1,721,053 research outputs found
Air pollution and emission reductions over the Po-valley: Air quality modelling and integrated assessment
No full textThe Po-valley located in northern Italy at the footstep of the Alps is characterized by a high density of anthropogenic emissions and by the frequent occurrence of stagnant meteorological conditions. The area has been identified as one hot spot place where pollution levels will remain problematic in spite of the application of the current European legislation devoted to air pollution control. By 2020, health impact on population and effects on ecosystems by ozone and eutrophication are indeed calculated to be amongst the highest in Europe and anthropogenic fine particulate matter levels are expected to be responsible for a loss of ten months of life expectancy. In general, long-range transported air pollution in the Po-Valley represents only a fraction of 30-40%, stressing the importance of local control measures in the area to efficiently reduce the impact of air pollution. This paper presents an overview of two connected projects focusing on air-quality modeling and integrated assessment. The POMI (PO-valley Model Inter-comparison) exercise aims at exploring the changes in urban air-quality predicted by different Air Quality Models (AQM) in response to changes in emissions. The first phase of the project has concentrated on the elaboration of the required input data for the AQM, i.e. meteorology, monitoring, and emissions. The latter have been elaborated based on the combination of various types of data originating from different Authorities and characterized by different spatial scales and levels of detail. During this process, priority has been given to the bottom-up approach believed to be more suitable to capture local information than a pure top-down disaggregation from the national emission inventory. The available POMI results at this stage indicate model performances in line with those obtained in the frame of previous model evaluation exercise but with a marked underestimation of the fine particulate matter (in particular of its organic fraction) and a significant model variability in the modeling of ozone concentrations. Work to investigate the sensitivity of the AQM to various parameters (e.g. meteorology and emission) is on-going with the aim to better understand the air quality processes in the Po-Valley region and better represent them in the AQM In parallel to POMI, an integrated assessment tool is being developed to design and assess the effectiveness of regional abatement policies. This tool is planned to make use of information available at the local/regional scale (technological changes, emission factors...) to allow investigating the efficiency of both technical and nontechnical abatement measures and to find the optimal cost allocation. POMI provides useful information for the development of sectoral local/regional source-receptor relationships and for better accounting for the different sources of model-related uncertainties (emissions, meteorology...) in the efficacy assessment of abatement strategies. It is believed that such an approach which combines (1) collecting high quality emission inventories, (2) running extensive AQM exercises and (3) optimizing the choice of emission abatement strategies via a specific integrated assessment tool will support the local/regional Authorities in designing effective AQP in the frame of the current European air quality directive
Performance criteria to evaluate air quality modeling applications
No full textA set of statistical indicators fit for air quality model evaluation is selected based on experience and literature: The Root Mean Square Error (RMSE), the bias (Bias), the standard Deviation (SD) and the correlation factor (R) are selected. Among these the RMSE is proposed as the key one for the description of the model skill. Model Performance Criteria (MPC) to investigate whether a model results are ‘good enough’ for a given application are calculated based on the observation uncertainty (U). The basic concept is to allow for model results a similar margin of tolerance (in terms of uncertainty) as for observations. U is pollutant, concentration level and station dependent, therefore the proposed MPC are normalized by U. Some existing composite diagrams are adapted to visualize model performance in terms of the proposed MPC and are illustrated in a real modeling application. The Target diagram, used to visualize the RMSE, is adapted with a new normalization on its axis, while complementary diagrams are proposed. In this first application the dependence of U on concentrations level and station is ignored, and an assumption on the pollutant dependent relative error is made. The advantages of this new approach are finally described.JRC.H.2 - Air and Climat
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Applying the delta tool to support the Air Quality Directive: evaluation of the TCAM chemical transport model
No full textThis paper presents an application of the DELTA evaluation tool V3.2 to support the EU Air Quality Directive (AQD 2008). This software, designed in the frame of the FAIRMODE project (Forum for Air Quality Modelling in Europe, http://fairmode.ew.eea.europa.eu/), is currently used as support to working groups of modelers across Europe in the diagnostics and assessment of air quality model performances under the AQD (2008). The skills of the DELTA tool V3.2 are tested by looking at the results of a 1-year (2005) simulation performed using the transport chemical aerosol model (Carnevale et al. 2008) at 6x6-km(2) resolution over the Po Valley. The modeled daily PM10 concentrations at surface level are compared to observations provided by approximately 50 stations distributed across the domain. The main statistical parameters (i.e., bias, root mean square error, correlation coefficient, standard deviation) as well as different types of diagrams (scatter plots, time series plots, Taylor and target plots) have been produced. A representation of the observation uncertainty in the target plot, used to derive model performance criteria for the main statistical indicators, is also presented and discussed
A methodology for the evaluation of re-analyzed PM10 concentration fields: a case study over the PO Valley
No full textThis study presents a general MonteCarlo-based methodology for the validation of chemical transport model (CTM) concentration re-analyzed fields over a certain domain. A set of re-analyses is evaluated by applying the observation uncertainty (U) approach (Thunis et al. Atmos Environ 59: 476-482 2012b), developed in the frame of Forum for Air Quality Modelling in Europe (FAIRMODE; http://fairmode.ew.eea.europa.eu/). Modeled results from the chemical transport model (Transport and Chemical Aerosol Model (TCAM)) (Carnevale et al. Sci Total Environ 390: 166-176 2008) for year 2005 are used as background values. The model simulation domain covers the Po Valley with a 6x6 km(2) resolution. Measured data for both assimilation and evaluation are provided by approximately 50 monitoring stations distributed across the Po Valley. The main statistical indicators (i.e., bias, root mean square error, correlation coefficient, standard deviation) as well as different types of diagrams (scatter plots and target plots) have been produced and visualized with the Delta evaluation tool V3.6. The target criteria are fulfilled by 97 % of the sites for the re-analyzed fields and by 61 % for the modeled values, showing how the application of the assimilation technique improves TCAM raw fields. The model underprediction of PM10 concentration (normalizedmean bias (NMB) up to -70 %) is reduced at almost all sites in the re-analysis (NMB in the range -20-+20 %,). The correlation coefficient R is higher for the re-analyzed fields (0.7-1) compared to the raw ones (0.2-0.8)
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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