Life-cycle assessment and multi-objective optimization of natural-insulated envelopes across Iranian climates

  • Peyman Naghipour orcid

    Department of Architecture, Ta.C., Islamic Azad University, Tabriz, Iran
  • Afshin Naghipour orcid

    Department of Civil Engineering-Civil, Ta.C., Islamic Azad University, Tabriz, Iran
  • Tarana Bakirova orcid

    Graphic and Media Design Department, Design Faculty, Azerbaijan University of Architecture and Construction, Baku, Azerbaijan
Article ID: 3952
DOI: https://doi.org/10.59400/be3952
Keywords: life-cycle assessment, multi-objective optimization, natural insulation, Iranian climates, operational energy, embodied carbon

Abstract

The building envelope plays a pivotal role in achieving sustainable energy performance, particularly in regions characterized by extreme climatic variations. This study investigates the holistic optimization of building envelopes—comprising walls, roofs, floors, and fenestrations—by integrating natural insulation materials with passive and smart design strategies. The research aims to enhance energy efficiency, reduce total CO₂ emissions, and improve occupants’ thermal comfort across four representative low-income climatic regions of Iran: Yazd (hot-arid), Tabriz (cold-dry), Rasht (temperate-humid), and Bandar Abbas (hot-humid). Addressing the existing research gap, the study extends beyond operational energy analysis by incorporating a full life cycle assessment (LCA), including embodied energy and life cycle carbon footprint. Multi-objective optimization (using NSGA-II) was performed to minimize annual energy demand, life-cycle cost (LCC), and environmental impact simultaneously. Building performance simulations were conducted using IES-VE and EnergyPlus, while LCA and economic analyses were executed via SimaPro and HOMER Pro. The results indicate that hybrid natural insulations-particularly straw–hemp composites-combined with passive strategies (dynamic shading, natural ventilation, and thermal mass enhancement) can reduce total CO₂ emissions by 42–58% compared with conventional materials. Also, the results demonstrate that the optimized design solutions can reduce annual energy consumption by approximately 25–35% compared to the baseline design, while achieving a 15–25% reduction in life-cycle costs over the building lifespan. Additionally, orientation-sensitive optimization improved thermal comfort indices (Predicted Mean Vote—PMV, Predicted Percentage of Dissatisfied—PPD) throughout the year. The developed predictive models based on machine learning (Random Forest) exhibited robust accuracy in estimating energy consumption. The findings provide an integrated framework for sustainable, low-cost, and climate-responsive envelope design, supporting the transition toward net-zero energy buildings in developing regions.

Published
2026-02-28
How to Cite
Naghipour, P., Naghipour, A., & Bakirova, T. (2026). Life-cycle assessment and multi-objective optimization of natural-insulated envelopes across Iranian climates. Building Engineering, 4(1). https://doi.org/10.59400/be3952
Issue
Vol. 4 No. 1 (2026)
Section
Article

Copyright (c) 2026 Peyman Naghipour, Afshin Naghipour, Tarana Bakirova

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

[1]Heinz E, Sovacool BK, Kwan T, et al. Critically reviewing the 50 sociotechnical risks of building sector decarbonization: Conceptualizing risk as a proximity spiral. Energy and Buildings. 2025; 344: 116042. doi: 10.1016/j.enbuild.2025.116042

[2]Vallati A, Di Matteo M, Sundararajan M, et al. Development and optimization of an energy saving strategy for social housing applications by water source-heat pump integrating photovoltaic-thermal panels. Energy. 2024. 301: 131531. doi: 10.1016/j.energy.2024.131531

[3]Lokko M, Manu, FW, Mboup N, et al. Comparing the whole life cycle carbon impact of conventional and biogenic building materials across major residential typologies in Ghana and Senegal. Sustainable Cities and Society. 2024; 106: 105332. doi: 10.1016/j.scs.2024.105332

[4]Omrany H, Soebarto V. Time to do More: Realisation of Life-Cycle Net-Zero Energy Buildings. In: Abraham MA (editor). Encyclopedia of Sustainable Technologies, 2nd, ed. Elsevier; 2024. pp. 459–472.

[5]Idrissi Kaitouni S, Romani Z, Jamil A, et al. Zero carbon urban buildings (ZCUBs) in the era of climate change, digital transformation and energy transition: A scoping review from 2000 to 2024. Building and Environment. 2025; 280: 113116. doi: 10.1016/j.buildenv.2025.113116

[6]Ulpiani G, Yenneti K, Pigliautile I, et al. Urban heat mitigation and adaptation: the state of the art. In: Aghamohammadi N, Santamouris M (editors). Mitigation and Adaptation of Urban Overheating: The Impact of Warmer Cities on Climate, Energy, Health, Environmental Quality, Economy, and Quality of Life. Elsevier: Amsterdam, The Netherlands; 2024. pp. 23–90.

[7]Jamilu G, Abdou A, Asif M. Dynamic facades for sustainable buildings: A review of classification, applications, prospects and challenges. Energy Reports. 2024; 11: 5999–6014. doi: 10.1016/j.egyr.2024.05.047

[8]Jia Z, Wang M, Xiang C. Photovoltaic Trombe wall system: Multi-functional performance, optimization parameters, and evolutionary insights—A comprehensive review. Journal of Building Engineering. 2025. 115: 114536. doi: 10.1016/j.jobe.2025.114536

[9]Ghasaban M, Yeganeh M, Irani M. Optimizing daylight, sky view and energy production in semi-transparent photovoltaic facades of office buildings: A comparative study in four climate zones. Applied Energy. 2025; 377(Part D): 124707. doi: 10.1016/j.apenergy.2024.124707

[10]Han M, Lu L, Sun B. Overall energy performance of building-integrated bifacial photovoltaic sunshades with different installation and building parameters in hot and humid regions. Solar Energy. 2024; 275: 112619. doi: 10.1016/j.solener.2024.112619

[11]Muñoz-Salcedo M, Saquinaula-Brito JL, Ortíz-Mata J, et al. A simple simultaneous envelope/system optimization for energy efficiency improvement in near-zero energy buildings. Energy Conversion and Management: X. 2025; 26: 100951. doi: 10.1016/j.ecmx.2025.100951

[12]Morsy A, Kandil S, Ewais HA, et al. Eco-conscious flame retardants for enhanced fire resistance in natural fiber reinforced polymers composite: A review bio-based, and industry implications. Chemosphere. 2025; 377: 144360. doi: 10.1016/j.chemosphere.2025.144360

[13]Wang M, Duan X, Li L, et al. Performance improvement of poly (lactic acid) films for bioelectronics with eco-friendly supercritical fluids combined with activated-carbon technique. Sustainable Materials and Technologies. 2023; 38: e00739. doi: 10.1016/j.susmat.2023.e00739

[14]Ye F, Wei H, Xiao Y, et al. Bio-based insulation materials in sustainable constructions: A review of environmental, thermal and acoustic insulation, durability, and mechanical performances. Renewable and Sustainable Energy Reviews. 2025; 223: 115872. doi: 10.1016/j.rser.2025.115872

[15]Gao X, Xiao F, Liu Q, et al. Increasing influence of compound dry-hot events on vegetation in northern China in recent years. Journal of Arid Environments. 2025; 229: 105393. doi: 10.1016/j.jaridenv.2025.105393

[16]Matongo TJ, Ngock GRH, Yamb E, et al. Data on air temperature, relative humidity, and dew point in three housing modes in a building in a hot and humid area of Douala, Cameroon. Data in Brief. 2025; 63: 112120. doi: 10.1016/j.dib.2025.112120

[17]Pang Y, Hao Z, Chen Y, et al. Amplified contrasts in evapotranspiration between wet and dry regions caused by compound drought-hot events. Global and Planetary Change. 2025. 255: 105108. doi: 10.1016/j.gloplacha.2025.105108

[18]Panigrahi SS, Hemis M, Singh CB. Energy and moisture source-term based distributive (luikov) parameter model to simulate rapeseed hot-air drying. Journal of Stored Products Research. 2025. 114: 102701. doi: 10.1016/j.jspr.2025.102701

[19]Fu C, Tseng ML, Sethanan K. A hybrid combined cooling, heating and power system with carbon emission, economic cost and energy consumption constrains: An optimization and performance analysis. Applied Thermal Engineering. 2025. 279(Part E): 127877. doi: 10.1016/j.applthermaleng.2025.127877

[20]Shu Z, Zhou Y, Liu W, et al. Multi-objective optimization approach for timber-concrete hybrid shear wall building structures considering construction cost and carbon emissions. Structures. 2025; 78: 109221. doi: 10.1016/j.istruc.2025.109221

[21]Polatoğlu A. A thorough examination of concurrent measurements cosmic ray radiation and meteorological parameters with the support of machine learning. Radiation Measurements. 2025; 181: 107375. doi: 10.1016/j.radmeas.2025.107375

[22]Zhou P, Qi Y, Yang Q, et al. Neural topic modeling of machine learning applications in building: Key topics, algorithms, and evolution patterns. Automation in Construction. 2025; 170: 105890. doi: 10.1016/j.autcon.2024.105890

[23]Baek D, Kim H, Wei Q, et al. Evaluating the impact of windows, artificial windows, and ceiling height on stress levels through subjective and objective measures. Building and Environment. 2025; 281: 113182. doi: 10.1016/j.buildenv.2025.113182

[24]Dogan A, Kayaci N, Demir H, et al. An experimental comparison of radiant wall and ceiling cooling system integrated with ground source heat pump and direct expansion fan coil system in a highly glazed office room. Energy and Buildings. 2022; 273: 112412. doi: 10.1016/j.enbuild.2022.112412

[25]Cheng M, Huang Z, Zheng Y. A review on life-cycle carbon emissions of reinforced concrete buildings: Calculation and reduction. Journal of Cleaner Production. 2025; 526: 146501. doi: 10.1016/j.jclepro.2025.146501

[26]Kong L, Wang L, Li, F, et al. An innovative life cycle scenario-driven method for product carbon emissions prediction in the early design phase. Computers & Industrial Engineering. 2025. 209: 111461. doi: 10.1016/j.cie.2025.111461

[27]Witte A, Garg N. Quantifying the global warming potential of low carbon concrete mixes: Comparison of existing life cycle analysis tools. Case Studies in Construction Materials. 2024; 20: e02832. doi: 10.1016/j.cscm.2023.e02832

[28]Keshavarz A, Farajzadeh Z. Exploring the impacts of climate change on ecological footprint in Iran: A dynamic input-output analysis. Environmental Development. 2025; 55: 101217. doi: 10.1016/j.envdev.2025.101217

[29]Roshan GR, Saman AA, Sarli R, et al. Projected shifts in wind energy availability in response to climate change in southwestern Iran. Sustainable Energy Technologies and Assessments. 2025; 83: 104655. doi: 10.1016/j.seta.2025.104655

[30]Yaghoubi F, Bannayan M. Toward climate-resilient agriculture in Iran: Modeling quinoa viability under future climate scenarios. Agricultural Systems. 2026; 231: 104551. doi: 10.1016/j.agsy.2025.104551

[31]Bian J, Yi D, Yao E, et al. Integrated assessment method for carbon emission and cost throughout the life cycle of office buildings: A comparative study of steel structure and timber structure. Structures. 2025; 77: 109103. doi: 10.1016/j.istruc.2025.109103

[32]Chen Y, Han M, Liu X, et al. Assessing the environmental and economic impacts of the oyster life cycle under renewable energy expansion. Journal of Environmental Management. 2025; 389: 126220. doi: 10.1016/j.jenvman.2025.126220

[33]Daoudi M, Daoudi I, Idrissi A, et al. Analyzing life cycle costs and carbon emission reduction of a first offshore wind farm in africa under the climatic conditions of Morocco: Case study. Physics and Chemistry of the Earth, Parts A/B/C. 2025; 139: 103937. doi: 10.1016/j.pce.2025.103937

[34]Ren Y, Ren Z, Zou G, et al. Multi-objective optimization of capacity configuration for district heating and cooling system based on life cycle cost and annual carbon dioxide emissions. Journal of Building Engineering. 2025; 109: 113038. doi: 10.1016/j.jobe.2025.113038

[35]Hasanov T, Charlier D. Classifying energy behaviors to optimize sustainability: Insights from French residential heating practices. Energy Economics. 2025; 152: 109000. doi: 10.1016/j.eneco.2025.109000

[36]Rabie D, Farzaneh H. A novel modeling framework for demand response-based energy management systems in smart electricity markets, using optimization and multi-criteria decision making techniques. Applied Energy. 2026; 405: 127228. doi: 10.1016/j.apenergy.2025.127228

[37]Ramsey P, Gingerich D, Best K, et al. Providing for occupant experience in optimized connected energy communities—A critical review. Building and Environment. 2024; 265: 111988. doi: 10.1016/j.buildenv.2024.111988

[38]Bounnah A, Bourbia PF. Optimizing urban morphology for thermal comfort: Real-time wind-solar synchronization via Ansys Discovery and Grasshopper. Energy and Buildings. 2026; 356: 117118. doi: 10.1016/j.enbuild.2026.117118

[39]Lee Y, Ng E. An adaptable framework for resilient subtropical low-income housing under future climate and predicted lifestyles: A Hong Kong case study. Energy and Buildings. 2025; 348: 116412. doi: 10.1016/j.enbuild.2025.116412

[40]Albadaineh R, Fattah AAE. Assessing cooling–lighting trade-offs in a low-income Jordanian housing archetype under climate change and heat waves. Building and Environment. 2026; 288: 114040. doi: 10.1016/j.buildenv.2025.114040

[41]Villada-Medina HD, Díez-Echavarría L. Unequal benefits of metro station proximity: Income-level differences in housing price effects in Medellín. Journal of Transport Geography. 2026; 131: 104571. doi: 10.1016/j.jtrangeo.2026.104571

[42]Shoaib Q, Mukherjee V, Marmaridou V, et al. Development and evaluation of sustainable henequen fibre foams for thermal insulation. Materials Today Sustainability. 2025; 31: 101111. doi: 10.1016/j.mtsust.2025.101111

[43]Huo D, Zhao J, Zhao Z, et al. A comprehensive life cycle cost model for high-temperature pipe insulation: Balancing heat dissipation, temperature resistance and economic benefits. Case Studies in Thermal Engineering. 2025; 73: 106492. doi: 10.1016/j.csite.2025.106492

[44]Likhon RWA, Khan MAH. Simulation-based analysis of thermal bridge reduction in multi-storey residential buildings of Bangladesh using recycled plastic waste insulation. International Journal of Thermofluids. 2025; 30: 101452. doi: 10.1016/j.ijft.2025.101452

[45]Marincu C, Dan D, Moga L. Investigating the influence of building shape and insulation thickness on energy efficiency of buildings. Energy for Sustainable Development. 2024; 79: 101384. doi: 10.1016/j.esd.2024.101384

[46]Castrejon-Esparza NM, González-Trevizo ME, Martínez-Torres KE, et al. Optimizing urban morphology: Evolutionary design and multi-objective optimization of thermal comfort and energy performance-based city forms for microclimate adaptation. Energy and Buildings. 2025; 342: 115750. doi: 10.1016/j.enbuild.2025.115750

[47]Jansen D, Richter V, Maier L, et al. Open-source framework for automated generation of building energy performance simulation models and beyond from BIM Data. Automation in Construction. 2025; 179: 106427. doi: 10.1016/j.autcon.2025.106427

[48]Pan Y, Zhu M, Lv Y, et al. Building energy simulation and its application for building performance optimization: A review of methods, tools, and case studies. Advances in Applied Energy. 2023; 10: 100135. doi: 10.1016/j.adapen.2023.100135

[49]Aloshan M, Aldali K. Empirical study of facade retrofits for optimizing energy efficiency and cooling in school buildings in Saudi Arabia. Energy Reports. 2024; 12: 4105–4128. doi: 10.1016/j.egyr.2024.09.076

[50]Golkar S, Baneshi M, Fathi A. Effect of cool and thermal paints on the cooling and heating loads in various climates. Energy Storage and Saving. In press. 2025. doi: 10.1016/j.enss.2025.05.007

[51]Hu M, Zhang K, Nguyen Q, et al. The effects of passive design on indoor thermal comfort and energy savings for residential buildings in hot climates: A systematic review. Urban Climate. 2023; 49: 101466. doi: 10.1016/j.uclim.2023.101466

[52]Liu B, Li H, Song Z, et al. Wrinkled-porous core-shell SiO2 aerogel fiber composites for thermal insulation coatings: Strain energy storage, unidirectional gas channels, and water resistance. Ceramics International. 2025; 51(28, Part B): 57355–57369. doi: 10.1016/j.ceramint.2025.09.445

[53]Dong X, He BJ. A standardized assessment framework for green roof decarbonization: A review of embodied carbon, carbon sequestration, bioenergy supply, and operational carbon scenarios. Renewable and Sustainable Energy Reviews. 2023; 182: 113376. doi: 10.1016/j.rser.2023.113376

[54]Xu P, Xu X. Thermal comfort, energy consumption, and carbon emissions of building envelope in office buildings: A comparative study of 46 envelope materials. Building and Environment. 2025; 285(Part C): 113578. doi: 10.1016/j.buildenv.2025.113578

[55]Lv J, Lin X, Liao S, et al. Computation of vertical density distribution of compressed wood as a function of temperature, moisture content, and compression load. Construction and Building Materials. 2025; 490: 142424. doi: 10.1016/j.conbuildmat.2025.142424

[56]Cornette JFP, Blondeau J. Operational greenhouse gas emissions of various energy carriers for building heating. Cleaner Energy Systems. 2024; 9: 100148. doi: 10.1016/j.cles.2024.100148

[57]Srikanth A, Ramesh SJ, Heath G, et al. Democratizing life cycle assessment by developing a streamlined model of greenhouse gas emissions from US natural gas supply chains. Cell Reports Sustainability. 2025; 3(1): 100554. doi: 10.1016/j.crsus.2025.100554

[58]Khan MHA, Sitaraman T, Haque N, et al. Strategies for life cycle impact reduction of green hydrogen production—Influence of electrolyser value chain design. International Journal of Hydrogen Energy. 2024; 62: 769–782. doi: 10.1016/j.ijhydene.2024.01.081

[59]Alaux N, Marton C, Steinmann J, et al. Whole-life greenhouse gas emission reduction and removal strategies for buildings: Impacts and diffusion potentials across EU Member States. Journal of Environmental Management. 2024; 370: 122915. doi: 10.1016/j.jenvman.2024.122915

[60]Xie M, Li J, Wei Z, et al. Multi-objective optimization for pipeline systems: A maintenance model using NSGA-II considering flow capacity and total cost. Reliability Engineering & System Safety. 2026; 266(Part A): 111663. doi: 10.1016/j.ress.2025.111663

[61]Alaa H, Yehia M, Ayoub M. Metaheuristic optimization of roof designs to enhance energy performance and thermal comfort using parametrization and machine learning. Solar Energy. 2025; 286: 113186. doi: 10.1016/j.solener.2024.113186

[62]Naghipour P, Naghipour A. Energy performance analysis of residential buildings in Bandar Anzali: Influence of orientation and aspect ratio. Next Sustainability. 2025; 5: 100140. doi: 10.1016/j.nxsust.2025.100140

[63]Song G, Chen Y, He Y, et al. Techno-economic and life cycle greenhouse gas assessment of green ammonia produced by low-pressure Haber-Bosch process. Energy Nexus. 2025; 17: 100379. doi: 10.1016/j.nexus.2025.100379

[64]Alamri S, Sadeq AM, Ayadi M, et al. Advanced optimization of a biogas-based multigeneration multi effect distillation system integrated with desalination process for enhancing sustainable energy resource efficiency: CatBoost-supported multi objective multi-verse optimization. Desalination. 2026; 619: 119514. doi: 10.1016/j.desal.2025.119514

[65]Naghipour P, Naghipour A. Evaluating heating energy consumption in residential buildings using hybrid machine learning models: The case of parsabad city. Next Research. 2025; 2(3): 100721. doi: 10.1016/j.nexres.2025.100721

[66]Wang C, Zhang Q, Xu X, et al. BPS-V: A blockchain-based trust model for the Internet of Vehicles with privacy-preserving. Ad Hoc Networks. 2024; 163: 103566. doi: 10.1016/j.adhoc.2024.103566

[67]Yao H, Wan C. Multi-factor portfolio optimization: A combined random Forest–AdaBoost model with cost-sensitive learning. Pacific-Basin Finance Journal. 2025; 94: 102946. doi: 10.1016/j.pacfin.2025.102946

[68]Mostafa Refat Ismail M, Aly Nessim A, Fathy F. Factors affecting museum buildings and heritage spaces in terms of energy optimization and comfort. Ain Shams Engineering Journal. 2024; 15(12): 103069. doi: 10.1016/j.asej.2024.103069

[69]Myroniuk K, Zhelykh V, Furdas Y, et al. Energy-saving of passive ventilation systems in thermally modernized residential buildings—A review. Energy and Buildings. 2026; 350: 116681. doi: https://doi.org/10.1016/j.enbuild.2025.116681

[70]Maaith N, Sharmin T, Bk S. Socio-technical dynamics of energy consumption in low-income housing in Amman, Jordan. Habitat International. 2025; 163: 103485. doi: 10.1016/j.habitatint.2025.103485

[71]Sunikka-Blank M, Galvin R. Extending the prebound effect: The gap between healthy and actual energy consumption among low-income households in the global south. Energy Research & Social Science. 2025; 129: 104390. doi: 10.1016/j.erss.2025.104390

[72]Choi BH, Song SY. Insulation performance evaluation of stone-finished exterior insulation systems with insulation frames for green remodeling of concrete exterior walls. Journal of Building Engineering. 2024; 90: 109412. doi: 10.1016/j.jobe.2024.109412

[73]Naghipour P, Naghipour A, Shirdel AH, et al. Sustainability in Historical Islamic Architecture: Lessons from Sheikh Lotfollah Mosque’s Construction Techniques. Journal of Islamic Architecture. 2025; 8(3): 585–603. doi: 10.18860/jia.v8i3.29053

[74]Spudys P, Jurelionis A, Fokaides P. Digitizing buildings sustainability assessment: Integrating energy audits, operational energy assessments, and life cycle assessments for enhanced building assessment. Energy. 2025; 316: 134429. doi: 10.1016/j.energy.2025.134429

[75]Soleimani K, Bakhshi A, Ghanian M. Voices from Iranian Farmers: Balancing livelihood and sustainability in the climate change Era. World Development Perspectives. 2025; 40: 100742. doi: 10.1016/j.wdp.2025.100742

[76]Bakthavatchalam B, Al-Doori GF, Algarni S, et al. Life cycle cost analysis of an innovative nanofluid assisted photovoltaic thermoelectric air conditioner for energy efficiency enhancement in buildings. Case Studies in Thermal Engineering. 2025; 73: 106494. doi: 10.1016/j.csite.2025.106494

[77]Malomo D, Xie Y, Doudak G. Unified life-cycle cost–benefit analysis framework and critical review for sustainable retrofit of Canada's existing buildings using mass timber. Canadian Journal of Civil Engineering. 2024; 51(7): 687–703. doi: h10.1139/cjce-2023-0222

[78]Erdiwansyah, Mamat R, Syafrizal, et al. Emerging role of generative AI in renewable energy forecasting and system optimization. Sustainable Chemistry for Climate Action. 2025; 7: 100099. doi: 10.1016/j.scca.2025.100099

[79]Ebekozien A, Aigbavboa CO, Samsurijan MS, et al. Developing a framework for housing financing: A case study of Nigeria’s sustainable low-cost housing via soft system methodology. Engineering, Construction and Architectural Management. 2025; 32(13): 27–48. doi: 10.1108/ECAM-09-2023-0895

[80]Naghipour P. Metaheuristic model tuning for energy forecasting in low-income housing in the MollaZeynal region of Tabriz city: Linking comfort and carbon. Next Research. 2026; 4: 101265. doi: 10.1016/j.nexres.2025.101265

[81]Ouria M, Moura P, Ouria A, et al. Multi-objective architectural parametric optimization toward decarbonizing building sector—Tabriz city case study. Journal of Building Engineering. 2025. 105: 112422. doi: 10.1016/j.jobe.2025.112422

[82]Luo X, Yang J, Fang Y, et al. Phased optimization of classroom units for low-carbon sustainability and occupant health. Energy. 2025; 335: 138009. doi: 10.1016/j.energy.2025.138009

[83]Thibault G, Simon L, Robin G. Integrating life cycle sustainability assessment into building renovation strategies. Building and Environment. 2025; 286: 113694. doi: 10.1016/j.buildenv.2025.113694

[84]Nasiri N, Rahbar N. A systematic review of thermal comfort in vernacular underground architecture of hot and arid climates: Emphasizing Iranian case studies. Energy and Buildings. 2026; 353: 116937. doi: 10.1016/j.enbuild.2025.116937

[85]Kamazani MA, Dixit MK, Shanbhag SS. Multi-objective genetic optimization of embodied and operational energy and carbon impacts of buildings in current and future scenarios. Energy and Buildings. 2025; 338: 115748. doi: 10.1016/j.enbuild.2025.115748

[86]Ibrahim MM, Suarez-Lopez MJ, Hanafy AA, et al. Optimizing NZEB performance: A review of design strategies and case studies. Results in Engineering. 2025; 25: 103950. doi: 10.1016/j.rineng.2025.103950

[87]Asadpour F, Shirdel AH, Naghipour P. Evaluation of perceptual indicators of physical environment affecting the inducement of citizen’s sense of place in urban neighborhoods. Energy and Buildings. 2024; 325: 114992. doi: 10.1016/j.enbuild.2024.114992

[88]Ran J, Qiu Y, Liu J, et al. Coordinated optimization design of buildings and regional integrated energy systems based on load prediction in future climate conditions. Applied Thermal Engineering. 2024; 241: 122338. doi: 10.1016/j.applthermaleng.2024.122338

[89]Pérez G, Cabeza LF. Buildings life cycle assessment. In: Abraham MA (editor). Encyclopedia of Sustainable Technologies, 2nd ed. Elsevier; 2024. pp. 427–445.

[90]Chen X, Yang H, Zhang W. Simulation-based approach to optimize passively designed buildings: A case study on a typical architectural form in hot and humid climates. Renewable and Sustainable Energy Reviews. 2018; 82(Part 2): 1712–1725. doi: 10.1016/j.rser.2017.06.018

[91]Ye J, Yang F. Towards multi-scale and context-specific heat health risk assessment: A systematic review. Sustainable Cities and Society. 2025; 119: 106102. doi: 10.1016/j.scs.2024.106102

[92]Ruan D, Fan C, Hu M, et al. Building-integrated photovoltaics through multi-physics synergies: A critical review of optical, thermal, and electrical models in facade applications. Renewable Energy. 2025; 251: 123332. doi: 10.1016/j.renene.2025.123332

[93]Abdalla A, Islam MD, Janajreh I. Influence of building orientation on cooling load: A comparative study. International Journal of Thermofluids. 2025; 27: 101244. doi: 10.1016/j.ijft.2025.101244

[94]Arul Babu ADC, Srivastava RS, Rai AC. Impact of climate change on the heating and cooling load components of an archetypical residential room in major Indian cities. Building and Environment. 2024; 250: 111181. doi: 10.1016/j.buildenv.2024.111181

[95]Borelli D, Cavalletti A, Cavalletti P, et al. A methodology to evaluate the optimal insulation thickness for heating and cooling needs in different climatic zones for buildings made of reinforced concrete with cavity walls. Heliyon. 2024; 10(10): e30653. doi: 10.1016/j.heliyon.2024.e30653

[96]Chaudhary GQ, Hu Z, He S, et al. Analysis of building-integrated solar desiccant air cooling systems considering the dynamic sensible and latent cooling loads. International Journal of Refrigeration. 2026; 181: 111–125. doi: 10.1016/j.ijrefrig.2025.10.007

[97]Bamdad K. Cool roofs: A climate change mitigation and adaptation strategy for residential buildings. Building and Environment. 2023; 236: 110271. doi: 10.1016/j.buildenv.2023.110271

[98]Jia S, Weng Q, Yoo C, et al. Global investigation of pedestrian-level cooling and energy-saving potentials of green and cool roofs in 43 megacities. Energy and Buildings. 2025; 337: 115671. doi: 10.1016/j.enbuild.2025.115671

[99]Lu M, Zeng L, Li Q, et al. Quantifying cooling benefits of cool roofs and walls applied in building clusters by scaled outdoor experiments. Sustainable Cities and Society. 2023; 97: 104741. doi: 10.1016/j.scs.2023.104741

[100]Zhou J, Fang Z, Yin G, et al. Automated roof segmentation for assessing urban scale energy performance and indoor thermal environment of photovoltaic and green roofs. Energy. 2025; 338: 138958. doi: 10.1016/j.energy.2025.138958

[101]Gong Q, Ding W, Liu X, et al. Multi-objective optimization framework for the building envelope of public rental housing in China's cold regions. Journal of Building Engineering. 2025; 104: 112261. doi: 10.1016/j.jobe.2025.112261

[102]Qiu Z, Yong Q, Wang J, et al. A multi-objective optimization framework for performance-based building design considering the interplay between buildings and urban environments. Energy Conversion and Management. 2024; 315: 118793. doi: 10.1016/j.enconman.2024.118793

[103]Wang W, Zhu L, Zhang T, et al. Integrating local climate considerations into dormitory energy optimization: An explainable machine learning and multi-objective design approach. Urban Climate. 2025; 64: 102629. doi: 10.1016/j.uclim.2025.102629

[104]Epelde L, Mendizabal M, Gutiérrez L, et al. Quantification of the environmental effectiveness of nature-based solutions for increasing the resilience of cities under climate change. Urban Forestry & Urban Greening. 2022; 67: 127433. doi: 10.1016/j.ufug.2021.127433

[105]Li J, Jian R, Bao S, et al. Quantifying the impact of building layouts on wind–thermal environments: A computational fluid dynamics-based approach for optimizing plans and designs in high-temperature, low-wind regions. Results in Engineering. 2025; 26: 104740. doi: 10.1016/j.rineng.2025.104740

[106]Lopez-Cabeza VP, Alzate-Gaviria S, Diz-Mellado E, et al. Albedo influence on the microclimate and thermal comfort of courtyards under Mediterranean hot summer climate conditions. Sustainable Cities and Society. 2022; 81: 103872. doi: 10.1016/j.scs.2022.103872

[107]Eloranta V, Inkeri E, Luoranen M, et al. Balancing trade-offs in Nordic smart local energy systems: Multi-objective and multi-criteria optimization for cost, emissions, and self-sufficiency. Renewable Energy. 2025; 257: 124696. doi: 10.1016/j.renene.2025.124696

[108]Khaled B, Abdelaziz AY, Attia MA, et al. Assessing the impact of climate change on wind energy penetration: Optimization of scheduling and carbon emission analysis. Electric Power Systems Research. 2025; 248: 111929. doi: 10.1016/j.epsr.2025.111929

[109]Liu T, Zhu H, Shen Y, et al. Carbon-friendly design method of tunnel lining segments based on Pareto optimal analysis. Tunnelling and Underground Space Technology. 2025; 161: 106602. doi: 10.1016/j.tust.2025.106602

[110]Wu Y, Zhong L. Assessing the affordability and independence of building-integrated household green hydrogen systems in Canadian urban households under climate change. Energy Conversion and Management. 2025; 346: 120432. doi: 10.1016/j.enconman.2025.120432