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Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

We use 2009–2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2–42.7 Tg a−1, as compared to 24.9–27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0–44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern–central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29–44 % of US anthropogenic methane emissions to livestock, 22–31 % to oil/gas, 20 % to landfills/wastewater, and 11–15 % to coal. Wetlands contribute an additional 9.0–10.1 Tg a−1.
Top-down constraints on atmospheric mercury emissions and implications for global biogeochemical cycling

We perform global-scale inverse modeling to constrain present-day atmospheric mercury emissions and relevant physiochemical parameters in the GEOS-Chem chemical transport model. We use Bayesian inversion methods combining simulations with GEOS-Chem and ground-based Hg0 observations from regional monitoring networks and individual sites in recent years. Using optimized emissions/parameters, GEOS-Chem better reproduces these ground-based observations and also matches regional over-water Hg0 and wet deposition measurements. The optimized global mercury emission to the atmosphere is ~ 5.8 Gg yr−1. The ocean accounts for 3.2 Gg yr−1 (55 % of the total), and the terrestrial ecosystem is neither a net source nor a net sink of Hg0. The optimized Asian anthropogenic emission of Hg0 (gas elemental mercury) is 650–1770 Mg yr−1, higher than its bottom-up estimates (550–800 Mg yr−1). The ocean parameter inversions suggest that dark oxidation of aqueous elemental mercury is faster, and less mercury is removed from the mixed layer through particle sinking, when compared with current simulations. Parameter changes affect the simulated global ocean mercury budget, particularly mass exchange between the mixed layer and subsurface waters. Based on our inversion results, we re-evaluate the long-term global biogeochemical cycle of mercury, and show that legacy mercury becomes more likely to reside in the terrestrial ecosystem than in the ocean. We estimate that primary anthropogenic mercury contributes up to 23 % of present-day atmospheric deposition.
Balancing aggregation and smoothing errors in inverse models

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.
In situ vertical profiles of aerosol extinction, mass, and composition over the southeast United States during SENEX and SEAC4RS: observations of a modest aerosol enhancement aloft

Vertical profiles of submicron aerosol from in situ aircraft-based measurements were used to construct aggregate profiles of chemical, microphysical, and optical properties. These vertical profiles were collected over the southeastern United States (SEUS) during the summer of 2013 as part of two separate field studies: the Southeast Nexus (SENEX) study and the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS). Shallow cumulus convection was observed during many profiles. These conditions enhance vertical transport of trace gases and aerosol and create a cloudy transition layer on top of the sub-cloud mixed layer. The trace gas and aerosol concentrations in the transition layer were modeled as a mixture with contributions from the mixed layer below and the free troposphere above. The amount of vertical mixing, or entrainment of air from the free troposphere, was quantified using the observed mixing ratio of carbon monoxide (CO). Although the median aerosol mass, extinction, and volume decreased with altitude in the transition layer, they were ~10 % larger than expected from vertical mixing alone. This enhancement was likely due to secondary aerosol formation in the transition layer. Although the transition layer enhancements of the particulate sulfate and organic aerosol (OA) were both similar in magnitude, only the enhancement of sulfate was statistically significant. The column integrated extinction, or aerosol optical depth (AOD), was calculated for each individual profile, and the transition layer enhancement of extinction typically contributed less than 10 % to the total AOD. Our measurements and analysis were motivated by two recent studies that have hypothesized an enhanced layer of secondary aerosol aloft to explain the summertime enhancement of AOD (2–3 times greater than winter) over the southeastern United States. The first study attributes the layer aloft to secondary organic aerosol (SOA) while the second study speculates that the layer aloft could be SOA or secondary particulate sulfate. In contrast to these hypotheses, the modest enhancement we observed in the transition layer was not dominated by OA and was not a large fraction of the summertime AOD.
Middle East versus Saharan dust extinction-to-backscatter ratios

Four years (2010–2013) of observations with polarization lidar and sun/sky photometer at the combined European Aerosol Research Lidar Network (EARLINET) and Aerosol Robotic Network (AERONET) site of Limassol (34.7° N, 33° E), Cyprus, were used to compare extinction-to-backscatter ratios (lidar ratios) for desert dust from Middle East deserts and the Sahara. In an earlier article, we analyzed one case only and found comparably low lidar ratios < 40 sr for Middle East dust. The complex data analysis scheme is presented. The quality of the retrieval is checked within a case study by comparing the results with respective Raman lidar solutions for particle backscatter, extinction, and lidar ratio. The applied combined lidar/photometer retrievals corroborate recent findings regarding the difference between Middle East and Saharan dust lidar ratios. We found values from 43–65 sr with a mean (±standard deviation) of 53 ± 6 sr for Saharan dust and from 33–48 sr with a mean of 41 ± 4 sr for Middle East dust for the wavelength of 532 nm. The presented data analysis, however, also demonstrates the difficulties in identifying the optical properties of dust even during outbreak situations in the presence of complex aerosol mixtures of desert dust, marine particles, fire smoke, and anthropogenic haze.
A simple formulation of the CH2O photolysis quantum yields

New expressions for the wavelength-dependent photolysis quantum yields of CH2O, Φj, are presented. They are based on combinations of functions of the type Ai/(1+exp[−(1/λ − 1/λ0i)/bi]). The parameters Ai, bi, and λ0i which have a physical meaning, are obtained by fits to the measured Φj data available from literature. The altitude dependence of the photolysis frequencies resulting from the new quantum yield expressions are compared to those derived from the Φj recommended by JPL and IUPAC.
Experimental investigation of ion–ion recombination under atmospheric conditions

We present the results of laboratory measurements of the ion–ion recombination coefficient at different temperatures, relative humidities and concentrations of ozone and sulfur dioxide. The experiments were carried out using the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at CERN, the walls of which are made of conductive material, making it possible to measure small ions. We produced ions in the chamber using a 3.5 GeV c−1 beam of positively charged pions (π+) generated by the CERN Proton Synchrotron (PS). When the PS was switched off, galactic cosmic rays were the only ionization source in the chamber. The range of the ion production rate varied from 2 to 100 cm−3 s−1, covering the typical range of ionization throughout the troposphere. The temperature ranged from −55 to 20 °C, the relative humidity (RH) from 0 to 70 %, the SO2 concentration from 0 to 40 ppb, and the ozone concentration from 200 to 700 ppb. The best agreement of the retrieved ion–ion recombination coefficient with the commonly used literature value of 1.6 × 10−6 cm3 s−1 was found at a temperature of 5 °C and a RH of 40 % (1.5 ± 0.6) × 10−6 cm3 s−1. At 20 °C and 40 % RH, the retrieved ion–ion recombination coefficient was instead (2.3 ± 0.7) × 10−6 cm3 s−1. We observed no dependency of the ion–ion recombination coefficient on ozone concentration and a weak variation with sulfur dioxide concentration. However, we observed a more than fourfold increase in the ion–ion recombination coefficient with decreasing temperature. We compared our results with three different models and found an overall agreement for temperatures above 0 °C, but a disagreement at lower temperatures. We observed a strong increase in the recombination coefficient for decreasing relative humidities, which has not been reported previously.
LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET

We present LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies), a 3-D multi-wavelength global aerosol and cloud optical database, optimized to be used for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. The LIVAS database provides averaged profiles of aerosol optical properties for the potential spaceborne laser operating wavelengths of 355, 532, 1064, 1570 and 2050 nm and of cloud optical properties at the wavelength of 532 nm. The global database is based on CALIPSO observations at 532 and 1064 nm and on aerosol-type-dependent backscatter- and extinction-related Ångström exponents, derived from EARLINET (European Aerosol Research Lidar Network) ground-based measurements for the UV and scattering calculations for the IR wavelengths, using a combination of input data from AERONET, suitable aerosol models and recent literature. The required spectral conversions are calculated for each of the CALIPSO aerosol types and are applied to CALIPSO backscatter and extinction data corresponding to the aerosol type retrieved by the CALIPSO aerosol classification scheme. A cloud optical database based on CALIPSO measurements at 532 nm is also provided, neglecting wavelength conversion due to approximately neutral scattering behavior of clouds along the spectral range of LIVAS. Averages of particle linear depolarization ratio profiles at 532 nm are provided as well. Finally, vertical distributions for a set of selected scenes of specific atmospheric phenomena (e.g., dust outbreaks, volcanic eruptions, wild fires, polar stratospheric clouds) are analyzed and spectrally converted so as to be used as case studies for spaceborne lidar performance assessments. The final global data set includes 4-year (1 January 2008–31 December 2011) time-averaged CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) data on a uniform grid of 1° × 1° with the original high vertical resolution of CALIPSO in order to ensure realistic simulations of the atmospheric variability in lidar end-to-end simulations.
Fire emission heights in the climate system – Part 1: Global plume height patterns simulated by ECHAM6-HAM2

We use the global circulation model ECHAM6 extended by the aerosol module HAM2 to simulate global patterns in wildfire emission heights. Prescribed plume heights in ECHAM6 are replaced by an implementation of a simple, semi-empirical plume height parametrization. In a first step, the global performance of the plume height parametrization is evaluated for plumes reported in the Multiangle Imaging Spectroradiometer (MISR) Plume Height Project (MPHP) data set. Our results show that the parametrization simulates a largely reasonable global distribution of plume heights. While the modeled global mean plume height (1411 ± 646 m) is in good agreement with the observed mean (1382 ± 702 m), the upper and lower tails of the plume height distribution tend to be slightly underrepresented. Furthermore, we compare plume heights simulated by the simple parametrization to a more complex, analytical plume model. Major differences in global plume height distributions are found for the lowest 1.5 km, but reasonable agreement is observed for higher plumes. In a second step, fire radiative power (FRP) as reported in the global fire assimilation system (GFAS) is used to simulate plume heights for observed fires globally for the period 2005–2011. The global fraction of simulated daytime plumes injecting emissions into the free troposphere (FT) ranges from 3.7 ± 0.7 to 5.2 ± 1.0 %. This range is comparable to results from observational studies, but it is much lower than results for prescribed plume heights in the ECHAM6-HAM2 standard setup. Nevertheless, occasionally deep emission injections exceeding 5–7 km in height are simulated for intense fires and favorable meteorological conditions. The application of a prescribed diurnal cycle in FRP turns out to be of minor importance. For a hypothetical doubling in FRP, moderate changes in plume heights of 100–400 m are simulated. These small changes indicate that a potential future increase in fire intensity will only slightly impact the emission heights on a global scale.
Fire emission heights in the climate system – Part 2: Impact on transport, black carbon concentrations and radiation

Wildfires represent a major source for aerosols impacting atmospheric radiation, atmospheric chemistry and cloud micro-physical properties. Previous case studies indicated that the height of the aerosol–radiation interaction may crucially affect atmospheric radiation, but the sensitivity to emission heights has been examined with only a few models and is still uncertain. In this study we use the general circulation model ECHAM6 extended by the aerosol module HAM2 to investigate the impact of wildfire emission heights on atmospheric long-range transport, black carbon (BC) concentrations and atmospheric radiation. We simulate the wildfire aerosol release using either various versions of a semi-empirical plume height parametrization or prescribed standard emission heights in ECHAM6-HAM2. Extreme scenarios of near-surface or free-tropospheric-only injections provide lower and upper constraints on the emission height climate impact. We find relative changes in mean global atmospheric BC burden of up to 7.9±4.4 % caused by average changes in emission heights of 1.5–3.5 km. Regionally, changes in BC burden exceed 30–40 % in the major biomass burning regions. The model evaluation of aerosol optical thickness (AOT) against Moderate Resolution Imaging Spectroradiometer (MODIS), AErosol RObotic NETwork (AERONET) and Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) observations indicates that the implementation of a plume height parametrization slightly reduces the ECHAM6-HAM2 biases regionally, but on the global scale these improvements in model performance are small. For prescribed emission release at the surface, wildfire emissions entail a total sky top-of-atmosphere (TOA) radiative forcing (RF) of −0.16±0.06 W m−2. The application of a plume height parametrization which agrees reasonably well with observations introduces a slightly stronger negative TOA RF of −0.20±0.07 W m−2. The standard ECHAM6-HAM2 model in which 25 % of the wildfire emissions are injected into the free troposphere (FT) and 75 % into the planetary boundary layer (PBL), leads to a TOA RF of −0.24±0.06 W m−2. Overall, we conclude that simple plume height parametrizations provide sufficient representations of emission heights for global climate modeling. Significant improvements in aerosol wildfire modeling likely depend on better emission inventories and aerosol process modeling rather than on improved emission height parametrizations.