No abstract

A multi-objective optimization methodology for hazardous liquid waste management is presented in this paper using industrially based LCA models and operating constraints. This approach is used to optimize the handling of waste streams introducing flexible mixing policy scenarios compared to the rigid policy scenarios of the industrial system. It is shown that increasing the degrees of freedom for the waste mixing reduces significantly both the operating cost and the environmental impact by avoiding the use of utilities. Moreover, the influence of waste availability as function of production planning without waste storage is analyzed in several multiperiod optimizations. There, it is demonstrated that this saving potential can be further increased by integration of multiperiod production planning with waste management policies, up to the level of 40% for the environmental impact, and more than 50% for the operating cost, compared to the industrial base case. In some specific cases, a proper matching of production planning and waste mixing policies can also turn the waste treatment into a source of profit exploiting energy production from the incineration process.Implications: This study reveals the savings potential of more flexible policies in waste management, in particular waste mixing of liquid waste in batch chemical industries treated in incineration, wet air oxidation, wastewater treatment plants, or recovered by distillation. Through a multi-objective optimization framework including models for operating costs and life-cycle inventories based on industrial data, operating constraints from industrial practice, and terminal constraints from legislation, savings potentials up to 50% for the operation cost and 40% for the environmental impact are demonstrated in two case studies.

One of the key principles of green chemistry is the minimization of energy consumption in the chemical industry. Besides continuous production processes, which have traditionally been the focus of energy saving potential studies, batch processes have also gained attention in recent years. To this end, detailed bottom-up approaches have been proposed for the modeling of energy utility consumption in multipurpose batch plants based on process documentation and high resolution sensor data. However, a simple procedure of general applicability for data extraction from process documentation facilitating the shortcut energy modeling approach for fast screening in multipurpose batch plants is still missing. In this paper, we introduce a new methodology for modeling the steam consumption in multipurpose chemical batch plants. This methodology is based on standard process documentation, rules of thumb, expert opinion, and thermodynamic principles. Additionally, we propose uncertainty intervals for the model outputs based on fuzzy set theory. Two case studies using production data from multipurpose batch plants of two different chemical companies have been carried out for parametrization and validation of the proposed methodology. In both cases, the steam consumption in several pieces of equipment involved in reaction and workup processes has been modeled and validated against reference values. The validation results showed that the new shortcut models provide acceptable estimations of steam consumption in multipurpose batch plants, and that the uncertainty intervals are in agreement with the batch-to-batch variability of the steam consumption. The output of these energy models can be used for the allocation of steam consumption to individual processes and products, enabling the identification of energy optimization potentials.