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Mixed phospholipid and glycolipid monolayers likely coat the surfaces of pressurised gas nanobubbles within the hydraulic systems of plants. The lipid coatings bond to water under negative pressure and are thus stretched out of equilibrium. In this work, we have used molecular dynamics simulations to produce trajectories of a biologically relevant mixed monolayer, pulled at mild negative pressures (-1.5 to -4.5 MPa). Pore formation within the monolayer is observed at both 270 and 310 K, and proceeds as an activated process once the lipid tails fully transition from the two dimensional liquid condensed to liquid expanded phase. Pressure:area isotherms showed reduced surface pressure under slight supercooling (T = 270 K) at all observed areas per lipid. Finally, Rayleigh-Plesset simulations were used to predict evolving nanobubble size using the calculated pressure:area isotherms as dynamic surface tensions. We confirm the existence of a second critical radius with respect to runaway growth, above the homogeneous cavitation radius.
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Computational modeling of atmospheric molecular clusters requires a comprehensive understanding of their complex configurational spaces, interaction patterns, stabilities against fragmentation, and even dynamic behaviors. To address these needs, we introduce the Jammy Key framework, a collection of automated scripts that facilitate and streamline molecular cluster modeling workflows. Jammy Key handles file manipulations between varieties of integrated third-party programs. The framework is divided into three main functionalities: (1) Jammy Key for configurational sampling (JKCS) to perform systematic configurational sampling of molecular clusters, (2) Jammy Key for quantum chemistry (JKQC) to analyze commonly used quantum chemistry output files and facilitate database construction, handling, and analysis, and (3) Jammy Key for machine learning (JKML) to manage machine learning methods in optimizing molecular cluster modeling. This automation and machine learning utilization significantly reduces manual labor, greatly speeds up the search for molecular cluster configurations, and thus increases the number of systems that can be studied. Following the example of the Atmospheric Cluster Database (ACDB) of Elm (ACS Omega, 4, 10965-10984, 2019), the molecular clusters modeled in our group using the Jammy Key framework have been stored in an improved online GitHub repository named ACDB 2.0. In this work, we present the Jammy Key package alongside its assorted applications, which underline its versatility. Using several illustrative examples, we discuss how to choose appropriate combinations of methodologies for treating particular cluster types, including reactive, multicomponent, charged, or radical clusters, as well as clusters containing flexible or multiconformer monomers or heavy atoms. Finally, we present a detailed example of using the tools for atmospheric acid-base clusters.
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Low-volatile organic compounds (LVOCs) drive key atmospheric processes, such as new particle formation (NPF) and growth. Machine learning tools can accelerate studies of these phenomena, but extensive and versatile LVOC datasets relevant for the atmospheric research community are lacking. We present the GeckoQ dataset with atomic structures of 31,637 atmospherically relevant molecules resulting from the oxidation of α-pinene, toluene and decane. For each molecule, we performed comprehensive conformer sampling with the COSMOconf program and calculated thermodynamic properties with density functional theory (DFT) using the Conductor-like Screening Model (COSMO). Our dataset contains the geometries of the 7 Mio. conformers we found and their corresponding structural and thermodynamic properties, including saturation vapor pressures (pSat), chemical potentials and free energies. The pSat were compared to values calculated with the group contribution method SIMPOL. To validate the dataset, we explored the relationship between structural and thermodynamic properties, and then demonstrated a first machine-learning application with Gaussian process regression.
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Water and butanol are used as working fluids in condensation particle counters, and condensation of a single vapor onto an ion can be used as a simple model system for the study of ion-induced nucleation in the atmosphere. Motivated by this, we examine heterogeneous nucleation of water (H2O) and n-butanol (BuOH) vapors onto three positively (Li+, Na+, K+) and three negatively charged (F-, Cl-, Br-) ions using classical nucleation theory and computational quantum chemistry methods. We study phenomena that cannot be captured by Kelvin-Thomson equation for small nucleation ion cores. Our quantum chemistry calculations reveal the molecular mechanism behind ion-induced nucleation for each studied system. Typically, ions become solvated from all sides after several vapor molecules condense onto the ion. However, we show that the clusters of water and large negatively charged ions (Cl- and Br-) thermodynamically prefer the ion being migrated to the cluster surface. Although our methods generally do not show clear sign-preference for ion-water nucleation, we identified positive sign-preference for ion-butanol nucleation caused by the possibility to form stabilizing hydrogen bonds between butanol molecules condensed onto a positively charged ion. These bonds cannot form when butanol condenses onto a negatively charged ion. Therefore, we show that ion charge, its sign, as well as vapor properties have effects on the prenucleation and critical cluster/droplet sizes and also on the molecular mechanism of ion-induced nucleation.
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Nucleation of clusters from the gas phase is a widely encountered phenomenon, yet rather little is understood about the underlying out-of-equilibrium dynamics of this process. The classical view of nucleation assumes isothermal conditions where the nucleating clusters are in thermal equilibrium with their surroundings. However, in all first-order phase transitions, latent heat is released, potentially heating the clusters and suppressing the nucleation. The question of how the released energy affects cluster temperatures during nucleation as well as the growth rate remains controversial. To investigate the nonisothermal dynamics and energetics of homogeneous nucleation, we have performed molecular dynamics simulations of a supersaturated vapor in the presence of thermalizing carrier gas. The results obtained from these simulations are compared against kinetic modeling of isothermal nucleation and classical nonisothermal theory. For the studied systems, we find that nucleation rates are suppressed by two orders of magnitude at most, despite substantial release of latent heat. Our analyses further reveal that while the temperatures of the entire cluster size populations are elevated, the temperatures of the specific clusters driving the nucleation flux evolve from cold to hot when growing from subcritical to supercritical sizes and resolve the apparent contradictions regarding cluster temperatures. Our findings provide unprecedented insight into realistic nucleation events and allow us to directly assess earlier theoretical considerations of nonisothermal nucleation.
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Studies of vapor phase nucleation have largely been restricted to one of two limiting cases-nucleation controlled by a substantial free energy barrier or the collisional limit where the barrier is negligible. For weakly bound systems, exploring the transition between these regimes has been an experimental challenge, and how nucleation evolves in this transition remains an open question. We overcome these limitations by combining complementary Laval expansion experiments, providing new particle formation data for carbon dioxide over a uniquely broad range of conditions. Our experimental data together with a kinetic model using rate constants from high-level quantum chemical calculations provide a comprehensive picture of new particle formation as nucleation transitions from a barrier-dominated process to the collisional limit.
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Using a combination of quantum chemistry and cluster size distribution dynamics, we study the heterogeneous nucleation of n-butanol and water onto sodium chloride (NaCl)10 seeds at different butanol saturation ratios and relative humidities. We also investigate how the heterogeneous nucleation of butanol is affected by the seed size through comparing (NaCl)5, (NaCl)10, and (NaCl)25 seeds and by seed electrical charge through comparing (Na10Cl9)+, (NaCl)10, and (Na9Cl10)- seeds. Butanol is a common working fluid for condensation particle counters used in atmospheric aerosol studies, and NaCl seeds are frequently used for calibration purposes and as model systems, for example, sea spray aerosol. In general, our simulations reproduce the experimentally observed trends for the NaCl-BuOH-H2O system, such as the increase of nucleation rate with relative humidity and with temperature (at constant supersaturation of butanol). Our results also provide molecular-level insights into the vapor-seed interactions driving the first steps of the heterogeneous nucleation process. The main purpose of this work is to show that theoretical studies can provide molecular understanding of initial steps of heterogeneous nucleation and that it is possible to find cost-effective yet accurate-enough combinations of methods for configurational sampling and energy evaluation to successfully model heterogeneous nucleation of multicomponent systems. In the future, we anticipate that such simulations can also be extended to chemically more complex seeds.
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Large scale molecular dynamics simulations of the homogeneous nucleation of carbon dioxide in an argon atmosphere were carried out at temperatures between 75 and 105 K. Extensive analyses of the nucleating clusters' structural and energetic properties were performed to quantify these details for the supersonic nozzle experiments described in the first part of this series [Dingilian et al., Phys. Chem. Chem. Phys., 2020, 22, 19282-19298]. We studied ten different combinations of temperature and vapour pressure, leading to nucleation rates of 1023-1025 cm-3 s-1. Nucleating clusters possess significant excess energy from monomer capture, and the observed cluster temperatures during nucleation - on both sides of the critical cluster size - are higher than that of the carrier gas. Despite strong undercooling with respect to the triple point, most clusters are clearly liquid-like during the nucleation stage. Only at the lowest simulation temperatures and vapour densities, clusters containing over 100 molecules are able to undergo a second phase transition to a crystalline solid. The formation free energies retrieved from the molecular dynamics simulations were used to improve the classical nucleation theory by introducing a Tolman-like term into the classical liquid-drop model expression for the formation free energy. This simulation-based theory predicts the simulated nucleation rates perfectly, and improves the prediction of the experimental rates compared to self-consistent classical nucleation theory.
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Air seeded nanobubbles have recently been observed within tree sap under negative pressure. They are stabilized by an as yet unidentified process, although some embolize their vessels in extreme circumstances. Current literature suggests that a varying surface tension helps bubbles survive, but few direct measurements of this quantity have been made. Here, we present calculations of dynamic surface tension for two biologically relevant lipids using molecular dynamics simulations. We find that glycolipid monolayers resist expansion proportionally to the rate of expansion. Their surface tension increases with the tension applied, in a similar way to the viscosity of a non-Newtonian fluid. In contrast, a prototypical phospholipid was equally resistant to all applied tensions, suggesting that the fate of a given nanobubble is dependent on its surface composition. By incorporating our results into a Classical Nucleation Theory (CNT) framework, we predict nanobubble stability with respect to embolism. We find that the metastable radius of glycolipid coated nanobubbles is approximately 35 nm, and that embolism is in this case unlikely when the external pressure is less negative than -1.5 MPa.
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Condensation particle counter (CPC) instruments are commonly used to detect atmospheric nanoparticles. They operate on the basis of condensing an organic working fluid on the nanoparticle seeds to grow the particles to a detectable size, and at the size of few nanometers, their efficiency depends on how well the working fluid interacts with the seeds under the measurement conditions. This study models the first steps of heterogeneous nucleation of two working fluids commonly used in CPCs (diethylene glycol (DEG) and n-butanol) onto two positively charged seeds, ammonium bisulfate and tetramethylammonium bromide. The nucleation process is modeled on a molecular level using a combination of systematic configurational sampling and density functional theory (DFT). We take into account the conformational flexibility of DEG and n-butanol and determine the key factors that can improve the efficiency of nanoparticle measurements by CPCs. The results show that hydrogen bonding between the seed and the working fluid molecules is central to the adsorption of the first DEG/n-butanol molecules onto the seeds. However, intermolecular hydrogen bonding between the adsorbed molecules can also enhance the nucleation process for the weakly adsorbing vapor molecules. Accordingly, the heterogeneous nucleation probability is higher for working fluid-nanoparticle combinations with a higher potential for hydrogen bonding; in this case, DEG and ammonium bisulfate. Moreover, conformational analysis and methodology evaluations indicate that the consideration of adsorbate conformers and step-wise addition of the vapor molecules to the seeds is not essential for qualitative modeling of heterogeneous nucleation systems, at least for systems where the adsorbate and seed chemical properties are clearly different. This is the first molecular-level modeling study reporting detailed chemical reasons for experimentally observed seed and working fluid preferences in CPCs and reproducing the experimental observations. Our presented approach can be likely used for predicting preferences in similar nucleating systems.
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Atmospheric amines can enhance methanesulfonic acid (MSA)-driven new particle formation (NPF), but the mechanism is fundamentally different compared to that of the extensively studied sulfuric acid (SA)-driven process. Generally, the enhancing potentials of amines in SA-driven NPF follow the basicity, while this is not the case for MSA-driven NPF, where structural effects dominate, making MSA-driven NPF more prominent for methylamine (MA) compared to dimethylamine (DMA). Therefore, probing structural factors determining the enhancing potentials of amines on MSA-driven NPF is key to fully understanding the contribution of MSA to NPF. Here, we performed a comparative study on DMA and MA enhancing MSA-driven NPF by examining cluster formation using computational methods. The results indicate that DMA-MSA clusters are more stable than the corresponding MA-MSA clusters for cluster sizes up to (DMA)2(MSA)2, indicating that the basicity of amines dominates the initial cluster formation. The methyl groups of DMA were found to present significant steric hindrance beyond the (DMA)2(MSA)2 cluster and this adds to the lower hydrogen bonding capacity of DMA, making the cluster growth less favorable compared to MA. This study implies that several amines could synergistically enhance MSA-driven NPF by maximizing the advantage of different amines in different amine-MSA cluster growth stages.
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Aminas , Mesilatos , Ligação de HidrogênioRESUMO
We studied the homogeneous nucleation of carbon dioxide in the carrier gas argon for concentrations of CO2 ranging from 2 to 39 mole percent using three experimental methods. Position-resolved pressure trace measurements (PTM) determined that the onset of nucleation occurred at temperatures between 75 and 92 K with corresponding CO2 partial pressures of 39 to 793 Pa. Small angle X-ray scattering (SAXS) measurements provided particle size distributions and aerosol number densities. Number densities of approximately 1012 cm-3, and characteristic times ranging from 6 to 13 µs, resulted in measured nucleation rates on the order of 5 × 1017 cm-3 s-1, values that are consistent with other nucleation rate measurements in supersonic nozzles. Finally, we used Fourier transform infrared (FTIR) spectroscopy to identify that the condensed CO2 particles were crystalline cubic solids with either sharp or rounded corners. Molecular dynamics simulations, however, suggest that CO2 forms liquid-like critical clusters before transitioning to the solid phase. Furthermore, the critical clusters are not in thermal equilibrium with the carrier gas. Comparisons with nucleation theories were therefore made assuming liquid-like critical clusters and incorporating non-isothermal correction factors.
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We tested the influence of various parameters on the new particle formation rate predicted for the sulfuric acid-ammonia system using quantum chemistry and cluster distribution dynamics simulations, in our case, Atmospheric Cluster Dynamics Code (ACDC). We found that consistent consideration of the rotational symmetry number of monomers (sulfuric acid and ammonia molecules, and bisulfate and ammonium ions) leads to a significant rise in the predicted particle formation rate, whereas inclusion of the rotational symmetry number of the clusters only changes the results slightly, and only in conditions where charged clusters dominate the particle formation rate. This is because most of the clusters stable enough to participate in new particle formation have a rotational symmetry number of 1, and few exceptions to this rule are positively charged clusters. In contrast, the application of the quasi-harmonic correction for low-frequency vibrational modes tends to generally decrease predicted new particle formation rates and also significantly alters the slope of the formation rate curve plotted against the sulfuric acid concentration, which is a typical convention in atmospheric aerosol science. The impact of the maximum size of the clusters explicitly included in the simulations depends on the simulated conditions. The errors arising from a limited set of clusters are higher for higher evaporation rates, and thus tend to increase with temperature. Similarly, the errors tend to be higher for lower vapor concentrations. The boundary conditions for outgrowing clusters (that are counted as formed particles) have only a small influence on the results, provided that the definition is chemically reasonable and that the set of simulated clusters is sufficiently large. A comparison with data from the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber and a cluster distribution dynamics model using older quantum chemistry input data shows improved agreement when using our new input data and the proposed combination of symmetry and quasi-harmonic corrections.
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Sampling the shallow free energy surface of hydrated atmospheric molecular clusters is a significant challenge. Using computational methods, we present an efficient approach to obtain minimum free energy structures for large hydrated clusters of atmospheric relevance. We study clusters consisting of two to four sulfuric acid (sa) molecules and hydrate them with up to five water (w) molecules. The structures of the "dry" clusters are obtained using the ABCluster program to yield a large pool of low-lying conformer minima with respect to free energy. The conformers (up to ten) lowest in free energy are then hydrated using our recently developed systematic hydrate sampling technique. Using this approach, we identify a total of 1145 unique (sa)2-4(w)1-5 cluster structures. The cluster geometries and thermochemical parameters are calculated at the ωB97X-D/6-31++G(d,p) level of theory, at 298.15 K and 1 atm. The single-point energy of the most stable clusters is calculated using a high-level DLPNO-CCSD(T0)/aug-cc-pVTZ method. Using the thermochemical data, we calculate the equilibrium hydrate distribution of the clusters under atmospheric conditions and find that the larger (sa)3 and (sa)4 clusters are significantly more hydrated than the smaller (sa)2 cluster or the sulfuric acid (sa)1 molecule. These findings indicate that more than five water molecules might be required to fully saturate the sulfuric acid clusters with water under atmospheric conditions. The presented methodology gives modelers a tool to take the effect of water explicitly into account in atmospheric particle formation models based on quantum chemistry.
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Despite the high abundance in the atmosphere, alcohols in general and methanol in particular are believed to play a small role in atmospheric new particle formation (NPF) largely due to the weak binding abilities of alcohols with the major nucleation precursors, e.g., sulfuric acid (SA) and dimethylamine (DMA). Herein, we identify a catalytic reaction that was previously overlooked, namely, the reaction between methanol and SO3, catalyzed by SA, DMA, or water. We found that alcohols can have unexpected quenching effects on the NPF process, particularly in dry and highly polluted regions with high concentrations of alcohols. Specifically, the catalytic reaction between methanol and SO3 can convert methanol into a less-volatile species--methyl hydrogen sulfate (MHS). The latter was initially thought to be a good nucleation agent for NPF. However, our simulation results suggest that the formation of MHS consumes an appreciable amount of atmospheric SO3, disfavoring further reactions of SO3 with H2O. Indeed, we found that MHS formation can cause a reduction of SA concentration up to 87%, whereas the nucleation ability of MHS toward new particles is not as good as that of SA. Hence, a high abundance of methanol in the atmosphere can lower the particle nucleation rate by as much as two orders of magnitude. Such a quenching effect suggests that the recently identified catalytic reactions between alcohols and SO3 need to be considered in atmospheric modeling in order to predict SA concentration from SO2, while also account for their potentially negative effect on NPF.
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Amines are recognized as significant enhancing species on methanesulfonic acid (MSA)-driven new particle formation (NPF). Monoethanolamine (MEA) has been detected in the atmosphere, and its concentration could be significantly increased once MEA-based postcombustion CO2 capture technology is widely implemented. Here, we evaluated the enhancing potential of MEA on MSA-driven NPF by examining the formation of MEA-MSA clusters using a combination of quantum chemical calculations and kinetics modeling. The results indicate that the -OH group of MEA can form at least one hydrogen bond with MSA or MEA in all MEA-containing clusters. The enhancing potential of MEA is higher than that of the strongest enhancing agent known so far, methylamine (MA), for MSA-driven NPF. Such high enhancing potential can be ascribed to not only the higher gas-phase basicity but also the role of the additional -OH group of MEA in increasing the binding free energy by forming additional hydrogen bonds. This clarifies the importance of hydrogen-bonding capacity from the nonamino group of amines in enhancing MSA-driven NPF. The main growth pathway for MEA-MSA clusters proceeds via the initial formation of the (MEA)1(MSA)1 cluster, followed by alternately adding one MSA and one MEA molecule, differing from the case of MA-MSA clusters.
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Etanolamina , Mesilatos , Atmosfera , Ligação de HidrogênioRESUMO
Over Boreal regions, monoterpenes emitted from the forest are the main precursors for secondary organic aerosol (SOA) formation and the primary driver of the growth of new aerosol particles to climatically important cloud condensation nuclei (CCN). Autoxidation of monoterpenes leads to rapid formation of Highly Oxygenated organic Molecules (HOM). We have developed the first model with near-explicit representation of atmospheric new particle formation (NPF) and HOM formation. The model can reproduce the observed NPF, HOM gas-phase composition and SOA formation over the Boreal forest. During the spring, HOM SOA formation increases the CCN concentration by ~10 % and causes a direct aerosol radiative forcing of -0.10 W/m2. In contrast, NPF reduces the number of CCN at updraft velocities < 0.2 m/s, and causes a direct aerosol radiative forcing of +0.15 W/m2. Hence, while HOM SOA contributes to climate cooling, NPF can result in climate warming over the Boreal forest.
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The effect of dust aerosols on accretion reactions of water, formaldehyde, and formic acid was studied in the conditions of earth's troposphere at the DLPNO-CCSD(T)/aug-cc-pVTZ//ωB97X-D/6-31++G** level of theory. A detailed analysis of the reaction mechanisms in the gas phase and on the surface of mineral dust, represented by mono- and trisilicic acid, revealed that mineral dust has the potential of decreasing reaction barrier heights. Specifically, at 0 K, mineral dust can lower the apparent energy barrier of the reaction of formaldehyde with formic acid to zero. However, when the entropic contributions to the reaction free energies were accounted for, mineral dust was found to selectively enhance the reaction of water with formaldehyde, while inhibiting the reaction of formaldehyde and formic acid, in the lower parts of the troposphere (with temperatures around 298 K). In the upper troposphere (with temperatures closer to 198 K), mineral dust catalyzes both reactions and also the reaction of methanol with formic acid. Despite the intrinsic potential of mineral dust, calculation of the catalytic enhancement parameter for a likely range of dust aerosol concentrations suggested that dust aerosols will not contribute to secondary organic aerosol formation via dimerization of closed-shell organic compounds. The main reason for this is the relatively low absolute concentration of tropospheric dust aerosol and its inefficiency in increasing the effective reaction rate coefficients.
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We studied the configurational sampling of noncovalently bonded molecular clusters relevant to the atmosphere. In this article, we discuss possible approaches to searching for optimal configurations and present one alternative based on systematic configurational sampling, which seems able to overcome the typical problems associated with searching for global minima on multidimensional potential energy surfaces. Since atmospheric molecular clusters are usually held together by intermolecular bonds, we also present a cost-effective strategy for treating hydrogen bonding and proton transferring by using rigid molecules and ions in different protonation states and illustrate its performance on clusters containing guanidine and sulfuric acid.
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Piperazine (PZ), a cyclic diamine, is one of 160 detected atmospheric amines and an alternative solvent to the widely used monoethanolamine in post-combustion CO2 capture. Participating in H2SO4 (sulfuric acid, SA)-based new particle formation (NPF) could be an important removal pathway for PZ. Here, we employed quantum chemical calculations and kinetics modeling to evaluate the enhancing potential of PZ on SA-based NPF by examining the formation of PZ-SA clusters. The results indicate that PZ behaves more like a monoamine in stabilizing SA and can enhance SA-based NPF at the parts per trillion (ppt) level. The enhancing potential of PZ is less than that of the chainlike diamine putrescine and greater than that of dimethylamine, which is one of the strongest enhancing agents confirmed by ambient observations and experiments. After the initial formation of the (PZ)1(SA)1 cluster, the cluster mainly grows by gradual addition of SA or PZ monomer, followed by addition of (PZ)1(SA)1 cluster. We find that the ratio of PZ removal by NPF to that by the combination of NPF and oxidations is 0.5-0.97 at 278.15 K. As a result, we conclude that participation in the NPF pathway could significantly alter the environmental impact of PZ compared to only considering oxidation pathways.