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Energy
Article . 2014 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
Energy
Article . 2014
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Co-benefits of energy efficiency improvement and air pollution abatement in the Chinese iron and steel industry

Authors: Shaohui Zhang; Ernst Worrell; Wina Crijns-Graus; Fabian Wagner; Janusz Cofala;

Co-benefits of energy efficiency improvement and air pollution abatement in the Chinese iron and steel industry

Abstract

In 2010, China was responsible for 45% of global steel production, while consuming 15.8EJ of final energy and emitting 1344Mt CO2eq, 8.4Mt of PM (particulate matter) emissions, and 5.3Mt of SO2 emissions. In this paper we analyse the co-benefits of implementing energy efficiency measures that jointly reduce greenhouse gas emissions and air pollutants, in comparison to applying only air pollution control (end-of-pipe technology). For this purpose we construct ECSC (energy conservation supply curves) that contain potentials and costs of energy efficiency measures and implement these in the GAINS (greenhouse gas and air pollution interactions and synergies) model. Findings show that the technical energy saving potential for the Chinese iron and steel industry for 2030 is around 5.7EJ. This is equivalent to 28% of reference energy use in 2030. The emissions mitigation of GHGs (greenhouse gases) and air pollutants in BAEEM_S3 scenario would be reduce 27% CO2eq, 3% of PM, and 22% of SO2, compared to the BL scenario in 2030. Investments and cost savings were calculated for different scenarios, showing that energy efficiency investments will result in significant reductions in air pollution control costs. Hence, Energy efficiency measures should be integrated in air quality policy in China.

Country
Netherlands
Keywords

690, 330, Pollution, Iron and steel industry, GHGs (greenhouse gases), General Energy, Energy efficiency, valorisation, Energy(all), Co-benefits, SDG 7 - Affordable and Clean Energy, Investment, Air pollutants

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    influence
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
162
Top 1%
Top 10%
Top 1%
Green