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The present study is motivated by the need to decouple economic growth from environmental degradation given the new wave of chase for higher economic growth trajectories comes with its environmental cost implications, especially among developing blocs like the Emerging 7 (E7) countries. There is a consistent trade-off between economic growth versus environmental quality. Government apparatus are perpetually on the chase for low-carbon emission policies via the pursuit for green economy. To this end, this present study extends the conventional environmental Kuznets curve (EKC) argument by incorporating the role of institution in emerging industrialized economies (E7) and using second-generation panel analysis methods like mean group (MG), augmented mean group (AMG), common correlated effects mean group (CCEMG), and the Dumitrescu and Hurlin causality test for more robust estimates and inferences. To this end, we explore the long-run and causality relationship between economic growth, quadratic form of economic growth, institutional quality, trade flow, investment in energy sector, and financial development in an EKC environment. Empirical analysis established a long-run equilibrium relationship among the outlined variables over the study period. The long-run regression shows the presence of EKC in the E7. Thus, suggesting the preference for GDP growth over environmental quality at the earlier stage of growth curve. Interestingly, investment in energy, trade flow dynamics across the blocs, and financial development dampens the detrimental effect of environmental pollution as we observed negative relationship with the ecological footprint. On the contrary, quality of institution is weak as institutional quality increase (worsen) the quality of environment in the E7 economies. From a policy perspective, this current study proposed the need for more stringent environmental treaties and regulations and promotion of green economy without compromising economic growth. In the conclusion part of the study, more details and specifics about the policy blueprint are presented.

The potential for global forest cover The restoration of forested land at a global scale could help capture atmospheric carbon and mitigate climate change. Bastin et al. used direct measurements of forest cover to generate a model of forest restoration potential across the globe (see the Perspective by Chazdon and Brancalion). Their spatially explicit maps show how much additional tree cover could exist outside of existing forests and agricultural and urban land. Ecosystems could support an additional 0.9 billion hectares of continuous forest. This would represent a greater than 25% increase in forested area, including more than 200 gigatonnes of additional carbon at maturity.Such a change has the potential to store an equivalent of 25% of the current atmospheric carbon pool. Science , this issue p. 76 ; see also p. 24

Abstract Both steady-state AC and DC power flow models are commonly used for techno-economic studies of power systems. The DC-based approach limits the computational burden by assuming small-angle approximation, ignoring power losses, reactive power flows, and voltage variations. It, therefore, matters to understand if this approach affects system vulnerability, reliability, and contingency assessments. To this aim, we use the time-sequential Monte Carlo simulation and an N-k′-1 scenario for reliability and contingency analyses, respectively. Further, we introduce a new index for vulnerability assessment. The IEEE reliability test system (RTS) and the modified RTS are modeled. The results show that the DC model underestimates the reliability indices by about 20% and more than 90% in a stressed network. We also show a small error of 5%, owing to the assumptions of the DC model, which can lead to inaccurate simulations concerning the cascading failures. Finally, the sources of the inaccuracy in the DC-based model are investigated. The results prove that AC power flow model should be privileged for the line capacity-based assessments.

Abstract In the Swiss canton of Geneva, an energy efficiency portfolio has been operated since 2009. In contrast, such programs have been in place for more than 40 years in the US. There are numerous lessons to be learnt from their experience. We have therefore conducted a comparative analysis including Geneva and 11 leading states in the US, with the objective to identify explanatory factors for the success of energy efficiency programs. First, we compared total investment in energy efficiency programs between 2006 and 2015 and public policies related to energy efficiency in each state. Second, we analyzed the levelized cost of saved energy (LCSE) of the programs from the perspective of program administrators. Our cost-effectiveness analysis showed that the program investment scale has been strongly influenced by i) the existence of public mandates, which require program administrators to set ambitious targets and maximize their investment in cost-effective energy efficiency measures, ii) financial instruments that ensure program expenditure to be recovered, and iii) complementary funding from other programs. Moreover, learning and accumulated experience of the program administrators allow to reduce the LCSE. We conclude that the combination of financial instruments with public mandates can ensure a high level of effectiveness.

Abstract In its 2016 Heating and Cooling Strategy, the European Commission (EC) highlighted the strategic importance of heating demand for the energy demand reduction, and further noted that District Heat Networks (DHN) can play an important role in decarbonising this sector. This study applied a thermal atlas approach to map the potential for district heat networks in Switzerland. It extended existing methods with a novel approach to estimating linear thermal demand density in DHN at a national scale. DHN potential for current-generation high temperature networks as well as cutting-edge low temperature networks were compared for current building space heating and hot water demand as well as for two demand reduction scenarios. The method was tested by comparing its results to those of a local engineering study conducted for a Swiss municipality (Brig-Glis). The potential percentage of demand supplied by high temperature DHN was shown to decrease from 66% to 41% with energy saving while the potential for low temperature systems increased significantly from 2.1% to 42%. The percentage of heat demand covered by heat networks decreases less than the percentage of buildings covered, reflecting the strength of heat networks for supplying large fractions of thermal demand in geographically confined areas.

Abstract The implementation of energy efficiency measures is an effective way to gain energy savings in the Italian residential sector. This paper assesses the embodied energy impact related to the envelope insulation and evaluates the energy and carbon payback of the efficiency measures. The proposed method consists of (1) an estimation of the baseline operational energy consumption, (2) simulations of realistic retrofit solutions and, (3) the assessment of the ‘retrofitting’ embodied energy and the energy and carbon payback time calculation. The payback is based on the comparison between the saved operational energy and the embodied energy of the materials selected for insulation. Ten Italian cities are analysed, and the results show a deep dependence on the climate zone. In Northern Italian cities, envelope insulation gains relevance as the energy and carbon payback periods are shorter, about 3 years against the 84 years for the Southern city of Palermo. The optimal thickness is estimated for the city of Milan considering the building’s typology, the insulation materials, and the energy payback. This study shows how the total energy savings can be used as a criterion to obtain design indications.

Shallow Geothermal Systems (SGS) are widely used to provide low-cost heating and cooling of residential and commercial buildings. SGS can be an economically-viable solution even for commercial buildings, where controlled temperature is fundamental for the production processes. To assess the thermal resistance of the soil and the performance of a SGS, Thermal Response Tests (TRT) must be performed. TRT machines are today designed mainly for short term monitoring, for relatively deep SGS (up to 200 m) and for being used by expert operators. Lightweight, low-cost machines for both fast and long term, reliable and unattended TRT for very Shallow Geothermal Systems (vSGS) are not available today. This paper describes the design of a micro-TRT machine (mTRT) for vSGS, which is gaining interest in the civil engineering, environmental, energy and food chain sectors. The paper describes the features of the wireless monitoring system, the design choices to achieve the required accuracy and the software developed for adding remote control capability. Experimental validation in a real test field demonstrates the quality of measurements collected for analysing the TRT data.

AbstractDigitalization and sustainability have been the core drivers of transformation of the financial industry in recent years. In this context, green fintech plays a major role, which, however, is still an unexplored field in business, information systems and finance research. This paper conducts a systematic literature analysis and develops a research agenda based on a framework, which is derived from clustering 74 academic research papers. The framework consists of the four clusters strategy, organization, technology, and potentials along nine dimensions. The research agenda reveals that green fintech is still a very premature field of research. The analysis shows that areas like customer‐ and government‐related services, insurance‐oriented approaches and SDGs which focus on life on land and life below water are still rare and that most of the approaches focus on blockchain technology, while other financial technologies like artificial intelligence are still underrepresented.