Skip to contents

SECFC

License: MITWebsite Website

SECFC (Survey-Embedded Carbon Footprint Calculator) is a transparent, open-source R package designed to assist researchers in environmental psychology with survey-based carbon footprint estimation.

It provides a modular structure that makes it easy to calculate and analyze emissions from various domains such as consumption, food, housing, transport, and pets.

SECFC is particularly suitable for academic studies requiring reproducibility, transparency, and process-level emissions output.

Shiny APP

Key Features

  • Twelve core functions to estimate individual-level carbon footprint based on survey data.
  • ️ Transparent processing: Choose between total emissions or detailed calculation steps.
  • Designed with survey data structure in mind.
  • Ideal for environmental psychology, behavioral science, and carbon impact studies.

️ Functions Overview

SECFC contains twelve main functions, divided into two groups:

➤ Simple Output Functions

These functions calculate total emissions by domain and append one new column to the dataset: - calc_cons_emissions(): consumption-related emissions - calc_food_emissions(): food-related emissions - calc_housing_emissions(): housing-related emissions - calc_pet_emissions(): pet-related emissions - calc_transport_emissions(): transport-related emissions - calc_total_emissions(): total emissions across all domains

Each function: - Takes a data frame as input - Appends a new column with calculated emissions - Returns the updated data frame and prints results

➤ Process-Level Functions

These functions provide detailed emissions breakdowns, appending multiple columns with intermediate steps: - calc_cons_emissions_process() - calc_food_emissions_process() - calc_housing_emissions_process() - calc_pet_emissions_process() - calc_transport_emissions_process() - calc_total_emissions_process()

Each function: - Adds multiple columns explaining the step-by-step calculation - Enhances transparency for research and teaching purposes - Also returns and prints the final emission result

Example Usage

Here’s a simple example of how to use the SECFC package in practice:

# Step 1: Load the package
library(SECFC)

# Step 2: Load your dataset
# Example: use "questionnaire_sample.rds"
df <- readRDS("questionnaire_sample.rds")

# Step 3: Calculate carbon emissions by domain
cons <- calc_cons_emissions(df)       # Adds consumption emissions
food <- calc_food_emissions(df)       # Adds food emissions
housing <- calc_housing_emissions(df)    # Adds housing emissions
pet <- calc_pet_emissions(df)        # Adds pet emissions
transport <- calc_transport_emissions(df)  # Adds transport emissions

# Step 4: Calculate total carbon footprint
total <- calc_total_emissions(df)

# Optional: Use process-level functions to view detailed steps
cons_process <- calc_cons_emissions_process(df)
food_process <- calc_food_emissions_process(df)
housing_process <- calc_housing_emissions_process(df)
pet_process <- calc_pet_emissions_process(df)
transport_process <- calc_transport_emissions_process(df)
total_process <- calc_total_emissions_process(df)

📫 Contact

For questions, bug reports, or suggestions, please reach out to:

Jianing Ding

Tongji University

Ka Leung Lam

Duke Kunshan University

Nathaniel Geiger

University of Michigan

Ziqian Xia

Stanford University

Jinliang Xie

Tsinghua University