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Involving Acceptability in the Optimal Design of Total Integrated Residential Complexes Involving the Water-Energy-Waste Nexus Jesús Manuel Núñez-López, Esbeydi Villicaña-García, Brenda Cansino-Loeza, Eusiel Rubio-Castro, and José María Ponce-Ortega ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.7b04854 • Publication Date (Web): 27 Apr 2018 Downloaded from http://pubs.acs.org on April 27, 2018

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ACS Sustainable Chemistry & Engineering

Involving Acceptability in the Optimal Design of Total Integrated Residential Complexes Involving the Water-Energy-Waste Nexus

Jesús Manuel Núñez-López, a Esbeydi Villicaña-García,a Brenda Cansino-Loeza,a Eusiel Rubio-Castro,b and José María PonceOrtega a*

a

Chemical Engineering Department, Universidad Michoacana de San Nicolás de

Hidalgo, Francisco J. Mujica S/N, Ciudad Universitaria, 58060, Morelia, Michoacán, México. b

Chemical and Biological Sciences Department, Universidad Autónoma de Sinaloa, Av. de las Américas S/N, 80010, Culiacán, Sinaloa, México.

* Corresponding author: Prof. José María Ponce-Ortega E-mail: [email protected] Phone: +52 443 3223500 ext. 1277 Fax: +52 443 3273584

ACS Paragon Plus Environment

ACS Sustainable Chemistry & Engineering 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract This work presents a multi-objective optimization model for the design of an integrated residential complex, which incorporates the proper use of available resources and wastes through recycling and reusing networks. The proposed model involves the proper use of water accounting for rainwater harvesting and the reuse of reclaimed water. The model also includes the design of a cogeneration system to satisfy electricity demands as well as hot water demands. The treatment of the produced solid waste is also incorporated through an incineration system, and an algae system is involved for sequestering the associated emissions. The proposed model aims to satisfy the energy, heat and water demands, and the treatment for the residues with the objective to minimize the associated cost and the associated emissions. Furthermore, the proposed model includes an objective function associated to the minimization of the damage to the health of the inhabitants.

Keywords: Sustainable residential complex; Acceptability; Human Health; Water and energy integration; Optimization.


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INTRODUCTION Currently, the inadequate management of natural resources represents one of the greatest problems for humanity,1 mainly water management in the agriculture,2 industry3 and housing sectors.4 For addressing this problem, different approaches have been reported for the integration of water in these sectors through water networks involving the proper use,5 reuse,6 recycling7 and regeneration of this resource,8 and currently considering storage and rainwater collection systems.9 Recently, different approaches have been reported for integrating residential complexes,10 considering both water and energy integration11 and trigeneration systems.12 Additionally, optimization approaches for designing cogeneration systems to satisfy water and energy needs in residential complexes have been proposed,13 and also for incorporating refrigeration systems through trigeneration approaches.14 Moreover, the importance to reduce the impact for the emissions associated to the use of fresh fuel (i.e., fuel purchased to external sellers) has been identified for several industrial processes,15 determining their social relationships.16 For designing integrated residential complexes, usually only economic objectives have been considered for the use of water17 and energy.18 Recently, objectives for reducing the associated greenhouse gas emissions have been incorporated,19 and the trade-offs between the stakeholders involved have been identified.20 It should be noted that the previous approaches have not considered the acceptability of the considered integrated systems. The acceptability refers to the acceptance of the stakeholders involved in the implementation of the integrated residential complex, including inhabitants and investors. Notice that these systems are part of a housing complex, and the economic implications for the reduction in the consumption of fresh resources is important; however, the economic implication associated to the initial investment has not properly addressed.21 Furthermore, the acceptability associated to the implications of the integrated complex to the inhabitants has not been considered. It should be noticed that the inhabitants can be exposed to unhealthy conditions, such as noise, bad smells22 and potential damages to health,23 and this point should be addressed to improve the acceptability of the designed integrated processes. Therefore, this paper presents an optimization approach for designing integrated residential complexes accounting for the



proper use of resources and reuse of wastes, and at the same time involving the acceptability of the proposed solutions. PROBLEM STATEMENT The addressed problem (Figure 1) consists in determining the optimal configuration of an integrated residential complex, which seeks to satisfy the water, electricity, heating and cooling needs as well as to treat the wastewater, emissions and wastes accounting for the minimization of the associated cost, emissions and the acceptability of the inhabitants. The economic objective functions include the minimization of the total annual cost and the return of investment, which include operating and capital costs for each of the required processing units, as well as the purchase and sale of resources to external costumers. The environmental objective functions involve the reduction of fresh water consumption, the minimization of greenhouse gas emissions and the quantification of the environmental impact caused by the use of fresh resources and by the management and installation of the selected units. In the same way, through the health objective function, the damage to health associated to the inhabitants is considered. To solve this problem, the superstructure shown in Figure 2 is proposed. In this superstructure, to satisfy the water needs, it is considered the consumption of fresh water from the public network and the implementation of a rainwater collection system on the housing complex. Electricity can be obtained from the grid or through a cogeneration unit, where waste heat is used for heating water together with a boiler. The hot water is used to satisfy the domestic needs (40° C) and for the operation of an absorption refrigeration system. Covering the needs of the residential complex generates wastewater, which is treated in a wastewater treatment plant, where the treated greywater can be used for irrigating gardens or for the production of algae, while the treated blackwater is dumped at the drain immediately after its treatment. Solid waste is treated through a gasification system and the carbon dioxide emissions generated by the process units are used in the algae production system. PROPOSED MODEL FORMULATION AND SOLUTION APPROACH The proposed model formation is presented in the electronic supporting information section as well as the used nomenclature, and this section only presents the objective functions and the solution approach.


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Objective Functions The objective function are described as follows. Total annual cost for the integrated system The total annual cost ( TAC ) is equal to the total operating cost ( TotOpCost ) plus the total capital cost ( TotCapCost ) minus the total sales ( TotSales ): (1)

TAC = TotOpCost + TotCapCost − TotSales

Fresh water consumption The total fresh water consumption ( FFwTot ) in the integrated system is equal to the sum of the fresh water used in each period of time:

FFwTot = ∑ FFwt

(2)

t

GHGC emissions The greenhouse gas emissions ( GDischargeTotal ) are equal to the emissions discharged to the environment by the ICE (Internal Combustion Engine) ( Fg tIce- Discharge ) plus the emissions by the boiler ( Fg tBoiler - Discharge ) and the gasification process ( Fg tGasification-Discharge ) as follows:

GDischargeTotal = ∑ Fg t

Ice-Discharge t

+ ∑ FgtBoiler-Discharge + ∑ FgtGasification-Discharge t

(3)

t

Environmental Impact The environmental impact ( EnvImp ) is quantified through the life cycle assessment using the eco-indicator 99 method with the following equations:

EnvImp = EI HH + EI EQ + EI DR

(4)

where EI HH represents the damage to human health, EI EQ is the environmental impact that affects the ecosystem quality and EI DR is the damage to resources and each one is calculated as follows:



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EI HH = EI algae − HH CTS algae Cap algae + EI ARC − HH CTS ARC Cap ARC + EI boiler − HH CTS boiler Cap boiler +

EI WW − HH CTS WW CapWW + EI gasification − HH CTS gasification Cap gasification + EI GW − HH CTS GW Cap GW + EI ICE − HH CTS ICE Cap ICE + EI NGT − HH CTS NGT Cap NGT + EI RWSS − HH CTS RWSS Cap RWSS + EI FWSS − HH CTS FWSS Cap FWSS + EI biodisel -HH ∑ Ft biodisel + EI BWW -HH ∑ Ft treated -ww + t

EI

CO2 -HH

∑ (G

ICE t

boiler t

+G

gasification t

+G

t

)+

(5)

t

EI e-HH ∑ (EtICE + etpurchased -algae + etpurchased + etpurchased -GWT + etpurchased -WWT )+ EI water-HH ∑ Ft FW + t

EI

GWW -HH

t

∑F

reclaimed -GW

t

+ EI

HW -HH

t

∑ (H

ICE t

+H

HW -boiler t

+ ht

purchase- ARC

)+

t

EI NG − HH ∑ ( Ft NG − ICE + Ft NG-boiler + Ft NG-GWT + Ft NG-WW )+ EI ref -HH ∑ (RtARC + rt purchased -residential )+ t

t

EI RW -HH ∑ Ft RW + EI SW -HH ∑ Ft solidwaste t

t

EI EQ = EI algae−EQCTS algaeCapalgae +EI ARC−EQCTS ARCCapARC +EI boiler −EQCTSboilerCapboiler +

EI WW−EQCTSWWCapWW +EI gasification−EQCTS gasificationCapgasification +EI GW −EQCTSGWCapGW + EI ICE−EQCTS ICECapICE +EI NGT −EQCTS NGT CapNGT +EI RWSS −EQCTS RWSSCapRWSS + EI FWSS−EQCTS FWSS CapFWSS + EI biodisel-EQ ∑Ftbiodisel +EI BWW-EQ ∑Fttreated-ww + t

EI

CO2 -EQ

∑(G

ICE t

boiler t

+G

gasification t

+G

t

)+

(6)

t

EI e-EQ ∑(EtICE +etpurchased-algae +etpurchased +etpurchased-GWT +etpurchased-WWT )+EI water-EQ ∑Ft FW + t

EI

GWW-EQ

t

∑F

reclaimed-GW

t

+EI

HW-EQ

t

∑(H

ICE t

HW-boiler t

+H

purchase-ARC t

+h

)+

t

EI NG−HH ∑(Ft NG−ICE + Ft NG-boiler +Ft NG-GWT +Ft NG-WW )+EI ref -HH ∑(RtARC +rt purchased-residential )+ t

EI

RW-EQ

t

∑F t

t

RW

+ EI

SW-EQ

∑F

solidwaste

t

t


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EI DR = EI algae−DRCTSalgaeCapalgae +EI ARC−DRCTS ARCCapARC +EI boiler−DRCTSboilerCapboiler +

EI WW −DRCTSWWCapWW +EI gasification−DRCTS gasificationCapgasification +EI GW−DRCTSGWCapGW + EI ICE−DRCTS ICECapICE +EI NGT −DRCTS NGT CapNGT +EI RWSS −DRCTS RWSSCapRWSS + EI FWSS−DRCTS FWSSCapFWSS + EI biodisel-DR ∑Ftbiodisel +EI BWW-DR ∑Fttreated-ww + t

EI

CO2 -DR

∑(G

ICE t

boiler t

+G

gasification t

+G

t

)+

(7)

t

EI e-DR ∑(EtICE +etpurchased-algae +etpurchased +etpurchased-GWT +etpurchased-WWT )+EI water-DR ∑Ft FW + t

EI

t

GWW-DR

∑F

reclaimed-GW

t

+EI

HW-DR

t

∑(H

ICE t

HW-boiler t

+H

purchase-ARC t

+h

)+

t

EI NG−HH ∑(Ft NG−ICE + Ft NG-boiler +Ft NG-GWT +Ft NG-WW )+EI ref -HH ∑(RtARC +rt purchased-residential )+ t

EI

RW-DR

t

∑F t

RW

+ EI

SW-DR

∑F

solidwaste

t

t

t

where EI's represents the ecopoints for each of the fresh resources and the material for the unit process needed, the ecopoints are listed in Table 1 and Table 2. Sustainability return of investment To assess the sustainability of a process, recently El-Halwagi21 proposed the sustainability return of investment ( SWSROIM ), and in this paper this is determined as follows: N

EnvImp ) Eco - indicator ref TAC ref

TAC[1+ ∑ wi ( SWSROIM =

i

(8)

where TAC ref and Eco - indicator ref are the total annual cost and the environmental impact, respectively, which are associated to satisfy the needs in the housing complex prior to the integration. wi is the weighting factor for the units associated to the integrated process. Process route healthiness index The process route healthiness index (PRHI) was used to evaluate the occupational health of the different processes involved in the superstructure (boiler, algae system, gasification, ICE, grey and black wastewater treatment, raw gases treatment unit). The PRHI is a dimensionless number, which indicates the potential occupational health hazard



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of a route, higher PRHI values indicate larger hazards. It assumes that all the airborne material releases are totally inhaled by the exposed inhabitants, regardless of the plume distribution effects. The development of the PRHI takes into account all of the factors that can potentially contribute to health hazards. The effects of chemicals are assessed by using the assigned values, which indicate their inherent level of hazard health22 and the required data available from OSHA23 for the health effects and workplace exposure limit.

OH indicates the contribution of each process, where they are determined by multiplying the associated factor PR times its input flow F or times the flue gases required for the algae system Gta lg ae . This way, it is obtained an indirect measure of the damage to health due to the quantity of present substances, which is modeled as follows: OH = PR BOILER × Ft NG -boiler + PR GW × Ft Inlet -GW + PRWW × FtWW + PR NGT × Ft NGT - Inlet + PR ICE × Ft NG- ICE + PR ALGAE × Gta lg ae + PR GASIFICATION × Ft NG -needed − gasification

(9)

PRHI is estimated as the procedure developed by Hassim and Edwards22, which is based on data from NFPA and OSHA. The PRHI is calculated as follows: PRHI = ICPHI * MHI * HHI

WECmax OELmin

(10)

PRHI is evaluated for each process, with the intention to determine which process is the most hazardous, to be able to rank all hazardous process involved in the superstructure proposed. Inherent Chemical and Process Hazard Index (ICPHI) Inherent Chemical and Process Hazard Index (ICPHI) involves process conditions and work activities that are potentially harmful to health. It includes the sum of penalties for activities or operations (AP) plus the penalties associated to process conditions and material properties (CP): (11)

ICPHI = AP+CP

ICPHI describes physical properties of materials, process conditions, and the type of process to cause exposure hazard at the workplace and it is based on the probability of the


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releases that will be caused by the activities or the process conditions. For the purposes of assessment, for each activity, process condition and process, there are assigned penalties, a higher penalty indicates a higher hazard posed by the activity. Health Hazard Index (HHI) Chemical hazards have a wide range of health hazards such as irritation, sensitization, carcinogenicity and physical hazards such as flammability, corrosion, and explosibility. Because of this, it is important to evaluate their ability to cause occupational diseases, which is expressed in the Health Hazard Index (HHI). For this purpose, the Occupational Health Administration (OSHA), Health Code (HC) and Health Effects (HE) list the main effects of exposure to each substance. Health codes are used in determining if a violation of an air contaminant standard is serious or other-than-serious, based on guidelines in the Field Operations Manual. Hassim and Edwards22 proposed a ranking matrix for occupational disease in which are listed the health effects with their respective values, these values range from 1 to 20, where 1 represents the most severe health effects and 20 the least effects. With the purpose of make consistent the penalties of every system for the index calculations, the value of HHI=21 (HE code) is used. Furthermore, to be consistent with the other penalties, HHI is scaled using the following relationship:

Scaled penalty =

21- ( HE code )

20

×5

(12)

Where a penalty of 0 represents the minimum health effect and 5 represents the maximum. Material Harm Index (MHI) The Material Harm Index is based on the NFPA data, which evaluates exposure limits that workers are exposed and the possible damages and/or health effects that could occur. Assigning values from 0 to 4, where 4 represents the most hazardous. This index is evaluated for each chemical present in the process. Worker Exposure Concentration (WEC) WECmax is the maximum concentration that a worker is exposed. It is calculated by means of possible leaking and fugitive emissions that can occur in the process, divided by



the ventilation rate that oscillates between 2 and 300 m3/h. In this case, it takes 300 m3/h as the best scenario; in addition, this value is multiplied by the ratio of exposure hours of workers and total hours of work. It is likely that the worker does not inhale for 8 continuous hours, so the exposure time is assumed to be 6 hours. This calculation is performed for each hazardous stream involved in each process. Occupational exposure limit (OEL) OELmin represents the minimum permissible exposure limit according to OSHA. This limit is used for each chemical present in the different streams of the process. Then, the minimum limit is selected because it is the minimum that a human can handle. Assumptions of each considered process This section presents the assumptions for the considered units. Boiler The boiler has a natural gas feed stream, which is composed by methane, ethane, CO2 and O2, this stream will be burned to generate heat and produce a flue gas stream, it is considered a complete combustion, which produces CO2 and water, but water has no harmful effect on human health, so it is omitted from the analyst. It is known that the boiler can produce different substances that are very harmful to health, such as SO2 that can cause bronchitis in people who inhale it, CO that occurs when oxygen in combustion is not enough and can cause dizziness or fainting; another compound is nitrogen oxide, which is the most harmful of all NOx present and produces many negative effects in the respiratory tract of people. In addition, it is possible to have the presence of ashes that cause severe irritations in the respiratory tract, which aggravate asthma in many patients and even causes cardiovascular diseases. However, it is important to emphasize that for this study there is considered a complete combustion that allows analyzing the best scenario and the least damage to the health of the people; also, for a future work, it would be better to take into account all the components that may be present to study the worst case scenario. Also, in the presented case study there was not considered a penalty for changing the used fuel and also a constant temperature for the fresh water was


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considered, but it should be interesting to include the effect of these issues in future works to model the partial load operation of the considered units. Blackwater treatment The blackwater is generally composed of proteins, carbohydrates, oil and greases; for these reasons, the blackwater stream is assumed to be composed of dissolved oxygen, free ammonia, nitrites, nitrates, total phosphorus, chlorides, sulfhydric acid and water. Once the stream is treated, it is produced a stream of clean water that could go to final disposal and another stream of raw gases that is composed of methane, water, carbon dioxide and sulfhydric acid. Greywater treatment In the same way, there is a treatment plant for the greywater produced. However, it is considered that the entire composition does not have nitrogen and phosphorus because these chemicals are associated to fecal matter and urine and for this reason that chemicals are omitted. Therefore, the composition of outflow is O2 dissolved, chlorides, H2S and water. Also, the composition of the outflow of raw gases is the same as the treated blackwater. Gas treatment unit Once the raw gas streams of both wastewater treatment units are obtained, they are mixed. The resulting stream is passed through a gas treatment unit, where the main purpose is to separate the natural gas from the inlet stream. In addition, the H2S that is present in wastewater can be recovered and represents one of the most hazardous chemical to human health. Internal Combustion Engine To evaluate the health risk associated with an Internal Combustion Engine, we take into account natural gas and flue gases as the most harmful streams. Possible health effects from combustion products include eye and respiratory irritation, headaches, fatigue, and dizziness. Algae system



In the algae system, the biofuel, flue gases and greywater streams are considered, being the last two the ones that have the greatest impact on the PRHI. Greywater stream contains H2S that causes a wide range of health effects. Workers are primarily exposed to H2S by breathing it and its exposure to very high concentrations can quickly lead to death. It should be noticed that the design of the algae production system was carried out roughly, because this represents only one option to mitigate CO2 emissions, while the main objective of this work is the formulation of the mathematical model for the design of the residential complex. Based on this, the algae system information, such as system parameters, costs and production were obtained from previously reported works.24 Gasification For the gasification process, there is considered the solid waste stream, which is the biomass for the process and the natural gas stream, in addition the combustion gas and syngas generated were evaluated, being these the ones that contain the more harmful components, such as HCN and H2S. Gasification process causes several issues such as dust, noise, odor and exhaust gases, which in turn can cause several health-related problems for humans. Carbon monoxide, carbon dioxide, and sulfhydric acid that are released during the gasification process may cause health problems like lung damage and skin and eye related problems. Because of this, gasification process should be carried out under controlled conditions that does not allow any leakages during the entire process. Multi-Stakeholder Approach Due to the number of objectives, it is not possible to find a solution to the problem through a Pareto curve and there may be a lot of dissatisfaction with one of the objectives. Therefore, for the solution of the problem, a different tool (multi-stakeholder optimization) is used to find a balance between the objective functions and give a reasonable solution to the problem, which is mathematically modeled as follows:


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TAC - TAC LB FFwTot - FFwTot LB FFwTot )+ w ( )+ j TACUB - TAC LB FFwTotUB - FFwTot LB GHGE - GHGE LB EnvImp - EnvImp LB EnvImp + wGHGE ( ) w ( )+ j j GHGEUB - GHGE LB EnvImpUB - EnvImp LB

f j = wTAC ( j

wSWSROIM ( j

(13)

SWSROIM - SWSROIM LB OH - OH LB OH )+ w ( ) j SWSROIM UB - SWSROIM LB OH UB - OH LB

where w j represents the priorities for each of the objectives and the superscript LB indicates the objective values obtained at the utopia point that is the point obtained by solving each objective separately and the superscript UB indicates the objective values at the nadir point that means the worst solution for each objective. As previously mentioned, it is not possible to analyze the results by means of a Pareto curve because of the number of objectives, for this reason the dissatisfaction term was included to find an attractive solution to the proposed problem. It should be noticed that the best solution for each individual objective is infeasible (Utopian point). This way, dissatisfaction indicates the distance from the best individual solution of each of the objectives for a feasible solution, while to calculate the total dissatisfaction of the problem for each of the scenarios allows getting an average of the individual dissatisfaction of each objective function, as follows:

100 TAC - TAC LB FFwTot - FFwTot LB GHGE - GHGE LB )(( )+( )+( )+ 6 TAC FFwTot GHGEUB EnvImp - EnvImp LB SWSROIM - SWSROIM LB OH - OH LB ( )+( )+( )) EnvImpUB SWSROIM UB OH UB

dis = (

(14)

The optimization model formulation is stated as a multi-objective mixed-integer nonlinear programing problem, whose objective functions are the minimization of the TAC, the total fresh water consumption, the minimization of the greenhouse gas emissions, the environmental impact, the sustainability return of investment, and the process route healthiness index. To solve this problem, first the single objective solution for minimizing each of the objectives is obtained. Based on these previous extreme solutions, the compromised solution through the multi-stakeholder approach is evaluated. CASE STUDY



As case study, there is considered a residential complex located in the central-west region of Mexico, which consists of 1,440 households. This residential complex has an overall consumption of 538,376 m3/year of fresh water and 36,689.20 m3/year of hot water. To satisfy these water requirements in this residential complex, it is considered to implement the proposed optimization formulation to design an integrated residential complex. The residential complex requires 2,400 kWh/year of refrigeration, which can be obtained by sale or from an absorption refrigeration system. The electricity demand profile is shown in Figure 3, which could be obtained from the grid and from the cogeneration system. It should be noticed that Figure 3 presents an average of the seasons of the year, the curve represents the need for electricity throughout the day, notice that at the beginning and at the end of the day is when there is the highest demand. It should be noticed that this curve was obtained from data of the considered residential complex.11 The residential complex generates 864 tonnes of solid waste per year that are treated by a gasification process to produce natural gas. All the data for the addressed case study were obtained from information of the considered residential complex.9,11,16,18-20 RESULTS The proposed muti-objective optimization model was coded and solved in the software GAMS.25 The model consists of 1,098 continuous variables, 10 binary variables, and 3,570 constraints. The solver Baron was used and it usually consumes 15-18 min to solve the model using a computer with an Intel processor at 2.4 GHz and 8 GB of RAM. It should be noticed that the model includes non-convex terms, so to solve the model in GAMS we need a global optimization solver; in this case, we selected Baron because a local solver (i.e., DICOPT) did not provide a good solution. The weights for the objective functions for each of the scenarios of the case study for the multi-stakeholder approach were generated randomly in the software MatLab through the Latin hypercube function. Assigning random weights to the objective functions is only a representative option to show the effect of prioritizing one objective and to show the trade-offs of the considered objectives. The parameters used to calculate the environmental impact and the damage to human health are shown in Tables 1, 2 and 3. The time needed to find a solution to each of the simulations was approximately between 15 and 18 minutes. For the simulation, we use average data per hour throughout the day for different seasons, which is considered a


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representative way to model the needs of the residential complex. Solving the problem for all the days of the year, considering the climatic conditions and demands, yields a very large problem that can not be solved in a reasonable CPU time, but the results are similar. The values obtained using the proposed methodology, as well as the utopia and nadir points, and the compromise solution are shown in Table 4. The dissatisfaction of each of the objective functions as well as the total dissatisfaction for all of the scenarios are shown in Table 5. Three of the scenarios were selected for analysis, the scenarios that have the lowest, the highest and an intermediate dissatisfaction, respectively. The values for the objective functions of these scenarios are listed in Table 6. We can observe in the scenario with the lowest dissatisfaction (Figure 4) how the TAC is far from its best solution by only 0.06%; this is because not all the units, such as the algae production system, the ICE and the gas treatment plant, are selected for installation in this case. Similarly, it can be seen that carbon dioxide emissions are very close to their minimum value, with only a dissatisfaction of 0.52%. For the sustainability return of investment, the solution is very close to the worst scenario because the difference between the total annual cost for the installation and operation of the residential complex and buying of resources by itself is very large compared with the difference between the impact to the environment caused by the purchase of fresh resources and the damage caused by the processing units. The objectives of fresh water consumption and environmental impact have dissatisfactions of 21.25% and 17.56%, respectively. Likewise, the results show that the function of the damage to human health for this scenario is at its utopian point, this is because in this scenario only those units that are necessarily required to satisfy the treatment needs were previously established for the waste produced by the residential complex, such as solid waste and the treatment of grey and blackwater. For the scenario of the highest dissatisfaction (Figure 5), it can be seen that the only function that is at its utopia point is the reduction of CO2 emissions into the environment. On the other hand, we observe how the TAC has an 83.27% dissatisfaction, which is the largest percentage observed for this objective function in all the proposed scenarios. Similarly, it is observed that the consumption of fresh water, the impact on the environment and the sustainability return of investment have dissatisfactions of 14.48%, 19.05% and 98.97%, respectively. The value obtained for the damage to human health for this scenario



is very close to the utopia point since it presents only 0.67% of dissatisfaction, this due to the selection to install the algae production system, unlike the scenario with the lowest dissatisfaction, which causes a slight increase in the inlet flow to the greywater treatment unit. In the scenario of the intermediate dissatisfaction (Figure 6), the binary variable for the installation of the ICE is activated to satisfy the hot water and electricity demands in the residential complex. In this scenario, the consumption of fresh water is at its utopia point and two more of the functions are practically on it, having only 0.01% of dissatisfaction for the part of the environmental impact and 0.007% for the damage to human health. While the TAC has 55.35% of dissatisfaction and the sustainability return of investment has 99.56% of dissatisfaction, the objective function of the reduction of carbon dioxide emissions presents a dissatisfaction of 7.28%, which is the highest one obtained from all the proposed scenarios. A very important point to consider in this problem is the damage caused to human health through the noise, odor and emissions generated by the installed process units to satisfy the needs of the residential complex. However, the impact caused to human health is very similar in each of the studied scenarios, this is because the solid and liquid waste generated by the households are constant in the problem and the grey and black wastewater treatment plants as the gasification system are those that have a very large impact compared to the other units of the process. Therefore, to reduce this impact, it was considered to send the wastewater to be treated externally, however, the total annual cost presents an increase. As it was mentioned above, PRHI was evaluated for each process and the results obtained are shown in Table 7. Higher PRHI means higher hazardous for inhabitants’ health. Scaled PRHI is obtained by the ratio of PRHI from each process with the higher PRHI, in this case blackwater. This index does not have any physical meaning, this index only shows which process is the most hazardous for health according of assumptions mentioned above. It can be observed that the high index corresponds to the blackwater treatment, the main reason is because H2S is present in that process. On the other hand, boiler was the process with less PHRI, this can be attributed to that it contains fewer streams that can be harmful to health in case of leak than other process. Table 8 shows the penalties for activities or operations, it


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is important to evaluate process operating mode because it will contribute to workplace exposure and depending on the process operating mode this requires maintenance works than could expose chemical hazards in workplace. On the other hand, Table 9 shows the penalties for process conditions and material properties, for example, it is important to determine material phase because affects the way a chemical will be exposed as well as its operating pressure and temperature, because there is a possibility to cause major accidents like burn accidents and potential fugitive emissions. One of the contributions to this methodology was to evaluate the noise in each process, repeated exposure to noise hazards can lead to permanent tinnitus or hearing loss, and also noise hazards can create physical and psychological stress, reduce productivity, interfere with communication and concentration and contribute to workplace accidents and injuries by making it difficult to hear warning signals. There are different levels of noise hazard according by the decibels issued (Institutions of Occupational Safety and Health), based on this, penalties for noise hazard are expressed in Table 9. The Material Harm Index is based on the NFPA data, which are shown in Table 10. CONCLUSIONS This work has presented an optimization formulation for designing integrated residential complexes accounting for satisfying the water and energy needs as well as the proper disposal of wastewater, solid waste and emissions. The proposed approach accounts for economic and environmental objective functions as well the acceptability, which is considered through the minimization of the damage to the human health of the inhabitants of the housing complex. There is presented a multi-stakeholder approach to trade-off the different objectives and to quantify the dissatisfaction level for different compromised solutions obtained. A case study for a residential complex of Mexico was considered. The results show that it is possible to obtain trade-off solutions. Particularly, when the sustainability return of investment is incorporated through a multi-stakeholder approach, it is possible to obtained solutions with low dissatisfaction for all the involved parts. It should be noticed that in the solutions with low dissatisfaction usually the economic and human health objectives are near for its best solutions, this because not all the units such the algae production system,



the ICE and the gas treatment plant are selected to be included and this reduces the costs and the damage caused to the occupational health for the inhabitants in the residential complex. NOMENCLATURE Variables

EI DR

Environmental impact for damage to resources

EI EQ

Environmental impact for ecosystem quality

EI HH

Environmental impact for human health

EnvImp

Total environmental impact for damage by the process

FFwTot

Total fresh water used by the process in m3/year

GDischargeTotal

Total carbon dioxide emissions by the whole process in tonne/year

OH

Process contribution to damage to the human health

PRHI

Process route healthiness index

SWSROIM

Return of investment for process

TAC

Total annual cost in US$/year

TotCapCost

Total capital cost in US$/year

TotOpCost

Total operating cost in US$/year

TotSales

Total sales in US$/year

Parameters AP

Penalties for activities or operations

CP

Penalties associated to process conditions and material properties


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Eco-indicator ref

Eco-indicator for the unintegrated system

HHI

Health hazard index

ICPHI

Inherent chemical and process hazard index

MHI

Material harm index

OELmin

Occupational exposure limit in kg/m3

PR

Contributed parameters for OH

TAC ref

Total annual cost for unintegrated system in US$/year

wi

Weighting factor for the process in return of investment objective

wj

Weighting factor for the compromise solution

WECmax

Worker exposure concentration

SUPPORTING INFORMATION The Supporting Information is available free of charge on the ACS Publications website. Detailed information for the case study can be found in this section. Efficiency parameters used for the process units are shown in Table S1. The constraints for the proposed model as well as its nomenclature are presented in the supporting information section.

Author Information Corresponding Author *Ponce-Ortega José M. Tel. +52-443-3223500. Ext. 1277. Fax. +52-443-3273584. E-mail: [email protected]

Notes The authors declare no competing financial interest.

Acknowledgements



Page 20 of 39

The authors appreciate the financial support provided by the Mexican National Council for Science and Technology (CONACYT). REFERENCES [1] González-Bravo, R.; Nápoles-Rivera, F.; Ponce-Ortega, J. M.; El-Halwagi, M. M. Multi-objective optimization of dual purpose power plants and water distribution networks.

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[24] Hernández-Calderón, O. M.; Ponce-Ortega, J. M.; Ortiz-del-Castillo, J. R.; CervantesGaxiola, M. E.; Milán-Carrillo, J.; Serna-González, M.; Rubio-Castro, E. Optimal design of distributed algae-based biorefineries using CO2 emissions from multiple industrial

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CAPTION FOR FIGURES Figure 1. Problem statement representation Figure 2. Proposed superstructure Figure 3. Electricity demand profile for the considered residential complex Figure 4. Scenario for the lowest dissatisfaction Figure 5. Scenario for the highest dissatisfaction Figure 6. Scenario for intermediate dissatisfaction


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Residential Complex Implement processes considering

Occupational Health Generating Satisfy needs

Solid wastes

Water

Wastewater

Electricity

Greenhouse Gas Emmisions

Heating and cooling

Environmental Economic performance impact

Noise

Figure 1. Problem statement representation.


ACS Sustainable Chemistry & Engineering 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Figure 2. Proposed superstructure.


Page 26 of 39

Page 27 of 39

Electricidad (kWh) 2500

Electricity demand (kW/h)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


2000

1500

1000

500

0 0

2

4

6

8

10

12

14

16

18

20

22

Time (h) Spring

Summer

Autumn

Winter

Figure 3. Electricity demand profile for the considered residential complex.19


24


Figure 4. Scenario for the lowest dissatisfaction.


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Figure 5. Scenario for the highest dissatisfaction.



Figure 6. Scenario for intermediate dissatisfaction.


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TABLES Table 1. Eco-indicator points for energy and resources used in the problem. Points Energy and Resources

Ecosystem quality

Human health

Resources

Biodiesel (kWh)

0.000025

0.000360

0.000012

CO2 (ton)

0.000027

0.000337

0.001870

0.010885

0.001047

0.039438

0.003000

0.004500

0.002500

Hot water (m )

0.002927

0.001849

0.001212

Natural gas (kWh)

0.005384

0.000616

0.024764

Refrigeration (kWh)

0.001283

0.000808

0.004003

Rainwater (m )

0.000160

0.000001

0.000016

Solid waste (kg)

0.020200

0.008807

0.000756

Water (m )

0.013854

0.006497

0.011885

Wastewater (m3)

0.024580

0.010580

0.017050

Electricity (kWh) 3

Greywater (m ) 3

3

3

Table 2. Eco-indicator points for the material used in the production of the technologies. Points (pts/kg material) Technology

Ecosystem quality

Human health

Resources

Algae system

0.00030000

0.00045000

0.00025000

ARC

2.74E-10

2.70E-11

2.70E-11

Boiler

0.00128000

0.00080800

0.00400300

Blackwater treatment

0.00015000

0.00001000

0.00001000

Fresh water storage system

0.00300000

0.00450000

0.00250000

Gasification system

0.00000174

0.00000174

0.00000174

Greywater treatment

0.0001500

0.0000100

0.0000100

ICE

2.74E-10

1.40E-10

2.50E-11

Natural gas treatment

0.00003000

0.00004500

0.00002500

Rainwater collecting system

0.00016000

0.00000100

0.00000160



Table 3. Parameters used to calculate the damage to human health in each process unit. Parameters Boiler

PR

PR

GW

WW

PR

PR

PR PR PR

NGT ICE Algae Gasification

Value 0.0000 0.4293 1.0000 0.0157 0.0000 0.0289 0.0154


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Table 4. Multi-stakeholder priorities, stakeholder individual solutions and compromise solutions. Stakeholder Weights (wj) GHGE (ton CO2/year)

Objectives TAC ($US/year)

FFwTot (m3/year)

GHGE (ton CO2/year)

EnvImp

SWSROIM

OH

Utopia

16,728,760

523,971

974

58,252

0.000

191,205

Nadir

100,000,000

722,244

1,159

3,246,632

0.002

192,520

Case

TAC ($US/year)

FFwTot (m3/year)

EnvImp

SWSROIM

OH

fj

1

1

0

0

0

0

0

0.00000

16,728,860

665,906

980

74,377

0.002

191,205

2

0

1

0

0

0

0

0.00000

69,313,010

523,971

1,051

63,936

0.001

191,220

3

0

0

1

0

0

0

0.00035

62,856,050

685,455

974

76,408

0.001

192,505

4

0

0

0

1

0

0

0.00000

19,625,890

577,557

1,052

58,252

0.002

191,220

5

0

0

0

0

1

0

0.17246

100,000,000

583,670

1,040

61,541

0.000

192,518

6

0

0

0

0

0

1

0.00000

62,835,230

681,413

979

74,851

0.001

191,205

7

1

1

1

1

1

1

2.22654

31,896,860

612,692

974

71,960

0.001

192,505

8

0.5000

0.0000

0.0000

0.0000

0.0000

0.5000

0.00000

16,728,790

665,321

979

74,356

0.002

191,205

9

0.3330

0.0000

0.0000

0.3330

0.0000

0.3330

0.00133

16,738,400

665,321

979

70,658

0.002

191,205

10

0.3156

0.0693

0.1350

0.3087

0.1556

0.0157

0.19947

32,145,970

612,984

974

72,003

0.001

192,505

11

0.3128

0.1559

0.3602

0.0431

0.0335

0.0945

0.21646

23,112,830

612,692

974

75,769

0.002

192,505

12

0.2823

0.3428

0.1275

0.1875

0.0592

0.0007

0.22596

23,122,610

612,692

974

71,960

0.002

192,505

13

0.2500

0.2500

0.0000

0.0000

0.2500

0.2500

0.17699

37,462,410

523,971

1,051

58,256

0.001

191,220

14

0.2201

0.0770

0.3573

0.0217

0.1882

0.1356

0.32086

34,177,310

612,692

974

71,960

0.001

192,505

15

0.0000

0.3330

0.3330

0.0000

0.3330

0.0000

0.21280

100,000,000

612,692

974

71,960

3.86E-04

192,505

16

0.0000

0.2500

0.2500

0.2500

0.2500

0.0000

0.18216

69,377,500

612,692

974

71,960

5.56E-04

192,505

17

0.0000

0.5000

0.0000

0.0000

0.0000

0.5000

0.00553

69,307,620

523,971

1,051

63,853

5.14E+02

191,220



Page 34 of 39

Table 5. Dissatisfaction for individual solutions and total dissatisfaction for the scenarios. Case

Dissatisfaction (%) EnvImp SWSROIM

TAC

FFwTot

GHGE

OH

TOTAL

1

0.00

21.31

0.57

21.68

99.80

0.0000

23.89

2

75.86

0.00

7.28

8.89

99.23

0.0076

31.88

3

73.39

23.56

0.00

23.76

99.38

0.6749

36.79

4

14.76

9.28

7.41

0.00

99.80

0.0076

21.88

5

83.27

10.23

6.33

5.34

98.86

0.6819

34.12

6

73.38

23.11

0.52

22.18

99.37

0.0000

36.42

7

47.55

14.48

0.00

19.05

99.60

0.6749

30.23

8

0.00

21.25

0.52

21.66

99.80

0.0000

23.87

9

0.06

21.25

0.52

17.56

99.80

0.0000

23.20

10

47.96

14.52

0.00

19.10

99.60

0.6749

30.31

11

27.62

14.48

0.00

23.12

99.80

0.6749

27.62

12

27.65

14.48

0.00

19.05

99.80

0.6749

26.94

13

55.35

0.00

7.28

0.01

99.56

0.0076

27.03

14

51.05

14.48

0.00

19.05

99.60

0.6749

30.81

15

83.27

14.48

0.00

19.05

98.97

0.6749

36.07

16

75.89

14.48

0.00

19.05

99.28

0.6749

34.90

17

75.86

0.00

7.28

8.77

100.00

0.0076

31.99

Table 6. Individual solutions for objective functions for the selected scenarios. Lowest Dissatisfaction

Intermediate Dissatisfaction

Highest Dissatisfaction

16,738,400

37,462,410

100,000,000

FFwTotal (m /year)

665,321

523,971

612,692

Gdischarge (Ton/year)

979

1,051

974

EnvImp

70,658

58,256

71,960

SWSROIM

0.002000

0.001000

0.000386

OH

191,205

191,220

192,505

TAC ($US/year) 3


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Table 7. Summary of results for PRHI ICPHI= Process

AP

CP

OELmin HHI

MHI

WECmax

AP+CP

(kg/m3)

PRHI

PRHIscaled

Boiler

5

4

9

30.9

3

0.0842

0.00900

7,806

0.0000

Greywater treatment

8

5

13

47

7

3.2732

0.00001

1,249,968,196

0.4294

Blackwater treatment

8

5

13

100.8

20

2.5580

0.00002

2,911,224,133

1.0000

Gas treatment unit

7

2

9

55.8

7

0.1460

0.00001

45,824,701

0.0157

Gasification

10

4

14

114.4

18

3.0987

0.00198

45,028,534

0.0155

Algae system

7

3

10

39.5

3

0.0929

0.00000

84,401,040

0.0290

ICE

8

3

11

31.9

11

0.1898

0.00801

91,521

0.0000



Page 36 of 39

Table 8. Summary of penalties for activities or operations. Activity Transport

Mode of process

Venting or Flaring

Maintenance works

Others

Noise level (dB)

Operation

Penalty

Pipe

1

Bag

2

Drum

3

Vibration

4

Continuous

1

Semi-continuous

2

Batch

3

Scrub vent effluent

1

Above occupiable platform level

2

Occupiable platform level

3

No

0

Yes

1

Agitation

1

Others

1

Solid handling

2

Size reduction

2

Extrusion

3

Air open mixing

3

Typical noise (0-40 dB)

0

Annoying, irritating, speech masking (40-70 dB)

1

Hazardous (70-100 dB)

2

High hazardous (100-140 dB)

3


Page 37 of 39 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Table 9. Summary of penalties for process conditions and material properties Conditions

Range

Temperature(°C)

Pressure

Viscosity (cp)

Ability to precipitate

Density difference (sg)

Ability to cause corrosion

Volume changes (%)

Solubility

Material state

Penalty

Low

0

High (>92°C)

1

Low

0

High (>68 atm)

1

Low (0-1 cp)

1

Medium (0-10 cp)

2

High (10-100 cp)

3

No

0

Yes

1

Low (0-1 sg)

1

Medium (0-1.5 sg)

2

High (0-2.5 sg)

3

No

0

Yes

1

Low (>25%)

1

Medium (25-32%)

2

High (33-50%)

3

Yes (50%)

0

Gas

1

Gas

0

Liquid

1

Slurry

2

Granules

3

Power

4



Page 38 of 39

Table 10. NFPA health rating criteria. Criteria

Rating

Materials which upon very limited exposure could cause death or major residual injury even though prompt

4

medical treatment is given which are too dangerous to be approached without specialized protective equipment. This degree should include: Materials which can penetrate ordinary rubber protective clothing; Materials that under normal conditions or under fire conditions give off gases that are extremely hazardous (i. e., toxic or corrosive) through inhalation or through contact with or absorption through the skin. Materials which upon short-term exposure could cause serious temporary or residual injury even though

3

prompt medical treatment is given, including those requiring protection from all bodily contact. This degree should include: Material giving off highly toxic combustion products; Materials corrosive to living tissue or toxic by skin absorption. Materials which one intense or continued exposure could cause temporary incapacitation or possible residual

2

injury unless prompt medical treatment is given, including those requiring use of respiratory protective equipment with independent air supply. This degree should include: Materials giving off toxic combustion products; or materials giving off highly irritating combustion products; Materials, which either under normal conditions or under fire conditions, give off toxic vapors lacking warning properties. Materials which on exposure would cause irritation but only minor residual injury even if no treatment is

1

given, including those which require use of an approved type of gas mask. This degree should include: Materials, which under fire conditions would give off irritating combustion products; Materials, which on the skin could cause irritation without destruction of tissue Materials that on exposure under fire conditions would offer no hazard beyond that of ordinary combustible material


0

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Synopsis: Integration approach for the acceptability of a sustainable residential complex involving the Water-Energy-Waste Nexus.


Involving Acceptability in the Optimal Design of ... - ACS Publications

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