimenez EEG. Contaminación por metales pesados: implicaciones en salud, ambiente y seguridad alimentaria. Ingeniería Investigación y Desarrollo 12 + D. 2016;16(2):66–77. https://doi.org/10.19053/1900771X.v16.n2.2016.5447.
Santoyo-Martínez M, Aguilera A, Gallegos Á, Puente C, Goguitchaichvili A, Bautista F. Pollution levels and potential health risks of potentially toxic elements in indoor and outdoor dust during the COVID-19 Era in Gómez Palacios City, Mexico. Land. 2022;12(1):29. https://doi.org/10.3390/land12010029.
USEPA. Environmental Protection Agency. EPA/540/1-89/002. RAGS Volume I. Human health evaluation manual (HHEM). Part E. Supplemental guidance for dermal risk assessment. U.S. Environmental Protection Agency. 1989.
USEPA (United States Environmental Protection Agency) [Internet]. Risk Assessment Guidance for Superfund (RAGS) Volume III: Part A; c2024 [cited 2023 Oct 8]. U.S. Environmental Protection Agency; [about 1 screen]. https://www.epa.gov/risk/risk-assessment-guidance-superfund-rags-volume-iii-part.
Zapata JA, Cruz-Díaz OL, Cabrera IE, Cupul-Rosado CA. Pueblo Mágico Valladolid. Revista GEON. 2021;8(2):e307. https://doi.org/10.22579/23463910.307.
Funding
The project “La contaminación por metales pesados en el polvo urbano dentro y fuera de las casas en 10 ciudades antes, durante y después de la COVID- 19: fuentes y rutas de ingreso al cuerpo humano”, Number IN208621 was funded by the “Dirección general de asuntos al personal académico” from Universidad Nacional Autónoma de México.
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FB and AGo conceived the study design. LR, AG. and J.A gathered and analyzed the data. LR wrote the first draft of the paper. FB, AGo. JA provided input to the study. LR, AG, and FB design and data analysis, FB, AGo, read the paper, revised it critically for important intellectual content and gave their final approval for the version to be published. The guarantor for the paper is FB.
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Reyes, L., Gallegos, M.Á., Gogichaishvili, A. et al. Diagnosis of heavy metals in urban dust during the COVID- 19 pandemic in a tourist city from Mexico. Discov Environ 3, 54 (2025). https://doi.org/10.1007/s44274-025-00242-6
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DOI: https://doi.org/10.1007/s44274-025-00242-6