Julius Vira

Mortality due to Vegetation-Fire Originated PM2.5 Exposure in Europe - Assessment for the Years 2005 and 2008.

Background: Vegetation fires can release substantial quantities of fine particles (PM2.5), which are harmful to health. The fire smoke may be transported over long distances and can cause adverse health effects over wide areas. Objective: We aimed to assess annual mortality attributable to short-term exposures to vegetation fire–originated PM2.5 in different regions of Europe. Methods: PM2.5 emissions from vegetation fires in Europe in 2005 and 2008 were evaluated based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data on fire radiative power. Atmospheric transport of the emissions was modeled using the System for Integrated modeLling of Atmospheric coMposition (SILAM) chemical transport model. Mortality impacts were estimated for 27 European countries based on a) modeled daily PM2.5 concentrations and b) population data, both presented in a 50 × 50 km2 spatial grid; c) an exposure–response function for short-term PM2.5 exposure and daily nonaccidental mortality; and d) country-level data for background mortality risk. Results: In the 27 countries overall, an estimated 1,483 and 1,080 premature deaths were attributable to the vegetation fire–originated PM2.5 in 2005 and 2008, respectively. Estimated impacts were highest in southern and eastern Europe. However, all countries were affected by fire-originated PM2.5, and even the lower concentrations in western and northern Europe contributed substantially (~ 30%) to the overall estimate of attributable mortality. Conclusions: Our assessment suggests that air pollution caused by PM2.5 released from vegetation fires is a notable risk factor for public health in Europe. Moreover, the risk can be expected to increase in the future as climate change proceeds. This factor should be taken into consideration when evaluating the overall health and socioeconomic impacts of these fires. Citation: Kollanus V, Prank M, Gens A, Soares J, Vira J, Kukkonen J, Sofiev M, Salonen RO, Lanki T. 2017. Mortality due to vegetation fire–originated PM2.5 exposure in Europe—assessment for the years 2005 and 2008. Environ Health Perspect 125:30–37; http://dx.doi.org/10.1289/EHP194

Cleaner fuels for ships provide public health benefits with climate tradeoffs

We evaluate public health and climate impacts of low-sulphur fuels in global shipping. Using high-resolution emissions inventories, integrated atmospheric models, and health risk functions, we assess ship-related PM2.5 pollution impacts in 2020 with and without the use of low-sulphur fuels. Cleaner marine fuels will reduce ship-related premature mortality and morbidity by 34 and 54%, respectively, representing a ~ 2.6% global reduction in PM2.5 cardiovascular and lung cancer deaths and a ~3.6% global reduction in childhood asthma. Despite these reductions, low-sulphur marine fuels will still account for ~250k deaths and ~6.4 M childhood asthma cases annually, and more stringent standards beyond 2020 may provide additional health benefits. Lower sulphur fuels also reduce radiative cooling from ship aerosols by ~80%, equating to a ~3% increase in current estimates of total anthropogenic forcing. Therefore, stronger international shipping policies may need to achieve climate and health targets by jointly reducing greenhouse gases and air pollution.Aerosol pollution from shipping contributes to cooling but also leads to premature mortality and morbidity. Here the authors combine emission inventories, atmospheric models and health risk functions to show how cleaner marine fuels will reduce premature deaths and childhood asthma but results in larger warming.

Comparison of tropospheric NO 2 columns from MAX-DOAS retrievals and regional air quality model simulations

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) tropospheric NO2 column retrievals from four European measurement stations are compared to simulations from five regional air quality models which contribute to the European regional ensemble forecasts and reanalyses of the operational Copernicus Atmosphere Monitoring Service (CAMS). Compared to other observational data usually applied for regional model evaluation, MAX-DOAS data are closer to the regional model data in terms of horizontal and vertical resolution, and multiple measurements are available during daylight, so that, for example, diurnal cycles of trace gases can be investigated. In general, there is good agreement between simulated and retrieved NO2 column values for individual MAX-DOAS measurements with correlations between 35 % and 70 % for individual models and 45 % to 75 % for the ensemble median for tropospheric NO2 vertical column densities (VCDs), indicating that emissions, transport and tropospheric chemistry of NOx are on average well simulated. However, large differences are found for individual pollution plumes observed by MAX-DOAS. Most of the models overestimate seasonal cycles for the majority of MAX-DOAS sites investigated. At the urban stations, weekly cycles are reproduced well, but the decrease towards the weekend is underestimated and diurnal cycles are overall not well represented. In particular, simulated morning rush hour peaks are not confirmed by MAX-DOAS retrievals, and models fail to reproduce observed changes in diurnal cycles for weekdays versus weekends. The results of this study show that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings. Published by Copernicus Publications on behalf of the European Geosciences Union. 2796 A.-M. Blechschmidt et al.: Comparison of NO2 columns from MAX-DOAS and regional air quality models

A Long-Term Re-Analysis of Atmospheric Composition and Air Quality

The paper presents a global-to-mesoscale model re-analysis of atmospheric composition for the period of 1980–2014 and the first outcome of the evaluation. The goals of the re-analysis were to assess the multi-decade evolution of atmospheric composition and air quality at several spatial scales and to evaluate the performance of SILAM dispersion model in this large-scale exercise. The dataset covered troposphere and the stratosphere, main anthropogenic pollutants and had a special line for natural constituents, such as sea salt and pollen. This dataset forms the starting point for episodic and meso-to-local-scale studies, which will refine its predictions.

Comparing Air Quality Forecast and a Reanalysis: Improvements Due to Chemical Data Assimilation and Better NWP Forcing

The paper discusses the operational experience of European-scale AQ hind- and fore-casting with the SILAM dispersion model and compares the performance of the two setups. Two parallel lines of daily AQ assessment in Europe have been established: the 72 h long stand-alone forecast and a previous-day 24 h hindcast followed by a 72 h forecast. In the hindcasting mode, 3D-VAR based data assimilation is used to refine the initial fields for O3, NO2 and SO2. The standalone forecast, on the other hand, is initialized from the previous forecast without data assimilation. According to preliminary statistics, the best score improvement in the forecast is obtained for O3, while only minor or no improvement is seen for SO2 and NO2. In addition, the data assimilation of gas-phase species has a visible effect on predictions of secondary inorganic aerosols.

Modelling Assessment of Atmospheric Composition and Air Quality in Eastern and Southern Asia

Current chapter outlines the model-based assessment of air pollution in Eastern and Southern Asia. The chemistry transport model SILAM, which covers the main sources of the air pollutants in the region, was applied to evaluate their influence on spatial and temporal characteristics of the regional pollution pattern. We showed that, apart from the anthropogenic sources, air pollution in several parts of Eastern and Southern Asia is dominated by other sources, such as desert dust and vegetation fires. In particular, South-East Asia and Eastern Russia are heavily impacted by the biomass burning smoke, largely from agriculture fires. Fire-induced pollution is also episodically significant in several provinces of China.

Uncertainties of Top-Down Fire Emission Estimates at Regional and Global Scales

Top-down emission estimation via inverse dispersion modelling is frequently used for estimation of emission from wild-land fires. The approach, efficiently constraining the emission from fires, also has major uncertainties, which are illustrated here with a few examples of the Integrated System for wild-land Fires (IS4FIRES).

Inverse Modelling of Volcanic SO2 Emissions Using the 4D-Var Method

This study compares two approaches for data assimilation in forecasting volcanic plumes of sulphuric dioxide released in the eruption of Grimsvotn in 2011. The first data assimilation approach is source term inversion, where the data are used for estimating an effective source term. In the second approach, the assimilation proceeds in cycles, and the observations are used for updating the initial condition. In both cases, the SO2 retrievals by the OMI instrument are assimilated. The results indicate that the source term inversion is more effective at constraining the three-dimensional structure of the plume. However, as the transport distance increases, updating the initial condition provides a better fit to the column observations.

Evaluation of Organic Aerosol and Its Precursors in the SILAM Model

Volatility basis-set (VBS) was implemented in the atmospheric chemistry and transport model SILAM for modelling organic aerosol (OA). We present the evaluation of the concentrations of OA and its precursors against observations available in the EBAS database. SILAM simulations with biogenic and anthropogenic emissions from different inventories and different assumptions about the chemical composition of the VOC emissions and OA volatility are analyzed. The contributions of different precursors to the total OA are evaluated.

Modelling the Budget of Main Atmospheric Pollutants in Paris Region

The paper evaluates the air pollution budget of Paris by means of multi-domain nested simulations with detailed import-export fluxes delivered by the SILAM model. It is demonstrated that as a grand-total, Paris is a net exporter of nitrogen compounds, several VOCs and primary PM emitted from anthropogenic sources or produced chemically on a short time scale (a few hours). The city is a net importer of NH3. The budgets of pollutants with long lifetime and high free-troposphere concentrations (CO, O3) were shown to depend on height.