• Energy Research
• 2021-2025close
• engineering and technology close
• 13. Climate action close
• 9. Industry and infrastructure close
• 14. Life underwater close

Hot flue gas evaporation technology is an effective strategy for zero liquid discharge of desulfurization wastewater. However, there is a potential risk that heavy metals such as Hg may be released from the wastewater during evaporation, disrupting the original balance of the power plant or even exceeding the Hg emission standard. Wastewater evaporation and Hg release behavior were obtained using a single droplet drying system. At an evaporation temperature of 300 °C, approximately 18.5% of Hg was released in the constant wet-bulb temperature period, and the remaining was released in the following evaporation periods. Furthermore, a fixed-bed experiment, in combination with density functional theory calculations, was used to investigate the possible migration mechanisms of released Hg. The results revealed that high HCl concentration, introduced fly ash, and precipitated evaporation products play a crucial role in the fate of Hg, and 85.3% of Hg finally turned into less harmful particulate-bound Hg. This study provides a new and effective strategy for evaluating the migration process of pollutants in wastewater treatment. Moreover, it will serve as an essential reference for advanced wastewater treatment and heavy metals control technologies in the future.

The growing interest in sustainable development is reflected in both the market’s sensitivity to environmental and social issues and companies’ interest in the opportunities that sustainable development objectives provide. SMEs, which account for most of the world’s pollution, have significant resource constraints for a sustainable development. Sharing their scarce resources can help them to overcome these constraints and to gain agility and organisational resilience against uncertainties, but the distrust inherent in belonging to different companies prevents them from sharing the necessary information for coordination purposes. This paper presents a coordination mechanism proposal with information asymmetry to allow independent companies’ resources to be sustainably shared as a technological driver. The proposed distributed coordination mechanism is compared to both a decentralised–uncoordinated and a centralised situation. The interest of the proposal is evaluated by a computer simulation experiment employing mathematical programming models with independent objectives in the Generic Materials and Operations Planning formulation with a rolling horizon procedure in different demand, uncertainty and product scenarios. Competitive improvement is identified for all members for their excess capacity use and their operations planning.

The prediction of gas productivity and reservoir stability of natural gas hydrate (NGH) reservoirs plays a vital role in the exploitation of NGH. In this study, we developed a THMC (thermal-hydrodynamic-mechanical-chemical) numerical model for the simulation of gas production behavior and the reservoir response. The model can describe the phase change, multiphase flow in porous media, heat transfer, and deformation behavior during the exploitation of NGH reservoirs. Two different production scenarios were employed for the simulation: depressurization and depressurization coupled with CO2 exchange. The simulation results suggested that the injection of CO2 promotes the dissociation of NGH between the injection well and the production well compared with depressurization only. The cumulative production of gas and water increased by 27.88% and 2.90%, respectively, based on 2000 days of production simulation. In addition, the subsidence of the NGH reservoir was lower in the CO2 exchange case compared with the single depressurization case for the same amount of cumulative gas production. The simulation results suggested that CO2 exchange in NGH reservoirs alleviates the issue of reservoir subsidence during production and maintains good reservoir stability. The results of this study can be used to provide guidance on field production from marine NGH reservoirs.

Floodplain soils and reservoir sediments are known for their fine-grained structure and rich organic-matter substances; therefore, they are able to sorb metals and other potential pollutants, which is is characteristic of their sink function [...]

The lifetime of offshore foundations is governed by a combination of harsh environmental conditions and complex service loads. The fatigue limit state (FLS) analysis needs to be performed in the time domain to capture the complex phenomenon. This study aims to investigate different parameters and design modifications that can impact the design life of an offshore jacket foundation. An OC4 jacket foundation is designed in industrial software from DNV and reduced to a super-element model. The super-element model is connected to an NREL 5-MW wind turbine designed in Bladed. The time-series loads are used to compute the fatigue damages faced by the foundation during the service life. The impact of soil non-linearity, marine growth, scour size, the mass of the transition piece, and the grouted connection’s design on the dynamic response and fatigue damages are compared. A 30% increase in life was observed by replacing the concrete transition piece with a lightweight steel configuration. The fatigue damages were considerably greater for the inclined pile in the leg grouted connection than for the leg in the pile concept. The study provides a different perspective by analysing the effect of design parameters and design changes in the complex and computationally expensive time-series domain.

AbstractLignocellulose-bearing sediments are legacies of the previously unregulated wastewater discharge from the pulp and paper industry, causing large quantities of toxic organic waste on the Baltic Sea floor and on the bottom of rivers and lakes. Several km2 are covered with deposits of lignocellulosic residues, typically heavily contaminated with complex mixtures of organic and inorganic pollutants, posing a serious threat to human and ecological health. The high toxicity and the large volume of the polluted material are challenges for remediation endeavours. The lignocellulosic material is also a considerable bioresource with a high energy density, and due to its quantity, it could appeal to commercialization as feedstock for various marketable goods. This study sets out to explore the potential of using this polluted material as a resource for industrial production at the same time as it is detoxified. Information about modern production methods for lignocellulosic material that can be adapted to a polluted feedstock is reviewed. Biochemical methods such as composting, anaerobic digestion, as well as, thermochemical methods, for instance, HTC, HTL, pyrolysis, gasification and torrefaction have been assessed. Potential products from lignocellulose-bearing sediment material include biochar, liquid and gaseous biofuels, growing substrate. The use of a contaminated feedstock may make the process more expensive, but the suggested methods should be seen as an alternative to remediation methods that only involve costs. Several experiments were highlighted that support the conception that combined remediation and generation of marketable goods may be an appropriate way to address polluted lignocellulose-bearing sediments. Graphic abstract

The purpose of this study is the fabrication and performance evaluation of a new type of solar humidification–dehumidification (HD) desalination unit to supply sufficient fresh water for a seawater greenhouse in the MAKRAN coast in southeast Iran. In the proposed design, a particular type of air-to-air condenser is used. The cold air coming out of the greenhouse ventilation system (fan and pad) in summer and the cold ambient air in winter is used to supply the required cooling of the system. In this way, when cold air passes over the pipes in air-to-air condensers, condensation of water vapor occurs in the moist air inside the pipes, and fresh water is produced. Greenhouse fans, which have an air flow rate of around 20,000 m3/hr, are used to create this air flow. By fabricating two condensers, each using 42 rows of PVC pipes with a diameter of 75 mm, it is possible to produce 400 L of fresh water per day in a 400 m2 greenhouse. The required heating is provided by the solar farm, which includes 96 square meters of flat plate collectors. The steps of unit fabrication are described in detail in this research. However, the effect of greenhouse air temperature and circulating seawater flow rate on freshwater production, energy consumption, and energy intensity are also investigated. By increasing the flow rate of circulating seawater and decreasing the greenhouse air temperature, the production rate of the system increases. When the hot seawater and greenhouse air temperature are 61.7 °C and 26 °C, respectively, the maximum instantaneous production is estimated to be 80 L/h. The energy intensity of the HD desalination unit is varied between 3192 and 4382 kJ/L, and the gain output ratio of the system is around 0.6. The proposed system can be easily paired with conventional greenhouses employing a fan and pad cooling system and produces around 1.25 (L/m2·day) fresh water.

The bubble point pressure (P b) is a crucial pressure-volume-temperature (PVT) property and a primary input needed for performing many petroleum engineering calculations, such as reservoir simulation. The industrial practice of determining P b is by direct measurement from PVT tests or prediction using empirical correlations. The main problems encountered with the published empirical correlations are their lack of accuracy and the noncomprehensive data set used to develop the model. In addition, most of the published correlations have not proven the relationships between the inputs and outputs as part of the validation process (i.e., no trend analysis was conducted). Nowadays, deep learning techniques such as long short-term memory (LSTM) networks have begun to replace the empirical correlations as they generate high accuracy. This study, therefore, presents a robust LSTM-based model for predicting P b using a global data set of 760 collected data points from different fields worldwide to build the model. The developed model was then validated by applying trend analysis to ensure that the model follows the correct relationships between the inputs and outputs and performing statistical analysis after comparing the most published correlations. The robustness and accuracy of the model have been verified by performing various statistical analyses and using additional data that was not part of the data set used to develop the model. The trend analysis results have proven that the proposed LSTM-based model follows the correct relationships, indicating the model's reliability. Furthermore, the statistical analysis results have shown that the lowest average absolute percent relative error (AAPRE) is 8.422% and the highest correlation coefficient is 0.99. These values are much better than those given by the most accurate models in the literature.