Urban Air Quality Design Lab
Your city's annual average PM2.5 is 35 µg/m³ — nearly 3× the EPA limit (12 µg/m³) and linked to tens of thousands of premature deaths per year. You are the city's chief engineer. Define your criteria and constraints, then build a solution portfolio and simulate 5 years of policy implementation.
📊 Baseline Conditions
- PM2.5: 35 µg/m³ | AQI: 99 (Moderate)
- WHO guideline: 5 µg/m³ | EPA standard: 12 µg/m³
- Sources: vehicle exhaust, industrial emissions, fuel combustion
- References: EPA AQI Technical Assistance Document (2024); WHO Global Air Quality Guidelines (2021).
Step 1 — Define Your Criteria & Constraints
Step 2 — Select Interventions
Budget used: $0M / $60M📈 Projected Equilibrium (if held for 5 years)
⚖️ Societal Trade-offs
Trade-offs reflect qualitative societal needs: economic disruption vs. public health equity.
Live Metrics
*Health Index (simplified): 100 = baseline risk; lower is better.
City Air Quality — Live View
PM2.5 Concentration Trend (green dashed = your target)
📋 Data Log
| Month | PM2.5 (µg/m³) | AQI | AQI Category | Health Index* | Budget Used |
|---|
*Health Index is a simplified instructional estimate proportional to PM2.5; not a clinical projection.
Understanding the Science & Engineering
🔬 Disciplinary Core Idea (ETS1.A)
PM2.5 (particulate matter ≤ 2.5 µm) penetrates deep into lung tissue, causing cardiovascular and respiratory disease. Urban sources include vehicle exhaust, industrial combustion, and fuel burning.
Engineering criteria must be quantified (e.g., AQI ≤ 50; budget ≤ $60M) and prioritized to reflect society's needs for clean air balanced against economic and political constraints.
🔗 Crosscutting Concept: Systems & Models
This simulation models a city's air quality system with defined boundaries (city air basin), components (emission sources), and interactions (interventions reducing source contributions).
Notice that interventions have multiplicative effects — combining an industrial filter with traffic controls reduces PM2.5 more than simply adding their percentages, because they target different emission sectors.
⚙️ Science & Engineering Practice
Asking Questions and Defining Problems: Before running the simulation, you specified a target AQI (criterion) and budget (constraint) — the same process engineers use to scope real-world air quality plans.
If your budget is $30M, can you meet an AQI target of 50? If not, what does this tell you about the relationship between constraints and feasible solutions? This is the core of HS-ETS1-1.