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Since long ago, pelagic Sargassum mats have been known to be abundant in the Sargasso Sea, where they provide habitat to diverse organisms. However, over the last few years, massive amounts of pelagic Sargassum have reached the coast of several countries in the Caribbean and West Africa, causing economic and environmental problems. Aiming for lessening the impacts of the blooms, governments and private companies remove the seaweeds from the shore, but this process results expensive. The valorization of this abundant biomass can render Sargassum tides into an economic opportunity and concurrently solve their associated environmental problems. Despite the diverse fields where algae have found applications and the relevance of this recurrent situation, Sargassum biomass remains without large scale applications. Therefore, this review aims to present the potential uses of these algae, identifying the limitations that must be assessed to effectively valorize this bioresource. Due to the constraints identified for each of the presented applications, it is concluded that a biorefinery approach should be developed to effectively valorize this abundant biomass. However, there is an urgent need for investigations focusing on holopelagic Sargassum to be able to truly valorize this seaweed.

Interest in the highly efficient energy hub (EH) model has been growing despite the high computational requirements of planning for a multi-energy, multi-device operation. To address both the device size limitation and the multi-scenario issue, we propose a new solution methodology for solving the EH planning problem. In the method, the decision variables are device sizes. First, a dimension reduction technique is proposed to address the curse of dimensionality based on the correlation of unknown variables such as the capacities of different devices in an EH. Second, to avoid local convergence, a solution method called the variable-sized unimodal searching (VUS) approach is proposed to assure a global optimal planning scheme for the one-dimensional non-convex optimization model obtained from the preceding dimension reduction process. The case study indicates that the proposed approach has a higher computing efficiency than the Benders decomposition (BD) algorithm to deal with a scenario-based stochastic planning problem with a large number of scenarios. Thus, the effectiveness of the EH planning approach is verified.

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

Abstract Molten salt reactors (MSRs) are a class of next-generation nuclear reactors that have received recent industrial and research interest. A generalized species transport solver was implemented in the Virtual Environment for Reactor Applications (VERA) computing suite to extend this tool to analyze liquid-fueled MSRs. This core simulator has been extended to model the transport of fission product gases into a collection of circulating gas bubbles with the purpose of removing the gases. This paper presents the governing species transport equation, along with various nuclear source terms. Development of the source term for phase migration is discussed, along with a simplified interfacial area tracking method. Finally, a case study on a simplified MSR loop is presented in which modeling parameters were varied to assess their impact on gas removal. The steady state results show that parameters such as bubble diameter, gas injection rate and mass transfer coefficient have a low to moderate effect on the fraction of xenon in the core region. Removal efficiency has the greatest effect on the fraction in the core region. After the pump bowl, bubble diameter has a minor effect on the fraction of xenon in the gas void. These results point out that increasing parameters such as mass transfer coefficient, gas injection rate, and removal efficiency drives the xenon into the circulating gas void, while decreasing bubble diameter also drives xenon into the gas void by increasing interfacial area.

Forest soil acidification caused by acid deposition is a serious threat to the forest ecosystem. To investigate the liming effects of biomass ash (BA) and alkaline slag (AS) on the acidic topsoil and subsoil, a three-year field experiment under artificial Masson pine was conducted at Langxi, Anhui province in Southern China. The surface application of BA and AS significantly increased the soil pH, and thus decreased exchangeable acidity and active Al in the topsoil. Soil exchangeable Ca2+ and Mg2+ in topsoil were significantly increased by the surface application of BA and AS, while an increase in soil exchangeable K+ was only observed in BA treatments. The soil acidity and active Al in subsoil were decreased by the surface application of AS. Compared with the control, soluble monomeric and exchangeable Al in the subsoil was decreased by 38.0% and 29.4% after 3 years of AS surface application. There was a minimal effect on soluble monomeric and exchangeable Al after the application of BA. The soil exchangeable Ca2+ and Mg2+ in the subsoil increased respectively by 54% and 141% after surface application of 10 t ha-1 AS. The decrease of soil active Al and increase of base cations in subsoil were mainly attributed to the high migration capacity of base cations in AS. In conclusion, the effect of surface application of AS was superior to BA in ameliorating soil acidity and alleviating soil Al toxicity in the subsoil of this Ultisol.

Load modeling plays an important role in transmission planning studies to anticipate the response of a power system following fault. The composite load model is the latest and the state-of-the-art load model available for transmission planning studies. Many utilities in the US are already using the composite load model or transitioning to use the composite load model for their transmission planning studies. However, the usage of any aggregated load model can in some cases lead to unanticipated and suspect simulation results during certain grid conditions. This paper briefly introduces the composite load model and presents two scenarios where an informed sensitivity study can help transmission planners gain deeper insights into otherwise ambiguous results obtained while using the composite load model during simulations.

Bioenergy is considered a sustainable substitute to fossil-fuel resources and the development of a prudent combination of renewable and innovative conversion technologies are essential for the valorization and effective conversion of biowaste to value-added commodities. Here, a negative pressure-induced carbonization process was proposed for the valorization of lignin-enriched biowaste precursor to bio-oil and environmental materials (biochar) at various temperatures. The high heating values (HHV) of the as-prepared biochars from the lignin enriched precursor under negative pressure (low-medium vacuum) were within 25.9-31.5 MJ/kg, which matched satisfactorily to the commercial charcoal. Whereas, the bio-oils produced from the lignin enriched precursor under vacuum conditions was a blend of complex aromatic and straight-chain hydro-carbons, including aldehyde, ketone, phenol, and furans, exhibiting ability as potential heating-oil with HHV within 21.2-28.2 MJ/kg. Moreover, the biochars produced under vacuum environments at higher temperature showed greater stability (22.5-35.9%) than those produced under N2 atmosphere.

Abstract Background Parabolic Trough Solar Collector (PTSC) is one of the most popular and an effective device that converts solar radiation into a heat or useful energy. However, it suffers from high temperature gradient and low thermal efficiency. The solution for this problem is to use new advanced coolants (hybrid nanofluids) in order to enhance PTSC's thermal efficiency. Methods A numerical analysis on the thermo-hydraulic performance of a PTSC receiver's tube equipped with conical turbulators is presented. The Navier-Stokes equations are solved using Finite Volume Method (FVM) coupled with Monte Carlo Ray Tracing (MCRT) method. The flow and thermal characteristics as well as entropy generation of the PTSC's receiver tube are investigated for three hybrid nanofluids (Ag-SWCNT, Ag-MWCNT, and Ag-MgO) having a mixing ratio of (50:50) dispersed in Syltherm oil 800, Reynolds number (5000 to 100,000) and fluid inlet temperatures (400 to 650 K). Significant findings The conical turbulators effectively augmented the thermal performance by 233.4% utilising Ag-SWCNT/Syltherm oil instead of pure Syltherm oil. The performance evaluation criterion is found to be in the range of 0.9–1.82. The thermal and exergetic efficiencies increased by 11.5% and 18.2%, respectively. The maximum decrement in the entropy generation rate and entropy generation ratio are 42.7% and 33.7%.

Many vulnerable people lose their health or lives each year as a result of unhealthy environmental conditions that perpetuate medical conditions within the scope of allergy and immunology specialists' expertise. While detrimental environmental factors impact all humans globally, the effect is disproportionately more profound in impoverished neighborhoods. Environmental injustice is the inequitable exposure of disadvantaged populations to environmental hazards. Professional medical organizations such as the American Academy of Allergy, Asthma & Immunology (AAAAI) are well positioned to engage and encourage community outreach volunteer programs to combat environmental justice. Here we discuss how environmental injustices and climate change impacts allergic diseases among vulnerable populations. We discuss pathways allergists/immunologists can use to contribute to addressing environmental determinants by providing volunteer clinical service, education, and advocacy. Furthermore, allergists/immunologists can play a role in building trust within these communities, partnering with other patient advocacy nonprofit stakeholders, and engaging with local, state, national, and international nongovernmental organizations, faith-based organizations, and governments. The AAAAI's Volunteerism Addressing Environmental Disparities in Allergy (VAEDIA) is the presidential task force aiming to promote volunteer initiatives by creating platforms for discussion and collaboration and by funding community-based projects to address environmental injustice.