#phreeqc — Public Fediverse posts

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

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

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:
🔗 https://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:
🔗 https://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

💧 Beyond Diffusion: Groundwater as a Rock–Fluid System

Contaminant plumes in groundwater are often seen as passive — just diffusion and advection through porous media.
But what if we treat them as active geochemical fronts instead?

In my recent modeling work, I describe contamination not as a mechanical process, but as a metasomatic transformation — a reaction zone between aggressive mine waters and carbonate aquifers.

Each sector of the aquifer develops its own thermodynamic balance and mineral stability field.
The plume itself becomes a chemical engine — reshaping host rocks, opening new pathways, and shifting the entire water–rock equilibrium.

📘 Draft monograph: https://zenodo.org/records/16741148

🧪 Data and modeling: PHREEQC + R + QGIS

#Geochemistry #Hydrogeology #MineWater #WaterPollution #PHREEQC #Metasomatism #Groundwater #EnvironmentalGeochemistry #IndependentResearch #OpenScience #Aquifer #RStats #FOSS #SvystunovaGully

🧠 Full-Stack Science — from raw data to the final PDF

While preparing the new version of my monograph, I realized something funny:
if I listed all the software I used, the “Used software” section would look more like a Linux manual than a scientific appendix.

Because, honestly — everything mattered.
From grep, awk, and apt, to PHREEQC, R, QGIS, and finally LaTeX.

Every single stage — data cleaning, modeling, visualization, mapping, typesetting — I did entirely on my own.
No outsourcing. No “sending for refinement.”
Just a full-stack, open-source workflow — from the first script to the final monograph PDF.

📘 Draft available on Zenodo:
🔗 https://zenodo.org/records/16741148

#OpenScience #IndependentResearch #Geochemistry #Hydrogeology #DataScience #PHREEQC #RStats #QGIS #Linux #LaTeX #EnvironmentalData #GeospatialAnalysis #FullStackResearch #ScientificWorkflow #Zenodo #SvystunovaGully

🌎 Mapping dominant chemical speciation in a polluted carbonate aquifer

In my recent modeling work, I modeled the dominant forms of element speciation in groundwater within a carbonate system.

Beyond pure geochemical curiosity, this approach provides a practical lens:
– it reveals where mineral precipitation is most probable,
– and helps identify zones where remediation can be most effective.

💻 Combining thermodynamic modeling (PHREEQC) with spatial analysis in R and QGIS turns subsurface processes into actionable insights for water-quality management and contamination mitigation.

Two figures below show the modeled distribution of cadmium species across the aquifer and their evolution with dilution

📘 Full details in the draft monograph:
🔗 https://zenodo.org/records/16741148

#Geochemistry #Hydrogeology #PHREEQC #GroundwaterContamination #MineWater #EnvironmentalGeochemistry #Metasomatism #Aquifer #RStats #QGIS #GeospatialAnalysis #OpenScience #IndependentResearch #WaterQuality #Remediation #SvystunovaGully

🔬 Metasomatic Zonation as a Model of Groundwater Contamination

One of the key theoretical bases in my research is the classical metasomatic zonation model (Korzhinskii, 1960s).

I interpret the contamination halo formed by mine waters not as passive dispersion — but as an active metasomatic system, where aggressive fluids drive alteration and re-precipitation reactions within the carbonate aquifer.

Highly mineralized mine waters create a complex interaction front.
Thermodynamic modeling (based on well-monitoring data) allows identification of several geochemical zones partly analogous to Korzhinskii’s metasomatic sequence.

📊 The image shows my preliminary zoning concept.

📘 All calculations and hypotheses are detailed in the draft monograph:
🔗 https://zenodo.org/records/16741148

#Geochemistry #Hydrogeology #PHREEQC #Metasomatism #MineWater #GroundwaterContamination #GeochemicalModeling #IndependentResearch #OpenScience #RStats #QGIS #EnvironmentalGeochemistry #Thermodynamics #Aquifer #Zenodo #SvystunovaGully

💧 Exploring how contaminated mine waters behave in a carbonate aquifer — through the lens of metasomatic zoning and thermodynamic #geochemical modeling.

Using #PHREEQC simulations, data analysis in #RStats, and geospatial visualization in #QGIS, I’m studying how mine drainage transforms groundwater systems and mineral equilibria over time.

📘 The draft version (v0.75) of my monograph on this topic has already been downloaded 550+ times on #Zenodo — showing how relevant this issue has become for both science and environmental policy.

It’s independent research that links theory, modeling, and practical hydrogeochemical assessment — focused on the long-term impact of mine waters in the Kryvyi Rih region.

🔗 Read or download:
https://zenodo.org/records/16741148

#Geochemistry #Groundwater #MineWater #EnvironmentalGeochemistry #Hydrogeology #WaterPollution #Metasomatism #OpenScience #IndependentResearch #EnvironmentalDataScience #Aquifer #HeavyMetals #Sustainability #SvystunovaGully