This article outlines how to show reduction targets for all
tilt_subsectors
per grouping_sector using product-level
output of Sector profile indicator.
Example subset of product-level output of Sector profile
sector_product_example <- product_sector |>
select(c("tilt_sector", "tilt_subsector", "scenario", "year", "reduction_targets")) |>
distinct()
kable(sector_product_example |> head(20))
construction |
construction residential |
1.5C RPS |
2030 |
0.18 |
construction |
construction residential |
1.5C RPS |
2050 |
0.98 |
construction |
construction residential |
NZ 2050 |
2030 |
0.40 |
construction |
construction residential |
NZ 2050 |
2050 |
0.97 |
metals |
other metals |
1.5C RPS |
2030 |
0.09 |
metals |
other metals |
1.5C RPS |
2050 |
0.95 |
metals |
other metals |
NZ 2050 |
2030 |
0.22 |
metals |
other metals |
NZ 2050 |
2050 |
0.96 |
metals |
iron & steel |
1.5C RPS |
2030 |
0.22 |
metals |
iron & steel |
1.5C RPS |
2050 |
0.96 |
metals |
iron & steel |
NZ 2050 |
2030 |
0.23 |
metals |
iron & steel |
NZ 2050 |
2050 |
0.94 |
Shows reduction targets for all tilt_subsectors per
grouping_sector
Reduction targets for all tilt_subsectors
per
grouping_sector
tilt_sector
|
tilt_subsector
|
IPR_2030
|
IPR_2050
|
WEO_2030
|
WEO_2050
|
construction
|
construction residential
|
0.18
|
0.98
|
0.40
|
0.97
|
metals
|
iron & steel
|
0.22
|
0.96
|
0.23
|
0.94
|
other metals
|
0.09
|
0.95
|
0.22
|
0.96
|