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Article

Salix humboldtiana as an Indicator of Air Pollution by Trace Metals in the Urban Areas of the City of Loja, Southern Ecuador

1
Biodiversidad de Ecosistemas Tropicales-BIETROP, Herbario HUTPL, Departamento de Ciencias Biológicas y Agropecuarias, Universidad Técnica Particular de Loja, San Cayetano s/n, 1101608 Loja, Ecuador
2
Carrera de Biología, Universidad Técnica Particular de Loja, San Cayetano s/n, 1101608 Loja, Ecuador
3
Departamento de Química, Universidad Técnica Particular de Loja (UTPL), San Cayetano s/n, 1101608 Loja, Ecuador
*
Author to whom correspondence should be addressed.
Atmosphere 2024, 15(10), 1160; https://doi.org/10.3390/atmos15101160
Submission received: 8 August 2024 / Revised: 21 September 2024 / Accepted: 25 September 2024 / Published: 28 September 2024
(This article belongs to the Special Issue Bioindicators in Air Pollution Monitoring)

Abstract

:
Air pollution is the most important environmental problem in urban areas related to vehicular traffic and industrial activities. The widespread presence of common urban trees, such as Salix humboldtiana, and their ability to tolerate diverse environmental conditions make this species an especially promising candidate for assessing environmental metal contamination. Therefore, biomonitoring with vascular plants has been widely used to assess air pollution, especially the accumulation of trace metal concentrations. Therefore, for the first time, we analyzed the concentration of trace metals using Salix humboldtiana in twelve areas with different levels of pollution in a city in Southern Ecuador. For this purpose, samples were taken from each site to assess the accumulation of trace metals such as Zn, Mn, Fe, Cd, Cr, Pb, Cu, Al, and Ni. The results obtained showed significant differences in the concentrations of Zn, Mn, Fe, and Cd between the urban areas and the control area, indicating that the central areas were the most polluted by vehicular traffic. However, these findings suggest that Salix humboldtiana may not be a particularly effective tool for quantifying levels of environmental metal contamination such as Cu and Ni, at least in urban areas in the city of Loja. This study has demonstrated that Salix humboldtiana leaves can effectively monitor trace metals associated with road traffic emissions in areas with varying levels of vehicular activity, indicating that vascular plants can be utilized for this purpose in tropical cities.

1. Introduction

Pollutants from anthropogenic activities mainly affect the quality of air [1], are related to economic growth and accelerated urbanization, and are linked to the increase in vehicular traffic with negative effects on human health [2]. In recent decades, urban air has been particularly characterized by elevated concentrations of heavy metals, with land transport identified as a prominent contributor to global pollution levels [3]. Therefore, industrial activity and vehicular traffic play an important role in the formation of particulate matter and heavy metals and contribute to the formation of secondary aerosols; consequently, pollution concentration is higher in urban areas compared to non-urban areas [4].
Studies on chemical element concentrations in plants, water, and soils indicate higher levels in proximity to roads compared to more distant locations [5]. Persistent vascular plant parts, such as conifer needles, have emerged as effective monitors for trace metals [6] due to the fact that the type of plant species plays a significant role in determining the deposition of pollutants on plant foliage [7,8,9,10]. Furthermore, the accumulation of contaminants, especially metals, in conifers has been shown to be higher than in broadleaf species [11]. For example, Turkyilmaz et al. [12] studied the accumulation of metals (Fe, Co, Ni, Cu, Zn, Cd, and Pb) in the needles of different conifer species, Pinus nigra, Pinus sylvestris, and Abies bornmulleriana. They found that they are good indicators of year-round pollution. Alexandrino et al. [13] conducted a study on Araucaria heterophylla and found that conifers have the ability to accumulate metals related to vehicular traffic [13]. Following this pattern, the concentrations of four heavy metals were determined in the leaves and bark of Platanus orientalis L. and Pinus nigra Arn. trees collected from polluted and non-polluted areas of three European cities [14].
Salix humboldtiana is the only native South American willow, found from Mexico to Argentina [15]. It is considered a pioneer species [16] and is commonly used as an ornamental tree in gardens, urban landscapes, and along roads [17,18]. In Ecuador, it is classified as both native and cultivated [19], and several studies have documented its presence in urban areas of Loja [20], Cuenca [21], and Quito [19]. In Ecuador, research has evaluated the diversity of lichens and bryophytes epiphytes [20], as well as the presence of Phoradendron nervosum in Salix humboldtiana trees as a host [20]. Furthermore, studies of floristic diversity in urban areas have determined that Salix humboldtiana is the most abundant species in the city of Loja [22]. However, no assessment has been made of its ability to accumulate heavy metals from root uptake or air pollution. For Ecuador, the passive monitoring of heavy metals using plants has only been studied in three species, such Araucaria heterophylla for the city of Quito [13], Tillandsia usneoides for the city of Loja [23], and Azadirachta indica for the city of Guayaquil [24]. However, until now, no studies have been conducted using the Salix humboldtiana tree as a bioindicator of air pollution. Thus, the aim of this study was to analyze the concentration of heavy metals in areas with varying levels of contamination using the S. humboldtiana tree. The hypothesis is that urban areas with higher traffic will have higher levels of heavy metals in S. humboldtiana compared to control areas, as previously observed in bryophyte and lichen [23], indicating that the downtown areas (urban areas) of the city exhibit higher levels of air pollution from heavy metals compared to the surrounding areas of the city (Forest). Exposure to heavy metals continues to increase in many parts of the world despite their known adverse health effects and persistent presence [25]. Chronic exposure to polluted air can aggravate diseases such as cardiorespiratory problems, inflammation, cancer, neurodegeneration, reproductive disorders, metabolic syndrome (MS), and diabetes [26]. In addition, heavy metals can cause toxicity in various human organs, including the kidneys (nephrotoxicity), nervous system (neurotoxicity), liver (hepatotoxicity), skin, and cardiovascular system [27].
Studies have shown that more than 90% of Cu emissions from road traffic are due to brake wear; for Ni, more than 80% are due to exhaust emissions; for Zn, it is estimated that about 40% of road traffic emissions are due to exhaust emissions; and for Pb, it is estimated that 90% are due to exhaust emissions [28]. Although research on air pollution is gaining ground in our country and there has been an increase in published research, much of this knowledge is widely scattered, and although publications in the past have provided scientific recommendations [29,30], a comprehensive effort to address all aspects of air pollution is still lacking. Leveraging existing local and international expertise, we can design effective interventions in Ecuador. Despite the city’s low industrialization and limited pollutant sources, targeted approaches, such as addressing transportation, dust, waste, and residential sectors, hold promise for enhancing the quality of life for our population.

2. Materials and Methods

2.1. Study Area

The study area was located in Southern Ecuador, specifically in the Andean city of Loja, which sits at an altitude between 2000–2300 m and covers a surface area of 1928.00 km2. The mean annual temperature is ca. 20 °C, with an average annual rainfall of approximately 1900 mm, and maintains an average relative humidity of around 80% throughout the year (Instituto Nacional de Meteorología e Hidrología, INAMI, Loja, Ecuador). To facilitate monitoring, the city was divided into three zones: north, center, and south, and a control zone (Forests) outside the city (Figure 1). The study design was based on previous environmental monitoring studies [23]. The study was conducted between June and October 2022.

2.2. Experimental Design

Salix humboldtiana was used to evaluate the presence of trace metals in locations exhibiting varying degrees of vehicular traffic intensity. This particular species was chosen because its ability to accumulate metals had not been previously assessed. S. humboldtiana (Figure 2), a dioecious deciduous tree that can reach a height of 25 m, was used for passive air quality sampling. Its leaves are simple, alternate, linearly lanceolate, and serrated, with a pointed tip and a wedge-shaped base, 6 to 12 cm long.
At each sampling location, five samples of approximately 1–2 g of Salix hum-boldtiana leaves were collected from trees positioned directly adjacent to the road. The leaves were gathered from outer branches at a height of 2 m above the ground, exhibiting a similar position within the tree canopy, with a total of 60 samples.
For vehicular traffic, three main categories were considered following the protocol proposed by Benítez et al. (2021) [23]:
-
Light vehicles (LV) = cars/small vans.
-
Heavy vehicles (HV) = trucks/buses.
-
Motorbikes (MT) = motorbikes.
The proposed protocol involved counting vehicles in each zone every 30 min over a 3-day period. The vehicle counts were conducted between 08:00 and 13:00 h.

2.3. Chemical Analysis

The samples were taken to the laboratory, where plant debris particles were manually removed. Leaf samples were washed with tap water and then rinsed with deionized water and dried in an oven at 40 °C for three days. Once dried, each sample was chopped to remove residues and very large particles; 0.5 g of each sample was weighed. The digestion method requires the addition of 0.5 g of sample and 10 mL of HNO3 (65% analytical grade, max 0.005 ppm Hg) by Merck (Darmstadt, Germany) in a digestion vessel, and a microwave digestion system, MARS (Microwave Accelerated Reaction System), from CEM Corporation (CEM Mars 6, manufactured by CEM Corp., Matthews, NC, USA) was used; this process lasted 40 min. After digestion, the volume of each sample was adjusted to 100 mL using double-distilled water [23], and the samples were measured using Atomic Absorption Analyst 400 (Perkin Elmer, Waltham, MA, USA). The concentration of cadmium (Cd), copper (Cu), manganese (Mn), lead (Pb), zinc (Zn), chromium (Cr), aluminum (Al), and iron (Fe) was performed for each parameter using certified standards from Merck. The mean of Standard Reference Material (SRM NIST 1577b) recoveries for Fe, Pb, Cd, Cr, Mn, Zn, and Al in vegetal samples were 97%, 106%, 99%, 98%, 101%, and 99%, respectively. Finally, the analytical results were statistically analyzed using linear regression and two independent mean tests to determine the analytical accuracy and precision of the method.

2.4. Data Analysis

To evaluate the changes in the concentration of heavy metals in each of the zones, the Kruskal–Wallis non-parametric test was performed because the data did not have a normal distribution (Shapiro–Wilk, p-value < 0.05). In addition, to identify significant differences in metal accumulation between zones, Dunn’s non-parametric test was implemented with Dunn’s package [31]. All analyses were performed using the statistical software Rstudio version 1.4.1103.

3. Results

The mean concentration found for most metals in leaves of S. humboldtiana was higher in the urbanized areas compared to the control samples (Table 1).
The values of Cd, Cr, and Fe were high for the urban areas compared to the control samples. On the other hand, Cd and Fe showed high values in the southern zone, followed by the northern and control zones and the northern and central zones, respectively, but for Cr, relatively high values were recorded in the central zone. Corroborating these results, the Kruskal–Wallis test showed that Mn, Al, Fe, and Cu had the highest values in the urban areas, while the metals Cd, Ni, and Pb had the lowest values.
Dunn’s test showed significant differences between metal accumulation in control samples and urban areas (south, central, and north) for all metals except Ni, Pb, and Cd (Table 2). Fe and Cr values show significant differences between the center–north and control–north zones, while Cu shows a similar pattern of Cu accumulation between the south–Center, south–north, and south–control zones. The metals Mn and Zn show significant differences for the zones control–south and control–north. Aluminum only showed significant differences in the accumulation of this metal between the central and north zones. Meanwhile, for Ni, Pb, and Cd, there were no significant differences in the accumulation of these metals between any of the zones of the city of Loja.
The highest number of vehicles was recorded in the central zone, where the average number of vehicles was 669.3 per day. On the other hand, the zone with the lowest average number of vehicles (20) was the control zone. These data are directly proportional to the metal concentration data, with the highest percentage of accumulation being recorded in the urban zones in relation to the control zone (Table 3).

4. Discussion

The results of this study showed that heavy metal accumulation significantly changed at the species level related to traffic density. Our investigation of metal pollution in Salix humboldtiana leaves identified high contamination in the central area compared with control zones. According to our results, studies with vascular and non-vascular epiphytic plants pointed out the central locations of the city of Loja as contamination hotspots due to a higher concentration of heavy metals [23,32]. This area is characterized by high concentrations of Mn, Zn, Fe, and Cd. These sources include exhaust emissions from fuel and lubricant combustion, as well as components like catalytic converters, particulate filters, lubricating oils, resuspension, engine corrosion, and tire wear [25]. Thus, this study confirms previous research, highlighting the various sources of pollutants linked to road traffic.
Previous studies have shown a strong correlation between airborne heavy metals and vehicle traffic in urban areas [33]. Additionally, heavy metal concentrations tend to be higher in urban areas with more traffic compared to rural areas with less traffic [34]. Studies on vascular plants have also revealed elevated heavy metal levels near roads [35,36] and confirm that the traffic volume and the distance to the road [37] are important factors.
According to Alexandrino et al. [13], in the study of Araucaria heterophylla, the concentration of Mn, Fe, Al, Zn, Cr, and Pb generally increases with traffic intensity. This study found that urban areas have one of the highest Fe values, with a mean concentration of 1084.92 ± 907.32 mg g−1. Our results are consistent with this, as the highest concentration in urban areas was also for Fe, with a mean concentration of 505.243 ± 140.433 mg g−1. Although Mn is one of the main contaminating metals in their work, with values of 1250.95 ± 1012.31 mg g−1, our results show a significant difference. Our highest values for Mn were 0.124 ± 0.087 mg g−1. These results suggest that Araucaria heterophylla may be a better metal accumulator species compared to Salix humboldtiana or that the latter was exposed to a higher concentration of this metal. Similarly, in the study by Giacomino et al. [38] on Taraxacum officinale, elevated Cr contents were found to be above the maximum range in two of the three urban sites sampled. This is relevant to our results, as Cr is one of the metals with the highest concentration values in urban areas. This is consistent with previous studies reported in the literature [39]. Increasing concentrations of Mn, Fe, Al, Zn, Cu, Cr, and Pb with increasing traffic intensity may indicate that these metals are related to vehicle emissions [13]. Although Mn, Fe, and Al are typical geological elements, they are also components of steel and alloys widely used in the automotive industry [40]. In accordance with our results, Morton-Bermea et al. [41], using Ficus benjamina, and Tomašević et al. [42], using Aesculus hippocastanum and Tilia sp., determined that the concentrations of heavy metals in the three species of trees showed different patterns. On the other hand, Cakaj et al. [43] showed that the concentrations of heavy metals in the different herb species (Lolium multiflorum, Trifolium pratense, Rumex acetosa, Amaranthus retroflexus, and Plantago lanceolata) varied greatly.
On the other hand, concentrations of copper (Cu), lead (Pb), and nickel (Ni) in Salix humboldtiana did not show significant differences between control and urban areas. This finding is consistent with reports suggesting higher concentrations of these metals in industrial rather than high vehicular traffic areas, particularly relevant in our case, given the city’s low level of industrial development [44]. Accumulation in Salix humboldtiana leaves (e.g., Fe, Cr, and Mn) showed a similar pattern to other bioindicator groups such as lichens, bryophytes, and bromeliads in the city of Loja [20,23,32], with higher accumulation of heavy metals in urban areas than in control areas related with vehicular traffic. In other regions, for example, other studies have shown that high concentrations of metals are associated with vehicular traffic [45,46,47]. However, it is crucial to note that while Salix humboldtiana exhibits metal accumulation, the levels are comparatively lower than those observed in lichens, mosses, and bromeliads used in previous biomonitoring studies. Therefore, monitoring heavy metal concentrations is extremely important. Along with increasing population and vehicle density, traffic pollution is a potential and important problem for this city in Southern Ecuador.
In this study, we determined the accumulation of heavy metals in the leaves of S. humboldtiana and confirmed the variability of the concentration. Studies have shown that the accumulation of heavy metals in plants depends on many factors, such as plant species [48]; climatic conditions [49]; traffic density [12]; the different parts of the plant, for example, bark, leaves, and roots [50,51]; and the developmental stage [52]. In order to monitor these changes and to be able to use plants effectively to reduce heavy metal concentrations, research on this topic is very important. It is particularly important that these studies compare different plant species to determine which plants can target different pollutants.

5. Conclusions

The three urban areas of the city showed high concentrations of Mn, Zn, Fe, and Cd compared to the control samples for the species Salix humboldtiana in relation to vehicular traffic. However, Cu and Ni showed the lowest concentration values. However, Salix humboldtiana was not a better accumulator of heavy metals compared to other species, such as Araucaria heterophylla and Tillandsia usneoides, and other bioindicators such as lichens or bryophytes in urban cities. In our study, S. humboldtiana plants, which showed more Mn, Zn, Fe, and Cd accumulation, thus can be considered more tolerant for these metals and, therefore, this species can serve as an organism model for assessing air pollution in other cities of Ecuador. However, another alternative is the possibility of monitoring other plants growing in the city, for example, Schinus molle L., Alnus acuminata Kunth., Jacaranda mimosifolia D.Don., Fraxinus chinensis Roxb., Vachellia macracantha Humb. & Bonpl. ex Willd, Casuarina equisetifolia J.R. Forst. & G. Forst., Acacia melanoxylon R. Br., Cupressus macrocarpa Hartw., and Castilla elastica Cerv. This result of the study is of national and international scientific significance because of the severity of the air pollution problem in our country and the lack of data and information in the area. In addition, the necessary governmental measures for the control or reduction in air pollution in Ecuador can lead to significant benefits for society in terms of the reduction in negative health effects.

Author Contributions

Conceptualization, J.C. and Á.B.; methodology, D.O. and J.C.; software, Á.B.; formal analysis, Á.B.; investigation, D.O., Á.B., and J.C.; writing—original draft preparation, J.C.; writing—review and editing, Á.B. and J.C.; supervision, J.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by UTPL (PROY_INV_BA_2022_3608).

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Acknowledgments

The authors are grateful to UTPL for funding the publication of this article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Abaje, I.B.; Bello, Y.; Ahmad, S.A. A Review of Air Quality and Concentrations of Air Pollutants in Nigeria. Appl. Sci. Environ. Manag. 2020, 24, 373–379. [Google Scholar] [CrossRef]
  2. Zhang, K.; Batterman, S. Air pollution and health risks due to vehicle traffic. Sci. Total Environ. 2013, 450, 307–316. [Google Scholar] [CrossRef] [PubMed]
  3. Piracha, A.; Chaudhary, M.T. Urban Air Pollution, Urban Heat Island and Human Health: A Review of the Literature. Sustainability 2022, 14, 9234. [Google Scholar] [CrossRef]
  4. Souto-Oliveira, C.E.; Andrade, M.D.F.; Kumar, P.; Lopes, F.J.D.S.; Babinski, M.; Landulfo, E. Effect of Vehicular Traffic, Remote Sources and New Particle Formation on the Activation Properties of Cloud Condensation Nuclei in the Megacity of São Paulo, Brazil. Atmos. Chem. Phys. 2016, 16, 14635–14656. [Google Scholar] [CrossRef]
  5. Khalid, N.; Hussain, M.; Young, H.S.; Boyce, B.; Aqeel, M.; Noman, A. Effects of Road Proximity on Heavy Metal Concentrations in Soils and Common Roadside Plants in Southern California. Environ. Sci. Pollut. Res. 2018, 25, 35257–35265. [Google Scholar] [CrossRef]
  6. Ceburnis, D. Conifer Needles as Biomonitors of Atmospheric Heavy Metal Deposition: Comparison with Mosses and Precipitation, Role of the Canopy. Atmos. Environ. 2000, 34, 4265–4271. [Google Scholar] [CrossRef]
  7. Stephens-Romero, S.; Carreras-Sospedra, M.; Brouwer, J.; Dabdub, D.; Samuelsen, S. Determining air quality and greenhouse gas impacts of hydrogen infrastructure and fuel cell vehicles. Environ. Sci. Technol. 2009, 43, 9022–9029. [Google Scholar] [CrossRef]
  8. Fellet, G.; Pošćić, F.; Licen, S.; Marchiol, L.; Musetti, R.; Tolloi, A.; Barbieri, P.; Zerbi, G. PAHs accumulation on leaves of six evergreen urban shrubs: A field experiment. Atmos. Pollut. Res. 2016, 7, 915–924. [Google Scholar] [CrossRef]
  9. Piccardo, M.T.; Pala, M.; Bonaccurso, B.; Stella, A.; Redaelli, A.; Paola, G.; Valerio, F. Pinus nigra and Pinus pinaster needles as passive samplers of polycyclic aromatic hydrocarbons. Environ. Pollut. 2005, 133, 293–301. [Google Scholar] [CrossRef]
  10. Ratola, N.; Amigo, J.M.; Oliveira, M.S.; Araújo, R.; Silva, J.A.; Alves, A. Differences between Pinus pinea and Pinus pinaster as bioindicators of polycyclic aromatic hydrocarbons. Environ. Exp. Bot. 2011, 72, 339–347. [Google Scholar] [CrossRef]
  11. Chen, L.; Liu, C.; Zhang, L.; Zou, R.; Zhang, Z. Variation in Tree Species Ability to Capture and Retain Airborne Fine Particulate Matter (PM2.5). Sci. Rep. 2017, 7, 3206. [Google Scholar] [CrossRef] [PubMed]
  12. Turkyilmaz, A.; Sevik, H.; Cetin, M.; Saleh, E. Changes in Heavy Metal Accumulation Depending on Traffic Density in Some Landscape Plants. Pol. J. Environ. Stud. 2018, 27, 2277–2284. [Google Scholar] [CrossRef] [PubMed]
  13. Alexandrino, K.; Viteri, F.; Rybarczyk, Y.; Guevara Andino, J.E.; Zalakeviciute, R. Biomonitoring of Metal Levels in Urban Areas with Different Vehicular Traffic Intensity by Using Araucaria heterophylla Needles. Ecol. Indic. 2020, 117, 106701. [Google Scholar] [CrossRef]
  14. Sawidis, T.; Breuste, J.; Mitrovic, M.; Pavlovic, P.; Tsigaridas, K. Trees as bioindicator of heavy metal pollution in three European cities. Environ. Pollut. 2011, 159, 3560–3570. [Google Scholar] [CrossRef] [PubMed]
  15. Gallo, L.A.; Amico, I.; Bozzi, J.; Gazo, M.C.; Cerrillo, T.; Datri, L.; Hansen, M.; Leyer, I.; López, H.; Marchelli, P.; et al. 7.2 Salix humboldtiana: A Very Ancient Willow and the Only Native to Argentina. In Low Intensity Breeding of Native Forest Trees in Argentina; Springer: Berlin/Heidelberg, Germany, 2020; Volume 192, pp. 1–20. [Google Scholar]
  16. Parolin, P.; Oliveira, A.C.; Piedade, M.T.F.; Wittmann, F.; Junk, W.J. Pioneer trees in Amazonian floodplains: Three key species form monospecific stands in different habitats. Folia Geobot. 2002, 37, 225–238. [Google Scholar] [CrossRef]
  17. Scarpa, G.F.; Rosso, C.N. Etnobotánica histórica de grupos Criollos de Argentina IV: Identificación taxonómica de las plantas y análisis de datos medicinales del Chaco Húmedo provenientes de la Encuesta Nacional de Folklore de 1921. Bonplandia 2019, 28, 5–42. [Google Scholar] [CrossRef]
  18. Mata-Balderas, J.M.; Alanís-Rodríguez, E.; Mora-Olivo, A.; Collantes-Chávez-Costa, A. Woody plant community structure and composition of an urban riparian forest in Monterrey metropolitan area, Northeast Mexico. J. Torrey Bot. Soc. 2022, 149, 210–218. [Google Scholar] [CrossRef]
  19. Carrera, M.; Altamirano, L.; Barragán, K. Host species of the hemiparasitic shrub Phoradendron nervosum Oliv. in densely urban areas of Quito, Ecuador. ACI Av. Cienc. Ing. 2023, 15, 9. [Google Scholar] [CrossRef]
  20. Ochoa-Jimenez, D.A.; Cueva-Agila, A.; Prieto, M.; Aragón, G.; Benitez, Á. Cambios en la composición de líquenes epífitos relacionados con la calidad del aire en la ciudad de loja (Ecuador). Caldasia 2015, 37, 333–343. [Google Scholar] [CrossRef]
  21. Muñoz, M.E.; Vásquez, E.; Portilla, F. Estimates of the Carbon Capture Potential in Urban Parks and Vehicle CO2 Emissions in Cuenca, Ecuador. In Communication, Smart Technologies and Innovation for Society, Proceedings of the CITIS 2021, Guayaquil, Ecuador, 26–28 May 2021; Springer: Singapore, 2022; pp. 405–417. [Google Scholar]
  22. Merino, B.; Gualán, R.; Macas, M.F.; Armijos, A.; Fernández, P.; Jumbo, N.; Pucha-Cofrep, D.A. Caracterización florística y estructura del arbolado urbano de la ciudad de Loja. Bosques Latid. Cero 2023, 13, 1–22. [Google Scholar]
  23. Benítez, Á.; Medina, J.; Vásquez, C.; Loaiza, T.; Luzuriaga, Y.; Calva, J. Lichens and Bromeliads as Bioindicators of Heavy Metal Deposition in Ecuador. Diversity 2019, 11, 28. [Google Scholar] [CrossRef]
  24. Morales-Estupiñan, M.J.; Recalde, S.; Orozco, K.; Ponce, W. Analysis of heavy metals in Azadirachta indica a. Juss leaves, as bioindicator for monitoring Enviromental pollution in Guayaquil, Ecuador. In Proceedings of the 6th World Congress on New Technologies (NewTech’20), Prague, Czech Republic, 19–21 August 2020; Volume 145, pp. 1–5. [Google Scholar]
  25. Jaishankar, M.; Tseten, T.; Anbalagan, N.; Mathew, B.B.; Beeregowda, K.N. Toxicity, mechanism and health effects of some heavy metals. Interdiscip. Toxicol. 2014, 7, 60–72. [Google Scholar] [CrossRef] [PubMed]
  26. Schiavo, B.; Meza-Figueroa, D.; Vizuete-Jaramillo, E.; Robles-Morua, A.; Angulo-Molina, A.; Reyes-Castro, P.A.; Lnguaggiato, C.; Gonzalez-Grijalva, B.; Pedroza-Montero, M. Oxidative potential of metal-polluted urban dust as a potential environmental stressor for chronic diseases. Environ. Geochem. Health 2023, 45, 3229–3250. [Google Scholar] [CrossRef] [PubMed]
  27. Mitra, S.; Chakraborty, A.J.; Tareq, A.M.; Emran, T.B.; Nainu, F.; Khusro, A.; Idris, A.M.; Khandaker, M.U.; Osman, H.; Alhumaydhi, F.A.; et al. Impact of Heavy Metals on the Environment and Human Health: Novel Therapeutic Insights to Counter the Toxicity. J. King Saud Univ. Sci. 2022, 34, 101865. [Google Scholar] [CrossRef]
  28. Johansson, C.; Norman, M.; Burman, L. Road traffic emission factors for heavy metals. Atmos. Environ. 2009, 43, 4681–4688. [Google Scholar] [CrossRef]
  29. Pant, P.; Harrison, R.M. Estimation of the Contribution of Road Traffic Emissions to Particulate Matter Concentrations from Field Measurements: A Review. Atmos. Environ. 2013, 77, 78–97. [Google Scholar] [CrossRef]
  30. Zwolak, A.; Sarzyńska, M.; Szpyrka, E.; Stawarczyk, K. Sources of soil pollution by heavy metals and their accumulation in vegetables: A review. Water Air Soil Pollut. 2019, 230, 164. [Google Scholar] [CrossRef]
  31. Dunn, O.J. Multiple Comparisons Using Rank Sums. Technometrics 1964, 6, 241. [Google Scholar] [CrossRef]
  32. Benítez, Á.; Armijos, L.; Calva, J. Monitoring Air Quality with Transplanted Bryophytes in a Neotropical Andean City. Life 2021, 11, 821. [Google Scholar] [CrossRef]
  33. Adamiec, E.; Jarosz-Krzemińska, E.; Wieszała, R. Heavy metals from non-exhaust vehicle emissions in urban and motorway road dusts. Environ. Monit. Assess. 2016, 188, 369. [Google Scholar] [CrossRef]
  34. Mateos, A.C.; Amarillo, A.C.; Carreras, H.A.; González, C.M. Land Use and Air Quality in Urban Environments: Human Health Risk Assessment due to Inhalation of Airborne Particles. Environ. Res. 2018, 161, 370–380. [Google Scholar] [CrossRef] [PubMed]
  35. Solgi, E.; Oshvandi, Z. Spatial Patterns, Hotspot, and Risk Assessment of Heavy Metals in Different Land Uses of Urban Soils (Case Study: Malayer City). Hum. Ecol. Risk Assess. Int. J. 2018, 24, 256–270. [Google Scholar] [CrossRef]
  36. Zhang, Q.; Yu, R.; Fu, S.; Wu, Z.; Chen, H.Y.H.; Liu, H. Spatial Heterogeneity of Heavy Metal Contamination in Soils and Plants in Hefei, China. Sci. Rep. 2019, 9, 1049. [Google Scholar] [CrossRef] [PubMed]
  37. Grigalavičienė, I.; Rutkovienė, V.; Marozas, V. The Accumulation of Heavy Metals Pb, Cu and Cd at Roadside Forest Soil. Pol. J. Environ. Stud. 2005, 14, 109–115. [Google Scholar]
  38. Giacomino, A.; Malandrino, M.; Colombo, M.L.; Miaglia, S.; Maimone, P.; Blancato, S.; Conca, E.; Abollino, O. Metal Content in Dandelion (Taraxacum officinale) Leaves: Influence of Vehicular Traffic and Safety upon Consumption as Food. J. Chem. 2016, 2016, 9842987. [Google Scholar] [CrossRef]
  39. Sevik, H.; Ozel, H.B.; Cetin, M.; Özel, H.U.; Erdem, T. Determination of Changes in Heavy Metal Accumulation Depending on Plant Species, Plant Organism, and Traffic Density in Some Landscape Plants. Air Qual. Atmos. Health 2019, 12, 189–195. [Google Scholar] [CrossRef]
  40. Fujiwara, F.; Rebagliati, R.J.; Dawidowski, L.; Gómez, D.; Polla, G.; Pereyra, V.; Smichowski, P. Spatial and Chemical Patterns of Size Fractionated Road Dust Collected in a Megacitiy. Atmos. Environ. 2011, 45, 1497–1505. [Google Scholar] [CrossRef]
  41. Morton-Bermea, O.; Hernández-Álvarez, E.; Ordoñez-Godínez, S.L.; Montes-Ávila, I. Mercury, platinum, antimony and other trace elements in the atmospheric environment of the urban area of Mexico City: Use of Ficus benjamina as biomonitor. Bull. Environ. Contam. Toxicol. 2021, 106, 106–665. [Google Scholar] [CrossRef]
  42. Tomasevic, M.; Rajšić, S.; Đorđević, D.; Tasić, M.; Krstić, J.B.; Novaković, V.T. Heavy metals accumulation in tree leaves from urban areas. Environ. Chem. Lett. 2004, 2, 151–154. [Google Scholar] [CrossRef]
  43. Cakaj, A.; Drzewiecka, K.; Hanć, A.; Lisiak-Zielińska, M.; Ciszewska, L.; Drapikowska, M. Plants as effective bioindicators for heavy metal pollution monitoring. Environ. Res. 2024, 256, 119222. [Google Scholar] [CrossRef]
  44. Mohanraj, R.; Azeez, P.A.; Priscilla, T. Heavy metals in airborne particulate matter of urban Coimbatore. Arch. Environ. Contam. Toxicol. 2004, 47, 162–167. [Google Scholar] [CrossRef] [PubMed]
  45. Turkyilmaz, A.; Cetin, M.; Sevik, H.; Isinkaralar, K.; Saleh, E.A.A. Variation of heavy metal accumulation in certain landscaping plants due to traffic density. Environ. Dev. Sustain. 2020, 22, 2385–2398. [Google Scholar] [CrossRef]
  46. Kaur, M.; Bhatti, S.S.; Katnoria, J.K.; Nagpal, A.K. Investigation of metal concentrations in roadside soils and plants in urban areas of Amritsar, Punjab, India, under different traffic densities. Environ. Monit. Assess. 2021, 193, 222. [Google Scholar] [CrossRef] [PubMed]
  47. Shrestha, S.; Baral, B.; Dhital, N.B.; Yang, H.H. Assessing air pollution tolerance of plant species in vegetation traffic barriers in Kathmandu Valley, Nepal. Sustain. Environ. Res. 2021, 31, 3. [Google Scholar] [CrossRef]
  48. Öztürk, S.; Bozdogan, E. The contribution of urban road trees on improving the air quality in an urban area. Fresenius Environ. Bull. 2015, 24, 1822–1829. [Google Scholar]
  49. Březinová, T.; Jan, V. Evaluation of heavy metals seasonal accumulation in Phalaris arundinacea in a constructed treatment wetland. Ecol. Eng. 2015, 79, 94–99. [Google Scholar] [CrossRef]
  50. Tošić, S.; Alagić, S.; Dimitrijević, M.; Pavlović, A.; Nujkić, M. Plant parts of the apple tree (Malus spp.) as possible indicators of heavy metal pollution. Ambio 2016, 45, 501–512. [Google Scholar] [CrossRef]
  51. Yabanli, M.; Yozukmaz, A.; Sel, F. Heavy metal accumulation in the leaves, stem and root of the invasive submerged macrophyte Myriophyllum spicatum L. (Haloragaceae): An example of Kadin Creek (Mugla, Turkey). Braz. Arch. Biol. Technol. 2014, 57, 434–440. [Google Scholar] [CrossRef]
  52. Shahid, M.; Dumat, C.; Khalida, S.; Schreck, E.; Xiong, T.; Nabeel, N.K. Foliar heavy metal uptake, toxicity and detoxification in plants: A comparison of foliar and root metal uptake. J. Hazard. Mater. 2017, 325, 36–58. [Google Scholar] [CrossRef]
Figure 1. Study area, sampling locations in the city of Loja. S = south, C = center, N = north, and F = control.
Figure 1. Study area, sampling locations in the city of Loja. S = south, C = center, N = north, and F = control.
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Figure 2. Salix humboldtiana used for passive monitoring of air quality in the city of Loja.
Figure 2. Salix humboldtiana used for passive monitoring of air quality in the city of Loja.
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Table 1. Mean concentration (mg Kg−1); standard deviation; Kruskal–Wallis; and p-value of Cd, Cr, Cu, Fe, Ni, Pb, Mn, Zn, and Al in Salix humboldtiana and data of heavy metal concentrations in other species.
Table 1. Mean concentration (mg Kg−1); standard deviation; Kruskal–Wallis; and p-value of Cd, Cr, Cu, Fe, Ni, Pb, Mn, Zn, and Al in Salix humboldtiana and data of heavy metal concentrations in other species.
Heavy MetalS. humboldtiana (S)S. humboldtiana (C)S. humboldtiana (N)S. humboldtiana (F)Ficus enjaminaAesculus hippocastanumTilia sp.Lolium multiflorumTrifolium pratenseRumex acetosaAmaranthus retroflexusPlantago lanceolataKWp Value
Cd0.40 ± 0.600.21 ± 0.140.45 ± 0.340.26 ± 0.31 0.2–4.90.9–1.413.3 ± 4.47.04 ± 0.3521.6 ± 4.915.5 ± 3.618 ± 105.170.1597
Cr2.94 ± 1.0862.59 ± 0.5214.17 ± 2.302.62 ± 0.951910.330.02 10.580.01423
Cu17.234 ± 6.602<LOD<LOD<LOD237.813.1–110.210.3–41.4 12.62NA
Fe394.69 ± 134.16337.03 ± 87.77505.24 ± 140.43306.08 ± 195.33 183–439.6105.9–324.5 17.340.0009
Ni<LOD<LOD0.187 ± 0.73<LOD69.6 1017 ± 405507 ± 54 1397 ± 207820 ± 2261022 ± 7273NA
Pb0.03 ± 0.0510.005 ± 0.020.028 ± 0.100.031 ± 0.091565.35–20.31.88–11.4175 ± 25120.5 ± 1.4704 ± 387463 ± 153407 ± 3207.010.07148
Mn0.07 ± 0.0940.124 ± 0.090.084 ± 0.110.362 ± 0.28 66.9–112.3 23.832.711
Zn0.07 ± 0.0470.059 ± 0.220.040 ± 0.290.057 ± 0.28654.317.2–47.115.2–28.63131 ± 12911727 ± 1983756 ± 6182754 ± 4653244 ± 193619.190.00025
Al0.25 ± 0.0930.218 ± 0.060.456 ± 0.530.271 ± 0.15 10.910.01223
Note: <LOD: limit of detection (<0.001). NA: no statistically significant difference.
Table 2. Dunn’s test for metal accumulation in Salix humboldtiana according to the different study areas.
Table 2. Dunn’s test for metal accumulation in Salix humboldtiana according to the different study areas.
Zones/Heavy MetalFePbCdCrMnZnAl
C vs. S
Ctrl vs. S 00.0001
N vs. S
C vs. N0.0117 0.0216 0.0038
Ctrl vs. N0.0002 0.01030.00020.0117
C vs. Ctrl 0.0245
Note: Ctrl = control, S = south, C = center, N = north.
Table 3. Vehicular traffic by zones.
Table 3. Vehicular traffic by zones.
HourZonesLocalityLDVHDVMS
08:20SouthArgelia18510523
09:00SouthTebaida1959025
09:40SouthCabo Minacho2556232
Total63525780
10:15CenterCatedral-10 Agosto3008033
10:55CenterParque Bolívar63529586
11.30 Center Iess40713042
Total1342505161
09:25NorthAmable María85324
10:00NorthSauces Norte1514616
10:40NorthTerminal63910440
Total87518260
09:00ControlToma De Agua “El Carmen”1020
10:15ControlEl Carmen430
11:15ControlSendero “Zamora Huayco”24116
Total38166
Note: LDV = light-duty vehicles, HDV = heavy-duty vehicles, MS = motorcycles and scooters.
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Benítez, Á.; Ordóñez, D.; Calva, J. Salix humboldtiana as an Indicator of Air Pollution by Trace Metals in the Urban Areas of the City of Loja, Southern Ecuador. Atmosphere 2024, 15, 1160. https://doi.org/10.3390/atmos15101160

AMA Style

Benítez Á, Ordóñez D, Calva J. Salix humboldtiana as an Indicator of Air Pollution by Trace Metals in the Urban Areas of the City of Loja, Southern Ecuador. Atmosphere. 2024; 15(10):1160. https://doi.org/10.3390/atmos15101160

Chicago/Turabian Style

Benítez, Ángel, Diego Ordóñez, and James Calva. 2024. "Salix humboldtiana as an Indicator of Air Pollution by Trace Metals in the Urban Areas of the City of Loja, Southern Ecuador" Atmosphere 15, no. 10: 1160. https://doi.org/10.3390/atmos15101160

APA Style

Benítez, Á., Ordóñez, D., & Calva, J. (2024). Salix humboldtiana as an Indicator of Air Pollution by Trace Metals in the Urban Areas of the City of Loja, Southern Ecuador. Atmosphere, 15(10), 1160. https://doi.org/10.3390/atmos15101160

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