cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4600852
title: Data_WP3_2_Atmospheric dispersion modelling results for the whole of Europe

description: This dataset is stored in various subfolders named based on the simulation day to which the modeling results are referring to (i.e. yyyymmdd-hh). The dataset has been operationally produced by the Atmospheric dispersion models applied in ICARUS. Air quality data (NO2, O3, PM10 and PM2.5) and meteorological data (precipitation, relative humidity, temperature, wind speed and direction) are available at European level using an outer grid with dimensions 12x12km consisting of 303 x 303 cells. The dataset has been used within WP3 to assess air quality levels at European scale and to produce concentration maps.The dataset is available in the form of concentration maps stored in png format. Row data in net-CDF format were not stored due to their huge size (i.e. we produced ca. 5,000 files each one of about 55GB). However, raw data in net-CDF format may be shared with interested users by means of individual requests made to the Project Coordinator with the expectation that both the ICARUS project and the European<br> Commission’s Horizon 2020 as the funding program are properly cited.
DOI: 10.5281/zenodo.4600851
title: Data_WP3_2_Atmospheric dispersion modelling results for the whole of Europe

description: This dataset is stored in various subfolders named based on the simulation day to which the modeling results are referring to (i.e. yyyymmdd-hh). The dataset has been operationally produced by the Atmospheric dispersion models applied in ICARUS. Air quality data (NO2, O3, PM10 and PM2.5) and meteorological data (precipitation, relative humidity, temperature, wind speed and direction) are available at European level using an outer grid with dimensions 12x12km consisting of 303 x 303 cells. The dataset has been used within WP3 to assess air quality levels at European scale and to produce concentration maps.The dataset is available in the form of concentration maps stored in png format. Row data in net-CDF format were not stored due to their huge size (i.e. we produced ca. 5,000 files each one of about 55GB). However, raw data in net-CDF format may be shared with interested users by means of individual requests made to the Project Coordinator with the expectation that both the ICARUS project and the European<br> Commission’s Horizon 2020 as the funding program are properly cited.
DOI: 10.5281/zenodo.4627738
title: Complex image segmentation (3D) for SAPHIR

description: See the README.txt file for details of files and the video associated in youtube live for the explanation of how to use the macro. This dataset is composed from the original image (19juil05a1.czi) of a peyer patch in intestine with 6 channels (CD3-eF450=Lympocyte T, Sytox Blue=nucleus,GFP+AF488=phagocyte, CD69+aGt-AF546=not used here, B220+AF594=Lymphocyte B, Ki67-eF660=proliferative nucelus used for the segmentation). The program with segment in 3D the proliferative cells (morpholibJ), the central plane for each nucleus will be used to create a ring and calculate the mean intensity in the channel LT and LB). These data will be saved in the Intensity_Normalized file). See the poster (histo_cytometry.pdf) for details. Theses results will serve for SAPHIR application for histo-cytometry.
description: Modified : Intensity_Normamlized_19juil05a1.txt
DOI: 10.5281/zenodo.4056000
title: Complex image segmentation (3D) for SAPHIR

description: See the README.txt file for details of files and the video associated in youtube live for the explanation of how to use the macro. This dataset is composed from the original image (19juil05a1.czi) of a peyer patch in intestine with 6 channels (CD3-eF450=Lympocyte T, Sytox Blue=nucleus,GFP+AF488=phagocyte, CD69+aGt-AF546=not used here, B220+AF594=Lymphocyte B, Ki67-eF660=proliferative nucelus used for the segmentation). The program with segment in 3D the proliferative cells (morpholibJ), the central plane for each nucleus will be used to create a ring and calculate the mean intensity in the channel LT and LB). These data will be saved in the Intensity_Normalized file). See the poster (histo_cytometry.pdf) for details. Theses results will serve for SAPHIR application for histo-cytometry.
description: Modified : Intensity_Normamlized_19juil05a1.txt
DOI: 10.5281/zenodo.4601542
title: Data_WP4_1_Multi-sensor data for personal exposure monitoring in the participating cities data set

description: This dataset includes data collected by personal sensors worn by each participant, and static sensors located in each household of the city campaigns in Athens, Thessaloniki, Madrid, Milan, Brno, Basel and Ljubljana. There are three types of sensors: the custom made by IoTech, the one provided by Garmin (Vivosmart 3) and the static sensors provided by uHoo. The custom-made sensors measured air pollution by capturing three types of particulate matter, PM1, PM2.5 and PM10, temperature, relative humidity, altitude and speed. The Garmin sensor provided measurements of personal movement/activity and intensity of activity, amount of burned<br> calories, sleeping time, stress levels and heart rate in 15-second time intervals.<br> The static sensors provided by uHoo took measurements of temperature, relative humidity, and air pollution levels (particulate matter – PM2.5, ozone, nitrogen dioxide, carbon dioxide, carbon monoxide and total volatile organic compounds. All the data measured by these three sensor types are stored in the open repository in different subfolders named according to the city where the data were collected and in further subfolders named according to device used (i.e., “GARMIN”; “PPM SENSORS”; and “uHoo”) and finally in two subfolders named on the basis of the season (“WINTER” and “SUMMER”). Single files encompassing the data measured are named according to the following scheme: City_Season_ParticipantID.xlsx (e.g. ATH_S_P039.xlsx).
DOI: 10.5281/zenodo.4601541
title: Data_WP4_1_Multi-sensor data for personal exposure monitoring in the participating cities data set

description: This dataset includes data collected by personal sensors worn by each participant, and static sensors located in each household of the city campaigns in Athens, Thessaloniki, Madrid, Milan, Brno, Basel and Ljubljana. There are three types of sensors: the custom made by IoTech, the one provided by Garmin (Vivosmart 3) and the static sensors provided by uHoo. The custom-made sensors measured air pollution by capturing three types of particulate matter, PM1, PM2.5 and PM10, temperature, relative humidity, altitude and speed. The Garmin sensor provided measurements of personal movement/activity and intensity of activity, amount of burned<br> calories, sleeping time, stress levels and heart rate in 15-second time intervals.<br> The static sensors provided by uHoo took measurements of temperature, relative humidity, and air pollution levels (particulate matter – PM2.5, ozone, nitrogen dioxide, carbon dioxide, carbon monoxide and total volatile organic compounds. All the data measured by these three sensor types are stored in the open repository in different subfolders named according to the city where the data were collected and in further subfolders named according to device used (i.e., “GARMIN”; “PPM SENSORS”; and “uHoo”) and finally in two subfolders named on the basis of the season (“WINTER” and “SUMMER”). Single files encompassing the data measured are named according to the following scheme: City_Season_ParticipantID.xlsx (e.g. ATH_S_P039.xlsx).
DOI: 10.5281/zenodo.4601580
title: Data_WP4_3_TAD Data

description: The datasets include data collected by time activity diaries (TAD) in the form of questionnaires from each participant of the city campaigns in Athens, Thessaloniki, Madrid, Milan, Brno, Basel and Ljubljana. The questionnaires were digitized in excel<br> format to match the sensors data. The information the time activity diaries provided relates to the type and the place of an activity the participant performs in a specific time frame. The activity (resting, playing, sleeping, sports, cooking, smoking, cleaning, running) can be indoor or outdoor, the participant can be in transit using public or personal means of transportation (bus, car, motorbike, bicycle,<br> foot, other). Also, information regarding the house conditions (candles on/off, air conditioning – fan on/off, fireplace, windows open/closed) is also provided. All the data collected through the TAD surveys are stored in the open repository in different subfolders named according to the city where the data were collected and in further two subfolders named according to the season when the data was collected (“WINTER” and “SUMMER”). Single files encompassing the data measured are named according to the following scheme: City_Season_ParticipantID.xlsx (e.g. ATH_S_P032.xlsx).<br> The anonymized data is stored in MS Excel xls and xlsx formats to maximise the potential for use with a variety of analytical software.
DOI: 10.5281/zenodo.4601575
title: Data_WP4_2_ ICARUS survey data

description: The dataset consists of quantitative and qualitative information collected from each participant during the personal exposure campaigns in the case-study cities (Athens, Thessaloniki, Madrid, Milan, Brno, Basel and Ljubljana). The survey data captured information related to participants’ socioeconomic status, age, gender, nationality, place of birth, health status, occupation, education level, marital status, children, annual income, daily schedule regarding work and exercise and time spent indoors and outdoors, details on their working conditions, preferred means of transportation and time spent weekly, medical treatments, illnesses and smoking. In addition, data regarding each participants’ household has also captured, such as the number of people (minor and adults) living in it, the house structure and surface, isolation, heating (type and autonomy of the thermostat), proximity to pollutants,<br> cooking, cleaning, smoking and ventilation habits, renovations, income and existence of pets. This data has been used to evaluate how SES and individual lifestyle should be taken into account in exposure modelling.<br>
DOI: 10.5281/zenodo.4601574
title: Data_WP4_2_ ICARUS survey data

description: The dataset consists of quantitative and qualitative information collected from each participant during the personal exposure campaigns in the case-study cities (Athens, Thessaloniki, Madrid, Milan, Brno, Basel and Ljubljana). The survey data captured information related to participants’ socioeconomic status, age, gender, nationality, place of birth, health status, occupation, education level, marital status, children, annual income, daily schedule regarding work and exercise and time spent indoors and outdoors, details on their working conditions, preferred means of transportation and time spent weekly, medical treatments, illnesses and smoking. In addition, data regarding each participants’ household has also captured, such as the number of people (minor and adults) living in it, the house structure and surface, isolation, heating (type and autonomy of the thermostat), proximity to pollutants,<br> cooking, cleaning, smoking and ventilation habits, renovations, income and existence of pets. This data has been used to evaluate how SES and individual lifestyle should be taken into account in exposure modelling.<br>
DOI: 10.5281/zenodo.4600807
title: Data_WP3_1_Atmospheric dispersion modelling results for the participating cities

description: This dataset is operationally produced by the atmospheric dispersion models applied in ICARUS and contains data stored in two main subfolders as follows: 1) Folder “Air quality data of Representative days” which includes air quality data for the Representative days (RD) which were estimated by the EUROCORDEX climate data. This data has been derived from the application of a nesting approach at the urban scale of the Eulerian WRF/WRF-Chem model in the 9 pilot cities addressed in ICARUS i.e. Thessaloniki, Athens, Roskilde/Copenhagen, Basel, Brno, Milan, Madrid, Ljubljana and Stuttgart. On the urban scale, nine (9) nests with dimensions 2x2km have been used consisting of 42x42 grid cells each. Daily concentrations were produced and stored for NO2, O3, PM10, PM2.5. Data are stored in various subfolders named according to the city to which they are referring to and in further subfolders named according to the policy/measure assessed. Within these subfolders the filename convention is the following: Domain/date of the RD. 2) The “GHG” folder which includes GHGs (CO2 and CH4) concentration data calculated for each ICARUS city under the BaU emission scenario. The filename conventions is the following: Cityname.csv
DOI: 10.5281/zenodo.4600806
title: Data_WP3_1_Atmospheric dispersion modelling results for the participating cities

description: This dataset is operationally produced by the atmospheric dispersion models applied in ICARUS and contains data stored in two main subfolders as follows: 1) Folder “Air quality data of Representative days” which includes air quality data for the Representative days (RD) which were estimated by the EUROCORDEX climate data. This data has been derived from the application of a nesting approach at the urban scale of the Eulerian WRF/WRF-Chem model in the 9 pilot cities addressed in ICARUS i.e. Thessaloniki, Athens, Roskilde/Copenhagen, Basel, Brno, Milan, Madrid, Ljubljana and Stuttgart. On the urban scale, nine (9) nests with dimensions 2x2km have been used consisting of 42x42 grid cells each. Daily concentrations were produced and stored for NO2, O3, PM10, PM2.5. Data are stored in various subfolders named according to the city to which they are referring to and in further subfolders named according to the policy/measure assessed. Within these subfolders the filename convention is the following: Domain/date of the RD. 2) The “GHG” folder which includes GHGs (CO2 and CH4) concentration data calculated for each ICARUS city under the BaU emission scenario. The filename conventions is the following: Cityname.csv
DOI: 10.5281/zenodo.4605750
title: Data_WP5_2_Health effects at the community level

description: This dataset contains the quantitative assessment of health impact at the population level as well as on vulnerable population subgroups (e.g. children) for several health endpoints. The latter includes the followings: PM2.5 mortality (all causes) &gt;30 years old; PM10 infant mortality (0-1 year); PM10 Incidence of Chronic bronchitis (adult); PM10 Cardiac Hospital admissions, PM10 Respiratory Hospital admissions; PM10 Prevalence of Chronic bronchitis (children aged between 6 and 12); NO2 mortality (all causes) &gt; 30 years old; and NO2 Prevalence of bronchitic symptoms in asthmatic children (between 5 and 14). Data are reported as central estimates as<br> well as lower and upper bound to reflect the associated uncertainty. The impact on human health has been estimated up to the year<br> 2040 as the total number of additional health outcomes for each health end point above mentioned in each ICARUS city for each policy/measure options identified in WP5. The filename convention is the following: City_ Health Impact_Pollutant_LT.xls (e.g. Milan Health Impact_PM LT.xlsx). All the files include two worksheets where the total number of additional health outcomes are reported respectively for the whole computational domain and for the municipality only. The only exceptions are Athens and Thessaloniki where results are reported only for the whole computational domain as all the policies analyzed are addressing the greater city areas. The datasets are available in MS–Excel xls(x) format to ensure full interoperability allowing easy parsing and information exchange.
DOI: 10.5281/zenodo.4605749
title: Data_WP5_2_Health effects at the community level

description: This dataset contains the quantitative assessment of health impact at the population level as well as on vulnerable population subgroups (e.g. children) for several health endpoints. The latter includes the followings: PM2.5 mortality (all causes) &gt;30 years old; PM10 infant mortality (0-1 year); PM10 Incidence of Chronic bronchitis (adult); PM10 Cardiac Hospital admissions, PM10 Respiratory Hospital admissions; PM10 Prevalence of Chronic bronchitis (children aged between 6 and 12); NO2 mortality (all causes) &gt; 30 years old; and NO2 Prevalence of bronchitic symptoms in asthmatic children (between 5 and 14). Data are reported as central estimates as<br> well as lower and upper bound to reflect the associated uncertainty. The impact on human health has been estimated up to the year<br> 2040 as the total number of additional health outcomes for each health end point above mentioned in each ICARUS city for each policy/measure options identified in WP5. The filename convention is the following: City_ Health Impact_Pollutant_LT.xls (e.g. Milan Health Impact_PM LT.xlsx). All the files include two worksheets where the total number of additional health outcomes are reported respectively for the whole computational domain and for the municipality only. The only exceptions are Athens and Thessaloniki where results are reported only for the whole computational domain as all the policies analyzed are addressing the greater city areas. The datasets are available in MS–Excel xls(x) format to ensure full interoperability allowing easy parsing and information exchange.
DOI: 10.5281/zenodo.4605944
title: Data_WP8_1_Stakeholders list

description: The dataset is available in xls(x) format. For each stakeholder identified the following metadata information is provided in the concise dataset:<br> • Organization name<br> • Field of activity<br> • Type of stakeholder Full details including:<br> • Name and Surname<br> • Role in the Organization<br> • Job title<br> • Contact details (i.e. email address, phone number, etc.)<br> cannot be shared for privacy issues and are included in the extended version (confidential).
DOI: 10.5281/zenodo.4605943
title: Data_WP8_1_Stakeholders list

description: The dataset is available in xls(x) format. For each stakeholder identified the following metadata information is provided in the concise dataset:<br> • Organization name<br> • Field of activity<br> • Type of stakeholder Full details including:<br> • Name and Surname<br> • Role in the Organization<br> • Job title<br> • Contact details (i.e. email address, phone number, etc.)<br> cannot be shared for privacy issues and are included in the extended version (confidential).
DOI: 10.5281/zenodo.4593861
title: Data_WP2_5_Life_cycle_data for relevant processes and activities data set

description: The dataset includes life cycle emission data relevant to the activities and processes identified in WP5. This includes life cycle emission factors for the road transport, heating sector as well as electricity consumption. Lifecycle emission factors for electricity consumption (filename: LCDB_Electricity_FINAL.xlsx) comprise several possible future developments of the European electricity market, including higher penetration of renewable energy.<br> For the buildings, separate emission factors are generated for insulation (filename: LCDB_Buildings_insulation_FINAL.xlsx)<br> and heating technologies (filename: LCDB_Buildings_heating_FINAL.xlsx). Lifecycle emissions comprise emissions from production,<br> transport (of goods/fuels) and disposal. For transport (filename: LCDB_Transport_Final.xlsx), separate lifecycle emission factors for different vehicle types are collected, split into production, operation, disposal, infrastructure and fuel cycle. All data are documented in deliverable D2.3 freely downloadable from the ICARUS website.
DOI: 10.5281/zenodo.4593797
title: Data_WP2_1_Future activity-emission factor matrices for the participating cities

description: The dataset includes data on future activity-emission factor matrices for all the ICARUS participating cities and for the classical air pollutants (NH3, NMVOC, NOX, PM10, PM2.5, CO, SO2, BC and OC), GHGs (CO2, CO, N2O, CH4), heavy metals, PAHs and dioxins, relevant to the years 2015, 2020 and 2030. A detailed description of the structure of the DB can be found in deliverable D2.2 freely downloadable from the ICARUS website.<br> Additionally, bottom-up activity data and emission factors are combined to sectoral emission grids (1x1 km) for each city. The sites targeted cover all the ICARUS pilot cities. The data are available in MS-Access format (accdb) to maximise the interoperability for use with a variety of analytical software. The sectoral emission grids are provided in standard GIS vector format (shp).
DOI: 10.5281/zenodo.4593796
title: Data_WP2_1_Future activity-emission factor matrices for the participating cities

description: The dataset includes data on future activity-emission factor matrices for all the ICARUS participating cities and for the classical air pollutants (NH3, NMVOC, NOX, PM10, PM2.5, CO, SO2, BC and OC), GHGs (CO2, CO, N2O, CH4), heavy metals, PAHs and dioxins, relevant to the years 2015, 2020 and 2030. A detailed description of the structure of the DB can be found in deliverable D2.2 freely downloadable from the ICARUS website.<br> Additionally, bottom-up activity data and emission factors are combined to sectoral emission grids (1x1 km) for each city. The sites targeted cover all the ICARUS pilot cities. The data are available in MS-Access format (accdb) to maximise the interoperability for use with a variety of analytical software. The sectoral emission grids are provided in standard GIS vector format (shp).
DOI: 10.5281/zenodo.4593827
title: Data_WP2_3_Emission inventory for the participating cities data set

description: The dataset includes model-ready gridded sector-specific emissions at a high spatial resolution for six air pollutants (NH3, NMVOC, NOX, PM10, PM2.5, SO2) for 2015, 2020 and 2030 using a bottom-up approach. The sites targeted cover the pilot cities addressed in ICARUS (i.e., Thessaloniki, Athens, Basel, Brno, Milan, Madrid, Ljubljana and Stuttgart). These emission inventories have been used as input for the atmospheric pollution models applied in WP3. The dataset is available in txt format (semicolon separated) as it is best suited for project internal data exchange (especially as input for the atmospheric pollution models applied in WP3).
DOI: 10.5281/zenodo.4593826
title: Data_WP2_3_Emission inventory for the participating cities data set

description: The dataset includes model-ready gridded sector-specific emissions at a high spatial resolution for six air pollutants (NH3, NMVOC, NOX, PM10, PM2.5, SO2) for 2015, 2020 and 2030 using a bottom-up approach. The sites targeted cover the pilot cities addressed in ICARUS (i.e., Thessaloniki, Athens, Basel, Brno, Milan, Madrid, Ljubljana and Stuttgart). These emission inventories have been used as input for the atmospheric pollution models applied in WP3. The dataset is available in txt format (semicolon separated) as it is best suited for project internal data exchange (especially as input for the atmospheric pollution models applied in WP3).
DOI: 10.5281/zenodo.4604851
title: Data_WP2_4_Emission inventory for the whole of Europe data set

description: This dataset includes model-ready gridded sector-specific emissions at a high spatial resolution for six standard air pollutants (NH3, NMVOC, NOX, PM10, PM2.5, SO2) and GHGs (CO2, CO, N2O, CH4) for 2015, 2020 and 2030 using a top-down approach for the spatial distribution. Gridded sector-specific emissions for the standard air pollutants are stored in the subfolder named “Air_pollutants” while gridded emissions for GHHs are stored in the sub-folder called “GHG”. These emission inventories were used as input for the<br> atmospheric pollution models applied in WP3. The dataset is available in txt format (semicolon separated) as it is best suited for project internal data exchange (especially as input for the atmospheric pollution models applied in WP3).