ALBERT

Description: National commitments under the Paris Agreement on climate change interact with other global environmental objectives, such as those of the Minamata Convention on Mercury. We assess how mercury emissions and deposition reductions from national climate policy in China under the Paris Agreement could contribute to the country's commitments under the Minamata Convention. We examine emissions under climate policy scenarios developed using a computable general equilibrium model of China's economy, end-of-pipe control scenarios that meet China's commitments under the Minamata Convention, and these policies in combination, and evaluate deposition using a global atmospheric transport model. We find climate policy in China can provide mercury benefits when implemented with Minamata policy, achieving in the year 2030 approximately 5\% additional reduction in mercury emissions and deposition in China when climate policy achieves a 5% reduction per year in carbon intensity (CO2 emissions 9.7 Gt in 2030). This corresponds to 63 Mg additional mercury emissions reductions in 2030 when implemented with Minamata Convention policy, compared to Minamata policy implemented alone. Climate policy provides emissions reductions in sectors not considered under the Minamata Convention, such as residential combustion. This changes the combination of sectors that contribute to emissions reductions. This data submission includes scripts to project China's 2012 mercury emissions from the Emissions Database for Global Atmospheric Research (EDGAR) and prepare them for input to the global chemical transport model, GEOS-Chem. It also includes scripts to plot projected emissions and plot deposition results (with required raw results from GEOS-Chem) for the figures included in the Environmental Science and Technology article.

Description: EDGARv5.0 provides emissions not only for the greenhouse gases per sector and country but also for the air pollutants: - Ozone precursor gases: Carbon Monoxide (CO), Nitrogen Oxides (NOx), Non-Methane Volatile Organic Compounds (NMVOC) and Methane (CH4). - Acidifying gases: Ammonia (NH3), Nitrogen oxides (NOx) and Sulfur Dioxide (SO2). - Primary particulates: Fine Particulate Matter (PM10 and PM2.5 and Carbonaceous speciation (BC, OC). Emissions from large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. Further information can be found at https://edgar.jrc.ec.europa.eu/overview.php?v=50_AP

Description: Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH4 yr−1. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8±55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs.

Description: Published

Description: 1197–1268

Description: OSA2: Evoluzione climatica: effetti e loro mitigazione

Description: JCR Journal

Description: Non-methane volatile organic compounds (NMVOCs) include a large number of chemical species which differ significantly in their chemical characteristics and thus in their impacts on ozone and secondary organic aerosol formation. It is important that chemical transport models (CTMs) simulate the chemical transformation of the different NMVOC species in the troposphere consistently. In most emission inventories, however, only total NMVOC emissions are reported, which need to be decomposed into classes to fit the requirements of CTMs. For instance, the Emissions Database for Global Atmospheric Research (EDGAR) provides spatially resolved global anthropogenic emissions of total NMVOCs. In this study the EDGAR NMVOC inventory was revised and extended in time and in sectors. Moreover the new version of NMVOC emission data in the EDGAR database were disaggregated on a detailed sector resolution to individual species or species groups, thus enhancing the usability of the NMVOC emission data by the modelling community. Region- and source-specific speciation profiles of NMVOC species or species groups are compiled and mapped to EDGAR processes (detailed resolution of sectors), with corresponding quality codes specifying the quality of the mapping. Individual NMVOC species in different profiles are aggregated to 25 species groups, in line with the common classification of the Global Emissions Initiative (GEIA). Global annual grid maps with a resolution of 0.1°  ×  0.1° for the period 1970–2012 are produced by sector and species. Furthermore, trends in NMVOC composition are analysed, taking road transport and residential sources in Germany and the United Kingdom (UK) as examples.

Description: The Emissions Database for Global Atmospheric Research (EDGAR) compiles anthropogenic global emissions and trends based on international statistics and best-available emission factors, for the use in atmospheric models and in policy evaluation. The new version v4.3.2 of the EDGAR emission inventory provides global emission estimates, disaggregated at source-sector level, for the historic period from 1970 (the year of EU's first Air Quality Directive) until 2012 (the end year of the first commitment period of the Kyoto Protocol). The global geo-coverage and continuous time-series are strengths of the EDGAR database, which applies the same methodology and mainly default emission factors to all world countries, in order to achieve comparability and full transparency. Region-specific emission factors are selected, when these are recommended by IPCC (2006) guidelines or when these are justified by robust information on significant differences in economic activities, in customs or in geographical ambient conditions and proven to be more representative than the global average. This database is not only unique in its space-time coverage, but also in the completeness and consistency of the estimated emissions of multiple pollutants: the greenhouse gases (GHG), air pollutants and aerosols. This publication documents the first part of the EDGAR v4.3.2 emissions database focusing on emissions of the three major greenhouse gases of CO2, CH4 and N2O, from human activities apart from the land-use, land-use change and forestry (LULUCF) sector (including forest and savannah burning). Unlike the activities of the LULUCF sector, which are typically estimated top-down from less certain land-use observations, all these activities are estimated bottom-up from standard annual statistics of fuel, products, waste, crops or livestock. We present country-specific emission totals and analyse the trends and variations in emissions of the largest emitting countries together with the EU in more detail, to uncover the effect of changes in human activities with time on each of the gases. The GWP-100 weighted global total GHG emission trend is predominantly determined by the global CO2 trend and in particular, by fuel markets trends, geopolitical changes and financial crises rather than population changes. We also evaluate the uncertainty in emissions for different sectors and three groups of countries (the OECD countries of 1990, the countries with economies in transition in 1990 and the remaining non-Annex I countries). Even though large progress has been made on emission inventory compilation, the uncertainty in global total GHG emissions has not decreased, because of the increasing share of emissions from countries with less developed statistical infrastructure and secondly the decreasing share of emissions from the activities (e.g. coal power plants) for which relatively accurate information is available. Finally, we discuss changes in geospatial distribution with a focus on hot spots and megacities using gridded information. Data is presented online for each source category with annual and monthly global emissions grid-maps of 0.1° × 0.1° resolution and can be freely accessed from the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432&SECURE=123 (DOI: https://data.europa.eu/doi/10.2904/JRC_DATASET_EDGAR).

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.