Interpreting contemporary trends in atmospheric methane

Atmospheric methane plays a major role in controlling climate, yet contemporary methane trends (1982–2017) have defied explanation with numerous, often conflicting, hypotheses proposed in the literature. Specifically, atmospheric observations of methane from 1982 to 2017 have exhibited periods of both increasing concentrations (from 1982 to 2000 and from 2007 to 2017) and stabilization (from 2000 to 2007). Explanations for the increases and stabilization have invoked changes in tropical wetlands, livestock, fossil fuels, biomass burning, and the methane sink. Contradictions in these hypotheses arise because our current observational network cannot unambiguously link recent methane variations to specific sources. This raises some fundamental questions: (i) What do we know about sources, sinks, and underlying processes driving observed trends in atmospheric methane? (ii) How will global methane respond to changes in anthropogenic emissions? And (iii), What future observations could help resolve changes in the methane budget? To address these questions, we discuss potential drivers of atmospheric methane abundances over the last four decades in light of various observational constraints as well as process-based knowledge. While uncertainties in the methane budget exist, they should not detract from the potential of methane emissions mitigation strategies. We show that net-zero cost emission reductions can lead to a declining atmospheric burden, but can take three decades to stabilize. Moving forward, we make recommendations for observations to better constrain contemporary trends in atmospheric methane and to provide mitigation support

Aerosol lidar observations of atmospheric mixing in Los Angeles: Climatology and implications for greenhouse gas observations

Atmospheric observations of greenhouse gases provide essential information on sources and sinks of these key atmospheric constituents. To quantify fluxes from atmospheric observations, representation of transport—especially vertical mixing—is a necessity and often a source of error. We report on remotely sensed profiles of vertical aerosol distribution taken over a 2 year period in Pasadena, California. Using an automated analysis system, we estimate daytime mixing layer depth, achieving high confidence in the afternoon maximum on 51% of days with profiles from a Sigma Space Mini Micropulse LiDAR (MiniMPL) and on 36% of days with a Vaisala CL51 ceilometer. We note that considering ceilometer data on a logarithmic scale, a standard method, introduces, an offset in mixing height retrievals. The mean afternoon maximum mixing height is 770 m Above Ground Level in summer and 670 m in winter, with significant day‐to‐day variance (within season σ = 220m≈30%). Taking advantage of the MiniMPL’s portability, we demonstrate the feasibility of measuring the detailed horizontal structure of the mixing layer by automobile. We compare our observations to planetary boundary layer (PBL) heights from sonde launches, North American regional reanalysis (NARR), and a custom Weather Research and Forecasting (WRF) model developed for greenhouse gas (GHG) monitoring in Los Angeles. NARR and WRF PBL heights at Pasadena are both systematically higher than measured, NARR by 2.5 times; these biases will cause proportional errors in GHG flux estimates using modeled transport. We discuss how sustained lidar observations can be used to reduce flux inversion error by selecting suitable analysis periods, calibrating models, or characterizing bias for correction in post processing.Key PointsAerosol lidar maps LA mixing depth in space (pilot mobile study) and time (2 years data)Automatic mixing depth retrieval system finds daily variability far exceeds seasonal differencePBL heights in models used for GHG monitoring show biases that will carry over to flux estimatesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134180/1/jgrd53200_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134180/2/jgrd53200.pd

Space-based observations of megacity carbon dioxide

Urban areas now house more than half the world's population, and are estimated to contribute over 70% of global energy-related CO_2 emissions. Many cities have emission reduction policies in place, but lack objective, observation-based methods for verifying their outcomes. Here we demonstrate the potential of satellite-borne instruments to provide accurate global monitoring of megacity CO_2 emissions using GOSAT observations of column averaged CO_2 dry air mole fraction (X_(CO_2)) collected over Los Angeles and Mumbai. By differencing observations over the megacity with those in nearby background, we observe robust, statistically significant X_(CO_2) enhancements of 3.2 ± 1.5 ppm for Los Angeles and 2.4 ± 1.2 ppm for Mumbai, and find these enhancements can be exploited to track anthropogenic emission trends over time. We estimate that X_(CO_2) changes as small as 0.7 ppm in Los Angeles, corresponding to a 22% change in emissions, could be detected with GOSAT at the 95% confidence level

Surface observations for monitoring urban fossil fuel CO_2 emissions: Minimum site location requirements for the Los Angeles megacity

The contemporary global carbon cycle is dominated by perturbations from anthropogenic CO_2 emissions. One approach to identify, quantify, and monitor anthropogenic emissions is to focus on intensely emitting urban areas. In this study, we compare the ability of different CO_2 observing systems to constrain anthropogenic flux estimates in the Los Angeles megacity. We consider different observing system configurations based on existing observations and realistic near-term extensions of the current ad hoc network. We use a high-resolution regional model (Stochastic Time-Inverted Lagrangian Transport-Weather Research and Forecasting) to simulate different observations and observational network designs within and downwind of the Los Angeles (LA) basin. A Bayesian inverse method is employed to quantify the relative ability of each network to improve constraints on flux estimates. Ground-based column CO_2 observations provide useful complementary information to surface observations due to lower sensitivity to localized dynamics, but column CO_2 observations from a single site do not appear to provide sensitivity to emissions from the entire LA megacity. Surface observations from remote, downwind sites contain weak, sporadic urban signals and are complicated by other source/sink impacts, limiting their usefulness for quantifying urban fluxes in LA. We find a network of eight optimally located in-city surface observation sites provides the minimum sampling required for accurate monitoring of CO_2 emissions in LA, and present a recommended baseline network design. We estimate that this network can distinguish fluxes on 8 week time scales and 10 km spatial scales to within ~12 g C m^(–2) d^(–1) (~10% of average peak fossil CO_2 flux in the LA domain)

Large Fugitive Methane Emissions From Urban Centers Along the U.S. East Coast

Urban emissions remain an underexamined part of the methane budget. Here we present and interpret aircraft observations of six old and leak‐prone major cities along the East Coast of the United States. We use direct observations of methane (CH4), carbon dioxide (CO2), carbon monoxide (CO), ethane (C2H6), and their correlations to quantify CH4 emissions and attribute to natural gas. We find the five largest cities emit 0.85 (0.63, 1.12) Tg CH4/year, of which 0.75 (0.49, 1.10) Tg CH4/year is attributed to natural gas. Our estimates, which include all thermogenic methane sources including end use, are more than twice that reported in the most recent gridded EPA inventory, which does not include end‐use emissions. These results highlight that current urban inventory estimates of natural gas emissions are substantially low, either due to underestimates of leakage, lack of inclusion of end‐use emissions, or some combination thereof.Plain Language SummaryRecent efforts to quantify fugitive methane associated with the oil and gas sector, with a particular focus on production, have resulted in significant revisions upward of emission estimates. In comparison, however, there has been limited focus on urban methane emissions. Given the volume of gas distributed and used in cities, urban losses can impact national‐level emissions. In this study we use aircraft observations of methane, carbon dioxide, carbon monoxide, and ethane to determine characteristic correlation slopes, enabling quantification of urban methane emissions and attribution to natural gas. We sample nearly 12% of the U.S. population and 4 of the 10 most populous cities, focusing on older, leak‐prone urban centers. Emission estimates are more than twice the total in the U.S. EPA inventory for these regions and are predominantly attributed to fugitive natural gas losses. Current estimates for methane emissions from the natural gas supply chain appear to require revision upward, in part possibly by including end‐use emissions, to account for these urban losses.Key PointsAircraft observations downwind of six major cities along the U.S. East Coast are used to estimate urban methane emissionsObserved urban methane estimates are about twice that reported in the Gridded EPA inventoryMethane emissions from natural gas (including end use) in five cities combined exceeds nationwide emissions estimate from local distributionPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151283/1/grl59329.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151283/2/grl59329_am.pd

Detecting Urban Emissions Changes and Events With a Near‐Real‐Time‐Capable Inversion System

In situ observing networks are increasingly being used to study greenhouse gas emissions in urban environments. While the need for sufficiently dense observations has often been discussed, density requirements depend on the question posed and interact with other choices made in the analysis. Focusing on the interaction of network density with varied meteorological information used to drive atmospheric transport, we perform geostatistical inversions of methane flux in the South Coast Air Basin, California, in 2015–2016 using transport driven by a locally tuned Weather Research and Forecasting configuration as well as by operationally available meteorological products. We find total‐basin flux estimates vary by as much as a factor of two between inversions, but the spread can be greatly reduced by calibrating the estimates to account for modeled sensitivity. Using observations from the full Los Angeles Megacities Carbon Project observing network, inversions driven by low‐resolution generic wind fields are robustly sensitive (p < 0.05) to seasonal differences in methane flux and to the increase in emissions caused by the 2015 Aliso Canyon natural gas leak. When the number of observing sites is reduced, the basin‐wide sensitivity degrades, but flux events can be detected by testing for changes in flux variance, and even a single site can robustly detect basin‐wide seasonal flux variations. Overall, an urban monitoring system using an operational methane observing network and off‐the‐shelf meteorology could detect many seasonal or event‐driven changes in near real time—and, if calibrated to a model chosen as a transfer standard, could also quantify absolute emissions.Key PointsLA CH4 flux estimates differ by driving meteorology but agree when calibrated for model sensitivityAliso Canyon leak can be detected by inversions using operational meteorologyOperational meteorology driven inversions significantly detect seasonal emission changes even with only one sitePeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149534/1/jgrd55279-sup-0001-Text_SI-S01.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149534/2/jgrd55279.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149534/3/jgrd55279_am.pd

Interpreting contemporary trends in atmospheric methane

Atmospheric methane plays a major role in controlling climate, yet contemporary methane trends (1982–2017) have defied explanation with numerous, often conflicting, hypotheses proposed in the literature. Specifically, atmospheric observations of methane from 1982 to 2017 have exhibited periods of both increasing concentrations (from 1982 to 2000 and from 2007 to 2017) and stabilization (from 2000 to 2007). Explanations for the increases and stabilization have invoked changes in tropical wetlands, livestock, fossil fuels, biomass burning, and the methane sink. Contradictions in these hypotheses arise because our current observational network cannot unambiguously link recent methane variations to specific sources. This raises some fundamental questions: (i) What do we know about sources, sinks, and underlying processes driving observed trends in atmospheric methane? (ii) How will global methane respond to changes in anthropogenic emissions? And (iii), What future observations could help resolve changes in the methane budget? To address these questions, we discuss potential drivers of atmospheric methane abundances over the last four decades in light of various observational constraints as well as process-based knowledge. While uncertainties in the methane budget exist, they should not detract from the potential of methane emissions mitigation strategies. We show that net-zero cost emission reductions can lead to a declining atmospheric burden, but can take three decades to stabilize. Moving forward, we make recommendations for observations to better constrain contemporary trends in atmospheric methane and to provide mitigation support

Spatial patterns and source attribution of urban methane in the Los Angeles Basin

Urban areas are increasingly recognized as a globally important source of methane to the atmosphere; however, the location of methane sources and relative contributions of source sectors are not well known. Recent atmospheric measurements in Los Angeles, California, USA, show that more than a third of the city's methane emissions are unaccounted for in inventories and suggest that fugitive fossil emissions are the unknown source. We made on-road measurements to quantify fine-scale structure of methane and a suite of complementary trace gases across the Los Angeles Basin in June 2013. Enhanced methane levels were observed across the basin but were unevenly distributed in space. We identified 213 methane hot spots from unknown emission sources. We made direct measurements of ethane to methane (C_2H_6/CH_4) ratios of known methane emission sources in the region, including cattle, geologic seeps, landfills, and compressed natural gas fueling stations, and used these ratios to determine the contribution of biogenic and fossil methane sources to unknown hot spots and to local urban background air. We found that 75% of hot spots were of fossil origin, 20% were biogenic, and 5% of indeterminate source. In regionally integrated air, we observed a wider range of C_2H_6/CH_4 values than observed previously. Fossil fuel sources accounted for 58–65% of methane emissions, with the range depending on the assumed C_2H_6/CH_4 ratio of source end-members and model structure. These surveys demonstrated the prevalence of fugitive methane emissions across the Los Angeles urban landscape and suggested that uninventoried methane sources were widely distributed and primarily of fossil origin

Observational and model evidence for a prominent stratospheric influence on variability in tropospheric nitrous oxide

The literature presents different views on how the stratosphere influences variability in surface nitrous oxide (N2O) and on whether that influence is outweighed by surface emission changes driven by the El Niño–Southern Oscillation (ENSO). These questions are investigated using a chemistry–climate model with a stratospheric N2O tracer; surface and aircraft-based N2O measurements; and indices for ENSO, polar lower stratospheric temperature (PLST), and the stratospheric quasi-biennial oscillation (QBO). The model simulates well-defined seasonal cycles in tropospheric N2O that are caused mainly by the seasonal descent of N2O-poor stratospheric air in polar regions with subsequent cross-tropopause transport and mixing. Similar seasonal cycles are identified in recently available N2O data from aircraft. A correlation analysis between the N2O atmospheric growth rate (AGR) anomaly in long-term surface monitoring data and the ENSO, PLST, and QBO indices reveals hemispheric differences. In the Northern Hemisphere, the surface N2O AGR is negatively correlated with winter (January–March) PLST. This correlation is consistent with an influence from the Brewer–Dobson circulation, which brings N2O-poor air from the middle and upper stratosphere into the lower stratosphere with associated warming due to diabatic descent. In the Southern Hemisphere, the N2O AGR is better correlated to QBO and ENSO indices. These different hemispheric influences on the N2O AGR are consistent with known atmospheric dynamics and the complex interaction of the QBO with the Brewer-Dobson circulation. More airborne surveys extending to the tropopause would help elucidate the stratospheric influence on tropospheric N2O, allowing for better understanding of surface sources.This research has been supported by the Earth Sciences Division (grant no. 80NSSC17K0350)

Constraining Aerosol Vertical Profile in the Boundary Layer Using Hyperspectral Measurements of Oxygen Absorption

This study attempts to infer aerosol vertical structure in the urban boundary layer using passive hyperspectral measurements. A spectral sorting technique is developed to retrieve total aerosol optical depth (AOD) and effective aerosol layer height (ALH) from hyperspectral measurements in the 1.27‐μm oxygen absorption band by the mountaintop Fourier Transform Spectrometer at the California Laboratory for Atmospheric Remote Sensing instrument (1,673 m above sea level) overlooking the LA basin. Comparison to AOD measurements from Aerosol Robotic Network and aerosol backscatter profile measurements from a Mini MicroPulse Lidar shows agreement, with coefficients of determination (r^2) of 0.74 for AOD and 0.57 for effective ALH. On average, the AOD retrieval has an error of 24.9% and root‐mean‐square error of 0.013, while the effective ALH retrieval has an error of 7.8% and root‐mean‐square error of 67.01 m. The proposed method can potentially be applied to existing and future satellite missions with hyperspectral oxygen measurements to constrain aerosol vertical distribution on a global scale