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Goal 13: Climate action

Emission statement from DCE

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GS Greenhouse gas emission by sector

# 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]
  )

StatBank

Method

Report

Show table

# 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	Nitrous oxide N2O	Methan CH4	Carbondioxid CO2
Total (net emissions)
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
* 1000 tons of CO2 equivalents

# 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]
  )

StatBank

Method

Report

Show table

# 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
Emissions from fuel combustion
Nitrous oxide N2O	2,481	2,545	2,585	2,726	2,501	2,653
Methan CH4	1,242	1,263	1,273	1,303	1,301	1,338
Carbondioxid CO2	522,545	539,657	540,255	550,961	532,904	562,527
Industrial Processes
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
Nitrous oxide N2O	0,001	0,001	0,001	0,001	0,001	0,001
Methan CH4	0,001	0,001	0,001	0,001	0,001	0,001
Carbondioxid CO2	0,696	0,721	0,949	1,014	0,854	0,715
Agriculture
Nitrous oxide N2O	2,306	1,830	1,611	2,354	2,482	2,671
Methan CH4	6,453	6,327	6,459	6,327	6,426	6,451
Carbondioxid CO2	0,004	0,004	0,004	0,004	0,004	0,004
Waste
Nitrous oxide N2O	5,340	5,358	5,493	5,617	5,824	5,662
Methan CH4	6,682	6,675	6,677	6,681	6,686	6,695
Carbondioxid CO2	3,361	3,385	3,409	3,427	3,450	3,474
* 1000 tons of CO2 equivalents

Key figures on greenhouse gas emissions from energy consumption

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GS Key figures on greenhouse gas emissions from energy consumption

# 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]
  )

StatBank

Show table

#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