On the CH4 and N2O emission inventory compiled by EDGAR and improved with the EPRTR data for the INGOS project

This report documents the EDGAR INGOS emission inventory for CH4 and N2O, as publicly made available on: http://edgar.jrc.ec.europa.eu/ingos/index.php?SECURE=123. The EDGAR INGOS CH4 and N2O emission inventory provides bottom‐up estimates of global anthropogenic CH4 and N2O emissions for the period 2000‐2010. The EDGAR InGOS product is an update of the EDGARv4.2FT2010 inventory, taking into account emissions reported as point sources by facilities under the European Pollutant Release and Transfer Register (EPRTR) for (1) power plants (N2O), (2) oil refineries (CH4 and N2O), (3) coal mining (CH4), (4) production of oil and gas (CH4), (5) chemicals production (inorganic, nitro‐fertilizers and other bulk chemicals) (N2O), industrial process and product use (N2O), (6) solid waste ‐ landfills (CH4), (7) industrial wastewater treatment (CH4 and N2O). In a first step gridmaps have been improved for the European region taking into account the geospatial data of the E‐PRTR database. In addition, for the last 4 years an option is given to select inventories solely based on officially reported emission data (for the categories covered by E‐PRTR), gapfilled with EDGARv4.2FT2010 for non‐reporting countries.JRC.H.2-Air and Climat

Evaluation of Copernicus Atmosphere Monitoring Service methane products

The Copernicus Atmosphere Monitoring Service (CAMS) provides continuous data and information on atmospheric composition in an operational mode. The CAMS products include analyses/re-analyses of the greenhouse gases (carbon dioxide, methane, and nitrous oxide) for recent years. In this report, we evaluate the quality of the CAMS methane (CH4) products, focussing on the "near real time analyses" of the atmospheric CH4 concentrations (from the ECMWF IFS assimilation system) and the re-analyses of CH4 concentrations and fluxes (from the TM5-4DVAR inverse modelling system, provided by TNO / SRON). The CAMS CH4 products are compared to comprehensive independent observational data sets (from surface monitoring stations, ship cruises, various aircraft programmes, AirCore balloon soundings up to the middle stratosphere, and measurements of column averaged CH4 mole fractions) during 2010-2017. Furthermore, CH4 flux inversions from the JRC TM5-4DVAR system (which was used as prototype of the operational CAMS inversion system) are included in the analysis, providing a benchmark to evaluate the CAMS CH4 flux inversion products. Overall, the CAMS and JRC inversions show very similar performance and compare well to observations over remote regions near the surface and within the free troposphere, confirming that in general CH4 mole fractions in the background troposphere far from CH4 emissions are realistically simulated. Due to the relatively coarse horizontal resolution of 3o (longitude) x 2o (latitude), however, both CAMS and JRC inversions show clear limitations in simulating regional surface monitoring stations (which are influenced by regional CH4 emissions), in most cases underestimating measured CH4 mole fractions in these areas. Furthermore, the inversions show large differences to the observed CH4 mole fractions in the lower to middle stratosphere at mid to high latitudes, most likely due to shortcomings in simulating the transport and/or chemistry in the stratosphere and the stratospheric-tropospheric exchange. In contrast to the flux inversions, the CAMS "near real time analyses" show generally large biases (varying in space and time) in the simulated CH4 mole fractions compared to observations in the background troposphere. These large biases are probably mainly due to the assimilation strategy of including only satellite retrievals (but no surface observations) and potential biases in the assimilated satellite products, while the flux inversions assimilate satellite retrievals and surface observations simultaneously and thus correct for biases in the satellite data (along with potential biases of the models to simulate the stratosphere). The surface CH4 fluxes derived from the CAMS inversion system are in general similar to the JRC estimates. However, the latitudinal gradients of the fluxes are slightly different between the two inversion systems, probably in part due to the two different convection schemes applied.JRC.C.5-Air and Climat

Three Years of Greenhouse Gas Column-Averaged Dry Air Mole Fractions Retrieved from Satellite - Part 2: Methane

Abstract. Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003-2005) of SCIAMACHY nearinfrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58µm absorption band), CH4 (1.66µm) and oxygen (O2 A-band at 0.76µm) using the scientific retrieval algorithm WFM-DOAS.We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (1 min per orbit, corresponding to 6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 Aband. Here we focus on a discussion of the XCH4 data set. The XCO2 data set is discussed in a separate paper (Part 1). For 2003 we present detailed comparisons with the TM5 model which has been optimally matched to highly accurate but sparse methane surface observations. After accounting for a systematic low bias of 2% agreement with TM5 is typically within 1¿2%. We investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from NOAA¿s CO2 assimilation system CarbonTracker. We show that the CO2 corrected and uncorrected XCH4 spatio-temporal pattern are very similar but that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with previous studies (e.g., Frankenberg et al., 2005b) we find higher methane over the tropics compared to the model. We show that tropical methane is also higher when normalizing the CH4 columns with retrieved O2 columns instead of CO2. In consistency with recent results of Frankenberg et al. (2008b) it is shown that the magnitude of the retrieved tropical methane is sensitive to the choice of the spectroscopic line parameters of water vapour. Concerning inter-annual variability we find similar methane spatio-temporal pattern for 2003 and 2004. For 2005 the retrieved methane shows significantly higher variability compared to the two previous years, most likely due to somewhat larger noise of the spectral measurements.JRC.H.2-Air and Climat

On the impact of transport model errors for the estimation of CO2 surface fluxes from GOSAT observations

A series of observing system simulation experiments is presented in which column averaged dry air mole fractions of CO2 (XCO2) from the Greenhouse gases Observing SATellite (GOSAT) are made consistent or not with the transport model embedded in a flux inversion system. The GOSAT observations improve the random errors of the surface carbon budget despite the inconsistency. However, we find biases in the inferred surface CO2 budget of a few hundred MtC/a at the subcontinental scale, that are caused by differences of only a few tenths of a ppm between the simulations of the individual XCO2 soundings. The accuracy and precision of the inverted fluxes are little sensitive to an 8-fold reduction in the data density. This issue is critical for any future satellite constellation to monitor XCO2 and should be pragmatically addressed by explicitly accounting for transport errors in flux inversion systems

What Can 14CO Measurements Tell Us about OH?

The possible use of 14CO measurements to constrain hydroxyl radical (OH) concentrations in the atmosphere is investigated. 14CO is mainly produced in the upper atmosphere from cosmic radiation. Measurements of 14CO at the surface show lower concentrations compared to the upper atmospheric source region, which is the result of oxidation by OH. In this paper, the sensitivity of 14CO mixing ratio surface measurements to the 3-D OH distribution is assessed with the TM5 model. Simulated 14CO mixing ratios agree within a few molecules 14COcm-3 (STP) with existing measurements at five locations worldwide. The simulated cosmogenic 14CO distribution appears mainly sensitive to the assumed upper atmospheric 14C source function, and to a lesser extend to model resolution. As a next step, the sensitivity of 14CO measurements to OH is calculated with the adjoint TM5 model. The results indicate that 14CO measurements taken in the tropics are sensitive to OH in a spatially confined region that varies strongly over time due to meteorological variability. Given measurements with an accuracy of 0.5 molecules 14COcm-3 STP, a good characterization of the cosmogenic 14CO fraction, and assuming perfect transport modeling, a single 14CO measurement may constrain OH to 0.2¿0.3×106 moleculesOHcm-3 on time scales of 6 months and spatial scales of 70×70 degrees (latitude×longitude) between the surface and 500 hPa. The sensitivity of 14CO measurements to high latitude OH is about a factor of five higher. This is in contrast with methyl chloroform (MCF) measurements, which show the highest sensitivity to tropical OH, mainly due to the temperature dependent rate constant of the MCF¿OH reaction. A logical next step will be the analysis of existing 14CO measurements in an inverse modeling framework. This paper presents the required mathematical framework for such an analysis.JRC.H.2-Climate chang

Tropical methane emissions: A revised view from SCIAMACHY onboard ENVISAT

Methane retrievals from near-infrared spectra recorded by the SCIAMACHY instrument onboard ENVISAT hitherto suggested unexpectedly large tropical emissions. Even though recent studies confirm substantial tropical emissions, there were indications for an unresolved error in the satellite retrievals. Here we identify a retrieval error related to inaccuracies in water vapor spectroscopic parameters, causing a substantial overestimation of methane correlated with high water vapor abundances. We report on the overall implications of an update in water spectroscopy on methane retrievals with special focus on the tropics where the impact is largest. The new retrievals are applied in a four-dimensional variational (4D-VAR) data assimilation system to derive a first estimate of the impact on tropical CH_4 sources. Compared to inversions based on previous SCIAMACHY retrievals, annual tropical emission estimates are reduced from 260 to about 201 Tg CH_4 but still remain higher than previously anticipated

Cerebrospinal fluid antibodies to aquaporin-4 in neuromyelitis optica and related disorders: frequency, origin, and diagnostic relevance

In 70-80% of cases, neuromyelitis optica (NMO) is associated with highly specific serum auto-antibodies to aquaporin-4 (termed AQP4-Ab or NMO-IgG). Recent evidence strongly suggests that AQP4-Ab are directly involved in the immunopathogenesis of NMO

Inverse modeling of CH4 emissions for 2010 - 2011 using different satellite retrieval products from GOSAT and SCIAMACHY

Beginning in 2009 new space-borne observations of dry-air column-averaged mole fractions of atmospheric methane (XCH4) became available from the Thermal And Near infrared Sensor for carbon Observations - Fourier Transform Spectrometer (TANSO-FTS) instrument onboard the Greenhouse Gases Observing SATellite (GOSAT). Until April 2012 concurrent CH4 measurements were provided by the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) instrument onboard ENVISAT. The GOSAT and SCIAMACHY XCH4 retrievals can be directly compared during their circa 32-month period of overlap. We estimate monthly average CH4 emissions between January 2010 and December 2011, using the TM5-4DVAR inverse modeling system. Additionally, high-accuracy measurements from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA ESRL) global air sampling network are used, providing strong constraints of the remote surface atmosphere. We discuss five inversion scenarios that make use of different GOSAT and SCIAMACHY XCH4 retrieval products, including two sets of GOSAT proxy retrievals processed independently by the Netherlands Institute for Space Research (SRON) / Karlsruhe Institute of Technology (KIT), and the University of Leicester (UL), and the RemoTeC "Full-Physics" (FP) XCH4 retrievals available from SRON/KIT. 2-year average emission maps show a good overall agreement among all GOSAT-based inversions, but also compared to the SCIAMACHY-based inversion, with consistent flux adjustment patterns, particularly across Equatorial Africa and North America. The inversions are validated against independent shipboard and aircraft observations, and XCH4 measurements available from the Total Carbon Column Observing Network (TCCON). All GOSAT and SCIAMACHY inversions show very similar validation performance.JRC.H.2-Air and Climat

JRC-Ispra Atmosphere - Biosphere - Climate Integrated monitoring Station: 2016 report

A comprehensive set of essential atmospheric variables have been measured at the JRC-Ispra Atmosphere - Biosphere - Climate Integrated monitoring Station (ABC-IS) for several years to assess the impact of European policies and international conventions on air pollution and climate forcing. The variables we measure at the Atmospheric Observatory in Ispra include greenhouse gas concentrations (CO2, CH4, N2O, SF6), radon (222Rn) activity concentration, short-lived gaseous and particulate pollutant (CO, SO2, NO, NO2, O3, PM2.5 and its main ionic and carbonaceous constituents) concentrations, atmospheric particle micro-physical characteristics (number concentration and size distribution) and optical properties (light scattering and absorption in-situ, light scattering and extinction vertical profiles remotely), eutrophying and acidifying species (SO42-, NO3-, NH4+) wet deposition. Vegetation atmosphere exchanges (CO2, O3, H2O and heat) are measured at our Forest Flux Station of San Rossore, backed up by meteorological and pedological measurements. The ABC-IS 2016 report presents the data produced during the past year in the context of the previous years of measurements.JRC.C.5-Air and Climat

Quantifying the uncertainties of transpiration calculations with the Penman-Monteith equation under different climate and optimum water supply conditions

The uncertainties of transpiration calculations with the Penman-Monteith equation were quantified under different climate conditions of Brazil, Germany and Israel using maize as a common crop type. All experiments were carried out under non-limiting growing conditions. Canopy resistance was determined by scaling to canopy level specific relations between in situ measurements of incident radiation and stomatal conductance using a light penetration model. The model was tested against heat-pulse measured sap flow in plant stems. The root mean square error (RMSE) of daily calculated transpiration minus measured sap flow was 0.4 mm/day. It was dominated by its variance component (variance = 0.2 {min/day}(2); bias = 0.0 mm/day). Calculated transpiration closely matched the measured trends at the three locations. No significant differences were found between seasons and locations. Uncertainties of canopy conductance parameterizations led to errors of up to 2.1 mm/day. The model responded most sensitively to a 30% change of net radiation (absolute bias error = 1.6 mm/day), followed by corresponding alterations of canopy resistances (0.8 mm/day), vapour pressure deficits (0.5 mm/clay) and aerodynamic resistances (0.34 mm/day). Measured and calculated 30-min or hourly averaged transpiration rates are highly correlated (r(2) = 0.95; n = 10634), and the slope of the regression line is close to unity. The overall RMSE of calculated transpiration minus measured sap flow was 0.08 mm/h and was dominated by its variance component (0.005 {mm/h}(2)). Measured sap flow consistently lagged behind calculated transpiration, because plant hydraulic capacitance delays the change of leaf water potential that drives water uptake. Calculated transpiration significantly overestimated sap flow during morning hours (mean = 0.068 mm/h, n = 321) and underestimated it during afternoon hours (mean = -0.065 mm/h; n = 316). The Penman-Monteith approach as implemented in the present study is sufficiently sensitive to detect small differences between transpiration and water uptake and provides a robust tool to manage plant water supply under unstressed conditions. (C) 2009 Elsevier B.V. All rights reserved