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(372r) Systematic Framework for Solvent Recovery, Reuse, and Recycling in Industries

Authors: 
Chea, J., Rowan University
Yenkie, K. M., Rowan University
Slater, S., Rowan University
Savelski, M., Rowan University
Christon, A., Rowan University
Pierce, V., Rowan University
Russ, M., Rowan University
Stengel, J., Rowan University

Systematic
Framework for Solvent Recovery, Reuse, and Recycling in Industries

 

John
D. Chea1, Amanda Christon1, Vanessa Pierce1,
Maxim Russ1, Jake Stengel1, Stewart Slater1,
Mariano Savelski1, and Kirti M. Yenkie1,*,

1Department
of Chemical Engineering, Henry M. Rowan College of Engineering,

Rowan
University, NJ - 08028, USA

(Tel:
856-256-5375; e-mail: yenkie@rowan.edu)

 

font-family:" times new roman>Abstract

line-height:107%;font-family:" times new roman>Solvents are commonly
used in both fine chemicals and pharmaceutical industries to aid chemical
reactions and purification of products. In pharmaceutical industries, active
pharmaceutical ingredients (APIs) are often formulated through organic
reactions that utilize solvents as a reaction medium, which can vary depending
on the process and physical properties of the system. The combined contribution
of the current solvent usage rate and solvent disposal method such as
incineration can release toxic chemicals to the environment
(Slater et al., 2010) font-family:" times new roman>. The US EPA has predicted that solvent
emissions are expected to double by 2030 and reach 10 million metric tons of
carbon dioxide equivalent (EPA, 2016). line-height:107%"> font-family:" times new roman>The potential detrimental effects on the
environment and safety considerations required the implementation and
optimization of existing solvent recovery technologies to improve the greenness
and overall sustainability of a given chemical process. Multiple unique
greenness analysis methods were developed in the past decade by (Heinzle et
al., 1998, Hoffman et al., 2001, Chen and Shonnard, 2004, Jimenéz-Gonz background:white">ález et al., 2002, Hossain et al., 2007) to identify
economic, environmental, and process efficiency indicators around specific
processes. Although these methods can eventually lead to sustainability and
improve process efficiency and cost, there has not been an integrated method
that accounts for factors concerning the environment, safety, and economics
(Slater et al., 2010). To accomplish this work, four objectives were devised. (1)
The initial stage involves information collection and consultation
with industries about solvent recovery issues in current manufacturing
practices. (2) A list of potential solvent recovery technologies was compiled
based on applicability, toxicity, physiochemical properties, etc. (3) Technology
models were developed which composed of material and energy balances, utility
requirements, equipment design, and cost. (4) Based on the properties of the
solvent rich stream, the best recovery pathway was determined using a
mathematical modeling and optimization approach to minimize cost, environmental
impact, and waste discharge, and encourage safe design and process operation.

line-height:107%;font-family:" times new roman>Pfizer and Rowan
University had carried out an investigation which aims to recover and purify
isopropanol (IPA) while minimizing waste from the celecoxib process, which
produces the API for an arthritis pain medicine known as Celebrex® (Slater et
al., 2011). The waste stream following the final purification stage contains a
significant amount of recoverable IPA. However, the results of laboratory scale
distillation and extraction conducted at the plant site failed to reach the
purity requirement.

Figure
1. A superstructure of the possible solvent recovery methods to separate IPA
from the water. MBR, UFT, ATPE, PVP, DST, and DCT represents membrane,
ultrafiltration, aqueous two-phase extraction, pervaporation, distillation, and
decanting, respectively. Recycle streams are included. The selected pathway for
IPA recovery is highlighted in red.

font-family:" times new roman> 

line-height:107%;font-family:" times new roman>In Figure 1, we
developed the case-specific superstructure as a starting point to analyzing
process efficiency, cost, and environmental impact of a solvent recovery
pathway. This includes a systematic representation of all the relevant
technologies and flow streams in the IPA recovery paths. A mixed-integer
non-linear programming (MINLP) problem was formulated and solved through General
Algebraic Modeling Systems (GAMS). The optimized IPA recovery pathway from GAMS,
as indicated by red arrows, required the selection of aqueous-two-phase
extraction (ATPE), followed by membrane (MBR) and decantation (DCT) for product
purification. This pathway will line-height:107%;font-family:" times new roman>cost $2.36/kg solvent
recovered. Based on the assumed flowrate of 1000 kg/hr of waste stream feed,
the amount of solvent recovered is approximately 500 kg/hr. This equates to
$9.36 million/yr to recover 3960 metric tons of IPA from the celecoxib process.
The cost distributions in different categories are shown by a pie-chart in Figure
2
.

Figure 2. Cost distribution
required to complete the optimal recovery process of IPA

 

We are in the
process of solving additional case studies from other industrial sectors that
will include economic evaluation, metrics from life cycle analysis with
considerations for environmental impact associated with each recovery pathway. Ultimately,
these multiple case studies will be used to develop the entire framework and
computational tool that can optimize solvent recovery, reuse, and recycling in any
solvent consuming industrial process.

font-family:" times new roman> 

font-family:" times new roman>Keywords 12.0pt;font-family:" times new roman>: Model formulation, process
optimization, solvent recovery

font-family:" times new roman>References

Chen, H., and Shonnard, D.R.
(2004) Ind, Eng. Chem, Res., 43, 535-552.

Henderson,
R., Jiménez-González, C., Constable, D., Alston, S., Inglis, G., Fisher, G.,
Sherwood, J., Binks, S. and Curzons, A. (2011). Expanding GSK's solvent
selection guide – embedding sustainability into solvent selection starting at
medicinal chemistry. Green Chemistry, 13(4), p.854.

Hoffman,
V.H., Hungerbuhler, K., and McRae, G.J. (2001) Ind. Eng. Chem. Res., 40,
4513-4524.

Hossain, K.A., Khan, F.I.,
and Hawboldt, K. (2007) Ind. Eng. Chem. Res., 46, 8787-8795.

Jimen background:white">éz-González, C., Constable, D.J.C., Curzons, A.D., and
Cunningham, V.L. (2002) Clean Tech. Environ. Policy, 4, 44-53.

Slater, S., Savelski, M., Carole, W. and
Constable, D. (2010). Green chemistry in the pharmaceutical industry.
Weinheim: Wiley-VCH, pp.49-66.

Slater, C., Savelski, M., Hounsell, G.,
Pilipauskas, D. and Urbanski, F. (2011). Green design alternatives for
isopropanol recovery in the celecoxib process. Clean Technologies and
Environmental Policy
, 14(4), pp.687-698.

US EPA. (2016). Global Mitigation of
Non-CO2 Greenhouse Gases: Solvents | US EPA
. [online] Available at:
https://www.epa.gov/global-mitigation-non-co2-greenhouse-gases/global-mi...
[Accessed 5 Dec. 2018].

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