Energy Efficiency and GHG Emissions: Prospective Scenarios for the Aluminium Industry

This study examines the possibilities for energy efficiency and GHG emission improvements in the European aluminium industry. The first part of the study presents the status quo of the industry in the EU28 and Iceland by compiling a database of existing plants with their production characteristics and the best available and innovative technologies (BATs/ITs). A model EU is then developed to simulate the trend in each plant towards 2050. The use of the model in different scenarios allows the analysis of the cost-effectiveness of investments in BATs/ITs. The results show that in absolute terms, for the whole industry the energy consumption and direct GHG emissions can decrease from 2010 to 2050 by 21% and 66%, respectively. And, in almost all scenarios, for the primary aluminium production there is a convergence in the reduction of specific energy consumption and direct GHG emissions of 23% and 72%, respectively. Since most of the savings come from technologies that are in early stages of research, there is a clear need of a decided push and of creating the right conditions to make these potential savings happen.JRC.F.6-Energy Technology Policy Outloo

Light-absorbing carbon in Europe – Measurement and modelling, with a focus on residential wood combustion emissions

The atmospheric concentration of elemental carbon (EC) in Europe during the six-year period 2005–2010 has been simulated with the EMEP MSC-W model. The model bias compared to EC measurements was less than 20% for most of the examined sites. The model results suggest that fossil fuel combustion is the dominant source of EC in most of Europe but that there are important contributions also from residential wood burning during the cold seasons and, during certain episodes, also from open biomass burning (wildfires and agricultural fires). The modelled contributions from open biomass fires to ground level concentrations of EC were small at the sites included in the present study, <3% of the long-term average of EC in PM10. The modelling of this EC source is subject to many uncertainties, and it was likely underestimated for some episodes. EC measurements and modelled EC were also compared to optical measurements of black carbon (BC). The relationships between EC and BC (as given by mass absorption cross section, MAC, values) differed widely between the sites, and the correlation between observed EC and BC is sometimes poor, making it difficult to compare results using the two techniques and limiting the comparability of BC measurements to model EC results. A new bottom-up emission inventory for carbonaceous aerosol from residential wood combustion has been applied. For some countries the new inventory has substantially different EC emissions compared to earlier estimates. For northern Europe the most significant changes are much lower emissions in Norway and higher emissions in neighbouring Sweden and Finland. For Norway and Sweden, comparisons to source-apportionment data from winter campaigns indicate that the new inventory may improve model-calculated EC from wood burning. Finally, three different model setups were tested with variable atmospheric lifetimes of EC in order to evaluate the model sensitivity to the assumptions regarding hygroscopicity and atmospheric ageing of EC. The standard ageing scheme leads to a rapid transformation of the emitted hydrophobic EC to hygroscopic particles, and generates similar results when assuming that all EC is aged at the point of emission. Assuming hydrophobic emissions and no ageing leads to higher EC concentrations. For the more remote sites, the observed EC concentration was in between the modelled EC using standard ageing and the scenario treating EC as hydrophobic. This could indicate too-rapid EC ageing in the model in relatively clean parts of the atmosphere

Variations in tropospheric submicron particle size distributions across the European continent 2008-2009

Beddows, D. C. S. ... et. al.-- 22 pages, 11 figures, 1 table, supplementary material related to this article is available online at http://www.atmos-chem-phys.net/14/4327/2014/acp-14-4327-2014-supplement.pdfClusteranalysis of particle number size distributions frombackground sites across Europeis presented. This generated a total of nine clusters of particle size distributions which could be further combined into two main groups, namely: a south-to-north category (four clusters) and a west-to-east category (five clusters). The first group was identified as most frequently being detected inside and around northern Germany and neighbouring countries, showing clear evidence of local afternoon nucleation and growth events that could be linked to movement of air masses from south to north arriving ultimately at the Arctic contributing to Arctic haze.The second group of particle size spectra proved to have narrower size distributions and collectively showed a dependence of modal diameter upon the longitude of the site (west to east) at which they were most frequently detected.These clusters indicated regional nucleation (at the coastal sites) growing to larger modes further inland. The apparent growth rate of the modal diameter was around 0.6-0.9 nm h-1. Four specific air mass back-trajectories were successively taken as case studies to examine in real time the evolution of aerosol size distributions across Europe. While aerosol growth processes can be observed as aerosol traverses Europe, the processes are often obscured by the addition of aerosol by emissions en route. This study revealed that some of the 24 stations exhibit more complex behaviour than others, especially when impacted by local sources or a variety of different air masses. Overall, the aerosol size distribution clustering analysis greatly simplifies the complex data set and allows a description of aerosol aging processes, which reflects the longer-term average development of particle number size distributions as air masses advect across Europe. © 2014 Author(s)The National Centre for Atmospheric Science is funded by the UK Natural Environment Research Council. This work was also supported by the European Union EUCAARI (Contract Ref. 036833) and EUSAAR (Contract Ref. 026140) research projectsPeer Reviewe

A 1990 global emission inventory of anthropogenic sources of carbon monoxide on 1° × 1° developed in the framework of EDGAR/GEIA

A global emission inventory of carbon monoxide (CO) emissions with 1° × 1° latitude-longitude resolution was compiled for 1990 on a sectoral basis. The sectoral sources considered include large-scale biomass burning (29%, of which savanna burning, 18%, and deforestation, 11%), fossil fuel combustion (27%, predominantly in road transport), biofuel combustion (19%, predominantly fuelwood combustion), agricultural waste burning (21%) and industrial process sources (4%). The inventory was compiled using mostly national statistics as activity data, emission factors at global or country level, and specific grid maps to convert, by sector, country total emissions to the 1° × 1° grid. A special effort was made to compile a global inventory of biofuel use, since this was considered to be a significant source on a global level, and a major source in some regions such as India and China. The global anthropogenic source of CO in 1990 is estimated at about 974 Tg CO yr-1. The inventory is available on a sectoral basis on a 1° × 1° grid for input to global atmospheric models and on a regional/country basis for policy analysis. © 1999 Elsevier Science Ltd. All rights reserved

Brake wear from vehicles as an important source of diffuse copper pollution

In this article we show that brake wear from road traffic vehicles is an important source of atmospheric (participate) copper concentrations in Europe. Consequently, brake wear also contributes significantly to deposition fluxes of copper to surface waters. We estimated the copper emission due to brake wear to be 2.4 kiloton per year. For comparison, the official database for Europe (without brake wear) totals 2.6 kiloton per year. In Western Europe the brake wear emissions dominate the total emission of copper. Using the spatially resolved emission data, copper distributions over Europe were calculated with the LOTOS-EUROS model. Without brake wear the model underestimates observed copper concentrations by a factor of 3, which is in accordance with other studies. Including the brake wear emissions largely removes the bias. We find that 75% of the atmospheric copper input in the North Sea may be due to brake wear. We estimate that about 25% of the total copper input in the Dutch part of the North Sea stems from brake wear. Although the estimated brake wear copper emission is associated with a large uncertainty, it significantly improves our understanding of the copper cycle in the environment. © IWA Publishing 2007

TNO-MACC_II emission inventory; a multi-year (2003-2009) consistent high-resolution European emission inventory for air quality modelling

Abstract. Emissions to air are reported by countries to EMEP. The emissions data are used for country compliance checking with EU emission ceilings and associated emission reductions. The emissions data are also necessary as input for air quality modelling. The quality of these “official” emissions varies across Europe. As alternative to these official emissions, a spatially explicit high-resolution emission inventory (7×7 km) for UNECE-Europe for all years between 2003 and 2009 for the main air pollutants was made. The primary goal was to supply air quality modellers with the input they need. The inventory was constructed by using the reported emission national totals by sector where the quality is sufficient. The reported data were analysed by sector in detail, and completed with alternative emission estimates as needed. This resulted in a complete emission inventory for all countries. For particulate matter, for each source emissions have been split in coarse and fine particulate matter, and further disaggregated to EC, OC, SO4, Na and other minerals using fractions based on the literature. Doing this at the most detailed sectoral level in the database implies that a consistent set was obtained across Europe. This allows better comparisons with observational data which can, through feedback, help to further identify uncertain sources and/or support emission inventory improvements for this highly uncertain pollutant. The resulting emission data set was spatially distributed consistently across all countries by using proxy parameters. Point sources were spatially distributed using the specific location of the point source. The spatial distribution for the point sources was made year-specific. The TNO-MACC_II is an update of the TNO-MACC emission data set. Major updates included the time extension towards 2009, use of the latest available reported data (including updates and corrections made until early 2012) and updates in distribution map

Toxaphene: An analysis of possible problems in the aquatic environment

This report reviews the most recent information on toxaphene. The presence, fate and effects in the aquatic environment will be analysed, and the (international) policy goals will be discussed. ______________________________________________________ Dit rapport bevat een overzicht van de meest recente informatie over toxafeen. Het beschrijft het voorkomen, het lot en de effecten van toxafeen in het aquatische milieu, evenals een overzicht van het beleid ten aanzien van toxafeen

Overview of greenhouse gas emission databases and validation activities in The Netherlands

An overview is presented of the Dutch emission registration activities with respect to greenhouse gases. This in-cludes the Dutch Pollutant Emission Register (PER) and the global Emission Database for Global Atmospheric Re-search (EDGAR). Objectives. tanks. methods and information systems present in PER and EDGAR are highlighted. Special attention is given to methods used to derive greenhouse gas emissions from biogenie sources in agriculture. Within the tramework of the Dutch National Research Programme on Global Air Pollution and Climate Change, a project has been initiated to establish and validate a detailed CH4 emission database for the Netherlands and North-western Europe (MEI DAT). Methods and results of this project are presented as wen, again focusing of emission from biogenic sources in agriculture. The METDAT emission database is validated using model and measurement resuits of CH.1 air concentrations. Moreover. an assessment is made of differences with official emission data pub-lished in so-called Nationai Communications of the different countries. An outlook is given on near-future activities in relation to PER. EDGAR and METDAT. respectively

Impact of a future H2 transportation on atmospheric pollution in Europe

Hydrogen (H2) is being explored as a fuel for passenger vehicles; it can be used in fuel cells to power electric motors or burned in internal combustion engines. In order to evaluate the potential influence of a future H2-based road transportation on the regional air quality in Europe, we implemented H2 in the atmospheric transport and chemistry model LOTOS-EUROS. We simulated the present and future (2020) air quality, using emission scenarios with different proportions of H2 vehicles and different H2 leakage rates. The reference future scenario does not include H2 vehicles, and assumes that all present and planned European regulations for emissions are fully implemented. We find that, in general, the air quality in 2020 is significantly improved compared to the current situation in all scenarios, with and without H2 cars. In the future scenario without H2 cars, the pollution is reduced due to the strict European regulations: annually averaged CO, NOx and PM2.5 over the model domain decrease by 15%, 30% and 20% respectively. The additional improvement brought by replacing 50% or 100% of traditionally-fueled vehicles by H2 vehicles is smaller in absolute terms. If 50% of vehicles are using H2, the CO, NOx and PM2.5 decrease by 1%, 10% and 1% respectively, compared to the future scenario without H2 cars. When all vehicles run on H2, then additional decreases in CO, NOx and PM2.5 are 5%, 40%, and 5% relative to the no-H2 cars future scenario. Our study shows that H2 vehicles may be an effective pathway to fulfill the strict future EU air quality regulations.O3 has a more complicated behavior - its annual average decreases in background areas, but increases in the high-NOx area in western Europe, with the decrease in NOx. A more detailed analysis shows that the population exposure to high O3 levels decreases nevertheless. In all future scenarios, traffic emissions account for only a small proportion of the total anthropogenic emissions, thus it becomes more important to better regulate emissions of non-traffic sectors. Although atmospheric H2 increases significantly in the high-leakage scenarios considered, the additional H2 added into the atmosphere does not have a significant effect on the ground level air pollution in Europe

Deep convolutional neural networks for surface coal mines determination from sentinel-2 images

Coal is a principal source of energy and the combustion of coal supplies around one-third of the global electricity generation. Coal mines are also an important source of CH4 emissions, the second most important greenhouse gas. Monitoring CH4 emissions caused by coal mining using earth observation will require the exact location of coal mines. This paper aims to determine surface coal mines from satellite images through deep learning techniques by treating them as a land use/land cover classification task. This is achieved using Convolutional Neural Networks (CNN) that has proven to be capable of complex land use/land cover classification tasks. With a list of known coal mine locations from various countries, a training dataset of “Coal Mine” and “No Coal Mine” image patches is prepared using Sentinel-2 satellite images with 13 spectral bands. Various pre-trained CNN network architectures (VGG, ResNet, DenseNet) are trained and validated with our prepared coal mine dataset of 3500 “Coal Mine” and 3000 “No Coal Mine” image patches. After several experiments with the VGG network combined with transfer learning is found to be an optimal model for this task. Classification accuracy of 98% has been achieved for the validation dataset of the pre-trained VGG architecture. The model produces more than 95% overall accuracy when tested on unseen satellite images from different countries outside the training dataset and evaluated against visual classification