Get started with cowfootR

In cowfootR: Dairy Farm Carbon Footprint Assessment

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Get started with cowfootR

This vignette provides a practical, end-to-end introduction to cowfootR. It is intended for new users who want to understand the core workflow of the package and obtain a first carbon footprint estimate for a dairy farm.

The focus is on: - understanding the workflow - knowing which functions to call and in what order - seeing actual outputs produced by the package

More detailed explanations of parameters, methodological choices, and advanced use cases are covered in the other vignettes.

What does cowfootR do?

cowfootR estimates greenhouse gas (GHG) emissions from dairy farms following IPCC (2019) and IDF (2022) guidelines.

The package: - calculates emissions by source - aggregates them into total farm emissions - computes intensity metrics per unit of milk or land - supports single-farm and batch (multi-farm) analysis

The standard workflow is: 1- Define system boundaries 2- Calculate emissions by source 3- Aggregate total emissions 4- Calculate intensity metrics

This vignette walks through these steps using a minimal example.

Installation and loading the package

install.packages("cowfootR")

Or install the development version:

devtools::install_github("juanmarcosmoreno-arch/cowfootR")

Load the package:

library(cowfootR)

Step 1: Define system boundaries

System boundaries determine which emission sources are included in the assessment.

The most common option is "farm_gate", which includes on-farm emissions only.

boundaries <- set_system_boundaries("farm_gate")
boundaries

Other options (e.g. "cradle_to_farm_gate") are described in the Workflow overview vignette.

Units and reporting basis

Unless otherwise stated, cowfootR reports: - Absolute emissions as annual farm totals in kg CO₂eq per year (kg CO₂eq yr⁻¹), within the selected system boundaries. - Milk intensity as kg CO₂eq per kg FPCM (FPCM computed following IDF). - Area intensity as kg CO₂eq per hectare (kg CO₂eq ha⁻¹ yr⁻¹).

Step 2: Calculate emissions by source

Each emission source is calculated using a dedicated function. All functions return structured objects with emissions expressed in kg CO₂eq.All functions return structured objects with emissions expressed as kg CO₂eq yr⁻¹ (annual totals), unless stated otherwise.

Enteric fermentation

Enteric fermentation accounts for methane (CH₄) produced during ruminal digestion.

enteric <- calc_emissions_enteric(
  n_animals = 100,
  cattle_category = "dairy_cows",
  boundaries = boundaries
)
enteric

Manure management

This includes CH₄ and N₂O emissions from manure handling systems.

manure <- calc_emissions_manure(
  n_cows = 100,
  boundaries = boundaries
)
manure

Soil emissions

Soil emissions mainly originate from nitrogen inputs such as fertilizers and excreta deposited during grazing.

soil <- calc_emissions_soil(
  n_fertilizer_synthetic = 1500,
  n_excreta_pasture = 5000,
  area_ha = 120,
  boundaries = boundaries
)
soil

Energy use

Energy-related emissions come from fuel combustion and electricity consumption.

energy <- calc_emissions_energy(
  diesel_l = 2000,
  electricity_kwh = 5000,
  boundaries = boundaries
)
energy

Purchased inputs

This category includes emissions embodied in feeds, fertilizers, and materials.

inputs <- calc_emissions_inputs(
  conc_kg = 1000,
  fert_n_kg = 500,
  boundaries = boundaries
)
inputs

Step 3: Aggregate total emissions

All emission sources are combined using calc_total_emissions().

total_emissions <- calc_total_emissions(
  enteric,
  manure,
  soil,
  energy,
  inputs
)
total_emissions

Step 4: Calculate intensity metrics

Intensity metrics relate total emissions to production or land use.

Milk intensity

Emissions per unit of milk are expressed as kg CO₂eq per kg of fat- and protein-corrected milk (FPCM).

milk_intensity <- calc_intensity_litre(
  total_emissions = total_emissions,
  milk_litres = 750000,
  fat = 4.0,
  protein = 3.3
)
milk_intensity

Area intensity

Emissions per hectare are useful for land-based comparisons.

area_intensity <- calc_intensity_area(
  total_emissions = total_emissions,
  area_total_ha = 120
)
area_intensity

Interpreting results

In most dairy systems: - Enteric fermentation is the largest emission source - Inputs and soils are often the second-largest contributors - Energy use typically represents a smaller share

Results should always be interpreted considering: - data quality - system boundaries - production system characteristics

What’s next?

This vignette covered the minimum workflow needed to use cowfootR.

Next steps: - See Introduction to Dairy Life Cycle Assessment for conceptual background - See Single Farm Analysis for a more detailed example - See Complete Parameter Reference Guide for full parameter documentation - See Workflow overview for batch processing and reporting

Summary

-   cowfootR follows a modular, step-by-step workflow
-   Each emission source is calculated independently
-   Results can be expressed as total emissions or intensities
-   This vignette provides a starting point; advanced topics are covered elsewhere

cowfootR documentation built on Jan. 13, 2026, 5:07 p.m.