| Abstract |
Industrial Energy Conservation and Emission Reduction (ECER) management is challenging due to the large number of objectives involved, and the complex synergies/conflicts amongst them. Most studies do not quantify these synergies/conflicts, resulting in high dimension ECER management problems. This study builds a 10-objective problem to optimize 5 heavy metals (Cd, Hg, Pb, As, Cr) and 5 conventional ECER-objectives (economic cost, energy, CO2, PM and NOx) in China's cement industry. First, NSGA-III is used to calculate optimal objective values under technology application constraints. Second, synergies/conflicts amongst objectives are quantified using Spearman's correlation. Finally, TOPSIS, Conservation Supply Curves and Quadrant methods are used to generate optimal ECER management policies. Results show that: (1) Optimal solutions are reliable as reflected by algorithm verification metrics - Error rate, Spacing metric and Hypervolume indicator; (2) The 10-objective problem is reduced to a 4-objective problem based on synergies. The four main-objectives are economic cost, energy consumption, CO2 and PM emission control. Therefore, ECER policies should focus on these objectives since optimizing them will synergistically improve all other objectives; (3) The average reduction potential for HMs and conventional objectives is 20% and 25% respectively, with an increase in economic cost of about 44-83 CNY/t; (4) From 72-ECER strategies assessed, 11-key strategies have better economic and environmental performances. They are mostly circular economy strategies utilizing industrial wastes, indicating that ECER policies should shift from traditional end-of-pipe approaches to a more circular economy approach. In sum, the proposed methodology can reduce the complexity of many-objective ECER management through a synergic control. |
