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Mitigating the effects of climate change is a costly affair, as it would require nations to spend trillions of dollars in order to upgrade their infrastructure and move towards a sustainable and low-carbon economy. Public funds alone won’t suffice as investment from the private sector remains essentialin order to meet the enormous funding needs. In order to attract private investment into programs aimed at adaptation and mitigation of climate change, the European Investment Bank in 2007 issued the first ever climate bond to mobilize funds in order to invest in renewable energy projects across Europe. The climate bonds, later dubbed as green bonds, have grown rapidly in the last one decade and may well be able to meet the enormous funding needs required to mitigate the effects of climate change. The following article, thus, aims to highlight the potential of green bonds as a catalyst for sustainable development and explains how its potential can be untapped by removing a few bottlenecks that may hinder its growth and potential in the long run.

This paper discusses the concept of 'sustainable water services' and suggests a multicriteria method to assess it. Although conceptual discussions around this notion are often confined to the triple bottom line (TBL) classification, it seems that the TBL approach does not provide the suitable framework to measure water services sustainability. It is argued that assets (or technical) and governance aspects are also indispensable dimensions. After revisiting the concept in broader terms, several criteria and metrics are suggested to operationalize and quantify the sustainability level of urban water services. To aggregate the numerous aspects that are relevant in this scope a multicriteria decision analysis approach is proposed. Furthermore, to illustrate the real-world application of the method, a multicriteria model applicable to the case of Portugal was developed and calibrated with the input of a decision-maker with extensive experience in the sector. With the suggested framework it is possible to assess the global sustainability level of the water services (e.g. of each utility) and also the performance in each particular dimension ('social', 'environmental', 'economic', 'governance' and 'assets').

Estonia is among the countries with the most energy-efficient Near Zero Energy Buildings (NZEBs) in Europe, i.e. their energy consumption is the lowest. From the energy management prospects, on one hand, the rising price of electricity and decreasing the feed-in prices, and on the other hand, the decreasing price of battery energy storage system (BESS) have made the self-consumption of NZEBs profitable. This paper develops a simple tool to study the optimal sizing of BESS and increase the profitability of NZEBs. The BESS sizing is done considering the installed PV capacity in the NZEB, the energy consumption profile, and the local electricity prices. The results of this paper demonstrate to the NZEB owner and planers that in case of self-consumption, investment in PV systems could be more profitable when it is combined with BESS. Simulation results are presented to validate the proposed BESS sizing tool and analyze the sensitivity of results to changes in electricity and battery system price.

Globalization, digitalization and rapid development of technology have made supply chains more complex than ever before. Complexity has forced many organizations to outsource their warehouse activities to Third-Party Logistics service providers. They, in turn, deploy automatization solutions and tools such as warehouse management system (WMS) software to manage in-house logistics services. However, research into third-party logistics (3PL) and WMS has so far been scarce, especially, regarding WMS and its sustainability supporting aspects. Large-scale outsourcing has recently received increasing attention from high-level decision-makers, in particular as regards the overall sustainability of logistics-related actions and processes. This systematic mapping-based study examines the current state of the art of academic literature considering WMS and its intersections with topics related to sustainability. As a result of the specific focus of the work, only a small set of 22 studies was found to add value to the topic, which opens up additional research opportunities in this direction. The majority of the studies were journal articles (13) rather than conference papers (9). The most frequently used keywords in these studies addressed the topics of WMS, ICT, sustainability, warehouse technology and operations. The content-based analysis revealed five main thematic areas, namely, WMS concept development, optimization and improvement, Internet of Things (IoT) and Industry 4.0, safety, and sustainability. Surprisingly, only one publication was devoted purely to WMS and indices built on the triple bottom line approach. The study considered neither the functions of WMS, nor sustainability-related features of WMS. The remaining studies discussed sustainability mainly from the safety perspective. It is concluded on the basis of this study that there are significant opportunities for further research in WMS and sustainability.

The globe is now in ecological turmoil as a result of the unrelenting increase in global warming. As a result, governments worldwide are committing to decarbonizing the environment, with the United Arab Emirates (UAE) and the Kingdom of Saudi Arabia (KSA) playing an important role in this effort. Hence, this paper evaluates the nonlinear (asymmetric) impact of natural gas consumption on renewable energy consumption and economic growth in the KSA and the UAE utilizing data stretching from 1990 to 2020. The study also considers other drivers of renewable energy consumption and economic growth, such as trade openness and CO2 emissions. The study utilizes nonlinear autoregressive distributed lag (ARDL) to evaluate these associations. The outcomes of bounds nonlinear ARDL (NARDL), affirm the long-run association between the variables in both countries. The nonlinear results show that positive and negative shocks in natural gas consumption have a negative impact on renewable energy in both UAE and KSA. In contrast, positive and negative shocks in natural gas consumption impact economic growth positively. The study proposed vital policy recommendations based on these results.

When attempting to avoid global warming, individuals often face a social dilemma in which, besides securing future benefits, it is also necessary to reduce the chances of future losses. In this manuscript, we introduce a simple approach to address this type of dilemmas, in which the risk of failure plays a central role in individual decisions. This model can be shown to capture some of the essential features discovered in recent key experiments, while allowing one to extend in non-trivial ways the experimental conditions to regions of more practical interest. Our results suggest that global coordination for a common good should be attempted by segmenting tasks in many small to medium sized groups, in which perception of risk is high and uncertainty in collective goals is minimized. Moreover, our results support the conclusion that sanctioning institutions may further enhance the chances of coordinating to tame the planet's climate, as long as they are implemented in a decentralized and polycentric manner.

PurposeThis study aims to explore the relationship among energy consumption, real income, financial development and oil prices in Italy over the period 1960-2014.Design/methodology/approachDifferent econometric techniques – such as the General Methods of Moment (GMM) or the AutoRegressive Distributed Lags (ARDL) bounds test – are usually used in the empirical analysis. Moreover, both the Toda and Yamamoto causality tests and the Granger causality tests are applied to the data.FindingsThe results of unit root and stationarity tests show that the variables are non-stationary at levels, but stationary in first-differences form, or I(1). The ARDL boundsF-test reveals an evidence of a long-run relationship among the four variables at 1% significance level. Moreover, an increase in real GDP and oil prices has a significant effect on energy consumption in the long run. The coefficients of estimated error correction term are also negative and statistically significant. In addition, the paper explores the causal relationship between the variables by using a VAR framework, with Toda and Yamamoto but also Granger causality tests, within both multivariate and bivariate systems. The findings indicate that energy consumption is affected by real GDP.Originality/valueThe study also filled the literature gap of applying ARDL technique to examine this relevant issue for Italy.

Photovoltaic (PV) modules and solar plants are one of the main drivers towards zero-carbon future. Energy communities that are engaging citizens through collective energy actions can reinforce positive social norms and support the energy transition. Furthermore, by incorporating Artificial Intelligence (AI) techniques, innovative applications can be developed with huge potential, such as supply and demand management, energy efficiency actions, grid operations and maintenance actions. In this context, the scope of this paper is to present an approach for forecasting an energy cooperative’s solar plant short term production by using its infrastructure and monitoring system. More specifically, four Machine Learning (ML) and Deep Learning (DL) algorithms are proposed and trained in an operational solar plant producing high accuracy short-term forecasts up to 6 hours. The results can be used for scheduling supply of the energy communities and set the base for more complex applications that require accurate short-term predictions, such as predictive maintenance.