Emissions of Particulate Matter in the Netherlands and abroad

Concerns research on emission data used as input for atmospheric dispersion modelling in the framework of the RIVM project "Air Pollution and Health" and the Netherlands Environmental Outlook 4. The data collected apply to primary particulate matter, SO2, NOX and NH3 for Europe and the Netherlands for base and future years. Economic developments and abatement measures used to calculate future emission trends are explained. A first analysis has been made of the uncertainties involved in the estimates of particulate matter emissions. On the basis of these reported emission data we recommend focusing future emission research on: i) closer analysis of the uncertainties in present emission estimates, ii) the subsequent effect of uncertainties in emission estimates on dispersion modelling, and iii) increasing the insight into the quality of present emission data and probable missing sources of data. This can be achieved through measurements at emission sources and a stronger linking of emission inventories to air quality monitoring in general.Dit rapport documenteert emissiebestanden in het kader van het project Luchtverontreiniging en Gezondheid en de Vierde Milieuverkenning ten behoeve van verspreidingsberekeningen. Het betreft emissiebestanden voor basis- en toekomstjaren voor primair fijn stof en NH3, SO2 en NOx als precursors van secundair fijn stof, voor binnen- en buitenland. In het rapport worden de economische scenario's en maatregelen die ten grondslag liggen aan de berekeningen voor toekomstjaren toegelicht. Ook wordt een eerste analyse gemaakt van onzekerheden in zowel binnen- als buitenlandse emissiegegevens voor fijn stof. Geadviseerd wordt vervolgonderzoek te richten op i) nadere analyse van onzekerheden in huidige emissiebestanden , ii) doorwerking daarvan, en van de onzekerheden in modelparameters in het verspreidingsmodel, in de berekende fijn-stofconcentraties en iii) het vergroten van het inzicht in de kwaliteit van huidige emissieschattingen, en eventuele hiaten daarin, door metingen aan de bron en versterkte koppeling van emissieinventarisaties aan luchtkwaliteitsmetingen

Emissions of Particulate Matter in the Netherlands and abroad

Dit rapport documenteert emissiebestanden in het kader van het project Luchtverontreiniging en Gezondheid en de Vierde Milieuverkenning ten behoeve van verspreidingsberekeningen. Het betreft emissiebestanden voor basis- en toekomstjaren voor primair fijn stof en NH3, SO2 en NOx als precursors van secundair fijn stof, voor binnen- en buitenland. In het rapport worden de economische scenario's en maatregelen die ten grondslag liggen aan de berekeningen voor toekomstjaren toegelicht. Ook wordt een eerste analyse gemaakt van onzekerheden in zowel binnen- als buitenlandse emissiegegevens voor fijn stof. Geadviseerd wordt vervolgonderzoek te richten op i) nadere analyse van onzekerheden in huidige emissiebestanden , ii) doorwerking daarvan, en van de onzekerheden in modelparameters in het verspreidingsmodel, in de berekende fijn-stofconcentraties en iii) het vergroten van het inzicht in de kwaliteit van huidige emissieschattingen, en eventuele hiaten daarin, door metingen aan de bron en versterkte koppeling van emissieinventarisaties aan luchtkwaliteitsmetingen.Concerns research on emission data used as input for atmospheric dispersion modelling in the framework of the RIVM project "Air Pollution and Health" and the Netherlands Environmental Outlook 4. The data collected apply to primary particulate matter, SO2, NOX and NH3 for Europe and the Netherlands for base and future years. Economic developments and abatement measures used to calculate future emission trends are explained. A first analysis has been made of the uncertainties involved in the estimates of particulate matter emissions. On the basis of these reported emission data we recommend focusing future emission research on: i) closer analysis of the uncertainties in present emission estimates, ii) the subsequent effect of uncertainties in emission estimates on dispersion modelling, and iii) increasing the insight into the quality of present emission data and probable missing sources of data. This can be achieved through measurements at emission sources and a stronger linking of emission inventories to air quality monitoring in general.DGM/L

Transportscenario's voor Nederland in 2030, een beschrijving van de scenario's in het kader van het OECD-project 'Environmental Sustainable Transport'

Het rapport beschrijft een referentie-scenario ('business-as-usual scenario') en drie scenario's die voldoen aan de criteria die binnen het OECD-project 'Environmental Sustainable Transport' (EST) zijn gesteld om duurzaam verkeer en vervoer te kunnen bereiken in het jaar 2030. In het OECD-project zijn drie criteria met betrekking tot het reduceren van emissies gesteld die gelden voor alle pilotstudies: CO2 -80%, NOx -90%, VOS -90% tussen 1990 en 2030. Drie aanvullende criteria met betrekking tot PM10-emissies, geluid en ruimtegebruik in 2030 zijn door de afzonderlijke landen ingevuld. De drie EST-scenario's zijn: (1) een scenario met alleen technische maatregelen ('high-technology scenario'), (2) een scenario met alleen mobiliteitsmaatregelen ('capacity-constraint scenario') en (3) een scenario met de 'optimale' combinatie van technische en mobiliteitsmaatregelen ('optimum-combination scenario'). Geconcludeerd wordt dat door alleen technische maatregelen, alleen mobiliteitsmaatregelen of een combinatie van technische en mobiliteitsmaatregelen de EST-criteria kunnen worden gehaald, mits sterke technologische ontwikkelingen en/of gedragsaanpassingen en wijzigingen van sociale en economische structuren op internationaal niveau worden verondersteld. Indien alleen technische maatregelen worden verondersteld, dan zullen kostbare technische maatregelen moeten worden geimplementeerd. Indien alleen mobiliteitsmaatregelen worden verondersteld, dan zullen deze grote sociale, culturele en ruimtelijke gevolgen hebben voor de samenleving. Een combinatie van technische en gedragsmaatregelen resulteert in minder stringente maatregelen, en zal waarschijnlijk het grootste potentiele draagvlak in de samenleving hebben.The Environmental Sustainable Transport (EST) project contains a business-as-usual scenario and three EST scenarios: (i) one 'high-technology' scenario containing only technological changes, (ii) one 'capacity-constraint' containing only mobility changes, (iii) one 'optimum-combination' scenario containing the 'optimum' combination of technological and mobility changes. Six EST criteria have been established for the purpose of planning more sustainable transportation systems. Three criteria based on reductions (%) of the polluting components: CO2 by 80%, NOx by 90%, VOC by 90% between 1990 and 2030, are common to the participation countries. Three additional EST criteria specified by the participating countries are related to particulate matter emissions, noise and land use in 2030. Concluding, the EST criteria can be met with: (i) only technological changes, (ii) only mobility changes or (iii) the combination of both technological and mobility changes, if a high increase in techological developments and/or very stringent behavioural adaptions and changes in spatial and economic structures at an international level are assumed. If the criteria have to met by technological measures, a very high increase in technological research is needed and expensive techniques will have to be developed and implemented. If the EST criteria are to be realised only by mobility changes, there is likely to be an impact on macro-economic developments and there will be social, cultural and land use implications. By combining technical and mobility changes, less stringent changes need to be made in the transport sector; impact on other sectors will also be less. These measures will probably also have the best potential societal support.DGM/L

Clinical presentation, disease course, and outcome of COVID-19 in hospitalized patients with and without pre-existing cardiac disease : a cohort study across 18 countries

AIMS: Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality. METHODS AND RESULTS: We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existing heart disease and in-hospital mortality. A total of 16 511 patients with COVID-19 were included (21.1% aged 66-75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male, and often had other comorbid conditions when compared with those without. Mortality was higher in patients with cardiac disease (29.7%; n = 1545 vs. 15.9%; n = 1797). However, following multivariable adjustment, this difference was not significant [adjusted risk ratio (aRR) 1.08, 95% confidence interval (CI) 1.02-1.15; P = 0.12 (corrected for multiple testing)]. Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure (aRR 1.19, 95% CI 1.10-1.30; P < 0.018) particularly for severe (New York Heart Association class III/IV) heart failure (aRR 1.41, 95% CI 1.20-1.64; P < 0.018). None of the other heart disease subtypes, including ischaemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in <1% of patients. CONCLUSION: Considerable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare during hospitalization

Clinical presentation, disease course, and outcome of COVID-19 in hospitalized patients with and without pre-existing cardiac disease: a cohort study across 18 countries

AIMS: Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality. METHODS AND RESULTS: We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existing heart disease and in-hospital mortality. A total of 16 511 patients with COVID-19 were included (21.1% aged 66-75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male, and often had other comorbid conditions when compared with those without. Mortality was higher in patients with cardiac disease (29.7%; n = 1545 vs. 15.9%; n = 1797). However, following multivariable adjustment, this difference was not significant [adjusted risk ratio (aRR) 1.08, 95% confidence interval (CI) 1.02-1.15; P = 0.12 (corrected for multiple testing)]. Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure (aRR 1.19, 95% CI 1.10-1.30; P < 0.018) particularly for severe (New York Heart Association class III/IV) heart failure (aRR 1.41, 95% CI 1.20-1.64; P < 0.018). None of the other heart disease subtypes, including ischaemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in <1% of patients. CONCLUSION: Considerable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare during hospitalization