
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Energy and emissions forecast of China over a long-time horizon

Abstract Forecasts of energy demand, the fuel mix meeting that demand and the associated emissions are a key requirement for informed energy planning and policy decisions to ensure energy security and address climate change. While there have been many studies on China focusing on the short and medium term (to 2020 and 2050) there is little in the literature focusing on the long term (to 2100). This paper seeks to address those gaps on sectoral energy demands and emissions on long term by following a two-stage approach. It develops key energy indicators on useful energy demand, transport mobility and end use fuel demand for various sectors. The main drivers of these indicators are socio-economic parameters. The indicators are used to project energy service demands and emissions forward for China in TIMES G5 model at least cost approach. The results from this reference scenario suggest that China will require approximately 4 Gtoe of primary energy, by the end of the 21st century to deliver 3 Gtoe final energy consumption, 10 PWh of electricity generation, 1.3 Gtoe of energy imports, which will results in 10 Gt CO 2 emissions.
- University College Cork Ireland
- Università degli studi di Salerno Italy
- University of Stuttgart Germany
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).131 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 1% 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 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
