Hydrofluorocarbons (HFCs) are used as substitutes for ozone-depleting substances regulated under the Montreal Protocol. While having zero ozone depletion potential, HFCs strongly absorb infrared (IR) radiation, making them potent greenhouse gases. Vibrational modes associated with C-F stretching absorb strongly within the atmospheric window (750-1250 cm(-1)), contributing substantially to radiative forcing. The low-frequency region (< 500 cm(-1)), which accounts for approximately 16% of the Earth's thermal emission, has however remained largely unexplored mainly due to instrumental challenges. Here, we present the first experimental measurements of IR absorption cross-sections in the 150-500 cm(-1) range for HFC-236fa, HFC-245fa, and HFC-43-10mee - three industrially relevant compounds with high global warming potentials (GWPs). The spectra were recorded at the Rutherford Appleton Laboratory using a high-resolution Fourier-transform infrared (FTIR) spectrometer in the temperature range between 225 and 298 K at resolution of 0.25 cm(-1). In addition, IR cross section spectra were simulated through quantum chemical (QC) calculations including a non-empirical treatment of anharmonic effects. From the experimental results, we derived effective radiative efficiencies (EREs) in the low-frequency region of 0.001, 0.005, and 0.003 W m(-2) ppb(-1) for HFC-236fa, HFC-245fa, and HFC-43-10mee, respectively, and revised global warming potentials over 20-, 100-, and 500-year time horizons. Comparison with values reported in the WMO Ozone Assessment Report 2022 reveals minor differences for HFC-245fa and HFC-43-10mee, whereas their value for HFC-236fa shows a significant overestimation, corresponding to a discrepancy of approximately 360 units in the 100-year GWP. Theoretical predictions reproduced experimental band strengths with an overall average deviation of 4%, confirming the reliability of the computational approach even in the low-frequency region. This indicates that the QC technique is likely to provide reliable estimates for RE and GWP for similar compounds where measurements are not available. These findings highlight that small variations in the treatment of low-frequency absorptions can propagate into substantial contributions in climate metrics, particularly for long-lived compounds. Overall, this study provides a consistent experimental-theoretical framework for quantifying the radiative forcing of HFCs and similar compounds and reduces current uncertainties in the estimation of their climate-relevant parameters.

Abstract. Understanding the renewed and accelerating growth of atmospheric methane requires satellite records that are long enough to span decadal change and consistent enough that instrumental differences are not mistaken for atmospheric signals. We present version 2.0 of the University of Leicester Proxy retrieval of column-averaged dry-air methane (XCH4) from the GOSAT-2 TANSO-FTS-2 instrument, comprising approximately 4.4 million quality-filtered soundings in land nadir and ocean glint observation modes between 5 February 2019 and 31 December 2025. The data are processed with the same algorithm, a priori fields, and quality-filtering framework as the established GOSAT Proxy v10.0 product, with the aim of producing a consistent multi-instrument climate data record. The on-board intelligent pointing of GOSAT-2 improves the yield of usable land soundings, particularly at coastal and island sites. The GOSAT-2 bias correction is cross-anchored to GOSAT over 124,206 matched-pair footprints and depends linearly on solar zenith angle. Anchoring to GOSAT rather than directly to the Total Carbon Column Observing Network (TCCON) leaves the corrected GOSAT-2 with a residual mean TCCON bias of +5.52 ppb, in exchange for sub-ppb inter-instrument consistency over the overlap period. Validation against the TCCON GGG2020.1 release yields a standard deviation of the satellite-minus-TCCON differences of 16.41 ppb and a correlation coefficient of 0.910 across 135,110 co-locations at 24 sites, compared to 16.42 ppb and 0.950 for GOSAT over 25 sites, demonstrating that GOSAT-2 reaches the precision of the heritage instrument. Co-located monthly 2° grid-cell means from GOSAT and GOSAT-2 during the 2019–2025 overlap correlate at 0.95 (land) and 0.97 (glint), with mean biases of +1.9 and +3.0 ppb. Beyond the cross-anchored correction, no further adjustment for either observation mode is required to merge the two records. The combined record forms a continuous Proxy XCH4 time series spanning 2009 to 2025, which will be extended as both missions continue to operate, and provides a reference for inter-comparison with TROPOMI and the next generation of greenhouse-gas monitoring missions. The GOSAT-2 Proxy XCH4 v2.0 dataset is available from the Centre for Environmental Data Analysis at https://doi.org/10.5285/8209b9acb92e4ba69188c9c8ff7a3b76 (Parker et al., 2026a).

Detecting and quantifying greenhouse gas (GHG) emissions is essential for understanding global GHG budgets, updating emission inventories, and evaluating climate change mitigation efforts. Most anthropogenic emissions occur at the scale of facilities, and emission distribution in time and space relates to facility operations. This paper presents a novel GHG monitoring technique for facility-scale, dynamic emission quantification under complex wind conditions, referred to as laser dispersion tomography (LDT), which integrates laser dispersion spectroscopy (LDS) with Bayesian inversion methods. It uses sequential multi-beam open-path LDS measurements and wind data to infer dynamic GHG concentration and source maps at facility scale. In this work, the use of LDT for monitoring methane emissions in agriculture is demonstrated by deploying it on an operational farm. For this aim, computational methods used in data analysis of LDT are also further developed. Particularly, we introduce spatial constraints to the tomographic reconstruction based on prior knowledge on potential source locations - information often available in facility-scale GHG monitoring applications. We investigate numerically whether such constraints could improve the tolerance of LDT to misrepresentations induced by complex wind fields caused by building effects, and/or presence of interfering external emission sources, both highly likely to characterize a real-world farm environment. The results of numerical studies indicate that including spatial constraints reduces the uncertainty and improves the reliability of source quantification in such conditions, with one simulation case showing an average reduction in posterior uncertainty of 36.2 %. In the experimental study, dynamic emission patterns caused by various operations in the farm, such as slurry and dry manure management, are well captured, both temporally and spatially. The results support the feasibility of LDT as a tool for robust quantification of GHG mass emission rates at farms, especially when the spatial constraining of sources is possible. Owing to the fine spatial and temporal resolution of LDT, we foresee its use in improving GHG emission inventories through fine parametrization, and also its extension to other GHGs and other sectors contributing to global emissions.

The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite provides daily global observations of atmospheric methane (CH4) and carbon monoxide (CO) at relatively high spatial resolution. The dense spatial and temporal coverage is achieved by the instrument’s wide swath, which permits detailed mapping of the worldwide distribution of these important atmospheric constituents. The adaptation and optimisation of the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFMD) algorithm for the simultaneous retrieval of the column-averaged dry-air mole fractions XCH4 and XCO from TROPOMI’s shortwave infrared (SWIR) radiance measurements has proven to be a valuable complement and alternative to the operational TROPOMI products. The latest release of the TROPOMI/WFMD product (version 2.0) includes several improvements expanding its suitability for a wider range of scientific applications. Data yield at mid and high latitudes has increased, accompanied by improved accuracy and precision according to the validation with the ground-based Total Carbon Column Observing Network (TCCON). These advancements are primarily due to more refined quality filtering that has been accomplished by replacing the previous Random Forest Classifier with the more efficient and potentially higher performing Extreme Gradient Boosting (XGBoost) algorithm in conjunction with improved training data incorporating an updated cloud product from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the TROPOMI Aerosol Index. This enhanced training data set enables more reliable identification of cloudy scenes and mitigates issues related to specific aerosol events over bright surfaces. Importantly, as with previous product versions, the actual quality classification does not depend on the real-time availability of these external data products, which are only required during the training phase.

The Harwell observatory, located in Oxfordshire, UK (51.571° N, 1.315° W), now part of the Total Carbon Column Observing Network (TCCON), has been performing ground-based remote sensing of averaged dry columns of atmospheric greenhouse gases since September 2020. Measurements are performed through near-infrared and shortwave infrared high-resolution spectroscopy of the atmosphere's transmission in direct sun viewing geometry, following the TCCON methodology. We report on the development, the measurements, and the performance of the observing system installed at Harwell. The hardware and software are described and characterized, as well as the outputted data quality, based on the 4-year data record collected so far. The Harwell site is demonstrated to produce data of high quality, well in line with the requirements for the TCCON infrastructure. The dataset is available at https://doi.org/10.14291/tccon.ggg2020.harwell01.R0 (Weidmann et al., 2023).

We perform a global inverse modelling analysis to quantify biomass burning emissions of carbon monoxide (CO) from the extreme wildfires in Canada between May and September 2023. Using the GEOS-Chem model, we assimilated observations at 3 d temporal and 2° × 2.5° horizontal resolution from the Tropospheric Monitoring Instrument (TROPOMI) separately and then jointly with Total Carbon Column Observing Network (TCCON) measurements. We also evaluated prior emissions from the Quick Fire Emissions Dataset (QFED), Blended Global Biomass Burning Emissions Product eXtended (GBBEPx), Global Fire Assimilation System (GFAS), and Canadian Forest Fire Emissions Prediction System (CFFEPS). The assimilation of TROPOMI-only measurements estimated posterior North America emissions for QFED, GBBEPx, GFAS, and CFFEPS of 110.4 ± 20, 112.8 ± 20, 127.2 ± 17, and 125.6 ± 18 Tg CO compared to prior estimates of 37.1, 42.7, 91.0, and 90.2 Tg CO, respectively. The joint assimilation of TROPOMI+TCCON reduced the posterior 1σ uncertainty on the North American emission estimates by up to about 30 %, while showing only a modest impact (<5 %) on the mean estimate of the inferred emissions. An evaluation against independent measurements reveals that adding TCCON data increases the correlations and slightly lowers the biases and standard deviations. Additionally, including an experimental TCCON product at East Trout Lake with higher surface sensitivity, we find better agreement of the assimilation results with nearby in situ tall tower and aircraft measurements. This highlights the potential importance of vertical sensitivity in these experimental data for constraining local surface emissions. Our results demonstrate the complementarity of the greater temporal coverage provided by TCCON with the spatial coverage of TROPOMI when these data are jointly assimilated.

The Total Carbon Column Observing Network (TCCON) and the Infrared Working Group of the Network for the Detection of Atmospheric Composition Change (NDACC-IRWG) are two ground-based networks that provide the retrieved concentrations of up to 30 atmospheric trace gases, using solar absorption spectrometry. Both networks provide reference measurements for the validation of satellites and models. TCCON concentrates on long-lived greenhouse gases (GHGs) for carbon cycle studies and validation. The number of sites is limited, and the geographical coverage is uneven, covering mainly Europe and the USA. A better distribution of stations is desired to improve the representativeness of the data for various atmospheric conditions and surface conditions and to cover a large latitudinal distribution. The two successive Fiducial Reference Measurements for Greenhouse Gases European Space Agency projects (FRM4GHG and FRM4GHG2) aim at the assessment of several low-cost portable instruments for precise measurements of GHGs to complement the existing ground-based sites. Several types of low spectral resolution Fourier transform infrared (FTIR) spectrometers manufactured by Bruker, namely an EM27/SUN, a Vertex70, a fiber-coupled IRCube, and a Laser Heterodyne spectro-Radiometer (LHR) developed by UK Rutherford Appleton Laboratory are the participating instruments to achieve the Fiducial Reference Measurements (FRMs) status. Intensive side-by-side measurements were performed using all four instruments next to the Bruker IFS 125HR high spectral resolution FTIR, performing measurements in the NIR (TCCON configuration) and MIR (NDACC configuration) spectral range. The remote sensing measurements were complemented by AirCore launches, which provided in situ vertical profiles of target gases traceable to the World Meteorological Organization (WMO) reference scale. The results of the intercomparisons are shown and discussed. Except for the EM27/SUN, all other instruments, including the reference TCCON spectrometer, needed modifications during the campaign period. The EM27/SUN and the Vertex70 provided stable and precise measurements of the target gases during the campaign with quantified small biases. As part of the FRM4GHG project, one EM27/SUN is now used as a travel standard for the verification of column-integrated GHG measurements. The extension of the Vertex70 to the MIR provides the opportunity to retrieve additional concentrations of N2O, CH4, HCHO, and OCS. These MIR data products are comparable to the retrieval results from the high-resolution IFS 125HR spectrometer as operated by the NDACC. Our studies show the potential for such types of spectrometers to be used as a travel standard for the MIR species. An enclosure system with a compact solar tracker and meteorological station has been developed to house the low spectral resolution portable FTIR systems for performing solar absorption measurements. This helps the spectrometers to be mobile and enables autonomous operation, which will help to complement the TCCON and NDACC networks by extending the observational capabilities at new sites for the observation of GHGs and additional air quality gases. The development of the retrieval software allows comparable processing of the Vertex70 type of spectra as the EM27/SUN ones, therefore bringing them under the umbrella of the COllaborative Carbon Column Observing Network (COCCON). A self-assessment following the CEOS-FRM Maturity Matrix shows that the COCCON is able to provide GHG data products of FRM quality and can be used for either short-term campaigns or long-term measurements to complement the high-resolution FTIR networks.

A global effort towards improved quantitative understanding of greenhouse gas emissions is taking pace. This includes developing source identification, quantification, and apportionment in an attempt to understand global budget and trends, but also developing monitoring systems making emission reduction commitment verifiable. In this context, we demonstrate a novel approach to continuous methane emission monitoring at the spatial scale of an industrial facility. By combining multi-directional measurements of path-integrated methane concentrations with Bayesian state estimation, we show a realistic tomographic gas plume reconstruction, its evolution in time, and the associated estimation of the source map. The method is validated using measurements from controlled methane releases over a domain of area 120×40 m2. For the first demonstration, a two dimensional geometry has been used in the gas flow model; nevertheless, sources are located within 3 to 12 meters, and mass emission rates are estimated within <30% for 80% of the cases.

Methane emissions from natural gas systems are increasingly scrutinized, and accurate reporting requires quantification of site- and source-level measurement. We evaluate the performance of 10 available state-of-the-art CH 4 emission quantification approaches against a blind controlled-release experiment at an inerted natural gas compressor station in 2021. The experiment consisted of 17 blind 2 h releases at a single exhaust point or multiple simultaneous ones. The controlled releases covered a range of methane flow rates from 0.01 to 50 kg h - 1 . Measurement platforms included aircraft, drones, trucks, vans, ground-based stations, and handheld systems. Herewith, we compare their respective strengths, weaknesses, and potential complementarity depending on the emission rates and atmospheric conditions. Most systems were able to quantify the releases within an order of magnitude. The level of errors from the different systems was not significantly influenced by release rates larger than 0.1 kg h - 1 , with much poorer results for the 0.01 kg h - 1 release. It was found that handheld optical gas imaging (OGI) cameras underestimated the emissions. In contrast, the "site-level" systems, relying on atmospheric dispersion, tended to overestimate the emission rates. We assess the dependence of emission quantification performance on key parameters such as wind speed, deployment constraints, and measurement duration. At the low wind speeds encountered (below 2 m s - 1 ), the experiments did not reveal a significant dependence on wind speed. The ability to quantify individual sources degraded during multiple-source releases. Compliance with the Oil and Gas Methane Partnership's (OGMP 2.0) highest level of reporting may require a combination of the specific advantages of each measurement technique and will depend on reconciliation approaches. Self-reported uncertainties were either not available or were based on the standard deviation in a series of independent realizations or fixed values from expert judgment or theoretical considerations. For most systems, the overall relative errors estimated in this study are higher than self-reported uncertainties.

A method for methane emissions monitoring at industrial facility level was developed based on a high precision multi-open-path laser dispersion spectrometer combined with Bayesian analysis algorithms using Monte Carlo Markov Chain (MCMC) inference. From the methane path-averaged concentrations spatially distributed over the facility under study, together with the wind vector, the analysis allows detection, localization and quantification of fugitive methane emissions. This paper describes the very first long term (3 months), continuous (24 h/7 days) deployment of this monitoring system at an operational gas processing and distribution facility. The continuous monitoring system, made of the combination of the open-path high-precision (<10 ppb) methane concentration analyser and the data analysis method, was evaluated with controlled releases of methane of about 5 kg/h for short periods of time (30–60 min). Quantification was successful, with actual emission rates lying well within the quoted uncertainty ranges. Source localisation was found to lack accuracy, with biases of 30–50 m in the direction of the line of sight of the spectrometer, due to the short duration of the controlled releases, the limited wind vector diversity, and complications from air flows around buildings not accounted for by the transport model. Using longer-term data from the deployment, the MCMC algorithm led to the identification of unexpected low intensity persistent sources (<1 kg/h) at the site. Localisation of persistent sources was mostly successful at equipment level (within ~20 m) as confirmed by a subsequent survey with an optical gas imaging (OGI) camera. Quantification of these individual sources was challenging owing to their low intensity, but a consistent estimate of the total methane emission from the facility could be derived using two different inference approaches. These results represent a stepping stone in the development of continuous monitoring systems for methane emissions, pivotal in driving greenhouse gas reduction from industrial facilities. The demonstrated continuous monitoring system gives promising performance in early detection of unexpected emissions and quantification of potentially time-varying emissions from an entire facility.

A laser-based open-path dispersion spectrometer for measuring atmospheric methane has been developed with the goal of achieving a very simple architecture, yet enabling molecular dispersion measurements immune to optical power variation. Well-mature, near-infrared photonics components were retained to demonstrate a compact, cost-effective, and low-power consumption dispersion spectrometer. In particular, measurements immune to received optical power variations are demonstrated despite the use of only phase modulation and are supported by the development of the corresponding physical model. The instrument has been validated under laboratory conditions, finding a precision of 2.6 ppb 100 m for a 2 s measurement, and demonstrated through atmospheric measurements performed continuously over six days with an 86 m path length.

The demonstration and first evaluation of chirped laser dispersion spectroscopy (CLaDS) for quantitative measurements of gas molecules with broad spectral features is reported. The demonstration is conducted on propyne (methyl acetylene) gas, using a widely tunable external cavity near infrared laser, λ ≈ 1.55 µm, whose frequency can be swept at 2.6 MHz/µs. A direct baseband downconversion scheme is implemented to recover molecular dispersion, with a cost-effective 32 GHz radio frequency architecture. Laboratory tests demonstrate in particular the value of laser dispersion spectroscopy for the sensing of turbid media with a large range of variations, owing to a significant immunity of the detection scheme to variations in received optical power. Normalized minimum concentration measurable in the 1.5 ms scan is ∼0.7 ppm.m.√Hz.

Abstract Background Sepsis and infection are the leading cause of morbidity and mortality after surgery, but the inflammatory response to the trauma of surgery can make diagnosis challenging. Carbon-13 breath delta value (13C BDV) has been shown to be discriminant as a novel diagnostic marker for sepsis and infection. We aim to assess biomarkers including BDV following major hepatopancreatobiliary (HPB) surgery to diagnose postoperative infection/sepsis. Methods 20 participants undergoing HPB surgery were recruited prospectively. Breath samples were collected from baseline preoperatively, and on postoperative days (POD) 1–9, with plasma and peripheral blood mononuclear cell (PBMC) samples preoperatively, POD1, 4 and 8. Breath samples were analysed using infrared laser spectroscopy to generate BDV (per mil). Plasma was analysed for cytokines using MesoScale Discovery immunoassay, Procalcitonin (PCT) using ELISA, and Cell surface marker expression on monocytes was phenotyped using flow cytometry. Differences between groups who did and did not develop infective complications was analysed using two-way ANOVA and Mann Whitney U test. Results 5/20 participants developed infective complications, with a mean day of diagnosis POD5. There was no difference between BDV in patients with or without infection. Monocyte count was increased in infected participants at all timepoints, and monocyte expression of PD-L1 on POD1, and CD155 and HLA-DR on POD4 was upregulated, +13.09% (95%CI 1.59 to 24.61, p<0.05), +422.5 MFI (95% CI -770.9 to -73.68, p<0.05), and +19.02% (95% CI 37.58 to 0.45, p<0.05) respectively. Conclusions Monocyte expression of PD-L1, HLA-DR and CD155 is associated with infection, +13.09% (p<0.05), +422.5 MFI (p<0.05), and +19.02% (p<0.05) respectively. The innate immune system is dysregulated in infection following major HPB surgery. In this cohort BDV did not predict infection. Further investigation of novel biomarkers including BDV and soluble monocyte markers is required.

The action to reduce anthropogenic greenhouse gas emissions is severely constrained by the difficulty of locating sources and quantifying their emission rates. Methane emissions by the energy sector are of particular concern. We report results achieved with a new area monitoring approach using laser dispersion spectroscopy to measure path-averaged concentrations along multiple beams. The method is generally applicable to greenhouse gases, but this work is focused on methane. Nineteen calibrated methane releases in four distinct configurations, including three separate blind trials, were made within a flat test area of 175 m by 175 m. Using a Gaussian plume gas dispersion model, driven by wind velocity data, we calculate the data anticipated for hundreds of automatically proposed candidate source configurations. The Markov-chain Monte Carlo analysis finds source locations and emission rates whose calculated path-averaged concentrations are consistent with those measured and associated uncertainties. This approach found the correct number of sources and located them to be within <9 m in more than 75% of the cases. The relative accuracy of the mass emission rate results was highly correlated to the localization accuracy and better than 30% in 70% of the cases. The discrepancies for mass emission rates were <2 kg/h for 95% of the cases.

Trace gas analysis provides a wide range of insights into environmental processes, particularly with regards to global warming and air quality. With the urgent need to identify sources and accurately measure the harmful emissions negatively impacting our planet, Laser Dispersion Spectroscopy (LDS) offers a unique approach. LDS technology measures optical molecular dispersion via a differential phase measurement of light and, operating in the mid-infrared, provides highly sensitive and robust measurements. This enables highly precise, real-time gas measurements even in adverse environmental conditions such as rain, fog, snow or dust. The technology can be used in both extractive and open-path formats, with real-world applications including emissions monitoring on oil and gas sites, measuring the impact of agricultural activities and monitoring carbon capture storage facilities.

A miniature thermal infrared laser heterodyne spectro-radiometer based on hybrid optical integration is demonstrated. A quantum cascade laser emitting at 953 cm-1 (10.5 μm) is used as the local oscillator. Integration is achieved using hollow waveguides inscribed in a copper substrate, with slot-encapsulated optical components positioned to maintain fundamental hybrid mode coupling. The demonstrator performances are studied in the laboratory and show a noise level within 1.6 times of the ideal case. Atmospheric high-resolution transmittance spectroscopy of carbon dioxide and water vapor in solar occultation is demonstrated. The total column concentrations are derived as well as measurement uncertainties, 399.5 ± 2.2 ppm for CO2 and 1066 ± 62 ppm for H2O. The miniature laser heterodyne spectro-radiometer demonstration opens the prospect for nanosatellite-based high spectral resolution thermal infrared atmospheric sounding.

Laser heterodyne spectro-radiometry offers significant combined benefits for molecular remote sensing: ultrahigh spectral resolution, narrow field of view, and ideally a shot noise limited radiometric sensitivity. In conjunction with the development of photonics, compact systems leveraging these benefits can be developed for atmospheric composition sounding applications. In this chapter, principles of laser heterodyning are presented, as well as those of molecular altitudinal profiling from passive spectrometers. Examples of developments of quantum cascade laser heterodyne spectro-radiometers are given in the context of ozone and greenhouse gas sensing, among others atmospheric constituents. Miniaturized heterodyne systems are also described in the context of small satellite space missions for high accuracy atmospheric profiling. Lastly, prospective space missions exploiting the benefits of laser heterodyne spectro-radiometers are outlined.

© Copyright © 2020 de Leede-Smith, Roodenrys, Horsley, Matrini, Mison and Barkus. Semantic processing underpins the organization of verbal information for both storage and retrieval. Deficits in semantic processing are associated with both the risk for and symptoms presented in schizophrenia. However, studies are mixed and could reflect the confounding effects of medication and symptom heterogeneity. Therefore, we considered whether two risk phenotypes, positive schizotypy and hallucinatory predisposition, present in the general population were associated with differential responding profiles for a semantic processing task. One hundred and eighty-three participants completed the Schizotypal Personality Questionnaire, Launay-Slade Hallucination Scale, National Adult Reading Test, a handedness measure, and a computerized semantic relatedness judgment task. Pairs of words were related through their dominant or subordinate meanings, or unrelated. Participants were divided into four groups using a mean split on cognitive-perceptual (positive) schizotypy and hallucination proneness. Significant differences between groups were found for reaction time on the semantic relatedness task, with the high cognitive-perceptual schizotypy groups responding significantly slower to all word pairs compared to their low scoring counterparts. There was some evidence that high hallucination proneness was associated with significantly faster reaction times which may reflect disinhibitive processes, however additional support is required. The results suggest that these two components of psychosis risk are associated with different patterns of responding to semantic processing. More diffuse activation of semantic information appeared to be associated with positive schizotypy, while those predisposed to hallucinations appeared to respond quicker. These results have significant implications in the re-conceptualization of hallucination proneness as distinct from positive schizotypy. Additional research is required to investigate the association between psychotic-like experiences separate from personality variables such as positive schizotypy and semantic processing.