File:Greenhouse gas emission and absorption by Turkey.svg

Size of this PNG preview of this SVG file: 576 × 432 pixels. Other resolutions: 320 × 240 pixels | 640 × 480 pixels | 1,024 × 768 pixels | 1,280 × 960 pixels | 2,560 × 1,920 pixels.

Original file ‎(SVG file, nominally 576 × 432 pixels, file size: 56 KB)

This is a file from the Wikimedia Commons. Information from its description page there is shown below.
Commons is a freely licensed media file repository. You can help.

Summary

Description

English: Greenhouse gas emission and absorption by Turkey by year from 1990

Date

22 April 2020

Source

Data from https://di.unfccc.int/detailed_data_by_party

Author

Chidgk1

SVG development

The SVG code is valid.

This plot was created with Matplotlib.

Source code

Python code

Source code

lang = "en"
#lang = "tr"

import numpy as np
import matplotlib.pyplot as plt
import sys
import pandas as pd
import seaborn as sns

# DATA - UPDATE EACH YEAR AND PUT NEW VERSION OF THIS AS CODE ON https://commons.wikimedia.org/wiki/File:Greenhouse_gas_emission_and_absorption_by_Turkey.svg

#Labelling all the years is a bit busy so just label some
numyears=(np.arange(32)) #ADD 1 TO THIS WHEN YOU ADD A YEAR
xyears=['1990','','','','','1995','','','','','2000','','','','','2005','','','','','2010','','','','','2015','','','','','2020','2021']

#Please add population from Turkstat "Population by Years"
#The resulting GhG per person per year graph can be checked against that in Turkstat press releases

population = (53921760, 54840590,  64729501, 55748948, 56653804, 57564204, 58486456, 59423282, 60372568, 61329676, 62287397, 64729502, 64729503, 64729504, 68010215, 68860539, 69729967, 70586256, 71517100, 72561312, 73722988, 74724269, 75627384, 76667864, 77695904, 78741053, 79814871, 80810525, 82003882, 83154997, 83614362, 84680273)

# Data from https://di.unfccc.int/detailed_data_by_party
# Select Turkey, All Years, Totals, Aggregate GHG, Mt CO2 equivalent
# Cut and paste in here: 'Total GHG emissions excluding LULUCF'
# Older figures are sometimes revised so worth recopying them all occasionally - last copied April 2022 but only 2015 onwards
# However new data is likely to be released first in a press release by Turkstat which cannot easily be copied and pasted
year =       ('1990','1991','1992','1993','1994','1995','1996','1997','1998','1999','2000','2001','2002','2003','2004','2005','2006','2007','2008','2009','2010','2011','2012','2013','2014','2015','2016','2017','2018','2019','2020','2021')

CO2 =         [151.5, 158.0, 163.9, 171.0, 167.4, 180.9, 199.5, 212.0, 212.0, 207.8, 229.8, 213.5, 221.0, 236.5, 244.5, 264.2, 281.6, 312.7, 309.3, 315.4, 314.4, 339.5, 353.7, 345.2, 361.7, 384.3, 405.3, 430.2, 422.6, 401.7, 413.4, 452.7]
CH4_CO2eq =   [ 42.5,  43.4,  43.3,  43.1,  42.8,  42.6,  43.0,  42.2,  42.4,  43.8,  43.7,  42.9,  41.0,  43.0,  43.5,  45.2,  46.6,  49.0,  49.9,  49.6,  51.4,  53.7,  57.1,  55.5,  57.5,  52.8,  55.6,  56.8,  60.3,  63.1,  64.0,  64.0]
N2O_CO2eq =   [ 25.0,  24.7,  25.3,  26.0,  23.6,  23.9,  24.5,  24.0,  25.3,  25.6,  24.8,  23.3,  23.3,  24.6,  25.4,  26.2,  28.4,  27.6,  26.2,  28.5,  29.8,  30.9,  32.1,  34.1,  34.6,  32.3,  34.4,  35.6,  35.5,  37.0,  40.5,  40.3]
Fgases_CO2eq = [ 0.6,   0.9,   0.7,   0.4,   0.7,   0.6,   0.6,   0.6,   0.6,   0.6,   0.7,   0.8,   1.0,   1.2,   1.5,   1.7,   1.9,   2.3,   2.4,   2.4,   3.6,   4.0,   4.7,   4.8,   5.3,   5.1,   5.5,   5.7,   5.6,   6.3,   6.0,   7.4]

# Probably will not be in press release. Don't forget minus signs when copying and pasting fron National Inventory Report - probably in Table ES 3 Greenhouse gas emissions by sectors
LULUCF =      [-55.7,   -56.7,  -56.9,  -56.1,  -57.6,  -57.4,  -57.6,  -61.7,  -62.7,  -64.1,  -61.6,  -64.9,  -72.6,  -74.6,  -73.7,  -74.5,  -74.8,  -74.5,  -69.5,  -73.2,  -73.6,  -77.5,  -74.8,  -76.9,  -77.9,  -97.5,  -96.0,  -99.8,  -94.4,  -84.0,  -56.9,  -47.1] 

# CALCULATION

# Could not see how to add more than 2 arrays
GHG_exc_LULUCF = np.add(CO2,CH4_CO2eq).tolist()
GHG_exc_LULUCF = np.add(GHG_exc_LULUCF,N2O_CO2eq).tolist()
GHG_exc_LULUCF = np.add(GHG_exc_LULUCF,Fgases_CO2eq).tolist()
# delete this? GHG_net =     [163.4, 169.9, 175.9, 184.1, 176.7, 190.2, 209.5, 216.9, 217.7, 213.7, 237.3, 215.7, 213.6, 231.0, 241.3, 262.5, 283.4, 317.0, 318.4, 322.7, 325.2, 350.5, 372.5, 362.5, 380.5, 375.3, 401.8, 423.9, 426.4, 422.1, ]

# Therefore add don't subtract - alternatively could just copy and paste from NIR
GHG_inc_LULUCF =     np.add(GHG_exc_LULUCF, LULUCF).tolist()
# left over from previous code - maybe can use to check GHG_exc_LULUCF_old =  [219.20,226.58,232.80,240.15,234.13,247.58,267.23,278.61,280.29,277.76,298.89,280.41,286.07,305.60,314.95,337.21,358.15,391.42,387.59,395.52,398.66,427.57,446.94,438.97,457.96,472.19,498.47,523.8,520.9]

# EMISSION AND ABSORPTION BAR GRAPH

#Dataframe 1 for the bars
df1 = pd.DataFrame({'GHG_exc_LULUCF': GHG_exc_LULUCF,  'LULUCF': LULUCF}, index=year)

#Dataframe 2 for the line
df2 = pd.DataFrame({'GHG_inc_LULUCF': GHG_inc_LULUCF}, index=year)

ax=df1.plot(kind='bar', stacked=True, color = ['grey', 'green'])

df2.plot(ax=ax)

#Avoid chopping off xlabel at bottom
plt.gcf().subplots_adjust(bottom=0.15)

#Label years
plt.xticks(ticks=numyears, labels=xyears)
#Vertical years so we can see which bar is which year 
plt.xticks(rotation=90)
#Don't need the frame
sns.despine(bottom = True, left = True)
#Don't need the dash marks
ax.tick_params(left=False, bottom=False)

if lang == "en":
 ax.set_title ("Greenhouse gases emitted in Turkey", fontsize = 'xx-large')
 ax.set_ylabel("Million metric tons of carbon dioxide equivalent")
# ax.figure.text(0.99, 0.01, 'Source: https://di.unfccc.int/detailed_data_by_party', ha='right', va='bottom', fontsize='small', color='grey')
 ax.set_xlabel('Source: https://di.unfccc.int/detailed_data_by_party', fontsize = 'small', color = 'grey')
 plt.legend(['Net emissions', 'Emissions:  mostly by fossil fuels','Absorption: mostly by forests'])
elif lang == "tr":
 ax.set_title ("Türkiye’de sera gazı emisyonu", fontsize = 'xx-large')
 ax.set_ylabel("Milyon ton karbon dioksit eşdeğer")
 ax.set_xlabel('Kaynak: https://di.unfccc.int/detailed_data_by_party', fontsize = 'small', color = 'grey')
 plt.legend(['net emisyonlar', 'emisyonlar: en çok fosil yakıt','emme:         en çok orman'])
else:
 print("Unknown language " + lang)
 sys.exit()

# Save graphic
if lang == "en":
 plt.savefig("Greenhouse gas emission and absorption by Turkey.svg")
elif lang == "tr":
 plt.savefig("sera_gazlar_Türkiye_emisyon_emme.svg")
else:
 print("Unknown language " + lang)
 sys.exit()  

# Show graphic
plt.show()

# GASES LINE GRAPH

color_CO2    = "black"
color_CH4    = "brown"
color_N2O    = "khaki"
color_Fgases = "pink"

plt.plot(year, CO2,          color=color_CO2) 
plt.plot(year, CH4_CO2eq,    color=color_CH4)
plt.plot(year, N2O_CO2eq,    color=color_N2O)
plt.plot(year, Fgases_CO2eq, color=color_Fgases)

#Avoid chopping off xlabel at bottom
plt.gcf().subplots_adjust(bottom=0.15)

#Label years
plt.xticks(ticks=numyears, labels=xyears)
#Vertical years as otherwise may overlap 
plt.xticks(rotation=90)
#Don't need the left part of frame
sns.despine(left = True)
#Don't need the dash marks
plt.tick_params(left=False, bottom=False)
#Start at zero to show how small f-gas is
plt.ylim(0)

#Chemical formula to label lines are same all languages
label_CO2    = "CO₂"
label_CH4    = "CH₄"
label_N2O    = "N₂O"

if lang == "en":
 plt.title ("Greenhouse gases emitted in Turkey",fontsize = 'x-large')
 plt.ylabel("Million metric tons of carbon dioxide equivalent")
 plt.xlabel('Source: https://di.unfccc.int/detailed_data_by_party', fontsize = 'small', color = 'grey')
 label_Fgases = "F-gases"
elif lang == "tr":
 plt.title ("Türkiye'de atmosfere giden karbondioksit eşdeğer",fontsize = 'x-large')
 plt.ylabel("Megatonne")
 plt.xlabel('Kaynak: https://di.unfccc.int/detailed_data_by_party', fontsize = 'small', color = 'grey')
 label_Fgases = "F-gazlar"
else:
 print("Unknown language: " + lang)
 sys.exit()

#Position labels manually to make them quicker to read than a legend in a corner - might need slight adjustment as years added
plt.text(32,445,label_CO2,    fontsize = 'large')
plt.text(32, 60,label_CH4,    fontsize = 'large')
plt.text(32, 30,label_N2O,    fontsize = 'large')
plt.text(32,  5,label_Fgases, fontsize = 'large')

# Save graphic
if lang == "en":
 plt.savefig("ghg_gases_by_year_Turkey.svg")
elif lang == "tr":
 plt.savefig("sera_gazlar_Türkiye.svg")
else:
 print("Unknown language " + lang)
 sys.exit()  

# Show graphic
plt.show()

# PER PERSON LINE GRAPH

pop_millions = np.divide(population,1000000)
GHG_inc_LULUCF_per_person = np.divide(GHG_inc_LULUCF,pop_millions)
GHG_exc_LULUCF_per_person = np.divide(GHG_exc_LULUCF,pop_millions)

plt.plot(year, GHG_inc_LULUCF_per_person)
plt.plot(year, GHG_exc_LULUCF_per_person)

#Label years
plt.xticks(ticks=numyears, labels=xyears)
#Vertical years so we can see which year is which 
plt.xticks(rotation=90)
#Don't need the frame
sns.despine(bottom = True, left = True)
#Don't need the dash marks
plt.tick_params(left=False, bottom=False)
#Start at zero to show that eventually country should go to net zero
plt.ylim(0)

if lang == "en":
 plt.title ("Greenhouse gases emitted per person in Turkey",fontsize = 'x-large')
 plt.ylabel("Tonnes")
 plt.xlabel('Source: https://di.unfccc.int/detailed_data_by_party', fontsize = 'small', color = 'grey')
 label_inc_LULUCF   = "Inc. LULUCF"
 label_exc_LULUCF = "Exc. LULUCF"
elif lang == "tr":
 plt.title ("Türkiye'de atmosfere giden karbondioksit kişi başı",fontsize = 'x-large')
 plt.ylabel("Tonne")
 plt.xlabel('Kaynak: https://di.unfccc.int/detailed_data_by_party', fontsize = 'small', color = 'grey')
 label_inc_LULUCF   = "net"
 label_exc_LULUCF = "brut"
else:
 print("Unknown language: " + lang)
 sys.exit()

#Position labels manually to make them quicker to read than a legend in a corner - might need slight adjustment as years added
plt.text(32, 6.1 ,label_inc_LULUCF, fontsize = 'large')
plt.text(32, 6.5 ,label_exc_LULUCF, fontsize = 'large')

#Avoid chopping off xlabel at bottom
plt.tight_layout()

# Save graphic
if lang == "en":
 plt.savefig("ghg_per_person_Turkey.svg")
elif lang == "tr":
 plt.savefig("sera_gazlar_Türkiye_kişi_başı.svg")
else:
 print("Unknown language " + lang)
 sys.exit()  

# Show graphic
plt.show()

Licensing

I, the copyright holder of this work, hereby publish it under the following license:

This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.

You are free:

to share – to copy, distribute and transmit the work
to remix – to adapt the work

Under the following conditions:

attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.

File history

Click on a date/time to view the file as it appeared at that time.

	Date/Time	Dimensions	User	Comment
current	09:41, 15 April 2023	576 × 432 (56 KB)	Chidgk1	added 2021
	08:42, 16 April 2022	576 × 432 (55 KB)	Chidgk1	added 2020
	08:29, 14 April 2021	576 × 432 (55 KB)	Chidgk1	added 2019
	08:50, 19 March 2021	576 × 432 (57 KB)	Chidgk1	make easier to read by bigger heading and fewer year labels
	12:19, 31 January 2021	576 × 432 (66 KB)	Chidgk1	added more years
	06:03, 16 May 2020	576 × 432 (32 KB)	Chidgk1	increased font size to 14 to match other diags in ghg article
	08:26, 15 May 2020	576 × 432 (32 KB)	Chidgk1	Increased font size slightly as text was hard to read
	14:26, 22 April 2020	576 × 432 (34 KB)	Chidgk1	Uploaded own work with UploadWizard