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The aim of this study is to understand the environmental benefits and economic savings associated with adoption of circular economy in the construction sector. The research findings will support different stakeholders and decision makers to develop business models based on responsible consumption of resources and build sustainable business models.

The research uses mixed methodology wherein inventory for life cycle assessment and life cycle costing for environmental and economic impacts is based on primary data using on-site visits for qualitative and quantitative data.

Different types of land transportation infrastructures are compared for their environmental impacts. It is found that bridges have the highest environmental impacts as compared to tunnels, roads and railways. Further, the results affirm the environmental and economic benefits of adopting circular economy practices.

This is one of a kind research that compares the environmental and economic tradeoffs of adopting circular economy in different types of land transportation infrastructures.

This study aims to investigate the behavior of the green biomass-derived copper (lignin/silica/fatty acids) complex, copper lignin/silica/fatty acids (Cu-LSF) complex, when incorporated into the nonpolar ethylene propylene diene (EPDFM) rubber matrix, focusing on its reinforcing and antioxidant effect on the resulting EPDM composites.

The structure of the prepared EPDM composites was confirmed by Fourier-transform infrared spectroscopy, and the dispersion of the additive fillers and antioxidants in the EPDM matrix was investigated using scanning electron microscopy. Also, the rheometric characteristics, mechanical properties, swelling behavior and thermal gravimetric analysis of all the prepared EPDM composites were explored as well.

Results revealed that the Cu-LSF complex dispersed well in the nonpolar EPDM rubber matrix, in thepresence of coupling system, with enhanced Cu-LSF-rubber interactions and increased cross-linking density, which reflected on the improved rheological and mechanical properties of the resulting EPDM composites. From the various investigations performed in the current study, the authors can suggest 7–11 phr is the optimal effective concentration of Cu-LSF complex loading. Interestingly, EPDM composites containing Cu-LSF complex showed better antiaging performance, thermal stability and fluid resistance, when compared with those containing the commercial antioxidants (2,2,4-trimethyl-1,2-dihydroquinoline and N-isopropyl-N’-phenyl-p-phenylenediamine). These findings are in good agreement with our previous study on polar nitrile butadiene rubber.

The current study suggests the green biomass-derived Cu-LSF complex to be a promising low-cost and environmentally safe alternative filler and antioxidant to the hazardous commercial ones.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

Though alternative building technologies (ABTs) have been encouraged to address accessible and affordable issues in low-cost housing (LCH) provision, their adoption is still overwhelmed with encumbrances. The encumbrances that hinder ABT adoption require an in-depth study, especially in developing countries like Nigeria. However, studies regarding ABT and its role in improving Nigeria's LCH to achieve Sustainable Development Goal (SDG) 11 are scarce. This research investigates encumbrances to ABT adoption in Nigeria's LCH provision and suggests feasible measures to prevent or reduce the encumbrances, thereby improving achieving SDG 11 (sustainable cities and communities).

This research utilised qualitative research and adopted a face-to-face interview as the primary data collection. The interviewees comprised ABT practitioners and end users in Nigeria who were chosen by a convenient sampling technique. The study's data were analysed manually through a thematic approach.

This study shows that stakeholders should embrace ABT in LCH provision to improve achieving SDG 11 in Nigeria. Also, it clustered the perceived 20 encumbrances to ABT adoption in LCH provision into government/policymaker, housing developers/building contractors, ABT users and ABT manufacturers-related issues in Nigeria's context. This study suggested mechanisms to mitigate encumbrances to ABT adoption in LCH provision, thereby improving achieving SDG 11.

This research adds to the limited literature by analysing ABT adoption encumbrances in Nigeria's LCH provision, which could assist policy formulation for the uptake of ABT in LCH provision and improve achieving Goal 11.

This paper aims to identify how a public client’s use of control systems (process, output and social control) affect innovation possibilities in construction projects.

Semi-structured interviews about six infrastructure projects were conducted to identify respondents’ views on innovation possibilities. These possibilities were then analyzed from an organizational control perspective within principal–agent relationships between the Swedish Transport Administration (STA) and their contractors.

How the client uses control systems affects innovation possibilities. Relying on process control could negatively affect innovation opportunities, whereas output control could have a positive influence. In addition, social control seems to have a weak effect, as the STA appears not to use social control to facilitate joint innovation. Public clients must comply with the Public Procurement Act and, therefore, retain the requirements specified in the tendering documents. Much of the steering of the execution is connected to the ex ante phase (before signing the contract), which affects innovation possibilities in the design and execution phases for the contractor.

This study was conducted with only one client, thus limiting its generalizability. However, the findings provide an important stepping stone to further investigation into balancing control systems and creating innovation possibilities in a principal–agent relationship.

Although public procurement has increasingly been emphasized as a major potential source of innovation, studying how a public client’s use of organizational control systems affects innovation possibilities in the construction sector has received scant attention.

The crude oil supply chain (COSC) is one of the most complex and largest supply chains in the world. It is easily vulnerable to extreme events. Recently, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (often known as COVID-19) pandemic created a massive imbalance between supply and demand which caused significant price fluctuations. The purpose of this study is to explore the influential factors affecting the international COSC in terms of consumption, production and price. Furthermore, it develops a model to predict the international crude oil price during disease outbreaks using Random Forest (RF) regression.

This study uses both qualitative and quantitative approaches. A qualitative study is conducted using a literature review to explore the influential factors on COSC. All the data are extracted from Web sources. In addition to COVID-19, four other diseases are considered to optimize the accuracy of predictive results. A principal component analysis is deployed to reduce the number of variables. A forecasting model is developed using RF regression.

The findings of the qualitative analysis characterize the factors that influence international COSC. The findings of quantitative analysis emphasize that production and consumption have a higher contribution to the variance of the data set. Also, this study found that the impact caused to crude oil price varies with the region. Most importantly, the model introduced using the RF technique provides a high predictive ability in short horizons such as infectious diseases. This study delivers future directions and insights to researchers and practitioners to expand the study further.

This is one of the few available pieces of research which uses the RF method in the context of crude oil price forecasting. Additionally, this study examines international COSC in the events of emergencies, specifically disease outbreaks using machine learning techniques.

Climate change is occurring around us and impacting on our daily lives, meaning that we have to deal with our cities in a different way. There is also increasing awareness of the need for daily contact with green spaces and the natural environment in order to live a happy, productive and meaningful life.

This reflective essay tells the narrative of how urbanisation has been disconnecting humans from nature. Non-sustainable, non-resilient patterns of urbanisation, along with the neglect of inner-city areas, have resulted in fragmentation and urban decline, led to a loss of biodiversity, and caused the deterioration of ecosystems and their services. Urban regeneration projects allow us to “repair” and restore some of this damage whilst enhancing urban resilience. Connecting existing and enhanced ecosystems, and re-establishing ecosystems both within cities and at the peri-urban fringe is vital for strengthening ecosystem resilience and building adaptive capacity for coping with the effects of climate change.

Cities worldwide need to look for suitable solutions to increase the resilience of their urban spaces in the face of climate change. This essay explores how this can be achieved through the integration of nature-based solutions, the re-greening of neighbourhoods and by correctly attributing value to natural capital. Transforming existing cities and neighbourhoods in this way will enable ecosystems to contribute their services towards healthier and more liveable cities.