Fixes for IEA Data
Matthew Kuperus Heun
2024-12-09
fix_iea_data.Rmd
Introduction
Some data in the IEA extended energy balances is incomplete or
incorrect. The IEATools
package provides functions to fix
the incomplete or incorrect data. These fixes emerge from detailed
country studies that lead to academic papers.
The fixes
At present, there are two fixes to IEA data.
Ghana Primary solid biofuels
Ghana’s Primary solid biofuels data show a very large and dramatic
decline from 1999 to 2000. This decline is due to new survey data being
used for the 2000 data.
When we look at the PSB data on a per-capita basis, it is clear that a
near-constant PSB/capita value was used to extrapolate per-capita usage
in the late 1990s. When new survey data became available for the 2000
reporting year, the per-capita consumption of PSB obviously
changed.
Our approach to this problem is to smooth out the large peak in PSB
consumption by reducing the per-capita consumption of PSB in the years
1991–1999. See the Supplementary material (especially section S2.7)
for
M. K. Heun and P. E. Brockway. Meeting 2030 primary energy and economic growth goals: Mission impossible? Applied Energy, 251(112697):1–24, May 2019
for additional details. See (http://www.doi.org/10.1016/j.apenergy.2019.01.255).
An example data frame can be constructed from the example data
supplied with this package using load_tidy_iea_df()
. We
pretend that 1971 is 1991 and 2000 is 1992.
example_tidy_iea_df <- load_tidy_iea_df() %>%
dplyr::filter(Country == "GHA") %>%
dplyr::filter(Product == "Primary solid biofuels") %>%
dplyr::mutate(
Year := dplyr::case_when(
Year == 1971 ~ 1991,
Year == 2000 ~ 1992
)
)
example_tidy_iea_df %>%
dplyr::filter(Product == "Primary solid biofuels") %>%
dplyr::select(Year, FlowAggregationPoint, Flow, Edot, Unit)
#> # A tibble: 10 × 5
#> Year FlowAggregationPoint Flow Edot Unit
#> <dbl> <chr> <chr> <dbl> <chr>
#> 1 1991 Total primary energy supply Production 87400. TJ
#> 2 1992 Total primary energy supply Production 162909. TJ
#> 3 1991 Transformation processes Charcoal production plants -20000. TJ
#> 4 1992 Transformation processes Charcoal production plants -45804. TJ
#> 5 1991 Industry Industry not elsewhere speci… 6100. TJ
#> 6 1992 Industry Industry not elsewhere speci… 28691. TJ
#> 7 1991 Other Residential 61300. TJ
#> 8 1992 Other Residential 84667. TJ
#> 9 1992 Other Commercial and public servic… 3630. TJ
#> 10 1992 Other Agriculture/forestry 117. TJ
fixed <- example_tidy_iea_df %>%
fix_GHA_psb()
Comparing production of Primary solid biofuels in 1991 shows that production rates have changed.
example_tidy_iea_df %>%
dplyr::filter(Year == 1991, Flow == "Production") %>%
dplyr::select("Edot", "Unit")
#> # A tibble: 1 × 2
#> Edot Unit
#> <dbl> <chr>
#> 1 87400. TJ
fixed %>%
dplyr::filter(Year == 1991, Flow == "Production") %>%
dplyr::select("Edot", "Unit")
#> # A tibble: 1 × 2
#> Edot Unit
#> <dbl> <chr>
#> 1 168519. TJ
The private object Fixed_GHA_PSB
contains the
replacement Primary solid biofuels data.