Industrial-environmental management in China's iron and steel industry under multiple objectives and uncertainties

Industrial-environmental management is a multi-objective optimization problem plagued with multiple uncertainties. Most studies only optimize few objectives and often neglect these uncertainties. This study builds a 6-objective optimization problem to quantify energy conservation and emission reduction (ECER) potentials in China's iron and steel industry. First, uncertainties are simulated through 100,000-time random sampling, NSGA-II and the mean-effective objective mechanism are applied to calculate optimal solutions. Finally, a global sensitivity analysis is performed to classify uncertainty parameters based on their impacts on objectives' performance. Results show: (1) There exist significant discrepancies between objectives' performance under certainty and uncertainty. For example, the deterministic CO2 intensity is 1148 kg/t, which is 11.93% lower than its value under uncertainty. Therefore, neglecting uncertainty increases the risk of noncompliance with policy targets as they might be too strict; (2) Two critical uncertainty parameters (steel ratios and technology penetration rates) have the most severe impacts on objectives' performance, hence, reducing their fluctuation can minimize uncertainties when estimating ECER potentials; (3) By-product recycling and energy efficiency measures have good performance in all objectives, thus, should be prioritized. Moreover, from 77-strategies assessed, 11 are identified as key-strategies due to their large ECER effects, hence, should be strongly promoted. •There exist significant discrepancies between objective values under certainty and uncertainty.•Neglecting uncertainty increases the risk of noncompliance with ECER targets.•Two uncertainty parameters are identified as critical since they have significant impacts on objectives' performance.•By-product recycling and energy efficiency measures have the best performance in all objectives.