ALBERT

Description: In the fall of 2011, iodine-131 (131I) was detected at several radionuclide monitoring stations in central Europe. After investigation, the International Atomic Energy Agency (IAEA) was informed by Hungarian authorities that 131I was released from the Institute of Isotopes Ltd. in Budapest, Hungary. It was reported that a total activity of 342 GBq of 131I was emitted between 8 September and 16 November 2011. In this study, we use the ambient concentration measurements of 131I to determine the location of the release as well as its magnitude and temporal variation. As the location of the release and an estimate of the source strength became eventually known, this accident represents a realistic test case for inversion models. For our source reconstruction, we use no prior knowledge. Instead, we estimate the source location and emission variation using only the available 131I measurements. Subsequently, we use the partial information about the source term available from the Hungarian authorities for validation of our results. For the source determination, we first perform backward runs of atmospheric transport models and obtain source-receptor sensitivity (SRS) matrices for each grid cell of our study domain. We use two dispersion models, FLEXPART and Hysplit, driven with meteorological analysis data from the global forecast system (GFS) and from European Centre for Medium-range Weather Forecasts (ECMWF) weather forecast models. Second, we use a recently developed inverse method, least-squares with adaptive prior covariance (LS-APC), to determine the 131I emissions and their temporal variation from the measurements and computed SRS matrices. For each grid cell of our simulation domain, we evaluate the probability that the release was generated in that cell using Bayesian model selection. The model selection procedure also provides information about the most suitable dispersion model for the source term reconstruction. Third, we select the most probable location of the release with its associated source term and perform a forward model simulation to study the consequences of the iodine release. Results of these procedures are compared with the known release location and reported information about its time variation. We find that our algorithm could successfully locate the actual release site. The estimated release period is also in agreement with the values reported by IAEA and the reported total released activity of 342 GBq is within the 99 % confidence interval of the posterior distribution of our most likely model.

Description: The EDGARv4.3.1 (Emissions Database for Global Atmospheric Research) global anthropogenic emissions inventory of gaseous (SO2, NOx, CO, non-methane volatile organic compounds and NH3) and particulate (PM10, PM2.5, black and organic carbon) air pollutants for the period 1970–2010 is used to develop retrospective air pollution emissions scenarios to quantify the roles and contributions of changes in energy consumption and efficiency, technology progress and end-of-pipe emission reduction measures and their resulting impact on health and crop yields at European and global scale. The reference EDGARv4.3.1 emissions include observed and reported changes in activity data, fuel consumption and air pollution abatement technologies over the past 4 decades, combined with Tier 1 and region-specific Tier 2 emission factors. Two further retrospective scenarios assess the interplay of policy and industry. The highest emission STAG_TECH scenario assesses the impact of the technology and end-of-pipe reduction measures in the European Union, by considering historical fuel consumption, along with a stagnation of technology with constant emission factors since 1970, and assuming no further abatement measures and improvement imposed by European emission standards. The lowest emission STAG_ENERGY scenario evaluates the impact of increased fuel consumption by considering unchanged energy consumption since the year 1970, but assuming the technological development, end-of-pipe reductions, fuel mix and energy efficiency of 2010. Our scenario analysis focuses on the three most important and most regulated sectors (power generation, manufacturing industry and road transport), which are subject to multi-pollutant European Union Air Quality regulations. Stagnation of technology and air pollution reduction measures at 1970 levels would have led to 129 % (or factor 2.3) higher SO2, 71 % higher NOx and 69 % higher PM2.5 emissions in Europe (EU27), demonstrating the large role that technology has played in reducing emissions in 2010. However, stagnation of energy consumption at 1970 levels, but with 2010 fuel mix and energy efficiency, and assuming current (year 2010) technology and emission control standards, would have lowered today's NOx emissions by ca. 38 %, SO2 by 50 % and PM2.5 by 12 % in Europe. A reduced-form chemical transport model is applied to calculate regional and global levels of aerosol and ozone concentrations and to assess the associated impact of air quality improvements on human health and crop yield loss, showing substantial impacts of EU technologies and standards inside as well as outside Europe. We assess that the interplay of policy and technological advance in Europe had substantial benefits in Europe, but also led to an important improvement of particulate matter air quality in other parts of the world.

Description: This paper deals with the urban land-surface impact (i.e., the urban canopy meteorological forcing; UCMF) on extreme air pollution for selected central European cities for present-day climate conditions (2015–2016) using three regional climate-chemistry models: the regional climate models RegCM and WRF-Chem (its meteorological part), the chemistry transport model CAMx coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. Most of the studies dealing with the urban canopy meteorological forcing on air pollution focused on change in average conditions or only on a selected winter and/or summer air pollution episode. Here we extend these studies by focusing on long-term extreme air pollution levels by looking at not only the change in average values, but also their high (and low) percentile values, and we combine the analysis with investigating selected high-pollution episodes too. As extreme air pollution is often linked to extreme values of meteorological variables (e.g., low planetary boundary layer height, low winds, high temperatures), the urbanization-induced extreme meteorological modifications will be analyzed too. The validation of model results show reasonable model performance for regional-scale temperature and precipitation. Ozone is overestimated by about 10–20 µg m−3 (50 %–100 %); on the other hand, extreme summertime ozone values are underestimated by all models. Modeled nitrogen dioxide (NO2) concentrations are well correlated with observations, but results are marked by a systematic underestimation up to 20 µg m−3 (−50 %). PM2.5 (particles with diameter ≤2.5 µm) are systematically underestimated in most of the models by around 5 µg m−3 (50 %–70 %). Our results show that the impact on extreme values of meteorological variables can be substantially different from that of the impact on average ones: low (5th percentile) temperature in winter responds to UCMF much more than average values, while in summer, 95th percentiles increase more than averages. The impact on boundary layer height (PBLH), i.e., its increase is stronger for thicker PBLs and wind speed, is reduced much more for strong winds compared to average ones. The modeled changes in ozone (O3), NO2 and PM2.5 show the expected pattern, i.e., increase in average 8 h O3 up to 2–3 ppbv, decrease in daily average NO2 by around 2–4 ppbv and decrease in daily average PM2.5 by around −2 µg m−3. Regarding the impact on extreme (95th percentile) values of these pollutants, the impact on ozone at the high end of the distribution is rather similar to the impact on average 8 h values. A different picture is obtained however for extreme values of NO2 and PM2.5. The impact on the 95th percentile values is almost 2 times larger than the impact on the daily averages for both pollutants. The simulated impact on extreme values further well corresponds to the UCMF impact simulated for the selected high-pollution episodes. Our results bring light to the principal question: whether extreme air quality is modified by urban land surface with a different magnitude compared to the impact on average air pollution. We showed that this is indeed true for NO2 and PM2.5, while in the case of ozone, our results did not show substantial differences between the impact on mean and extreme values.

Description: The Eurodelta-Trends multi-model chemistry-transport experiment has been designed to facilitate a better understanding of the evolution of air pollution and its drivers for the period 1990–2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional scale air quality. The present paper formulates the main scientific questions and policy issues being addressed by the Eurodelta-Trends modelling experiment with an emphasis on how the design and technical features of the modelling experiment answer these questions. The experiment is designed in three tiers with increasing degree of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000 and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emissions, (ii) chemical boundary conditions and (iii) meteorology complements it. The most demanding tier consists two complete time series from 1990 to 2010, simulated using either time varying emissions for corresponding years or constant emissions. Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and three models have – to date – completed the full set of simulations (and 21-year trend calculations have been performed by four models). The modelling results are publicly available for further use by the scientific community. The main expected outcomes are (i) an evaluation of the models performances for the three reference years, (ii) an evaluation of the skill of the models in capturing observed air pollution trends for the 1990–2010 time period, (iii) attribution analyses of the respective role of driving factors (emissions/boundary conditions/meteorology), (iv) a dataset based on a multi-model approach, to provide more robust model results for use in impact studies related to human health, ecosystem and radiative forcing.

Description: Urban surfaces due to specific geometry and physical properties bring modified transport of momentum, moisture and heat between them and the air above and perturb the radiative, thermal and mechanical balance resulting in changed meteorological condition (e.g. the UHI – urban heat island phenomenon). From an air quality perspective, many studies argue that one of the most important changes is the increased turbulence enhancing vertical mixing of pollutants above cities, although increased temperatures and wind stilling play an important role too. Using the regional climate model RegCM4 coupled to chemistry transport model CAMx over central Europe we study how urban surfaces affect the vertical turbulent transport of selected pollutants through modifications of the vertical eddy diffusion coefficient (Kv). For the period of 2007–2011 and over central Europe numerous experiments are carried out in order to evaluate the impact of six different methods for Kv calculation on the surface concentrations as well as vertical profiles of ozone and PM2.5 over selected cities (Prague and Berlin). Three cascading domains are set up at 27 km, 9 km and 3 km resolutions, which further enables to analyze the sensitivity to model grid resolution. Numerous experiments are performed where urban surfaces are considered or replaced by rural ones in order to isolate the urban canopy meteorological forcing. Apart from the well pronounced and expected impact on temperature (increases up to 2 °C) and wind (decreases up to −2 m s−1) there is strong impact on vertical eddy diffusion in all of the six Kv methods. The Kv enhancement ranges from a few 0.5 up to 30 m2 s−1 at the surface and from 1 to 100 m2 s−1 at higher levels depending on the methods, while the turbulent kinetic energy (TKE) based methods produce the largest impact. The range of impact on the vertical eddy diffusion coefficient propagates to a range of ozone (O3) increase of 0.4 to 4 ppbv near the surface in both summer and winter, while at higher levels, decreases occur from a few −0.4 ppbv to as much as −2 ppbv. In case of PM2.5, enhanced vertical eddy diffusion leads to decrease of near surface concentrations ranging from almost zero to −1 μg m−3 in summer and to decreases from −0.5 to −2 μg m−3 in winter. Comparing these results to the total-impact, i.e. to the impact of all considered urban meteorological changes, we can conclude that much of the overall urban meteorological forcing is explained by acting of the enhanced vertical eddy diffusion, which counterweights the opposing effects of other components of this forcing (temperature, humidity and wind impact). The results further show that this conclusion holds regardless of the resolution chosen and in both the warm and cold part of the year. Our study demonstrates the dominant role of turbulent transport of pollutants above urban areas and stresses the need for further investigation how variation of urban land-use influence the pollutant transport from the urban canopy.

Description: Formaldehyde (HCHO) being a high-yield product in the oxidation of most volatile organic compounds (VOCs) emitted by fires, vegetation and anthropogenic activities, satellite observations of HCHO are well-suited to inform us on the spatial and temporal variability of the underlying VOC sources. The long-record of space-based HCHO column observations from the Ozone Monitoring Instrument (OMI) is used to infer emission flux estimates from pyrogenic and biogenic volatile organic compounds (VOCs) on the global scale over 2005–2013. This is realized through the method of source inverse modelling, which consists in the optimization of emissions in a chemistry-transport model (CTM) in order to minimize the discrepancy between the observed and modelled HCHO columns. The top-down fluxes are derived in the global CTM IMAGESv2 by an iterative minimization algorithm based on the full adjoint of IMAGESv2, starting from a priori emission estimates provided by the newly released GFED4s (Global Fire Emission Database, version 4s) inventory for fires, and by the MEGAN-MOHYCAN inventory for isoprene emissions. The top-down fluxes are compared to two independent inventories for fire (GFAS and FINNv1.5) and isoprene emissions (MEGAN-MACC and GUESS-ES). The inversion indicates a moderate decrease (ca. 20 %) of the average annual global fire and isoprene emissions, from 2028 TgC in the a priori to 1653 TgC for burnt biomass, and from 343 to 272 Tg for isoprene fluxes. Those estimates are acknowledged to depend on the accuracy of formaldehyde data, as well as on the assumed fire emission factors and the oxidation mechanisms leading to HCHO production. Strongly decreased top-down fire fluxes (30–50 %) are inferred in the peak fire season in Africa, and during years with strong a priori fluxes associated to forest fires in Amazonia (in 2005, 2007 and 2010), bushfires in Australia (in 2006 and 2011), and peat burning in Indonesia (in 2006 and 2009), whereas generally increased fluxes are suggested in Indochina and during the 2007 fires in Southern Europe. Moreover, changes in fire seasonal patterns are suggested, e.g. the seasonal amplitude is reduced over Southeast Asia. In Africa, the inversion indicates increased fluxes due to agricultural fires, and decreased maxima when natural fires are dominant. The top-down fire emissions are much better correlated with MODIS fire counts than the a priori inventory in regions with small and agricultural fires, indicating that the OMI-based inversion is well-suited to assess the associated emissions. Regarding biogenic sources, significant reductions of isoprene fluxes are inferred in tropical ecosystems (30–40 %), suggesting overestimated basal emission rates in those areas in the bottom-up inventory, whereas strongly positive isoprene emission updates are derived over semi-arid and desert areas, especially in Southern Africa and Australia. This finding suggests that the parameterization of the soil moisture stress used in MEGAN greatly exaggerates the flux reduction due to drought in those regions. The isoprene emission trends over 2005–2013 are often enhanced after optimization, with positive top-down trends in Siberia (4.2 %/yr) and Eastern Europe (3.9 %/yr), likely reflecting forest expansion and warming temperatures, and negative trends in Amazonia (−2.1 %/yr), South China (−1 %/yr), the United States (−3.7 %/yr), and Western Europe (−3.3 %/yr), which are generally corroborated by independent studies, yet their interpretation warrants further investigation.

Description: In the fall of 2011, iodine-131 (I-131) was detected at several radionuclide monitoring stations in Central Europe. After investigation, the International Atomic Energy Agency (IAEA) was informed by Hungarian authorities that I-131 was released from the Institute of Isotopes Ltd in Budapest, Hungary. It was reported that a total activity of 342 GBq of I-131 was emitted between September 8 and November 16, 2011. In this study, we use the ambient concentration measurements of I-131 to determine the location of the release as well as its magnitude and temporal variation. Although the location of the release became eventually known, its temporal variation is still uncertain and only partial information is available. For our source reconstruction, we use no prior knowledge. Instead, we estimate the source location and emission variation using only the available I-131 measurements. Subsequently, we use the information about the source term for validation of our results. For the source determination, we first perform backward runs of atmospheric transport models and obtain source-receptor-sensitivity (SRS) matrices for each grid cell of our study domain. We use two dispersion models, Flexpart and Hysplit, driven with meteorological analysis data from the global forecast system (GFS) weather forecast model. Second, we use a recently developed inverse method, least-squares with adaptive prior covariance (LS-APC), to determine the I-131 emissions and their temporal variation from the measurements and computed SRS matrices. For each grid cell of our simulation domain, we evaluate the probability that the release was generated in that cell using Bayesian model selection. The model selection procedure also provides information about the most suitable dispersion model for the source term reconstruction. Third, we select the most probable location of the release with its associated source term and perform forward calculation to study the consequences of the iodine release. Results of these procedures are compared with the known release location and reported information about its time variation. We find that our algorithm could successfully locate the actual release site. The estimated release period is also in agreement with the values reported by IAEA, while our estimate for the total released activity (490 GBq) is higher than the reported one (342 GBq). Nevertheless, even using our larger source term, dose amounts were very low and never exceeded regulatory limits.

Description: As formaldehyde (HCHO) is a high-yield product in the oxidation of most volatile organic compounds (VOCs) emitted by fires, vegetation, and anthropogenic activities, satellite observations of HCHO are well-suited to inform us on the spatial and temporal variability of the underlying VOC sources. The long record of space-based HCHO column observations from the Ozone Monitoring Instrument (OMI) is used to infer emission flux estimates from pyrogenic and biogenic volatile organic compounds (VOCs) on the global scale over 2005–2013. This is realized through the method of source inverse modeling, which consists in the optimization of emissions in a chemistry-transport model (CTM) in order to minimize the discrepancy between the observed and modeled HCHO columns. The top–down fluxes are derived in the global CTM IMAGESv2 by an iterative minimization algorithm based on the full adjoint of IMAGESv2, starting from a priori emission estimates provided by the newly released GFED4s (Global Fire Emission Database, version 4s) inventory for fires, and by the MEGAN-MOHYCAN inventory for isoprene emissions. The top–down fluxes are compared to two independent inventories for fire (GFAS and FINNv1.5) and isoprene emissions (MEGAN-MACC and GUESS-ES). The inversion indicates a moderate decrease (ca. 20 %) in the average annual global fire and isoprene emissions, from 2028 Tg C in the a priori to 1653 Tg C for burned biomass, and from 343 to 272 Tg for isoprene fluxes. Those estimates are acknowledged to depend on the accuracy of formaldehyde data, as well as on the assumed fire emission factors and the oxidation mechanisms leading to HCHO production. Strongly decreased top–down fire fluxes (30–50 %) are inferred in the peak fire season in Africa and during years with strong a priori fluxes associated with forest fires in Amazonia (in 2005, 2007, and 2010), bushfires in Australia (in 2006 and 2011), and peat burning in Indonesia (in 2006 and 2009), whereas generally increased fluxes are suggested in Indochina and during the 2007 fires in southern Europe. Moreover, changes in fire seasonal patterns are suggested; e.g., the seasonal amplitude is reduced over southeast Asia. In Africa, the inversion indicates increased fluxes due to agricultural fires and decreased maxima when natural fires are dominant. The top–down fire emissions are much better correlated with MODIS fire counts than the a priori inventory in regions with small and agricultural fires, indicating that the OMI-based inversion is well-suited to assess the associated emissions. Regarding biogenic sources, significant reductions in isoprene fluxes are inferred in tropical ecosystems (30–40 %), suggesting overestimated basal emission rates in those areas in the bottom–up inventory, whereas strongly positive isoprene emission updates are derived over semiarid and desert areas, especially in southern Africa and Australia. This finding suggests that the parameterization of the soil moisture stress used in MEGAN greatly exaggerates the flux reduction due to drought in those regions. The isoprene emission trends over 2005–2013 are often enhanced after optimization, with positive top–down trends in Siberia (4.2 % year−1) and eastern Europe (3.9 % year−1), likely reflecting forest expansion and warming temperatures, and negative trends in Amazonia (−2.1 % year−1), south China (−1 % year−1), the United States (−3.7 % year−1), and western Europe (−3.3 % year−1), which are generally corroborated by independent studies, yet their interpretation warrants further investigation.