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Cloud data center’s total operating cost is conquered by electricity cost and carbon tax incurred due to energy consumption from the grid and its associated carbon emission. In this work, we consider geo-distributed sustainable datacenter’s with varying on-site green energy generation, electricity prices, carbon intensity and carbon tax. The objective function is devised to reduce the operating cost including electricity cost and carbon cost incurred on the power consumption of servers and cooling devices. We propose renewable-aware algorithms to schedule the workload to the data centers with an aim to maximize the green energy usage. Due to the uncertainty and time variant nature of renewable energy availability, an investigation is performed to identify the impact of carbon footprint, carbon tax and electricity cost in data center selection on total operating cost reduction. In addition, on-demand dynamic optimal frequency-based load distribution within the cluster nodes is performed to eliminate hot spots due to high processor utilization. The work suggests optimal virtual machine placement decision to maximize green energy usage with reduced operating cost and carbon emission.

The current study aims to examine the reverse association between circular economy innovation (CEI) and digital sustainability (DS), as well as the dual mediation of government incentives (GI) among firms. Data was collected through a structured-questionnaire-based survey among financial institutions (banks, insurance, and financial companies) in Pakistan, Malaysia, and China. The study collected data via structured questionnaires in an online survey and analysed the data using partial least squares structural equation modelling (PLS-SEM), to find results. The results revealed that CEI has a two-way relationship with the DS among firms in the defined context. Furthermore, the results confirmed the dual mediating role of GI between CEI and DS among firms. The outcomes can guide the policy makers to focus on the practices of CEI in the settings of the relevant state support schemes, to enhance the practices of DS among firms in emerging markets. The implications of the study are presented at the end of this study.

Spent coffee grounds (SCG) are industrial biowaste resulting from the coffee-brewing process, and they are often underutilized and end up in landfills, thereby leading to the emission of toxic gases and environmental damage. Hydrothermal carbonization (HTC) is an attractive approach to valorize wet biomass such as SCG to valuable bioproducts (i.e., hydrochar). Thus, in this work, the HTC of SCG was carried out in a 500 L stainless steel vessel at 150, 170, 190, 210, and 230 °C for 30 min, 60 min, 90 min, and 120 min and a feedstock to water weight ratio of 1:5, 1:10, and 1:15, and the use of the resulting hydrochar as a solid fuel was evaluated. The results showed that a high energy recovery (83.93%) and HHV (23.54 MJ/kg) of hydrochar was obtained at moderate conditions (150 °C, 30 min, and feedstock to water weight ratio of 1:5) when compared with conventional approaches such as torrefaction. Following this, the surface morphology, functionality, and combustion behavior of this hydrochar were characterized by SEM, FTIR, and TGA, respectively. In short, it can be concluded that HTC is an effective approach for producing solid fuel from SCG and the resulting hydrochar has the potential to be applied either in domestic heating or large-scale co-firing plants.

Cannabis consumption has become the center of much debate globally. The positive public perception of the medicinal benefits of cannabis and the rise of recreational usage of cannabis necessitate dramatic changes in cannabis reform policy. As a consequence, there is an increase in cannabis legalization around the globe, although it is still facing many rejections. It is crucial to understand the factors affecting public acceptance of cannabis use to support the contextualization and success of cannabis legalization. This review aims to address consumer cultural, social and psychological factors regarding the legal use of cannabis. Based on this review, cultures influence the endorsement or rejection of cannabis use depending on political views, religious sentiments and affiliated subcultures (adult, youth and adolescent subcultures). Regarding the social factors, socioeconomic status, measured by income, education level and occupation, is a key determinant of cannabis use. The beliefs opposing cannabis legalization are due to the negative stigma surrounding cannabis use. Nevertheless, growing awareness about the pharmaceutical and therapeutic effects of cannabis has led to an increase in positive attitudes towards cannabis legalization. Thus, dissemination of cannabis use benefits reaffirmed by scientific evidence could be a strategic way to alleviate the public’s negative feedback on cannabis legalization.

This essay introduces the political market framework (PMF) and discusses its implications for understanding local sustainability policy. The PMF conceptualizes public policy related to sustainability as the product of exchange between governmental policy suppliers and voter and interest group policy demanders. After presenting a political market model, the role of political institutions is introduced. Institutions structure exchange relationships by determining transaction costs of searching for mutually beneficial agreements, bargaining over outcomes, and monitoring and enforcing decisions. The central implication for research is the need to account for the moderating role that political institutions play in sustainability policy decisions. A research agenda based on the PMF is advanced. The conclusion addresses the limitations of the framework as well as its implications for policy adoptions, program designs, and individual behavior.

Cycles of boom and bust plague mining communities around the globe, and decades after the bust the skeletons of shrunken cities remain. This article evaluates strategies for how former mining communities cope and strive for sustainability in the decades well beyond the bust, using a case study of Calumet, Michigan. In 1910, Calumet was at the center of the mining industry in the Upper Peninsula of Michigan, but in the century since its peak, mining employment steadily declined until the last mine closed in 1968, and the population declined by over 80%. This paper explores challenges, opportunities, and progress toward sustainability associated with arts-related development in this context. Methods are mixed, including observation, interviews, document review, a survey, and secondary data analysis. We follow Flora and Flora’s Community Capitals Framework to analyze progress toward sustainability. Despite key challenges associated with the shrunken city context (degraded tax base, overbuilt and aging infrastructure, diminished human capital, and a rather limited set of volunteers and political actors), we find the shrunken city also offers advantages for arts development, including low rents, less risk of gentrification, access to space, and political incentive. In Calumet, we see evidence of a spiraling up pattern toward social sustainability resulting from arts development; however impacts on environmental and economic sustainability are limited.

Today, introducing useful and practical solutions to residential load disaggregation as subsets of energy management has created numerous challenges. In this study, an intelligence hybrid solution based on manifold learning and deep learning applications is presented. The proposed solution presents a combined structure of Laplacian eigenmaps (LE), a convolutional neural network (CNN), and a recurrent neural network (RNN), called LE-CRNN. In the proposed model architecture, LE, with its high ability in dimensional reduction, transfers the salient features and specific values of power consumption curves (PCCs) of household electrical appliances (HEAs) to a low-dimensional space. Then, the combined model of CRNN significantly improves the structure of CNN in fully connected layers so that the process of identification and separation of the HEA type can be performed without overfitting problems and with very high accuracy. In order to implement the suggested model, two real-world databases have been used. In a separate scenario, a conventional CNN is applied to the data for comparing the performance of the suggested model with the CNN. The designed networks are trained and validated using the PCCs of HEAs. Then, the whole energy consumption of the building obtained from the smart meter is used for load disaggregation. The trained networks, which contain features extracted from PCCs of HEAs, prove that they can disaggregate the total power consumption for houses intended for the Reference Energy Disaggregation Data Set (REDD) and Almanac of Minutely Power Dataset (AMPds) with average accuracies (Acc) of 97.59% and 97.03%, respectively. Finally, in order to show the accuracy of the developed hybrid model, the obtained results in this study are compared with the results of similar works for the same datasets.

This paper examines a Business Model (BM) from a socio-economic system perspective to discern key factors and understand its interactions resulting in the Scaling of Social Impact (SSI) in Social Entrepreneurship (SE). Previously, studies have explained the importance of the BM in relation to SE. However, there is a lack of empirical studies on how a BM’s transitions through participation of various actors result in the SSI, causing a gap in this field’s research. This research applies a qualitative analysis on a single case study of a Japanese social startup, “mymizu”, the first water refill application platform in Japan. The findings show that collaboration amongst different stakeholders on the initial phase of the BM could increase awareness of responsible consumption, convert into actual users for sustainability, and change their behavior. Secondly, members of society could take on dual roles, both as users and collaborators in the BM, which results in an exponential scaling effect of the Social Impact (SI). This paper contributes towards adding a Participatory Stakeholder (PS) to the ecosystem of the SSI and building a Regenerative BM (RBM) that is relevant in SE towards sustainability.