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EPOCHS. IV. SED Modeling Assumptions and Their Impact on the Stellar Mass Function at 6.5 ≤ z ≤ 13.5 Using PEARLS and Public JWST Observations
No full textWe utilize deep JWST Near Infrared Camera (NIRCam) observations for the first direct constraints on the Galaxy Stellar Mass Function (GSMF) at z > 10. Our EPOCHS v1 sample includes 1120 galaxy candidates at 6.5 < z < 13.5 taken from a consistent reduction and analysis of publicly available deep JWST NIRCam data covering the Prime Extragalactic Areas for Reionization Science, CEERS, GLASS, JADES GOOD-S, NGDEEP, and SMACS0723 surveys, totaling 187 arcmin2. We investigate the impact of spectral energy distribution fitting methods, assumed star formation histories (SFHs), dust laws, and priors on galaxy masses and the resultant GSMF. While our fiducial GSMF agrees with the literature at z < 13.5, we find that the assumed SFH model has a large impact on the GSMF and stellar mass density (SMD), finding a 0.75 dex increase in the SMD at z = 10.5 between a flexible nonparametric and standard parametric SFH. Overall, we find a flatter SMD evolution at z ≥ 9 than some studies predict, suggesting a rapid buildup of stellar mass in the early Universe. We find no incompatibility between our results and those of standard cosmological models, as suggested previously, although the most massive galaxies may require a high star formation efficiency. We find that the “little red dot” galaxies dominate the z = 7 GSMF at high masses, necessitating a better understanding of the relative contributions of active galactic nucleus and stellar emission. We show that assuming a theoretically motivated top-heavy initial mass function (IMF) reduces stellar mass by 0.5 dex without affecting fit quality, but our results remain consistent with existing cosmological models with a standard IMF
Two-stage scheduling optimization model and benefit allocation strategy for virtual power plant clusters aggregated by multidimensional information indicators
No full textWith the large-scale integration of distributed energy resources into the distribution network, virtual power plant clusters (VPPs) control based on "intra-group autonomy and inter-group coordination" can reduce the difficulty of grid operation and control. Effective cluster partitioning is the key to realize the optimal operation of VPPs. Based on different types of distributed energy flexibility output models, this paper proposes the structural-functional aggregation strategy for VPPs. Additionally, A two-stage robust scheduling optimization model for VPPs is proposed. This model considers a multi-subject cooperative game for calculating the optimal operation strategy of the system. The solution algorithm is constructed through the integration of strong dyadic theory and the C&CG algorithm. Then, an improved Shapley-based benefit allocation strategy for VPPs by the cooperative game is proposed. Finally, an example analysis is carried out in Huangyuan County, Xining City, Qinghai Province, China. The results show that: (1) The proposed structure-function aggregation optimization strategy, the self-balancing indicator of the system increased by 24.65 %, and the upward flexibility deficit and downward flexibility deficit decreased by 72.52 MW and 94.92 MW, compared to the case where the distributed energy sources are independently connected to the grid.(2) The proposed two-stage scheduling optimization model for VPPs reduces the required balancing power by 58.37 %. Compared to the non-considered robustness factor, the average energy supply cost of the proposed model is reduced by 12.02¥/MW. (3) Utilizing the proposed two-layer benefit allocation strategy, the profits obtained by VPPs for 45.49 %, 26.03 %, and 28.49 % of the total incremental gains. Non-Adjustable Generation Unit (Non-AGU) needs to make a profit of 29.09¥/MWh due to the uncertainty of output. Adjustable Generation Unit (AGU), Energy Storage Device (ESD) and Adjustable Load (AL) gain 6.24¥/MWh, 18.16¥/MWh, and 4.67¥/MWh. Overall, the two-stage scheduling optimization model and benefit allocation strategy for VPPs aggregated by multidimensional information indicators can promote the aggregation of distributed energy resources It is conducive to the overall energy structure transformation, improve new energy consumption, and promote the power system structure transformation
Mercury bioaccumulation and assimilation in marine plankton in meltwater influenced fjords and shelf waters along the east coast of Greenland
No full textThe rapid melting of the Arctic cryosphere due to climate change will result in significant freshwater input into Arctic marine ecosystems. This might also cause the release of legacy mercury (Hg) stored in the cryosphere, increasing Hg concentration and its subsequent effects on the marine biota. However, there is scarce knowledge on the concentration of Hg in the lower trophic level organisms at the base of the Arctic pelagic food web. This is particularly important since these organisms modulate the transfer of Hg to higher trophic levels, including fish and marine mammals. We quantified the Hg concentration in two plankton size classes (> 200 and 50 - 200 μm) in coastal waters along the east Greenland coast and investigated the potential assimilation efficiency of both inorganic Hg (IHg) and methyl Hg (MeHg) in mesozooplankton and their faecal pellets in experimental incubations. The concentration of Hg in plankton ranged from 12 to 109 ng (g dw)-1 without clear trends between geographic locations or between fjords and coastal areas. Also, the concentrations did not vary between the different plankton size fractions. MeHg concentrations were lower in the mesozooplankton faecal pellets than IHg, which may be due to the higher assimilation of MeHg than IHg in mesozooplankton tissue. Our results confirm that Arctic zooplankton assimilates MeHg more efficiently than IHg and may contribute significantly to the partitioning and cycling of different Hg types in Arctic marine ecosystems
Unraveling thermodynamic anomalies of water: A molecular simulation approach to probe the two-state theory with atomistic and coarse-grained water models
No full textThermodynamic and dynamic anomalies of water play a crucial role in supporting life on our planet. The two-state theory attributes these anomalies to a dynamic equilibrium between locally favored tetrahedral structures (LFTSs) and disordered normal liquid structures. This theory provides a straightforward, phenomenological explanation for water's unique thermodynamic and dynamic characteristics. To validate this two-state feature, it is critical to unequivocally identify these structural motifs in a dynamically fluctuating disordered liquid. In this study, we employ a recently introduced structural parameter (θavg) that characterizes the local angular order within the first coordination shell to identify these LFTSs through molecular dynamics simulations. We employ both realistic water models with a liquid-liquid critical point (LLCP) and a coarse-grained water model without an LLCP to study water's anomalies in low-pressure regions below 2 kbar. The two-state theory consistently describes water's thermodynamic anomalies in these models, both with and without an LLCP. This suggests that the anomalies predominantly result from the two-state features rather than criticality, particularly within experimentally accessible temperature-pressure regions
Distribution characteristics and transformation mechanism of <i>per</i>- and polyfluoroalkyl substances in drinking water sources: A review
No full textPer- and polyfluoroalkyl substances (PFASs) have raised significant concerns within the realm of drinking water due to their widespread presence in various water sources. This prevalence poses potential risks to human health, ecosystems, and the safety of drinking water. However, there is currently a lack of comprehensive reviews that systematically categorize the distribution characteristics and transformation mechanisms of PFASs in drinking water sources. This review aims to address this gap by concentrating on the specific sources of PFASs contamination in Chinese drinking water supplies. It seeks to elucidate the migration and transformation processes of PFASs within each source, summarize the distribution patterns of PFASs in surface and subsurface drinking water sources, and analyze how PFASs molecular structure, solubility, and sediment physicochemical parameters influence their presence in both the water phase and sediment. Furthermore, this review assesses two natural pathways for PFASs degradation, namely photolysis and biodegradation. It places particular emphasis on understanding the degradation mechanisms and the factors that affect the breakdown of PFASs by microorganisms. The ultimate goal is to provide valuable insights for the prevention and control of PFAS contamination and the assurance of drinking water quality
Cumulative Impacts of Oil Pollution, Ocean Warming, and Coastal Freshening on the Feeding of Arctic Copepods
No full textThe Arctic is undergoing rapid changes, and biota are exposed to multiple stressors, including pollution and climate change. Still, little is known about their joint impact. Here, we investigated the cumulative impact of crude oil, warming, and freshening on the copepod species Calanus glacialis and Calanus finmarchicus. Adult females were exposed to ambient conditions (control; 0 °C + 33 psu) and combined warming and freshening: 5 °C + 27 psu (Scenario 1), 5 °C + 20 psu (Scenario 2) for 6 days. All three conditions were tested with and without dispersed crude oil. In Scenario 1, fecal pellet production (FPP) significantly increased by 40-78% and 42-122% for C. glacialis and C. finmarchicus, respectively. In Scenario 2, FPP decreased by 6-57% for C. glacialis, while it fluctuated for C. finmarchicus. For both species, oil had the strongest effect on FPP, leading to a 68-83% reduction. This overshadowed the differences between climatic scenarios. All variables (temperature, salinity, and oil) had significant single effects and several joint effects on FPP. Our results demonstrate that Arctic copepods are sensitive to environmentally realistic concentrations of crude oil and climate change. Strong reductions in feeding can reduce the copepods' energy content with potential large-scale impacts on the Arctic marine food web
Ionic liquid binary mixtures:Machine learning-assisted modeling, solvent tailoring, process design, and optimization
No full textThis work conducts a comprehensive modeling study on the viscosity, density, heat capacity, and surface tension of ionic liquid (IL)-IL binary mixtures by combining the group contribution (GC) method with three machine learning algorithms: artificial neural network, XGBoost, and LightGBM. A large number of experimental data from reliable open sources is exhaustively collected to train, validate, and test the proposed ML-based GC models. Furthermore, the Shapley Additive Explanations technique is employed to quantify the influential factors behind all the studied properties. Finally, these ML-based GC models are sequentially integrated into computer-aided mixed solvent design, process design, and optimization through an industrial case study of recovering hydrogen from raw coke oven gas. Optimization results demonstrate their high computational efficiency and integrability in solvent and process design, while also highlighting the significant potential of IL-IL binary mixtures in practical applications.</p
Chitosan-coated Oleaginous Microalgae-Fungal Pellets for Improved Bioremediation of Non-sterile Secondary Effluent and Application in Carbon Dioxide Sequestration in Bubble Column Photobioreactors
No full textOleaginous microalga Scenedesmus sp. SPP was rapidly immobilized in oleaginous fungal pellets by their opposite-surface-charges. Microalgae-fungal (MF) pellets were more effective in bioremediation of non-sterile secondary effluent than mono-culture. The optimal hydraulic retention time for dual bioremediation in semi-continuous mode was 72 h. The MF pellets coated with 0.4%-chitosan improved removal efficiencies of COD, total nitrogen (TN), and total phosphorus (TP) up to 96.2±0.0%, 88.2±2.8% and 71.5±0.7%, respectively, likely because of better cell retention and more nutrient adsorption and assimilation. Dual bioremediation by coated MF pellets was also successfully scaled up in 30-L bubble-column photobioreactors with improved COD, TN, and TP removal efficiencies of 98.5±0.0%, 90.2±0.0% and 79.5±2.1%, respectively. This system also effectively removed CO2 from simulated flue gas at 71.2±0.4% and produced biomass with high lipid content. These results highlight the effectiveness of bio-immobilization by fungal pellets; chitosan coating; and their practical applications in bioremediation and CO2 sequestration
The impact of sunlight on fouling behaviors and microbial communities in membrane bioreactors
No full textMembrane fouling is a significant obstacle to applying membrane bioreactors (MBRs) for wastewater treatment. Here we report the impact of sunlight irradiation on membrane fouling, biopolymers, signal molecules, and microbial communities in MBRs. The degradation of signal molecules, which induce membrane biofouling, occurred through solar photolysis in batch tests. However, MBR sludge exposed to sunlight exhibited different biological behaviors creating more soluble microbial products (SMP) and signal molecules (particularly autoinducer-2). Cell lysis and deflocculation occurred when the MBR mixed liquor was exposed to sunlight. MBR fouling rates coincided with the temporal concentration profiles of SMP and signal molecules. Sunlight caused drastic changes in the MBR microbial community, stimulating the preferential growth of specific bacteria (e.g., Deinococcus Runella, Flavitalea, Glaiimonas, and Rurimicrobium). The nonmetric multidimensional scaling analysis of the MBR community structures with and without sunlight irradiation showed two distinct microbial community clusters and their reversibility. Network analysis based on Spearman's rank correlations revealed that with sunlight irradiation, fouling rates had significant positive connections with SMP proteins and the Flavitalea genus. The findings of this study demonstrate that sunlight is a considerable factor affecting membrane fouling and microbial ecology in MBRs, needing shade for fouling mitigation and sustainable operation
Performance improvement of air-based solar photovoltaic/thermal collectors using wavy channels
No full textThe rise in the temperature of photovoltaic (PV) cells leads to a great reduction in their power output; therefore, having a cooling mechanism is critically important to keep the cells of practical benefit in hot climates. The use of wavy surfaces for effective cooling of PV cells seems very promising due to an increased turbulence intensity, generating secondary flows, and improved mixing fluid flows, and has never been studied before. Thus, this study numerically examines the impact of wavy channels with different wavelength (λ), amplitude (α) ratios, and the Reynolds number to reach an optimal geometry for the wavy channel utilized in PV/T collectors using ANSYS CFX. For this purpose, the Reynolds-averaged Navier-stokes equations are applied and the SST k-ω turbulent model is utilized. The results prove the strong impact of the wavy channels where a channel with wavelength & amplitude ratios of 0.1 and 1 has the most increase in the overall efficiency by 20.41% enhancement compared to conventional collectors. In addition, the highest increase in the Nusselt number is 69.7% at λ = 2 and α = 0.2 compared with the smooth channel. At α = 0.3 and λ = 3, the electrical efficiency can be enhanced by up to 1.66% at Re = 40,000