Mars Methane Sources in Northwestern Gale Crater Inferred From Back Trajectory Modeling

During its first seven years of operation, the Sample Analysis at Mars Tunable Laser Spectrometer (TLS) on board the Curiosity rover has detected seven methane spikes above a low background abundance in Gale crater. The methane spikes are likely sourced by surface emission within or around Gale crater. Here, we use inverse Lagrangian modeling techniques to identify upstream emission regions on the Martian surface for these methane spikes at an unprecedented spatial resolution. Inside Gale crater, the northwestern crater floor casts the strongest influence on the detections. Outside Gale crater, the upstream regions common to all the methane spikes extend toward the north. The contrasting results from two consecutive TLS methane measurements performed on the same sol point to an active emission site to the west or the southwest of the Curiosity rover on the northwestern crater floor. The observed spike magnitude and frequency also favor emission sites on the northwestern crater floor, unless there are fast methane removal mechanisms at work, or either the methane spikes of TLS or the non-detections of ExoMars Trace Gas Orbiter cannot be trusted.

Source Partitioning of Methane Emissions and its Seasonality in the U.S. Midwest

The methane (CH₄) budget and its source partitioning are poorly constrained in the Midwestern United States. We used tall tower (185 m) aerodynamic flux measurements and atmospheric scale factor Bayesian inversions to constrain the monthly budget and to partition the total budget into natural (e.g., wetlands) and anthropogenic (e.g., livestock, waste, and natural gas) sources for the period June 2016 to September 2017. Aerodynamic flux observations indicated that the landscape was a CH₄ source with a mean annual CH₄ flux of +13.7 ± 0.34 nmol m^-2 s^-1 and was rarely a net sink. The scale factor Bayesian inversion analyses revealed a mean annual source of +12.3 ± 2.1 nmol m^-2 s^-1. Flux partitioning revealed that the anthropogenic source (7.8 ± 1.6 Tg CH₄ yr^-1) was 1.5 times greater than the bottom-up gridded United States Environmental Protection Agency inventory, in which livestock and oil/gas sources were underestimated by 1.8-fold and 1.3-fold, respectively. Wetland emissions (4.0 ± 1.2 Tg CH₄ yr^-1) were the second largest source, accounting for 34% of the total budget. The temporal variability of total CH₄ emissions was dominated by wetlands with peak emissions occurring in August. In contrast, emissions from oil/gas and other anthropogenic sources showed relatively weak seasonality.

Constraints on carbon monoxide emissions based on tall tower measurements in the US Upper Midwest

We interpret a full year of high-frequency CO measurements from a tall tower in the U.S. Upper Midwest with a time-reversed Lagrangian Particle Dispersion Model (STILT LPDM) and an Eulerian chemical transport model (GEOS-Chem CTM) to develop top-down constraints on U.S. CO sources in 2009. Our best estimate is that anthropogenic CO emissions in the U.S. Upper Midwest in 2009 were 2.9 Tg, 61% lower (a posteriori scale factor of 0.39) than our a priori prediction based on the U.S. EPA's National Emission Inventory for 2005 (NEI 2005). If the same bias applies across the contiguous U.S., the inferred CO emissions are 26 Tg/y, compared to the a priori estimate of 66 Tg/y. This discrepancy is significantly greater than would be expected based solely on emission decreases between 2005 and 2009 (EPA estimate: 23% decrease). Model transport error is an important source of uncertainty in the analysis, and we employ an ensemble of sensitivity runs using multiple meteorological data sets and model configurations to assess its impact on our results. A posteriori scale factors for the U.S. anthropogenic CO source from these sensitivity runs range from 0.22 to 0.64, corresponding to emissions of 1.6-4.8 Tg/y for the U.S. Upper Midwest and 15-42 Tg/y for the contiguous U.S. The data have limited sensitivity for constraining biomass + biofuel burning emissions and photochemical CO production from precursor organic compounds. Our finding of a NEI 2005 overestimate of CO emissions is consistent with recent assessments for individual cities and with earlier analyses based on the NEI 1999, implying the need for a better mechanism for refining such bottom-up emission estimates in response to top-down constraints.

Constraining ecosystem processes from tower fluxes and atmospheric profiles

The planetary boundary layer (PBL) provides an important link between the scales and processes resolved by global atmospheric sampling/modeling and site-based flux measurements. The PBL is in direct contact with the land surface, both driving and responding to ecosystem processes. Measurements within the PBL (e.g., by radiosondes, aircraft profiles, and flask measurements) have a footprint, and thus an integrating scale, on the order of 1-100 km. We use the coupled atmosphere-biosphere model (CAB) and a Bayesian data assimilation framework to investigate the amount of biosphere process information that can be inferred from PBL measurements. We investigate the information content of PBL measurements in a two-stage study. First, we demonstrate consistency between the coupled model (CAB) and measurements, by comparing the model to eddy covariance flux tower measurements (i.e., water and carbon fluxes) and also PBL scalar profile measurements (i.e., water, carbon dioxide, and temperature) from Canadian boreal forest. Second, we use the CAB model in a set of Bayesian inversions experiments using synthetic data for a single day. In the synthetic experiment, leaf area and respiration were relatively well constrained, whereas surface albedo and plant hydraulic conductance were only moderately constrained. Finally, the abilities of the PBL profiles and the eddy covariance data to constrain the parameters were largely similar and only slightly lower than the combination of both observations.

Understanding of coupled terrestrial carbon, nitrogen and water dynamics-an overview

Coupled terrestrial carbon (C), nitrogen (N) and hydrological processes play a crucial role in the climate system, providing both positive and negative feedbacks to climate change. In this review we summarize published research results to gain an increased understanding of the dynamics between vegetation and atmosphere processes. A variety of methods, including monitoring (e.g., eddy covariance flux tower, remote sensing, etc.) and modeling (i.e., ecosystem, hydrology and atmospheric inversion modeling) the terrestrial carbon and water budgeting, are evaluated and compared. We highlight two major research areas where additional research could be focused: (i) Conceptually, the hydrological and biogeochemical processes are closely linked, however, the coupling processes between terrestrial C, N and hydrological processes are far from well understood; and (ii) there are significant uncertainties in estimates of the components of the C balance, especially at landscape and regional scales. To address these two questions, a synthetic research framework is needed which includes both bottom-up and top-down approaches integrating scalable (footprint and ecosystem) models and a spatially nested hierarchy of observations which include multispectral remote sensing, inventories, existing regional clusters of eddy-covariance flux towers and CO(2) mixing ratio towers and chambers.