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Prompt Examples

Overview

This page provides complete, real-world examples of EcoSemantic prompts for various industries and use cases. Each example shows the full conversation flow from initial question to final results.

Energy Sector Examples

Example 1: Renewable Energy Comparison

Scenario: Compare carbon footprint of different renewable energy sources

Complete Conversation:

You:

I need to compare the carbon footprint of solar, wind, and hydroelectric 
power for a 1 MWh energy output. Use IPCC 2013 GWP100 method and 
ecoinvent-3.11-cutoff database.

AI:

I'll help you compare these renewable energy sources. Let me search for 
each technology and calculate their carbon footprints.

[Searches for solar PV activities]
Found: electricity production, photovoltaic, 3kWp slanted-roof, multi-Si | GLO

[Searches for wind activities]
Found: electricity production, wind, >3MW turbine, onshore | GLO

[Searches for hydro activities]  
Found: electricity production, hydro, run-of-river | GLO

Now calculating carbon footprints for 1000 kWh each...

[Performs 3 calculations]

✅ Results Complete

Renewable Energy Comparison (1 MWh = 1000 kWh)
Method: IPCC 2013 GWP100
Database: ecoinvent-3.11-cutoff

Technology          | Carbon Footprint | Ranking
--------------------|------------------|--------
Wind (onshore)      | 11.2 kg CO2-eq   | 1 (Best)
Hydroelectric (RoR) | 24.3 kg CO2-eq   | 2
Solar PV (rooftop)  | 45.6 kg CO2-eq   | 3

Key Insights:
- Wind power has the lowest carbon footprint
- All renewable sources are significantly better than fossil fuels
- Solar PV impact mainly from panel manufacturing
- Hydro impact varies greatly by reservoir type

For context: Coal electricity would produce ~950 kg CO2-eq for the same 1 MWh.

You:

What if I want to use ground-mounted solar instead of rooftop? 
Does that change the results?

AI:

Good question! Let me search for ground-mounted solar installations.

[Searches for ground-mounted solar]
Found: electricity production, photovoltaic, 570kWp open ground, multi-Si | GLO

[Calculates for 1000 kWh]

✅ Updated Comparison

Technology               | Carbon Footprint | Change from Rooftop
------------------------|------------------|--------------------
Solar PV (ground, 570kW)| 38.2 kg CO2-eq   | -16% lower
Solar PV (rooftop, 3kW) | 45.6 kg CO2-eq   | Baseline

Ground-mounted systems have lower impacts per kWh because:
1. Better orientation optimization
2. Economy of scale (570kW vs 3kW)
3. More efficient operation and maintenance
4. Lower installation impacts per kW

Example 2: Grid Mix Analysis

Scenario: Analyze carbon intensity of electricity by country

You:

Compare the carbon footprint of electricity from the US, Germany, 
and France grids for 100 kWh

AI:

I'll search for the national electricity grid mixes and calculate 
their carbon footprints.

[Searches and calculates for each country]

✅ National Grid Comparison (100 kWh)

Country    | Carbon Footprint | Primary Sources
-----------|------------------|------------------
France     | 8.5 kg CO2-eq    | Nuclear (70%), Hydro, Wind
Germany    | 45.2 kg CO2-eq   | Coal, Gas, Renewables
USA        | 56.8 kg CO2-eq   | Coal, Gas, Nuclear

Analysis:
- France has the lowest due to nuclear dominance
- Germany's coal phase-out is in progress
- US mix heavily depends on state/region

Regional variations within countries can be significant.
Would you like to see specific states or regions?

Manufacturing Sector Examples

Example 3: Material Selection Study

Scenario: Choose between primary and recycled aluminum

You:

I'm designing a product and need to choose between primary aluminum 
and recycled aluminum. Calculate the environmental impacts of producing 
1000 kg of each, including climate change, acidification, and resource depletion.

AI:

I'll search for both types of aluminum production and calculate 
multiple impact categories for comparison.

[Searches for aluminum activities]
Primary: aluminum production, primary, liquid | GLO
Recycled: aluminum production, secondary, from old scrap | GLO

[Calculates 6 impacts: 3 categories × 2 materials]

✅ Aluminum Comparison (1000 kg)
Database: ecoinvent-3.11-cutoff

Impact Category          | Primary Al | Recycled Al | Reduction
------------------------|------------|-------------|----------
Climate Change (IPCC)   | 9,240 kg   | 890 kg      | -90.4%
Acidification (CML)     | 42.5 kg    | 4.2 kg      | -90.1%
Resource Depletion      | 8,450 MJ   | 1,240 MJ    | -85.3%

Units: kg CO2-eq, kg SO2-eq, MJ surplus

Key Findings:
-eq per m³
- Difference: 445 kg CO2-eq savings per m³ with timber

For a typical building using 100 m³ of structural material:
- Concrete: 35 tonnes CO2-eq
- Timber: -9.5 tonnes CO2-eq (net carbon storage!)
- Savings: 44.5 tonnes CO2-eq

Recommendation: Use timber where structurally appropriate. 
Massive carbon benefit + renewable resource.

Example 9: Insulation Material Comparison

Scenario: Select insulation for energy efficiency retrofit

You:

I need to insulate 100 m² of wall space. Compare fiberglass, 
mineral wool, and cellulose insulation for environmental impact

AI:

I'll calculate the embodied carbon for each insulation type.
Assuming 15cm thickness for equivalent thermal performance.

[Searches and calculates]

✅ Insulation Material Comparison (100 m², 15cm thick)

Material              | Volume  | Carbon Footprint | Thermal R-value | Cost
----------------------|---------|------------------|-----------------|------
Fiberglass batts      | 15 m³   | 285 kg CO2-eq    | R-15            | $600
Mineral wool (rockwool)| 15 m³  | 340 kg CO2-eq    | R-15            | $750
Cellulose (recycled)  | 15 m³   | 95 kg CO2-eq     | R-15            | $450

Long-term Analysis (20-year lifecycle):

Material    | Embodied | Heating Savings | Net Impact | ROI
------------|----------|-----------------|------------|--------
Fiberglass  | 285 kg   | -8,500 kg       | -8,215 kg  | 3.2 years
Mineral wool| 340 kg   | -8,500 kg       | -8,160 kg  | 3.8 years
Cellulose   | 95 kg    | -8,500 kg       | -8,405 kg  | 2.4 years

Key Insights:
1. All insulation types have HUGE net carbon savings (30-89× payback)
2. Operational savings dwarf embodied carbon
3. Cellulose has lowest embodied carbon (recycled content)
4. Focus on proper installation > material selection

Recommendation: Cellulose for best environmental + economic performance,
but ANY insulation is dramatically better than no insulation.

Annual heating energy savings: ~2,400 kWh/year
Annual CO₂ savings: ~425 kg CO2-eq/year (with gas heating)

Electronics & Technology Examples

Example 10: Device Lifecycle Analysis

Scenario: Evaluate laptop replacement decision

You:

Should I replace my 4-year-old laptop or keep using it? 
Calculate the carbon footprint of manufacturing a new laptop 
vs the electricity use of keeping the old one for 2 more years

AI:

Interesting question! Let me calculate both scenarios.

[Searches for laptop manufacturing and electricity use]

✅ Laptop Replacement Decision Analysis

Option 1: Keep Old Laptop (2 more years)
- Manufacturing impact: 0 kg (already incurred)
- Electricity: 50W × 8 hours/day × 730 days = 292 kWh/year × 2 years
- Grid electricity impact: 292 kWh × 2 years = 584 kWh total
- Carbon footprint: 331 kg CO2-eq

Option 2: Buy New Laptop
- Manufacturing new laptop: 340 kg CO2-eq
- Electricity (more efficient): 30W × 8 hours/day × 730 days = 175 kWh/year × 2
- Carbon footprint: 340 + 199 = 539 kg CO2-eq
- Old laptop disposal: +15 kg CO2-eq
- Total: 554 kg CO2-eq

Comparison Over 2 Years:
- Keep old: 331 kg CO2-eq
- Buy new: 554 kg CO2-eq
- Difference: +223 kg CO2-eq (67% higher)

Recommendation: Keep using your current laptop from an 
environmental perspective. The manufacturing impact is significant 
and not offset by efficiency gains in just 2 years.

Break-even point: ~3.5 years (when efficiency savings equal manufacturing impact)

Other considerations:
- Performance needs: If current laptop is too slow, quality of life matters
- Repair option: Often cheaper and greener than replacement
- Lifespan extension: Every extra year amortizes manufacturing impact

Environmental best practice: Use devices as long as functionally possible.

Example 11: Data Center Location

Scenario: Choose data center location for cloud service

You:

Compare the carbon footprint of running a server (consuming 1000 kWh/month) 
in data centers located in: US (grid mix), Iceland (geothermal), 
and China (coal-heavy)

AI:

I'll calculate monthly and annual emissions for each location.

[Searches for electricity by region and calculates]

✅ Data Center Location Comparison (1000 kWh/month)

Location        | Monthly Impact | Annual Impact | Primary Energy Source
----------------|----------------|---------------|----------------------
Iceland         | 2.8 kg CO2-eq  | 34 kg CO2-eq  | Geothermal (100%)
US (average)    | 57 kg CO2-eq   | 684 kg CO2-eq | Mixed (gas, coal, nuclear)
China (average) | 92 kg CO2-eq   | 1,104 kg CO2-eq| Coal-dominant

Annual Comparison:
- Iceland: 34 kg CO2-eq (baseline)
- US: 684 kg CO2-eq (+1,912%)
- China: 1,104 kg CO2-eq (+3,147%)

For 100 servers:
- Iceland: 3.4 tonnes CO2-eq/year
- US: 68.4 tonnes CO2-eq/year
- China: 110.4 tonnes CO2-eq/year

Recommendations by Priority:

Environmental Priority: Iceland
- Near-zero emissions electricity
- Natural cooling (climate advantage)
- 97% lower carbon footprint than China

Economic Priority: Depends on scale
- Iceland: Higher upfront costs, lower operating
- US: Moderate across the board
- China: Lower costs but reputational risk

Hybrid Strategy:
- Critical workloads: Iceland (premium green hosting)
- Standard workloads: US (balance)
- Consider: Google/AWS regions with renewable energy commitments

For a company with sustainability goals, Iceland or renewable-powered 
regions in US/EU offer dramatic carbon reductions.

Chemical & Pharmaceutical Examples

Example 12: Solvent Selection

Scenario: Choose environmentally preferable solvent

You:

Compare the environmental impact of 100 kg of: 
ethanol, acetone, and dichloromethane as industrial solvents

AI:

I'll calculate multiple impact categories for these common solvents.

[Searches and calculates]

✅ Industrial Solvent Comparison (100 kg)

Solvent          | Climate | Human Toxicity | Ecotoxicity | Ozone Depletion
-----------------|---------|----------------|-------------|----------------
Ethanol          | 185 kg  | 2.4 CTUh       | 12 CTUe     | 0
Acetone          | 245 kg  | 8.7 CTUh       | 45 CTUe     | 0  
Dichloromethane  | 320 kg  | 156 CTUh       | 892 CTUe    | 2.3 × 10⁻⁶

Units: kg CO2-eq, CTUh (human), CTUe (ecosystem), kg CFC-11-eq

Safety & Environmental Profile:

Ethanol:
✅ Bio-based option available
✅ Low toxicity
✅ Biodegradable
⚠️  Flammable

Acetone:
✅ Low toxicity relative to other solvents
✅ Biodegradable
⚠️  Highly flammable
⚠️  Moderate environmental impact

Dichloromethane:
❌ High human toxicity (65× worse than ethanol)
❌ High ecotoxicity (74× worse than ethanol)
❌ Ozone depletion potential
❌ Suspected carcinogen
❌ Persistent in environment

Recommendation Hierarchy:
1. Ethanol: Best overall environmental profile
2. Acetone: Acceptable compromise if ethanol doesn't work
3. Dichloromethane: Avoid unless absolutely necessary; 
   use with strict controls and disposal

Green Chemistry Principles:
- Prefer bio-based solvents (ethanol from biomass)
- Design for degradation
- Minimize toxicity
- Consider solvent recovery/recycling systems

If dichloromethane is currently used, switching to ethanol 
could reduce toxicity impacts by 98% and eliminate ozone depletion.

Waste Management Examples

Example 13: Waste Treatment Comparison

Scenario: Choose municipal waste management strategy

You:

Compare the environmental impact of treating 1000 kg of mixed 
municipal waste through: landfill, incineration with energy recovery, 
and recycling (assuming 60% recyclable content)

AI:

I'll calculate impacts for each waste management option.

[Searches and calculates for each scenario]

✅ Waste Management Comparison (1000 kg municipal waste)

Method                  | Climate Impact | Energy Recovery | Land Use
------------------------|----------------|-----------------|----------
Landfill                | +450 kg CO2-eq | None            | 0.8 m³
Incineration + Energy   | -95 kg CO2-eq  | 1,850 kWh       | Minimal
Recycling (60%)         | -285 kg CO2-eq | -              | Minimal

Wait - negative emissions? Here's the breakdown:

Incineration with Energy Recovery:
+ Combustion emissions: +720 kg CO2-eq
- Avoided electricity production: -815 kg CO2-eq (replacing grid mix)
= Net: -95 kg CO2-eq (carbon benefit!)

Recycling System (600 kg recycled, 400 kg incineration):
+ Collection & sorting: +45 kg CO2-eq
+ Processing 400 kg residual: -38 kg CO2-eq (with energy recovery)
- Avoided virgin material production: -292 kg CO2-eq
= Net: -285 kg CO2-eq (best option!)

Waste Hierarchy Performance:
1. Recycling: -285 kg CO2-eq (best)
2. Incineration with energy: -95 kg CO2-eq (good)
3. Landfill: +450 kg CO2-eq (worst)

Additional Considerations:

Landfill Issues:
- Methane emissions (25× more potent than CO₂)
- Leachate contamination risk
- Long-term land use
- No resource recovery

Incineration Benefits:
- Energy recovery offsets fossil fuels
- Volume reduction (90%)
- Eliminates biological activity
- But: Air emissions need controls

Recycling Benefits:
- Avoids virgin material production
- Conserves resources
- Creates jobs
- But: Requires sorting infrastructure

Recommended Strategy (Integrated Waste Management):
1. Prevent/Reduce: Target 20% reduction
2. Recycle: 60% of remaining
3. Energy recovery: 35% of remaining  
4. Landfill: <5% (only non-recyclable, non-combustible)

For a city of 100,000 producing 50,000 tonnes/year:
- Current (50% landfill): +11,250 tonnes CO2-eq
- Optimized strategy: -7,125 tonnes CO2-eq
- Net benefit: 18,375 tonnes CO2-eq/year saved

Advanced Multi-Tool Examples

Example 14: Supply Chain Optimization

Scenario: Optimize product supply chain

You:

I manufacture bicycles in the US. My steel comes from China (shipped), 
and I'm considering switching to US steel (trucked). Calculate the total 
carbon footprint difference including: steel production, transportation, 
and assembly. Each bicycle uses 15 kg of steel.

AI:

I'll analyze both supply chain scenarios comprehensively.

Scenario Analysis: 15 kg steel per bicycle

[Performs multiple calculations]

✅ Supply Chain Comparison (per bicycle)

Component          | China Steel | US Steel  | Difference
-------------------|-------------|-----------|------------
Steel production   | 138 kg      | 142 kg    | +4 kg
Transportation     | 24 kg       | 8 kg      | -16 kg
Assembly           | 5 kg        | 5 kg      | 0 kg
**Total per bike** | **167 kg**  | **155 kg**| **-12 kg**

Annual Impact (10,000 bicycles):
- China route: 1,670 tonnes CO2-eq
- US route: 1,550 tonnes CO2-eq  
- Savings: 120 tonnes CO2-eq/year (-7.2%)

Detailed Breakdown:

China Steel Route:
1. Steel production (China): 138 kg CO2-eq
   - More coal-intensive electricity
   - But: newer, efficient facilities
2. Ocean freight (8,000 km): 18 kg CO2-eq
3. Truck delivery to plant (200 km): 6 kg CO2-eq

US Steel Route:
1. Steel production (US): 142 kg CO2-eq
   - Mix of old and new facilities
   - Cleaner electricity mix
2. Truck delivery (1,500 km): 8 kg CO2-eq

Additional Considerations:

Economic Analysis:
- China steel: $0.65/kg delivered = $9.75/bike
- US steel: $0.85/kg delivered = $12.75/bike
- Premium: $3.00/bike for US steel

Carbon Price Equivalence:
- At $25/tonne CO2: Saves $0.30/bike in carbon costs
- At $50/tonne CO2: Saves $0.60/bike
- At $100/tonne CO2: Saves $1.20/bike

Risk Factors:
- Supply chain resilience: US domestic supply more secure
- Lead time: US steel 2 weeks vs China 8 weeks
- Quality consistency: Both generally equivalent
- Trade policy: Tariff risks with China

Recommendation:
Switch to US steel for:
- 7% carbon footprint reduction
- Supply chain risk mitigation
- "Made with US steel" marketing value
- Faster inventory cycles

The carbon savings may not fully offset cost premium now,
but increasing carbon regulations favor domestic sourcing.

Example 15: Product Life Cycle Assessment

Scenario: Complete product LCA

You:

Conduct a full lifecycle assessment for a laptop computer including:
manufacturing, use phase (5 years, 4 hours/day), and end-of-life. 
Compare scenarios with and without recycling.

AI:

I'll perform a comprehensive lifecycle assessment across all phases.

[Performs multiple calculations across lifecycle stages]

✅ Complete Laptop Lifecycle Assessment (5 years)

=== MANUFACTURING PHASE ===

Component Manufacturing:
- Display (LCD): 85 kg CO2-eq
- Processor & electronics: 120 kg CO2-eq
- Battery: 45 kg CO2-eq
- Chassis & housing: 55 kg CO2-eq
- Other components: 35 kg CO2-eq
Subtotal: 340 kg CO2-eq

=== USE PHASE (5 years) ===

Electricity Consumption:
- Power: 45W average
- Usage: 4 hours/day × 365 days × 5 years = 7,300 hours
- Energy: 328.5 kWh total over 5 years
- Grid mix impact: 186 kg CO2-eq

=== END-OF-LIFE PHASE ===

Scenario A: Recycling
- Collection & transport: 3 kg CO2-eq
- Dismantling & sorting: 5 kg CO2-eq
- Material recovery: 8 kg CO2-eq
- Avoided virgin materials: -45 kg CO2-eq
Net: -29 kg CO2-eq (benefit!)

Scenario B: Landfill
- Collection & transport: 3 kg CO2-eq
- Landfilling: 12 kg CO2-eq
- No material recovery: 0 kg
Net: +15 kg CO2-eq (burden)

=== TOTAL LIFECYCLE IMPACT ===

Phase          | With Recycling | With Landfill | Difference
---------------|----------------|---------------|------------
Manufacturing  | 340 kg         | 340 kg        | 0
Use            | 186 kg         | 186 kg        | 0
End-of-life    | -29 kg         | +15 kg        | +44 kg
**Total**      | **497 kg**     | **541 kg**    | **+44 kg**

Key Insights:

1. Manufacturing Dominance: 68% of total impact
   - Design for longevity is critical
   - Material selection matters

2. Use Phase: 37% of impact (with recycling)
   - Energy efficiency important
   - Grid mix dependency

3. End-of-Life: -6% to +3%
   - Recycling provides net benefit
   - Recovers valuable materials

Lifetime Distribution:
- Years 1-5: ~100 kg CO2-eq/year
- Extended to 7 years: ~71 kg CO2-eq/year (-29%)
- Extended to 10 years: ~50 kg CO2-eq/year (-50%)

**Lifespan Extension Impact:**
Every additional year reduces annual impact by ~14%

Recommendations for Lower Impact:

1. Product Design:
   - Modular for repairs (extend life +40%)
   - Recyclable materials
   - Energy-efficient components

2. User Behavior:
   - Use as long as functionally possible
   - Enable power-saving modes
   - Consider renewable electricity

3. End-of-Life:
   - Always recycle electronics
   - Use certified e-waste recyclers
   - Recover valuable materials

Circular Economy Potential:
- Current: 497 kg CO2-eq over 5 years
- Optimal (10 years + recycling + renewables): 312 kg CO2-eq
- Improvement potential: -37%

Comparison to Annual Activities:
497 kg CO2-eq equivalent to:
- Driving 2,100 km in average car
- 875 kWh of US grid electricity
- 3.8 transatlantic flights (per passenger)

Custom Project Example

Example 16: Building a Custom LCA Model

Scenario: Model a novel technology not in Ecoinvent

You:

I need to create a custom LCA model for a new hydrogen fuel cell 
system. Help me set up the project structure.

AI:

I'll help you create a custom project for your hydrogen fuel cell system.

[Creates project]

✅ Project Created

Project: Hydrogen Fuel Cell System LCA
Database: ecoinvent-3.11-cutoff
Description: Custom LCA model for novel hydrogen fuel cell technology

Now let's build the project structure. I recommend creating these activities:

1. Hydrogen production
2. Fuel cell stack manufacturing  
3. Balance of plant (BoP) components
4. System assembly
5. Operation (electricity generation)
6. End-of-life treatment

Shall we start by creating the first activity?

You:

Yes, let's start with hydrogen production. We use electrolysis 
powered by solar PV.

AI:

[Validates units and creates activity]

✅ Activity Created

Activity: Hydrogen production via solar-powered electrolysis
Code: h2_production_solar
Unit: kilogram
Location: US

Now let's add exchanges. We need:

INPUTS (what it consumes):
1. Electricity from solar PV - how many kWh per kg H2?
2. Water - how many kg per kg H2?
3. Electrolyzer use - infrastructure

OUTPUTS:
1. Hydrogen (reference product) - 1 kg
2. Oxygen (co-product) - if utilized
3. Direct emissions - if any

What are your specific process parameters?

You:

The electrolyzer requires 50 kWh of electricity and 9 kg of water 
to produce 1 kg of hydrogen.

AI:

Perfect! Let me create the exchanges.

[Searches for solar PV electricity]
[Searches for water supply]
[Creates exchanges]

✅ Exchanges Created for h2_production_solar

Reference Product (OUTPUT):
- Hydrogen, gaseous: 1.0 kg

Inputs from Ecoinvent:
- Electricity, solar PV, GLO: -50 kWh
- Water, deionised: -9 kg

The activity is now ready for calculations! 

Next steps:
1. Create fuel cell stack manufacturing activity
2. Link activities together  
3. Add biosphere flows (if any direct emissions)
4. Run custom calculation

Would you like to continue building the model?

This example shows how to build complex custom projects step-by-step.

Next Steps

These examples demonstrate the range of analyses possible with EcoSemantic:

  • Simple queries: Single calculations
  • Comparisons: Multiple alternatives
  • Supply chains: Connected activities
  • Full LCAs: Complete lifecycle assessment
  • Custom models: Novel technologies

Ready for advanced techniques? Continue exploring the documentation for more capabilities.


Need help with your specific use case? Check the Tools Reference for detailed documentation.