Determining economic and environmental impact of insulation by thermoeconomic and life cycle assessment analysis for different climate regions of Turkey

Akyüz, Mehmet Kadri

doi:10.1080/15567036.2020.1813223

Cited by 8 publications

(3 citation statements)

References 41 publications

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“…(5) where t is the amount of insulating material used as building materials with variable thickness, and N is the environmental effects of electricity usage in a specific time period. The life cycle cost criterion is employed as another constraint of the optimization (Akyüz, 2021). This analysis specifies a system based on the collected total heating costs of the insulation.…”

Section: Optimization Of the Nano Insulationmentioning

confidence: 99%

Thermal conductivity improvement in a green building with Nano insulations using machine learning methods

et al. 2023

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Section: Optimization Of the Nano Insulationmentioning

confidence: 99%

Thermal conductivity improvement in a green building with Nano insulations using machine learning methods

et al. 2023

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“…For example, in Malatya [10], Denizli [15,18,22], Erzurum [17], İstanbul [20], Bilecik [23], Bursa [24], İzmir and Ankara [25], Diyarbakır [26]. Moreover, some studies are carried out by selecting only one [27][28][29][30][31][32][33][34][35][36] or more [11][12][13][37][38][39] cities from each climatic zone; furthermore, by merely opting for cold towns [9,14] in Turkey. In most of them, different parameters (types of bricks, insulation materials, and fuels) are investigated by economic and environmental analysis to find the ideal configuration.…”

Section: Introductionmentioning

confidence: 99%

“…The optimum insulation thickness, payback period, and the annual prevented environmental impact for natural gas, coal and fuel oil was found to be 0.057 m, 0.066 m, and 0.089 m, 2.85, 3.57 years and 2.05 years and 17.45 kgCO 2 / m 2 , 51.28 kgCO 2 /m 2 and 26.7 kgCO 2 /m 2 , respectively. Akyüz [35] determined the economic and environmental impact of thermal insulation for building walls in the cities of İzmir, İstanbul, Ankara, and Erzurum in Turkey. He employed expanded polystyrene, glass wool rock wool, and extruded polystyrene as insulation material and natural gas as an energy source.…”

Section: Introductionmentioning

confidence: 99%

Optimisation on the thermal insulation layer thickness in buildings with environmental analysis: an updated comprehensive study for Turkey’s all provinces

Aktemur

Bilgin

Tunçkol

2021

Journal of Thermal Engineering

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This study determines the optimum insulation layer thickness to be applied to external building walls considering the heating degree-day (HDD) method, then energy saving costs, payback periods, and carbon dioxide (CO 2 ) emissions are calculated accordingly. The optimisation analysis is performed for four different thermal insulation materials (glass wool, rock wool, extruded polystyrene, and expanded polystyrene). Natural gas is chosen as fuel for heating purposes, and horizontal perforated brick is preferred in the wall. One of the original features in this study is environmental analysis to determine the CO 2 emission for the insulated wall in Turkey provinces. Another feature is that it has the most up-to-date data about HDD values and fuel and insulation material costs. The worst and best insulation materials are obtained as rock wool and glass wool, respectively. The optimum insulation layer thickness for the best case is varied between 0.07 m and 0.23 m, depending on the HDD values of provinces. The annual total energy saving cost is in the range of 4.4-53.5 $/(m 2 year), and the payback period is 0.11-0.38 years. Besides, the reduction in annual CO 2 emission is changed between 53.2% and 94% for the best case, compared to the uninsulated wall.

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The application of life cycle assessment in buildings: challenges, and directions for future research

Fnais

Rezgui

Petri

et al. 2022

Int J Life Cycle Assess

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Purpose This paper reviews the state-of-the art research in life cycle assessment (LCA) applied to buildings. It focuses on current research trends, and elaborates on gaps and directions for future research. Methods A systematic literature review was conducted to identify current research and applications of LCA in buildings. The proposed review methodology includes (i) identifying recent authoritative research publications using established search engines, (ii) screening and retaining relevant publications, and (iii) extracting relevant LCA applications for buildings and analyzing their underpinning research. Subsequently, several research gaps and limitations were identified, which have informed our proposed future research directions. Results and discussions This paper argues that humans can attenuate and positively control the impact of their buildings on the environment, and as such mitigate the effects of climate change. This can be achieved by a new generation of LCA methods and tools that are model based and continuously learn from real-time data, while informing effective operation and management strategies of buildings and districts. Therefore, the consideration of the time dimension in product system modeling is becoming essential to understand the resulting pollutant emissions and resource consumption. This time dimension is currently missing in life cycle inventory databases. A further combination of life cycle impact assessment (LCIA) models using time-dependent characterization factors can lead to more comprehensive and reliable LCA results. Conclusions and recommendations This paper promotes the concept of semantic-based dynamic (real-time) LCA, which addresses temporal and spatial variations in the local built and environmental ecosystem, and thus more effectively promotes a “cradle-to-grave-to-reincarnation” environmental sustainability capability. Furthermore, it is critical to leverage digital building resources (e.g., connected objects, semantic models, and artificial intelligence) to deliver accurate and reliable environmental assessments.

show abstract

Determining economic and environmental impact of insulation by thermoeconomic and life cycle assessment analysis for different climate regions of Turkey

Cited by 8 publications

References 41 publications

Thermal conductivity improvement in a green building with Nano insulations using machine learning methods

Thermal conductivity improvement in a green building with Nano insulations using machine learning methods

Optimisation on the thermal insulation layer thickness in buildings with environmental analysis: an updated comprehensive study for Turkey’s all provinces

The application of life cycle assessment in buildings: challenges, and directions for future research

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