Investigating the environmental impact of reinforced-concrete and structural-steel frames on sustainability criteria in green buildings

Ranjbar, Nima; Balali, Amirhossein; Valipour, Alireza; Yunusa‐Kaltungo, Akilu; Edwards, Rodger; Pignatta, Gloria; Moehler, Robert; Wei, Shen

doi:10.1016/j.jobe.2021.103184

Cited by 14 publications

(13 citation statements)

References 66 publications

(65 reference statements)

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“…Parida [ 51 ] and Ranjbar et al [ 52 ] discussed the interactive relationship between green building and the sustainable development of the environment. Xie and Zhu [ 53 ] studied how manufacturing enterprises broke through the dilemma of system and efficiency with the help of green innovation to achieve the sustainable development of enterprises. Scholars have carried out in-depth research on how to incorporate environmental factors into port efficiency measurements in different countries and regions, such as the research on China’s ports by Luo et al [ 54 ], Qi et al [ 55 ], and Liu et al [ 56 ], and the research on European and Spanish ports by Quintano et al [ 57 ] and Tovar and Wall [ 58 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Green TFP Heterogeneity in the Ports of China’s Pilot Free Trade Zone under Environmental Constraints

Lan

2021

IJERPH

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In the context of China’s Pilot Free Trade Zone (FTZ), ports have a new opportunity to realize high-quality development. Based on the analysis of the current situation of pollutant emissions from ports in China’s Pilot Free Trade Zones (FTZs), this paper introduces environmental factors into the analysis framework of the total factor productivity (TFP) of ports in China’s FTZs, and uses the Global Malmquist–Luenberger index method to analyze the evolution trend and heterogeneity of green TFP in 28 ports of China’s 19 FTZs from 2011 to 2017. The results show that firstly, the emissions of sulfur dioxide (SO2), nitrogen oxides (NOX) and other pollutants in China’s FTZs have been decreasing year by year. Secondly, both the green TFP and the traditional TFP of the ports in FTZs are on the rise. The absence of environmental factors leads to the underestimation of the TFP of ports. For the green TFP, the main source of its growth is technological progress. Thirdly, there is obvious port heterogeneity in the green TFP of FTZ ports. Nanjing Port has the highest green TFP growth rate, with an average annual growth rate of 21.95%. Ningbo Port, which ranks 14th, has an average annual growth rate of 5.46%. Fuzhou Port, which is rated last, has negative growth. Fourthly, there is also obvious types and regional heterogeneity in the green TFP of FTZ ports. When categorized by type, the average annual growth rate of green TFP in inland ports is significantly higher than that of coastal ports. When categorized by region, the descending order of the average annual growth rate of green TFP is the western region, the eastern region and the central region. Fifthly, the green TFP differences among the eastern, central, and western regions, as well as between inland ports and coastal ports, are shrinking. Moreover, the green TFP differences within inland ports and coastal ports and within central ports and eastern ports are also shrinking, implying there may be σ convergence. The conclusions of this paper have important implications for the scientific understanding of the heterogeneity of green TFP growth in ports in China’s FTZs, and how to promote the green development of ports in China’s FTZs under environmental constraints.

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Section: Literature Reviewmentioning

confidence: 99%

Green TFP Heterogeneity in the Ports of China’s Pilot Free Trade Zone under Environmental Constraints

Lan

2021

IJERPH

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“…In recent years, the activities of the construction industry and residents have accounted for approximately 30% to 40% of the global final energy consumption, but this figure may vary by country and time period [1][2][3]. In the United States, the energy consumption of the construction sector accounts for 39% of the total energy consumption, while the energy consumption of residential buildings in the European Union accounts for approximately 40% of the total BEC [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…Finally, a study on the sustainable driving role of BEC on China's economic development by using the quantitative research method of SDF is conducted. The innovations of this article are the following two points: (1) This study takes the lead in establishing an SDF model and proves its objective reality based on common cases; and (2) With the help of econometrics, the method of quantitative research on SDF is systematically explored.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the Sustainable Driving Effect of Building Energy Consumption on Economic Development Based on the Sustainable Driving Force Model

et al. 2023

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The environmental problems caused by building energy consumption (BEC) are becoming increasingly prominent. Reducing building energy consumption can not only effectively curb environmental pollution, but also continue to promote economic development. However, there are few reports on reducing building energy consumption to continuously promote economic development. Sustainable driving force (SDF) has been widely mentioned in past research as a common-sense concept, but few systematic studies have been carried out. The main research objectives of this article include two aspects: On the one hand, this study takes the lead in establishing an SDF model and conducting systematic research on SDF. On the other hand, based on the SDF model, an empirical study is conducted on the sustainable driving effect of reducing building energy consumption on economic development in China. The main conclusions are as follows: (1) Research on the SDF model: Based on common examples, the objective reality of SDF has been theoretically proven. Based on the relevant theories of econometrics, this article believes that the “Granger causality test” and the “distributed lag regression model” can be used as basic tools for quantitative research of SDF models. (2) Research on the application of SDF model: From the Granger causality test, it can be seen that the current BEC intensity is the Granger cause of China’s economic development in the first and eighth cycles of the future. According to the results of the distributed lag regression model, reducing BEC intensity has a sustainable driving effect on economic development. Specifically, in the lagged period 1~8, the sustainable driving effect (reverse effect) of BEC on economic development gradually increases at first (coefficient value from 3878.52 to 5163.87), and then gradually decreases (coefficient value from 5163.87 to 783.534). To sum up, the SDF model can provide a reference for the quantitative study of SDF; studying the sustainable driving effect of BEC on economic development can provide a macro reference for the government to formulate “energy conservation and emission reduction” measures.

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“…Besides, the consumption of landfills due to disposal of construction and demolition waste (CDW) is another important problem around the world, especially in densely populated big cities. Consequently, these global concerns about economic and environmental issues of concrete production have forced stricter requirements for construction and urban development (Ranjbar et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Models for Predicting Mechanical Properties of Recycled Aggregate Concrete (RAC): Critical Review

Ahmed

Ali

2022

ACT

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Recycled aggregate concrete (RAC) has attracted more interesting in the past several years because it is an economical and eco-friendly building material. But generally, the mechanical properties of RAC are poor compared to natural aggregate concrete (NAC). So, the mechanical properties of RAC need robust predictive models to be evaluated before its application. Traditional (empirical based) models, e.g., linear, and non-linear regression methods, have been extensively proposed. But these models lack flexibility in updating (i.e., limited to a finite number of variables) and can give inaccurate results. Consequently, to handle such shortcomings, several Artificial Intelligence (AI) models have been suggested as an alternative strategy for predicting the mechanical properties of RAC. In this study, state-of-the-art AI models were reviewed to predict the mechanical properties of RAC. The application of each predictive model and its training, testing, and performance are critically examined and analysed, consequently identifying present knowledge gaps, practical recommendations, and required future investigation.

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Investigating the environmental impact of reinforced-concrete and structural-steel frames on sustainability criteria in green buildings

Cited by 14 publications

References 66 publications

Green TFP Heterogeneity in the Ports of China’s Pilot Free Trade Zone under Environmental Constraints

Green TFP Heterogeneity in the Ports of China’s Pilot Free Trade Zone under Environmental Constraints

Analysis of the Sustainable Driving Effect of Building Energy Consumption on Economic Development Based on the Sustainable Driving Force Model

Artificial Intelligence Models for Predicting Mechanical Properties of Recycled Aggregate Concrete (RAC): Critical Review

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