Hadi Farahani, PhD

Independent environmental data consultant

Environmental monitoring data you can defend.

I help environmental, compliance and operations teams draw reliable conclusions from measurement data: QA/QC, detection limits, measurement uncertainty, compliance analysis and risk maps. Analytics, GIS and reporting built on analytical chemistry rigor, delivered as fixed-scope, reproducible projects.

Taking 1–2 projects at a time · any industry · remote

Send me your problem View services

Try it: is this result compliant?

Decision explorer: measured value, expanded uncertainty and a limit A measured value with an uncertainty interval is plotted against a limit of 100 mg/L. Sliders change the value and the uncertainty, and the verdict updates. Limit 100 mg/L 406080100120140160 Concentration (mg/L)

Inconclusive: the interval straddles the limit. A decision rule is needed.

SYNTHETIC Probability the true value is below the limit: 84%. Simplified: normal distribution, no prior information. Decision rules follow JCGM 106 / ILAC-G8.

Services

Fixed scope, written deliverables, reproducible code. Pricing is quoted per project after a short conversation.

Which fits you?

Pick one and I’ll highlight the best starting point.

Scoping sprint

A few days, fixed fee. A data-readiness check and a written plan with scope, timeline and price for the full project.

2–4 page memo · fee credited to the project

Data quality & uncertainty audit

Review of a monitoring dataset: QA/QC, non-detects, detection-limit changes, and a defensible uncertainty statement.

Typically 1–2 weeks

Compliance-ready analysis & report

Trend, exceedance and decision-rule analysis delivered as a reproducible report with code.

Typically 2–4 weeks

Geospatial risk map

QGIS and Python mapping of exposure, sensitivity and risk, with documented sources and assumptions.

Typically 2–3 weeks

Case studies & planned methods

Each study uses synthetic data with known truth, so methods can be scored against the right answer. A study is marked Published only when its data, code and report are in the repository.

Flagship Case Studies (OGE)

  • OGE-01: Produced water analytics
  • OGE-02: Gas flaring performance
  • OGE-03: Methane emission monitoring
  • OGE-04: Drilling waste characterization
  • OGE-05: Oil spill risk mapping
  • OGE-06: Groundwater quality trends flagship
  • OGE-07: Industrial air quality
  • OGE-08: Climate hazard exposure
  • OGE-09: Oily sludge & contaminated soil
  • OGE-10: Microplastics & emerging pollutants

EnvIntel Method Catalogue (25 planned)

A Data quality & metrology

  • A01: Industrial Environmental Data Quality Screening
  • A02: Measurement Uncertainty and Decision Reliability Assessment
  • A03: Automated Laboratory Quality Control Intelligence
  • A04: Environmental Monitoring Network Data Reliability Assessment
  • A05: Environmental Data Fitness-for-Purpose Assessment

B Industrial operations

  • B01: Industrial Environmental Performance Intelligence
  • B02: Automated Environmental Monitoring and Reporting
  • B03: Industrial Wastewater Quality Trend and Compliance Screening
  • B04: Multi-Source Environmental Data Integration
  • B05: Industrial Emissions Variability and Operational Drivers

C Geospatial & Earth observation

  • C01: Satellite-Based Environmental Change Detection
  • C02: Industrial Environmental Proximity Screening
  • C03: GIS-Based Environmental Monitoring Network Optimization
  • C04: Watershed Environmental Pressure Mapping
  • C05: Remote Sensing for Industrial Land Disturbance Monitoring

D Risk & forecasting

  • D01: Environmental Risk Prioritization Under Uncertainty
  • D02: Environmental Monitoring Anomaly and Early-Warning Intelligence
  • D03: Environmental Indicator Forecasting and Scenario Analysis
  • D04: Environmental Sampling Strategy Optimization
  • D05: Environmental Decision Support Using Evidence Confidence

E Compliance & governance

  • E01: Environmental Compliance Evidence Readiness Assessment
  • E02: Environmental Reporting Data Lineage and Auditability
  • E03: Multi-Site Environmental KPI Harmonization
  • E04: Environmental Regulatory Threshold Screening Framework
  • E05: Environmental Intelligence Executive Reporting

How I work

Validate

Establish reliability first. Missing values, anomalies, drift, reporting limits and provenance are checked before any analysis.

Quantify uncertainty

Say how sure you are. Measurement uncertainty and censored-data methods, following the GUM (JCGM 100/101).

Decide

Turn evidence into action. Explicit decision rules (JCGM 106, ILAC-G8) and findings written for the people who must act.

Confidentiality: client data stays under NDA. I do not put client data into external AI tools without written consent, and every AI-assisted step is checked by me.

Background

PhD in analytical chemistry, with experience in research and industrial environmental projects. Peer-reviewed work is listed on Google Scholar. I also share a short insight every weekday on LinkedIn.

Publications LinkedIn GitHub
Python (pandas, SciPy, statsmodels)QGIS & rasterioSQLiteQuartoPowerShellExcelGitGUM / JCGM 100, 101, 106

Tell me about your data problem.

A short description is enough. I reply within two working days with questions or a proposed next step.

Email me