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The largest contributor to pollutant emissions is the sintering process in steel industry. Ultra-low emission policy for the Chinese steel industry states that emission concentrations of particulate matter, SO2 and NOx should not exceed 10, 35 and 50 mg/m3 respectively. The emission concentrations of the steel industry are the same as the ultra-low emission policy for the coal-fired power industry, but the pollutant control technologies of the two industries are different. Life cycle assessment method is applied to analyze the latest ultra-low treatment process for sintering flue gas emissions which includes electrostatic precipitation, ozone oxidation, wet desulfurization, wet denitration, condensation dehumidification and wet electrostatic precipitation. Following this novel ultra-low emission treatment, the concentrations of particulate matter, SO2, NOx, and PCDDs in the sintering flue gas decreased very significantly, attaining the new emission standard. With 1 ton of sinter as the functional unit and “cradle to gate” as the system boundary, the environmental impact of the process is 0.1811 and the total economic cost is 172.79 RMB, of which internal cost is 34.64 RMB and external cost is 138.15 RMB. The main environmental impacts result from applying the wet denitration and ozone oxidation processes. Sodium sulfite in the wet denitration process, and electricity and liquid oxygen in the ozone oxidation process are the key inputs that cause environmental impact. These findings are useful for a further optimization of the ultra-low emissions process from both the environmental and economic perspective, which is applicable in other regions of the world.

Regional sustainable development has become a worldwide issue in recent years, but there is no single and universally agreed method of choosing indicators for sustainable development assessment. The subjective selection of indicators will affect the results of assessment. Each evaluation method has its own advantages and disadvantages, and the methods used to determine indicator weight also differ. Regional sustainable development is a complex system, which is difficult to evaluate objectively and scientifically using a single method. Therefore, a new integrated indicator system and evaluation model is constructed here to more accurately reflect regional sustainable development level. The indicator system and evaluation model were constructed using a case study of 17 cities in Shandong Province, China. The indicator system includes 4 subsystems, i.e., economy, society, resource, and environment. These indicators were selected through correlation analysis and discrimination analysis. A back propagation neural network was applied to evaluate the respective scores of the 4 subsystems. The comprehensive score for regional sustainable development was evaluated using the analytic hierarchy process with entropy correction. The results show that sustainable development levels in these 17 cities show a gradually decreasing trend from east to west and from coast to inland. Cities with an underdeveloped economy usually display poor levels of social development and serious environmental pollution. Through the improvement of indicator screening, evaluation model, and result correction, the error caused by a single evaluation method can be reduced significantly. This new methodology for indicator selection and comprehensive evaluation provides a new perspective for the assessment of regional sustainable development.