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We combine sustained observations from a network of atmospheric monitoring stations with inverse modeling to uniquely obtain spatiotemporal (3‐km, 4‐day) estimates of methane emissions from the Los Angeles megacity and the broader South Coast Air Basin for 2015–2016. Our inversions use customized and validated high‐fidelity meteorological output from Weather Research Forecasting and Stochastic Time‐Inverted Lagrangian model for South Coast Air Basin and innovatively employ a model resolution matrix‐based metric to disentangle the spatiotemporal information content of observations as manifested through estimated fluxes. We partially track and constrain fluxes from the Aliso Canyon natural gas leak and detect closure of the Puente Hills landfill, with no prior information. Our annually aggregated fluxes and their uncertainty excluding the Aliso Canyon leak period lie within the uncertainty bounds of the fluxes reported by the previous studies. Spatially, major sources of CH4 emissions in the basin were correlated with CH4‐emitting infrastructure. Temporally, our findings show large seasonal variations in CH4 fluxes with significantly higher fluxes in winter in comparison to summer months, which is consistent with natural gas demand and anticorrelated with air temperature. Overall, this is the first study that utilizes inversions to detect both enhancement (Aliso Canyon leak) and reduction (Puente Hills) in CH4 fluxes due to the unintended events and policy decisions and thereby demonstrates the utility of inverse modeling for identifying variations in fluxes at fine spatiotemporal resolution. Key Points: We detected and spatio‐temporally resolved major methane flux anomalies in the Los Angeles Megacity DomainWe characterized sub‐weekly scale variability in methane fluxes of South Coast Air BasinWe evaluated the impact of the loss of observational sensitivity on methane flux estimates [ABSTRACT FROM AUTHOR] more...

With the pending withdrawal of the United States from the Paris Climate Accord, cities are now leading US actions toward reducing greenhouse gas emissions. Implementing effective mitigation strategies requires the ability to measure and track emissions over time and at various scales. We report CO2 emissions in the Boston, MA, urban region from September 2013 to December 2014 based on atmospheric observations in an inverse model framework. Continuous atmospheric measurements of CO2 from five sites in and around Boston were combined with a high-resolution bottom-up CO2 emission inventory and a Lagrangian particle dispersion model to determine regional emissions. Our model-measurement framework incorporates emissions estimates from submodels for both anthropogenic and biological CO2 fluxes, and development of a CO2 concentration curtain at the boundary of the study region based on a combination of tower measurements and modeled vertical concentration gradients. We demonstrate that an emission inventory with high spatial and temporal resolution and the inclusion of urban biological fluxes are both essential to accurately modeling annual CO2 fluxes using surface measurement networks. We calculated annual average emissions in the Boston region of 0.92 kg C·m-2·y-1 (95% confidence interval: 0.79 to 1.06), which is 14% higher than the Anthropogenic Carbon Emissions System inventory. Based on the capability of the model-measurement approach demonstrated here, our framework should be able to detect changes in CO2 emissions of greater than 18%, providing stakeholders with critical information to assess mitigation efforts in Boston and surrounding areas. [ABSTRACT FROM AUTHOR] more...

Abstract: North American nitrous oxide (N2O) emissions of 1.6 ± 0.3 Tg N/yr over 2008–2014 are estimated using the CarbonTracker‐Lagrange regional inversion framework. The estimated N2O emissions are largely consistent with the EDGAR (Emission Database for Global Atmospheric Research) global inventory and with the results of global atmospheric inversions but offer more spatial and temporal detail over North America. Emissions are strongest from the Midwestern Corn/Soybean Belt, which accounts for nearly one third of the total North American N2O source. The emissions are maximum in spring/early summer, consistent with a nitrogen fertilizer‐driven source, and also show a late winter spike suggestive of freeze‐thaw effects. Interannual variability in emissions across the primary months of fertilizer application is positively correlated to mean precipitation. The estimated N2O flux from the Midwestern Corn/Soybean Belt and the more northerly United States/Canadian wheat belt corresponds to 4.2–4.6% and 2.2–3.0%, respectively, of total synthetic + organic N fertilizer applied to those regions. Consideration of nonagricultural sources and additional N inputs from soybean N2 fixation could reduce the N2O yield from the Midwestern Corn/Soybean Belt to ~2.2–2.4% of total N inputs. [ABSTRACT FROM AUTHOR] more...

Methane emissions from natural gas delivery and end use must be quantified to evaluate the environmental impacts of natural gas and to develop and assess the efficacy of emission reduction strategies. We report natural gas emission rates for 1 y in the urban region of Boston, using a comprehensive atmospheric measurement and modeling framework. Continuous methane observations from four stations are combined with a high-resolution transport model to quantify the regional average emission flux, 18.5 ± 3.7 (95% confidence interval) g CH4·m-2·y-1. Simultaneous observations of atmospheric ethane, compared with the ethane-to-methane ratio in the pipeline gas delivered to the region, demonstrate that natural gas accounted for ~60-100% of methane emissions, depending on season. Using government statistics and geospatial data on natural gas use, we find the average fractional loss rate to the atmosphere from all downstream components of the natural gas system, including transmission, distribution, and end use, was 2.7 ± 0.6% in the Boston urban region, with little seasonal variability. This fraction is notably higher than the 1.1% implied by the most closely comparable emission inventory. [ABSTRACT FROM AUTHOR] more...

A recent National Research Council report highlighted the potential utility of atmospheric observations and models for detecting trends in concentrated emissions from localized regions, such as urban areas. The Salt Lake City (SLC), Utah, area was chosen for a pilot study to determine the feasibility of using ground-based sensors to identify trends in anthropogenic urban emissions over a range of time scales (from days to years). The Weather Research and Forecasting model (WRF) was combined with a Lagrangian particle dispersion model and an emission inventory to model carbon dioxide (CO2) concentrations that can be compared with in situ measurements. An accurate representation of atmospheric transport requires a faithful modeling of the meteorological conditions. This study examines in detail the ability of different configurations of WRF to reproduce the observed local and mesoscale circulations, and the diurnal evolution of the planetary boundary layer (PBL) in the SLC area. Observations from the Vertical Transport and Mixing field experiment in 2000 were used to examine the sensitivity of WRF results to changes in the PBL parameterization and to the inclusion of an urban canopy model (UCM). Results show that for urban locations there is a clear benefit from parameterizing the urban canopy for simulation of the PBL and near-surface conditions, particularly for temperature evolution at night. Simulation of near-surface CO2 concentrations for a 2-week period in October 2006 showed that running WRF at high resolution (1.33 km) and with a UCM also improves the simulation of observed increases in CO2 during the early evening. [ABSTRACT FROM AUTHOR] more...

Methane and nitrous oxide are potent greenhouse gases whose atmospheric abundances have increased significantly in the past 200 years, together accounting for approximately half of the radiative forcing associated with increasing concentrations of carbon dioxide. In order to understand the factors causing increase of these gases globally, we need to determine their emission rates at regional to continental scales. We directly link atmospheric observations with surface emissions using a Lagrangian Particle Dispersion Model, and then determine emission rates by optimizing prior emissions estimates. We use measurements from NOAA's tall tower and aircraft program in 2004, The Stochastic Time-Inverted Lagrangian Transport model (STILT) driven by meteorological fields from a customized version of the Weather Research and Forecasting (WRF) model, and EDGAR32FT2000 and Global Emissions Inventory Activity (GEIA) as prior emission estimates. In the US and Canada, methane emission rates are found to be consistent with observations, while nitrous oxide emissions are significantly low, by a factor 2.5-3 in the peak emissions time period found to be February through May. [ABSTRACT FROM AUTHOR] more...