LAUSR

Abstract This study applied a slacks-based data envelopment analysis (DEA) model to assess the eco-efficiencies of 44 coal-fired combined heat and power (CHP) plants (with 160 units) in 31 Chinese eco-industrial parks. The inputs of the DEA model include coal consumption, freshwater consumption, capital depreciation, and operating cost. The outputs are electricity, heat, and GHG emission. The key findings are that the eco-efficiencies of the CHP plants considered are quite different from thermal energy efficiencies, and annual working time is the most important factor affecting eco-efficiency positively. It is indicated by sensitivity analysis that consideration of freshwater consumption and capital depreciation will have a significant impact on eco-efficiency. The results also present that the CHP plants with a capacity less than 120 MW are generally more scale-effective. The role of featured industries in the host park was explored by a hierarchical clustering method, and we found that the more energy-intensive industries the parks host, the lower CHP eco-efficiencies they will have. Based on the findings, policy implications were proposed for improving CHP eco-efficiency in industrial parks, including enhancing utilization level, retrofitting turbine technology, and increasing heat-to-electric ratio of in-use CHP stocks, and controlling the plant-level capacity of new CHP projects.