• Energy Research
• Open Access close
• 12. Responsible consumption close
• 6. Clean water close
• IR close

The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

Iran, endowed with abundant renewable and non-renewable energy resources, particularly non-renewable resources, faces challenges such as air pollution, climate change and energy security. As a leading exporter and consumer of fossil fuels, it is also attempting to use renewable energy as part of its energy mix toward energy security and sustainability. Due to its favorable geographic characteristics, Iran has diverse and accessible renewable sources, which provide appropriate substitutes to reduce dependence on fossil fuels. Therefore, this study aims to examine trends in energy demand, policies and development of renewable energies and the causal relationship between renewable and non-renewable energies and economic growth using two methodologies. This study first reviews the current state of energy and energy policies and then employs Granger causality analysis to test the relationships between the variables considered. Results showed that renewable energy technologies currently do not have a significant and adequate role in the energy supply of Iran. To encourage the use of renewable energy, especially in electricity production, fuel diversification policies and development program goals were introduced in the late 2000s and early 2010s. Diversifying energy resources is a key pillar of Iran’s new plan. In addition to solar and hydropower, biomass from the municipal waste from large cities and other agricultural products, including fruits, can be used to generate energy and renewable sources. While present policies indicate the incorporation of sustainable energy sources, further efforts are needed to offset the use of fossil fuels. Moreover, the study predicts that with the production capacity of agricultural products in 2018, approximately 4.8 billion liters of bioethanol can be obtained from crop residues and about 526 thousand tons of biodiesel from oilseeds annually. Granger’s causality analysis also shows that there is a unidirectional causal relationship between economic growth to renewable and non-renewable energy use. Labor force and gross fixed capital formation cause renewable energy consumption, and nonrenewable energy consumption causes renewable energy consumption.

The united nations educational, scientific and cultural organization (UNESCO) considers the historic urban landscapes as the world heritages. Managing historic city centers and maintaining historic cores are the emerging challenges for sustainable urban planning. Today, the historic cores form an important part of the economic, social, environmental, and physical assets and capacities of contemporary cities, and play a strategic role in their development. One of the most important approaches to the development of central textures, especially in historical and cultural cities, is the sustainable urban regeneration approach, which encompasses all aspects of sustainability, such as the economic, social, cultural and environmental aspects. To maintain sustainability and regeneration of historic cores of cities, it is necessary to provide insight into the underlying characteristics of the local urbanization. Furthermore, the fundamental assets are to be investigated as indicators of sustainable regeneration and drivers of urban development. In the meantime, a variety of research and experience has taken place around the world, all of which has provided different criteria and indicators for the development of strategies for the historic cores of cities. The present study, through a meta-analytic and survey method, analyzing the experience and research reported in 139 theoretical and empirical papers in the last twenty years, seeks to provide a comprehensive conceptual model taking into account the criteria and indices of sustainable regeneration in historic cores of cities. The quality of the survey has been ensured using the preferred reporting items for systematic reviews and meta-analysis (PRISMA).

Water shortage in terms of both physical and economic water scarcity is still a major issue globally. The looming climate change threat has increased the adverse threats to water security in different regions. However, policy solutions to water security vary in different geographical regions and at different scales (local, regional, national, etc.). Understanding the successes and challenges of different policy solutions is critical to scaling-up successful policies and addressing water security holistically. This paper aims to explore the effects of implementing policies at different scales in three different case study contexts: 1. two Counties in California in the USA, 2. the City of Cape Town in South Africa and 3. the Country of Bangladesh. These case studies highlight various implemented policies and their effectiveness in each context. We reviewed relevant research papers consisting of peer-reviewed journal articles, conference proceedings and gray literature using a content analysis approach based on keywords such as water scarcity, water shortage, climate change, policies, interventions and solutions. Based on this cross-case analysis, we present key strategies moving forward, including: reallocation of water based on different community and sector needs, the importance of stakeholders engagement and public awareness, and a need to implement both short and long-term management plans. There is no one-size fits all policy solution to water scarcity. Understanding the context, scale, and cultural environment will be a key to future water security-focused interventions and policies.

The sustainable development goals (SDGs) are required to be achieved by 2030, and measurement indicators are needed to properly visualize individual efforts toward SDGs. Here, we developed a Japanese version of the Sustainability Consciousness Questionnaire (SCQ), the most well-known individual measure of SDGs, and examined its reliability and validity. Three online surveys were conducted with 1,268 Japanese adults. The results of confirmatory factor analysis showed that the Japanese version of the SCQ consists of two single-level factors: sustainability knowingness/attitude and sustainability behavior. These two factors demonstrated sufficient internal consistency by Cronbach's alpha and McDonald's omega coefficient, which ensured measurement reliability. Additionally, cocorrelations with other scales indicated that the higher the level of sustainability knowledge and attitude, the less positive attitude toward climate change and the higher the level of sustainability behavior, indicating the construct validity of these factors. These results indicate that the Japanese version of the SCQ is reliable and valid.

The ever-increasing need of the human beings to energy has brought about concerns regarding the decrease in the amount of energy resources. So, renewable energies have become very important and have obtained a special status in today's world. Using bioethanol as a renewable resource to be blended with other fuels in internal combustion engines has attracted many researchers to itself. Thus, in this study, we assess the amount of bioethanol extracted from cantaloupe waste (Magassi Neishabouri Cultivar) to be used as a fuel. To do so, considering the 15 kg capacity of the device's fermenter, 12 kg of refined cantaloupe sugar syrup and three kilograms of water (with the standard ratio of 4 to 1), i.e. a total of 15 kg of substrate with the brix degree of 20, as well as 75 g of saccharomyces cerevisiae yeast, cultured in standard conditions (5 g of yeast for each kilogram of substrate) were transferred into the fermenter. The tests were conducted in 35 h with three replications and at three different rotation speeds of the fermenter's mixer. Sampling took place every five hours. Fermentation temperature was set as 30 °C and distillation temperature was set to be 78.5 °C which is the standard temperature of bioethanol's boiling point. The results showed that about 49.5 g of bioethanol were extracted from each kilogram of cantaloupe syrup. In comparison to the results obtained by other researchers, it became clear that due to its high sugar level, cantaloupe waste is one of the appropriate options for the production of bioethanol. In addition, considering the rate of the alcohol produced and in order to optimize energy consumption, it was seen that the best speed for the fermenter's mixer, was 120 rpm. Keywords: Bioethanol, Renewable energy, Cantaloupe waste

AbstractSteam Assisted Gravity Drainage (SAGD) as a successful enhanced oil recovery (EOR) process has been applied to extract heavy and extra heavy oils. Huge amount of global heavy oil resources exists in carbonate reservoirs which are mostly naturally fractured reservoirs. Unlike clastic reservoirs, few studies were carried out to determine the performance of SAGD in carbonate reservoirs. Even though SAGD is a highly promising technique, several uncertainties and unanswered questions still exist and they should be clarified for expansion of SAGD methods to world wide applications especially in naturally fractured reservoirs. In this communication, the effects of some operational and reservoir parameters on SAGD processes were investigated in a naturally fractured reservoir with oil wet rock using CMG-STARS thermal simulator. The purpose of this study was to investigate the role of fracture properties including fracture orientation, fracture spacing and fracture permeability on the SAGD performance in naturally fractured reservoirs. Moreover, one operational parameter was also studied; one new well configuration, staggered well pair was evaluated. Results indicated that fracture orientation influences steam expansion and oil production from the horizontal well pairs. It was also found that horizontal fractures have unfavorable effects on oil production, while vertical fractures increase the production rate for the horizontal well. Moreover, an increase in fracture spacing results in more oil production, because in higher fracture spacing model, steam will have more time to diffuse into matrices and heat up the entire reservoir. Furthermore, an increase in fracture permeability results in process enhancement and ultimate recovery improvement. Besides, diagonal change in the location of injection wells (staggered model) increases the recovery efficiency in long-term production plan.