carbonr: An R Package for Estimating Carbon-Equivalent Emissions'
In carbonr: Calculate Carbon-Equivalent Emissions

Summary

The carbonr package provides a user-friendly, open-source tool for calculating carbon-equivalent emissions based on various sources, primarily the UK Government’s greenhouse gas reporting guidelines [@ukgov_greenhouse_gas_reporting_2023].

Designed for flexibility and ease of use, carbonr enables users from different sectors to estimate emissions from travel, construction, office environments, and, more recently, clinical settings, thereby aiding in informed decision-making for environmental impact reduction.

Statement of Need

Climate change and environmental sustainability are pressing global challenges that require sophisticated methods for assessing and mitigating carbon emissions across various sectors [@WHO2023]. Traditional tools for carbon accounting often lack flexibility, transparency, and/or accessibility. These limitations can hamper scientific advancements and the widespread adoption of best practices accounting for in carbon emissions.

To address these issues, carbonr offers an open-source solution that improves the reproducibility of carbon emission calculations and enhances the understanding of these emissions within the research community. Key features of carbonr include its simplicity, user-friendly Shiny interface, and adaptability to different sector needs, making it accessible to a broader audience.

By being hosted on GitHub, carbonr encourages global community engagement. This collaborative environment not only keeps the tool up-to-date but also allows it to be tailored to specific sectors. A notable enhancement in the application of carbonr is its role in assessing emissions from operating theatres, which are significant contributors to hospital carbon footprints. In a collaborative initiative hosted on GitHub, carbonr was adapted to include a set of functions that calculate carbon emissions specifically for operating theatres [@ma2024green].

Furthermore, the open-source nature of carbonr allows for ongoing verification and comparison of emissions data, this is important for accurate environmental impact assessments.

The emission calculations of carbonr are primarily based on the UK Government’s greenhouse gas reporting guidelines [@ukgov_greenhouse_gas_reporting_2023]. The integration of a straightforward Shiny interface broadens its usability beyond technically skilled users to anyone interested in carbon management, reflecting our commitment to making carbon estimation as inclusive and user-friendly as possible.

By bridging these gaps, carbonr not only facilitates precise and comprehensive emission calculations, but also promotes a deeper understanding of emissions across different sectors. Its ongoing development and adaptability highlight its potential to significantly influence both research and practical applications in environmental sustainability, ensuring it remains relevant and effective in the face of evolving challenges.

Usage

With carbonr, users can estimate emissions for various activities such as air travel, hotel stays, and construction work using straightforward functions like airplane_emissions() or construction_emissions().

The carbonr package complements other R tools by providing functions to estimate and analyse emissions from various activities such as air travel, hotel stays, and construction work. Below are detailed examples demonstrating common uses in estimating travel emissions

Estimating Travel Emissions

First, use the airport_finder function to lookup IATA codes for airports. Here's how you find the code for London Heathrow and Nairobi airports:

library(carbonr)
library(dplyr)

library(carbonr)
library(dplyr)
# Finding the airport code for London Heathrow
airport_finder(name = "Heathrow")

| Name | City | Country | IATA | |:------------------------:|:-------:|:--------------:|:----:| | London Heathrow Airport | London | United Kingdom | LHR |

# Finding the airport codes for airports in Nairobi
carbonr::airport_finder(city = "Nairobi")

Using these codes, calculate the emissions for a round-trip journey:

# Calculating emissions for a round-trip flight
airplane_emissions(from = "LHR", to = "KIS", via = "NBO")

Analysing Emissions Data Sets

For a more comprehensive analysis, integrate information for multiple travellers and journey types:

# Example dataset of multiple individuals' travel details
multiple_ind <- tibble::tribble(
  ~ID, ~rail_from, ~rail_to, ~air_from, ~air_to, ~air_via,
  "Clint", "Bristol Temple Meads", "Paddington", "LHR", "KIS", "NBO",
  "Zara", "Bristol Temple Meads", "Paddington", "LHR", "LAX", "ORL"
)

multiple_ind %>%
  dplyr::rowwise() %>%
  dplyr::mutate(plane_emissions = airplane_emissions(air_from, air_to, air_via)) %>%
  dplyr::mutate(train_emissions = rail_emissions(rail_from, rail_to)) %>%
  dplyr::mutate(total_emissions = plane_emissions + train_emissions)

| ID | Rail from | Rail to | Air from | Air to | Air via | Air emissions | Rail emissions | Total emissions | |:---:|:--------------------:|:--------:|:--------:|:------:|:-------:|:---------------:|:---------------:|:---------------:| | Clint | Bristol Temple Meads | Paddington | LHR | KIS | NBO | 2.091 | 0.007 | 2.098 | | Zara | Bristol Temple Meads | Paddington | LHR | LAX | ORL | 3.086 | 0.007 | 3.093 |

Future Goals

The ongoing development of carbonr is focused on enhancing its utility and sustainability as a key research tool. We are committed to multiple objectives.

First, we aim to expand carbonr's capabilities to process annual data from both companies and individuals, enabling detailed emissions reporting with advanced visualisations and tailored data tables. This feature would support researchers in tracking temporal trends and assessing long-term environmental strategies.

Futhermore, reflecting on successful collaborations, such as the one that led to the inclusion of operating theatre emissions [@ma2024green], we encourage the community to actively participate in carbonr's evolution. Our GitHub platform is open for researchers, developers, and environmental practitioners to contribute insights, refine methodologies, and address emerging challenges.

We plan to regularly update carbonr by integrating the latest research findings and environmental reporting standards. Our release cycle includes bi-annual updates to maintain relevance and accuracy, supporting both practical application and scientific research.

By integrating these changes, we hope for carbonr to both remain relevant as a practical tool and to grow as a research tool. This can contribute to the scientific community’s efforts to combat climate change through better data understanding and informed policy-making.