Industrial Pollution Source Identification

Groundwater contamination 50x safe limits near 15 industrial units. Students will identify responsible parties using chemical fingerprinting and build legal cases.

# Aplly.xyz Case Study Submission

## Title
Industrial Pollution Source Identification

## Type
Environmental Crime Investigation

## Difficulty
Intermediate

## Estimated Time
60 minutes

## Overview
Groundwater contamination 50x safe limits near 15 industrial units. Students will identify responsible parties using chemical fingerprinting and build legal cases.

## Case Details

Function Focus: Environmental Crime Investigation — manual reasoning, decomposition, and critical judgment (no spreadsheet or AI tool permitted in Phase 1)

Scenario:
You are the analyst at a fictional consultancy ("Praxis Advisors") tasked with answering: Industrial Pollution Source Identification. You have a clean, synthetic dataset described below. You must produce a defensible answer using structured reasoning — no tool-assisted shortcut on the first pass.

Dataset Structure:
- sample_id
- date_collected
- location
- water_body
- ph
- tds_mg_per_L
- heavy_metal_detected
- metal_concentration_ppm
- permissible_limit_ppm
- industrial_units_upstream
- discharge_point_identified
- violation_notice_issued
- legal_action
- remediation_done
- days_to_compliance

Tasks:
1. List the records and separate evidence types; classify each as primary/secondary/circumstantial by hand.
2. Identify the most probable source/location using spatial or attribute clustering and distance/direction reasoning.
3. Quantify the scale of impact (area, volume, cost) with back-of-envelope estimation and explicit assumptions.
4. Evaluate the strongest counter-hypothesis (natural vs. man-made, accidental vs. deliberate) and decide using the data.
5. After your manual reasoning, cross-check the numbers with a calculator/spreadsheet and note discrepancies.

Expected Output:
A one-page investigation memo: source hypothesis, evidence classification, impact quantification, counter-hypothesis ruling.

Evaluation Criteria:
Quality of source attribution reasoning, correct scale quantification, balanced hypothesis evaluation.

## Data Sources

| sample_id | date_collected | location | water_body | ph | tds_mg_per_L | heavy_metal_detected | metal_concentration_ppm | permissible_limit_ppm | industrial_units_upstream | discharge_point_identified | violation_notice_issued | legal_action | remediation_done | days_to_compliance |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 85 | Dropped | True | Inconclusive | Low | 25000 | Bangalore | Confirmed | PER-0157-001 | Rural | Urban | Under investigation | Detected | REM-0157-001 | Arrested |
| Positive | N/A | Under investigation | Kolkata | Under investigation | Medium | HEA-0157-002 | 3.5 | Unresolved | 85 | DIS-0157-002 | High | LEG-0157-002 | Closed | Detected |
| High | 25000 | 2026-04-01 | Filed | True | Chennai | Low | True | PER-0157-003 | 2026-04-15 | DIS-0157-003 | Pending | | REM-0157-003 | Secure |
| Resolved | Rural | Detected | 100000 | Delhi | 100000 | Chennai | 100000 | Inconclusive | Arrested | Pending | 85 | 2026-03-15 | At large | Active |
| Dropped | Unresolved | Delhi | Closed | 12.5 | True | True | Positive | Closed | Dropped | False | Compromised | Inconclusive | Negative | DAY-0157-005 |
| SAM-0157-006 | Dropped | LOC-0157-006 | | Positive | 1 | Secure | MET-0157-006 | PER-0157-006 | Dropped | DIS-0157-006 | 2026-04-01 | Pending | False | Bangalore |
| No | N/A | Closed | Pending | 2026-03-15 | 12.5 | False | Bangalore | 2026-04-15 | IND-0157-007 | No | Filed | Bangalore | Compromised | Compromised |
| Not detected | Unresolved | Resolved | 0 | Negative | TDS-0157-008 | 3.5 | 3.5 | Detected | Mumbai | Delhi | Detected | Filed | 1 | N/A |
| N/A | 100000 | | Closed | High | Yes | Rural | Yes | Delhi | 2026-04-01 | 85 | Delhi | Active | 0 | 2026-04-01 |
| Unresolved | Confirmed | Closed | Unresolved | Urban | Positive | Bangalore | Inconclusive | | Urban | No | Medium | Inconclusive | Compromised | Urban |


Full dataset: https://github.com/arora200/aplly_case_db/datasets/105-enviro-industrial-pollution (synthetic, 13 records)

## Solution Frameworks
Source identification & dispersion reasoning, impact assessment, satellite/remote-sensing triangulation, regulatory checklist

## Solver Guidance & Tutorials
_Solver guidance added by the pipeline (tutorial links) — see `solver_guidance` field._

## What You'll Learn
- Attribute a source from scattered evidence
- Quantify impact with estimation
- Argue against your own hypothesis

## Tags
Environmental Crime, Pollution, Chemical Fingerprinting, Geographic Analysis

## Registration Links
Register as Solver / Register as Evaluator