MWTools

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 et al. (2022) 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, Owen, and Brockway (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)
#> Rows: 2,232
#> Columns: 7
#> $ Country <chr> "CHNM", "CHNM", "CHNM", "CHNM", "CHNM", "CHNM", "CHNM", "CHNM"…
#> $ Year    <dbl> 1960, 1960, 1960, 1960, 1960, 1960, 1960, 1960, 1960, 1960, 19…
#> $ Species <chr> "Asses", "Asses", "Asses", "Asses", "Asses", "Asses", "Buffalo…
#> $ Stage   <chr> "Useful", "Useful", "Final", "Final", "Primary", "Primary", "U…
#> $ Sector  <chr> "Agriculture", "Transport", "Agriculture", "Transport", "Agric…
#> $ Unit    <chr> "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "E…
#> $ E.dot   <dbl> 0.0006684719, 0.0037880073, 0.0102033866, 0.0578191910, 0.0226…

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.

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)
#> Rows: 1,098
#> Columns: 7
#> $ Country <chr> "GBR", "GBR", "GBR", "GBR", "GBR", "GBR", "GBR", "GBR", "GBR",…
#> $ Year    <dbl> 1960, 1960, 1960, 1960, 1960, 1960, 1960, 1960, 1960, 1960, 19…
#> $ Species <chr> "Human females", "Human females", "Human females", "Human fema…
#> $ Stage   <chr> "Final", "Final", "Final", "Primary", "Primary", "Primary", "U…
#> $ Sector  <chr> "Agriculture", "Industry", "Services", "Agriculture", "Industr…
#> $ Unit    <chr> "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "EJ", "E…
#> $ E.dot   <dbl> 8.681814e-04, 1.539860e-02, 2.819406e-02, 1.400293e-03, 2.4836…

PSUT matrices

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

mw_psut <- MWTools::prep_psut(.hmw_df = hmw_pfu_data,
                              .amw_df = amw_pfu_data)
tibble::glimpse(mw_psut)
#> Rows: 246
#> Columns: 13
#> $ Country     <chr> "CHNM", "CHNM", "CHNM", "CHNM", "CHNM", "CHNM", "CHNM", "C…
#> $ Year        <dbl> 1960, 1960, 1961, 1961, 1962, 1962, 1963, 1963, 1964, 1964…
#> $ Method      <chr> "PCM", "PCM", "PCM", "PCM", "PCM", "PCM", "PCM", "PCM", "P…
#> $ Energy.type <chr> "E", "E", "E", "E", "E", "E", "E", "E", "E", "E", "E", "E"…
#> $ Last.stage  <chr> "Final", "Useful", "Final", "Useful", "Final", "Useful", "…
#> $ R           <list> <matrix[1 x 1]>, <matrix[1 x 1]>, <matrix[1 x 1]>, <matri…
#> $ U           <list> <<matrix[2 x 2]>>, <<matrix[3 x 14]>>, <<matrix[2 x 2]>>,…
#> $ V           <list> <<matrix[2 x 2]>>, <<matrix[14 x 14]>>, <<matrix[2 x 2]>>…
#> $ Y           <list> <<matrix[1 x 2]>>, <<matrix[12 x 2]>>, <<matrix[1 x 2]>>,…
#> $ S_units     <list> <<matrix[2 x 1]>>, <<matrix[4 x 1]>>, <<matrix[2 x 1]>>, …
#> $ U_feed      <list> <<matrix[2 x 2]>>, <<matrix[3 x 14]>>, <<matrix[2 x 2]>>,…
#> $ U_EIOU      <list> <<matrix[2 x 2]>>, <<matrix[3 x 14]>>, <<matrix[2 x 2]>>,…
#> $ r_EIOU      <list> <<matrix[2 x 2]>>, <<matrix[3 x 14]>>, <<matrix[2 x 2]>>,…

Conclusion

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

Heun, Matthew Kuperus, Anne Owen, and Paul E. Brockway. 2018. “A Physical Supply-Use Table Framework for Energy Analysis on the Energy Conversion Chain.” Applied Energy 226 (September): 1134–62. https://doi.org/10.1016/j.apenergy.2018.05.109.

Steenwyk, Paul, Matthew Kuperus Heun, Paul Brockway, Tânia Sousa, and Sofia Henriques. 2022. “The Contributions of Muscle and Machine Work to Land and Labor Productivity in World Agriculture Since 1800.” Biophysical Economics and Sustainability 7 (2): 1–17. https://doi.org/10.1007/s41247-022-00096-z.