Optimization of low-grade coal and refuse-derived fuel blends for improved co-combustion behavior in coal-fired power plants.

This study is aimed at utilizing three waste materials, i.e., solid refuse fuel (SRF), tire derived fuel (TDF), and sludge derived fuel (SDF), as eco-friendly alternatives to coal-only combustion in co-firing power plants. The contribution of waste materials is limited to ≤5% in the composition of the mixed fuel (coal + waste materials). Statistical experimental design and response surface methodology are employed to investigate the effect of mixed fuel composition (SRF, TDF, and SDF) on gross calorific value (GCV) and ash fusion temperature (AFT). A quadratic model is developed and statistically verified to apprehend mixed fuel constituents' individual and combined effects on GCV and AFT. Constrained optimization of fuel blend, i.e., GCV >1,250 kcal/kg and AFT >1,200 °C, using the polynomial models projected the fuel-blend containing 95% coal with 3.84% SRF, 0.35% TDF, and 0.81% SDF. The observed GCV of 5,307 kcal/kg and AFT of 1225 °C for the optimized blend were within 1% of the model predicted values, thereby establishing the robustness of the models. The findings from this study can foster sustainable economic development and zero CO2 emission objectives by optimizing the utilization of waste materials without compromising the GCV and AFT of the mixed fuels in coal-fired power plants.

Identifying the socioeconomic determinants of industrial hazardous waste generation: South Korea as a case study.

The South Korean government has set an ambitious target to reduce industrial hazardous waste (IHW) as part of its transition towards a circular economy. Moreover, effective management of IHW within the country has become crucial, given that IHW trade is regulated by the Basel Convention. Despite the urgent need for well-founded environmental policies, there is a lack of essential information on the characteristics and determinants of IHW generation, which hinders the effectiveness of existing IHW policies. To address this information gap, this study developed a South Korean extended IHW input-output model for 2008 and 2018 to characterize IHW generation and applied structural decomposition analysis to identify the socioeconomic determinant of change of IHW generation. The results reveal that consumption, export, and direct IHW intensity change of 'Chemical', 'Electronic and electrical equipment', 'Basic metal', and 'Other service' emerge as dominant determinants for IHW growth. Conversely, technology change, including technological structure change and direct IHW intensity change, of 'Basic metal' and 'Other service' is the key driver for IHW reduction. In addition, an intriguing aspect of the study relates to the supply chain's influence on IHW generation. The indirect growth of IHW resulting from expanding exports and consumption contributes nearly twice as much to the overall increase in IHW as direct IHW growth. These valuable insights pave the way for the South Korean government to establish holistic and customized environmental policies regarding IHW. It emphasizes the importance of considering expanded global system boundaries, technological advancements, and purchasers' consumption patterns as dominant factors in formulating these policies. Furthermore, this study not only provides crucial guidance for the government's decision-making but also suggests strengthening environmental management and monitoring practices.

Optimization of tetracycline removal from water by iron-coated pine-bark biochar.

We synthesized iron-coated pine-bark biochar (Fe-PBB) and determined the optimal conditions for removing the antibiotic tetracycline from water. The Fe-PBB was synthesized by depositing iron oxide on pyrolyzed pine-bark waste via a facile co-precipitation method. Characterization (SEM, EDX, and TGA) showed successful deposition of a mass of approximately 27% (w/w) iron on the PBB to synthesize Fe-PBB. Fe-PBB exhibited five times higher adsorption capacity (~ 10 mg/g) for tetracycline compared with PBB. The effects of initial tetracycline concentration, pH, temperature, and Fe-PBB dose on the adsorption removal of tetracycline from water were systematically investigated and optimized using a statistical experimental design and response surface methodology. The empirical relationship between the experimental factors and tetracycline removal was modeled, statistically validated through the analysis of variance, and used to predict the optimal conditions for adsorption removal of tetracycline. We found that ≥ 95% of the tetracycline can be removed at a tetracycline concentration of 1 mg/L, pH of 7, temperature of 50 °C, and a Fe-PBB dose of 2 g/L. The adsorption isotherm modeling study suggests that the adsorption of tetracycline can be attributed to the pore filling phenomenon and multilayer adsorption on the Fe-PBB. A thermodynamics study showed that the adsorption occurs spontaneously with an endothermic reaction.

Production and characterization of cost-effective magnetic pine bark biochar and its application to remove tetracycline from water.

Low-cost adsorbent, pine bark biochar (PBB) from the forest residue, was produced and applied to remove tetracycline (TC) from aqueous solution via adsorption pathway. The PBB, hence obtained, was modified using aqueous ferric and ferrous ion solutions to obtain magnetic pine bark biochar (M-PBB). Batch adsorption experiments were conducted to examine the adsorption of TC by PBB and M-PBB in the variation of pH, contact time, dosage, and temperature. The adsorbents were characterized by SEM/EDX, TGA, and pHpzc. The adsorption mechanism was evaluated by fitting Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich (D-R) isotherms model. Also, the experimental data were analyzed by kinetics models (pseudo-first-order, pseudo-second-order, intra-particle diffusion, and Elovich) and thermodynamics. The maximum adsorption capacity (qm) of M-PBB was 15.3 mg/g from the experiment at pH 6. A high correlation coefficient (R2 ≈ 0.9) of Freundlich isotherm postulated multi-layer adsorption of TC on M-PBB at pH 6. The kinetic studies showed that the pseudo-first-order was more suitable for representing the adsorption of TC molecules on the surface. The thermodynamic analysis was showed that the adsorption process is favorable, spontaneous, and endothermic at studied temperatures. M-PBB demonstrated a potential for removal of TC from water as a low-cost and convenient adsorbent.

High-Resolution Environmentally Extended Input-Output Model to Assess the Greenhouse Gas Impact of Electronics in South Korea.

South Korea is a global leader in electronics, but little is known about their climate change impact. Here, we estimate the direct and indirect greenhouse gas (GHG) emissions of Korean electronics by developing a new and high-resolution (∼380 sectors) environmentally extended input-output model, named KREEIO. We find that final demand for Korean electronics led to nearly 8% of national GHG emissions in 2017, mostly because of indirect emissions embodied in the electronics supply chain. Notably, the semiconductor and display sectors contributed 3.2% and 2.4% to national emissions, with capital investment accounting for 17% of the two sectors' total emissions or nearly 1% of national emissions. For other electronic products, scope 1, scope 2, and upstream scope 3 emissions on average accounted for 3%, 10%, and 87% of a sector's GHG intensity, respectively. Detailed contribution analysis suggests that reducing Korean electronics GHG emissions would benefit most from the transition to a low-carbon electricity grid, but mitigation efforts in many other sectors such as metals and chemicals are also important. Overall, our study underscores the significance of electronics GHG emissions in South Korea, especially those from semiconductors and displays, and the mitigation challenges these sectors face as demand continues to grow globally.

Characteristics of industrial hazardous waste generation in South Korea from 2008 to 2018 based on decoupling and decomposition analysis.

The industrial hazardous waste (IHW) generation to meet consumption is steadily increasing, resulting in environmental, health, and social problems around the world. To address IHW at the source, it is critical to understand the generation characteristics and key drivers on industrial hazardous waste generation (IHWG). This study analysed the generation characteristics of IHW of South Korea from 2008 to 2018 by decoupling and index decomposition analysis using Log Mean Divisia Index (LMDI) model. South Korea presented unstable decoupling of IHWG from economic growth, so more effective waste management regulations are needed to support a stable decoupling. One most critical finding was that the factors of industrial output and industrial characteristic of IHWG-to-energy were major driving factors influencing the increase of IHWG, whereas those of industrial structure and energy efficiency affect to the decrease of IHWG in most industries. In addition, the result clearly confirmed that the contribution of driving factors affecting the IHWG differs by industry. These results provide significant policy insights that the South Korean government needs institutional improvement and refinement of customised IHW management according to the characteristics of IHWG.

Experimental modeling and optimization for the reduction of hexavalent chromium in aqueous solutions using ascorbic acid.

In this study, we investigated the reduction of toxic Cr(VI) to less toxic Cr(III) using ascorbic acid in various aqueous solutions: deionized water, synthetic soft water, synthetic hard water, and real tap water. The experiments were performed using a statistical experimental design. Response surface methodology (RSM) was used to correlate Cr(VI) reduction (response variable) with experimental parameters such as initial Cr(VI) concentration, humic acid concentration, and ascorbic acid dosage. The empirical model obtained from the experiments was used to estimate and optimize the quantity of ascorbic acid required for the reduction of ≥ 99% Cr(VI) in water. The optimized dosages of ascorbic acid were predicted and experimentally validated for > 99.5% reduction of Cr(VI) (1, 10, 20, and 100 mg/L) in the solutions. Even a solution containing an initial Cr(VI) concentration of 100 mg/L was reduced in concentration ≥ 99.9% with optimal dosage of ascorbic acid (500 mg/L) in the presence of 20 mg/L humic acid. Moreover, the reaction kinetics (kobs-Cr(VI) = 0.71 mM-1 s-1) were sufficient to reduce the ≥ 99.9% Cr(VI) in 20 min. This study sheds new light on the effect of ascorbic acid on Cr(VI) reduction, and provides knowledge fundamental to optimize treatment of Cr(VI) contaminated water to environmentally acceptable endpoints.

Decarbonization of Vietnam's economy: decomposing the drivers for a low-carbon growth.

Vietnam has witnessed a rapid increase in national-level CO2 emissions due to rising urbanization, economic expansion, export growth, and industrial development. Moreover, to support the ambitious economic growth targets, reliance on and consumption of fossil fuels are increasing by each passing year. With this circumstance, this study aims to analyze the key drivers of CO2 emissions in Vietnam from 1990 to 2016 using the Kaya identity and decomposition method. Following this approach, CO2 emissions have been decomposed into five effect categories comprising population, affluence, energy intensity, fuel mix, and emission intensity. As per the results, CO2 emissions in Vietnam were mainly driven by rising affluence (58.5%) and changing fuel mix (33.2%) which have resulted from improved living standards, rapid industrial development, and higher fossil fuel consumption. Moreover, population (13.8%) and emission intensity (3.1%) exhibited a relatively lower impact on CO2 emissions during 1990-2016. However, energy intensity (- 8.7%) was the only negative driver which has resulted in the slowdown of carbon emissions in Vietnam. Based on the analysis of energy policy development, the share of renewable energy resources was still quite low in the national energy mix with higher reliance on traditional fossil fuels (mainly coal and petroleum). Therefore, to make a transition towards low-carbon economic growth, significant improvements in energy efficiency and emission intensity are necessary together with national energy mix restructuring for low-carbon economic growth.

Fuzzy multi-objective optimization case study based on an anaerobic co-digestion process of food waste leachate and piggery wastewater.

This paper presents the development and evaluation of fuzzy multi-objective optimization for decision-making that includes the process optimization of anaerobic digestion (AD) process. The operating cost criteria which is a fundamental research gap in previous AD analysis was integrated for the case study in this research. In this study, the mixing ratio of food waste leachate (FWL) and piggery wastewater (PWW), calcium carbonate (CaCO3) and sodium chloride (NaCl) concentrations were optimized to enhance methane production while minimizing operating cost. The results indicated a maximum of 63.3% satisfaction for both methane production and operating cost under the following optimal conditions: mixing ratio (FWL: PWW) - 1.4, CaCO3 - 2970.5 mg/L and NaCl - 2.7 g/L. In multi-objective optimization, the specific methane yield (SMY) was 239.0 mL CH4/g VSadded, while 41.2% volatile solids reduction (VSR) was obtained at an operating cost of 56.9 US$/ton. In comparison with the previous optimization study that utilized the response surface methodology, the SMY, VSR and operating cost of the AD process were 310 mL/g, 54% and 83.2 US$/ton, respectively. The results from multi-objective fuzzy optimization proves to show the potential application of this technique for practical decision-making in the process optimization of AD process.

Solidification/stabilization of ASR fly ash using Thiomer material: Optimization of compressive strength and heavy metals leaching.

Optimization studies of a novel and eco-friendly construction material, Thiomer, was investigated in the solidification/stabilization of automobile shredded residue (ASR) fly ash. A D-optimal mixture design was used to evaluate and optimize maximum compressive strength and heavy metals leaching by varying Thiomer (20-40wt%), ASR fly ash (30-50wt%) and sand (20-40wt%). The analysis of variance was utilized to determine the level of significance of each process parameters and interactions. The microstructure of the solidified materials was taken from a field emission-scanning electron microscopy and energy dispersive X-ray spectroscopy that confirmed successful Thiomer solidified ASR fly ash due to reduced pores and gaps in comparison with an untreated ASR fly ash. The X-ray diffraction detected the enclosed materials on the ASR fly ash primarily contained sulfur associated crystalline complexes. Results indicated the optimal conditions of 30wt% Thiomer, 30wt% ASR fly ash and 40wt% sand reached a compressive strength of 54.9MPa. For the optimum results in heavy metals leaching, 0.0078mg/LPb, 0.0260mg/L Cr, 0.0007mg/LCd, 0.0020mg/L Cu, 0.1027mg/L Fe, 0.0046mg/L Ni and 0.0920mg/L Zn were leached out, being environmentally safe due to being substantially lower than the Korean standard leaching requirements. The results also showed that Thiomer has superiority over the commonly used Portland cement asa binding material which confirmed its potential usage as an innovative approach to simultaneously synthesize durable concrete and satisfactorily pass strict environmental regulations by heavy metals leaching.

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach.

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box-Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand-metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model-genetic algorithm (RSM-GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47µg/g) is facilitated at 30.22mg C/L of EtOH with initial As(III) concentration of 196.77µg/L at pH5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.

Novel synthesis and applications of Thiomer solidification for heavy metals immobilization in hazardous ASR/ISW thermal residue.

The present paper reports the novel synthesis and application of Thiomer solidification for heavy metal immobilization in hazardous automobile shredder residues and industrial solid waste (ASR/ISW) thermal residues. The word Thiomer is a combination of the prefix of a sulfur-containing compound "Thio" and the suffix of "Polymer" meaning a large molecule compound of many repeated subunits. To immobilize heavy metals, either ASR/ISW thermal residues (including bottom and fly ash) was mixed well with Thiomer and heated at 140°C. After Thiomer solidification, approximately 91-100% heavy metal immobilization was achieved. The morphology and mineral phases of the Thiomer-solidified ASR/ISW thermal residue were characterized by field emission-scanning electron microscopy, energy dispersive X-ray spectroscopy and X-ray diffraction (XRD), which indicated that the amounts of heavy metals detectable on the ASR/ISW thermal residue surface decreased and the sulfur mass percent increased. XRD indicated that the main fraction of the enclosed/bound materials on the ASR/ISW residue contained sulfur associated crystalline complexes. The Thiomer solidified process could convert the heavy metal compounds into highly insoluble metal sulfides and simultaneously encapsulate the ASR/ISW thermal residue. These results show that the proposed method can be applied to the immobilization of ASR/ISW hazardous ash involving heavy metals.

Optimization of co-digestion of various industrial sludges for biogas production and sludge treatment: methane production potential experiments and modeling.

Optimal biogas production and sludge treatment were studied by co-digestion experiments and modeling using five different wastewater sludges generated from paper, chemical, petrochemical, automobile, and food processing industries situated in Ulsan Industrial Complex, Ulsan, South Korea. The biomethane production potential test was conducted in simplex-centroid mixture design, fitted to regression equation, and some optimal co-digestion scenarios were given by combined desirability function based multi-objective optimization technique for both methane yield and the quantity of sludge digested. The co-digestion model incorporating main and interaction effects among sludges were utilized to predict the maximum possible methane yield. The optimization routine for methane production with different industrial sludges in batches were repeated with the left-over sludge of earlier cycle, till all sludges have been completely treated. Among the possible scenarios, a maximum methane yield of 1161.53 m(3) is anticipated in three batches followed by 1130.33 m(3) and 1045.65 m(3) in five and two batches, respectively. This study shows a scientific approach to find a practical solution to utilize diverse industrial sludges in both treatment and biogas production perspectives.

Characterization of co-digestion of industrial sludges for biogas production by artificial neural network and statistical regression models.

The characteristics and impact of industrial sludges of paper, chemical, petrochemical, automobile, and food industries situated in the Ulsan Industrial Complex, Ulsan, Republic of Korea in co-digestion for biogas production were assessed by artificial neural network (ANN) and statistical regression models. The regression model was based on a simplex-centroid mixture design and the ANN was based on a resilient back-propagation algorithm (topology 5-7-1). Using connection weights and bias of the trained ANN model, the impact of each sludge of co-digestion was assessed using Garsons' algorithm. Results suggested that the modelling and predictability of ANN were superior to the regression model with accuracy (A(f)) 1.01, bias (B(f)) 1.00, root mean square error 3.56, and standard error of prediction 2.51%. Sludge from the chemical industry showed the highest impact on specific methane yield (SMY(VS)) with a relative importance of 28.59% followed by sludges from paper (20.07%), food (19.59%), petrochemical (15.92%), and automobile (15.82%) industries. The interactions between diverse industrial sludges were successfully modelled and partitioned into various synergistic and antagonistic effects on SMY(VS). Synergistic interactions between the chemical industry sludge and either petrochemical or food industry sludges on SMY(VS) were detected. However, strong negative interaction between automobile sludge and other sludges was observed. This study indicates that though the ANN model performed better in prediction and impact assessments, the regression model reveals the synergistic and antagonistic interactions among sludges.

Back propagation neural network model for predicting the performance of immobilized cell biofilters handling gas-phase hydrogen sulphide and ammonia.

Lab scale studies were conducted to evaluate the performance of two simultaneously operated immobilized cell biofilters (ICBs) for removing hydrogen sulphide (H2S) and ammonia (NH3) from gas phase. The removal efficiencies (REs) of the biofilter treating H2S varied from 50 to 100% at inlet loading rates (ILRs) varying up to 13 g H2S/m(3) ·h, while the NH3 biofilter showed REs ranging from 60 to 100% at ILRs varying between 0.5 and 5.5 g NH3/m(3) ·h. An application of the back propagation neural network (BPNN) to predict the performance parameter, namely, RE (%) using this experimental data is presented in this paper. The input parameters to the network were unit flow (per min) and inlet concentrations (ppmv), respectively. The accuracy of BPNN-based model predictions were evaluated by providing the trained network topology with a test dataset and also by calculating the regression coefficient (R (2)) values. The results from this predictive modeling work showed that BPNNs were able to predict the RE of both the ICBs efficiently.

Occurrence and removal of antibiotics, hormones and several other pharmaceuticals in wastewater treatment plants of the largest industrial city of Korea.

Occurrence and removal efficiencies of 20 pharmaceuticals and personal care products (PPCPs) including antibiotics, hormones, and several other miscellaneous pharmaceuticals (analgesics, antiepileptics, antilipidemics, antihypertensives, antiseptics, and stimulants) were investigated in five wastewater treatment plants (WWTPs) of Ulsan, the largest industrial city of Korea. The compounds were extracted from wastewater samples by solid-phase extraction (SPE) and analyzed by High-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). The results showed that acetaminophen, atenolol and lincomycin were the main individual pollutants usually found in concentrations over 10 µg/L in the sewage influent. In the WWTPs, the concentrations of analgesic acetaminophen, stimulant caffeine, hormones estriol and estradiol decreased by over 99%. On the contrary, the antibiotic sulfamethazine, the antihypertensive metoprolol, and the antiepileptic carbamazepine exhibited removal efficiencies below 30%. Particularly, removal of antibiotics was observed to vary between -11.2 and 69%. In the primary treatment (physico-chemical processes), the removal of pharmaceuticals was insignificant (up to 28%) and removal of majority of the pharmaceuticals occurred during the secondary treatment (biological processes). The compounds lincomycin, carbamazepine, atenolol, metoprolol, and triclosan showed better removal in WWTPs employing modified activated sludge process with co-existence of anoxic-oxic condition. Further investigation into the design and operational aspects of the biological processes is warranted for the efficient removal of PPCPs, particularly antibiotics, to secure healthy water resource in the receiving downstream, thereby ensuring a sustainable water cycle management.

Enhanced methane recovery by food waste leachate injection into a landfill in Korea.

The current food waste leachate (FWL) disposal practice in Korea warrants urgent attention and necessary action to develop an innovative and sustainable disposal strategy, which is both environmentally friendly and economically beneficial. In this study, methane production by FWL injection into a municipal solid waste landfill with landfill gas (LFG) recovery facility was evaluated for a period of more than 4 months. With the target of recovering LFG with methane content ~50%, optimum LFG extraction rate was decided by a trial and error approach during the field investigation in five different phases. The results showed that, upon FWL injection, LFG extraction rate of ~20 m(3)/h was reasonable to recover LFG with methane content ~58%. Considering the estimated methane production potential of 31.7 m(3) CH(4) per ton of FWL, methane recovery from the landfill was enhanced by 14%. The scientific findings of this short-term investigation indicates that FWL can be injected into the existing sanitary landfills to tackle the present issue and such landfills with efficient liner and gas collection facility can be utilized as absolute and sustainable environmental infrastructures.

Sorption of triclosan onto activated carbon, kaolinite and montmorillonite: effects of pH, ionic strength, and humic acid.

Sorption of triclosan on three sorbents, viz., activated carbon, kaolinite and montmorillonite was studied as a function of pH, ionic strength and humic acid (HA) concentration through controlled batch experiments. Triclosan sorption was found to be higher in the acidic pH range, as varying pH showed significant influence on the surface charge of the sorbents and degree of ionization of the sorbate. Sorption capacity of the sorbents increased with an increase in the ionic strength of solution. At low pH (pH 3), the overall increase in triclosan sorption was 1.2, approximately 4 and 3.5 times, respectively for activated carbon, kaolinite and montmorillonite when ionic strength was increased from 1x10(-3) to 5x10(-1) M. Triclosan sorption onto activated carbon decreased from 31.4 to 10.6 mg g(-1) by increasing the HA concentration to 200 mg C L(-1). However, during sorption onto kaolinite and montmorillonite, the effect of HA was very complex probably due to (i) hydrophobicity (log K(ow)=4.76) of triclosan; and (ii) complexation of HA with triclosan. Though triclosan sorption onto activated carbon is higher, the potential of kaolinite and montmorillonite in controlling the transport of triclosan in subsurface environment can still be appreciable.

Methane production from food waste leachate in laboratory-scale simulated landfill.

Due to the prohibition of food waste landfilling in Korea from 2005 and the subsequent ban on the marine disposal of organic sludge, including leachate generated from food waste recycling facilities from 2012, it is urgent to develop an innovative and sustainable disposal strategy that is eco-friendly, yet economically beneficial. In this study, methane production from food waste leachate (FWL) in landfill sites with landfill gas recovery facilities was evaluated in simulated landfill reactors (lysimeters) for a period of 90 d with four different inoculum-substrate ratios (ISRs) on volatile solid (VS) basis. Simultaneous biochemical methane potential batch experiments were also conducted at the same ISRs for 30 d to compare CH(4) yield obtained from lysimeter studies. Under the experimental conditions, a maximum CH(4) yield of 0.272 and 0.294 L/g VS was obtained in the batch and lysimeter studies, respectively, at ISR of 1:1. The biodegradability of FWL in batch and lysimeter experiments at ISR of 1:1 was 64% and 69%, respectively. The calculated data using the modified Gompertz equation for the cumulative CH(4) production showed good agreement with the experimental result obtained from lysimeter study. Based on the results obtained from this study, field-scale pilot test is required to re-evaluate the existing sanitary landfills with efficient leachate collection and gas recovery facilities as engineered bioreactors to treat non-hazardous liquid organic wastes for energy recovery with optimum utilization of facilities.

Urban water infrastructure optimization to reduce environmental impacts and costs.

Urban water planning and policy have been focusing on environmentally benign and economically viable water management. The objective of this study is to develop a mathematical model to integrate and optimize urban water infrastructures for supply-side planning and policy: freshwater resources and treated wastewater are allocated to various water demand categories in order to reduce contaminants in the influents supplied for drinking water, and to reduce consumption of the water resources imported from the regions beyond a city boundary. A case study is performed to validate the proposed model. An optimal urban water system of a metropolitan city is calculated on the basis of the model and compared to the existing water system. The integration and optimization decrease (i) average concentrations of the influents supplied for drinking water, which can improve human health and hygiene; (ii) total consumption of water resources, as well as electricity, reducing overall environmental impacts; (iii) life cycle cost; and (iv) water resource dependency on other regions, improving regional water security. This model contributes to sustainable urban water planning and policy.