Environmental Performance Research Articles

Multi-Objective Optimization Scheduling of Microgrids Considering Single Use Cost of Energy Storage and Unit Combination Startup and Shutdown Cost

Abstract Microgrids typically consist of various energy resources such as thermal power, solar energy, wind energy, energy storage, and so on. These energy resources have different characteristics and fluctuations. By utilizing the characteristics of different energy resources in a complementary and synergistic manner, their energy utilization efficiency can be promoted and the system stability can be improved. This paper considers the energy storage device in the completion of a single charge and discharge loss, that is, the single-use cost. Special attention to the impact of start-stop costs of unit combinations on microgrid operations. It proposes that in the daily dispatch and operation of microgrids, sinking costs can be reasonably reduced within a reasonable range, and power supply reliability can be appropriately lowered to improve the economic performance of power systems. Using the single-use cost of energy storage devices and the start-stop costs of unit combinations as variables, their impact on the economic operation of isolated microgrids is analyzed. For grid-connected microgrids with the objectives of minimizing operating costs and achieving optimal environmental protection, an optimal balance between economic and environmental performance is achieved through solving by Anti-Entropy weight method and Particle Swarm Optimization combination.

Health burden, environmental decentralization and associated political achievements in China

Environmental pollution has had a negative impact on the population’s well-being, impeding the pursuit of a better standard of living. This study seeks to investigate the impact of environmental decentralization in China on the health burden, thereby expanding research on environmental federalism, health, and welfare. Using panel data from 30 Chinese provinces, the empirical findings show that good environmental performance and moderate economic development significantly reduce the environmental health burden. Notably, as environmental decentralization increases, the impact of environmental performance becomes more pronounced, particularly in terms of environmental administration and monitoring. The effect of environmental performance in reducing health burdens is more visible in the northern and western regions with relatively severe pollution, as well as in the subsample with higher health burdens. Overall, this paper emphasizes the importance of political institutional factors in reducing the health burden.

Do investors benefit from investing in stocks of green bond issuers?

We investigate the environmental and financial performance of portfolios comprising stocks from worldwide green bond issuers compared to matched non-green but otherwise similar portfolios. Portfolios formed by stocks of green bond issuing companies show superior environmental performance, notably reflected in reduced CO2 emissions over the medium to long term. Furthermore, these portfolios exhibit financial performance, as measured by the five-factor model of Fama and French (2015), at least comparable to their non-green counterparts, even outperforming them over a 12-month investment horizon. Overall, investing in stocks of green bond issuers seemingly offers competitive risk-adjusted returns.

Experimental, modeling and optimisation of adipic acid reactive extraction using ionic liquids

Adipic acid (hexanedioic acid, AA) can be utilised as an essential monomer in the production of nylon-6,6 (75 %), but also for urethane foams, fibers, elastomers, tire reinforcements, and synthetic lubricants. Considerable work has been done to develop sustainable biosynthetic processes for its manufacture, especially for adipic acid efficient separation (one of the main challenges for industrialisation). As for scale-up, process optimisation, and thorough engineering mathematical models that describe the system efficiently are required, this study proposes mathematical models for a reactive extraction using ionic liquids as extractants for adipic acid separation to improve the biosynthetic route’s sustainability, efficiency, and environmental performance. Heptane as the solvent and 117.8 g/L [P6,6,6,14][Phos] as the extractant at 2.8 pH of the aqueous phase were the optimum mixture for reactive extraction, resulting in an extraction yield of 97.55 % for adipic acid. The process was modeled using an artificial neural network optimised with a differential evolution algorithm. The optimal model structure had one hidden layer with 20 neurons, and its performance in the testing phase was: explained variance score of 0.974, mean absolute error of 1.917, and coefficient of determination of 0.974.

Bi-level optimal configuration of renewable electricity based heating in substations of district heating systems

District heating systems (DHS) are the largest energy consumers in the building energy sector. Substituting electricity in DHS is a pivotal way to achieve its low-carbon development. Existing studies configure the electric heating equipment on the heat source or load side, ignoring the influence of the thermal characteristics of the heat network on the system design and scheduling operation. The impact of the configuration location of the electric heating equipment on system performance is also not emphasized. This paper proposes a new renewable electricity based heating mode in substations of DHS. A bi-level optimal configuration model based on thermal-electricity synergy is proposed to determine the ideal placement, capacity, and operational planning for these heating equipment. The results show that the proposed model reduces operational and environmental benefit costs by 13.31% and 5.35% during the heating season. Additionally, it lowers the annualized cost by 6.24% and curtails the annual discarded wind/photovoltaic power output by 88.76% through a bi-level optimal configuration model. This method realizes the integration of electrical and thermal energy, enhancing renewable energy consumption while concurrently diminishing operating expenses. Consequently, the heating system achieves superior economic and environmental performance.

Analysis of methane production using peach fruit waste as substrate and sludge from parboiled rice as inoculum: Valorization of agro-industrial waste in Southern Brazil

This research shows an experimental study of methane production using as inoculum and substrate, respectively, the sludge and biowaste from parboiled rice and canned peach industries, both located in Southern Brazil. As main results, the highest biogas generation index was equal to 97.6 mLCH4 in the reactor with a 1.35 S/I ratio, during the initial 12 hours of the experiment. R2 reactor in its turn produced 88.5 mLCH4, with an S/I ratio of 1.7. Therefore, the canned peach industry presents significant opportunities for the implementation of circular economy practices and the utilization of waste for energy production. By converting peach waste into bioenergy and biofuels through processes such as anaerobic digestion, these industries can contribute to the decarbonization efforts and mitigate greenhouse gas emissions. Moreover, canned peach industries can not only enhance their environmental performance but also contribute to the transition toward a more sustainable and energy-efficient future.

Techno-economic evaluation of a hybrid HVAC system combining double-layer pipe-embedded external wall and multi-stage fresh air treatment

Double-layer pipe-embedded external wall (DPEW) offers the advantages of load interception and high-temperature cooling/low-temperature heating. However, complete heating, ventilation, and air-conditioning systems using DPEWs and the combination of DPEWs with organized fresh air supply have not yet been investigated. To address this issue, this study proposes a hybrid HVAC system that combines DPEWs and a multi-stage fresh air handling unit (FAHU) utilizing shallow geothermal energy and ground source heat pumps (GSHPs). A dynamic simulation model of the proposed system is developed in TRNSYS software. A comparison of the energy, economic and environmental performance between the proposed system and a reference fan coil system with single-stage FAHU is performed in an office building in Beijing. The results indicate that the cumulative cooling load and cumulative heating load of the proposed system are 42.3 and 60.7 kWh/m2, respectively. The proposed system utilizes shallow geothermal energy to handle 18 % of the cumulative cooling and heating loads, and high-temperature chilled water/low-temperature hot water provided by an efficient GSHP to handle 60 % of the cumulative cooling and heating loads. The proposed system consumes 5.8 kWh/m2 electricity in summer and 12.1 kWh/m2 electricity in winter, and achieves 30 % annual energy savings compared with the reference system while maintaining the same level of thermal comfort. The discounted payback period of the proposed system is 3.3 years. The CO2 emissions can be reduced by 4.8 kg/m2 annually by implementing the proposed system. This study provides theoretical support and data basis for the design and operation of DPEW systems.

Chemical characterization of green liquor dregs from 16 Swedish pulp and paper mills between 2017 and 2019

Green liquor dregs (GLD) is an alkaline by-product from the pulp and paper industry with a pH between 10 and 14. Today most of the produced GLD in Sweden is landfilled. As a fine-grained alkaline material, it might be possible to use it for acid-generating mining waste remediation. To increase the utilization, quality characteristics and environmental performance need to be determined. In this study samples were collected 5 times from 16 mills during a period of 2.5 years, and were characterized by analyzing dry matter content, loss on ignition (LOI) 550 °C and LOI 950 °C, elemental analysis, pH, electrical conductivity, and calorific value. The results were then evaluated using multivariate statistics (PCA) as well as being compared to other studies and Swedish till. The results show that even if GLD is heterogenous (both within a mill and between different mills) trends can be seen for samples from most mills. When samples do stand out, it is predominately related to the same four mills. Most of the studied parameters showed characteristics favorable for use as a remediant; however, TOC, sulfur, and some of the elements require further study. In general, this study concludes that GLD can be a viable option for the remediation of small orphaned sulfidic mining sites and thus worthy of further studies on the interaction between GLD and acidic mining waste.Overall, GLD can be a good alternative for cost-effective remediation of smaller orphaned mining sites. It is readily available in large quantities, has the qualities needed for remediation of many orphaned acidic mining sites, and can often be locally sourced near the mining site. The use of GLD for mining site remediation is likely also a more sustainable method compared to traditional remediation methods.

Redox-active hydrogel electrolytes for carbon-based flexible supercapacitors over a wide temperature range

Hydrogel electrolytes are attractive for fabricating flexible supercapacitors (FSCs) due to their relatively high ionic conductivity, adjustable mechanical properties, and easy preparation processes. However, they still face challenges such as a narrow operational temperature range due to the presence of abundant free water molecules, and comparatively less favorable electrochemical properties compared to liquid electrolytes. In this study, a redox-active hydrogel electrolyte was synthesized, consisting of polyvinyl alcohol-H2SO4, TiO2 nanoparticles, carbon nanofibers and a mixture of redox-active species (FeBr3, Fe2(SO4)3 and KBr). The addition of thermally stable TiO2 and carbon nanofibers not only increased the thermal stability but also enhanced the ionic conductivity of the hydrogel. The Faradaic reactions of redox-active species during the charging/discharging processes contributed to improved electrochemical performance. Subsequently, binder-free carbon nanofiber@carbon cloth electrodes were prepared by directly growing carbon nanofibers on carbon cloth. By combining the electrodes with the redox-active hydrogel electrolyte, a redox electrolyte-enhanced FSC was assembled. It exhibited a capacitance of 182.8 mF cm−2 at 3.5 mA cm−2, an energy density of 8.3 Wh kg−1, and a capacitance retention of 84.3 % after 5000 charging/discharging cycles. The device was capable of operating under various temperature conditions (0–60 °C) and bending angles (0–180°). Overall, this work provides a novel but facile approach for fabricating FSCs with high electrochemical performance and versatile applications in different environments.

Broad learning system based on maximum multi-kernel correntropy criterion

The broad learning system (BLS) is an effective machine learning model that exhibits excellent feature extraction ability and fast training speed. However, the traditional BLS is derived from the minimum mean square error (MMSE) criterion, which is highly sensitive to non-Gaussian noise. In order to enhance the robustness of BLS, this paper reconstructs the objective function of BLS based on the maximum multi-kernel correntropy criterion (MMKCC), and obtains a new robust variant of BLS (MKC-BLS). For the multitude of parameters involved in MMKCC, an effective parameter optimization method is presented. The fixed-point iteration method is employed to further optimize the model, and a reliable convergence proof is provided. In comparison to the existing robust variants of BLS, MKC-BLS exhibits superior performance in the non-Gaussian noise environment, particularly in the multi-modal noise environment. Experiments on multiple public datasets and real application validate the efficacy of the proposed method.

Facile dual-functionalization of PEN nanofibrous membranes with solar evaporation and photocatalysis for efficient dye wastewater purification

Purification of dye wastewater by combining photocatalytic degradation with solar energy-driven interfacial water evaporation has emerged as a promising approach to address water pollution in recent years. In this work, a high-performance polymer, polyarylene ether nitrile (PEN), was electrostatically spun to construct a robust nanofibrous substrate, then dual-functionalized using polyaniline (PANI) and titanium dioxide (TiO2) via a facile polydopamine (PDA)-assisted vacuum self-assembly method. Moreover, the CA of the PEN membrane after PDA and PANI@TiO2 treatment changes from 20° to 0° within 0.4s, showing superhydrophilic properties and providing rapid water supply for water evaporation. PANI and TiO2 were employed as the photo-thermal conversion component and photocatalytic component, respectively. The fabricated dual-functionalized PANI@TiO2/PEN composite nanofibrous membrane exhibited a high water evaporation rate of up to 3.23kgm-2 h-1 under a simulated solar illumination of 1 KW m-2. Owing to the reduction in the photoelectron-hole recombination rate promoted by PANI, the composite nanofibrous membrane demonstrated a favorable dye removal rate of 92.18% in 6h for methylene blue (MB). Furthermore, the robust PEN nanofibrous skeleton conferred the composite membrane with thermal resistance and corrosion resistance properties, ensuring long-term performance in harsh environments. The facile fabricated PANI@TiO2/PEN membrane achieved comprehensive performance, offering a promising strategy by combining solar-driven interfacial water evaporation and photocatalytic degradation for water purification.

Tailoring the crystallinity and phase composition of MoS2 nanosheets for better lubrication performance

Molybdenum disulfide (MoS2), a typical lubricant material in vacuum environments, encounters limitations in broader industrial applications due to its vulnerability to oxidative degradation. Adjusting crystal structure or improving crystallinity can effectively increase the oxidation resistance of MoS2, and then enhance its lubrication performance. Herein, a simple hydrothermal method combined with post-annealing treatments was used to synthesize MoS2 and tailor crystal structure and crystallinity. Structural and morphological analyses indicated that the crystal structure of MoS2 had been transformed from 1 T′-MoS2 to 2H-MoS2, and the improved crystallinity with larger grain sizes reduced grain boundaries after annealing treatment. These structural variations were corroborated by in-situ Raman spectroscopy during laser annealing and subsequent tribological evaluation, which demonstrated 2H phase and higher crystallinity were beneficial for improving the oxidation resistance and longevity of MoS2 coating. These results were further validated by density functional theory calculation. The enhanced oxidation resistance could be ascribed to the protective role of the S atomic layer on Mo layer, coupled with high hydrophobicity and reduced grain boundaries by high crystallinity. Furthermore, the oxidation mechanism of MoS2 in the sliding process has been clarified, which can provide a novel pathway to improve its lubrication performance in atmospheric environment.

3D reconstruction of semantic-rich digital twins for ACMV monitoring and anomaly detection via scan-to-BIM and time-series data integration

Current research in air-conditioning and mechanical ventilation (ACMV) operation focuses on isolated sub-processes and analytical models. Digital twins, as digital replicas of assets, processes, or systems in the built environment, enable facilities manager (FM) to gain insights into the physical features of space, equipment performance, and energy efficiency. This study presents the 3D reconstruction of semantic-rich digital twins, which encompasses conditional and machine learning-enabled monitoring with 3D geometric models, for ACMV modeling and operation. The proposed framework involves a hybrid rule-based and data-driven approach to forecast the performance of indoor environment and identify potential anomalies throughout ACMV operation. Following this, a scan-to-BIM process is undertaken, with the aid of Simultaneous Localization and Mapping algorithms, to semi-automatically generate the as-built geometric models. Lastly, semantic enrichment of BIM is performed by incorporating time-series data from the rule-based and data-driven approach with 3D geometric models. The proposed approach supports the reconstruction of content-aware and semantic-rich digital twins, which utilize sensor-derived time-series data and 3D geometric models, to conduct advanced analysis for intelligent ACMV operation towards energy efficiency and occupant comfort.

Unified control of diverse actions in a wastewater treatment activated sludge system using reinforcement learning for multi-objective optimization

The operation of modern wastewater treatment facilities is a balancing act in which a multitude of variables are controlled to achieve a wide range of objectives, many of which are conflicting. This is especially true within secondary activated sludge systems, where significant research and industry effort has been devoted to advance control optimization strategies, both domain-driven and data-driven. Among data-driven control strategies, reinforcement learning (RL) stands out for its ability to achieve better than human performance in complex environments. While RL has been applied to activated sludge process optimization in existing literature, these applications are typically limited in scope, and never for the control of more than three actions. Expanding the scope of RL control has the potential to increase the optimization potential while concurrently reducing the number of control systems that must be tuned and maintained by operations staff. This study examined several facets of the implementation of multi-action, multi-objective RL agents, namely how many actions a single agent could successfully control and what extent of environment data was necessary to train such agents. This study observed improved control optimization with increasing action scope, though control of waste activated sludge remains a challenge. Furthermore, agents were able to maintain a high level of performance under decreased observation scope, up to a point. When compared to baseline control of the Benchmark Simulation Model No. 1 (BSM1), an RL agent controlling seven individual actions improved the average BSM1 performance metric by 8.3%, equivalent to an annual cost savings of $40,200 after accounting for the cost of additional sensors.

Utilization of Virtual Reality (VR) in Developing Interactive Learning Experiences

The development of Virtual Reality (VR) technology has opened up new opportunities for creating more immersive and interactive learning experiences. With its ability to simulate realistic virtual environments, Virtual Reality has the potential to increase student engagement in the learning process, aid understanding of complex concepts, and promote active learning. This research aims to explore the use of Virtual Reality technology in developing interactive learning experiences. The main focus is evaluating the effectiveness of Virtual Reality in increasing student motivation, engagement and learning outcomes, as well as identifying supporting factors and challenges in implementing Virtual Reality in educational environments. This research uses a combination of qualitative and quantitative approaches. Data was collected through observation, interviews, surveys and analysis of student performance in a Virtual Reality-based learning environment. A prototype Virtual Reality application for learning was built and tested on a group of students with diverse backgrounds. The research results show that the use of Virtual Reality in the learning environment significantly increases student motivation and engagement. Students feel more interested and involved in the learning process due to the immersive and interactive nature of the virtual environment. Additionally, understanding complex concepts becomes easier with the visualizations and simulations provided by Virtual Reality. However, challenges such as implementation costs, training needs, and technical issues were also identified. The research conclusion states that Virtual Reality is a promising technology for developing interactive learning experiences. Although there are challenges that must be overcome, research results show that Virtual Reality can increase student motivation, engagement and understanding in the learning process. Further research is needed to explore the potential of Virtual Reality in more depth.

Synergistic effects of interface and phase engineering on telluride toward alkaline/neutral hydrogen evolution reaction in freshwater/seawater

The development of efficient, stable, and versatile hydrogen evolution electrocatalysts is of great meaning, but still faces challenging. Interface engineering and phase engineering have been immensely applied in the field of hydrogen evolution reaction (HER) because of their unique physicochemical properties. However, they are typically used separately, which limits their effectiveness. Herein, we propose an interface-engineered CoMo/CoTe electrocatalyst, consisting of an amorphous CoMo (a-CoMo) layer-encapsulated crystalline CoTe array, achieving the profound optimization of catalytic performance. The experimental results and density functional theory calculations show that the d-band center of the catalyst shifts further upward in contrast with its crystalline–crystalline counterpart, optimizing the electronic structure and the intermediate adsorption, thereby reducing the kinetic barrier of HER. The a-CoMo/CoTe with superhydrophilic/superaerophobic features shows excellent catalytic performance in alkaline, neutral, and simulated seawater environments.

Enhancing mathematics education in the UAE: Elementary teachers’ views on distance education methods

The COVID-19 pandemic has brought about an unprecedented reliance on digital technologies in education, regardless of the pre-existing attitude of teachers. This study explores elementary school teachers’ perceptions about teaching mathematics through distance education. Using a quantitative approach, an online questionnaire was administered to primary teachers in the UAE during the spring semester of 2020-2021. The results show teachers’ readiness to adopt digital technology in teaching against increased workload. Difficulties emerged in optimizing student performance in online environments. While the institution supports digital integration, teachers prefer traditional in-person classroom instruction. Therefore, the research would inform some educational systems and curriculum planning worldwide on the best way to integrate digital technology within elementary mathematics education. The study aims to close the gap in mathematics education within a digital context to solve the emerging educational demands.

Broad learning system based on maximum multi-kernel correntropy criterion

The broad learning system (BLS) is an effective machine learning model that exhibits excellent feature extraction ability and fast training speed. However, the traditional BLS is derived from the minimum mean square error (MMSE) criterion, which is highly sensitive to non-Gaussian noise. In order to enhance the robustness of BLS, this paper reconstructs the objective function of BLS based on the maximum multi-kernel correntropy criterion (MMKCC), and obtains a new robust variant of BLS (MKC-BLS). For the multitude of parameters involved in MMKCC, an effective parameter optimization method is presented. The fixed-point iteration method is employed to further optimize the model, and a reliable convergence proof is provided. In comparison to the existing robust variants of BLS, MKC-BLS exhibits superior performance in the non-Gaussian noise environment, particularly in the multi-modal noise environment. Experiments on multiple public datasets and real application validate the efficacy of the proposed method.

Bioinspired multiscale hierarchical structure enables solar-thermal conversion for low-temperature aqueous electrochromic device

Solar-thermal conversion can mitigate the inadequate electrochemical performance in extreme cold environment for aqueous electrochromic devices (AEDs). However, the limited intrinsic absorptance of electrochromic materials impedes a satisfying solar-thermal conversion. Herein, bioinspired by the Paradisaeidae’s super black feathers, multiscale hierarchical structure is purposely made to compose of WO3-x nanowires (WNWs) and silver nanowires (AgNWs), where WNWs are grown on AgNWs in different orientations (denoted as WAg). Our ray tracing simulation reveals its underlying absorption mechanism, demonstrating both an increased optical path and a concentrated energy distribution. Comparably, the WAg-AED exhibits much enhanced absorption (87.0 vs. 68.5 % across the entire solar spectrum) and a broader surface temperature change (51.2 vs. 39.7 °C within 8 min) under 1 solar illumination. This leads to a rapid recovery of electrochromic/electrochemical performance even conducted at −20 °C. Notably, upon irradiation for 12 min, the areal capacities of WAg-AED at 0.5mA cm−2 increase by 3.8 and 1.7 times, when compared to the device operating at −20 °C and room temperature, respectively. The WAg-AED establishes a close connection between the photo-thermal conversion and electrochemistry, proving a new pathway in the development of sustainable electronics.

UV photosensitized N-CQDs@In2O3 ordered porous film elaborated optical fiber acetone gas sensor with ppb-level at room temperature

An optical fiber acetone gas sensor based on N-CQDs@In2O3 porous ordered thin film is proposed. The probe adopts the hollow malposition structure (HMS) to excite the evanescent field on the surface of hollow-core fiber (HCF). N-CQDs@In2O3 porous and ordered thin film was formed on the surface of optical fiber after calcining polystyrene (PS) microspheres at high temperature. The experimental results reveal the ultraviolet (UV) sensitization function for the proposed sensor at room temperature. The enhanced sensitivity is 7.1 pm/ppm, which is ∼5.9 times of the spiritual density of unsensitized sensor. In addition, the sensor has a limit of detection (LOD) of 500 ppb and excellent time response characteristics (response time 6.2 s and recovery time 7.1 s). The sensitization mechanism of N-CQDs to In2O3 is explained by the results of the universal density function (DFT). The frontier electron orbital studies show that N-CQDs@In2O3 has more abundant electron clouds. The good moisture resistance enables its stable performance in humid environment. UV sensitization is an effective way to improve the sensitivity of optical fiber gas sensor, which is of great significance for detecting the acetone gas with ultra-low concentration.