Utertiguk

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Anguniagaq 13: Silap pissusia suliniuteqarfigalugu

DCE-mit nukissiuutinik atuinermi silaannarmik mingutsitsisumik aniatitsinermik naatsorsuutit

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GS Nukissiuutinik atuinermi silaannarmik mingutsitsisumik aniatitsineq suliaqarfik malillugu

# 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]
  )

Kisitsisaataasivik

Periaaseq

Rapport

Tabel nuisiguk

# 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	Lattergassi N2O	Metani CH4	Kuldioxidi CO2
Gassimik silaannarmik kissattoortitsisussamik aniatitsineq tamakkiisumik
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
* CO2-mik aniatitsineq tonsinngorlugu tuusintikkaartunik.

# 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]
  )

Kisitsisaataasivik

Periaaseq

Rapport

Tabel nuisiguk

# 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
Nukimmik atuineq
Lattergassi N2O	2,481	2,545	2,585	2,726	2,501	2,653
Metani CH4	1,242	1,263	1,273	1,303	1,301	1,338
Kuldioxidi CO2	522,545	539,657	540,255	550,961	532,904	562,527
Suliffissuaqarnermi atortussiassat kemiimi akulerunnerat
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
Lattergassi N2O	0,001	0,001	0,001	0,001	0,001	0,001
Metani CH4	0,001	0,001	0,001	0,001	0,001	0,001
Kuldioxidi CO2	0,696	0,721	0,949	1,014	0,854	0,715
Nunalerineq
Lattergassi N2O	2,306	1,830	1,611	2,354	2,482	2,671
Metani CH4	6,453	6,327	6,459	6,327	6,426	6,451
Kuldioxidi CO2	0,004	0,004	0,004	0,004	0,004	0,004
Eqqakkanik aqutsineq
Lattergassi N2O	5,340	5,358	5,493	5,617	5,824	5,662
Metani CH4	6,682	6,675	6,677	6,681	6,686	6,695
Kuldioxidi CO2	3,361	3,385	3,409	3,427	3,450	3,474
* CO2-mik aniatitsineq 1000 tonsinngorlugu

Gassimik silaannarmik kissattoortitsisussamik nukissiuutinik atuinernit anitsinermit atuinermi kisitsisit pingaarnerit

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GS Gassimik silaannarmik kissattoortitsisussamik nukissiuutinik atuinernit anitsinermit atuinermi kisitsisit pingaarnerit

# 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]
  )

Kisitsisaataasivik

Tabel nuisiguk

#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