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The Intergovernmental Panel on Climate Change (IPCC) report that to limit warming to 1.5 °C, Bioenergy with Carbon Capture and Storage (BECCS) is required. Integrated assessment models (IAMS) predict that a land area between the size of Argentina and Australia is required for bioenergy crops, a 3–7 time increase in the current bioenergy planting area globally. The authors pose the question of whether vertical farming (VF) technology can enable BECCS deployment, either via land sparing or supply. VF involves indoor controlled environment cultivation, and can increase productivity per unit land area by 5–10 times. VF is predominantly being used to grow small, high value leafy greens with rapid growth cycles. Capital expenditure, operational expenditure, and sustainability are challenges in current VF industries, and will affect the ability to utilise this technology for other crops. The authors argue that, whilst challenging, VF could help reach wider climate goals. Application of VF for bioenergy crops could be a game changer in delivering BECCS technologies and may reduce the land footprint required as well as the subsequent associated negative environmental impacts. VF bioenergy could allow us to cultivate the future demand for bioenergy for BECCS on the same, or less, land area than is currently used globally.

Climate change, environmental degradation, and limited resources are motivations for sustainable forest management. Forests, the most abundant renewable resource on earth, used to make a wide variety of forest-based products for human consumption. To provide a scientific measure of a product’s sustainability and environmental performance, the life cycle assessment (LCA) method is used. This article provides a comprehensive review of environmental performances of forest-based products including traditional building products, emerging (mass-timber) building products and nanomaterials using attributional LCA. Across the supply chain, the product manufacturing life-cycle stage tends to have the largest environmental impacts. However, forest management activities and logistics tend to have the greatest economic impact. In addition, environmental trade-offs exist when regulating emissions as indicated by the latest traditional wood building product LCAs. Interpretation of these LCA results can guide new product development using biomaterials, future (mass) building systems and policy-making on mitigating climate change. Key challenges include handling of uncertainties in the supply chain and complex interactions of environment, material conversion, resource use for product production and quantifying the emissions released.

Bridges in Ukraine are one of the most important components of the infrastructure, requiring attention from government agencies and constant funding. The object of the study was the methodology for quantifying the condition of bridge components. The Artificial Neural Network-based (ANN) tool was developed to quantify the technical condition of bridge components. The literature analysis showed that in most cases the datasets were obtained during the inspection of bridges to solve the problems of assessing the current technical condition. The lack of such a database prompted the creation of a dataset on the basis of the Classification Tables of the Operating Conditions of the Bridge Components (CT). Based on CTs, five datasets were formed to assess the condition of the bridge components: bridge span, bridge deck, pier caps beam, piers and abutments, approaches. The next step of this study was creating, training, validating and testing ANN models. The network with ADAM loss function and softmax activation showed the best results. The optimal values of MAPE and R2 were achieved at the 100th epoch with 64 neurons in the hidden layer and were equal to 0.1% and 0.99998, respectively. The practical application of the ANN models was carried out on the most common type of bridge in Ukraine, namely, a road beam bridge of small length, made of precast concrete. The novelty of this study consists of the development of a tool based on the use of ANN model, and the proposal to modify the methodology for quantifying the condition of bridge components. This will allow minimizing the uncertainties associated with the subjective judgments of experts, as well as increasing the accuracy of the assessment.

Although the United Nations’ Sustainable Development Goals (SDGs) advocate, through SDG 4 and SDG 10, equitable quality education and the reduction of inequalities within and between countries, respectively, few studies have examined how inequalities in regional sustainability influence higher education. Therefore, this study aims to examine the relationship between regional sustainability and higher education in China using fixed-effects panel modelling. A systematic force framework showing how regional sustainability drives higher education was constructed from economic, social, and environmental perspectives, and the endogeneity in the process of how regional sustainability affects higher education was explored by introducing one-year lagged values as instrumental variables. Our results show that regional sustainability has a significant impact on higher educational attainment in China, with differing effects in the eastern, central, and western regions, respectively. In central China, economic sustainability plays a significant positive role in higher educational attainment; in the western region, economic and social sustainability have stronger positive effects, while environmental sustainability has significantly negative effects. In terms of policy implications, our findings can be used to support regional development policies to promote regional higher education.

We use household survey data and results from a lab-in-the-field experiment to examine the impact of governance perceptions on the cooperativeness of water users in the maintenance of 19 small-scale irrigation schemes in northern Ghana. Cooperativeness is measured by two indicators, one indicator derived from the experiment and the other obtained from the survey. We distinguish the governance perceptions of users into six main components, and regress the two indicators on these six components. We consistently find for both indicators that cooperativeness is lower when users perceive that their water user association (WUA) is more successful in resolving conflicts. We also find that perceptions of accountability, transparency, and participation in governance jointly affect cooperativeness in a positive way, but collinearity problems refrain us from identifying which component(s) do(es) so. Type of leadership—whether or not the WUA leader was democratically elected—does not have a significant effect on cooperativeness, while having received irrigation-related training positively affects cooperativeness as measured by labor contributions to scheme maintenance. We argue that these novel insights can be of great importance for promoting sustainable management of small-scale irrigation schemes, but needs further research to examine its external validity.

COVID-19, caused by a member of the coronavirus family of viruses, has spread to most countries around the world since it was first recorded in humans in China in late 2019. Closing universities and cancelling all face-to-face activities have become a COVID-19 inevitable reality in many parts of the world. Its impact on university programs, particularly to maintain academic standards and quality assurance procedures, has become significantly more challenging and complex. New ways of working digitally, to minimize disruption to daily operations, have also led to enormous anxiety and uncertainty within the student population, and meeting students’ expectations has also become significantly more difficult. This paper reviews actions taken by universities to safeguard high academic standards and quality assurance procedures during this time and appraise the challenges and impacts on students’ academic performance.

Walkability has become a research topic of great concern for preserving public health, especially in the era of the COVID-19 outbreak. Today more than ever, urban and transport policies, constrained by social distancing measures and travel restrictions, must be conceptualized and implemented with a particular emphasis on sustainable walkability. Most of the walkability models apply observation and subjective methods to measure walkability, whereas few studies address walkability based on sense perception. To fill this gap, we aim at investigating the perceived neighbourhood walkability (PNW) based on sense perception in a neighbourhood of Brussels. We designed a survey that integrates 22 items grouped into 5 dimensions (cleanness, visual aesthetics, landscape and nature, feeling of pressure, feeling of safety), as well as the socio-demographic attributes of the participants. Using various statistical methods, we show that socio-demographics have almost no effects on perceived neighbourhood walkability. Nonetheless, we found significant differences between groups of different educational backgrounds. Furthermore, using a binomial regression model, we found strong associations between PNW and at least one item from each grouping dimension. Finally, we show that based on a deep neural network for classification, the items have good predictive capabilities (78% of classification accuracy). These findings can help integrate sense perception into objective measurement methods of walkable environments. Additionally, policy recommendations should be targeted based on differences of perception across socio-demographic groups.

This study uniquely employs a fuzzy-set qualitative comparative analysis (fsQCA) technique to account for complex relationships in consumption. The fsQCA technique assumes that relationships are based on a set–subset relationship. This assumption is fundamental when decision-makers are affected by information asymmetry and are, thus, required to jointly evaluate the credibility and reliability of a range of external signals. This issue also affects consumers in markets for cultural goods, where the quality of products is not known with certainty in advance of the purchase decision. Our study uses fsQCA to establish the effect of different quality signals on consumption in the US market for video game software. Our results show that reviews from professional critics alongside brand extension and multi-platform release strategies act as signals of product quality and, therefore, lead to high sales performance.