Comparative Environmental Assessments of VOC Recovery and

Results from an economic analysis show that both of the adsorption processes are ... Hyprotech Ltd., Calgary, Canada) employing the Universal Quasi Ch...
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Environ. Sci. Technol. 2000, 34, 5222-5228

Comparative Environmental Assessments of VOC Recovery and Recycle Design Alternatives for a Gaseous Waste Stream DAVID R. SHONNARD* AND DENNIS S. HIEW† Chemical Engineering Department, Michigan Technological University, Building 19 Room 203, 1400 Townsend Drive, Houghton, Michigan 49931

Decisions involving chemical process design, including selection of technologies and operating conditions, should integrate environmental considerations. The assessment methodology presented in this article includes nine environmental and human health impact indices, a “level I” multimedia fate and transport model, and an air emissions estimation calculator based on emission factors and correlations. The methodology and software tool was used to evaluate two case studies involving mixed-solvent recovery from a gaseous waste stream utilizing output from a commercial process simulator. The assessment methodology was applied for two evaluations: (a) separation technology selection and (b) choice of process operating conditions. It was found that two adsorption technologies with either steam stripping or vacuum regeneration are superior to three absorption technology configurations based on environmental and health indices. With suitable weightings, a single process composite index was defined and served as an environmental objective function for the evaluation of absorber oil flow rate changes using a single absorption technology configuration. It was found that the process composite index exhibited a reduction in environmental impact of 94% when operated at the “environmental impact minimum” absorber oil flow rate, compared to releasing the VOCs directly to the environment.

Introduction Pollution prevention (P2) is a response to the dual challenges of environmental and human health protection and also the need to maintain globally competitive industries. A number of pollution prevention design methodologies have recently emerged in the literature. These methodologies are intended to improve chemical process efficiency by taking an integrated view of process design and improvement. These process integration methodologies have been categorized as (1) (a) pinch analysis (2-4), (b) knowledge-based approaches (5, 6), and (c) graphical/numerical optimization (1, 7-9). The approach commonly taken has been to minimize capital and operating annualized costs under the constraints of imposed emissions reduction targets, typically * Corresponding author phone: (906)487-3468; fax: (906)487-2313; e-mail: [email protected]. † Current address: Essential Technologies Inc., 17225 El Camino Real, Suite 230, Houston, TX 77058. 5222

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on a single pollutant (1, 10, 11). Even though this approach can effectively identify the optimum process configuration from an economic perspective, there is no guarantee that the pollution reduction targets are in any way optimum, from an environmental perspective. The purpose of this article is to combine environmental impact assessment with chemical process design and then to demonstrate the approach using case studies for the recovery and recycle of VOCs from a gaseous waste stream. Also, we compare and contrast the presented impact assessment method with a similar method from the literature. The impact assessment methods employed are in the Supporting Information, process flowsheets are described, and environmental assessments are made for technology selection and for various process operating conditions. The latter two applications are very important avenues for process improvement. Finally, a software tool that is based on the presented method is intended to be applied alongside with economic, safety, and decision analysis tools as process simulator enhancements for process improvement and pollution prevention (12). Process and Product Environmental Impact Assessment Methodologies. The assessment of environmental/health impacts is one very important component within modern process design. Life Cycle Assessment (LCA) methodologies have been applied to the manufacture of products (13), but fewer applications of impact assessment have been applied to chemical processes and their designs. There are several recently developed methodologies that can be used to perform environmental assessments of products and processes. The following is a brief review of the key features for current methods. The Eco-Indicator 95, developed for product LCA purposes (14), uses nine environmental indices for assessment. Each index has a weighting factor from between 2.5 and 100 depending on the “distance-to-target” concept for the importance of each impact category (greenhouse effect, ozone layer depletion, acidification, eutrophication, summer smog, winter smog, pesticides, heavy metals, and carcinogenic substances). This method is one of the most widely applied LCA approaches, and example applications using the tool can be found in a recent publication (15). The Uniform System for the Evaluation of Substances (USES 1.0) (16), developed for evaluation of chemicals, is used for quantitative risk assessment, including new and existing chemicals, agricultural pesticides, and biocides. It was developed as a decision-making tool with incorporation of emission estimation, a fate and transport model, and exposure estimation. The method of Minimizing Environmental Impact (MEI) (17-20) embeds principles from LCA within a chemical process optimization framework. It involves definition of the process boundary, includes waste emissions, quantifies environmental impact via defined metrics, and incorporates these metrics into process design and optimization. It has been applied to determine waste treatment, the optimum degree of pollution abatement, and optimum solvent design. The Waste Reduction (WAR) algorithm, developed by the U.S. Environmental Protection Agency (9, 21-23), characterizes the flow and generation of potential environment impact through a chemical process. Nine potential impact indices ranging from ozone depletion potential to human toxicity and ecotoxicity are used; however the effects of energy consumption in the process are not considered in the method. Applications include the effect of in-process recycle on the output of potential environmental impact from a methyl ethyl 10.1021/es0010857 CCC: $19.00

 2000 American Chemical Society Published on Web 11/01/2000

FIGURE 2. Simplified process flow diagram for adsorption processes using either steam stripping or pressure swing to recover VOCs.

FIGURE 1. The information flow diagram of the Environmental Fate and Risk Assessment Tool (EFRAT) methodology/software. ketone production plant (9). A software tool based on the methodology is reported to be linked with a commercial process simulator (23). The impact assessment methodology presented in this article, the Environmental Fate and Risk Assessment Tool (EFRAT), integrates all of the key steps of impact assessment into a single methodology and software tool. These steps include (1) process release estimation, (2) pollutant fate and transport, (3) assessment of exposure potential, and (4) relative risk assessment. This assessment methodology and tool has been integrated with a commercial process simulator package, HYSYS (24, 25).

Environmental Fate and Risk Assessment Tool (EFRAT): Assessment Framework EFRAT performs in-process gate-to-gate assessments including the impact of energy consumption and is organized into three calculation modules: air emission estimation, environmental fate and transport, and relative risk assessment. More detailed information regarding these equations and calculation methods is found in the Supporting Information. Figure 1 shows the information flows occurring in the methodology. Input from a process design simulator includes (a) numbers and sizes of equipment, (b) chemicals, (c) annual throughput in each piece of equipment, (d) utility type and consumption, (e) production rate, and (f) other design specifications depending on the unit operations involved. Physical, chemical, and toxicological properties of the chemicals are included in databases resident to the software with the additional feature of being able to add properties manually for new chemicals. The environmental impact indices can be used directly in decision-making or may be combined with each other or with nonenvironmental performance measures (economic, safety, controllability, flexibility, etc.) using suitable weighting approaches (14).

Methods: Process Simulation and Environmental Assessment The environmental assessment methodology presented here was applied to several chemical processes for the recovery and recycle of toluene and ethyl acetate from a gaseous waste

stream. The gaseous waste stream originated from a cellophane production facility but could have come from any number of industrial processes (26). The waste stream parameters are as follows: (a) a flow rate of 12,000 standard cubic feet per minute (scfm, 5.66 m3/s), (b) a temperature of 170 °F (76.7 °C), (c) a pressure of 1 atm, and (d) 0.5% (vol) of toluene and ethyl acetate (50/50 wt mixture) in dry nitrogen. The process simulators used in this study were HYSYS (Hyprotech Ltd., Calgary, Canada) with a Universal Quasi Chemical (UNIQUAC) calculation method in the fluid thermodynamics package for the absorption technology processes and AdDesign (Michigan Technological University, Houghton, MI) for the activated carbon technology processes. Using mass and energy balance calculations from the process simulators, the Environmental Fate and Risk Assessment Tool (EFRAT) was used to estimate process emissions to the air of individual chemicals and then to calculate nine environmental and human health impact indices for the entire process.

Environmental Assessment Results: Technology Selection Adsorption Technology Configurations. A simplified process flow diagram of two adsorption technology configurations is shown in Figure 2. The adsorption processes utilize activated carbon beds to capture the VOCs and either steam stripping (Process 1) or pressure swing regeneration (Process 2) to recover the VOCs from the activated carbon (27). The activated carbon bed is assumed to remove 99% (wt) of the solvent from the gas steam (28, 29). The frequency of bed regeneration was determined by simulation using AdDesign. In the steam stripping configuration (Process 1), the steam containing VOCs is condensed and separated into two layers (organic rich and water rich layers), plus a vent for the noncondensable gases (i.e. N2). The vent stream is recycled back for further VOC recovery, while the water rich layer is sent to a steam stripping column to separate residual organics from the aqueous phase. The wastewater from the stripping column has essentially no VOCs remaining in it. The organic layer from the decanter is sent to the distillation column to separate the water from the organics, with the water stream from the top of the column being recycled back to the decanter. The bottom product of the distillation column is a 50/50% (wt) mixed product of toluene and ethyl acetate, suitable for recycle and reuse. The adsorption technology configuration using a pressure swing regeneration technique (Process 2) requires a vacuum to be drawn on the packed bed after adsorption is completed. The VOC vapors are recovered using a refrigerated condenser. The uncondensed gases in the vapor stream (i.e. N2) are sent back to the packed bed for further recovery. The mixed product is accumulated in a storage tank for recycle. VOL. 34, NO. 24, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1: Emission Estimation for Different Solvent Recovery Processes process, emission rate (kg/h)

FIGURE 3. Process flow diagram for VOC recovery through absorption using n-C14 as the absorption oil. The major air emission sources for the adsorption processes are the vent from the activated carbon bed, the utility consumption for steam generation and the distillation reboiler for Process 1, and the vacuum pump and refrigerated condenser for Process 2. In addition, there are vent emissions from the distillation column condenser, from the storage tanks (not shown in Figure 1), and from fugitive sources (pumps, valves, fittings, etc.). Absorption Technology Configurations. Figure 3 is a simplified process flow diagram of a countercurrent absorption process to recover and recycle the gaseous waste stream VOCs (26). The VOCs are separated from the absorption oil in a distillation column, with toluene and ethyl acetate exiting the top and the absorption oil exiting the bottom, respectively. A heat exchanger (center in Figure 3) accomplishes heat integration; however not all of the absorption process configurations considered in this study incorporated heat integration. In Processes 3 and 4, all heating and cooling of process streams were carried out by external utilities. Two absorber oils were included in the study to assess the effects of oil choice. The major sources of air pollution originate from the vent of the absorption column and the consumption of utilities, mainly by the reboiler and preheater of the distillation column. In addition, there are vent emissions from the distillation column condenser, from the storage tanks (not shown in Figure 3), and from fugitive sources. The process simulator was run for all of these absorption processes with the constraint that at least 96-98% (wt) of the VOCs entering the process are recovered. Emission Estimation for Solvent Recovery Processes. Figure S.1 in the Supporting Information shows the predicted rates of ethyl acetate and toluene emission to the atmosphere from the solvent recovery process using the absorption technology with n-C14 as the absorption oil (Process 5). The relative contributions by process units are typical for all the other cases (Processes 1-5). Either the absorption column or the adsorption bed are the major contributors to the air emissions. The process simulator predicted the absorption column emissions and EFRAT predicted all other unit-specific emission rates. The emission estimates for all five of the solvent recovery processes and can be found in Table 1 (see the footnotes to Table 1 for descriptions of all process configurations). All the solvent recovery processes have percentage recoveries between 96.4 and 98.7%. Even though the percentage recoveries for all the processes are similar, the emission rates vary by over 2 orders of magnitude for several of the pollutants. In addition to toluene and ethyl acetate, the utilities release carbon dioxide (CO2), carbon monoxide (CO), oxides of nitrogen (NOx) and sulfur (SOx), and organic compounds. The absorption process using n-C23 as the absorption oil has a very high-energy demand in the distillation column reboiler. The absorption oil must be 5224

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pollutant

1a

2b

3c

4d

5e

6f

CO2 CO ethyl acetate SOx NOx toluene total organic compds

101 0.05 2.83 0.29 0.83 1.30 0.01

129 0.08 3.48 1.09 0.55 1.29 0.07

40914 10.61 13.68 322.59 42.45 0.22 2.70

3096 0.80 8.19 24.42 3.21 0.09 4.06

1602 0.42 7.99 12.63 1.66 0.08 4.06

0 0 193.55 0 0 193.55 0

a Process 1 - VOCs recovered using adsorption followed by steam stripping and distillation. b Process 2 - VOCs recovered using adsorption followed by pressure swing process. c Process 3 - VOCs recovered using absorption with n-C23 oil, followed by distillation; no heat integration. d Process 4 - VOCs recovered using absorption with n-C14 oil, followed by distillation, no heat integration. e Process 5 - VOCs recovered using absorption with n-C14 oil, followed by distillation, with heat integration. f Process 6 - no VOCs recovery process (gaseous waste stream released into the atmosphere).

TABLE 2: Environmental Partitioning of All the Chemicals Involved in Processes To Recover VOCs from a Gaseous Waste Stream percentage in compd

air

water

soil

carbon dioxide, CO2 99.50 0.29 0.20 carbon monoxide, CO 100.00 0.00 0.00 ethyl acetate 77.13 14.04 8.73 NOx 99.99 0.00 0.00 SOx 99.58 0.30 0.12 tetradecane, n-C14 8.33 0.00 90.17 toluene 99.19 0.04 0.77 total organic compds (TOC) 99.92 0.00 0.08 tricosane, n-C23 1.69 0.00 96.70

sediment 0.00 0.00 0.09 0.00 0.00 1.50 0.01 0.00 1.61

heated to its boiling point, 380 °C. When the n-C14 is used as the absorption oil, the energy demand drops by 92.4%, and after heat integration a further reduction of 48.3% is achieved. The adsorption processes are more energy efficient in comparison to the absorption processes. The adsorption process with pressure swing produces 93.7% less carbon dioxide than the best case in the absorption category. However, the adsorption process with pressure swing (Process 2) has a higher emission for toluene compared to the absorption process using n-C14 as the absorption oil (Process 5). Because of these and other tradeoffs in chemical emissions, the relative risk indices are needed for a more detailed comparison of environmental impacts. Environmental Partition of the Chemicals Involved. The partitioning behavior of all the chemicals involved in the solvent recovery processes can be found in Table 2. The partition model predicts that most of the chemicals will equilibrate into the air compartment, except for the heavy hydrocarbons, n-C14 and n-C23. The heavy hydrocarbons partition mostly into the soil and sediment. Ethyl acetate has the highest percentage of partitioning in the water compartment. These partitioning patterns are used to explain the behavior of some of the relative risk indices later in this article. The predictions of the EFRAT environmental partitioning model are in good agreement with those of published fugacity-based models (30). Relative Risk Assessment. The relative risk indices for all six processes are shown in Table 3. Since there are no chemicals that have the potential for stratospheric ozone depletion or for causing cancer to humans, these three indices

TABLE 3: Relative Risk Indices for the Solvent Recovery Processes relative risk index (kg/h) process

IGW

ISF

IAR

IING

IINH

IFT

1a

123 163 15967 3256 1698 1040

8.1 8.7 8.6 8.4 7.7 230.4

1.0 1.5 131.8 26.7 13.8 0.0

313 384 563 901 879 21615

12.9 16.6 215.5 67.3 47.2 837.3

2.2 2.7 3.9 6.2 6.1 151.5

2a 3a 4a 5a 6b

a Processes 1-5 are the same as in Table 1. b Process 6 - no VOCs recovery process (gaseous waste stream released to atmosphere).

are zero and are omitted from Table 3. Direct emission of the VOCs (Process 6, Table 1) has the highest risk indices, with the exception of the acid rain index (IAR) and the global warming index (IGW). The absorption process using n-C23 has the highest IGW and IAR because of the extremely high energy demands, and it also scores high in many other indices. A key question is which process has the least impact on the environment (lowest index scores). From the results presented in Table 3, it is clear that processes 1 and 2 are as good as (within expected uncertainty) or superior to all other VOC recovery and recycle processes (Processes 3, 4, and 5) for all indices. Results from an economic analysis show that both of the adsorption processes are profitable, with payback periods of approximately 1 year (31). On the other hand, none of the absorption technology processes had acceptable economic performance measures. The most suitable process for the VOC recovery will depend on the importance of a particular index to the community, regulators, or corporate decision-makers. These results show that EFRAT is a useful methodology for choosing among competing technologies for a given chemical processing task, based on environmental impacts of releases and energy consumption. However, other factors also need to be considered simultaneously, for example economic viability and safety concerns. To address these issues simultaneously, process evaluation software tools for economic and safety performance measures have been developed recently and have been applied to this and other case studies (12, 26, 27).

FIGURE 4. VOC percentage recoveries with increasing absorption oil flow rate.

Environmental Assessment Results: Evaluation of Technology Operation In the previous analysis, pollution prevention technologies were compared using flowsheets that were constrained by relatively high percentages of VOC recovery. In this section, flowsheet evaluation will be performed using the environmental impact metrics as the objective functions. The key question for the evaluation is how much of the VOCs should be recovered before the benefits of further recovery are overwhelmed by the environmental costs (impacts) of processing. The manipulated variable in the evaluation is the absorption oil flow rate (using Process 5, Table 1 and Figure 3). Altering this parameter from between 0 and 500 kg mol/h and using absorption and distillation columns of constant configuration (number of equilibrium stages, reflux ratios, etc.) will affect the recovery of VOCs and will also drive the utility consumption in the process. The flowsheet mass and energy balances for the evaluations were again generated using a process simulator (HYSYS, Hyprotech Ltd., Calgary, Canada) employing the Universal Quasi Chemical (UNIQUAC) calculation method. Evaluation Based on Relative Risk Indices. The trend in VOC recovery as a function of n-C14 flow rate is shown in Figure 4. The process simulator results indicate that at a flow rate of 50 kg mol/h, 99.5% of toluene is recovered (only 0.97

FIGURE 5. Variation of environmental indices with absorber oil flow rate for (A) global warming (IGW), smog formation (ISF), and acid rain (IAR) and for (B) human ingestion toxicity (IING), human inhalation toxicity (IINH), and ecotixicity (IFT). kg/h of toluene is emitted from the absorption column) compared to only 17.3% recovery of ethyl acetate. Between a flow rate of 50 and 300 kg mol/h, most of the ethyl acetate is recovered. Furthermore, simulator and assessment results show that energy consumption and related emissions of CO2, CO, SOx, NOx, and TOC increase in nearly direct proportion to the oil flow rate in the process. Figure 5 shows the variation of several environmental indices as a function of absorption oil flow rate. There is a sharp decrease in the global warming index (IGW) with increasing oil flow rate until about 50 kg mol/h, due mostly to toluene recovery. (Note that toluene and ethyl acetate have global warming impacts assuming that all emitted VOCs are oxidized to CO2 in the environment and that the VOCs are fossil fuel-based). Thereafter, increasing utility-related emissions of greenhouse gases (primarily CO2) drive this index up faster than its rate of decrease by further recovery of ethyl VOL. 34, NO. 24, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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acetate. The smog formation index (ISF) decreases sharply with absorber oil flow rate in the range of 0-50 kg mol/h, again due to recovery of toluene. Afterward, there is a slow decline in ISF with increasing oil flow rate above 50 kg mol/h as ethyl acetate is recovered. The acid rain index IAR increases in nearly direct proportion to oil flow rate. Sulfur oxides and nitrogen oxides are the precursors emitted from utility consumption that cause acid rain, driving the IAR up with higher oil flow rates. The human toxicity ingestion route index (IING) shows a gradual reduction until the absorption oil flow rate exceeds 300 kg mol/h. This index is mainly governed by the toxicity of ethyl acetate and also by its high partitioning into water at equilibrium compared to the benchmark compound (toluene). The human toxicity inhalation route index (IINH) achieves a minimum value at near 300 kg mol/h. There are several chemicals that effect this index, including toluene, ethyl acetate, and carbon monoxide, though primarily by ethyl acetate. The initial sharp reduction in this index is due to the recovery of toluene from the gaseous waste stream. The index goes down with increasing absorption oil flow rate until it reaches the minimum point due to a further recovery of ethyl acetate. Above 300 kg mol/h, the index increases due to the emissions of carbon monoxide, from energy utilization. Here, the benefit of further recovery of ethyl acetate does not match the harm caused by the emission of carbon monoxide. The difference in scale between IING and IINH (about a factor of 100) is due to the choice of benchmark chemical for these indices. Toluene, the benchmark chemical for IING has a very low water solubility, thus driving ethyl acetate’s contribution to the index higher in proportion (see Table S.1 in the Supporting Information for impact index equations). This difference in scale of IING and IINH illustrates the important effects that choosing a benchmark compound can have in risk index methodologies. Adjustments will be made to the benchmark compounds for both IING and IINH in the future. IFT shows a similar trend as does IING. It is difficult to make a decision as to the most environmentally benign absorption oil flow rate as a result of using individual risk indices. If global warming is the main concern, then operating at 50 kg mol/h is the best choice. In addition, significant reductions in smog formation and human toxicity inhalation route (77.1% and 77.8%, respectively) can be realized by operating at 50 kg mol/yr. Significant reductions in human toxicity ingestion route and fish toxicity (93.4% and 93.5%, respectively) are evident when operating at a flow rate of 300 kg mol/h but only at the expense of higher values of IGW and IAR. Also, there is no minimum for the acid rain index, unless the process is operated at 0 kg mol/h (no VOC recovery at all). Clearly, for a decision to be made, a method for combining the individual indices to form a single process composite index is needed. Then, the evaluation can be repeated using this process composite index as the objective function. A detailed description of the method to develop a process composite index is found in the Supporting Information. Briefly, the method includes a normalization step for the indices in Figure 5 using national emissions data and a valuation step based on their “distance to target” for each category of impact (14), where the target value is sufficiently low to ensure adequate protection for human and ecosystem health. Figure 6 shows the effects of absorption oil flow rate on the process composite index (IPC). This composite index decreases rapidly from 0 to 50 kg mol/h, decreases less rapidly between 50 and 300 kg mol/h, and has a minimum at 400 kg mol/h. At 50 kg mol/h, there is a 43% reduction in overall environmental impact and when operated at 400 kg mol/h (at minimum impact), there is a 94% reduction. The shape of the IPC curve in Figure 6 is a reflection of the normalization 5226

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FIGURE 6. Variation of the process composite environmental index (IPC) for the absorption technology gaseous waste stream process. and weighting factors applied to the process indices in Figure 5, which in turn are dependent upon the magnitudes of the process indices relative to national environmental impact output. It is clear from our analysis that for this case study, IPC is dominated by the smog formation (ISF) and ingestion toxicity (IING) indices.

Discussion This absorption case study clearly demonstrates that environmental risk reduction is achieved by recovering and recycling the VOCs from the gaseous waste stream and that the assessment methodology provides a quantitative measure for comparison of design options. The degree of risk reduction is dependent upon how the VOC recovery process is operated, taking into account utility consumption and the rates of release of pollutants, their fate in the environment, and their inherent impacts. Whether the project is actually implemented will depend on whether the process is economically viable, after simultaneously considering capital, operating, and pollution control costs. It is illustrative to compare and contrast the predicted environmental impact indices developed in this study with those of similar methodologies in the literature. The method of the WAste Reduction algorithm (WAR) (23) was applied to the gaseous waste stream case study, and the results are compared to those previously shown in Figure 5. Further details of the method of applying the WAR algorithm to this case study can be found in the Supporting Information. Figure 7 shows the WAR indices as a function of absorber oil flow rate. There are similarities between the EFRAT (Figure 5) and the WAR (Figure 7) profiles. There are similar decreases in ISF, IING, IINH, and IFT with increasing oil flow rate as more VOCs are recovered from the waste stream. However, there are distinct differences in the profiles for the two methods. The magnitudes for each of the WAR indices is smaller by between a factor of 3 to 105, depending upon the index. The reason for these large differences is due to the method of normalization found in WAR, which ensures that 95% of the normalized chemical scores are between 0 and 1 for any set of database chemicals. Also, in WAR there is no accounting for energy consumption and their related emissions and impacts. Therefore, the indices for global warming and acid rain are zero for all oil flow rates as shown in Figure 7. In EFRAT, utility-related emissions are a key aspect of the assessment methodology, and because of this, EFRAT provides a more comprehensive flowsheet environmental evaluation that integrates fully chemical industry process simulator mass and energy balance calculations. There are a number of advantages, limitations, and performance characteristics of the process design environ-

FIGURE 7. Variation of WAR environmental indices with absorber oil flow rate for (A) global warming (IGW), smog formation (ISF), and acid rain (IAR) and for (B) human ingestion toxicity (IING), human inhalation toxicity (IINH), and ecotoxicity (IFT). mental assessment methodology. One of the main advantages of EFRAT is that all of the assessment calculations are performed using a single software tool. The chemical list (200 chemicals) in the EFRAT database covers many of the hazardous air pollutants (HAPs), some pesticides, the most toxic and most emitted chemicals listed in the Toxics Release Inventory (TRI) (32, 33), and the top 100 of the High Production Volume chemicals. Although the list of chemicals is modest, the chemicals on the list will likely be the first targets of pollution prevention initiatives in industry due to their toxic and hazardous nature and relatively large production volumes. In addition, over 90% of the chemical properties are from actual data, thereby allowing the uncertainty characteristics of the model input properties to be estimated. One of the major limitations of this and other environmental assessment methodologies is the wide range of uncertainty in the model parameters and estimation methods. The emission rate estimations can be in error by as much as 2 orders of magnitude, depending on numerous factors (age of the equipment, plant location, pollution control technology, etc.). It is worthy of mentioning that the emissions estimated for the absorber unit (the dominant source) in this current study were much more accurate than indicated above, being calculated using the process simulator. There will be uncertainties in other parameters used to generate the relative risk indices, for example Henry’s constant, atmospheric reaction half-life, lethal dose 50%, and others. Furthermore, the process simulator output, which provides input for the environmental assessments, has uncertainty that may be difficult to quantify. The characterization and incorporation of uncertainty into the environmental assessment activity is beyond the scope of this study. However, uncertainty analysis is currently being

incorporated into the assessment methodology and will be discussed in a future publication. The emission estimations in this method and software tool are limited to primary and secondary air releases, as methods are not currently available to predict liquid and solid waste generation and release from chemical processes. However, air emissions are a significant release route for hazardous chemicals from industry, and the software is able to accept waste generation and release data that are input directly by the user. A better mechanistic understanding of process emissions to air, water, and soil and of unit-specific waste generation will lead to superior estimation methods in the future. The Level I partitioning model used in the current methodology is not the most sophisticated version of multimedia compartment models available. However, the inclusion of reaction residence times in the calculation of relative risks indices is de-facto Level II. We are currently incorporating a Level III model into the methodology, though it was not ready for inclusion in this study. In the future, EFRAT will incorporate more sophisticated health impact assessment methods such as the human toxicity potential approach (34). EFRAT has been developed in conjunction with other software tools, taking inputs from a process simulator and conducting assessments on chemical process designs in terms of economic (Design Option Ranking Tool, DORT) (35), environmental (EFRAT), and safety (Dow Hazard Evaluation Indices) (36) performance measures. The Design Enhancement Analytic Hierarchy Process ranking tool (DEAR) (31) takes the indices from the three process assessment software tools and performs process design rankings by assigning weightings to the indices based on survey results. EFRAT has previously been applied to the design of facilities for cogeneration of heat and power (12, 37) and more recently to evaluate VOC recovery and recycle technologies for gaseous waste streams (38, 26, 31). In summary, modern chemical process designs utilize commercial process simulators or other process models to assess energy and mass efficiency, and they account for environmental impacts at the source of waste generation and at all levels of the product’s life cycle. There are several contemporary methodologies that have the ability to perform environmental assessment of processes. However, the singular aspect of the Environmental Fate and Risk Assessment Tool (EFRAT) is the integration of those assessment functions. Because the area of environmental impact assessment for processes continues to evolve, the reported methodology and software tool are viewed as a framework for environmental assessment of chemical process designs to be improved and expanded upon in the future.

Acknowledgments This research was supported by the U.S. EPA, National Risk Management Research Laboratory, the Center for Clean Industrial and Treatment Technologies (CenCITT), and by and Department of Energy, Office of Industrial Technologies by grant no. CR824506-01. This research has not been subjected to USEPA’s required peer and policy review and therefore does not necessarily reflect the views of USEPA or CenCITT and no official endorsement should be inferred. The adsorption simulation package (AdDesign) was provided by Dr. David Hand and Dr. John Crittenden, Department of Civil and Environmental Engineering, Michigan Technological University. Helpful comments by three anonymous reviewers is appreciated.

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Received for review March 13, 2000. Revised manuscript received September 18, 2000. Accepted September 26, 2000. ES0010857