Integration of Biogas Upgrading and Enzyme-boosted CO2 Mineralization for Eco-friendly and Cost-effective Production of Synthetic Aggregates
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03 NATURAL GAS↗
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Investigation of competitive sorption and plasticization of hyperaged CANAL ladder polymers for acid gas purification
Identifying membrane materials that have exceptional separation performance and stability to complex CO 2 -containing mixtures is a pressing topic in separation science. In this work, the membrane separation performance for a recently discovered class of contorted polymers synthesized via catalytic arene-norbornene annulation (CANAL) polymerization is presented. These CANAL polymers achieve high CO 2 /CH 4 selectivity of 68 after physical aging (up to ∼1 year), which significantly augments the size-sieving capabilities of the membranes. Binary CO 2 /CH 4 and ternary H 2 S/CO 2 /CH 4 testing result in a 41 % and 50 % enhancement in selectivities, respectively, for hyperaged (∼1 year) contorted CANAL polymers, highlighting their size-sieving capabilities. The remarkably high CO 2 /CH 4 mixed-gas and combined acid gas (CAG, (CO 2 +H 2 S)/CH 4 ) selectivities of 88 and 95, respectively, for CANAL-Me-S 5 F in particular surpass both the 2018 CO 2 /CH 4 mixed-gas and CAG upper bounds. Performance stability was also investigated for high concentrations of CO 2 , revealing a reduction in CO 2 /CH 4 mixed-gas selectivity without compromising CO 2 permeability, suggesting strong sorption of CO 2 but minimal plasticization effects for short testing periods. In addition, time-dependent plasticization shows negligible effects on CO 2 /CH 4 mixed-gas selectivity despite an increase in CO 2 permeability when exposed to high concentrations of plasticizing CO 2 over an extended period of 170 h. This study provides valuable insights into hyperaged CANAL polymers and their performance in practical industrial processes.
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Why Boron Nitride is such a Selective Catalyst for the Oxidative Dehydrogenation of Propane
Boron–containing materials, and in particular boron nitride, have recently been identified as highly selective catalysts for the oxidative dehydrogenation of alkanes such as propane. To date, no mechanism exists that can explain both the unprecedented selectivity, the observed surface oxyfunctionalization, and the peculiar kinetic features of this reaction. Here, we combine catalytic activity measurements with quantum chemical calculations to put forward a bold new hypothesis. We argue that the remarkable product distribution can be rationalized by a combination of surface–mediated formation of radicals over metastable sites, and their sequential propagation in the gas phase. Based on known radical propagation steps, we quantitatively describe the oxygen pressure–dependent relative formation of the main product propylene and by–product ethylene. Free radical intermediates most likely differentiate this catalytic system from less selective vanadium–based catalysts.
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Highly Selective Carbon-Supported Boron for Oxidative Dehydrogenation of Propane
Bulk boron materials, such as hexagonal boron nitride (h-BN), are highly selective catalysts for the oxidative dehydrogenation of propane (ODHP). Previous attempts to improve the productivity of these systems involved the immobilization of boron on silica and resulted in less selective catalysts. Here, we report that acid-treated, activated carbon-supported boron prepared via incipient wetness impregnation with boric acid (B/OAC) exhibits equal propylene selectivity and improved productivity (kg propylene kg cat -1 hr -1 ) as compared to h-BN. Characterization of the fresh and spent catalysts with infrared, Raman, X-ray photoelectron, and solid-state NMR spectroscopies reveals the presence of oxidized/hydrolyzed boron that is clustered on the surface of the support.
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Characterization of ambient polychlorinated biphenyl background conditions in surface waters of the Pajarito Plateau, New Mexico
Abstract This study presents the development of polychlorinated biphenyl (PCB) background threshold values (BTVs) that statistically characterize ambient background conditions for surface waters in undeveloped and developed landscapes of the Pajarito Plateau in the Rio Grande Basin of New Mexico. Between 2009 and 2018, surface water data were collected at 45 locations under a variety of flow conditions and regimes. A total of 163 samples were collected, with roughly 1/3 of samples and locations being in undeveloped areas (n = 53 from 17 locations), and the remainder being in developed areas (n = 110 from 28 locations). While there are areas on the Pajarito Plateau where PCB point sources are known or likely to have contributed to PCBs in soils, PCB BTVs calculated for undeveloped portions of watersheds (upstream of areas where PCB point sources are known or likely to have contributed to PCBs in soils, and therefore not affected by PCB sources within the watershed) are well above New Mexico's human health organism-only (HH-OO) water quality criterion (0.64 ng/L). Background threshold values are even higher in developed areas upstream of managed soil sites, suggesting that in developed areas, both diffuse ambient PCB sources (e.g., atmospheric deposition) and localized urban sources (e.g., building materials, paints, and electrical equipment) contribute to PCBs in those watersheds. These findings indicate that New Mexico's current HH-OO water quality criterion for PCBs cannot practicably be met due to ambient conditions. It is also impracticable to meet the US Environmental Protection Agency (EPA) criterion continuous concentration (CCC) of 14 ng/L in developed background areas, where the BTV is approximately 1.5 times the CCC. Integr Environ Assess Manag 2023;19:1307–1319. © 2022 SETAC
54 ENVIRONMENTAL SCIENCES↗
Recent Advances in the Understanding of Boron-Containing Catalysts for the Selective Oxidation of Alkanes to Olefins
The production of ethylene and propylene through aerobic alkane oxidation without significant coproduction of CO and CO 2 (CO x ) presents a challenge to academic and industrial researchers alike. Recently, boron-containing materials such as hexagonal boron nitride (hBN) have been identified as active and selective catalysts for the oxidative dehydrogenation (ODH) of propane to propylene with minimal CO x selectivity. Additionally, high olefin selectivity is also obtained in the oxidation of other alkanes and other materials such as metal borides and supported B/SiO 2 have been successfully applied to this transformation. Here, recent advances in the understanding of these catalysts in the oxidation of light alkanes are presented here providing a framework for further study of this exciting field.
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O 2 dosage as a descriptor of TWC performance under lean/rich dithering in stoichiometric natural gas engines
The effects of oscillations in gas composition, known as lean/rich dithering, on the performance of a commercial Pd-based three-way catalyst (TWC) for stoichiometric natural gas (NG) engines were evaluated using synthetic exhaust flow reactor experiments. Under simulated NG exhaust conditions, NO conversion was intimately correlated to CH 4 conversion at slightly fuel-rich operating conditions. CH 4 conversion significantly varied with lambda (or O 2 concentration) and depended on the direction of the lambda change. The dynamic CH 4 conversion is likely related to the change of catalyst oxidation state and structures of Pd active sites. The CH 4 -NO cross-over point was found at a rich-biased lambda rather than stoichiometry. Compared to static operation, catalyst performance was much higher under a realistic dithering condition. The impacts of dithering parameters including amplitude and frequency on CH 4 and NO conversions were explored. O 2 dosage is proposed as an effective descriptor of the TWC dithering performance. In the O 2 -dosage space, the performance of distinct dithering parameters collapse, helping to elucidate the fundamental influence of dithering parameters on TWC performance. With the help of O2 dosage, an optimal operating window leading to high CH 4 and NO conversions was identified. A higher dithering amplitude is required to keep the catalyst in a reduced state for higher CH 4 and NO conversions, while an appropriate O 2 dosage that does not exceed the breakthrough OSC is necessary to avoid excess O 2 that results in NO slip. The dithering amplitude and O 2 -dosage-metric maps provide a new method for studying dynamic TWC performance and identifying optimum operation strategies.
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The Dynamic Temperate and Boreal Fire and Forest-Ecosystem Simulator (DYNAFFOREST): Development and evaluation
Not Available
54 ENVIRONMENTAL SCIENCES↗
Thermal and solubility effects on fault leakage during geologic carbon storage
Geologic carbon storage (GCS) is a promising method for reducing anthropogenic CO 2 emissions to the atmosphere. To safely deploy GCS in the field, it is necessary to assess risks and the effect of uncertainty on safe storage. The effect of uncertainty can be quantified using batches of simulations, but the high computational costs of high-resolution simulations necessitate use of reduced-order models (ROMs). Previous work involves ROMs for quantifying the risk of different potential leakage paths from storage reservoirs to shallow formations. However, previous studies on development of fault-leakage ROMs have limited numbers of uncertain parameters and do not explicitly examine impacts of CO 2 solubility and thermal stresses on fault reactivation, which can generate high-permeability pathways and compromise CO 2 storage. Here, we analyze an ensemble of simulations considering CO 2 leakage from a storage reservoir to a shallow aquifer through a fault while varying a number of uncertain parameters related to thermo-hydro-mechanical properties and CO 2 injection. We show the effects of solubility on: free-phase CO 2 -leakage rates, brine-leakage rates, and poroelastic fault destabilization. We find that CO 2 solubility is more important for estimating free-phase CO 2 -leakage rates compared to brine-leakage rates or poroelastic fault destabilization. We also find that thermal stresses and overpressures have different spatial distributions within the fault, indicating that the spatial variability of overpressures due to variation in flow parameters does not necessarily make the spatial variability of thermal stresses negligible. We suggest the use of the CO 2 phase-change path as a variable in future fault-leakage ROMs.
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Corrosion protection of steel pipelines with metal-polymer composite barrier liners
Pipelines are efficient in transporting natural gas over large distances. Wet carbon dioxide present in pipelines can create an environment that is corrosive to steel. Polymer liners made from either polyethylene or polyamide (nylon) are presently used to mitigate internal corrosion in natural gas pipelines. Gas diffuses through all polymers over time, and polymer-only liners lower the steel corrosion rate by reducing the reactive gas flux to the internal surface of a pipeline. Composite liners, which incorporate one or more metallic layers that are impermeable to corrosive gases, offer better protection than polymer-only liners. In this study, we measured the methane, water vapor, and carbon dioxide permeability of a multi-layer barrier film and found it to be more effective in resisting gas permeation than polyethylene and nylon-11 films.
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Non-structural carbohydrates mediate seasonal water stress across Amazon forests
Non-structural carbohydrates (NSC) are major substrates for plant metabolism and have been implicated in mediating drought-induced tree mortality. Despite their significance, NSC dynamics in tropical forests remain little studied. We present leaf and branch NSC data for 82 Amazon canopy tree species in six sites spanning a broad precipitation gradient. During the wet season, total NSC (NSC T ) concentrations in both organs were remarkably similar across communities. However, NSC T and its soluble sugar (SS) and starch components varied much more across sites during the dry season. Notably, the proportion of leaf NSC T in the form of SS (SS:NSC T ) increased greatly in the dry season in almost all species in the driest sites, implying an important role of SS in mediating water stress in these sites. This adjustment of leaf NSC balance was not observed in tree species less-adapted to water deficit, even under exceptionally dry conditions. Thus, leaf carbon metabolism may help to explain floristic sorting across water availability gradients in Amazonia and enable better prediction of forest responses to future climate change.
54 ENVIRONMENTAL SCIENCES↗
Photobiological production of high-value pigments via compartmentalized co-cultures using Ca-alginate hydrogels
Abstract Engineered cyanobacterium Synechococcus elongatus can use light and CO 2 to produce sucrose, making it a promising candidate for use in co-cultures with heterotrophic workhorses. However, this process is challenged by the mutual stresses generated from the multispecies microbial culture. Here we demonstrate an ecosystem where S. elongatus is freely grown in a photo-bioreactor (PBR) containing an engineered heterotrophic workhorse (either β-carotene-producing Yarrowia lipolytica or indigoidine-producing Pseudomonas putida ) encapsulated in calcium-alginate hydrogel beads. The encapsulation prevents growth interference, allowing the cyanobacterial culture to produce high sucrose concentrations enabling the production of indigoidine and β-carotene in the heterotroph. Our experimental PBRs yielded an indigoidine titer of 7.5 g/L hydrogel and a β-carotene titer of 1.3 g/L hydrogel, amounts 15–22-fold higher than in a comparable co-culture without encapsulation. Moreover, 13 C-metabolite analysis and protein overexpression tests indicated that the hydrogel beads provided a favorable microenvironment where the cell metabolism inside the hydrogel was comparable to that in a free culture. Finally, the heterotroph-containing hydrogels were easily harvested and dissolved by EDTA for product recovery, while the cyanobacterial culture itself could be reused for the next batch of immobilized heterotrophs. This co-cultivation and hydrogel encapsulation system is a successful demonstration of bioprocess optimization under photobioreactor conditions.
59 BASIC BIOLOGICAL SCIENCES↗
LandScan mosaic enables high-resolution gridded population estimates with explicit uncertainty
Gridded population datasets represent high-resolution distributions of human occupancy, enabling informed decision-making across a broad range of fields. These data products are valuable for assessing environmental risk, urban development, disaster preparedness and resource allocation—areas where accurate population estimates directly enhance policy effectiveness and optimize resource distribution. Despite the importance of gridded population datasets, traditional population modeling approaches often overlook inherent uncertainties in the estimation process. This limitation can create a false sense of certainty in population estimates, potentially leading to flawed decisions by those who rely on the data. To address this methodological gap, we introduce a probabilistic machine learning modeling framework, LandScan Mosaic, that explicitly incorporates uncertainty into the population modeling process. Our approach systematically quantifies uncertainty in three key modeling parameters of the LandScan HD gridded population dataset: building use types, floor counts, and occupancy rates. By employing Monte Carlo simulations, we propagate these uncertainties through the modeling process, yielding probability distributions of population counts in place of deterministic point estimates. We demonstrate the practical application of this framework in Iloilo City, Philippines, using structured decision-making techniques and our probabilistic estimates to identify and prioritize areas most affected by projected flooding, supporting targeted interventions that address both economic and social risks. In doing so, we propose a population-specific approach for incorporating confidence into structured decision making processes. Through a comparative analysis with conventional deterministic approaches and point estimate approaches, including LandScan HD and WorldPop, we evaluate how the incorporation of machine learning and uncertainty influences decision rankings. This research advances population distribution modeling by offering a robust, quantitative approach that explicitly accounts for uncertainty in the underlying data, along with guidance for how users can apply uncertainty in their decision-making.
Environmental sciences↗
Nanocluster and single-atom catalysts for thermocatalytic conversion of CO and CO 2
In this Minireview, we discuss recent advances in understanding nanocluster and single-atom catalysts for CO and CO 2 emissions control applications. Through analyzing thermocatalytic CO oxidation and CO 2 reduction, two fundamentally and industrially important reactions, we compare representative nanocluster and single-atom catalytic systems from perspectives of intrinsic chemistry and reaction engineering. Generally, nanoclusters and single atoms display different catalytic performances (i.e., activity, selectivity, and stability) for these reactions depending on the synthesis methods, support materials, and reaction conditions. Key observations of activity and selectivity tradeoffs between nanoclusters and single-atom catalysts are highlighted. Here, the dynamic structural responses of these catalytic species under CO oxidation or CO 2 reduction reaction conditions are also discussed. Synthetic control and detailed experimental and computational characterization of single-atom and nanocluster catalysts for CO and CO 2 conversion have led to exciting progress over the past decade. Still, more efforts are needed to understand and develop catalysts that meet the environmental, energy, and technical requirements to power a sustainable global economy.
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Oxygenates production in a microfluidic dielectric barrier discharge device sustained in Ar/CH 4 /O 2
Reforming of methane (CH 4 ) is a process to produce syngas (CO/H 2 ) and other value-added chemicals including oxygenates such as methanol (CH 3 OH). Atmospheric pressure plasmas have the potential to be more energy efficient than traditional reforming methods as value-added chemicals can be synthesized directly in the plasma without requiring an additional step. In this paper, we discuss the results from a computational investigation of the formation of oxygenates by CH 4 oxidation in the presence of Ar, including CH 3 OH and CH 2 O, in a nanosecond pulsed dielectric barrier discharge. The plasma is formed in a microfluidic channel whose small dimensions are ideal for plasma formation at atmospheric pressure. The production and consumption mechanisms of dominant radicals and long-lived species are discussed in detail for the base case conditions of Ar/CH 4 /O 2 = 50/25/25. CH 3 OH is produced primarily by CH 3 O reacting with CH 3 O and CH 3 O 2 reacting with OH, while CH 2 O formation relies on reactions involving CH 3 O and CH 3 . The most abundant oxygenate formed is CO (produced by H abstraction from CHO). However, the greenhouse gas CO 2 is also formed as a by-product. The effects of gas mixture are examined to maximize the CH 3 OH and CH 2 O densities while decreasing the CO 2 density. Increasing the Ar percentage from 0% to 95% decreased the CH 3 OH and CH 2 O densities. At low Ar percentages, this is due to an increase in consumption of CH 3 OH and CH 2 O, while at high Ar percentages (>40% Ar), the production of CH 3 OH and CH 2 O is decreased. However, both CO and CO 2 reached peak densities at 70%–90% Ar. Changing the CH 4 /O 2 ratio while keeping 50% Ar in the discharge led to increased CH 3 OH and CH 2 O production, reaching peak densities at 35%–40% CH 4 . The CO and CO 2 densities decreased beyond 20% CH 4 , indicating that a CH 4 rich discharge is ideal for forming the desired oxygenates.
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Cytochromes P450 involved in bacterial RiPP biosyntheses
Abstract Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a large class of secondary metabolites that have garnered scientific attention due to their complex scaffolds with potential roles in medicine, agriculture, and chemical ecology. RiPPs derive from the cleavage of ribosomally synthesized proteins and additional modifications, catalyzed by various enzymes to alter the peptide backbone or side chains. Of these enzymes, cytochromes P450 (P450s) are a superfamily of heme-thiolate proteins involved in many metabolic pathways, including RiPP biosyntheses. In this review, we focus our discussion on P450 involved in RiPP pathways and the unique chemical transformations they mediate. Previous studies have revealed a wealth of P450s distributed across all domains of life. While the number of characterized P450s involved in RiPP biosyntheses is relatively small, they catalyze various enzymatic reactions such as C–C or C–N bond formation. Formation of some RiPPs is catalyzed by more than one P450, enabling structural diversity. With the continuous improvement of the bioinformatic tools for RiPP prediction and advancement in synthetic biology techniques, it is expected that further cytochrome P450-mediated RiPP biosynthetic pathways will be discovered. Summary The presence of genes encoding P450s in gene clusters for ribosomally synthesized and post-translationally modified peptides expand structural and functional diversity of these secondary metabolites, and here, we review the current state of this knowledge.
59 BASIC BIOLOGICAL SCIENCES↗
Computer-aided, resistance gene-guided genome mining for proteasome and HMG-CoA reductase inhibitors
Secondary metabolites (SMs) are biologically active small molecules, many of which are medically valuable. Fungal genomes contain vast numbers of SM biosynthetic gene clusters (BGCs) with unknown products, suggesting that huge numbers of valuable SMs remain to be discovered. It is challenging, however, to identify SM BGCs, among the millions present in fungi, that produce useful compounds. One solution is resistance gene-guided genome mining, which takes advantage of the fact that some BGCs contain a gene encoding a resistant version of the protein targeted by the compound produced by the BGC. The bioinformatic signature of such BGCs is that they contain an allele of an essential gene with no SM biosynthetic function, and there is a second allele elsewhere in the genome. We have developed a computer-assisted approach to resistance gene-guided genome mining that allows users to query large databases for BGCs that putatively make compounds that have targets of therapeutic interest. Working with the MycoCosm genome database, we have applied this approach to look for SM BGCs that target the proteasome β6 subunit, the target of the proteasome inhibitor fellutamide B, or HMG-CoA reductase, the target of cholesterol reducing therapeutics such as lovastatin. Our approach proved effective, finding known fellutamide and lovastatin BGCs as well as fellutamide- and lovastatin-related BGCs with variations in the SM genes that suggest they may produce structural variants of fellutamides and lovastatin. Gratifyingly, we also found BGCs that are not closely related to lovastatin BGCs but putatively produce novel HMG-CoA reductase inhibitors.
59 BASIC BIOLOGICAL SCIENCES↗
An Uncertainty Management Framework for Integrated Gas-Electric Energy Systems
In many parts of the world, electric power systems have seen a significant shift toward generation from renewable energy and natural gas. Because of their ability to flexibly adjust power generation in real time, gas-fired power plants are frequently seen as the perfect partner for variable renewable generation. However, this reliance on gas generation increases interdependence and propagates uncertainty between power grids and gas pipelines and brings coordination and uncertainty management challenges. To address these issues, we propose an uncertainty management framework for uncertain, but bounded gas consumption by gas-fired power plants. The admissible ranges are computed based on a joint optimization problem for the combined gas and electricity networks, which involves chance-constrained scheduling for the electric grid and a novel robust optimization formulation for the natural-gas network. This formulation ensures feasibility of the integrated system with a high probability, while providing a tractable numerical formulation. A key advance with respect to existing methods is that our method is based on a physically accurate, validated model for transient gas pipeline flows. Our case study benchmarks our proposed formulation against methods that ignore how reserve activation impacts the fuel use of gas power plants and only consider predetermined gas consumption. Here, the results demonstrate the importance of considering uncertainty to avoid operating constraint violations and curtailment of gas to the generators.
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