Ecological and Economic Objective Functions for Screening in

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Ind. Eng. Chem. Res. 1998, 37, 3408-3413

Ecological and Economic Objective Functions for Screening in Integrated Development of Fine Chemical Processes. 2. Stream Allocation and Case Studies Guntram Koller, Diane Weirich, Franz Brogli,† Elmar Heinzle,* Volker H. Hoffmann, Marcel A. Verduyn, and Konrad Hungerbu 1 hler Safety and Environmental Technology Group, Chemical Engineering Department, ETHsSwiss Federal Institute of Technology, CH-8092 Zu¨ rich, Switzerland

Process design in the chemical industry is challenged to integrate environmental and safety aspects in addition to economic and technical considerations in the early development phase of a new process. To achieve this goal, a flexible assessment framework of ecological and economic indices presented in part 1 of this paper is applied to two industrial case studies, one relying on purely chemical literature data and the other including early process knowledge. An allocation method for waste streams, components, and costs is presented and mass loss indices (MLI), cost indices (CI), and ecological indices (EI) are calculated. Using this index system, the ecological and economical problems of a process can be identified at their roots. Hence, this method supports the search for more cost-effective and environmentally friendlier chemical processes. Introduction In the first part of this paper (Heinzle et al., 1998) further referred to as part 1, a general methodology for the ecological and economic assessment of chemical processes during their development was presented. Critical steps in this assessment are the identification and the allocation of waste streams and of individual components in these waste streams. A further important step is to assign these waste streams to appropriate treatment technologies. For cost estimation as well as for the environmental assessment, this allocation is essential since the technology of waste treatment largely influences the real impact of a compound. It would be desirable to validate the methodology presented in part 1 of the paper. This is, however, usually impossible, at least in a strict sense. Most processes and process variations considered in early phases of development are never realized in full scale. Detailed information on those processes which are built on a larger scale is usually not disclosed by industry and only limited information is accessible to the public (e.g., Ku¨ru¨m et al., 1997). Even those processes realized in larger scale are rarely assessed for their actual environmental impact. In this paper some processes were assessed but usually only in historical versions. Most recent versions of operation remain confidential. This is, however, not very important as far as the methodology of ecological assessment is concerned. Therefore, the only validation available at this point is careful reasoning and the presentation of case studies to illustrate the methodology. In this paper the method for calculation of reactor outputs and the allocation method for waste streams * To whom correspondence should be addressed. New address: Technische Biochemie, Universita¨t des Saarlandes, Postfach 15 11 50, Geb.2, D-66041 Saarbru¨cken, Germany. Fax: +49-681-3024572. Tel.: +49-681-3022905. E-mail: [email protected]. † Ciba Specialty Chemicals Schweizerhalle Inc., CH-4133 Pratteln, Switzerland.

and for the distribution of the individual components in these waste streams are described first. Then, the method of cost allocation for the waste treatment processes is presented. The last, but largest part, includes two case studies illustrating how the methodology can be applied. The whole procedure as depicted in Figure 3 of part 1 of this paper is an iterative process. Newly available information can be included as soon as available, thereby expanding balancing regions and making estimates more accurate. Allocation Methods During the earliest steps of process design, where only the desired reaction is considered, just the formation of coupled products is relevant. Stream allocation is not required at this step. Only when information about substrate impurities, degree of conversion, and side reactions is available, a first estimation of expected compounds after reaction makes sense. Reactor Output Estimation. The fate of reaction raw materials is traced through the reaction step as depicted in Figure 1. After the identification and quantification of the substrate impurities, the actual amount of useful starting material is known. In the next steps, thermodynamic and kinetic information must be introduced. In principle, the knowledge of all thermodynamic and kinetic data would allow a complete calculation of reaction products and of conversion. In a first run reasonable guesses may be used. Later, thermodynamic equilibria may be estimated using thermal data, but kinetic data usually require experimental work. Shortcut estimations or screening experiments may provide valuable initial information. Modified thermal measurement methods similar to differential scanning calorimetry may be used for these purposes in the future (Hugo, 1993; Keller et al., 1997; Koch et al., 1970). Possible side reactions should be identified as early as possible. Typically, only the product yield is known from the organic chemists’ early laboratory data. The side reactions have to be estimated by the careful use

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Figure 1. Fate of raw materials during reaction.

of chemical knowledge as given in the literature, as existing as expert knowledge both in academia and industry and as being accessible through software for organic synthesis (Ihlenfeldt and Gasteiger, 1995). This can only be done in a comprehensive way after definition of all auxiliary materials such as solvents and catalysts. Knowledge of the excess of substrate and measurement of nonreacted substrate allows the calculation of the amounts of product, coupled products, nonreacted substrates, and byproducts. Impurities can be considered as inert materials at first. If they are identified and exist in a significant amount, the same procedure as for the identification of substrate side reactions can be used to obtain possible byproducts from these impurities. As soon as the reactor output is estimated, the first part of MLIs (part 1: balance region 1 (reaction) from Figure 1 and equations from Table 1) can be calculated. Next, the fate of individual components has to be tracked through the workup procedures in order to identify and allocate the waste streams which are entering the general waste treatment processes of the plant (balance region 5 from Figure 1 in part 1). Further information about treatment of waste streams can be included, if it is available at the early stage of design, and the real emissions entering the environment can be estimated (balance region 7 from Figure 1 in part 1). Waste Stream Allocation. The principles of phase equilibria are well-established (Prausnitz et al., 1986). The concept of equal chemical potential as introduced by Gibbs is, however, too abstract to be used in design phases discussed here. The translation of this theory into real world is tedious and often needs experimental data not available in these early phases. A simplifying pragmatic approach is therefore required to handle this problem. Extensive knowledge may be introduced even in early stages, if this information is made easily accessible (e.g., Linninger et al., 1996). It is relatively easy to identify gaseous waste streams. Estimating the exact composition is, however, more difficult. In a first approach, equilibrium conditions can be assumed. If the exact thermodynamic equilibria are

not known, ideal behavior may be assumed as a first approach. The vapor pressure of pure compounds is usually known and can be collected from various data sources (e.g., Ullmann, 1985; Kirk and Othmer, 1992). For many compounds and mixtures more precise data are available in data banks (e.g., Dechema, ASPEN PLUS). The assumption of equilibrium conditions corresponds to a worst case scenario when the gas is evaporated from a liquid. If the gas is released after a condensation step, the assumption of equilibrium has to be used with care. A worst case estimation could use the temperature before condensation. Liquid streams are more difficult to estimate. The exact phase behavior is usually not known. Mutual solubilities often known for binary mixtures may serve as first estimates. More detailed evaluation needs adequate thermodynamic models which are only available for a restricted number of components. If exact models or experimental data are not available, estimation methods (e.g., group contribution) may be used to get approximations. If thermodynamic data cannot be obtained, phase distribution has to be judged by experts. Using one of these methods, the individual components are followed through the separation processes and the mass loss indices for MI3 (balance region 3 from Figure 1 in part 1) can be calculated. Cost Allocation. As soon as the waste streams have been identified, a suitable treatment technology and associated costs have to be determined. Methodologies for selecting the optimal waste treatment technology are subject to extensive research projects (Wentz, 1995). However, many of these methods require detailed information about waste streams and a significant amount of time, which often is not available at the early design stage. In the pharmaceutical and fine chemical industry, the possibilities of waste treatment usually are limited to a set of standard treatment technologies which exist at a certain industrial site, such as incineration or biological degradation. Therefore, a first estimation of treatment processes can be done quite early since the composition of the waste stream and the constraints for the treatment systems are known (e.g., threshold values for biological treatment). Additional process-specific waste pretreatment methods have to be identified, if they are required for preparing the process waste for the general waste treatment system of the site (e.g., neutralization). Using this information, all required MLIs can be calculated. (Figure 1 and Table 2 in part 1 of this paper). The costs associated with the waste treatment processes usually are known from cost accounting. In principle, two possibilities exist to allocate these costs to the economic indices. On one hand, costs are distributed according to the relative mass proportions of all individual components of the waste stream. On the other hand, they can be allocated totally to the compounds which are responsible for the required treatment. Using the latter approach, the consequence (of high costs) can be linked to their causes (e.g., byproduct due to bad selectivity). Therefore, this allocation method simplifies the search for improvement options to eliminate or reduce waste. In practice, costs for waste treatment obtained from accounting often are negligible compared to other cost factors, such as raw materials. This can partly be explained by the current system of cost accounting and environmental legislation. In any case, the allocation

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Figure 2. Synthesis routes for 4-(2-methoxyethyl)phenol.

method presented above should be applied, as soon as waste treatment costs significantly contribute to the total costs. In future, this method could be developed further by similarly allocating all expenses for downstream processes. Fixed and/or variable separation costs could, for instance, be distributed to the components which require specific separation methods. Case Studies The assessment methodology presented in part 1 and the allocation methodology presented above are applied to two case studies. The first example shows the early, “chemical” design phase of an intermediate for the pharmaceutical industry. Three different chemical synthesis routes for 4-(2-methoxyethyl)phenol are compared using only information from literature available at the early laboratory stage. The second example is taken from the additive producing industry, where a two-step synthesis of an antioxidant is analyzed using limited process information available at the early process design phase. Early Laboratory Stage. 4-(2-Methoxyethyl)phenol is used as the starting material in the pharmaceutical industry and was produced by Ciba Geigy. It was selected for the case study because there exists a variety of possible syntheses, part of them realized in industry. To resemble the real situation at the early laboratory stage of process design, we applied current methods of literature search (Beilstein-Crossfire Database) as well as general chemical knowledge and selected three promising routes starting from different raw materials and using different reagents, solvents, and catalysts (Figure 2). Following the procedure of Figure 3 of part 1, the goal is to produce the desired intermediate. From literature (route A, Bakke, 1967; Merz, 1973; Ullmann, 1985, 1987a. Route B, Ullmann, 1987b,c; Newman et al., 1949. Route C: Denis and Krief, 1981), the basic reaction conditions, yields, and (where mentioned) selectivities could be obtained for all synthesis steps. With this information the reactor output could be estimated and MLIs for coupled products (CP), byproducts (BP), nonconverted substrates (S), solvents (Solv), and other auxiliary materials for reaction (1Aux) could be calculated for the mass-balance region reaction (Figure 1 in part 1).

Figure 3. Environmental assessment of synthesis of 4-(2-methoxyethyl)phenol. MLI: mass loss index. EI output: output-oriented ecological index. EI input: input-oriented ecological index. 1Aux: auxiliaries required for reaction. Solv: solvents. 2Aux: auxiliary materials required for downstream processing. S: nonconverted substrates. BP: byproducts. CP: coupled products. id: product.

Next, cost indices and ecological indices were determined for this process. Economic indices were calculated using prices from commercial catalogues (Fluka, 1995/96) and waste treatment costs from industry according to the equations presented in Table 6 of part 1. For obtaining more realistic cost indices, industrial raw material prices should be used. Therefore, the presented costs do not represent real values. They should, however, allow comparison. For the environmental classification of input and output materials, we applied the ABC-classification scheme presented in Tables 3 and 4 of part 1. Each compound was assigned to a certain class in each category using information from public data collections (Hommel, 1995; ECDINonline databank, etc.). If no environmental data could be obtained for specific substances, we used data of comparable compounds, for instance, di-tert-butylphenol instead of all substituted phenolic products and byproducts. According to the methodology, the value of 4 was used for each class A membership and the value of 1.3 for each class B membership. By multiplying these factors the final environmental factors (EF) were obtained and used for calculation of the EIs. Environmental factors and class membership values of all compounds used in the case studies are presented in Table 5 of part 1. So far, all indices of balance region reaction (region 1 of Figure 1 of part 1) were determined. After the results of this initial design estimate were investigated, major problems can be identified and the redesign and improvement process can start. The system boundaries should further be expanded as soon as additional information about product recovery and purification or waste pretreatment is available. Product losses (Loss) during separation as well as energy, material, and equipment requirements could be considered to calculate the indices corresponding to regions 3 and 5 of Figure 1 (part 1). However, for this case study no such information was available from literature or industry and would be available at the very early design stage. Only the auxiliaries required for neutralization of the reaction mixture could be estimated at this point. This information (2Aux) was included in the results of the case study. Figure 3 shows that these processes are quite material-intensive, as all of them require between 35 and 50 kg of raw materials for 1 kg of product. Additionally,

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Figure 4. Comparison of different synthesis steps of route B of Figure 2.

60-75% of lost mass is caused by solvents. This fact is not acceptable for industrial production. The search for improvement could start with looking for solvent-free processes or solvent recycling. When the outputoriented EIs are analyzed, the key compounds causing environmental problems can be identified (Figure 3). In routes A and B, EIBP is dominant because of the high mass of byproduct of nitration (step 3, route B) and formaldehyde addition (step 1, route A) combined with the strict regulation of nitroaromatic compounds in the environment. If these problems are unacceptable for the design, they must be solved before advancing in the project. Possibilities would be to search for enhanced selectivity or to completely change the reaction pathway. If the input-oriented indices are applied, coupled products are the major contribution besides the solvents in routes A and B. About 50% of the raw materials (including dimethyl sulfate as a carcinogenic compound in stoichiometric amounts) are lost in steps 2 and 3 of route A (steps 4 and 5 of route B) due to the high mass of coupled product. For route C, all indices are similarly dominated by the mass of the solvent, which shows that simple and nonproblematic raw materials are used and that comparably “harmless” waste is produced. Therefore, improving this route would mean to question the need of solvents or to find ways of recovering them. In Figure 4, we compare different synthesis steps of route B according to their relative importance. Steps 5 for the MLI and 3 for the EI can be identified as major contributions to the index for the whole process. These process steps or the preceding ones should further be investigated before the design can be accepted. Combining these indices, some key problems of all three processes can be identified at one sight. Consequently, the research for improvement options can be directed at the most important points. However, it must be mentioned that this method does not allow a quantitative calculation of environmental impacts of a process alternative because later emissions of the (optimized) process will always be different from estimated waste streams from the early process design phase. Therefore, the optimal reaction route cannot be determined for sure at this level of information. Each process should first be optimized starting at the mentioned improvement options, and the system boundaries should be expanded to include separation and waste pretreatment. Remaining economic and process safety aspects should be taken into consideration. There is only one indication that route C probably will cause less problems during the further design process. The output-oriented EI of this route is significantly lower. Therefore, routes A and B might require larger efforts of costs and time

Figure 5. Process for methyl-3-(4-hydroxy-3,5-di-tert-butylphenyl)propanoate. ASME: methylacrylate. DTBP: 2,6-di-tert-butylphenol.

Figure 6. Production of stearyl-3-(4-hydroxy-3,5-di-tert-butylphenyl)propanoate.

during the design or operation of waste pretreatment facilities. This result of route C as the most promising process alternative is supported by the fact that route C is mainly used by industry today. The CIs for the different routes (not shown) have compositions similar to the MLIs apart from the decreased importance of solvents, because water, a comparably cheap solvent, was used in most synthesis steps. The calculated waste treatment costs were negligible in all processes. Therefore, no additional information for comparing these processes could be obtained from the CIs. Cases with Limited Downstream Knowledge. For the second case study, a two-step process to an antioxidant, stearyl-3-(4-hydroxy-3,5-di-tert-butylphenyl)propanoate, was assessed. The first step (Figure 5) was an aromatic addition of methylacrylate (MA) to 2,6-di-tert-butylphenol (DTBP) catalyzed by NaOCH3. After the reaction was quenched with acetic acid, the resulting methyl-3-(4-hydroxy-3,5di-tert-butylphenyl)propanoate was separated by distilling off MA as a nonconverted substrate and methanol as a catalyst residue. The crude intermediate was purified by crystallization using 2-propanol (86%) as a solvent. The second step (Figure 6) consisted of alcoholysis of the intermediate replacing methanol with stearol and using lithiumamide as a catalyst. To achieve complete conversion, methanol as a coupled product was distilled off. Similar to the first step, the reaction was quenched with acetic acid and the product, stearyl-3-(4-hydroxy-3,5-di-tert-butylphenyl)propanoate, was crystallized, washed, and dried. A large part of used solvent for crystallization and washing (2propanol and water) was regenerated via distillation and reused. To mimic the early development phase, we used industrial operating instructions of a historical version of this process for setting up the material balances. The

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Figure 7. Ecological assessment of synthesis of stearyl-3-(4hydroxy-3,5-di-tert-butylphenyl)propanoate. Cat: catalyst. Imp: impurities of raw materials. Loss: product loss during workup. For other indices see Figure 3.

Figure 8. Economic assessment of synthesis of stearyl-3-(4hydroxy-3,5-di-tert-butylphenyl)propanoate. MLI: mass loss index. CI: cost index. For other indices see Figure 3.

balance region includes reaction as well as product recovery and purification, which corresponds to region 3 from Figure 1 in Heinzle et al. (1998). Overall yields, amounts of byproducts, raw material, and recycle streams, could directly be taken from industrial data, whereas the individual composition of waste streams and the yields of single process steps had to be estimated using simple rules of thumb (e.g., total removal in distillation, 90% yield in crystallization, 30% of washing liquid adsorbed on crystals, regenerated solvent with no impurities). These rules are based on industrial experience. On the basis of this information the MIs of balance region 3 (Figure 1, part 1) were calculated. To obtain CIs and EIs, raw material prices and industrial waste treatment costs as well as the class memberships in all environmental categories were determined. As described in the first case study, environmental factors were fixed (Table 5, part 1) and the second part of the index system (EI, CI) was calculated. The results are presented as relative values in Figures 7 and 8. Absolute values could only deliver additional information, if different processes were compared, since the ABCcharacterization scheme is based on relative values. Both synthesis steps represent partly optimized batch processes as 35-40% of total mass is converted into product. Nearly all of the lost mass is caused by the auxiliaries for downstream processing (MLI2Aux) (i.e., water and 2-propanol required for washing. On the basis of MLIs, reducing the amount of washing solvent is the only obvious option to improve the design. However, applying environmental factors completely changes this result. The most problematic substances arise from product losses (EIloss) during workup as well as incomplete conversion (EIS) and low selectivity (EIBP) for the first step. As these substituted aromatic phenols

exhibit high persistence and aquatic toxicity, they are classified as class A in the category water pollution. As they must not be released to the aqueous environment, special treatment of all aqueous waste streams is required. The high weighing factor is applied not because of environmental pollution of the real process (as the aromatic phenols must and will not be released) but because of the additional complication of process design due to the required waste treatment technologies. The recovered product itself is not considered in the output-oriented index according to the methodology. For improving the design, three starting points are obvious (conversion, selectivity, and separation). Product losses can only be minimized by improving the crystallization and washing steps. The possibility of a total change of the separation concept (distillation) should be studied. Such a new separation concept could allow the recycling of nonconverted raw materials, hence reducing the EIS. The problem of byproducts can only be reduced, if first all substances are identified and the mechanisms of all reactions are investigated. With this knowledge the relevant factors of influence can be identified and the reaction conditions (solvent, catalyst, dosing profile, temperature) can be changed in order to reduce EIBP. The input-oriented EIs show that two-thirds of ecologically important raw materials (65%) are converted into the product. This fact seems to be satisfying and does not lead to additional conclusions for the design. Further process optimization should therefore try to reduce the output-oriented indices, for instance, by improving the workup process to minimize product losses. The economic assessment in Figure 8 indicates that the costs exceed the hypothetical minimum product price only by 60%. In other words, besides the unavoidable raw material costs for the product itself (CIP), 60% of additional expenses are required because of auxiliary materials, byproducts, and so forth. Waste treatment costs (CIWaste), which included only actual volume-based cost rates for industrial wastewater treatment, were negligible when allocated to individual categories and therefore lumped into an overall waste term. However, it must be mentioned that equipment and indirect costs (CIequip, CIInd) of downstream processing units were not considered since they would hardly be available at the early design stage. If considered, they could lead to a significant increase of the indices of those compounds which are difficult to separate (CIBP, CIS). Conclusions The case studies used here clearly show that the presented economic and ecological objective functions can easily be applied to characterize a chemical process at its early design stage. With only basic information about the reaction, the corresponding indices can be calculated and used for improving processes and comparing alternatives. These basic values can further be refined with process information as the design process evolves. If a combination of input- and output-based environmental indices (EI) is applied in addition to the mass loss and cost indices (MLI, CI), a comprehensive impression of the problems of a process can be obtained on one sight. Consequently, the most promising starting points for improving the design of the process can be identified. Process safety issues not considered so far are currently being implemented in the index

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system. Using the presented allocation method, the origins of the problems can be identified easily. Therefore, this index system could present a useful assessment framework for the integrated development of chemical processes at their early stages. Acknowledgment The authors thank Oemer Kut and Martin Scheringer of ETH, Zu¨rich, for reading the manuscript and Willy Regenass for the suggestion of the first case study. Nomenclature MA ) methylacrylate CI ) cost index (economic index) EI ) environmental index MI ) mass index MLI ) mass loss index Indices 1Aux ) auxiliary materials for reaction 2Aux ) auxiliary materials for product recovery and purification BP ) byproduct Cat ) catalyst CP ) coupled product Imp ) impurities of raw materials Loss ) product loss during workup P ) product S ) nonconverted substrate Solv ) solvent Waste ) related to general waste treatment

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Received for review November 17, 1997 Revised manuscript received May 14, 1998 Accepted May 18, 1998 IE9708541