File:Greenhouse gas emission and absorption by Turkey.svg

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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()

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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