Package 'carbonr'

Description

For use in the shiny_emissions() function. Adding an unknown quantity of textInputs.

Usage

add_inputs(numeric_input, label, value)

Arguments

Value

Returns textInput for use in the shiny_emissions() function.

Examples

if(interactive()) {
ui <- shinydashboard::dashboardPage(header = shinydashboard::dashboardHeader(),
                                    sidebar = shinydashboard::dashboardSidebar(),
                                    shinydashboard::dashboardBody(
                                    shiny::fluidRow(
                                    shiny::column(12, align = "left",
                                    shiny::splitLayout(shinydashboard::box(width = NULL,
                                    shiny::numericInput("newbox_add",
                                                        "Number of new boxes:",
                                                        value = 0, min = 0),
                                    shiny::uiOutput("newbox_input")))))))
server <- function(input, output) {
  K_plane <- shiny::reactive({ input$newbox_add })
  output$newbox_input <- shiny::renderUI({ add_inputs(numeric_input = K_plane(),
                                                      label = "New Box:",
                                                      value = "textbox") })
}
shiny::shinyApp(ui, server)
}

Description

This function calculates the CO2e emissions between airports based on the provided parameters. The distances are calculated using the "airport_distance" function from the "airportr" package.

Usage

airplane_emissions(
  from,
  to,
  via = NULL,
  num_people = 1,
  radiative_force = TRUE,
  include_WTT = TRUE,
  round_trip = FALSE,
  class = c("Average passenger", "Economy class", "Business class",
    "Premium economy class", "First class")
)

Arguments

Details

The distances are calculated using the "airport_distance" function from the "airportr" package. This means that the distances between locations uses the Haversine formula. This is calculated as the crow flies.

Value

Returns CO2e emissions in tonnes.

Examples

# Calculate emissions for a flight between Vancouver (YVR) and Toronto (YYZ)
airplane_emissions("YVR", "YYZ")
# Calculate emissions for a flight between London Heathrow (LHR)
# and Kisumu Airport (KIS), with layovers in Amsterdam (AMS) and Nairobi
# (NBO), flying in Economy class.
airplane_emissions("LHR", "KIS", via = c("AMS", "NBO"),
                   class = "Economy class")

Description

Find the name, city, country, and IATA code of an airport. For use in the airplane_emissions function.

Usage

airport_finder(
  name,
  city,
  country,
  IATA_code,
  distance = 0.1,
  ignore.case = FALSE
)

Arguments

Value

Data frame containing the name, city, country, and IATA code of an airport.

Examples

# Can get the IATA code from the name of an airport. Gets similar matches.
airport_finder(name = "Bristo")

# Can get the IATA code from the name and city of an airport
airport_finder(name = "Bristo", country = "United Kingdom")

# Can find the name and city of an airport given the IATA code
airport_finder(IATA_code = "BRS")

Description

This dataset is adapted from the airportr package. Full credit and acknowledgment go to the original authors of the airportr package for their contribution. A dataset containing names, codes, locations, altitude, and timezones for airports.

Usage

airports

Format

A data frame with 7698 rows and 14 variables:

OpenFlights ID

OpenFlights database ID

Name

Airport name, sometimes contains name of the city

City

Name of the city served by the airport

IATA

3-letter IATA code

ICAO

4-letter ICAO code

Country

Country name as in OpenFlights database. Note that country names may not be ISO 3166-1 standard.

Country Code

ISO 3166-1 numeric country code

Country Code (Alpha-2)

Two-letter ISO country code

Country Code (Alpha-3)

Three-letter ISO country code

Latitude

Latitude in decimal degrees

Longitude

Longitude in decimal degrees

Altitude

Altitude in feet

UTC

Hours offset from UTC

DST

Daylight Savings Time. One of E (Europe), A (US/Canada), S (South America), O (Australia), Z (New Zealand), N (None) or U (Unknown)

Timezone

Timezone in Olson format

Type

Type of airport (e.g., large airport, medium airport, small airport)

Source

Source of data, generally sourced from OurAirports

Source

https://cran.r-project.org/package=airportr

Description

Estimates the CO2e emissions associated with different anaesthetic agents.

Usage

anaesthetic_emissions(
  desflurane = 0,
  sevoflurane = 0,
  isoflurane = 0,
  N2O = 0,
  methoxyflurane = 0,
  propofol = 0
)

Arguments

Details

These estimates are based on available literature and may vary depending on factors such as specific anaesthetic agents, usage conditions, and waste gas management practices.

Value

The total CO2e emissions in tonnes.

References

• McGain F, Muret J, Lawson C, Sherman JD. Environmental sustainability in anaesthesia and critical care. Br J Anaesth. 2020 Nov;125(5):680-692. DOI: 10.1016/j.bja.2020.06.055. Epub 2020 Aug 12. PMID: 32798068; PMCID: PMC7421303.

• ACS Sustainable Chem. Eng. 2019, 7, 7, 6580–6591. Publication Date: January 20, 2019. Link

• Sherman, Jodi MD*; Le, Cathy; Lamers, Vanessa; Eckelman, Matthew PhD. Life Cycle Greenhouse Gas Emissions of Anesthetic Drugs. Anesthesia & Analgesia 114(5):p 1086-1090, May 2012. DOI: 10.1213/ANE.0b013e31824f6940. Link

Examples

anaesthetic_emissions(desflurane = 200, sevoflurane = 30, N2O = 5)

Description

Further options are given in the raw_fuels function.

Usage

building_emissions(
  water_supply = 0,
  water_trt = TRUE,
  water_unit = c("cubic metres", "million litres"),
  electricity_kWh = 0,
  electricity_TD = TRUE,
  electricity_WTT = TRUE,
  heat_kWh = 0,
  heat_TD = TRUE,
  heat_WTT = TRUE
)

Arguments

Value

Returns CO2e emissions in tonnes.

References

Descriptions from 2022 UK Government Report: https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2022

Examples

# specify emissions in an office
building_emissions(electricity_kWh = 200,
                 heat_kWh = 100, water_supply = 100, water_trt = FALSE)

Description

This function calculates the carbon price credit for a given jurisdiction, year, period, and CO2e value. It uses CPI (Carbon Price Index) data to determine the carbon price for the specified jurisdiction and time period. The carbon price credit is calculated by multiplying the CO2e value by the corresponding carbon price.

Usage

carbon_price_credit(
  jurisdiction = NULL,
  year = NULL,
  period = 0,
  manual_price = NULL,
  co2e_val
)

Arguments

Value

The calculated carbon price credit in USD ($).

Examples

# Calculate carbon price credit for the United Kingdom in the year 2000,
# period 2, and CO2e value of 100
carbon_price_credit("United Kingdom", 2022, 2, co2e_val = 100)

# Or manually enter a value
carbon_price_credit(manual_price = 66.9, co2e_val = 100)

Description

The carbonr package provides a flexible tool for calculating carbon-equivalent emissions.

Author(s)

Maintainer: Lily Clements [email protected] (ORCID)

See Also

See the README on GitHub

Description

Find jurisdictions available in the Carbon Credits data. If a jurisdiction is specified, find the years associated with that jurisdiction.

Usage

check_CPI(jurisdiction = NULL, period = FALSE)

Arguments

Value

A vector or data frame containing the information.

Examples

which_jur <- check_CPI()
which_years <- check_CPI(jurisdiction = "Switzerland")
which_years_and_period <- check_CPI(jurisdiction = "Switzerland", period = TRUE)

Description

Get the clinical theatre emissions after a data frame is inputted into the function.

Usage

clinical_theatre_data(
  data,
  time,
  date_format = c("%d/%m/%Y"),
  name,
  wet_clinical_waste = 0,
  wet_clinical_waste_unit = c("tonnes", "kg"),
  desflurane = 0,
  sevoflurane = 0,
  isoflurane = 0,
  methoxyflurane = 0,
  N2O = 0,
  propofol = 0,
  water_supply = 0,
  water_trt = TRUE,
  water_unit = c("cubic metres", "million litres"),
  electricity_kWh = 0,
  electricity_TD = TRUE,
  electricity_WTT = TRUE,
  heat_kWh = 0,
  heat_TD = TRUE,
  heat_WTT = TRUE,
  glass = 0,
  board = 0,
  mixed = 0,
  paper = 0,
  average = 0,
  average_film = 0,
  average_rigid = 0,
  HDPE = 0,
  LDPE = 0,
  LLDPE = 0,
  PET = 0,
  PP = 0,
  PS = 0,
  PVC = 0,
  glass_WD = 0,
  glass_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  board_WD = 0,
  mixed_WD = 0,
  paper_WD = 0,
  paper_waste_disposal = c("Closed-loop", "Combustion", "Composting", "Landfill"),
  average_WD = 0,
  average_film_WD = 0,
  average_rigid_WD = 0,
  HDPE_WD = 0,
  LDPE_WD = 0,
  LLDPE_WD = 0,
  PET_WD = 0,
  PP_WD = 0,
  PS_WD = 0,
  PVC_WD = 0,
  plastic_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  fridges = 0,
  freezers = 0,
  electric_waste_disposal = c("Landfill", "Open-loop"),
  glass_units = c("kg", "tonnes"),
  paper_units = c("kg", "tonnes"),
  plastic_units = c("kg", "tonnes"),
  electrical_units = c("kg", "tonnes"),
  include_cpi = FALSE,
  jurisdiction = NULL,
  year = NULL,
  period = 0,
  manual_price = NULL,
  gti_by = c("default", "month", "year"),
  overall_by = c("default", "month", "year"),
  single_sheet = FALSE
)

Arguments

Value

Returns list containing two objects. A table containing CO2e emissions for each row of data (and carbon price index in USD if include_cpi is TRUE), and a ggplot2 object plotting the CO2e emissions. The second object is a single sheet containing summaries if single_sheet = TRUE.

Examples

# Example with dummy data
df <- data.frame(time = c("10/04/2000", "10/04/2000", "11/04/2000",
                          "11/04/2000", "12/04/2000", "12/04/2000"),
                 theatre = rep(c("A", "B"), times = 3),
                 clinical_waste = c(80, 90, 80, 100, 120, 110),
                 electricity_kwh = c(100, 110, 90, 100, 100, 110),
                 general_waste = c(65, 55, 70, 50, 60, 30))

clinical_theatre_data(df, time = time, name = theatre,
                 wet_clinical_waste = clinical_waste,
                 wet_clinical_waste_unit = "kg",
                 desflurane = 10,
                 average = general_waste,
                 plastic_units = "kg",
                 electricity_kWh = electricity_kwh,
                 include_cpi = TRUE,
                 jurisdiction = "Australia",
                 year = 2023,
                 single_sheet = FALSE)

Description

Calculate carbon-equivalent emissions following an operating theatre

Usage

clinical_theatre_emissions(
  wet_clinical_waste,
  wet_clinical_waste_unit = c("tonnes", "kg"),
  desflurane = 0,
  sevoflurane = 0,
  isoflurane = 0,
  methoxyflurane = 0,
  N2O = 0,
  propofol = 0,
  water_supply = 0,
  water_trt = TRUE,
  water_unit = c("cubic metres", "million litres"),
  electricity_kWh = 0,
  electricity_TD = TRUE,
  electricity_WTT = TRUE,
  heat_kWh = 0,
  heat_TD = TRUE,
  heat_WTT = TRUE,
  glass = 0,
  board = 0,
  mixed = 0,
  paper = 0,
  average = 0,
  average_film = 0,
  average_rigid = 0,
  HDPE = 0,
  LDPE = 0,
  LLDPE = 0,
  PET = 0,
  PP = 0,
  PS = 0,
  PVC = 0,
  glass_WD = 0,
  glass_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  board_WD = 0,
  mixed_WD = 0,
  paper_WD = 0,
  fridges = 0,
  freezers = 0,
  electric_waste_disposal = c("Landfill", "Open-loop"),
  electrical_units = c("kg", "tonnes"),
  paper_waste_disposal = c("Closed-loop", "Combustion", "Composting", "Landfill"),
  average_WD = 0,
  average_film_WD = 0,
  average_rigid_WD = 0,
  HDPE_WD = 0,
  LDPE_WD = 0,
  LLDPE_WD = 0,
  PET_WD = 0,
  PP_WD = 0,
  PS_WD = 0,
  PVC_WD = 0,
  plastic_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  glass_units = c("kg", "tonnes"),
  paper_units = c("kg", "tonnes"),
  plastic_units = c("kg", "tonnes")
)

Arguments

Value

Returns CO2e emissions in tonnes.

Examples

# clinical theatre emissions for the default options, with 100kg of wet clinical waste
 clinical_theatre_emissions(wet_clinical_waste = 100, wet_clinical_waste_unit = "kg")

Description

: This function calculates the construction emissions based on the input parameters.

Usage

construction_emissions(
  aggregates = 0,
  average = 0,
  asbestos = 0,
  asphalt = 0,
  bricks = 0,
  concrete = 0,
  insulation = 0,
  metals = 0,
  soils = 0,
  mineral_oil = 0,
  plasterboard = 0,
  tyres = 0,
  wood = 0,
  aggregates_WD = 0,
  average_WD = 0,
  asbestos_WD = 0,
  asphalt_WD = 0,
  bricks_WD = 0,
  concrete_WD = 0,
  insulation_WD = 0,
  metals_WD = 0,
  soils_WD = 0,
  mineral_oil_WD = 0,
  plasterboard_WD = 0,
  tyres_WD = 0,
  wood_WD = 0,
  units = c("kg", "tonnes"),
  waste_disposal = c("Closed-loop", "Combustion", "Composting", "Landfill", "Open-loop")
)

Arguments

Details

The function calculates the construction emissions based on the input quantities of different materials used in construction and the quantities of those materials disposed of as waste. The emissions values are obtained from a data source and are multiplied by the corresponding quantities to calculate the total emissions. The units of emissions can be specified as either kilograms (kg) or tonnes.

All assume ⁠Primary material production⁠ for the material used in construction, except soils which assumes Closed-loop

The waste disposal method can be selected from the options: "Closed-loop", "Combustion", "Composting", "Landfill", or "Open-loop". Note that: "Closed-loop" is valid for aggregates, average, asphalt, concrete, insulation, metal, soils, mineral oil, plasterboard, tyres, and wood. "Combustion" is valid for average, mineral oil, and wood. "Composting" is valid for wood only. "Landfill" is valid for everything except average, mineral oil, and tyres. "Open-loop" is valid for aggregates, average, asphalt, bricks, concrete, If one of these is used for a value that does not provide it, then an "NA" is given.

Value

The calculated construction emissions as a numeric value in tonnes.

Examples

#Calculate construction emissions with default values
construction_emissions()

#Calculate construction emissions with specified quantities
construction_emissions(aggregates = 1000, concrete = 500, wood = 2000,
                       units = "kg", waste_disposal = "Landfill")

Description

Convert degrees to radians.

Usage

degree_conversion(deg)

Arguments

Value

Value in radians.

Examples

# Convert 90 degrees into radians
degree_conversion(90)

Description

Calculate distances between locations in miles using the Haversine formula. This is calculated as the crow flies.

Usage

distance_calc(lat1, lat2, long1, long2)

Arguments

Value

Distance between locations in miles

Examples

# Distance between the London Eye and the Eiffel Tower in miles
distance_calc(51.5033, 48.8584, 0.1196, 2.2945)

Description

This function calculates the emissions produced from different electrical items and their waste disposal based on the specified inputs. It considers emissions from primary material production and waste disposal of electrical items.

Usage

electrical_emissions(
  fridges = 0,
  freezers = 0,
  large = 0,
  IT = 0,
  small = 0,
  alkaline_batteries = 0,
  LiIon_batteries = 0,
  NiMh_batteries = 0,
  fridges_WD = 0,
  freezers_WD = 0,
  large_WD = 0,
  IT_WD = 0,
  small_WD = 0,
  alkaline_batteries_WD = 0,
  LiIon_batteries_WD = 0,
  NiMh_batteries_WD = 0,
  waste_disposal = c("Landfill", "Open-loop"),
  units = c("kg", "tonnes")
)

Arguments

Value

The calculated electrical emissions as a numeric value in tonnes.

Examples

# Calculate electrical emissions using default values
electrical_emissions()

# Calculate electrical emissions with specific quantities and waste disposal
# method
electrical_emissions(fridges = 10, IT = 5, alkaline_batteries = 100,
                     waste_disposal = "Open-loop", units = "tonnes")

Description

This dataset contains activities within a clinical theatre setting related to healthcare services or medical supplies. It is structured to facilitate analysis of healthcare operations, costs, and estimate CO2e emissions.

Usage

example_clinical_theatre

Format

A data frame with 4,386 rows and 6 columns, including:

time

The date of transaction or activity in DDMMYYYY format.

prices

The cost associated with each transaction or activity in AUD, related to services provided or medical supplies used.

quantities

The amount or volume of a product or service provided, indicating the number of items used or procedures performed.

prodID

A unique identifier for each type of product or service, such as medical supplies, medications, or surgical procedures.

retID

A code identifying the department, supplier, or healthcare provider involved in the transaction, or the entity receiving the product or service.

description

Categorises the clinical theatre activities into medical specialties or types of procedures, with 'ent' (Ear, Nose, and Throat), 'colorectal', 'hbt' (hematology or blood treatment), 'ortho' (orthopedics), 'paedsurg' (pediatric surgery), and 'gensurg' (general surgery).

Details

The dataset provides an overview of clinical theatre operations.

Description

A function that calculates CO2e emissions between ferry ports.

Usage

ferry_emissions(
  from,
  to,
  via = NULL,
  type = c("Foot", "Car", "Average"),
  num_people = 1,
  times_journey = 1,
  include_WTT = TRUE,
  round_trip = FALSE
)

Arguments

Details

The distances are calculated using the Haversine formula. This is calculated as the crow flies.

Value

Returns CO2e emissions in tonnes for the ferry journey.

Examples

# Emissions for a ferry journey between Belfast and New York City
seaport_finder(city = "Belfast")
seaport_finder(city = "New York")
ferry_emissions(from = "BEL", to = "BOY")

Description

This function creates a value box for use in reports.

Usage

gg_value_box(values, information, icons)

Arguments

Details

This function creates a value box with customizable values, information, and icons. The function takes inputs for the values, information, icons, and color of the value box. The values and information are provided as vectors, while the icons are specified using Font Awesome unicode symbols. The color of the value box can be customized using a factor variable. The resulting value box is a ggplot2 object that can be further customized or combined with other plots or elements in a report.

Value

A ggplot2 object with a value box for report use.

References

Modified from Stack Overflow post: https://stackoverflow.com/questions/47105282/valuebox-like-function-for-static-reports

Examples

# Create a value box with custom values and icons
gg_value_box(
  values = c(100, 500, 1000),
  information = c("Sales", "Revenue", "Customers"),
  icons = c("\U0000f155", "\U0000f155", "\U0000f0f7")
)

Description

Indirect emissions from a stay at a hotel. Values to calculate emissions are from UK government 2022 report.

Usage

hotel_emissions(location = "UK", nights = 1, rooms = 1)

Arguments

Value

Tonnes of CO2e emissions for a stay in a hotel.

Examples

# Emissions for a two night stay in Fiji.
hotel_emissions(location = "Fiji", nights = 2)

Description

Calculate household material emissions

Usage

household_emissions(
  glass = 0,
  clothing = 0,
  food = 0,
  drink = 0,
  compost_from_garden = 0,
  compost_from_food_and_garden = 0,
  board = 0,
  mixed = 0,
  paper = 0,
  fridges = 0,
  freezers = 0,
  large_electrical = 0,
  IT = 0,
  small_electrical = 0,
  alkaline_batteries = 0,
  LiIon_batteries = 0,
  NiMh_batteries = 0,
  aluminuim_cans = 0,
  aluminuim_foil = 0,
  mixed_cans = 0,
  scrap = 0,
  steel_cans = 0,
  average = 0,
  average_film = 0,
  average_rigid = 0,
  HDPE = 0,
  LDPE = 0,
  LLDPE = 0,
  PET = 0,
  PP = 0,
  PS = 0,
  PVC = 0,
  glass_WD = 0,
  books_WD = 0,
  clothing_WD = 0,
  gcb_waste_disposal = c("Closed-loop", "Combustion", "Landfill"),
  household_residual_waste = 0,
  hh_waste_disposal = c("Combustion", "Landfill"),
  food_WD = 0,
  drink_WD = 0,
  compost_from_garden_WD = 0,
  compost_from_food_and_garden_WD = 0,
  compost_waste_disposal = c("Anaerobic digestion", "Combustion", "Composting",
    "Landfill"),
  aluminuim_cans_WD = 0,
  aluminuim_foil_WD = 0,
  mixed_cans_WD = 0,
  scrap_WD = 0,
  steel_cans_WD = 0,
  metal_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  board_WD = 0,
  mixed_WD = 0,
  paper_WD = 0,
  paper_waste_disposal = c("Closed-loop", "Combustion", "Composting", "Landfill"),
  average_WD = 0,
  average_film_WD = 0,
  average_rigid_WD = 0,
  HDPE_WD = 0,
  LDPE_WD = 0,
  LLDPE_WD = 0,
  PET_WD = 0,
  PP_WD = 0,
  PS_WD = 0,
  PVC_WD = 0,
  plastic_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  fridges_WD = 0,
  freezers_WD = 0,
  large_electrical_WD = 0,
  IT_WD = 0,
  small_electrical_WD = 0,
  alkaline_batteries_WD = 0,
  LiIon_batteries_WD = 0,
  NiMh_batteries_WD = 0,
  electric_waste_disposal = c("Landfill", "Open-loop"),
  units = c("kg", "tonnes")
)

Arguments

Details

⁠*_waste_disposal⁠ methods: "Open-loop" is the process of recycling material into other products. "Closed-loop" is the process of recycling material back into the same product. "Combustion" energy is recovered from the waste through incineration and subsequent generation of electricity. "Compost" CO2e emitted as a result of composting a waste stream. "Landfill" the product goes to landfill after use. "Anaerobic digestion" energy is recovered from the waste through anaerobic digestion.

Value

The calculated household emissions as a numeric value in tonnes.

Examples

household_emissions(glass = 100, clothing = 10, glass_WD = 10, units = "kg")

Description

This function uses the downloaded data from the World Bank Carbon Pricing Dashboard (https://carbonpricingdashboard.worldbank.org/). It imports data from an Excel file containing CPI (Carbon Price Index) data. It filters the data for ETS (Emissions Trading Scheme) instruments, performs necessary transformations, and returns a processed data frame.

Usage

import_CPI(path, sheet = "Data_Price", skip = 2)

Arguments

Value

A processed data frame containing CPI data.

Description

A function that calculates CO2e emissions on a journey on land.

Usage

land_emissions(
  distance,
  units = c("miles", "km"),
  num = 1,
  vehicle = c("Cars", "Motorbike", "Taxis", "Bus", "National rail", "International rail",
    "Light rail and tram", "London Underground", "Coach"),
  fuel = c("Petrol", "Diesel", "Unknown", "Battery Electric Vehicle",
    "Plug-in Hybrid Electric Vehicle"),
  car_type = c("Average car", "Small car", "Medium car", "Large car", "Mini",
    "Supermini", "Lower medium", "Upper medium", "Executive", "Luxury", "Sports",
    "Dual purpose 4X4", "MPV"),
  bike_type = c("Average", "Small", "Medium", "Large"),
  bus_type = c("Local bus (not London)", "Local London bus", "Average local bus"),
  taxi_type = c("Regular taxi", "Black cab"),
  TD = TRUE,
  include_WTT = TRUE,
  include_electricity = TRUE,
  owned_by_org = TRUE
)

Arguments

Value

Tonnes of CO2e emissions per mile travelled.

Examples

# Emissions for a 100 mile car journey
land_emissions(distance = 100)

# Emissions for a 100 mile motorbike journey where the motorbike is 500+cc
land_emissions(distance = 100, vehicle = "Motorbike", bike_type = "Large")

Description

Material (and waste) emissions

Usage

material_emissions(
  glass = 0,
  board = 0,
  mixed = 0,
  paper = 0,
  fridges = 0,
  freezers = 0,
  large_electrical = 0,
  IT = 0,
  small_electrical = 0,
  alkaline_batteries = 0,
  LiIon_batteries = 0,
  NiMh_batteries = 0,
  aluminuim_cans = 0,
  aluminuim_foil = 0,
  mixed_cans = 0,
  scrap = 0,
  steel_cans = 0,
  average = 0,
  average_film = 0,
  average_rigid = 0,
  HDPE = 0,
  LDPE = 0,
  LLDPE = 0,
  PET = 0,
  PP = 0,
  PS = 0,
  PVC = 0,
  glass_WD = 0,
  glass_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  industrial_waste = 0,
  industrial_waste_disposal = c("Combustion", "Landfill"),
  aluminuim_cans_WD = 0,
  aluminuim_foil_WD = 0,
  mixed_cans_WD = 0,
  scrap_WD = 0,
  steel_cans_WD = 0,
  metal_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  board_WD = 0,
  mixed_WD = 0,
  paper_WD = 0,
  paper_waste_disposal = c("Closed-loop", "Combustion", "Composting", "Landfill"),
  average_WD = 0,
  average_film_WD = 0,
  average_rigid_WD = 0,
  HDPE_WD = 0,
  LDPE_WD = 0,
  LLDPE_WD = 0,
  PET_WD = 0,
  PP_WD = 0,
  PS_WD = 0,
  PVC_WD = 0,
  plastic_waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  fridges_WD = 0,
  freezers_WD = 0,
  large_electrical_WD = 0,
  IT_WD = 0,
  small_electrical_WD = 0,
  alkaline_batteries_WD = 0,
  LiIon_batteries_WD = 0,
  NiMh_batteries_WD = 0,
  electric_waste_disposal = c("Landfill", "Open-loop"),
  aggregates = 0,
  construction_average = 0,
  asbestos = 0,
  asphalt = 0,
  bricks = 0,
  concrete = 0,
  insulation = 0,
  metals = 0,
  soils = 0,
  mineral_oil = 0,
  plasterboard = 0,
  tyres = 0,
  wood = 0,
  aggregates_WD = 0,
  construction_average_WD = 0,
  asbestos_WD = 0,
  asphalt_WD = 0,
  bricks_WD = 0,
  concrete_WD = 0,
  insulation_WD = 0,
  metals_WD = 0,
  soils_WD = 0,
  mineral_oil_WD = 0,
  plasterboard_WD = 0,
  tyres_WD = 0,
  wood_WD = 0,
  construction_waste_disposal = c("Closed-loop", "Combustion", "Composting", "Landfill",
    "Open-loop"),
  construction_units = c("kg", "tonnes"),
  metal_units = c("kg", "tonnes"),
  glass_units = c("kg", "tonnes"),
  paper_units = c("kg", "tonnes"),
  plastic_units = c("kg", "tonnes"),
  electrical_units = c("kg", "tonnes")
)

Arguments

Details

⁠*_waste_disposal⁠ methods: "Open-loop" is the process of recycling material into other products. "Closed-loop" is the process of recycling material back into the same product. "Combustion" energy is recovered from the waste through incineration and subsequent generation of electricity. "Compost" CO2e emitted as a result of composting a waste stream. "Landfill" the product goes to landfill after use. "Anaerobic digestion" energy is recovered from the waste through anaerobic digestion.

Value

The calculated household emissions as a numeric value in tonnes.

Examples

material_emissions(glass = 100, glass_WD = 10, glass_units = "kg")

Description

This function calculates the emissions produced from different metal sources based on the specified inputs. It considers emissions from primary material production and waste disposal of various metal types.

Usage

metal_emissions(
  aluminuim_cans = 0,
  aluminuim_foil = 0,
  mixed_cans = 0,
  scrap = 0,
  steel_cans = 0,
  aluminuim_cans_WD = 0,
  aluminuim_foil_WD = 0,
  mixed_cans_WD = 0,
  scrap_WD = 0,
  steel_cans_WD = 0,
  waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  units = c("kg", "tonnes")
)

Arguments

Value

The function returns the calculated CO2-equivalent emissions as a numeric value in tonnes.

Examples

metal_emissions(aluminuim_cans = 1.4, units = "tonnes")

Description

Office emissions

Usage

office_emissions(
  specify = FALSE,
  office_num = 1,
  WFH_num = 0,
  WFH_hours = 0,
  WFH_type = c("Office Equipment", "Heating"),
  water_supply = 0,
  water_trt = TRUE,
  water_unit = c("cubic metres", "million litres"),
  electricity_kWh = 0,
  electricity_TD = TRUE,
  electricity_WTT = TRUE,
  heat_kWh = 0,
  heat_TD = TRUE,
  heat_WTT = TRUE
)

Arguments

Value

Returns CO2e emissions in tonnes.

References

Descriptions from 2022 UK Government Report: https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2022

Examples

# specify emissions in an office
office_emissions(specify = TRUE, electricity_kWh = 200,
                 heat_kWh = 100, water_supply = 100, water_trt = FALSE)

Description

This function generates a grid of plots and tables, including a value box, data table, relative GPI plot, and total output plot.

Usage

output_display(
  data = x$data,
  time = time,
  date_format = c("%d/%m/%Y"),
  name = theatre,
  relative_gpi_val = emissions,
  gti_by = c("default", "month", "year"),
  plot_val = carbon_price_credit,
  plot_by = "default",
  pdf = TRUE
)

Arguments

Details

The function utilises other auxiliary functions such as relative_gti() and total_output().

Value

A grid of plots and tables showing the value box, data table, relative GPI plot, and total output plot.

Description

This function calculates the emissions produced from different paper sources based on the specified inputs. It considers emissions from primary material production and waste disposal of paper materials.

Usage

paper_emissions(
  board = 0,
  mixed = 0,
  paper = 0,
  board_WD = 0,
  mixed_WD = 0,
  paper_WD = 0,
  waste_disposal = c("Closed-loop", "Combustion", "Composting", "Landfill"),
  units = c("kg", "tonnes")
)

Arguments

Value

The function returns the calculated paper emissions as a numeric value in tonnes.

Examples

paper_emissions(board = 10, board_WD = 10, paper = 100, paper_WD = 100, units = "kg")

Description

This function calculates the emissions produced from different plastic sources based on the specified inputs. It considers emissions from primary material production and waste disposal of plastic materials.

Usage

plastic_emissions(
  average = 0,
  average_film = 0,
  average_rigid = 0,
  HDPE = 0,
  LDPE = 0,
  LLDPE = 0,
  PET = 0,
  PP = 0,
  PS = 0,
  PVC = 0,
  average_WD = 0,
  average_film_WD = 0,
  average_rigid_WD = 0,
  HDPE_WD = 0,
  LDPE_WD = 0,
  LLDPE_WD = 0,
  PET_WD = 0,
  PP_WD = 0,
  PS_WD = 0,
  PVC_WD = 0,
  waste_disposal = c("Closed-loop", "Combustion", "Landfill", "Open-loop"),
  units = c("kg", "tonnes")
)

Arguments

Value

The calculated plastic emissions as a numeric value in tonnes.

Examples

# Calculate plastic emissions using default values
plastic_emissions()

# Calculate plastic emissions with specific quantities and waste disposal
# method
plastic_emissions(average = 100, HDPE = 50, PET = 25,
                  waste_disposal = "Combustion", units = "tonnes")

Description

A function that calculates CO2e emissions between train stations in the UK.

Usage

rail_emissions(
  from,
  to,
  via = NULL,
  num_people = 1,
  times_journey = 1,
  include_WTT = TRUE,
  round_trip = FALSE
)

Arguments

Details

The distances are calculated using the Haversine formula. This is calculated as the crow flies. As a result, inputting the "via" journeys will make for a more reliable function.

Value

Returns CO2e emissions in tonnes for the train journey.

Examples

# Emissions for a train journey between Southampton Central and
# Manchester Piccadilly Station
rail_emissions("Southampton Central", "Manchester Piccadilly")

# Emissions for a train journey between Bristol Temple Meads and
# London Paddington via Bath, Swindon, and Reading
# Use the \code{rail_finder} function to find the name of London Paddington
rail_finder(region = "London")
# Then calculate emissions
rail_emissions("Bristol Temple Meads", "Paddington", via = c("Bath Spa",
"Swindon", "Reading"))

Description

Find the name, area, and code of a train station in the UK. For use in the rail_emissions function.

Usage

rail_finder(
  station,
  region,
  county,
  district,
  station_code,
  distance = 0.1,
  ignore.case = FALSE
)

Arguments

Value

Data frame containing the station code, station name, region, county, district, latitude, and longitude of a train station in the UK.

Examples

# Can get the station code from the station. Gets similar matches.
rail_finder(station = "Bristo")

# Can get the code from the station and city.
rail_finder(station = "Bristo", county = "Bristol")

# Can find the name and district of a train station given the IATA code
rail_finder(station_code = "BRI")

Description

Raw Fuels Emissions

Usage

raw_fuels(
  num_people = 1,
  butane = 0,
  CNG = 0,
  LPG = 0,
  LNG = 0,
  natural_gas = 0,
  natural_gas_mineral = 0,
  other_petroleum_gas = 0,
  propane = 0,
  aviation = 0,
  aviation_fuel = 0,
  burning_oil = 0,
  diesel = 0,
  diesel_mineral = 0,
  fuel_oil = 0,
  gas_oil = 0,
  lubricants = 0,
  naptha = 0,
  petrol_biofuel = 0,
  petrol_mineral = 0,
  residual_oil = 0,
  distillate = 0,
  refinery_miscellaneous = 0,
  waste_oils = 0,
  marine_gas = 0,
  marine_fuel = 0,
  coal_industrial = 0,
  coal_electricity_gen = 0,
  coal_domestic = 0,
  coking_coal = 0,
  petroleum_coke = 0,
  coal_home_produced_gen = 0,
  bioethanol = 0,
  biodiesel = 0,
  biomethane = 0,
  biodiesel_cooking_oil = 0,
  biodiesel_tallow = 0,
  biodiesel_HVO = 0,
  biopropane = 0,
  bio_petrol = 0,
  renewable_petrol = 0,
  wood_log = 0,
  wood_chips = 0,
  wood_pellets = 0,
  grass = 0,
  biogas = 0,
  landfill_gas = 0,
  butane_units = c("kwh", "litres", "tonnes"),
  CNG_units = c("kwh", "litres", "tonnes"),
  LPG_units = c("kwh", "litres", "tonnes"),
  LNG_units = c("kwh", "litres", "tonnes"),
  natural_gas_units = c("kwh", "cubic metres", "tonnes"),
  natural_gas_mineral_units = c("kwh", "cubic metres", "tonnes"),
  other_petroleum_gas_units = c("kwh", "litres", "tonnes"),
  propane_units = c("kwh", "litres", "tonnes"),
  aviation_units = c("kwh", "litres", "tonnes"),
  aviation_fuel_units = c("kwh", "litres", "tonnes"),
  burning_oil_units = c("kwh", "litres", "tonnes"),
  diesel_units = c("kwh", "litres", "tonnes"),
  diesel_mineral_units = c("kwh", "litres", "tonnes"),
  fuel_oil_units = c("kwh", "litres", "tonnes"),
  gas_oil_units = c("kwh", "litres", "tonnes"),
  lubricants_units = c("kwh", "litres", "tonnes"),
  naptha_units = c("kwh", "litres", "tonnes"),
  petrol_biofuel_units = c("kwh", "litres", "tonnes"),
  petrol_mineral_units = c("kwh", "litres", "tonnes"),
  residual_oil_units = c("kwh", "litres", "tonnes"),
  distillate_units = c("kwh", "litres", "tonnes"),
  refinery_miscellaneous_units = c("kwh", "litres", "tonnes"),
  waste_oils_units = c("kwh", "tonnes"),
  marine_gas_units = c("kwh", "tonnes"),
  marine_fuel_units = c("kwh", "tonnes"),
  coal_industrial_units = c("kwh", "tonnes"),
  coal_electricity_gen_units = c("kwh", "tonnes"),
  coal_domestic_units = c("kwh", "tonnes"),
  coking_coal_units = c("kwh", "tonnes"),
  petroleum_coke_units = c("kwh", "tonnes"),
  coal_home_produced_gen_units = c("kwh", "tonnes"),
  bioethanol_units = c("litres", "GJ", "kg"),
  biodiesel_units = c("litres", "GJ", "kg"),
  biomethane_units = c("litres", "GJ", "kg"),
  biodiesel_cooking_oil_units = c("litres", "GJ", "kg"),
  biodiesel_tallow_units = c("litres", "GJ", "kg"),
  biodiesel_HVO_units = c("litres", "GJ", "kg"),
  biopropane_units = c("litres", "GJ", "kg"),
  bio_petrol_units = c("litres", "GJ", "kg"),
  renewable_petrol_units = c("litres", "GJ", "kg"),
  wood_log_units = c("kwh", "tonnes"),
  wood_chips_units = c("kwh", "tonnes"),
  wood_pellets_units = c("kwh", "tonnes"),
  grass_units = c("kwh", "tonnes"),
  biogas_units = c("kwh", "tonnes"),
  landfill_gas_units = c("kwh", "tonnes")
)

Arguments

Details

This function calculates CO2e emissions from a wide variety of fuels, considering different unit conversions for each type of fuel. It supports the calculation of emissions from commonly used fuels such as diesel, petrol, natural gas, and biodiesel, as well as more specific fuels like aviation fuel, marine fuel, and landfill gas.

Unit conversions are done internally based on the specified units for each type of fuel (e.g., kWh, litres, tonnes). The function is useful for assessing the carbon footprint associated with different fuel sources over a specified time period.

Value

A data frame with calculated emissions in tonnes of CO2e for each type of fuel input.

References

• DEFRA Conversion Factors for Greenhouse Gas (GHG) Reporting: https://www.gov.uk/government/collections/government-conversion-factors-for-company-reporting

• Descriptions from 2021 UK Government Report: https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2021

Examples

# Calculate emissions for 100 litres of diesel and 500 kWh of natural gas:
raw_fuels(
  diesel = 100, diesel_units = "litres",
  natural_gas = 500, natural_gas_units = "kwh",
)

# Calculate emissions for 10 tonnes of aviation fuel:
raw_fuels(
  aviation_fuel = 10, aviation_fuel_units = "tonnes",
)

Description

Calculate and plot the relative growth to index (GTI) over time

Usage

relative_gti(
  data = data,
  time = time,
  date_format = c("%d/%m/%Y"),
  name = theatre,
  val = emissions,
  gti_by = c("default", "month", "year")
)

Arguments

Value

A ggplot2 object showing the relative GTI (Growth to Index) over time.

Examples

# Example dataset
emission_data <- data.frame(
  theatre = c("Theatre A", "Theatre A", "Theatre B", "Theatre B", "Theatre A", "Theatre B"),
  emissions = c(200, 250, 150, 180, 300, 220),
  date = c("01/01/2023", "01/02/2023", "01/01/2023", "01/02/2023", "01/03/2023", "01/03/2023")
  )
  
# Using the relative_gti function
relative_gti_plot <- relative_gti(
  data = emission_data,
  time = date,
  date_format = "%d/%m/%Y",  # Date format used in the dataset
  name = theatre,
  val = emissions,
  gti_by = "default"  # Calculating based on default time period
)

# Plot the relative GTI
print(relative_gti_plot)

Description

Find the name and/or code of a seaport. For use in the ferry_emissions function.

Usage

seaport_finder(city, country, port_code, distance = 0.1, ignore.case = FALSE)

Arguments

Value

Data frame containing the country, city, country code, port code, latitude, and longitude of a seaport.

Examples

# Look up the city of Aberdeen to find the port_code for it
seaport_finder(city = "Aberdeen")

# Search for a country and city and it finds matches
seaport_finder(country = "United", city = "borunemouth", ignore.case = TRUE)

Description

A dataset containing the country, country code, city, city code, and coordinates of seaports

Usage

data(seaports)

Format

A data frame with 8736 rows and 7 variables:

country

Name of the country with the port

city

Name of the city with the port

country_code

Code of the country name

port_code

Code of the city port

latitude

Latitude of the port

longitude

Longitude of the port

Source

https://www.kaggle.com/therohk/world-seaport-airport-dataset-and-codes/script

Description

Runs a GUI to the functions in the 'carbonr' package to calculate carbon-equivalent emissions.

Usage

shiny_emissions()

Value

'shiny' app to calculate carbon-equivalent emissions

Examples

if(interactive()){shiny_emissions()}

Description

A dataset containing the city, station code, and coordinates of seaports

Usage

data(stations)

Format

A data frame with 2608 rows and 4 variables:

station

Name of the station

station_code

Code of the station

region

Region of the station. One of "London", "Scotland", "Wales - Cymru", "North West", "West Midlands", "North East", "East", "South East", "East Midlands", "Yorkshire And The Humber", "South West", NA

county

County of the station

district

District of the station

latitude

Latitude of the station

longitude

Longitude of the station

Source

https://www.data.gov.uk/dataset/ff93ffc1-6656-47d8-9155-85ea0b8f2251/national-public-transport-access-nodes-naptan

https://www.theguardian.com/news/datablog/2011/may/19/train-stations-listed-rail#data

Description

This function calculates the total output and generates a plot based on the specified parameters.

Usage

total_output(
  data = x$data,
  time = time,
  date_format = c("%d/%m/%Y"),
  name = theatre,
  val = carbon_price_credit,
  plot_by = c("default", "month", "year")
)

Arguments

Details

This function calculates the total output by grouping the data based on the specified parameters (grouping variable and time dimension). It then summarises the specified variable (CPI or emissions) using the sum function. The resulting data is used to create a line plot showing the total output over time, with each group represented by a different color. The plot can be grouped by the default grouping, month, or year, based on the plot_by parameter.

Value

A ggplot object showing the total output plot.

Description

A function that calculates CO2e emissions on a journey on land.

Usage

vehicle_emissions(
  distance,
  units = c("miles", "km"),
  num = 1,
  vehicle = c("Cars", "Motorbike"),
  fuel = c("Petrol", "Diesel", "Unknown", "Battery Electric Vehicle",
    "Plug-in Hybrid Electric Vehicle"),
  car_type = c("Average car", "Small car", "Medium car", "Large car", "Mini",
    "Supermini", "Lower medium", "Upper medium", "Executive", "Luxury", "Sports",
    "Dual purpose 4X4", "MPV"),
  bike_type = c("Average", "Small", "Medium", "Large"),
  TD = TRUE,
  include_WTT = TRUE,
  include_electricity = TRUE,
  owned_by_org = TRUE
)