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Aim: Climate change poses a major threat to human health, with significant contributions from healthcare systems, with the UK National Health Service (NHS) accounting for 4% of national CO 2 emissions. Radiology departments, with high energy consumption from heating, ventilation, cooling (HVAC), and scanners, also contribute significantly. Workstations, though less power-intensive than scanners, are numerous and offer an avenue for emission reduction potential. This study investigates the impact of an automatic power-off/on protocol for radiology workstations at an acute hospital trust on energy consumption, carbon emissions, and financial savings., Materials and Methods: Data from 88 reporting workstations were collected on power usage, CO 2 emissions, and the associated energy cost before and after implementing an automatic shutdown protocol, which ensured workstations were turned off out of hours and over weekends., Results: Average weekly workstation on-time fell from 148 to 75.5 hours, resulting in an annual energy saving of 17 MWh, equivalent to a reduction of 3.4 tonnes CO 2 equivalent and a financial saving of £5000. No complaints or issues with workflow disruption were reported., Conclusion: This intervention demonstrates a significant reduction in emissions and energy costs without workflow disruption, offering an easy and replicable sustainability measure for radiology departments. While savings are modest compared to HVAC and scanner emissions, the protocol's simplicity and effectiveness in addressing human factors in power management highlight its potential. Broader application across hospital networks could yield substantial environmental and financial benefits. These findings contribute to the ongoing efforts to improve sustainability within radiology and health care., (Copyright © 2024 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.)

This study investigates the pivotal role of green strategies in achieving carbon neutrality by exploring the synergistic contributions of green finance, green technological innovation, and green energy adoption. The study has implemented several panel data estimation techniques including second generation panel unit root test commonly known as CADF and CIPS, an error correction-based panel cointegration test, for documenting the elasticities of GF, GTI, and GE on carbon neutrality through Continuously-Update Fully Modified[CUP-FM], Continuously-Update Bias-Corrected [CUP-BC], and Dynamic Seemingly Unrelated Regression [DSUR]. The asymmetric coefficients have exploded with the implementation of a nonlinear framework, which is well known as NARDL. Our findings underscore the significance of green finance mechanisms in mobilizing resources for sustainable initiatives, including renewable energy projects and energy-efficient technologies. Study shed light on the catalytic impact of green Technological innovation in driving technological advancements, reducing emissions, and fostering economic growth. Furthermore, our study delves into the transformative potential of clean energy adoption, elucidating how it can substantially reduce carbon footprints and bolster the transition to a low-carbon economy. This study contributes to the growing body of knowledge on the critical nexus of green strategies and carbon neutrality, offering a roadmap for a more sustainable and environmentally responsible future. In a world grappling with the pressing challenges of climate change, our research offers valuable insights into the strategies that institutions, policymakers, and businesses can employ to facilitate the transition toward carbon neutrality., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Qamruzzaman, Karim. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Plant factories with artificial lighting (PFALs) can boost food production per unit area but require resources such as carbon dioxide and energy to maintain optimal plant growth conditions. Here we use computational modelling and artificial intelligence (AI) to examine plant-environment interactions across ten diverse global locations with distinct climates. AI reduces energy use by optimizing lighting and climate regulation systems, with energy use in PFALs ranging from 6.42 kWh kg -1 in cooler climates to 7.26 kWh kg -1 in warmer climates, compared to 9.5-10.5 kWh kg -1 in PFALs using existing, non-AI-based technology. Outdoor temperatures between 0 °C and 25 °C favour ventilation-related energy use reduction, with outdoor humidity showing no clear pattern or effect on energy use. Ventilation-related energy savings negatively impact other resource utilization such as carbon dioxide use. AI can substantially enhance energy savings in PFALs and support sustainable food production., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Government-led national comprehensive demonstration cities for Energy Conservation and Emission Reduction Fiscal Policy (ECERFP) are pivotal for China in addressing environmental governance. Using a panel dataset covering 278 Chinese cities from 2003 to 2019, this study adopts the staggered difference-in-differences (DID) approach to investigate the synergistic impacts of ECERFP on pollution and carbon reduction. The findings indicate that ECERFP contributes to a 3% improvement in pollution reduction performance, a 1.5% enhancement in carbon reduction performance, and a 4% overall increase in combined pollution and carbon reduction efforts. Furthermore, the study examines the heterogeneous effects of ECERFP on environmental performance. ECERFP significantly influences the synergistic efforts in pollution and carbon reduction by fostering green innovation, enhancing energy allocation, and optimizing industrial structures. This study both theoretically and empirically outlines the specific pathways and mechanisms through which "incentive-based" green fiscal policy promotes synergistic pollution and carbon reduction, thus providing a pragmatic foundation for enhancing the role of fiscal policy in environmental governance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

In recent years, due to global climate change, increasing resource scarcity, and environmental constraints, countries have prioritized energy conservation and emissions reduction. However, enterprises are primarily responsible for energy saving and emissions reduction. To encourage industrial enterprises to engage in energy conservation and emissions reduction, high-carbon enterprises must purchase carbon emission rights from low-carbon counterparts. Common modes of energy conservation and emission reduction of industrial enterprises include reducing production scale, improving energy utilization efficiency, and expanding renewable energy. This article constructs three differential game models to identify the applicable scope of various energy conservation and emission reduction strategies, comparing and analyzing the equilibrium results. The study concludes that when the cost of changing the production mode and the income obtained from the production of unit product is large, the low-carbon enterprise can obtain the maximum benefit by reducing the production scale mode. Otherwise, low carbon enterprises can be maximized through improving energy efficiency mode. For both low-carbon and high-carbon enterprises, reducing production scale is the fastest way to enhance efficiency when the costs of energy conservation and emission reduction are substantial., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Xueli Zhu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study presents a novel approach to integrating combined cooling, heating, and power (CCHP) systems with water desalination for enhanced energy and water management in educational buildings. Two distinct layouts for CCHP and desalination systems are introduced: one prioritizing efficient power generation to meet electricity demands while providing waste heat for desalination, and the other focusing on balancing cooling and heating loads alongside water desalination. Both layouts are tailored to meet the building's energy and water demands while considering operational efficiency. Optimization of these layouts against traditional systems using the bat search algorithm emphasizes economic viability and the gas engine's operational flexibility, which are crucial for partial load operation. In addition, an environmental assessment compares the proposed CCHP-desalination systems with conventional setups, assessing CO 2 emission reductions and overall sustainability. The evaluation encompasses key environmental metrics, such as resource consumption and the integration of renewable energy sources. Results highlight significant CO 2 emission reductions across various gas engine capacities, with notable enhancements in economic and environmental performance achieved by selecting a 3,250 kW gas engine within the CCHP-desalination system. This choice not only maximizes the annual profit but also reduces CO 2 emissions by 57% compared to conventional systems, underscoring the system's sustainability benefits., Competing Interests: The authors declare there is no conflict., (© 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).)

Competing Interests: Competing interests: none declared

Energy consumption of constructed educational facilities significantly impacts economic, social and environment sustainable development. It contributes to approximately 37% of the carbon dioxide emissions associated with energy use and procedures. This paper aims to introduce a study that investigates several artificial intelligence-based models to predict the energy consumption of the most important educational buildings; schools. These models include decision trees, K-nearest neighbors, gradient boosting, and long-term memory networks. The research also investigates the relationship between the input parameters and the yearly energy usage of educational buildings. It has been discovered that the school sizes and AC capacities are the most impact variable associated with higher energy consumption. While 'Type of School' is less direct or weaker correlation with 'Annual Consumption'. The four developed models were evaluated and compared in training and testing stages. The Decision Tree model demonstrates strong performance on the training data with an average prediction error of about 3.58%. The K-Nearest Neighbors model has significantly higher errors, with RMSE on training data as high as 38,429.4, which may be indicative of overfitting. In contrast, Gradient Boosting can almost perfectly predict the variations within the training dataset. The performance metrics suggest that some models manage this variability better than others, with Gradient Boosting and LSTM standing out in terms of their ability to handle diverse data ranges, from the minimum consumption of approximately 99,274.95 to the maximum of 683,191.8. This research underscores the importance of sustainable educational buildings not only as physical learning spaces but also as dynamic environments that contribute to informal educational processes. Sustainable buildings serve as real-world examples of environmental stewardship, teaching students about energy efficiency and sustainability through their design and operation. By incorporating advanced AI-driven tools to optimize energy consumption, educational facilities can become interactive learning hubs that encourage students to engage with concepts of sustainability in their everyday surroundings., (© 2024. The Author(s).)

It is important to ensure energy security and achieve carbon-haze collaborative management for sustainable development. Reducing imported energy dependence is necessary to maintain energy security, while its impact on environmental quality remains unclear. From the perspective of biased technological progress, this paper estimates the level of biased technological progress towards self-sufficient energy by a heterogeneous stochastic frontier analysis (SFA) function, and then empirically examines whether self-sufficient energy biased technological progress has a dampening effect on haze pollution and carbon emissions. It is found that: (1) Self-sufficient energy biased technological progress can effectively reduce haze pollution and carbon emissions, achieving a synergistic effect between energy security and carbon-haze collaborative management. (2) "Efficiency enhancement" and "quality improvement" are the essential mechanisms for the synergistic effect. (3) Environmental regulation, abundant resource and technology endowments can enhance the haze reduction effect. And the lower dependence on foreign trade and stable global economic policy environment are more conducive to achieving carbon-haze collaborative control. (4) In the Eastern and Western regions, self-sufficient energy biased technology can be sped up to alleviate haze pollution. The findings can enrich the research exploring pollution control from the perspective of biased technological progress, and provide policy recommendations for promoting high-quality development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

As the global demand for clean energy continues to grow, the sustainable development of clean energy projects has become an important topic of research. in order to optimize the performance and sustainability of clean energy projects, this work explores the environmental and economic benefits of the clean energy industry. through the use of Support Vector Machine (SVM) Multi-factor models and a bi-level multi-objective approach, this work conducts comprehensive assessment and optimization. with wind power base a as a case study, the work describes the material consumption of wind turbines, transportation energy consumption and carbon dioxide (CO2) emissions, and infrastructure material consumption through descriptive statistics. Moreover, this work analyzes the characteristics of different wind turbine models in depth. On one hand, the SVM multi-factor model is used to predict and assess the profitability of Wind Power Base A. On the other hand, a bi-level multi-objective approach is applied to optimize the number of units, internal rate of return within the project, and annual average equivalent utilization hours of the Wind Power Base A. The research results indicate that in March, the WilderHill New Energy Global Innovation Index (NEX) was 0.91053, while the predicted value of the SVM multi-factor model was 0.98596. The predicted value is slightly higher than the actual value, demonstrating the model's good grasp of future returns. The cumulative rate of return of Wind Power Base A is 18.83%, with an annualized return of 9.47%, exceeding the market performance by 1.68%. Under the optimization of the bi-level multi-objective approach, the number of units at Wind Power Base A decreases from the original 7004 to 5860, with total purchase and transportation costs remaining basically unchanged. The internal rate of return of the project increases from 8% to 9.3%, and the annual equivalent utilization hours increase to 2044 h, comprehensively improving the investment return and utilization efficiency of the wind power base. Through optimization, significant improvements are achieved in terAs the global demand for clean energy continues to grow, the sustainable development of clean energy projects has become an important topic of research. In order to optimize the performance and sustainability of clean energy projects, this work explores the environmental and economic benefits of the clean energy industry. Through the use of Support Vector Machine (SVM) multi-factor models and a bi-level multi-objective approach, this work conducts comprehensive assessment and optimization. With Wind Power Base A as a case study, the work describes the material consumption of wind turbines, transportation energy consumption and carbon dioxide (CO2) emissions, and infrastructure material consumption through descriptive statistics. Moreover, this work analyzes the characteristics of different wind turbine models in depth. On one hand, the SVM multi-factor model is used to predict and assess the profitability of Wind Power Base A. On the other hand, a bi-level multi-objective approach is applied to optimize the number of units, internal rate of return within the project, and annual average equivalent utilization hours of the Wind Power Base A. The research results indicate that in March, the WilderHill New Energy Global Innovation Index (NEX) was 0.91053, while the predicted value of the SVM multi-factor model was 0.98596. The predicted value is slightly higher than the actual value, demonstrating the model's good grasp of future returns. The cumulative rate of return of Wind Power Base A is 18.83%, with an annualized return of 9.47%, exceeding the market performance by 1.68%. Under the optimization of the bi-level multi-objective approach, the number of units at Wind Power Base A decreases from the original 7004 to 5860, with total purchase and transportation costs remaining basically unchanged. The internal rate of return of the project increases from 8% to 9.3%, and the annual equivalent utilization hours increase to 2044 h, comprehensively improving the investment return and utilization efficiency of the wind power base. Through optimization, significant improvements are achieved in terms of the number of units, internal rate of return within the project, and annual average equivalent utilization hours at Wind Power Base A. The number of units decreases to 5860, with total purchase and transportation costs remaining basically unchanged, the internal rate of return increases to 9.3%, and annual equivalent utilization hours increase to 2044 h. Energy consumption and CO2 emissions are significantly reduced, with energy consumption decreasing by 0.68 × 109 kgce and CO2 emissions decreasing by 1.29 × 109 kg. The optimization effects are mainly concentrated in the production and installation stages, with emission reductions achieved through the recycling and disposal of materials consumed in the early stages. In terms of investment benefits, environmental benefits are enhanced, with a 13.93% reduction in CO2 emissions. Moreover, there is improved energy efficiency, with the energy input-output ratio increasing from 7.73 to 9.31. This indicates that the Wind Power Base A project has significant environmental and energy efficiency advantages in the clean energy industry. This work innovatively provides a comprehensive assessment and optimization scheme for clean energy projects and predicts the profitability of Wind Power Base A using SVM multi-factor models. Besides, this work optimizes key parameters of the project using a bi-level multi-objective approach, thus comprehensively improving the investment return and utilization efficiency of the wind power base. This work provides innovative methods and strong data support for the development of the clean energy industry, which is of great significance for promoting sustainable development under the backdrop of green finance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Buildings are significant end-users of global energy. About 20% of the energy consumption worldwide is used for maintaining a comfortable indoor climate. Therefore, passive systems for indoor temperature and humidity regulation that can respond to environmental changes are very promising to reduce buildings' energy consumption. We developed a process to improve the responsiveness of wood to humidity changes by laser-drilling microscopic holes and incorporating a hygroscopic salt (calcium chloride). The resulting "transpiring wood" displays superior water adsorption capacity and high moisture exchange rate, allowing regulation of humidity and temperature by the exchange of moisture with the surrounding air. We proved that the hygrothermal performance of transpiring wood can be used to regulate indoor climate, with associated energy savings, for various climate types, thus favoring its application in the building sector. The reduction of temperature fluctuations, thanks to the buffering of temperature peaks, can lead to an indirect energy saving of about 10% for cooling and between 4-27% for heating depending on the climate. Furthermore, our transpiring wood meets different sustainability criteria, from raw materials to the fabrication process, resulting in a product with a low overall environmental impact and that is easy to recycle.

Background: The German healthcare system is responsible for 5% of the national greenhouse gas emissions with inpatient medicine in particular resulting in high energy consumption. Buildings needing renovation, a high demand for consumer goods with the resulting high volume of waste, and the release of greenhouse gases from anesthetic gases contribute to climate-damaging effects in clinics. In order to achieve the goal of climate neutrality by 2045 declared by the federal government, comprehensive structural changes and the establishment of sustainable measures are therefore also necessary in dermatological clinics., Objectives: This work is intended to give dermatologists a compact overview of the possible fields of action., Materials and Methods: Selective literature research on sustainability in clinics and development of concrete proposals for action as well as a summary of own experiences in establishing an environmental management system at the SLK Clinics of Heilbronn., Results: The know-how of professional climate and environmental management is often not yet available. In order to offer motivated dermatologists and employees of clinics concrete assistance, this article shows possible courses of action in the following fields: Energy management and information technology (IT), durable and consumer goods, waste management, sustainable food supply, mobility, public relations, and diagnostics and therapy., Conclusion: Environmental protection measures and energy efficiency in clinics are difficult to implement due to limiting factors such as staff shortages, financial constraints, and a lack of instructions. As shown here, however, the implementation of these measures through resource savings, such as saving energy, is often also financially worthwhile and can make a significant contribution to achieving climate neutrality., (© 2022. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Resolving the negative externality of environmental pollution has always been a concern in both the theoretical and practical space. To stimulate enterprises to participate in environmental governance actively, China has implemented a series of environmental regulation policies. The Emission Trading Pilot Scheme (ETPS) is an example of such policies implemented to ensure the gradual transition toward marketization. From a micro-enterprise perspective, the study examines how this policy achieves the dual effects of reducing emissions and promoting energy efficiency. We further explore potential channels through which this policy influences the dual effects. We empirically find ETPS to reduce the pollution emissions of enterprises significantly. However, the pollution reduction effect is mainly achieved by encouraging enterprises to strengthen cleaner production rather than through end governance. In addition to bringing environmental dividends, we observe ETPS to improve fossil energy efficiency by about 7.5% indirectly. We conclude by urging policy makers and participants to optimize energy structures and adjust intermediate input as they serve as significant pathways through which ETPS can affect fossil energy efficiency. The ETPS can encourage enterprises to actively step out of their "comfort zone" of environmental governance to be viewed as an effective environmental regulation policy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The EU emissions trading system's (ETS) invalidation rule implies that shocks and overlapping policies can change cumulative carbon emissions. This paper explains these mechanisms and simulates the effect of COVID-19, the European Green Deal, and the recovery stimulus package on cumulative EU ETS emissions and allowance prices. Our results indicate that the negative demand shock of the pandemic should have a limited effect on allowance prices and rather translates into lower cumulative carbon emissions. Aligning EU ETS with the 2030 reduction target of -55% might increase allowance prices to 45-94 €/ton CO 2 today and reduce cumulative carbon emissions to 14.2-18.3 GtCO 2 compared to 23.5-33.1 GtCO 2 under a -40% 2030 reduction target. Our results crucially depend on when the waterbed will be sealed again, which is an endogenous market outcome, driven by the EU ETS design, shocks and overlapping climate policies such as the recovery plan., (© 2022. The Author(s).)

Cost and safety are critical factors in the oil and gas industry for optimizing wellbore trajectory, which is a constrained and nonlinear optimization problem. In this work, the wellbore trajectory is optimized using the true measured depth, well profile energy, and torque. Numerous metaheuristic algorithms were employed to optimize these objectives by tuning 17 constrained variables, with notable drawbacks including decreased exploitation/exploration capability, local optima trapping, non-uniform distribution of non-dominated solutions, and inability to track isolated minima. The purpose of this work is to propose a modified multi-objective cellular spotted hyena algorithm (MOCSHOPSO) for optimizing true measured depth, well profile energy, and torque. To overcome the aforementioned difficulties, the modification incorporates cellular automata (CA) and particle swarm optimization (PSO). By adding CA, the SHO's exploration phase is enhanced, and the SHO's hunting mechanisms are modified with PSO's velocity update property. Several geophysical and operational constraints have been utilized during trajectory optimization and data has been collected from the Gulf of Suez oil field. The proposed algorithm was compared with the standard methods (MOCPSO, MOSHO, MOCGWO) and observed significant improvements in terms of better distribution of non-dominated solutions, better-searching capability, a minimum number of isolated minima, and better Pareto optimal front. These significant improvements were validated by analysing the algorithms in terms of some statistical analysis, such as IGD, MS, SP, and ER. The proposed algorithm has obtained the lowest values in IGD, SP and ER, on the other side highest values in MS. Finally, an adaptive neighbourhood mechanism has been proposed which showed better performance than the fixed neighbourhood topology such as L5, L9, C9, C13, C21, and C25. Hopefully, this newly proposed modified algorithm will pave the way for better wellbore trajectory optimization., Competing Interests: The authors have declared that no competing interests exist.

Ethiopia unveiled homegrown economic reform agenda aimed to achieve a lower-middle status by 2030 and sustain its economic growth to achieve medium-middle and higher-middle status by 2040 and 2050 respectively. In this study, we evaluated the optimal renewable energy mix for power generation and associated investment costs for the country to progressively achieve upper-middle-income countries by 2050. Two economic scenarios: business as usual and Ethiopia's homegrown reform agenda scenario were considered. The study used an Open Source energy Modeling System. The model results suggest: if projected power demand increases as anticipated in the homegrown reform agenda scenario, Ethiopia requires to expand the installed power capacity to 31.22GW, 112.45GW and 334.27GW to cover the current unmet and achieve lower, medium and higher middle-income status by 2030, 2040 and 2050 respectively. The Ethiopian energy mix continues to be dominated by hydropower and starts gradually shifting to solar and wind energy development towards 2050 as a least-cost energy supply option. The results also indicate Ethiopia needs to invest about 70 billion US$ on power plant investments for the period 2021-2030 to achieve the lower-middle-income electricity per capita consumption target by 2030 and staggering cumulative investment in the order of 750 billion US$ from 2031 to 2050 inclusive to achieve upper-middle-income electricity consumption rates by 2050. Ethiopia has enough renewable energy potential to achieve its economic target. Investment and financial sourcing remain a priority challenge. The findings could be useful in supporting decision-making concerning socio-economic development and investment pathways in the country., Competing Interests: No authors have competing interest.

Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species' cells. In this perspective, we discuss opportunities afforded by single-cell technologies for energy and environmental science and grand challenges that must be tackled to apply these approaches to plants, fungi and algae. We highlight the need to develop better and more comprehensive single-cell technologies, analysis and visualization tools, and tissue preparation methods. We advocate for the creation of a centralized, open-access database to house plant single-cell data. Finally, we consider how such efforts should balance the need for deep characterization of select model species while still capturing the diversity in the plant kingdom. Investments into the development of methods, their application to relevant species, and the creation of resources to support data dissemination will enable groundbreaking insights to propel energy and environmental science forward., (© 2021. The Author(s).)

To develop a new gangue polymer filling material with low compressive ratio, this paper intends to add high water cementing material to the gangue for backfilling. Uniaxial and tri-axial bearing experiments were conducted to study its bearing characteristics and residual strength. Based on Hock-Brown model theory, it is proposed that friction angle φr can be introduced to substitute model parameter mi, and the degree of cohesion loss can characterize the value of s. So the improved H-B model is established to characterize the residual strength of materials with ductile failure characteristics. The results show that the compressive strength of high water filling material increases linearly corresponding to the rise of confining pressure, and its strength characteristics conform to Mohr-Coulomb strength criterion. The ductile failure characteristics of the sample endow it with high residual strength, which in turn qualifies it for underground filling. After the introduction of cohesion and friction angle, the improved H-B criterion can fit the residual strength curve of the high water filling material more competently. The fitting coefficient of the samples with three water contents is 1.00, 0.99, and 1.00, respectively. The improved H-B model of residual strength demonstrates the change rule of residual strength of the samples corresponding to the change of confining pressure; under tri-axial loading, the angle between fracture surface and axial direction becomes larger as the confining pressure rises; and the failure mode of the material transforms from splitting failure to shear failure., Competing Interests: The authors declare no conflict of interest.

Disposable surgical face masks are usually used by medical/nurse staff but the current Covid-19 pandemic has caused their massive use by many people. Being worn closely attached to the people's face, they are continuously subjected to routine movements, i.e., facial expressions, breathing, and talking. These motional forces represent an unusual source of wasted mechanical energy that can be rather harvested by electromechanical transducers and exploited to power mask-integrated sensors. Typically, piezoelectric and triboelectric nanogenerators are exploited to this aim; however, most of the current devices are too thick or wide, not really conformable, and affected by humidity, which make them hardly embeddable in a mask, in contact with skin. Different from recent attempts to fabricate smart energy-harvesting cloth masks, in this work, a wearable energy harvester is rather enclosed in the mask and can be reused and not disposed. The device is a metal-free hybrid piezoelectric nanogenerator (hPENG) based on soft biocompatible materials. In particular, poly(vinylidene fluoride) (PVDF) membranes in the pure form and with a biobased plasticizer (cardanol oil, CA) are electrospun onto a laser-ablated polyimide flexible substrate attached on a skin-conformable elastomeric blend of poly(dimethylsiloxane) (PDMS) and Ecoflex. The multilayer structure of the device harnesses the piezoelectricity of the PVDF nanofibers and the friction triboelectric effects. The ultrasensitive mechanoelectrical transduction properties of the composite device are determined by the strong electrostatic behavior of the membranes and the plasticization effect of cardanol. In addition, encapsulation based on PVDF, PDMS, CA, and parylene C is used, allowing the hPENG to exhibit optimal reliability and resistance against the wet and warm atmosphere around the face mask. The proposed device reveals potential applications for the future development of smart masks with coupled energy-harvesting devices, allowing to use them not only for anti-infective protection but also to supply sensors or active antibacterial/viral devices.

Air-conditioning systems make the most significant part of energy consumption in the residential sector. There is no denying that it is essential to produce a comfortable indoor thermal environment for residents in a building. The actual goal is to achieve thermal comfort level without putting too much cost on the ecological system by trying to conserve the amount of energy consumed. An effective way to help achieve such a goal is by incorporating thermal insulation in buildings. Thermal insulations help reduce thermal energy gained during the implementation of a desired thermal comfort level. This study aims to use an environmentally friendly nanoparticle of date pits to create thermal insulations that can be used in buildings. Different ratios of the nanoparticle of the date pits and sand composite were investigated. Fourier transform infrared spectroscopy and scanning electron microscopy were used to characterize the new materials. The material with nanoparticles of date pits and 50% by-volume epoxy provided good thermal insulation with thermal conductivity of 0.26 W⁄mK that could be used in the existing buildings. This has the potential to reduce the overall energy consumption by 4,494 kWh and thereby reduce CO2 emissions of a 570 m2 house by 1.8 tons annually. In conclusion, the future of using nanoparticles of date pits in construction is bright and promising due to their promising results., Competing Interests: The authors have declared that no competing interests exist.

Heat poses an urgent threat to public health in cities, as the urban heat island (UHI) effect can amplify exposures, contributing to high heat-related mortality and morbidity. Urban trees have the potential to mitigate heat by providing substantial cooling, as well as co-benefits such as reductions in energy consumption. The City of Boston has attempted to expand its urban canopy, yet maintenance costs and high tree mortality have hindered successful canopy expansion. Here, we present an interactive web application called Right Place, Right Tree-Boston that aims to support informed decision-making for planting new trees. To highlight priority regions for canopy expansion, we developed a Boston-specific Heat Vulnerability Index (HVI) and present this alongside maps of summer daytime land surface temperatures. We also provide information about tree pests and diseases, suitability of species for various conditions, land ownership, maintenance tips, and alternatives to tree planting. This web application is designed to support decision-making at multiple spatial scales, to assist city officials as well as residents who are interested in expanding or maintaining Boston's urban forest., Competing Interests: The authors have declared that no competing interests exist.

The tri-functional purpose of Microbial Desalination Cell (MDC) has shown a great promise in our current scarcity of water, an increase in water pollution and the high cost of electricity production. As a biological system, the baseline force that drives its performance is the presence of exoelectrogens in the anode chamber. Their presence in the anodic chamber of MDC systems enables the treatment of water, desalination of seawater, and the production of electrical energy. This study reviews the characteristics of exoelectrogens, as a driving force in MDC and examines factors which influence their growth and the performance efficiency of MDC systems. It also addresses the efficiency of mixed cultures with certain predominant species as compared to pure cultures used in MDC systems. Furthermore, the study suggests the need to genetically modify certain predominant strains in mixed cultures to enhance their performance in COD removal, desalination and power output and the integration of MDC with other technologies for cost-effective processes.

Nowadays, humanity is consuming unsustainably the planet's resources. In the scope of energy resource consumption, e.g., the intense use of fossil fuels has contributed to the acceleration of climate changes on the planet, and the overriding need to increase energy efficiency in all sectors is now widely recognized, aiming to reduce greenhouse gases (GHG) emissions by 69% in 2030. Largely due to climate changes, water has also become a critical resource on the planet and hydric stress risk will rise significantly in the coming decades. Accordingly, several countries will have to apply measures to increase water efficiency in all sectors, including at the building level. These measures, in addition to reducing water consumption, will contribute to the increase of energy efficiency and to the decrease of GHG emissions, especially of CO 2 . Therefore, the nexus water energy in buildings is relevant because the application of water efficiency measures can result in a significant contribution to improve buildings' energy efficiency and the urban water cycle (namely in abstraction, treatment, and pumping). For Mediterranean climate, there are few studies to assess the extent and impact of this nexus. This study presents the assessment of water-energy nexus performed in a university building located in a mainland Portugal central region. The main goals are to present the results of the water and energy efficiency measures implemented and to assess the consequent reduction of water, above 37%, and energy (30%) consumption, obtained because of the application of water-efficient devices and highly efficient light systems in the building. The water efficiency increase at the building level represents at the urban level an energy saving in the water supply system of 406 kWh/year, nearly 0.5% of the building energy consumption, with a consequent increase in the energy efficiency and in the reduction of GHG emissions. Complementarily, other energy-efficient measures were implemented to reduce the energy consumption. As the building under study has a small demand of domestic hot water with no hydro pressure pumps and has a small water-energy nexus, it was concluded that the significant reduction of the building energy consumption did not influence the indoor comfort.

Clients receiving weatherization/energy services with an added injury prevention home assessment with modifications/repairs experienced a decline in falls and thus fall-related costs. Interventions in 35 homes were associated with significant reductions in falls from baseline to 6 months postintervention (from 94% to 9%; P < .001) and falls with calls for assistance (from 23% to 3%; P < .02). The decline in falls with calls for assistance in the intervention group was significant when adjusted for a comparison group effect (P = .07). At a median cost of $2058 per home, the addition of an injury prevention component led by an occupational therapist offers the potential to avoid expensive fall-related medical costs (lift assistance, hospital transport and admission, long-term care). Integration of injury prevention into weatherization work, which targets lower-income seniors with high energy use, offers potential to reduce costly hospitalizations and poor health outcomes.

Introduction: Health and climate change are inexorably linked through the exacerbation of health risks and the contribution of the health sector to greenhouse gas emissions. Climate action in healthcare settings is critical to reduce risks and impacts of climate change through the smarter use of energy, minimising waste and enhancing disaster preparedness. Globally, hospital climate action is growing; however, the potential for further progress and impacts remains. The literature on this topic lacks synthesis, and this poses challenges for hospital leadership in tracking the impact of climate action. This scoping review will summarise the current knowledge about hospital climate action and existing tools to measure progress in this area., Methods and Analysis: This scoping review will be conducted applying the six-stage protocol proposed by Arksey and O'Malley. The study includes literature of how hospitals have addressed climate change (mitigation and adaptation) since the Kyoto Protocol was signed in 1997. All identified studies indexed in Medline, Scopus, Embase and CINAHL will be examined. The search strategy will also include Google Scholar to capture relevant grey literature. Quantitative and thematic analysis will be used to evaluate and categorise the study results., Ethics and Dissemination: This scoping review is part of the climate-smart healthcare initiative which will provide a valuable synthesis to aid understanding of hospitals' climate actions, and tools used to measure its implementation. As such it will contribute to mobilising and accelerating the implementation of climate action in hospitals. The findings will be disseminated with all members of the International Health Promoting Hospital and Health Services (HPH) and the Global Green and Healthy Hospital network. Dissemination will occur through peer-reviewed publications; and with the HPH and GGHH members through its annual conference and newsletter., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The research provided scientific evidences for improved rice straw management. Rice cultivation with in-field burning of rice straw is the worst option with the lowest energy efficiency and highest air pollution emission. This article comprises a comparative assessment of energy efficiency and the environmental footprint of rice production using four different rice straw management scenarios, namely, straw retained, straw burned, partial straw removal, and complete straw removal. Paddy yield, grain quality, and energy balance were assessed for two seasons while greenhouse gas emissions (GHGE) were measured weekly starting from land preparation through to the cropping and fallow period. Despite the added energy requirements in straw collection and transport, the use of collected rice straw for mushroom production can increase the net energy obtained from rice production systems by 10-15% compared to burning straw in the field. Partial and complete removal of rice straw reduces GHGE by 30% and 40% compared to complete straw retention, respectively.

Desalination is increasingly put forward as a sustainable local solution to water scarcity in combination with the exploitation of renewable energy sources. However, the complexity of the resource nexus entails the unavoidable existence of pros and cons across its various dimensions that can only be assessed at different scales of analysis. In turn, these pros and cons entail different winners and losers among the different social actors linked through the nexus. To address these challenges, a novel approach to resource nexus assessment is put forward, based on multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM) and recognizing the resource nexus as a wicked problem. The integrated representation identifies the existence of biophysical constraints determined by processes both under human control (in the technosphere) and beyond human control (in the biosphere). The approach is illustrated with a local case study of desalination in the Canary Islands, Spain. The material presented has been generated in the context of the project "Moving towards adaptive governance in complexity: Informing nexus security" (MAGIC) for use in participatory processes of co-production of knowledge claims about desalination, a prerequisite for informed policy deliberation., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Developing photocatalytic H2 production devices is the one of the key steps for constructing a global H2-based renewable energy infrastructure. A number of photoactive assemblies have emerged where a photosensitizer and cobaloxime-based H2 production catalysts work in tandem to convert light energy into the H-H chemical bonds. However, the long-term instability of these assemblies and the need for hazardous proton sources have limited their usage. Here, in this work, we have integrated a stilbene-based organic dye into the periphery of a cobaloxime core via a distinct axial pyridine linkage. This strategy allowed us to develop a photosensitizer-catalyst hybrid structure with the same molecular framework. In this article, we have explained the detailed procedure of the synthesis of this hybrid molecule in addition to its comprehensive chemical characterization. The structural and optical studies have exhibited an intense electronic interaction between the cobaloxime core and the organic photosensitizer. The cobaloxime was active for H2 production even in the presence of water as the proton source. Here, we have developed a simple airtight system connected with an online H2 detector for the investigation of the photocatalytic activity by this hybrid complex. This photosensitizer-catalyst dyad present in the experimental setup continuously produced H2 once it was exposed in the natural sunlight. This photocatalytic H2 production by the hybrid complex was observed in aqueous/organic mixture media in the presence of a sacrificial electron donor under complete aerobic conditions. Thus, this photocatalysis measurement system along with the photosensitizer-catalyst dyad provide valuable insight for the development of next generation photocatalytic H2 production devices.

Pakistan has an abundant solar power potential which can be effectively utilized for the electricity generation. There are various sites across the country which have sufficient solar irradiation across the year, and thus, suitable for the installation of solar photovoltaic (PV) power projects. This study, therefore, aims to undertake research on the establishment of solar power project site selection in Pakistan. In this context, 14 promising cities of Pakistan are considered as alternatives and studied in terms of economic, environmental, social, location, climate, and orography criteria and further supplemented with 20 sub-criteria. Initially, the analytical hierarchy process (AHP) method has been used to prioritize each of the main criteria and sub-criteria. Later, fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (F-VIKOR) method has been employed to prioritize the 14 alternatives. The present investigation reveals that Khuzdar (C2), Badin (C3), and Mastung (C7) are the most suitable cities for the installation of solar PV power projects in Pakistan. Finally, the outcome of the sensitivity analysis revealed that obtained results are reliable and robust for the installation of solar PV power projects in Pakistan. This study shall assist government, energy planners, and policymakers in making cities sustainable by establishing solar power projects in Pakistan.

Because meat is more resource intensive than vegetal protein sources, replacing it with efficient plant alternatives is potentially desirable, provided these alternatives prove nutritionally sound. We show that protein conserving plant alternatives to meat that rigorously satisfy key nutritional constraints while minimizing cropland, nitrogen fertilizer (Nr) and water use and greenhouse gas (GHG) emissions exist, and could improve public health. We develop a new methodology for identifying nutritional constraints whose satisfaction by plant eaters is challenging, disproportionately shaping the optimal diets, singling out energy, mass, monounsaturated fatty acids, vitamins B 3,12 and D, choline, zinc, and selenium. By replacing meat with the devised plant alternatives-dominated by soy, green pepper, squash, buckwheat, and asparagus-Americans can collectively eliminate pastureland use while saving 35-50% of their diet related needs for cropland, Nr, and GHG emission, but increase their diet related irrigation needs by 15%. While widely replacing meat with plants is logistically and culturally challenging, few competing options offer comparable multidimensional resource use reduction.

We assessed 45 multifamily buildings (240 apartments) from Finland and 20 (96 apartments) from Lithuania, out of which 37 buildings in Finland and 15 buildings in Lithuania underwent energy retrofits. Building characteristics, retrofit activities, and energy consumption data were collected, and Indoor Air Quality (IAQ) parameters, including carbon monoxide (CO), nitrogen dioxide (NO 2 ), formaldehyde (CH 2 O), selected volatile organic compounds (benzene, toluene, ethylbenzene, and xylenes (BTEX), radon, and microbial content in settled dust were measured before and after the retrofits. After the retrofits, heating energy consumption decreased by an average of 24% and 49% in Finnish and Lithuanian buildings, respectively. After the retrofits of Finnish buildings, there was a significant increase in BTEX concentrations (estimated mean increase of 2.5 µg/m 3 ), whereas significant reductions were seen in fungal (0.6-log reduction in cells/m 2 /d) and bacterial (0.6-log reduction in gram-positive and 0.9-log reduction in gram-negative bacterial cells/m 2 /d) concentrations. In Lithuanian buildings, radon concentrations were significantly increased (estimated mean increase of 13.8 Bq/m 3 ) after the retrofits. Mechanical ventilation was associated with significantly lower CH 2 O concentrations in Finnish buildings. The results and recommendations presented in this paper can inform building retrofit studies and other programs and policies aimed to improve indoor environment and health., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

In this experimental study, the feasibility of using the oil obtained from waste fishing net as a substitute for diesel fuel was investigated. Waste fishing net oil (WFNO) was obtained through pyrolysis process on a laboratory scale setup and used as a fuel in diesel engine. The properties of oil obtained from waste fishing net were examined and compared with conventional diesel fuel. Results indicated that the WFNO possesses excellent fuel properties. The calorific value of WFNO is 44,450 kJ/kg, which is higher than diesel by 1.48%. In order to study the possibility of using WFNO and its blends (WFNO 25%, WFNO 50%, WFNO 75% and WFNO 100%) with diesel as a fuel, an experimental investigation was carried out on a single-cylinder, four-stroke diesel engine. Experimental results proved that WFNO works satisfactorily on a diesel engine without any engine modifications. Brake thermal efficiency was decreased and brake-specific fuel consumption was increased while using WFNO and its blends. Moreover, there was a slight increase in engine emissions like CO, UHC, NO with WFNO and its blends.

The yeast Lipomyces accumulates triacylglycerols (TAGs) as intracellular fat globules, and these TAGs can be used as source materials for biodiesel production. In this study, we aimed to use this yeast to produce lipids from renewable resources. Using plate culture and micrograph methods, strains with a high lipid-accumulation ability were screened from 15,408 types of systems combining renewable resources, strains, and culture temperatures. The lipid-accumulation ability of the strains was estimated from the fat globule volume, which was calculated using a micrograph. The reliability of this method was examined, and strains with a high lipid-accumulation ability were identified for each renewable resource. Seventy-seven Lipomyces strains (7 deposit, 68 wild-type, 2 mutants) with a high lipid-accumulation ability were selected. A few strains possessed the ability to accumulate large amounts of TAGs from more than four different renewable resources. We found that strains with a high lipid-accumulation ability could efficiently convert consumed carbon sources into TAGs, which could be easily recovered from the fat globules of these strains through physical disruption.

Energy innovations are critical to combating global warming and climate change. In this context, we focus on the impact of energy research-development (R&D) expenditures, which are the input of energy innovations, on CO 2 emissions. For this purpose, we investigate the effect of disaggregated energy R&D expenditures on CO 2 emission in 19 high-income OECD countries over the period 2003-2015. The dynamic panel data method is followed for empirical analysis. The results of the study show that R&D expenditures for energy efficiency and fossil energy have an increasing effect on CO 2 emissions. Contrary to expectations, there is no significant relationship between renewable energy R&D expenditures and CO 2 emissions. Remarkably, there is strong evidence that the power and storage R&D expenditures have a reducing effect on CO 2 emissions. In light of the empirical findings, policy implications and recommendations to potential readers and authorities are further discussed.

Fossil fuel depletion and the environmental concerns have been under discussion for energy production for many years and finding new and renewable energy sources became a must. Biomass is considered as a net zero CO 2 energy source. Gasification of biomass for H 2 and syngas production is an attractive process. The main target of this research is to improve the production of hydrogen and syngas from palm kernel shell (PKS) steam gasification through defining the optimal operating parameters' using a modern optimization algorithm. To predict the gaseous outputs, two PKS models were built using fuzzy logic based on the experimental data sets. A radial movement optimizer (RMO) was applied to determine the system's optimal operating parameters. During the optimization process, the decision variables were represented by four different operating parameters. These parameters include; temperature, particle size, CaO/biomass ratio and coal bottom ash (CBA) with their operating ranges of (650-750 °C), (0.5-1 mm), (0.5-2) and wt% (0.02-0.10), respectively. The individual and interactive effects of different combinations were investigated on the production of H 2 and syngas yield. The optimized results were compared with experimental data and results obtained from Response Surface Methodology (RSM) reported in literature. The obtained optimal values of the operating parameters through RMO were found 722 °C, 0.92 mm, 1.72 and 0.06 wt% for the temperature, particle size, CaO/biomass ratio and coal bottom ash, respectively. The results showed that syngas production was significantly improved as it reached 65.44 vol% which was better than that obtained in earlier studies., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Moving resource management and allocation away from sectoral silos to a paradigm founded in integration and leveraging cross-sectoral and trans-disciplinary synergies will result in expanded opportunities for economic development and improved social well-being (Mohtar, 2017; Mohtar and Daher, 2017). Interventions to address complex resource challenges must identify opportunities while cognizant of holistic, system level trade-offs (Daher and Mohtar, 2015; Daher et al., 2018a, b, c). These interventions must be contextualized locally: Texas has spatially varied water scarcity, energy resource abundance, and rapid population growth; in the northeastern United States water quality, drainage, and extreme weather events pose far greater challenges. While the overall system-of-systems quantification of water, energy, food and other interconnected systems remains similar across hotspots, the solutions to the challenges posed within each hotspot are bound by local knowledge, physical resource constraints, and governance challenges. This paper introduces the experience of the Texas A&M University Water-Energy-Food Nexus Initiative (WEFNI) in creating a University wide, three-year investigatory experience in which an interdisciplinary group addressed the resource challenges facing the San Antonio region. This Science of the Total Environment (STOTEN) Special Issue documents, in 9 distinct, yet complementary, research articles, the multiple dimensions of this resource hotspot. This paper reflects on the process of creating interdisciplinary teams and presents an overview of the questions and research conducted under thematic foci: data and modeling, trade-off analysis, water for food, water for energy, and governance. Lessons learned from the interdisciplinary experience are presented; potentially transferrable to addressing other resource hotspots within the US, and globally., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Energy is a foundation for a city to create economic wealth, satisfy people's desires, and achieve benefits. However, the increasing mismatch between energy supply and demand and the worsening of environmental pollution have highlighted the importance of improving urban energy performance, so the number of studies related to urban energy performance evaluation is increasing. Based on describing the authors, numbers, regional sources, and themes of these studies, this paper reviews and analyzes the conceptions, evaluation indicators, influencing factors, evaluation methods, and evaluation systems related to urban energy performance. Most countries have expressed concern about this topic. Researchers in China, Belgium, and the USA have had the most achievements and collaborations. The concept of urban energy performance further extends to a comprehensive performance. It is measured based on an input-output process. In addition to the original evaluation indicators, new desirable outputs and undesirable outputs are included. Industrial structure, energy price, population density, home car ownership, climate factors, Gini coefficient, health expenditure level, and unemployment rate are regarded as influencing factors. Therefore, a new framework of evaluation indicators and influencing factors is constructed. Stochastic frontier analysis (SFA) and data envelopment analysis (DEA) are commonly used to evaluate. With changes in conceptions, evaluation indicators, and influencing factors, the evaluation method should rather focus on measuring multiple input-output variables, determining the evaluation results and the impacts of factors at the same analysis stage, and highlighting policy orientations. As an important management tool, the evaluation system would continue to be studied and developed.

Many campaigns targeting pro-environmental behavior combine multiple approaches without properly understanding how these different approaches interact. Here we study the effect of such combinations. We apply construal level theory to classify different intervention approaches, which can either be at a high construal level (abstract and distant) or at a low construal level (concrete and proximal). In a field experiment we recruited 197 students living in one-person apartments in an all-inclusive student housing facility. We objectively measured their individual electricity and warm water use, and measured psychological variables through surveys. We expected that the (commonly considered superior) combination between a high and a low construal level approach would be least effective. Participants were randomly assigned to a 2(Construal Level: low vs. high) × 2(Social Distance: low vs. high) plus control condition mixed-model design targeting a reduction in warm water use. Our findings suggest that a congruent combination at a high construal level (i.e., the high construal level condition combined with the high social distance condition) has the largest effect on warm water use and that spillover to electricity use is most likely to occur when a high construal level is used (i.e., high social distance). Moreover, especially participants who valued nature and the environment less were most strongly influenced by the combination of two high construal level approaches. In sum, our study suggests that when designing interventions one should consider the construal level and when targeting pro-environmental behavior high construal levels appear most appropriate., Competing Interests: The authors have declared that no competing interests exist.

The development path of the lighting industry in mainland China was studied in this work. Lighting electricity accounts for about 12% of social electricity consumption in mainland China, while only approximately 15% of electricity is conversed into light when incandescent light bulbs are used. To reduce electrical energy consumption and mercury emission from coal burning in the lighting industry, China worked out a roadmap to replace incandescent light bulbs with energy-saving fluorescent lamps (FLs). However, FL products utilize mercury to give out light and release mercury in their production, consumption and disposal processes. Therefore, the challenges of the lighting industry that mainland China are facing are controlling mercury pollution through the environmentally-friendly producing of fluorescent lamps, effective collecting and treating of spent fluorescent lamps. It was proposed that to effectively reduce energy consumption and mercury pollution, a good way to do this is developing energy-saving and mercury-free light emitting diode lighting industry. The mainland China Government's strategies to develop lighting industry are worthy of consideration and emulation by other countries.

The recent decades have witnessed refrigeration systems playing an important role in the life of human beings, with wide applications in various fields, including building comfort, food storage, food transportation and the medical special care units. However, if the temperature is not controlled well, it will lead to many harmful public health effects, such as the human being catching colds, food spoilage and harm to the recovering patients. Besides, refrigeration systems consume a significant portion of the whole society's electricity usage, which consequently contributes a considerable amount of carbon emissions into the public environment. In order to protect human health and improve the energy efficiency, an optimal control strategy is designed in this paper with the following steps: (1) identifying the refrigeration system model based on a least squares method; (2) tuning an initial group of parameters of the proportional-integral-derivative (PID) controller via the pidTuner Toolbox of Matlab; (3) using an intelligent algorithm, namely fruit fly optimization (FOA), to further optimize the parameters of the PID controller. By comparing the optimal PID controller and the controller provided in the reference, the simulation results demonstrate that the proposed optimal PID controller can produce a more controllable temperature, with less tacking overshoot, less settling time, and more stable performance under a constant set-point.

Information concerning carbon reduction efficiency is of great significance to supply chain operations. Considering the impact of information asymmetry on the performance of low-carbon supply chain, we therefore analyze a chain system with a single product designer and a single manufacturer. The manufacturer owns information on carbon reduction efficiency, whereas the product designer only knows that the carbon reduction efficiency of the manufacturer is either high or low. To induce the manufacturer to reveal his true private information of carbon-reduction efficiency to the product designer, we devise the pooling and separating equilibrium models to compare the impacts of these two models on supply chain performance, respectively. We find that the high-efficiency manufacturer gets his first-best choice at the equilibrium decision in the separating model, and obtains the information rent in the pooling model. The information rent increases in the efficiency difference between the two emission-reduction types. Additionally, we examine how the probability of the high (or low)-efficiency manufacturer being chosen impacts on both the profits of chain members and carbon-reduction levels. The research provides a reference for companies about how to cooperate with partner who possess private information of carbon emissions.

Improved quality of life has led to a growing demand for better indoor air quality (IAQ). Buildings are becoming more airtight and insulated in order to minimize energy consumption. The importance of both energy conservation and IAQ improvement has been recognized and addressed by many studies. Bake-out is the process of using indoor heating to remove volatile compounds present in building materials and furnishings so that they can be vented out into the atmosphere. Indiscriminate use of heating to increase the surface temperature of materials during this process can result in significant loss of energy. Therefore, energy-efficient bake-out should be performed by considering both the floor temperature and the emission amount of pollutants. This study aims to investigate an effective and economical bake-out implementation strategy via experimentation and computational fluid dynamics analysis. The results showed weak direct correlation between the heating energy consumption and the amount of pollutants emitted. The study also highlights the passive option of installing sorptive building materials for improving IAQ economically.

Ensuring that the wealth of resources contained in our oceans are managed and developed in a sustainable manner is a priority for the emerging 'blue economy'. However, modern ecosystem-based management approaches do not translate well to regions where we know almost nothing about the individual species found in the ecosystem. Here, we propose a new taxon-focused approach to deep-sea conservation that includes regulatory oversight to set targets for the delivery of taxonomic data. For example, a five-year plan to deliver taxonomic and genomic knowledge on a thousand species in regions of the ocean earmarked for industrial activity is an achievable target. High-throughput, integrative taxonomy can, therefore, provide the data that is needed to monitor various ecosystem services (such as the natural history, connectivity, value and function of species) and to help break the regulatory deadlock of high-seas conservation., Competing Interests: AG, HW, CC, TD No competing interests declared, (© 2018, Glover et al.)

Additional degrees of freedom existed in dual-motor coupling system bring considerable challenge to the optimal control of electric vehicles. Moreover, the stochastic characteristic of vehicle mass can further increase this challenge. A receding horizon control (RHC) strategy in consideration of stochastic vehicle mass is proposed in this study to respond to this challenge. Aiming at an electric vehicle with dual-motor coupling, a Markov chain is firstly deployed to predict future driving conditions by a formulated state transition probability matrix, based on historical driving cycles in real-world. Then, future required power is predicted by the predicted driving conditions, stochastic vehicle mass and road gradient, where the stochastic vehicle mass is formulated as stochastic variables in different bus stops. Finally, dynamic programming is employed to calculate the optimal vector of the vehicle within the defined prediction horizon, and only the first control values extracted from the optimal control vector are used to execute real-time power distribution control. The simulation results show that the proposed strategy is reasonable and can at least reduce electric consumption by 4.64%, compared with rule-based strategy., Competing Interests: The authors have declared that no competing interests exist.