Chemical Model Research Articles

A Comparative Study of Phase I and II Hepatic Microsomal Biotransformation of Phenol in Three Species of Salmonidae: Hydroquinone, Catechol, and Phenylglucuronide Formation

The in vitro biotransformation of phenol at 11 °C was studied using pre-spawn adult rainbow (Oncorhynchus mykiss) (RBT), brook (Salvelinus fontinalis) (BKT), and lake trout (Salvelinus namaycush) (LKT) hepatic microsomal preparations. The incubations were optimized for time, cofactor concentration, pH, and microsomal protein concentration. Formation of Phase I ring-hydroxylation and Phase II glucuronidation metabolites was quantified using HPLC with dual-channel electrochemical and UV detection. The biotransformation of phenol over a range of substrate concentrations (1 to 180 mM) was quantified, and the Michaelis–Menten kinetics constants, Km and Vmax, for the formation of hydroquinone (HQ), catechol (CAT), and phenylglucuronide (PG) were calculated. Species differences were noted in the Km values for Phase I enzyme production of HQ and CAT, with the following rank order of apparent enzyme affinity for substrate: RBT > BKT = LKT. However, no apparent differences in the Km for Phase II metabolism of phenol to PG were detected. Conversely, while there were no apparent differences in Vmax between species for HQ or CAT formation, the apparent maximum capacity for PG formation was significantly less in LKT than that observed for RBT and BKT. These experiments provide a means to quantify metabolic activation and deactivation of xenobiotics in fish, to compare activation and deactivation reactions across species, and to act as a guide for future predictions of new chemical biotransformation pathways and rates in fish. These experiments provided the necessary rate and capacity (Km and Vmax) inputs that are required to parameterize a fish physiologically based toxicokinetic (PB-TK) model for a reactive chemical that is readily biotransformed, such as phenol. In the future, an extensive database of these rate and capacity parameters on important fish species for selected chemical structures will be needed to allow the effective use of predictive models for reactive, biotransformation chemicals in aquatic toxicology and environmental risk assessment.

Unveiling 3-D evolution and mechanisms of ozone pollution in Changzhou, China: Insights from lidar observations and modelling

Ground ozone (O3) pollution has emerged as a prominent environmental concern in eastern cities of China, particularly during the summer and autumn seasons. However, a comprehensive investigation into the three-dimensional (3-D) evolution characteristics of O3 within complicated urban environments, especially in lake-land environment, is notably scarce. To enhance our understanding of the mechanisms underlying elevated O3 concentrations within a 3-D scale, this study employed an ozone lidar to delineate vertical ozone profiles in Changzhou, a typical city in China with complicated anthropogenic and biogenic emissions and complex land cover. The process analysis tool integrated into the Weather Research and Forecasting with Chemistry (WRF-Chem) model was further utilized to analyze the formation processes of O3. The results unveil a persistent O3 pollution episode lasting over 15 days in Changzhou during the study period, with multiple peaks exceeding 200 μg m⁻³. Notably, O3 predominantly accumulated within the boundary layer, confined below 1.2 km. Both ground and vertical contributions to this pollution were mainly due to local chemical reactions, with a maximum near-surface contribution reaching 19 ppb h−1 and a vertical contribution of 10 ppb h−1 at the height of 900 ± 200 m. Furthermore, episodes of the enhanced O3 concentrations on August 9 and August 26, 2021, were influenced by external advection process. Our study also found that local circulation plays an important role in the accumulation of surface O3 during certain periods. There was a temperature difference between the surface of Lake Tai and the adjacent land, resulting in the formation of lake-land breezes that facilitate the transport of O3 from the lake surface to the terrestrial environment during pollution events. Our study emphasizes the necessity of reducing local pollutant emissions and implementing joint emission controls as the primary strategies for mitigating O3 pollution in Changzhou and the surrounding region.

The influence of plant water stress on vegetation–atmosphere exchanges: implications for ozone modelling

Abstract. Evapotranspiration is important for Earth's water and energy cycles as it strongly affects air temperature, cloud cover, and precipitation. Leaf stomata are the conduit of transpiration, and their opening is sensitive to weather and climate conditions. This feedback can exacerbate heat waves and can play a role in their spatiotemporal propagation. Sustained high temperatures strongly favour high ozone levels, with significant negative impacts on air quality and thus on human health. Our study evaluates the process representation of evapotranspiration in the atmospheric chemistry–climate European Centre for Medium-Range Weather Forecasts – Hamburg(ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry model. Different water stress parameterizations are implemented in a stomatal model based on CO2 assimilation. The stress factors depend on either soil moisture or leaf water potential, which act on photosynthetic activity, and mesophyll and stomatal conductance. The new functionalities reduce the initial overestimation of evapotranspiration in the model globally by more than an order of magnitude, which is most important in the Southern Hemisphere. The intensity of simulated warm spells over continents is significantly improved. For ozone, we find that a realistic model representation of plant water stress suppresses uptake by vegetation and enhances photochemical production in the troposphere. These effects lead to an overall increase in simulated ground-level ozone, which is most pronounced in the Southern Hemisphere over the continents. More sophisticated land surface models with multi-layer soil schemes could address the uncertainties in representing plant dynamics representation due to too-shallow roots. In regions with low evaporative loss, the representation of precipitation remains the largest uncertainty.

Estimation of Surface Methane Concentration based on the Ensemble Kalman Filter Algorithm using a Transport Chemical Model

Estimation of Surface Methane Concentration based on the Ensemble Kalman Filter Algorithm using a Transport Chemical Model

Short-Term Exposure to Wildfire-Specific PM2.5 and Hospitalization for Diabetes Morbidity: A Study in Multiple Countries and Territories.

To evaluate associations of wildfire fine particulate matter (PM2.5) with diabetes across multiple countries and territories. We collected data on 3,612,135 diabetes hospitalizations from 1,008 locations in Australia, Brazil, Canada, Chile, New Zealand, Thailand, and Taiwan during 2000-2019. Daily wildfire-specific PM2.5 levels were estimated through chemical transport models and machine-learning calibration. Quasi-Poisson regression with distributed lag nonlinear models and random-effects meta-analysis were applied to estimate associations between wildfire-specific PM2.5 and diabetes hospitalization. Subgroup analyses were by age, sex, location income level, and country or territory. Diabetes hospitalizations attributable to wildfire-specific PM2.5 and nonwildfire PM2.5 were compared. Each 10 µg/m3 increase in wildfire-specific PM2.5 levels over the current day and previous 3 days was associated with relative risks (95% CI) of 1.017 (1.011-1.022), 1.023 (1.011-1.035), 1.023 (1.015-1.032), 0.962 (0.823-1.032), 1.033 (1.001-1.066), and 1.013 (1.004-1.022) for all-cause, type 1, type 2, malnutrition-related, other specified, and unspecified diabetes hospitalization, respectively. Stronger associations were observed for all-cause, type 1, and type 2 diabetes in Thailand, Australia, and Brazil; unspecified diabetes in New Zealand; and type 2 diabetes in high-income locations. Relative risks (95% CI) of 0.67% (0.16-1.18%) and 1.02% (0.20-1.81%) for all cause and type 2 diabetes hospitalizations were attributable to wildfire-specific PM2.5. Compared with nonwildfire PM2.5, wildfire-specific PM2.5 posed greater risks of all-cause, type 1, and type 2 diabetes and were responsible for 38.7% of PM2.5-related diabetes hospitalizations. We show the relatively underappreciated links between diabetes and wildfire air pollution, which can lead to a nonnegligible proportion of PM2.5-related diabetes hospitalizations. Precision prevention and mitigation should be developed for those in advantaged communities and in Thailand, Australia, and Brazil.

QC-GN2oMS2: a Graph Neural Net for High Resolution Mass Spectra Prediction.

Predicting the mass spectrum of a molecular ion is often accomplished via three generalized approaches: rules-based methods for bond breaking, deep learning, or quantum chemical (QC) modeling. Rules-based approaches are often limited by the conditions for different chemical subspaces and perform poorly under chemical regimes with few defined rules. QC modeling is theoretically robust but requires significant amounts of computational time to produce a spectrum for a given target. Among deep learning techniques, graph neural networks (GNNs) have performed better than previous work with fingerprint-based neural networks in mass spectra prediction. To explore this technique further, we investigate the effects of including quantum chemically derived information as edge features in the GNN to increase predictive accuracy. The models we investigated include categorical bond order, bond force constants derived from extended tight-binding (xTB) quantum chemistry, and acyclic bond dissociation energies. We evaluated these models against a control GNN with no edge features in the input graphs. Bond dissociation enthalpies yielded the best improvement with a cosine similarity score of 0.462 relative to the baseline model (0.437). In this work we also apply dynamic graph attention which improves performance on benchmark problems and supports the inclusion of edge features. Between implementations, we investigate the nature of the molecular embedding for spectra prediction and discuss the recognition of fragment topographies in distinct chemistries for further development in tandem mass spectrometry prediction.

Impact of regioisomerism on unimolecular decomposition reactions of energetic materials: Quantum chemistry modeling of ICM-103 and NAPTO

Energetic regioisomers usually behave different physicochemical properties, and the thermal decomposition mechanism might also be different. In this work, the unimolecular decomposition reactions of two novel energetic isomers, ICM-103 and NAPTO, were investigated through quantum chemistry calculations to reveal the decay mechanism of energetic regioisomers. The molecular properties were first explored to reveal their differences in the molecular properties of ICM-103 and NAPTO. Then, six initial decomposition channels were obtained, including N2 release of azide group, H transfer, O transfer, nitro dissociation, nitro-nitrite isomerization, and ring-opening reaction. Thermochemistry results show that the most possible decay reaction is the cleavage of NN bonds of azide group to generate N2, and the energy barrier of ICM-103 is lower than that of NAPTO, which is consistent with the conclusion that NAPTO is more stable form the experiment. Specially, two molecules react differently, and a sequential N2 loss is expected in one, and N2O loss in the other is almost lost in the clutter. Besides, the nitro dissociation, nitro-nitrite isomerization, and ring-opening reaction energy of ICM-103 are also lower than that of NAPTO. However, for the other same reaction, the energy barrier of ICM-103 is higher than that of NAPTO. These findings in the initial decomposition pathways of ICM-103 and NAPTO could gain more understanding of the effect of regiochemical control on the thermal stability of energetic materials.

Increases in Global and East Asian Nitrogen Trifluoride (NF3) Emissions Inferred from Atmospheric Observations.

Nitrogen trifluoride (NF3) is a potent and long-lived greenhouse gas that is widely used in the manufacture of semiconductors, photovoltaic cells, and flat panel displays. Using atmospheric observations from eight monitoring stations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and inverse modeling with a global 3-D atmospheric chemical transport model (GEOS-Chem), we quantify global and regional NF3 emission from 2015 to 2021. We find that global emissions have grown from 1.93 ± 0.58 Gg yr-1 (± one standard deviation) in 2015 to 3.38 ± 0.61 Gg yr-1 in 2021, with an average annual increase of 10% yr-1. The available observations allow us to attribute significant emissions to China (0.93 ± 0.15 Gg yr-1 in 2015 and 1.53 ± 0.20 Gg yr-1 in 2021) and South Korea (0.38 ± 0.07 Gg yr-1 to 0.65 ± 0.10 Gg yr-1). East Asia contributes around 73% of the global NF3 emission increase from 2015 to 2021: approximately 41% of the increase is from emissions from China (with Taiwan included), 19% from South Korea, and 13% from Japan. For Japan, which is the only one of these three countries to submit annual NF3 emissions to UNFCCC, our bottom-up and top-down estimates are higher than reported. With increasing demand for electronics, especially flat panel displays, emissions are expected to further increase in the future.

Simulation of hexavalent chromium removal by electrocoagulation using iron anode in flow-through reactor

An electrocoagulation (EC) model is developed for hexavalent chromium reduction and precipitation, using iron electrodes. Parallel removal mechanisms such as adsorption of chromium on ferrihydrite and direct reduction at the cathode is assumed negligible due to low concentration of Cr(VI). The reaction model presented for batch system represents species complexation, precipitation/dissolution, acid/base, and oxidation-reduction reactions. Batch reactor simulation is verified using experimental data obtained by Sarahney et al. (2012), where the effect of initial chromium concentration, pH, volumetric current density, and ionic strength is considered (Sarahney et al., 2012). The model couples multicomponent ionic transport in MATLAB with chemical reaction model in PHREEQC, as a widely used computational programming tool and a geochemical reaction simulator with comprehensive geochemistry databases. The suggested current density is 0.05−0.3mA/cm2 and the surface to volume ratio in batch reactor is considered 0.017 1/cm. Design parameters are presented for operation of a flow-through hexavalent chromium removal using electrocoagulation by iron electrode to treat Cr(VI) in range of 10–50 mg/L. The operational parameters for a flow-through EC reactor for Cr(VI) removal is suggested to follow 0.05mA/cm2≤3nFeQcCrVIinlet≤0.3mA/cm2.

Short- and Long-Term Neurobehavioral Effects of Developmental Exposure to Valproic Acid in Zebrafish.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and communication, anxiety, hyperactivity, and interest restricted to specific subjects. In addition to the genetic factors, multiple environmental factors have been related to the development of ASD. Animal models can serve as crucial tools for understanding the complexity of ASD. In this study, a chemical model of ASD has been developed in zebrafish by exposing embryos to valproic acid (VPA) from 4 to 48 h post-fertilization, rearing them to the adult stage in fish water. For the first time, an integrative approach combining behavioral analysis and neurotransmitters profile has been used for determining the effects of early-life exposure to VPA both in the larval and adult stages. Larvae from VPA-treated embryos showed hyperactivity and decreased visual and vibrational escape responses, as well as an altered neurotransmitters profile, with increased glutamate and decreased acetylcholine and norepinephrine levels. Adults from VPA-treated embryos exhibited impaired social behavior characterized by larger shoal sizes and a decreased interest for their conspecifics. A neurotransmitter analysis revealed a significant decrease in dopamine and GABA levels in the brain. These results support the potential predictive validity of this model for ASD research.

Resetting tropospheric OH and CH4 lifetime with ultraviolet H2O absorption.

The decay of methyl chloroform, a banned ozone-depleting substance, has provided a clear observational metric of mean tropospheric hydroxyl radical (OH) abundance. Almost all current global chemistry models calculate about 15% too much OH and thus too rapid methane loss. Methane is a short-lived climate forcer, critical to achieving global warming targets, and this error affects our model projections of climate change. New observations of water vapor absorption in the ultraviolet region (290 to 350 nanometers) imply reductions in sunlight with key photolysis rates decreasing by 8 to 12% in the near-surface tropical atmosphere. Incorporation of this new mechanism in a chemistry-transport model reduces OH and methane loss by only 4%, but combined with other proposed mechanisms, such as tropospheric halogen chemistry (7%), we may be able to resolve this conundrum.

The NIRVANDELS survey: the stellar and gas-phase mass-metallicity relations of star-forming galaxies at z = 3.5

ABSTRACT We present determinations of the gas-phase and stellar metallicities of a sample of 65 star-forming galaxies at $z \simeq 3.5$ using rest-frame far-ultraviolet (FUV) spectroscopy from the VANDELS survey in combination with follow-up rest-frame optical spectroscopy from VLT/KMOS and Keck/MOSFIRE. We infer gas-phase oxygen abundances ($Z_{\mathrm{g}}$; tracing O/H) via strong optical nebular lines and stellar iron abundances ($Z_{\star }$; tracing Fe/H) from full spectral fitting to the FUV continuum. Our sample spans the stellar mass range $8.5 \lt \mathrm{log}(M_{\star }/\mathrm{M}_{\odot }) \lt 10.5$ and shows clear evidence for both a stellar and gas-phase mass-metallicity relation (MZR). We find that our O and Fe abundance estimates both exhibit a similar mass-dependence, such that $\mathrm{Fe/H}\propto M_{\star }^{0.30\pm 0.11}$ and $\mathrm{O/H}\propto M_{\star }^{0.32\pm 0.09}$. At fixed $M_{\star }$ we find that, relative to their solar values, O abundances are systematically larger than Fe abundances (i.e. α-enhancement). We estimate an average enhancement of $\mathrm{(O/Fe)} = 2.65 \pm 0.16 \times \mathrm{(O/Fe)_\odot }$ which appears to be independent of $M_{\star }$. We employ analytic chemical evolution models to place a constraint on the strength of galactic-level outflows via the mass-outflow factor ($\eta$). We show that outflow efficiencies that scale as $\eta \propto M_{\star }^{-0.32}$ can simultaneously explain the functional form of of the stellar and gas-phase MZR, as well as the degree of α-enhancement at fixed Fe/H. Our results add further evidence to support a picture in which α-enhanced abundance ratios are ubiquitous in high-redshift star-forming galaxies, as expected for young systems whose interstellar medium is primarily enriched by core-collapse supernovae.

Mechanistic Insight into the Thermal "Blueing" of Cyanine Dyes.

In recent work to develop cyanine dyes with especially large Stokes shifts, we encountered a "blueing" reaction, in which the heptamethine cyanine dye Cy7 (IUPAC: 1,3,3-trimethyl-2-((1E,3E,5E)-7-((E)-1,3,3-trimethylindolin-2-ylidene)hepta-1,3,5-trien-1-yl)-3H-indol-1-ium) undergoes shortening in two-carbon steps to form the pentamethine (Cy5) and trimethine (Cy3) analogs. Each step blue-shifts the resulting absorbance wavelength by ca. 100 nm. Though photochemical and oxidative chain-shortening reactions had been noted previously, it is simple heating alone or with amine bases that effects this unexpected net C2H2 excision. Explicit acetylene loss would be too endothermic to merit consideration. Our mechanistic studies using 2H labeling, mass spectrometric and NMR spectroscopic analyses, and quantum chemical modeling point instead to electrocyclic closure and aromatization of the heptamethine chain in Cy7 forming Fischer's base FB (1,3,3-trimethyl-2-methyleneindoline), a reactive carbon nucleophile that initiates chain shortening of the cyanine dyes by attack on their polymethine backbones. The byproduct is the cationic indolium species TMP (IUPAC: 1,3,3 trimethyl-2-phenyl indolium).

Comprehensive measurement of carbonyls in Lhasa, Tibetan Plateau: Implications for strong atmospheric oxidation capacity

Carbonyls are ubiquitous in the troposphere and play a crucial role in atmospheric oxidation capacity (AOC), particularly in photochemistry-active regions such as the Tibetan Plateau (TP). However, the composition and evolution of carbonyls over the TP is still poorly understood due to a lack of comprehensive observations and modelling. Here, we conducted an intensive field measurement of 37 carbonyls and their precursors at a suburban site in Lhasa during summer 2022. Markedly higher levels of carbonyls (7.24 ± 3.83 ppbv) were found during ozone pollution episodes, with 36 % higher than those during non-episodes. Formaldehyde was the most abundant carbonyl (38 %), which primarily originating from photochemical secondary formations. Simulations using the Rapid adaptive Optimization Model for Atmospheric Chemistry (ROMAC) indicated strong AOC in Lhasa, with the daytime maximum of ·OH and ·HO2 of 9.8 × 106 and 4.2 × 108 molecules cm−3, respectively, which were even higher than that in most of the megacities in China. Notably, AOC significantly enhanced with the increasing carbonyls during the episodes, with the concentrations of ·OH and ·HO2 were boosted 21 % and 67 % than those during non-episodes, respectively. Budget analysis revealed that the ·HO2 + NO (88 %) and ·OH + VOC (74 %) pathways dominated the generation and loss of ·OH, respectively. And for ·HO2, they were ·RO2 + NO (67 %) and ·HO2 + NO (83 %). This study provides valuable insights into the strong AOC in the ecologically-fragile and climate-sensitive TP region, and highlighted the crucial role of anthropogenic–biogenic interactions in the active photochemistry of TP.

Numerical Analysis on the Quantitative Separation of Different NOx Formation and Reduction Routes during MILD Oxy-Coal Combustion with the Improved Nitrogen Chemistry Model

Numerical Analysis on the Quantitative Separation of Different NO_<i>x</i> Formation and Reduction Routes during MILD Oxy-Coal Combustion with the Improved Nitrogen Chemistry Model

Unique impacts of strong and westward-extended western Pacific subtropical high on ozone pollution over eastern China

As a subtropical anticyclonic high-pressure system that typically forms over the northwestern Pacific Ocean in summer, the Western Pacific subtropical high (WPSH) affects meteorological conditions and ozone pollution in China. The relationship between maximum daily 8-h average ozone (MDA8 O3) concentrations and the extremely strong and westward-extended WPSH occurred in 2022 is investigated using observations, reanalysis data and atmospheric chemistry model simulations. During July–August 2022, a significant positive relationship existed between the intensity of the WPSH and MDA8 O3 over southern China, with a correlation coefficient of +0.44, but the correlation is negative (−0.40) in northern China. During the strong WPSH days, MDA8 O3 increased by 16.5 μg m−3 (16.4% relative to July–August average) over southern China and decreased by 19.0 μg m−3 (14.5%) in northern China compared to the weak WPSH days. The unique dipole pattern in the relationship between ozone levels and the WPSH in 2022 exhibited a contrast to that during 2015–2021. The difference is primarily due to the extremely strong WPSH intensity and its unusual westward expansion in 2022. In this case, an anomalous anticyclone at 500 hPa dominates over southern China, which creates conditions conducive for ozone formation and accumulation. The anticyclone weakened horizontal winds and reduced the dispersion of ozone, alongside a high temperature and low relative humidity, which favored the chemical production of ozone. In contrast, abnormal northerly winds enhanced ozone diffusion in northern China and the low temperature reduced ozone chemical production. This study reveals the mechanism for the significant impact of strong and westward-extended WPSH on ozone concentrations over China, emphasizing the role of the WPSH location in modulating meteorology and ozone levels.

Accurately Predicting Spatiotemporal Variations of Near-Surface Nitrous Acid (HONO) Based on a Deep Learning Approach.

Gaseous nitrous acid (HONO) is identified as a critical precursor of hydroxyl radicals (OH), influencing atmospheric oxidation capacity and the formation of secondary pollutants. However, large uncertainties persist regarding its formation and elimination mechanisms, impeding accurate simulation of HONO levels using chemical models. In this study, a deep neural network (DNN) model was established based on routine air quality data (O3, NO2, CO, and PM2.5) and meteorological parameters (temperature, relative humidity, solar zenith angle, and season) collected from four typical megacity clusters in China. The model exhibited robust performance on both the train sets [slope = 1.0, r2 = 0.94, root mean squared error (RMSE) = 0.29 ppbv] and two independent test sets (slope = 1.0, r2 = 0.79, and RMSE = 0.39 ppbv), demonstrated excellent capability in reproducing the spatiotemporal variations of HONO, and outperformed an observation-constrained box model incorporated with newly proposed HONO formation mechanisms. Nitrogen dioxide (NO2) was identified as the most impactful features for HONO prediction using the SHapely Additive exPlanation (SHAP) approach, highlighting the importance of NO2 conversion in HONO formation. The DNN model was further employed to predict the future change of HONO levels in different NOx abatement scenarios, which is expected to decrease 27-44% in summer as the result of 30-50% NOx reduction. These results suggest a dual effect brought by abatement of NOx emissions, leading to not only reduction of O3 and nitrate precursors but also decrease in HONO levels and hence primary radical production rates (PROx). In summary, this study demonstrates the feasibility of using deep learning approach to predict HONO concentrations, offering a promising supplement to traditional chemical models. Additionally, stringent NOx abatement would be beneficial for collaborative alleviation of O3 and secondary PM2.5.

Evaluation of modelled versus observed non-methane volatile organic compounds at European Monitoring and Evaluation Programme sites in Europe

Abstract. Atmospheric volatile organic compounds (VOCs) constitute a wide range of species, acting as precursors to ozone and aerosol formation. Atmospheric chemistry and transport models (CTMs) are crucial to understanding the emissions, distribution, and impacts of VOCs. Given the uncertainties in VOC emissions, lack of evaluation studies, and recent changes in emissions, this work adapts the European Monitoring and Evaluation Programme Meteorological Synthesizing Centre – West (EMEP MSC-W) CTM to evaluate emission inventories in Europe. Here we undertake the first intensive model–measurement comparison of VOCs in 2 decades. The modelled surface concentrations are evaluated both spatially and temporally, using measurements from the regular EMEP monitoring network in 2018 and 2019, as well as a 2022 campaign. To achieve this, we utilised the UK National Atmospheric Emissions Inventory to derive explicit emission profiles for individual species and employed a tracer method to produce pure concentrations that are directly comparable to observations. The degree to which the modelled and measured VOCs agree varies depending on the specific species. The model successfully captures the overall spatial and temporal variations of major alkanes (e.g. ethane, n-butane) and unsaturated species (e.g. ethene, benzene) but less so for propane, i-butane, and ethyne. This discrepancy underscores potential issues in the boundary conditions for the latter species and in their primary emissions from, in particular, the solvent and road transport sectors. Specifically, potential missing propane emissions and issues with its boundary conditions are highlighted by large model underestimations and smaller propane-to-ethane ratios compared to the measurement. Meanwhile, both the model and measurements show strong linear correlations among butane isomers and among pentane isomers, indicating common sources for these pairs of isomers. However, modelled ratios of i-butane to n-butane and i-pentane to n-pentane are approximately one-third of the measured ratios, which is largely driven by significant emissions of n-butane and n-pentane from the solvent sector. This suggests issues with the speciation profile of the solvent sector, underrepresented contributions from transport and fuel evaporation sectors in current inventories, or both. Furthermore, the modelled ethene-to-ethyne and benzene-to-ethyne ratios differ significantly from measured ratios. The different model performance strongly points to shortcomings in the spatial and temporal patterns and magnitudes of ethyne emissions, especially during winter. For OVOCs, the modelled and measured concentrations of methanal and methylglyoxal show a good agreement, despite a moderate underestimation by the model in summer. This discrepancy could be attributed to an underestimation of contributions from biogenic sources or possibly a model overestimation of their photolytic loss in summer. However, the insufficiency of suitable measurements limits the evaluation of other OVOCs. Finally, model simulations employing the CAMS inventory show slightly better agreements with measurements than those using the Centre on Emission Inventories and Projections (CEIP) inventory. This enhancement is likely due to the CAMS inventory's detailed segmentation of the road transport sector, including its associated sub-sector-specific emission profiles. Given this improvement, alongside the previously mentioned concerns about the model's biased estimations of various VOC ratios, future efforts should focus on a more detailed breakdown of dominant emission sectors (e.g. solvents) and the refinement of their speciation profiles to improve model accuracy.

Climate and air quality impact of using ammonia as an alternative shipping fuel

As carbon-free fuel, ammonia has been proposed as an alternative fuel to facilitate maritime decarbonization. Deployment of ammonia-powered ships is proposed as soon as 2024. However, NO x , NH3 and N2O from ammonia combustion could impact air quality and climate. In this study, we assess whether and under what conditions switching to ammonia fuel might affect climate and air quality. We use a bottom–up approach combining ammonia engine experiment results and ship track data to estimate global tailpipe NO x , NH3 and N2O emissions from ammonia-powered ships with two possible engine technologies (NH3–H2 (high NO x , low NH3 emissions) vs pure NH3 (low NO x , very high NH3 emissions) combustion) under three emission regulation scenarios (with corresponding assumptions in emission control technologies), and simulate their air quality impacts using GEOS–Chem high performance global chemical transport model. We find that the tailpipe N2O emissions from ammonia-powered ships have climate impacts equivalent to 5.8% of current shipping CO2 emissions. Globally, switching to NH3–H2 engines avoids 16 900 mortalities from PM2.5 and 16 200 mortalities from O3 annually, while the unburnt NH3 emissions (82.0 Tg NH3 yr−1) from pure NH3 engines could lead to 668 100 additional mortalities from PM2.5 annually under current legislation. Requiring NH3 scrubbing within current emission control areas leads to smaller improvements in PM2.5-related mortalities (22 100 avoided mortalities for NH3–H2 and 623 900 additional mortalities for pure NH3 annually), while extending both Tier III NO x standard and NH3 scrubbing requirements globally leads to larger improvement in PM2.5-related mortalities associated with a switch to ammonia-powered ships (66 500 avoided mortalities for NH3–H2 and 1200 additional mortalities for pure NH3 annually). Our findings suggest that while switching to ammonia fuel would reduce tailpipe greenhouse gas emissions from shipping, stringent ammonia emission control is required to mitigate the potential adverse effects on air quality.

Discovery of HCCCH_2CCH in TMC-1 with the QUIJOTE line survey

We present the first detection in space of 1,4-pentadiyne. It has been found towards TMC-1 with the QUIJOTE line survey in the 31-50 GHz range. We observed a total of 17 transitions with $J$ = 2 up to 13 and $K_a$ = 0,1 and 2. The observed transitions allowed us to derive a rotational temperature of 9.5 pm 0.5 K and a column density of (5.0 pm 0.5)times 1012 cm$^ $. This molecule was the last non-cyclic isomer of the C$_5$H$_4$ family that could be detected via radio astronomy. A computational chemistry study was performed to determine the energies of the five most stable isomers. The isomer ($c$-C$_3$H$_3$CCH) has a considerably higher energy than the others, and it has not yet been detected. To better understand the chemical reactions involving these species, we compared the ethynyl and cyano derivatives. The observed abundances of these species are in good agreement with the branching ratios of the formation reactions studied with our chemical model of TMC-1.