Assessing Transport of PM Pollution from Europe to the Arctic

Arctic pollution is a topic of high priority on the global agenda, especially due to its connection with the rapid warming the Arctic is experiencing. During recent decades, the Arctic has warmed about 1 degree Celsius per decade, which is almost double the global average warming rate. Part of the warming is due to the deposition of black carbon to the ice, which decreases the surface albedo and thus leads to melting of the ice. This study investigates the European origins of Arctic primary fine particulate matter (PPM2.5) and black carbon aerosol (BC). Five years of monthly averaged output from the EMEP Chemical Transport Model are analyzed to calculate the source-receptor relationships of PPM2.5 from European countries to the Arctic. These source-receptor relationships are then applied to BC emissions inventories in order to investigate the relevance of different source regions of Arctic BC both for the present and for future scenarios. Russia (European part) and Norway are identified as the largest European contributors to Arctic PPM2.5 and BC, together accounting for more than 50 percent of the European PPM2.5 input to the Arctic. The relative importance of these two countries for future contributions to Arctic BC depends on the emissions scenario used. As a rather unexpected result, ship emissions from the north-east Atlantic Ocean are among the largest contributors to Arctic PPM and BC, and are predicted to rank third by 2030. On a sectoral basis, emissions from the household sector dominate over industrial and other emissions. In addition to the emissions already accounted for in the EMEP model runs, vegetation fires are shown to play a significant role. Furthermore, the variability of Arctic PPM2.5 levels, transfer coefficients, and contributions is investigated. Large annual cycles of sectoral contributions can be observed, which are partly due to annual cycles of emissions and partly to meteorological variability. The North Atlantic Oscillation is shown to influence Arctic PPM2.5 concentrations in the sense that under highly positive NAO conditions, Arctic PPM levels are significantly enhanced by up to factors of 20 and more, as compared to highly negative NAO conditions

Institutional Rank and Budget Efficiency in Academic Libraries

This study describes budget trends at Harvard University, Stanford University, Montana State University at Bozeman and New Mexico State University at Las Cruces. These financial trends are connected to the Shanghai Jiao Tong Academic Ranking of World Universities' rankings from 2004-2008. The connected data indicates that effective budget patterns include keeping collection and materials budgets as large as possible without sacrificing from a human resources perspective. The data also suggests that universities should aim to allocate at least three percent of the total organization's budget to the library system. After establishing the connection between healthy libraries and parent organizations, it is also recommended that libraries treat employees more like business people who are responsible for the well-being of the organization than like librarians whose primary concern is short-term

Impact of NOx vehicle emission standards failure on Air Quality in Europe

Vehicle exhaust emission standards have been tightened in the EU for several decades now, in order to protect health and the environment. This has led to a substantial decrease in total pollutant emissions, despite the growing volumes of passenger and freight transport. However, national emissions, particularly of NOx, exceed the ceilings accorded under the Gothenburg Protocol of the UNECE's Convention on Long-Range Transboundary Air Pollution (LRTAP) (EEA 2012) in twelve EU Member States. The main reasons for such exceedances are that more diesel cars have been sold than originally predicted when fixing the targets, and that diesel cars emit much more than expected under real-world driving conditions. The latter appears as a consequence of the effort to achieve high fuel efficiency. While this has largely helped to control CO2 emissions, it was to the detriment of NOx. In this study we estimate what the impact of the different vehicle emission standards has been so far and to predict what the impact of upcoming emission standards will be in the future, using the best current knowledge on road transport activity statistics and emission factors in Europe. We present several sensitivity calculations to reflect the considerable uncertainty about the real-driving NOx emissions of diesel light duty vehicles. The results of this work can be useful in designing both limits for upcoming standards but also in assessing the impact of deviating from such limits. This is necessary in both deciding on the next steps of emission control policy and to relevant air quality prediction models

Ozone concentrations and damage for realistic future European climate and air quality scenarios

Ground level ozone poses a significant threat to human health from air pollution in the European Union. While anthropogenic emissions of precursor substances (NOx, NMVOC, CH4) are regulated by EU air quality legislation and will decrease further in the future, the emissions of biogenic NMVOC (mainly isoprene) may increase significantly in the coming decades if short-rotation coppice plantations are expanded strongly to meet the increased biofuel demand resulting from the EU decarbonisation targets. This study investigates the competing effects of anticipated trends in land use change, anthropogenic ozone precursor emissions and climate change on European ground level ozone concentrations and related health and environmental impacts until 2050. The work is based on a consistent set of energy consumption scenarios that underlie current EU climate and air quality policy proposals: a current legislation case, and an ambitious decarbonisation case. The Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) integrated assessment model was used to calculate air pollutant emissions for these scenarios, while land use change because of bioenergy demand was calculated by the Global Biosphere Model (GLOBIOM). These datasets were fed into the chemistry transport model LOTOS-EUROS to calculate the impact on ground level ozone concentrations. Health damage because of high ground level ozone concentrations is projected to decline significantly towards 2030 and 2050 under current climate conditions for both energy scenarios. Damage to plants is also expected to decrease but to a smaller extent. The projected change in anthropogenic ozone precursor emissions is found to have a larger impact on ozone damage than land use change. The increasing effect of a warming climate (+2–5 °C across Europe in summer) on ozone concentrations and associated health damage, however, might be higher than the reduction achieved by cutting back European ozone precursor emissions. Global action to reduce air pollutant emissions is needed to make sure that ozone damage in Europe decreases towards the middle of this century

Compliance with EU air quality limit values - A first set of sensitivity and optimization analyses

This report provides additional information to the baseline and optimized scenarios that have been developed for the review and revision of the Thematic Strategy on Air Pollution in TSAP Reports #6 and #7. The report examines the implications of different assumptions on the implementation of the Euro-6 emission standards for light duty diesel vehicles on compliance with NO2 air quality limit values in Europe. For the baseline assumptions of the TSAP-2012 baseline scenario, i.e., a decline of real-driving emission in two stages down to 1.5 times the value of test cycle value in 2018, it is estimated that almost all AIRBASE stations that have been modelled in this exercise would achieve the NO2 limit values by 2030 at the latest. However, in the least optimistic sensitivity case, i.e., under the assumption of a failure of Euro-6 (no change in real-driving emissions compared to Euro-4), about 100 out of the 1173 AIRBASE monitoring stations would still remain in non-compliance with the limit value in 2030. A second analysis examines the optimization results presented in TSAP Report #7 in more detail and provides, for each of the optimized scenarios, the sectors in which emission reductions would occur in the cost-optimal cases. These emission reductions will lead to lower background pollution concentrations in Europe, which will affect PM10 levels within cities. It is estimated, e.g., for the high ambition case, that in 2030 the number of stations for which non-compliance is robustly estimated will decline by about 20%. The number of stations for which compliance seems possible but not certain would fall by 30% compared to the baseline. In contrast, the optimized scenarios do not yield significant improvements in the compliance with NO2 limit values, as the series of scenarios did not consider further measures for road vehicle emissions. Finally, an initial assessment of current and future emissions of mercury in Europe suggests for the TSAP-2012 baseline a decline of Hg emissions of 22% in 2020 and about 30% in 2030 (relative to 2005), mainly as a consequence of lower coal use in the power sector. Full implementation of the available technical emission controls, especially of certain measures to reduce PM emissions, could eliminate Hg emissions in the EU by another third, so that in 2030 the total release of Hg in the EU could be more than 50% lower than in 2005

A Scalable Approach to Modelling Health Impacts of Air Pollution Based on Globally Available Data

Integrated assessment of air pollution and its impacts typically requires pre-calculated atmospheric transfer relations on a fine spatial resolution. While such concepts have been applied successfully for Europe and other regions with high data coverage, extending calculations to world regions with low local data availability is challenging and needs to be based on globally available data sets. Here we introduce a scalable approach which has been developed to expand the calculations of health impacts from exposure to ambient fine particulate matter (PM2.5) in the Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) integrated assessment model to (almost) any desired region on the globe, depending on actual requirements for policy analysis. We use global sensitivity simulations of the EMEP atmospheric chemistry transport model to derive linear transfer coefficients at a resolution of 0.5 degrees. A major challenge lies in the realistic representation of inner urban PM2.5 concentrations, which depend to a large extent on local pollution sources on scales below grid resolution. We derive sub-grid concentration increments from emission densities of primary PM from low-level sources, based on (almost) globally available gridded population data with approximately 100m resolution. From ambient PM2.5 concentrations, increased risk of mortality is then calculated following the methodology of the Global Burden of Disease studies. We have implemented and validated the described approach for India, China, and Indonesia, with extensions to other G-20 member countries underway. Health impact projections under different energy policy scenarios are discussed. Due to the inherent treatment of urban areas, the effects of urbanization trends are captured explicitly, which lead to higher average population exposure as people move into polluted cities

Semantic data integration from Multi Linked Model Framework

Model integration is becoming increasingly important due to the requirements for multi-scale and multi-objective assessment and decision making. Moreover, instead of incorporating all complex related information system models that are relevant for different related aspects into one super-model, a multi linked model framework has been proposed to extract data and output from multiple linked models into the coherent data warehouse, which respects the interdependency of data from different model as well as additional knowledge already contained in its existing data cubes. In this paper, first the multi linked model framework is defined in a very formal manner. The mathematical abstract specification provides the basis for handling data exchange among various linked models as well as data from those models integrated into a data warehouse. In this context, an ETL (extract- transform-load) process has been specified to integrate data from linked models. A new feature of our approach in comparison with other ETL processes is that our transformations also require input from the data warehouse, i.e. exchanging data from linked models with the data warehouse. Hereafter, the data warehouse is developed in term of multidimensional database. While each model may keep very detailed and intermediate ('raw') data and results, the data warehouse only contains integrated data that are appropriate for the task at hand. As a proof of concept, the multi linked model framework is used to develop a common knowledge pool in term of data warehouse on the representation of socio-economic heterogeneity, and strengthen the information flows among multi linked models, e.g. population projections, energy-economic, and air pollution integrated assessment models etc., which have been developed at International Institute for Applied Systems Analysis (IIASA)