Assessing Pollution and Diatom-Based Bioindicators in the Arieș River, Romania

Abstract

The Arieș River, in the Apuseni Mountains of Romania, has been historically impacted by gold mining, resulting in elevated concentrations of metal trace elements. This study assessed the river’s ecological status between 2022 and 2024 by integrating physico-chemical parameters at four sites and diatom-based bioindicators at the same sites in 2024 across monitoring sectors. Key results showed strong mining influence downstream of Baia de Arieș, with episodic acidification (pH down to 5.7), elevated conductivity (>400 μS/cm), and notable exceedances in metal trace elements, particularly Cu (up to 237 μg/L) and Cd (up to 4.18 μg/L). Analysis showed a dominance of α-mesosaprobic taxa (e.g., Amphora ovalis, Navicula cryptocephala, Nitzschia inconspicua), including teratological forms, at polluted sites, while sensitive species persisted upstream. Multivariate analyses indicated that metal trace elements and nutrients are the main drivers of chemical and biological patterns. These findings highlight diatoms as sensitive bioindicators of mining-related impacts. Incorporating diatom-based monitoring into management strategies can support early detection of pollution and more effective protection of freshwater ecosystems.

1. Introduction

Rivers, vital for ecological balance, are often polluted by industry and agriculture, harming biodiversity and human health [1]. Water contamination endangers drinking safety and aquatic ecosystems, disrupting ecological balance. Because of its scale and complexity, relying solely on remediation after pollution occurs is not an effective solution [2].

Human activities have led to the release of substantial amounts of metal trace elements into both surface watercourses and groundwater resources [3,4]. The introduction of hazardous substances—including chemical agents, pathogenic microorganisms, and particulate matter—disrupts ecological balance and poses serious risks to public health. A particular concern is bioaccumulation, where aquatic plants and organisms absorb and retain contaminants such as metal trace elements, pesticides, and persistent organic pollutants, which can then enter the human food chain through consumption [5]. These challenges highlight the importance of baseline studies in sensitive regions affected by anthropogenic pressures. For instance, the first comprehensive assessment of heavy metal pollution in surface sediments of Boka Kotorska Bay provides essential baseline data for environmental evaluation, monitoring, and management [6].

The Arieș River, located near the Roșia Montană–Roșia Poieni area, is a watercourse severely affected by human activities. The rivers and streams of the Apuseni Mountains, Romania, especially the Arieș River, are continuously exposed to heavy metal pollution originating from local mining activities, many of which are now inactive [7]. In the Roșia Montană area, mining has a long history dating back to the pre-Roman period. However, both historical and recent mining operations have led to the uncontrolled accumulation of waste rock, surface mining structures, and tailings ponds, contributing significantly to acid mine drainage and watercourse contamination [8]. The resulting discharge of metal trace elements and acidic waters into the local hydrological network has caused extensive pollution, notably affecting sections of the Arieș River basin.

Few studies, most of them now considered outdated, have examined the effects of mining on Romanian rivers, particularly in the Arieș River basin. A study conducted between 2005 and 2007 identified mining facilities in the Roșia Montană–Roșia Poieni region, along with domestic waste, river regulation, and other industrial activities, as the main pollution sources. The resulting high impact scores were associated with a decline in water quality, most evident in biotic communities, with benthic invertebrates and diatoms proving the most sensitive indicators of degradation [9]. Water quality in the Arieș River basin was assessed in 2008 using 18 sampling stations (10 on the main river and 8 on tributaries), based on the Saprobic Index (SI), the Diatom Biological Index (IBD), and the Shannon–Wiener Diversity Index (H). Diatomological samples were collected in 2008, providing a detailed perspective on the ecological status of the river system. Water quality in the Arieș River declines from good in the upper course to mediocre downstream, while most tributaries remain good except those affected by mining and wastewater inputs. The absence of diatoms in Valea Șesii indicates severe toxicity, and the SI confirms a rising organic load from source to confluence [10].

A study from 2006 to 2007 regarding the physico-chemical and biological characteristics of the Arieș River highlights local pollution, particularly in the Abrud area, caused by mining, industrial activities, and domestic waste; analysis of diatom communities and water isotopes showed increasing pollution and eutrophication from the upper to the lower course of the river [11].

Diatom communities and water chemistry were studied in 2013–2014 at 16 sites in the Abrud River catchment (a tributary of the Arieș River), including areas affected by mining pollution. A total of 274 diatom taxa from 63 genera were identified. Results showed severe reductions in species richness in impacted tributaries, while cleaner upstream sites maintained diverse diatom assemblages. The study highlights diatoms as effective indicators of water quality and demonstrates the localized impact of mining on river biodiversity [12].

Recent studies have demonstrated the effectiveness of diatoms as bioindicators of water quality in mining-impacted rivers, highlighting declines in species richness and changes in community structure in polluted sites [12,13], thereby providing updated evidence to support assessments of ecological impacts and guide ecosystem management.

In addition to mining-related pollution, the region experiences further contamination from ore flotation processes, runoff from waste dumps, effluents from ore processing plants, and municipal sewage [14]. Among the most severe environmental impacts are those observed in the middle basin of the Arieș River, particularly near the mining areas of Roșia Montană and Roșia Poieni, where extensive land degradation has occurred, including the formation of quarries, waste dumps, and tailings ponds [15]. These activities have profoundly altered the hydrographic network, modifying the morphology and hydrology of rivers and streams, changing catchment surface areas, slopes, drainage density, and land use patterns [16]. Consequently, water quality has been severely compromised, with elevated metal trace element levels, acidification, and sediment accumulation affecting stream profiles downstream of mining operations [17].

In this context, diatoms have emerged as effective bioindicators for assessing water quality and pollution due to their rapid response to environmental changes and sensitivity to chemical stressors [18]. Their community composition reflects not only nutrient levels but also the presence of contaminants such as metal trace elements, making them particularly useful for monitoring pollution gradients [19]. With short life cycles and widespread abundance in freshwater systems, shifts in diatom abundance and distribution provide early warnings of ecological deterioration. Using diatoms in bioassessment allows the integration of spatial and temporal variations in water quality, offering a more comprehensive understanding of ecosystem health compared to chemical analyses alone [20]. Moreover, diatoms can exhibit valve deformities (teratologies), which serve as indicators of sub-lethal stress and provide insights into the ecological impacts of contaminants such as metals and organic pollutants [21]. These deformities, combined with changes in community composition, make diatoms a powerful tool for detecting and assessing environmental stress in freshwater ecosystems.

The study tests the hypothesis that heavy metal pollution originating from mining activities significantly influences water quality and diatom community structure in the Arieș River, Romania. To address this, physico-chemical parameters were measured and correlated with diatom species composition, structure, and diversity, highlighting the potential of diatoms as bioindicators of contamination.

2. Materials and Methods

2.1. The Studied Region and Its Characteristics

The monitored watercourse is part of the Arieș–Turda hydrotechnical system within the Arieș River Basin (3005 km²). The main watercourses of the basin include the Arieș River and its tributaries: Gârda Seacă, Albac, Arieșul Mic, Valea Buciumanilor, Abrud, Bistra, Valea Mare, Cheia, Poșaga, Ocoliș, Ocolișel, Iara, Șoimul, Râmetea, Hășdate, Micuș, Valea Racilor, Pârâul Florilor, Valea Largă, Tritul, Valea Lată, and others. The Arieș River originates in the Apuseni Mountains, Alba County, Romania, and is a left tributary of the Mureș River in Transylvania. Its total length is 166 km.

The investigated area is located within Alba and Cluj counties (Figure 1). The monitoring points (Figure 2) are distributed along the river course, in the immediate vicinity of the mining operations in the Roșia Montană region. The coding of the sampling points and the characteristics of the study area are presented in

Table 1. Coding and sampling points for river water and substrate for biofilm scraping and material collection along the Arieș River.

Sample	Sampling Points Coding	Sampling Area	Site Characteristics/Pollution Sources
1	A1	Upstream of Arieseni village	In the upstream sector of the two sampling points (A1 and A2), the Arieș River is predominantly influenced by diffuse pollution sources generated by tourism and household activities (inadequately collected and treated wastewater), nutrient and organic matter inputs from surface runoff related to livestock waste management, as well as possible natural contributions linked to erosion and sediment transport processes. There are no major industrial pollution sources in the area, but the aquatic ecosystem is highly vulnerable due to the relatively low flow and limited dilution capacity.
2	A2	Downstream of the Mihoești reservoir and dam
3	A3	In the area of Baia de Arieș	In the Baia de Arieș area, the Arieș River is affected by pressures from both point and diffuse sources, mainly associated with inadequately collected and treated domestic wastewater, as well as stormwater that drains various discharges from historical mining waste deposits (acidic waters loaded with metal trace elements and suspended solids-TSS). Industrial wastewater from the only active mining site in the area (Cupru Min SA Abrud), which exploits the local copper deposit, also contributes to pollution. Additionally, diffuse inputs from agricultural and household activities, as well as livestock waste management, are noticeable in the area.
4	A4	Upstream of the confluence with the Mureș River	In the section of the Arieș River located upstream of its confluence with the Mureș River, the water is influenced by cumulative pollution sources across the entire watershed. These include domestic and industrial discharges from urban areas (Turda, Câmpia Turzii), historical and ongoing inputs of mining pollutants (TSS, metal trace elements), diffuse runoff of nutrients and pesticides from agriculture, as well as impacts from livestock activities. These anthropogenic pressures result in an increased pollutant load in the river.

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2.2. Water Sample Collection

Water samples were collected during the years 2022, 2023, and 2024, in January, April, July, and October, in order to cover all seasons as well as various climatic and river flow conditions. The selection of these specific months was motivated by the need to analyze the variability of water quality parameters throughout the year, taking into account seasonal fluctuations in temperature, precipitation, and river discharge. Moreover, sampling at different times of the year allowed us to observe seasonal variations in pollution levels, which may be influenced by environmental factors such as heavy rainfall or low summer flows, although these potential effects were not directly measured in this study. This sampling strategy was essential for obtaining a comprehensive and representative overview assessment of the ecological status of rivers in the Arieș River basin.

2.3. Physico-Chemical Analysis of River Water Samples

2.3.1. River Water Quality Parameters

pH: The pH was measured using a WTW pH 340i portable pH meter and an electrochemical cell with a SenTix 81 electrode. The electrode was calibrated with pH 4.01, 7.00, and 10.00 buffers at 25 °C and rinsed with distilled water between measurements.

Total Suspended Solids (TSS) [22]: Within 24 h of collection, 100 mL water sample, stored in the dark at 1–5 °C, was filtered under vacuum through a pre-weighed glass fiber filter (pore size 1 μm). The filter retaining the suspended solids was dried at 105 °C to constant weight. TSS concentration (mg/L) was calculated as: TSS = (q₂ − q₁)·1000/V (mg/L). q₁-mass of the flask with filter (mg); q₂-mass of flask with filter and retained solids (mg), V-volume of the analyzed water sample (mL).

Dissolved oxygen-Winkler method (DO) [23]: 250 mL of water was mixed with a 40% MnSO₄ solution (Merck KGaA, Darmstadt, Germany) and 100 mL of a solution containing 30 g NaOH (ChimReactiv SRL, Bucurest, Romania) and 15 g KI (Sigma-Aldrich, Saint Louis, MO, USA). The iodine generated was titrated with 0.025 N Na₂S₂O₃ (PENTA s.r.o., Katovice, Czech Republic). DO concentration (mg O₂/L), was calculated as: DO = (V·f·C_N·E_Oxygen)/(V₁ − 4)·1000 (mg O₂/L water), where V is the volume (mL) of Na₂S₂O₃ 0.025N solution used in the titration, V₁ is the volume (mL) of the water sample used, f is the factor of the Na₂S₂O₃ 0.025N solution, C_N is the normal concentration of the Na₂S₂O₃ solution (0.025 N, equivalents/L), Eo_xygen is the equivalent weight of oxygen (8 mg/equiv O₂).

Biochemical Oxygen Demand (BOD₅) [24]: BOD₅ was determined by measuring the oxygen consumption of microorganisms over a five-day incubation period at 20 °C in the dark. The 5-day BOD value was calculated as: BOD₅ = q₁ − q₂ (mg/L), where q₁ represents the initial DO concentration in mg/L at the time of sampling, q₂ represents the DO concentration in mg/L after the five-day incubation period.

Chemical Oxygen Demand (COD) [25]: A 2 mL of the homogenized sample was mixed in a vial with 0.5 mL of 0.015 mol/L potassium dichromate (Merck KGaA, Darmstadt, Germany), 0.2 mL of mercury(II) sulfate (ISOLAB Laborgeräte GmbH, Eschau, Germany), and 2.5 mL of sulfuric acid–silver sulfate solution (0.0385 mol/L, Sigma-Aldrich Chemie Gmbh, München, Germany). The vials were heated at 150 °C for 2 h in a COD reactor and then cooled for 20 min. Two blank vials were prepared using distilled water instead of the sample. The contents of the vials were transferred to titration beakers, the vials were rinsed with ~1 mL water, and the remaining oxidant was titrated with 0.012 mol/L ammonium iron(II) sulfate solution using 2 drops of ferroin indicator until a reddish-brown endpoint was reached. Calculation: COD-Cr = ((8000·c·(V₁ − V₂))/V_o)·r (mg/L), where c-concentration of ammonium iron(II) sulfate solution (mol/L); V_o-volume of sample analyzed (mL); V₁-volume of ammonium iron(II) sulfate solution used for titrating the blank (mL); V₂-volume of ammonium iron(II) sulfate solution used for titrating the sample (mL); 8000-molar mass of O₂ in mg/mol; r-dilution factor.

Ammonium (NH₄) [26]: A 40 mL water sample was mixed with 4.00 mL of coloring reagent and 4.00 mL of sodium dichloroisocyanurate (Sigma-Aldrich (Taufkirchen, Germany) solution, and homogenized. The volume is brought to the mark with water, shaken, and placed in a water bath maintained at 25 °C for 60 min. Absorbance was measured at 655 nm against a blank. For samples exceeding 1.0 mg/L NH₄⁺, the water sample was diluted accordingly. Calculations: Ammonium = c·r [mg/L], where c-concentration in the photometered solution, in mg/L; r = dilution factor (40 mL/sample volume). (1 mg/L NH₄⁺ corresponds to a nitrogen concentration of 0.777 mg/L N).

Nitrites (NO₂⁻) [27]: A measured volume of the water sample was mixed with 1 mL of color reagent, homogenized, and brought to volume with water, then left to stand for 20 min. Absorbance was measured at 540 nm against a reagent blank. For samples with N > 0.25 mg/L, appropriate dilution was performed. Calculations: Nitrites = c·r [mg/L]; where c-nitrogen content in the photometered solution, in mg/L; r-dilution factor (40 mL/sample volume); (1 mg/L NO₂⁻ corresponds to 0.304 mg/L N).

Nitrates (NO₃⁻) [28]: A 5 mL water sample (pH adjusted to approximately 7) was treated with 0.5 mL sodium azide (ThermoFisher Scientific, Waltham, MA, USA) and 0.2 mL acetic acid (Chempur, Piekary Śląskie, Poland), then evaporated to dryness on a sand bath. After adding 1 mL sodium salicylate (Merck KGaA, Darmstadt, Germany) and evaporating again, 1 mL sulfuric acid (Merck KGaA, Darmstadt, Germany), 10 mL water, and 10 mL alkaline solution were added. The mixture was quantitatively transferred to a 25 mL volumetric flask, placed in a water bath at 25 °C for 10 min, and brought to volume with water. Absorbance was measured at 415 nm against a reagent blank. For samples with N > 0.2 mg/L, appropriate dilution was performed. Calculations: Nitrates = c·r·25/V_sample [mg/L] where c-nitrogen concentration, in mg/L, in the photometered solution; r-dilution factor; V_sample-volume of sample taken, in mL. (1 mg/L NO₃⁻ = 0.226 mg/L N).

2.3.2. River Water Salinity Parameters

Electrical conductivity (EC): EC was measured with a Waterproof multiparameter meter for pH/ORP/EC/TDS/Salinity/DO/Pressure/Temperature–HI98194 (Hanna Instruments Limited, Nusfalau, Romania).

Solids, Filterable Residue (FR): FR was determined at 105 °C [29]. A 100 mL water sample was filtered, and the filtrate was evaporated to dryness on a sand bath, then dried in an oven at 105 °C to constant weight. FR = (q₂ − q₁) × 1000/V (mg/L), where q₁-mass of the empty crucible (mg), q₂-mass of the crucible with the filterable residue dried at 105 °C (mg), and V-volume of the water sample (mL).

Bicarbonates (HCO₃⁻) [30]: A 50–100 mL water sample was mixed with methyl orange indicator (Merck KGaA, Darmstadt, Germany) and titrated with standardized HCl (Fisher Scientific, Pittsburgh, PA, USA) until an orange endpoint was reached. The volume of HCl used (V₂) is recorded. Calculation: HCO₃⁻ (mg/L) = (V × N × 61 × 1000)/sample volume [mL], where V = volume of HCl used for bicarbonate titration (L); N = normality of HCl; 61 = molar mass of HCO₃⁻ (mg/mmol).

Chlorides [31]: Chloride concentration was determined by argentometric titration (Mohr method). A 100 mL of the water sample was mixed with potassium chromate indicator (Sigma-Aldrich, St. Louis, MO, USA) and titrated with 0.02 mol/L AgNO₃ (Sigma Aldrich, Cairo, Egypt) a reddish-brown endpoint was reached. A blank was prepared with distilled water under the same conditions. Calculation: (Cl⁻) [mg/L] = ((V − V₀) × N_AgNO3 × F_AgNO3 × d × f)/V₁; where V = volume of 0.02 mol/L AgNO₃ used to titrate the sample (mL); V₀ = volume of 0.02 mol/L AgNO₃ used to titrate the blank (mL); N_AgNO3 = normality of the AgNO₃ solution; F_AgNO3 = factor of the AgNO₃ solution; d = dilution factor; f = conversion factor, 35,453 mg/mol; V₁ = volume of sample taken for determination (mL, usually 100 mL).

Sulfates [32]: Sulfate concentrations were determined turbidimetrically after precipitation with BaCl₂ (PENTA s.r.o., Katovice, Czech Republic). Turbidity was measured at 420 nm using a UV/VIS spectrophotometer (Lambda 20, Perkin Elmer, Waltham, MA, USA). Concentrations were calculated from a calibration curve and expressed as mg/L SO₄²⁻.

2.3.3. Metal Analysis in River Water Samples [33,34,35,36,37]

The river water samples were collected in pre-cleaned PET bottles (500 mL), transported on ice, and filtered within 2 h of collection using a 1 μm glass fiber filter to remove suspended solids.

As, Cd, Co, Cr, Cu, Fe, Mn, Ni, and Zn concentrations were determined by ICP-MS: Water samples were filtered through 0.45 μm cellulose acetate membrane filters, acidified using 2 mL of 65% nitric acid (Merck KGaA, Darmstadt, Germany) per 100 mL of sample to preserve them at pH < 2, and stored at 4 °C until analysis, with gentle mixing before aliquoting. Samples (10 mL each) were digested in TFM-PTFE vessels with 10 mL of aqua regia (3:1 HCl:HNO₃) (Merck KGaA, Darmstadt, Germany) using the Transform 680 microwave system (Aurora Instruments Ltd., Vancouver, BC, Canada) under a controlled program: ramp to 180 °C in 10 min, hold 20 min, with real-time monitoring of temperature and pressure. Blanks and triplicate samples were processed similarly. The digested solutions were diluted to 25 mL with Milli-Q water (Millipore, Merck, Darmstadt, Germany). Elemental concentrations were determined by ICP-MS using an Agilent 7700x instrument (Agilent Technologies, Inc., Tokyo, Japan). Calibration was performed using multi-element standard solutions (Certipur^®, Merck KGaA), and all measurements were performed in triplicate. All analyses were carried out in triplicate using the MassHunter Workstation Software, version G7201A A.01.02.

2.4. Periphytic Biofilm Sampling and Interpretation

The samples were collected in April 2024, by scraping with a disposable plastic toothbrush, from at least five stones completely submerged in water, each from an area of at least 10 cm², selecting zones with a current of less than 20 cm/s. After scraping, the toothbrush was periodically rinsed in a plastic tray containing approximately 50 mL of river water. Once the sampling was completed, the suspension was transferred into a polyethylene container and preserved with Lugol’s (Merck KGaA, Darmstadt, Germany) solution (1 mL solution/1 L sample) in order to prevent cell division and the decomposition of organic material [38].

In the laboratory, benthic diatoms were cleaned using the hot hydrogen peroxide method in order to remove cellular contents and fix the diatoms. The sample was homogenized by shaking, and 10 mL of the suspension was transferred into a laboratory beaker. Then, 20 mL of H₂O₂ (Merck KGaA, Darmstadt, Germany) was added, and the mixture was heated in a water bath at 90 °C until complete oxidation of the organic material (1–3 h). After removal from the bath, the beaker walls were rinsed with distilled water, and the suspension was allowed to settle. The washing process was repeated three times to eliminate any traces of peroxide. Subsequently, the diatom suspension was reconstituted in a small volume of distilled water and transferred into a clean vial. The sample was allowed to settle, and the excess supernatant was removed using a Pasteur pipette. A drop of the remaining suspension was placed on a new coverslip and left to evaporate by heating on a hot plate. The sample was analyzed under an Axio LAB.A1 light microscope (Carl Zeiss Microscopy GmbH, Jena, Germany) at 1000× magnification, with 300 to a maximum of 600 individuals (valves) identified and counted.

Data interpretation was performed using the SI method [39]. The saprobic value of each species was taken from Order of the Romanian Ministry of Environment and Water Management no. 161/2006 [40]. According to the saprobic valence of each species, the values were assigned as follows: Oligosaprobic–1 (o), Oligo–beta-mesosaprobic–1.5 (o-β), Beta-mesosaprobic–2 (β), Beta–alpha-mesosaprobic–2.5 (β-α), Alpha-mesosaprobic–3 (α), Alpha–meso–polisaprobic–3.5 (α-p), Polisaprobic–4 (p). The relative frequency of each species was expressed as a percentage (F. Rel%), using the formula F. Rel% = (p/Ʃp) × 100, where p is the number of individuals of a species, and Ʃp is the total number of individuals in the sample. Based on the relative frequency, the weighted frequency (h) was calculated according to the following classification: <1% → h = 1; 1–3% → h = 2; 3–10% → h = 3; 10–20% → h = 4; 20–30% → h = 5; 30–40% → h = 7; 40–100% → h = 9. The SI was calculated using the formula S = Ʃ(s_i·h_i)/Ʃh, where s is the saprobic value of the species, h is the weighted frequency, and i is the taxon. The interpretation of the obtained SIS was performed as follows: 1.0–<1.5 → oligosaprobic zone (no pollution, quality class I); 1.5–<1.8 → oligo–beta-mesosaprobic zone (slight pollution, quality class I); 1.8–<2.3 → beta-mesosaprobic zone (moderate pollution, quality class II); 2.3–<2.7 → beta–alpha-mesosaprobic zone (moderate to critical pollution, quality class III); 2.7–<3.2 → alpha-mesosaprobic zone (strong pollution, quality class IV); 3.2–<3.5 → alpha–meso–polisaprobic zone (strong to very strong pollution, quality class V); 3.5–4.0 → polisaprobic zone (very strong pollution, quality class V) [41].

2.5. Statistical Analysis

PAST software (version 5.2.1) was used to analyze variations in water quality and the distribution of diatom species across sites. Pearson correlation coefficients between metal trace elements and diatom species distribution were calculated using Minitab (version 21.4.1).

3. Results

For the qualitative assessment of water, a chemical analysis of the rivers in the Arieș Basin is carried out in order to identify natural and anthropogenic influences and to monitor the seasonal and geographical variations in chemical composition.

In

Table 2. Physico-chemical parameters of the Arieș River upstream of Arieșeni (A1).

	Parameter	pH	TSS, mg/L	DO, mgO/L	BOD5, mgO/L	COD-Cr, mgO/L	NH4+, mgN/L	NO2−, mgN/L	NO3−, mgN/L
Time, Year/Month
2022	January	7.5	10.8	9.87	0.83	1.13	0.002	0.005	0.167
	April	7.7	13.4	10.01	0.87	1.74	0.003	0.006	0.214
	July	7.6	14.9	8.04	1.34	2.32	0.005	0.011	0.584
	October	7.5	9.8	10.81	0.81	1.81	0.004	0.007	0.298
2023	January	7.8	10.3	9.60	0.91	1.56	0.001	0.006	0.170
	April	7.6	13.4	9.91	0.91	1.71	0.002	0.008	0.199
	July	7.4	15.4	7.98	1.12	2.14	0.006	0.009	0.604
	October	7.5	9.1	10.47	0.94	1.75	0.003	0.008	0.304
2024	January	7.6	12.3	9.74	0.82	1.38	0.002	0.005	0.186
	April	7.7	14.1	10.24	0.86	1.69	0.004	0.007	0.228
	July	7.6	13.6	8.45	1.27	2.09	0.008	0.008	0.527
	October	7.5	9.8	10.57	0.89	1.94	0.001	0.005	0.356
Quality class [40]	I	6.5– 8.5	-	6.2, not less than 80% oxygen saturation	6	10	0.4	0.01	1
	II					25	0.8	0.03	3
	III					50	1.2	0.06	5.6
	IV					125	3.2	0.3	11.2
	V					>125	>3.2	>0.3	>11.2

,

Table 3. Salinity parameters of the Aries River water upstream of Arieseni locality (A1).

	Parameter	EC, μS/cm	FR, mg/L	Ca, mg/L	Mg, mg/L	Na, mg/L	Bicarbonates, mg/L	Chlorides, mg/L	Sulfates, mg/L
Time, Year/Month
2022	January	104.42	71.4	13.7	1.9	5.8	52.4	0.8	32.4
	April	127.42	116.4	19.6	2.5	4.6	76.8	1.6	41.6
	July	211.79	147.4	41.5	4.7	7.1	125.7	4.1	58.0
	October	163.09	124.7	35.0	1.8	4.2	48.6	1.5	21.4
2023	January	124.93	83.6	17.4	1.4	4.7	55.2	0.1	28.2
	April	131.14	125.1	24.2	1.9	4.4	84.7	1.8	45.5
	July	198.72	138.1	34.8	3.8	6.3	113.0	3.5	51.7
	October	173.47	121.0	30.1	2.4	3.7	51.8	2.1	18.6
2024	January	142.72	79.2	13.6	1.6	5.5	64.1	1.7	31.3
	April	139.71	132.7	29.1	2.1	5.1	75.7	2.1	38.2
	July	199.67	152.4	38.3	4.1	6.6	132.4	3.8	54.8
	October	156.77	118.7	29.9	2.6	3.9	53.1	2.5	21.1
Quality class [40]	I	-	500	50	12	25	-	25	60
	II		750	100	50	50		50	120
	III		1000	200	100	100		250	250
	IV		1300	300	200	200		300	300
	V		>1300	>300	>200	>200		>300	>300

and

Table 4. The content of toxic metal trace elements in the water of the Aries River upstream of the Arieseni locality (A1).

	Parameter	As, μg/L	Cd, μg/L	Co, μg/L	Cr, μg/L	Cu, μg/L	Fe, mg/L	Mn, mg/L	Ni, μg/L	Zn, μg/L
Time, Year/Month
2022	January	0.29	0.23	0.21	1.18	9.37	0.07	0.001	0.69	6.74
	April	0.30	0.29	0.35	2.59	10.97	0.09	0.002	0.54	14.54
	July	0.32	0.44	1.74	8.41	13.13	0.11	0.005	1.44	31.84
	October	0.28	0.20	0.13	1.93	12.08	0.08	0.004	0.41	0.11
2023	January	0.31	0.19	0.19	1.24	7.62	0.05	0.001	0.73	7.78
	April	0.29	0.23	0.33	3.08	9.07	0.06	0.002	0.47	20.14
	July	0.35	0.51	1.56	7.96	12.24	0.09	0.006	1.54	39.14
	October	0.27	0.28	0.27	2.06	8.30	0.04	0.003	0.58	0.24
2024	January	0.35	0.25	0.13	1.45	9.51	0.07	0.001	0.98	9.16
	April	0.29	0.31	0.38	2.77	11.64	0.08	0.004	3.41	18.1
	July	0.37	0.53	1.62	8.25	12.47	0.10	0.007	1.47	31.71
	October	0.33	0.22	0.19	2.17	9.14	0.03	0.006	0.69	0.19
Quality class [40]	I	10	0.5	10	25	20	0.3	0.05	10	100
	II	20	1	20	50	30	0.5	0.1	25	200
	III	50	2	50	100	50	1.0	0.3	50	500
	IV	100	5	100	250	100	2	1	100	1000
	V	>100	>5	>100	>250	>100	>2	>1	>100	>1000

, the physico-chemical parameters of the Arieș River at the source (A1) are presented, allowing the analysis of seasonal variations in water quality, as well as the identification of potential natural and anthropogenic influences on the chemical composition.

According to the physico-chemical parameters, the water quality of the Arieș River at the source is relatively stable, with no significant fluctuations in the indicators, reflecting good water status in this area.

The salinity parameters of the Arieș River upstream of the Arieșeni village showed seasonal fluctuations, with higher values in the summer months, but without exceeding the analyzed parameter limits. These seasonal variations are typical of mountain freshwater ecosystems, where temperature and precipitation conditions influence the concentrations of salts and minerals in the water.

The content of toxic trace elements in the water of the Arieș River, upstream of the Arieșeni village, varied significantly depending on the season, but remained within limits that do not indicate severe pollution. In most cases, the concentrations of trace elements were below the maximum admissible limits, placing the water most of the time in quality classes I and II, which are considered good or very good for aquatic ecosystems.

In July, heavy metal concentrations reached higher values (0.53 μg/L Cd), which could be associated with evaporation and the accumulation of toxic substances during the summer period.

In

Table 5. Physico-chemical parameters of the Arieș River downstream of the Mihoești reservoir (A2).

	Parameter	pH	TSS, mg/L	DO, mgO/L	BOD5, mgO/L	COD-Cr, mgO/L	NH4+, mgN/L	NO2−, mgN/L	NO3−, mgN/L
Time, Year/Month
2022	January	7.6	18.4	10.53	0.97	1.21	0.004	0.003	0.327
	April	7.8	42.9	11.18	0.79	1.80	0.014	0.005	0.381
	July	7.7	21.4	8.14	1.84	3.34	0.021	0.010	0.847
	October	7.8	31.7	10.93	1.21	2.47	0.019	0.008	0.401
2023	January	7.9	12.4	10.21	1.04	1.06	0.008	0.001	0.352
	April	7.8	51.3	10.84	0.86	1.62	0.009	0.005	0.436
	July	7.6	31.1	8.59	1.89	3.21	0.014	0.009	0.773
	October	7.6	28.2	10.58	1.12	2.23	0.011	0.007	0.485
2024	January	7.7	23.8	11.23	0.93	1.17	0.003	0.004	0.318
	April	7.8	35.5	11.04	1.13	2.32	0.007	0.006	0.388
	July	7.6	12.2	8.04	1.97	3.07	0.028	0.011	0.686
	October	7.7	24.6	10.82	1.34	1.94	0.014	0.010	0.425

,

Table 6. Salinity parameters of the Aries River water downstream of the Mihoești reservoir (A2).

	Parameter	EC, μS/cm	FR, mg/L	Ca, mg/L	Mg, mg/l	Na, mg/l	Bicarbonates, mg/L	Chlorides, mg/L	Sulfates, mg/L
Time, Year/Month
2022	January	134.47	84.7	19.1	3.4	5.1	91.9	0.8	3.4
	April	145.31	123.3	19.6	6.6	5.8	101.2	2.9	15.7
	July	184.02	124.5	22.3	12.1	6.2	105.1	7.2	17.6
	October	169.33	124.7	21.5	9.8	4.4	84.8	4.6	13.7
2023	January	144.21	91.2	18.6	2.7	5.3	87.4	0.7	4.1
	April	157.09	116.3	19.0	1.9	5.5	84.7	3.8	16.3
	July	169.23	118.9	21.6	7.2	5.9	98.5	6.4	14.6
	October	171.17	121.0	20.7	10.1	4.1	91.1	4.9	18.1
2024	January	128.14	88.5	20.1	4.1	4.8	94.3	0.5	4.8
	April	145.44	105.8	21.3	8.3	5.7	75.6	4.4	13.3
	July	177.08	122.2	22.7	11.7	6.0	98.7	6.8	16.8
	October	167.49	118.7	21.8	10.5	4.5	79.4	5.1	10.8

and

Table 7. The content of toxic metal trace elements in the water of the Arieș River downstream of the Mihoești reservoir (A2).

	Parameter	As, μg/L	Cd, μg/L	Co, μg/L	Cr, μg/L	Cu, μg/L	Fe, mg/L	Mn, mg/L	Ni, μg/L	Zn, μg/L
Time, Year/Month
2022	January	0.30	0.53	0.86	3.53	5.32	0.03	0.006	0.69	2.24
	April	0.35	0.66	1.71	6.38	11.89	0.11	0.012	1.48	11.17
	July	0.41	0.98	3.17	9.14	12.87	0.18	0.022	1.91	39.18
	October	0.39	0.41	0.62	6.14	11.42	0.06	0.018	1.09	1.31
2023	January	0.33	0.46	0.60	4.07	6.08	0.04	0.011	0.73	7.78
	April	0.36	0.57	2.07	5.17	10.43	0.09	0.013	1.37	10.53
	July	0.37	0.81	3.22	8.22	11.45	0.17	0.018	1.72	34.8
	October	0.25	0.39	0.55	4.49	9.96	0.07	0.015	1.24	1.29
2024	January	0.35	0.54	0.94	4.58	4.97	0.01	0.008	0.98	1.31
	April	0.42	0.62	1.22	6.18	9.74	0.12	0.009	1.56	5.67
	July	0.48	0.79	2.85	7.73	13.08	0.13	0.013	1.83	43.01
	October	0.31	0.44	0.51	5.16	10.22	0.05	0.011	1.22	0.91

, the physico-chemical parameters of the Arieș River downstream of the Mihoești reservoir (A2) are presented, highlighting the evolution of water quality under the influence of natural and anthropogenic factors, as well as the seasonal and spatial variations in the main pollution indicators.

Between 2022 and 2024, the physico-chemical parameters of the Arieș River water downstream of the Mihoești reservoir showed seasonal fluctuations, but overall, the values remained within limits that do not severely affect water quality.

The salinity parameters of the Arieș River water downstream of the Mihoești reservoir varied seasonally, but generally remained within acceptable limits, indicating water quality favorable to the aquatic ecosystem.

These parameters increase slightly in summer, they remain within permissible limits, which does not indicate excessive pollution but rather naturally higher concentrations commonly found in river water. Only Cd shows a slight exception, with concentrations (0.39–0.98 μg/L) corresponding to quality classes I–II.

In

Table 8. Physico-chemical parameters of the Arieș River water downstream of Baia de Arieș (A3).

	Parameter	pH	TSS, mg/L	DO, mgO/L	BOD5, mgO/L	COD-Cr, mgO/L	NH4+, mgN/L	NO2−, mgN/L	NO3−, mgN/L
Time, Year/Month
2022	January	7.6	48.7	10.53	0.97	1.46	0.017	0.002	0.157
	April	7.8	143.5	11.27	0.69	2.04	0.024	0.006	0.287
	July	5.7	75.8	8.48	1.84	4.17	0.078	0.009	0.612
	October	6.9	118.3	9.42	1.41	3.26	0.063	0.007	0.398
2023	January	7.9	33.56	10.21	1.04	1.13	0.011	0.003	0.189
	April	7.4	113.7	11.09	0.76	1.96	0.029	0.007	0.335
	July	5.9	47.3	9.14	1.89	3.97	0.081	0.008	0.585
	October	7.2	96.3	10.17	1.17	2.45	0.047	0.006	0.512
2024	January	7.7	49.7	11.23	0.93	1.21	0.008	0.004	0.201
	April	7.3	163.9	11.41	1.23	2.04	0.031	0.005	0.314
	July	6.1	78.5	8.39	1.97	3.68	0.092	0.010	0.537
	October	7.1	104.6	10.13	1.47	2.27	0.054	0.009	0.476

,

Table 9. Salinity parameters of the Arieș River water downstream of Baia de Arieș (A3).

	Parameter	EC, μS/cm	FR, mg/L	Ca, mg/L	Mg, mg/L	Na, mg/L	Bicarbonates, mg/L	Chlorides, mg/L	Sulfates, mg/L
Time, Year/Month
2022	January	169.17	122.4	53.5	4.2	4.2	41.8	6.2	118.7
	April	238.36	175.48	61.9	4.9	5.1	52.7	7.9	129.3
	July	367.12	201.7	72.7	7.5	7.2	101.5	11.2	198.4
	October	244.37	124.7	59.4	6.7	5.9	77.3	9.1	175.4
2023	January	174.20	114.3	51.7	3.1	3.9	38.4	5.8	121.0
	April	198.47	154.7	69.6	4.6	4.4	44.1	7.1	141.7
	July	417.13	196.4	81.4	11.2	6.9	94.5	10.8	201.5
	October	315.81	121.0	75.3	9.3	6.2	82.2	8.3	168.9
2024	January	168.49	128.3	48.3	2.3	5.1	54.4	6.8	116.8
	April	211.38	199.6	71.2	4.3	6.6	75.6	7.1	135.8
	July	354.25	234.7	78.0	11.7	8.1	63.8	9.8	187.2
	October	298.74	118.7	68.2	7.4	7.1	66.7	8.2	174.6

and

Table 10. Content of toxic metal trace elements in the water of the Arieș River downstream of Baia de Arieș (A3).

	Parameter	As, μg/L	Cd, μg/L	Co, μg/L	Cr, μg/L	Cu, μg/L	Fe, mg/L	Mn, mg/L	Ni, μg/L	Zn, μg/L
Time, Year/Month
2022	January	0.27	0.32	0.78	2.42	18.18	0.09	0.038	1.23	74.85
	April	0.31	2.14	3.26	10.04	47.33	0.36	0.096	1.84	125.39
	July	0.49	4.18	4.74	15.7	237.27	0.72	0.541	8.52	327.14
	October	0.35	1.27	2.22	8.82	101.71	0.19	0.384	3.16	165.28
2023	January	0.35	0.45	1.13	3.61	9.23	0.28	0.053	1.35	84.61
	April	0.37	3.07	2.39	9.28	39.52	0.52	0.137	2.22	120.84
	July	0.42	3.99	5.17	19.23	142.08	0.84	0.422	7.27	214.71
	October	0.40	1.52	1.56	6.74	58.32	0.43	0.226	3.69	156.71
2024	January	0.41	0.53	1.54	5.27	13.78	0.24	0.031	1.08	96.74
	April	0.42	2.25	2.34	11.29	23.27	0.41	0.127	4.26	122.6
	July	0.45	4.11	3.85	20.05	98.70	0.67	0.315	6.25	284.57
	October	0.44	1.19	1.89	7.69	44.28	0.33	0.285	5.60	165.38

, the physico-chemical parameters of the Arieș River downstream of Baia de Arieș (A3) are presented, providing relevant information for assessing the impact of mining activities and other pollution sources on water quality.

The water pH ranged from 5.7 to 7.9, with a significant decrease in July 2022 (5.7), which could indicate a temporary acidification of the water, possibly due to decomposition processes or the input of acidic substances during that period. In other periods, the pH remained within the normal range for river waters. Suspended solids showed significantly high values in April 2022 (143.5 mg/L) and April 2024 (163.9 mg/L), suggesting increased turbidity during these periods. These values may have been caused by heavy rainfall, leading to erosion and sediment transport into the water.

DO exhibited moderate fluctuations between 8.39 and 11.41 mg/L. BOD₅ showed an increase during the summer, which suggests a higher organic load during that period, possibly due to the input of organic waste or the decomposition of organic matter. COD-Cr presented higher values during the summer months, peaking at 1.84 mgO/L in July 2022, which may indicate a greater load of organic and inorganic substances, but without exceeding pollution limits.

Ammonium, nitrites and nitrates concentrations indicate potential temporary organic pollution, but without reaching levels dangerous to the ecosystem.

The water conductivity varied between 168.49 μS/cm in January 2024 and 417.13 μS/cm in July 2023, indicating significant fluctuations, with peaks in the summer months. The increase in conductivity during summer may be related to higher evaporation and the concentration of salts in the water under high temperatures and low precipitation conditions. Filterable residue suggests an increase in suspended materials in the water during the summer period, possibly due to rainfall and sediment influx, as well as a higher load of solid substances.

Ca²⁺ concentrations (48.3–81.4 mg/L) fall within quality Class II, indicating good water quality. Sulfates (116.8–201.5 mg/L), mainly falling within quality Class III, indicating moderate water quality typical of areas with natural or slightly anthropogenic sulfate input.

Cadmium showed notable fluctuations, with values (0.32–4.18 μg/L) falling within classes I–IV, most of them in Class IV. This indicates moderate to poor water quality for this metal, without any extreme exceedances (Class V). Copper concentrations range from 9.23 to 237.27 μg/L, indicating possible industrial sources, and covering quality classes I–V, with three values exceeding the permissible limit (Class V). Iron values falling within quality classes I–III, indicating good to moderate water quality without exceeding upper limits. Manganese (0.031–0.541 mg/L) fall within quality classes I–IV, indicating water quality from very good to moderate without exceeding permissible limits. Zinc varied between 74.85 μg/L and 327.14 μg/L, falling within quality classes I–III, indicating water quality from very good to moderate and suggesting influence from industrial sources, as well as precipitation and transport in the aquatic environment.

In

Table 11. Physico-chemical parameters of the Arieș River water upstream of Gligorești (A4).

	Parameter	pH	TSS, mg/L	DO, mgO/L	BOD5, mgO/L	COD-Cr, mgO/L	NH4+, mgN/L	NO2−, mgN/L	NO3−, mgN/L
Time, Year/Month
2022	January	7.9	38.5	10.69	0.83	1.27	0.021	0.003	0.164
	April	8.2	112.7	11.03	0.57	1.67	0.027	0.007	0.294
	July	6.7	68.1	8.98	1.58	3.74	0.084	0.011	0.617
	October	7.2	105.2	9.67	1.27	2.67	0.071	0.008	0.427
2023	January	8.1	30.0	10.61	0.89	1.04	0.019	0.004	0.217
	April	7.9	109.6	10.87	0.57	1.72	0.034	0.009	0.367
	July	6.4	43.8	9.63	1.36	3.30	0.091	0.011	0.597
	October	7.7	91.9	10.45	1.07	2.17	0.053	0.009	0.542
2024	January	8.1	39.3	10.87	0.84	1.07	0.015	0.007	0.231
	April	7.9	154.9	11.23	1.18	1.79	0.042	0.008	0.333
	July	6.3	69.4	8.25	1.84	3.34	0.107	0.013	0.550
	October	7.8	98.3	10.05	1.36	2.11	0.068	0.011	0.497

,

Table 12. Salinity parameters of the Arieș River water downstream but upstream of Gligorești (A4).

	Parameter	EC, μS/cm	FR, mg/L	Ca, mg/L	Mg, mg/L	Na, mg/L	Bicarbonates, mg/L	Chlorides, mg/L	Sulfates, mg/L
Time, Year/Month
2022	January	178.23	135.4	64.0	5.8	5.2	52.3	6.2	18.7
	April	247.37	181.2	61.3	6.7	6.4	63.1	7.9	29.3
	July	388.28	212.6	74.5	12.8	8.3	96.5	11.2	98.4
	October	269.07	135.0	48.2	9.4	7.7	78.7	9.1	75.4
2023	January	184.69	123.1	54.7	6.9	4.5	61.4	5.8	21.0
	April	217.01	161.9	55.1	8.1	5.6	69.9	7.1	41.7
	July	432.07	201.3	75.0	14.4	9.1	102.8	10.8	101.5
	October	356.61	142.5	62.1	9.9	7.0	94.4	8.3	68.9
2024	January	187.10	133.8	48.2	5.3	5.4	52.3	6.8	16.8
	April	232.24	212.4	55.3	7.6	5.6	63.8	7.1	35.8
	July	369.41	245.3	67.8	12.5	7.9	89.6	9.8	87.2
	October	301.17	137.7	74.9	8.8	7.7	78.5	8.2	74.6

and

Table 13. The content of toxic metal trace elements in the Arieș River water upstream of Gligorești (A4).

	Parameter	As, μg/L	Cd, μg/L	Co, μg/L	Cr, μg/L	Cu, μg/L	Fe, mg/L	Mn, mg/L	Ni, μg/L	Zn, μg/L
Time, Year/Month
2022	January	0.31	0.11	1.12	3.41	12.27	0.09	0.096	1.19	8.85
	April	0.32	1.29	2.98	8.96	35.71	0.10	0.124	1.74	42.56
	July	0.41	2.01	3.45	25.41	187.13	0.12	0.285	8.52	101.42
	October	0.39	1.43	2.01	7.62	74.36	0.11	0.181	2.97	71.38
2023	January	0.34	0.09	1.23	2.94	10.21	0.04	0.108	1.20	14.61
	April	0.37	1.42	2.11	6.52	23.84	0.06	0.143	2.74	37.62
	July	0.39	2.27	4.06	19.69	122.17	0.09	0.199	6.88	94.08
	October	0.40	1.19	1.79	9.96	63.86	0.07	0.162	4.19	75.36
2024	January	0.28	0.18	1.42	4.18	13.78	0.03	0.088	1.08	19.97
	April	0.31	1.36	1.84	12.49	28.73	0.12	0.117	1.23	32.86
	July	0.36	1.94	3.97	30.17	98.69	0.14	0.214	6.25	87.63
	October	0.37	0.85	1.49	7.12	54.28	0.08	0.249	3.48	44.20

, the physicochemical parameters of the Arieș River water are presented upstream of its confluence with the Mureș River, near the locality of Gligorești (A4), to highlight water quality before the river leaves the Arieș watershed. This represents a strategic monitoring point, located near the river’s exit from the basin, allowing assessment of the cumulative impact of anthropogenic and natural activities from the entire upper and middle basin on water quality.

The Arieș River, upstream of Mihai Viteazu, shows a pH ranging between 6.3 and 8.2, indicating generally neutral water, with some fluctuations that could be influenced by climatic conditions or human activities. Suspended solids reached high values in April 2024 (154.9 mg/L), suggesting a possible increase in sedimentation, likely due to heavy rainfall or soil erosion.

Overall, this water parameters fall within quality classes I and II, but seasonal fluctuations and increased organic pollution and nutrient levels during the summer require continuous monitoring to prevent long-term deterioration of water quality.

The salinity parameters of the Arieș River water upstream of Gligorești show significant seasonal variations. Overall, they fall within water quality class II, due to the exceedances of the Ca, Mn, and sulfate parameters.

Contamination with toxic metal trace elements in the Arieș River water upstream of Gligorești has varied considerably over the past three years, showing notable seasonal fluctuations.

Arsenic concentrations were relatively low. Cadmium showed a maximum of 2.27 μg/L in 2023, falling within quality classes I–IV, mostly in Class III, indicating moderate water quality. Chromium, peaking at 25.41 μg/L in July 2022 and 30.17 μg/L in 2023, ranged mostly within Class I, with a few values in Class II, indicating generally good water quality. Copper values ranged from 10.21 to 187.13 μg/L, covering classes I–V, with most values in Classes IV and V, indicating variable water quality with two exceedances of permissible limits. Manganese concentrations (0.088–0.285 mg/L) ranged mostly within Class III, with a few values in Class II, indicating moderate water quality.

Most of the analyzed trace metals fall within the limits of water quality class II, but during summer months, when pollution values are highest, there is an increased environmental risk. Elevated Cu, Cd, and Zn concentrations can affect aquatic organisms, such as fish, invertebrates, and algae, and may bioaccumulate, potentially impacting human health through water or food consumption.

After performing various physico-chemical analyses, including metal trace element concentrations, it was found necessary to complement the water quality assessment with biological indicators. Thus, diatom communities were analyzed, with particular attention given to abnormal forms, which can reflect ecological stress or the impact of contaminants on the aquatic ecosystem.

Table 14. Taxonomic structure and saprobic values of diatoms identified at the source of the Arieș River (A1).

Species Name	Number of Individuals	Saprobic Zone	Saprobic Value
Planothidium rostratoholarcticum Lange-Bertalot & Bak	1	β	2
Achnanthidium minutissimum (Kützing) Czarnecki	188	o-β	1.5
Achnanthidium minutissimum (Kützing) Czarnecki-teratological form	11	-	-
Cymbella affinis Kützing	1	o-β	1.5
Cymbella ventricosa Agardh	3	o-β	1.5
Gomphonella olivacea (Hornemann) Rabenhorst	156	β	2
Gomphonella olivacea (Hornemann) Rabenhorst-teratological form	1	-	-
Gomphonema pumilum (Grunow) E.Reichardt & Lange-Bertalot	50	o	1
Total	411	-	-
SI value	1.40	-	-

presents the structure of the diatom community identified at the source, sampling point A1 in the Arieșeni area of the Arieș River, including the number of individuals, corresponding saprobic zones, and saprobic values associated with each species. The data were used to calculate the SI, reflecting the level of organic loading in the water.

The community is dominated by A. minutissimum and G. olivacea, species characteristic of waters with low to moderate organic load. The calculated SI value for this station is 1.40, which indicates Class I quality water, corresponding to an oligosaprobic–β-mesosaprobic zone, therefore clean water with reduced anthropogenic influence.

Table 15. Taxonomic structure and saprobic value of diatoms identified in the Arieș River at the Mihoești sampling point (A2).

Species Name	Number of Individuals	Saprobic Zone	Saprobic Value
Planothidium lanceolatum (Brébisson ex Kützing) Lange-Bertalot	2	β	2
Achnanthidium minutissimum (Kützing) Czarnecki	339	o-β	1.5
Achnanthidium minutissimum Kützing) Czarnecki-teratological form	24	-	-
Amphora pediculus (Kützing) Grunow	13	β	2
Hannaea arcus (Ehrenberg) R.M.Patrick	2	o	1
Cocconeis placentula Ehrenberg	1	β	2
Cymbella gracilis (Ehrenberg) Kützing	3	o	1
Cymbella ventricosa Agardh	35	o-β	1.5
Odontidium mesodon (Ehrenberg) Kützing	1	o	1
Diatoma vulgaris Bory	50	β-α	2.5
Diatoma vulgaris Bory-teratological form	1	-	-
Didymosphenia geminata (Lyngbye) Mart.Schmidt	5	o	1
Fragilaria capucina Desmazières	9	β	2
Fragilaria capucina Desmazières-teretological form	4	-	-
Gomphonema pumilum (Grunow) E.Reichardt & Lange-Bertalot	5	o	1
Navicula cryptotenella Lange-Bertalot	4	β	2
Nitzschia dissipata (Kützing) Rabenhorst	2	o-β	1.5
Ulnaria ulna (Nitzsch) Compère	2	β	2
Total	502	-	-
SI value	1.39	-	-

presents the diatom community from station A2 (Mihoești) of the Arieș River.

The community is dominated by A. minutissimum (339 individuals) and D. vulgaris, species characteristic of clean waters or those slightly affected by organic matter. The SI value is 1.39, indicating Class I quality water, oligosaprobic to β-mesosaprobic. Thus, at station A2, the water maintains a low level of pollution, similar to that at the source (A1), without significant anthropogenic influences.

Table 16. Taxonomic structure and saprobic value of diatoms identified in the Arieș River, Baia de Arieș station (A3).

Species Name	Number of Individuals	Saprobic Zone	Saprobic Value
Planothidium lanceolatum (Brébisson ex Kützing) Lange-Bertalot	5	β	2
Planothidium rostratoholarcticum Lange-Bertalot & Bak	1	β	2
Achnanthidium minutissimum (Kützing) Czarnecki	193	o-β	1.5
Achnanthidium minutissimum Kützing) Czarnecki-teratological form	34	-	-
Amphora pediculus (Kützing) Grunow	1	β	2
Hannaea arcus (Ehrenberg) R.M.Patrick	1	o	1
Discostella stelligera (Cleve & Grunow) Houk & Klee	3	-	-
Cymbella ventricosa Agardh	9	o-β	1.5
Fragilaria capucina Desmazières	13	β	2
Fragilaria capucina Desmazières-teratological form	3	-	-
Fragilaria vaucheriae (Kützing) J.B.Petersen	13	β	2
Fragilaria vaucheriae (Kützing) J.B.Petersen-teratological form	3	-	-
Gomphonema parvulum Kützing	3	β	2
Gomphonema pumilum (Grunow) E.Reichardt & Lange-Bertalot	1	o	1
Navicula cryptotenella Lange-Bertalot	4	β	2
Navicula gregaria Donkin	8	β	2
Navicula cryptocephala Kützing	2	α	3
Navicula viridula (Kützing) Ehrenberg	2	α	3
Nitzschia dissipata (Kützing) Rabenhorst	41	o-β	1.5
Nitzschia gracilis Hantzsch	7	β	2
Nitzschia palea (Kützing) W.Smith	13	α	3
Surirella angusta Kützing	3	β	2
Ulnaria ulna (Nitzsch) Compère	1	β	2
Total	364	-	-
SI value	1.65	-	-

presents the diatom community from sampling point A3 of the Arieș River, located in the area of Baia de Arieș.

The diatom community at A3 is more diverse, with the presence of species characteristic of waters with higher organic load, such as N. cryptocephala and N. palea. The dominance of A. minutissimum (193 individuals) remains, but the relative increase in α-mesosaprobic species indicates a greater influence of organic matter. The SI value is 1.65, corresponding to Class I–II quality water, with slight organic pollution, suggesting that at A3 the water begins to be affected by more pronounced anthropogenic influences compared to A1 and A2.

Table 17. Taxonomic structure and saprobic value of diatoms identified in the Arieș River, Gligorești station (A4).

Species Name	Number of Individuals	Saprobic Zone	Saprobic Value
Planothidium lanceolatum (Brébisson ex Kützing) Lange-Bertalot	2	β	2
Amphora ovalis (Kützing) Kützing	3	α	3
Amphora pediculus (Kützing) Grunow	2	β	2
Cocconeis pediculus Ehrenberg	4	β	2
Cymbella affinis Kützing	19	o-β	1.5
Encyonema cespitosum Kützing	66	β	2
Cymbella tumida (Brébisson) Van Heurck	19	β-α	2.5
Cymbella ventricosa Agardh	3	o-β	1.5
Diatoma vulgaris Bory	3	β-α	2.5
Fragilaria capucina Desmazières	35	β	2
Fragilaria capucina Desmazières-teretological form	5	-	-
Gomphonella olivacea (Hornemann) Rabenhorst	33	β	2
Gomphonema parvulum Kützing	23	β	2
Luticola mutica (Kützing) D.G. Mann	7	α	3
Melosira varians Agardh	34	β	2
Navicula cincta (Ehrenberg) Ralfs	93	β-α	2.5
Navicula cryptocephala Kützing	9	α	3
Navicula cryptotenella Lange-Bertalot	15	β	2
Navicula recens (H.Lange-Bertalot) H.Lange-Bertalot	2	α	3
Nitzschia dissipata (Kützing) Rabenhorst	20	o-β	1.5
Nitzschia inconspicua Grunow	21	α	3
Nitzschia inconspicua Grunow-teratological form	3	-	-
Rhoicosphenia curvata (Kützing) Grunow	1	β	2
Ulnaria ulna (Nitzsch) Compère	8	β	2
Ulnaria ulna (Nitzsch) Compère-teratological form	10	-	-
Total	440	-	-
SI value	1.93	-	-

presents the identified diatom species, the number of individuals, and the saprobic values used to assess the degree of organic load of the water and the potential impact of anthropogenic activities.

The diatom community at the sampling point in the Mureș River (A4) is diverse, with the presence of several α-mesosaprobic species, such as A. ovalis, N. cryptocephala, and N. inconspicua, indicating an increase in organic load and a greater influence of anthropogenic factors. The dominance of β and o-β species, such as E. cespitosum and N. cincta, suggests that the water still maintains moderate to oligosaprobic characteristics. The SI value is 1.93, which indicates Class I–II quality water, with a slight influence of organic pollution and mining activities on the diatom community.

Figure 3a–g present teratological forms of diatoms, which indicate community responses to ecological stress and the presence of pollutants, reflecting alterations in frustule development.

These examples of teratological forms, observed for instance in A. minutissimum, F. capucina, F. vaucheriae, and U. ulna, reflect local ecological disturbances associated with chemical stress or the presence of pollutants. The observations were integrated into the community analysis, and the data were used to calculate the SI, providing a quantitative assessment of the organic load and the ecological status of the water.

4. Discussion

4.1. Influence of Physico-Chemical Parameters on Water Quality

Living organisms, dead organic matter, and dissolved mineral and organic compounds in an aquatic ecosystem are never in an inert state; they are constantly undergoing transformation and circulation, which sustains the existence of living systems [42]. Thus, complex relationships develop among the ecosystem components, ensuring either the stability of these components over time or the dynamic equilibrium of the ecosystem structure as a whole [43].

Nitrogen, an essential nutrient in aquatic ecosystems, enters water through multiple pathways and occurs in various chemical forms: molecular nitrogen, nitrogen oxides, ammonia, ammonium, nitrites, and nitrates [44]. In the ecosystem, nitrogen participates in the biogeochemical cycle and is utilized by autotrophic organisms such as algae, which can consume both free nitrogen in water and ammonium salts, and after their depletion, nitrates [45]. Upon biomass death, decomposition by aerobic microorganisms consumes DO, reflected in the BOD₅ and influencing water quality [11]. Data from the Arieș River show seasonal variations in nitrogen parameters upstream and downstream of the studied locations. For example, N-NH₄ and N-NO₃ concentrations are lower upstream and increase downstream of the Mihoești and Baia de Arieș reservoirs, particularly in summer months, which may be linked to enhanced biological activity and organic matter decomposition at higher water temperatures. BOD₅ values are also higher downstream, suggesting increased oxygen consumption due to organic matter decomposition. These correlations highlight nitrogen’s role in the biogeochemical dynamics of the aquatic ecosystem and reveal the impact of anthropogenic activities on the water quality of the Arieș River.

Our results are in agreement with the findings of Butiuc-Keul et al. [11], who analyzed ions from the Arieș River water (NO₃⁻, NO₂⁻, PO₄³⁻, Cu²⁺, Fe³⁺), highlighting the impact of these parameters on water quality. Alongside this, an analysis of diatom communities was carried out in order to quantify the level of water pollution in the Arieș River, as diatoms are well-known bioindicators of environmental changes. The similarities between our results and those reported by Butiuc-Keul et al. [11] confirm that both chemical indicators and biological communities provide complementary insights into the ecological status of the river.

Many rivers in Europe affected by mining activities show similar patterns of metal enrichment, with high levels of Zn, Cu and Cd reported in sediments and waters downstream of mining and smelting areas. Examples include the Tisza basin (affected by tailings discharges from Baia Mare and Baia Borsa), where high levels of Cu, Zn and Cd have been documented [46], and the Odra River with long-standing Zn–Cu–Cd contamination linked to mining and processing activities from Ostrava and Legnica-Głogów [47]. Studies on Czech rivers (Teplá Vltava and Řasnice) similarly identify localized metal hotspots related to historical industry and glassworks [48]. Recent assessments (18 July 2019) of the Arieș Basin indicate that legacy contamination from mining persists but has declined in some locations over time, with persistent hotspots requiring targeted management [49]. Compared with these cases, the patterns observed in our study—episodic summer increases and localized exceedances of Cu, Cd and Zn—are consistent with diffuse remobilization of legacy mining residues rather than with a single catastrophic release; this emphasizes the need for ongoing monitoring and site-specific mitigation measures.

The analysis of the physicochemical parameters of the Arieș River shows a clear impact of anthropogenic pollution on water quality. Upstream, pH remains stable and DO levels are sufficient to support biological self-purification processes. Downstream of reservoirs and settlements, significant increases in suspended solids, ammonium, and nitrates were observed, indicating contamination with nutrients and organic substances. The BOD₅/COD ratio suggests a moderate capacity for biological self-purification, limited in areas with strong anthropogenic influence, highlighting the need for continuous monitoring and measures to protect the aquatic ecosystem [50,51].

The analysis of salinity parameters in the Arieș River highlights the influence of both natural conditions and anthropogenic pollution. Sulfates, for example, may originate from natural sources, such as gypsum-rich soils or lignite layers, but also from the decomposition of organic substances in wastewater, acid rain, or other impurities [52]. Electrical conductivity and total dissolved solids increase significantly downstream of reservoirs and settlements, indicating the accumulation of salts and contaminants. Maximum sulfate concentrations (up to 201.5 mg/L) and dissolved solids reflect the impact of human activities, while seasonal variations suggest the combined influence of river flow, temperature, and nutrient runoff. These parameters point to localized salinization and underline the need for continuous monitoring to prevent deterioration of the aquatic ecosystem. In other areas of Romania, sulfate concentrations can exceed this threshold. For example, in the Baia Mare region, where mining activities have impacted water quality, sulfate concentrations can reach or exceed 200 mg/L. Additionally, in the case of acid mine waters from the Certej area, sulfate concentrations can reach up to 2.2 g/L [53,54].

In general, the primary sources of elevated heavy metal accumulation in the environment are industrial activities and mining operations. Industrial processes, including metal processing, chemical manufacturing, and improper waste management, can lead to significant releases of metal trace elements into soil, water, and the atmosphere. Similarly, mining activities, through ore extraction and processing, contribute to environmental contamination with metals such as lead, cadmium, and mercury, which can accumulate over time in ecosystems and pose substantial risks to human health and biodiversity [55]. Among the inorganic pollutants found in river water, metal trace elements are of particular concern due to their non-degradable nature and tendency to bioaccumulate along the trophic chain, leading to harmful effects on living organisms [56].

Numerous international studies [57,58] highlight the impact of anthropogenic activities on surface water quality and heavy metal accumulation. Studies from Turkey have reported relatively high concentrations of metal trace elements in surface waters. Observed levels include Cd (between 0.33 and 2.88 µg/L), Co (between 0.7 and 17.2 µg/L), Cr (between 0.13 and 2.02 µg/L), Cu (between 0.06 and895 µg/L), Fe (between 53.3 and 3140 µg/L), Mn (between 5.8 and 402 µg/L), Ni (between 1.4 and 21.0 µg/L), Pb (between 0.1 and 73.0 µg/L), and Zn (between 7.6 and 537 µg/L) [59]. In China, mining activities have affected water quality by increasing concentrations of As (between 0.0 and 6.90 µg/L), Cr (between 0.95 and 42.9 µg/L), Cu (between 1.20 and 19.0 µg/L), Mn (between 2.65 and 168 µg/L), Ni (between 1.69 and 164 µg/L), Pb (between 0.91 and 28.2 µg/L), and Zn (between 2.74 and 490 µg/L) [60]. These findings indicate that certain regions may be subject to significant heavy metal contamination, with potential implications for human health and aquatic ecosystems.

4.2. Diatom Communities of the Arieș River

To interpret the diatom communities identified in the Arieș River, it is important to correlate them with the main sources of pollution in the Arieș River basin. Thus, the first and most historically significant is mining, as the surrounding mountains are rich in gold and other non-ferrous metal deposits; mining activities have generated persistent contamination of water and sediments [61]. The second source is intensive deforestation, which contributes to increased erosion, sediment transport and nutrient loading in rivers [62]. The third group refers to human settlements, including domestic wastewater discharges and agricultural practices, which introduce organic matter, nutrients and other pollutants into the river system. Together, these sources exert a strong influence on the ecological status of the Arieș River, shaping both the chemical environment and the composition of diatom communities.

Table 18. Comparative synthesis of Arieș River water quality from source to discharge (A1–A4).

Stations	Total Number of Individuals	Dominant Species	SI Value	Water Quality Interpretation	Observations Regarding the Influence of Mining Activities
A1–Arieșeni	411	A. minutissimum, G. olivacea	1.40	Class I–clean water	Typical community of oligosaprobic waters; low anthropogenic influence
A2–Mihoești	502	A. minutissimum, D. vulgaris	1.39	Class I–clean water	Water maintains oligotrophic characteristics; minimal anthropogenic influences
A3–Baia de Arieș	364	A. minutissimum, N. dissipata	1.65	Class I–II–slight organic pollution	Increase in α-mesosaprobic species indicating more pronounced anthropogenic influences, likely from wastewater and mining activities
A4–Gligorești	440	N. cincta, E. cespitosum, F. capucina	1.93	Class I–II–slight organic pollution	More diverse community, with α and β–α species, indicating the impact of mining activities and moderate pollution; slightly increased organic load

summarizes the water quality of the Arieș River from source to discharge (A1–A4).

Along the course of the Arieș River, the water starts relatively clean at A1 and A2, with a community dominated by oligosaprobic species, indicating good water quality and minimal anthropogenic influence. At A3 and A4, α-mesosaprobic species appear and the SI value increases, showing slight organic pollution and a greater influence of anthropogenic activities, especially mining. The diatom community becomes more diverse downstream, reflecting adaptation to conditions with higher dissolved substances, yet the water still remains suitable for sustaining a moderate aquatic biodiversity. Thus, a gradual deterioration of water quality is observed along the course of the river, from good status at the source to slight pollution before the discharge, mainly caused by mining activities and the input of organic matter.

Table 19. Biodiversity indices by each sampling point.

Sampling Point	Shannon (H’)	Simpson (1-D)	Richness (Number of Species)	Total Cells
A1	0.85	0.46	6	224
A2	1.90	0.78	14	139
A3	1.55	0.59	20	364
A4	2.61	0.91	21	347

presents the values of biodiversity indices (Shannon, Simpson, and Richness) for the studied sites, providing an overview of the structure and complexity of ecological communities in relation to environmental conditions and the degree of disturbance.

At site A1, diversity is very low, the community being almost entirely dominated by G. olivacea and G. pumilum. In contrast, at A2 diversity is moderate, with the presence of several species, although their abundances are moderate. At A3, higher diversity is observed due to the greater number of identified species, but the dominance of a few of them keeps the Shannon index relatively low. Site A4 exhibits the highest diversity and a good balance among species, as reflected by the maximum values of the Shannon and Simpson indices.

Although the present study provides insights into the relationship between metal contamination and diatom deformities in mining-affected rivers, several limitations should be acknowledged. Sampling was restricted to a single year, which may not fully capture seasonal or interannual variability in metal concentrations and diatom community responses. Furthermore, the number of sampling sites was limited, and additional long-term monitoring would be necessary to confirm the observed patterns and strengthen the ecological interpretation. Future research should include multi-year sampling campaigns and integrate complementary biological and geochemical indicators to better assess the temporal dynamics of metal-induced stress in fluvial ecosystems.

4.3. Teratological Forms of Diatoms

Morphological deformities in diatom communities have been increasingly recognized as sensitive indicators of sub-lethal metal stress in aquatic ecosystems. Exposure to elevated concentrations of trace metals such as Cd, Pb, Zn, or Cu can disrupt the normal valve morphogenesis in diatoms, leading to teratological forms that reflect physiological impairment rather than lethal toxicity [63]. Such abnormalities, including irregular valve outlines, deformities in striae patterns, or incomplete silicification, provide an integrative biological signal of chronic metal exposure, complementing chemical monitoring data [64]. The occurrence and frequency of these deformities have therefore been proposed as reliable indicators of anthropogenic contamination, particularly in mining-impacted river systems [63]. Teratological forms of diatoms provide a valuable biological complement to chemical monitoring in mining-affected rivers [65].

The analysis of teratological forms of diatoms along the Arieș River revealed variations in the degree of sub-lethal stress across different sampling sites. At the source (A1), teratological individuals accounted for about 2.9% of the diatom community. This low percentage indicates minimal anthropogenic influence and reflects the relatively pristine condition of the upstream water. At Mihoești (A2), deformities increased to 5.8%, suggesting slight environmental stress, possibly linked to local human activities, although water quality remained generally high, as indicated by the SI. The highest proportion, 11%, occurred at Baia de Arieș (A3), reflecting increased organic load and anthropogenic impact compared to upstream sites. This rise in deformities is likely linked to the input from the Abrud River, which drains areas with historical and recent mining activities, introducing elevated levels of metal trace elements and other contaminants into the Arieș River. At A4, the percentage of teratological diatoms decreases slightly but remains above the levels recorded at the source (A1), suggesting that moderate pollution effects persist further downstream.

Downstream at Gligorești (A4), the percentage of teratologies decreased slightly to 4.1%, with F. capucina, N. inconspicua, and U. ulna showing deformities. Despite this decrease, the presence of teratological forms indicates that anthropogenic influence persists, and water quality is moderately affected by organic and chemical stressors.

Considering the Arieș River as a whole, teratological diatoms accounted for approximately 5.8% of the total community, highlighting the cumulative impact of environmental stress along the river course. The distribution of deformities demonstrates the sensitivity of diatoms to anthropogenic pressures and underlines their value as bioindicators for assessing sub-lethal stress and ecological integrity in freshwater ecosystems.

The presence of teratological forms in diatom communities along the Arieș River provides a clear indication of ecological stress and metal contamination, particularly from cadmium. Our results suggest that some species, such as Cocconeis pediculus, C. placentula, Eolimna minima, Gomphonema parvulum, Nitzschia fonticola, Planothidium frequentissimum, and Ulnaria ulna, exhibit morphological deformities in response to Cd pollution. This aligns with previous studies of Szekely-Andorko et al. [10] demonstrating that specific diatoms respond with valve abnormalities to heavy metal exposure, while other species remain relatively unaffected, reflecting differences in tolerance and adaptive capacity.

Species such as A. minutissimum, known for its ecological tolerance [66,67], showed relatively low levels of teratologies despite Cd presence, whereas sensitive species like G. parvulum displayed higher percentages of abnormalities [67,68,69]. This pattern highlights the potential use of teratological forms as bioindicators for assessing the severity and distribution of metal pollution in freshwater ecosystems.

While Cd appears to be the primary stressor, we cannot exclude the potential additive or synergistic effects of other metals (e.g., Zn, Cu, or Ni) or environmental factors, such as hydrological changes or nutrient fluctuations. The development of teratologies may therefore reflect both direct chemical stress and indirect ecological pressures [70].

Similarly to studies conducted on the Bormida River [67], where Cd contamination was identified as the main factor influencing diatom teratologies in Mayamaea permitis, Navicula gregaria and Nitzschia dissipata, our analysis of the Arieș River revealed a significant correlation between the presence of deformed cells in certain species (Cocconeis pediculus, C. placentula, Gomphonema parvulum, Nitzschia fonticola, Ulnaria ulna) and Cd concentrations. However, statistical analysis showed that only a subset of species could be considered reliable indicators of heavy metal pollution. Comparison with previous research by Morin et al. [71] suggests that while correlations with Cd may vary between studies, additive or synergistic effects of multiple metals, as well as other environmental stressors, likely contribute to the development of teratological forms [60]. They showed that Cocconeis pediculus, C. placentula, Eolimna minima, Gomphonema parvulum, Nitzschia fonticola, Planothidium frequentissimum, and Ulnaria ulna can develop abnormal forms in response to Cd pollution.

Overall, the analysis confirms that monitoring teratological forms in diatom communities provides valuable insights into water quality and metal contamination, offering a practical tool for ecological assessment and pollution management in rivers affected by anthropogenic activities.

The results of this study have important ecological and policy implications, particularly in the context of the European Union Water Framework Directive (WFD) [72], which emphasizes the use of biological quality elements, including benthic diatoms, for assessing the ecological status of surface waters. The presence of teratological diatom forms associated with metal contamination indicates sub-lethal stress that may precede significant ecological degradation, thus offering an early-warning signal relevant for water management and restoration planning [63,65]. Integrating diatom deformity analyses with chemical monitoring could improve the detection of subtle anthropogenic pressures and support the development of more responsive remediation strategies in mining-impacted catchments [21,73]. Consequently, the inclusion of diatom-based indicators in national biomonitoring programs would contribute to achieving the WFD objectives of “good ecological status” and guiding targeted restoration actions in contaminated river systems [72,74].

4.4. Statistical Analysis [75]

4.4.1. Principal Component Analysis of Water Chemical Parameters

In performing the Principal Component Analysis, all physico-chemical, salinity and metal trace element parameters were considered (Figure 4).

The Principal Component Analysis (Figure 4) highlighted that the first three components explain approximately 81% of the total variance in the dataset, indicating a strong structure within the environmental dataset. PC1 accounts for 61% of the variance and clearly reflects a general pollution gradient. It is strongly positively associated with electrical conductivity, ammonium, organic matter indicators (COD-Cr, BOD₅), and several metals (Cd, Co, Cr, Cu, Mn, Ni, Zn). This axis therefore represents a clear gradient of mineralization and pollution, separating well-oxygenated, less impacted waters from those enriched in dissolved ions and trace metals.

PC2, which explains 14% of the variance, has positive correlations with dissolved oxygen and total suspended solids and negative ones with nitrates, bicarbonates, and organic load, suggesting differences in oxygenation and nutrient balance among sites.

PC3, responsible for 6.5% of the total variance, captured additional variability related mainly to iron and zinc concentrations, reflecting localized metal inputs.

The PCA indicates that water samples are distributed along a continuum from clean, oxygen-rich conditions to more mineralized and organically enriched environments.

4.4.2. Canonical Correspondence Analysis of Heavy Metal Effects on Diatoms

Figure 5 illustrates the results of a Canonical Correspondence Analysis (CCA), highlighting the relationship between environmental variables and the distribution of diatom species. The plot also shows how dominant taxa respond to variations in water quality, providing insight into the ecological effects of pollution and the potential use of these species as bioindicators.

The CCA ordination focusing on environmental variables (physico-chemical, salinity and trace metal parameters) and diatom abundance revealed clear ecological gradients. Axis 1 (36.8% of constrained inertia) mainly reflects organic pollution and nutrient enrichment, with variables such as BOD₅, COD-Cr, NH₄⁺, and EC associated with tolerant taxa like Nitzschia palea, Surirella angusta, and Navicula viridula. In contrast, species such as Achnanthidium minutissimum and Gomphonema pumilum occur in cleaner, better-oxygenated waters. Axis 2 (33.4%) represents a secondary gradient related to dissolved oxygen and nutrient balance, separating taxa typical of low-oxygen, nutrient-rich sites from those of oligotrophic environments. Axis 3 (29.8% of constrained inertia) reflects secondary variation related to slight changes in salinity and metal levels (especially Fe, Cu, and Zn). Overall, the three axes show that diatom communities respond along a gradient from clean, oxygen-rich, low-nutrient waters to more mineralized and organically polluted environments. Although Monte Carlo tests showed no statistical significance (p > 0.05), the ordination still indicates that diatom communities respond predictably to variations in organic load, nutrients, and ionic composition, confirming their usefulness as bioindicators of water quality.

4.4.3. Metal Trace Elements–Diatom Correlations (Pearson)

Table 20. Pearson correlation coefficients between metal trace elements and diatom species distribution.

Diatoms vs. Metal Trace Elements	As	Cd	Cr	Cu	Fe	Ni	Zn
Planothidium rostratoholarcticu	−0.083	0.194	−0.294	−0.112	0.472	0.967	0.556
Achnanthidium minutissimum	0.547	0.840	0.422	0.339	0.985	0.785	0.976
Cymbella affinis	−0.522	0.142	0.602	0.743	−0.301	−0.625	−0.171
Cymbella ventricosa	0.714	−0.247	−0.219	−0.587	−0.091	−0.358	−0.323
Gomphonella olivacea	−0.809	−0.631	−0.698	−0.347	−0.531	0.242	−0.386
Gomphonema pumilum	−0.623	−0.684	−0.848	−0.564	−0.472	0.343	−0.379
Planothidium lanceolatum	0.742	0.935	0.719	0.498	0.939	0.371	0.874
Amphora pediculus	0.584	−0.327	−0.174	−0.518	−0.256	−0.561	−0.472
Hannaea arcus	0.898	0.034	−0.069	−0.467	0.233	−0.111	−0.003
Cocconeis placentula	0.573	−0.397	−0.295	−0.627	−0.273	−0.483	−0.492
Cymbella gracilis	0.573	−0.397	−0.295	−0.627	−0.273	−0.483	−0.492
Odontidium mesodon	0.573	−0.397	−0.295	−0.627	−0.273	−0.483	−0.492
Diatoma vulgaris	0.555	−0.394	−0.262	−0.593	−0.294	−0.530	−0.510
Didymosphenia geminata	0.573	−0.397	−0.295	−0.627	−0.273	−0.483	−0.492
Fragilaria capucina	−0.074	0.466	0.865	0.835	0.043	−0.587	0.097
Navicula cryptotenella Lange-Be	−0.200	0.345	0.788	0.797	−0.094	−0.653	−0.024
Nitzschia dissipata	0.396	0.994	0.808	0.749	0.909	0.451	0.946
Ulnaria ulna	−0.428	0.134	0.621	0.709	−0.313	−0.710	−0.211
Discostella stelligera	0.573	0.860	0.457	0.359	0.992	0.753	0.978
Fragilaria vaucheriae	0.573	0.860	0.457	0.359	0.992	0.753	0.978
Gomphonema parvulum	−0.418	0.296	0.719	0.833	−0.148	−0.555	−0.023
Navicula gregaria	0.573	0.860	0.457	0.359	0.992	0.753	0.978
Navicula cryptocephala Kützing	−0.369	0.384	0.775	0.881	−0.055	−0.491	0.071
Navicula viridula	0.573	0.860	0.457	0.359	0.992	0.753	0.978
Nitzschia gracilis	0.573	0.860	0.457	0.359	0.992	0.753	0.978
Nitzschia palea	0.573	0.860	0.457	0.359	0.992	0.753	0.978
Surirella angusta	0.573	0.860	0.457	0.359	0.992	0.753	0.978
Ulnaria ulna_1	0.573	0.860	0.457	0.359	0.992	0.753	0.978
Amphora ovalis	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150
Cocconeis pediculus	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150
Encyonema cespitosum	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150
Cymbella tumida	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150
Luticola mutica	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150
Melosira varians	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150
Navicula recens	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150
Nitzschia inconspicua	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150
Rhoicosphenia curvata	−0.478	0.174	0.634	0.757	−0.273	−0.634	−0.150

presents the Pearson correlation coefficients between the concentrations of various trace elements (As, Cd, Cr, Cu, Fe, Ni, Zn) and the diatom species identified at the studied sites. The values highlight how dominant species respond to heavy metal contamination, providing insights into their potential as bioindicators of water quality.

The Pearson correlation analysis between heavy metal concentrations and diatom species in the Arieș River reveals differentiated responses of the communities to metal pollution (Table 20). Cadmium shows strong positive correlations with species such as N. dissipata (r = 0.994) and A. minutissimum (r = 0.840). In contrast, species such as G. olivacea and G. pumilum show negative correlations. Correlations with other metals, such as As, Fe, Cu, and Zn, show similar patterns. These relationships allow for the identification of more impacted areas and provide a basis for long-term ecological monitoring, using diatoms as reliable bioindicators of aquatic ecosystem health.

5. Conclusions

The study demonstrates that water quality in the Arieș River is generally good at most monitoring points, corresponding to Class I–II physico-chemical status. Seasonal increases in physico-chemical parameters, particularly in summer, reflect combined natural and anthropogenic influences, highlighting the need for continuous monitoring. However, downstream sites (A3–A4) reflected the impact of mining and industrial activities, particularly through elevated concentrations of trace elements such as Cd and Cu.

A novel aspect of this study is the integration of diatom deformities with chemical data as indicators of sub-lethal metal stress. The occurrence of teratological forms in species such as Amphora ovalis, Navicula cryptocephala, and Nitzschia inconspicua provides a sensitive biological signal of ecological stress associated with heavy metal accumulation.

These findings highlight the importance of long-term biomonitoring in mining-impacted rivers, as diatom deformities can serve as early-warning indicators of ecological deterioration before water quality reaches critical levels. The results support specific management recommendations for the Arieș River, including targeted monitoring of heavy metals, regular assessment of benthic diatom communities, and implementation of restoration measures to mitigate metal and organic pollution downstream of mining areas.