kishorkukreja/awesome-supply-chain/carbon-footprint-tracking

CO2e Emissions = Activity Data × Emission Factor
 
Where:
  Activity Data = Quantity of activity (kWh, liters, kg, tkm, etc.)
  Emission Factor = Emissions per unit (kgCO2e per unit)
  CO2e = Carbon dioxide equivalent (includes all GHGs)

import pandas as pd
import numpy as np
class CarbonFootprintCalculator:
    """Comprehensive carbon footprint calculator"""
    def __init__(self):
        self.emission_factors = self._load_emission_factors()
        self.gwp_factors = {
            'CO2': 1,
            'CH4': 25,      # Methane (100-year GWP)
            'N2O': 298,     # Nitrous oxide
            'HFCs': 1430,   # Hydrofluorocarbons (avg)
            'PFCs': 7390,   # Perfluorocarbons (avg)
            'SF6': 22800    # Sulfur hexafluoride
        }
    def _load_emission_factors(self):
        """Load standard emission factors database"""
        # Based on EPA, DEFRA, and other sources
        return {
            # Energy (kgCO2e per kWh)
            'electricity_us_grid': 0.417,
            'electricity_eu_grid': 0.295,
            'electricity_renewable': 0.000,
            'natural_gas': 0.202,  # per kWh
            # Fuels (kgCO2e per liter)
            'diesel': 2.68,
            'gasoline': 2.31,
            'jet_fuel': 2.50,
            # Transportation (kgCO2e per tonne-km)
            'truck_full_truckload': 0.062,
            'truck_less_than_truckload': 0.091,
            'rail': 0.022,
            'ocean_shipping': 0.008,
            'air_freight': 0.602,
            # Materials (kgCO2e per kg)
            'steel': 1.85,
            'aluminum': 8.24,
            'plastic_pet': 2.15,
            'cardboard': 0.95,
            'glass': 0.85,
            'concrete': 0.11,
            # Manufacturing (kgCO2e per unit - examples)
            'electronics_assembly': 50,
            'textile_production': 15,
            'food_processing': 2.5
        }
    def calculate_scope1_facilities(self, fuel_consumption):
        """
        Calculate Scope 1 emissions from facility fuel use
        fuel_consumption: dict with fuel types and quantities
        Example: {'diesel_liters': 10000, 'natural_gas_kwh': 50000}
        """
        emissions = 0
        breakdown = []
        # Diesel/gasoline combustion
        if 'diesel_liters' in fuel_consumption:
            diesel_co2 = fuel_consumption['diesel_liters'] * self.emission_factors['diesel']
            emissions += diesel_co2
            breakdown.append({
                'source': 'Diesel combustion',
                'activity': fuel_consumption['diesel_liters'],
                'unit': 'liters',
                'emissions_kgco2e': diesel_co2
            })
        if 'gasoline_liters' in fuel_consumption:
            gas_co2 = fuel_consumption['gasoline_liters'] * self.emission_factors['gasoline']
            emissions += gas_co2
            breakdown.append({
                'source': 'Gasoline combustion',
                'activity': fuel_consumption['gasoline_liters'],
                'unit': 'liters',
                'emissions_kgco2e': gas_co2
            })
        # Natural gas (converted to kWh)
        if 'natural_gas_kwh' in fuel_consumption:
            ng_co2 = fuel_consumption['natural_gas_kwh'] * self.emission_factors['natural_gas']
            emissions += ng_co2
            breakdown.append({
                'source': 'Natural gas',
                'activity': fuel_consumption['natural_gas_kwh'],
                'unit': 'kWh',
                'emissions_kgco2e': ng_co2
            })
        return {
            'scope': 'Scope 1',
            'total_emissions_kgco2e': round(emissions, 2),
            'total_emissions_tco2e': round(emissions / 1000, 2),
            'breakdown': breakdown
        }
    def calculate_scope1_fleet(self, vehicle_data):
        """
        Calculate Scope 1 emissions from company fleet
        vehicle_data: list of dicts with vehicle info
        Example: [{'type': 'diesel', 'distance_km': 50000, 'fuel_efficiency_l_per_100km': 8}]
        """
        emissions = 0
        breakdown = []
        for vehicle in vehicle_data:
            distance = vehicle['distance_km']
            fuel_efficiency = vehicle['fuel_efficiency_l_per_100km']
            fuel_type = vehicle['type']
            # Calculate fuel consumed
            fuel_consumed = (distance / 100) * fuel_efficiency
            # Get emission factor
            if fuel_type in ['diesel']:
                ef = self.emission_factors['diesel']
            elif fuel_type in ['gasoline', 'petrol']:
                ef = self.emission_factors['gasoline']
            else:
                ef = 2.5  # default
            vehicle_emissions = fuel_consumed * ef
            emissions += vehicle_emissions
            breakdown.append({
                'vehicle_id': vehicle.get('id', 'Unknown'),
                'fuel_type': fuel_type,
                'distance_km': distance,
                'fuel_consumed_liters': round(fuel_consumed, 2),
                'emissions_kgco2e': round(vehicle_emissions, 2)
            })
        return {
            'scope': 'Scope 1 - Fleet',
            'total_emissions_kgco2e': round(emissions, 2),
            'total_emissions_tco2e': round(emissions / 1000, 2),
            'breakdown': breakdown
        }
    def calculate_scope2_electricity(self, electricity_consumption, region='us', renewable_pct=0):
        """
        Calculate Scope 2 emissions from electricity
        electricity_consumption: kWh consumed
        region: 'us', 'eu', or custom
        renewable_pct: percentage of renewable energy (0-1)
        """
        # Select emission factor based on region
        if region == 'us':
            ef = self.emission_factors['electricity_us_grid']
        elif region == 'eu':
            ef = self.emission_factors['electricity_eu_grid']
        else:
            ef = 0.40  # global average
        # Adjust for renewable percentage
        grid_electricity = electricity_consumption * (1 - renewable_pct)
        renewable_electricity = electricity_consumption * renewable_pct
        emissions_grid = grid_electricity * ef
        emissions_renewable = renewable_electricity * self.emission_factors['electricity_renewable']
        total_emissions = emissions_grid + emissions_renewable
        return {
            'scope': 'Scope 2',
            'total_electricity_kwh': electricity_consumption,
            'grid_electricity_kwh': grid_electricity,
            'renewable_electricity_kwh': renewable_electricity,
            'emission_factor_kgco2e_per_kwh': ef,
            'total_emissions_kgco2e': round(total_emissions, 2),
            'total_emissions_tco2e': round(total_emissions / 1000, 2)
        }
    def calculate_scope3_transportation(self, shipments):
        """
        Calculate Scope 3 emissions from transportation
        shipments: list of dicts
        Example: [{'mode': 'truck_ftl', 'distance_km': 500, 'weight_tonnes': 20}]
        """
        emissions = 0
        breakdown = []
        for shipment in shipments:
            mode = shipment['mode']
            distance = shipment['distance_km']
            weight = shipment['weight_tonnes']
            # Calculate tonne-kilometers
            tkm = distance * weight
            # Get emission factor
            mode_map = {
                'truck_ftl': 'truck_full_truckload',
                'truck_ltl': 'truck_less_than_truckload',
                'rail': 'rail',
                'ocean': 'ocean_shipping',
                'air': 'air_freight'
            }
            ef_key = mode_map.get(mode, 'truck_full_truckload')
            ef = self.emission_factors[ef_key]
            shipment_emissions = tkm * ef
            emissions += shipment_emissions
            breakdown.append({
                'shipment_id': shipment.get('id', 'Unknown'),
                'mode': mode,
                'distance_km': distance,
                'weight_tonnes': weight,
                'tonne_km': tkm,
                'emission_factor': ef,
                'emissions_kgco2e': round(shipment_emissions, 2)
            })
        return {
            'scope': 'Scope 3 - Transportation',
            'total_emissions_kgco2e': round(emissions, 2),
            'total_emissions_tco2e': round(emissions / 1000, 2),
            'breakdown': breakdown
        }
    def calculate_scope3_materials(self, materials_purchased):
        """
        Calculate Scope 3 emissions from purchased materials
        materials_purchased: dict with material types and quantities (kg)
        Example: {'steel': 10000, 'plastic_pet': 5000}
        """
        emissions = 0
        breakdown = []
        for material, quantity_kg in materials_purchased.items():
            if material in self.emission_factors:
                ef = self.emission_factors[material]
                material_emissions = quantity_kg * ef
                emissions += material_emissions
                breakdown.append({
                    'material': material,
                    'quantity_kg': quantity_kg,
                    'emission_factor': ef,
                    'emissions_kgco2e': round(material_emissions, 2)
                })