The challenges, uncertainties and opportunities of bioaerosol dispersion modelling from open composting facilities

Bioaerosols are ubiquitous organic particles that comprise viruses, bacteria and coarser fractions of organic matter. Known to adversely affect human health, the impact of bioaerosols on a population often manifests as outbreaks of illnesses such as Legionnaires Disease and Q fever, although the concentrations and environmental conditions in which these impacts occur are not well understood. Bioaerosol concentrations vary from source to source, but specific human activities such as water treatment, intensive agriculture and composting facilitate the generation of bioaerosol concentrations many times higher than natural background levels. Bioaerosols are not considered ‘traditional’ pollutants in the same way as PM10, PM2.5, and gases such as NO2, and consequently dispersion models do not include a bespoke method for their assessment. As identified in previous studies, priority areas for improving the robustness of these dispersion models include: 1) the development of bespoke monitoring studies designed to generate accurate modelling input data; 2) the publication of a robust emissions inventory; 3) a code of practice to provide guidelines for consistent bioaerosol modelling practices; and 4) a greater understanding of background bioaerosol emissions. The aim of this research project, funded by the Natural Environmental Research Council (NERC), is to address these key areas through a better understanding of the generation, concentration and potential dispersion of bioaerosols from intensive agricultural and biowaste facilities, using case studies developed at specific locations within the UK. The objective is to further refine existing bioaerosol monitoring and modelling guidelines to provide a more robust framework for regulating authorities and site operators. This contribution outlines the gaps that hinder robust dispersion modelling, and describes the on-site bioaerosol data collection methods used in the study, explaining how they might be used to close these gaps. Examples of bioaerosol dispersion modelled using ADMS 5 are presented and discussed

Towards improved bioaerosol model validation and verification

Bioaerosols, comprised of bacteria, fungi and viruses are ubiquitous in ambient air. Known to adversely affect human health, the impact of bioaerosols on a population often manifests as outbreaks of illnesses such as Legionnaires Disease and Q fever, although the concentrations and environmental conditions in which these impacts occur are not well understood. Bioaerosol concentrations vary from source to source, but specific industrialised human activities such as water treatment, intensive agriculture and open windrow composting facilitate the generation of bioaerosol concentrations many times higher than natural background levels. Bioaerosol sampling is currently undertaken according to the requirements of the Environment Agency’s regulatory framework, in which the collection of bioaerosols and not its long-term measurement is of most importance. As a consequence, sampling devices are often moved around site according to changing wind direction and sampling intervals are invariably short-term. The dispersion modelling of bioaerosols from composting facilities typically relies on proxy pollutant parameters. In addition, the use of short term emission data gathering strategies in which monitors are moved frequently with wind direction, do not provide a robust reliable and repeatable dataset by which to validate any modelling or to verify its performance. New sampling methods such as the Spectral Intensity Bioaerosol Sensor (SIBS) provide an opportunity to address several gaps in bioaerosol model validation and verification. In the context of model validation, this paper sets out the current weaknesses in bioaerosol monitoring from the perspective of robust modelling requirements

A Controlled Study on the Characterisation of Bioaerosols Emissions from Compost

Bioaerosol emissions arising from biowaste treatment are an issue of public concern. To better characterise the bioaerosols, and to assess a range of measurement methods, we aerosolised green waste compost under controlled conditions. Viable and non-viable Andersen samplers, cyclone samplers and a real time bioaerosol detection system (Spectral Intensity Bioaerosol Sensor (SIBS)) were deployed simultaneously. The number-weighted fraction of fluorescent particles was in the range 22–26% of all particles for low and high emission scenarios. Overall fluorescence spectral profiles seen by the SIBS exhibited several peaks across the 16 wavelength bands from 298 to 735 nm. The size-fractionated endotoxin profile showed most endotoxin resided in the 2.1–9 μm aerodynamic diameter fraction, though up to 27% was found in a finer size fraction. A range of microorganisms were detected through culture, Matrix Assisted Laser Desorption and Ionisation Time of Flight Mass Spectrometry (MALDI-TOF) and quantitative polymerase chain reaction (qPCR), including Legionella pneumophila serogroup 1. These findings contribute to our knowledge of the physico-chemical and biological characteristics of bioaerosols from composting sites, as well as informing future monitoring approaches and data interpretation for bioaerosol measurement

Sources of Airborne Endotoxins in Ambient Air and Exposure of Nearby Communities—A Review

Endotoxin is a bioaerosol component that is known to cause respiratory effects in exposed populations. To date, most research focused on occupational exposure, whilst much less is known about the impact of emissions from industrial operations on downwind endotoxin concentrations. A review of the literature was undertaken, identifying studies that reported endotoxin concentrations in both ambient environments and around sources with high endotoxin emissions. Ambient endotoxin concentrations in both rural and urban areas are generally below 10 endotoxin units (EU) m−3; however, around significant sources such as compost facilities, farms, and wastewater treatment plants, endotoxin concentrations regularly exceeded 100 EU m−3. However, this is affected by a range of factors including sampling approach, equipment, and duration. Reported downwind measurements of endotoxin demonstrate that endotoxin concentrations can remain above upwind concentrations. The evaluation of reported data is complicated due to a wide range of different parameters including sampling approaches, temperature, and site activity, demonstrating the need for a standardised methodology and improved guidance. Thorough characterisation of ambient endotoxin levels and modelling of endotoxin from pollution sources is needed to help inform future policy and support a robust health-based risk assessment process

Adaptive sampling by citizen scientists improves species distribution model performance: a simulation study

1. Volunteer recorders generate large amounts of biodiversity data through citizen science which is used in conservation planning and policy decision-making. Unstructured sampling, where the volunteer can record what they want, where they want, leads to spatial unevenness in these data. While there are many statistical techniques to account for the resulting biases, it may be possible to improve datasets by directing a subset of recorders to sample in the most informative locations, known as adaptive sampling. We investigated the potential for adaptive sampling to improve the performance of species distribution models built on citizen science data using simulated ecological communities. 2. We simulated ecological assemblages across Great Britain based on current butterfly data and modelled the distributions of each species. We then simulated the sampling of new data based on five adaptive sampling methods (one empirical method based simply on gap-filling, and four model-based methods using various measures from the model outputs) and one non-adaptive method (a method in which recording continued in the current pattern), and re-ran the species distribution models. In these, we also varied the rate of recording effort that was distributed according to adaptive sampling. The model predictions using the original and adaptively sampled data were compared to true species distributions to evaluate the performance of each method. 3. We found that all adaptive sampling approaches improved model performance, with greatest improvement for model-based approaches compared to the empirical sampling method (i.e. simple gap-filling). All four model-based adaptive sampling approaches provided similar benefits for model outputs. Improvements in model performance were greatest when the amount of adaptive sampling changed from no uptake to 1% uptake, indicating that only a small amount of change in recorder behaviour is needed to improve model performance. 4. Directing volunteer recorders to places where records are most needed, based on information from model outputs, can improve species distribution models built on citizen science data, even with minimal uptake of suggested locations. Our results therefore suggest that adaptive sampling by recorders could be beneficial for real-world citizen science datasets

Scoping studies to establish the capability and utility of a real-time bioaerosol sensor to characterise emissions from environmental sources

A novel dual excitation wavelength based bioaerosol sensor with multiple fluorescence bands called Spectral Intensity Bioaerosol Sensor (SIBS) has been assessed across five contrasting outdoor environments. The mean concentrations of total and fluorescent particles across the sites were highly variable being the highest at the agricultural farm (2.6 cm−3 and 0.48 cm−3, respectively) and the composting site (2.32 cm−3 and 0.46 cm−3, respectively) and the lowest at the dairy farm (1.03 cm−3 and 0.24 cm−3, respectively) and the sewage treatment works (1.03 cm−3 and 0.25 cm−3, respectively). In contrast, the number-weighted fluorescent fraction was lowest at the agricultural site (0.18) in comparison to the other sites indicating high variability in nature and magnitude of emissions from environmental sources. The fluorescence emissions data demonstrated that the spectra at different sites were multimodal with intensity differences largely at wavelengths located in secondary emission peaks for λex 280 and λex 370. This finding suggests differences in the molecular composition of emissions at these sites which can help to identify distinct fluorescence signature of different environmental sources. Overall this study demonstrated that SIBS provides additional spectral information compared to existing instruments and capability to resolve spectrally integrated signals from relevant biological fluorophores could improve selectivity and thus enhance discrimination and classification strategies for real-time characterisation of bioaerosols from environmental sources. However, detailed lab-based measurements in conjunction with real-world studies and improved numerical methods are required to optimise and validate these highly resolved spectral signatures with respect to the diverse atmospherically relevant biological fluorophores

Prototype digital twin: recreation and biodiversity cultural ecosystem services

•Digital twin approaches have the potential to revolutionise usage, planning and management of cultural ecosystem services i.e. the non-material benefits people obtain from ecosystems, including recreation, tourism, intellectual development, spiritual enrichment, reflection and aesthetic experiences. •Here, we outline our blueprint for a prototype digital twin (pDT) for cultural ecosystem services. The pDT consists of two modelling components; a recreation potential model to quantify the cultural ecosystem services of the physical landscape and species distribution models to quantify the biodiversity component. •It is envisaged that the digital twin will be used primarily by two user types: 1. those who wanted to enjoy the area and potentially contribute to citizen science programmes and 2. people who want to inform or make evidence-based management decisions (land managers, policy-makers, researchers)

USP27X variants underlying X-linked intellectual disability disrupt protein function via distinct mechanisms

Neurodevelopmental disorders with intellectual disability (ND/ID) are a heterogeneous group of diseases driving lifelong deficits in cognition and behavior with no definitive cure. X-linked intellectual disability disorder 105 (XLID105, #300984; OMIM) is a ND/ID driven by hemizygous variants in the USP27X gene encoding a protein deubiquitylase with a role in cell proliferation and neural development. Currently, only four genetically diagnosed individuals from two unrelated families have been described with limited clinical data. Furthermore, the mechanisms underlying the disorder are unknown. Here, we report 10 new XLID105 individuals from nine families and determine the impact of gene variants on USP27X protein function. Using a combination of clinical genetics, bioinformatics, biochemical, and cell biology approaches, we determined that XLID105 variants alter USP27X protein biology via distinct mechanisms including changes in developmentally relevant protein-protein interactions and deubiquitylating activity. Our data better define the phenotypic spectrum of XLID105 and suggest that XLID105 is driven by USP27X functional disruption. Understanding the pathogenic mechanisms of XLID105 variants will provide molecular insight into USP27X biology and may create the potential for therapy development.</p

A standard protocol to report discrete stage-structured demographic information

Stage-based demographic methods, such as matrix population models (MPMs), are powerful tools used to address a broad range of fundamental questions in ecology, evolutionary biology and conservation science. Accordingly, MPMs now exist for over 3000 species worldwide. These data are being digitised as an ongoing process and periodically released into two large open-access online repositories: the COMPADRE Plant Matrix Database and the COMADRE Animal Matrix Database. During the last decade, data archiving and curation of COMPADRE and COMADRE, and subsequent comparative research, have revealed pronounced variation in how MPMs are parameterized and reported. Here, we summarise current issues related to the parameterisation and reporting of MPMs that arise most frequently and outline how they affect MPM construction, analysis, and interpretation. To quantify variation in how MPMs are reported, we present results from a survey identifying key aspects of MPMs that are frequently unreported in manuscripts. We then screen COMPADRE and COMADRE to quantify how often key pieces of information are omitted from manuscripts using MPMs. Over 80% of surveyed researchers (n = 60) state a clear benefit to adopting more standardised methodologies for reporting MPMs. Furthermore, over 85% of the 300 MPMs assessed from COMPADRE and COMADRE omitted one or more elements that are key to their accurate interpretation. Based on these insights, we identify fundamental issues that can arise from MPM construction and communication and provide suggestions to improve clarity, reproducibility and future research utilising MPMs and their required metadata. To fortify reproducibility and empower researchers to take full advantage of their demographic data, we introduce a standardised protocol to present MPMs in publications. This standard is linked to www.compa dre-db.org, so that authors wishing to archive their MPMs can do so prior to submission of publications, following examples from other open-access repositories such as DRYAD, Figshare and Zenodo. Combining and standardising MPMs parameterized from populations around the globe and across the tree of life opens up powerful research opportunities in evolutionary biology, ecology and conservation research. However, this potential can only be fully realised by adopting standardised methods to ensure reproducibility

Disruption of RFX family transcription factors causes autism, attention-deficit/hyperactivity disorder, intellectual disability, and dysregulated behavior

Purpose We describe a novel neurobehavioral phenotype of autism spectrum disorder (ASD), intellectual disability, and/or attention-deficit/hyperactivity disorder (ADHD) associated with de novo or inherited deleterious variants in members of the RFX family of genes. RFX genes are evolutionarily conserved transcription factors that act as master regulators of central nervous system development and ciliogenesis. Methods We assembled a cohort of 38 individuals (from 33 unrelated families) with de novo variants in RFX3, RFX4, and RFX7. We describe their common clinical phenotypes and present bioinformatic analyses of expression patterns and downstream targets of these genes as they relate to other neurodevelopmental risk genes. Results These individuals share neurobehavioral features including ASD, intellectual disability, and/or ADHD; other frequent features include hypersensitivity to sensory stimuli and sleep problems. RFX3, RFX4, and RFX7 are strongly expressed in developing and adult human brain, and X-box binding motifs as well as RFX ChIP-seq peaks are enriched in the cis-regulatory regions of known ASD risk genes. Conclusion These results establish a likely role of deleterious variation in RFX3, RFX4, and RFX7 in cases of monogenic intellectual disability, ADHD and ASD, and position these genes as potentially critical transcriptional regulators of neurobiological pathways associated with neurodevelopmental disease pathogenesis