This study quantitatively estimates the spatial distribution of anthropogenic methane sources in the United States by combining comprehensive atmospheric methane observations, extensive spatial datasets, and a high-resolution atmospheric transport model. Results show that current inventories from the US Environmental Protection Agency (EPA) and the Emissions Database for Global Atmospheric Research underestimate methane emissions nationally by a factor of ∼1.5 and ∼1.7, respectively. Our study indicates that emissions due to ruminants and manure are up to twice the magnitude of existing inventories. In addition, the discrepancy in methane source estimates is particularly pronounced in the south-central United States, where we find total emissions are ∼2.7 times greater than in most inventories and account for 24 ± 3% of national emissions. The spatial patterns of our emission fluxes and observed methane-propane correlations indicate that fossil fuel extraction and refining are major contributors (45 ± 13%) in the south-central United States. This result suggests that regional methane emissions due to fossil fuel extraction and processing could be 4.9 ± 2.6 times larger than in EDGAR, the most comprehensive global methane inventory. These results cast doubt on the US EPA's recent decision to downscale its estimate of national natural gas emissions by 25-30%. Overall, we conclude that methane emissions associated with both the animal husbandry and fossil fuel industries have larger greenhouse gas impacts than indicated by existing inventories.climate change policy | geostatistical inverse modeling

The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Abstract. The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column average dry-air mole fractions of CO 2 , CO, CH 4 , N 2 O and H 2 O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with sufficient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Orga-

We present a gridded inventory of US anthropogenic methane emissions with 0.1° × 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a wide range of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show large differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.

Quantification of fossil fuel CO 2 emissions at fine space and time resolution is emerging as a critical need in carbon cycle and climate change research. As atmospheric CO 2 measurements expand with the advent of a dedicated remote sensing platform and denser in situ measurements, the ability to close the carbon budget at spatial scales of ~100 km 2 and daily timescales requires fossil fuel CO 2 inventories at commensurate resolution.Additionally, the growing interest in U.S. climate change policy measures are best served by emissions that are tied to the driving processes in space and time. Here we introduce a high resolution data product (the "Vulcan" inventory:www.purdue.edu/eas/carbon/vulcan/) that has quantified fossil fuel CO 2 emissions for the contiguous U.S. at spatial scales less than 100 km 2 and temporal scales as small as hours. Comparison to the global 1°x1° fossil fuel CO 2 inventory used widely by the carbon cycle and climate change community prior to the construction of the Vulcan inventory, highlights the space/time biases inherent in the population-based approach.3

[1] Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO 2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO 2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site-years, 10 biomes, and includes two large-scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models' ability to simulate the seasonal cycle of CO 2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model-data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.

Climate models show that particles formed by nucleation can affect cloud cover and, therefore, the earth's radiation budget. Measurements worldwide show that nucleation rates in the atmospheric boundary layer are positively correlated with concentrations of sulfuric acid vapor. However, current nucleation theories do not correctly predict either the observed nucleation rates or their functional dependence on sulfuric acid concentrations. This paper develops an alternative approach for modeling nucleation rates, based on a sequence of acid-base reactions. The model uses empirical estimates of sulfuric acid evaporation rates obtained from new measurements of neutral molecular clusters. The model predicts that nucleation rates equal the sulfuric acid vapor collision rate times a prefactor that is less than unity and that depends on the concentrations of basic gaseous compounds and preexisting particles. Predicted nucleation rates and their dependence on sulfuric acid vapor concentrations are in reasonable agreement with measurements from Mexico City and Atlanta.amines | atmospheric aerosol | climate forcing | nanoparticle | chamber study N ucleation of atmospheric trace gases occurs regularly throughout the continental boundary layer (1). Nucleated particles grow at typical rates of 1-10 nm/h, and can be a significant source of condensation nuclei (2) and cloud condensation nuclei (CCN) (3). The cloud albedo effect is a major source of uncertainty in estimates of climate radiative forcing (4). Because nucleation may affect CCN concentrations, there is a need for microphysical models that reliably predict atmospheric nucleation rates. Fig. 1 summarizes results for the dependence of boundary layer nucleation rates on the number concentration of sulfuric acid vapor, "[H 2 SO 4 ]," measured by the University of Minnesota-National Center for Atmospheric Research (NCAR) research team over the past two decades (5). Also included are data from the University of Helsinki group (6, 7). The considerable scatter in the measurements of the nucleation rate J at a given value of [H 2 SO 4 ] may be due to factors including dependencies on other nucleation precursor gases, temperature, and relative humidity (RH), as well as uncertainties introduced when J is deduced from measurements. Significantly, Fig. 1 shows that for all of these studies nucleation rates range from 1 × 10 −2 to 5 × 10 −6 times the sulfuric acid vapor collision rate, 0.5k 11 [H 2 SO 4 ] 2 , where k 11 is the hard-sphere collision rate constant for sulfuric acid vapor (8).The literature includes a lively debate about the relative importance of ion-induced and neutral nucleation (9, 10). Our work aims to explain nucleation rates observed in the polluted boundary layer atmospheres of Atlanta and Mexico City, where estimated nucleation rates (∼1-10 3 cm −3 ·s −1 ) were often much greater than typical ion production rates (∼2-30 cm −3 ·s −1 ). Therefore, although ion-induced nucleation could contribute to particle production in these locations it is not the dominant ...

The California Research at the Nexus of Air Quality and Climate Change (CalNex) field study was conducted throughout California in May, June, and July of 2010. The study was organized to address issues simultaneously relevant to atmospheric pollution and climate change, including (1) emission inventory assessment, (2) atmospheric transport and dispersion, (3) atmospheric chemical processing, and (4) cloud‐aerosol interactions and aerosol radiative effects. Measurements from networks of ground sites, a research ship, tall towers, balloon‐borne ozonesondes, multiple aircraft, and satellites provided in situ and remotely sensed data on trace pollutant and greenhouse gas concentrations, aerosol chemical composition and microphysical properties, cloud microphysics, and meteorological parameters. This overview report provides operational information for the variety of sites, platforms, and measurements, their joint deployment strategy, and summarizes findings that have resulted from the collaborative analyses of the CalNex field study. Climate‐relevant findings from CalNex include that leakage from natural gas infrastructure may account for the excess of observed methane over emission estimates in Los Angeles. Air‐quality relevant findings include the following: mobile fleet VOC significantly declines, and NOx emissions continue to have an impact on ozone in the Los Angeles basin; the relative contributions of diesel and gasoline emission to secondary organic aerosol are not fully understood; and nighttime NO3 chemistry contributes significantly to secondary organic aerosol mass in the San Joaquin Valley. Findings simultaneously relevant to climate and air quality include the following: marine vessel emissions changes due to fuel sulfur and speed controls result in a net warming effect but have substantial positive impacts on local air quality.