This article explores the relationship between economic development (GDP) and carbon emission. Carbon is emitted as a consequence of energy use as most fuel sources are carbon-based. Therefore, the two measures of carbon we use here are carbon intensity (metric tonnes of carbon per $1,000 of GDP produced) and per capita carbon emission (metric tonnes per capita). GDP is measured in constant US dollar in 2000. The thrust of the analysis is to look at the relationship between economics and carbon emission, without going in to the debate about whether CO2 is contributing to global warming or not, and how much of climate change is induced by anthropogenic emission of greenhouse gases.
Among G-20 countries, there is a clear inverse relationship between levels of income and carbon intensity. This broadly implies that while the technology is currently available that could significantly improve energy efficiency and reduce carbon intensity, either the technology is not widely available, or accessible; or that some countries are not in position to adopt the technologies.
In the case of India, China, Japan and the US, it?s clear that carbon intensity diverges sharply as GDP increases. For China and India, the divergence is very sharp, since their growth rates are much higher, and they started from a low base. But in both cases, carbon intensity begins to decline sharply after an initial increase following the economic reforms in late 1970s and early 1980s for China, and early 1990s for India.
For India, there was a steady increase in carbon intensity, from 1970 to 1990, during a period of controlled economic conditions, and regulated industrialisation, characterised by lack of competition. But with economic liberalisation, and increased competition following the reforms in 1991, not only did economic growth pick up, but efficiency improved and carbon intensity began to decline.
In richer countries, like Japan or the US, economic development and carbon intensity have decoupled. But in India, it is startling how there was a clear phase where the two factors were coupled together till the early 1990s, and then decoupled, following liberalisation.
Between 1970 and 2008, the US economy reduced its carbon intensity by over 50%, but Japan traditionally has remained more efficient. But the gap in carbon intensity between the two economic giants has greatly narrowed in the past four decades. In 1970, the US produced 1.18 metric tonnes of CO2 for every $1000 of GDP, which declined in 2008 by 0.49 metric tonnes. Similarly, between 1970-2008, Japan?s carbon intensity decreased from 0.45 to 0.24 metric tonnes CO2 per $1000 of GDP.
The same pattern is more dramatically reflected in two of the most significant emerging economies, bearing in mind that China began its economic reforms about a decade before India. Between 1980-2008, China reduced its carbon intensity from 8.01 metric tonnes to 2.63 metric tonnes. Between the 1970s and early 1990s, India?s carbon intensity increased from 1.76 to 2.25 metric tonnes, but then it decreased to 2.14 metric tonnes by 2008.
In the 1970s, China had a virtually closed economy, and consequently, China was much more inefficient, and its carbon intensity was therefore much higher than India?s. But over the past decade, as both countries attempted to reform their economies, their carbon intensity declined, and have begun to converge significantly, although the Chinese economy remains somewhat more carbon intensive than India?s.
Among G-20 countries, the lower the income level, there is a positive trend between per capita carbon emission and increase in per capita GDP. When income levels are low, countries consume less energy, and carbon emissions are low. As economies grow from this low level, energy consumption increases and so do carbon emissions. But as counties move to higher GDP brackets, the slopes of the curves tend to become flatter, indicting that decoupling the economy from carbon emissions is a possibility.
With further increases in GDP levels, the slope of the curve may turn downwards, as it has for many of the European countries, and also the US. While the per capita carbon emission in the US at present is double that of the EU, nevertheless the slopes of the curves are headed distinctly south for many of the rich countries. No doubt there are significant variations among countries, yet the prospect of a Kuznet?s curve in carbon has perhaps never been brighter. Clearly, it needs to be explored further.
Effective saving in carbon
We measured effective savings in carbon emissions by calculating possible carbon emissions at actual GDP level using the carbon intensities prevailing in 1970, 1980, 1990, 2000 and 2008. By this measure, China has had an effective saving in carbon emission of 110%, between 1990-2008, when China?s carbon intensity declined from 5.53 to 2.63 metric tonnes per $1,000 of GDP. That is an effective saving in carbon of over 100%, had the Chinese economy grown to the same level as today, with carbon intensity remaining at the level of 1990. The effective carbon saving for India is a more modest 33%, between 1990-2008, with the carbon intensity declining from 2.87 to 1.86 metric tonnes
Carbon intensity in Japan today is one-sixth that of India, and one-tenth that of China. If both China and India could improve their energy efficiencies and lower their carbon intensity to the Japanese level, their total carbon emissions would be a fraction of today?s, at the same GDP level as today.
Japan, with 0.24 metric tonnes of carbon emissions per $1,000 of GDP, has achieved this low carbon intensive economy with the technologies currently available. So the conclusion is that there is enormous scope for countries like China and India to improve energy efficiency and reduce carbon emission, by adopting state-of-the-art technologies that are already in the market today. The question is, do emerging economies have access to these technologies? Or are conditions within developing countries not conducive for quick adoption of the best available technologies?
The author is director of Liberty Institute, and independent think tank. Nitu Maurya, research consultant at the institute, contributed data analysis. All data is from the World Bank?s online World Development Indicators database
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