Targeted emission reductions from global super-polluting power plant units

Dan Tong, Qiang Zhang (), Steven J. Davis (), Fei Liu, Bo Zheng, Guannan Geng, Tao Xue, Meng Li, Chaopeng Hong, Zifeng Lu, David G. Streets, Dabo Guan and Kebin He
Additional contact information
Dan Tong: Tsinghua University
Qiang Zhang: Tsinghua University
Steven J. Davis: Tsinghua University
Fei Liu: Tsinghua University
Bo Zheng: Tsinghua University
Guannan Geng: Tsinghua University
Tao Xue: Tsinghua University
Meng Li: Tsinghua University
Chaopeng Hong: Tsinghua University
Zifeng Lu: Argonne National Laboratory
David G. Streets: Argonne National Laboratory
Dabo Guan: Tsinghua University
Kebin He: Tsinghua University

Nature Sustainability, 2018, vol. 1, issue 1, 59-68

Abstract: Abstract There are more than 30,000 biomass- and fossil-fuel-burning power plants now operating worldwide, reflecting a tremendously diverse infrastructure, which ranges in capacity from less than a megawatt to more than a gigawatt. In 2010, 68.7% of electricity generated globally came from these power plants, compared with 64.2% in 1990. Although the electricity generated by this infrastructure is vital to economic activity worldwide, it also produces more CO2 and air pollutant emissions than infrastructure from any other industrial sector. Here, we assess fuel- and region-specific opportunities for reducing undesirable air pollutant emissions using a newly developed emission dataset at the level of individual generating units. For example, we find that retiring or installing emission control technologies on units representing 0.8% of the global coal-fired power plant capacity could reduce levels of PM2.5 emissions by 7.7–14.2%. In India and China, retiring coal-fired plants representing 1.8% and 0.8% of total capacity can reduce total PM2.5 emissions from coal-fired plants by 13.2% and 16.0%, respectively. Our results therefore suggest that policies targeting a relatively small number of ‘super-polluting’ units could substantially reduce pollutant emissions and thus the related impacts on both human health and global climate.

Date: 2018
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DOI: 10.1038/s41893-017-0003-y

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