In the paragraphs below we describe one methodology that has been used to compare technologies, the details of which have been published.10It has been utilized by a major international pharmaceutical company to build a green technology guide for pharmaceutical unit operations.11There are, of course, other methodologies that can be used to undertake these sorts of comparisons, and this comparative assessment methodology is presented here to illustrate one such approach.
23.3.1 Definition of the Target and Alternative Technologies
This methodology utilizes the case scenario approach but applies life cycle assessment metrics. As noted above, the first step of any case scenario is rigorous definition of the particular objective or goal that is desired. For example, the objective may be the removal of solvent on the basis of kilograms of product crystallized or recovered. The goal or objective that defines each case scenario may comprise an entire reaction system (e.g., a separative reactor), a unit operation to achieve separation (e.g., purification, recovery, waste treatment or recycle, or cleanup), or an entire process. The objective should be defined quantitatively and include any important qualitative or quantitative constraints. For example, objectives might include such things as the purification of 1 kg of crystalline product, the removal of 90% of the solvent from a reaction mixture, or the recovery of substance X present in an inlet stream at a concentration of 100 g/L. The added constraints may be that the product is temperature sensitive or that the recovered solvent purity must be 95% or greater.
After the objective is clearly defined, suitable technologies to accomplish the objective are identified. Such technologies could be either traditional or emerging, as long as there is evidence that the case scenario objectives may be achieved reproducibly. In other words, special care needs to be taken to make sure that the alternatives are applicable and can actually be implemented. This step, even though it may appear to be obvious, is crucial for selecting technologies to be evaluated. There also needs to be sufficient information to perform the assessment. Additional technologies not covered in the study that could be employed to accomplish the same objective should be mentioned within the definition of the scenario.
In addition, when dealing with an emerging technology, it is important to highlight its degree of development. It is common for emerging technologies to be downplayed because they are compared with well-developed processes or technologies that have been optimized over a period of years. It is therefore important to level the playing field to assure that the emerging technologies will be compared with their potential performance at a given stage of development. Conversely, in early stages of development the output of the comparison can be used as a benchmark for setting improvement targets.
23.3.2 Metric and Indicator Definition
A group of core and complementary metrics were proposed that provide the best differenti- ation between the technologies selected. For this methodology, four principal categories are scored: environment, energy, efficiency, and safety. The score for each of these categories is generated based on measurable metrics or indicators, as shown in Fig. 23.1. A life cycle
– –
– –
–
Environment Energy Efficiency Safety
Process Materials
Occupational exposure Mass
Mass intensity
Cooling Yield
Conversion Cycle Time
Throughput Purity Complexity Operability Heating
Electricity Solvent intensity
Waste intensity Emission Life Cycle
LCA Metrics Materials Energy Emissions
Regulatory
– –
Technology Comparisons
FIGURE 23.1 Technology comparison: metrics and categories.
viewpoint. Where possible and appropriate, these indicators include cradle-to-gate envi- ronmental life cycle inventories that take into consideration emissions for the extraction and transformation of raw materials, energy, and even for waste treatment. As we saw in previous chapters, this is especially important when considering energy. Different utilities, such as steam and electricity, have different associated emission profiles. Only a qualitative view for safety and operational considerations was defined, but it is possible to include quantitative measurements for these two categories.
23.3.3 Data Gathering
Once the technologies have been selected, we need to collect data to estimate the metrics.
Industrial-scale data or process validation data is extremely valuable and is preferred, but such information is not always available. Full- or pilot-scale data are usually easier to obtain with in-house and traditional technologies and rather difficult to obtain for emerging technologies. In the case of emerging technologies, bench-scale data are normally the only information available. When only bench-scale data are found, it should be noted in the description of the technology and there should be an assessment of the data quality for scaling-up to pilot or full scale. Data required for the assessment are identical to those required for a mass and energy balance for the system, such as principles of operation, process flow diagrams, mass flows, efficiencies, temperatures, pressures, concentrations, toxicological data, and hazard characteristics.
23.3.4 Estimation of Metrics
This step is for calculating the metrics defined above using the data gathered. Table 23.1 shows some examples of a few common metrics, although more (or fewer) metrics may be needed to properly define and compare the technologies. The mass metrics include both environmental impacts and raw material utilization (e.g., emissions, mass intensity). The energy indicators evaluate energy consumption for each alternative.
To derive the mass and energy metrics, the mass and energy balance principles described in Chapters 9 and 12 are used. The basis for the mass and energy balance calculations should be the same as the objective of the scenario (e.g., 1 kg of product, 1 kg of waste treated) and for each technology alternative evaluated. The process emissions metrics should be derived from such things as the chemical reaction conversion efficiency, process separation efficiency, physical properties of the materials, and product and by-product formation. Once the mass and energy balances are completed for each technology alterna- tive, the mass indicators are calculated and tabulated for comparison. All data and any assumptions made should be transparent.
For the life cycle metrics, the principles discussed in Chapters 16, 18, and 19 were applied. The emissions for energy and the production of raw materials are added to the unit process emissions to obtain an estimate of the total emissions generated throughout the life cycle of the unit operation. Life cycle information was extracted from databases and literature to estimate the life cycle burdens associated with raw material and energy production.12–22
Significant quantitative and qualitative operational differences that affect process efficiency (e.g., yield, conversion, separation efficiency) and quality (e.g., percent
TABLE 23.1 Examples of Mass and Energy Metris
Definition Mass Metric
Mass intensity (MI) MIẳtotal mass input to the process; excluding water basis of the mass balance calculations
Waste intensity (WI) WIẳ total waste produced
basis of the mass balance calculations Emissions of specific
compounds released (Ei)
Eiẳamount of compoundireleased as an emission basis of the mass balance calculations (a separate indicator is calculated for each compound released)
Energy Metric total heating requirementsẳX
n
mCpðT2T1ị h
T
2>T1
þX
n
UAðTwTịt h
T
w>T
þX
n DHTR
endothermic
heat recovered
total cooling requirementsẳX
n
mCpðT2T1ị h
T
1>T2
þX
n
UAðTwTịt h
T>Tw
þX
n
DHRT
exothermic
heat recovered
Sensible heat QẳmCpðT2T1ị
h Variables:
nẳchange in stoichiometric coefficients
hẳefficiency Heating or cooling a
vessel at a constant temperature
QẳUAðTwTịt
h DHRT ẳheat of reaction at
temperatureT
Cpẳheat capacity at constant pressure
Eẳelectricity requirements mẳmass
Qẳheating or cooling requirements
Q0ẳrefrigeration requirements Heat of reaction DHRT ẳm
h DHR298þ Z T
298
nCpdT
Tẳtemperature of the system tẳtime
T1ẳinitial temperature T2ẳfinal temperature Refrigeration Qẳ1:2Q0
EẳQ0ðT1T2ịt hT1
Twẳtemperature of heating/cooling media
assessed for each alternative and compared. Other considerations include the operational ranges and limits, typical processing time or reactor or unit operation residence times, process control issues, selectivity issues, the type of operation (e.g., continuous vs. batch), potential operational problems (e.g., fouling, blockages), and ease of scaling up the technology.
Potential material and process safety issues are qualitatively identified. Since the analysis is typically based on calculations and an estimation of the operating conditions, safety issues related to the placement of the process or unit operation in facilities are more difficult to evaluate but need to be included as more information becomes available. Materials with known and reported hazards, such as the potential for flammability, adverse reactions, explosivity, corrosivity, and toxicity should be identified. Material hazard information may be found in a variety of places, including material safety data sheets, SAXs,23other published compendia, or a variety of Internet sites. Process conditions that lead to extremes in pressure or temperature should be identified through calorimetry studies and modeling and noted along with any process condition that would tend to make it easier for a process release, uncontrolled reaction, or similar incident to occur.
23.3.5 Comparative Ranking
Once all the technology options are evaluated, a relative rank is assigned to each category (i.e., environmental, energy, safety, efficiency). The ranking is performed by technical experts and is based on the results of the technology analysis and the values for all the metrics.
Technical experts are used because technology comparisons need to be made in their appropriate context, and there is a blend of quantitative and qualitative results. In some instances, absolute numbers or ranges (e.g., mass or energy use) may be compared; in other cases, semiquantitative or qualitative relative comparisons must be employed.
The applicable indicators in each category are assigned a numerical value of 0, 5, or 10.
This range of 0 to 10 is merely used as a relative scale that is assumed to be easy to apply and understand. A value of zero is given if the technology is perceived as having a disadvantage, 10 if it is perceived as having an advantage, and 5 if the indicator is not perceived as a significant advantage or disadvantage. Once the indicators are assigned a relative numerical ranking, the arithmetic average of the indicators comprising each category is calculated and a color code is assigned. For an average ranking lower than 2.5, the category color is red. If the average ranking is equal to or higher than 2.5 but lower than 7.5, the category color is yellow.
Finally, if the average ranking is 7.5 or higher, the category color is green. A visually simple presentation of the comparison is employed using the color coding presented in Table 23.2.
The main purpose of the comparative ranking is to identify adverse issues, favorable characteristics, and possible trade-offs among the alternatives that facilitate an informed and perhaps more sustainable business decision. The ranking is limited by the comparison of TABLE 23.2 Color Code for Comparative Ranking
Color If. . . Description
Green Score7.5 Technologies considered to have significant advantages Yellow 2.5score<7.5 Technologies with no significant advantages or disadvantages.
Red Score<2.5 Technologies considered to have significant disadvantages
each case scenario and by the added subjectivity of the ranking. General conclusions about the technologies in all applications and conditions should not be drawn from the rankings in a given case scenario. At this stage a degree of subjectivity is involved, especially for nonnumerical metrics (e.g., operability, material safety).
Example 23.1 Look back at Example 15.1, where we discussed vortex mixers. In that example we estimated the energy requirements of a process using vortex mixers and a batch process. Laboratory conditions for the vortex mixer and batch conditions are given in Table 23.3: How would the two processes compare using the methodology described above? You can refer to Example 15.1 for the process descriptions.
Solution
Mass metrics. The production of 1 kg of intermediate B was used as the basis for calculating the mass and energy balances. The nonisolation and vortex mixer processes have better results for mass, waste, and solvent intensity. The improved performance is due primarily to lower solvent use, but in the case of the vortex mixers, it is also due to an improvement in the yield. The results for the mass intensity, solvent intensity, and waste intensity for each option are provided in Table 23.4.
Energy metrics. In Example 15.1 the energy requirements were estimated, so there is no need to recalculate. Our results then were as shown in Table 23.5:
TABLE 23.3 Laboratory Conditions
Parameter Qualification Batch Laboratory Vortex Mixer
Intermediate A required 125 kg/batch (393.7 mol) 2.5 kg/h (7.9 mol/h) Weight % of intermediate A in THF 30.2% (w/w) 27.3% (w/w)
Chloroacetonitrile use 1.12 equiv. 1.2 equiv.
PTC use 4.4 kg/batch 90 g/h
Concentration of base 30% (w/w) KOH 30% (w/w) KOH
Intermediate B produced 114.7 kg/batch (325.8 mol) 2.4 kg/h (7.1 mol/h)2
Reaction temperature 0–10C Room temperature
TABLE 23.4 Mass Metric Results
Mass Metrics Vortex Mixer Batch Reactor
Mass intensity (kg/kg intermediate B) 10.2 15.9
Added solvent intensity (kg/kg intermediate B) 0.9 8.9
Waste intensity (kg/kg intermediate B) 9.2 14.9
TABLE 23.5 Energy Requirement Results
Energy Requirements Vortex Mixer Batch Reactor
Heating (MJ/kg intermediate B) 0.51 3.17
Cooling with cooling water (MJ/kg intermediate B) 0.51 3.23
Refrigeration (MJ/kg intermediate B) 0 0.5
Electricity (MJ/kg intermediate B) 0.36 0.53
Simplified life cycle approach. A simplified life cycle inventory for energy and solvent production was included in the comparison of the three processing options. Life cycle inventory work has demonstrated that solvent production and use account for the greatest proportion of life cycle impacts in a pharmaceutical manufacturing context, so this approach is not without merit.24Using this simplified approach, the use of a vortex mixer results in considerably lower life cycle emissions than for the batch and nonisolation processes. For example, as can be seen in Table 23.6, CO2emissions associated with vortex mixer use are about 20% of the CO2emissions associated with use of the current batch reactor and 30% of the CO2emissions associated with use of the nonisolation batch reactor process.
Safety indicators.In general, all processing options described above can be operated safely, and there are only relatively minor safety differences for this case scenario. Both batch processes operate at low temperatures (around 0C), whereas the vortex mixer system operates at ambient temperature. It should be noted, however, that vortex mixers represent a potentially safer operating environment, due to the small volumes in the mixing chambers and short residence times of the substances in the system at any given time. This reduces the overall risks of accidental fire or explosion. Furthermore, reduced solvent use in the vortex mixer and nonisolation processes have the potential to reduce volatile organic compound emissions during solvent handling and processing, thereby reducing the potential for occupational exposure to solvent vapors.
Efficiency and operational indicators. The vortex mixer process has the following operational advantages over the current batch reactor process:
. Continuous operation of traditional batch processes
. Improved mass and heat transfer
. Improved control of reactant and reagent residence times and temperature profile
. Reduced solvent use
. The potential for fewer work-ups if continuous separation operations are used Emission (g/kg B)
Vortex Current
Air emissions
CO2 1.16104 6.43104
CO 3.59102 1.96103
CH4 1.7810 1.04102
NMVOC 4.2210 2.50102
NOX 4.8410 2.73102
SOX 5.2910 2.94102
Water emissions
BOD 6.77101 4.09E
COD 0.189714 1.11102
TDS 3.6810 2.04102
Solid waste 1.10104 5.96104
. Generally higher selectivity, yield, and quality, especially for exothermic and fast reactions
. Linear scale-up (larger-scale vortex mixers will yield the same results given that the residence time and flow velocities used at laboratory scale are matched) or the ability to easily number-up
. Faster development of new processes or substances
Based on the results from an analysis of the three processing options described above, the reaction systems were comparatively ranked. A color-coded summary of the comparative ranking is presented in Table 23.7.
These results suggest that the vortex mixer is a better option for this particular process.
Additional Points to Ponder How would a batch process with no isolations fare in this assessment? How would vortex mixers fare in comparison with static mixers?