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Published on: June 12, 2019
Multifactor configurations of coal power technology in China substantially differ in life-cycle environmental impacts
Junjie Li1, Yulong Yan2, Yirong Wang2
1Engineering Research Center of Clean and Low-carbon Technology for Intelligent Transportation, Ministry of Education, School of Environment, Beijing Jiaotong University, Beijing 100044, China; School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China.
Abstract:
The expansion of coal power in China has led to a coexistence of multiple technologies, whereas differences in environmental impacts of each other remain hitherto unclear. This gap is largely a result of the difficulty of fully covering the factors that significantly affect environmental performances and the lack of fine data inventory. The limitation welcomes an approach that can go well beyond characterizing coal power technology with a single factor. To this end, we surveyed the information data for all coal power units in China to couple four factors (viz. operating parameter, boiler type, cooling approach, and turbine mode) into 22 types of multifactor technology configurations, as well as the first-hand operating data of nearly half of all coal power units in China to compile an elaborate data inventory that each configuration includes 88 input and output data. These fine data were modeled by the life cycle assessment method of CML 2016 to quantify twelve environmental impact categories. The results show substantial differences in environmental impacts exist for different technology configurations. High operating parameters gain environmental friendliness but the diversification of boiler type and cooling approach to improve the applicability of coal quality and water resources increases environmental impacts. The insignificant impact of the turbine mode is owning to the exergy allocation that eliminates the quality gap in electrical and thermal energy. The technology-level differences are aggregated into the provincial level by various configuration structures, which show markedly spatial heterogeneity varying by impact categories. This implies a great potential for structural adjustment and an overall improvement requires cleaner production beyond that, focused on the coal power generation process and its upstream coal supply process. Our modeling shows a majority of results with an uncertainty of lower than 10 %, which is robust for the proposal of policy suggestions.
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