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This paper describes the development of emission scenarios for non-CO2 greenhouse gases in the European Union as consistent with the energy scenarios used for the EU Low carbon Roadmap 2050. The analysis includes estimates of technical mitigation potentials and costs for mitigation of these gases until 2050 in the 27 EU member states. Results show that it would be technically possible to cut overall emissions of non-CO2 greenhouse gases by about half between base year 2005 and 2050 in both of the energy scenarios defined. The adoption of mitigation efforts already in the baseline will, however, significantly depend on the expected development in the carbon price levels in the EU-ETS and non-ETS sectors.

Using the GAINS (Greenhouse Gas-Air Pollution Interactions and Synergies) model, we derived Annex I marginal abatement cost curves for the years 2020 and 2030 for three World Energy Outlook baseline scenarios (2007-2009) of the International Energy Agency. These cost curves are presented by country, by greenhouse gas and by sector. They are available for further inter-country comparisons in the GAINS Mitigation Efforts Calculator-a free online tool. We illustrate the influence of the baseline scenario on the shape of mitigation cost curves, and identify key low cost options as well as no-regret priority investment areas for the years 2010-2030. Finally, we show the co-effect of GHG mitigation on the emissions of local air pollutants and argue that these co-benefits offer strong local incentives for mitigation.

This report examines the health and environmental impacts of the TSAP-2012 baseline emission scenarios that have been presented in the TSAP Report #1 to the Stakeholder Expert Group in June 2012. The baseline suggests for the next decades a steady decline of energy-related emissions from industry, households and transport while no significant changes are foreseen for NH3 from agricultural activities. These emission trajectories will lead to significant improvements in air quality. For instance, loss of statistical life expectancy from exposure to fine particulate matter (PM2.5) is expected to decline from 9.6 months in 2000 and 6.9 months in 2010 to 5.5 months in 2020 and 5.0 months in 2030. It is estimated that the number of premature deaths attributable to short-term exposure of ground-level ozone will drop by about 30% by 2020. Ecosystems area where biodiversity is threatened by excess nitrogen deposition will shrink from 1.2 million km2 in 2000 to 900,000 km2 in 2030, and acidification will remain an issue at only four percent of the European forest area. However, by 2020 the baseline improvements for fine particular matter health impacts and eutrophication will fall short of the targets established in the 2005 Thematic Strategy on Air Pollution, while for acidification and ozone these targets will be met. Furthermore, it is unlikely that the baseline development will achieve full compliance with the air quality limit values for PM10 and NO2 throughout Europe. Equally, the baseline scenario will not provide protection against excess nitrogen deposition at almost 50% of the legally protected Natura2000 areas and other protected zones. In addition, the magnitude of air pollution impacts and resulting damage remains substantial. It is estimated that for the baseline in 2030, the European population would still suffer a loss of 210 million life-years and experience 18,000 premature deaths because of ozone exposure. Biodiversity will remain threatened by excess nitro

This report reviews recent developments that are potentially relevant for the control of agricultural emissions in Europe. As a consequence of a several decades long history of ammonia emission controls in agriculture, principles of current methods and techniques have a sound scientific basis that is well proven in practice. No fundamentally new insights and fundamentally new techniques have emerged over the last decade. However, in the last 10 years, the known techniques have been applied at a much larger scale in an increasing number of countries, the practical functioning of these techniques has improved, and costs have declined through learning effects. In several countries specialized contractors have taken over some of the activities (e.g., low-emission manure application), which has substantially reduced costs. For the major sources of agricultural ammonia emissions (i.e., animal manure and urea fertilizer application), a range of emission control options is now proven in practice in more and more countries. Many of these measures are cost-effective, especially when additional synergistic effects are considered. Modified animal feeding, covered slurry storages, low-emission manure and urea fertilizer application techniques are now cost-effective means in many situations. In particular, modified animal feeding can decrease NH3 emissions from all stages of the animal manure management chain, and, at the same time, decrease N2O emissions and odour. Emission reduction efficiencies and costs of these measures are sensitive against chosen reference system and depend on local factors, such as weather and soil conditions, differences in management practices and in the technical performances of abatement measures. Yet, in many countries, there is only limited experience with low-emissions techniques, due to technical, economical and cultural barriers that prohibit their implementation. Information and experience gained in other countries is often not readily accepted

In this chapter we present an integrated model for long term and geographically explicit planning of agricultural activities to meet demands under resource constraints and ambient targets. Environmental, resource and production feasibility indicators permit estimating impacts of agricultural practices on environment to guide agricultural policies regarding production allocation, intensification, and fertilizer application while accounting for local constraints. Physical production potentials of land are incorporated in the model, together with demographic and socio-economic variables and behavioral drivers to reflect spatial distribution of demands and production intensification levels. The application of the model is demonstrated with a case study of nitrogen accounting at the level of China counties. We discuss current intensification trends and estimate the ranges of agricultural impacts on China's environment under plausible pollution mitigation scenarios with a particular focus on nitrogen sources and losses.

The future effects of nitrogen in the environment will depend on the extent of nitrogen use and the practical application techniques of nitrogen in a similar way as in the past. Projections and scenarios are appropriate tools for extrapolating current knowledge into the future. However, these tools will not allow future system turnovers to be predicted.

This paper compares data on N fluxes compiled by Schulze and colleagues, with information available in the literature and publicly available open databases, and finds important discrepancies for a number of such fluxes for Europe (emissions, deposition, aerosol formation of compounds containing N) -- exceeding a factor of two in several cases. A qualitative assessment of the uncertainties of the respective approaches indicates that these differences are beyond the uncertainty margins that can be reasonably attributed to the respective data. We conclude that the results should be used with caution, that agricultural application of N should still be considered to be the largest source of N released to the environment, and that this agricultural N affects soils more strongly than atmospheric deposition, at the European scale.

Environmental policies in Europe have successfully eliminated the most visible and immediate harmful effects of air pollution in the last decades. However, there is ample and robust scientific evidence that even at present rates Europe's emissions to the atmosphere pose a significant threat to human health, ecosystems and the global climate, though in a less visible and immediate way. As many of the low hanging fruits have been harvested by now, further action will place higher demands on economic resources, especially at a time when resources are strained by an economic crisis. In addition, interactions and interdependencies of the various measures could even lead to counter-productive outcomes of strategies if they are ignored. Integrated assessment models, such as the GAINS (Greenhouse gas - Air pollution Interactions and Synergies) model, have been developed to identify portfolios of measures that improve air quality and reduce greenhouse gas emissions at least cost. Such models bring together scientific knowledge and quality-controlled data on future socio-economic driving forces of emissions, on the technical and economic features of the available emission control options, on the chemical transformation and dispersion of pollutants in the atmosphere, and the resulting impacts on human health and the environment. The GAINS model and its predecessor have been used to inform the key negotiations on air pollution control agreements in Europe during the last two decades. This paper describes the methodological approach of the GAINS model and its components. It presents a recent policy analysis that explores the likely future development of emissions and air quality in Europe in the absence of further policy measures, and assesses the potential and costs for further environmental improvements. To inform the forthcoming negotiations on the revision of the Gothenburg Protocol of the Convention on Long-range Transboundary Air Pollution, the paper discusses the implicat

Reactive nitrogen compounds play a key role both in air pollution and its multiple effects and as greenhouse gas. The well-known interferences of environmental nitrogen pertain to their behavior in general, but also affect their release to the atmosphere and any measure to control such a release. Considerable interest exists in the scientific literature compiled here to investigate such interferences, with a focus on co-benefits. Cost considerations are essential information for policy purposes, and costs can be divided among environmental targets if co-benefits of measures can be identified. Recent scientific work demonstrates that abatement of nitrogen compounds (especially ammonia and nitrogen oxides) is decisive for cost-efficient reduction of the effects of air pollution like the impacts of nitrogen deposition on ecosystems or its contribution formation of secondary ozone and particulate matter and associated health effects. Likewise, such results show that cost efficient abatement of greenhouse gases also needs to include mitigation of nitrous oxide emissions.

We investigate the possibility to replace the -- so-called -- Tier 1 IPCC approach to estimate soil N2O emissions with stratified emissions factors that take into account both N-input and the spatial variability of the environmental conditions within the countries of the European Union, using the DNDC-Europe model. Spatial variability in model simulations is high and corresponds to the variability reported in literature for field data. Our results indicate that (a) much of the observed variability in N2O fluxes reflects the response of soils to external conditions, (b) it is likely that national inventories tend to overestimate the uncertainties in their estimated direct N2O emissions from arable soils; (c) on average over Europe, the fertilizer-induced emissions (FIE) coincide with the IPCC factors, but they display large spatial variations. Therefore, at scales of individual countries or smaller, a stratified approach considering fertilizer type, soil characteristics and climatic parameters is preferable.

Europe, and especially the European Union (EU), has many governmental policy measures aimed at decreasing unwanted reactive nitrogen (N_r) emissions from combustion, agriculture and urban wastes. Many of these policy measures have an "effects-based approach", and focus on single N_r compounds, single sectors and either on air or waters. This chapter addresses the origin, objectives and targets of EU policy measures related to N_r emissions, considers which instruments are being used to implement the policies and briefly discusses the effects of the policy measures.

An uncertainty assessment of the Austrian greenhouse gas inventory provided the basis for this analysis. We isolated the factors that were responsible for the uncertainty observed, and compared our results with those of other countries. Uncertainties of input parameters were used to derive the uncertainty of the emission estimate. Resulting uncertainty using a Monte Carlo approach was 5.2% for the emission levels of 2005 and 2.4 percentage points for the 1990-2005 emission trend. Systematic uncertainty was not assessed. This result is in the range expected from previous experience in Austria and other countries. The determining factor for the emission level uncertainty (not the trend uncertainty) is the uncertainty associated with soil nitrous oxide N2O emissions. Uncertainty of the soil N2O release rate is huge, and there is no agreement even on the magnitude of the uncertainty when country comparisons are made. In other words, reporting and use of N2O release uncertainty are also different between countries; this is important, as this single factor fully determines a country's national greenhouse gas inventory uncertainty. Inter-country comparisons of emission uncertainty are thus unable to reveal much about a country's inventory quality. For Austria, we also compared the results of the Monte Carlo approach to those obtained from a simpler error propagation approach, and find the latter to systematically provide lower uncertainty. The difference can be explained by the ability of the Monte Carlo approach to account for statistical dependency of input parameters, again regarding soil N2O emissions. This is in contrast to the results of other countries, which focus less on statistical dependency when performing Monte Carlo analysis. In addition, the error propagation results depend on treatment of skewed probability distributions, which need to be translated into normal distributions. The result indicates that more attention needs to be given to identifying statisti

Curbing nitrogen emissions is a central environmental challenge for the twenty-first century, argue Mark Sutton and his colleagues.

The assessment of greenhouse gases emitted to and removed from the atmosphere is high on the international political and scientific agendas. Growing international concern and cooperation regarding the climate change problem have increased the need for policy-oriented solutions to the issue of uncertainty in, and related to, inventories of greenhouse gas (GHG) emissions. The approaches to addressing uncertainty discussed in this Special Issue reflect attempts to improve national inventories, not only for their own sake but also from a wider, systems analytical perspective - a perspective that seeks to strengthen the usefulness of national inventories under a compliance and/or global monitoring and reporting framework. These approaches demonstrate the benefits of including inventory uncertainty in policy analyses. The authors of the contributed papers show that considering uncertainty helps avoid situations that can, for example, create a false sense of certainty or lead to invalid views of subsystems. This may eventually prevent related errors from showing up in analyses. However, considering uncertainty does not come for free. Proper treatment of uncertainty is costly and demanding because it forces us to make the step from "simple to complex" and only then to discuss potential simplifications. Finally, comprehensive treatment of uncertainty does not offer policymakers quick and easy solutions. The authors of the papers in this Special Issue do, however, agree that uncertainty analysis must be a key component of national GHG inventory analysis. Uncertainty analysis helps to provide a greater understanding and better science helps us to reduce and deal with uncertainty. By recognizing the importance of identifying and quantifying uncertainties, great strides can be made in ongoing discussions regarding GHG inventories and accounting for climate change. The 17 papers in this Special Issue deal with many aspects of analyzing and dealing with uncertainty in emissions es

Nitrogen (N) budgets of agricultural systems give important information for assessing the impact of N inputs on the environment, and identify levers for action.

When assembling the 17 papers for this volume, the editors decided to put together general concluding thoughts on dealing with uncertainty in emission inventories. There is a wealth of research in this volume, and this has encouraged us to present both the systematic classification of contributions that is included in our introductory paper and also - here - a comprehensive overview of uncertainty treatment that contains broad take-home messages. It is hoped that this concluding perspective will help readers focus on the benefits, for science and for policy, of properly covering uncertainty.

Reactive nitrogen (N_r) is of fundamental importance in biological and chemical processes in the atmosphere-biosphere system, altering the Earth's climate balance in many ways. These include the direct and indirect emissions of nitrous oxide (N2O), atmospheric N_r deposition and tropospheric ozone formation (O3), both of which alter the biospheric CO2 sink, N_r supply effects on CH4 emissions, and the formation of secondary atmospheric aerosols resulting from the emissions of nitrogen oxides (NOx) and ammonia (NH3). Human production and release of N_r into the environment is thus expected to have been an important driver of European greenhouse balance. Until now, no assessment has been made of how much of an effect European N_r emissions are having on net warming or cooling.

The Convention on Long-range Transboundary Air Pollution has started negotiations on the revision of its Gothenburg multi-pollutant/multi-effect protocol. Among other topics, emissions of ammonia have been subject of specific scrutiny. To inform negotiations, the Task Force on Reactive Nitrogen (TFRN) has compiled a list of potential ammonia emission control measures that could form an annex to the protocol. This "Draft Annex IX" defines three ambition levels, ranging from the most stringent level "A" to the least ambitious level "C". This report presents estimates of the ammonia emission reductions and costs of the measures that are included in the Draft Annex IX prepared for the revision of the Gothenburg Protocol. The estimates for the three different ambition levels have been derived with the GAINS model, and it is assumed that these measures are equally implemented for all countries, even if they are not cost-effective. The specific assumptions in translating the specifications provided in the Draft Annex IX into GAINS input data are described in this paper. Costs for implementing the ambition levels vary across countries. Taking into account recent information on ammonia emission control costs that has been compiled by the Task Force on Reactive Nitrogen it is found that overall costs of the proposed measures are generally low. Per unit of emissions abated, costs are typically only up to 1 Euro per kg NH3-N abated with a few outliers which, however, stay below 5 Euro per kg NH3-N abated. Total abatement costs are modest, for the most ambitious scenario A they amount to 8/1000 of 1% of the GDP in 2020. In relative terms (e.g., expressed as percentage of GDP) costs are higher in the non-EU countries than in the EU-27. It is found that the specific measures, if uniformly implemented in all countries, would be less cost-effective than the (country-specific) least-cost set of measures that are derived from the GAINS optimization, e.g., for the MID and LOW cases in

There is growing recognition that a comprehensive and combined analysis of air pollution and climate change could reveal important synergies of emission control measures. Insight into the multiple benefits of measures could make emission controls economically more viable, both in industrialized and developing countries. However, while scientific understanding on many individual aspects of air pollution and climate change has considerably increased in the last years, little attention has been paid to a holistic analysis of the interactions between both problems. The Greenhouse gas - Air pollution Interactions and Synergies (GAINS) model has been developed as a tool to identify emission control strategies that maximize synergies between the control of local air quality and the mitigation of greenhouse emissions. GAINS investigates how specific mitigation measures simultaneously influence different pollutants that threaten human health via the exposure of fine particles and ground-level ozone, damage natural vegetation and crops, contribute to climate change. In recent years the GAINS model has been implemented for India in collaboration between the International Institute for Applied Systems Analysis (IIASA) and The Energy and Resources Institute (TERI). This report presents a first analysis conducted with the GAINS model that highlights how strategies to control local air quality could be designed in such a way that co-benefits on greenhouse gas mitigation could be maximized.

An uncertainty assessment of the Austrian greenhouse gas inventory provided the basis for this analyss. We isolated the factors that were responsible for the uncertainty observed, and compared our results with those of other counries. Uncertainties of input parameters were used to derive the uncertainty of the emission estimate. Resulting uncertainty using a Monte Carlo approach was 5.2% for the emission levels of 2005 and 2.4 percentage points for the 1990-2005 emission trend. Systematic uncertainty was not assessed. This result is in the range expected from previous experience in Austria and other countries. The determining factor for the emission level uncertainty (not the trend uncertainty) is the uncertainty ssociated with soil nitrous oxide N2O emissions. Uncertainty of the soil N2O release rate is huge, and there is no agreement even on the magnitude of the uncertainty when country comparisons are made. In other words, reporting and use of N2O release uncerainty are also different between countries; this is important, as this single factor fully determines a country's national grenhouse gas inventory uncertainty. Inter-country comparisons of emission uncertainty are thus unable to reveal much about a country's inventory quality. For Austria, we also compared the results of the Monte Carlo approach to those obtained from a simpler error propagation approach, and find the latter to systematically provide lower uncertainty. The difference can be explained by the ability of the Monte Carlo approach to account for statistical dependency of input parameters, again regarding soil 2O emissions. This is in contrast to the results of other countries, which focus less on statistical dependency when performing Monte Carlo analysis. In addition, the error propagation results depend on treatment of skewed probability distributions, which need to be translated into normal distributions. The result indicates that more attention needs to be given to identifying statitically d

The assessment of greenhouse gases emitted to and removed from the atmosphere is high on the internatonal political and scientific agendas. Growing international concern and cooperation regarding the climate change proble have increased the need for policy-oriented solutions to the issue of uncertainty in, and related to, inventories of greenhoue gas (GHG) emissions. The approaches to addressing uncertainty discussed in this Special Issue reflect attempts to improve natinal inventories, not only for their own sake but also from a wider, systems analytical perspective-a perspective that seeks to trengthen the usefulness of national inventories under a compliance and/or global monitoring and reporting framework. These aproaches demonstrate the benefits of including inventory uncertainty in policy analyses. The authors of the contributed papersshow that considering uncertainty helps avoid situations that can, for example, create a false sense of certainty or lead t invalid views of subsystems. Thismay eventually prevent related errors from showing up in analyses. However, considering uncertainy does not come for free. Proper treatment of uncertainty is costly and demanding because it forces us to make the step from "simple to complex" and only then to discuss potential simplifications. Finally, comprehensive treatment of uncertainty does not ofer policymakers quick and easy solutions. The authors of the papers in this Special Issue do, however, agree that uncertainty aalysis must be a key component of national GHG inventory analysis. Uncertainty analysis helps to provide a greater understnding and better science helps us to reduce and deal with uncertainty. By recognizing the importance of identifying and quantiying uncertainties, great strides can be made in ongoing discussions regarding GHG inventories and accounting for climate chang. The 17 papers in this Special Issue deal with many aspects of analyzing and dealing with uncertainty in emissions estimates

Based on the results of a livestock and crop production model, the GAINS model was applied to simulate agricultural N2O emissions in China. Data available from Chinese provinces were applied for a time horizon of 30 years from 2000 to 2030 with 5-year time steps. Results demonstrate an increasing trend of agricultural N2O emissions from 2000 to 2030 as a result of the increasing quantities of livestock and N-fertilizer use. Total agricultural N2O emissions in 2000 are 1533 kt N2O for an INMIC_central scenario, with an increase of 31% by 2030. N2O emissions from cropland are 1258 kt N2O in 2030, accounting for 80% of total agricultural N2O emissions, with an increase of 37%. N2O emissions from manure management only increased 3% by 2030. Agricultural N2O emissions mainly come from provinces including Shandong, Henan, Sichuan, Hebei, Jiangsu, Hunan, Yunnan, and Anhui. As a mitigation measure, nitrification inhibitors will reduce agricultural N2O emissions by 4-16%.

The GAINS model allows for estimation of costs and potentials for greenhouse gas (GHG) mitigation by individual GHGs. In this article, the GAINS model is used to assess mitigation potentials for non-CO2 GHGs in 2020 for all countries covered in the Annex-I of the Kyoto protocol. Mitigation measures for methane, nitrous oxide or fluorinated gases and their costs are identified and mitigation potentials and costs are compared with other available studies. Differences in the structure of economic sectors between countries are important determinants for the differences in the respective contribution of non-CO2 GHGs. For some countries, a successful application of mitigation options clearly hampers the potential still available for future reductions. While a number of options exist to reduce CO2 even at negative costs (~25% of the overall reduction potential), this is not the case for non-CO2 gases. Non-CO2 gases, however, provide considerable potential in the very low cost range (less than 10 /t CO2-eq), in particular as they are affected by options to abate CO2 as well. In the range for very cheap options, non-CO2 gases cover about 36% of the reduction potential, a fraction which is decreasing for the higher cost range, to about 26% for a carbon price of 100 /t CO2-eq. These figures have been calculated for the total of Annex-I countries, assuming a social discount rate of 4%.

The human-driven production of reactive nitrogen to stimulate agricultural productivity and its unintended formation in combustion processes both have major impacts on the global environment. Effects of excess reactive nitrogen include reductions in air quality, water quality, soil quality and biodiversity. One of the most controversial impacts of nitrogen, however, is on the greenhouse gas balance. While recent papers have highlighted a possible benefit of nitrogen in enhancing rates of carbon sequestration, there remain many trade-offs between nitrogen and greenhouse gas exchange. The result is that the net effect of reactive nitrogen on the global radiative balance is currently far from clear. To better quantity these relationships requires measurement data and modelling that make the link between different nitrogen forms and their fate in the environment. It is essential to measure fluxes for a wide range of ecosystems considering the biosphere-atmosphere exchange each of the reactive nitrogen components and greenhouse gases, as well as the fixation and denitrification of di-nitrogen. Long term observations are needed for representative ecosystems, together with results from experiments addressing the responses of the key nitrogen and greenhouse gas fluxes to different global change drivers. The NitroEurope Integrated Project of the 6th Framework Programme of the European Commission European has developed a strategy to quantifying these different terms on multiple scales. This presentation reports some of the emerging results. It highlights the first estimates of net greenhouse gas exchange for a series of 13 flux ‘supersites’, complemented by the emerging results of reactive nitrogen concentrations a large network of 58 ‘inferential sites’, which are being used to estimate nitrogen inputs. In addition to these, new low cost methods to measure nitrogen fluxes will be reported, which are being tested at the ‘supersites’ and a network of regional sites, which exte

Atmospheric concentration measurements of tracers for primary biological aerosol particles (PBAPs) have been used to obtain estimates of their release into the atmosphere. Emission flux data of surrogate compounds, for which concurrent concentration measurements were available, were used to quantify the release of PBAPs as PM10 mass. Results indicate fungal spores to be the most important contributors. One other main source is plant debris. Area-based emission rates of 24 kg km-2 and year (range 6-90) have been assessed. Results scaled for Europe indicate a contribution of PBAPs to PM10 concentrations in the low percentage range, with a maximum in summer when concentration levels are small. This is consistent with the range of measurements. Despite of the large uncertainties, results contribute to clarify the potential contribution of biological particles to global load of particle mass.

This paper reviews information on emission inventories of particulate matter (PM) in Europe. A large body of scientific literature is available to cover many different aspects. Studies focus on specific sources or source sectors (road transport as well as off-road machinery, domestic heating, industry, agriculture, and natural sources), among which especially road transport emissions are clearly best established. Emission inventories comprising all sources are available for specific European regions, often pointing out regional differences, but also for the entire continent. Still these inventories often are not able to satisfy the needs. Due to PM specific circumstances such as the large number of sources, very different release pathways and differences of the individual particles in terms of chemical composition or size, it is very difficult to to appropriately handle measurement conditions to arrive at adequate emission factors, especially when emission points cannot be defined clearly. Information on fugitive emissions (caused by wind shear, material transfer processes or other mechanical forces from non-point sources) is sparse, except for road traffic emissions where recent data seems to converge. The problem of data gaps concerns activities in industry (quarries), agriculture, but also natural particles like sea salt and wind-blown dust. Comparing complete inventories to independent efforts in assessing emissions, e.g. atmospheric measurements combined with source apportionment, allows to better understand and quantify the reliability of inventory data. Methodological improvements and harmonization currently under way in Europe will focus efforts and allow for more reliable PM inventories in the near future.

This study was conducted to estimate annual CH4 efflux from wetlands and watercourses in Europe and some adjacent areas. Wet ecosystems were divided into seven categories: ombrotrophic mires, minerotrophic mires, freshwater marshes, saltwater marshes, small lakes, large lakes and rivers. The geographical distribution and total area coverage for each of these respective ecosystems were taken from CORINE 2000, Global Land Cover 2000 [JRC, 2003. Harmonisation, mosaicing and production of the Global Land Cover 2000 database (Beta Version). EUR 20849 EN, Joint Research Center, Ispra, Italy] and ESRI 2003 databases. CH4 release factors were obtained from an extensive overview of published literature. Less than 3% of the study area of 22,560,000 km2 consisted of wetlands and watercourses. Large lakes (40%), minerotrophic mires (24%) and ombrotrophic mires (20%) covered almost 85% of the total area of wetlands and watercourses. The total CH4 release from European wetlands and watercourses was estimated to be 5.2 Tg a-1. CH4 release from minerotrophic mires (48%), large lakes (24%), and ombrotrophic mires (12%) composed most of the total CH4 efflux. High variation in the rate of CH4 release within the main ecosystem types, small number of studies in some ecosystems and ecologically inadequate land-cover classification are the main reasons for the uncertainties of the estimate. A better estimation of European CH4 effluxes from natural sources, now and future, would require: a much more detailed and ecologically relevant mapping of the area of different types of wetlands and watercourses, and long-term measurements of CH4 fluxes and their controlling environmental factors in poorly studied types of wetlands and watercourses. Finally, the data could be used for dynamic modelling of CH4 fluxes in the current and changing environmental conditions.

In this study we propose a global average quantitative criterion for the Nitrogen to dry matter ratio, r(N/dm), in the harvested plant material, which shows the degree to which the reduced global warming, reduced by using plant biomass instead of fossil fuels as an energy source (“saved CO2”), is counteracted by the release of N2O. The results indicate that the specific use of agricultural crops for energy production in several cases can be counterproductive from a climate point of view due to accompanying N2O emissions. This effect has been much underrated in studies of the climatic impact of biofuel production.

The relationship, on a global basis, between the amount of N fixed by chemical, biological or atmospheric processes entering the terrestrial biosphere, and the total emission of nitrous oxide (N2O), has been re-examined, using known global atmospheric removal rates and concentration growth of N2O as a proxy for overall emissions. For both the pre-industrial period and in recent times, after taking into account the large-scale changes in synthetic N fertiliser production, we find an overall conversion factor of 3-5% from newly fixed N to N2O-N. We assume the same factor to be valid for biofuel production systems. It is covered only in part by the default conversion factor for "direct" emissions from agricultural crop lands (1%) estimated by IPCC (2006), and the default factors for the "indirect" emissions (following volatilization/deposition and leaching/runoff of N:0.35-0.45%) cited therein. However, as we show in the paper, when additional emissions included in the IPCC methodology, e.g. those from livestock production, are included, the total may not be inconsistent with that given by our "top-down"method When the extra N2O emission from biofuel production is calculated in "CO2 equivalent"global warming terms, and compared with the quasi-cooling effect of "saving" emissions of fossil fuel derived CO2, the outcome is that the production of commonly used biofuels, such as biodiesel from rapeseed and bioethanol from corn (maize), depending on N fertilizer uptake efficiency by the plants, can contribute as much or more to global warming by N2O emissions than cooling by fossil fuel savings. Crops with less N demand, such as grasses and woody coppice species, have more favourable climate impacts. This analysis only considers the conversion of biomass to biofuel. It does not take into account the use of fossil fuel on the farms and for fertilizer and pesticide production, but it also neglects the production of useful co-products. Both factors partially compensate each ot

This report describes initial policy analyses with the Greenhouse gas – Air pollution Interactions and Synergies (GAINS) model. It summarizes the exogenous projections on energy and agricultural activities up to 2030 and discusses the resulting implications on air quality and greenhouse gas emissions. An illustrative scenario explores the health benefits from a substitution of solid fuels in households by LPG and explores the side-effects on greenhouse gas emissions. The paper summarizes the optimization methodology that has been developed for the GAINS-Asia model and presents a range of alternative strategies to improve air quality and reduce greenhouse gas emissions. It shows that with a targeted approach, emission control costs can be reduced by up to 80 percent compared to an across-the-board application of technologies. Furthermore, the paper presents systematic analyses of the costs (i.e., cost curves) for reducing health impacts from fine particulate matter as well as for reducing greenhouse gas emissions.

Although over 78% of the atmosphere is composed of nitrogen, it exists in its chemically and biologically unusable gaseous form. Haber discovered how ammonia, a chemically reactive, highly usable form of nitrogen, could be synthesized by reacting atmospheric dinitrogen with hydrogen in the presence of iron at high pressures and temperatures.

The assessment of greenhouse gases (GHGs) emitted to and removed from the atmosphere is high on both political and scientific agendas internationally. As increasing international concern and cooperation aim at policy-oriented solutions to the climate change problem, several issues have begun to arise regarding verification and compliance under both proposed and legislated schemes meant to reduce the human-induced global climate impact. The approaches to addressing uncertainty introduced in this article attempt to improve national inventories or to provide a basis for the standardization of inventory estimates to enable comparison of emissions and emission changes across countries. Authors of the accompanying articles use detailed uncertainty analyses to enforce the current structure of the emission trading system and attempt to internalize high levels of uncertainty by tailoring the emissions trading market rules. Assessment of uncertainty can help improve inventories and manage risk. Through recognizing the importance of, identifying and quantifying uncertainties, great strides can be made in the process of Accounting for Climate Change.

The contribution of liquid water to measured aerosol mass was estimated using a numerical approach applied to European measurement data. Aerosol mass is determined after conditioning of the filter under dry conditions for a predefined period according to a standard procedure. After this procedure, water in aerosols is assumed to be at very low concentrations. However, we find indications that the equilibrium of aerosol is not fully established and water is not completely evaporated after the drying operation. To estimate the aerosol humidity, a mass transfer coefficient was derived for evaporation from the filters. Data from a few available measurements of aerosol humidity were applied with a numerical kinetic approach, using thermodynamic equilibrium as boundary conditions. The calculated coefficient ranged from 10-5 to 10-4 (s-1), with an average value of 3.2×10-5 s-1. Using this average value the expected water content of aerosol was assessed for sites in Austria. Most of the samples are expected to still contain 1-5% water. In winter, the air is humid and the concentration of inorganic hygroscopic compounds is also high, resulting in high uptake of water from the air. Under such conditions, approximately 70% of unidentified non-carbonaceous components, or about 10% of PM2.5 mass, were considered to be water.