Lessons learned from a UAV survey and methane emissions calculation at a UK landfill.

Accurate quantification of methane emissions from landfills is crucial for improving greenhouse gas inventories and mitigating climate change impacts. Existing methodologies, such as theoretical gas production models and labour-intensive measurement approaches, present limitations including large uncertainties and high operational costs. This study adds to a growing body of research and applications which aim to bridge this gap. To this end, we present a case study using Unmanned Aerial Vehicles (UAVs) equipped with methane and wind instrumentation for a survey of a landfill site in Bury, Manchester, UK, in summer 2022, in order to evaluate and reflect the challenges of the UAV-based mass balance method for quantification of methane emissions from a large heterogeneous source such as landfill. This study offers guidance on defining an appropriate methane background concentration, geospatial interpolation of sampled date, survey sampling strategy, and more importantly, addresses the challenges surrounding UAV wind measurements and spatial characterisation of emission plumes. For the period of the case study, we quantified methane flux for the landfill site to be 150.7 kg h-1 with a 1 standard deviation uncertainty range of 83.0 kg h-1 to 209.5 kg h-1.

Pandemic-Related Post-traumatic Stress Symptomatology in COVID-19 Patients with and without Post-COVID Conditions.

Trauma and stressor-related symptoms have been frequently reported during the COVID-19 pandemic. Few studies compare post-traumatic stress symptoms (PTSS) between patients and non-infected controls. Using data from an ongoing natural history study of COVID-19, this study compared PTSS between patients infected with SARS-CoV-2 during the first year of the pandemic and controls. Within the COVID-19 patient cohort, we also compared PTSS between patients with and without post-COVID conditions, also known as post-acute sequelae of SARS-CoV-2 infection (PASC). This study also examined the association of PTSS with trait resilience and prior trauma exposure. PTSS were assessed using the Impact of Event Scaled-Revised (IES-R), which has a validated probable PTSD cutoff (score ≥33). The results showed that patients (n=131) reported significantly higher IES-R scores than controls (n=82) and had significantly higher odds of having scores indicative of PTSD [AOR: 4.17 p: 0.029]. IES-R scores among PASC patients (n=68) were significantly elevated compared to patients without PASC (n=63) and PASC patients did not have higher odds for probable PTSD [AOR: 2.60; p: 0.14]. Trait resilience was associated with lower PTSS. These findings help characterize the mental health impact of the COVID-19 illness experience and highlight elevated PTSS in patients with persistent post-COVID conditions.

The Relationship Between First Presenting Neuropsychiatric Symptoms in Older Adults and Autopsy-Confirmed Memory Disorders.

OBJECTIVES: Although dementia is typically considered a disease of cognitive decline, almost all patients present with neuropsychiatric symptoms (NPS) at some stage of their disease. Few studies have assessed the timing of NPS onset in relation to pathological diagnoses of neurodegenerative diseases. We sought to examine the association between the first presenting clinically significant NPS in aging individuals and neuropathological diagnoses of memory disorders. DESIGN: This retrospective longitudinal cohort study utilized the National Alzheimer's Coordinating Center (NACC) dataset, which includes participant data from 37 Alzheimer's Disease Research Centers collected between 2005 and 2022. PARTICIPANTS: Participants (N = 5,416) aged 45 years or older with Clinical Dementia Rating-Global ratings of less than or equal to 1 were included in this analysis. A total of 4,033 (74.5%) participants presented with at least one NPS at any NACC visit. MEASUREMENTS: To measure first NPS, the NACCBEHF variable was used, a clinician-rated variable defined as "the predominant symptom that was first recognized as a decline in the subject's behavior." Neuropathologic variables included assessments of Alzheimer's Disease, Frontotemporal Dementia, Lewy Body Dementia, Cerebral Amyloid Angiopathy, Hippocampal Sclerosis, and Cerebrovascular Disease. RESULTS: Presentation with any clinically significant first NPS was associated with several neuropathological diagnoses including Alzheimer's Disease, Frontotemporal Lobar Dementia with TDP-43 pathology, and Lewy Body Dementia. While specific first NPS were associated with Frontotemporal Dementia neuropathology (personality change and disinhibition) and Lewy Body Dementia neuropathology (psychosis and REM behavior disturbance), Alzheimer's Disease neuropathology was associated with the majority of NPS. CONCLUSIONS: Since neuropsychiatric symptoms are frequently the first presenting symptom of dementia, their associations with well-defined neuropathological diagnoses may help clinicians predict the subtype of future dementias.

Multimodal nanoparticle-containing modified suberoylanilide hydroxamic acid polymer conjugates to mitigate immune dysfunction in severe inflammation.

Excessive immune activation and immunosuppression are opposing factors that contribute to the dysregulated innate and adaptive immune responses seen in severe inflammation and sepsis. Here, a novel analog of the histone deacetylase inhibitor (HDACi), suberoylanilide hydroxamic acid (SAHA-OH), was incorporated into immunomodulatory poly(lactic acid)-based nanoparticles (iNP-SAHA) by employing a prodrug approach through the covalent modification of poly(lactic-co-glycolic acid) (PLGA) with SAHA-OH. iNP-SAHA formulation allowed for controlled incorporation and delivery of SAHA-OH from iNP-SAHA and treatment led to multimodal biological responses including significant reductions in proinflammatory cytokine secretions and gene expression, while increasing the survival of primary macrophages under lipopolysaccharide (LPS) challenge. Using a lethal LPS-induced endotoxemia mouse model of sepsis, iNP-SAHA administration improved the survival of mice in a dose-dependent manner and tended to improve survival at the lowest doses compared to iNP control. Further, iNP-SAHA reduced the levels of plasma proinflammatory cytokines and chemokines associated with sepsis more significantly than iNP and similarly improved inflammation-induced spleen and liver toxicity as iNP, supporting its potential polypharmacological activity. Collectively, iNP-SAHA offers a potential drug delivery approach to modulate the multifaceted inflammatory responses observed in diseases such as sepsis.

Toward Personalized Cognitive Training in Older Adults: A Pilot Investigation of the Effects of Baseline Performance and Age on Cognitive Training Outcomes.

BACKGROUND: Cognitive training holds potential as a non-pharmacological intervention to decrease cognitive symptoms associated with Alzheimer's disease (AD), but more research is needed to understand individual differences that may predict maximal training benefits. OBJECTIVE: We conducted a pilot study using a six-month training regimen in healthy aging adults with no cognitive decline. We investigated the effects of baseline performance and age on training and transfer improvements. METHODS: Out of 43 participants aged 65-84 years, 31 successfully completed cognitive training (BrainHQ) in one of three cognitive domains: processing speed (N = 13), inhibitory control (N = 9), or episodic memory (N = 9). We used standardized assessments to measure baseline performance and transfer effects. RESULTS: All 31 participants improved on the cognitive training regimen and age was positively associated with training improvement (p = 0.039). The processing speed group improved significantly across many near- and far-transfer tasks. In the inhibitory control group, individuals with lower baseline performance improved more on inhibitory control and cognitive flexibility tasks. In the episodic memory group, older individuals improved most on a memory task while younger individuals improved most on an executive function far-transfer task. CONCLUSIONS: Individual differences are predictive of cognitive training gains, and the impact of individual differences on training improvements is specific to the domain of training. We provide initial insight regarding how non-pharmacological interventions can be optimized to combat the onset of cognitive decline in older adults. With future research this work can inform the design of effective cognitive interventions for delaying cognitive decline in preclinical AD.

Cell and biomaterial delivery strategies to induce immune tolerance.

The prevalence of immune-mediated disorders, including autoimmune conditions and allergies, is steadily increasing. However, current therapeutic approaches are often non-specific and do not address the underlying pathogenic condition, often resulting in impaired immunity and a state of generalized immunosuppression. The emergence of technologies capable of selectively inhibiting aberrant immune activation in a targeted, antigen (Ag)-specific manner by exploiting the body's intrinsic tolerance pathways, all without inducing adverse side effects, holds significant promise to enhance patient outcomes. In this review, we will describe the body's natural mechanisms of central and peripheral tolerance as well as innovative delivery strategies using cells and biomaterials targeting innate and adaptive immune cells to promote Ag-specific immune tolerance. Additionally, we will discuss the challenges and future opportunities that warrant consideration as we navigate the path toward clinical implementation of tolerogenic strategies to treat immune-mediated diseases.

Trends in Language Use During the COVID-19 Pandemic and Relationship Between Language Use and Mental Health: Text Analysis Based on Free Responses From a Longitudinal Study.

BACKGROUND: The COVID-19 pandemic and its associated restrictions have been a major stressor that has exacerbated mental health worldwide. Qualitative data play a unique role in documenting mental states through both language features and content. Text analysis methods can provide insights into the associations between language use and mental health and reveal relevant themes that emerge organically in open-ended responses. OBJECTIVE: The aim of this web-based longitudinal study on mental health during the early COVID-19 pandemic was to use text analysis methods to analyze free responses to the question, "Is there anything else you would like to tell us that might be important that we did not ask about?" Our goals were to determine whether individuals who responded to the item differed from nonresponders, to determine whether there were associations between language use and psychological status, and to characterize the content of responses and how responses changed over time. METHODS: A total of 3655 individuals enrolled in the study were asked to complete self-reported measures of mental health and COVID-19 pandemic-related questions every 2 weeks for 6 months. Of these 3655 participants, 2497 (68.32%) provided at least 1 free response (9741 total responses). We used various text analysis methods to measure the links between language use and mental health and to characterize response themes over the first year of the pandemic. RESULTS: Response likelihood was influenced by demographic factors and health status: those who were male, Asian, Black, or Hispanic were less likely to respond, and the odds of responding increased with age and education as well as with a history of physical health conditions. Although mental health treatment history did not influence the overall likelihood of responding, it was associated with more negative sentiment, negative word use, and higher use of first-person singular pronouns. Responses were dynamically influenced by psychological status such that distress and loneliness were positively associated with an individual's likelihood to respond at a given time point and were associated with more negativity. Finally, the responses were negative in valence overall and exhibited fluctuations linked with external events. The responses covered a variety of topics, with the most common being mental health and emotion, social or physical distancing, and policy and government. CONCLUSIONS: Our results identify trends in language use during the first year of the pandemic and suggest that both the content of responses and overall sentiments are linked to mental health.

The Emotional and Personal Experiences of the COVID-19 Illness During the Early Pandemic: A Qualitative Study.

BACKGROUND: Several studies report the incidence of psychiatric symptoms and disorders among patients who recovered from coronavirus disease 2019 (COVID-19); however, little is known about the emotional impact of acute COVID-19 illness and recovery on these survivors. Qualitative methods are ideal for understanding the psychological impact of a novel illness. OBJECTIVE: To describe the emotional experience of the acute COVID-19 illness and recovery in patients who contracted the virus during the early months of the pandemic. METHODS: Semi-structured interviews conducted by consultation-liaison (C-L) psychiatrists were used to elicit participant responses about the emotional impact of the acute and recovery phases of the COVID-19 illness. Participants recruited from the Maryland, District of Columbia, and Virginia area were interviewed which was audio recorded between June 2020 and December 2020. The research team extracted qualitative themes from the recordings using the principles of thematic analysis. RESULTS: One hundred and one COVID-19 survivors (54 women; mean [SD] age, 50 [14.7] years) were interviewed at a mean of 5.16 months after their acute illness, and their responses were audio-recorded. Most participants were White (77%), non-Hispanic/Latino (86.1%), and not hospitalized for COVID-19 (87.1%). Coders identified 26 themes from participant responses. The most frequently coded themes included anxiety/worry (49), uncertainty (37), supportfrom others (35), alone/isolation (32), and positive reframe/positive emotions (32). CONCLUSIONS: Survivors who contracted severe acute respiratory syndrome coronavirus 2 during the early months of the pandemic described both negative and positive valence emotions. They experienced emotional distress and psychosocial stressors associated with the acute illness and recovery but also drew upon personal resiliency to cope. This report highlights the utility of qualitative research methods in identifying emotional responses to a novel illness that may otherwise go unnoted. Consultation-liaison psychiatrists may be uniquely positioned to work in collaboration with medical colleagues in developing a multidimensional approach to evaluating an emerging illness.

Examining the factor structure of the DSM-5 Level 1 cross-cutting symptom measure.

OBJECTIVES: The DSM-5 Level 1 Cross-Cutting Symptom Measure (DSM-XC) was developed by the American Psychiatric Association as a transdiagnostic mental health symptom survey. Despite its promise as a screening tool, few studies have assessed its latent dimensionality or provided guidance on interpreting responses. We examined the factor structure of the DSM-XC in a convenience sample of participants with varying degrees of psychopathology. METHODS: Participants (n = 3533) were enrolled in an online study on the mental health impact of COVID-19 (NCT04339790). We used a factor analytic framework with exploratory and confirmatory analyses to evaluate candidate factor solutions. Convergent validity analysis with concurrent study measures was also performed. RESULTS: Six-factor and bifactor candidate solutions both had good fit and full measurement invariance across age, sex, and enrollment date. The six-factor solution resulted in constructs labeled as: mood, worry, activation, somatic, thought, and substance use. A general psychopathology factor and two residual factors (mood and anxiety constructs) explained the variance of the bifactor solution. CONCLUSIONS: Our analysis supports that the DSM-XC is a multidimensional instrument spanning many mental health symptoms. We provide scoring solutions for two factor structures that capture broader constructs of psychopathology. Use of a convenience sample may limit generalizability of findings.

Modified Suberoylanilide Hydroxamic Acid Reduced Drug-Associated Immune Cell Death and Organ Damage under Lipopolysaccharide Inflammatory Challenge.

Histone deacetylase inhibitors (HDACi) induce potent anti-inflammatory responses when used to treat inflammatory diseases. Suberoylanilide hydroxamic acid (SAHA), a pan-HDACi, decreases pro-inflammatory cytokine levels and attenuates cytokine storm in sepsis; however, its toxicity profile toward immune cells has limited its use as a sepsis therapeutic. Here, we developed a modification to SAHA by para-hydroxymethylating the capping group to generate SAHA-OH. We discovered that SAHA-OH provides a favorable improvement to the toxicity profile compared to SAHA. SAHA-OH significantly reduced primary macrophage apoptosis and splenic B cell death as well as mitigated organ damage using a lipopolysaccharide (LPS)-induced endotoxemia mouse model. Furthermore, SAHA-OH retained anti-inflammatory responses similar to SAHA as measured by reductions in LPS-induced proinflammatory cytokine secretions in vitro and in vivo. These effects were attributed to a decreased selectivity of HDAC1, 2, 3, 8 and an increased selectivity for HDAC6 for SAHA-OH as determined by IC50 values. Our results support the potential for SAHA-OH to modulate acute proinflammatory responses while mitigating SAHA-associated drug toxicity for use in the treatment of inflammation-associated diseases and conditions.

The NIMH intramural healthy volunteer dataset: A comprehensive MEG, MRI, and behavioral resource.

The NIMH Healthy Research Volunteer Dataset is a collection of phenotypic data characterizing healthy research volunteers using clinical assessments such as assays of blood and urine, mental health assessments, diagnostic and dimensional measures of mental health, cognitive and neuropsychological functioning, structural and functional magnetic resonance imaging (MRI), along with diffusion tensor imaging (DTI), and a comprehensive magnetoencephalography battery (MEG). In addition, blood samples of healthy volunteers are banked for future analyses. All data collected in this protocol are broadly shared in the OpenNeuro repository, in the Brain Imaging Data Structure (BIDS) format. In addition, task paradigms and basic pre-processing scripts are shared on GitHub. There are currently few open access MEG datasets, and multimodal neuroimaging datasets are even more rare. Due to its depth of characterization of a healthy population in terms of brain health, this dataset may contribute to a wide array of secondary investigations of non-clinical and clinical research questions.

A Longitudinal Study of COVID-19 Sequelae and Immunity: Baseline Findings.

BACKGROUND: A substantial proportion of persons who develop COVID-19 report persistent symptoms after acute illness. Various pathophysiologic mechanisms have been implicated in the pathogenesis of postacute sequelae of SARS-CoV-2 infection (PASC). OBJECTIVE: To characterize medical sequelae and persistent symptoms after recovery from COVID-19 in a cohort of disease survivors and controls. DESIGN: Cohort study. (ClinicalTrials.gov: NCT04411147). SETTING: National Institutes of Health Clinical Center, Bethesda, Maryland. PARTICIPANTS: Self-referred adults with laboratory-documented SARS-CoV-2 infection who were at least 6 weeks from symptom onset were enrolled regardless of presence of PASC. A control group comprised persons with no history of COVID-19 or serologic evidence of SARS-CoV-2 infection, recruited regardless of their current health status. Both groups were enrolled over the same period and from the same geographic area. MEASUREMENTS: All participants had the same evaluations regardless of presence of symptoms, including physical examination, laboratory tests and questionnaires, cognitive function testing, and cardiopulmonary evaluation. A subset also underwent exploratory immunologic and virologic evaluations. RESULTS: 189 persons with laboratory-documented COVID-19 (12% of whom were hospitalized during acute illness) and 120 antibody-negative control participants were enrolled. At enrollment, symptoms consistent with PASC were reported by 55% of the COVID-19 cohort and 13% of control participants. Increased risk for PASC was noted in women and those with a history of anxiety disorder. Participants with findings meeting the definition of PASC reported lower quality of life on standardized testing. Abnormal findings on physical examination and diagnostic testing were uncommon. Neutralizing antibody levels to spike protein were negative in 27% of the unvaccinated COVID-19 cohort and none of the vaccinated COVID-19 cohort. Exploratory studies found no evidence of persistent viral infection, autoimmunity, or abnormal immune activation in participants with PASC. LIMITATIONS: Most participants with COVID-19 had mild to moderate acute illness that did not require hospitalization. The prevalence of reported PASC was likely overestimated in this cohort because persons with PASC may have been more motivated to enroll. The study did not capture PASC that resolved before enrollment. CONCLUSION: A high burden of persistent symptoms was observed in persons after COVID-19. Extensive diagnostic evaluation revealed no specific cause of reported symptoms in most cases. Antibody levels were highly variable after COVID-19. PRIMARY FUNDING SOURCE: Division of Intramural Research, National Institute of Allergy and Infectious Diseases.

Nanoparticle personalized biomolecular corona: implications of pre-existing conditions for immunomodulation and cancer.

Nanoparticles (NPs) have demonstrated great promise as immunotherapies for applications ranging from cancer, autoimmunity, and infectious disease. Upon encountering biological fluids, NPs rapidly adsorb biomolecules, forming the "biomolecular corona" (BC), and the altered character of NPs due to their newly acquired biological identity can impact their in vivo fate. Recently, it has been shown that the NP-BC is person-specific, and even minute differences in the biomolecule composition can give rise to altered immune recognition, cellular interactions, pharmacokinetics, and biodistribution. Given the current rise in the development of NP-based therapeutics, it is of utmost importance to better understand how pre-existing conditions, that result in the formation of a personalized BC, can be leveraged to aid in the prediction of the therapeutic outcomes of NPs. In this minireview, we will discuss the formation of the BC, implications of the BC for NP-biological interactions, and its clinical importance in the context of immunomodulation and cancer therapeutics.

Isotopic signatures of methane emissions from tropical fires, agriculture and wetlands: the MOYA and ZWAMPS flights.

We report methane isotopologue data from aircraft and ground measurements in Africa and South America. Aircraft campaigns sampled strong methane fluxes over tropical papyrus wetlands in the Nile, Congo and Zambezi basins, herbaceous wetlands in Bolivian southern Amazonia, and over fires in African woodland, cropland and savannah grassland. Measured methane δ13CCH4 isotopic signatures were in the range -55 to -49‰ for emissions from equatorial Nile wetlands and agricultural areas, but widely -60 ± 1‰ from Upper Congo and Zambezi wetlands. Very similar δ13CCH4 signatures were measured over the Amazonian wetlands of NE Bolivia (around -59‰) and the overall δ13CCH4 signature from outer tropical wetlands in the southern Upper Congo and Upper Amazon drainage plotted together was -59 ± 2‰. These results were more negative than expected. For African cattle, δ13CCH4 values were around -60 to -50‰. Isotopic ratios in methane emitted by tropical fires depended on the C3 : C4 ratio of the biomass fuel. In smoke from tropical C3 dry forest fires in Senegal, δ13CCH4 values were around -28‰. By contrast, African C4 tropical grass fire δ13CCH4 values were -16 to -12‰. Methane from urban landfills in Zambia and Zimbabwe, which have frequent waste fires, had δ13CCH4 around -37 to -36‰. These new isotopic values help improve isotopic constraints on global methane budget models because atmospheric δ13CCH4 values predicted by global atmospheric models are highly sensitive to the δ13CCH4 isotopic signatures applied to tropical wetland emissions. Field and aircraft campaigns also observed widespread regional smoke pollution over Africa, in both the wet and dry seasons, and large urban pollution plumes. The work highlights the need to understand tropical greenhouse gas emissions in order to meet the goals of the UNFCCC Paris Agreement, and to help reduce air pollution over wide regions of Africa. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.

Microfluidic-Generated Immunomodulatory Nanoparticles and Formulation-Dependent Effects on Lipopolysaccharide-Induced Macrophage Inflammation.

Nanoparticles (NPs) have emerged as a highly useful and clinically translatable drug delivery platform for vast therapeutic payloads. Through the precise tuning of their physicochemical properties, NPs can be engineered to exhibit controlled drug release properties, enhanced circulation times, improved cellular uptake and targeting, and reduced toxicity profiles. Conventional bulk methods for the production of polymeric NPs suffer from the ability to control their size and polydispersity, batch-to-batch variability, significant preparation times, and low recovery. Here, we describe the development and optimization of a high-throughput microfluidic method to produce cargo-less immunomodulatory nanoparticles (iNPs) and their formulation-dependent anti-inflammatory properties for the modulation of lipopolysaccharide (LPS)-induced macrophage responses. Using poly(lactic acid) (PLA) as the core-forming polymer, a rapid and tunable microfluidic hydrodynamic flow-focusing method was developed and optimized to systematically evaluate the role of polymer and surfactant concentration, surfactant chemistry, and flow rate ratio (FRR) on the formation of iNPs. A set of iNPs with 6 different surface chemistries and 2 FRRs was then prepared to evaluate their inherent anti-inflammatory effects using bone marrow-derived macrophages stimulated with the Toll-like receptor 4 agonist, LPS. Finally, a lyophilization study was performed using various cryoprotectants and combinations to identify preferable conditions for iNP storage. Overall, we demonstrate a highly controlled and reproducible method for the formulation of iNPs using microfluidics and their formulation-dependent inherent anti-inflammatory immunomodulatory properties, which represents a potentially promising strategy for the management of inflammation.

COVID-19 and Mental Health: Predicted Mental Health Status is Associated with Clinical Symptoms and Pandemic-Related Psychological and Behavioral Responses.

BACKGROUND: The COVID-19 pandemic led to dramatic threats to health and social life. Study objectives - develop a prediction model leveraging subsample of known Patient/Controls and evaluate the relationship of predicted mental health status to clinical outcome measures and pandemic-related psychological and behavioral responses during lockdown (spring/summer 2020). METHODS: Online cohort study conducted by National Institute of Mental Health Intramural Research Program. Convenience sample of English-speaking adults (enrolled 4/4-5/16/20; n=1,992). Enrollment measures: demographics, clinical history, functional status, psychiatric and family history, alcohol/drug use. Outcome measures (enrollment and q2 weeks/6 months): distress, loneliness, mental health symptoms, and COVID-19 survey. NIMH IRP Patient/Controls survey responses informed assignment of Patient Probability Scores (PPS) for all participants. Regression models analyzed the relationship between PPS and outcome measures. OUTCOMES: Mean age 46.0 (±14.7), female (82.4%), white (88.9 %). PPS correlated with distress, loneliness, depression, and mental health factors. PPS associated with negative psychological responses to COVID-19. Worry about mental health (OR 1.46) exceeded worry about physical health (OR 1.13). PPS not associated with adherence to social distancing guidelines but was with stress related to social distancing and worries about infection of self/others. INTERPRETATION: Mental health status (PPS) was associated with concurrent clinical ratings and COVID-specific negative responses. A focus on mental health during the pandemic is warranted, especially among those with mental health vulnerabilities. We will include PPS when conducting longitudinal analyses of mental health trajectories and risk and resilience factors that may account for differing clinical outcomes. FUNDING: NIMH (ZIAMH002922); NCCIH (ZIAAT000030).

Methods for quantifying methane emissions using unmanned aerial vehicles: a review.

Methane is an important greenhouse gas, emissions of which have vital consequences for global climate change. Understanding and quantifying the sources (and sinks) of atmospheric methane is integral for climate change mitigation and emission reduction strategies, such as those outlined in the 2015 UN Paris Agreement on Climate Change. There are ongoing international efforts to constrain the global methane budget, using a wide variety of measurement platforms across a range of spatial and temporal scales. The advancements in unmanned aerial vehicle (UAV) technology over the past decade have opened up a new avenue for methane emission quantification. UAVs can be uniquely equipped to monitor natural and anthropogenic emissions at local scales, displaying clear advantages in versatility and manoeuvrability relative to other platforms. Their use is not without challenge, however: further miniaturization of high-performance methane instrumentation is needed to fully use the benefits UAVs afford. Developments in the models used to simulate atmospheric transport and dispersion across small, local scales are also crucial to improved flux accuracy and precision. This paper aims to provide an overview of currently available UAV-based technologies and sampling methodologies which can be used to quantify methane emission fluxes at local scales. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

Examining the Factor Structure of the DSM-5 Level 1 Cross-Cutting Symptom Measure.

OBJECTIVES: The DSM-5 Level 1 Cross-Cutting Symptom Measure (DSM-XC) is a transdiagnostic mental health symptom measure that has shown promise in informing clinical diagnostic evaluations and as a screening tool for research. However, few studies have assessed the latent dimensionality of the DSM-XC. We examined the factor structure of the DSM-XC in a large convenience sample of participants with varying degrees of psychological health. METHODS: Participants (n=3533) enrolled in a protocol conducted at the National Institute of Mental Health (NCT04339790). We used a factor analytic framework to evaluate an existing two-factor solution (Lace & Merz, 2020) and two additional candidate solutions. RESULTS: The Lace and Merz solution had acceptable fit. Exploratory factor analysis yielded two candidate solutions: a six-factor (characterized as mood, worry, activation, somatic, thoughts, and substance use) and a bifactor (general factor of non-specific psychopathology, residual factors characterized as internalizing and thought disorder), which both had good fit and full measurement invariance across age, sex, and enrollment date. CONCLUSIONS: Our findings confirm that the DSM-XC may be conceptualized as a multidimensional instrument and provide a scoring solution for researchers who wish to measure distinct constructs. Future research on the psychometric profile of the DSM-XC is needed, focused on the validity of these candidate solutions and their performance across research populations and settings.

Methane flux from flowback operations at a shale gas site.

We report measurements of methane (CH4) mixing ratios and emission fluxes derived from sampling at a monitoring station at an exploratory shale gas extraction facility in Lancashire, England. Elevated ambient CH4 mixing ratios were recorded in January 2019 during a period of cold-venting associated with a nitrogen lift process at the facility. These processes are used to clear the well to stimulate flow of natural gas from the target shale. Estimates of CH4 flux during the emission event were made using three independent modeling approaches: Gaussian plume dispersion (following both a simple Gaussian plume inversion and the US EPA OTM 33-A method), and a Lagrangian stochastic transport model (WindTrax). The three methods yielded an estimated peak CH4 flux during January 2019 of approximately 70 g s-1. The total mass of CH4 emitted during the six-day venting period was calculated to be 2.9, 4.2 ± 1.4(1σ) and 7.1 ± 2.1(1σ) tonnes CH4 using the simple Gaussian plume model, WindTrax, and OTM-33A methods, respectively. Whilst the flux approaches all agreed within 1σ uncertainty, an estimate of 4.2 (± 1.4) tonnes CH4 represents the most confident assessment due to the explicit modeling of advection and meteorological stability permitted using the WindTrax model. This mass is consistent with fluxes calculated by the Environment Agency (in the range 2.7 to 6.8 tonnes CH4), using emission data provided by the shale site operator to the regulator. This study provides the first CH4 emission estimate for a nitrogen lift process and the first-reported flux monitoring of a UK shale gas site, and contributes to the evaluation of the environmental impacts of shale gas operations worldwide. This study also provides forward guidance on future monitoring applications and flux calculation in transient emission events. Implications: This manuscript discusses atmospheric measurements near to the UK's first hydraulic fracturing facility, which has very high UK public, media, and policy interest. The focus of this manuscript is on a single week of data in which a large venting event at the shale gas site saw emissions of ~4 tonnes of methane to atmosphere, in breach of environmental permits. These results are likely to beresults are likely to be reported by the media and may influence future policy decisions concerning the UK hydraulic fracturing industry.

Environmental baseline monitoring for shale gas development in the UK: Identification and geochemical characterisation of local source emissions of methane to atmosphere.

Baseline mobile surveys of methane sources using vehicle-mounted instruments have been performed in the Fylde and Ryedale regions of Northern England over the 2016-19 period around proposed unconventional (shale) gas extraction sites. The aim was to identify and characterise methane sources ahead of hydraulically fractured shale gas extraction in the area around drilling sites. This allows a potential additional source of emissions to atmosphere to be readily distinguished from adjacent sources, should gas production take place. The surveys have used ethane:methane (C2:C1) ratios to separate combustion, thermogenic gas and biogenic sources. Sample collection of source plumes followed by high precision δ13C analysis of methane, to separate and isotopically characterise sources, adds additional biogenic source distinction between active and closed landfills, and ruminant eructations from manure. The surveys show that both drill sites and adjacent fixed monitoring sites have cow barns and gas network pipeline leaks as sources of methane within a 1 km range. These two sources are readily separated by isotopes (δ13C of -67 to -58‰ for barns, compared to -43 to -39‰ for gas leaks), and ethane:methane ratios (<0.001 for barns, compared to >0.05 for gas leaks). Under a well-mixed daytime atmospheric boundary layer these sources are generally detectable as above baseline elevations up to 100 m downwind for gas leaks and up to 500 m downwind for populated cow barns. It is considered that careful analysis of these proxies for unconventional production gas, if and when available, will allow any fugitive emissions from operations to be distinguished from surrounding sources.