#phreeqc — Public Fediverse posts

🧪 Differential material balance of cascade EFC: from flowsheet to FEED

💻 Thermodynamic modeling of eutectic freeze crystallization for hypersaline mine waters (Kryvyi Rih Iron Ore Basin, n = 40 samples, PHREEQC + FREZCHEM):
🔹 Mirabilite (Na₂SO₄·10H₂O): Depletes before −20.0 °C as free SO₄²⁻ is exhausted; residual trace sulfates are bound by gypsum.
🔹 Purity buffer (−20.0 … −22.5 °C): Zero salt yield almoust (0.00 g). Pure ice generation prevents cross-contamination during crystallization swings.
🔹 Hydrohalite (NaCl·2H₂O): Surges below −22.5 °C with peak yields of 15–17 g/step across the entire ensemble.
🔹 Trace minerals: Sub-gram gypsum & ikaite (CaCO₃·6H₂O) stay ≤0.16 g/step.
🔹 Refrigeration design: Differential ice profile yields exact thermal loads for crystallizer sizing.

☝️ Transitions EFC scoping directly into Front-End Engineering Design (FEED).

#Geochemistry #WaterTreatment #Mining #EFC #PHREEQC #ProcessEngineering #FREZCHEM #IndustrialWastewater #KryvyiRih #DataScience #SvystunovaGully

💻 Continuing the visualization of the obtained dataset of thermodynamic calculations for 40 samples of hypersaline mine water from the Kryvyi Rih iron ore basin (modeling in PHREEQC, FREZCHEM database).

❗ The calculation of cascade eutectic freeze crystallization reveals a fundamentally picture:
🔹 Stage 1 (0 … −20°C): down to −6.5…−9.5°C, only pure ice freezes out (freezing point depression zone). Then, the precipitation of mirabilite (Na₂SO₄·10H₂O) begins.
🔹 Interstage buffer (−20.0 … −22.5°C, yellow band): key technological buffer (ΔT = 2.5°C). In this range, exclusively secondary ice crystallizes. In none of the 40 samples does hydrohalite precipitate earlier than the calculated −22.5°C.
🔹 Stage 2 (−22.5 … −35°C, orange zone): avalanche-like precipitation of hydrohalite (NaCl·2H₂O).

#Geochemistry #WaterManagement #PHREEQC #DataScience #EnvironmentalEngineering #Mining #SvystunovaGully #KryvyiRihBasin #EFC #EutecticFreezeCrystallization #FREZCHEM #RStats

📝 У роботі представлено термодинамічне обґрунтування технології двостадійного каскадного евтектичного виморожування (Eutectic Freeze Crystallization, EFC) для очищення та комплексної переробки розсолів зі ставка-накопичувача у балці Свистунова.

☝️ Доведено, що проведення процесу в дві стадії з міжстадійною сепарацією при -20,0°C формує температурний буфер у 2,5°C до початку осадження хлоридів і дозволяє селективно розділити сульфатну та хлоридну фракції.
🧪 Загальний вихід опрісненої води (льоду) становить 964,07 г на 1 кг вихідної H2O (96,4% рекуперації). При цьому об'єм первинного розчину скорочується у 62 рази.

🔗 www.doi.org/10.5281/zenodo.22821615

#Hydrogeology #Geochemistry #WaterManagement #PHREEQC #DataScience #EnvironmentalEngineering #Mining #SvystunovaGully #KryvyiRihBasin #EFC #EutecticFreezeCrystallization #FREZCHEM

⚙️ My latest preprint presents a thermodynamic rationale for a two-stage cascade Eutectic Freeze Crystallization (EFC) process, developed for the treatment and resource recovery of hypersaline mine water from the Svystunova Gully impoundment (published in Ukrainian).

☝️ Key highlights:
🔹 Selective phase separation: Conducting the process in two stages with inter-stage solids separation at -20.0°C provides a 2.5°C operating buffer before chloride salts begin to precipitate, ensuring clean separation of sulfate and chloride fractions.
🔹 High water recovery: The total yield of desalinated water (as pure ice) reaches 964.07 g per 1 kg of initial H2O (96.4% recovery rate).
🔹 Effluent minimization: The initial wastewater volume is reduced 62-fold, concentrating the residual components into a compact, heavy bittern.

🔗 Full preprint: https://doi.org/10.5281/zenodo.22821616

#MineWater #WaterTreatment #Geochemistry #Thermodynamics #PHREEQC #EFC #Mining #CriticalRawMaterials #CircularEconomy #SvystunovaGully #KryvyiRihBasin #FREZCHEM

🧪 Continuing my computational experiments on Kryvbas high-mineralized mine water management.

☝️ This time, I took available water chemical analyses covering a 10+ year period (2012-2023) - a total of 40 water samples from the storage pond in the Svystunova gully. Freeze crystallization is modeled in two stages: the first stage ends at -20℃ and involves removing the formed mirabilite to prevent further dissolution during the hydrohalite precipitation stage.

📈 The graph shows the averaged results. Despite variations in the initial water composition - the freezing crystallization pathway remains stable. The variation in the onset of precipitation in the first stage is ∓3,5℃, in the second - tenths of a degree. The precipitate mass yields differ. Meanwhile, magnesium and potassium minerals - remain undersaturated all the way to the boundary of the modeling zone.

#WaterManagement #PHREEQC #EnvironmentalEngineering #Mining #SvystunovaGully #KryvyiRihBasin #EFC #EutecticFreezeCrystallization #FREZCHEM

🧪 Two-stage eutectic freeze crystallization of Kryvbas mine waters (EFC)

💻 Modeling with PHREEQC and FREZCHEM model.

☝️ The process is divided into two stages with inter-stage separation at -20 °C:
🔹 Stage 1 (0 to -20 °C): Freezing of fresh ice (up to ~890 g per 1 kg of feed water). Selective precipitation of mirabilite (Na₂SO₄·10H₂O), which is completely separated on the filter (~4.6 g).
🔹 Stage 2 (-20.5 to -35 °C): Deep eutectic crystallization of hydrohalite (NaCl·2H₂O) after sulfate removal (~40 g of pure salt). The total yield of technical fresh water across both stages reaches ~968 g (96.8% solvent recovery).

❗ At the output, we obtain pure solid phases and a minimal residual mother brine (~1.3% by volume) for the subsequent extraction of trace elements (Br, Li, B, I).

#Geochemistry #PHREEQC #FREZCHEM #WaterManagement #KryvyiRih #OpenScience #DataScience #EnvironmentalEngineering #Mining #SvystunovaGully #KryvyiRihBasin #EFC

Thermodynamic Modeling & Policy Relevance

As regulatory discussions and technical feasibility studies for the Svystunova Gully mine-water retention system (2026–2027 period) get underway, integrating rigorous thermodynamic modeling into the engineering baseline is critical.

Simple dilution metrics do not account for mass-balance limits, bedrock dissolution, concrete leaching, or secondary mineral precipitation along the waterway. Following today’s session of the government interdepartmental working group, I submitted key findings from my open-access research to support evidence-based decisions. The submitted package includes speciation models, phase equilibria calculations, and reactive transport assessments focused on mining wastewater management and dam stability evaluation.

#Hydrogeology #Geochemistry #WaterManagement #PHREEQC #DataScience #EnvironmentalEngineering #OpenScience #Mining #SvystunovaGully #Ukraine #KryvyiRihBasin

🧪 Bridging Hydrochemistry, Thermodynamic Modeling & GIS: A Relational Schema

🗂️ Hydrogeochemical workflows are often fragmented across spreadsheets, standalone PHREEQC runs, and GIS layers, creating transfer errors and scaling friction.

⚙️ To build a reproducible pipeline, I structured a relational schema connecting raw chemistry, thermodynamic speciation, and spatial topology:
🔑 Relational Keys: Linked via Solution ID and Sampling Location to preserve data integrity across all stages.
⚛️ Automated Speciation: Raw ionic assays are ingested into PHREEQC to computation.
🗺️ Spatial Binding: Speciation outputs join spatial geometries in R (sf and terra packages) for contaminant plume mapping and cross-sections.

📖 Full methodology and regional case studies are detailed in my open-access monograph on mineralized groundwater plume.

💬 Open-access link:
https://doi.org/10.5281/zenodo.20709306

#Hydrogeology #Geochemistry #PHREEQC #RStats #SpatialData #GIS #OpenScience #Groundwater #SvystunovaGully

🔥 The draft PDF of my hydrogeochemical modeling monograph on Zenodo (CERN/OpenAIRE) just surpassed 50,000 views and 2,550+ downloads (over 33 GB of bandwidth).

☝️ This proves that dense, rigorous technical analysis easily transcends language barriers. Even with the manuscript written in Ukrainian, the detailed geochemical speciation charts, balance tables, and spatial maps speak a universal engineering language. Verifiable methodologies and clear analytical visuals always find their audience.

👇 The link to download the current version of monograph (v0.80, Open Access, in Ukrainian):
https://doi.org/10.5281/zenodo.20709306

#KryvyiRihBasin #IronOre #MineWater #Hydrogeology #PHREEQC #SvystunovaGully #Geochemistry #Contamination #RStats #Groundwater #DataScience #Zenodo

🧪 Aquatic zinc speciation modeling across the Inhulets River (September 2025) highlights why total metal concentrations fail to reflect true ecotoxicity:

☝️ Key Hydrogeochemical Trends:
🔹 Free aqua-ion (Zn²⁺): Dominates at most stations (57–64%). This fraction is the most bioavailable and drives aquatic toxicity.
🔹 Carbonate complex (ZnCO₃⁰): Secondary background form (18–24%), facilitating conservative transit migration.
🔹 Sulfate complex (ZnSO₄⁰): Consistently 6–11% due to elevated background sulfate mineralization.
🔹 Shift at Sample Point 6_1 (pH 8.66): Alkaline buffering radically alters speciation—free Zn²⁺ drops to 32%, while ZnCO₃⁰ becomes dominant (49%) alongside rising ZnOH⁺ (8%).

Methodology:
⚙️ Speciation: PHREEQC (Thermoddem database)
⚙️ Pipeline & Dataviz: R (tidyverse, ggplot2)
⚙️ Minor species (<0.5%) aggregated into "Other" (Інші форми).

#Hydrogeochemistry #PHREEQC #RStats #WaterQuality #EnvironmentalDataScience #InhuletsRiver #KryvyiRih #Geochemistry #OpenScience #Mining #IronOreMining

Added 25 mg/L Silicon (Si) and 5 mg/L Aluminium (Al) to the hydrogeochemical baseline of the Svystunova Gully mine water impoundment, modeling clay mineral phase equilibria using RedModRphree + PHREEQC (Thermoddem database, T = 12°C).

Key thermodynamic outcome (pe–pH diagrams across pH 2–10):
The solid-phase stability field is completely dominated by Beidellite(Na) and acidic forms of montmorillonite (Hmontmorillonite).

#Geochemistry #Hydrogeology #PHREEQC #ThermodynamicModeling #EnvironmentalDataScience #Rstats #Geoscience #ClayMineralogy #SvystunovaGully

🛠 What does an end-to-end open-source stack look like for an independent hydrogeochemical monograph?

Doing full-cycle research—from thermodynamic calculations to print-ready LaTeX typesetting—requires a synchronized toolkit. Here is the exact stack:

🧪 Thermodynamics & Analytics:
• #PHREEQC 3.7.3 for aqueous speciation&equilibrium modeling.
• #Rstats Stack: RedModRphree, ggtern, sf/terra, tidyverse (ETL).

🗺 GIS & Literature Search:
• #QGIS for spatial alignment & cartography.
• #Recoll for local full-text search across reference databases.

📚 Typesetting & Reproducibility:
• #LaTeX2e + #TeXStudio + #JabRef for typography & #BibTeX references.
• xtable for automated R-to-LaTeX data exporting.
• #Debian Linux as a main engine.

💡 Takeaway: Zero proprietary software licenses needed. Complete reproducibility from raw analytical data to a print-ready PDF.

🔗 The published version of monoghraph is here:
https://zenodo.org/records/20709306

#Hydrogeology #Geochemistry #LaTeX #GIS #OpenScience #DataScience #SvystunovaGully

A methodological audit of regional hydrogeochemical literature reveals a systemic gap. Legacy environmental assessments for the Kryvyi Rih Iron Ore Basin rely on frameworks designed for fresh water, which fail when applied to highly mineralized mine waters. Standard equilibrium algorithms are inadequate for environments with extreme ionic strength.

This limitation extends to mass transport: conventional modeling overlooks density-driven convection and gravitational settling of heavy brines, leading to inaccurate spatial migration models.

Overcoming this inertia requires a return to the fundamental laws of chemical thermodynamics and multiphase flow physics, aligning predictive models with actual environmental constraints.

👇 The link to download the updated monograph (v0.80, Open Access, in Ukrainian):
https://doi.org/10.5281/zenodo.20709306

#KryvyiRihBasin #IronOre #MineWater #Hydrogeology #PHREEQC #SvystunovaGully #Geochemistry #Contamination #RStats #Groundwater #DataScience

🔥 Dear colleagues! I present to you the new version (0.80) of my monograph dedicated to the hydrogeochemical (thermodynamic) modeling of the contamination plume around the storage pond in the Svystunova Gully (in Ukrainian).
I have significantly expanded the theoretical and practical sections, adding a description of the hydrodynamic properties and behavior of highly mineralized plumes.

The comprehensive concept of the gradual advancement of the contamination plume and the resulting technogenic karst is now revealed.

❗ In the section 1.2 I critically analyze the methodologies and conclusions of previous studies on the technogenic water bodies of the Kryvbas and the propagation processes of contamination plumes from these sites.

The link to the new version of the monograph:
https://doi.org/10.5281/zenodo.20709306

#phreeqc #SvystunovaGully #geochemistry #minewater #contamination #RStats #groundwater #DataScience #IronOreMining #GIS #EnvironmentalDataScience

Updating the graphical materials for the new edition of the monograph on the thermodynamic modeling of processes in technogenic waters. The figures present pe-pH stability (Pourbaix) diagrams for the vanadium and zinc systems, calculated using the PHREEQC core engine. Unlike simplified "water–element" systems, these models compute the thermodynamic equilibrium of the comprehensive solution matrix, accounting for actual macrocomponent concentrations, ionic strength, and ligand competition at every point of the computational space. Utilizing multicomponent calculations allows for the analysis of physicochemical processes in real water samples, rather than simply reproducing idealized "textbook diagrams".

#Geochemistry #PHREEQC #RStats #MineWater #EnvironmentalScience #DataScience #SvystunovaGully #RedModRphree #FOSS

A slightly tongue-in-cheek AI animation of a conceptual model showing leakage of highly mineralized mine waters into a carbonate aquifer:
https://youtu.be/WDIze8QNMYs

Yes - it’s simplified. Yes - real systems are messier.
But sometimes a "clean" visual helps to communicate density-driven flow and reactive processes more intuitively than 20 pages of equations.

The animation idea emerged while working on my monograph. Draft versions are available here:
https://zenodo.org/records/16741148

Engineering humor is allowed - even in hydrogeochemistry 😁

#Hydrogeochemistry #Groundwater #MineWater #ReactiveTransport #CarbonateAquifer #PHREEQC #AIinScience #Geoscience #SvystunovaGully

How reliable are dilution estimates in contaminated aquifers?

In my current monograph, I validated the dilution coefficient using two fully independent approaches:
- chloride concentrations as a conservative tracer
- solution density calculated in PHREEQC (Laliberté–Cooper model)

I then performed a robust statistical comparison of both dilution estimates (n ≈ 2000).
The result: no statistically significant difference between the two methods (Mann–Whitney test), with very close median values and negligible effect size.

❗What does this mean in practice?
It confirms that density-based calculations — often ignored in groundwater contamination studies — provide robust, independent validation of classical tracer-based approaches.
This is especially important for highly mineralized mine waters, where density-driven processes (e.g. buoyancy effects, Rayleigh–Taylor instability) can critically affect plume behavior.

#Groundwater #Geochemistry #PHREEQC #MineWater #Hydrogeology #RStats #SvystunovaGully

Thousands of studies describe Rayleigh–Taylor instability, and most hydrogeological models acknowledge its importance in contaminant transport.

However, in studies of the Svystunova gully mine-water storage pond, I have not seen density explicitly accounted for — despite highly mineralized waters where this factor can fundamentally change plume behaviour.
By calculating solution density within the contamination halo, I demonstrated a real risk of gravity-driven sinking of the contamination plume to the base of the aquifer. This finding adds a critical dimension to impact assessment and is now documented as a standalone section in my ongoing report.

If you work with mine water, aquifers contamination, or long-term contamination modelling, this is a parameter worth revisiting.

#Hydrogeochemistry #Groundwater #MineWater #PHREEQC #RStats #QGIS #EnvironmentalRisk #Contamination #RiskAnalysis #SvystunovaGully

Based on the metasomatic (thermodynamic) zonation of the groundwater contamination plume identified in my study, I prepared a schematic impact map.

Unlike conventional chloride concentration isolines (which are often weakly informative), this approach reflects the thermodynamic state of the aquifer. The map clearly shows that the aggressive corrosion-by-mixing zone (Subzone III) occupies a large area and, in several places, extends beyond the existing monitoring well network.

This indicates that the current monitoring system is insufficient to delineate the full zone of influence of the mine water impoundment.

The criteria for defining metasomatic subzones and the associated risks are described in detail in the current published version of my monograph:
https://zenodo.org/records/16741148

#PHREEQC #RStats #QGIS #Geochemistry #Groundwater #Contamination #Hydrogeology #EnvironmentalGeochemistry #SvystunovaGully

I’m currently open to opportunities related to environmental geochemistry, groundwater, and geochemical modeling.

My background includes PHREEQC-based modeling, reproducible workflows (R, QGIS), environmental data analysis, applied machine learning (exploratory / environmental) and applied research on mine-water impacts on carbonate aquifers.

An example of my applied research and methodology (open access):
https://zenodo.org/records/16741148

Based in Canada (Calgary). Open to discussions and professional connections.

#Hydrogeochemistry #Groundwater #EnvironmentalGeochemistry
#PHREEQC #GeochemicalModeling #ReproducibleResearch #Canada #Alberta #Calgary #YYC

#SvystunovaGully
I’ve published a short methodological paper on Zenodo, derived from my ongoing monograph on mine-water impact on carbonate aquifers.

The note introduces the pre-dissolution effect — a positive feedback mechanism where aggressive saline waters accelerate carbonate dissolution, increasing permeability and prolonging contamination even after the source is isolated.

The focus is not on a single case study, but on a transferable geochemical interpretation framework (PHREEQC-based, reproducible, field-data driven).

📄 Open access: https://zenodo.org/records/18142106

#Hydrogeochemistry #EnvironmentalGeochemistry #PHREEQC #Groundwater #ReproducibleResearch #RStats #QGIS #FOSS

Seven months after publishing the draft of my monograph on Zenodo, it has passed 2,000 downloads.

I take this as a signal of ongoing interest in the topic and in the proposed methodological approach. It also suggests that the framework may be applicable beyond the original case study.

Currently working on the next version with further refinements and extensions.

#Hydrogeochemistry #PHREEQC #GeochemicalModeling #ReproducibleResearch #EnvironmentalGeochemistry #rstats #qgis #SvystunovaGully #mining

🧪 Davis vs Pitzer: stress-testing a geochemical model

In hydrogeochemical modeling, there is a common concern:
are “simpler” activity models reliable for saline waters, or do they break down beyond their formal limits?

In my study, I primarily use minteq.v4.dat (Davies equation) in PHREEQC. Formally, Davies is recommended up to ionic strength ~0.5–0.7, while Pitzer theory is considered the gold standard for brines.

Instead of assuming, I tested it.

What I did
- Recalculated >1000 real water samples
- Compared saturation indices (SI) computed with:
- Davies-based MINTEQ.V4
- Pitzer formulation (pitzer.dat)

What I found
For calcite, results are nearly identical:
- points lie close to the 1:1 line
- median SI differs by <0.1
- no statistically significant difference (Mann–Whitney p = 0.22)

This is not an argument against Pitzer.
It is evidence that Davies-based models can remain robust for certain systems when their

#Hydrogeochemistry #PHREEQC #GeochemicalModeling #ReproducibleResearch #SvystunovaGully

The “Hydrochemical Gap”: why manual saturation indices don’t work
Many Kryvbas studies still estimate calcite saturation as if high-salinity waters behaved like distilled water.
This plot shows the opposite.

🔵 Blue line: textbook Ksp for calcite.
🔴 Red points: actual ion activity product (IAP) for real samples (PHREEQC).

Key facts:

1️⃣ At 30–40 g/L salinity, real IAP is 1.5–1.6 log units lower — meaning free Ca²⁺ activity is ~38× lower than concentration-based formulas predict.

2️⃣ The dip at 2–5 g/L marks the mixing zone, where ionic strength and ion-pairing change non-linearly and break simple calculations.

3️⃣ Main reason:
• high ionic strength suppresses activity,
• Ca²⁺ forms complexes,
• multicomponent interactions are non-linear.

Result:
Manual SI calculations suggest “precipitation,” but real activity shows undersaturation and aggressive water.
Only thermodynamic modelling reveals the true behaviour.

#Hydrogeochemistry #Geochemistry #Mining #PHREEQC #RStats #SvystunovaGully #Kryvbas #SvystunovaGully

🧪 The “Oversaturation Illusion” in Kryvbas Mine Waters

While modeling Kryvbas water chemistry (R + PHREEQC), I found a fundamental issue in how saturation is often evaluated.

We usually calculate calcite equilibrium from ion concentrations — fine for fresh water.
But Kryvbas mine waters are brines, where ionic strength and complexation dominate.

📉 Results from ~1000 samples (minteq.v4):
- Once salinity exceeds ~3 g/L, Ca²⁺ activity drops sharply.
- At 15–20 g/L, calcium activity coefficient is ≈ 0.35.

Meaning: more than half of the “calcium concentration” is inert — a dead load that cannot form precipitates.

This explains why traditional methods predicted oversaturation where the water was actually aggressive and dissolving rocks.

Modeling: PHREEQC + minteq.v4 (US EPA), Davis equation.

#Hydrogeochemistry #WaterChemistry #PHREEQC #Geochemistry #Groundwater
#Mining #Tailings #IonActivity #Thermodynamics #Kryvbas #OpenScience #RStats #SvystunovaGully

#SvystunovaGully
888 downloads!
Looks like I’ve created something that people actually find interesting.

But here’s the real question: with a daily rate of 30–40 downloads... what are the odds of catching such a perfectly round number by accident? 🤣

(Maybe the Universe has a soft spot for hydrogeochemistry!) 😁

#OpenScience #Zenodo #Geochemistry #Hydrogeology #MineWater #DataScience #ResearchLife #ScienceHumor #Groundwater #EnvironmentalScience #Contamination #PHREEQC #RStats #LaTeX #QGIS #FOSS #WaterPollution

🎉 A small milestone for my hydrogeochemistry monograph about #SvystunovaGully

Today, my Zenodo record passed 1,500 downloads across both released versions — something I never expected when I began this project as a personal, curiosity-driven exploration.

It’s an independent study on groundwater–rock interaction, technogenic metasomatism, and carbonate–water equilibria, based largely on PHREEQC thermodynamic modelling and geospatial data.

I’m grateful to everyone who took an interest, skimmed, downloaded, or shared it.
Your attention gives this work a life I didn’t imagine it would ever have.

❗ And one more thing: in the monograph’s preamble I explicitly thank the developers of free and open-source software. Without their tools — R, PHREEQC, QGIS, LaTeX, Linux, JabRef and many others — this research would simply not have been possible.

#Hydrogeochemistry #Geochemistry #Groundwater #PHREEQC #FOSS #OpenScience #RStats #QGIS #Zenodo #EnvironmentalScience #Carbonates #Metasomatism #GeoData #WaterPollution

In my study of the highly mineralized mine-water storage impoundment in #SvystunovaGully , I used PHREEQC to quantify the equilibrium dissolution potential of calcite for every of >1000 groundwater sample collected over more than 10 years.

For each sample, I modeled how much calcite the water could dissolve if it encountered carbonate rocks along its flow path (SI = 0 at equilibrium). Each sample was treated as an independent thermodynamic system, and the resulting dissolution values were aggregated spatially using Voronoi polygons.

The map below shows the median Δmass of calcite (g/L) for each polygon.
Areas with more negative values represent water that remains capable of dissolving additional carbonate minerals — a long-term indicator of the water’s aggressiveness.

This approach highlights the zones where the aquifer is most vulnerable to carbonate dissolution around the mine-water pond.

#Hydrogeology #Geochemistry #PHREEQC #Groundwater #MineWater #GIS #RStats #Hydrochemistry #OpenScience #Ukraine

In my research on the impoundment for highly mineralized mine water, I identified two distinct zones of carbonate mineral dissolution within the underlying carbonate aquifer.

The inner zone is caused by the primary aggressiveness of the mine water toward carbonates.

The outer zone appears after the leaking water has almost reached equilibrium with carbonate minerals — and its behaviour closely resembles freshwater–seawater mixing dissolution.

On the figure, outer zone (III) is marked by the sharp drop in the calcite saturation index.

The crucial point is this:
👉 The outer dissolution zone (III) creates enhanced pathways for further migration of mine water through the aquifer.
❗ It behaves like a positive-feedback system, progressively increasing its own permeability.

All details, and modelling results are documented in the latest draft of my monograph (v0.75):
🔗 https://zenodo.org/records/16741148

#Geochemistry #Rstats #MixingCorrosion #PHREEQC #SvystunovaGully #Contamimation #Groundwater #Thermodynamics #MineWater

📘 A small milestone for my independent research project

I’m honestly a bit shocked.
When I published the first version of my hydrogeochemical monograph on May 27 (v0.72), and then the updated version on August 4 (v0.75), I expected almost no reactions at all.

Today, the combined statistics on Zenodo show:
1,400 downloads
almost 3,000 views

For a niche, highly technical, openly accessible monograph created by one person — this is far beyond anything I imagined.

Thank you to everyone who found the work useful enough to download, save, or read it.
Your interest is the only reason this project keeps growing.

#Geochemistry #Hydrogeology #MineWater #PHREEQC #EnvironmentalGeochemistry #Groundwater #Metasomatism #RStats #QGIS #OpenScience #IndependentResearch #SvystunovaGully #KryvyiRih #WaterPollution #Contamination #Mining #Zenodo

(Full Zenodo record — in the ALT of the second image, for anyone interested.)

Behind the scenes of “beautiful scientific graphics”

If you think that clean, elegant visuals in scientific reports are produced in a couple of clicks — I’m here to disappoint you. 🙂

Here’s one of many failed attempts to visualize results based on thermodynamic modeling of geochemical processes.

Turning raw multidimensional data into something that a human reader can intuitively grasp is a separate challenge — with dozens of input parameters and only a few truly useful outcomes.

Good science is not only about computation, but also about communication.

#Geochemistry #DataViz #Rstats #Clustering #EnvironmentalModelling #ScienceCommunication #PHREEQC #WaterPollution #SvystunovaGully #Contamimation #Groundwater #Infographics #PCA #Thermodynamics

Parsing PHREEQC output into a clean, structured dataset opens the door to far more than just looking at a few components.
Once everything is tidy, you can explore the whole chemical system at once — speciation, mineral phases, spatial trends, and more.

Here are a few examples from my zinc modeling workflow in R:
📌 1 — Speciation distribution
A violin/boxplot view of modeled zinc species across all samples.
📌 2 — Saturation index statistics
Summary table showing how different mineral phases behave across the aquifer.
📌 3 — Spatial trends
Activity of ZnCl⁺ decreasing with distance from the impoundment.

This is only a small part of what becomes possible once PHREEQC results are organized properly.
A tidy dataset = full access to statistics, machine learning, and geospatial analysis.

Curious how others approach PHREEQC post-processing — do you parse everything, or focus only on a few components?

#PHREEQC #Geochemistry #Rstats #Groundwater #EnvironmentalModelling #OpenScience #SvystunovaGully

💧 In my geochemical research, I often go beyond pure PHREEQC and use the RedModRphree package in R.
It’s a powerful bridge between thermodynamic modeling and data analysis — allowing Pourbaix (Eh–pH) diagrams to be computed for complex, multicomponent systems with a focus on a specific element.

Here are examples of modeled speciation diagrams for vanadium, lead, and zinc, based on the same high mineralized water sample composition.
They clearly illustrate how each element behaves under changing redox and pH conditions — from soluble oxyanions to sparingly soluble solid phases.

#Geochemistry #Rstats #PHREEQC #DataScience #EnvironmentalChemistry #Hydrogeology #Redox #PourbaixDiagram #Thermodynamics #OpenScience #RedModRphree

🧪 Mine water + fresh water ≠ simple average

When high mineralized mine waters mix with fresh groundwater, mineral reactions don’t behave linearly.

The graphs below show how saturation indices for selected minerals respond to dilution:
🔹 Copper sulfates (Antlerite, Brochantite, Langite) display clear peaks and drops.
🔹 Gypsum remains undersaturated — yet falls sharply at high dilution.

Each “dip” or “window” reflects a short-lived equilibrium where new mineral phases may form or dissolve — revealing the hidden dynamics of technogenic metasomatism in aquifer systems.

📖 Draft monograph (v0.75) available on Zenodo:
🔗 https://zenodo.org/records/16741148

#Geochemistry #Hydrogeology #MineWater #PHREEQC #EnvironmentalGeochemistry #Groundwater #Metasomatism #RStats #QGIS #OpenScience #IndependentResearch #SvystunovaGully #KryvyiRih #WaterPollution #Contamination #Mining

🎨 When visualization becomes part of thinking

In geochemical modeling, diagrams are not decoration — they’re analytical tools.

Every chart and map I create goes through many iterations: filtering, reshaping, and transforming multi-dimensional geochemical data until patterns start to reveal themselves.

Good visualization doesn’t just show results — it creates insight.
It helps trace hidden geochemical transitions, test hypotheses, and understand how contamination evolves through space and chemistry.

🧩 For me, plotting and modeling are inseparable parts of one process — the science of seeing.

📘 All supporting data and modeling results are included in the draft monograph:
🔗 zenodo.org/records/16741148

🧪 Modeling & visualization: PHREEQC + R + QGIS

#Geochemistry #GeochemicalModeling #DataVisualization #ScientificGraphics #EnvironmentalScience #GroundwaterQuality #PHREEQC #RStats #QGIS #GeoscienceCommunication #IndependentResearch #SvystunovaGully

💧 Aggressive groundwater and the long memory of contamination

Even after more than a decade of monitoring, the groundwater in this carbonate aquifer remains undersaturated with respect to calcite — consistently showing negative SI values across nearly all observation wells.

This means that the system is still chemically aggressive toward limestone, slowly dissolving the host rock.
The impoundment, operating since 1976, continues to influence the aquifer — with the geometry of possible subsurface voids still uncertain to this day.

📘 All supporting data and modeling results are included in the draft monograph:
🔗 zenodo.org/records/16741148

🧪 Data & visualization: PHREEQC + R + QGIS

#Hydrogeochemistry #Geochemistry #MineWater #Groundwater #PHREEQC #EnvironmentalGeoscience #IndependentResearch #OpenScience #QGIS #RStats #Aquifer #Zenodo #SvystunovaGully #GroundwaterContamination #FOSS

🔍 Exploring groundwater chemistry — from ions to equilibrium

This ternary diagram shows how groundwater samples affected by mine water vary in anion composition. Each point represents one sample, colored by its calcite saturation index (SI) from PHREEQC calculations.

Such early-stage exploration helps reveal subtle geochemical trends — where equilibrium breaks down, reactions intensify, and contamination fronts begin to form.

🧪 Data exploration: PHREEQC + R

#Geochemistry #Hydrogeology #MineWater #Groundwater #PHREEQC #DataExploration #EnvironmentalGeochemistry #GeochemicalModeling #DataVisualization #RStats #OpenScience #SvystunovaGully