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

High-latitude ecosystems have the capacity to release large amounts of carbon dioxide (CO2) to the atmosphere in response to increasing temperatures, representing a potentially significant positive feedback within the climate system. Here, we combine aircraft and tower observations of atmospheric CO2 with remote sensing data and meteorological products to derive temporally and spatially resolved year-round CO2 fluxes across Alaska during 2012–2014. We find that tundra ecosystems were a net source of CO2 to the atmosphere annually, with especially high rates of respiration during early winter (October through December). Long-term records at Barrow, AK, suggest that CO2 emission rates from North Slope tundra have increased during the October through December period by 73% ± 11% since 1975, and are correlated with rising summer temperatures. Together, these results imply increasing early winter respiration and net annual emission of CO2 in Alaska, in response to climate warming. Our results provide evidence that the decadal-scale increase in the amplitude of the CO2 seasonal cycle may be linked with increasing biogenic emissions in the Arctic, following the growing season. Early winter respiration was not well simulated by the Earth System Models used to forecast future carbon fluxes in recent climate assessments. Therefore, these assessments may underestimate the carbon release from Arctic soils in response to a warming climate.

Anthropogenic methane emissions from China are likely greater than in any other country in the world. The largest fraction of China’s anthropogenic emissions is attributable to coal mining, but these emissions may be changing; China enacted a suite of regulations for coal mine methane (CMM) drainage and utilization that came into full effect in 2010. Here, we use methane observations from the GOSAT satellite to evaluate recent trends in total anthropogenic and natural emissions from Asia with a particular focus on China. We find that emissions from China rose by 1.1 ± 0.4 Tg CH4 yr−1 from 2010 to 2015, culminating in total anthropogenic and natural emissions of 61.5 ± 2.7 Tg CH4 in 2015. The observed trend is consistent with pre-2010 trends and is largely attributable to coal mining. These results indicate that China’s CMM regulations have had no discernible impact on the continued increase in Chinese methane emissions.

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Wetlands comprise the single largest global source of atmospheric methane, but current flux estimates disagree in both magnitude and distribution at the continental scale. This study uses atmospheric methane observations over North America from 2007 to 2008 and a geostatistical inverse model to improve understanding of Canadian methane fluxes and associated biogeochemical models. The results bridge an existing gap between traditional top-down, inversion studies, which typically emphasize total emission budgets, and biogeochemical models, which usually emphasize environmental processes. The conclusions of this study are threefold. First, the most complete process-based methane models do not always describe available atmospheric methane observations better than simple models. In this study, a relatively simple model of wetland distribution, soil moisture, and soil temperature outperformed more complex model formulations. Second, we find that wetland methane fluxes have a broader spatial distribution across western Canada and into the northern U.S. than represented in existing flux models. Finally, we calculate total methane budgets for Canada and for the Hudson Bay Lowlands, a large wetland region (50-60• N, 75-96• W). Over these lowlands, we find total methane fluxes of 1.8 ± 0.24 Tg C yr −1 , a number in the midrange of previous estimates. Our total Canadian methane budget of 16.0 ± 1.2 Tg C yr −1 is larger than existing inventories, primarily due to high anthropogenic emissions in Alberta. However, methane observations are sparse in western Canada, and additional measurements over Alberta will constrain anthropogenic sources in that province with greater confidence.

Significance HCFC-22 (CHClF 2 ) and HFC-134a (CH 2 FCF 3 ) are two major gases currently used worldwide in domestic and commercial refrigeration and air conditioning. HCFC-22 contributes to stratospheric ozone depletion, and both species are potent greenhouse gases. We find pronounced seasonal variations of global emissions for these two major refrigerants, with summer emissions two to three times higher than in winter. Thus results suggest that global emissions of these potent greenhouse gases might be mitigated by improved design and engineering of refrigeration systems and/or by reinforcing system service regulations.

Abstract. We analyze the North American budget for carbon monoxide using data for CO and formaldehyde concentrations from tall towers and aircraft in a model-data assimilation framework. The Stochastic Time-Inverted Lagrangian Transport model for CO (STILT-CO) determines local to regional-scale CO contributions associated with production from fossil fuel combustion, biomass burning, and oxidation of volatile organic compounds (VOCs) using an ensemble of Lagrangian particles driven by high resolution assimilated meteorology. In many cases, the model demonstrates high fidelity simulations of hourly surface data from tall towers and point measurements from aircraft, with somewhat less satisfactory performance in coastal regions and when CO from large biomass fires in Alaska and the Yukon Territory influence the continental US.Inversions of STILT-CO simulations for CO and formaldehyde show that current inventories of CO emissions from fossil fuel combustion are significantly too high, by almost a factor of three in summer and a factor two in early spring, consistent with recent analyses of data from the INTEX-A aircraft program. Formaldehyde data help to show that sources of CO from oxidation of CH 4 and other VOCs represent the dominant sources of CO over North America in summer.

Obtaining the d‐excess parameter from oxygen and hydrogen stable isotope composition of meteoric waters has the potential power to reconstruct changes in atmospheric water pools (e,g. sources, origins and overall balance) and the climatic conditions that prevail during surface evaporation. Recently, plant and ecosystem scientists turned their attention using d‐excess information to inform questions at these scales. Here, we use the d‐excess parameter to evaluate the influence of forest canopies on atmospheric humidity within a mixed evergreen forest in coastal California. We found that during the day, when transpiration was at a maximum, the d‐excess of atmospheric water vapour exceeded model predictions for the background atmosphere into which the ecosystem evapotranspiration mixes. At night when transpiration was minor, the d‐excess of atmospheric water vapour was on average less than model predictions for an ocean derived water vapour source. The observed diurnal fluctuations around the d‐excess of the modelled background water vapour provided a strong evidence that during the day as the land surface warms and the boundary layer grows plants alter the isotope composition of atmospheric humidity via non‐steady state isotope effects. In contrast, at night equilibrium isotope effects dominate as the atmosphere stabilizes. These day and nighttime fluctuations around the d‐excess of ocean derived water vapour highlight the importance of plant transpiration for the isotope hydrology of near surface humidity and subsequently for the isotope composition of condensate like dew, an important water input to this ecosystem. Copyright © 2013 John Wiley & Sons, Ltd.