Abstract
Introduction:
High-altitude glaciers in the Western European Alps have yielded crucial records of anthropogenic air pollution, revealing a sharp rise in pollutant levels over the past two centuries due to industrialisation. In contrast, studies in the Eastern Alps have been scarce, as their lower-elevation glaciers were often considered less suitable for preserving undisturbed records. Nevertheless, recent findings indicate that, under specific conditions, cold ice frozen to bedrock can persist below 4,000 m. This is exemplified by the Weißseespitze (WSS) summit ice cap (3,499 m a.s.l.), which, despite ongoing surface mass loss, preserved a 6000-year-old record within just ∼10 m of ice depth.
Methods:
Building on earlier research, this study provides an expanded chemical dataset of the upper 8.5 m of the 9.95 m ice core drilled in 2019 (core 2), now including 18 trace elements (Li, V, Cr, Mn, Co, Ni, Cu, Zn, As, Rb, Sr, Ag, Cd, Ba, Tl, Pb, Bi, U), carboxylic and dicarboxylic acids, and a deepened discussion on ionic compounds, which refines the already published record. To differentiate between natural contributions and anthropogenic sources, a Positive Matrix Factorisation analysis was applied to the full dataset. This analysis was further supported by Enrichment Factors calculations, which helped to discriminate between crustal and non-crustal sources.
Results:
Thanks to the novel age-depth scale obtained with 39Ar dating, in addition to previous 14C ages, the glacier’s age-depth model was further refined, revealing that the glacier surface formed approximately years before 2019, while tying the prominent peak in chemistry found at 640 cm depth to about 891 years before 2019. Further insights on this horizon came from the comparison between the levoglucosan record, measured within the WSS ice core, and the micro-charcoal data available for the nearby Schwarzboden mire.
Discussion:
This study underscores the exceptional value of the WSS glacier as a long-term archive of pre-industrial pollution. Alarmingly, approximately 4.5 m of ice have been lost as of 2025, accelerating the disappearance of this archive. With industrial-era layers already lost due to ice mass reduction and projections showing 30% of Ötztal glaciers could vanish by 2030, preserving and studying these records appears increasingly urgent.
1 Introduction
Long-term historical records of anthropogenic air pollution are well-preserved in high-altitude glaciers of the Western European Alps, as confirmed by numerous ice core studies conducted over the past three decades (e.g., ; ; ; ; ; ). These records reveal a marked increase in anthropogenic aerosol components and trace pollutants over the past two centuries, closely linked to the onset of industrialisation, with pollutants transported from nearby regions (; , and references therein). In contrast, systematic, long-term studies of airborne anthropogenic compounds in the Eastern Alps are limited to the few sparse ice core records (; ; ; ).
Historically, ice cores were primarily collected from glaciers in the Western Alps (; ; ; ; ; ; ; ; ) due to their higher elevation and the presence of the cold firn zone, which effectively preserves environmental and climatic signals (; ; ). In contrast, lower-elevation glaciers in the Eastern Alps were considered unsuitable for preserving undisturbed ice cores due to melting and temperate basal conditions (). However, recent studies have shown that cold ice frozen to bedrock, under specific circumstances, can exist at elevations below 4,000 m in the Eastern Alps (; ; ). This is exemplified by the Weißseespitze (WSS) summit ice cap (3,499 m a.s.l.), which in 2019 still preserved about 6000 years of record within approximately 10 m of ice depth (; ). Despite ongoing ice loss, mainly driven by sublimation, combined with winter wind scouring that prevents accumulation during the colder winter months (), the chemical and isotopic records have been found to be well-preserved (). No supraglacial runoff systems were observed, nor any geomorphological evidence of meltwater flowing on or in the ice body, and water penetration appeared restricted to microcracks (Fisher et al., 2022). Nevertheless, no evidence of recent anthropogenic contamination was found at the surface, indicating that the topmost layers dated to the pre-industrial era (). Further insights on the surface age have recently been provided by 39Ar dating ().
In this study, we provide an expanded dataset from the upper 8.5 m of the 2019 Weißseespitze 9.95 m ice core, capturing a timeline from the Early Modern era (ca. 1641 CE) to the Roman Empire (ca. 128 CE). This record provides insights into long-term pre-industrial anthropogenic impacts through detailed profiles of 18 trace elements (TE) – Li, V, Cr, Mn, Co, Ni, Cu, Zn, As, Rb, Sr, Ag, Cd, Ba, Tl, Pb, Bi, and U–carboxylic (Acetic, Glycolic, Oxalic), and dicarboxylic acids (Malonic, Succinic), resulting from offline analysis of discrete samples collected during the 2022 melting campaign (). Given the extensive dataset available for the WSS ice core, source attribution was conducted using Positive Matrix Factorisation (PMF) to enhance data interpretation and identify potential anthropogenic contributions. Enrichment factors were also computed to better distinguish between crustal and non-crustal sources. Additionally, to address the unresolved question concerning the origin of the major chemistry peak at 640 cm depth (), a comparative analysis between the levoglucosan record from the 2019 WSS ice core and the micro-charcoal record from the nearby Schwarzboden mire was performed, revealing a notable correspondence that sheds new light on the region’s environmental history.
2 Methods and materials
2.1 Location and coring
2.1.1 Recent ice core drilling campaigns at the Weißseespitze glacier
The Weißseespitze ice cap (3,499 m a.s.l.), which covers the top sections of Gepatschferner glacier in the Austrian Alps, has recently hosted four drilling campaigns, which took place in 2019, 2021, 2023, and 2024, respectively, in the framework of Cold Ice and Cold Ice II projects (Supplementary Table S1). Cores drilled in March 2021 and March 2019 reached 8.7 m (core 2) and 9.95 m (core 2) depth to bedrock, respectively, encountering nearly flat bed conditions as confirmed by Ground-Penetrating Radar (GPR) measurements. They were analysed for water stable isotopes (δ18O, δ2H), levoglucosan, major ion chemistry, and micro-charcoal, finding a substantial absence of melting and refreezing processes on the cm-scale, and a distinct variability in the chemical and isotopic signals ().
During the 2023 and 2024 sampling campaigns, technical difficulties with the drilling equipment limited core recovery. As a result, only a shallow core was obtained in 2023, followed by two shallow cores and several surface samples in 2024 (Supplementary Table S1). By the time of the most recent field measurements in 2025, the ice thickness at the drilling site had decreased to about 5.5 m.
2.1.2 Schwarzboden mire
The Schwarzboden mire, located at 2150 m a.s.l. (46°40′29″ N; 10°45′10″ E, ∼110 m diameter) in the Maneid valley, a few kilometers southeast of the Weißseespitze glacier, hosted a sampling campaign in 2009, when a 110 cm peat core was extracted from the mire. Palynological and micro-charcoal analyses aimed to investigate ancient human impact in the sub-alpine region in the frame of the study conducted by .
2.2 Data used
This study combines previously published records, including micro-charcoal (), 39Ar and 14C based age–depth model () and levoglucosan record () with newly generated chemical data from the 2019 WSS ice core (trace elements and major ions). Details on data acquisition and analytical procedures are reported in the original publications and briefly summarised below.
2.2.1 Micro-charcoal analyses from the Schwarzboden mire
Samples for micro-charcoal and pollen analyses were contiguously at 1 cm resolution. Peat samples were prepared according to standard procedure in pollen analyses (see for details on preparation). Micro-charcoal particles were quantified along with pollens, as common practice in palynological studies. An updated age-depth model using the dates published in was established for the present study using the Bchron package version 4.7.6 () for R (). Micro-charcoal accumulation rates were calculated and plotted against the chronological model for comparison with WSS data.
2.2.2 Ice sample preparation, argon extraction and ATTA measurement
Five ice samples from the three shallow cores retrieved during the 2023 (Core 1, Supplementary Table S1) and 2024 (Core 1 and Core 2, Supplementary Table S1) sampling campaigns were measured for 39Ar. Their depths ranged between 2 m and 3.3 m below the 2019 surface ().
Sample preparation and argon extraction were carried out at the Institute of Environmental Physics, Heidelberg, following the procedure outlined by and . The ice was cleaned by cutting off the outermost 2.0 mm of ice to prevent any environmental contamination, and it was melted inside an evacuated 12.6 L stainless steel container. All non-noble gases were removed by titanium sponge getters to obtain >99% pure argon.
Measurements of 39Ar concentrations were performed in the ATTA laboratory at the Kirchhoff-Institute for Physics, Heidelberg, following the procedures described by and . Sample analyses were conducted over a 20-h period, with reference measurements - consisting of 2-h sessions using an enriched reference gas (10 RA) - taken before and after the sample measurements. Final data evaluation and age calculation included an atmospheric input function correction similar to the one reported by . The full information on the 39Ar analysis is reported in .
2.3 39Ar and 14C based age-depth attribution to levoglucosan record and archives intercomparison
The levoglucosan record retrieved from the WSS ice core (1.24 cm resolution) was linearly interpolated to match the 39Ar and 14C based age-depth relationship, ensuring a consistent resolution for analysis. The age-depth scale and levoglucosan measurements were indeed independently obtained from parallel ice cores analysed at Heidelberg University (ATTA team) and Ca’ Foscari University–CNR-ISP (CFA team), respectively. Data span from 23.76 cm to 858 cm depth, covering the most suitable interval for continuous analysis, thus excluding surface snow-firn and clustered debris at the core’s bottom. A linear interpolation was used to estimate the age of levoglucosan record along the ice core depth profile, based on the available age-depth model. This approach ensures a continuous and unbiased assignment of ages between dated horizons. Both the ice core and peat records were then interpolated onto a common temporal resolution to enable direct comparison of levoglucosan and micro-charcoal concentrations across synchronized time intervals. Once the levoglucosan and micro-charcoal records shared the same time scale, the data were normalised using a min-max scaling (between 0 and 1) for direct comparison.
To evaluate the robustness of this approach and assess potential uncertainties related to age interpolation, we performed a Monte Carlo simulation (n = 1,000 iterations), introducing Gaussian perturbations based on age-model uncertainties for both the ice core and peat core records. In each simulation, levoglucosan and micro-charcoal records were re-interpolated, normalised, and their respective peak ages identified. This procedure allowed us to estimate the probability distribution of peak timings for each proxy.
2.4 Chemical analyses on the 2019 WSS ice core
The 9.95 m WSS ice core (core 2), collected in March 2019, was processed at Ca’ Foscari University of Venice in collaboration with the National Research Council–Institute of Polar Science (CNR-ISP). From the top 8.5 m, deemed suitable for Continuous Flow Analysis (CFA), twenty-three ice sticks (bags) with 32 × 32 mm base sections were prepared. During the 2022 melting campaign, continuous measurements of levoglucosan were conducted alongside the collection of discrete samples for offline analysis of water stable isotopes (). Additionally, two sets of 346 discrete samples, with an average spatial resolution of approximately 2.6 cm, were collected for offline analysis of major ions (Na+, NH4+, K+, Mg2+, Ca2+, Cl−, NO3−, SO42−, MSA−, Br−), carboxylic acids (Acetic, Glycolic, Oxalic), dicarboxylic acids (Malonic, Succinic), and 18 trace elements, including Li, V, Cr, Mn, Co, Ni, Cu, Zn, As, Rb, Sr, Ag, Cd, Ba, Tl, Pb, Bi, and U. Given the time-intensive nature of completing all the offline analyses, only the major ion results were reported in the previous study by . Organic acid and trace element analyses were conducted thereafter, and their findings are presented here for the first time.
The quantification of organic acids (Acetic, Glycolic, Oxalic, Malonic, Succinic) and anionic species (Cl−, NO3−, SO42−, Br−, MSA−) was carried out using an ion chromatograph (IC, Thermo Scientific Dionex™ ICS-5000, Waltham, MA, USA) coupled with a single quadrupole mass spectrometer (MS, MSQ Plus™, Thermo Scientific, Bremen, Germany). The separation was performed using an anionic exchange column (Dionex Ion Pac AS 19 2 mm ID × 250 mm length) equipped with a guard column (Dionex Ion Pac AG19 2 mm ID × 50 mm length). Sodium hydroxide (NaOH), used as mobile phase, was produced by an eluent generator (Dionex ICS 5000EG, Thermo Scientific). The NaOH gradient with a 0.25 mL min−1 flow rate was: 0–6 min at 15 mM; 6–15 min gradient from 15 to 45 mM; 15–23 min column cleaning with 45 mM; 23–33 min equilibration at 15 mM. The injection volume was 100 μL. A suppressor (ASRS 500, 2 mm, Thermo Scientific) removed NaOH before entering the MS source. The IC-MS operated with a negative electrospray source (ESI) with a temperature of 500 °C and a needle voltage of 3 kV. The other MS parameters are reported by . To determine the cations (Na+, K+, Ca2+, and NH4+), a capillary ion chromatograph (Thermo Scientific Dionex ICS-5000) equipped with a capillary cation exchange column (Dionex IonPac CS19-4 μm, 0.4 × 250 mm) and a guard column (Dionex IonPac CG19- 4 μm, 0.4 × 50 mm) coupled to a conductivity detector was used. Methanesulfonic acid, produced by an eluent generator (Dionex ICS 5000EG, Thermo Scientific), was applied as the mobile phase. The gradient was 0–17.3 min: 1.5 mM; 17.3–21.9 min: from 1.5 to 11 mM; 21.9–30 min: equilibration at 1.5 mM. The injection volume was 0.4 µL and the flow rate was 13 μL min−1.
The quantification of trace elements was conducted on one out of the two sets (n = 346) of samples collected during the melting campaign. Aliquots were treated under a HEPA-laminar class 100 airflow bench, acidified with HNO3 2%, and analysed with an iCAP™ 7000 RQ ICP-MS (Thermo Scientific™, US) operating in standard mode (STD). This approach provided an optimal balance between sensitivity, efficiency, and cost while maintaining the required analytical rigor for studying trace element concentrations in ice cores. The instrument was equipped with an ASX-560 autosampler (Teledyne Cetac Technologies), a PolyPro PFE nebulizer (Elemental Scientific, Omaha, Nebraska), a PFE cyclonic spray chamber at 2.7 °C, sapphire injector, quartz torch, and Ni cones (ThermoFisher Scientific, Milan, Italy). Operating conditions included 1550 W plasma RF power and He as the collision gas (0.8 L min−1). Instrument tuning minimised oxides (<1%) and doubly charged species (<3%). Internal standard 103Rh (10 μg L−1) was used to correct for instrumental drift and interferences. Analytical blanks of HNO3 diluted at 2% in ultrapure water were included in the analysis, and the Method Detection Limit (MDL) was set to 3 times the standard deviation of the blank values. Checks for accuracy were made by running certified reference material CRM TMRAIN-04 every 10 samples, including blanks. This CRM was supplied by National Water Research Institute (NWRI) of Environmental Canada, and certified for 26 trace elements (ng g−1).
2.5 Positive matrix factorisation (PMF) and enrichment factors (EFs)
The PMF is an explicit least-squared approach developed by , employed to identify and allocate the major sources of a consistent group of analytes. Although typically used in numerous studies of source apportionment of particulate matter in ambient air (, and reference therein), it has shown potential for applications to ice cores, overcoming significant limitations in addressing environmental data issues (e.g., missing data, rotational ambiguities, detection limits), routinely encountered with principal component analysis (PCA) and related models (). Therefore, large datasets with over 100 samples, which exceed the number of variables by at least a factor of three (), are eligible to enhance the consistency between the actual and modelled source profiles, as well as the source contributions to pollution.
The Weißseespitze ice core dataset, partly populated by cationic (Na+, K+, Ca2+, and NH4+), anionic (Cl−, NO3, and SO42-), and levoglucosan records presented in , has been implemented with a group of trace elements (i.e., Li, Be, V, Cr, Mn, Co, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Ag, Cd, In, Ba, Tl, Pb, Bi, U), anions (Br−, MSA−), and organic acids (Acetic, Glycolic, Oxalic, Malonic, and Succinic). The complete dataset, which comprises the concentrations of identified chemical species (n = 37) for over 300 samples, was explored through the PMF method, with the EPA PMF 5.0 code, which applies the Multilinear Engine (ME-2) for its implementation. To minimise potential uncertainties, only directly measured variables were included in the analysis. Outliers have been identified and excluded, based on the quartile test. Missing values for each analyte were imputed using its median concentration, and values under the limits of detection (LODs) were substituted by half of LODs. Organic acids were summarised - and reported as “CA” (carboxylic acids) for simplicity - to offer a comprehensive perspective on their contribution while reducing bias caused by over 50% missing values. The uncertainty matrix was calculated using the PMF 5.0 guide formula, incorporating an additional 10% modelling uncertainty during the calculations. Notably, the uncertainties of determined values were computed as the sum of the measurement uncertainty and the method detection limit (MDL) divided by 3, while the uncertainties of missing values were four times the median values, and the uncertainties of values under the LOD were 5/6 LOD. Chemical species were categorised based on the signal-to-noise (S/N) criterion () and the percentage of data above detection limits (). All variables were classified as “strong” based on the S/N criterion, except for Ba, which was excluded due to “bad” S/N evaluation. Uncertainties in PMF results were assessed using the bootstrap method (100 runs). This approach confirmed the robustness of all identified chemical species.
To complement the PMF analysis and further distinguish crustal from non-crustal sources, Enrichment Factors (EFs) were calculated (), using both Ba () and Rb (Reimann et al., 2000) as crustal elements of reference. Rubidium was used as a secondary conservative reference element for EFs calculations as commonly used elements were not available in the current dataset (e.g., Al, Ti, Fe) (e.g., ).
3 Results and discussion
3.1 Available dating and regional context
3.1.1 39Ar and 14C age-depth results
The uppermost layers of the glacier in 2019 appear to be older than 60 years, as evidenced by the lack of tritium activity in the first 4 m of the core, which would have been introduced by nuclear bomb tests of the 1960s (). This observation was recently corroborated by results from 39Ar dating (). The 39Ar analyses on samples from the 2023 and 2024 surface yielded ages of around 400 years. In combination with the previous micro-radiocarbon ages from a 2019 ice core (), the 39Ar ages were used to derive an age-depth model (), which yields an estimated age of the glacier’s surface in 2019 of 371 years (before 2019), with an uncertainty range of −60 to +96 years, placing its formation between 1,552 and 1708 CE. Deeper in the core, a prominent levoglucosan peak at approximately 640 cm depth, also marked by concurrent chemical signatures (), was dated to 891 years before 2019, with an uncertainty range of −151 to +227 years. This corresponds to a calibrated age interval between 902 and 1280 CE. At the base of the core, larger chronological uncertainties were observed, with modelled ages ranging from 349 BCE to 420 CE, corresponding approximately to the period from just before the late Roman Republic through the Roman Empire.
3.1.2 Micro-charcoal record from Schwarzboden mire and levoglucosan from WSS ice core
The levoglucosan profile from the WSS ice core exhibits concentrations ranging from 0.07 to 51.07 ng g−1, with a prominent peak centred at approximately 1128 CE. Similarly, the micro-charcoal record from the Schwarzboden mire peat core – located 20 km southeast of the WSS glacier () – displays concentrations ranging from 56 to 71,586 particles cm-2 yr−1, with a major peak centred around 955 CE and constrained within a range from 822 CE to 1092 CE. The Monte Carlo simulation approach accounted for the reported age uncertainties of both the 39Ar ice core and the 14C peat core chronologies by iteratively perturbing the age models and re-interpolating the proxy records. The resulting distributions of peak timings revealed a temporal offset between the two proxies (Supplementary Figure S2), supporting the robustness of the observed peak lag (Figure 1) and suggesting that it is unlikely to be an artifact due to interpolation procedure. These results indicate that the offset is plausibly attributable to dating uncertainties inherent in the respective geochronological methods. Both records indicate cumulative deposition resulting from recurrent or prolonged fire events, rather than a single combustion episode. The prominent peaks likely reflect the combined influence of climatic factors – such as the Medieval Warm Period (950 CE – 1250 CE) and episodic droughts, which may have triggered cycles of vegetation growth followed by desiccation, increasing biomass flammability – with human activities, including alpine grasslands exploitation, agricultural expansion, and warfare. This interpretation is further supported by high-resolution peat records from south and north of the Alpine ridge within a 100 km distance from Weißseespitze. Records from the Valmalenco (Italian Alps), located approximately 94 km southwest of Weißseespitze and 84 km southwest of Schwarzboden mire (Supplementary Figure S1), show increased fire frequency and intensity during Medieval drought phases (950–1040 CE) (, and reference therein), supporting the idea that fire activity during this period was both regionally extensive and likely of human origin, amplified by the climatic variability. Similarly, on the Austrian side, a pronounced peak in micro-charcoal particles is evident at the site of Rauber () between 800 and 1000 CE, while in the Schwarzenbergmoos record from Brixlegg (Austria, (), shows a marked increase in micro-charcoal starting from 900 CE.
FIGURE 1
To further investigate the sources of this signal, the ratio of levoglucosan to the sum of CA was computed across the entire record, revealing its highest value corresponding to levoglucosan maximum (Figure 2). This suggests direct deposition from prolonged nearby fire events, as the low CA concentrations – derived from oxidation products during atmospheric transport – indicate a short-range transport mechanism. This interpretation is supported by the dominance of larger micro-charcoal particles (up to 50 µm in diameter), which are generally associated with local to regional deposition due to their rapid gravitational settling (). However, since a portion of the particles falls within the fine dust range (5–20 µm), which can travel over subcontinental distances (Clark, 1988), a contribution from more distant sources cannot be entirely excluded.
FIGURE 2
3.2 New chemical characterisation and source attribution
3.2.1 Trace elements and their characterisation
Among the 18 trace elements analysed (Li, V, Cr, Mn, Co, Ni, Cu, Zn, As, Rb, Sr, Ag, Cd, Ba, Tl, Pb, Bi, U), Pb (1.12 ng g−1) and Zn (2.8 ng g−1) exhibited some of the highest average concentrations, together with Mn (1.59 ng g−1), Sr (1.04 ng g−1), and Ba (1.22 ng g−1) (Table 1). While flux-based comparisons would generally be more meaningful for assessing deposition, this approach is not feasible at WSS due to the highly uncertain snow accumulation rates at the site. Strong wind exposure and redistribution of surface snow make it difficult to reliably estimate accumulation, limiting interpretation to concentration data alone (Figure 3).
TABLE 1
| Element | Weißseespitze Av.conc(ng g−1). This work. 1,641–128 CE | Alto dell’Ortles Av.conc(ng g−1). . 20th century | Colle gnifetti Av.conc(ng g−1). . 20th century | Colle gnifetti Av.conc(ng g−1). . Pre-20th century | Grenzgletscher Av.conc(ng g−1). . End of 20th century | Dome du gouter Av.conc(ng g−1). . 20th century | Dome du gouter Av.conc(ng g−1). . Pre-20th century |
|---|---|---|---|---|---|---|---|
| Li | 0.02 | 0.02 | |||||
| V | 0.09 | 0.05 | 0.11 | ||||
| Cr | 0.08 | 0.32 | 0.11 | 0.14 | 0.06 | ||
| Co | 0.05 | 0.01 | 0.16 | 0.04 | 0.021 | 0.15 | 0.07 |
| Ni | 0.29 | 0.13 | 0.03 | 0.08 | 0.14 | ||
| Cu | 0.39 | 0.46 | 0.07 | 0.14 | 0.02 | ||
| As | 0.13 | 0.1 | |||||
| Ag | 0.01 | 0.002 | 0.024 | 0.005 | 0.001 | 0.002 | 0.0003 |
| Cd | 0.03 | 0.05 | 0.007 | 0.01 | 0.025 | 0.003 | |
| Tl | 0.02 | 0.001 | |||||
| Bi | 0.06 | 0.004 | 0.0009 | 0.003 | 0.004 | 0.0008 | |
| U | 0.02 | 0.005 | 0.003 | 0.004 | 0.005 | 0.002 | |
| Zn | 2.8 | 2.28 | 0.27 | 0.87 | 1.79 | 0.36 | |
| Pb | 1.12 | 0.2 | 1.08 | ||||
| Mn | 1.59 | 1 | 1.25 | ||||
| Rb | 0.07 | 0.05 | |||||
| Sr | 1.04 | 0.6 | |||||
| Ba | 1.22 | 0.6 |
Average concentrations (ng g-1) of the 18 trace elements analysed within the WSS ice core, compared to concentrations reported in literature for the 20th century and pre-20th century periods. Glaciers are listed in order of increasing distance from Weißseespitze.
FIGURE 3
Over the shared timeframe of 700–1200 CE, Pb concentration levels in the WSS ice core generally align with those observed in other Alpine ice cores, including Col du Dôme (CDD) (), Colle Gnifetti (CG) (), and, particularly, Alto dell’Ortles (). Between 850 and 950 CE, CDD records Pb concentrations of approximately 0.1 ng g−1, closely matching the low levels found at WSS (0.16 ng g−1). Likewise, data from CG () indicate Pb concentrations comparable to those of WSS during this period, suggesting a coherent regional signal in atmospheric Pb deposition across the Alps in the early part of the millennium. In a more recent context, Pb concentrations at Grenzgletscher reached similar levels (1.08 ng g−1) during the periods 1980–84 and 1990–92 (; Table 1). However, unlike the pre-industrial peaks, these values reflect a long-term decline in Pb emissions, largely attributed to air quality regulations implemented across Europe beginning in the 1970s ().
Zinc concentrations found in WSS ice core and referred to pre-industrial period are similar to those found in two cores (2.28 ng g−1) drilled in 1982 and 1995 at Colle Gnifetti saddle (Mt Rosa massif, Swiss-Italian Alps, 4,450 m a.s.l.), which span the 20th century (). Similarly, the average concentrations of Li (0.02 ng g−1), V (0.09 ng g−1), Mn (1.59 ng g−1), Rb (0.07 ng g−1), and Cd (0.03 ng g−1) in the WSS ice core align closely with those reported for Grenzgletscher during the 1980–84, 1990–92 period (), while Ni (0.29 ng g−1), Cu (0.39 ng g−1), and Ag (0.01 ng g−1) are consistent with the 20th-century concentrations found in the Colle Gnifetti ice core () (Table 1). These similarities can be attributable either to some anthropogenic emissions during pre-industrial times linked to ancient mining and smelting, or to a high percentage of crustal material inputs during the 20th century, as a consequence of fallouts of Saharan dust (, and reference therein).
The average concentration of As (0.13 ng g−1) in the WSS ice core is comparable to the 20th-century average recorded in one of the four ice cores drilled at the Alto dell’Ortles glacier in 2011 (South Tyrol, Italy, 3,859 m a.s.l.) (; ; ). However, this similarity appears to be largely influenced by the presence of pronounced arsenic peaks in the WSS record between 1,366 and 1029 CE (4.33 ng g−1) and 1,652–1464 CE (2.54 ng g−1) (Figure 3). These peaks, aligned with Pb maxima, likely reflect periods of intensified mining and smelting activities of silver and copper across Europe. Notable regions include Schneeberg in the Rudnaun Valley (Alto Adige), mining areas in the Bergamasque Alps, such as Ardesio and Valseriana, as well as Upper Valtellina, the Upper and Lower Engadine regions, Monte Calisio near Trento, and the Harz Mountains in Germany, all known for producing Pb and As as common by-products. These findings are consistent with historical evidence of large-scale metal extraction and processing during the medieval and early modern periods (). The two prominent As concentration peaks may also reflect the influence of major natural forcing factors, including large volcanic eruptions and associated atmospheric perturbations. Arsenic maxima coincide with SO42− peaks (Supplementary Figure S3) around 1235 CE and 1580 CE, suggesting a volcanic contribution linked to major 13th century eruptions recorded in Greenland and Antarctic ice cores () and to volcanic activity occurred in the Northern Hemisphere around 1580 CE, respectively. Around 1580 CE, several trace elements (Ag, Cu, Ni, Co, Cr, and V) show synchronous concentration maxima.
While As, Ag and Cu can be consistent with volcanic emissions associated with Northern Hemisphere eruptions (e.g., ), the concurrent enrichment in refractory elements such as Cr, Ni, Co, and V indicates an additional contribution from enhanced atmospheric dust transport and regional crustal sources, likely related to high hydrological variability during the 16th century (). Together with the synchronous low Rb/Sr ratio and depleted ∂18O signal (), these observations support a mixed volcanic-crustal origin of the 1580 CE geochemical anomaly rather than a purely volcanic signal (Supplementary Figure S4). Indeed, low Rb/Sr ratio aligned with depleted ∂18O values may be suggestive of drought conditions (), as those occurred in the early and middle 14th century () (Supplementary Figure S4), when a major peak in Zn, Cu, Ni and Co was also observed (Supplementary Figure S3).
Cr and Co, for which rock and soil dust represent about 2/3 of natural emissions (), are comparable with concentrations observed in the pre-industrial period for both Colle Gnifetti and Dôme de Goûter (Mt Blanc Massif) ice cores ().
The average concentrations of Sr and Ba found within the WSS ice core are respectively 1.73 and 2 times higher than those found at Grenzgletscher (). Since Sr and Ba are often associated with crustal dust, this could suggest variations in regional dust sources, potentially influenced by shifts in atmospheric circulation patterns.
A distinct case is represented by Tl, Bi, and U, whose concentrations within the WSS ice core appear to be 20, 20, and 5 times higher, respectively, than those found in Grenzgletscher, which reflects deposition from the end of the 20th century (). These elevated concentrations are surprising, particularly for Tl, which is strongly associated with industrial activities such as coal combustion and metal smelting. In contrast, Bi and U have both natural and anthropogenic sources, making their interpretation more complex, especially in pre-industrial contexts. The enrichment observed at WSS may result from a combination of natural geogenic inputs (e.g., mineral dust), early regional mining or smelting activities in the Eastern Alps, or atmospheric circulation patterns that enhanced the deposition of these elements at this high-altitude site.
Among the investigated carboxylic (C2-Acetic, C2-Glycolic, C2-Oxalic) and dicarboxylic acids (C3-Malonic, C4-Succinic), the Acetic acid (C2-Acetic) represented 67% of the total mass concentration, followed by Oxalic acid (C2-Oxalic) with 28%. The sum of the remanent CA was 5% (Supplementary Figure S5). Despite the few available measurements for C3-Malonic acid, a C3-Malonic acid to C4-Succinic acid ratio was calculated, as an indicator of enhanced photochemical production of diacids. Indeed, the C4-succinic acid can be degraded to C3-Malonic acid by decarboxylation reactions activated by OH radicals (). The average value obtained was 0.86, slightly higher than C3/C4 for vehicular exhaust, which is typically between 0.25 and 0.44 (). This result pointed out a weak secondary reactivity in the atmosphere, probably due to the vicinity to urban areas and the consequent short-range transport. However, to deeply investigate the formation pathway of each CA, a correlation matrix was calculated (Supplementary Table S2), revealing moderate correlation coefficients (0.6 ≤ r ≤ 0.7) among C4-succinic - C2-acetic; C2-glycolic – C2-oxalic. These results confirmed their common source and a probable weak secondary reactivity in the atmosphere.
Nitrate (37.19%) and sulphate (23.09%) dominated the ionic mass concentration, followed by calcium (11.97%) and ammonium (11.07%). Other ions, including Cl−, K+, Na+, and Mg2+, accounted for smaller fractions, with MSA− and Br− contributing minimally ().
As NO3− plays a crucial role in the nitrogen cycle and affects atmospheric chemistry, its sources were investigated using the nitrate-to-sulphate ratio, yielding a mean r = 1.95 neq/neq. This value is significantly higher than those reported for aerosol in the Himalayan region, French Alps, Jungfraujoch station, and Col Margherita observatory (; ; ; ), and more comparable to values found in urban areas (; ). Since NOx oxidises more rapidly than SO2, higher NO3−/SO42- ratios are typically observed near emission sources. However, the elevated NO3− concentrations observed in the WSS ice core cannot be attributed to modern industrial pollution, given the pre-industrial age of the ice. Instead, they could reflect local or regional sources such as agricultural activity or pre-industrial emissions from nearby valleys, although long-range atmospheric transport from other sources cannot be entirely excluded. However, literature values refer to aerosol, while this study computed the ratio in ice, introducing uncertainty due to the lack of information on snow accumulation rate at the site. Although this factor cannot be fully disentangled, it should be considered when interpreting the data.
To differentiate sulphate sources, sea-salt sulphate (ss-SO42−) and non-sea salt sulphate (nss-SO42−) contributions were calculated. Nss-SO42-, calculated as SO42− - (Na+ * 0.252), where 0.252 is the sea water mass ratio (), accounted for approximately 93.4% of total sulphate, indicating a negligible marine influence. Nss-SO42− originates either from natural oxidation of dimethyl sulphide (DMS) released by marine algae () or from anthropogenic emissions of SO2 linked to activities such as biomass burning or pre-industrial metal smelting (). The anthropogenic fraction was estimated using the equation reported by , excluding ss-SO42− and mineral dust sulphate, with concentrations expressed in neq m−3. In this formula, 0.12 is the SO42− to Na+ molar ratio, and 0.175 is the pre-industrial nss-SO42− to nss-Ca2+ ratio of mineral dust in snow: [ex-SO42−] = [SO42−] − (0.12 [Na+]) − (0.175[Ca2+]). Results showed that 80.62% of nss-SO42- originated from anthropogenic sources (e.g., metal smelting and coal burning), aligning with aerosol findings from Col Margherita (∼98 km SE of WSS, ), and Sonnblick station (). However, the scale of these emissions (out of the total 23% SO42− found in the WSS ice core) would have been much smaller than what we observe with the industrialisation of the 19th century.
Additionally, the low MSA− concentration in WSS ice suggests minimal biogenic sulphate input, though oxidation during long-range transport or temperature-dependent emissions may have influenced levels (). The NH4+ - SO42− relationship was also assessed, revealing a weak correlation with ss-SO42− (r = 0.15) at 0.05 confidence level, but a strong correlation with ex-SO42− (r = 0.84), indicating a predominantly anthropogenic origin, excluding significant mixed sources (; ).
3.2.2 PMF
A source apportionment approach using positive matrix factorisation yielded a reasonable resolution employing four factors. To individuate the right number of factors different solutions were explored. The parameters IM (maximum of the average of the scaled residuals) and IS (maximum of the standard deviation of the scaled residuals), together with the Q value (quality of the factorisation) were examined, following the approach reported in . Different runs were also performed incrementing the factors number. The high R2 value (0.86) obtained from the linear regression between real and simulated concentrations further confirms the robustness and reliability of the obtained results, reinforcing the validity of the PMF approach.
The profiles of contributions are reported in Figure 4a in terms of absolute and relative concentrations. The error bars represent the standard deviations of the bootstrap runs.
FIGURE 4
Factor 1 (F1) was associated to Secondary Organic Aerosols (SOA) influenced by atmospheric oxidation processes, as evidenced by high concentrations of CA. Potential sources include the photochemical oxidation of Volatile Organic Compounds (VOCs), leading to SOA formation, as well as aged biomass burning aerosols, given that biomass combustion can lead to the secondary formation of oxalic acid and other organic acids (). High concentration of ammonium (NH4+), a key marker of secondary aerosol formation, was also identified. Additionally, the presence of nitrate (NO3−) suggests contributions from ammonium nitrate, likely linked to agricultural ammonia emissions.
Factor 2 (F2) was interpreted as a mixed source, as it exhibited a high concentration of levoglucosan (∼80%), a key marker of biomass burning, along with K+ (∼30%), Mn, and Zn, indicative of crustal contribution. The inability to separate biomass burning (BB) and crustal sources by adjusting the number of factors suggests that their co-variation is driven by similar atmospheric transport pathways, possibly influenced by synoptic-scale meteorological patterns, such as seasonal wind patterns, or convective uplift.
Factor 3 (F3) showed the co-variation of several trace elements, including Ag, Cd, Bi, and a suite of lithogenic elements (V, Cr, Co, Sr, Tl, and U), suggesting a mixed anthropogenic-lithogenic origin.
Factor 4 (F4) was recognised as a mix of sea salt and biological sources, characterised by a high contribution of Na+, Cl−, Mg, MSA−, and Br−. The minimal presence of other pollutants further supports a natural origin. Enhanced contribution of sea salt and MSA− may indeed be modulated by periods of intensified atmospheric circulation and marine air-mass advection associated with large-scale climatic variability, such as the Medieval Climate Anomaly and the Little Ice Age. These climatic phases, which temporally correspond to the peaks observed at ∼ 6.0, 3.0 and 1.5 m of depth in Figure 4c, are known to have influenced atmospheric circulation patterns over the North Atlantic, thus likely affecting marine aerosol production and transport ().
Figure 4b displays the percentage contributions of the different source factors, revealing that the mixed sea salt and biological source (F4) is the dominant contributor, accounting for approximately 47% of total ice impurities. This substantial presence of sea salt aerosols reflects the influence of marine air masses as a key component of the atmospheric composition in the studied region. The second-largest contributor is the F1, comprising about 37% of the total. Its high contribution suggests influence from long-range transport and atmospheric processing of ammonium-rich aerosols, potentially linked to volcanic activity, biogenic emissions, or widespread biomass burning. However, no corresponding SOA signal is observed alongside the major levoglucosan peak at ∼640 cm depth in the WSS ice core (Figure 4c), supporting the hypothesis of a short-range transport event for that specific episode. The third contributor is a mixed source of biomass burning and crustal material (F2), accounting for roughly 10%, followed by an anthropogenic source (F3) at approximately 7%. The relatively minor presence of F2 suggests sporadic but notable inputs from wildfires, domestic combustion, and dust transport, with a concentration peak aligning with the levoglucosan maximum. Finally, the limited contribution from anthropogenic sources (F3), below 10%, aligns with the historical timeframe of the core, spanning from the Early Middle Ages to the Early Modern Period, well before the onset of industrialisation and widespread fossil fuel use.
3.2.3 EFs
Enrichment Factors (EFs) were computed as a post-hoc analysis to support the interpretation of the PMF results, rather than being included directly in the PMF input, in order to avoid potential statistical artefacts such as collinearity and distortion of factor profiles (). The EFs results, firstly conducted with Ba as reference element, indicates that among the anthropogenic group of elements (F3) identified by the PMF analysis, only Ag, Cd and Bi show strong enrichment relative to the local crustal background (EFs clearly above 100), and can therefore be interpreted as predominantly anthropogenic. In contrast, V, Cr, Co, Sr and U exhibit low enrichment (EFs <10), consistent with a mainly crustal origin. Thallium (Tl) shows intermediate enrichment, with EFs between 10 and 100, suggesting a mixed or variable contribution (Supplementary Figure S6a) (). This classification, further supported by EFs calculated using the conservative element Rb as a reference (Supplementary Figure S6b), is consistent throughout the entire core profile. Accordingly, Supplementary Figures S6a, b reports median values for three historically defined time intervals: the Advanced Pre-Industrial period (1,639–1200 CE), the Early to High Middle Ages (1,200–500 CE), and the Roman–Late Antique period (500–100 CE). Overall, these results suggest that the temporal co-variation identified by the PMF does not necessarily reflect a single common source, but rather the superposition of anthropogenic contributions on a persistent lithogenic background.
4 Conclusion
This study expands the Weiβseesptize ice core record presented in with an extended multi-proxy dataset - now including 18 trace elements and organic acids - and applies a PMF analysis to investigate the dominant drivers of pre-industrial atmospheric composition. Results show that natural sources control the chemical variability at WSS, with sea-salt/biological emissions and secondary organic aerosol accounting for the majority of the signal (47% and 37%, respectively), while biomass burning, crustal material, and anthropogenic inputs contribute more modestly (17% in total) but persistently throughout the record. Enrichment Factor analysis further shows that only a limited subset of trace elements (Ag, Cd, Bi) is clearly enriched above the lithogenic background, indicating that anthropogenic metal pollution remained limited during the Roman to Early Modern period. Accordingly, the co-variation of other trace elements (i.e., V, Cr, Co, Sr, Tl, and U) identified by the PMF analysis reflects the superposition of weak anthropogenic inputs on a stable natural background rather than the dominance of single pollution source. Departures from this background are episodic and coincide with intervals of major natural forcing, including large volcanic eruptions and periods of enhanced atmospheric dust transport during the 13th and 16th century, respectively. These events are reflected in synchronous peaks of sulphate and volatile trace elements (e.g., As, Ag, Cu), as well as in concurrent depletion of the Rb/Sr ratio and the δ18O signal, highlighting the sensitivity of the WSS record to regional-to-hemispheric perturbations.
A prominent levoglucosan peak in the WSS ice core (∼640 cm depth, dated between 902 and 1280 CE) mirrors a micro-charcoal maximum in the Schwarzboden mire peat record (822–1092 CE). Although not strictly synchronous, their temporal overlap, the micro-charcoal particle size range (7 < ø < 50 µm), and the elevated levoglucosan-to-carboxylic acid ratio suggest a cumulative signal of regionally sustained fire activity, potentially driven by the combined effects of the Medieval climatic anomaly and anthropogenic land-use pressures. Taken together, the refined age-depth model for the WSS ice core – established through 39Ar dating – and its contextual comparison with the Schwarzboden mire record enhance the regional interpretation of fire-related horizons and improve our understanding of environmental and anthropogenic dynamics within the pre-industrial Europe, particularly in the Eastern Alpine sector.
Despite substantial ice loss, the WSS glacier has demonstrated to preserve a uniquely well-dated archive of pre-industrial atmospheric composition. However, with only about 5.5 m of ice remaining in 2025, this archive is under imminent threat, underscoring the urgency of documenting and preserving the remaining record.
Statements
Data availability statement
The original contributions presented in the study are publicly available. This data can be found here: 10.5281/zenodo.16632022.
Author contributions
AS: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Writing – original draft, Writing – review and editing. DW: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Writing – review and editing. PB: Conceptualization, Validation, Visualization, Writing – review and editing. EB: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Writing – review and editing. MF: Data curation, Formal Analysis, Writing – review and editing. DF: Conceptualization, Formal Analysis, Writing – review and editing. KO: Validation, Visualization, Writing – review and editing. JG: Validation, Visualization, Writing – review and editing. WA: Conceptualization, Data curation, Funding acquisition, Supervision, Writing – review and editing. MO: Conceptualization, Data curation, Funding acquisition, Supervision, Validation, Writing – review and editing. MS-W: Resources, Writing – review and editing. AG: Funding acquisition, Supervision, Visualization, Writing – review and editing. CB: Funding acquisition, Supervision, Validation, Writing – review and editing. AF: Funding acquisition, Resources, Validation, Visualization, Writing – review and editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This research was funded in whole or in part by the Austrian Science Fund (FWF) [10.55776/P34399]. For open access purposes, the author has applied a CC BY public copyright license to any author accepted manuscript version arising from this submission. The work on glacier dating by 39Ar-ATTA was supported by the German Science Foundation (DFG) with the grants AE 93/22-1 and OB 164/17-1. This study was partially funded by the FWF project P 34399-N and the DACH project I 5246.
Acknowledgments
The authors warmly thank Linus Langebacher for sampling and age modeling, and gratefully acknowledge the laboratory teams at Heidelberg University, Ca’ Foscari University and CNR-ISP (Venice) for their contribution to the laboratory work and data evaluation.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feart.2026.1680019/full#supplementary-material
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Summary
Keywords
39Ar dating, alpine glaciers, anthropogenic pollution, ice cores, trace elements
Citation
Spagnesi A, Wachs D, Bohleber P, Barbaro E, Feltracco M, Festi D, Oeggl K, Gabrieli J, Aeschbach W, Oberthaler M, Stocker-Waldhuber M, Gambaro A, Barbante C and Fischer A (2026) New chemical signatures from Weißseespitze ice cores (Eastern Alps): pre-industrial pollution traces from Roman Empire to early modern period. Front. Earth Sci. 14:1680019. doi: 10.3389/feart.2026.1680019
Received
05 August 2025
Revised
04 January 2026
Accepted
07 January 2026
Published
13 March 2026
Volume
14 - 2026
Edited by
Summer Rupper, The University of Utah, United States
Reviewed by
Akshaya Verma, National Institute of Hydrology (Roorkee), India
Emilie Beaudon, The Ohio State University, United States
Updates
Copyright
© 2026 Spagnesi, Wachs, Bohleber, Barbaro, Feltracco, Festi, Oeggl, Gabrieli, Aeschbach, Oberthaler, Stocker-Waldhuber, Gambaro, Barbante and Fischer.
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*Correspondence: Azzurra Spagnesi, azzurra.spagnesi@unive.it; Pascal Bohleber, pascal.bohleber@awi.de; Andrea Fischer, andrea.fischer@uibk.ac.at
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