The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of Argentina, Thailand and Czech Republic (ranked 31st, 32nd and 33rd). The share of Argentina is increasing while the share of Thailand has flattened out.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of Austria, Indonesia and Venezuela (ranked 28th, 29th and 30th). In 2015, the shares of each of the three countries were 0.40 or 0.41% of global Climate Debt.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of Poland, Belgium and Brazil (ranked 25th, 26th and 27th). By 2015, the shares of the three countries were similar. Since then, the Polish performance has declined, relatively.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of Kazakhstan, Mexico and South Africa (ranked 22nd, 23rd and 24th). Kazakhstan’s share increased dramatically in a short period of time due to growing Fossil CO2 Emissions.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of Oman, Netherlands and Turkey (ranked 19th, 20th and 21st). The share Netherlands is decreasing steadily, whereas Turkey’s is increasing.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of the United Kingdom, Spain and Malaysia (ranked 16th, 17th and 18th). The shares of the United Kingdom and Spain are decreasing, while the Malaysian share is increasing.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of France, United Arab Emirates and Italy (ranked 13th, 14th and 15th). The share of United Arab Emirates has increased along with an extreme population growth.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of Qatar, Iran and Kuwait (ranked 10th, 11th and 12th). The share of Qatar has increased fast along with the extreme population growth. All three countries seem to have peaked on global shares around 2015.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of South Korea, Australia and Germany (ranked 7th, 8th and 9th). The South Korean share is stable over time, Australia’s is decreasing although at a slower rate lately, while Germany’s is increasing.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of Canada, Russia and Saudi Arabia (ranked 4th, 5th and 6th). Canada’s share is decreasing, while Russia’s and Saudi Arabia’s are increasing. Global Climate Debt accumulated since 2000 is $7.2 Trillion.
The diagram below shows ‘Share of global Climate Debt‘ in 2010, 2015 and 2017, of the United States, Japan and China (ranked 1st, 2nd and 3rd). The shares of the United States and Japan are decreasing at slower rates lately, whereas China’s is increasing fast. Global Climate Debt accumulated since 2000 is $7.2 Trillion.
National per capita CO2 Emissions from Fossil Fuels (without bunkers) and industrial processes in 2016 have been released by ‘EDGAR‘. At the same time, recalculated historic emissions have been released, which for some countries make a considerable difference¹ (also with regard to Climate Debt in ClimatePositions). The updated calculations are available in ‘Calculation (Excel)‘, and new rankings of 163 countries are available in the menu “Climate Debt”.
The table below shows World average, and the 15 countries with the largest per capita CO2 Emissions from Fossil Fuels and industrial processes in 2016, in tons, in comparison with average emissions 1990-1999, 2000-2009 and 2010-2015.
In continuation of the previous article about aboveground forest carbon losses, the following is about soil carbon losses due to warming and agriculture, respectively.
Melillo et al. performed a ‘26-year soil-warming experiment‘ in a mid-latitude mixed hardwood forest with results published October 2017 in the peer-review journal Science. Some forest areas (plots) were heated up with underground cables to 5°C above normal levels, while other forest areas were left as a control. The experiment then documented changes in soil carbon cycling in the top 60 cm and investigated the possible consequences for the climate system.
A new ‘Study‘ from ‘Woods Hole Research Center‘ and Boston University reveals tropical forests now emit twice as much carbon than they capture. This is alarming news, since forests are the only carbon capture and storage “technology” that is safe, inexpensive and immediately available.
New approach to measuring forest carbon density using 1) satellite imagery 2003-2014, 2) laser remote sensing technology and 3) field measurements, were able to capture aboveground losses in forest carbon from full-scale deforestation as well as fine-scale degradation and disturbance. The latter has previously been a challenge to the scientific community over large areas. According to the study tropical forests in Americas, Africa and Asia are now releasing 425 (± 22%) teragrams (million tons) of carbon annually¹, equivalent to more than 4% (calculated by me) of global CO2 Emissions from Fossil Fuels and industrial processes. For perspectivation, global CO2 Emissions dropped 0.34% in 2016 compared to 2015.
UNs 17 ‘Sustainable Development Goals‘, or Global Goals, consist of simple headings with underlying ‘Clarifications and indicators‘ (pdf, 25 pages) that interact with each other in complex ways. The following examines the links between The Global Goals and greenhouse gas emissions.
Global Goal 13: “Take urgent action to combat climate change…”. The action is indicated by the number of countries that have communicated (..) an integrated policy/strategy/plan which increases their ability to (..) foster (..) low greenhouse gas emissions development in a manner that does not threaten food production.
In other words, the key action-instrument to ensure that global temperatures rise no more than 2°C is national plans to promote low emissions without reducing food production. Consequently, all goals related to food production will have to be included the survey.
In ClimatePositions Nuclear Power generation is not accepted as a national CO2 Emission reduction instrument and the generation must be phased out parallel to CO2 Emissions from Fossil Fuels and cement production¹.
The table below shows the Nuclear Power generation in billion kWh in 2014, 2015 and 2016, of all 32 countries and the world. The global generation 2016 was 2% higher than in 2015. However, the increase was caused sole by China’s 49% increase.
24 countries or administrative regions with populations larger than 100,000 are excluded from ClimatePositions due to incomplete ‘Indicator‘ data. However, approximate Climate Debts can be calculated by using assumptions of the missing values of: 1) GDP(ppp-$), 2) Environmental Performance, 3) Ecological Footprint (without Carbon Footprint), 4) Forest Cover, Primary Forest and Protected Waters.
First, the table below shows the estimated Climate Debt of the 24 countries or regions. Together, they represent 1.3% of the Population and 2.5% of the total Climate Debt of the 163 countries with full data in ClimatePositions (see the ‘Ranking‘). The estimated average Climate Debt of the 24 countries is $1,765 per capita compared to $905 of the 163 countries with full data.
The updated per capita Ecological Footprint¹ for 192 is available for licensing by ‘Global Footprint Network‘ (Public Data Package – Free Download). The average Ecological Footprint without the weighty Carbon Footprint², since 2005, is used as an ‘Indicator‘ in ClimatePositions when calculating national Climate Debts. The footprint-indicator includes: 1) Built-up Land, 2) Cropland, 3) Grazing Land, 4) Forest Product and 5) Fishing Ground, all allocated to the consumption components of Food, Shelter, Mobility, Goods and Services.
The relative per capita Ecological Footprints without carbon, over time, of the ‘90 countries with Climate Debt‘ are shown in the table below. An average country among 172 countries in ClimatePositions is set at 100. Note that the data-year is about 4 years prior to the release year.
As announced in the previous ‘Article‘ the calculations of Climate Debt by country in ClimatePositions has now been updated with CO2 Emissions data from ‘EDGAR‘ (European Commission), instead of data from Global Carbon Project (CDIAC).
At the same time, the global CO2 target has been raised by 0.2 tons per capita by 2025, and the indicators of Ecological Footprint (without carbon) and GDP (ppp-$) 2016 have been updated as well. New updated rankings are available in the menu “Climate Debt” above. Updated data and diagrams with all ‘Indicators‘ and all countries are available in the submenu ‘Calculations (Excel)‘.
The table below shows the new ranking of 163 countries in comparison with the previous (last) ranking (159 countries) with emission data from Global Carbon Project (CDIAC). No Climate Debt is marked “free”. Only Montenegro is excluded from the new ranking due to missing CO2 Emission data (ranks 69th in the previous ranking).
The Carbon Dioxide Information Analysis Center (CDIAC), located at the U.S. Department of Energy’s (DOE) Oak Ridge National Laboratory, has published annual Carbon Emissions from Fossil Fuels and cement production by country since 1959 (‘Global Carbon Project‘), but now this continuous time series has come to an end and 2015 will be the last data-year (as it seems).
Since carbon emissions data from CDIAC (Global Carbon Project) is the core ‘Indicator‘ in ClimatePositions’ calculation of Climate Debt, carbon emissions data will be replaced with nearly similar data from ‘EDGAR‘ (‘European Commission‘ / ‘Climate Action‘), retroactively since 1990, in connection with the coming updates [done 16-08-2017].
The following describes the differences between CO2 Emissions data from Global Carbon Project (CDIAC) and EDGAR (sourced: European Commission, Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency (PBL). Emission Database for Global Atmospheric Research (EDGAR)), and the consequences in terms of Climate Debt in ClimatePositions – illustrated with a range of country examples. Note that other sources, such as ‘IEA‘, ‘EIA‘ and ‘BP‘, provides CO2 Emissions data-sets different from the ones of CDIAC and EDGAR.