Tilbage

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Delmål 13: Klimaindsats

Emissionsopgørelse fra DCE

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GS Emission af drivhusgasser efter sektor

# Import
ENX1EM1_raw <-
  read_csv(
    paste0("https://bank.stat.gl:443/sq/53af71be-9a37-48a3-983c-e98720f29d40.csv", "?lang=", language),
    locale = locale(encoding = "latin1"))

# Transform
ENX1EM1 <- 
  ENX1EM1_raw %>% 
  rename(
    "gas"    = 1,
    "sector" = 2,
    "time"   = 3,
    "value"  = 4
  ) %>% 
  mutate(
    gas    = gas %>% fct_inorder() %>% fct_rev(),
    time   = time %>% make_date(),
    value  = value / 1000
  )

# Plot
ENX1EM1 %>% 
  ggplot(aes(
    x    = time,
    y    = value,
    fill = gas
  )) +
  geom_col() +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE) +
  labs(
    title    = sdg13$figs$fig1$title[language],
    subtitle =  ENX1EM1[[2]][1],
    x        = " ",
    y        = sdg13$figs$fig1$y_lab[language],
    fill     = sdg13$figs$fig1$fill[language],
    caption  = sdg13$figs$fig1$cap[language]
  )

Statistikbanken

Metode

Rapport

Vis tabel

# Transform
ENX1EM1 <- 
  ENX1EM1_raw %>% 
  rename(
    "gas"    = 1,
    "sector" = 2,
    "time"   = 3,
    "value"  = 4
  ) %>% 
  mutate(
    gas    = gas %>% fct_inorder() %>% fct_rev(),
    value  = value / 1000,
    value  = round(value, 3)
  ) %>% 
  filter(time >= year(Sys.time()) - 8) %>% 
  spread(1, ncol(.)) %>% 
  arrange(desc(time))

# Table
ENX1EM1 %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table(year_col = " ") %>% 
  pack_rows(index = table(ENX1EM1[[1]])) %>% 
  add_footnote(sdg13$figs$fig1$foot[language], notation = "symbol")

	SF6	HFC	Lattergas N2O	Metan CH4	Kuldioxid CO2
Samlet nettoemission
2021	0,003	12,98	11,04	14,5	568
2020	0,003	12,91	10,86	14,4	538
2019	0,003	11,11	10,75	14,3	557
2018	0,003	9,73	9,74	14,4	546
2017	0,003	10,08	9,79	14,3	545
2016	0,003	9,99	10,18	14,4	528
* Tusind ton C02-ækvivalenter

# Import
ENX1EM1_raw <-
  read_csv(
    paste0("https://bank.stat.gl:443/sq/ca6d79eb-6230-4f07-ba49-c486f6e1edd4.csv", "?lang=", language),
    locale = locale(encoding = "latin1"))


# Transform
ENX1EM1 <-
  ENX1EM1_raw %>% 
  rename(
    "time"   = 1,
    "gas"    = 2,
    "sector" = 3,
    "value"  = 4
  ) %>% 
  filter(sector != unique(ENX1EM1_raw[[3]])[5]) %>% 
  mutate(
    gas    = gas %>% fct_inorder() %>% fct_rev(),
    sector = sector %>% str_remove_all("[1-5]|\\.") %>% trimws(),
    sector = sector %>% fct_inorder(),
    value  = value / 1000
  )


ENX1EM1 %>% 
  ggplot(aes(
    x    = time,
    y    = value,
    fill = gas
  )) +
  geom_area() +
  facet_wrap(~ sector, scales = "free") +
   scale_y_continuous(labels = scales::unit_format(
    suffix       = " ",
    big.mark     = ".",
    decimal.mark = ","
  )) +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE) +
  labs(
    title   = sdg13$figs$fig2$title[language],
    x       = " ",
    y       = sdg13$figs$fig2$y_lab[language],
    fill    = str_to_title(colnames(ENX1EM1_raw)[2]),
    caption = sdg13$figs$fig2$cap[language]
  )

Statistikbanken

Metode

Rapport

Vis tabel

# Transform
ENX1EM1 <-
  ENX1EM1_raw %>% 
  rename(
    "time"   = 1,
    "gas"    = 2,
    "sector" = 3,
    "value"  = 4
  ) %>% 
  filter(
    sector != unique(ENX1EM1_raw[[3]])[5],
    time >= year(Sys.time())- 8,
    value != 0) %>% 
  mutate(
    gas    = gas %>% fct_inorder() %>% fct_rev(),
    sector = sector %>% str_remove_all("[1-5]|\\.") %>% trimws(),
    sector = sector %>% fct_inorder(),
    value  = value / 1000
  ) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>% factor(levels = unique(time))) %>% 
  spread(1, ncol(.)) %>% 
  arrange(sector)

# Table
ENX1EM1 %>% 
  select(-2) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = table(ENX1EM1[[2]])) %>% 
  add_footnote(sdg13$figs$fig2$foot[language],
               notation = "symbol")

	2016	2017	2018	2019	2020	2021
Emission fra energiforbrug
Lattergas N2O	2,481	2,545	2,585	2,726	2,501	2,653
Metan CH4	1,242	1,263	1,273	1,303	1,301	1,338
Kuldioxid CO2	522,545	539,657	540,255	550,961	532,904	562,527
Industrielle processer
SF6	0,003	0,003	0,003	0,003	0,003	0,003
HFC	9,994	10,078	9,733	11,108	12,910	12,979
Lattergas N2O	0,001	0,001	0,001	0,001	0,001	0,001
Metan CH4	0,001	0,001	0,001	0,001	0,001	0,001
Kuldioxid CO2	0,696	0,721	0,949	1,014	0,854	0,715
Emission fra landbrug
Lattergas N2O	2,306	1,830	1,611	2,354	2,482	2,671
Metan CH4	6,453	6,327	6,459	6,327	6,426	6,451
Kuldioxid CO2	0,004	0,004	0,004	0,004	0,004	0,004
Emission fra affaldshåndtering
Lattergas N2O	5,340	5,358	5,493	5,617	5,824	5,662
Metan CH4	6,682	6,675	6,677	6,681	6,686	6,695
Kuldioxid CO2	3,361	3,385	3,409	3,427	3,450	3,474
* Tusind ton CO2-ækvivalenter

Nøgletal for emission af drivhusgasser fra energiforbrug

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GS Nøgletal for emission af drivhusgasser fra energiforbrug

# Import
url <- "https://bank.stat.gl:443/api/v1/da/Greenland/EN/EN20/ENX6KEY.px"

ENX6KEY_raw <- 
  url |> 
  statgl_fetch(
    "key figure" = 18:20,
    time         = px_all(),
    .col_code    = T
  ) |> 
  as_tibble()
  

# Transform
ENX6KEY <- 
  ENX6KEY_raw |> 
  rename(key = `key figure`) |> 
  mutate(time = as.numeric(time))



# Plot
ENX6KEY |> 
  ggplot(aes(
    x = time,
    y = value,
    color = key
  )) +
  geom_line(size = 2) +
  facet_wrap(~ key, nrow = 3, scales = "free_y") +
  theme_statgl() +
  scale_color_statgl() +
  theme(legend.position = "none") +
  labs(
    title    = sdg13$figs$fig5$title[language],
    subtitle = sdg13$figs$fig5$sub[language],
    y        = " ",
    x        = " ",
    caption  = sdg13$figs$fig5$cap[language]
  )

Statistikbanken

Vis tabel

#Table
ENX6KEY %>% 
  filter(time >= year(Sys.time()) - 8) %>% 
  mutate(time = time %>% factor(levels = unique(time))) %>% 
  spread(time, value) %>% 
  rename(" " = 1) %>% 
  statgl_table(replace_0s = TRUE)

	2016	2017	2018	2019	2020	2021	2022
Faktisk emission i alt [1.000 ton CO2e]	526,3	543,5	544,1	555,0	536,7	566,5	613,6
Faktisk emission i alt pr. indbygger [ton CO2e]	9,4	9,7	9,7	9,9	9,5	10,0	10,8
Faktisk emission pr. BNP-enhed [ton CO2e pr. mio. BNP]	35,5	36,8	36,5	36,3	34,8	36,5	NA