Worldwide emissions: how does each country compare?

Worldwide emissions vary significantly from one country to another, largely due to differences in size, population, economic activities, and energy sources.

Industrialised nations and large economies such as the United States, China, and India are among the top emitters of greenhouse gases, contributing a substantial portion of global CO2 emissions primarily through energy production, manufacturing, and transportation.

China has become the world's largest emitter due to its rapid industrial growth and reliance on coal for energy. 

Smaller countries or those with robust renewable energy policies and lower industrial activity tend to have much lower emissions. European nations like Sweden and Denmark, for example, have successfully implemented green initiatives that significantly reduce their carbon footprint.

The comparison of emissions between countries highlights the disparity in per capita emissions, which can provide a different perspective on a nation's environmental impact.

Countries with high per capita emissions, such as the United States, Canada, and Australia, indicate a high level of fossil fuel consumption per person, often linked to a lifestyle that includes high energy use in transportation, heating, and electricity.

Many developing countries have low per capita emissions, reflecting limited access to energy and lower consumption levels.

Why Land Use is excluded from this data

Under the United Nations Framework Convention on Climate Change any process, activity or mechanism which removes a greenhouse gas from the atmosphere is referred to as a ‘sink’. 

Land Use, Land-Use Change and Forestry (LULUCF) refers to human activities that create sinks. 

OnlyFacts sources its global emissions data from Germany's Potsdam Institute for Climate Impact Research (PRIMAP-hist), which excludes LULUCF from its data. Here's why:

LULUCF data has high annual fluctuations which makes it difficult to combine datasets by scaling of one dataset to match the other (and use the growth rates of the scaled dataset to extend the other dataset). Thus in PRIMAP-hist v1 we used unscaled data, which introduces sudden changes in emissions timeseries that were often understood by users as changes in actual emissions instead of changes in underlying dataset. LULUCF emissions estimates vary strongly between different datasets and the methodologies used can be very different. There are also changes in methodologies within datasets, which again introduce sudden emissions changes into the timeseries. With the data currently available, we cannot produce time series that fulfill our requirements for internal consistency and easy usability by a broad audience. Describing the inconsistencies and the limitations to the use of the dataset resulting from these issues has proven not to suffice as the LULUCF data lead to misunderstandings. Thus we have decided to stop publishing LULUCF timeseries until either there are more consistent datasets or we develop an improved methodology to create a consistent and easy to use LULUCF dataset.

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