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Emission accounting and drivers in East African countries

East Africa is typical of the less developed economies that have emerged since the 21st century, whose brilliant economic miracle has also triggered the rapid growth of energy consumption and carbon dioxide emissions. However, previous carbon accounting studies have never focused on the region. Based on multi-source data, this paper rebuilt the 45-sectors carbon emission inventories of eight East African countries from 2000 to 2017, and used index decomposition analysis to quantify the drivers of growth. Here we found that overall the CO2 emissions show a 'two-stage exponential growth' pattern, with significant heterogeneity between countries. In terms of the energy mix, technical progress in hydro and geothermal energy was almost offset by a growing appetite for oil and coal, making it the weak and valuable factor driving emissions reduction (−1.4Mt). But it was far from enough to overcome the pressure of economic and population growth, which brought about a 13Mt and 11Mt emission growth respectively from 2000 to 2017. Increasing energy intensity due to industrialization and transport development also contributed to an increment of 6.4Mt. Low-carbon policies should be tailored to local conditions and targeted at the improvement of energy efficiency and use of renewable energy so as to achieve a win-win situation between sustainable economic growth and emission reduction.
- University College London United Kingdom
- Tsinghua University China (People's Republic of)
- University of Birmingham United Kingdom
- Shanghai University of Finance and Economics China (People's Republic of)
- Nanjing University China (People's Republic of)
CO emissions, CO2 emissions, East Africa, Driving factors, 339, LMDI
CO emissions, CO2 emissions, East Africa, Driving factors, 339, LMDI
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).34 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
