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Atmospheric dispersion models use mathematical equations to calculate pollution concentrations in the receiving environment; however, there can be variations in the accuracy of a pollutant's calculated concentration among different models due to the nature of the modeling environment and limitations on computational complexities. In this study two types of popular Gaussian pollution dispersion models, AERMOD and ADMS, were investigated to analyze their behavior under specific conditions. Initially, both models were simulated for point and line sources of emission. Subsequently, their output results were compared with passive samplers placed for varying periods (2 weeks, 2 months, and 3 months) at modeled receptor locations. The results indicated that both models underestimate the passive sampler results. However, AERMOD's underestimation was found to be more than ADMS's, resulting in ADMS performing slightly better. Additionally, to study the effectiveness of input parameters such as surface characteristics and solar insolation, a relative sensitivity analysis was conducted under two different atmospheric conditions: convective mixing dominance (CMD) and mechanical mixing dominance (MMD). It was found that AERMOD was relatively more sensitive to surface roughness, especially in MMD conditions than to albedo, surface moisture, and solar insolation. Both models were somewhat insensitive to albedo and Bowen, and solar insolation; however, in CMD conditions, AERMOD was more sensitive to these sunlight-related parameters. Also, both models were more sensitive to surface roughness than other input parameters. The results emphasize the importance of selecting precise parameters, particularly surface roughness, with more care for AERMOD than for the ADMS model. [ABSTRACT FROM AUTHOR]

The implementation of advanced distribution management systems (ADMS) in today's distribution networks (DNs) is critical for efficient operation. However, ADMS deployment poses significant challenges, particularly in gathering the extensive and diverse data required to model DNs. This paper presents a generalized, systematic, and algorithm-driven procedure for optimizing the missing data-gathering process during ADMS deployment. The procedure identifies the required DN model data by layers, considers distribution power utility (DPU) data sources, identifies missing data, and evaluates methods and the missing data-gathering ways, considering cost, duration, and specific constraints for data gathering. The developed approach provides DPUs with a clear, structured, and proactive approach to data gathering, significantly reducing complexity and enhancing efficiency. The practical application of this procedure is demonstrated using a real-world unbalanced DN example from a North American DPU, showcasing its potential to streamline ADMS deployment and deliver tangible operational benefits. [ABSTRACT FROM AUTHOR]

Local urban air quality models must be able to account for complex road geometries if they are to predict near-road concentrations accurately. This includes flyovers, which are often used to improve flow at busy junctions or to take traffic through urban greenspace. We present a new methodology for modelling elevated roads in which the plume is only allowed to grow downwards once it has left the downwind road edge, thus accounting for road shielding. This new approach has been implemented in the operational dispersion model ADMS-Urban. The updated model is validated against monitoring data from two sites located next to busy flyovers—one in London, UK, the other in Antwerp, Belgium. It is shown to perform very well compared with simulations in which the flyovers are modelled at ground level, and slightly better than simulations when the traditional approach to modelling elevated roads (no road shielding) is used. Near-ground concentrations are significantly reduced with road elevation due to (i) increased vertical source-receptor distance, (ii) greater dispersion from the source where wind speeds are higher, and (iii) reduced impact of ground-level plume reflections. Pollutant trapping in street canyons is also minimised in cases where a flyover is elevated above the local building level. A sensitivity analysis is also presented in which multiple road elevations are tested; these results can be used by urban planners when designing new flyovers or by modellers in deciding whether it is important to account for road elevation near sensitive receptors. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are the main precursors of pollution from ground ozone (O3) and PM2.5, which cause the deterioration of urban air quality. The emissions of VOCs from industrialized areas are significant and their characteristics are complex, which nowadays contribute significantly to the challenges of investigating the emission inventory. Taking a typical industrialized area in Tianjin as a case study, the anthropogenic VOCs emission inventory for 2020 was established in this study by using the activity data from a large-scale survey and the latest emission factors. The impact of VOCs on the environment was analyzed from the perspective of the combined control of PM2.5 and O3. The results showed that the total emission of VOCs in 2020 was about 1.68 Gg, mainly from industrial processes and mobile sources, which accounted for 38.4% and 36.5% of the total emissions, respectively. The top 10 emitted VOCs were toluene, acetone, ethylbenzene, m/p-xylene, i-pentane, n-hexane, formaldehyde, benzene, ethyl acetate and ethylene. The dominant species of O3 formation potential (OFP) were almost all aromatic hydrocarbons and alkenes, with m/p-xylene contributing the most to the OFP emissions (8.90%). The top 10 secondary organic aerosols formation potential (SOAP) emission species were aromatic hydrocarbons and long-chain alkanes, and the largest emission came from toluene (39.9%). An analysis of an ADMS diffusion model showed that VOCs emitted from traffic-heavy main roads and industrialized central areas had the greatest impact on the air quality in the surrounding areas. The VOCs concentration was higher in winter due to unfavorable meteorological conditions. Our research updated the VOC inventory of industrialized areas and evaluated VOCs species reactivity and their impact on ambient air quality. [ABSTRACT FROM AUTHOR]

Gaussian dispersion modeling has implemented significant developments in the description of the planetary boundary layer characteristics along with research work, particularly on plume buoyancy and momentum, as well as airflow in complex terrain. Advanced Gaussian models show a remarkable performance in validation studies, providing sophisticated algorithms to take into account building downwash, deposition, chemical reactions, and so forth. This work aims to essentially validate the SYMOS model, currently referenced in the Czech Republic, and comparatively evaluate further modeling approaches applied to emissions from a stationary source in the suburban background of Prague. Sulfur dioxide was targeted as one of the criteria gaseous pollutants, relatively representing the sulfur content in the solid mineral fuel commonly used in local industrial facilities. Meteorological preprocessing, complex terrain, and plume rise were analyzed in-depth to determine the effect of the different algorithms in the estimation of ground-level concentrations. The obtained contour plots showed moderate similarities between SYMOS and the advanced models ADMS and AERMOD, but largely overestimated the concentrations when plume rise was considered. The descriptive statistical analysis revealed ADMS tended to predict higher hourly peak concentrations, while AERMOD estimated higher annual averages, attributed to differences in meteorological conditions and dispersion algorithms. Moreover, surface roughness was identified as a critical factor in the calculation of concentrations in complex terrain. Extensive assessment and validation of SYMOS algorithms are essential to investigate a different approach to characterize atmospheric stability and thermal lift. [ABSTRACT FROM AUTHOR]

The Air quality modeling systems were imported from SCRAM of US Environmental Protection Agency (EPA). The suggested modeling system included SCREEN3, AERMOD, ADMS and CALPUFF were provided by EPA in the form of FORTRAN source codes. However, the programs were written as console applications, and they are inconvenient to the end users. It is necessary to develop a software tool which runs in windows platform. SCREEN-SPR is a software package as similar to the USEPA SCREEN3Model was developed in C# language and run on the VisualBasic platform which can be used as a tool for assessing the air quality impact of stationary source with preliminary estimation scheme (screening scheme). Also, theSCREEN SPR model is used to calculate the maximum Ground Level Concentration (GLC)of pollutant which prevail at the shortest downwind locations from the source under the combinations of various possible wind speed andits corresponding atmosphericsabilityclassesfor thegiven inputs such as source details and plant emission characteristics. [ABSTRACT FROM AUTHOR]

Depression is an eminently treatable disorder that responds to psychotherapy or medications; the efficacy of each has been established in hundreds of controlled trials. Nonetheless, the prevalence of depression has increased in recent years despite the existence of efficacious treatments-a phenomenon known as the treatment-prevalence paradox. We consider several possible explanations for this paradox, which range from a misunderstanding of the very nature of depression, inflated efficacy of the established treatments, and a lack of access to efficacious delivery of treatments. We find support for each of these possible explanations but especially the notion that large segments of the population lack access to efficacious treatments that are implemented as intended. We conclude by describing the potential of using lay therapists and digital technologies to overcome this lack of access and to reach historically underserved populations and simultaneously guarantee the quality of the interventions delivered.

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• Development of an integrated modelling-measurement system to estimate harbour pollution. • The system operates near-real-time with harbour data and a low-cost sensor network. • Impact of shipping traffic and harbor-related activities is separately estimated. • The impact of harbour on NO X is that of major concern for air quality in this area. • Shipping gives the highest contribution to SO 2 and the lowest to CO compared to harbour logistics. Several studies focused on harbour impact on air quality of port-cities showing that maritime emissions could be comparable to traffic emissions of a medium-size town having relevant impact on air quality nearby the harbours. In order to plan efficient mitigation strategies, environmental and port authorities have an increasing need of reliable tools for investigating the impact of ships traffic and harbour logistics on atmospheric pollutants. In this work a system based on the integration of measurements collected using a network of low-cost on-line sensors with local scale dispersion modelling was developed. It was implemented, as a pilot action, in the information and management software of the Bari harbour (SE Italy). It can operate in near-real-time, in forecast mode, and on archived data for long-term assessments. It was tested studying the impact of the Bari harbour for the year 2018. The lowest impact was observed for CO, being the pollutant with the lowest share of the contribution of ships (between 8% and 68%) compared with the total harbour contribution. The impacts on PM 2.5 and PM 10 are larger arriving up to 11.8% of concentrations in the harbour area with an influence of shipping between 44% and 97%. The impact on SO 2 is almost solely due to ships and it arrives up to 80% in the harbour area. The impact on NO X ranges from a few percent in the urban area up to 40% in the harbour area and it is the pollutant of major concern regarding compliance with air quality standards. [ABSTRACT FROM AUTHOR]

Highlights • Bioaerosols emitted from composting facilities pose a concern to public health. • Dispersion models can be used to estimate spatiotemporal bioaerosol concentrations. • First nationwide A. fumigatus exposure assessment of composting facilities. • A. fumigatus concentrations deplete rapidly, reaching background levels at ∼2 km. • Distance bands are poor indicators of areas of highest exposure. Abstract Bioaerosols, ubiquitous in ambient air, are released in elevated concentrations from composting facilities with open-air processing areas. However, spatial and temporal variability of bioaerosols, particularly in relation to meteorology, is not well understood. Here we model relative concentrations of Aspergillus fumigatus at each postcode-weighted centroid within 4 km of 217 composting facilities in England between 2005 and 2014. Facilities were geocoded with the aid of satellite imagery. Data from existing bioaerosol modelling literature were used to build emission profiles in ADMS. Variation in input parameters between each modelled facility was reduced to a minimum. Meteorological data for each composting facility was derived from the nearest SCAIL-Agriculture validated meteorological station. According to our results, modelled exposure risk was driven primarily by wind speed, direction and time-varying emissions factors incorporating seasonal fluctuations in compostable waste. Modelled A.fumigatus concentrations decreased rapidly from the facility boundary and plateaued beyond 1.5–2.0 km. Where multiple composting facilities were within 4 km of each other, complex exposure risk patterns were evident. More long-term bioaerosol monitoring near facilities is needed to help improve exposure estimation and therefore assessment of any health risks to local populations. [ABSTRACT FROM AUTHOR]

Atmospheric dispersion models are widely applied to simulate pollutant concentrations such as PM 2.5 for use in long- and short-term health studies. A significant proportion of PM 2.5 originates outside urban areas in which many people live. It is important to reflect this 'background' component in the modelling process in order to provide an accurate representation of the total pollution load experienced by human populations. To be credible, model outputs must be verified against available monitoring data, which, in the case of PM 2.5 , may be limited to a small number of monitoring sites across a large urban area. Here we evaluate four different approaches to representing background PM 2.5 in an atmospheric dispersion model (ADMS-Urban) for Nottingham, UK. A directional approach, based on multiple urban background monitoring sites located outside the study area provides the most robust estimates. Our adopted approach allows us to model both short- and long-term air quality conditions, whilst accounting for local- and regional-scale variations in the pollution burden, and will ultimately enable us to assess short- and long-term effects of air pollution on health. • Background data in local scale air quality models represent regional PM 2.5. • Accounting for wind direction in models improves background estimates. • Proximate sources close to monitoring sites influence model verification. • Improved model outputs will aid assessment of acute and long-term health impacts. [ABSTRACT FROM AUTHOR]

Post combustion using amine solvents is the most mature technology for the capture of CO 2 from coal-fired power plants. Yet, amines atmospheric fate and their environmental and human health impacts, after their release by evaporation and solvent degradation from post combustion CO 2 capture (PCCC) plants to the surrounding air, remains a key area to address in view of the worldwide installation of large-scale carbon capture and storage facilities. It is therefore crucial to test potential industrial applications with respect to plant design parameters influencing the fate of the amine degradation products. In this work, a method is developed to propose ideal PCCC plant parameters with respect to its design and operation. A risk limiting scenario was modelled on the UK’s largest CO 2 capture pilot plant (CCPilot100+) in Ferrybridge using the air dispersion model ADMS, such that the total nitrosamines and nitramines from the amines realised did not exceed the reported atmospheric safety limits of 0.3 ng/m 3 with respect to human health in the local environment. A parametric sensitivity study was performed to determine the plant design parameters that most influenced the fate of the nitrosamines and nitramines. It was found that stack height and diameter, exit flue gas temperature and velocity are parameters of the PCCC plant can influence the total sum of nitrosamine (NS) and nitramine (NA) from +58% to −42% compared to the baseline parameterization. Environmental parameters, such as the site specific background meteorology and the background photochemistry were also inspected. Meteorology, i.e. mainly wind speed and wind flow field, affected the total NS and NA baseline concentrations from +28% to −10%, and background photochemistry from +165% −65%. In conclusion, if a PCCC plant is constructed with advantageous exhaust geometry, environmentally optimised operation conditions, and placed in an area with low background pollution, the risk associated with employing amines for capturing CO 2 emissions might be reduced to a minimum. [ABSTRACT FROM AUTHOR]

Two schemes for the determination of NO2 concentrations in the atmospheric dispersion model ADMS are evaluated using data from two sites in Alaska. Both schemes take account of the rate of oxidation of NO and photolysis of NO2 in the plume using identical chemical formulations. The differences lie in the approaches used for the entrainment and mixing of ambient ozone into the plume. In the standard scheme it is assumed that ozone is mixed instantaneously into the plume at source; in the entrainment limited scheme ozone is entrained into the plume at a rate determined by the rate of dilution of the instantaneous plume. A methodology comprising a scatter plot of the ratio of modelled to observed NO2 vs. modelled to observed NOx is used to distinguish errors in the chemistry schemes from errors in the prediction of NOx. Both schemes show good performance statistics with the standard scheme predicting higher NO2 concentrations. [ABSTRACT FROM AUTHOR]

This paper presents a review of pollutant dispersion modelling from non-point sources, focused on agricultural and bioaerosol sources. Relevant non-point source characteristics were collated from a literature review. These values were used to describe a 'typical' agricultural source using line, area, volume and jet source types in the plume dispersion models ADMS and AERMOD; predicted downwind pollutant concentrations are compared. The modelling shows that predicted ground-level concentrations beyond approximately 100 m downwind are similar for the majority of non-point source types. ADMS and AERMOD were used to represent releases from four sheds housing intensively farmed poultry as a case study. When the emission and volume flow rates used in the modelling were derived from measurements, the models give reasonably accurate predictions. However for releases with non-negligible efflux, modelling using non-point sources allowing for the momentum and buoyancy of the release has much better agreement with observations than those that do not. [ABSTRACT FROM AUTHOR]

Autologous bone remains the gold standard bone substitute in clinical practice. Therefore, the microarchitecture of newly developed synthetic bone substitutes, which reflects the spatial distribution of materials in the scaffold, aims to recapitulate the natural bone microarchitecture. However, the natural bone microarchitecture is optimized to obtain a mechanically stable, lightweight structure adapted to the biomechanical loading situation. In the context of synthetic bone substitutes, the application of a Triply Periodic Minimum Surface (TPMS) algorithm can yield stable lightweight microarchitectures that, despite their demanding architectural complexity, can be produced by additive manufacturing. In this study, we applied the TPMS derivative Adaptive Density Minimal Surfaces (ADMS) algorithm to produce scaffolds from hydroxyapatite (HA) using a lithography-based layer-by-layer methodology and compared them with an established highly osteoconductive lattice microarchitecture. We characterized them for compression strength, osteoconductivity, and bone regeneration. The in vivo results, based on a rabbit calvaria defect model, showed that bony ingrowth into ADMS constructs as a measure of osteoconduction depended on minimal constriction as it limited the maximum apparent pore diameter in these scaffolds to 1.53 mm. Osteoconduction decreased significantly at a diameter of 1.76 mm. The most suitable ADMS microarchitecture was as osteoconductive as a highly osteoconductive orthogonal lattice microarchitecture in noncritical- and critical-size calvarial defects. However, the compression strength and microarchitectural integrity in vivo were significantly higher for scaffolds with their microarchitecture based on the ADMS algorithm when compared with high-connectivity lattice microarchitectures. Therefore, bone substitutes with high osteoconductivity can be designed with the advantages of the ADMS-based microarchitectures. As TPMS and ADMS microarchitectures are true lightweight structures optimized for high mechanical stability with a minimal amount of material, such microarchitectures appear most suitable for bone substitutes used in clinical settings to treat bone defects in weight-bearing and non-weight-bearing sites., Competing Interests: The ADMS algorithm is patented by Spherene AG where C.W., R.B., L.F., and D.S. own stocks or stock options. Otherwise, the authors declare no conflicts of interest., (© Ekaterina Maevskaia et al., 2023; Published by Mary Ann Liebert, Inc.)

A Moon-based Earth radiation observatory (MERO) could provide a longer-term continuous measurement of radiation exiting the Earth system compared to current satellite-based observatories. In order to parameterize the detector for such a newly-proposed MERO, the evaluation of the instrument’s entrance pupil irradiance (EPI) is of great importance. The motivation of this work is to build an EPI estimating model for a simplified single-pixel MERO instrument. The rationale of this model is to sum the contributions of every location in the MERO-viewed region on the Earth’s top of atmosphere (TOA) to the MERO sensor’s EPI, taking into account the anisotropy in the longwave radiance at the Earth TOA. Such anisotropy could be characterized by the TOA anisotropic factors, which can be derived from the Clouds and the Earth’s Radiant Energy System (CERES) angular distribution models (ADMs). As an application, we estimated the shortwave (SW) (0.3–5 µm) and longwave (LW) (5–200 µm) EPIs for a hypothetic MERO instrument located at the Apollo 15 landing site. Results show that the SW EPI varied from 0 to 0.065 W/m2, while the LW EPI ranged between 0.061 and 0.075 W/m2 from 1 to 29 October, 2017. We also utilized this model to predict the SW and LW EPIs for any given location within the MERO-deployable region (region of 80.5°W–80.5°E and 81.5°S–81.5°N on the nearside of the Moon) for the future 18.6 years from October 2017 to June 2036. Results suggest that the SW EPI will vary between 0 and 0.118 W/m2, while the LW EPI will range from 0.056 to 0.081 W/m2. Though the EPI estimating model in this study was built for a simplistic single-pixel instrument, it could eventually be extended and improved in order to estimate the EPI for a multi-pixel MERO sensor.

Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are unclear. Exposure levels are difficult to quantify as established sampling methods are costly, time-consuming and current data provide limited temporal and spatial information. Confidence in dispersion model outputs in this context would be advantageous to provide a more detailed exposure assessment. We present the calibration and validation of a recognised atmospheric dispersion model (ADMS) for bioaerosol exposure assessments. The model was calibrated by a trial and error optimisation of observed Aspergillus fumigatus concentrations at different locations around a composting site. Validation was performed using a second dataset of measured concentrations for a different site. The best fit between modelled and measured data was achieved when emissions were represented as a single area source, with a temperature of 29°C. Predicted bioaerosol concentrations were within an order of magnitude of measured values (1000-10,000CFU/m3) at the validation site, once minor adjustments were made to reflect local differences between the sites (r2>0.7 at 150, 300, 500 and 600m downwind of source). Results suggest that calibrated dispersion modelling can be applied to make reasonable predictions of bioaerosol exposures at multiple sites and may be used to inform site regulation and operational management. [ABSTRACT FROM AUTHOR]

Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are not well understood, and require improved exposure classification. Dispersion modelling has great potential to improve exposure classification, but has not yet been extensively used or validated in this context. We present a sensitivity analysis of the ADMS dispersion model specific to input parameter ranges relevant to bioaerosol emissions from open windrow composting. This analysis provides an aid for model calibration by prioritising parameter adjustment and targeting independent parameter estimation. Results showed that predicted exposure was most sensitive to the wet and dry deposition modules and the majority of parameters relating to emission source characteristics, including pollutant emission velocity, source geometry and source height. This research improves understanding of the accuracy of model input data required to provide more reliable exposure predictions. [ABSTRACT FROM AUTHOR]

Atmospheric boundary layer height is one of the most important parameters in atmospheric dispersion modelling because it has a large effect on predicted air quality. Comparisons between Atmospheric Dispersion Modelling System, version 4 (ADMS 4) and lidar data were carried out on boundary layer height data from central London. The comparison showed that the boundary layer height predicted by the ADMS 4 was, on average, lower than lidar for the subset of data taken. ADMS 4 has a very simple surface scheme which is not representative of complex urban environments and the results from this research imply that there is not sufficient surface roughness within the model to produce a large enough boundary layer height. The aim of this study is to create an improved model to better forecast the growth of the daytime urban boundary layer and predict boundary layer height, h , in an air quality dispersion model using lidar measurements. The combined model was developed by using a surface model and an atmospheric boundary layer height model. Measurements of atmospheric boundary layer height by lidar used vertical velocity variance and the overall conclusion was that the combined model improved the performance of ADMS in urban areas. [ABSTRACT FROM AUTHOR]

This paper reports on the performance of Atmospheric Dispersion Modelling System (ADMS) 4.2 in predicting peak and mean ambient sulfur dioxide concentrations at two sites adjacent to the Map Ta Phut Industrial Estate in Eastern Thailand, the centre of the country's petrochemical industry. The model comprised 100 individual stacks and utilised four separate meteorological datasets from different points around the site. We show that model performance varies according to the location at which the meteorological data were obtained, with considerable differences in model outputs observed for meteorological stations that are relatively close to each other. The best performances were observed when there was co-location of the meteorological data and receptor. In such cases, acceptance criteria for the majority of performance parameters were satisfied across averaging periods ranging from 1 h to 7 days. We have also compared the results from this study with those obtained from a recent literature American Meteorological Society/United States Environmental Protection Agency Regulatory Model (AERMOD) study for the same site and time period; the comparison indicates that AERMOD is likely to be similarly influenced by the choice of meteorological dataset. Using ADMS model simulations for all four meteorological datasets and a breakdown of the local population by electoral ward, we were able to estimate exposure over 1 h, 24 h and yearly averaging periods and compare these to air quality standards and guidelines published by Thailand, the World Health Organisation (WHO) and the European Union (EU). The results of this analysis showed that despite the large variations in overall model performance, the impact of choice of meteorological dataset on prediction of compliance with the standards and guidelines is relatively small: the WHO 24-h guideline of 7.5 ppb (100th percentile) was predicted to be exceeded in all of the wards for all meteorological datasets, whilst compliance with Thai and EU standards was predicted for at least 86 % of the population, with relatively little variation between the different meteorological datasets. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) phenomenon may produce several cascade effects on citizens' health, energy consumption and air quality. Numerical modelling is recognised to be a powerful tool for the analysis of the UHI, although the question of which model to use (as implied in the 'fit-for-purpose' approach) much depends on the application and on the result of satisfactory validation against field measurements. In this paper, two different modelling approaches are applied, namely the integral-semi-Gaussian model ADMS-TH and the CFD-based model ENVI-met, to assess the UHI phenomenon in a city of south Italy (Lecce). Modelling results are validated against field measurements collected during summer 2012. The results suggest that the integral model has the ability of capturing the UHI cycle at city scale, while CFD modelling did not provide any substantial improvements in terms of local geometric effects on temperature distribution. [ABSTRACT FROM AUTHOR]

Poor air quality impacts life expectancy and quality of life of populations worldwide. Numerical models generate comprehensive air pollutant concentration datasets, useful for quantifying historic, current and, through projections, future air pollution effects on health. However, it is challenging to accommodate the full range of dispersion and chemistry processes affecting both regional and local scales in a single model. The scientific formulation and evaluation of a new quasi-Gaussian road source dispersion model, ADMS-Local, is presented. This model has been developed as a component for the 'Multi-model Air Quality System for Health Research' (MAQS-Health). ADMS-Local accounts for the influence of urban morphology on dispersion, as well as near-road NO X chemistry processes, leading to the spatial resolution of pollutant concentration gradients occurring over distances of a few metres. The model is optimised for use within the MAQS-Health system, where local modelling for each regional model grid cell is run in parallel. [Display omitted] • Air quality datasets are required for respiratory disease health research. • Street-scale air quality models can generate extensive pollutant datasets. • ADMS-Local is a new road source dispersion model for use in MAQS-Health. • ADMS-Local accounts for near-field NOx chemistry and street canyon dispersion. • ADMS-Local has been evaluated in open road, street canyon and urban environments. [ABSTRACT FROM AUTHOR]

Abstract: The Institut de Radioprotection et de Sureté Nucléaire (IRSN) performed a series of 85Kr air sampling campaigns at mesoscale distances (18–50 km) from the AREVA NC La Hague nuclear reprocessing plant (North West France) between 2007 and 2009. The samples were collected in order to test and optimise a technique to measure low krypton-85 (85Kr) air concentrations and to investigate the performance of three atmospheric dispersion models (RIMPUFF, HYSPLIT, and ADMS), This paper presents the 85Kr air concentrations measured at three sampling locations which varied from 2 to 8000 Bq m−3, along with the 85Kr air concentrations output by the dispersion models. The dispersion models made reasonable estimates of the mean concentrations of 85Kr field measurements during steady wind conditions. In contrast, the models failed to accurately predict peaks in 85Kr air concentration during periods of rapid and large changes in wind speed and/or wind direction. At distances where we made the comparisons (18–50 km), in all cases, the models underestimated the air concentration activities. [Copyright &y& Elsevier]

After nuclear power plants (NPPs) accidents in Cernobyl and Fukushima the radioactive plume has dispersed throughout the world, thus confirming the importance of evaluation the risk of the radioactive hazard with respect to the public health. Although many numerical or mathematical dispersion models have been developed over time, they have various limitations in representing the real situation. It is, therefore, essential to reduce the sources of model uncertainties coming from various factors such as source intensity, the dispersion model or meteorological input data. The objective of this paper was to assess an advanced Gaussian Puff model - Atmospheric Dispersion Modeling System (ADMS) by comparison with a CFD (Computational Fluid Dynamics) Lagrange Particle Tracking (LPT) method and to use it for local scale dispersion studies of fugitive hazardous emissions. The source terms were established on the basis of the accident spectrum postulated in Final Safety Analysis Report for a CANDU6 NPP. [ABSTRACT FROM AUTHOR]

Many countries perform national air quality assessments using grid-based numerical air dispersion models, generally referred to as 'regional' models. Advantages of these models include the ability to use temporally and spatially varying meteorology and model chemical reactions over large temporal and spatial scales. These models usually perform reasonably well against rural and urban background monitors, but predictions at roadside monitors are underestimated. City-scale air dispersion models have been developed to give high spatial resolution, but are usually restricted to use spatially homogeneous meteorological data and to model simplified chemical reactions over short time scales. Thus, regional and city-scale air dispersion models have complementary strengths and a system where a city-scale model is nested within a regional model allows accurate air dispersion modelling over a range of spatial scales. This paper presents preliminary modelling results from a system where the local model ADMS-Urban is nested within the regional model, CMAQ. [ABSTRACT FROM AUTHOR]

Abstract: The French Institute for Radiological Protection and Nuclear Safety (IRSN), in collaboration with VEOLIA (French environmental services company), conducted experimental campaigns to study atmospheric dispersion around an Energy Recycling Unit (EUR). The objectives were to study dispersion for an elevated release in a rural environment and to compare results with those of models. The atmospheric dispersion was studied by SF6 tracer injection into a 40 m high stack. Maximum values of experimental Atmospheric Transfer Coefficients (ATCmax) and horizontal dispersion standard deviations (σ h) were compared to predictions from a first generation Briggs gaussian model as well as results from the latest generation ADMS 4.1 gaussian model. In neutral atmospheric conditions, the Briggs and ADMS models are in good agreement with experimental data in terms of ATC and σ h. In unstable condition, for σ h, both ADMS and Briggs models slightly overestimate the data for winter and summer conditions. In unstable conditions, ADMS and Briggs models overestimated ATCmax. The statistical evaluation of the models versus experimental data shows neither models ever meets all of the criteria for good performance. However, statistical evaluation indicates that the ADMS model is more suitable for neutral condition, and that the Briggs model is more reliable for summer unstable conditions. [Copyright &y& Elsevier]

Abstract: Recurved passive ammonia flux (PAF) samplers based on absorption by oxalic acid were evaluated in two contrasting field environments. First, a flux frame 12m high and 55.2m long was used to support a vertical array of up to 156 flux samplers downwind of a controlled point or line source of ammonia (NH3). The upwind distance of the NH3 source was chosen so that the whole NH3 plume was captured by the flux frame. These measurements were used to calibrate the flux frame''s collection efficiency (CE). The plume dispersion was modelled with ADMS. Second, individual columns of seven flux samplers at heights between 0.3 and 10.4m were used to measure the NH3 emissions from a free-range sow paddock. The controlled release measurements gave measured overall CEs of over 80% and strong agreement between the measured and modelled flux densities (). The farm measurements showed that this method is insufficiently sensitive for use in a climate for which the wind direction and other critical meteorological parameters may vary widely throughout the several days required for a measurement. [Copyright &y& Elsevier]

Abstract: A flux frame method using recurved passive ammonia flux (PAF) samplers for the measurement of distributed outdoor agricultural sources of ammonia (NH3) was evaluated in a controlled environment. The collection efficiency of the samplers was determined in a wind tunnel at controlled values of NH3 flux density (0.77–13.5mg NH3m-2s-1), and over a range of angles of orientation to the flow direction (0°, 30°, 60°, 70°, 80° and 90°). The samplers were effective up to a wind speed of 7ms-1 and an angle of 80° with a mean collection efficiency of 71%. The flux frame method had a mean collection efficiency of 87.4% when used with ground level point sources under controlled conditions in an open-circuit wind tunnel with boundary layer airflow characteristics. [Copyright &y& Elsevier]