Code
out
Output
# A tibble: 68 x 6
sector year region scenario_source emission_factor_metric emission_factor_v~
<chr> <dbl> <chr> <chr> <chr> <dbl>
1 cement 2020 global demo_2020 projected 1
2 cement 2021 global demo_2020 projected 2
3 cement 2022 global demo_2020 projected 3
4 cement 2020 global demo_2020 corporate_economy 1
5 cement 2021 global demo_2020 corporate_economy 2
6 cement 2022 global demo_2020 corporate_economy 3
7 cement 2020 global demo_2020 target_b2ds 1
8 cement 2021 global demo_2020 target_b2ds 0.978
9 cement 2022 global demo_2020 target_b2ds 0.956
10 cement 2023 global demo_2020 target_b2ds 0.933
# ... with 58 more rows
Code
out_company
Output
# A tibble: 68 x 7
sector year region scenario_source name_abcd emission_factor_metric
<chr> <dbl> <chr> <chr> <chr> <chr>
1 cement 2020 global demo_2020 shaanxi auto projected
2 cement 2021 global demo_2020 shaanxi auto projected
3 cement 2022 global demo_2020 shaanxi auto projected
4 cement 2020 global demo_2020 market corporate_economy
5 cement 2021 global demo_2020 market corporate_economy
6 cement 2022 global demo_2020 market corporate_economy
7 cement 2020 global demo_2020 shaanxi auto target_b2ds
8 cement 2021 global demo_2020 shaanxi auto target_b2ds
9 cement 2022 global demo_2020 shaanxi auto target_b2ds
10 cement 2023 global demo_2020 <NA> target_b2ds
# ... with 58 more rows, and 1 more variable: emission_factor_value <dbl>
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