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Throughout the Mediterranean, salinization threatens water quality, especially in coastal areas. This salinization is the result of concomitant processes related to both seawater intrusion and water–rock interaction, which in some cases are virtually indistinguishable. In the Nurra region of northwestern Sardinia, recent salinization related to marine water intrusion has been caused by aquifer exploitation. However, the geology of this region records a long history from the Palaeozoic to the Quaternary, and is structurally complex and comprises a wide variety of lithologies, including Triassic evaporites. Determining the origin of the saline component of the Jurassic and Triassic aquifers in the Nurra region may provide a useful and more general model for salinization processes in the Mediterranean area, where the occurrence of evaporitic rocks in coastal aquifers is a common feature. In addition, due to intensive human activity and recent climatic change, the Nurra has become vulnerable to desertification and, in common with other Mediterranean islands, surface water resources periodically suffer from severe shortages. With this in mind, we report new data regarding brackish and surface waters (outcrop and lake samples) of the Na-Cl type from the Nurra region, including major ions and selected trace elements (B, Br, I, and Sr), in addition to isotopic data including δ18O, δD in water, and δ34S and δ18O in dissolved SO4. To identify the origin of the salinity more precisely, we also analysed the mineralogical and isotopic composition of Triassic evaporites. The brackish waters have Cl contents of up to 2025 mg L−1 , and the ratios between dissolved ions and Cl, with the exception of the Br / Cl ratio, are not those expected on the basis of simple mixing between rainwater and seawater. The δ18O and δD data indicate that most of the waters fall between the regional meteoric water line and the global meteoric water line, supporting the conclusion that they are meteoric in origin. A significant consequence of the meteoric origin of the Na-Cl-type water studied here is that the Br / Cl ratio, extensively used to assess the origin of salinity in fresh water, should be used with care in carbonate aquifers that are near the coast. Overall, δ34S and δ18O levels in dissolved SO4 suggest that water–rock interaction is responsible for the Na-Cl brackish composition of the water hosted by the Jurassic and Triassic aquifers of the Nurra, and this is consistent with the geology and lithological features of the study area. Evaporite dissolution may also explain the high Cl content, as halite was detected within the gypsum deposits. Finally, these Na-Cl brackish waters are undersaturated with respect to the more soluble salts, implying that in a climate evolving toward semi-arid conditions, the salinization process could intensify dramatically in the near future.

European CH4 emissions are estimated for the period 2001–2006 using a four‐dimensional variational (4DVAR) inverse modeling system, based on the atmospheric zoom model TM5. Continuous observations are used from various European monitoring stations, complemented by European and global flask samples from the NOAA/ESRL network. The available observations mainly provide information on the emissions from northwest Europe (NWE), including the UK, Ireland, the BENELUX countries, France and Germany. The inverse modeling estimates for the total anthropogenic emissions from NWE are 21% higher compared to the EDGARv4.0 emission inventory and 40% higher than values reported to U.N. Framework Convention on Climate Change. Assuming overall uncertainties on the order of 30% for both bottom‐up and top‐down estimates, all three estimates can be still considered to be consistent with each other. However, the uncertainties in the uncertainty estimates prevent us from verifying (or falsifying) the bottom‐up inventories in a strict sense. Sensitivity studies show some dependence of the derived spatial emission patterns on the set of atmospheric monitoring stations used, but the total emissions for the NWE countries appear to be relatively robust. While the standard inversions include a priori information on the spatial and temporal emission patterns from bottom‐up inventories, a further sensitivity inversion without this a priori information results in very similar NWE country totals, demonstrating that the available observations provide significant constraints on the emissions from the NWE countries independent from bottom‐up inventories.

Uncertainty analysis facilitates identification of the most important categories affecting greenhouse gas (GHG) inventory uncertainty and helps in prioritisation of the efforts needed for development of the inventory. This paper presents an uncertainty analysis of GHG emissions of all Kyoto sectors and gases for Finland consolidated with estimates of emissions/removals from LULUCF categories. In Finland, net GHG emissions in 2003 were around 69 Tg (±15 Tg) CO₂ equivalents. The uncertainties in forest carbon sink estimates in 2003 were larger than in most other emission categories, but of the same order of magnitude as in carbon stock change estimates in other land use, land-use change and forestry (LULUCF) categories, and in N₂O emissions from agricultural soils. Uncertainties in sink estimates of 1990 were lower, due to better availability of data. Results of this study indicate that inclusion of the forest carbon sink to GHG inventories reported to the UNFCCC increases uncertainties in net emissions notably. However, the decrease in precision is accompanied by an increase in the accuracy of the overall net GHG emissions due to improved completeness of the inventory. The results of this study can be utilised when planning future GHG mitigation protocols and emission trading schemes and when analysing environmental benefits of climate conventions.

The new version of the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) compiles gaseous and particulate air pollutant emissions, making use of the same anthropogenic sectors, time period (1970–2012), and international activity data that is used for estimating GHG emissions, as described in a companion paper (Janssens-Maenhout et al., 2017). All human activities, except large scale biomass burning and land use, land-use change, and forestry are included in the emissions calculation. The bottom-up compilation methodology of sector-specific emissions was applied consistently for all world countries, providing methodological transparency and comparability between countries. In addition to the activity data used to estimate GHG emissions, air pollutant emissions are determined by the process technology and end-of-pipe emission reduction abatements. Region-specific emission factors and abatement measures were selected from recent available scientific literature and reports. Compared to previous versions of EDGAR, the EDGAR v4.3.2 dataset covers all gaseous and particulate air pollutants, has extended time series (1970–2012), and has been evaluated with quality control and quality assurance (QC and QA) procedures both for the emission time series (e.g. particulate matter – PM – mass balance, gap-filling for missing data, the split-up of countries over time, few updates in the emission factors, etc.) and grid maps (full coverage of the world, complete mapping of EDGAR emissions with sector-specific proxies, etc.). This publication focuses on the gaseous air pollutants of CO, NOx, SO2, total non-methane volatile organic compounds (NMVOCs), NH3, and the aerosols PM10, PM2.5, black carbon (BC), and organic carbon (OC). Considering the 1970–2012 time period, global emissions of SO2 increased from 99 to 103 Mt, CO from 441 to 562 Mt, NOx from 68 to 122 Mt, NMVOC from 119 to 170 Mt, NH3 from 25 to 59 Mt, PM10 from 37 to 65 Mt, PM2.5 from 24 to 41 Mt, BC from 2.7 to 4.5 Mt, and OC from 9 to 11 Mt. We present the country-specific emission totals and analyze the larger emitting countries (including the European Union) to provide insights on major sector contributions. In addition, per capita and per GDP emissions and implied emission factors – the apparent emissions per unit of production or energy consumption – are presented. We find that the implied emission factors (EFs) are higher for low-income countries compared to high-income countries, but in both cases decrease from 1970 to 2012. The comparison with other global inventories, such as the Hemispheric Transport of Air Pollution Inventory (HTAP v2.2) and the Community Emission Data System (CEDS), reveals insights on the uncertainties as well as the impact of data revisions (e.g. activity data, emission factors, etc.). As an additional metric, we analyze the emission ratios of some pollutants to CO2 (e.g. CO∕CO2, NOx∕CO2, NOx∕CO, and SO2∕CO2) by sector, region, and time to identify any decoupling of air pollutant emissions from energy production activities and to demonstrate the potential of such ratios to compare to satellite-derived emission data. Gridded emissions are also made available for the 1970–2012 historic time series, disaggregated for 26 anthropogenic sectors using updated spatial proxies. The analysis of the evolution of hot spots over time allowed us to identify areas with growing emissions and where emissions should be constrained to improve global air quality (e.g. China, India, the Middle East, and some South American countries are often characterized by high emitting areas that are changing rapidly compared to Europe or the USA, where stable or decreasing emissions are evaluated). Sector- and component-specific contributions to grid-cell emissions may help the modelling and satellite communities to disaggregate atmospheric column amounts and concentrations into main emitting sectors. This work addresses not only the emission inventory and modelling communities, but also aims to broaden the usefulness of information available in a global emission inventory such as EDGAR to also include the measurement community. Data are publicly available online through the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432_AP and registered under https://doi.org/10.2904/JRC_DATASET_EDGAR.

The Emissions Database for Global Atmospheric Research (EDGAR) compiles anthropogenic emissions data for greenhouse gases (GHGs), and for multiple air pollutants, based on international statistics and emission factors. EDGAR data provide quantitative support for atmospheric modelling and for mitigation scenario and impact assessment analyses as well as for policy evaluation. The new version (v4.3.2) of the EDGAR emission inventory provides global estimates, broken down to IPCC-relevant source-sector levels, from 1970 (the year of the European Union's first Air Quality Directive) to 2012 (the end year of the first commitment period of the Kyoto Protocol, KP). Strengths of EDGAR v4.3.2 include global geo-coverage (226 countries), continuity in time, and comprehensiveness in activities. Emissions of multiple chemical compounds, GHGs as well as air pollutants, from relevant sources (fossil fuel activities but also, for example, fermentation processes in agricultural activities) are compiled following a bottom-up (BU), transparent and IPCC-compliant methodology. This paper describes EDGAR v4.3.2 developments with respect to three major long-lived GHGs (CO2, CH4, and N2O) derived from a wide range of human activities apart from the land-use, land-use change and forestry (LULUCF) sector and apart from savannah burning; a companion paper quantifies and discusses emissions of air pollutants. Detailed information is included for each of the IPCC-relevant source sectors, leading to global totals for 2010 (in the middle of the first KP commitment period) (with a 95 % confidence interval in parentheses): 33.6(±5.9) Pg CO2 yr−1, 0.34(±0.16) Pg CH4 yr−1, and 7.2(±3.7) Tg N2O yr−1. We provide uncertainty factors in emissions data for the different GHGs and for three different groups of countries: OECD countries of 1990, countries with economies in transition in 1990, and the remaining countries in development (the UNFCCC non-Annex I parties). We document trends for the major emitting countries together with the European Union in more detail, demonstrating that effects of fuel markets and financial instability have had greater impacts on GHG trends than effects of income or population. These data (https://doi.org/10.5281/zenodo.2658138, Janssens-Maenhout et al., 2019) are visualised with annual and monthly global emissions grid maps of 0.1∘×0.1∘ for each source sector.

A common paradigm when the reduction of emissions from deforestations is estimated for the purpose of promoting it as a mitigation option in the context of the United Nations Framework Convention on Climate Change (UNFCCC) is that high uncertainties in input data—i.e., area change and C stock change/area—may seriously undermine the credibility of the estimates and therefore of reduced deforestation as a mitigation option. In this paper, we show how a series of concepts and methodological tools—already existing in UNFCCC decisions and IPCC guidance documents—may greatly help to deal with the uncertainties of the estimates of reduced emissions from deforestation.

Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aimed at extracting nutrient patterns with respect to breast cancer (BC) aetiology. Nutrient patterns were derived with treelet transform (TT) and related to BC risk. TT was applied to twenty-three log-transformed nutrient densities from dietary questionnaires. Hazard ratios (HR) and 95 % confidence intervals computed using Cox proportional hazards models quantified the association between quintiles of nutrient pattern scores and risk of overall BC, and by hormonal receptor and menopausal status. Principal component analysis was applied for comparison. The European Prospective Investigation into Cancer and Nutrition (EPIC). Women (n 334 850) from the EPIC study. The first TT component (TC1) highlighted a pattern rich in nutrients found in animal foods loading on cholesterol, protein, retinol, vitamins B12 and D, while the second TT component (TC2) reflected a diet rich in β-carotene, riboflavin, thiamin, vitamins C and B6, fibre, Fe, Ca, K, Mg, P and folate. While TC1 was not associated with BC risk, TC2 was inversely associated with BC risk overall (HRQ5 v. Q1=0·89, 95 % CI 0·83, 0·95, P trend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, P trend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, P trend<0·01). TT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC.