We exploit satellite datasets of spatio-temporal distributions of atmospheric composition for the rainforest and savanna region on the southern boundary of the Amazon to understand how its emissions of biogenic volatile organic compounds (BVOCs) and local pyrogenic emissions impact the atmosphere. In particular, we explore the relationship between land cover change, considering vegetation type (e.g. broadleaf forest, savanna, grassland) and Leaf Area Index (LAI), and burned area and atmospheric composition. In this study, we investigate these relationships over the southern Amazon for the period 2001-2019, focussing on seasonal and spatial patterns. We utilise data for five chemical species: total column isoprene (TCC5H8), total column methanol (TCCH3OH), tropospheric column nitrogen dioxide (TCNO2), total column carbon monoxide (TCCO) and total column formaldehyde (TCHCHO), as well as aerosol optical depth (AOD).We find burned area approximately delineates the areas of change in dominant vegetation cover type over time. Robust relationships were found between TCC5H8 and forest cover, and TCNO­2­ and burned area. Here, we find that TCC5H8 linearly increases by 1 × 1014 molecules cm-2 with an increase of 1 percentage point in broadleaf forest cover. This is equivalent to densely forested regions having column isoprene ­­values four times greater than those with no­ forest cover. There is a strong power law relationship between TCNO2 and burned area. Overall, there is a larger increase in TCNO2 in regions of lower, though still substantial, biomass burning (i.e. potentially new regions of burning/deforestation). These relationships highlight the relatively short lifetimes of the two species such that their spatial extent is largely confined to their emission source regions.Conversely, TCHCHO, TCCO and AOD reach maximum values for high broadleaf forest coverage and high burned areas, suggesting a mixed influence of both biogenic and pyrogenic sources, likely due to the longer lifetimes of these species and aerosols, allowing them to mix and be transported further from their emissions sources. Broadleaf forest cover and burned area do not appear to have a substantial impact on methanol, which is elevated over a region of savanna and grasslands in the northeast of the study region.The results highlight the potential for air quality impacts from the biogenic and pyrogenic emissions and their interactions that differ seasonally and regionally, and illustrates how land cover and land use change exerts a strong control on isoprene and nitrogen dioxide concentrations over remote regions.

The chemical transport models face challenges in simulating the concentrations of surface ozone accurately in all conditions when meteorology and chemical environment are changing. The capability of capturing the principle physical and chemical processes is clearly limited. We propose a unified framework based on deep learning to provide a more accurate prediction of surface ozone. The model is tailored to individual observation sites in China, forming a specific graph that would reflect the interaction between spatial and temporal connection in physics and chemistry. This mitigates the uncertainty associated with model resolution and emissions. We show that the model achieves the State-of-the-Art (SOTA) performance in simulating MDA8 ozone among current process-based and other deep learning models. The model structure is also flexible to be applied to other places where observations are available such as Europe and North America. This work underscores great benefits that can be gained through implementing more measurement sites to enhance the density of the model graph.

Biogenic volatile organic compounds (BVOCs), such as isoprene, impact aerosols, ozone and methane, adding uncertainty to assessments of the climate impacts of land cover change. Recent United Kingdom Earth System Model (UKESM) developments allow us to study how various processes impact biosphere–atmosphere interactions and their implications for atmospheric chemistry, while advances in remote sensing provide new opportunities for assessing biases in isoprene alongside formaldehyde and aerosol optical depth (AOD). The standard setup of UKESM1.1 underestimates the regional formaldehyde column by up to 80 %, despite positive isoprene biases of over 500 %. Seasonal average AOD values are underestimated by over 60 % in parts of the Northern Hemisphere but overestimated (> 180 %) in the Congo. The effects of several processes are studied to understand their impacts on satellite–model biases. Of these, changing from the default to a more detailed chemistry mechanism has the greatest impact on the simulated trace gases. Here, the isoprene lifetime decreases by 50 %, the formaldehyde column increases by > 20 %, whilst reductions in upper-tropospheric oxidant mixing ratios decrease sulfate nucleation (−32 %). Organically mediated boundary layer nucleation and contributions to aerosol mass from isoprene oxidation decrease AOD values in the Northern Hemisphere, while revised BVOC emission factors and land cover representation affect the emissions of BVOCs and dust. The combination of processes substantially affects regional model–satellite biases, typically decreasing isoprene and AOD and increasing formaldehyde. We find significant differences in the aerosol direct radiative effects (+0.17 W m−2), highlighting that these processes may have substantial ramifications for impact assessments of land use change.

Humans spend a large proportion of their time at home, where exposure to poor indoor air quality has detrimental - and often inequitably distributed - impacts on health and wellbeing. Unprecedented changes to residential indoor environments are expected in the coming decades, especially in order to meet net zero energy and greenhouse gas emissions targets. However, it is unclear how these changes will affect indoor air quality, and to what extent they will differentially impact different social groups. In this paper, we pose and address ten questions concerning the future of residential indoor air quality and its environmental justice implications. We pay attention to environmental justice in relation to indoor air quality, including distributive, procedural, recognition, capabilities, and epistemic dimensions. The ten questions specifically address: social gradients in health and exposure, and how changes in climate, policies, behaviours, technologies, populations, and demographics might affect residential indoor air quality and environmental justice. We also highlight the role that transdisciplinary research can play in improving residential indoor air quality in a more environmentally just way.

The extent to which populations will successfully adapt to continued warming temperatures will be a crucial factor in determining future health burdens. Previous health impact assessments of future temperature-related mortality burdens mostly disregard adaptation or make simplistic assumptions. We apply a novel evidence-based approach to model adaptation that takes into account the fact that adaptation potential is likely to vary at different temperatures. Temporal changes in age-specific mortality risk associated with low and high temperatures were characterised for Scotland between 1974 and 2018 using temperature-specific RR ratios to reflect past changes in adaptive capacity. Three scenarios of future adaption were constructed consistent with the SSPs. These adaptation projections were combined with climate and population projections to estimate the mortality burdens attributable to high (above the 90th percentile of the historical temperature distribution) and low (below the 10th percentile) temperatures up to 2080 under five RCP-SSP scenarios. A decomposition analysis was conducted to attribute the change in the mortality burden into adaptation, climate and population. In 1980-2000, the heat burden (21 deaths/year) was smaller than the colder burden (312 deaths/year). In the 2060-2080 period, the heat burden was projected to be the highest under RCP8.5-SSP5 (1285 deaths/year), and the cold burden was the highest under RCP4.5-SSP4 (320 deaths/year). The net burden was lowest under RCP2.6-SSP1 and highest under RCP8.5-SSP5. Improvements in adaptation was the largest factor reducing the cold burden under RCP2.6-SSP1 whilst temperature increase was the biggest factor contributing to the high heat burdens under RCP8.5-SSP5. Ambient heat will become a more important health determinant than cold in Scotland under all climate change and socio-economic scenarios. Adaptive capacity will not fully counter projected increases in heat deaths, underscoring the need for more ambitious climate mitigation measures for Scotland and elsewhere.

Like other environmental concerns that affect human health, indoor air quality (IAQ) needs to be understood not only scientifically but also by the citizens who are affected by it. Six online focus groups sessions were conducted with people living in London who could be considered particularly vulnerable to air pollution exposure, namely older people, parents with young children and people with underlying health conditions. Each session involved an iterative process of group discussion, information provision and reflection/further discussion. A deductive thematic analysis guided by an environmental health literacy (EHL) lens was used to explore participants’ awareness of, and lived experience with, IAQ. The findings contribute to a better understanding of the EHL of vulnerable people, whilst also suggesting that learning more about IAQ (given the participants’ low level of prior knowledge) can be effective in increasing people’s willingness to make behavioural changes in indoor contexts. Several practical measures could be taken by various stakeholders to reduce residents’ exposure, especially those who have limited agency due to vulnerability (e.g. reduced mobility) or other personal circumstances (e.g. residing in a rental property). Policy relevance The findings from this study contribute to a better understanding of the EHL of vulnerable London residents, whilst also suggesting that information provision in the format of iterative discussion and group learning is effective at increasing people’s willingness and ability to make behavioural changes in indoor contexts. They also underscore the importance of providing occupants with information that not only encourages the use of ventilation systems but also includes awareness-raising materials concerning the sources and negative health impacts of poor IAQ. Furthermore, filtration technology should be made affordable which could require subsidies as part of national or regional air pollution policy; or new legislation to require air filtration systems in all new build or rented properties. Meanwhile, action from other stakeholders, notably landlords and housing authorities/associations, is also required to ensure good IAQ in rental properties, whilst tailored building design is needed to support people with reduced mobility.

Non-technical skills (NTS) are crucial in healthcare, encompassing cognitive and social skills that support technical ability. Traditional NTS training is evolving with the emergence of artificial intelligence (AI) models that can intelligently converse with their users, known as large language models (LLMs). This study investigated the capabilities and limitations of a popular model named generative pre-trained transformer 4 (GPT-4) in NTS training, comparing its performance to that of human evaluators. Urology trainees identified NTS events in simulated scenarios and discussed them in blinded feedback sessions with AI and human consultants. Experts assessed the blinded interaction data, providing quantitative ratings and qualitative evaluations using annotated transcripts. Wilcoxon signed-rank tests compared pre- and post-intervention ratings, whilst Mann–Whitney U tests compared post-intervention ratings between AI and human feedback. Thematic analysis identified strengths, limitations, and differences between AI and human feedback approaches. The AI model demonstrated significant strengths in reinforcing knowledge gathering (p = 0.04), providing accurate and evidence-based feedback (p = 0.013), conveying empathy (p = 0.021), and tailoring explanations to complexity (p = 0.002). However, human feedback excelled in language terminology (p = 0.003), complexity (p = 0.020), and fact-based feedback (p = 0.025). The study highlights the potential for AI to augment assessment of NTS training in healthcare. A blended approach utilising AI and human expertise may boost training efficacy.

Land surface changes can have substantial impacts on biosphere-atmosphere interactions. In South America, rainforests abundantly emit biogenic volatile organic compounds (BVOCs), which, when coupled with pyrogenic emissions from deforestation fires, can have substantial impacts on regional air quality. We use novel and long-term satellite records of five trace gases, namely isoprene (C5H8), formaldehyde (HCHO), methanol (CH3OH), carbon monoxide (CO), and nitrogen dioxide (NO2), in addition to aerosol optical depth (AOD), vegetation (land cover and leaf area index), and burned area. We characterise the impacts of biogenic and pyrogenic emissions on atmospheric composition for the period 2001 to 2019 in the southern Amazon, a region of substantial deforestation. The seasonal cycle for all of the atmospheric constituents peaks in the dry season (August-October), and the year-to-year variability in CO, HCHO, NO2, and AOD is strongly linked to the burned area. We find a robust relationship between the broadleaf forest cover and total column C5H8 (R2 = 0.59), while the burned area exhibits an approximate fifth root power law relationship with tropospheric column NO2 (R2 = 0.32) in the dry season. Vegetation and burned area together show a relationship with HCHO (R2 = 0.23). Wet-season AOD and CO follow the forest cover distribution. The land surface variables are very weakly correlated with CH3OH, suggesting that other factors drive its spatial distribution. Overall, we provide a detailed observational quantification of biospheric process influences on southern Amazon regional atmospheric composition, which in future studies can be used to help constrain the underpinning processes in Earth system models.

Objectives: To assess the feasibility of performance enhancement coaching (PEC) for newly appointed Urology registrars (ST3s), specifically: whether the concept appealed, and which areas beyond technical skills acquisition were felt to be most relevant or useful. Subjects and methods: All delegates on the Urology Bootcamp 2023 were invited to take part in an online survey before and after a 2-hour PEC workshop, collecting: basic demographic data, performance challenges, and the important aspects to include in, and consider with, a coaching programme. The workshop was delivered by a surgeon with a professional coaching qualification, to groups of four delegates at a time over 4 days. Ten pre-defined areas were offered during the session. Results: On a scale of 1 (poor) to 10 (excellent), the 62 participants' overall health was reported as a median of 8/10 (physical) and 7/10 (mental). Anxiety during performance was the most common concern (63%) and was accompanied by a tremor in 55%. The next most popular concerns, with 19% of responses each, were: sleep, insufficient operative skill or expertise, and worry about relationships with trainers. The commonest topics discussed were 'the inner critic' (100%), 'autonomic modulation' (69%), 'not working, well' (13%) and 'optimising study' (6%). Seventy-seven per cent were unaware of PEC for practising surgeons. All respondents felt that they would benefit from PEC to some extent (80% >= 8/10 where 10/10 was 'very useful'), ideally at the ST3 level. Sixty-two percent of respondents said there should be a fee for trainees, whereas 38% thought it should be free and paid for by their training authorities. Conclusion: The concept of PEC is acceptable to ST3 Urology trainees, with particular interest in techniques to mitigate negative self-talk and autonomic modulation techniques. Existing barriers to coaching for the surgical community would need to be addressed in designing an acceptable coaching programme.

Net-zero emission policies principally target climate change but may have a profound influence on surface ozone pollution. To investigate this, we use a chemistry-climate model to simulate surface ozone changes in China under a net-zero pathway and examine the different drivers that govern these changes. We find large monthly mean surface ozone decreases of up to 16 ppb in summer and small ozone decreases of 1 ppb in winter. Local emissions are shown to have the largest influence on future ozone changes, outweighing the effects of changes in emissions outside China, changes in global methane concentrations, and a warmer climate. Impacts of local and external emissions show strong seasonality, with the largest contributions to surface ozone in summer, while changes in global methane concentrations have a more uniform effect throughout the year. We find that while a warmer climate has a minor impact on ozone change compared to the net-zero scenario, it will alter the spatial patterns of ozone in China, leading to ozone increases in the south and ozone decreases in the north. We also apply a deep learning model to correct biases in our ozone simulations and to provide a more robust assessment of ozone changes. We find that emission controls may lead to a surface ozone decrease of 5 ppb in summer. The number of days with high-ozone episodes with daily mean ozone greater than 50 ppb will be reduced by 65 % on average. This is smaller than that simulated with the chemistry-climate model, reflecting overestimated ozone formation under present-day conditions. Nevertheless, this assessment clearly shows that the strict emission policies needed to reach net zero will have a major benefit in reducing surface ozone pollution and the occurrence of high-ozone episodes, particularly in high-emission regions in China.

This dataset contains the smoothed and detrended time series of methane from the TOMCAT regional tagged tracer simulations between 1995-2020 at 22 NOAA surface observation sites. Each file contains the Site Code and the latitude and longitude of of each observation site. The regional file contains the region code of each regional tagged tracer. More information on the TOMCAT simulation and the Site Codes and Region Codes can be found at: https://doi.org/10.5194/egusphere-2023-132, 2023

We use the United Kingdom Earth System Model, UKESM1, to investigate the influence of the winter large-scale circulation on daily concentrations of PM2.5 (particulate matter with an aerodynamic diameter of 2.5 µm or less) and their sensitivity to emissions over major populated regions of China over the period 1999–2019. We focus on the Yangtze River delta (YRD), where weak flow of cold, dry air from the north and weak inflow of maritime air are particularly conducive to air pollution. These provide favourable conditions for the accumulation of local pollution but limit the transport of air pollutants into the region from the north. Based on the dominant large-scale circulation, we construct a new index using the north–south pressure gradient and apply it to characterise PM2.5 concentrations over the region. We show that this index can effectively distinguish different levels of pollution over YRD and explain changes in PM2.5 sensitivity to emissions from local and surrounding regions. We then project future changes in PM2.5 concentrations using this index and find an increase in PM2.5 concentrations over the region due to climate change that is likely to partially offset the effect of emission control measures in the near-term future. To benefit from future emission reductions, more stringent emission controls are required to offset the effects of climate change.

OBJECTIVE:This study aimed to develop and evaluate a virtual reality (VR)-based nontechnical skills (NTS) training application for urology trainees and assess its effectiveness in improving their skills and confidence. DESIGN:A mixed-methods study was conducted to develop and evaluate a VR-based NTS training application for 32 urology trainees. The development process involved collaboration with 5 urology experts, 2 medical education specialists, and a human factors researcher. The study evaluated the application's usability, acceptability, and efficacy through 3 phases: scenario development with expert feedback integration, storyboarding and creation processes with facilitators and urology trainees, and a final evaluation by trainees. SETTING:The data were collected during a 4-day urology boot camp in October 2022. PARTICIPANTS:Thirty-two urology trainees participated in the study and completed 2 VR scenarios designed to enhance their NTS skills RESULTS: The System Usability Scale (SUS) showed a moderate usability score of 66. The Training Evaluation Inventory (TEI) and additional feedback demonstrated positive effects on trainees' learning and confidence in their NTS abilities. Most participants found the application easy to use, and effective and they expressed interest in using similar VR applications for other aspects of surgical training. CONCLUSIONS:VR-based NTS training applications show potential for enhancing urology trainees' nontechnical skills. The integration of expert feedback and immersive technology offers a promising, accessible, and cost-effective solution to the challenges of delivering NTS training. Future research should explore the long-term impact of VR-based NTS training on trainees' performance and patient outcomes and consider incorporating advanced AI technologies for personalized and dynamic learning experiences.