Search Results (54)

From the urban sustainability perspective and from the steps essential for regulating/balancing the microclimate features, the creation and maintenance of urban green spaces (UGS) are vital. The UGS include vegetation of any kind in urban areas such as parks, gardens, vertical gardens, trees, hedge plants, and roadside plants. This “urban green infrastructure” is a cost-effective and energy-saving means for ensuring sustainable development. The relationship between urban landscape patterns and microclimate needs to be sufficiently understood to make urban living ecologically, economically, and ergonomically justifiable. In this regard, information on diverse patterns of land use intensity or spatial growth is essential to delineate both beneficial and adverse impacts on the urban environment. With this background, the present study aimed to address water requirements of UGS plants and trees during the non-rainy months from Panaji city (Koppen classification: Am) situated on the west coast of India, which receives over 2750 mm of rainfall, almost exclusively during June–September. During the remaining eight months, irrigating the plants in the UGS becomes a serious necessity. In this regard, the daily water requirements (DWR) of 34 tree species, several species of hedge plants, and lawn areas were estimated using standard methods that included primary (field survey-based) and secondary (inputs from key-informant survey questionnaires) data collection to address water requirement of the UGS vegetation. Monthly evapotranspiration rates (ET_o) were derived in this study and were used for calculating the water requirement of the UGS. The day–night average ET_o was over 8 mm, which means that there appears to be an imminent water stress in most UGS of the city in particular during the January–May period. The DWR in seven gardens of Panaji city were ~25 L/tree, 6.77 L/m² hedge plants, and 4.57 L/m² groundcover (=lawns). The water requirements for the entire UGS in Panaji city were calculated. Using this information, the estimated total daily volume of water required for the entire UGS of 1.86 km² in Panaji city is 7.10 million liters. The current supply from borewells of 64,200 L vis a vis means that the ET_o-based DWR of 184,086 L is at a shortage of over 2.88 times and is far inadequate for meeting the daily demand of hedge plants and lawn/groundcover. Full article

As the proportion of renewable energy in power system continues to increase, that power system will face the risk of a multi-time-scale supply and demand imbalance. The rational planning of energy storage facilities can achieve a dynamic time–delay balance between power system supply and demand. Based on this, and in order to realize the location and capacity optimization determination of multiple types of energy storage in power system, this paper proposes a collaborative optimization planning framework for multiple types of energy storage. The proposed planning framework is modelled as a two-stage MILP model based on scenarios via the stochastic optimization method. In the first stage, investment decisions are made for two types of energy storage: battery energy storage (short term) and hydrogen energy storage (long term). In the second stage, power system operation simulation is conducted based on typical scenarios. Finally, the progressive hedging (PH) algorithm is applied to realize the efficient solving of the proposed model. A modified IEEE 39-bus test system is used to verify the validity of the proposed multiple types of energy storage collaborative optimization planning model and PH algorithm. Full article

The integration of renewable energy sources (RESs) is rapidly increasing within energy systems worldwide. However, this shift introduces intermittency and uncertainty on the supply side. To hedge against RES intermittency, demand-side flexibility introduces a practical solution. Therefore, further studies are required to unleash demand-side flexibility in power systems. This flexibility is relevant across various sectors of power systems, including residential, industrial, commercial, and agricultural sectors. This paper reviews the key aspects of demand-side flexibility within the residential sector. To achieve this objective, a general introduction to demand flexibility across the four sectors is provided. As a contribution of this paper, and in comparison with previous studies, household appliances are classified based on their flexibility and controllability. The flexibility potential of key residential demands, including heat pumps, district heating, electric vehicles, and battery systems, is then reviewed. Another contribution of this paper is the exploration of demand-side flexibility scheduling under uncertainty, examining three approaches: stochastic programming, robust optimization, and information-gap decision theory. Additionally, the integration of demand flexibility into short-term electricity markets with high-RES penetration is discussed. Finally, the key objective functions and simulation software used in the study of demand-side flexibility are reviewed. Full article

The efficient operation of multi-reservoirs is highly beneficial for securing supply for prevailing demand and ecological flow. This study proposes a monthly hedging rule-based aggregation–decomposition model for optimizing a parallel reservoir system. The proposed model, which is an aggregated hedging rule for ecological flow (AHRE), uses external optimization to determine the total release of the reservoir system based on improved hedging rules—the optimization model aims to minimize water demand and ecological flow deficits. Additionally, inner optimization distributes the release to individual reservoirs to maintain equal reservoir storage rates. To verify the effectiveness of the AHRE, a standard operation policy and transformed hedging rules were selected for comparison. Three parallel reservoirs in the Naesung Stream Basin in South Korea were selected as a study area. The results of this study demonstrate that the AHRE is better than the other two methods in terms of supplying water in line with demand and ecological flow. In addition, the AHRE showed relatively stable operation results with small water-level fluctuations, owing to the application of improved hedging rules and a decomposition method. The results indicate that the AHRE has the capacity to improve downstream river ecosystems while maintaining human water use and provide a superior response to uncertain droughts. Full article

The Brassicaceae genus consists of many economically important mustards of value for food and medicinal purposes, namely Asian mustard (Brassica juncea), ball mustard (Neslia paniculata), black mustard (B. nigra), garlic mustard (Alliaria petiolata), hedge mustard (Sisymbrium officinale), Asian hedge mustard (S. orientale), oilseed rape (B. napus), rapeseed (B. rapa), treacle mustard (Erysimum repandum), smooth mustard (S. erysimoides), white ball mustard (Calepina irregularis), white mustard (Sinapis alba), and Canola. Some of these are commercially cultivated as oilseeds to meet the global demand for a healthy plant-derived oil, high in polyunsaturated fats, i.e., B. napus and B. juncea. Other species are foraged from the wild where they grow on roadsides and as a weed of arable land, i.e., E. repandum and S. erysimoides, and harvested for medicinal uses. These plants contain a diverse range of bioactive natural products including sulfur-containing glucosinolates and other potentially valuable compounds, namely omega-3-fatty acids, terpenoids, phenylpropanoids, flavonoids, tannins, S-methyl cysteine sulfoxide, and trace-elements. Various parts of these plants and many of the molecules that are produced throughout the plant have been used in traditional medicines and more recently in the mainstream pharmaceutical and food industries. This study relates the uses of mustards in traditional medicines with their bioactive molecules and possible mechanisms of action and provides an overview of the current knowledge of Brassicaceae oilseeds and mustards, their phytochemicals, and their biological activities. Full article

Electricity retailers in an electricity market use over-the-counter (OTC) contracts, or bilateral, and spot market purchases to meet the energy demands of their users. In some markets, OTC contracts face issues with price discrimination and accessibility. This study reveals some inefficiencies of OTC contracts in Colombia that expose regulated users—approximately 70% of the national demand—to market risk. This risk is aggravated by the current tariff design. To mitigate these inefficiencies, this article proposes the incorporation of a market maker that will improve the liquidity of existing energy futures in the country. These futures are mechanisms that the retailers could implement to hedge their demand and reduce the adverse effects of market risk. The characteristics of the market maker and a quantitative analysis of its impact are developed in this paper. While the characterization of the problem with its solution is developed with Colombian data, the conceptual framework could be extended to other countries that are concerned about how energy users are being affected by increases in tariffs due to high exposure to spot market price volatility. Full article

Background: This study aimed to conduct a detailed and comparative analysis of body composition and dietary habits in elite swimming and water polo athletes. Through the examination of these key parameters, this study seeks to compare the dietary intake of these two distinct aquatic sports disciplines. Methods: A total of 10 top-level swimmers and 13 water polo athletes participated in anthropometric and body composition assessments, as well as a detailed analysis of nutritional intake. To compare the two groups, an independent samples t-test was used, and variance homogeneity was checked using Levene’s test. The effect size of the group differences was evaluated using Hedges’ g. Results: Water polo athletes showed significantly greater height (189.4 ± 2.9 vs. 186.5 ± 2.0 cm, p = 0.013), body mass index (24.3 ± 1.4 vs. 22.1 ± 0.5 kg/m², p < 0.001), fat-free mass (62.9 ± 1.4 vs. 61.1 ± 1.38 kg, p < 0.001), skeletal muscle mass (47.1 ± 1.3 vs. 43.9 ± 1.6 kg, p < 0.001), and overall weight (86.9 ± 6.9 vs. 76.7 ± 2.2 kg, p < 0.001) in comparison to swimmers. Swimmers consumed greater amounts of mean daily energy (60.0 ± 1.0 vs. 39.0 ± 1.0 kcal/kg, p < 0.001), carbohydrate (7.8 ± 0.3 vs. 4.4 ± 0.5 g/kg, p < 0.001), protein (1.7 ± 0.5 vs. 1.4 ± 0.5 g/kg, p < 0.001), and fat (2.4 ± 0.5 vs. 1.7 ± 0.5 g/kg, p < 0.001) compared to water polo athletes. Conclusion: Our findings highlight the need for differentiated targeted nutritional interventions to enhance athletic performance in different types of water sports. Compared to water polo athletes, swimmers consumed significantly higher amounts of calories, matching their increased calorie demand from their specific training regime. However, this is an observational study and the differential needs of energy and macronutrients in water sports should be confirmed by studies with energy expenditure measurements. Full article

The offshore RMB exchange rate is affected by the supply and demand relationship in the international market, investor sentiment, market liquidity, and other factors, while the onshore RMB exchange rate is mainly affected by government regulation and intervention. Therefore, the offshore RMB exchange rate may be a better reflection of the market’s macroeconomic expectations and risk appetite for China. Stock index futures are mainly affected by macroeconomic factors, so studying the correlation between the offshore RMB exchange rate and stock index futures is helpful for risk management, hedging, and price discovery. In this study, we selected the offshore RMB exchange rate, the volume of stock index futures, and the absolute rate of return as variables of investor sentiment. Through the Granger causality test, impulse response function, and variance decomposition, we studied the correlation between the rate of return of stock index futures and the rate of return of the offshore RMB exchange rate. Furthermore, we constructed a GARCH conditional volatility model. It was concluded that the trading volume and the absolute rate of return of stock index futures could explain the price fluctuations of stock index futures very well. A change in the offshore RMB exchange rate yield causes a change in the yield of stock index futures. Policymakers need to pay close attention to changes in the offshore RMB exchange rate in order to better grasp market trends and manage risks accordingly. Full article

This work considers the incorporation of renewable ammonia manufacturing sites into existing ammonia supply chain networks while accounting for ammonia price uncertainty from existing producers. We propose a two-stage stochastic programming approach to determine the optimal investment decisions such that the ammonia demand is satisfied and the net present cost is minimized. We apply the proposed approach to a case study considering deploying in-state renewable ammonia manufacturing in Minnesota’s supply chain network. We find that accounting for price uncertainty leads to supply chains with more ammonia demand met via renewable production and thus lower costs from importing ammonia from existing producers. These results show that the in-state renewable production of ammonia can act as a hedge against the volatility of the conventional ammonia market. Full article

Natural gas is the most growing fossil fuel due to its environmental advantages. For the economical transportation of natural gas to distant markets, physical (i.e., liquefaction and compression) or chemical (i.e., direct and indirect) monetisation options must be considered to reduce volume and meet the demand of different markets. Planning natural gas supply chains is a complex problem in today’s turbulent markets, especially considering the uncertainties associated with final market demand and competition with emerging renewable and hydrogen energies. This review study evaluates the latest research on mathematical programming (i.e., MILP and MINLP) as a decision-making tool for designing and planning natural gas supply chains under different planning horizons. The first part of this study assesses the status of existing natural gas infrastructures by addressing readily available natural monetisation options, quantitative tools for selecting monetisation options, and single-state and multistate natural gas supply chain optimisation models. The second part investigates hydrogen as a potential energy carrier for integration with natural gas supply chains, carbon capture utilisation, and storage technologies. This integration is foreseen to decarbonise systems, diversify the product portfolio, and fill the gap between current supply chains and the future market need of cleaner energy commodities. Since natural gas markets are turbulent and hydrogen energy has the potential to replace fossil fuels in the future, addressing stochastic conditions and demand uncertainty is vital to hedge against risks through designing a responsive supply chain in the project’s early design stages. Hence, hydrogen supply chain optimisation studies and the latest works on hydrogen–natural gas supply chain optimisation were reviewed under deterministic and stochastic conditions. Only quantitative mathematical models for supply chain optimisation, including linear and nonlinear programming models, were considered in this study to evaluate the effectiveness of each proposed approach. Full article

Decision support systems tackle problems and require systematic planning. They consider physical data, hydrological data, and sediment levels to achieve efficiency and adaptability in various situations. Therefore, this research aims to identify alternative engineering choices for the management of a river basin with a single reservoir system. Optimization techniques, including marine predator algorithm (MPA), genetic algorithm (GA), genetic programming (GP), tabu search (TS), and flower pollination algorithm (FPA), were applied to find the optimal reservoir rule curves using a reservoir simulation model. The study focused on the Ubolratana Reservoir in Thailand’s Khon Kaen Province, considering historic inflow data, water demand, hydrologic and physical data, and sedimentation volume. Four scenarios were considered: normal water scarcity, high water scarcity, normal excess water, and high excess water. The optimal rule curves derived from the reservoir simulation model, incorporating sedimentation and hedging rule (HR) criteria, were found to be the best engineering choices. In the normal and high water scarcity scenarios, they minimized the average water shortage to 95.558 MCM/year, with the lowest maximum water shortage 693.000 MCM/year. Similarly, in the normal and high excess water scenarios, the optimal rule curves minimized the average excess water, resulting in a minimum overflow of 1087.810 MCM/year and the lowest maximum overflow 4105.660 MCM/year. These findings highlight the effectiveness of integrating optimization techniques and a reservoir simulation model to obtain the optimal rule curves. By considering sedimentation and incorporating HR criteria, the selected engineering alternatives demonstrated their ability to minimize water shortage and excess water. This contributes to improved water resource management and decision-making in situations of scarcity and excess. Full article

The decarbonisation of the electricity grid is expected to create new electricity flows. As a result, it may require that network planners make a significant amount of investments in the electricity grids over the coming decades so as to allow the accommodation of these new flows in a way that both the thermal and voltage network constraints are respected. These investments may include a portfolio of infrastructure assets consisting of traditional technologies and smart grid technologies. One associated key challenge is the presence of uncertainty around the location, the timing, and the amount of new demand or generation connections. This uncertainty unavoidably introduces risk into the investment decision-making process as it may lead to inefficient investments and inevitably give rise to excessive investment costs. Smart grid technologies have properties that enable them to be regarded as investment options, which can allow network planners to hedge against the aforementioned uncertainty. This paper focuses on key smart technologies by providing a critical literature review and presenting the latest mathematical modelling that describes their operation. Full article

This paper examines how the initiation of credit default swap (CDS) trading affects the product market competition faced by the referenced firms in the US. The trading of CDS provides an avenue for creditors to hedge default risks, thereby weakening the incentives to monitor the borrowers. Our paper shows that the trading of CDS increases firm-level product market competition because a reduced creditor monitoring effect can lead to growing shareholder demand for information disclosure, revealing strategic information that may undermine the product market competency of the firm when disclosed. While prior literature shows that CDS-traded firms increase both the likelihood and frequency of earnings forecasts as a direct response to shareholder demand, we observe that firms made their mandatory disclosure (i.e., Form 10-K) less readable as a potential way to reduce strategic disclosure. We also find that the presence of institutional investors generally reduces a firm’s competition, but this positive effect is overturned in the presence of CDS trading. Full article

This study points out a new explanation of the non-trading effect of financial derivatives from the perspective of hedging demand. We examine the influence of hedging demand on the non-trading effect of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) Futures. By dividing the sample period into trading period and non-trading period and testing the difference between the risk premiums in these two intervals, we find that there is a non-trading effect in TAIEX Futures, which means that the holding returns of TAIEX Futures in the non-trading period are higher than those in the trading period. By estimating a dummy-regression model, the evidence shows that when the VIX (Taiwan Index Option Volatility Index) indicator is relatively high, the non-trading effect will be more significant, indicating that the non-trading effect may come from investors’ hedging needs. In addition, it is found that when the futures index is higher than the spot index, the non-trading effect becomes less obvious. The possible reason is that when there is a positive spread in index futures, investors will expect a bull market, thus reducing the hedging demand of index futures. In the end, we find that the liquidity in the after-hours trading session is poor, resulting in high hedging costs, and forcing investors to hedge during the regular trading period. Therefore, the after-hours trading of TAIEX Futures fails to reduce the non-trading effect. Full article

This study attempts to examine the existence of interdependencies between specific stock market indices, exchange rates and crude oil for the period January 2021 to July 2022 with daily data. In the period we have chosen, the post-vaccination phase against COVID-19, as well as the war in Ukraine, is covered. The variables selected for this study are RTSI, Eurostoxx, S&P 500, EUR/USD and RUB/USD exchange rates and crude oil prices. The selection of the specific variables was made because they are directly related to the pre-war period that coincides with the post-vaccine period of the pandemic, which allowed us to characterize it as the normal period and to characterize the period of the war in Ukraine that coincides with the energy crisis as the unstable period. In this way, the present study covers the markets of Russia and other developed economies. For empirical purposes, we applied a wavelet coherence approach in order to investigate the possible existence of simultaneous coherence between the variables at different times and scales for all the considered times. The findings of the study reveal the existence of strong correlations between all variables, during different time periods and for different frequencies during the period under review. Of particular interest is the finding that shows that during the crisis period, the RTSI significantly affects both the European and American stock markets, while also determining the evolution of the Russian currency. In addition, it appears that capital constraints in the Russian stock market, combined with increased demand for crude oil, determine the interdependence between RTSI and crude oil. Finally, an interesting finding of the study is the existence of a negative correlation between the US stock index and crude oil in low-frequency bands and the RTSI and Eurostoxx with crude oil for the post-vaccination and pre-war periods in the medium term. These findings can be used by both investors and portfolio managers to hedge risks and make more confident investment decisions. In addition, these findings can be used by policy makers in the planning of regulatory policies regarding the limitations of the systemic risks in capital markets. Full article