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The virus and socioeconomic inequality: An agent-based model to simulate and assess the impact of interventions to reduce the spread of COVID-19 in Rio de Janeiro, Brazil
<p>This video shows de simulation of scenarios presented in the article "The virus and socioeconomic inequality: An agent-based model to simulate and assess the impact of interventions to reduce the spread of COVID-19 in Rio de Janeiro, Brazil"</p>
d5-6-assessment-of-impacts-liguria
<p>Data output from the tool set application for the assessment of the environmental (emissions, carbon footprint, ambient air concentrations), health (exposure and health effects), and economic impacts (e.g. health-related costs).</p> <ul> <li><strong>Liguria shapefile</strong><br> file: genova.7z<br> Shapefile with the urban scale domain over Genova/ Liguria with 25 km x 15 km</li> <li><strong>3_LIG_Air Quality_Baseline (mesoscale/NO2 concentrations)</strong><br> file: no2_2010010100_2010123123_lcc.png<br> Annual NO2 average concentrations (µg/m^3) from WRF-CAMx modelling system, for the mesoscale domain D2.</li> <li><strong>3_LIG_Air Quality_Baseline (mesoscale/PM2.5 concentrations)</strong><br> file: pm2.5_2010010100_2010123123_lcc.png<br> Annual PM2.5 average concentrations (µg/m^3) from WRF-CAMx modelling system, for the mesoscale domain D2.</li> <li><strong>3_LIG_Air Quality_Baseline (mesoscale/PM10 concentrations)</strong><br> file: pm10_2010010100_2010123123_lcc.png<br> Annual PM10 average concentrations (µg/m^3) from WRF-CAMx modelling system, for the mesoscale domain D2.</li> <li><strong>3_LIG_Air Quality_Baseline (urban scale/ NO2 concentrations)</strong><br> file: gen_aq2app_no2.txt<br> Annual NO2 average concentrations from URBAIR model Coordinate system: LCP clicurb (meters)</li> <li><strong>3_LIG_Air Quality_Baseline (urban scale/ PM10 concentrations)</strong><br> file: gen_aq2app_pm10.txt<br> Annual PM10 average concentrations from URBAIR model Coordinate system: LCP clicurb (meters)</li> <li><strong>3_LIG_Air Quality_Baseline (urban scale/ PM2.5 concentrations)</strong><br> file: gen_aq2app_pm2.5.txt<br> Annual PM2.5 average concentrations from URBAIR model Coordinate system: LCP clicurb (meters)</li> <li><strong>6_LIG_CarbonFootprint_Baseline</strong><br> file: ech.ma.15-fr2-wp5-carbon-footprint-ed2.pdf<br> Carbon footprint methodologies and estimation for the baseline year for Liguria Region</li> <li><strong>3_LIG_Air Quality_Baseline (mesoscale-report)</strong><br> file: lig_mesoscale.pdf<br> This report provides an overview of the modelling approach used to characterize the air quality in the Liguria region, which includes a detailed description of the air quality modelling system WRF-CAMx (section 1.1.) and a description of the methodology applied to evaluate the model performance (section 1.2.). It also includes results of concentration fields and a source apportionment for NO2, PM10 and PM2.5.</li> <li><strong>3_LIG_Air Quality_Baseline (urbanscale-report)</strong><br> file: lig_aq_urbanscale_report.pdf<br> This report provides a brief overview oh the methodology used. It presents an analysis of concentration fields for NO2, PM10, PM2.5 of the total and by modeled sectors, it also includes an analysis of the source contribution and for the maximum values.</li> <li><strong>2_LIG_IRCI_baseline</strong><br> file: ech.ma.15-fr1-wp5-irc-ed5.3.pdf</li> <li><strong>2_LIG_IRCI_Scenarios</strong><br> file: ech.ma.15-fr3-wp5-irc-future-ed5.pdf</li> <li><strong>2_LIG_temporal_profiles</strong><br> file: liguaria-daily_hourlytd_res_comm_emi.xlsx<br> Temporal profiles of Liguria's residential sector and commercial sector scale in %: Daily emissions, typical days emissions and hourly typical days emissions of PM10 and NOX variables.</li> <li><strong>2_LIG_Transport_baseline_map</strong><br> file: roadnetwork_lig.zip<br> Map with lines, link with emissions using filed "ID"</li> <li><strong>2_LIG_Transport_baseline_values</strong><br> file: emission_values_lig.zip<br> Part 2 of 2 files that make the Liguria transport emissions baseline: total emissions per link in .csv: To be linked to the road network file using the identifier "uniqueID" shapefile with road links units: g emissions at link level consisting of a zip file with 2 .csv-files, in the following format: first column: link-ID (link with shapefile of the road network) second column: pollutant (PM, PM non-exhaust or NOx) third column: mode ("BESTEL"= van or light freight, "MIDZWVR" = medium freight, "MOTOR" = motorcycles, "OVBUS" = bus, "PERSAUTO" = passenger cars, "ZWAARVR" = heavy freight columns DAY: hourly intervals for weekday ("WD") and weekend ("WE") all units in g 2 files with values: aggregates over type, by type of day, per hour of day and a separate file for annual totals (at link level, per pollutant (including FC))</li> <li><strong>2_LIG_transport_scenarios</strong><br> file: 191121_gen_scenario_results_summary_v2.xlsx<br> This data-set reflects the relative changes of road transport emissions in different years and scenario's compared to the baseline. 2 sets of scenario's are given, one per tab: "SDW": BAU & scenario's established in the stakeholder dialogue workshop "UPS": updated BAU (if applicable) & final Unified Policy Scenario (UPS) selected in the policy workshop. reported for 3 future years compared to the 2015 baseline: 2025, 2035 and 2050 reported for NOx & PM for 6 modes: "MIDZWR": medium truck "ZWVR": heavy truck "BUS": busses "MOTO": motorcycles "CAR": passenger cars "VAN": light freight, assumed to be a mix of passenger cars and medium trucks all units: %</li> <li><strong>5_LIG_health_statistics</strong><br> file: lig_health-analysis.xlsx<br> demographics and population data to calculate the health statistics</li> <li><strong>5_LIG_health_scenarios</strong><br> file: summary_results_liguria.xlsx<br> Health-related impacts (selected mortality and morbidity endpoints) related to exposure to PM2.5, NO2, and PM10, considering concentration-response functions and baseline concentrations recommended by WHO.</li> <li><strong>3_LIG_NO2_AQ_latlong</strong><br> file: genova_no2_latlong.rar<br> The shapefile includes total NO2 concentrations (µg/m^3) , as well as concentrations by sector (transport, shipping, IRCI and industrial). Coordiante system: WGS1984</li> <li><strong>3_LIG_PM2_AQ_latlong</strong><br> file: genova_pm2_latlong.rar<br> The shapefile includes total PM2 concentrations (µg/m^3) , as well as concentrations by sector (transport, shipping, IRCI and industrial). Coordiante system: WGS1984</li> <li><strong>3_LIG_PM10_AQ_latlong</strong><br> file: genova_pm10_latlong.rar<br> The shapefile includes total PM10 concentrations (µg/m^3) , as well as concentrations by sector (transport, shipping, IRCI and industrial). Coordiante system: WGS1984</li> <li><strong>6_LIG_CarbonFootprint_Scenarios</strong><br> file: ech.ma.15-fr4-wp5-carbon-footprint-future-ed3-.pdf<br> Carbon footprint business as usual and scenario projections for Liguria Region.</li> <li><strong>3_LIG_Air Quality_Baseline (mesoscale/SourceApportionment)</strong><br> file: lig_psat.xlsx<br> Time series of daily average contributions for each source group for PM10, PM2.5 and NO2 concentrations from WRF-CAMx modelling system with the SA tool, for the Genoa urban area.</li> <li><strong>3_LIG_Air Quality Scenarios_urban scale NO2 matrix</strong><br> file: lig_no2_scenarios.mat<br> Annual NO2 average concentrations (µg/m^3) from URBAIR model, considering the impact of all scenarios in all the emission sectors: transport, industrial and IRCI, together with the background concentrations. The file contains X, Y coordinates, together with the total annual average concentrations for BAU scenarios, low and high ambition scenarios from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>3_LIG_Air Quality Scenarios_ urban scale PM10 matrix</strong><br> file: lig_pm10_scenarios.mat<br> Annual PM10 average concentrations (µg/m^3) from URBAIR model, considering the impact of all scenarios in all the emission sectors: transport, industrial and IRCI, together with the background concentrations. The file contains X, Y coordinates, together with the total annual average concentrations for BAU scenarios, low and high ambition scenarios from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>3_LIG_Air Quality Scenarios_urban scale PM2 matrix</strong><br> file: lig_pm2_scenarios.mat<br> Annual PM2.5 average concentrations (µg/m^3) from URBAIR model, considering the impact of all scenarios in all the emission sectors: transport, industrial and IRCI, together with the background concentrations. The file contains X, Y coordinates, together with the total annual average concentrations for BAU scenarios, low and high ambition scenarios from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_LIG_Exposure_EU_Baseline NO2 matrix</strong><br> file: lig_no2_exposureeu_baseline.mat<br> Population potentially exposed to the annual NO2 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 40 ug/m^3 for the baseline year.</li> <li><strong>4_LIG_Exposure_EU_Baseline PM10 matrix</strong><br> file: lig_pm10_exposureeu_baseline.mat<br> Population potentially exposed to the annual PM10 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 40 ug/m^3 for the baseline year.</li> <li><strong>4_LIG_Exposure_WHO_Baseline PM10 matrix</strong><br> file: lig_pm10_exposurewho_baseline.mat<br> Population potentially exposed to the annual PM10 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the WHO annual guideline value of 20 ug/m^3 for the baseline year.</li> <li><strong>4_LIG_Exposure_EU_Baseline PM2 matrix</strong><br> file: lig_pm2_exposureeu_baseline.mat<br> Population potentially exposed to the annual PM2.5 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 25 ug/m^3 for the baseline year.</li> <li><strong>4_LIG_Exposure_WHO_Baseline PM2 matrix</strong><br> file: lig_pm2_exposurewho_baseline.mat<br> Population potentially exposed to the annual PM2.5 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the WHO annual guideline value of 10 ug/m^3 for the baseline year.</li> <li><strong>4_LIG_Exposure_EU_Scenarios NO2 matrix</strong><br> file: lig_no2_exposureeu_scenarios.mat<br> Population potentially exposed to the annual NO2 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 40 ug/m^3 for BAU scenarios, low and high ambition scenarios from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_LIG_Exposure_EU_Scenarios PM10 matrix</strong><br> file: lig_pm10_exposureeu_scenarios.mat<br> Population potentially exposed to the annual PM10 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 40 ug/m^3 for BAU scenarios, low and high ambition scenarios from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_LIG_Exposure_WHO_Scenarios PM10 matrix</strong><br> file: lig_pm2_exposurewho_scenarios.mat<br> Population potentially exposed to the annual PM10 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the WHO annual guideline value of 20 ug/m^3 for BAU scenarios, low and high ambition scenarios from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_LIG_Exposure_EU_Scenarios PM2 matrix</strong><br> file: lig_pm2_exposureeu_scenarios.mat<br> Population potentially exposed to the annual PM2.5 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 25 ug/m^3 for BAU scenarios, low and high ambition scenarios from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_LIG_Exposure_WHO_Scenarios PM2 matrix</strong><br> file: lig_pm2_exposurewho_scenarios.mat<br> Population potentially exposed to the annual PM2.5 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the WHO annual guideline value of 10 ug/m^3 for BAU, scenarios, low and high ambition scenarios from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> </ul>
d5-5-assessment-of-impacts-bristol
<p>Data output from the tool set application for the assessment of the environmental (emissions, carbon footprint, ambient air concentrations), health (exposure and health effects), and economic impacts (e.g. health-related costs).</p> <ul> <li><strong>D5.5 Assessment of Impacts - First City</strong><br> file: d5.5-assessment-of-impacts-first-city_-revised-june-2020.pdf<br> This is an action deliverable consisting of the impact assessment work undertaken in WP5 encompassing: 1. the integrated urban module based on the household and dwelling characteristics; 2. the transport emission sector; 3. the industrial, residential, commercial and institutional emission sectores; 4. the energy/ power generation 5. the air quality and related population exposure; 6. the health-related impacts and costs; and 7. the carbon footprint. This report aims to describe the framework developed for the assessment of the environmental, health, and economic impacts for the first ClairCity case study (Bristol City Council). The impact assessment analysis data can be found on the ClairCity Data Portal and this report is the submitted formal deliverable to record that the work has been delivered.</li> <li><strong>specifications of modelling tool set</strong><br> file: module_specifications_report.pdf<br> The general purpose of this document is to come up with an aligned view of the model toolset developed to be applied to the 6 ClairCity case studies.</li> <li><strong>Bristol shapefile</strong><br> file: bristol_200mx200m.rar<br> Shapefile with the urban scale domain over Bristol with 20 km x 20 km, with a grid resolution of 200m x 200m</li> <li><strong>1_BRS_Integrated_household_BAU_Scenarios</strong><br> file: bristol_household_projections.xlsx<br> Official ONS projections of Bristol's household population by age group of household head, and household structure (household size and number of children)</li> <li><strong>1_BRS_Integrated_BAU_Scenarios_2025</strong><br> file: bristol_hh_energy_use_2025.xlsx<br> Household energy use projections for 2025, based on official ONS household population projections and the dataset</li> <li><strong>1_BRS_Integrated_BAU_Scenarios_2035</strong><br> file: bristol_hh_energy_use_2035.xlsx<br> Household energy use projections for 2035, based on official ONS household population projections and the dataset</li> <li><strong>1_BRS_Integrated_BAU_Scenarios_2050</strong><br> file: bristol_hh_energy_use_2050.xlsx<br> Household energy use projections for 2050, based on official ONS household population projections and the dataset</li> <li><strong>2_BRS_Natural_baseline</strong><br> file: claircity_naturalemissions_brs_jan2019.pdf<br> Emissions (in kg/year) were based on EMEP emission inventory for nature at 0.1x0.1 degrees resolution (~ 10 km) for the year 2015 disaggregated for the urban domain of Bristol by forest, grass, parks and nature reserve areas classified in the Open Street Map database.</li> <li><strong>2_BRS_Agriculture_baseline</strong><br> file: claircity_agricultureemissions_brs_jan2019.pdf<br> Emissions (in kg/year) were based on EMEP emission inventory for agriculture and livestock at 0.1x0.1 degrees resolution (~ 10 km) for the year 2015 disaggregated for the urban domain of Bristol by farms, meadows, vineyards land uses classified in the Open Street Map database</li> <li><strong>2_BRS_IRCI_baseline</strong><br> file: ech.ma.15-fr1-wp5-irc-ed5.3.pdf<br> This document reports about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular its scope is to: • Develop a specific tool to evaluate emissions using existing industrial emissions data (EMEP, E-PRTR, others) and EMEP/EEA Emission inventory Guidebook; • Develop a specific tool to estimate emissions from small combustion in residential, commercial and institutional sector.</li> <li><strong>2_BRS_IRCI_baseline_not_industry_area_fuel_cons</strong><br> file: 2_brs_irci_baseline_not_industry_area_fuel_cons.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports area fuel consumptions from small combustion in residential, commercial and institutional sector evaluated using UK statistical official data. The methodology and results are described in "2_BRS_IRCI_baseline2" document.</li> <li><strong>2_BRS_IRCI_baseline_not_industry_area_emi</strong><br> file: 2_brs_irci_baseline_not_industry_area_emi.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports area NOX and PM10 emissions from small combustion in residential, commercial and institutional sector evaluated using EMEP/EEA Emission inventory Guidebook and UK statistical official data. The methodology and results are described in "2_BRS_IRCI_baseline" document.</li> <li><strong>2_BRS_IRCI_baseline_industry_area_emi</strong><br> file: 2_brs_irci_baseline_industry_area_emi.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports NOX and PM10 Emissions from minor PRTR sources allocated to 20x20 grid. The methodology and results are described in "2_BRS_IRCI_baseline" document.</li> <li><strong>2_BRS_IRCI_baseline_industry_point_emi</strong><br> file: 2_brs_irci_baseline_industry_point_emi.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports NOX and PM10 Emissions from main PRTR sources by source. The methodology and results are described in "2_BRS_IRCI_baseline" document.</li> <li><strong>2_BRS_IRCI_BAU_Scenario</strong><br> file: ech.ma.15-fr3-wp5-irc-future-ed5.pdf<br> This document reports about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module activities related to BAU and scenarios definition. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In this report methodology and results are reported for: • Business as Usual (BAU): future situation without any policy interventions beyond what is decided upon at this point with three-time horizons: 2025, 2035 and 2050; • Scenario: added policy interventions to the BAU, same time horizon as results from Stakeholder Dialogue Workshop; • Unified Policy Scenario: final scenario as a results of Policy Workshop.</li> <li><strong>2_BRS_IRCI_BAU_not_industry_area_emi_2025</strong><br> file: 2_brs_irci_bau_not_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) area NOX and PM10 emissions, in Business As Usual scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_BAU_not_industry_area_emi_2035</strong><br> file: 2_brs_irci_bau_not_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) area NOX and PM10 emissions, in Business As Usual scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_BAU_not_industry_area_emi_2050</strong><br> file: 2_brs_irci_bau_not_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) area NOX and PM10 emissions, in Business As Usual scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_BAU_industry_area_emi_2025</strong><br> file: 2_brs_irci_bau_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in Business As Usual scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_BAU_industry_area_emi_2035</strong><br> file: 2_brs_irci_bau_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in Business As Usual scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_BAU_industry_area_emi_2050</strong><br> file: 2_brs_irci_bau_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in Business As Usual scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_BAU_industry_point_emi_2025</strong><br> file: 2_brs_irci_bau_industry_point_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in Business As Usual scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_BAU_industry_point_emi_2035</strong><br> file: 2_brs_irci_bau_industry_point_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in Business As Usual scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_BAU_industry_point_emi_2050</strong><br> file: 2_brs_irci_bau_industry_point_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in Business As Usual scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_not_industry_area_emi_2025</strong><br> file: 2_brs_irci_s1_not_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) area NOX and PM10 emissions, in S1 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_not_industry_area_emi_2035</strong><br> file: 2_brs_irci_s1_not_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) area NOX and PM10 emissions, in S1 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_not_industry_area_emi_2050</strong><br> file: 2_brs_irci_s1_not_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) area NOX and PM10 emissions, in S1 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_industry_area_emi_2025</strong><br> file: 2_brs_irci_s1_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in S1 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_industry_area_emi_2035</strong><br> file: 2_brs_irci_s1_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in S1 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_industry_area_emi_2050</strong><br> file: 2_brs_irci_s1_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in S1 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_industry_point_emi_2025</strong><br> file: 2_brs_irci_s1_industry_point_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in S1 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_industry_point_emi_2035</strong><br> file: 2_brs_irci_s1_industry_point_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in S1 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S1_industry_point_emi_2050</strong><br> file: 2_brs_irci_s1_industry_point_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in S1 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_not_industry_area_emi_2025</strong><br> file: 2_brs_irci_s2_not_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) area NOX and PM10 emissions, in S2 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_not_industry_area_emi_2035</strong><br> file: 2_brs_irci_s2_not_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) area NOX and PM10 emissions, in S2 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_not_industry_area_emi_2050</strong><br> file: 2_brs_irci_s2_not_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) area NOX and PM10 emissions, in S2 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_industry_area_emi_2025</strong><br> file: 2_brs_irci_s2_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in S2 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_industry_area_emi_2035</strong><br> file: 2_brs_irci_s2_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in S2 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_industry_area_emi_2050</strong><br> file: 2_brs_irci_s2_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in S2 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_industry_point_emi_2025</strong><br> file: 2_brs_irci_s2_industry_point_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in S2 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_industry_point_emi_2035</strong><br> file: 2_brs_irci_s2_industry_point_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in S2 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S2_industry_point_emi_2050</strong><br> file: 2_brs_irci_s2_industry_point_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in S2 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_not_industry_area_emi_2025</strong><br> file: 2_brs_irci_s3_not_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) area NOX and PM10 emissions, in S3 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_not_industry_area_emi_2035</strong><br> file: 2_brs_irci_s3_not_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) area NOX and PM10 emissions, in S3 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_not_industry_area_emi_2050</strong><br> file: 2_brs_irci_s3_not_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) area NOX and PM10 emissions, in S3 scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_industry_area_emi_2025</strong><br> file: 2_brs_irci_s3_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in S3 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_industry_area_emi_2035</strong><br> file: 2_brs_irci_s3_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in S3 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_industry_area_emi_2050</strong><br> file: 2_brs_irci_s3_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in S3 scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_industry_point_emi_2025</strong><br> file: 2_brs_irci_s3_industry_point_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in S3 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_industry_point_emi_2035</strong><br> file: 2_brs_irci_s3_industry_point_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in S3 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_S3_industry_point_emi_2050</strong><br> file: 2_brs_irci_s3_industry_point_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in S3 scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_not_industry_area_emi_2025</strong><br> file: 2_brs_irci_ups_not_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) area NOX and PM10 emissions, in UPS scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_not_industry_area_emi_2035</strong><br> file: 2_brs_irci_ups_not_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) area NOX and PM10 emissions, in UPS scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_not_industry_area_emi_2050</strong><br> file: 2_brs_irci_ups_not_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) area NOX and PM10 emissions, in UPS scenario, from small combustion in residential, commercial and institutional sector evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_industry_point_emi_2025</strong><br> file: 2_brs_irci_ups_industry_point_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in UPS scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_industry_point_emi_2035</strong><br> file: 2_brs_irci_ups_industry_point_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in UPS scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_industry_point_emi_2050</strong><br> file: 2_brs_irci_ups_industry_point_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in UPS scenario, from main PRTR sources by source, evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_industry_area_emi_2025</strong><br> file: 2_brs_irci_ups_industry_area_emi_2025.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2025) NOX and PM10 Emissions, in UPS scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_industry_area_emi_2035</strong><br> file: 2_brs_irci_ups_industry_area_emi_2035.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2035) NOX and PM10 Emissions, in UPS scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_IRCI_UPS_industry_area_emi_2050</strong><br> file: 2_brs_irci_ups_industry_area_emi_2050.csv<br> This dataset reports results about the WP5 Task 5.2.4 Design & development of Industry Residential/Commercial & Other services module. The module integrates in the overall model the industrial, residential, commercial and institutional emissions sources. In particular the dataset reports future (2050) NOX and PM10 Emissions, in UPS scenario, from minor PRTR sources, allocated to 20x20 grid evaluated during the project as described in "2_BRS_IRCI_BAU_Scenario" document.</li> <li><strong>2_BRS_Transport_baseline_map</strong><br> file: baseline_map_v3.zip<br> Part 1 of 2 files that make the Bristol transport emissions baseline 1. total emissions per link in .csv: To be linked to the road network file using the identifier "uniqueID" 2. shapefile with road links units: g ___ GIS-map of Bristol road network.</li> <li><strong>2_BRS_Transport_baseline_values</strong><br> file: baseline_emissions_v3.zip<br> Part 2 of 2 files that make the Bristol transport emissions baseline: 1. total emissions per link in .csv: To be linked to the road network file using the identifier "uniqueID" 2. shapefile with road links units: g ___ emissions at link level consisting of a zip file with 18+1 .csv-files, in the following format: first column: link-ID (link with shapefile of the road network) second column: pollutant (PM, PM non-exhaust or NOx) third column: mode ("BESTEL"= van or light freight, "MIDZWVR" = medium freight, "MOTOR" = motorcycles, "OVBUS" = bus, "PERSAUTO" = passenger cars, "ZWAARVR" = heavy freight columns D-AY: hourly intervals for weekday ("WD") and weekend ("WE") all units in g additional file added with all data combined "T_ALL_EMISSIONS_v3.xlsx"</li> <li><strong>2_BRS_Transport_source_apportionment</strong><br> file: 190919_behavior_v6_2015is1.xlsx<br> describes the share of road transport emissions by behavior-properties and population properties. Pure data & pivot-table for easy use: 1. male/female 2. 2 income-classes 3. 5 age groups 4. 3 car-ownership groups (0, 1, 2 or more) 5. Time of day: morning-, evening peak, midday and night 6. Type of day (weekend/weekday) 7. Motive: 8 classes 8. mode</li> <li><strong>2_BRS_transport_scenarios</strong><br> file: 190219_bristol_scenario_results_pw_summary.xlsx<br> This data-set reflects the relative changes of road transport emissions in different years and scenario's compared to the baseline. 2 sets of scenario's are given, one per tab: "SDW": BAU & scenario's established in the stakeholder dialogue workshop "UPS": updated BAU (if applicable) & final Unified Policy Scenario (UPS) selected in the policy workshop. reported for 3 future years compared to the 2015 baseline: 2025, 2035 and 2050 reported for NOx & PM for 6 modes: "MIDZWR": medium truck "ZWVR": heavy truck "BUS": busses "MOTO": motorcycles "CAR": passenger cars "VAN": light freight, assumed to be a mix of passenger cars and medium trucks all units: %</li> <li><strong>2_BRS_temporal_profiles</strong><br> file: bristol-daily_hourlytd_res_comm_emi.xlsx<br> Temporal profiles of Bristol's residential sector and commercial sector scale in %: Daily emissions, typical days emissions and hourly typical days emissions of PM10 and NOX variables. The data sources in synthesizing the temporal profiles are: 1. Monthly gas pattern (Gas) is available at Eurostat's energy database https://ec.europa.eu/eurostat/web/energy/data/database?p_p_id=NavTreeportletprod_WAR_NavTreeportletprod_INSTANCE_QAMy7Pe6HwI1&p_p_lifecycle=0&p_p_state=normal&p_p_mode=view&p_p_col_id=column-2&p_p_col_count=1. The files are available in tab-delimited (.tsv) file extensions. In total, it has 129 variables and 815 columns. The variables consist of "unit,product,indic_nrg,geo", while the rest use the time in monthly periods from "2018M08" back to "2008M01". Since we have selected 2015 as the reference year, we selected "2015M01" to "2015M12". For each country selected, we choose all the observations marked with the country's ID, given that each country's ID is unique. 2. Hourly local temperature (Temp) is obtained from UK's Meteorological Office https://www.metoffice.gov.uk/ . The dataset is taken from the Filton station as an .xlsx file and it has three variables: "date", "hour" and "hourly temperature". 3. Hourly national electricity load (El) is available at open power system data https://data.open-power-system-data.org/time_series/ . The dataset has four variables: utc_timestamp is the start of time period in Coordinated Universal Time in datetime format, cet_cest_timestamp is the start of time period in Central European (Summer) Time in datetime format, Interpolated_values is the marker for missing data column in source data, which has been interpolated in string and the selected country's load in MW. 4. Share of fuel resources (%), especially wood heaters is calculated from Techne's emission area dataset. This dataset is available in .csv files and consists of eight variables: "year", "city", "zone", "codvariable", "namevariable", "pollutant", "emissions" and "unit".</li> <li><strong>3_BRS_Air Quality_Baseline (mesoscale/NO2 concentrations)</strong><br> file: no2_2010010100_2010123123_lcc.png<br> Annual NO2 average concentrations (µg/m^3) from WRF-CAMx modelling system, for the mesoscale domain D2.</li> <li><strong>3_BRS_Air Quality_Baseline (mesoscale/PM10 concentrations)</strong><br> file: pm10_2010010100_2010123123_lcc.png<br> Annual PM10 average concentrations (µg/m^3) from WRF-CAMx modelling system, for the mesoscale domain D2.</li> <li><strong>3_BRS_Air Quality_Baseline (mesoscale/PM2.5 concentrations)</strong><br> file: pm2.5_2010010100_2010123123_lcc.png<br> Annual PM2.5 average concentrations (µg/m^3) from WRF-CAMx modelling system for the mesoscale domain D2.</li> <li><strong>3_BRS_Air Quality_Baseline (mesoscale/SourceApportionment)</strong><br> file: psat_brs.xlsx<br> Time series of daily average contributions for each source group for PM10, PM2.5 and NO2 concentrations from WRF-CAMx modelling system with the SA tool, for the Bristol urban area.</li> <li><strong>3_BRS_Air Quality_Baseline (mesoscale-report)</strong><br> file: brs_mesoscale.pdf<br> This report provides an overview of the modelling approach used to characterize the air quality in the Bristol region, which includes a detailed description of the air quality modelling system WRF-CAMx (section 1.1.) and a description of the methodology applied to evaluate the model performance (section 1.2.). It also includes results of concentration fields and a source apportionment for NO2, PM10 and PM2.5.</li> <li><strong>3_BRS_Air Quality_Baseline (urban scale/ NO2 concentrations)</strong><br> file: brs_no2.mat<br> Annual NO2 average concentrations (µg/m^3) from URBAIR model (considering all the emission sectors: transport, industrial and IRCI) plus the background concentrations from the WRF-CAMx-SA system. The file contains X, Y coordinates from the LCP Clicurb coordinate system.</li> <li><strong>3_BRS_Air Quality_Baseline (urban scale/ PM10 concentrations)</strong><br> file: brs_pm10.mat<br> Annual PM10 average concentrations (µg/m^3) from URBAIR model (considering all the emission sectors: transport, industrial and IRCI) plus the background concentrations from the WRF-CAMx-SA system. The file contains X, Y coordinates from the LCP Clicurb coordinate system.</li> <li><strong>3_BRS_Air Quality_Baseline (urban scale/ PM2.5 concentrations)</strong><br> file: brs_pm2.mat<br> Annual PM2.5 average concentrations (µg/m^3) from URBAIR model (considering all the emission sectors: transport, industrial and IRCI) plus the background concentrations from the WRF-CAMx-SA system. The file contains X, Y coordinates from the LCP Clicurb coordinate system.</li> <li><strong>3_BRS_NO2_AQ_latlong</strong><br> file: brs_no2_latlong.rar<br> The shapefile includes total NO2 concentrations (µg/m^3) , as well as concentrations by sector (transport, IRCI and industrial). Coordiante system: WGS1984</li> <li><strong>3_BRS_PM10_AQ_latlong</strong><br> file: brs_pm10_latlong.rar<br> The shapefile includes total PM10 concentrations (µg/m^3) , as well as concentrations by sector (transport, IRCI and industrial). Coordiante system: WGS1984</li> <li><strong>3_BRS_PM2_AQ_latlong</strong><br> file: brs_pm2_latlong.rar<br> The shapefile includes total PM2 concentrations (µg/m^3) , as well as concentrations by sector (transport, IRCI and industrial). Coordiante system: WGS1984</li> <li><strong>3_BRS_Air Quality_Baseline (urbanscale-report)</strong><br> file: brs_aq_urbanscale_report.pdf<br> This report provides a brief overview oh the methodology used. It presents an analysis of concentration fields for NO2, PM10, PM2.5 of the total and by modeled sectors, it also includes an analysis of the source contribution and for the maximum values.</li> <li><strong>3_BRS_Air Quality Scenarios_urban scale NO2 matrix</strong><br> file: brs_no2_scenarios.mat<br> Annual NO2 average concentrations (µg/m^3) from URBAIR model, considering the impact of all scenarios in all the emission sectors: transport, industrial and IRCI, together with the background concentrations. The file contains X, Y coordinates, together with the total annual average concentrations for BAU, scenarios S1, S2, and S3 from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>3_BRS_Air Quality Scenarios_ urban scale PM10 matrix</strong><br> file: brs_pm10_scenarios.mat<br> Annual PM10 average concentrations (µg/m^3) from URBAIR model, considering the impact of all scenarios in all the emission sectors: transport, industrial and IRCI, together with the background concentrations. The file contains X, Y coordinates, together with the total annual average concentrations for BAU, scenarios S1, S2, and S3 from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>3_BRS_Air Quality Scenarios_urban scale PM2 matrix</strong><br> file: brs_pm2_scenarios.mat<br> Annual PM2.5 average concentrations (µg/m^3) from URBAIR model, considering the impact of all scenarios in all the emission sectors: transport, industrial and IRCI, together with the background concentrations. The file contains X, Y coordinates, together with the total annual average concentrations for BAU, scenarios S1, S2, and S3 from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_BRS_Exposure_EU_Baseline NO2 matrix</strong><br> file: brs_no2_exposureeu_baseline.mat<br> Population potentially exposed to the annual NO2 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 40 ug/m^3 for the baseline year.</li> <li><strong>4_BRS_Exposure_EU_Baseline PM10 matrix</strong><br> file: brs_pm10_exposureeu_baseline.mat<br> Population potentially exposed to the annual PM10 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 40 ug/m^3 for the baseline year.</li> <li><strong>4_BRS_Exposure_WHO_Baseline PM10 matrix</strong><br> file: brs_pm10_exposurewho_baseline.mat<br> Population potentially exposed to the annual PM10 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the WHO annual guideline value of 20 ug/m^3 for the baseline year.</li> <li><strong>4_BRS_Exposure_EU_Baseline PM2 matrix</strong><br> file: brs_pm2_exposureeu_baseline.mat<br> Population potentially exposed to the annual PM2.5 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 25 ug/m^3 for the baseline year.</li> <li><strong>4_BRS_Exposure_WHO_Baseline PM2 matrix</strong><br> file: brs_pm2_exposurewho_baseline.mat<br> Population potentially exposed to the annual PM2.5 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the WHO annual guideline value of 10 ug/m^3 for the baseline year.</li> <li><strong>4_BRS_Exposure_EU_Scenarios NO2 matrix</strong><br> file: brs_no2_exposureeu_scenarios.mat<br> Population potentially exposed to the annual NO2 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 40 ug/m^3 for BAU, scenarios S1, S2, and S3 from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_BRS_Exposure_EU_Scenarios PM10 matrix</strong><br> file: brs_pm10_exposureeu_scenarios.mat<br> Population potentially exposed to the annual PM10 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 40 ug/m^3 for BAU, scenarios S1, S2, and S3 from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_BRS_Exposure_WHO_Scenarios PM10 matrix</strong><br> file: brs_pm10_exposurewho_scenarios.mat<br> Population potentially exposed to the annual PM10 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the WHO annual guideline value of 20 ug/m^3 for BAU, scenarios S1, S2, and S3 from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_BRS_Exposure_EU_Scenarios PM2 matrix</strong><br> file: brs_pm2_exposureeu_scenarios.mat<br> Population potentially exposed to the annual PM2.5 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the EU annual legal limit value of 25 ug/m^3 for BAU, scenarios S1, S2, and S3 from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>4_BRS_Exposure_WHO_Scenarios PM2 matrix</strong><br> file: brs_pm2_exposurewho_scenarios.mat<br> Population potentially exposed to the annual PM2.5 average concentrations. The file contains X, Y coordinates, together with the total number of inhabitants, and the total number of inhabitants in each grid cell with an annual concentration exceeding the WHO annual guideline value of 10 ug/m^3 for BAU, scenarios S1, S2, and S3 from the SDW, as well as the FUPS for the time-window 2025, 2035, and 2050.</li> <li><strong>5_BRS_Health_Statistics</strong><br> file: brs_health-analysis.xlsx<br> demographics and population data to calculate the health statistics</li> <li><strong>5_BRS_Health_Scenarios</strong><br> file: summary_results_hia_brs.xlsx<br> Health-related impacts (selected mortality and morbidity endpoints) related to exposure to PM2.5, NO2, and PM10, considering concentration-response functions and baseline concentrations recommended by WHO.</li> <li><strong>6_BRS_Carbon Footprint_Baseline</strong><br> file: ech.ma.15-fr2-wp5-carbon-footprint-ed2.pdf<br> This document reports about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities. The goal of the task is to integrate in the overall model a specific module to compute the carbon footprint of the cities and in particular its scope is to: • Review existing carbon footprinting methodologies • Establish best methodology and relevant emission factors. • Apply footprinting methodologies to six pilot cities based on activity data from previous tasks</li> <li><strong>6_BRS_Carbon Footprint_Baseline</strong><br> file: area_cf_bristol_2015.csv<br> Carbon footprint for Bristol Baseline</li> <li><strong>6_BRS_Carbon Footprint_BAU_Scenarios</strong><br> file: ech.ma.15-fr4-wp5-carbon-footprint-future-ed3-.pdf<br> This document reports about the WP5 Task 5.2.4 Carbon Footprint module activities related to BAU and scenario definition. The module integrates in the overall model the Carbon Footprint evaluation. Another report1 describes methodology and results to integrate in the overall model the specific module to compute the carbon footprint of the cities. In this report methodology and results are reported for: • BAU "business as usual": future situation without any policy interventions beyond what is decided upon at this point with 5-time horizons: 2020, 2025, 2030, 2035 and 2050; • Scenario: added policy interventions to the BAU, same time horizon as results from Stakeholder Dialogue Workshop; • Unified Policy Scenario: final scenario as a results of Policy Workshop.</li> <li><strong>6_BRS_Carbon Footprint_BAU_2025</strong><br> file: 6_brs_carbon-footprint_bau_2025.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2025) footprinting results, in Business As Usual scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_BAU_2035</strong><br> file: 6_brs_carbon-footprint_bau_2035.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2035) footprinting results, in Business As Usual scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_BAU_2050</strong><br> file: 6_brs_carbon-footprint_bau_2050.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2050) footprinting results, in Business As Usual scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S1_2025</strong><br> file: 6_brs_carbon-footprint_s1_2025.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2025) footprinting results, in S1 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S1_2035</strong><br> file: 6_brs_carbon-footprint_s1_2035.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2035) footprinting results, in S1 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S1_2050</strong><br> file: 6_brs_carbon-footprint_s1_2050.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2050) footprinting results, in S1 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S2_2025</strong><br> file: 6_brs_carbon-footprint_s2_2025.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2025) footprinting results, in S2 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S2_2035</strong><br> file: 6_brs_carbon-footprint_s2_2035.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2035) footprinting results, in S2 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S2_2050</strong><br> file: 6_brs_carbon-footprint_s2_2050.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2050) footprinting results, in S2 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S3_2025</strong><br> file: 6_brs_carbon-footprint_s3_2025.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2025) footprinting results, in S3 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S3_2035</strong><br> file: 6_brs_carbon-footprint_s3_2035.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2035) footprinting results, in S3 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_S3_2050</strong><br> file: 6_brs_carbon-footprint_s3_2050.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2050) footprinting results, in S3 scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_UPS_2025</strong><br> file: 6_brs_carbon-footprint_ups_2025.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2025) footprinting results, in UPS scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_UPS_2035</strong><br> file: 6_brs_carbon-footprint_ups_2035.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2035) footprinting results, in UPS scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> <li><strong>6_BRS_Carbon Footprint_UPS_2050</strong><br> file: 6_brs_carbon-footprint_ups_2050.csv<br> This dataset reports results about the WP5 Task 5.2.8 Carbon footprint methodologies & estimation for the pilot cities module. The module integrates in the overall model a specific module to compute the carbon footprint of the cities. In particular the dataset reports future (2050) footprinting results, in UPS scenario, evaluated during the project as described in "6_BRS_Carbon Footprint_BAU_Scenarios" document.</li> </ul>
Biodiversity impact assessment considering land use intensities and fragmentation
<p>The data provide supplementary information for the paper entitled "Biodiversity impact assessment considering land use intensities and fragmentation".</p><p> </p><p><strong>Coverage of the characterization factors</strong></p><ul><li>5 species groups: plants, amphibians, birds, mammals, and reptiles</li><li>5 broad land use types: cropland, pasture, plantations, managed forests, and urban areas</li><li>3 land use intensities: minimal, light, intense (sometimes, intensity levels had to be merged because the data did not allow to differentiate between them)</li><li>825 terrestrial ecoregions of the world (according to WWF / Olson et al. 2001)</li></ul><p> </p><p><strong>Files</strong></p><p>Main data</p><ul><li>CF.csv: characterization factors (CFs) for ecoregions and 5 species groups</li></ul><p>Taxonomically aggregated data</p><ul><li>CF_kingdom.csv: CFs aggregated from 5 species groups to plant and animal kingdoms</li><li>CF_domain.csv: CFs aggregated from plant and animal kingdoms to the domain of Eukaryota</li></ul><p>Spatially aggregated data</p><ul><li>CF_country.csv: CFs aggregated from ecoregions to countries</li><li>CF_global.csv: CFs aggregated from ecoregions to the globe</li></ul><p>Taxonomically and spatially aggregated data</p><ul><li>CF_kingdom_country.csv: CFs aggregated to countries and plant and animal kingdoms</li><li>CF_domain_country.csv: CFs aggregated to countries and the domain of Eukaryota</li><li>CF_kingdom_global.csv: CFs aggregated to the globe and plant and animal kingdoms</li><li>CF_domain_global.csv: CFs aggregated to the globe and the domain of Eukaryota</li></ul><p> </p><p><strong>Units</strong></p><p>CFs for land occupation: PDF/m2</p><p>CFs for land transformation: PDF⋅yr/m2</p><p> </p><p><strong>Columns</strong></p><ul><li>realm: 2-letter code to identify one of 8 biogeographical realms</li><li>biome: ID to identify one of 14 biomes</li><li>eco_id: ID to identify the ecoregion, combining numbers for the realm, biome, and ecoregion within each biome nested within each realm</li><li>eco_name: ecoregion name</li><li>species_group: species group</li><li>kingdom: kingdom as a taxonomic rank</li><li>habitat_id: ID to link to the land use type and intensity as used in land_use.tif. An ID with .5 represents a merged land use class considering the two habitats with the IDs when rounding the value both up and down.</li><li>habitat: land use type and intensity</li><li>CF_*: characterization factor</li><li>*_occ*: land occupation</li><li>*_tra*: land transformation</li><li>*_avg*: average approach</li><li>*_mar*: marginal approach</li><li>*_reg: regional relative species loss</li><li>*_glo: global relative species loss</li><li>*_rsd: relative standard deviation as a measure of spatial uncertainty due to aggregation (only concerns country and globally aggregated CFs)</li><li>quality_*: data quality, distinguishing between original estimates and the use of proxies</li><li>objectid: object id of the country</li><li>iso3cd: iso3 code of the country</li><li>romnam: romanized name of the country</li><li>m49code: M49 code of the country, a standard code used by the United Nations</li><li>weighting: aspect based on which the CFs were weighted (only concerns globally aggregated CFs)</li></ul><p> </p><p><strong>Data quality</strong></p><ul><li>original: original estimate (for globally aggregated CFs: mostly original estimates, proxies only considered in areas with current land use)</li><li>proxy_intensity: intensity level was missing; CF was derived from another CF of the same ecoregion and land use type but different intensity level and scaled to the right intensity level</li><li>proxy_type: land use type was missing; CF was derived from the average regional CFs for light use in the same biome and the ecoregion-specific GEP and scaled to the right intensity level if needed</li><li>proxy_gep: global extinction probability (GEP) was missing (only concerns CFs for global relative species loss); GEP estimated based on average GEP per area unit in the same biome and the ecoregion area</li><li>proxy_partial: some species groups were missing but not all (only concerns taxonomically aggregated CFs); aggregation done based on partly original estimates and partly proxies</li><li>proxy_neighbours: country was missing (only concerns country-aggregated CFs); values were estimated based on the average of the three nearest neighbouring countries</li><li>proxy: proxies were considered even in areas without current land use (only concerns globally aggregated CFs)</li></ul><p>Note: proxies in country-aggregated CFs apply to at least one of the ecoregions overlapping with the country and not necessarily all ecoregions</p><p> </p><p><strong>Land use type and intensity data</strong></p><p>Raster file: land_use.tif</p><p>Spatial resolution: 0.08333333, 0.08333333 (x, y)</p><p>Spatial extent: -180, 180, -90, 90 (xmin, xmax, ymin, ymax)</p><p>Coordinate reference system: WGS 84 (EPSG:4326)</p><p> </p><p>Codes</p><ol><li>Primary_vegetation_Minimal (incl. sparse/no vegetation)</li><li>Cropland_Intense</li><li>Cropland_Light</li><li>Cropland_Minimal</li><li>Managed_forest_Intense</li><li>Managed_forest_Light</li><li>Managed_forest_Minimal</li><li>Pasture_Intense</li><li>Pasture_Light</li><li>Pasture_Minimal</li><li>Plantation_Intense</li><li>Plantation_Light</li><li>Plantation_Minimal</li><li>Urban_Intense</li><li>Urban_Light</li><li>Urban_Minimal</li></ol>
High quality figures of "Assessing Climate Change Impacts on Crop Yields and Exploring Adaptation Strategies in Northeast China"
<p>This repository provides the figures for the publication "Assessing Climate Change Impacts on Crop Yields and Exploring Adaptation Strategies in Northeast China" in their original resolution, ensuring clarity and high-quality visual representations for readers.</p>
Data for the submitted paper by Yasunari et al., "Comprehensive Impact of Changing Siberian Wildfire Severities on Air Quality, Climate, and Economy: MIROC5 Global Climate Model's Sensitivity Assessments"
<p>The dataset contains some of the outputs from the global climate model experiments by MIROC5 on changing Siberian wildfire severities, the other data used in the paper (see READ_ME files on the data sources), the analyzed data, and the scripts for analyses, which were used in the following submitted paper. Note that this dataset also includes unused data for the paper:</p> <p><br>Yasunari, T. J., D. Narita, T. Takemura, S. Wakabayashi, and A. Takeshima, Comprehensive Impact of Changing Siberian Wildfire Severities on Air Quality, Climate, and Economy: MIROC5 Global Climate Model's Sensitivity Assessments, submitted.</p> <p>Please read the READ_ME files for detailed information in each directory (especially see the "about_figures_and_tables/" directory first). Because of their large sizes, the data were separated into three zipped files.</p>
F I G U R E 2 in Assessing the sub-lethal impacts of insecticides on aphid parasitoids through laboratory-based studies
F I G U R E 2 Mummification rate of Aphidius colemani and Aphelinus abdominalis per aphid alive at 5 days after parasitoid introductions. The horizontal black lines represent the mean aphid mummification rate across all replicates, and the blue boxes represent the 95% credible intervals.
F I G U R E 6 in Assessing the sub-lethal impacts of insecticides on aphid parasitoids through laboratory-based studies
F I G U R E 6 The proportion of female F1 Aphelinus abdominalis and Aphidius colemani adults that emerged from females exposed to insecticides. The horizontal black lines represent the mean emergence rate of females across all replicates, and the blue boxes represent the 95% credible intervals.
F I G U R E 1 in Assessing the sub-lethal impacts of insecticides on aphid parasitoids through laboratory-based studies
F I G U R E 1 Mortality for each parasitoid species following exposure to each treatment after 72 h. The horizontal black lines represent the mean mortality across all replicates, and the blue boxes represent the 95% credible intervals.
F I G U R E 5 in Assessing the sub-lethal impacts of insecticides on aphid parasitoids through laboratory-based studies
F I G U R E 5 Reduction in reproductive capacity estimated for Aphelinus abdominalis and Aphidius colemani following insecticide exposure. The horizontal black lines represent the mean reduced reproductive capacity across all replicates, and the orange boxes represent the 95% credible intervals.
F I G U R E 3 in Assessing the sub-lethal impacts of insecticides on aphid parasitoids through laboratory-based studies
F I G U R E 3 Reduction in parasitism capacity estimated for Aphelinus abdominalis and Aphidius colemani following insecticide exposure. The horizontal black lines represent the mean reduced parasitism capacity across all replicates, and the orange boxes represent the 95% credible intervals.
F I G U R E 4 in Assessing the sub-lethal impacts of insecticides on aphid parasitoids through laboratory-based studies
F I G U R E 4 Emergence rates of F1 Aphelinus abdominalis and Aphidius colemani adults following insecticide exposure. The horizontal black lines represent the mean emergence rates across all replicates, and the blue boxes represent the 95% credible intervals.
POTENTIAL ENVIRONMENTAL IMPACTS OF SOLID WASTE MANAGEMENT IN YOGYAKARTA, INDONESIA: A COMPARATIVE STUDY USING LIFE CYCLE ASSESSMENT
<p>Life Cycle Assessment (LCA) serves as a tool to estimate the potential impacts of a waste management system. Sleman Regency needs a scenario of waste management with a lower environmental impact. The present study aims to determine the potential impact of the existing business as usual (BAU) waste management practice in Sleman Regency and compare it with several alternatives to waste management strategies. The LCA method was applied following ISO 14040 and ISO 14044 standards. The impact was assessed using the CML-1A Baseline and ILCD 2011 Midpoint+ methods, along with data from the Ecoinvent database. In the BAU scenario, the impact values observed in every 1 ton of waste managed were Global Warming Potential (GWP) of 4.90E+03 kg CO2 eq, Acidification Potential (ADP) of 2.78E-03 kg SO2 eq, Eutrophication Potential (EP) of 4.92E-02 kg PO4-eq, Human Toxicity Potential (HTP) of 2.06E+01 kg 1.4 DB eq, and Land Use Potential (LUP) of 4.71E+01 kg C deficit. Processing waste into biomass pellets and Refuse Derived Fuel accompanied by waste reduction could decrease the GWP value to 34.04 kg CO2 eq, ADP to 2.96E-06 kg SO2 eq, EP to 7.33E-05 kg PO4-eq, HTP to 3.70E-04 kg 1.4 DB eq, and LUP to 2.11E-03 kg C deficit. The results of waste management with the lowest impact value can serve as a reference for formulating waste management policies in the study area.</p>
Data to support the publication "The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment" https://doi.org/10.3390/land10090964
<p>Underlying data of soil measurements and analysis by TUC team for the publication “The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment” <a href="https://doi.org/10.3390/land10090964">https://doi.org/10.3390/land10090964</a> from the SoilCare project study sites in Crete. </p> <p>Abstract:</p> <p>The risk of erosion is particularly high in Mediterranean areas, especially in areas that are subject to a not so effective agricultural management–or with some omissions–, land abandonment or wildfires. Soils on Crete are under imminent threat of desertification, characterized by loss of vegetation, water erosion, and subsequently, loss of soil. Several large-scale studies have estimated average soil erosion on the island between 6 and 8 Mg/ha/year, but more localized investigations assess soil losses one order of magnitude higher. An experiment initiated in 2017, under the framework of the SoilCare H2020 EU project, aimed to evaluate the effect of different management practices on the soil erosion. The experiment was set up in control versus treatment experimental design including different sets of treatments, targeting the most important cultivations on Crete (olive orchards, vineyards, fruit orchards). The minimum-to-no tillage practice was adopted as an erosion mitigation practice for the olive orchard study site, while for the vineyard site, the cover crop practice was used. For the fruit orchard field, the crop-type change procedure (orange to avocado) was used. The experiment demonstrated that soil-improving cropping techniques have an important impact on soil erosion, and as a result, on soil water conservation that is of primary importance, especially for the Mediterranean dry regions. The demonstration of the findings is of practical use to most stakeholders, especially those that live and work with the local land.</p>
Data sets for assessing potential CC impacts on the activity of the Vögelsberg landslide
<p>Bias-corrected air temperature and precipitation time series (RCM sample from EURO CORDEX) for Kleinvolderberg station near the Vögelsberg landslide (OAL-AT) under RCP8.5, monthly water balance components derived from an empirical model for six elevation steps under current and potential land cover conditions for 1950-2100, median monthly displacement and current hydrological forcing of the Vögelsberg landslide</p>
Assessing the Impact of Pest Monitoring Traps on Bombus griseocollis (Hymenoptera: Apidae) Colony Growth and Development
<p>Insect traps use visual and olfactory cues to attract target pests; however, they vary in their specificity and often unintentionally capture non-target beneficial insects (bycatch), including <em>Bombus</em>. Concerns have been expressed that bycatch may contribute to <em>Bombus</em> mortality and the consequential loss of pollination services. Here, we quantified the impact of trap captures on <em>Bombus griseocollis</em> colony growth and development by evaluating the following four treatments: colonies paired with traps, colonies paired with traps and pheromone lures, traps and pheromone lures (but no colonies), and colonies with no trap and no lure. Trap contents were collected biweekly to determine <em>B. griseocollis </em>capture rates. Colony growth and development data were collected weekly by weighing colonies and recording foraging activity. Based on microsatellite polymerase chain reaction (PCR) amplification, three <em>B. griseocollis </em>were collected from released colonies, while the remaining five were residents within the environment. Given the low number of <em>B. griseocollis </em>workers collected, any differences in colony weight change and active foraging were likely not a result of pest monitoring trap captures. However, trap captures could have a greater impact by interfering with functional diversity, colony establishment, and pollination services, emphasizing the need for additional research. Building on this research will provide a more comprehensive view of the impact of pest monitoring traps on <em>Bombus </em>populations, which could minimize risk to pollinator populations and pollination services.</p>
Data from: A hierarchical model for jointly assessing ecological and anthropogenic impacts on animal demography
<p>1. The management of sustainable harvest of animal populations is of great ecological and conservation importance. Development of formal quantitative tools to estimate and mitigate the impacts of harvest on animal populations has positively impacted conservation efforts.</p> <p>2. The vast majority of existing harvest models, however, do not simultaneously estimate ecological and harvest impacts on demographic parameters and population trends. Given that the impacts of ecological drivers are often equal to or greater than the effects of harvest, and can covary with harvest, this disconnect has the potential to lead to flawed inference.</p> <p>3. In this study, we used Bayesian hierarchical models and a 43-year capture-mark-recovery dataset from 404,241 female mallards (Anas platyrhynchos) released in the North American midcontinent to estimate mallard demographic parameters. Further, we model the dynamics of waterfowl hunters and habitat, and the direct and indirect effects of anthropogenic and ecological processes on mallard demographic parameters.</p> <p>4. We demonstrate that density-dependence, habitat conditions, and harvest can simultaneously impact demographic parameters of female mallards, and discuss implications for existing and future harvest management models.</p> <p>5. Our results demonstrate the importance of controlling for multicollinearity among demographic drivers in harvest management models, and provide evidence for multiple mechanisms that lead to partial compensation of mallard harvest. We provide a novel model structure to assess these relationships that may allow for improved inference and prediction in future iterations of harvest management models across taxa.</p>
Scenario data for article: Effects of the energy transition on environmental impacts of cobalt supply: A prospective Life Cycle Assessment study on future supply of cobalt
<p>This dataset contains the background data for the paper '<a href="https://onlinelibrary.wiley.com/doi/10.1111/jiec.13258">Effects of the energy transition on environmental impacts of the cobalt supply: A prospective Life Cycle Assessment study on the future cobalt supply</a>' as published in the Journal of Industrial Ecology.</p> <p><strong>Please note that an easier to use version of this data for LCA is available through the Premise (<a href="https://www.sciencedirect.com/science/article/pii/S136403212200226X">Sacchi et al. 2022</a>) Community Scenarios <a href="https://github.com/premise-community-scenarios/cobalt-perspective-2050">here</a>.</strong> This version is slightly adapted to fit into the Premise architecture and is compatible with ecoinvent v3.8 cutoff.</p> <p>This repository contains:</p> <ul> <li>Python code + readme to model the variables, generate presamples packages and generate LCA results based on those. (code folder)</li> <li>Input and output data for Variables 1-3 (files 1&2)</li> <li>Presamples excel sheets for each variable/scenario combination (file 3)</li> <li>Summarized LCA results (the full results can be generated through running the code provided) (file 4)</li> <li>Full LCA results used for the contribution analysis (file 5)</li> <li>Underlying data for each of the figures (file 6)</li> </ul> <p>We refer to the paper (linked above) for more information on the study.<br> </p> <p><strong>License: </strong>The metal supply scenario data is licensed under the CC-BY 4.0 license.</p> <p><strong>Access: </strong>Open access</p> <p> </p> <p>[Changelog]</p> <p>2023-03-23 - 1.3.1: Add link to Premise Community scenario page.<br> 2022-05-18 - 1.3.0: Fix minor error in data files '4 - LCA results' and '6 - Figure data' in demand amounts for total impacts.<br> 2022-04-06 - 1.2.1: Included link to article after publication<br> 2022-03-30 - 1.2.0: Included underlying figure data<br> 2022-01-24 - 1.1.1: Opened repository after paper acceptance<br> 2021-11-26 - 1.1.0: Update of code to comply with peer-review<br> 2021-07-12 - 1.0.0: Set-up of repository</p>
SMDRM Model for Impact Assessment
<p>This model is the result of the training of a Convolutional Neural Network. Training datasets were tweets collected during historical floods in Sao Paulo (PT,EN) and Barcelona (ES,EN). </p>
Assessing the impacts of conservation volunteering on participant wellbeing: a review protocol
<p>Original search titles for the review : </p> <p>Assessing the impacts of conservation volunteering on participant wellbeing:</p> <p>a review protocol</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.