Environmentally Conscious Design of Chemical Processes Based on

Article Cite This: Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

pubs.acs.org/IECR

Environmentally Conscious Design of Chemical Processes Based on Prediction of Environmental Damage Alencar Heidrich,* Marcelo Farenzena, and Jorge O. Trierweiler

Downloaded via UNIV OF LOUISIANA AT LAFAYETTE on January 16, 2019 at 14:40:55 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

Grupo de Intensificaçaõ , Modelagem, Simulaçaõ , Controle e Otimizaçaõ de Processos (GIMSCOP), Departamento de Engenharia Química, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Rio Grande do Sul 90040-060, Brazil ABSTRACT: In environmentally conscious design of chemical processes, environmental assessment is applied systematically during each of the different stages of the conceptual design process to help select options that are benign from an environmental perspective. Nevertheless, deviations from the design conditions over the course of operation of the industrial plant may compromise the environmental performance that was initially forecast, causing environmental damage liable to compensation. This paper presents an alternative method for assessment of chemical processes that is based on utilization of an index called the Environmental Return TimeERT. This index represents, for a given set of design conditions, the time needed to compensate for predictable environmental damage and return to an acceptable level of environmental quality. A case study is used to demonstrate application of the proposed method to a stage of the conceptual design phase of a process for production of benzene by hydrodealkylation of toluene (the HDA process). In this case study, the design conditions for the conversion reaction and for the gas purge fraction of the process that will enable an ERT ≤ 1 to be achieved are defined. This exercise, based on selection of alternative design options from an environmental perspective, leads to the conclusion that utilization of the ERT index enables choice of environmental quality criteria with lower subjectivity than utilization of absolute values for potential environmental impacts. The study’s results also include prediction, during the design phase, of the operational conditions and the time operating under these conditions necessary to compensate in advance for the environmental damage that is likely to occur during the life cycle of the operation.

1. INTRODUCTION Since the 1960s, significant progress has been achieved in development of techniques to facilitate synthesis of chemical processes. This progress was driven by the need to overcome obstacles created by changing economic scenarios and to incorporate new objectives. Initially, methods for synthesis of chemical processes only had one objective: to maximize their economic performance. Gradually, environmental variables were incorporated into the design process in the form of a cost factor applied to the fixed investment capital. This factor, which ranged from 8 to 35% of the fixed investment capital, covered, among other services and facilities, the costs of investments in installations for treatment and disposal of industrial waste.1 External factors, such as intensification of environmental regulations and the chemical industry’s public image, placed additional demands on development of chemical processes. According to data from 1996, the North American chemical industry’s capital investment and operating costs expenditure on measures for control and remediation of environmental damage totaled around US$ 14 billion/year, which is comparable to the sums spent on research and development.2 These elevated costs are a consequence of the conventional design process, which introduces environmental control © XXXX American Chemical Society

techniques after synthesis of the structure of the process. When the environmental variables are not considered in the preliminary design brief, the results of the chemical process are suboptimal.3 These factors drive incorporation of environmental variables into design of chemical processes, using an approach known as environmentally conscious design of chemical processes.2 These variables are measured using environmental impact potentials, which in turn are used to calculate the magnitude of the environmental performance of the process. However, over the operational life cycle of a chemical plant, departures from the original design conditions can cause a process to exceed its projected industrial emissions. When emission loads exceed what the ecosystem can sustain, environmental damage occurs, and all environmental damage that cannot be reversed must always be compensated for. Therefore, if the process design method does not take into account the risk of such departures, even processes designed to incorporate techniques for prevention of pollution may be Received: Revised: Accepted: Published: A

August 23, 2018 December 31, 2018 January 8, 2019 January 8, 2019 DOI: 10.1021/acs.iecr.8b04074 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

Article

Industrial & Engineering Chemistry Research

Process integration is based on formulation of problems of synthesis of chemical processes described in the form of mass and energy integration networks. The integration networks consist of mathematical models that represent the chemical process in the form of structures of reuse and recycling of materials and energy streams, and the objective is to minimize consumption of natural resources. Process integration projects employ graphical procedures and mathematical programming to obtain processes with maximum integration and the greatest economic performance.7,8 Nápoles-Rivera et al.9 presented a mathematical representation for minimization of the total annual cost of an integrated process, including, in addition to the process restrictions, environmental restrictions in the form of restrictions on properties such as toxicity, pH, and chemical oxygen demand, among others. In life cycle analysis (LCA), even greater attention is paid to the environmental impacts caused by the production process. All of the stages in the production chain of a product are considered, from extraction of the raw materials to final disposal. This type of analysis, known as cradle-to-grave analysis, employs metrics to determine the environmental impacts caused along the production chain. This approach includes environmental variables in the design objectives. Here, chemical process synthesis is solution of a multiobjective optimization problem, in which total annual cost and environmental impacts are minimized. Since LCA considers the entire production chain, the greatest reductions in environmental impacts may occur in stages that are external to the main production process. The optimization problems are formulated to obtain solutions using LP or MILP mathematical programming.10,11 In environmental impact assessment, the way that the environmental variable is considered within design of chemical processes is similar to LCA. Environmental variables are not incorporated into the design brief as restrictions but as objectives. Environmental impacts are defined using metrics to measure potential impacts, and the optimization problems formulated during process synthesis are of the multiobjective type. Unlike LCA, the assessment of environmental impacts in the chemical process is not committed to considering the entire production chain, but only the main production process. Garciá and Caballero12 provide an instructional description of how to include environmental impacts in the objectives of chemical process designs. Li et al.13 employed this approach in a process synthesis for DMC production, using a genetic algorithm (NSGA-II) to solve the optimization problem. These different approaches to environmentally conscious design of chemical processes can be employed during the conceptual design process. Development of the conceptual design for a chemical process involves application of hierarchical procedures that combine heuristic rules and mathematical procedures based on the solutions to optimization problems.1,14 In both cases (heuristic rules and optimization problems), the conceptual design of a chemical process must employ a function for environmental performance to delineate the set of possible process alternatives that offer an acceptable environmental result, which can then undergo economic feasibility analysis.

susceptible to causing environmental damage, which in turn must be evaluated and compensated for. This paper presents a method for assessing the environmental performance of chemical processes, utilizing the concepts of environmental damage and compensation. The objective of this new approach to environmental assessment of chemical process designs is to determine in advance the conditions necessary for compensation of foreseeable environmental damage. Thus, the design choices made on the basis of this criterion should avert the need for future commitments to compensation. In this method, the environmental damage caused over the operational life cycle is predicted and a method for compensating this damage is incorporated. The procedure for environmental compensation considered is similar to the Habitat Equivalency Analysis (HEA) method,4 but it has been adapted to employ potential environmental impacts as the unit of measurement. The approach converges to a proposed index of environmental performance, which, as will be demonstrated in the subsequent sections of this paper, is committed to minimizing the subjectivity involved in measurement of the environmental quality of different alternatives when designing chemical processes. The main body of this paper begins by reviewing the concepts involved in environmentally conscious design of chemical processes, before moving on to environmental metrics. A function is then derived for calculating the environmental performance index Environmental Potential of Emissions (EPE), formulated using metrics employed for specifying the environmental characteristics of chemical processes. After formulation of the EPE function for determination of potential environmental impacts, the environmental performance index Environmental Return Time (ERT) is presented. This index is based on the concepts of prediction and compensation of environmental damage. Finally, these concepts are applied in a case study, in which the EPE and ERT indexes are used to conduct an environmental assessment of the design conditions of a hypothetical plant for production of benzene by hydrodealkylation of toluene, using the HDA process.

2. ENVIRONMENTALLY CONSCIOUS CHEMICAL PROCESS DESIGN Cano-Ruiz and McRae2 identified four approaches to designing chemical processes that are conscious of the environmental perspective: inclusion of systems for waste treatment in the process structure; integration of processes; life cycle analysis; and assessment of environmental impacts. Inclusion of systems for waste treatment in the process structure takes installations for treatment and final disposal of industrial waste into the preliminary design. The objective of the chemical process design is still to maximize economic performance, but the pollution control processes are defined together with the primary equipment, enabling the design to meet environmental restrictions. Ulrich and Vasudevan5 have proposed methodology for selection of systems for treatment of industrial emissions in the preliminary designs of processes. Linninger and Chakraborty6 formulated an optimization problem incorporating flow diagrams for waste treatment into the chemical process. Their model includes environmental restrictions defined from the industrial emissions standards defined in regulatory instruments. Integration of the process and of the pollution control techniques is achieved using mathematical programming.

3. ENVIRONMENTAL POTENTIAL OF EMISSIONSEPE There are several indices available in the literature that have been proposed for quantification of environmental impacts.15 B

DOI: 10.1021/acs.iecr.8b04074 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

Article


exergy, the greater the work needed to bring wastes to their natural state and the greater the environmental impact.30 Considering only the chemical contribution relating to the type of waste as a measure of the exergy content, PEI can be computed as follows:

These metrics enable environmental models to be constructed using Potential Environmental Impacts (PEI or E). The first class of models quantify E based on the ratio of the rate of pollutant emission and its maximum acceptable concentration (MAC). Fathi-Afshar and Yang16 used threshold limit values (TLV) and lethal dose 50 (LD50) to assess MAC. The maximum allowed value (MAV), which is fixed by environmental regulations, may also be used to assess MAC, but this criterion is not universal, because the MAV may differ between regions.17 According to this metric, E is given by the volume of the environmental compartment contaminated by a given pollutant. Guinée et al.17 presented a classification for environmental problems, in three groups: depletion, pollution, and disturbances. Within these groups, the main environmental impact categories used for the purposes of chemical process analysis are depletion of natural resources, global warming, ozone depletion, acidification, photochemical oxidant formation, eutrophication, human toxicity, ecotoxicity, and, finally, solid wastes. For each category and compound, there is a characterization factor that multiplies the respective emission rate. This approach sets an index Ek for each environmental impact category k. Multiobjective analysis procedures using these multiple environmental indicators have been employed for LCA.18,19 Decision-making procedures using sets of multicriteria indicators are more complicated. Thus, efforts have been made to combine environmental properties into single indicators. Two examples of such single indicators are the Eco-Indicator 95 and its updated version, the Eco-Indicator 99.20 Other metrics that quantify the environmental impact using a single indicator have also been proposed, including the Sustainable Process Index (SPI),21 the Waste Reduction algorithm (WAR),22,23 and the Standard Chemical Exergy (SCE) indicator.24 The WAR metric was developed by United States Environmental Protection Agency (USEPA). This metric generates a single indicator for environmental impact assessment based on impact categories. The complete procedure for formulating the index has been described in work by Cabezas et al.22,23 and Young and Cabezas.25 Here, the PEI given by WAR (E) will be determined for industrial emissions as follows:

i=1

∑ fi wi i=1

(2)

where Mi is the molecular weight of the pollutant i and the bch,i is the standard chemical exergy of the component i, which is given by ne

bch, i = ΔGf,0i −

∑ νjbch,0j j=1

(3)

ΔG0f,i

where is the standard Gibbs energy of formation of the component i, ne is the number of elements j in the reference standard state, b0ch,j is the standard chemical exergy of the element j, and νj is the stoichiometric coefficient of the formation reaction from the elements j of the reference state for the component i. Definitions of the reference environment as the reference standard state and data on the chemical exergy of elements have been published in the literature.31,32 The environmental impacts calculated using WAR and SCE are not equivalent. These metrics have different meanings. The characterization factors used for the WAR metric are higher for more hazardous molecules. In contrast, the characterization factors used for the SCE metric are higher for more complex molecules, since their exergetic content is higher. The features of these two metrics, WAR and SCE, provide complementary information, and both are important for assessment of the potential environmental impact. Therefore, in this paper these properties are both used to calculate a new, single index called the Environmental Potential of Emissions (EPE). This proposed index is the product of two factors, a factor to represent the hazard potential of pollutants and another to represent depletion of natural resources by these pollutants, and is given by

ij B S yz E = KWAR jjj WS zzz jB z (4) k P{ In eq 4, the first factor KWAR is expressed in PEI/h or PEI/ year and is the portion of the environmental impact that is computed using the WAR metric alone. This factor is used to assess the impact of hazardous substances. The second factor is given by the dimensionless ratio BSW/BSP, where BSW is the standard chemical exergy of the emissions and BSP is the standard chemical exergy of all product streams leaving the process, including waste streams. This second factor is a measure of the magnitude of the irreversibility of emissions. Irreversibility means the work needed to return the emissions to the natural reference state; i.e., it represents the natural resources used to restore the natural reference state. In other words, the second factor is a correction factor applied to the first factor that matches the properties of SCE to the properties of WAR. One can make an analogy between eq 4 and equations for modeling transport phenomena. Given a transport property, the flow of the process transfer J is proportional to the potential difference between the current state and the equilibrium state of that property. The proportionality constant gives the rate at which this transport occurs through

n

E=

i wi yz zz zz M i k {

∑ bch,ijjjjj n

E=

(1)

where wi is the sum of the total emissions rate of pollutants discharged into the environment, n is the total number of components considered as pollutants, and f i is the impact potential factor for component i. The units of E are PEI/h, and the potential factors for the environmental index can be computed using the WAR GUI software, available at http:// www.epa.gov/nrmrl/std/war/sim_war.htm. The SCE metric24 represents the chemical contribution of the exergy content of a process stream. The exergy of the emissions is the maximum work done by process streams to bring the components from their current state to equilibrium with a reference state. This property has been used to assess the thermodynamic efficiency of chemical processes.26−28 When the reference state is the natural environment, exergy represents the maximum work done by a stream to reach equilibrium with the natural environment.29 The greater the C


Article


risk of occurrence of environmental damage. Failures that cause environmental damage can be predicted by, for example, considering uncertainties in the design or from knowledge of similar processes that are already operating. To enable these predictions to be incorporated into the design of a new chemical process, an environmental risk factor (ERF) is defined as follows:

these different potentials. The model of this process is as follows: J = K(Φ − Φ*)

(5)

where K is the transport coefficient, Φ is the current potential related to the transferred property, and Φ* is the equilibrium potential. The potential difference, also written as ΔΦ, is associated with the quantity or intensity of the transferred property as a consequence of the process irreversibility. Thus, flow J is the product of the rate of transference and the factor that measures the irreversibility. This model is analogous to the environmental model proposed, in which the rate of environmental impact is the product of the rate of transferred impact of the emission, KWAR, and the factor BSW/BSP, which quantifies irreversibility as the work needed to bring the chemical species back to a state of equilibrium with the environment.

erf =

(8)

Minimum compensation is determined as the equality in the in eq 7. Assuming this equality and rearranging the equation, we have θC ΔE D/E P = θD 1 − EC /E P

4. ENVIRONMENTAL RETURN TIMEERT This subsection presents the Environmental Return Time (ERT) index, which is intended to enable classification of chemical process designs in terms of their environmental performance, using measures of potential impacts. The ERT has a fundamental difference to the equivalent indexes reviewed in Section 3. As will be shown, ERT is determined on the basis of estimates of the environmental damage that will occur over the life cycle of a chemical process design, making it possible to conduct a predictive analysis of this operational problem while still in the conceptual design phase. The process of deriving this index from measures of the potential environmental impacts of the chemical process will now be presented. Consider a chemical process, the industrial emissions from which meet the environmental limits defined by the regulatory authorities. The potential environmental impact of these emissions can be given as EP. As these limits are exceeded, environmental damage is caused and the potential environmental impact is increased by a quantity ΔED. The time elapsed between the start and the end of environmental damage is given by θD. The magnitude of environmental damage can be assessed using the product of the increment ΔED and the time elapsed θD, as shown in expression 6: {Magnitude of Environmental Damage} = θDΔE D (6)

(9)

The term to the left of the equality sign in eq 9 represents the number of years needed to compensate for one year of environmental degradation, i.e., the time needed to return to compensated environmental quality, per unit of time under degradation conditions. This time ratio is defined as the Environmental Return Time (ERT). The definitions of ERT and ERF enable eq 9 to be rewritten as follows: ERT =

ERF 1−

EC EP

(10)

Analyzing expression 10, it was observed that the lower the value of EC, the lower the value of ERT, i.e., the shorter the return time needed to ensure environmental compensation when the process causes environmental damage, and, consequently, it can be stated that the lower the value of EC, the better the environmental performance of the design. In other words, if the predicted industrial emissions of a new chemical process design result in a low potential environmental impact (low EC), one that is below the limit accepted by EP, then the design will be compensating in advance for environmental damage that may occur over the course of its operation. The ERT index can therefore be used to evaluate the environmental performance of different alternatives during the conceptual design stage of the chemical process. Once the alternative that offers the best environmental performance has been selected, the ERT value can be employed to define prior compensation of damage that may occur with the magnitude given by ERF, since, when put into operation, the process will produce environmental impacts below the limits accepted by the regulatory authorities. Additionally, if the environmental objective is to operate with impact potentials lower than the values established by regulatory limits, it is possible to use the modified ERT index. For this, we use ERF = (ΔED + δ)/EP, where δ is the decrease defined as reduction on the EP. The viable values of ERT are dependent on EC, which has a range of variation given by 0 < EC ≤ EP. Thus, these limits can be determined from eq 10, as shown in the following the expressions:

Environmental damage ceases when the potential environmental impact returns to the value of EP as a result of implementation of environmentally conscious design techniques. However, although the conditions that return potential environmental impact to EP have been reestablished, the environmental damage caused previously is not recoverable and so the principles of environmental compensation discussed by Dunford et al.4 are applicable. Environmental compensation can be achieved by implementing design changes that reduce the potential environmental impact to a value given by EC, which is lower than EP. This state of compensation should be maintained for a period of time referred to as the compensation period θC. The following restriction must be met to guarantee environmental compensation: θC(E P − EC) ≥ θDΔE D

ΔE D EP

lim ERT = erf

EC → 0

(7)

lim ERT = ∞

EC → E P

Using eq 6, environmental damage can be measured as it takes place, throughout the industrial operational life cycle. However, during the design phase, it is necessary to predict the

(11) (12)

The results of expressions 11 and 12 show that the ERT index could take values between the limits ERF ≤ ERT < ∞. D


Article


Figure 1. Flowsheet of the HDA process case study.

5.1. HDA Process. In the HDA process, benzene (C6H6) is produced by a reaction between toluene (C7H8) and hydrogen (H2) in a gas-phase reactor at 1150 °F and 500 psia.1 The equations for this reaction system are as follows:

When the value of EC approaches the maximum potential impact permitted, EP, there will be no environmental compensation, and, obviously, ERT tends toward infinity. When the value of EC tends toward zero, ERT tends toward the finite value ERF. This result shows that there is a minimum finite value that the ERT index can take. For example, this signifies that for ERF = 0.5 and θD = 2 years, it is impossible to compensate for the resulting environmental damage within a time period for which θC < 1 year. The next subsection presents a conceptual design case study in which the ERT index is utilized to classify the environmental performance of alternative process options and then goes on to discuss the results and their significance for design and operation of the chemical process.

C7H8 + H 2 → C6H6 + CH4

(13)

2C6H6 ⇔ C12H10 + H 2

(14)

This reaction system produces two industrial waste products, a liquid waste, diphenyl (C12H10), and a gaseous waste, comprising a mixture of methane (CH4) and hydrogen. Elevated process selectivity guarantees that a low quantity of diphenyl is produced. The feedstock contains excess hydrogen which should be returned to the reactor via a gas recycle. However, in addition to the hydrogen, the gas leaving the reactor also contains the methane that has been formed and which cannot be allowed to accumulate in the process. Accumulation of methane in the gas system is avoided using a gas purge. The process is illustrated schematically in the flow diagram shown in Figure 1. Formation of industrial wastes in the HDA process is influenced by the rate of conversion of toluene and by the ratio between the purge volume and the total volume of gas leaving the flash drum. The higher the conversion of toluene, the higher the rate of formation of pollutants such as methane and diphenyl. In addition, increasing the ratio between the purge and the recycle of gas also increases the emission rate of pollutants such as methane. However, there is an interaction

5. CONCEPTUAL APPLICATIONHDA CASE STUDY The HDA process, hydrodealkylation of toluene, has been used as a case study for analysis of problems related to design of chemical processes. Douglas1 and Smith14 used the HDA process to illustrate application of the stages of a hierarchical procedure for designing chemical processes. Dimian33 used the HDA process to analyze chemical process and control structure design. Here, the HDA process will be used to show how the concepts developed in Sections 3 and 4 could be applied to a preliminary stage of the conceptual design of this chemical process. All results in this case study were produced using the HYSYS process simulator. E


Article


Figure 2. Behavior of potential environmental impact under different conditions of gas purge fraction and reactor conversion percentage in the HDA process design.

Figure 3. Behavior of ERT under different conditions of gas purge fraction and reactor conversion percentage in the HDA process design.

between these variables, since the drop in the conversion also increases the gaseous recycle, increasing the concentration of pollutants, while promoting the reduction ratio between purge and gas recycling. Therefore, the specifications of these variables, conversion percentage and purge fraction, influence the design’s environmental performance. In this example application, the effects on the environmental return time of these two process variables are determined via process simulation. 5.2. Environmental Performance Data. Environmental performance data were obtained from the simulation results of processing 100 kg mol/h of toluene, with conversion values ranging from 20 to 90% and purge fractions from 10 to 0.1%. The potential impact of emissions was determined for each of these conditions using the eq 4. These results are shown in the graph in Figure 2, which relates the potential environmental

impact to different values of the gas purge fraction, under a range of different conditions defined for reactor conversion percentage. Using the data for the potential environmental impact of the process illustrated in Figure 2, ERT values were determined using eq 10. This was done by assuming that the potential environmental impact values correspond to the value of EC for each alternative design option. In this example, the ERF values and the restriction value EP were set arbitrarily to 0.5 and 100 PExI/h, respectively. The results of this step are illustrated in Figure 3, in a graph that relates the ERT values to different conditions set for purge fraction and reactor conversion percentage. 5.3. Discussion of the Results. Observing the results shown in Figure 2, it can be seen that, for conversion rates of 50% and greater, there is a point of maximum environmental F


Article


compensation are incorporated into the design phase. To achieve this, an ERT (environmental return time) index is proposed. In analogy to PBT (pay back time), used for economic analysis of designs, the ERT index signifies the return time needed for environmental compensation per unit of degradation time. This index is defined from three elements: the maximum allowable potential environmental impact, determined from limits set by environmental regulatory authorities; predicted environmental damage, expressed as an incremental fraction of the maximum potential environmental impact allowable; and the potential environmental impact, determined from the design conditions selected for compensation of predicted environmental damage. The potential environmental impact is evaluated using the proposed index EPE (Environmental Potential of Emissions), which combines the properties of the WAR (Waste Reduction) and SCE (Standard Chemical Exergy) indexes. An application of the ERT index to selection of design conditions was demonstrated in a case study of the hydrodealkylation of the toluene process for benzene production (the HDA process). The results of this example enabled each design condition for variables of the chemical process (gas purge fraction and conversion rate) to be related to the time needed to compensate for an assumed environmental damage of 50% of the maximum allowable environmental impact of 100 PExI/h, per unit of time elapsed under degradation conditions. Since all environmental damage must be compensated, definition of the maximum production campaign length of the processing unit that can be dedicated to this purpose is a criterion that opens an objective dialogue with the decisions taken in the operational management scenario. This minimizes the subjectivity associated with definition of environmental criteria, contributing to selection between alternatives for an environmentally conscious design. In the case study conducted for this paper, it was possible to limit conversion of the environmentally safe reactor, for ERT ≤ 1, to the range 20 to 60%, irrespective of the gas purge fraction employed. The contribution of the two indexes ERT and EPE, proposed in this work, can be summarized as the ERT index introduces the need for an increase in the reduction of the environmental impact potential in addition to the conventional objectives, due to the predicted environmental damage. In addition, this index is formulated in time-of-operation units, assigning a practical meaning from the industrial point of view; the EPE index, used to size the environmental impact potential, adds complementary characteristics such as dangerousness and irreversibility of pollutants. Another relevant conclusion that can be drawn from this exercise is the fact that, if the environmental damage can be predicted, the design conditions that compensate this damage can also be defined in advance. In other words, compensation can be achieved in advance, conferring a period of credit with duration equivalent to 1/ERT, during which environmental damage can occur, for each unit of time during which the process is operated with potential environmental impact below the maximum allowable value.

impact caused by industrial wastes. This is because, as the purge fraction is reduced from 10 to 3% of the recycle volume, the recycle volume itself also increases, producing high levels of gaseous waste emissions. However, when the purge fraction is reduced from 3 to 0.1%, the volume of the waste gases is curtailed drastically, reducing the corresponding potential environmental impact. At low conversion percentages, this behavior is no longer pronounced, since the recycle volume is already high, irrespective of the purge fraction. For higher conversion rates, the potential environmental impact is not very sensitive to the purge fraction, since it is more correlated with the low selectivity of the reaction system that generates higher volumes of waste diphenyl in the liquid state. Determination of the potential environmental impact of the process enables the environmental performance of different design conditions to be delimited. However, the absolute value of the potential environmental impact does not have a practical correlation with operation of the environmentally safe process, unless a restrictive maximum value is set as a target. A similar analysis of the environmental performance profile can be conducted on the basis of determination of the ERT index, as illustrated in Figure 3. The results illustrated in Figure 3 show that at 90% conversion, the reactor produces negative ERT values, which classifies these design conditions as nonviable from an environmental perspective. Ruling out this option, choice of the remaining design conditions is limited to conversion rates ranging from 20 to 80%. The choice between options that fall within the range of conditions that are viable from an environmental perspective can be based on the operational significance of the ERT index, which offers a closer relationship with operational management of the process. The ERT index indicates the period of time for which the industrial process must be operated under the conditions of reduced potential environmental impact to compensate for the damage produced over a unit time period (1 month, 1 year, etc.). If, for example, the selection criterion is ERT ≤ 1, this signifies that, if the process causes the predicted environmental damage for around 1 year, environmental compensation with a duration of 1 year, whether before or after the damage occurs, will be sufficient for design conditions that result in ERT values ≤ 1. To illustrate this, applying a criterion of ERT ≤ 1 to the results illustrated in Figure 3, it can be observed that conditions with 80% conversion have poor environmental performance and can be ruled out, limiting choice to conditions with conversion rates within the range of 20 to 70%. Conversion rates of 20 to 60% give ERT values lower than 1 for any purge fraction employed and the design criteria to be used are therefore no longer restricted to environmental criteria. It can also be observed that conversion rates in the range from 20 to 50% and purge fractions lower than 1% ensure ERT values close to the minimum viable value of 0.5, corresponding to the value established for ERF. For a conversion rate of 70%, the purge fraction should be less than 3% or greater than 4% to give ERT values lower than 1. This phenomenon is due to the observed peak for the purge fraction of 3%, as explained in the text above.

■

6. CONCLUSIONS This paper proposes a different approach to environmental assessment during the conceptual design of chemical processes. According to this approach, the concepts of risk of occurrence of environmental damage and prediction of the respective

AUTHOR INFORMATION

Corresponding Author

*(A.H.) E-mail: [email protected]. G


Article

Industrial & Engineering Chemistry Research ORCID

(23) Cabezas, H.; Bare, J. C.; Mallick, S. K. Pollution Prevention with Chemical Process Simulators: The Generalized Waste Reduction (WAR) AlgorithmFull Version. Comput. Chem. Eng. 1999, 23, 623. (24) Rosen, M. A.; Dincer, I. Exergy Analysis of Waste Emissions. Int. J. Energy Res. 1999, 23, 1153. (25) Young, D. M.; Cabezas, H. Designing Sustainable Processes with Simulation: The Waste Reduction (WAR) Algorithm. Comput. Chem. Eng. 1999, 23, 1477. (26) Henley, E. J.; Seader, J. D. Equilibrium-stage separation operations in chemical engineering, 1st ed.; John Wiley & Sons, New York, 1981. (27) Ratkje, S. K.; De Swaan Arons, J. Denbigh Revisited: Reducing Lost Work in Chemical Processes. Chem. Eng. Sci. 1995, 50, 1551. (28) Seider, W. D.; Seader, J. D.; Lewin, D. R. Product and process design principles - Synthesis, analysis and evaluation, 2nd ed.; John Wiley & Sons: New York, 2003. (29) Szargut, J. International Progress in Second Law Analysis. Energy 1980, 5, 709. (30) Ayres, R. U.; Ayres, L. W.; Martinas, K. Exergy, Waste Accounting, and Life-Cycle Analysis. Energy 1998, 23, 355. (31) Morris, D. R.; Szargut, J. Standard Chemical Exergy of Some Elements and Compounds on the Planet Earth. Energy 1986, 11, 733. (32) Rivero, R.; Garfias, M. Standard Chemical Exergy of Elements Updated. Energy 2006, 31, 3310. (33) Dimian, A. C. Integrated Design and Simulation of Chemical Processes, 1st ed.; Elsevier Science B. V.: Amsterdam, 2003.

Alencar Heidrich: 0000-0002-8473-9712 Notes

The authors declare no competing financial interest.

■

REFERENCES

(1) Douglas, J. M. Conceptual design of chemical processes, 1st ed.; McGraw-Hill: Singapore, 1988. (2) Cano-Ruiz, J. A.; McRae, G. J. Environmentally Conscious Chemical Process Design. Annual Review of Energy and the Environment 1998, 23, 499. (3) Kheawhom, S.; Hirao, M. Decision support tools for process design and selection. Comput. Chem. Eng. 2002, 26, 747. (4) Dunford, R. W.; Ginn, T. C.; Desvousges, W. H. The Use of Habitat Equivalency Analysis in Natural Resource Damage Assessments. Ecological Economics 2004, 48, 49. (5) Ulrich, G. D.; Vasudevan, P. T. Predesign for Pollution Prevention and Control. CEP Magazine; June 2007, p 53. (6) Linninger, A. A.; Chakraborty, A. Synthesis and Optimization of Waste Treatment Flowsheets. Comput. Chem. Eng. 1999, 23, 1415. (7) El-Halwagi, M. M. Pollution Prevention through Process Integration − Systematic Design Tools, 1st ed.; Elsevier Science (USA): Amsterdam, 1997. (8) El-Halwagi, M. M. Process Integration, 1st ed.; Elsevier Inc., Amsterdam, 2006. (9) Nápoles-Rivera, F.; Ponce-Ortega, J. M.; El-Halwagi, M. M.; Jiménez-Gutiérrez, A. Global Optimization of Mass and Property Integration Networks with in-Plant Property Interceptors. Chem. Eng. Sci. 2010, 65, 4363. (10) Azapagic, A.; Millington, A.; Collett, A. A Methodology for Integrating Sustainability Considerations into Process Design. Chem. Eng. Res. Des. 2006, 84, 439. (11) Azapagic, A.; Clift, R. Life cycle assessment and multiobjective optimization. J. Cleaner Prod. 1999, 7, 135. (12) García, N.; Caballero, J. A. How to Implement Environmental Considerations in Chemical Process Design: An Approach to Multiobjective Optimization for Undergraduate Students. Education for Chemical Engineers 2012, 7, e56. (13) Li, C.; Zhang, X.; Zhang, S. Environmental Benign Design of DMC Production Process. Chem. Eng. Res. Des. 2006, 84, 1. (14) Smith, R. Chemical process design and integration, 1st ed.; John Wiley & Sons: Chichester, 2005. (15) Yang, Y.; Shi, L. ’Integrating Environmental Impact Minimization into Conceptual Chemical Process Design  a Process Systems Engineering Review. Comput. Chem. Eng. 2000, 24, 1409. (16) Fathi-Afshar, S.; Yang, J. C. Designing the optimal structure of the petrochemical industry for minimum cost and least gross toxicity of chemical production. Chem. Eng. Sci. 1985, 40, 781. (17) Guinée, J. B.; Heijungs, R.; Udo de Haes, H. A.; Huppes, G. Quantitative Life Cycle Assessment of Products: 2. Classification, Valuation and Improvement Analysis. J. Cleaner Prod. 1993, 1, 81. (18) Azapagic, A.; Perdan, S. Indicators of Sustainable Development for Industry: A General Framework. Process Saf. Environ. Prot. 2000, 78, 243. (19) Singh, A.; Lou, H. H.; Yaws, C. L.; Hopper, J. R.; Pike, R. W. Environmental Impact Assessment of Different Design Schemes of an Industrial Ecosystem. Resources, Conservation and Recycling 2007, 51, 294. (20) Sonnemann, G.; Castells, F.; Schuhmacher, M. Integrated lifecycle and risk assessment for industrial processes, 1st ed., Lewis Publishers: Boca Raton, 2004. (21) Narodoslawsky, M.; Krotscheck, C. The sustainable process index (SPI): evaluating processes according to environmental compatibility. J. Hazard. Mater. 1995, 41, 383. (22) Cabezas, H.; Bare, J. C.; Mallick, S. K. Pollution Prevention with Chemical Process Simulators: The Generalized Waste Reduction (WAR) Algorithm. Comput. Chem. Eng. 1997, 21, S305. H


Environmentally Conscious Design of Chemical Processes Based on

Recommend Documents