Zn concentrations and Zn stable isotopes fractionation in snow, glacier ice, and glacier water from high mountains in central Mexico (Iztaccíhuatl and Citlaltépetl): Implications for Zn sources and atmospheric trajectories

Zn concentrations and Zn stable isotopes fractionation in snow, glacier ice, and glacier water from high mountains in central Mexico (Iztaccíhuatl and Citlaltépetl): Implications for Zn sources and atmospheric trajectories | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Zn concentrations and Zn stable isotopes fractionation in snow, glacier ice, and glacier water from high mountains in central Mexico (Iztaccíhuatl and Citlaltépetl): Implications for Zn sources and atmospheric trajectories D. K. Calvo-Ramos, A. Carrillo-Chávez, L. F. Rueda-Garzón, L. Corona-Martínez, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9226638/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract This study investigates the elemental and isotopic composition of zinc (Zn) in snow, glacial ice, and glacial meltwater from two high-altitude volcanic regions in central Mexico: Iztaccíhuatl (5215 m a.s.l.) and Citlaltépetl (5610 m a.s.l.). Zn concentrations ranged from 0.01 ppb in ice and snow to 0.89 ppb in glacial water, with the highest concentration measured in the “Agua Piedra Grande” sample. Stable isotope ratios of Zn (δ⁶⁶Zn) measured via MC-ICP-MS revealed significant fractionation, ranging from − 1.66 to + 0.65‰. Iztaccíhuatl samples were enriched in heavier isotopes (up to + 0.65‰), consistent with atmospheric input from nearby urban-industrial centers and volcanic emissions. Typically, isotopic compositions become lighter relative to their starting values when heated. The residual condensate or pool (depending on concentration and partitioning) would be heavier. Smelting produces a lighter Zn isotope composition. Corresponds to Raeleigh fractionation (Ochoa et al., 2016 ). Conversely, Citlaltépetl samples exhibited more negative δ⁶⁶Zn values (down to − 0.40‰), attributed to enhanced leaching and bedrock interactions. HYSPLIT air mass trajectories corroborated aerosol transport from Mexico City, Puebla, and Coatzacoalcos. The findings are like glacial Zn studies in the Alps, Andes, and Himalayas, which reflect isotopic signatures of both anthropogenic and lithospheric sources. These results provide novel insight into Zn mobilization and isotopic fractionation in tropical glaciers, with implications for environmental monitoring, water resource management, and atmospheric pollution tracing. Zinc stable isotopes natural vs anthropogenic sources geochemical glaciology environmental monitoring Mexican high mountains Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Zinc (Zn) is an essential trace element involved in biological and geochemical processes (Black et al., 2011 ; International Atomic Energy Agency -IAEA-, 2018). However, its elevated concentrations in the environment are increasingly linked to industrial emissions, fossil fuel combustion, and agricultural runoff. While Zn is naturally present in atmospheric aerosols, anthropogenic inputs in urban and volcanic regions can affect its biogeochemical cycling, especially in high-mountain ecosystems that serve as natural archives of atmospheric deposition (van Kooten & Moynier, 2019 ; Borrok et al., 2007 ). In recent decades, stable isotope analysis (particularly δ⁶⁶Zn/⁶⁴Zn) has emerged as a robust tool to trace Zn sources and transformations (Fekiacova et al., 2015 ; van Kooten & Moynier, 2019 ; Voldrichova et al., 2014 ; Bullen, 2011 ; Black et al., 2011 ). Multiple Collector Inductively Coupled Plasma Mass Spectrometry (MC-ICP-MS) now enables high-precision isotopic measurements, revealing whether Zn is derived from crustal materials, industrial aerosols, or urban particulates (Borrok et al., 2007 ; Black et al., 2011 ; Moynier & Le Borgne, 2015 ; Araújo et al., 2019 ; Wang et al., 2023 ). However, limited isotopic approaches have been applied to tropical glacier systems, particularly in Mexico, where industrial corridors and active volcanism converge. Zinc isotopes have proven to be effective tracers in various ecosystems, both contaminated and uncontaminated (Bullen, 2011 ). However, the effectiveness of δ 66 Zn as a tracer can be limited. When the isotopic compositions of potential Zn sources are not well defined, it can be difficult to accurately determine source contributions in a given area (International Atomic Energy Agency - IAEA -, 2018). Atmospheric deposition is a primary pathway for pollutants to enter ecosystems, occurring by both wet and dry deposition. Wet deposition includes vertical forms (rain and snow) and horizontal forms (fog and ice accumulation). Dry deposition is enhanced on rough surfaces and can contribute significantly to pollutant accumulation. Larger particles tend to be deposited closer to the source, while smaller particles can be transported over longer distances. Studying metals (concentrations and isotopic compositions) in glaciers is crucial for understanding the environment and the impacts of climate change (Zheng et al., 2023 ). Glaciers serve as natural reservoirs, storing water and contaminants like snow and ice over extended periods. Analyzing samples for Zn concentrations and isotopic composition ( 66 Zn/ 64 Zn) in snow and glacial water from Iztaccíhuatl and Citlaltépetl provides valuable insight into the sources and processes of contamination in these environments. The presence of Zn in glaciers can indicate the influence of anthropogenic activities, such as mining, industry, and vehicular traffic, which release Zn into the environment (Liang et al., 2022; Packman et al., 2023 ). By studying Zn concentrations and isotopic variations, it is possible to identify potential contamination sources and assess their impacts on glacial ecosystems and freshwater reserves. Ice accumulation in industrial areas often exhibit higher metal concentrations than snow. While some studies have examined the isotopic composition of Zn in snow and ice accumulations, further research is needed to fully characterize these isotopes in both accumulation types. This information can then be used to inform policies and mitigation strategies aimed at protecting these valuable natural resources. This study aims to evaluate Zn concentrations and isotope fractionation in snow, ice, and meltwater from Iztaccíhuatl and Citlaltépetl volcanoes. By integrating MC-ICP-MS data with NOAA HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) atmospheric trajectory modeling, we identify Zn sources and deposition patterns, offering comparative insights to global glacial systems such as the Andes, Alps, and Himalayas. SITE DESCRIPTION Samples were collected in 2022 from two Mexican mountains (Fig. 1 ): Citlaltépetl, located between the states of Veracruz and Puebla, is the highest peak at 5,610 m above sea level. (CONANP, 2025 ). Iztaccíhuatl, located in central Mexico, is the country's third-highest mountain at 5,215 m above sea level. (CONANP, 2025 ). Snow samples were collected at a depth of 30 cm, ice cores were extracted with a 1.2-meter-deep auger, and glacial water samples were taken from surface locations. MATERIALS AND METHODS Materials, reagents, and sample preparation Snow, ice, and glacier water samples were collected from various locations on Iztaccíhuatl and Citlaltépetl. The samples were melted at room temperature and filtered through Millipore nitrocellulose membranes (0.45 µm pore size) under vacuum. Intra-grade HCl and HNO 3 were distilled using a Savillex DST-1000 to achieve the required concentration for column separation. Anion-exchange resin AG MP-1 (100–200 mesh) from Bio-Rad, with an exchange capacity of 1 meq/mL, was used (Borrok et al., 2007 ). All materials (columns, pipettes, Teflon beakers, and flasks) were pre-cleaned in 8 M HCl at 100°C for 12 hours, then rinsed with deionized water (18 MΩ). The AG MP-1 resin was washed 10 times with 8 M HCl, several times with 5% HNO 3 , and finally with deionized water. Homogeneous aliquots of the filtered water samples were evaporated and reconstituted with 1 mL of 10 M HCl (Borrok et al., 2007 ). The required volume of the evaporated sample was calculated based on the initial Zn concentration, determined using a Thermo iCAP 6500 Duo View ICP-OES, to ensure sufficient metal mass for isotopic analysis. Column separation procedure For Zn separation, columns were prepared with 3-mL transfer pipettes. The pipettes were modified by removing half of the bulb and cutting the tip to accommodate a frit (0.7 µm pore size). The modified pipettes were loaded with approximately 5 cm (0.85-1 mL) of Anion exchange resin AG MP-1 (100–200 mesh), as described by Borrok et al. ( 2007 ). The evaporated sample was reconstituted with 1 mL of 10 M HCl and loaded onto the column in a single step using a micropipette. The column was then eluted with 4 mL of 10 M HCl to remove most matrix cations and anions while retaining Cu, Zn, and Fe. All acid additions were performed in 0.5 or 1 mL increments, allowing sufficient time for elution between additions. The Cu fraction was eluted using 6 mL of 5 M HCl, followed by the Fe fraction using 4 mL of 1 M HCl. Finally, Zn was eluted using 4 mL of deionized water. The eluted Zn fractions were evaporated (100°C) to dryness, dissolved in 2% HNO 3 , re-evaporated, and re-dissolved in 2% HNO 3 to remove residual HCl before MC-ICP-MS analysis (Borrok et al., 2007 ). Zn stable isotopes analysis Zinc isotope analysis was performed at the USGS laboratories in Denver, Colorado, using a Nu instrument double-focusing, high-resolution MC-ICP-MS. Samples dissolved in 2% HNO 3 were introduced into the argon plasma via a desolvating nebulizer system (Nu Instruments DSN 100). The concentration of Zn solutions analyzed ranged from 12 to 50 µg/L, which was also the concentration of the Zn reference standard solution (JMC 3-0749-L). During isotopic measurements, all three masses were monitored using time-resolved software for ~ 360 s. Analysis times were optimized to achieve the best internal precision. Wash times between samples (using 2% HNO 3 ) were monitored and adjusted to ensure complete return to the background signal before subsequent analysis. The internal standard error (1σ/number of integrations) for each measurement of 66 Zn/ 64 Zn was approximately 0.004‰. Each unknown sample was bracketed by the JMC Zn standard solution (also passed through the column ion exchange system), and the isotopic results are expressed in parts per thousand using the delta notation (‰) relative to the average of the bracketed standards (JMCave), as shown in Eq. 1. HYSPLIT Trajectory Model Potential sources and trajectories of Zn in central Mexico were simulated using the HYSPLIT model ( https://www.arl.noaa.gov/hysplit/ ). HYSPLIT, a comprehensive system for calculating air parcel trajectories, simulates transport, dispersion, chemical transformation, and deposition (García et al., 2020 ). This model is freely available from the U.S. NOAA ( https://www.ready.noaa.gov/HYSPLIT_applehysp.php ). RESULTS AND DISCUSSION Elemental composition of samples Zinc concentrations in snow and ice samples were consistently low, averaging around 0.01 ppb (Table 2), suggesting low Zn concentrations from atmospheric deposition. In contrast, glacial meltwater exhibited significantly higher and more variable Zn concentrations, ranging from 0.05 to 0.89 ppb. The highest concentration was recorded in the “Agua Piedra Grande” water sample, indicating possible contributions from substrate leaching, erosion, or anthropogenic contamination. Snow samples from Iztaccíhuatl resulted in a broader concentration range (up to 0.07 ppb), likely reflecting spatial heterogeneity in aerosol deposition or differences in local substrate chemistry. In comparison, both snow and ice samples from Citlaltépetl showed consistently low concentrations (~ 0.01 ppb), suggesting more stable chemical conditions and reduced influence from external Zn sources. The elevated Zn concentrations in glacial meltwater indicate increased zinc mobility in the liquid phase, potentially due to dissolution of mineral substrates, transport via suspended particulates, or surface inputs. The relative stability of Zn in the ice matrix indicates poor incorporation into crystalline structures, implying that Zn primarily exists in the dissolved or adsorbed form rather than as structural inclusions. Variations between glaciers may be attributed to differences in proximity to pollution sources, prevailing wind patterns, and geochemical characteristics of the underlying bedrock. Isotopic compositions of Zn The variability in δ 66 Zn isotope concentrations in snow, ice, and glacial water samples reveals fractionation processes and possible sources of Zn in the Iztaccíhuatl and Citlaltépetl glaciers, with values ranging from − 1.66 to 0.65‰ (Table 3). There is considerable variability in δ 66 Zn values; some samples exhibit high positive values, indicating enrichment in 66 Zn, while others display negative values, suggesting enrichment in 64 Zn. A notable difference is observed between the two volcanoes. At Iztaccíhuatl, samples exhibit enrichment of 66 Zn (up to 0.65‰), suggesting a strong influence of atmospheric deposition. In contrast, at Citlaltépetl, some samples yielded negative δ 66 Zn values (down to -0.40‰), which may indicate differences in the sources of Zn deposited in each region. The Agua Piedra Grande sample (-1.66‰ in δ 66 Zn) suggests fractionation during mobilization, possibly due to mineral leaching or chemical erosion, or a geogenic Zn isotopic signature. This contrasts with other glacial water samples, where the values are less negative. The variability in ice core samples is lower, with δ 66 Zn values ranging from − 0.09‰ to 0.18‰. This supports the theory that Zn trapped in the ice undergoes minimal fractionation, possibly reflecting a mixture of initial atmospheric deposition. Figure 2 illustrates the positive and negative isotopic compositions of each sample with respect to concentration. Samples with positive values indicate that Zn deposition is enriched in 66 Zn. In contrast, negative values in glacial water may reflect leaching and mobilization of light Zn, likely influenced by mineral dissolution and transport in the liquid phase. The extreme difference observed in Agua Piedra Grande suggests that Zn in glacial water originates from melting ice and is highly influenced by interactions with the rock substrate. The atmospheric source most enriched in heavy Zn at Iztaccíhuatl is possibly related to aerosols of volcanic, industrial, or urban origin. The very negative Zn isotopic composition in glacial water at Citlaltépetl may indicate a strong influence of erosion and leaching processes from the glacial bed on Zn isotopic composition. The negative values observed in ice and glacial water at Citlaltépetl suggest that the initially deposited Zn undergoes removal of heavier isotopes during its mobilization within the glacial system. Figure 3 illustrates that samples with low Zn concentrations (~ 0.01 ppb) exhibit high variability in δ 66 Zn. This suggests that the total Zn content does not directly control isotopic fractionation but rather reflects mobilization, deposition, and leaching processes, or that it reflects fractionation among multiple sources. In contrast, the glacial water sample “Agua Piedra Grande” has the highest Zn concentration (0.89 ppb) along with the most negative isotopic value for δ 66 Zn of -1.66‰. This may indicate that Zn in glacial water is more reflective of local mineral dissolution and chemical erosion. Ice core samples exhibit isotopic values close to zero and generally low Zn concentrations (~ 0.01 ppb). This suggests that Zn trapped in the ice has not undergone significant fractionation and instead reflects initial Zn composition in the snow before compaction. Figure 4 presents histograms for each sample type (snow, glacial water, and ice). Negative values in specific samples may indicate preferential zinc fractionation, potentially influenced by temperature, dissolution, or precipitation processes. Variability in core samples could reflect seasonal changes or the uptake of atmospheric contaminants. Variations in δ 66 Zn isotope concentrations in snow, glacial water, and ice samples can be influenced by several biogeochemical processes. During precipitation and snow accumulation, zinc may undergo isotopic fractionation depending on its source and atmospheric conditions. Adsorption onto atmospheric particles or selective deposition can generate differences in δ 66 Zn values. The deposition of aerosols, dust, and other contaminants on glacier surfaces can introduce zinc with distinct isotopic signatures. The presence of anthropogenic or natural contaminants may alter δ 66 Zn values in ice and meltwater, as observed in these results. Comparative Global Context The zinc (Zn) concentrations and δ⁶⁶Zn isotopic signatures observed in the Iztaccíhuatl and Citlaltépetl glaciers in central Mexico are consistent with, yet uniquely complex relative to, those reported in other high-altitude glacier systems worldwide. This global comparison contextualizes the influence of natural and anthropogenic Zn sources under varying geoclimatic conditions. In the Alps, Zn enrichment in glacial meltwaters is primarily attributed to industrial aerosols and vehicular emissions transported from the Po Valley and central Europe. Fekiacova et al. ( 2015 ) reported δ⁶⁶Zn values ranging from + 0.2‰ to + 0.4‰ in snow and runoff from alpine glaciers. These values suggest deposition of Zn-rich fine aerosols enriched in heavier isotopes, consistent with Iztaccíhuatl glacier data (+ 0.65‰), where urban and volcanic emissions dominate. Seasonal snow accumulation in the Alps also displays clear δ⁶⁶Zn shifts in response to regional pollution events (Zhao et al., 2019 ). Andean glacier systems, particularly in Patagonia and northern Chile, are heavily influenced by geogenic sources such as mining and natural rock weathering. Fernández-Martínez et al. ( 2022 ) recorded δ⁶⁶Zn values ranging from − 0.5‰ to − 1.1‰ in meltwaters proximal to mining districts, reflecting isotopically light Zn mobilized via mineral leaching and sulfide oxidation. This isotopic depletion closely resembles the negative δ⁶⁶Zn values (down to − 1.66‰) observed in Citlaltépetl meltwater (e.g., the Agua Piedra Grande sample), where Zn appears to be liberated from bedrock weathering and substrate interaction processes. In the Himalayan region, especially near the Indo-Gangetic Plain, long-range atmospheric transport from coal combustion and biomass burning contributes both particulate and soluble Zn. Zhang et al. ( 2021 ) observed δ⁶⁶Zn values in glacial snow and meltwater ranging from − 0.3‰ to + 0.5‰, with seasonal peaks during post-monsoon deposition and anthropogenic haze events. This range reflects a complex mix of isotopically heavy anthropogenic emissions and lighter natural contributions. The Mexican glaciers show similar dual-source signals, urban-industrial emissions (Iztaccíhuatl) and natural bedrock dissolution (Citlaltépetl). Studies in the Colorado Rockies also highlight anthropogenic Zn input from regional industrial activity and transboundary air pollution. Bullen & Walczyk ( 2009 ) noted δ⁶⁶Zn variability up to ± 0.6‰ in snowpacks, suggesting both source heterogeneity and post-depositional transformations. While less directly comparable in geologic setting, these studies affirm that snowpacks are dynamic reservoirs of trace metal isotope signatures. HYSPLIT Trajectory Model and Atmospheric Source Attribution The distribution and isotopic composition of zinc (Zn) in high-mountain environments are strongly influenced by atmospheric transport mechanisms, including the origin, trajectories, and residence times of air masses before deposition. To evaluate the potential sources and transport pathways of Zn-bearing aerosols reaching the Iztaccíhuatl and Citlaltépetl glaciers, the NOAA HYSPLIT model was employed. This model calculates air parcel trajectories using meteorological reanalysis data, allowing for the identification of dominant wind patterns and potential upwind source regions. Figure 5 presents 72-hour backward trajectory simulations for both study sites, modeling air mass movement during key snowfall events in 2022. These trajectories provide crucial insights into the origin of Zn inputs observed in glacial snow and meltwater. Citlaltépetl Site (Fig. 5 a) Citlaltépetl, situated along the transition zone between the Gulf of Mexico coastal plain and the Mexican Central Highlands, receives air masses originating from multiple regional sectors. HYSPLIT trajectories for this site frequently pass through: Sugarcane-producing regions in Veracruz, where seasonal biomass burning contributes particulate emissions. The Coatzacoalcos–Minatitlán industrial corridor, approximately 300 km to the southeast is home to major petrochemical complexes, oil-refining infrastructure, and heavy metal emissions (SEMARNAT, 2021 ). Eastern urban zones and agricultural areas, adding further contributions of combustion-derived Zn. These sources are likely responsible for the Zn concentrations and isotopic signatures (e.g., negative δ⁶⁶Zn values in glacial water), particularly those linked to pyrometallurgical aerosols and leachates from mineralized soils. Iztaccíhuatl Site (Fig. 5 b) In contrast, Iztaccíhuatl is located within 50 km of two major anthropogenic emission hotspots: Mexico City, a metropolitan area with over 20 million residents, is a known emitter of Zn through traffic (tire and brake wear), industrial processes, construction dust, and landfill incineration (Chow et al., 2019 ): Puebla, another significant urban center contributing mixed industrial and vehicular emissions. HYSPLIT simulations also show that air masses often travel over or near the Popocatépetl volcano, which is less than 20 km from the glacier. Volcanic degassing and explosive eruptions introduce metal-rich aerosols, including Zn, Cd, and Pb, into the local atmosphere. Volcanic ash transport via prevailing winds could contribute to the enriched δ⁶⁶Zn values observed in snow samples from Iztaccíhuatl (+ 0.65‰). The frequent convergence of volcanic plumes and anthropogenic pollutants in this region complicates the interpretation of Zn deposition signatures, creating a layered isotopic signal. The HYSPLIT modeling underscores the contrasting atmospheric regimes influencing Zn deposition at each site: Citlaltépetl receives a higher proportion of Zn from regional combustion and geogenic leaching (light isotopes). Iztaccíhuatl is exposed to dense urban-industrial plumes and volcanic fallout (heavy isotopes). This dual-source scenario is critical for interpreting the spatial variability in Zn isotopic data. It also supports the use of isotopic fingerprinting, combined with atmospheric trajectory modeling, to apportion trace metals in glacier environments. CONCLUSIONS This study demonstrates that the elemental and isotopic composition of zinc (Zn) in snow, glacier ice, and meltwater from the Iztaccíhuatl and Citlaltépetl volcanoes is shaped by complex environmental and geochemical processes. The observed variability in δ⁶⁶Zn values reflects diverse deposition regimes, mobilization pathways, and Zn-substrate interactions, resulting in distinct isotopic signatures between the two glacier systems. At Iztaccíhuatl, enrichment in heavier Zn isotopes suggests a dominant contribution from atmospheric deposition, particularly aerosols of volcanic, industrial, and urban origins. In contrast, Citlaltépetl exhibits isotopic depletion in glacial waters, indicative of Zn mobilization through mineral dissolution and bedrock leaching. The highly negative δ⁶⁶Zn value recorded in the Agua Piedra Grande sample highlights the significant role of weathering and erosion in controlling Zn release and isotopic fractionation in meltwater. Ice core samples, showing minimal isotopic variability, likely preserve the original Zn composition derived from atmospheric inputs, with limited alteration during firnification and glacial evolution. This underscores the role of tropical glaciers not only as climate-sensitive water reserves but also as complex geochemical integrators of metal inputs. Future work should incorporate time-series sampling, air mass back-trajectory modeling, and complementary trace elements to refine source apportionment and assess the long-term impacts of Zn dynamics in glacier-fed ecosystems. Declarations Author Contribution Carrillo-Chávez, A. Prepare original draft and outline, project responsible.Calvo-Ramos, D. Worked in the methodology development, final writing, prepared figures .Rueda-Garzon, F. Help in prepare figures and references review.Corona-Martinez, L. Worked in the methodology development.Muños-Torres, C. Worked in the methodology development.Gutierrez-Ruiz, M. Worked in the methodology development.Cisneros-Gómez, A. Worked in the methodology development.García-Martínez, R. Worked in the methodology development.All authors reviewed the manuscript. Acknowledgement We extend our sincere appreciation to Michael Pribil and Danny Rutherford of the U.S. Geological Survey’s Laboratory of Geochemistry of Stable Isotopes in Denver, Colorado, for their invaluable training, guidance, and supervision in the measurement of Zn isotopes, as well as for their critical review and refinement of the final manuscript. We are deeply grateful to the members of the “Grupo Geoquímica Montañismo UNAM” for their enthusiastic support and collaboration during fieldwork and ice core drilling on the Citlaltépetl and Iztaccíhuatl glaciers. Special thanks to: Jaime Carrera, Dora Carreón, Erandi Cerca, Gabriela Ponce (“Gaby”), Lorenzo Ortíz (“Lencho”), Juan Carlos Gómez de la Fuente (“Jano”), Samael Oliver (“Sama”), Javier Cortés Rosas, Julio Zacatzi, Daniela Montaño (“Dany”), Jehú Hinojosa, Eber Ramírez (“Gerber”), Jonatán Hortelano (“Jona”), Libertad Barrón, Luis Acosta, and Raúl Gómez—for their hard work, camaraderie, and enduring friendship. This research was made possible through funding from the UNAM-PAPIIT project IN110421, “Concentrations and isotopic fractionation of Zn and Hg in rainwater and high-mountain glacial ice: geochemical processes, sources, and trajectories of metals in central Mexico,” and the CONAHCyT (now SECITHI México) project CBF2023-2024-1068, “Stable isotope geochemistry of heavy metals (Zn, Cu, Hg): environmental applications, mineral exploration, and health sciences (medical geochemistry),” both awarded to Dr. Alejandro Carrillo-Chávez. We also acknowledge the foundational work on Zn stable isotopes at the Instituto de Geociencias, UNAM, made possible by a PASPA-DGAPA, UNAM sabbatical grant awarded to Alejandro Carrillo-Chávez (January 2017 – January 2018). Finally, we express our heartfelt thanks to Joaquín Canchola (“Don Canchola”) and his generous family in Tlachichuca (Summit Orizaba), and Roberto Flores Rodríguez (“El Oso”) and his exceptional team from San Miguel Zoapan (Orizaba Mountain Guides), Puebla, for their many years of field support, transportation, lodging, meals, and unwavering friendship. Data Availability Partial data are included in the paperAll isotopic data supporting the findings of this study are available within the paper in Table 1. References Araújo DF, Ponzevera E, Briant N, Knoery J, Sireau T, Mojtahid M, Brach-Papa C (2019) Assessment of the metal contamination evolution in the Loire estuary using Cu and Zn stable isotopes and geochemical data in sediments. 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Atmos Environ 262:118613. https://doi.org/10.1016/j.atmosenv.2021.118613 Zhao Y et al (2019) Tracing pollution sources in Alpine snow using Zn isotopes. Chem Geol 511:60–70. https://doi.org/10.1016/j.chemgeo.2019.02.008 Zheng K, Li Y, Wang N, Zhou Y, Li Z (2023) Pollution revealed by stable lead isotopes in recent snow from the northern and central Tibetan plateau. Ecotoxicol Environ Saf 263:115296. https://doi.org/10.1016/j.ecoenv.2023.115296 Tables Table 1 List of samples, date collected, site, location, type of sample, elevation, total Zn in ppm, 𝛿 66 Zn, and 𝛿 68 Zn Additional Declarations No competing interests reported. Supplementary Files GA.png Fig 0a. Graphical Abstract 1 Fig 0b. 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Carrillo-Chávez","email":"data:image/png;base64,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","orcid":"","institution":"Universidad Nacional Autónoma de México (UNAM)","correspondingAuthor":true,"prefix":"","firstName":"A.","middleName":"","lastName":"Carrillo-Chávez","suffix":""},{"id":633502253,"identity":"d8aff9ab-e1d1-4341-9442-9cbd41459ea0","order_by":2,"name":"L. F. Rueda-Garzón","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México (UNAM)","correspondingAuthor":false,"prefix":"","firstName":"L.","middleName":"F.","lastName":"Rueda-Garzón","suffix":""},{"id":633502254,"identity":"353f2476-a474-4c37-b61b-134ade504987","order_by":3,"name":"L. Corona-Martínez","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México (UNAM)","correspondingAuthor":false,"prefix":"","firstName":"L.","middleName":"","lastName":"Corona-Martínez","suffix":""},{"id":633502255,"identity":"d762a6ed-e17d-4c6a-a213-78445e9d18a7","order_by":4,"name":"C. Muñoz-Torres","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México (UNAM)","correspondingAuthor":false,"prefix":"","firstName":"C.","middleName":"","lastName":"Muñoz-Torres","suffix":""},{"id":633502256,"identity":"43e728de-63eb-479e-836a-ab4bab1b28b9","order_by":5,"name":"M. E. Gutiérrez Ruíz","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México (UNAM)","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"E. Gutiérrez","lastName":"Ruíz","suffix":""},{"id":633502257,"identity":"b013cec4-61eb-4eb2-8c66-a3c73be8955f","order_by":6,"name":"A. E. Cisneros Gómez","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México (UNAM)","correspondingAuthor":false,"prefix":"","firstName":"A.","middleName":"E. Cisneros","lastName":"Gómez","suffix":""},{"id":633502258,"identity":"761fd6e4-2c6f-448b-a467-286469dc6e8b","order_by":7,"name":"R. García-Martínez","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México (UNAM)","correspondingAuthor":false,"prefix":"","firstName":"R.","middleName":"","lastName":"García-Martínez","suffix":""}],"badges":[],"createdAt":"2026-03-25 19:23:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9226638/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9226638/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108494103,"identity":"8910797c-5a44-4d63-a2a9-59dd02935875","added_by":"auto","created_at":"2026-05-05 10:02:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":898484,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the Citlaltépetl and Iztaccíhuatl\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9226638/v1/b06b689b97e2f9a9aba6120c.png"},{"id":108459576,"identity":"edae8795-98f0-4482-9a99-0447eea14571","added_by":"auto","created_at":"2026-05-05 00:21:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":154682,"visible":true,"origin":"","legend":"\u003cp\u003e7\u003csup\u003e66/68\u003c/sup\u003eZn isotopic composition in glacial water, snow, and ice samples.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9226638/v1/ecab52eb7622c46aa950df2c.png"},{"id":108493767,"identity":"56fb5d21-470f-4840-ada7-5aeda0889d1f","added_by":"auto","created_at":"2026-05-05 10:01:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":147789,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the concentration of 7\u003csup\u003e66\u003c/sup\u003eZn and total Zn of the samples.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9226638/v1/c8cb667298dc98056c72c95a.png"},{"id":108803850,"identity":"1bc94cda-1a6e-4400-bd11-8d004d973eee","added_by":"auto","created_at":"2026-05-08 15:09:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":100236,"visible":true,"origin":"","legend":"\u003cp\u003eHistograms of 7\u003csup\u003e66\u003c/sup\u003eZn isotopic composition in glacial water, snow, and ice.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9226638/v1/0bd2c839c15067232a23bc87.png"},{"id":108459578,"identity":"ae19cf1a-621d-4b6e-a767-700b25337310","added_by":"auto","created_at":"2026-05-05 00:21:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 5. Model of the trajectories corresponding to the sampling sites in a) Citlaltépetl and\u003c/p\u003e\n\u003cp\u003eb) Iztaccíhuatl\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9226638/v1/ff208cf0f54e59d931ea6ebe.png"},{"id":108808943,"identity":"489bd43b-39a0-4929-a2fc-3997591470a7","added_by":"auto","created_at":"2026-05-08 15:48:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1727195,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9226638/v1/b1ff492b-e0b6-4d80-abfd-e32e34734bcb.pdf"},{"id":108459575,"identity":"4930f5dc-c1b8-4ef3-9c9e-2028da28bb8b","added_by":"auto","created_at":"2026-05-05 00:21:21","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":345753,"visible":true,"origin":"","legend":"\u003cp\u003eFig 0a. Graphical Abstract 1\u003c/p\u003e\n\u003cp\u003eFig 0b. Graphical Abstract 2\u003c/p\u003e","description":"","filename":"GA.png","url":"https://assets-eu.researchsquare.com/files/rs-9226638/v1/8b742c19cb7bb3ce33b2ae4f.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Zn concentrations and Zn stable isotopes fractionation in snow, glacier ice, and glacier water from high mountains in central Mexico (Iztaccíhuatl and Citlaltépetl): Implications for Zn sources and atmospheric trajectories","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eZinc (Zn) is an essential trace element involved in biological and geochemical processes (Black et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; International Atomic Energy Agency -IAEA-, 2018). However, its elevated concentrations in the environment are increasingly linked to industrial emissions, fossil fuel combustion, and agricultural runoff. While Zn is naturally present in atmospheric aerosols, anthropogenic inputs in urban and volcanic regions can affect its biogeochemical cycling, especially in high-mountain ecosystems that serve as natural archives of atmospheric deposition (van Kooten \u0026amp; Moynier, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Borrok et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn recent decades, stable isotope analysis (particularly δ⁶⁶Zn/⁶⁴Zn) has emerged as a robust tool to trace Zn sources and transformations (Fekiacova et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; van Kooten \u0026amp; Moynier, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Voldrichova et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Bullen, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Black et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Multiple Collector Inductively Coupled Plasma Mass Spectrometry (MC-ICP-MS) now enables high-precision isotopic measurements, revealing whether Zn is derived from crustal materials, industrial aerosols, or urban particulates (Borrok et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Black et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Moynier \u0026amp; Le Borgne, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ara\u0026uacute;jo et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, limited isotopic approaches have been applied to tropical glacier systems, particularly in Mexico, where industrial corridors and active volcanism converge.\u003c/p\u003e \u003cp\u003eZinc isotopes have proven to be effective tracers in various ecosystems, both contaminated and uncontaminated (Bullen, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, the effectiveness of δ\u003csup\u003e66\u003c/sup\u003eZn as a tracer can be limited. When the isotopic compositions of potential Zn sources are not well defined, it can be difficult to accurately determine source contributions in a given area (International Atomic Energy Agency - IAEA -, 2018).\u003c/p\u003e \u003cp\u003eAtmospheric deposition is a primary pathway for pollutants to enter ecosystems, occurring by both wet and dry deposition. Wet deposition includes vertical forms (rain and snow) and horizontal forms (fog and ice accumulation). Dry deposition is enhanced on rough surfaces and can contribute significantly to pollutant accumulation. Larger particles tend to be deposited closer to the source, while smaller particles can be transported over longer distances.\u003c/p\u003e \u003cp\u003eStudying metals (concentrations and isotopic compositions) in glaciers is crucial for understanding the environment and the impacts of climate change (Zheng et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Glaciers serve as natural reservoirs, storing water and contaminants like snow and ice over extended periods. Analyzing samples for Zn concentrations and isotopic composition (\u003csup\u003e66\u003c/sup\u003eZn/\u003csup\u003e64\u003c/sup\u003eZn) in snow and glacial water from Iztacc\u0026iacute;huatl and Citlalt\u0026eacute;petl provides valuable insight into the sources and processes of contamination in these environments. The presence of Zn in glaciers can indicate the influence of anthropogenic activities, such as mining, industry, and vehicular traffic, which release Zn into the environment (Liang et al., 2022; Packman et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). By studying Zn concentrations and isotopic variations, it is possible to identify potential contamination sources and assess their impacts on glacial ecosystems and freshwater reserves. Ice accumulation in industrial areas often exhibit higher metal concentrations than snow. While some studies have examined the isotopic composition of Zn in snow and ice accumulations, further research is needed to fully characterize these isotopes in both accumulation types. This information can then be used to inform policies and mitigation strategies aimed at protecting these valuable natural resources.\u003c/p\u003e \u003cp\u003eThis study aims to evaluate Zn concentrations and isotope fractionation in snow, ice, and meltwater from Iztacc\u0026iacute;huatl and Citlalt\u0026eacute;petl volcanoes. By integrating MC-ICP-MS data with NOAA HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) atmospheric trajectory modeling, we identify Zn sources and deposition patterns, offering comparative insights to global glacial systems such as the Andes, Alps, and Himalayas.\u003c/p\u003e\n\u003ch3\u003eSITE DESCRIPTION\u003c/h3\u003e\n\u003cp\u003eSamples were collected in 2022 from two Mexican mountains (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e): Citlalt\u0026eacute;petl, located between the states of Veracruz and Puebla, is the highest peak at 5,610 m above sea level. (CONANP, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Iztacc\u0026iacute;huatl, located in central Mexico, is the country's third-highest mountain at 5,215 m above sea level. (CONANP, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Snow samples were collected at a depth of 30 cm, ice cores were extracted with a 1.2-meter-deep auger, and glacial water samples were taken from surface locations.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMaterials, reagents, and sample preparation\u003c/h2\u003e \u003cp\u003eSnow, ice, and glacier water samples were collected from various locations on Iztacc\u0026iacute;huatl and Citlalt\u0026eacute;petl. The samples were melted at room temperature and filtered through Millipore nitrocellulose membranes (0.45 \u0026micro;m pore size) under vacuum. Intra-grade HCl and HNO\u003csub\u003e3\u003c/sub\u003e were distilled using a Savillex DST-1000 to achieve the required concentration for column separation. Anion-exchange resin AG MP-1 (100\u0026ndash;200 mesh) from Bio-Rad, with an exchange capacity of 1 meq/mL, was used (Borrok et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAll materials (columns, pipettes, Teflon beakers, and flasks) were pre-cleaned in 8 M HCl at 100\u0026deg;C for 12 hours, then rinsed with deionized water (18 MΩ). The AG MP-1 resin was washed 10 times with 8 M HCl, several times with 5% HNO\u003csub\u003e3\u003c/sub\u003e, and finally with deionized water. Homogeneous aliquots of the filtered water samples were evaporated and reconstituted with 1 mL of 10 M HCl (Borrok et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The required volume of the evaporated sample was calculated based on the initial Zn concentration, determined using a Thermo iCAP 6500 Duo View ICP-OES, to ensure sufficient metal mass for isotopic analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eColumn separation procedure\u003c/h3\u003e\n\u003cp\u003eFor Zn separation, columns were prepared with 3-mL transfer pipettes. The pipettes were modified by removing half of the bulb and cutting the tip to accommodate a frit (0.7 \u0026micro;m pore size). The modified pipettes were loaded with approximately 5 cm (0.85-1 mL) of Anion exchange resin AG MP-1 (100\u0026ndash;200 mesh), as described by Borrok et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe evaporated sample was reconstituted with 1 mL of 10 M HCl and loaded onto the column in a single step using a micropipette. The column was then eluted with 4 mL of 10 M HCl to remove most matrix cations and anions while retaining Cu, Zn, and Fe. All acid additions were performed in 0.5 or 1 mL increments, allowing sufficient time for elution between additions. The Cu fraction was eluted using 6 mL of 5 M HCl, followed by the Fe fraction using 4 mL of 1 M HCl. Finally, Zn was eluted using 4 mL of deionized water. The eluted Zn fractions were evaporated (100\u0026deg;C) to dryness, dissolved in 2% HNO\u003csub\u003e3\u003c/sub\u003e, re-evaporated, and re-dissolved in 2% HNO\u003csub\u003e3\u003c/sub\u003e to remove residual HCl before MC-ICP-MS analysis (Borrok et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eZn stable isotopes analysis\u003c/h3\u003e\n\u003cp\u003eZinc isotope analysis was performed at the USGS laboratories in Denver, Colorado, using a Nu instrument double-focusing, high-resolution MC-ICP-MS. Samples dissolved in 2% HNO\u003csub\u003e3\u003c/sub\u003e were introduced into the argon plasma via a desolvating nebulizer system (Nu Instruments DSN 100). The concentration of Zn solutions analyzed ranged from 12 to 50 \u0026micro;g/L, which was also the concentration of the Zn reference standard solution (JMC 3-0749-L). During isotopic measurements, all three masses were monitored using time-resolved software for ~\u0026thinsp;360 s. Analysis times were optimized to achieve the best internal precision. Wash times between samples (using 2% HNO\u003csub\u003e3\u003c/sub\u003e) were monitored and adjusted to ensure complete return to the background signal before subsequent analysis.\u003c/p\u003e \u003cp\u003eThe internal standard error (1σ/number of integrations) for each measurement of \u003csup\u003e66\u003c/sup\u003eZn/\u003csup\u003e64\u003c/sup\u003eZn was approximately 0.004\u0026permil;. Each unknown sample was bracketed by the JMC Zn standard solution (also passed through the column ion exchange system), and the isotopic results are expressed in parts per thousand using the delta notation (\u0026permil;) relative to the average of the bracketed standards (JMCave), as shown in Eq.\u0026nbsp;1.\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"498\" height=\"94\"\u003e\u003c/p\u003e\n\u003ch3\u003eHYSPLIT Trajectory Model\u003c/h3\u003e\n\u003cp\u003ePotential sources and trajectories of Zn in central Mexico were simulated using the HYSPLIT model \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arl.noaa.gov/hysplit/\u003c/span\u003e\u003cspan address=\"https://www.arl.noaa.gov/hysplit/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e HYSPLIT, a comprehensive system for calculating air parcel trajectories, simulates transport, dispersion, chemical transformation, and deposition (Garc\u0026iacute;a et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This model is freely available from the U.S. NOAA \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ready.noaa.gov/HYSPLIT_applehysp.php\u003c/span\u003e\u003cspan address=\"https://www.ready.noaa.gov/HYSPLIT_applehysp.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eElemental composition of samples\u003c/h2\u003e \u003cp\u003eZinc concentrations in snow and ice samples were consistently low, averaging around 0.01 ppb (Table\u0026nbsp;2), suggesting low Zn concentrations from atmospheric deposition. In contrast, glacial meltwater exhibited significantly higher and more variable Zn concentrations, ranging from 0.05 to 0.89 ppb. The highest concentration was recorded in the \u0026ldquo;Agua Piedra Grande\u0026rdquo; water sample, indicating possible contributions from substrate leaching, erosion, or anthropogenic contamination. Snow samples from Iztacc\u0026iacute;huatl resulted in a broader concentration range (up to 0.07 ppb), likely reflecting spatial heterogeneity in aerosol deposition or differences in local substrate chemistry. In comparison, both snow and ice samples from Citlalt\u0026eacute;petl showed consistently low concentrations (~\u0026thinsp;0.01 ppb), suggesting more stable chemical conditions and reduced influence from external Zn sources.\u003c/p\u003e \u003cp\u003eThe elevated Zn concentrations in glacial meltwater indicate increased zinc mobility in the liquid phase, potentially due to dissolution of mineral substrates, transport via suspended particulates, or surface inputs. The relative stability of Zn in the ice matrix indicates poor incorporation into crystalline structures, implying that Zn primarily exists in the dissolved or adsorbed form rather than as structural inclusions. Variations between glaciers may be attributed to differences in proximity to pollution sources, prevailing wind patterns, and geochemical characteristics of the underlying bedrock.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIsotopic compositions of Zn\u003c/h3\u003e\n\u003cp\u003eThe variability in δ\u003csup\u003e66\u003c/sup\u003eZn isotope concentrations in snow, ice, and glacial water samples reveals fractionation processes and possible sources of Zn in the Iztacc\u0026iacute;huatl and Citlalt\u0026eacute;petl glaciers, with values ranging from \u0026minus;\u0026thinsp;1.66 to 0.65\u0026permil; (Table\u0026nbsp;3). There is considerable variability in δ\u003csup\u003e66\u003c/sup\u003eZn values; some samples exhibit high positive values, indicating enrichment in \u003csup\u003e66\u003c/sup\u003eZn, while others display negative values, suggesting enrichment in \u003csup\u003e64\u003c/sup\u003eZn.\u003c/p\u003e \u003cp\u003eA notable difference is observed between the two volcanoes. At Iztacc\u0026iacute;huatl, samples exhibit enrichment of \u003csup\u003e66\u003c/sup\u003eZn (up to 0.65\u0026permil;), suggesting a strong influence of atmospheric deposition. In contrast, at Citlalt\u0026eacute;petl, some samples yielded negative δ\u003csup\u003e66\u003c/sup\u003eZn values (down to -0.40\u0026permil;), which may indicate differences in the sources of Zn deposited in each region.\u003c/p\u003e \u003cp\u003eThe Agua Piedra Grande sample (-1.66\u0026permil; in δ\u003csup\u003e66\u003c/sup\u003eZn) suggests fractionation during mobilization, possibly due to mineral leaching or chemical erosion, or a geogenic Zn isotopic signature. This contrasts with other glacial water samples, where the values are less negative. The variability in ice core samples is lower, with δ\u003csup\u003e66\u003c/sup\u003eZn values ranging from \u0026minus;\u0026thinsp;0.09\u0026permil; to 0.18\u0026permil;. This supports the theory that Zn trapped in the ice undergoes minimal fractionation, possibly reflecting a mixture of initial atmospheric deposition.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the positive and negative isotopic compositions of each sample with respect to concentration. Samples with positive values indicate that Zn deposition is enriched in \u003csup\u003e66\u003c/sup\u003eZn. In contrast, negative values in glacial water may reflect leaching and mobilization of light Zn, likely influenced by mineral dissolution and transport in the liquid phase. The extreme difference observed in Agua Piedra Grande suggests that Zn in glacial water originates from melting ice and is highly influenced by interactions with the rock substrate. The atmospheric source most enriched in heavy Zn at Iztacc\u0026iacute;huatl is possibly related to aerosols of volcanic, industrial, or urban origin. The very negative Zn isotopic composition in glacial water at Citlalt\u0026eacute;petl may indicate a strong influence of erosion and leaching processes from the glacial bed on Zn isotopic composition. The negative values observed in ice and glacial water at Citlalt\u0026eacute;petl suggest that the initially deposited Zn undergoes removal of heavier isotopes during its mobilization within the glacial system. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates that samples with low Zn concentrations (~\u0026thinsp;0.01 ppb) exhibit high variability in δ\u003csup\u003e66\u003c/sup\u003eZn. This suggests that the total Zn content does not directly control isotopic fractionation but rather reflects mobilization, deposition, and leaching processes, or that it reflects fractionation among multiple sources.\u003c/p\u003e \u003cp\u003eIn contrast, the glacial water sample \u0026ldquo;Agua Piedra Grande\u0026rdquo; has the highest Zn concentration (0.89 ppb) along with the most negative isotopic value for δ\u003csup\u003e66\u003c/sup\u003eZn of -1.66\u0026permil;. This may indicate that Zn in glacial water is more reflective of local mineral dissolution and chemical erosion. Ice core samples exhibit isotopic values close to zero and generally low Zn concentrations (~\u0026thinsp;0.01 ppb). This suggests that Zn trapped in the ice has not undergone significant fractionation and instead reflects initial Zn composition in the snow before compaction. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents histograms for each sample type (snow, glacial water, and ice). Negative values in specific samples may indicate preferential zinc fractionation, potentially influenced by temperature, dissolution, or precipitation processes. Variability in core samples could reflect seasonal changes or the uptake of atmospheric contaminants. Variations in δ\u003csup\u003e66\u003c/sup\u003eZn isotope concentrations in snow, glacial water, and ice samples can be influenced by several biogeochemical processes. During precipitation and snow accumulation, zinc may undergo isotopic fractionation depending on its source and atmospheric conditions. Adsorption onto atmospheric particles or selective deposition can generate differences in δ\u003csup\u003e66\u003c/sup\u003eZn values. The deposition of aerosols, dust, and other contaminants on glacier surfaces can introduce zinc with distinct isotopic signatures. The presence of anthropogenic or natural contaminants may alter δ\u003csup\u003e66\u003c/sup\u003eZn values in ice and meltwater, as observed in these results.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eComparative Global Context\u003c/h2\u003e \u003cp\u003eThe zinc (Zn) concentrations and δ⁶⁶Zn isotopic signatures observed in the Iztacc\u0026iacute;huatl and Citlalt\u0026eacute;petl glaciers in central Mexico are consistent with, yet uniquely complex relative to, those reported in other high-altitude glacier systems worldwide. This global comparison contextualizes the influence of natural and anthropogenic Zn sources under varying geoclimatic conditions.\u003c/p\u003e \u003cp\u003eIn the Alps, Zn enrichment in glacial meltwaters is primarily attributed to industrial aerosols and vehicular emissions transported from the Po Valley and central Europe.\u003c/p\u003e \u003cp\u003eFekiacova et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) reported δ⁶⁶Zn values ranging from +\u0026thinsp;0.2\u0026permil; to +\u0026thinsp;0.4\u0026permil; in snow and runoff from alpine glaciers. These values suggest deposition of Zn-rich fine aerosols enriched in heavier isotopes, consistent with Iztacc\u0026iacute;huatl glacier data (+\u0026thinsp;0.65\u0026permil;), where urban and volcanic emissions dominate. Seasonal snow accumulation in the Alps also displays clear δ⁶⁶Zn shifts in response to regional pollution events (Zhao et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAndean glacier systems, particularly in Patagonia and northern Chile, are heavily influenced by geogenic sources such as mining and natural rock weathering.\u003c/p\u003e \u003cp\u003eFern\u0026aacute;ndez-Mart\u0026iacute;nez et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) recorded δ⁶⁶Zn values ranging from \u0026minus;\u0026thinsp;0.5\u0026permil; to \u0026minus;\u0026thinsp;1.1\u0026permil; in meltwaters proximal to mining districts, reflecting isotopically light Zn mobilized via mineral leaching and sulfide oxidation. This isotopic depletion closely resembles the negative δ⁶⁶Zn values (down to \u0026minus;\u0026thinsp;1.66\u0026permil;) observed in Citlalt\u0026eacute;petl meltwater (e.g., the Agua Piedra Grande sample), where Zn appears to be liberated from bedrock weathering and substrate interaction processes.\u003c/p\u003e \u003cp\u003eIn the Himalayan region, especially near the Indo-Gangetic Plain, long-range atmospheric transport from coal combustion and biomass burning contributes both particulate and soluble Zn. Zhang et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) observed δ⁶⁶Zn values in glacial snow and meltwater ranging from \u0026minus;\u0026thinsp;0.3\u0026permil; to +\u0026thinsp;0.5\u0026permil;, with seasonal peaks during post-monsoon deposition and anthropogenic haze events. This range reflects a complex mix of isotopically heavy anthropogenic emissions and lighter natural contributions. The Mexican glaciers show similar dual-source signals, urban-industrial emissions (Iztacc\u0026iacute;huatl) and natural bedrock dissolution (Citlalt\u0026eacute;petl).\u003c/p\u003e \u003cp\u003eStudies in the Colorado Rockies also highlight anthropogenic Zn input from regional industrial activity and transboundary air pollution. Bullen \u0026amp; Walczyk (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) noted δ⁶⁶Zn variability up to \u0026plusmn;\u0026thinsp;0.6\u0026permil; in snowpacks, suggesting both source heterogeneity and post-depositional transformations. While less directly comparable in geologic setting, these studies affirm that snowpacks are dynamic reservoirs of trace metal isotope signatures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHYSPLIT Trajectory Model and Atmospheric Source Attribution\u003c/h2\u003e \u003cp\u003eThe distribution and isotopic composition of zinc (Zn) in high-mountain environments are strongly influenced by atmospheric transport mechanisms, including the origin, trajectories, and residence times of air masses before deposition. To evaluate the potential sources and transport pathways of Zn-bearing aerosols reaching the Iztacc\u0026iacute;huatl and Citlalt\u0026eacute;petl glaciers, the NOAA HYSPLIT model was employed. This model calculates air parcel trajectories using meteorological reanalysis data, allowing for the identification of dominant wind patterns and potential upwind source regions. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents 72-hour backward trajectory simulations for both study sites, modeling air mass movement during key snowfall events in 2022. These trajectories provide crucial insights into the origin of Zn inputs observed in glacial snow and meltwater.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCitlalt\u0026eacute;petl Site (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e5\u003c/span\u003ea)\u003c/h2\u003e \u003cp\u003eCitlalt\u0026eacute;petl, situated along the transition zone between the Gulf of Mexico coastal plain and the Mexican Central Highlands, receives air masses originating from multiple regional sectors. HYSPLIT trajectories for this site frequently pass through: Sugarcane-producing regions in Veracruz, where seasonal biomass burning contributes particulate emissions. The Coatzacoalcos\u0026ndash;Minatitl\u0026aacute;n industrial corridor, approximately 300\u003c/p\u003e \u003cp\u003ekm to the southeast is home to major petrochemical complexes, oil-refining infrastructure, and heavy metal emissions (SEMARNAT, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Eastern urban zones and agricultural areas, adding further contributions of combustion-derived Zn. These sources are likely responsible for the Zn concentrations and isotopic signatures (e.g., negative δ⁶⁶Zn values in glacial water), particularly those linked to pyrometallurgical aerosols and leachates from mineralized soils.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eIztacc\u0026iacute;huatl Site (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e5\u003c/span\u003eb)\u003c/h2\u003e \u003cp\u003eIn contrast, Iztacc\u0026iacute;huatl is located within 50 km of two major anthropogenic emission hotspots: Mexico City, a metropolitan area with over 20\u0026nbsp;million residents, is a known emitter of Zn through traffic (tire and brake wear), industrial processes, construction dust, and landfill incineration (Chow et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e): Puebla, another significant urban center contributing mixed industrial and vehicular emissions. HYSPLIT simulations also show that air masses often travel over or near the Popocat\u0026eacute;petl volcano, which is less than 20 km from the glacier. Volcanic degassing and explosive eruptions introduce metal-rich aerosols, including Zn, Cd, and Pb, into the local atmosphere. Volcanic ash transport via prevailing winds could contribute to the enriched δ⁶⁶Zn values observed in snow samples from Iztacc\u0026iacute;huatl (+\u0026thinsp;0.65\u0026permil;). The frequent convergence of volcanic plumes and anthropogenic pollutants in this region complicates the interpretation of Zn deposition signatures, creating a layered isotopic signal. The HYSPLIT modeling underscores the contrasting atmospheric regimes influencing Zn deposition at each site: Citlalt\u0026eacute;petl receives a higher proportion of Zn from regional combustion and geogenic leaching (light isotopes). Iztacc\u0026iacute;huatl is exposed to dense urban-industrial plumes and volcanic fallout (heavy isotopes).\u003c/p\u003e \u003cp\u003eThis dual-source scenario is critical for interpreting the spatial variability in Zn isotopic data. It also supports the use of isotopic fingerprinting, combined with atmospheric trajectory modeling, to apportion trace metals in glacier environments.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThis study demonstrates that the elemental and isotopic composition of zinc (Zn) in snow, glacier ice, and meltwater from the Iztacc\u0026iacute;huatl and Citlalt\u0026eacute;petl volcanoes is shaped by complex environmental and geochemical processes. The observed variability in δ⁶⁶Zn values\u003c/p\u003e \u003cp\u003ereflects diverse deposition regimes, mobilization pathways, and Zn-substrate interactions, resulting in distinct isotopic signatures between the two glacier systems. At Iztacc\u0026iacute;huatl, enrichment in heavier Zn isotopes suggests a dominant contribution from atmospheric deposition, particularly aerosols of volcanic, industrial, and urban origins. In contrast, Citlalt\u0026eacute;petl exhibits isotopic depletion in glacial waters, indicative of Zn mobilization through mineral dissolution and bedrock leaching. The highly negative δ⁶⁶Zn value recorded in the Agua Piedra Grande sample highlights the significant role of weathering and erosion in controlling Zn release and isotopic fractionation in meltwater. Ice core samples, showing minimal isotopic variability, likely preserve the original Zn composition derived from atmospheric inputs, with limited alteration during firnification and glacial evolution. This underscores the role of tropical glaciers not only as climate-sensitive water reserves but also as complex geochemical integrators of metal inputs.\u003c/p\u003e \u003cp\u003eFuture work should incorporate time-series sampling, air mass back-trajectory modeling, and complementary trace elements to refine source apportionment and assess the long-term impacts of Zn dynamics in glacier-fed ecosystems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eCarrillo-Ch\u0026aacute;vez, A. Prepare original draft and outline, project responsible.Calvo-Ramos, D. Worked in the methodology development, final writing, prepared figures .Rueda-Garzon, F. Help in prepare figures and references review.Corona-Martinez, L. Worked in the methodology development.Mu\u0026ntilde;os-Torres, C. Worked in the methodology development.Gutierrez-Ruiz, M. Worked in the methodology development.Cisneros-G\u0026oacute;mez, A. Worked in the methodology development.Garc\u0026iacute;a-Mart\u0026iacute;nez, R. Worked in the methodology development.All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe extend our sincere appreciation to Michael Pribil and Danny Rutherford of the U.S. Geological Survey\u0026rsquo;s Laboratory of Geochemistry of Stable Isotopes in Denver, Colorado, for their invaluable training, guidance, and supervision in the measurement of Zn isotopes, as well as for their critical review and refinement of the final manuscript. We are deeply grateful to the members of the \u0026ldquo;Grupo Geoqu\u0026iacute;mica Monta\u0026ntilde;ismo UNAM\u0026rdquo; for their enthusiastic support and collaboration during fieldwork and ice core drilling on the Citlalt\u0026eacute;petl and Iztacc\u0026iacute;huatl glaciers. Special thanks to: Jaime Carrera, Dora Carre\u0026oacute;n, Erandi Cerca, Gabriela Ponce (\u0026ldquo;Gaby\u0026rdquo;), Lorenzo Ort\u0026iacute;z (\u0026ldquo;Lencho\u0026rdquo;), Juan Carlos G\u0026oacute;mez de la Fuente (\u0026ldquo;Jano\u0026rdquo;), Samael Oliver (\u0026ldquo;Sama\u0026rdquo;), Javier Cort\u0026eacute;s Rosas, Julio Zacatzi, Daniela Monta\u0026ntilde;o (\u0026ldquo;Dany\u0026rdquo;), Jeh\u0026uacute; Hinojosa, Eber Ram\u0026iacute;rez (\u0026ldquo;Gerber\u0026rdquo;), Jonat\u0026aacute;n Hortelano (\u0026ldquo;Jona\u0026rdquo;), Libertad Barr\u0026oacute;n, Luis Acosta, and Ra\u0026uacute;l G\u0026oacute;mez\u0026mdash;for their hard work, camaraderie, and enduring friendship. This research was made possible through funding from the UNAM-PAPIIT project IN110421, \u0026ldquo;Concentrations and isotopic fractionation of Zn and Hg in rainwater and high-mountain glacial ice: geochemical processes, sources, and trajectories of metals in central Mexico,\u0026rdquo; and the CONAHCyT (now SECITHI M\u0026eacute;xico) project CBF2023-2024-1068, \u0026ldquo;Stable isotope geochemistry of heavy metals (Zn, Cu, Hg): environmental applications, mineral exploration, and health sciences (medical geochemistry),\u0026rdquo; both awarded to Dr. Alejandro Carrillo-Ch\u0026aacute;vez. We also acknowledge the foundational work on Zn stable isotopes at the Instituto de Geociencias, UNAM, made possible by a PASPA-DGAPA, UNAM sabbatical grant awarded to Alejandro Carrillo-Ch\u0026aacute;vez (January 2017 \u0026ndash; January 2018). Finally, we express our heartfelt thanks to Joaqu\u0026iacute;n Canchola (\u0026ldquo;Don Canchola\u0026rdquo;) and his generous family in Tlachichuca (Summit Orizaba), and Roberto Flores Rodr\u0026iacute;guez (\u0026ldquo;El Oso\u0026rdquo;) and his exceptional team from San Miguel Zoapan (Orizaba Mountain Guides), Puebla, for their many years of field support, transportation, lodging, meals, and unwavering friendship.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003ePartial data are included in the paperAll isotopic data supporting the findings of this study are available within the paper in Table 1.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAra\u0026uacute;jo DF, Ponzevera E, Briant N, Knoery J, Sireau T, Mojtahid M, Brach-Papa C (2019) Assessment of the metal contamination evolution in the Loire estuary using Cu and Zn stable isotopes and geochemical data in sediments. 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Ecotoxicol Environ Saf 263:115296. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecoenv.2023.115296\u003c/span\u003e\u003cspan address=\"10.1016/j.ecoenv.2023.115296\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003eList of samples, date collected, site, location, type of sample, elevation, total Zn in ppm, 𝛿\u003csup\u003e66\u003c/sup\u003eZn, and 𝛿\u003csup\u003e68\u003c/sup\u003eZn\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" 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Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Zinc stable isotopes, natural vs anthropogenic sources, geochemical glaciology, environmental monitoring, Mexican high mountains","lastPublishedDoi":"10.21203/rs.3.rs-9226638/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9226638/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the elemental and isotopic composition of zinc (Zn) in snow, glacial ice, and glacial meltwater from two high-altitude volcanic regions in central Mexico: Iztacc\u0026iacute;huatl (5215 m a.s.l.) and Citlalt\u0026eacute;petl (5610 m a.s.l.). Zn concentrations ranged from 0.01 ppb in ice and snow to 0.89 ppb in glacial water, with the highest concentration measured in the \u0026ldquo;Agua Piedra Grande\u0026rdquo; sample. Stable isotope ratios of Zn (δ⁶⁶Zn) measured via MC-ICP-MS revealed significant fractionation, ranging from \u0026minus;\u0026thinsp;1.66 to +\u0026thinsp;0.65\u0026permil;. Iztacc\u0026iacute;huatl samples were enriched in heavier isotopes (up to +\u0026thinsp;0.65\u0026permil;), consistent with atmospheric input from nearby urban-industrial centers and volcanic emissions. Typically, isotopic compositions become lighter relative to their starting values when heated. The residual condensate or pool (depending on concentration and partitioning) would be heavier. Smelting produces a lighter Zn isotope composition. Corresponds to Raeleigh fractionation (Ochoa et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Conversely, Citlalt\u0026eacute;petl samples exhibited more negative δ⁶⁶Zn values (down to \u0026minus;\u0026thinsp;0.40\u0026permil;), attributed to enhanced leaching and bedrock interactions. HYSPLIT air mass trajectories corroborated aerosol transport from Mexico City, Puebla, and Coatzacoalcos. The findings are like glacial Zn studies in the Alps, Andes, and Himalayas, which reflect isotopic signatures of both anthropogenic and lithospheric sources. These results provide novel insight into Zn mobilization and isotopic fractionation in tropical glaciers, with implications for environmental monitoring, water resource management, and atmospheric pollution tracing.\u003c/p\u003e","manuscriptTitle":"Zn concentrations and Zn stable isotopes fractionation in snow, glacier ice, and glacier water from high mountains in central Mexico (Iztaccíhuatl and Citlaltépetl): Implications for Zn sources and atmospheric trajectories","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-05 00:21:17","doi":"10.21203/rs.3.rs-9226638/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-23T03:29:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-27T07:17:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-27T07:17:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Earth Sciences","date":"2026-03-25T19:14:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-earth-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enge","sideBox":"Learn more about [Environmental Earth Sciences](https://www.springer.com/journal/12665)","snPcode":"12665","submissionUrl":"https://submission.nature.com/new-submission/12665/3","title":"Environmental Earth Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"26adb17d-0c39-4873-986e-bf6f6cb219a6","owner":[],"postedDate":"May 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T00:21:17+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-05 00:21:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9226638","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9226638","identity":"rs-9226638","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}