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Abstract This study investigates the non-linear relationship between urbanization paths and CO2 emissions in selected South, South-East, and East Asian countries over the period 1971–2014. Based on the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework, we applied the advanced and robust methods of dynamic seemingly unrelated regression (DSUR), dynamic OLS (DOLS), and fully modified OLS (FMOLS) to estimate the long-term effects. The empirical findings revealed the inverted U-shaped effects of urbanization and urban agglomeration and the U-shaped impact of the largest city ratio on CO2 emissions. Urbanization and urban agglomerations improve environmental quality in the long-run and support ecological modernization theory. However, excessive concentration in the largest cities have severely affected the environmental quality and violates the notion of compact-city efficiencies. Moreover, energy intensity and economic growth positively affect CO2 emissions, while trade openness negatively influences CO2 emissions. Our robustness analysis at the country-level applies the augmented mean group (AMG) panel ARDL technique, which further supports the non-linear effect of urbanization paths on CO2 emissions except for a few countries. The results of the panel Granger non-causality approach unveil bidirectional causality of energy efficiency, economic growth, urbanization, and largest city ratio with CO2 emissions. In contrast, unidirectional causality runs from urban agglomeration to CO2 emissions. Our findings have important policy implications as we suggest green urban infrastructures, eco-friendly dwellings, smart cities, country-specific trade policies, and renewable energy options to improve the environmental quality.

Abstract Socio-technical transformations towards low-carbon energy systems are on the way in developed countries. Conversely, developing countries tend to be locked in fossil fuels and foster coal-based energy structures, emphasizing reliable and cost-effective energy provision and sidelining environmental concerns. In this study, we identified and analysed the predominant factors related to coal-based power generation in Bangladesh. We applied a mixed-method approach, initially conducting a systematic literature review and, subsequently, semi-structured expert interviews to identify and validate relevant factors. We then assessed their relative importance using an Analytical Hierarchy Process based on expert judgments. The results of this assessment reveal that socio-economic aspects and environmental issues scored highest, while technological aspects and sector regulations were considered to be less relevant for large-scale coal power implementation. We conclude that future energy policies created in Bangladesh will need to use appropriate legal instruments and address issues such as human displacement and resettlement, low levels of public acceptance, health hazards and environmental pollution. Participative policy frameworks should be deployed in coal plant projects, and active monitoring systems are necessary to reduce the negative consequences associated with increased electrification and energy consumption. To address foreseeable structural challenges, it furthermore will be crucial to explore sustainable alternatives.

Abstract As a burgeoning theoretical framework, energy justice has been mostly focused on the energy transition in Western countries, where socio-political settings are largely featured by liberalism and democracy, leaving an obvious gap in its application in other socio-political contexts. As a major energy consumer and a leader of the global low-carbon transition, China is characterized by a distinctive socio-political regime. An array of grand strategies to transform its coal-dominant energy structure have been initiated to ameliorate deteriorating environmental crises in particular and materialize a low-carbon transition in general. Based on extensive evidence, this article incorporates the energy justice framework into the analysis of an ongoing energy transition project in rural Northern China. It contributes to the related research in three dimensions. First, empirically, it demonstrates that the coal-to-gas heating transition project has been swamped with social injustices; the absence of measures to address these would lead this mega-project to profound failure. Second, theoretically, it illustrates that the concerns of justice are even more paramount in an authoritarian context where policy processes are characterized by strong political-administrative intervention and the pursuit of efficiency at all cost. In light of this, it stresses the indispensable role of restorative justice as a core tenet in achieving energy justice in authoritarian socio-political contexts, such as China. Third, this study advocates expanding the evaluation parameters of authoritarian environmentalism to include social consequences.

Abstract Building energy performance is often inadequate given design goals. While different types of assessment methods exist, they either do not consider design goals and/or are not general enough to integrate new and innovative energy concepts. Furthermore, existing assessment methods focus mostly on the building and system level while ignoring more detailed data. With the availability and affordability of more detailed measured data, the increased number of measured data points requires a structure to organize these data. This paper presents the Energy Performance Comparison Methodology (EPCM), which enables the identification of performance problems based on a comparison of measured data and simulated data representing design goals. The EPCM is based on an interlinked building object hierarchy that structures the detailed performance data from a spatial and mechanical perspective. This research is developed and tested on multiple case studies that provide real-life context and more generality compared to single case studies.

Abstract The central role of occupants for achieving energy savings in residential buildings is increasingly recognised. Simulation programmes able to take into account occupant behaviour are considered to be powerful tools for bridging the gap between the predicted and the actual energy consumption for new buildings. Nevertheless, the majority of residential buildings that will constitute the housing stock in 2050 have already been built today, therefore occupant behaviour and building simulation tools need to be fully exploited for supporting the renovation of existing housing stock. The aim of this paper is to explore the role of occupant behaviour modelling in supporting decision-makers dealing with the design of renovation strategies for residential buildings. An Italian multi-family public housing building is assumed as case study to estimate the influence of three dimensions linked with occupant behaviour – management of the thermostat, management of the heating system, variation of building characteristics – on energy heating consumption. The results show that, while the occupant behaviour influences the heating loads up to 1/3 in case of high level of building retrofit, the less the building is renovated, the higher is the behavioural impact in absolute terms of energy reduction. Therefore, in order to be effective, renovation strategies are required to design appropriate informative instruments at an early stage to support behaviour changes towards responsible energy consumption.

The oil industry is extremely important to China's overall economic growth, fiscal stability and international trade. But oil industry reforms have been undertaken slowly and gradually. In 1994 the government reimposed central control over its oil industry by fixing the price of crude and petroleum products, and channelling virtually all sales through state agencies. This move marks a temporary retreat from the ongoing experiment with oil deregulation, which picked up speed since 1992. For as long as it lasts, this renewed central recontrol over oil prices and distribution will create increased uncertainty for foreign participation.

Abstract This paper aims to investigate sustainable waste management solutions for the city of Rio de Janeiro in Brazil, based on a life cycle approach. The Life Cycle Assessment (LCA) was performed by using the LCA-IWM methodology. The model was adapted to the Brazilian solid waste context and to the local characteristics, including waste composition, electricity mix and regulations. The annual amount of waste generated was the functional unit adopted. Eight municipal solid waste management strategies were evaluated. Scenarios including mixed waste collection and source separated collection as well as materials recovery and energy from waste were investigated. Scenarios were ranked based on the LCA results. Sensitivity analysis was carried out by varying the electricity mix. The results indicate that the current situation of municipal solid waste (MSW) in Rio de Janeiro presents the worst performance in terms of aggregated environmental burdens, indicating the urgency for implement new strategies toward a more environmentally friendly and sustainable MSW management system. It is noted that the better LCA performances were obtained in scenarios with high separately collection rates. Among them, the scenario based on recyclables recovery and anaerobic digestion shows to be a promising strategy to improve environmental sustainability. Sensitivity analysis demonstrates that the ranking of scenarios was not affected by changes in the electricity mix. From the results, the investment in source separated waste collection and materials recovery is the most environmentally friendly MSW strategy for Rio de Janeiro. In addition, scenarios with an emphasis in materials recovery presented higher environmental benefits than the alternatives focused on energy generation.

Abstract In recent years living walls have increasingly spread, thus becoming a diffuse architectural envelope cladding technology. Consequently, a more precise understanding of their thermal behavior and impact on the building energy balance are needed. One of the most important effects provided by the use of living walls is the shading of the building envelope, with clear benefits during the cooling period. Furthermore, many features characterize the thermal behavior of living walls, namely plant species, leaf area index (LAI), evapotranspiration, emissivity and air cavity type. All these particular characteristics have been accounted in the mathematical model developed in the frame of the presented research, whose aim is to provide a tool for the prediction of the thermal behavior of living walls. Two kinds of living walls, one with grass and closed air cavity and the other one with vertical garden and open air cavity were considered. The results achieved by means of the developed model show a good agreement with the measurements also supported by model efficiency indexes such as Nash–Sutcliffe efficiency index (NSEC). Values of around 0.7 were obtained for the NSEC index for both the investigated living walls.

Following the environmental crises of recent decades, a turning point in the awareness of the fragility of ecosystems has been marked, i.e., environmental awareness. This has contributed to the development of various environmental laws and regulations such as the “Waste Electrical and Electronic Equipment,” the “Restriction of Hazardous Substances,” and the “Registration, Evaluation, Authorization and Restriction of Chemicals” regulations and the “Energy Using Products” Directives. Our work contributes to the development of eco-friendly product manufacturing processes. In order to estimate and optimize the environmental impacts of a product, most of the methodologies, concepts, and tools that integrate computer-aided design (CAD) and life cycle assessment systems generally exploit the feature technology at the level of each feature independently of the others, i.e., “microplanning.” The feature interaction technology (FIT) is treated only in few studies, but it is pivotal in the eco-manufacturing process. In this paper, we propose a new manufacturing-scenarios-based methodology by using FIT and a Multi-criteria Decision Support Method (MCDSM), which helps manufacturers maintain their marketplaces by producing goods in an eco-friendly way. In fact, this methodology helps designers choose from the CAD design phase the most ecological manufacturing process from possible existent scenarios in real time.