Tools to estimate the carbon footprint of dairy farms.
Implements methods based on IDF (International Dairy Federation)
and IPCC guidelines for greenhouse gas accounting.
Overview
cowfootR provides a comprehensive toolkit for calculating carbon footprints of dairy farms following IPCC guidelines. The package includes:
- Individual emission calculations from enteric fermentation, manure, soil, energy, and inputs
- Batch processing capabilities for multiple farms
- Intensity metrics per liter of milk and per hectare
- System boundary flexibility (farm gate, cradle-to-farm gate, etc.)
- Excel integration for data input and report generation
Installation
You can install the development version of cowfootR from GitHub:
# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("juanmarcosmoreno-arch/cowfootR")Quick Start
Single Farm Analysis
This is a basic example of how to calculate the carbon footprint of a single farm:
library(cowfootR)
# 1. Define system boundaries
boundaries <- set_system_boundaries("farm_gate")
# 2. Calculate emissions by source
enteric <- calc_emissions_enteric(
n_animals = 100,
cattle_category = "dairy_cows",
boundaries = boundaries
)
manure <- calc_emissions_manure(
n_cows = 100,
boundaries = boundaries
)
soil <- calc_emissions_soil(
n_fertilizer_synthetic = 1500,
n_excreta_pasture = 5000,
area_ha = 120,
boundaries = boundaries
)
energy <- calc_emissions_energy(
diesel_l = 2000,
electricity_kwh = 5000,
boundaries = boundaries
)
inputs <- calc_emissions_inputs(
conc_kg = 1000,
fert_n_kg = 500,
boundaries = boundaries
)
# 3. Calculate total emissions
total_emissions <- calc_total_emissions(enteric, manure, soil, energy, inputs)
print(paste("Total emissions:", round(total_emissions$total_co2eq, 1), "kg CO2eq"))
# 4. Calculate intensity metrics
milk_intensity <- calc_intensity_litre(
total_emissions = total_emissions,
milk_litres = 750000,
fat = 4.0,
protein = 3.3
)
print(paste("Milk intensity:", round(milk_intensity$intensity_co2eq_per_kg_fpcm, 2),
"kg CO2eq/kg FPCM"))
area_intensity <- calc_intensity_area(
total_emissions = total_emissions,
area_total_ha = 120
)
print(paste("Area intensity:", round(area_intensity$intensity_per_total_ha, 1),
"kg CO2eq/ha"))Batch Processing Workflow
For analyzing multiple farms, use the Excel template approach:
# 1. Download and fill template
cf_download_template("my_farms_template.xlsx")
# Open the file, fill with your farm data, and save
# 2. Read data and process multiple farms
farm_data <- readxl::read_excel("my_farms_data.xlsx")
results <- calc_batch(
data = farm_data,
tier = 2,
benchmark_region = "uruguay" # optional
)
# 3. View processing summary
print(results$summary)
# 4. Export comprehensive results to Excel
export_hdc_report(results, "carbon_footprint_results.xlsx")Working with Data Frames
You can also work directly with data frames:
# Example farm data
farm_data <- data.frame(
FarmID = c("Farm_A", "Farm_B", "Farm_C"),
Year = c("2023", "2023", "2023"),
Milk_litres = c(500000, 750000, 300000),
Fat_percent = c(4.0, 3.8, 4.2),
Protein_percent = c(3.3, 3.2, 3.4),
Cows_milking = c(100, 150, 60),
Area_total_ha = c(200, 300, 120),
N_fertilizer_kg = c(2000, 3000, 1200),
Diesel_litres = c(4000, 6000, 2400),
Electricity_kWh = c(10000, 15000, 6000)
)
# Process all farms
results <- calc_batch(farm_data, tier = 2)
# Check results for each farm
for (i in seq_along(results$farm_results)) {
farm <- results$farm_results[[i]]
if (farm$success) {
cat("Farm", farm$farm_id, ":", round(farm$emissions_total, 1), "kg CO2eq\n")
} else {
cat("Farm", farm$farm_id, ": ERROR -", farm$error, "\n")
}
}Key Features
Emission Sources Covered
- Enteric fermentation: CH₄ from ruminal fermentation
- Manure management: CH₄ and N₂O from manure systems
- Soil emissions: N₂O from fertilizer application and excreta
- Energy consumption: CO₂ from diesel, electricity, and other fuels
- External inputs: CO₂eq from feed, fertilizers, and materials
System Boundaries
# Farm gate (direct on-farm emissions only)
boundaries_fg <- set_system_boundaries("farm_gate")
# Cradle to farm gate (includes upstream production)
boundaries_cfg <- set_system_boundaries("cradle_to_farm_gate")
# Use in calculations
results <- calc_batch(farm_data, boundaries = boundaries_cfg)Data Requirements
Required Columns
-
FarmID: Unique farm identifier -
Year: Year of data collection
-
Milk_litres: Annual milk production (liters) -
Cows_milking: Number of milking cows -
Area_total_ha: Total farm area (hectares)
Optional Columns
- Animal data:
Cows_dry,Heifers_total,Calves_total,Bulls_total - Production:
Fat_percent,Protein_percent,Milk_yield_kg_cow_year - Feed:
MS_intake_cows_milking_kg_day,Ym_percent,Concentrate_feed_kg - Fertilizer:
N_fertilizer_kg,N_fertilizer_organic_kg - Energy:
Diesel_litres,Electricity_kWh,Petrol_litres - Land use:
Area_productive_ha,Pasture_permanent_ha
Use cf_download_template() to get the complete column structure.
Error Handling
The package includes robust error handling for batch processing:
# Process with error handling
results <- calc_batch(farm_data)
# Check for processing errors
if (results$summary$n_farms_with_errors > 0) {
error_farms <- results$farm_results[
sapply(results$farm_results, function(x) !x$success)
]
for (farm in error_farms) {
cat("Farm", farm$farm_id, "failed:", farm$error, "\n")
}
}Contributing
This package is under active development. Please report issues or suggest improvements on GitHub.
