Designing sustainable processes with simulation: the waste reduction (WAR) algorithm

Incorporating sustainable development in the design of mineral processing operations – Review and analysis of current approaches

“…They identify challenges in environmental design of minerals technologies: the limited availability of thermodynamic information covering the full spectrum of chemical conversions embodied in minerals technologies; the low grade of mineral ores (and as a result, the myriad of impurities which must be removed typically); the variability and non-homogeneity of ores resulting in significant variation between ore bodies, as well as over the life of a single mine; the large energy demand for physical transformations; the significant role of poorly understood particulate processes in beneficiation and refining; the relative conservatism of the industry for technological change, itself captured in the dominance of vendor-driven design solutions; and Whilst not focusing on all elements of the TBL, ''Green chemistry'', ''green engineering'' and DfE are all closely linked (and sometimes interchangeable) concepts that aim to improve sustainability by reducing impact on the environment through changing processing pathways and eliminating damaging products, by-products. These methodologies aim to compare the impacts of different processing alternatives by determining indicators of the potential for process flows to impact on the environment [43][44][45][46][47][48][49]. Cano-Ruiz and McRae [20] offer a very comprehensive review of current practices in process plant DfE.…”

Application of environmental and economic metrics to guide the development of biocatalytic processes

“…Nevertheless, LCA is often a laborious task, since it requires a large amount of data from a variety of sources [46] and therefore its applicability to bioprocess is reserved only for late development, when detailed information about the raw materials is available. In order to facilitate environmental assessments, several companies have developed in-house modified LCA methodologies and software tools, such as FLASC [42], BASF Eco-efficiency method [78], GREENSCOPE [79] [a Waste Reduction Algorithm (WAR [80]) based software], EATOS [81] and EcoScale [82]. Nevertheless, the simpler approaches still require a defined process (i.e., defined solvent, auxiliaries, upstream and DSP) and are thus not suitable for the previous development stage (Phase II: early development) when neither the biocatalyst and process are under development; whereas, to be used at Phase III, many of the above-mentioned tools fail on providing an objective (e.g., EcoScale penalties does not distinguish the amount of solvent or reaction time [15]) and a complete picture of the environmental impacts (e.g., EATOS and BASF methods are exclusively based on the mass metrics and on potential toxicity impacts and safety of the materials used, while the other impact categories are not accounted for [15]).…”

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

“…The normalization was done using a procedure similar to the WAR algorithm (Young & Cabezas, 1999). The normalization within each category allows for a more independent analysis from spatial and temporal references which in the case of process optimization can have some advantages, since sometimes that information may not exist.…”