Monitoring Environmental Quality Standards with Power BI

Category: Environmental Reporting & Dashboards
Tags: Power BI, EQS, water quality, dashboards, environmental compliance, data visualization

A Surface Water EQS System for Belgium

Evaluating Environmental Quality Standards (EQS) requires precise calculations, transparent logic, and clear communication.

Raw data alone is not sufficient — interpretation must be consistent, validated, and accessible.

For Brussels Environment, I developed a Power BI-based EQS monitoring system for surface water — a pioneering solution in Belgium.

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The Challenge

Surface water data:

• Comes from multiple monitoring sources
• Requires regulatory calculations (min, max, annual averages)
• Must detect inconsistencies automatically
• Needs to be understandable by scientists and policymakers

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The Solution

I designed a Power BI system that:

• Calculates EQS indicators automatically
• Evaluates compliance against regulatory thresholds
• Computes inflow/outflow percentages, BCR contributions, and BCR load
• Detects data inconsistencies across sources
• Consolidates all information into a unified data model

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Code Example: EQS Calculations in Python

python
import pandas as pd

data = {"concentration": [2.1, 1.8, 2.5, 2.0, 1.9]}
df = pd.DataFrame(data)

summary = {
    "minimum": df["concentration"].min(),
    "maximum": df["concentration"].max(),
    "annual_average": df["concentration"].mean()
}

summary