161 research outputs found

    Meteorology applied to urban air pollution problems: concepts from COST 715

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    International audienceThe outcome of COST 715 is reviewed from the viewpoint of a potential user who is required to consider urban meteorology within an air pollution assessment. It is shown that descriptive concepts are helpful for understanding the complex structure of the urban boundary layer, but that they only apply under a limited number of conditions. However such concepts are necessary to gain insight into both simple and complex air pollution models. It is argued that wider considerations are needed when considering routine air quality assessments involving an air quality model's formulation and pedigree. Moreover there appears to be a reluctance from model developers to move away from familiar concepts of the atmospheric boundary layer even if they are not appropriate to urban areas. An example is given from COST 715 as to how routine urban meteorological measurements of wind speed may be used and adapted for air quality assessments. Reference to the full COST 715 study is made which provides further details

    Meteorology applied to urban air pollution problems: concepts from COST 715

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    International audienceThis selective review of the COST 715 considers simple descriptive concepts in urban meteorology with particular attention to air pollution assessment. It is shown that these are helpful for understanding the complex structure of the urban boundary layer, but that simple concepts only apply under a limited number of occasions. However such concepts are necessary for insight into how both simple and complex air pollution models perform. Wider considerations are needed when considering routine air quality assessments involving an air quality model's formulation and pedigree. It is argued that there is a reluctance from model developers to move away from familiar concepts of the atmospheric boundary layer even if they are not appropriate to urban areas. An example is given from COST 715 as to how routine urban meteorological measurements of wind speed may be used and adapted for air quality assessments. Reference to the full COST 715 study is made which provides further details

    Are empirical equations an appropriate tool to assess separation distances to avoid odour annoyance?

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    Annoyance due to environmental odour exposure is in many jurisdictions evaluated by a yes/no decision. Such a binary decision has been typically achieved via odour impact criteria (OIC) and, when applicable, the resultant separation distances between emission sources and residential areas. If the receptors lie inside the required separation distance, odour exposure is characterised with the potential of causing excessive annoyance. The state-of-the-art methodology to determine separation distances is based on two general steps: (i) calculation of the odour exposure (time series of ambient odour concentrations) using dispersion models and (ii) determination of separation distances through the evaluation of this odour exposure by OIC. Regarding meteorological input data, dispersion models need standard meteorological observations and/or atmospheric stability typically on an hourly basis, which requires expertise in this field. In the planning phase, and as a screening tool, an educated guess of the necessary separation distances to avoid annoyance is in some cases sufficient. Therefore, empirical equations (EQs) are in use to substitute the more time-consuming and costly application of dispersion models. Because the separation distance shape often resembles the wind distribution of a site, wind data should be included in such approaches. Otherwise, the resultant separation distance shape is simply given by a circle around the emission source. Here, an outline of selected empirical equations is given, and it is shown that only a few of them properly reflect the meteorological situation of a site. Furthermore, for three case studies, separation distances as calculated from empirical equations were compared against those from Gaussian plume and Lagrangian particle dispersion models. Overall, our results suggest that some empirical equations reach their limitation in the sense that they are not successful in capturing the inherent complexity of dispersion models. However, empirical equations, developed for Germany and Austria, have the potential to deliver reasonable results, especially if used within the conditions for which they were designed. The main advantage of empirical equations lies in the simplification of the meteorological input data and their use in a fast and straightforward approach

    Visual parameter optimisation for biomedical image processing

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    Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches
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