(208e) A Techno-Economic Assessment of Acrylates Downstream Processing with Membrane Extraction

Acrylate esters represent a versatile family of building blocks for thousands of copolymer compositions. This includes butyl acrylate (BA), 2-ethylhexylacrylate (2-EHA), methyl methacrylate (MMA), butyl methacrylate (BMA), and others. Acrylic resins based on these monomers exhibit excellent weather resistance, high gloss and colour retention, and durability. They are primarily used to prepare emulsion and solution polymers. The global market for commodity acrylate esters is over 3 million metric tons, the EU production capacity is currently about 850,000 tons of acrylate esters. 2-Ethylhexylacrylate (2-EHA), is an important bulk chemical used in the production of homo and copolymers and it will be considered as a model acrylate in this work. On industrial scale, 2-EHA is produced by esterification of acrylic acid (AA) and 2-ethylhexanol (2-EH), with formation of water as byproduct. The reaction is performed batch-wise in the presence of an organic solvent and sulfuric acid as catalyst. The plants have capacities in the same order of magnitude of 20,000 t/year of 2-EHA.

For the downstream processing needed for product separation, all remaining base materials and by products resulting from the acrylate synthesis reaction need to be removed. This is typically done in two steps: 1) washing with water to remove the acrylic acid; afterwards, the water-acrylic acid solution is fed into an organic stripper/water distillation column. The left waste from the bottom of the column is either treated biologically or incinerated after concentration; and, 2) the organic solution containing the acrylate product is sent to a distillation unit to remove the product from the solvent. To avoid self-polymerisation and the formation of other by-products, the separations need to be done at a maximum temperature of 50°C. The conventional separation processes are inefficient water-washing and vacuum distillation. However, a large amount of washing water and energy is demanded in this traditional process. An efficient membrane extraction process has potential to replace the current complex and costly distillations, washing and decanting steps. The technical feasibility and advantages of replacing the traditional water wash process with membrane extraction have been demonstrated by Buekenhoudt et al. (2021). But there is not yet a full-scale application for this process. Moreover, the availability of economic assessments of downstream processing with membrane extraction is limited. It is still unclear whether membrane extraction of acrylic acid by is more economically attractive than the traditional waster wash process.

Given that an economic analysis of membrane extraction for acrylate downstream processing is lacking, a techno-economic assessment (TEA) is presented in this paper to understand the main drivers of the manufacturing costs. The water wash process is also analyzed to benchmark the membrane processes against the traditional process. A representative acrylate 2-EHA is taken as the product in the analysis. The TEA consists of four steps: 1) market study, 2) process flow diagram and mass and energy balance, 3) economic analysis, and 4) uncertainty analysis. Step 1 identifies the market trends, related prices, and competitive processes, etc. Step 2 describes the alternatives in more detail based on their process flow diagrams. It also outlines the modelling assumptions (a) that are key to enable comparability across the evaluation of the selected alternatives and (b) that are specific to each alternative. Further, in Step 2, the mass and energy balances of the two processes are calculated by identifying and quantifying the different input and output streams. Step 3 assesses the economic profitability of the two cases by estimating the manufacturing cost. The technological and economic parameters are integrated by linking the prices of the inputs and outputs to the mass and energy balance of the process. Step 4 entails a Monte Carlo sensitivity analysis to identify the impact of the key parameters on the manufacturing cost. The influence of the input parameters is evaluated by drawing 10,000 observations from the respective distributions and recalculating the manufacturing cost, using the Crystal Ball extension. A triangular distribution (−10%; +10% from the default values) was applied to the input parameters. The rank order correlation can then be used to identify which of the input parameters causes the most variation in the manufacturing cost. This is followed by a local sensitivity analyses on those parameters.

A solute AA distribution equation was formulated to determine the amount of extractant water needed, which determines the cost of the AA removal step in the two processes. The results, shown in Figure 1, indicate that the two processes have the same cost of €1.70/kg 2-EHA for the esterification step. The calculated downstream processing costs of the two processes were €0.87/kg 2-EHA for the membrane process and €0.60/kg 2-EHA for the water wash process. The personnel cost was found to have the largest share in the cost for both processes, which is €0.28/kg 2-EHA. For the water wash process, the cost for AA removal (€0.21/kg 2-EHA) has the second largest contribution. This indicates that there is a margin for improvement from the economic point of view in the water wash step for the traditional downstream processing. Correspondingly, the cost for AA removal in the membrane process has a much higher CapEx for the membrane (€0.25/kg 2-EHA) than the waster wash column (€0.02/kg 2-EHA). This is mostly related to the membrane cost (€1,500/m2) and the membrane area needed (336 m2). However, the membrane process has a lower cost for energy (€0.08/kg 2-EHA) and waste disposal (€0.09/kg 2-EHA) than the water wash process. This is because less extractant water is needed for the membrane extraction process. Therefore, more energy is consumed for the water distillation to concentrate the AA waste solution afterwards, and more AA waste is generated. A global and local sensitivity analysis was carried out to guide the process development by defining the influence of the process parameters on the downstream processing cost. It can be concluded that the membrane parameters have a major impact on the downstream processing cost. This mostly includes the AA flux, cost, extraction time. When the membrane cost is lower than €0.14/kg 2-EHA, the downstream processing cost of the membrane process will be lower than the traditional water wash process.