Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0 – Part 1: The country contributions

A large fraction of the urban population in Europe is exposed to particulate matter levels above the WHO guideline value. To make more effective mitigation strategies, it is important to understand the influence on particulate matter (PM) from pollutants emitted in different European nations. In this study, we evaluate a country source contribution forecasting system aimed at assessing the domestic and transboundary contributions to PM in major European cities for an episode in December 2016. The system is composed of two models (EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0), which allows the consideration of differences in the source attribution. We also compared the PM10 concentrations, and both models present satisfactory agreement in the 4 d forecasts of the surface concentrations, since the hourly concentrations can be highly correlated with in situ observations. The correlation coefficients reach values of up to 0.58 for LOTOS-EUROS and 0.50 for EMEP for the urban stations; the values are 0.58 for LOTOS-EUROS and 0.72 for EMEP for the rural stations. However, the models underpredict the highest hourly concentrations measured by the urban stations (mean underestimation of 36 %), which is to be expected given the relatively coarse model resolution used (0.25∘ longitude × 0.125∘ latitude). For the source attribution calculations, LOTOS-EUROS uses a labelling technique, while the EMEP/MSC-W model uses a scenario having reduced anthropogenic emissions, and then it is compared to a reference run where no changes are applied. Different percentages (5 %, 15 %, and 50 %) for the reduced emissions in the EMEP/MSC-W model were used to test the robustness of the methodology. The impact of the different ways to define the urban area for the studied cities was also investigated (i.e. one model grid cell, nine grid cells, and grid cells covering the definition given by the Global Administrative Areas – GADM). We found that the combination of a 15 % emission reduction and a larger domain (nine grid cells or GADM) helps to preserve the linearity between emission and concentrations changes. The nonlinearity, related to the emission reduction scenario used, is suggested by the nature of the mismatch between the total concentration and the sum of the concentrations from different calculated sources. Even limited, this nonlinearity is observed in the NO-3, NH+4, and H2O concentrations, which is related to gas–aerosol partitioning of the species. The use of a 15 % emission reduction and of a larger city domain also causes better agreement on the determination of the main country contributors between both country source calculations. Over the 34 European cities investigated, PM10 was dominated by domestic emissions for the studied episode (1–9 December 2016). The two models generally agree on the dominant external country contributor (68 % on an hourly basis) to PM10 concentrations. Overall, 75 % of the hourly predicted PM10 concentrations of both models have the same top five main country contributors. Better agreement on the dominant country contributor for primary (emitted) species (70 % is found for primary organic matter (POM) and 80 % for elemental carbon – EC) than for the inorganic secondary component of the aerosol (50 %), which is predictable due to the conceptual differences in the source attribution used by both models. The country contribution calculated by the scenario approach depends on the chemical regime, which largely impacts the secondary components, unlike the calculation using the labelling approach

avaldebe/PyPMS: PyPMS 0.3.0 (202009)

Serial Air Quality Sensors Tools for reading Air Quality Sensors with serial (UART) interface, data acquisition and logging. Command Line Interface Usage: pms [OPTIONS] COMMAND [ARGS]... Read serial sensor Options: --sensor-model -m [PMSx003|PMS3003|PMS5003S|PMS5003ST|PMS5003T|SDS01x|SDS198|HPMA115S0|HPMA115C0|SPS30|MCU680] sensor model [default: PMSx003] -s, --serial-port TEXT serial port [default: /dev/ttyUSB0] -i, --interval INTEGER seconds to wait between updates [default: 60] -n, --samples INTEGER stop after N samples --debug print DEBUG/logging messages [default: False] --install-completion [bash|zsh|fish|powershell|pwsh] Install completion for the specified shell. --show-completion [bash|zsh|fish|powershell|pwsh] Show completion for the specified shell, to copy it or customize the installation. --help Show this message and exit. Commands: bridge Bridge between MQTT and InfluxDB servers csv Read sensor and print measurements influxdb Read sensor and push PM measurements to an InfluxDB server mqtt Read sensor and push PM measurements to a MQTT server serial Read sensor and print measurements For details on a particular command and their options pms COMMAND --hel

metno/emep-ctm: OpenSource rv4.33 (201906)

<p><a href="http://emep-ctm.readthedocs.io/en/latest/?badge=ug4_33"></a></p> <p>The EMEP/MSC-W model version planned to be used on the <a href="http://emep.int/publ/emep2019_publications.html">EMEP status reporting of the year 2019</a> - rv4.33 - is released, together with a set of input data and a full year model results for the year 2015 under <a href="http://www.gnu.org/copyleft/gpl.html">GPL license v3</a>.</p> <p>This release contains the following set of information:</p> <ul> <li>a complete set of 'input data' to allow for model runs for year 2015</li> <li>the open source 'model code' of the EMEP/MSC-W model version rv4_33</li> <li>'model results' for the year 2015 for comparison of a successful run</li> </ul> <p>Retrieve datasets using the <a href="https://github.com/metno/emep-ctm/tree/tools">catalog tool</a> with:</p> <pre><code class="lang-bash">catalog.py -R rv4_33 </code></pre&gt

GenChem v1.0-a chemical pre-processing and testing system for atmospheric modelling

This paper outlines the structure and usage of the GenChem system, which includes a chemical preprocessor GenChem.py) and a simple box model (box-Chem). GenChem provides scripts and input files for converting chemical equations into differential form for use in atmospheric chemical transport models (CTMs) and/or the boxChem system. Although GenChem is primarily intended for users of the Meteorological Synthesizing Centre West of the European Monitoring and Evaluation Programme (EMEP MSC-W) CTM and related systems, boxChem can be run as a stand-Alone chemical solver, enabling for example easy testing of chemical mechanisms against each other. This paper presents an outline of the usage of the GenChem system, explaining input and output files, and presents some examples of usage. The code needed to run GenChem is released as opensource code under the GNU license

Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model

A description of the new air quality downscaling model – the urban EMEP (uEMEP) and its combination with the EMEP MSC-W model (European Monitoring and Evaluation Programme Meteorological Synthesising Centre West) – is presented. uEMEP is based on well-known Gaussian modelling principles. The uniqueness of the system is in its combination with the EMEP MSC-W model and the “local fraction” calculation contained within it. This allows the uEMEP model to be imbedded in the EMEP MSC-W model and downscaling can be carried out anywhere within the EMEP model domain, without any double counting of emissions, if appropriate proxy data are available that describe the spatial distribution of the emissions. This makes the model suitable for high-resolution calculations, down to 50 m, over entire countries. An example application, the Norwegian air quality forecasting and assessment system, is described where the entire country is modelled at a resolution of between 250 and 50 m. The model is validated against all available monitoring data, including traffic sites, in Norway. The results of the validation show good results for NO2, which has the best known emissions, and moderately good for PM10 and PM2.5. In Norway, the largest contributor to PM, even in cities, is long-range transport followed by road dust and domestic heating emissions. These contributors to PM are more difficult to quantify than NOx exhaust emission from traffic, which is the major contributor to NO2 concentrations. In addition to the validation results, a number of verification and sensitivity results are summarised. One verification showed that single annual mean calculations with a rotationally symmetric dispersion kernel give very similar results to the average of an entire year of hourly calculations, reducing the runtime for annual means by 4 orders of magnitude. The uEMEP model, in combination with EMEP MSC-W model, provides a new tool for assessing local-scale concentrations and exposure over large regions in a consistent and homogenous way and is suitable for large-scale policy applications

Isolation of lactic acid bacteria from swine milk and characterization of potential probiotic strains with antagonistic effects against swine-associated gastrointestinal pathogens

Probiotics are usually isolated from the gastrointestinal tract of humans and animals. The search of probiotics in human milk is a recent field of research, as the existence of the human milk microbiome was discovered only about a decade ago. To our knowledge, no reports regarding the potential probiotic effect of bacteria from swine milk were published. In this work, we isolated several lactic acid bacteria from swine milk and evaluated them for them potential as probiotics. Among the isolated strains, Lactobacillus curvatus TUCO-5E showed antagonistic effects against swine-associated gastrointestinal pathogens. TUCO-5E was able to reduce the growth of enterotoxigenic and enterohemorragic E. coli strains as well as pathogenic Salmonella. In vitro exclusion and displacement assays in intestinal epithelial cells showed a remarkable antagonistic effect for L. curvatus TUCO-5E against Salmonella TUCO-I7 and S. enterica ATCC 13096. Moreover, by using a mice model of Salmonella infection we were able to demonstrated that L. curvatus TUCO-5E preventive administration during 5 consecutive days was capable of decreasing the number of S. typhimurium in the liver and spleen of treated mice when compared to controls, and avoided dissemination of the pathogen to the blood stream. Then, we demonstrated here that swine milk is an interesting source for finding beneficial bacteria. In addition, the results of this work suggest that L. curvatus TUCO-5E is a good candidate for in vivo studying the protective effect of probiotics against intestinal infection and damage induced by Salmonella infection in the porcine host.On isole habituellement les probiotiques du tractus gastro-intestinal d’humains et d’animaux. La recherche de probiotiques dans du lait humain est un domaine de recherche récent, puisque la découverte du microbiome laitier humain ne date que d’environ 10 ans. À notre connaissance, on n’a jamais publié de rapport sur le possible effet probiotique de bactéries issues de lait porcin. Dans le présent ouvrage, nous avons isolé plusieurs bactéries lactiques du lait porcin et avons évalué leur potentiel probiotique. Parmi les souches isolées, Lactobacillus curvatus TUCO-5E a fait preuve d’antagonisme a` l’encontre de pathogènes gastro-intestinaux porcins. TUCO-5E a su diminuer la multiplication de souches entérotoxinogènes et entérohémorragiques d’Escherichia coli et de salmonelles pathogènes. Des expériences d’exclusion et de déplacement chez des cellules épithéliales intestinales ont permis de mettre en évidence une action antagoniste remarquable exercée par L. curvatus TUCO-5E envers Salmonella sp. souche TUCO-I7 et Salmonella enterica ATCC 13096. Par ailleurs, un modèle murin d’infection a` la salmonelle nous a permis de démontrer qu’une administration préventive de L. curvatus TUCO-5E pendant 5 jours consécutifs parvenait a` réduire le nombre de Salmonella enterica serovar Typhimurium dans le foie et la rate des souris traitées, comparativement aux témoins, et a` endiguer la propagation du pathogène dans la circulation sanguine. Dès lors, nous avons démontré que le lait porcin serait une source intéressante de bactéries bénéfiques. De plus, les résultats de cette étude laissent entendre que L. curvatus TUCO-5E pourrait faire l’objet d’études in vivo sur l’effet protecteur des probiotiques envers les infections intestinales et les dommages connexes occasionnés par les salmonelles dans l’hôte porcin. [Traduit par la Rédaction].Fil: Quilodrán Vega, Sandra Rayén. Universidad de Concepción. Facultad de Ciencias Veterinarias. Laboratorio de Microbiología de los Alimentos; ChileFil: Villena, Julio Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucuman. Centro de Referencia Para Lactobacilos; ArgentinaFil: Valdebenito, José. Universidad de Concepción. Facultad de Ciencias Veterinarias. Laboratorio de Microbiología de los Alimentos; ChileFil: Salas, María José. Universidad de Concepción. Facultad de Ciencias Biológicas. Departamento de Microbiología. Laboratorio de Patogénesis Bacteriana; ChileFil: Parra, Cristian. Universidad de Concepción. Facultad de Ciencias Biológicas. Departamento de Microbiología. Laboratorio de Patogénesis Bacteriana; ChileFil: Ruiz, Alvaro. Universidad de Concepción. Facultad de Ciencias Veterinarias. Laboratorio de Microbiología de los Alimentos; ChileFil: Kitazawa, Haruki. Tohoku University. Graduate School of Agricultural Science. Laboratory of Animal Products Chemistry. Food and Feed Immunology Group; Japón. Tohoku University. Graduate School of Agricultural Science. International Education and Research Center for Food Agricultural Immunology. Livestock Immunology Unit ; JapónFil: García, Apolinaria. Univesidad de Concepción. Facultad de Ciencias Biológicas. Laboratorio de Patogénesis Bacteriana. Grupo de Investigación de Immunobiótica; Chil