In EnergyEconomyDecoupling/MWTools: Functions For Calculation of Muscle Work Within the PSUT Framework

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Introduction

In societal energy analysis and societal exergy analysis (SEA), animals and humans provide energy to society by performing muscle work. A previous study by @Steenwyk:2022ww developed and standardized ways to estimate muscle work contributed to society by animals and humans. And data exist from the UN's Food and Agriculture Organization (FAO) and the International Labor Organization (ILO) that could be used for such purposes. However, none of the data are in the PSUT format proposed by @Heun:2018. Computational tools are needed to gather and shape relevant data.

The examples below show how to use MWTools to address the needs described above.

Examples

Animal Muscle Work

Raw data for the estimation of animal muscle work is obtained from the Food and Agriculture Organisation of the United Nations Statistical Database (FAOSTAT), via the R package FAOSTAT as follows.

raw_amw_data <- FAOSTAT::get_faostat_bulk(code = "QCL",  data_folder = tempdir())

The helper function calc_amw_pfu returns a tidy data frame containing data for the primary, final, and useful energy by species, country, year and in the agriculture, transport, and total sectors.

test_amw_data <- read.csv(file = MWTools::amw_test_data_path())

amw_pfu_data <- MWTools::calc_amw_pfu(.df = test_amw_data,
                                      concordance_path = MWTools::fao_concordance_path(),
                                      amw_analysis_data_path = MWTools::amw_analysis_data_path())
tibble::glimpse(amw_pfu_data)

Human Muscle Work

Raw data for the estimation of human muscle work is obtained from the International Labor Organisation (ILO), via the R package Rilostat as follows:

ilo_working_hours_data <- Rilostat::get_ilostat(id = MWTools::ilo_codes$working_hours_code,
                                                quiet = TRUE) |>
  Rilostat::label_ilostat(code = c("ref_area"))

ilo_employment_data <- Rilostat::get_ilostat(id = MWTools::ilo_codes$employment_code,
                                             quiet = TRUE) |>
  Rilostat::label_ilostat(code = c("ref_area"))

Using data for the number of employed persons and mean yearly working hours the primary, final, and useful energy associated with human muscle work can be estimated using the helper function MWTools::calc_hmw_pfu as below.

``` {r calc_hmw_example} ilo_working_hours_data <- read.csv(file = MWTools::ilo_working_hours_test_data_path()) ilo_employment_data <- read.csv(file = MWTools::ilo_employment_test_data_path())

preparedILOData <- MWTools::prepareRawILOData(ilo_working_hours_data = ilo_working_hours_data, ilo_employment_data = ilo_employment_data)

hmw_pfu_data <- MWTools::calc_hmw_pfu(.df = preparedILOData, concordance_path = MWTools::fao_concordance_path(), hmw_analysis_data_path = MWTools::hmw_analysis_data_path()) tibble::glimpse(hmw_pfu_data)

### PSUT matrices

PFU data can be converted to PSUT matrices using `prep_psut()`.

```r
mw_psut <- MWTools::prep_psut(.hmw_df = hmw_pfu_data,
                              .amw_df = amw_pfu_data)
tibble::glimpse(mw_psut)

Conclusion

The functions in the MWTools package can streamline and assist inclusion of animal and human muscle work in societal exergy analysis.

EnergyEconomyDecoupling/MWTools documentation built on April 14, 2025, 9:27 a.m.