Net Production Rates Research Articles

Enhancing reef carbonate budgets through coral restoration.

Complex reef structure, built via calcium carbonate production by stony corals and other calcifying taxa, supports key ecosystem services. However, the decline in coral cover on reefs of the Florida Reef Tract (US), caused by ocean warming, disease, and other stressors, has led to erosion exceeding accretion, causing net loss of reef framework. Active coral restoration, aimed at rapidly increasing coral cover, is essential for recovering reef structure and function. Traditionally, restoration success focused on the survivorship and growth of transplanted corals. This is the first empirical study to examine the role of high-density outplants of the endangered staghorn coral, Acropora cervicornis, in restoring positive carbonate accretion on Florida reefs. Successful transplantation of staghorn corals contributed to positive net carbonate production. Restored plots yielded a mean net carbonate production rate of 3.06kg CaCO3 m- 2 yr- 1, whereas control plots exhibited net erosive states. Staghorn restoration plots sustained positive net carbonate production at a threshold of ~ 2.96% coral cover. However, bleaching, storms, and disease challenge these reefs, highlighting the need for restoration strategies that enhance resilience to environmental stressors. Establishing Acroporid aggregations through outplanting, alongside climate adaptation strategies, could foster reef habitat growth and enhance the recovery of ecosystem services.

Distribution characteristics and photochemical effects of isoprene in a coastal city of southeast China

As forest coverage and urban greening increase in China, the impact of biogenic volatile organic compounds (BVOCs) on urban atmospheric environment cannot be neglected. As one of the most abundant and reactive BVOCs globally, isoprene plays a crucial role in atmospheric radical chemistry. However, the reports on quantifying the impact of isoprene on atmospheric photochemistry remain scarce. This study selected Xiamen, a typical coastal city in Fujian Province, as the research area. By employing field observation and Photochemical Box Model (PBM), the study investigated the distribution characteristics, pollution mechanisms, and impact on O3 of the atmospheric photochemical active species isoprene in coastal urban area. The study found that the average concentration of isoprene in summer was 4.7 times higher than that in autumn. Isoprene degradation primarily occurred through oxidation by OH· radicals, reaching 88 % and 86 % in summer and autumn, respectively. Based on scenario simulations using the PBM model, it was observed that isoprene photochemistry led to increased daytime concentrations of ROx radicals (summer: 24 %, autumn: 23 %), peroxyacetyl nitrate (PAN, 49 %, 44 %), and formaldehyde (HCHO, 37 %, 38 %). Additionally, isoprene photochemistry enhanced reaction rates of HO₂· + NO (summer: 21 %, autumn: 16 %) and RO₂· + NO (50 %, 52 %), ultimately resulting in a 19 % and 15 % increase in net O3 production rates in summer and autumn, respectively. This study provides scientific evidence for exploring the photochemical mechanisms and pollution control strategies of O3 in coastal atmospheric environments.

Physicochemical perturbation increases nitrous oxide production from denitrification in soils and sediments

Abstract. Atmospheric concentrations of nitrous oxide (N2O), a potent greenhouse gas that is also responsible for significant stratospheric ozone depletion, have increased in response to the intensified use of agricultural fertilizers and other human activities that have accelerated nitrogen cycling processes. Microbial denitrification in soils and sediments is a major source of N2O, produced as an intermediate during the reduction of oxidized forms of nitrogen to dinitrogen gas (N2). Substrate availability (nitrate and organic matter) and environmental factors such as oxygen levels, temperature, moisture, and pH influence rates of denitrification and N2O production. Here we describe the role of physicochemical perturbation (defined here as a change from the ambient environmental conditions) in influencing rates of denitrification and N2O production. Changes in salinity, temperature, moisture, pH, and zinc in agricultural soils induced a short-term perturbation response characterized by lower rates of total denitrification and higher rates of net N2O production. The ratio of N2O to total denitrification (N2O : DNF) increased strongly with physicochemical perturbation. A salinity press experiment on tidal freshwater marsh soils revealed that increased N2O production was likely driven by transcriptional inhibition of the nitrous oxide reductase (nos) gene and that the microbial community adapted to altered salinity over a relatively short time frame (within 1 month). Perturbation appeared to confer resilience to subsequent disturbance, and denitrifiers from an environment without salinity fluctuations (tidal freshwater estuarine sediments) demonstrated a stronger N2O perturbation response than denitrifiers from environments with more variable salinity (oligohaline and mesohaline estuarine sediments), suggesting that the denitrifying community from physicochemically stable environments may have a stronger perturbation response. These findings provide a framework for improving our understanding of the dynamic nature of N2O production in soils and sediments, in which changes in physical and/or chemical conditions initiate a short-term perturbation response that promotes N2O production that moderates over time and with subsequent physicochemical perturbation.

Multi-criteria study and machine learning optimization of a novel heat integration for combined electricity, heat, and hydrogen production: Application of biogas-fueled S-Graz plant and biogas steam reforming

The current research introduces an environmentally friendly heat design method by employing biogas fuel, aiming to yield electricity, hydrogen, and heating load simultaneously. The proposed arrangement consists of a biogas-powered S-Graz plant and a biogas steam reforming cycle. Although methane-fueled S-Graz plants for multigeneration purposes have been studied in previous studies, research on employing biogas fuel to launch a S-Graz plant and integrating a biogas steam reforming cycle with such a plant has yet to be examined. The model is simulated using the engineering equation solver software, and the study includes thermodynamic, exergoeconomic, and sustainability assessments to show the potential of the suggested configuration. By conducting a sensitivity study, a machine learning optimization method within MATLAB is implemented to exhibit the final optimal solution for the proposed arrangement. This optimization uses artificial neural networks and a non-dominated sorting genetic algorithm-II algorithm in a triple-objective framework based on energy efficiency, sustainability index, and products’ specific cost. The optimization demonstrates that the mentioned objectives reach optimal values of 58.26 %, 4.56, and 15.56 $/GJ, respectively. Also, the optimal net output power and hydrogen production rate equal 5746 kW and 1.45 m3/s, respectively. Besides, the process determines the optimal exergy efficiency, total net present value, and payback period as 52.70 %, 50.3 M$, and 8.96 years, respectively. The total investment cost rate for this system also is found to be 219.8 $/h.

Analysis of Ozone Pollution and Precursor Control Strategies in the Pearl River Delta During Summer and Autumn Transition Season

To analyze the causes of ozone pollution in the Pearl River Delta （PRD） Region during the summer and autumn transition seasons, a case study was carried out in Guangzhou, which is located in the center of the PRD Region, to analyze the ozone photochemical production and destruction pathways as well as emission reduction scenarios using a box model based on comprehensive observation. The results showed that the stagnant meteorological conditions and high temperature during the observation period were suitable for the photochemical production of ozone, which led to widespread and prolonged ozone pollution. Aromatic hydrocarbons （AHs） contributed the most to the ozone formation potential （OFP）, and m/p-xylene, toluene, and o-xylene were the major three VOC species contributing to the OFP. Box model analysis revealed that the averaged net O3 production rate during the polluted period was 23.2×10-9 h-1 and the peak reached 39.2×10-9 h-1. The HO2·+NO and NO2+·OH reaction pathways contributed the most to the local photochemical ozone production （51.2%） and destruction （47.0%）, respectively. Observed ozone concentration was primarily controlled by both the local photochemical O3 production and the export-dominated transport. The RIR and EKMA analyses showed that O3 formation in Guangzhou during the summer-autumn transition seasons was mainly a VOC-limited regime and AHs showed the greatest sensitivity to O3 production. Toluene, m/p-xylene, o-xylene, n-butane, and propylene were the five key components affecting O3 generation. The analysis of reduction scenarios showed that reducing anthropogenic VOC emissions was the most favorable way to reduce O3 concentrations； however, if NOx emission was controlled after reducing VOCs, the O3 concentration would rebound in a short time. Our results suggested that the synergistic reduction of VOCs and NOx while mainly focusing on VOCs alleviation should be implemented to continuously reduce ozone concentrations in the future.

Comparing the differing effects of host species richness on metrics of disease

AbstractChanges in host species richness can alter infection risk and disease levels in multi‐host communities. I review theoretical predictions for direct and environmental transmission pathogens about the effects of host additions (or removals) on three commonly used disease metrics: the pathogen community reproduction number and infection prevalence and infected density in a focal host. To extend this prior work and explain why predictions differ between metrics, I analyze Susceptible Infected‐Recovered‐type models of an environmentally transmitted pathogen and multiple host species that compete for resources. Using local sensitivity analysis, I show how trait‐mediated and density‐mediated indirect effects drive each metric's response to variation in an added host's ability to transmit a pathogen, the added host's density, and the pathogen transmission mechanism. For each disease metric, the responses are typically predicted by the added host's ability to transmit the pathogen when interspecific competition is weak whereas the responses can be altered by shifts in host densities when interspecific competition is strong. In addition, the three metrics often respond in the same direction. However, the metrics can respond in different directions for three reasons: (1) differences between the ability of exposed individuals to transmit the pathogen over the length of time the individuals are infected (i.e., host competence) and a host population's instantaneous net rate of production of infectious propagules; (2) strong density‐mediated feedbacks driven by disease‐induced mortality; and (3) host additions or removals cause large changes in focal host density via competition or disease‐induced mortality. This study extends and unifies prior theoretical studies, and helps identify the rules governing the context‐dependent relationships between host species richness and the three metrics of disease.

Antagonistic Effects of Light Pollution and Warming on Habitat-Forming Seaweeds.

Artificial Light at Night (ALAN) is an emerging global stressor that is likely to interact with other stressors such as warming, affecting habitat-forming species and ecological functions. Seaweeds are dominant habitat-forming species in temperate marine ecosystems, where they support primary productivity and diverse ecological communities. Warming is a major stressor affecting seaweed forests, but effects of ALAN on seaweeds are largely unknown. We manipulated ALAN (0 lx vs. 25 lx at night) and temperature (ambient vs. +1.54°C warming) to test their independent and interactive effects on the survival, growth (biomass, total-, blade- and stipe-length) and function (photosynthesis, primary productivity and respiration) on the juveniles of two habitat-forming seaweeds, the kelp Ecklonia radiata and the fucoid Sargassum sp. Warming significantly increased Ecklonia mortality; however, ALAN did not affect mortality. ALAN had positive effects on Ecklonia biomass, total and blade growth rates and gross primary productivity; however, warming largely counterbalanced these effects. We found no significant effects of warming or ALAN on Ecklonia photosynthetic yield, stipe length, net primary productivity or respiration rates. We found no effects of ALAN or warming on Sargassum for any of the measured variables. Synthesis. Our findings indicate that ALAN can have positive effects on seaweed growth and functioning, but such effects are likely species-specific and can be counterbalanced by warming, suggesting an antagonistic interaction between these global stressors. These findings can help us to predict and manage the effects of these stressors on seaweeds, which underpin coastal biodiversity.

Using observed urban NOx sinks to constrain VOC reactivity and the ozone and radical budget in the Seoul Metropolitan Area

Abstract. Ozone (O3) is an important secondary pollutant that impacts air quality and human health. Eastern Asia has high regional O3 background due to the numerous sources and increasing and rapid industrial growth, which also impacts the Seoul Metropolitan Area (SMA). However, the SMA has also been experiencing increasing O3 driven by decreasing NOx emissions, highlighting the role of the local in situ O3 production on the SMA. Here, comprehensive gas-phase measurements collected on the NASA DC-8 during the National Institute of Environmental Research (NIER)/NASA Korea–United States Air Quality (KORUS-AQ) study are used to constrain the instantaneous O3 production rate over the SMA. The observed NOx oxidized products support the importance of non-measured peroxy nitrates (PNs) in the O3 chemistry in the SMA, as they accounted for ∼49 % of the total PNs. Using the total measured PNs (ΣPNs) and alkyl and multifunctional nitrates (ΣANs), unmeasured volatile organic compound (VOC) reactivity (R(VOC)) is constrained and found to range from 1.4–2.1 s−1. Combining the observationally constrained R(VOC) with the other measurements on the DC-8, the instantaneous net O3 production rate, which is as high as ∼10 ppbv h−1, along with the important sinks of O3 and radical chemistry, is constrained. This analysis shows that ΣPNs play an important role in both the sinks of O3 and radical chemistry. Since ΣPNs are assumed to be in a steady state, the results here highlight the role that ΣPNs play in urban environments in altering the net O3 production, but ΣPNs can potentially lead to increased net O3 production downwind due to their short lifetime (∼1 h). The results provide guidance for future measurements to identify the missing R(VOCs) and ΣPN production.

Trends of peroxyacetyl nitrate and its impact on ozone over 2018–2022 in urban atmosphere

Peroxyacetyl nitrate (PAN) is an important photochemical product and affects ozone (O3) formation in the troposphere. Yet, the long-term observation of PAN remains scarce, limiting the full understanding of its impacts on photochemical pollution. Here, we observed PAN from 2018 to 2022 in urban Fuzhou, Southeastern China. We found that, in contrast to upward trend of O3, PAN concentrations shown a significant decreasing trend at an average rate of −0.07 ppb/year. NO2, CO, UVB, and T contributed to the decreasing trend of PAN according to Machine learning analyses, while the effect of O3-represented atmospheric oxidation capacity on PAN was fluctuating from year to year. Chemical box model revealed active PA production and depletion in Fuzhou. Thus, despite the decreasing PAN concentration, PAN chemistry effectively promoted O3 formation by rising ROx levels, leading to increases of 2.18%–58.4% in net O3 production rate in different years. Our results provide valuable insights into the evolution of photochemical pollution in urban environments.

Regional polarity in the laminar premixed flame considering the combined effect of positive and negative charge

The study of flame charge is helpful in analyzing the combustion regime, which is significant for optimizing energy conversion in the combustion. In this article, a method to calculate the charge density considering polarity (CDCP) for flame is presented. The charge in the flame local area is obtained by combining the effect of charged particles with positive and negative polarity. The CDCP in different zones of the premixed methane flame with three equivalence ratios of 0.9, 1.0, and 1.3 is measured in the Langmuir probe measurement experiment. The experiment result found that the regional polarity is shown in the premixed flame. Subsequently, the premixed methane flame was simulated using Fluent, and then the simulation distribution of CDCP in the premixed methane flame was obtained. The CDCP and polarity across the reactant, preheat, reaction, and product zones of the premixed flame are analyzed based on the experiment and simulation results. The CDCP of the reaction zone is greater than 0 C/m3 and reaches a peak, showing obvious positive polarity. The CDCP of the reactant zone is less than 0 C/m3, showing negative polarity. The CDCP changes rapidly from less than 0 C/m3 to greater than 0 C/m3 with the approach of the reactant zone to the preheating and reaction zones. The CDCP in the product zone gradually decreases with the increase of the distance from the reaction zone and finally less than and close to 0 C/m3, showing weak negative polarity. Finally, the cause of regional polarity formation is discussed based on the net production rate of charged particles and the velocity distribution of the flow field in the simulation results. The distribution of positive ions and electrons in the premixed flame is different due to the effect of the flow field and the different diffusion properties of charged particles. Thus, the regional polarity is exhibited in the premixed flame.

Hollow porous silica nanoreactors encapsulating VOx-decorated Pt nanoparticles for the reverse water–gas shift reaction

Reverse water–gas shift (RWGS) reaction is a desirable strategy for achieving CO2 utilization and enhancing CO production. Due to the endothermic nature and the chemical equilibrium of this reaction, the reaction is typically conducted at high temperatures (300 ∼ 1000 °C); however, high temperature conditions lead to the sintering of the catalyst, resulting in a catalyst deactivation. Herein we report the synthesis of a metal oxide (V or Mo oxide)-decorated Pt nanoparticles encapsulated in hollow porous silica nanoreactors (HPSNs) by a W/O micro-emulsion system using branched poly(ethyleneimine) (PEI) as a sacrificial metal–ligand. The HPSNs encapsulating VOx-decorated Pt nanoparticles (Pt-VOx@HPSNs) afforded a 1.8-fold increased activity in RWGS reaction at 500 °C compared with Pt@HPSNs with a net CO production rate of 1140.3 mmol/gcat/h and with nearly 100 % CO selectivity. In situ XAFS measurement and reaction kinetic analysis reveal that the interplay of Pt nanoparticles and the decorated V oxide, which simultaneously activate H2 and CO2, respectively, leads to a lowering of the activation energy and a faster CO production rate. Furthermore, the Pt-VOx@HPSNs catalyst retains over 92 % activity after 50 h of continuous operation at 500 °C with the aid of a protective silica shell. This work offers a strategy for the design and development of an efficient and stable heterogeneous catalyst for RWGS reactions.

Exercise and resting periods: Thermal comfort dynamics in gym environments

Physical exercise spaces emerged as popular facilities due to recognizing the significance of physical well-being. This study investigates the relationship among physiological responses, human body energy transfer modes, and indoor environmental conditions in influencing thermal comfort perception within indoor physical exercise space. Seven male participants engaged in a 30 min constant-work-rate cycling exercise and a 20 min resting period in a climatic chamber. The physiological and environmental responses were recorded during the experiments, and the body’s energy transfer modes were calculated using the collected data. The dataset was prepared using the 2 min averages of the collected data and calculated parameters across the experiment phases, including the features of skin temperature, core temperature, skin relative humidity, heart rate, oxygen consumption, body’s heat transfer rates through convection, radiation, evaporation, and respiration, net metabolic heat production rate (metabolic rate minus external work rate), indoor air temperature, indoor relative humidity, air velocity, and radiant temperature. Gradient boosting regressor (GBR) was selected as the analyzing method to estimate predicted mean vote (PMV) and thermal sensation vote (TSV) indices during exercise and resting periods using features determined in the study. Thus, the four GBR models were defined as PMV-Exercise, PMV-Resting, TSV-Exercise, and TSV-Resting. In order to optimize the models’ performances, the hyperparameter tuning process was executed using the GridSearchCV method. A permutation feature importance analysis was performed, emphasizing the significance of net metabolic heat production rate (24.2%), radiant temperature (17.0%), and evaporative heat transfer rate (13.1%). According to the results, PMV-Exercise, PMV-Resting, and TSV-Resting GBR models performed better, while TSV-Exercise faced challenges in predicting exercise thermal sensations. Critically, this study addresses the need to understanding the interrelationship among physiological responses, environmental conditions, and human body energy transfer modes during both exercise and resting periods to optimize thermal comfort within indoor exercise spaces. The results of this study contribute to the operation of indoor gym environments to refine their indoor environmental parameters to optimize users’ thermal comfort and well-being. The study is limited to a small sample size consisting solely of male participants, which may restrict the generalizability of the findings. Future research could explore personalized thermal comfort control systems and synergies between comfort optimization and energy efficiency in indoor exercise spaces.

Net primary productivity and litter decomposition rates in two distinct Amazonian peatlands.

Measurements of net primary productivity (NPP) and litter decomposition from tropical peatlands are severely lacking, limiting our ability to parameterise and validate models of tropical peatland development and thereby make robust predictions of how these systems will respond to future environmental and climatic change. Here, we present total NPP (i.e., above- and below-ground) and decomposition data from two floristically and structurally distinct forested peatland sites within the Pastaza Marañón Foreland Basin, northern Peru, the largest tropical peatland area in Amazonia: (1) a palm (largely Mauritia flexuosa) dominated swamp forest and (2) a hardwood dominated swamp forest (known as 'pole forest', due to the abundance of thin-stemmed trees). Total NPP in the palm forest and hardwood-dominated forest (9.83 ± 1.43 and 7.34 ± 0.84 Mg C ha-1 year-1, respectively) was low compared with values reported for terra firme forest in the region (14.21-15.01 Mg C ha-1 year-1) and for tropical peatlands elsewhere (11.06 and 13.20 Mg C ha-1 year-1). Despite the similar total NPP of the two forest types, there were considerable differences in the distribution of NPP. Fine root NPP was seven times higher in the palm forest (4.56 ± 1.05 Mg C ha-1 year-1) than in the hardwood forest (0.61 ± 0.22 Mg C ha-1 year-1). Above-ground palm NPP, a frequently overlooked component, made large contributions to total NPP in the palm-dominated forest, accounting for 41% (14% in the hardwood-dominated forest). Conversely, Mauritia flexuosa litter decomposition rates were the same in both plots: highest for leaf material, followed by root and then stem material (21%, 77% and 86% of mass remaining after 1 year respectively for both plots). Our results suggest potential differences in these two peatland types' responses to climate and other environmental changes and will assist in future modelling studies of these systems.

S-containing molecular markers of dissolved organic carbon attributing to riverine dissolved methane production across different land uses

The emission of methane (CH4) from streams and rivers contributes significantly to its global inventory. The production of CH4 is traditionally considered as a strictly anaerobic process. Recent investigations observed a “CH4 paradox” in oxic waters, suggesting the occurrence of oxic methane production (OMP). Human activities promoted dissolved organic carbon (DOC) in streams and rivers, providing significant substrates for CH4 production. However, the underlying DOC molecular markers of CH4 production in river systems are not well known. The identification of these markers will help to reveal the mechanism of methanogenesis. Here, Fourier transform ion cyclotron mass spectrometry and other high-quality DOC characterization, ecosystem metabolism, and in-situ net CH4 production rate were employed to investigate molecular markers attributing to riverine dissolved CH4 production across different land uses. We show that endogenous CH4 production supports CH4 oversaturation and positively correlates with DOC concentrations and gross primary production. Furthermore, sulfur (S)-containing molecules, particularly S-aliphatics and S-peptides, and fatty acid-like compounds (e.g., acetate homologs) are characterized as markers of water-column aerobic and anaerobic CH4 production. Watershed characterization, including riverine discharge, allochthonous DOC input, turnover, as well as autochthonous DOC, affects the CH4 production. Our study helps to understand riverine aerobic or anaerobic CH4 production relating to DOC molecular characteristics across different land uses.

Variability in Ice Cover Does Not Affect Annual Metabolism Estimates in a Small Eutrophic Reservoir

AbstractTemperate reservoirs and lakes worldwide are experiencing decreases in ice cover, which will likely alter the net balance of gross primary production (GPP) and respiration (R) in these ecosystems. However, most metabolism studies to date have focused on summer dynamics, thereby excluding winter dynamics from annual metabolism budgets. To address this gap, we analyzed 6 years of year‐round high‐frequency dissolved oxygen data to estimate daily rates of net ecosystem production (NEP), GPP, and R in a eutrophic, dimictic reservoir that has intermittent ice cover. Over 6 years, the reservoir exhibited slight heterotrophy during both summer and winter. We found winter and summer metabolism rates to be similar: summer NEP had a median rate of −0.06 mg O2 L−1 day−1 (range: −15.86 to 3.20 mg O2 L−1 day−1), while median winter NEP was −0.02 mg O2 L−1 day−1 (range: −8.19 to 0.53 mg O2 L−1 day−1). Despite large differences in the duration of ice cover among years, there were minimal differences in NEP among winters. Overall, the inclusion of winter data had a limited effect on annual metabolism estimates in a eutrophic reservoir, likely due to short winter periods in this reservoir (ice durations 0–35 days), relative to higher‐latitude lakes. Our work reveals a smaller difference between winter and summer NEP than in lakes with continuous ice cover. Ultimately, our work underscores the importance of studying full‐year metabolism dynamics in a range of aquatic ecosystems to help anticipate the effects of declining ice cover across lakes worldwide.

Net Community Production and Inorganic Carbon Cycling in the Central Irminger Sea

AbstractThe subpolar North Atlantic plays an outsized role in the atmosphere‐to‐ocean carbon sink. The central Irminger Sea is home to well‐documented deep winter convection and high phytoplankton production, which drive strong seasonal and interannual variability in regional carbon cycling. We use observational data from moored carbonate chemistry system sensors and annual turn‐around cruise samples at the Ocean Observatories Initiative's Irminger Sea Array to construct a near‐continuous time series of mixed layer total dissolved inorganic carbon (DIC), pCO2, and total alkalinity from summer 2015 to summer 2022. We use these carbonate chemistry system time series to deconvolve the physical and biological drivers of surface ocean carbon cycling in this region on seasonal, annual, and interannual time scales. We find high annual net community production within the seasonally varying mixed layer, averaging 9.8 ± 1.6 mol m−2 yr−1 with high interannual variability (range of 6.0–13.9 mol m−2 yr−1). The highest daily net community production rates occur during the late winter and early spring, prior to the observed high chlorophyll concentrations associated with the spring phytoplankton bloom. As a result, the winter and early spring play a much larger role in biological carbon export from the mixed layer than traditionally thought.

Numerical Investigation of Combustion Characteristics in a Binary Fuel Blend of C <sub>8</sub> H <sub>18</sub> and H <sub>2</sub>

<div>The escalating energy demand in today’s world has amplified exhaust emissions, contributing significantly to climate change. One viable solution to mitigate carbon dioxide emissions is the utilization of hydrogen alongside gasoline in internal combustion engines. In pursuit of this objective, combustion characteristics of iso-octane/hydrogen/air mixtures are numerically investigated to determine the impact of hydrogen enrichment. Simulations are conducted at 400 K over a wide range of equivalence ratio 0.7 ≤ Ф ≤ 1.4 and pressure 1–10 atm. Adiabatic flame temperature, thermal diffusivity, laminar burning velocity, and chemical participation are assessed by varying hydrogen concentration from 0 to 90% of fuel molar fraction. As a result of changes in thermal properties and chemical participation, it is noticed that the laminar burning velocity (LBV) increases with higher hydrogen concentration and decreases as pressure increases. Chemical participation and mass diffusion were found to be the main contributors to the LBV increase in binary fuel blends. To circumvent NO<sub>X</sub> formation, a binary fuel blend at Ф = 0.7 and 80% H<sub>2</sub> is selected to increase combustion intensity while maintaining a relatively low flame temperature and retaining 85% of energy density by volume. It is noted that the concentration of H, O, and OH radicals increase with hydrogen enrichment. Furthermore, the analysis revealed that the LBV increases linearly with the peak mole fraction of radicals. Key reactions are identified through sensitivity analysis and net reaction rates. A significant increase in net reaction rate is observed for H<sub>2</sub> + O <=> H + OH and H<sub>2</sub> + OH <=> H + H<sub>2</sub>O, which in turn increases the pool of radicals. This is evident by the increase in the net production rate of H, O, and OH radicals.</div>

A comprehensive approach to enhance wood cutting productivity: Integration of spherical fuzzy DEMATEL and artificial neural networks

Productivity plays a pivotal role in profitability and success of business. In this study, the wood cutting activity in Indian sawmills is selected. This study replicates the novel approach by integrating spherical fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and artificial neural networks (ANN) to improve the wood cutting productivity in Indian sawmills. The measure of betterness is selected as net productivity rate (NPR), a time-based labor productivity measure. The methodology unfolds in two crucial steps. First, SF-DEMATEL is employed to unearth influential factors affecting wood cutting, delving into their interrelationships through fuzzy logic. This process provides relationships between key determinants and their interconnected dynamics. Secondly, an ANN, a machine learning algorithm, is harnessed to predict wood cutting performance based on these identified factors. The ANN is trained using historical or simulation data, paving the way for predictions under diverse scenarios. The novelty of this approach lies in its holistic precision. The results showcase that lifting index and log weight emerge as primary influencers on productivity, with NPR, occupational risk index, and perceived exertion ranking lower. In the grand tapestry of factors, the study unveils universal driving forces, such as the weight of the log and lifting index. The ANN model, attaining a remarkable RMSE = 0.0478 and R2 = 0.9783 for training set and for training data and RMSE = 0.0487 and R2 = 0.9727 for testing data. This contributes to the comprehensive ranking comparison of factors derived from both Fuzzy DEMATEL and ANN. In summation, the fusion of Fuzzy DEMATEL and ANN unravels the intricacies of wood cutting dynamics. By identifying key factors and predicting performance, this approach provides a transformative gateway to enhance wood cutting quality and efficiency, thereby elevating the overall productivity of the woodworking industry.

Photoacclimation and photophysiology of four species of toxigenic Dinophysis

This study aimed to explore the effects of different light intensities on the ecophysiology of eight new Dinophysis isolates comprising four species (D. acuminata, D. ovum, D. fortii, and D. caudata) collected from different geographical regions in the US. After six months of acclimation, the growth rates, photosynthetic efficiency (Fv/Fm ratio), toxin content, and net toxin production rates of the Dinophysis strains were examined. The growth rates of D. acuminata and D. ovum isolates were comparable across light intensities, with the exception of one D. acuminata strain (DANY1) that was unable to grow at the lowest light intensity. However, D. fortii and D. caudata strains were photoinhibited and grew at a slower rate at the highest light intensity, indicating a lower degree of adaptability and tolerance to such conditions. Photosynthetic efficiency was similar for all Dinophysis isolates and negatively correlated with exposure to high light intensities. Multiple toxin metrics, including cellular toxin content and net production rates of DSTs and PTXs, were variable among species and even among isolates of the same species in response to light intensity. A pattern was detected, however, whereby the net production rates of PTXs were significantly lower across all Dinophysis isolates when exposed to the lowest light intensity. These findings provide a basis for understanding the effects of light intensity on the eco-physiological characteristics of Dinophysis species in the US and could be employed to develop integrated physical-biological models for species and strains of interest to predict their population dynamics and mitigate their negative effects.

Evaluation of metrics and thresholds for use in national-scale river harmful algal bloom assessments

The spatiotemporal distribution of harmful algal blooms (HABs) in rivers remains poorly understood, and there is an urgent need to develop a consistent set of metrics to better document HAB occurrences and forecast future events. Using data from seven sites in the Illinois River Basin, we computed metrics focused on HAB conditions related to excess algal growth and hypoxia. Daily mean chlorophyll and dissolved oxygen (DO) concentrations, gross primary productivity (GPP), and net ecosystem productivity (NEP) rates, focused on water quality status, identifying the timing of the transition from a clear-water to an algal dominated state. Early warning indicators (EWIs), the first-order autoregressive process (Ar1) and standard deviation (SD) of chlorophyll concentrations, focused on future events, forecasting blooms. Metrics were compared to either literature-derived or statistical-based thresholds and were normalized by total number of daily samples for an exceedance rate. Exceedances of a daily mean chlorophyll concentration averaged 50 % across all sites using a 10 µg L−1 threshold but increasing the threshold to 50 μg L−1 reduced the average exceedance rate to 5 %. The average exceedance rate for GPP (∼8 g O2 m2d−1 threshold) was 15 %, similar to the daily amplitude DO concentration (∼3 mg L−1 threshold), but the average for NEP (0 g O2 m2 d−1 threshold) was higher, at 28 %. The number of days with at least 1 continuous DO concentration below the threshold of 5, 3, or 2 mg L−1, had basin wide exceedance rates of 9 %, 3 %, and 2 %, respectively. Thresholds for EWIs, Ar1 and SD, were exceeded at 5 of the 7 sites with high chlorophyll concentrations and GPP rates. The correlation between proxies for algal biomass (chlorophyll concentration) and productivity (GPP) was strongest for sites in the middle region of the basin, with R2 values between 0.54 and 0.74. Although, cyanotoxin concentrations are the most commonly used metrics by states to define an inland water HAB, there is a paucity of publicly available data. The wider availability of chlorophyll and oxygen data combined with the results from this study suggest that biomass and productivity state and event-based metrics may be a promising way to assess and predict the vulnerability of rivers to some of the deleterious effects of HABs at broad spatial scales.