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This paper aims to assess the relationship between energy poverty and the well-being of people using Amartya Sen’s capability approach to development as theoretical underpinning.

The study uses household-level energy access data collected by the Harvard Dataverse in 2015 and 2018. The authors use multidimensional indices to measure energy poverty and well-being. Further, the authors apply quantile regression approach to measure the relationship between energy poverty and well-being.

The study’s findings reveal that energy poverty and well-being are negatively related. India has made progress in reducing energy poverty and improving well-being during the study period. However, progress in reducing energy poverty is largely due to improved access to electricity and improvement in well-being due to income and financial inclusion. Using modern cooking fuel has a greater negative impact on well-being compared to lighting using electricity. Further, households spending a greater proportion of their income on modern energy fuels leads to a lower quality of life as it precludes them from using it for other purposes. The study records wide variations in the observed relationship between energy poverty and well-being across various socioeconomic groups.

This calls for improvement in the production and distribution of modern energy resources, which have substantial welfare implications.

This is the first study to measure the relationship between energy poverty and quality of life using multidimensional indices. The findings of this paper have policy implications for the pricing of energy resources and energy access measures.

The study aims to examine the potential benefits of integrating nature-based solutions (NbS) in the housing sector.

The approach adopted was a systematic literature review aided by the Preferred Reporting Items for Systematic Reviews criteria and the VOSviewer software. Abductive reasoning was used to analyze the collected data, which was then subjected to content analysis through an iterative read-and-review procedure.

The study identified green walls, indoor greenery, porous pavement and landscaping, rainwater harvesting and water purification and green roofs as elements of buildings where NbS should be incorporated. Although nature-based research on integrated greenery facades and roof applications was noted, rainwater harvesting and water purification-oriented research remained dominant. These findings demonstrate the advantages of implementing NbS in the housing sector, including energy efficiency, environmental development, flood prevention and sustainable water management. Integrating NbS into housing designs can considerably contribute to the creation of more resilient, eco-friendly and comfortable living environments. However, the adoption of NbS faces hurdles, including a lack of awareness, limited policy support and economic constraints.

This study recommends that NbS be mainstreamed into housing development and knowledge exchange opportunities between sub-Saharan Africa and Europe, as well as other regions, to promote the adoption of NbS through research and collaborations. Also, it contributes to the discourse of sustainable affordable housing in the Global South while addressing United Nations Sustainable Development Goals 11, 12, 13 and 15. This study offers valuable guidance to stakeholders, thereby fostering the development of more sustainable and resilient housing practices and policies.

The study used VOSviewer software visualization to identify structural patterns and track prominent research frontiers, allowing for a more thorough yet concise mapping and capture of a scientific knowledge domain.

This paper aims to develop a framework for the bioaccounting measurement of environmental assets based on natural wealth sustainability. Specifically, this paper proposes a theoretical structure for qualitative and quantitative organization-level assessments of the existence and circulation of water, air, wildlife, flora, soil and subsoil resources.

This research used an inductive method with a qualitative and quantitative approach. The authors postulate a systemic and comprehensive bioaccounting measurement of environmental assets, including heterogeneous and homogeneous methods and quantitative and qualitative valuations of the resources that comprise environmental assets.

The authors describe a theoretical structure for the bioaccounting measurement of environmental assets based on the sustainability of natural wealth through heterogeneous and homogeneous measurement methods and show how to integrate these assets through an homogeneous method.

The development of this general theoretical structure will require the integration of theoretical, conceptual and technical developments from multiple disciplines. The authors hope that the scientific community will evaluate and study this proposal for faster progress towards its practical implementation in organizations.

The authors structured the bioaccounting measurements, which are presented individually for each class of environmental assets. Each of these assets requires subcategories (accounts, subaccounts and resources) and recognition/measurement units. Environmental value units (EVUs) are used to standardize the plurality of measurement units.

This paper aims to examine the impacts of unstable off-farm employment on the probability and stability of farmland rent-out and explore its mechanisms.

The paper adopts Ordinary Least Squares (OLS), Probit, Tobit, Order probit models with two-way fixed effects to conduct empirical analysis based on the balanced panel data collected in 2016 and 2023 with a national representativeness sample of 1,206 rural households in 100 villages across 5 provinces in China.

The empirical results showed that unstable off-farm employment had negative effects on the probability of farmland rent-out, but it had no effects on the stability of farmland rent-out. The mechanism analysis showed that unstable off-farm employment affected the probability of farmland rent-out by decreasing the probability of purchasing houses in city and endowment insurance with high pension. Heterogeneity analysis indicated that the negative effect of unstable off-farm employment was much larger for the households with higher share of labor engaging in off-farm employment outside home county, elder members in the households and those located in the villages of mountain areas.

This paper is the first to define the unstable off-farm employment from the perspective of incontiguous off-farm employment for several years, which could capture the normality rather than particular case in a certain year of off-farm employment among rural labors. Using these new measurements of unstable off-farmland, this paper examined the impacts and mechanisms of share of unstable off-farm employment on the probability and stability of farmland rent-out.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail. The operating environment of the high-speed rail is complex, and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters, perimeter intrusion and external environmental hazards. The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.

In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments, the research status is elaborated, and the latest research progress and achievements of the team are introduced. This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological, perimeter and external environmental situation perception methods for high-speed rail operation.

Based on the technical route of “situational awareness evaluation warning active control,” a technical system for monitoring the safety of high-speed train operation environments has been formed. Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters, perimeter intrusion and the external environment on high-speed rail safety. These works strongly support the improvement of China’s railway environmental safety guarantee technology.

With the operation of CR450 high-speed trains with a speed of 400 km per hour and the application of high-speed train autonomous driving technology in the future, new and higher requirements have been put forward for the safety of high-speed rail operation environments. The following five aspects of work are urgently needed: (1) Research the single factor disaster mechanism of wind, rain, snow, lightning, etc. for high-speed railways with a speed of 400 kms per hour, and based on this, study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment, revealing the coupling disaster mechanism of multiple influencing factors; (2) Research covers multi-source data fusion methods and associated features such as disaster monitoring data, meteorological information, route characteristics and terrain and landforms, studying the spatio-temporal evolution laws of meteorological disasters, perimeter intrusions and external environmental hazards; (3) In terms of meteorological disaster situation awareness, research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines; (4) In terms of perimeter intrusion, research a multi-modal fusion perception method for typical scenarios of high-speed rail operation in all time, all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and (5) In terms of external environment, based on the existing general network framework for change detection, we will carry out research on change detection and algorithms in the surrounding environment of high-speed rail.