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许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.0
统计：⭐ 0 · 553 · 1 current installs · 1 all-time installs
⭐ 0
安装量（当前） 1
🛡 VirusTotal ：良性 · OpenClaw ：可疑
Package：datadrivenconstruction/lifecycle-carbon-calculator
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：可疑
OpenClaw 评估
The skill's description and code align with a lifecycle-carbon calculator, but the runtime instructions include runnable Python code (importing pandas and using EPD URLs) while the skill declares no required binaries/dependencies or install steps — a mismatch worth reviewing before installing.
目的
The name, description, and SKILL.md content consistently describe a lifecycle/embodied-carbon calculator for construction, with sample material datasets, benchmarks, and calculation logic. The requested capability matches the stated purpose.
说明范围
SKILL.md includes substantial Python implementation (classes, calculation methods, sample datasets) that imports pandas and references EPD URLs. The instructions are implementation-level rather than purely conceptual. The file does not explicitly tell the agent how/when to execute code, nor does it declare required runtime environment; running it would require Python and third‑party libraries and could lead to network requests (EPD URLs) if im…
安装机制
There is no install spec (lowest-risk form). However, the bundled code expects Python and pandas; the absence of declared dependencies or an install step is an incoherence — the skill assumes runtime capabilities that may not exist on the agent host.
证书
The skill declares no required environment variables, credentials, or config paths. The code shown does not request secrets or unrelated system credentials. This is proportionate to the stated purpose.
持久
always:false and no install hooks are present. The skill does not request persistent agent privileges or modify other skills. Autonomous invocation is allowed (platform default) but is not combined with other high-risk flags.
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Lifecycle Carbon Calculator」。简介：Calculate embodied carbon and lifecycle emissions for construction materials an…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/datadrivenconstruction/lifecycle-carbon-calculator/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
slug: "lifecycle-carbon-calculator"
display_name: "Lifecycle Carbon Calculator"
description: "Calculate embodied carbon and lifecycle emissions for construction materials and projects. Support sustainable design decisions with carbon data."
---
# Lifecycle Carbon Calculator for Construction
## Overview
Calculate embodied carbon (EC) and lifecycle carbon emissions for construction materials, assemblies, and projects. Support sustainable design decisions and carbon reduction targets.
## Business Case
Carbon calculation supports:
- **Regulatory Compliance**: Meet carbon reporting requirements
- **Green Certifications**: LEED, BREEAM, Living Building Challenge
- **Design Optimization**: Choose lower-carbon alternatives
- **Sustainability Goals**: Track progress toward net-zero
## Technical Implementation
```python
from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional
from enum import Enum
import pandas as pd
class LifecycleStage(Enum):
A1_A3 = "Product Stage (A1-A3)" # Raw materials, transport, manufacturing
A4 = "Transport to Site (A4)"
A5 = "Construction (A5)"
B1_B7 = "Use Stage (B1-B7)" # Maintenance, repair, replacement
C1_C4 = "End of Life (C1-C4)" # Demolition, transport, disposal
D = "Beyond Lifecycle (D)" # Reuse, recycling potential
@dataclass
class MaterialCarbon:
material_id: str
name: str
category: str
unit: str
carbon_a1_a3: float # kgCO2e per unit
carbon_a4: float
carbon_a5: float
carbon_b: float
carbon_c: float
carbon_d: float # Usually negative (credit)
density: float # kg/m³ if applicable
source: str
epd_url: str = ""
@dataclass
class AssemblyCarbon:
assembly_id: str
name: str
materials: List[Dict[str, Any]]
total_carbon: float
carbon_by_stage: Dict[str, float]
@dataclass
class ProjectCarbon:
project_id: str
name: str
gross_area: float
assemblies: List[AssemblyCarbon]
total_embodied_carbon: float
carbon_per_area: float
carbon_by_stage: Dict[str, float]
carbon_by_category: Dict[str, float]
benchmark_comparison: Dict[str, Any]
class LifecycleCarbonCalculator:
"""Calculate lifecycle carbon for construction."""
# Sample material carbon data (kgCO2e per unit)
DEFAULT_MATERIALS = {
'concrete_30mpa': MaterialCarbon(
material_id='C30', name='Concrete 30MPa', category='Concrete',
unit='m³', carbon_a1_a3=300, carbon_a4=5, carbon_a5=2,
carbon_b=0, carbon_c=10, carbon_d=-20, density=2400,
source='EPD Database'
),
'concrete_40mpa': MaterialCarbon(
material_id='C40', name='Concrete 40MPa', category='Concrete',
unit='m³', carbon_a1_a3=350, carbon_a4=5, carbon_a5=2,
carbon_b=0, carbon_c=10, carbon_d=-20, density=2400,
source='EPD Database'
),
'steel_rebar': MaterialCarbon(
material_id='REBAR', name='Steel Reinforcing Bar', category='Steel',
unit='kg', carbon_a1_a3=1.99, carbon_a4=0.05, carbon_a5=0.02,
carbon_b=0, carbon_c=0.05, carbon_d=-0.5, density=7850,
source='WorldSteel EPD'
),
'steel_structural': MaterialCarbon(
material_id='STEEL', name='Structural Steel', category='Steel',
unit='kg', carbon_a1_a3=1.55, carbon_a4=0.05, carbon_a5=0.03,
carbon_b=0, carbon_c=0.05, carbon_d=-0.8, density=7850,
source='AISC EPD'
),
'timber_clt': MaterialCarbon(
material_id='CLT', name='Cross-Laminated Timber', category='Timber',
unit='m³', carbon_a1_a3=-500, carbon_a4=10, carbon_a5=5,
carbon_b=0, carbon_c=50, carbon_d=-100, density=500,
source='AWC EPD'
),
'gypsum_board': MaterialCarbon(
material_id='GYP', name='Gypsum Board 12.5mm', category='Finishes',
unit='m²', carbon_a1_a3=3.2, carbon_a4=0.2, carbon_a5=0.1,
carbon_b=0, carbon_c=0.3, carbon_d=-0.1, density=10,
source='EUROGYPSUM EPD'
),
'insulation_mineral': MaterialCarbon(
material_id='INS_MW', name='Mineral Wool Insulation', category='Insulation',
unit='m³', carbon_a1_a3=45, carbon_a4=2, carbon_a5=1,
carbon_b=0, carbon_c=5, carbon_d=-2, density=40,
source='EURIMA EPD'
),
'glass_double': MaterialCarbon(
material_id='GLASS', name='Double Glazed Unit', category='Glazing',
unit='m²', carbon_a1_a3=35, carbon_a4=1, carbon_a5=0.5,
carbon_b=0, carbon_c=2, carbon_d=-5, density=25,
source='Glass for Europe EPD'
),
'aluminum': MaterialCarbon(
material_id='ALU', name='Aluminum Profile', category='Metals',
unit='kg', carbon_a1_a3=8.0, carbon_a4=0.1, carbon_a5=0.05,
carbon_b=0, carbon_c=0.1, carbon_d=-4.0, density=2700,
source='EAA EPD'
),
}
# Building type benchmarks (kgCO2e/m²)
BENCHMARKS = {
'Office': {'typical': 500, 'good': 350, 'best': 200},
'Residential': {'typical': 400, 'good': 280, 'best': 150},
'Retail': {'typical': 450, 'good': 320, 'best': 180},
'Industrial': {'typical': 350, 'good': 250, 'best': 150},
'Healthcare': {'typical': 700, 'good': 500, 'best': 350},
}
def __init__(self):
self.materials: Dict[str, MaterialCarbon] = dict(self.DEFAULT_MATERIALS)
self.assemblies: Dict[str, AssemblyCarbon] = {}
def add_material(self, material: MaterialCarbon):
"""Add or update a material."""
self.materials[material.material_id] = material
def calculate_material_carbon(self, material_id: str, quantity: float,
stages: List[LifecycleStage] = None) -> Dict:
"""Calculate carbon for a material quantity."""
if material_id not in self.materials:
raise ValueError(f"Unknown material: {material_id}")
material = self.materials[material_id]
if stages is None:
stages = list(LifecycleStage)
carbon_by_stage = {}
total = 0
for stage in stages:
if stage == LifecycleStage.A1_A3:
carbon = material.carbon_a1_a3 * quantity
elif stage == LifecycleStage.A4:
carbon = material.carbon_a4 * quantity
elif stage == LifecycleStage.A5:
carbon = material.carbon_a5 * quantity
elif stage == LifecycleStage.B1_B7:
carbon = material.carbon_b * quantity
elif stage == LifecycleStage.C1_C4:
carbon = material.carbon_c * quantity
elif stage == LifecycleStage.D:
carbon = material.carbon_d * quantity
else:
carbon = 0
carbon_by_stage[stage.value] = carbon
total += carbon
return {
'material_id': material_id,
'material_name': material.name,
'quantity': quantity,
'unit': material.unit,
'total_carbon': total,
'carbon_by_stage': carbon_by_stage
}
def create_assembly(self, assembly_id: str, name: str,
components: List[Dict]) -> AssemblyCarbon:
"""Create an assembly from multiple materials."""
total_carbon = 0
carbon_by_stage = {stage.value: 0 for stage in LifecycleStage}
material_details = []
for comp in components:
material_id = comp['material_id']
quantity = comp['quantity']
result = self.calculate_material_carbon(material_id, quantity)
total_carbon += result['total_carbon']
for stage, carbon in result['carbon_by_stage'].items():
carbon_by_stage[stage] += carbon
material_details.append({
'material': result['material_name'],
'quantity': quantity,
'unit': result['unit'],
'carbon': result['total_carbon']
})
assembly = AssemblyCarbon(
assembly_id=assembly_id,
name=name,
materials=material_details,
total_carbon=total_carbon,
carbon_by_stage=carbon_by_stage
)
self.assemblies[assembly_id] = assembly
return assembly
def calculate_project_carbon(self, project_id: str, project_name: str,
gross_area: float, building_type: str,
quantities: List[Dict]) -> ProjectCarbon:
"""Calculate total project carbon."""
assemblies = []
total_carbon = 0
carbon_by_stage = {stage.value: 0 for stage in LifecycleStage}
carbon_by_category = {}
for qty in quantities:
if 'assembly_id' in qty:
# Use predefined assembly
if qty['assembly_id'] in self.assemblies:
assembly = self.assemblies[qty['assembly_id']]
multiplier = qty.get('multiplier', 1)
scaled_carbon = assembly.total_carbon * multiplier
assemblies.append(AssemblyCarbon(
assembly_id=assembly.assembly_id,
name=assembly.name,
materials=assembly.materials,
total_carbon=scaled_carbon,
carbon_by_stage={k: v * multiplier for k, v in assembly.carbon_by_stage.items()}
))
total_carbon += scaled_carbon
elif 'material_id' in qty:
# Direct material
result = self.calculate_material_carbon(
qty['material_id'], qty['quantity']
)
total_carbon += result['total_carbon']
for stage, carbon in result['carbon_by_stage'].items():
carbon_by_stage[stage] += carbon
# Track by category
material = self.materials[qty['material_id']]
cat = material.category
carbon_by_category[cat] = carbon_by_category.get(cat, 0) + result['total_carbon']
# Calculate metrics
carbon_per_area = total_carbon / gross_area if gross_area > 0 else 0
# Compare to benchmarks
benchmark = self.BENCHMARKS.get(building_type, self.BENCHMARKS['Office'])
benchmark_comparison = {
'carbon_per_area': carbon_per_area,
'typical_benchmark': benchmark['typical'],
'good_benchmark': benchmark['good'],
'best_benchmark': benchmark['best'],
'vs_typical': (carbon_per_area / benchmark['typical'] - 1) * 100,
'rating': self._get_rating(carbon_per_area, benchmark)
}
return ProjectCarbon(
project_id=project_id,
name=project_name,
gross_area=gross_area,
assemblies=assemblies,
total_embodied_carbon=total_carbon,
carbon_per_area=carbon_per_area,
carbon_by_stage=carbon_by_stage,
carbon_by_category=carbon_by_category,
benchmark_comparison=benchmark_comparison
)
def _get_rating(self, carbon: float, benchmark: Dict) -> str:
"""Get rating based on benchmark comparison."""
if carbon <= benchmark['best']:
return 'A (Best Practice)'
elif carbon <= benchmark['good']:
return 'B (Good Practice)'
elif carbon <= benchmark['typical']:
return 'C (Typical)'
else:
return 'D (Above Typical)'
def compare_alternatives(self, base_project: ProjectCarbon,
alternatives: List[Dict]) -> pd.DataFrame:
"""Compare carbon of design alternatives."""
comparisons = [{
'Option': 'Base Design',
'Total Carbon (tCO2e)': base_project.total_embodied_carbon / 1000,
'Carbon/m² (kgCO2e)': base_project.carbon_per_area,
'vs Base': '0%',
'Rating': base_project.benchmark_comparison['rating']
}]
for alt in alternatives:
project = self.calculate_project_carbon(
alt['id'], alt['name'], alt['gross_area'],
alt.get('building_type', 'Office'), alt['quantities']
)
change = (project.total_embodied_carbon - base_project.total_embodied_carbon) / base_project.total_embodied_carbon * 100
comparisons.append({
'Option': alt['name'],
'Total Carbon (tCO2e)': project.total_embodied_carbon / 1000,
'Carbon/m² (kgCO2e)': project.carbon_per_area,
'vs Base': f'{change:+.1f}%',
'Rating': project.benchmark_comparison['rating']
})
return pd.DataFrame(comparisons)
def suggest_reductions(self, project: ProjectCarbon) -> List[Dict]:
"""Suggest carbon reduction opportunities."""
suggestions = []
# Analyze by category
if 'Concrete' in project.carbon_by_category:
concrete_carbon = project.carbon_by_category['Concrete']
if concrete_carbon > project.total_embodied_carbon * 0.3:
suggestions.append({
'category': 'Concrete',
'current_carbon': concrete_carbon,
'suggestion': 'Consider low-carbon concrete (GGBS/PFA replacement)',
'potential_reduction': '20-40%',
'impact': concrete_carbon * 0.3
})
if 'Steel' in project.carbon_by_category:
steel_carbon = project.carbon_by_category['Steel']
if steel_carbon > project.total_embodied_carbon * 0.2:
suggestions.append({
'category': 'Steel',
'current_carbon': steel_carbon,
'suggestion': 'Specify high recycled content steel',
'potential_reduction': '10-25%',
'impact': steel_carbon * 0.2
})
# Benchmark-based suggestions
if project.benchmark_comparison['vs_typical'] > 0:
suggestions.append({
'category': 'Overall',
'current_carbon': project.total_embodied_carbon,
'suggestion': 'Project exceeds typical benchmark - review high-carbon elements',
'potential_reduction': f"{abs(project.benchmark_comparison['vs_typical']):.0f}%",
'impact': project.total_embodied_carbon * abs(project.benchmark_comparison['vs_typical']) / 100
})
return sorted(suggestions, key=lambda x: -x['impact'])
def generate_report(self, project: ProjectCarbon) -> str:
"""Generate carbon assessment report."""
lines = ["# Embodied Carbon Assessment Report", ""]
lines.append(f"**Project:** {project.name}")
lines.append(f"**Gross Area:** {project.gross_area:,.0f} m²")
lines.append(f"**Assessment Date:** {pd.Timestamp.now().strftime('%Y-%m-%d')}")
lines.append("")
# Summary
lines.append("## Carbon Summary")
lines.append(f"- **Total Embodied Carbon:** {project.total_embodied_carbon/1000:,.0f} tCO2e")
lines.append(f"- **Carbon Intensity:** {project.carbon_per_area:,.0f} kgCO2e/m²")
lines.append(f"- **Rating:** {project.benchmark_comparison['rating']}")
lines.append("")
# By lifecycle stage
lines.append("## Carbon by Lifecycle Stage")
for stage, carbon in project.carbon_by_stage.items():
if carbon != 0:
pct = carbon / project.total_embodied_carbon * 100
lines.append(f"- {stage}: {carbon/1000:,.1f} tCO2e ({pct:.1f}%)")
lines.append("")
# By category
lines.append("## Carbon by Material Category")
for cat, carbon in sorted(project.carbon_by_category.items(), key=lambda x: -x[1]):
pct = carbon / project.total_embodied_carbon * 100
lines.append(f"- {cat}: {carbon/1000:,.1f} tCO2e ({pct:.1f}%)")
lines.append("")
# Benchmark
lines.append("## Benchmark Comparison")
bc = project.benchmark_comparison
lines.append(f"- Project: {bc['carbon_per_area']:.0f} kgCO2e/m²")
lines.append(f"- Typical: {bc['typical_benchmark']} kgCO2e/m²")
lines.append(f"- Good Practice: {bc['good_benchmark']} kgCO2e/m²")
lines.append(f"- Best Practice: {bc['best_benchmark']} kgCO2e/m²")
lines.append("")
# Reduction opportunities
suggestions = self.suggest_reductions(project)
if suggestions:
lines.append("## Reduction Opportunities")
for sug in suggestions[:5]:
lines.append(f"n### {sug['category']}")
lines.append(f"- **Suggestion:** {sug['suggestion']}")
lines.append(f"- **Potential Reduction:** {sug['potential_reduction']}")
lines.append(f"- **Impact:** {sug['impact']/1000:,.1f} tCO2e")
return "n".join(lines)
```
## Quick Start
```python
# Initialize calculator
calc = LifecycleCarbonCalculator()
# Calculate project carbon
project = calc.calculate_project_carbon(
project_id="PROJ-001",
project_name="Office Building",
gross_area=5000,
building_type="Office",
quantities=[
{'material_id': 'concrete_40mpa', 'quantity': 1500}, # m³
{'material_id': 'steel_rebar', 'quantity': 150000}, # kg
{'material_id': 'steel_structural', 'quantity': 200000},
{'material_id': 'gypsum_board', 'quantity': 8000}, # m²
{'material_id': 'glass_double', 'quantity': 1200}, # m²
]
)
print(f"Total Carbon: {project.total_embodied_carbon/1000:,.0f} tCO2e")
print(f"Carbon Intensity: {project.carbon_per_area:,.0f} kgCO2e/m²")
print(f"Rating: {project.benchmark_comparison['rating']}")
# Get reduction suggestions
suggestions = calc.suggest_reductions(project)
for sug in suggestions:
print(f"- {sug['category']}: {sug['suggestion']}")
# Generate full report
report = calc.generate_report(project)
print(report)
```
## Dependencies
```bash
pip install pandas
```