Carbon dioxide (CO2) is a gas essential for life—animals exhale it, plants sequester it. It exists in Earth’s atmosphere in comparably small concentrations, but is vital for sustaining life. CO2 is also known as a greenhouse gas (GHG)—a gas that absorbs and emits thermal radiation, creating the ‘greenhouse effect’. Along with other greenhouse gases, such as nitrous oxide and methane, CO2 is important in sustaining a habitable temperature for the planet: if there were absolutely no GHGs, our planet would simply be too cold. It has been estimated that without these gases, the average surface temperature of the Earth would be about -18 degrees celsius.1
Since the Industrial Revolution, however, energy-driven consumption of fossil fuels has led to a rapid increase in CO2 emissions, disrupting the global carbon cycle and leading to a planetary warming impact. Rising average temperatures may be hard to notice, but the consequences are wide-ranging and grave. With a warming planet, and an increase in energy stored in the atmosphere, we can expect a greater frequency of extreme weather events: floods, droughts, intense summer heat waves, and more violent storms. Meanwhile, melting ice sheets and glaciers combined with the expansion of warming sea water culminates in rising sea levels. How does all of this affect life on earth? In nature, it might mean an acceleration of already-speedy extinction rates. For humanity, consequences can arise in the form of disrupted water systems and food production, a rise in infectious diseases, displacement, and conflict. Strikingly, because of their geographic location and fewer resources, poorer countries will be—and in fact already are—disproportionately affected by climate change. In light of these facts, UN member parties have set a target of limiting average warming to 2 degrees celsius above pre-industrial temperatures.
This entry provides a historic through present day perspective of how CO2 emissions have evolved, how emissions are distributed, and the key factors that both drive these trends and hold the key to mitigating climate change.
To set the scene, let’s briefly look at how the planet has warmed since the Industrial Revolution. In the chart below, the x-axis shows the time spanning 1850 to 2013. On the y-axis, we see the global average temperature rise above or below the 1961-1990 baseline temperature. This means that we use the average temperature over the 1961-1990 period as a baseline against which yearly changes in temperature are measured.
The red line represents the average annual temperature trend through time while the blue line represents the decadal smoothed mean. We can see that during the period 1850-1940, temperatures were lower than the baseline—the anomaly is therefore negative. By 2013, the temperature rise reached approximately 0.5 degrees celsius above the 1961-1900 baseline. Since the anomaly in 1850 was approximately 0.3 degrees celsius below the baseline, the total temperature change since pre-industrial times was approximately 0.8 degrees celsius.
In our interactive chart, we have extended this dataset to 2017, showing a range from 1948-2017. Here, the red line represents global average warming as before, with the grey lines representing the upper and lower 95% certainty bounds. We see that over the last few years, temperatures have risen sharply. Combining the 0.8 degrees celsius increase since our 1961-1990 baseline, with the 0.3 degrees increase since 1850, average temperature increase since pre-industrial times has now surpassed the one-degree mark. This is an important marker as it brings us halfway to the global limit of keeping warming below two degrees celsius.
# Empirical View
The long-run history: Cumulative CO2
If we extend our timeline back to 1750 and total up how much CO2 each country has emitted to date, we calculate each nation’s ‘cumulative emissions’.
In the chart below, we have plotted the cumulative emissions of each nation through time from the industrial revolution in 1750. The UK was the world’s first industrial-scale CO2 emitter. Emissions in other European countries and North America shortly followed and produced CO2 over the majority of this time period. Other regions—Latin America, Asia and Africa—started contributing to global CO2 emissions much later, largely contained to the 20th and 21st centuries.
If we fast-forward to the accumulated totals we see today, the USA and Europe dominate in terms of cumulative emissions. China’s rapid growth in emissions over the last few decades now makes it the world’s second largest cumulative emitter, although it still comes in at less than 50% of the USA’s total.
Annual CO2 emissions
If we forget the cumulative time dimension and focus only on annual emissions, how do more recent annual emission trends compare? In the chart below, we can view annual CO2 emissions by country. You can select a range of countries to compare through time in the “chart” tab, or alternatively click on a country on the “map” tab to see its time series. In support of the cumulative chart we explored above, we can see that the annual trends of European and North American nations have grown much earlier than in other regions.
Emissions from a number of growing economies have been increasing rapidly over the last few decades. Fast-forwarding to annual emissions in 2014, we can see that a number of low to middle income nations are now within the top global emitters. In fact, China is now the largest emitter, followed by (in order) the USA, EU-28, India, Russia, Indonesia, Brazil, Japan, Canada and Mexico. Note that a number of nations who are already top emitters are likely to continue to increase emissions as they undergo development.
In contrast to CO2 emissions growth in low to middle income economies, trends across many high income nations have stabilized, and in several cases decreased in recent decades. Despite this downward trend across some nations, emissions growth in transitioning economies dominates the global trend—as such, global annual emissions have continued to increase over this period.
Per capita CO2 emissions
The key drawback of measuring the total national emissions is that it takes no account of the nation’s population size. China is currently the world’s largest emitter, but since it also has the largest population, all being equal we would expect this to be the case. To make a fair comparison of contributions, we have to therefore compare emissions in terms of CO2 emitted per person.
In the map below we compare CO2 emissions per capita through time since 1950. Again, if we cycle through time by moving the slider below the map, we see that per capita emissions in most countries have continued to increase in line with development. However, if we look at the distribution of per capita emissions in 2014, large global inequalities remain.
Note that carbon dioxide is not the only greenhouse gas which contributes to climate change—nitrous oxide and methane are also greenhouse gases, but are not included here. Food production, especially intensive livestock-rearing for meat and dairy, is a major contributor to both of these non-CO2 GHGs. Since capita meat intake is strongly linked to GDP levels, per capita emissions of nitrous oxide and methane tend to be much larger in high-income nations. Therefore, if these gases were included alongside CO2, the global inequalities would be even higher.
With a few exceptions, there is an important north-south divide in terms of per capita emissions. Most nations across sub-Saharan Africa, South America and South Asia have per capita emissions below five tonnes per year (many have less than 1-2 tonnes). This contrasts with the global north where emissions are typically above five tonnes per person (with North America above 15 tonnes). The monthly emissions per capita in rich countries are mostly higher than the yearly emissions per capita in poorer countries. The largest emitter, Qatar, has per capita emissions of 50 tonnes per year (1243 times that of Chad, the lowest emitter).
CO2 emissions by source
Carbon dioxide emissions associated with energy and industrial production can come from a range of fuel types. The contribution of each of these sources has changed significantly through time, and still shows large differences by region. In the chart below we see the absolute and relative contribution of CO2 emissions by source, differentiated between gas, liquid (i.e. oil), solid (coal and biomass), flaring, and cement production.
At a global level we see that early industrialisation was dominated by the use of solid fuel—this is best observed by switching to the ‘relative’ view in the chart. Coal-fired power at an industrial-scale was the first to emerge in Europe and North America during the 1700s. It wasn’t until the late 1800s that we begin to see a growth in emissions from oil and gas production. Another century passed before emissions from flaring and cement production began. In the present day, solid and liquid fuel dominate, although contributions from gas production are also notable. Cement and flaring at the global level remain comparably small.
You can also view these trends across global regions in the chart below, by clicking on ‘change region’. The trends vary significantly by region. Overall patterns across Europe and North America are similar: early industrialisation began through solid fuel consumption, however, through time this energy mix has diversified. Today, CO2 emissions are spread fairly equally between coal, oil and gas. In contrast, Latin America and the Caribbean’s emissions have historically been and remain a product of liquid fuel—even in the early stages of development coal consumption was small.2 Asia’s energy remains dominant in solid fuel consumption, and has notably higher cement contributions relative to other regions.3 Africa also has more notable emissions from cement and flaring; however, its key sources of emissions are a diverse mix between solid, liquid and gas.
CO2 emissions- global and regional trends
The visualisation below presents the long-run perspective on global CO2 emissions. Global emissions increased from 2 billion tonnes of carbon dioxide in 1900 to over 26 billion tonnes 115 years later.
What do our most recent trends in emissions and concentrations look like? Are we making any progress in reduction?
Our latest data suggests that over the last few years (2014-2016), global annual emissions of CO2 have approximately stabilized. This slowdown is too recent to ascertain whether this stabilization in emissions represents a peak (with a reduction trend to follow), or a plateau. A large contribution to a stabilization in global emissions is thought to be a recent plateau in China’s (the world’s largest emitter) emissions. Regionally, we see that the emissions across a number of high-income countries in Europe and the Americas have peaked and were falling during the last decade.
# Impact of emissions on atmospheric concentrations
The large growth in global CO2 emissions has had a significant impact on the concentrations of CO2 in Earth’s atmosphere. If we look at atmospheric concentrations over the past 2000 years (see the Data Quality and Measurement section in this entry for explanation on how we estimate historical emissions), we see that levels were fairly stable at 270-285 parts per million (ppm) until the 18th century. Since the Industrial Revolution, global CO2 concentrations have been increasing rapidly.
However, CO2 is not the only GHG we’re concerned about—emissions of nitrous oxide (N2O) and methane (CH4) have also been increasing rapidly through agricultural, energy, and industrial sources. Like CO2, the atmospheric concentration of both of these gases has also been rising rapidly.
Has a global stabilization of CO2 emissions over the last few years had an impact on global atmospheric concentrations? While it appears progress is being made on global emissions, atmospheric concentrations continue to rise, as shown below. Atmospheric concentrations have now broken the 400ppm threshold—considered its highest level in the last three million years. To begin to stabilise—or even reduce—atmospheric CO2 concentrations, our emissions need to not only stabilise but also decrease significantly.
Why would a stabilization in CO2 emissions not directly translate into the same for atmospheric concentrations? This is because CO2 accumulates in the atmosphere based on what we call a ‘residence time’. Residence time is the time required for emitted CO2 to be removed from the atmosphere through natural processes in Earth’s carbon cycle. The length of this time can vary—some CO2 is removed in less than 5 years through fast cycling processes, meanwhile other processes, such as absorption through land vegetation, soils and cycling into the deep ocean can take hundreds to thousands of years. If we stopped emitting CO2 today, it would take several hundred years before the majority of human emissions were removed from the atmosphere.4
# Correlates, Determinants & Consequences
CO2 emissions and prosperity
Historically, CO2 emissions have been primarily driven by increasing fuel consumption. This energy driver has (and continues to be) a fundamental pillar for economic growth and poverty alleviation. As a result, we see in the visualisation below that there is a strong correlation between per capita CO2 emissions and GDP per capita.
This correlation is also present over time: Countries begin in the bottom-left of the chart at low CO2 and low GDP, moving upwards and to the right. Historically (where fossil fuels are the dominant form of energy), we therefore see increases in CO2 as an unintended consequence of development and economic prosperity.
Whilst we see this general relationship between CO2 and GDP, there are outliers in this correlation, and important differences in the rate with which per capita emissions have been growing.
These differences are exemplified in global inequalities in energy provision, CO2 emissions and economic disparities. In the chart below we see the change in CO2 emissions (i.e. the growth rates) over the last few decades (1998-2013) across the global spectrum of emitters. On the x-axis we have the spectrum of global emitters (where those at the far left have very low per capita emissions, and those at the far right have the world’s highest per capita emissions).
On the y-axis we have the growth (in %) in CO2 emissions that each segment of emitters has undergone from 1998-2013. We see that in the middle of the spectrum- typically those near the middle of the global income spectrum- have experienced a large growth in CO2 emissions over the last few decades (most between 25-40%). Insofar as emissions are a correlate of development this is good news and is reflecting the fact that a global middle class is developing, but it does present important challenges in terms of global CO2 emissions.
Of concern is therefore that at the bottom of the spectrum (the group of people of which many are part of the world’s poorer population) have seen a 12% decline in CO2 emissions over this same period. Whilst a decline in emissions is necessary and possible for individuals with high per capita emissions, for the poorest, this potentially suggests stagnation or a decline in living conditions.
Growth rate in CO2 emissions (from 1998-2013) across the spectrum of global emitters5
Not only cross-country inequalities in CO2 emissions are important- there are also noticeable within-country inequalities. In fact, as the global inequalities in CO2 emissions between countries begins to converge, within-country inequalities become more important.
As the chart below shows, in 1998 two-thirds of inequality in CO2 emissions were due to between-country differences. Within-country differences then became more important, and by 2013, within and between-country differences were responsible for roughly the same share of total inequalities.
Levels of CO2 inequality between and within countries6
CO2 growth and poverty alleviation
The link between economic growth and CO2 described above raises an important question: do we actually want the emissions of low-income countries to grow despite trying to reduce global emissions? In our historical and current energy system (which has been primarily built on fossil fuels), CO2 emissions have been an almost unavoidable consequence of the energy access necessary for development and poverty alleviation.
In the two charts below, we see per capita CO2 emissions, and energy use per capita (both on the y-axes), plotted against the share of the population living in extreme poverty (%) on the x-axis. In general, we see a very similar correlation in both CO2 and energy: higher emissions and energy access are correlated to lower levels of extreme poverty. Energy access is therefore an essential component in improved living standards and poverty alleviation.7
In an ideal world, this energy could be provided through 100% renewable energy: in this case, CO2 emissions could be an avoidable consequence of development. However, currently we would expect that some of this energy access will have to come from fossil fuel consumption (although potentially with a higher mix of renewables than older industrial economies). Therefore, although the global challenge is to reduce emissions, some growth in per capita emissions from the world’s poorest countries remains a sign of progress in terms of changing living conditions and poverty alleviation.
CO2 intensity of economies
If economic growth is historically linked to growing CO2 emissions, why do countries have differing levels of per capita CO2 emissions despite having similar GDP per capita levels? These differences are captured by the differences in the CO2 intensity of economies; CO2 intensity measures the amount of CO2 emitted per unit of GDP (kgCO2 per int-$). There are two key variables which can affect the CO2 intensity of an economy:
- energy efficiency: the amount of energy needed for one unit of GDP output. This is often related to productivity and technology efficiency, but can also be related to the type of economic activities. If a country transitions from a country with a large share of manufacturing in economic output towards a service-based economy, this is likely to fall.
- carbon efficiency: the amount of CO2 emitted per unit energy (grams of CO2 emitted per kilowatt-hour) . This is largely related to a country’s energy mix. An economy powered through coal-fired energy will produce higher CO2 emissions per unit of energy versus an energy system with a high percentage of renewable energy. As economies increase their share of renewable capacity, this variable will fall.
In the chart below, we see that the global CO2 intensity has been steadily falling since 1990.8 This is likely to be through both improved energy and technology efficiency, and increases in the capacity of renewables.9 The carbon intensity of nearly all national economies has also fallen in recent decades. Today, we see the highest intensities in Asia, Eastern Europe and South Africa. This is likely to be a compounded effect of coal-dominated energy systems and heavily industrialised economies. The shift in industrial production from high-income to transitioning economies, and its impact on CO2 emissions, is discussed in the next section.
Although carbon intensities have generally shown a steady, gradual decline in recent decades, dramatic short-term fluctuations in intensity can occur and are typically the result of significant short-term political or economic change. The most dramatic example of this was seen in China during its ‘Great Leap Forward’ campaign in the 1950s-60s, which we have explored in detail on our blog here.
CO2 embedded in trade
CO2 emissions are most typically measured and reported in terms of CO2 “production”. This accounting method is also sometimes referred to as “territorial-based” emissions because it reports emissions as those emitted within a country’s given geographical boundaries. As a result, this method takes no account of emissions which may be imported or exported in the form of traded goods.10 “Consumption-based” accounting adjusts CO2 emissions for this trade of emissions and more accurately reflecting the emissions necessary in supporting a given country’s way of living.
What does a global map of traded CO2 emissions look like? Below we see emissions embedded in trade in 2004 (in million tonnes per year); the thickness of the arrow is representative of the size of traded CO2. This shows an important East-to-West relation, with large exports from Asia and Eastern Europe into Western Europe and North America.
In other words: some of the CO2 produced (and reported) in emission records of Asian and Eastern European countries is for the production of goods consumed in Western Europe and North America. This particular study estimated that if we switched to a consumption-based reporting system (which corrects for this trade), the annual CO2 emissions of several European economies would increase by more than 30%; the USA would increase by 10% and China’s emissions would decrease by 22%.
The composition of this trade is also important in terms of carbon intensity. In the figure below we see the carbon intensity (kgCO2 per $ of trade) for imports and exports across several countries. The goods exported from Russia, China, India and the Middle East typically have a high carbon intensity- reflecting the fact that their exports are often manufactured goods. In contrast, we see that exports from the UK, France, Germany and Italy are low; this is likely to be the higher share of export of more service-based goods relative to those produced from heavy industry.
CO2 emission flows from embedded carbon in global trade11
CO2 intensity of goods imported and exported by country12
# Agriculture and land use
Although many people typically attribute CO2 emissions to energy production, there are other important contributing activities, such as transportation or agriculture. The most recent Intergovernmental Panel on Climate Change (IPCC) reported that the agriculture, forestry and land use (AFOLU) sector was responsible for about one-quarter of global greenhouse gas emissions.13 14
Greenhouse Gas Emissions by Economic Sector15
Why have emissions from agriculture been increasing with time? There are two key contributors to increasing emissions. Firstly, a growing global population requires an overall higher food production. This increased requirement for food has led to both expansion of agricultural land and an intensification of farming practices.16
The expansion of agricultural land is often into previously forested areas; this process of deforestation releases CO2 stored in trees and soils, and is included in the accounting of emissions relating to agriculture, forestry and land use (ALOFU). It’s estimated that up to 80 percent of deforestation is the result of agricultural expansion.
Secondly, global economic growth has not only resulted in an increase in food demand (richer people tend to eat more), but also in changes in dietary composition; that is, changes in what we eat. Economic growth is typically related to an increase in meat consumption. 17 Livestock are an important source of greenhouse gas emissions, with variations between animal products (lamb and beef are usually the most carbon-intensive and chicken the least).18
A growing global middle class has led to significant increases in global meat consumption in recent decades- this is shown in the chart below which gives the average annual consumption through time.
The cost of global CO2 mitigation
Once we have an understanding of the relationship between CO2 and global temperature, and sources of emissions, the obvious question which arises is: how much could we reduce our emissions by, and how much would it cost? The possible cost-benefit of taking global and regional action of climate change is often a major influencing factor on the effectiveness of mitigation agreements and measures. How we work out the potential costs of global climate mitigation has been covered in an explainer post to follow.
# Data Quality, Definitions and Measurement
How do we reconstruct long-term CO2 concentrations?
In more recent years, global concentrations of CO2 can be measured directly in the atmosphere using instrumentation sensor technology. The longest and most well-known records from direct CO2 measurement comes from the Mauna Loa Observatory (MLO) in Hawaii. The MLO has been measuring atmospheric composition since the 1950s, providing the clearest record of CO2 concentrations across the 20th and 21st century.
To reconstruct long-term CO2 concentrations, we have to rely on a number of geological and chemical analogues which record changes in atmospheric composition through time. The process of ice-coring allows for the longest extension of historical CO2 records, extending back 800,000 years. The most famous ice core used for historical reconstructions is the Vostok Ice Core in Antarctica. This core extends back 420,000 years and covers four glacial-interglacial periods.
Ice cores provide a preserved record of atmospheric compositions- with each layer representing a date further back in time. These can extend as deep at 3km. Ice cores preserve tiny bubbles of air which provide a snapshot of the atmospheric composition of a given period. Using chemical dating techniques (such as isotopic dating) we can relate time periods to depths through an ice core. If we look at the Vostok Ice Core, we can say that the section of core 500m deep was formed approximately 30,000 years ago. We can then use CO2 concentration sensors to measure the concentration in air bubbles at 500m depth- this was approximately 190 parts per million. Combining these two methods, we could estimate that 3000 years ago, the CO2 concentration was 190ppm. Repeating this process across a range of depths, we can reconstruct how these concentrations have changed through time.
How do we measure or estimate CO2 emissions?
Historical fossil fuel CO2 emissions can be reconstructed back to 1751 based on energy statistics. These reconstructions detail the production quantities of various forms of fossil fuels (coal, brown coal, peat and crude oil), which when combined with trade data on imports and exports, allow for national-level reconstructions of fossil fuel production and resultant CO2 emissions. More recent energy statistics are sourced from the UN Statistical Office which compiles data from official national statistical publications and annual questionnaires. Data on cement production and gas flaring can also be sourced from UN data, supplemented by data from the US Department of Interior Geological Survey (USGS) and US Department of Energy Information Administration. A full description of data acquisition and original sources can be found at the Carbon Dioxide Information Analysis Center (CDIAC).
As an example: how do we estimate Canada’s CO2 emissions in 1900? Let’s look at the steps involved in this estimation.
- Step 1: we gather industrial data on how much coal, brown coal, peat and crude oil Canada extracted in 1900. This tells us how much energy it could produce if it used all of this domestically.
- Step 2: we cannot assume that Canada only used fuels produced domestically- it might have imported some fuel, or exported it elsewhere. To find out how much Canada actually burned domestically, we therefore have to correct for this trade. If we take its domestic production (account for any fuel it stores as stocks), add any fuel it imported, and minus any fuel it exported, we have an estimate of its net consumption in 1900. In order words, if we calculate: (coal extraction – coal exported + coal imported – coal stored as stocks), we can estimate the amount of coal Canada burned in 1900.
- Step 3: converting energy produced to CO2 emissions. we know, based on the quality of coal, its carbon content and how much CO2 would be emitted for every kilogram burned (i.e. its emission factor). Multiplying the quantity of coal burned by its emission factor, we can estimate Canada’s CO2 emissions from coal in 1900.
- Step 4: doing this calculation for all fuel types, we can calculate Canada’s total emissions in 1900.
Providing good estimates of CO2 emissions requires reliable and extensive coverage on domestic and traded energy- the international framework and monitoring of this reporting has significantly improved through time. For this reason, our understanding of emissions in the late 20th and 21st centuries is more reliable than our long-term reconstructions. The Intergovernmental Panel on Climate Change (IPCC) provide clear guidelines on methodologies and best practice for measuring and monitoring CO2 estimates at the national level.19
There are two key ways uncertainties can be introduced: the reporting of energy consumption, and the assumption of emissions factors (i.e. the carbon content) used for fuel burning. Since energy consumption is strongly related to economic and trade figures (which are typically monitored closely), uncertainties are typically low for energy reporting. Uncertainty can be introduced in the assumptions nations make on the correct CO2 emission factor for certain fuel types.
Country size and the level of uncertainty in these calculations have a significant influence on the inaccuracy of our global emissions figures. In the most extreme example to date, Lui et al. (2015) revealed that China overestimated its annual emissions in 2013 by using global average emission factors, rather than specific figures for the carbon content of its domestic coal supply.20 As the world’s largest CO2 emitter, this inaccuracy had a significant impact on global emissions estimates, resulting in a 10% overestimation. More typically, uncertainty in global CO2 emissions ranges between 2-5%.21
# Data Sources
# Carbon Dioxide Information Analysis Center
- Data: CO2 emissions (also by fuel type), and data on trace gas emissions, aerosols, the carbon cycle, the Full Global Carbon Budget (1959-2013), land use and more.
- Geographical coverage: Global, regional, national, subnational (for some) and globally gridded (1°x1°; since 1751).
- Time span: Since 1751
- Available at: Online here.
- CDIAC is the climate-change data and information analysis center of the U.S. Department of Energy (DOE).
- The Historical Carbon Dioxide Record from the Vostok Ice Core is available here – it covers the period 417,160 – 2,342 years BP.
- The Atmospheric Carbon Dioxide Record from Mauna Loa is available here – it goes back to 1958.
- The Clio Infra Project is also using CDIAC data. The data is available for download here.
# T.A. Boden, G. Marland, and R.J. Andres. 2017. Global, Regional, and National Fossil-Fuel CO2 Emissions
- Data: CO2 emissions by source
- Geographical coverage: Global- by region
- Time span: 1751-2013
- Available at: doi:10.3334/CDIAC/00001_V2010
# National Oceanic and Atmospheric Administration (NOAA)
- Data: Global CO2 concentrations
- Geographical coverage: Global
- Time span: 1980-2016
- Available at: www.esrl.noaa.gov/gmd/ccgg/trends/
# Met Office Hadley Centre for Climate Science and Services
- Data: Atmospheric and marine global temperatures and pressure data
- Geographical coverage: UK-based and global
- Time span: 1850-2017
- Available at: http://www.metoffice.gov.uk/hadobs/
# Climate Tracker
- Data: National, regional and global level analysis on progress on greenhouse gas mitigation and targets
- Geographical coverage: Global, regional and national
- Time span: 1990-2100 (projections)
- Available at: http://climateactiontracker.org/global.html
# World Resources Institute (WRI)
- Data: National and global level GHG emissions, global temperature trends and climate change impacts
- Geographical coverage: Global, regional and national
- Time span: 1860-2015
- Available at: http://www.wri.org/blog/2017/04/climate-science-explained-10-graphics
# Intergovernmental Panel on Climate Change (IPCC)
IPCC reports are produced periodically, and provide the most complete and comprehensive aggregation of our knowledge and understanding of climatic change, including emissions, temperature correlation, mitigation and adaptation potential. This analysis provides a long-term historical outlook and covers data at both a national, regional and global level. IPCC publications and datasets are available at: