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Minimizing Carbon Dioxide (CO2) Emissions of POME Treatment System Using MILP Model

PROCESSES 2025年第2期13卷 583-583页

作者： Pallikodathan, Sivakumar Man, Hasfalina Che Ghazi, Tinia Idaty Mohd Sulaiman, Alawi Nagarajoo, Gunasilan Shukery, Mohamad Firdza Univ Putra Malaysia Fac Engn Dept Biol & Agr Engn Serdang 43300 Selangor Malaysia Engn Dept Hargy Oil Palms Ltd POB 21 Bialla Papua N Guinea Univ Putra Malaysia Fac Engn Smart Farming Technol Res Ctr Serdang 43300 Selangor Malaysia Univ Putra Malaysia Fac Engn Dept Chem & Environm Engn Serdang 43300 Selangor Malaysia Univ Teknol MARA Fac Plantat & Agrotechnol Melaka 77300 Malaysia

This paper presents a strategic planning model aimed at optimizing the economic and environmental impacts of palm oil mill effluent (POME) treatment systems. The model determines the optimal selection of POME treatment systems to minimize the environmental impact, specifically focusing on three systems: an anaerobic digester tank system (ADT), a covered lagoon system (CL) with biogas capture, and an open pond system (OP). The model incorporates constraints related to fresh fruit bunch (FFB) production, POME generation, the biological oxygen demand (BOD), the chemical oxygen demand (COD), and carbon dioxide (CO2) emissions. The optimization framework, formulated as a mixed-integer linear programming (MILP) model, is solved using the GAMS 40.1.0 software. Integer decision variables are used to represent the choice of POME treatment system that minimizes the environmental impact. The study specifically considers the ADT, CL, and OP systems, with the results indicating that the ADT system is the most effective in reducing the BOD, COD, and CO2-equivalent emissions, thereby highlighting its environmental benefits. The model selects the ADT treatment system, which exhibits the lowest COD, BOD, and CO2e emissions. Specifically, the COD registered an 85% reduction, from 84,830 mg/L to 12,725 mg/L. The BOD level was reduced by 88%, resulting in a BOD level of 41,208 mg/L to 4945 mg/L. The minimum CO2e emissions that could be achieved was about 3173 t CO2e per annum. This model provides a valuable tool for governmental agencies and policymakers to guide the private sector in developing environmentally sustainable POME treatment strategies.

关键词： palm oil mill effluent optimization modeling mixed-integer linear programming carbon dioxide emission

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An optimization-based approach to fleet reliability and allocation in open-pit mining

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Decision Analytics Journal 2025年 15卷

作者： Senses, Sena Kumral, Mustafa Department of Mining and Materials Engineering McGill University 3450 University Street Montreal H3A 0E8 QC Canada

Open-pit mining operations depend heavily on the availability and reliability of complex equipment fleets, where the failure of one component can disrupt overall productivity. This study proposes two complementary optimization models to enhance fleet allocation and reliability in the mining industry. The first model — a Mixed-Integer Nonlinear Programming (MINLP) formulation — supports short-term planning by maximizing the minimum reliability of heterogeneous truck–shovel sub-systems under production and utilization constraints. The second model focuses on medium-term reliability enhancement, allocating targeted reliability improvements to critical components based on equipment degradation and operational history. Both models are validated using real operational data from an open pit mine, which includes failure and repair time datasets from 17 trucks and 2 hydraulic shovels. Reliability curves are estimated using the power law model under a Non-Homogeneous Poisson Process (NHPP) assumption. Results show that optimal allocation can achieve production targets of 4,489 tons per hour with a minimum sub-system reliability of 0.7. Furthermore, reliability improvements tailored to engine-hour-based cost functions can effectively restore operational performance over a one-week horizon. This research bridges the gap between fleet allocation and reliability allocation and introduces a novel framework for integrating reliability into equipment planning. The models provide actionable insights for mining operations to optimize equipment deployment, reduce failure risk, and support more resilient and cost-effective planning. © 2025 The Author(s)

关键词： Fleet management Mining operations Operational efficiency optimization modeling Performance enhancement Reliability allocation

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A Dynamic Risk-Based Framework for BTEX Bioremediation: Integrating Micro-Exposure Events and optimization Strategies

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Environmental Pollution 2025年 126452页

作者： Hadi Mouraki Aliabad Saeed Alimohammadi Dept. of Civil Water and Environmental Engineering Faculty Shahid Beheshti Univ. P.O. Box 16765-1719 Bahar Blvd. Hakimieh Tehran *** Iran Dept. of Civil Engineering Civil Water and Environmental Engineering Faculty Shahid Beheshti Univ. P.O. Box 16765-1719 Bahar Blvd. Hakimieh Tehran *** Iran

Groundwater contamination by BTEX compounds—benzene, toluene, ethylbenzene, and xylene—poses serious environmental and public health risks, particularly in hydrogeologically complex industrial areas. This study proposes a novel, dynamic framework for in situ bioremediation of BTEX-contaminated groundwater at the Shiraz oil refinery site, integrating the Micro-Exposure Event (MEE) method as a central component for high-resolution, time-sensitive health risk assessment. Unlike conventional risk models that rely on long-term average concentrations, the MEE approach evaluates individual exposure events across temporal intervals, enabling the identification of short-term contaminant spikes that may otherwise go undetected. This enhances the accuracy and responsiveness of risk estimations, particularly in heterogeneous aquifer settings. To address the site's geological complexity—characterized by variable stratigraphy, non-uniform flow directions, and multiple pollution sources—the framework couples advanced simulation tools (MODFLOW 6 and MT3D-USGS) with adaptive optimization algorithms. A Genetic Algorithm (GA) is employed for spatial optimization of well placement, while Differential Evolution (DE) is used for temporal adjustment of injection and extraction rates. Simulation results over a ten-year period demonstrate a 92% reduction in benzene concentrations and sustained health risk levels below the U.S. EPA threshold of 1×10 -6 . Additionally, the optimized strategy achieves an 18% reduction in total operational costs compared to baseline scenarios. By linking MEE-based risk evaluation with simulation-optimization techniques, the proposed framework offers a replicable and scalable approach for managing BTEX pollution in complex subsurface environments. It advances the state of practice by balancing environmental performance, cost-efficiency, and health protection in groundwater remediation.

关键词： BTEX In Situ Bioremediation Micro-Exposure Event optimization modeling

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optimization of lignocellulosic biomass-to-biofuel supply chains with mobile pelleting

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2019年 122卷 545-562页

作者： Albashabsheh, Nibal T. Stamm, Jessica L. Heier Kansas State Univ Dept Ind & Mfg Syst Engn 2061 Rathbone Hall1701B Platt St Manhattan KS 66506 USA

Mobile pelleting machines (MPMs) provide an as-yet-unexplored opportunity to reduce logistic costs associated with biomass-to-biofuel supply chains We develop an optimization model to minimize the overall cost of producing ethanol from lignocellulosic biomass. We present results from a case study that considers multiple biomass types (switchgrass and corn stover) and forms (round and rectangular bales) and the potential for mobile pelleting. Our analyses offer insight into conditions under which mobile densification is economically viable. Results indicate that MPM utilization is sensitive to changes in biomass densification costs, transportation distances, satellite storage location fixed cost, and the number of MPMs.

关键词： Biomass-to-biofuel supply chain Densification Logistics optimization modeling Mobile densification units Lignocellulosic biomass

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Recreational System optimization to Reduce Conflict on Public Lands

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ENVIRONMENTAL MANAGEMENT 2012年第3期50卷 381-395页

作者： Shilling, Fraser Boggs, Jennifer Reed, Sarah Univ Calif Davis Dept Evironmental Sci & Policy Davis CA 95616 USA Wilderness Soc Ctr Landscape Anal San Francisco CA USA Colorado State Univ Ft Collins CO 80523 USA

In response to federal administrative rule, the Tahoe National Forest (TNF), California, USA engaged in trail-route prioritization for motorized recreation (e.g., off-highway-vehicles) and other recreation types. The prioritization was intended to identify routes that were suitable and ill-suited for maintenance in a transportation system. A recreational user survey was conducted online (n = 813) for user preferences for trail system characteristics, recreational use patterns, and demographics. Motorized trail users and non-motorized users displayed very clear and contrasting preferences for the same system. As has been found by previous investigators, non-motorized users expressed antagonism to motorized use on the same recreational travel system, whereas motorized users either supported multiple-use routes or dismissed non-motorized recreationists' concerns. To help the TNF plan for reduced conflict, a geographic information system (GIS) based modeling approach was used to identify recreational opportunities and potential environmental impacts of all travel routes. This GIS-based approach was based on an expert-derived rule set. The rules addressed particular environmental and recreation concerns in the TNF. Route segments were identified that could be incorporated into minimal-impact networks to support various types of recreation. The combination of potential impacts and user-benefits supported an optimization approach for an appropriate recreational travel network to minimize environmental impacts and user-conflicts in a multi-purpose system.

关键词： Off-highway vehicles Recreation Multiple-use optimization modeling Conflict Public lands

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optimization of nitrate reduction by EDTA catalyzed zero-valent bimetallic nanoparticles in aqueous medium

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2012年第9期19卷 3914-3924页

作者： Singh, Kunwar P. Singh, Arun K. Gupta, Shikha Indian Inst Toxicol Res CSIR Div Environm Chem Lucknow 226001 Uttar Pradesh India

The present study aims to investigate the EDTA catalyzed reduction of nitrate (NO (3) (-) ) by zero-valent bimetallic (Fe-Ag) nanoparticles (ZVBMNPs) in aqueous medium and to enumerate the effect of temperature, solution pH, ZVBMNPs dose and EDTA concentration on NO (3) (-) reduction. Batch experimental data were generated using a four-factor Box-Behnken design. optimization modeling was performed using the response surface method for maximizing the reduction of NO (3) (-) by ZVBMNPs. Significance of the independent variables and their interactions were tested by the analysis of variance and t test statistics. The model predicted maximum reduction capacity (340.15 mg g(-1) NO (3) (-) ) under the optimum conditions of temperature, 60 A degrees C;pH 4;dose, 1.0 g l(-1);and EDTA concentration, 2.0 mmol l(-1) was very close to the experimental value (338.62 mg g(-1)) and about 16 % higher than the experimentally determined capacity (291.32 mg g(-1)). Study demonstrated that ZVBMNPs had higher reduction efficiency than Fe-0 nanoparticles for NO (3) (-) . EDTA significantly enhanced the NO (3) (-) reduction by ZVBMNPs. The EDTA catalyzed reduction of NO (3) (-) by ZVBMNPs can be employed for the effective decontamination of water.

关键词： Zero-valent bimetallic nanoparticles Nitrate reduction Box-Behnken design optimization modeling Response surface method EDTA catalysis

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Spatial and temporal synchronization of water and energy systems: Towards a single integrated optimization model for long-term resource planning

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APPLIED ENERGY 2018年 210卷 499-517页

作者： Khan, Zarrar Linares, Pedro Rutten, Martine Parkinson, Simon Johnson, Nils Garcia-Gonzalez, Javier Univ Pontificia Comillas Inst Invest Tecnol Alberto Aguilera 23 Madrid 28015 Spain Delft Univ Technol Water Management Civil Engn & Geosci POB 5048 NL-2600 GA Delft Netherlands Univ Victoria Inst Integrated Energy Syst Victoria BC Canada Int Inst Appl Syst Anal Schlosspl 1 A-2361 Laxenburg Austria

Predictions show that pressure on already limited water and energy resources is expected to increase in many parts of the world as a result of growing populations, rapid urbanization, increasing pollution and climate change impacts. With water and energy playing a critical role in socio-economic development, ensuring resource security is a top policy concern. However, achieving this efficiently requires taking into account the various links between the two sectors through their joint management. Feedback between the water and energy sectors exists across system life-cycles and links the resources both spatially and temporally. Tracking the impacts of policies made in one sector on the other can thus be complicated and several 'nexus' methodologies have beep developed to try and address these issues. However, the different physical, temporal and spatial characteristics of the water and energy systems present several hurdles in analyzing the two resources simultaneously. This paper overcomes many of these problems with a new, fully coupled water-energy optimization model. Based on a review of contemporary literature, the model develops an original methodology to hard-link the two systems in detail across spatial and temporal scales, as well as between individual system processes throughout the life-cycle of each resource. In addition, the model also tracks changes in water quality through each process, allowing for detailed accounting of the energy needs for water treatment. The methodology proposed in this paper can be used to investigate various cross-sectoral issues and policies such as: water availability and temperature impacts on power plant cooling;emission constraint and biofuel expansion planning impacts on water resources;and the implications of water infrastructure expansion on the energy system. The capabilities of the coupled model are investigated in an example case study for Spain. An integrated approach is shown to have several benefits including lower

关键词： Water-energy nexus Integrated planning optimization modeling

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Managing for ecosystem services in northern Arizona ponderosa pine forests using a novel simulation-to-optimization methodology

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ECOLOGICAL MODELLING 2016年 324卷 11-27页

作者： Bagdon, Benjamin A. Huang, Ching-Hsun Dewhurst, Stephen No Arizona Univ Sch Forestry 200 East Pine Knoll DrPOB 15018 Flagstaff AZ 86011 USA

Forest managers are faced with the difficulty of promoting multiple ecosystem services (ES) with an incomplete understanding of the complex ways these ES interact. We developed a quantitative model to help managers better understand the effect of different management options on eight ES over time. These ES were (1) Mexican spotted owl (Strix occidentalis lucida) habitat, (2) the harvest of merchantable timber, (3) the harvest of woody biomass for potential conversion to bioenergy, (4) northern goshawk (Accipiter gentilis) habitat, (5) scenic beauty, (6) fire hazard reduction, (7) carbon storage, and (8) restoration of pre-European settlement forest structure represented through larger quadratic mean diameters (QMD). We integrated production functions for these eight ES with a forest growth-and-yield model to simulate the effects of three management actions over a 45-year period in northern Arizona, USA. We scaled ES values based on their observed maximum and minimum values as a means to compare achievement levels between ES. These scaled ES values were input into a goal-programming model to identify the optimal management regimes given a corresponding set of five different management objectives. The combination of simulation modeling with goal-programming is a novel approach for evaluating ES responses to management and for optimizing ES attainment objectives. To illustrate the value of this novel approach, we designed management objectives to reflect the likely goals a forest manager may choose for each ES in this region. ES goals were distinguished at the forest- and stand-level spatial extents. Results demonstrate the flexibility of the ES optimization model to plan for a variety of situations and preferences. For instance, two ES management goals viewed as conflicting are the protection of Mexican Spotted Owl habitat and the reduction of fire hazard risk. One ES optimization scenario (Scenario 5) produces a plan that reduces area considered as having a high fire

关键词： Ecosystem services Goal-programming Forest management and planning optimization modeling Forest Vegetation Simulator

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System optimization of turbo-expander process for natural gas liquid recovery

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2017年 124卷 159-169页

作者： Li, Yajun Xu, Feiyu Gong, Canteng South China Univ Technol Key Lab Heat Transfer Enhancement & Energy Conser Minist Educ Guangzhou Guangdong Peoples R China

Turbo-expander process is a complex technology to recover the light hydrocarbon in natural gas where energy is highly integrated and some important parameters such as demethanizer pressure and precooling temperature interact with each other, which also codetermine both the recovery and energy consumption of the system. Based on an NGL recovery engineering of 60 x 10(4) Nm(3)/h pipeline gas, this paper focuses on the optimization for NGL recovery system. The overall profits of whole process are chosen as objective function and optimization model is developed. Considering all the influential factors and restrictions such as CO2 freezing, a proper optimization strategy is put forward which is based on SQP (Sequential Quadratic Programming) along with constraint boundary research. The optimization model is solved by Aspen Plus combined with Excel VBA to determine the optimal value of parameters which satisfy both the constraints of the process and the maximum economic benefits of the system. After optimization, it turns out that the overall profits have been improved by 13.5%. The optimization model and the corresponding solution algorithm can provide theoretical guidance for process design and production practice of the turbo-expander process. (C) 2017 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： NGL recovery Turbo-expander process CO2 freezing optimization modeling SQP Algorithm

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Desalination supply chain decision analysis and optimization

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DESALINATION 2014年 347卷 144-157页

作者： Al-Nory, Malak T. Brodsky, Alexander Bozkaya, Burcin Graves, Stephen C. MIT Engn Syst Div Cambridge MA 02139 USA George Mason Univ Dept Comp Sci Fairfax VA 22030 USA Sabanci Univ Sch Management Istanbul Turkey

The desalination industry has been growing progressively in the last few decades. A large number of new plants are contracted every year. Strategic decisions related to plant locations and capacity, the selection of the desalination technology, and many other technical decisions related to the plant design and operation are very critical to these strategic investments. Viewing the desalination industry network as a supply chain provides a holistic view allowing decision makers to perform optimization of water desalination operations end to end. The methodology we propose provides the decision makers with (1) a set of investment alternatives comprising combinations of the different desalination locations, capacities, technologies, and energy sources, and (2) a decision graph showing the performance of each decision alternative in terms of quantitative and qualitative performance metrics chosen by the decision maker. The case study of Saudi Arabia, the world leader in desalination, shows how the methodology can present strategic planners with an optimal configuration of the desalination supply chain. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Desalination Supply chain Decision analysis Strategic planning optimization modeling

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