Ind. Eng. Chem. Res. 2010, 49, 1351–1358
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Interfactory and Intrafactory Water Network System To Remodel a Conventional Industrial Park to a Green Eco-industrial Park Seong-Rin Lim† and Jong Moon Park*,‡ Department of Chemical Engineering and Materials Science, UniVersity of California, DaVis, California 95616, and AdVanced EnVironmental Biotechnology Research Center, Department of Chemical Engineering, School of EnVironmental Science and Engineering, Pohang UniVersity of Science and Technology, San 31, Hyoja-dong, Pohang 790-784, South Korea
Water network synthesis is to optimize a water supply system by connecting water sources to sinks in order to maximize water reuse. This synthesis has been applied within a factory to reduce freshwater consumption. This study illustrates (i) the synthesis and design of an interfactory and intrafactory water network system for an eco-industrial park (EIPWNS) utilizing more opportunities for water reuse within an industrial park, and (ii) an environmental and economic feasibility study to demonstrate benefits from industrial symbiosis. An EIPWNS is synthesized, designed, and compared to a conventional water system (CWS). The feasibility study using life cycle assessment and life cycle costing shows that the total environmental impacts of the EIPWNS are 7.5% to 16.0% less than those of the CWS, and the life cycle cost of the EIPWNS is 15.6% less. Therefore, the EIPWNS can be employed in remodeling a conventional industrial park to an eco-industrial park. This study provides a good example for disseminating EIPWNSs. 1. Introduction Water network synthesis is used to reduce the flow rate and cost of freshwater, thus reducing environmental and economic burdens simultaneously. This synthesis is optimizing a water supply system by connecting water sources to sinks in order to maximize water reuse.1 For example, wastewater from a given process is transferred to and used for another process in the case where the wastewater meets the water quality requirement of another process. The synthesis contributes to reducing the flow rates of freshwater consumption and wastewater generation, to the conservation of water resources, and to the competitiveness of factories. Therefore, the water network synthesis is performed within the context of cleaner production and ecodesign. Most previous studies for the synthesis have focused on solving mathematical formulations, such as nonlinear programming (NLP) and mixed integer nonlinear programming (MINLP), to find global optima.2–6 Genetic algorithms were also applied to search global optima.7 These approaches are necessary because of nonconvexities resulting from bilinear variables in the mass balances on contaminants. Pinch analysis technologies have been studied to graphically analyze the process limiting data of processes and heuristically synthesize water network systems.8–12 These methods identify the minimum freshwater consumption rate of a given water system and the bottleneck processes that need to be improved in order to further reduce freshwater consumption. The environmental and economic performance of water network systems has recently become the main issue in water network synthesis in line with sustainable development. The economic feasibility of a water network system has been performed to demonstrate its high economic performance.13 The environmental and economic impacts of a water network system have been evaluated to provide information needed to synthesize the most environmentally and economically friendly system.14 * To whom all correspondence should be addressed: Tel.: +82-54279-2275. Fax: +82-54-279-2699. E-mail:
[email protected]. † University of California. ‡ Pohang University of Science and Technology.
Mathematical optimization models have been developed to synthesize the most economical or environmentally friendly water network system.15,16 Multiobjective optimization has been studied to minimize the total annualized cost and environmental impacts of a water network system.17 Water network synthesis can be applied to generate an interfactory and intrafactory water network system to remodel a conventional industrial park to an eco-industrial park. The concept of the interfactory and intrafactory water network system is expanded from a water network system for a factory because the aim of the interfactory and intrafactory water network system is to increase opportunities for water reuse by extending the system boundary for networking over a factory and thus by including more processes of many factories within an industrial park. Mixed integer linear programming (MILP) has been suggested to design multiple plant water networks.18 Interfactory water networks have been developed by directly and indirectly reusing wastewater from other factories19 and by extending automated targeting technique for a single network system.20 Cooperation between two factories has been emphasized to reduce more greenhouse gases.21 This is in the context of the industrial symbiosis where raw material consumption, waste generation, and environmental impacts are minimized due to the exchange of waste, byproduct, and energy between factories.22,23 In other words, wastewater from a process in a factory can be reused for other processes in the same factory (i.e., intrafactory) and in the other factories (i.e., interfactory). The interfactory and intrafactory water network system can be employed in converting conventional industrial parks to ecoindustrial parks in order to enhance the environmental and economic performance of industrial parks. This study illustrates (i) the synthesis and design of an interfactory and intrafactory water network system for an ecoindustrial park (EIPWNS), and (ii) its environmental and economic feasibility study to show the necessity and importance for the interfactory network as well as the intrafactory network to improve eco-efficiency. This study can be used as a good example in disseminating interfactory and intrafactory water network systems into conventional industrial parks and as a
10.1021/ie9014233 2010 American Chemical Society Published on Web 12/28/2009
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Table 1. Limiting Process Data Used To Synthesize the Interfactory and Intrafactory Water Network System for an Eco-industrial Park (EIPWNS) factory
process
contaminant
c,max Cf*_p* (mg/L)
c,max Cf*_p*,f_p (mg/L)
c Mf*_p* (kg/h)
L Ff*_p* (m3/h)
A
A1
COD SS COD SS COD SS COD SS COD SS COD SS
65 70 45 5 60 80 15 10 20 15 2 3
210 220 120 30 230 250 80 60 90 70 15 15
0.65 0.71 0.27 0.03 0.49 0.53 1.81 1.44 1.90 1.59 0.01 0.02
0.2
4.6
7.7
0.5
2.7
4.5
0.3
3.5
5.7
1.8
33.5
56.3
2.0
36.4
60.6
0.1
2.2
3.2
A2 A3 B
B1 B2
C
C
Table 2. Distance Matrix between Processes (Unit: Meter)
A2 A3 B1 B2 C
A1
A2
A3
B1
B2
200 200 430 430 2100
200 430 430 2100
430 430 2100
200 1600
1600
guideline and procedure needed to implement the systems. Six processes from three factories in an iron and steel industrial park were used as water sources and sinks. The EIPWNS was synthesized from a mathematical optimization model by minimizing the consumption of industrial water. The existing conventional water system (CWS) in the industrial park and EIPWNS were designed as a preparatory stage for the feasibility study. Life cycle assessment (LCA) and life cycle costing (LCC) were performed to evaluate the environmental impacts and economic costs of the CWS and EIPWNS. The interfactory and intrafactory network approach can be extended to the generation of heat and energy network systems in industrial parks in order to more recover and utilize waste energy and improve their environmental and economic performances. 2. Methods Six processes of three factories in an iron and steel industrial park in Korea were employed as water sources and sinks for synthesizing the EIPWNS: three cleaning, cooling, and brushing processes in factory “A” which produces galvanized and aluminized steel sheets; two cleaning processes for coppercoated and tin-coated plates in the factory “B”, which produces electrolytic steel plates used in manufacturing bottles and cans; and a rinsing process in the factory “C”, which produces a reinforced material for automobile tires. The process limiting data for the synthesis of the EIPWNS are summarized in Table 1, showing operational conditions required for each process. COD (chemical oxygen demand) and SS (suspended solid) were used as water quality indicators because these concentrations can represent the amount of organic contaminants and particles. The distance matrix between water sources and sinks is shown in Table 2, which is used to estimate the length of pipes. The concentration of industrial water used for the processes is 0 mg/L for COD and for SS. 2.1. Water Network Synthesis. A generalized superstructure model was used to formulate the mathematical optimization model for the EIPWNS (Figure 1). This model includes all possible interconnections between water sources and sinks of factories within an industrial park. However, local recycling from the outlet to the inlet within a process is prohibited to prevent excessive electricity cost incurred from pumping with a high flow rate because the small gap between the concentra-
min Ff*_p* (m3/h)
max Ff*_p* (m3/h)
tions of the inlet and outlet requires a high flow rate to transfer the contaminant load of the process into water.13 It is assumed that the mixers combine many streams into a single stream and that the splitters divide a stream into all possible streams flowing to water sinks. A generalized mathematical optimization model was formulated on the basis of the superstructure model, as shown in Appendix A; the objective function is to minimize the total consumption of industrial water rather than total economic cost or environmental impact because the industrial park has been suffering from water shortage during dry winter seasons and needs to cope with future water shortage from climate change. The original EIPWNS was generated from the optimal solution to the mathematical optimization model. The limiting process data and industrial water data were used for the model. The General Algebraic Modeling System (GAMS) software was used to find an optimal solution, employing MINOS as an NLP solver due to nonlinearity from the bilinear variables, that is, the multiplication of flow rates and concentrations, in the mathematical optimization model,24 even though its global optimality cannot be guaranteed. However, it should be mentioned that even local solutions are useful for industrial application if they significantly reduce the flow rate of industrial water. 2.2. Water System Design. A simplified EIPWNS were specifically designed with respect to retrofitting the CWS into an EIPWNS for the iron and steel industrial park. The original EIPWNS from the optimal solution to the mathematical optimization model was modified by eliminating inefficient interconnections with a flow rate of less than 3.0 m3/h in order to obtain its simplified EIPWNS.13,14 This is because the constraints on the minimum flow rates of interconnections can make the mathematical optimization model complicated and thus prevent easily obtaining optimum solutions. This simplification approach is more practical for implementing water network systems to real situations, even though the simplification slightly increases freshwater consumption and wastewater generation by replacing reused wastewater in the eliminated interconnections with freshwater.13,14 The simplified EIPWNS was compared to the CWS in the water system design, LCA, and LCC. The design of the simplified EIPWNS focused on retrofitting the CWS to the EIPWNS to utilize the existing pipes, pumps, and motors in the CWS, most of which were replaced a year ago. Therefore, the pipes, pumps, motors, and pump pits for water reuse were additionally designed for the EIPWNS and were evaluated for the environmental and economic feasibility study. In other words, the existing CWS was regarded as a baseline for comparative assessment. However, the consumption of industrial water and electricity in the operations and
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Figure 1. Generalized superstructure model used to synthesize the interfactory and intrafactory water network system for an eco-industrial park (EIPWNS).
maintenance (O&M) stage of the CWS was compared to that of the EIPWNS. Pipe diameter and head loss are calculated simultaneously with the flow rate and pipe length. Head loss is calculated using the Darcy-Weisbach equation.25 The maximum head loss basis was set at 200 kPa to prevent designing pipes with too small diameter, which can require excessive pump capacities. Carbon steel was selected for the pipe material. The Korean Standard, KS D3507, was used to take into account the specific characteristics of the pipe.26 The distances between the water sources and sinks are used as the pipe lengths of the interconnections. The specifications of the pumps and electric motors for transferring freshwater are determined in relation to the flow rate and water head requirement. The discharge pressure of a pump is determined by summing the head losses through the pipes and the water pressure needed for the process. The water pressures at the end of the pipe were assumed to be 250 kPa for the processes. Pump pits are needed for the storage of wastewater prior to its being pumped to the processes. The hydraulic retention times of the pump pits were set at 30 min. 2.3. Life Cycle Assessment. LCA was performed to evaluate and compare environmental impacts associated with the CWS and EIPWNS during the life cycle on the basis of the design results. The LCA procedure was performed in accordance with the ISO 14040 series of standards:27 goal and scope definition, life cycle inventory analysis (LCI), life cycle impact assessment (LCIA), and life cycle interpretation. The goal of this LCA is to compare the environmental impacts of the EIPWNS to those of the CWS in order to illustrate that the EIPWNS was more suitable for an eco-industrial park. The scope definition includes the system, function, functional unit, reference flow, and system boundaries. The system and its function are defined as a water system designed to supply the processes with industrial water. The functional unit is defined as a water system needed for the six processes for 15 years. This service time took into account the remaining lifetime of the existing pipes and mechanical equipment. The reference flow was set to a water system, that is, EIPWNS or CWS. System boundaries include all components in each water system. However, the components used as a baseline for comparative assessment were excluded in the system boundaries, as in the water system design. LCI was performed to quantify all inputs and outputs associated with each water system throughout its construction,
operations and maintenance (O&M) and disposal. The GaBi 4.028 and Ecoinvent v1.229 databases were used for the LCI: the databases show the quantity of all the materials and energy required to obtain the unit quantity of a component. All the components in the EIPWNS are as follows: in the construction stage were the manufacture of pipes, pumps, and motors and the construction of pump pits; in the O&M stage were the consumption of industrial water and electricity and maintenance and repairs (M&R); and in the disposal stage were the recycling of iron, steel and copper scraps and the landfill of wasted concrete. LCIA was performed to evaluate the significance of potential environmental impacts on the basis of the LCI results. The CML 2001 methodology was used for the classification and characterization.30 To take into account a variety of burdens on humans and the environment, the environmental impact categories in the methodology consist of abiotic depletion, acidification, eutrophication, freshwater aquatic ecotoxicity, global warming, human toxicity, marine aquatic ecotoxicity, ozone layer depletion, photochemical ozone creation, radioactive radiation, and terrestrial ecotoxicity. Life cycle interpretation was performed to comprehensively analyze the results of the preceding steps. The characterization results of the EIPWNS were compared to those of the CWS to illustrate the variation of environmental impacts through the water network synthesis. 2.4. Life Cycle Costing. LCC was performed to estimate all economic costs incurred from each water system and to determine which system was more economical. All costs are divided into four life cycle stages: in the design and supervision stage are the costs for basic and detailed designs, and supervision; in the construction stage are the costs for piping, equipment (pump and motor), and pump pits, construction expenses, and the contractor’s overhead and profits; in the O&M stage are the costs of industrial water, electricity, and M&R; in the disposal stage are the costs for the decommission of pipes, equipment, and pump pits, the recycling of iron, steel, and copper scraps, landfill of wasted concrete, construction expenses, and the contractor’s overhead and profits. These costs were estimatedusingdatabasesconsistingofpriceandcostinformation.31,32 The service life for the LCC was set at 15 years, as in the LCA. The components used as a baseline for comparative assessment was excluded in the cost estimation, as in the water system design and LCA.
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All the costs were discounted to their present values with respect to the time value of money. The discounted costs can be equally compared to one another on the same time point. For example, the O&M and disposal costs cannot be directly compared to the construction costs because the O&M costs recurred annually and the disposal costs were incurred at the end of the service life. Discounting the O&M and disposal costs enables their direct comparison with the construction cost. The present value was estimated using the following equation: PV ) P(1 + e)t /(1 + i)t
(1)
where PV ) present value; P ) future value; e ) escalation rate; i ) discount rate; t ) time. The discount rate was set at 5.7% in relation to the yields of treasury bonds (5-years) over the last 10 years in South Korea,33 and the escalation rate (i.e., inflation rate) was assumed to be the 3.0% targeted by the Bank of Korea for the period between 2004 and 2006.34 All the discounted costs are summed to obtain the life cycle costs of the CWS and EIPWNS. 3. Results and Discussion 3.1. Water Network Synthesis. The original EIPWNS was generated from the optimal solution to the mathematical optimization model, as shown in Figure 2b. The original EIPWNS was compared to the CWS (Figure 2a). The water network synthesis generated the 10 interconnections between water sources and sinks to reuse wastewater. The consumption of industrial water in the original EIPWNS was 22.6% less than that in the CWS: the synthesis contributed to the conservation of water resources and to the reduction of economic costs. The wastewater generation in the original EIPWNS was 24.0% less than that in the CWS: the synthesis could contribute to enhancing the removal efficiencies and to lower the operating cost in wastewater treatment plants because the decrease of hydraulic loads enable effective physical and chemical treatments due to the high reaction rates of chemicals with contaminants, even though contaminant loads remained unchanged. 3.2. Water System Design. The simplified EIPWNS was obtained by simplifying the original one, as shown in Figure 2c. The wastewater reused through the eliminated interconnections was replaced with industrial water. This simplification is useful in implementing EIPWNSs into industrial parks because the interconnections with a low flow rate are inefficient in transferring reused wastewater through pipes and pumps and are ineffective for water reuse. The simplified EIPWNS was compared to the CWS. The four interconnections were employed to reuse wastewater. The consumption of industrial water in the EIPWNS was 18.3% less than that in the CWS, and the wastewater generation in the EIPWNS was 19.5% less. Three pumps were needed to transfer wastewater to the processes, that is, from process B1 to processes A1 and A3, from process B1 to process B2, and from process B2 to process B1. Two pump pits were needed in the processes B1 and B2 to store wastewater. The water network synthesis incurred the trade-offs between the decrease in industrial water consumption as well as wastewater generation and the increase in the quantities of pipes, equipment, and pump pits as well as electricity consumption. The design results are summarized in Table 3. Additional pipes, pumps, motors and pump pits were needed for water reuse in the EIPWNS: their quantities in the CWS were zero because the configuration of the CWS was used as a baseline for comparative assessment with respect to retrofitting the CWS.
Figure 2. Configurations of the water supply systems: (a) conventional water system (CWS); (b) original water network system (WNS) generated from the optimal solution to the mathematical optimization model; (c) simplified WNS, modified by eliminating interconnections with a flow rate of less than 3.0 m3/h in the original WNS (FW, freshwater; WW, wastewater; unit, m3/h). Table 3. Summary of the Design Results for the Conventional Water System (CWS) and the Interfactory and Intrafactory Water Network System for an Eco-industrial Park (EIPWNS)a contributor pipe pump motor pump pit industrial water electricity consumption wastewater generation a
unit length weight weight weight volume flow rate power flow rate
m kg kg kg m3 m3/h kW m3/h
CWS
EIPWNS
82.9 22.8 78.0
1260 6695 244 86 14.3 67.7 23.8 62.8
The blanks for the CWS mean the baseline in the comparison.
The electricity consumption in the EIPWNS was 4.4% greater than that in the CWS because the increase of the power requirement for water reuse outweighed the decrease of that for supplying industrial water, which was derived from the reduction of industrial water. 3.3. Life Cycle Assessment. The EIPWNS was more environmentally friendly than the CWS. The LCA results are summarized in Table 4. The environmental impacts of the CWS in the construction and disposal stages were set to zero for comparative assessment. Each total environmental impact of the
subtotal
landfill
copper recycling
steel and iron recycling
subtotal
maintenance and repairs
electricity
industrial water
subtotal
pump pit
motor
pump
pipe
CWS EIPWNS
CWS EIPWNS CWS EIPWNS CWS EIPWNS CWS EIPWNS
CWS EIPWNS CWS EIPWNS CWS EIPWNS CWS EIPWNS
CWS EIPWNS CWS EIPWNS CWS EIPWNS CWS EIPWNS CWS EIPWNS
3.4 × 104 3.1 × 104
5.3 × 101
1.9 × 100
2.4 × 10-1
5.1 × 101
9.9 × 100 3.4 × 104 3.1 × 104
104 104 103 103
2.5 × 104 2.1 × 104
2.9 × 101
2.4 × 100
3.1 × 100
2.3 × 101
7.6 × 100 2.5 × 104 2.1 × 104
2.1 1.7 3.5 3.6
× × × ×
104 104 104 104
× × × ×
2.2 1.8 1.3 1.3
1.7 × 101
5.3 × 100
3.5 × 100
5.4 × 10-1
7.6 × 100
2.2 × 101
4.7 × 100
9.4 × 10-1
1.7 × 100
1.5 × 101
AP
× × × × 103 103 102 102
3.9 × 103 3.3 × 103
3.2 × 100
1.3 × 100
1.4 × 10-2
1.9 × 100
3.3 × 100 3.9 × 103 3.2 × 103
3.5 2.9 3.6 3.7
7.3 × 100
5.6 × 100
4.3 × 10-2
6.3 × 10-2
1.6 × 100
EP
× × × × 105 105 105 105
9.1 × 105 8.0 × 105
1.4 × 104
6.7 × 100
1.4 × 104
8.3 × 100
4.6 × 102 9.1 × 105 7.9 × 105
7.3 6.0 1.8 1.9
1.0 × 103
4.9 × 101
5.8 × 100
1.3 × 100
9.7 × 102
FAETP
× × × × 106 106 106 106
6.2 × 106 5.5 × 106
5.6 × 103
1.7 × 102
3.0 × 101
5.4 × 103
2.0 × 103 6.2 × 106 5.5 × 106
4.0 3.2 2.2 2.3
4.4 × 103
2.2 × 103
1.4 × 102
2.8 × 102
1.8 × 103
GWP
× × × × 106 106 105 105
3.9 × 106 3.4 × 106
3.5 × 103
6.7 × 101
5.5 × 101
3.3 × 103
3.0 × 103 3.9 × 106 3.4 × 106
3.2 2.6 7.3 7.6
6.8 × 103
2.3 × 102
1.5 × 102
1.7 × 102
6.2 × 103
HTP
× × × ×
109 109 108 109
3.1 × 109 2.8 × 109
4.4 × 106
1.7 × 104
2.9 × 106
1.5 × 106
5.7 × 105 3.1 × 109 2.8 × 109
2.1 1.7 9.8 1.0
1.3 × 106
7.0 × 104
4.6 × 104
1.6 × 104
1.1 × 106
MAETP
× × × ×
10-1 10-1 10-2 10-2
× × × ×
103 103 102 102
4.1 × 100 2.5 × 103 2.1 × 103
2.6 × 10-1 2.3 × 10-1
3.5 × 10-1
1.7 × 10-1
3.6 × 100
1.3 × 100 2.5 × 103 2.1 × 103
2.2 1.8 3.3 3.4
3.0 × 100
5.9 × 10-1
2.1 × 10-1
1.0 × 10-1
2.1 × 100
POCP
4.3 × 10-4
4.5 × 10-5
9.9 × 10-6
3.8 × 10-4
1.2 × 10-4 2.6 × 10-1 2.3 × 10-1
2.0 1.6 5.9 6.1
2.7 × 10-4
7.2 × 10-5
1.3 × 10-5
6.4 × 10-6
1.8 × 10-4
ODP
× × × ×
10-2 10-2 10-2 10-2
7.4 × 10-2 6.6 × 10-2
3.1 × 10-5
3.4 × 10-7
5.4 × 10-6
2.5 × 10-5
1.0 × 10-5 7.4 × 10-2 6.6 × 10-2
5.3 4.3 2.2 2.3
2.2 × 10-5
4.4 × 10-6
5.9 × 10-6
2.5 × 10-7
1.2 × 10-5
RAD
× × × ×
104 104 104 104
6.2 × 104 5.8 × 104
2.4 × 100
5.1 × 10-1
1.9 × 10-1
1.7 × 100
8.9 × 100 6.2 × 104 5.7 × 104
3.2 2.6 3.0 3.1
2.0 × 101
4.3 × 100
5.8 × 10-1
1.2 × 10-1
1.5 × 101
TETP
a CML 2001 methodology was employed for the classification and characterization. ADP, abiotic depletion potential (kg Sb-equivalents); AP, acidification potential (kg SO2-equivalents); EP, eutrophication potential (kg Phosphate-equivalents); FAETP, freshwater aquatic ecotoxicity potential (kg DCB-equivalents); GWP, global warming potential (100 years) (kg CO2-equivalents); HTP, human toxicity potential (kg DCB-equivalents); MAETP, marine aquatic ecotoxicity potential (kg DCB-equivalents); POCP, photochemical ozone creation potential (kg ethene-equivalents); RAD, radioactive radiation potential (DALY); TETP, terrestrial ecotoxicity potential (kg DCB-equivalents); DCB, 1,4-dichlorobenzene. b The blanks for the CWS mean the baseline in the comparison.
total (A + B + C)
disposal (C)
O&M (B)
construction (A)
ADP
Table 4. Results of the Life Cycle Impact Assessment for the Conventional Water System (CWS) and Interfactory and Intrafactory Water Network System for an Eco-industrial Park (EIPWNS) in the Life Cycle Stagea,b
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Figure 3. Results of the life cycle costing (LCC) on the conventional water system (CWS) and the interfactory and intrafactory water network system for an eco-industrial park (EIPWNS): (a) total cost estimates in each life cycle stage and life cycle costs. Future costs were discounted to present values; (b) cost estimates in the construction stage; (c) in the operations and maintenance (O&M) stage (on an annual basis); and (d) in the disposal stage.
EIPWNS during the life cycle was 7.5%-16.0% less than that of the CWS in all the environmental impact categories: the tradeoffs between the environmental impact categories from the CML 2001 methodology were not incurred through the water network synthesis. Most environmental impacts in the EIPWNS were incurred from the consumption of industrial water and electricity in the O&M stages because industrial water and electricity were steadily consumed over the service life. The proportion of the environmental impacts from the O&M stage to the total environmental impacts incurred during the life cycle in the EIPWNS was 98.1%-100.0% for the environmental impact categories. The environmental impacts from pipes, pumps, motors, and pump pits were negligible, even though the LCA evaluated the environmental impacts from additional pipes, motors, and pump pits needed for water reuse in the EIPWNS. The most principal contributor to the environmental impacts of the EIPWNS was the consumption of industrial water in all the environmental impact categories, with the exception of the terrestrial ecotoxicity potential category: its environmental impacts accounted for 56.4%-88.1%.
3.4. Life Cycle Costing. The EIPWNS was more economical as well as environmentally friendly than the CWS. The LCC results are summarized in Figure 3. The costs of the CWS in the construction and disposal stages were zero for comparative assessment. The life cycle cost of the EIPWNS was 15.6% less than that of the CWS because the decrease of the O&M cost through the water network synthesis outweighed the increase of the construction and disposal costs: the proportion of the O&M cost to the life cycle cost in the EIPWNS was 98.0%, and those of the construction and disposal costs were 1.6% and 0.4%, respectively. The costs of design, supervision, construction, and disposal were not significant from a life cycle perspective. The increase or decrease of the costs of each contributor through the water network synthesis was in accordance with the results of the water system design. The most principal contributor to the life cycle cost in the EIPWNS was the consumption of industrial water. Therefore, industrial water was the hot spot to be minimized with a first priority in order to improve the environmental and economic performance of an EIPWNS. The cost of industrial water accounted for 95.7% of
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the O&M cost in the EIPWNS. The second principal contributor to the life cycle cost in the EIPWNS was the electricity cost, but this cost accounted for only 3.7% of the O&M cost. Revenue was obtained from the recycling of the steel, iron and copper scraps from the disposal of pipes and equipment.
∑F
w,f*_p*+
w∈W
∑F
∑ ∑F
f_p,f*_p*
f∈F p∈P
c w,f*_p*Cw+
w∈W
The interfactory and intrafactory water network system for the eco-industrial park was synthesized and designed, and its environmental and economic performance was evaluated using LCA and LCC. The EIPWNS was more environmentally friendly and economical than the CWS and was therefore in line with an eco-industrial park. To practically implement the interfactory and intrafactory water network system, the close cooperation between companies is essential to share environmental and economic costs and benefits from the system because the operation of a process in a factory affects the processes in other factories. Therefore, stable operation would be a key factor to the success of the interfactory and intrafactory water network system. Furthermore, this study needs to take into account the variability of process limiting data in the mathematical optimization model, even though the data in this study are stable. Water network synthesis for processes in various factories within an industrial park can effectively improve its ecoefficiency by utilizing more opportunities for water reuse within an industrial park than within a factory. This synthesis can be employed in remodeling a conventional industrial park to an eco-industrial park as well as in constructing a new ecoindustrial park. This study provides a good example to disseminate interfactory and intrafactory water network systems into conventional industrial parks. In addition, the interfactory and intrafactory network approach can be extended to the generation of heat and energy network systems in industrial parks in order to more recover and utilize waste energy and improve the eco-efficiency of industrial parks. Acknowledgment This work was financially supported in part by the Korean Science and Engineering Foundation (R11-2003-006) through the Advanced Environmental Biotechnology Research Center at Pohang University of Science and Technology and in part by the Korean Ministry of Commerce, Industry, and Energy through the Korean National Cleaner Production Center. This work was also supported by the program for Advanced Education of Chemical Engineers (2nd stage of BK21). Appendix
- Ff*_p* ) 0 ∀f* ∈ F and ∀p* ∈ P (A2)
∑ ∑F
c f_p,f*_p*Cf_p,f*_p*
f∈F p∈P
4. Conclusions
1357
∀f* ∈ F,
- Ff*_p*Ccf*_p* ) 0
∀p* ∈ P,
and ∀c ∈ C (A3)
For the flow rate and concentration mass balances of a process (p*) releasing contaminants in a factory (f*) and its splitter, Ff*_p* - FLf*_p* -
∑ ∑F
f*_p*,f_p
f∈F p∈P
Ff*_p*Ccf*_p* + Mcf*_p* -
- Ff*_p*,ww ) 0
∀f* ∈ F,
∑ ∑F
and ∀p* ∈ P (A4)
c f*_p*,f_pCf*_p*,f_p
-
f∈F p∈P Ff*_p*,wwCcf*_p*,f_p
)0 ∀f* ∈ F, ∀p* ∈ P, and ∀c ∈ C (A5) For the constraints of the flow rate and concentration on a process (p*) in a factory (f*), max Fmin f*_p* e Ff*_p* e Ff*_p*
(A6)
Ccf*_p* e Cc,max f*_p*
(A7)
Ccf*_p*,f_p e Cc,max f*_p*,f_p
(A8)
For the constraints for the prevention of local recycling on a process (p*) in a factory (f*), Ff*_p*,f_p ) 0
(A9)
where the value of “f*_p*” is the same as that of “f_p”. In this model, the total number of the variables is fp(fp + 2c + w + 1) + 1, and the total number of equality constraints is 2fp(c + 1) + 1 (the number of the contaminants, freshwater sources, processes, and factories are c, w, p, and f, respectively). Therefore, the number of independent variables is equal to fp(fp + w - 1). B. Nomenclature. Sets C ) {c|c is a contaminant in the water}, c ) 1, 2, ..., Nc F ) {f|f is a factory}, f ) 1, 2, ..., Nk P ) {p|p is a process}, p ) 1, 2, ..., Nn W ) {w|w is freshwater available}, w ) 1, 2, ..., Nm WW ) {ww|ww is wastewater}, ww ) 1, 2, ..., Nn Variables
A. Generalized Mathematical Optimization Model for an EIPWNS. A generalized mathematical optimization model for an EIPWNS is formulated as follows: For the objective function to minimize the total flow rate of freshwater used in an EIPWNS, minimize Ftw )
∑ ∑ ∑F
w,f_p
(A1)
w∈W f∈F p∈P
Subject to the following: For the flow rate and concentration mass balances of a mixer at the inlet of a process (p*) in a factory (f*),
c ) concentration at the inlet of a process (p*) in a factory Cf*_p* (f*) c Cf_p,f*_p* ) concentration from the outlet of a process in a factory to the inlet of a process (p*) in a factory (f*) c Cf*_p*,f_p ) concentration from the outlet of a process (p*) in a factory (f*) to the inlet of a process in a factory Ff*_p* ) flow rate at the inlet of a process (p*) in a factory (f*) Ff_p,f*_p* ) flow rate from the outlet of a process in a factory to the inlet of a process (p*) in a factory (f*) Ff*_p*,f_p ) flow rate from the outlet of a process (p*) in a factory (f*) to the inlet of other processes Ff*_p*,ww ) flow rate from the outlet of a process (p*) in a factory (f*) to wastewater Fw,f_p ) flow rate from freshwater to a process in a factory
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Fw,f*_p* ) flow rate from freshwater to a process (p*) in a factory (f*) Fwt ) total flow rate of industrial water used in a water network system Parameters c ) contaminant mass load of a process (p*) in a factory (f*) Mf*_p* c,max Cf*_p* ) maximum concentration at the inlet of a process (p*) in a factory (f*) c,max Cf*_p*,f_p ) maximum concentration from the outlet of a process (p*) in a factory (f*) to the inlet of a process in a factory Cwc ) freshwater concentration L Ff*_p* ) water loss rate in a process (p*) in a factory (f*) Fmax f*_p* ) maximum flow rate at the inlet of a process (p*) in a factory (f*) Fmin f*_p* ) minimum flow rate at the inlet of a process (p*) in a factory (f*)
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ReceiVed for reView September 10, 2009 ReVised manuscript receiVed November 19, 2009 Accepted December 17, 2009 IE9014233
